= 0.5:\n refs[i] = z1[i]\n\n assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)","def interpolateSpline(x, y) :\n n = len(x)\n\n dim = 4 * (n - 1)\n b = np.zeros((dim, 1))\n A = np.zeros((dim, dim))\n\n for i in range(n-1):\n x1 = x[i]\n x2 = x[i+1]\n y1 = y[i]\n y2 = y[i+1]\n b[i*4:(i+1)*4, 0] = [y1, y2, 0, 0]\n\n A[i*4, i*4:(i+1)*4] = [pow(x1,3), pow(x1,2), x1, 1] \n A[i*4+1, i*4:(i+1)*4] = [pow(x2,3), pow(x2,2), x2, 1]\n if (i != n-2):\n A[i*4+2, i*4:(i+2)*4] = [3*pow(x2,2), 2 * x2, 1, 0, -3*pow(x2,2), -2 * x2, -1, 0, ]\n A[i*4+3, i*4:(i+2)*4] = [6*x2, 2, 0, 0, -6*x2, -2, 0, 0]\n else: \n A[i*4+2, 0:4] = [6*x[0], 2, 0, 0]\n A[i*4+3, i*4:(i+1)*4] = [6*x2, 2, 0, 0]\n \n # solve linear system for the coefficients of the spline\n coeffs = np.linalg.solve(A, b)\n\n # extract local pieces\n spline = []\n for k in range(n-1):\n spline.append(np.poly1d(coeffs[k*4:(k+1)*4, 0]))\n\n return spline","def interpolate_hold_last(self):\n\n # Initialize variables\n n_ensembles = len(self.u_mps)\n\n # Get data from object\n self.u_processed_mps = np.copy(self.u_mps)\n self.v_processed_mps = np.copy(self.v_mps)\n self.u_processed_mps[self.valid_data[0, :] == False] = np.nan\n self.v_processed_mps[self.valid_data[0, :] == False] = np.nan\n\n n_invalid = 0\n # Process data by ensembles\n for n in range(1, n_ensembles):\n # Check if ensemble is invalid and number of consecutive invalids is less than 9\n if (self.valid_data[0, n] == False) and (n_invalid < 9):\n self.u_processed_mps[n] = self.u_processed_mps[n - 1]\n self.v_processed_mps[n] = self.v_processed_mps[n - 1]","def trilinear_interpolate(point, atom_index, emap, emap_max, emap_min):\n point1 = []\n point0 = []\n dif = []\n for p in point:\n if round(p) == p:\n p += 1E-10\n point0.append(math.floor(p))\n point1.append(math.ceil(p))\n dif.append((p - point0[-1]) / (point1[-1] - point0[-1]))\n\n i000 = energy_map_index(point0, emap_max, emap_min) # (0, 0, 0)\n i100 = energy_map_index([point1[0], point0[1], point0[2]], emap_max, emap_min) # (1, 0, 0)\n i001 = energy_map_index([point0[0], point0[1], point1[2]], emap_max, emap_min) # (0, 0, 1)\n i101 = energy_map_index([point1[0], point0[1], point1[2]], emap_max, emap_min) # (1, 0, 1)\n i010 = energy_map_index([point0[0], point1[1], point0[2]], emap_max, emap_min) # (0, 1, 0)\n i110 = energy_map_index([point1[0], point1[1], point0[2]], emap_max, emap_min) # (1, 1, 0)\n i011 = energy_map_index([point0[0], point1[1], point1[2]], emap_max, emap_min) # (0, 1, 1)\n i111 = energy_map_index(point1, emap_max, emap_min) # (1, 1, 1)\n\n c00 = emap[i000][atom_index] * (1 - dif[0]) + emap[i100][atom_index] * dif[0]\n c01 = emap[i001][atom_index] * (1 - dif[0]) + emap[i101][atom_index] * dif[0]\n c10 = emap[i010][atom_index] * (1 - dif[0]) + emap[i110][atom_index] * dif[0]\n c11 = emap[i011][atom_index] * (1 - dif[0]) + emap[i111][atom_index] * dif[0]\n\n c0 = c00 * (1 - dif[1]) + c10 * dif[1]\n c1 = c01 * (1 - dif[1]) + c11 * dif[1]\n\n c = c0 * (1 - dif[2]) + c1 * dif[2]\n\n return c","def interpolatePeriodicSpline(x, y) :\n n = len(x)\n\n dim = 4 * (n - 1)\n b = np.zeros((dim, 1))\n A = np.zeros((dim, dim))\n\n for i in range(n-1):\n x1 = x[i]\n x2 = x[i+1]\n y1 = y[i]\n y2 = y[i+1]\n b[i*4:(i+1)*4, 0] = [y1, y2, 0, 0]\n\n A[i*4, i*4:(i+1)*4] = [pow(x1,3), pow(x1,2), x1, 1] \n A[i*4+1, i*4:(i+1)*4] = [pow(x2,3), pow(x2,2), x2, 1]\n if (i != n-2):\n A[i*4+2, i*4:(i+2)*4] = [3*pow(x2,2), 2 * x2, 1, 0, -3*pow(x2,2), -2 * x2, -1, 0, ]\n A[i*4+3, i*4:(i+2)*4] = [6*x2, 2, 0, 0, -6*x2, -2, 0, 0]\n else: \n A[i*4+2, 0:4] = [3 * pow(x[0],2), 2 * x[0], 1, 0]\n A[i*4+2, i*4:(i+1)*4] = [-3 * pow(x2,2), -2 * x2, -1, 0]\n A[i*4+3, 0:4] = [6 * x[0], 2, 0, 0]\n A[i*4+3, i*4:(i+1)*4] = [-6 * x2, -2, 0, 0]\n # solve linear system for the coefficients of the spline\n coeffs = np.linalg.solve(A, b)\n\n # extract local pieces\n spline = []\n for k in range(n-1):\n spline.append(np.poly1d(coeffs[k*4:(k+1)*4, 0]))\n\n return spline","def test_constant_interpolation_basic(self):\n\n # Define pixel centers along each direction\n x = numpy.array([1.0, 2.0, 4.0])\n y = numpy.array([5.0, 9.0])\n\n # Define ny by nx array with corresponding values\n A = numpy.zeros((len(x), len(y)))\n\n # Define values for each x, y pair as a linear function\n for i in range(len(x)):\n for j in range(len(y)):\n A[i, j] = linear_function(x[i], y[j])\n\n # Then test that interpolated points are always assigned value of\n # closest neighbour\n xis = numpy.linspace(x[0], x[-1], 10)\n etas = numpy.linspace(y[0], y[-1], 10)\n points = combine_coordinates(xis, etas)\n\n vals = interpolate2d(x, y, A, points, mode='constant')\n\n # Find upper neighbours for each interpolation point\n xi = points[:, 0]\n eta = points[:, 1]\n idx = numpy.searchsorted(x, xi, side='left')\n idy = numpy.searchsorted(y, eta, side='left')\n\n # Get the four neighbours for each interpolation point\n x0 = x[idx - 1]\n x1 = x[idx]\n y0 = y[idy - 1]\n y1 = y[idy]\n\n z00 = A[idx - 1, idy - 1]\n z01 = A[idx - 1, idy]\n z10 = A[idx, idy - 1]\n z11 = A[idx, idy]\n\n # Location coefficients\n alpha = (xi - x0) / (x1 - x0)\n beta = (eta - y0) / (y1 - y0)\n\n refs = numpy.zeros(len(vals))\n for i in range(len(refs)):\n if alpha[i] < 0.5 and beta[i] < 0.5:\n refs[i] = z00[i]\n\n if alpha[i] >= 0.5 and beta[i] < 0.5:\n refs[i] = z10[i]\n\n if alpha[i] < 0.5 and beta[i] >= 0.5:\n refs[i] = z01[i]\n\n if alpha[i] >= 0.5 and beta[i] >= 0.5:\n refs[i] = z11[i]\n\n assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)","def showAsPointsInterpolated(self, lToRRatio = 2.0):\n MonkeyPatchMayaVi()\n import enthought.mayavi.mlab as mlab\n from mayavi import mlab\n \n @mlab.show\n def _showSimple():\n maxInterpolPts = 10\n \n def interpolateSection(section):\n sStart = section.getDistalNPA4()\n sEnd = section.getProximalNPA4()\n length = section.getLength()\n rad = min(section.d_r, section.p_r) \n n = min( max( int( lToRRatio * length / rad ), 1 ), maxInterpolPts)\n jVecSteps = ( sEnd-sStart ) / n\n \n intPts = [ sStart + k*jVecSteps for k in range(0,n) ]\n return intPts \n \n lbs = []\n for morph in self.morphs:\n lb = Flatten( ListBuilderSectionVisitor(functor=interpolateSection, morph=morph ) () ) \n lbs.extend( lb )\n \n \n pts = numpy.array( lbs )\n\n x = pts[:, 0]\n y = pts[:, 1]\n z = pts[:, 2]\n s = pts[:, 3]\n \n mlab.points3d(x, y, z, s, colormap=self.colormap, scale_factor=self.scale_factor)\n mlab.outline()\n _showSimple()","def interpolate(self, x_pivot, f_pivot):\n interpolation = interp1d(x_pivot, f_pivot,\n kind=self.kind, bounds_error=False)\n return interpolation","def interpolate(series, indices):\r\n not_included = [t for t in indices if t not in series.index.values]\r\n new_indices_series = pd.Series(index=not_included, data=[np.nan] * len(not_included))\r\n with_new_indices = series.append(new_indices_series).sort_index()\r\n interpolated = with_new_indices.interpolate(method=\"linear\")\r\n\r\n # We want the values on the indices before the (originally) first index to be equal to the first value. Similarly,\r\n # we want the values after the (originally) last index to be equal to the last value.\r\n min_index = min(series.index.values)\r\n max_index = max(series.index.values)\r\n start_value = series.values[0]\r\n end_value = series.values[-1]\r\n\r\n new_values = []\r\n for t, p in interpolated.items():\r\n if t < min_index:\r\n new_values.append(start_value)\r\n elif t > max_index:\r\n new_values.append(end_value)\r\n else:\r\n new_values.append(p)\r\n\r\n new_series = pd.Series(data=new_values, index=interpolated.index)\r\n\r\n return new_series","def interpolate_meridional(self, *interp1d_args, **interp1d_kwargs):\n return self.interp1d_meridional(*interp1d_args, **interp1d_kwargs)(self.lat)","def test_isentropic_pressure():\n lev = [100000., 95000., 90000., 85000.] * units.Pa\n tmp = np.ones((4, 5, 5))\n tmp[0, :] = 296.\n tmp[1, :] = 292.\n tmp[2, :] = 290\n tmp[3, :] = 288.\n tmp[:, :, -1] = np.nan\n tmpk = tmp * units.kelvin\n isentlev = [296.] * units.kelvin\n isentprs = isentropic_interpolation(isentlev, lev, tmpk)\n trueprs = np.ones((1, 5, 5)) * (1000. * units.hPa)\n trueprs[:, :, -1] = np.nan\n assert isentprs[0].shape == (1, 5, 5)\n assert_almost_equal(isentprs[0], trueprs, 3)","def interpolate_matrix(matrix):","def test_linear_interpolation_nan_array(self):\n\n # Define pixel centers along each direction\n x = [0.0, 1.0, 2.0, 3.0, 4.0, 5.0]\n y = [4.0, 5.0, 7.0, 9.0, 11.0, 13.0]\n\n # Define ny by nx array with corresponding values\n A = numpy.zeros((len(x), len(y)))\n\n # Define values for each x, y pair as a linear function\n for i in range(len(x)):\n for j in range(len(y)):\n A[i, j] = linear_function(x[i], y[j])\n A[2, 3] = numpy.nan # (x=2.0, y=9.0): NaN\n\n # Then test that interpolated points can contain NaN\n xis = numpy.linspace(x[0], x[-1], 12)\n etas = numpy.linspace(y[0], y[-1], 10)\n points = combine_coordinates(xis, etas)\n\n vals = interpolate2d(x, y, A, points, mode='linear')\n refs = linear_function(points[:, 0], points[:, 1])\n\n # Set reference result with expected NaNs and compare\n for i, (xi, eta) in enumerate(points):\n if (1.0 < xi <= 3.0) and (7.0 < eta <= 11.0):\n refs[i] = numpy.nan\n\n assert nanallclose(vals, refs, rtol=1e-12, atol=1e-12)","def apply_interpolation(self, transect, interpolation_method=None):\n\n # Reset processed data\n if self.u_mps is not None:\n self.u_processed_mps = np.copy(self.u_mps)\n self.v_processed_mps = np.copy(self.v_mps)\n self.u_processed_mps[self.valid_data[0, :] == False] = np.nan\n self.v_processed_mps[self.valid_data[0, :] == False] = np.nan\n\n # Determine interpolation methods to apply\n if interpolation_method is None:\n interpolation_method = self.interpolate\n else:\n self.interpolate = interpolation_method\n\n # Apply specified interpolation method\n\n if interpolation_method == 'None':\n # Sets invalid data to nan with no interpolation\n self.interpolate_none()\n\n elif interpolation_method == 'ExpandedT':\n # Set interpolate to none as the interpolation done is in the QComp\n self.interpolate_next()\n\n elif interpolation_method == 'Hold9':\n # Interpolates using SonTek method of holding last valid for up to 9 samples\n self.interpolate_hold_9()\n\n elif interpolation_method == 'HoldLast':\n # Interpolates by holding last valid indefinitely\n self.interpolate_hold_last()\n\n elif interpolation_method == 'Linear':\n # Interpolates using linear interpolation\n self.interpolate_linear(transect)\n\n elif interpolation_method == 'Smooth':\n # Interpolates using smooth interpolation\n self.interpolate_smooth(transect)\n\n elif interpolation_method == 'TRDI':\n # TRDI interpolation is done in discharge.\n # For TRDI the interpolation is done on discharge not on velocities\n self.interpolate_none()","def interpolate(m):\n \n x1 = m[0]\n x2 = m[1]\n x3 = m[2]\n y1 = m[3]\n y2 = m[4]\n y3 = m[5]\n denom = (x1 - x2)*(x1 - x3)*(x2 - x3)\n A = (x3 * (y2 - y1) + x2 * (y1 - y3) + x1 * (y3 - y2)) / denom\n B = (x3**2 * (y1 - y2) + x2**2 * (y3 - y1) + x1**2 * (y2 - y3)) / denom\n C = (x2 * x3 * (x2 - x3) * y1 + x3 * x1 * (x3 - x1) * y2 + x1 * x2 * (x1 - x2) * y3) / denom\n xext = -B/(2*A)\n yext = A*xext**2 + B*xext + C\n \n return(np.array([xext,yext]))","def interpolate_na(\n self, method: str = \"nearest\", extrapolate: bool = False, **kwargs\n ):\n dim0 = self.dim0\n kwargs.update(dict(method=method, extrapolate=extrapolate))\n if dim0:\n interp_data = np.empty(self._obj.shape, dtype=self._obj.dtype)\n for i, (_, sub_xds) in enumerate(self._obj.groupby(dim0)):\n interp_data[i, ...] = self._interpolate_na(\n sub_xds.load().data, **kwargs\n )\n else:\n interp_data = self._interpolate_na(self._obj.load().data, **kwargs)\n interp_array = xr.DataArray(\n name=self._obj.name,\n dims=self._obj.dims,\n coords=self._obj.coords,\n data=interp_data,\n attrs=self._obj.attrs,\n )\n interp_array.raster.set_nodata(self.nodata)\n interp_array.raster.set_crs(self.crs)\n return interp_array","def _LinearInterpolate(x0, target, x1, y0, y1):\n if x0 == x1:\n return (y0 + y1) / 2\n return (y1 - y0) * (target - x0) / (x1 - x0) + y0","def splitting_intensity(self, **kwargs):\n \n if 'pol' not in kwargs:\n raise Exception('pol must be specified')\n \n copy = self.data.copy()\n copy.rotateto(kwargs['pol'])\n copy.x = np.gradient(copy.x)\n rdiff, trans = copy.chopdata()\n s = -2 * np.trapz(trans * rdiff) / np.trapz(rdiff**2)\n return s","def section_coordinates():\n \n gh_width = 30.0 # in feet\n gh_width_west = gh_width/2.0\n N_x = 100\n dx = gh_width_west/100.0\n gh_length = 48 # in feet\n \n xvalues = np.linspace(0,(N_x)*dx,N_x+1) # array for width\n yvalues = np.linspace(0,gh_length,num=gh_length+1) # array for height\n zvalues_west = np.zeros(N_x+1) # array for height\n \n for i in range(0,len(xvalues)):\n zvalues_west[i] = 7.29944696 + (1.27415518*xvalues[i]) + (-0.0680139854*xvalues[i]**2) + (0.00152035861*xvalues[i]**3)\n i += 1\n \n roof_slopes_west = np.zeros(N_x+1)\n roof_lengths = np.zeros(N_x+1)\n\n total_length_west = 0\n\n for i in range(1,len(xvalues)):\n dz = zvalues_west[i] - zvalues_west[i-1]\n roof_slopes_west[i] = dz/dx\n roof_lengths[i] = (dz**2 + dx**2)**0.5\n total_length_west += roof_lengths[i]\n \n zvalues_east = np.flip(zvalues_west, axis=0)\n zvalues_west = zvalues_west[:-1]\n zvalues = np.concatenate((zvalues_west, zvalues_east), axis=0)\n \n xx, yy = np.meshgrid(xvalues, yvalues) \n \n plt.plot(xx, yy, marker='.', color='k', linestyle='none')\n plt.axis('equal')\n plt.show() \n\n return roof_slopes_west","def interpolate(self, lon, lat, egy=None):\n raise NotImplementedError(\"MapBase.interpolate()\")","def test_isentropic_pressure_p_increase_rh_out():\n lev = [85000., 90000., 95000., 100000.] * units.Pa\n tmp = np.ones((4, 5, 5))\n tmp[0, :] = 288.\n tmp[1, :] = 290.\n tmp[2, :] = 292.\n tmp[3, :] = 296.\n tmpk = tmp * units.kelvin\n rh = np.ones((4, 5, 5))\n rh[0, :] = 20.\n rh[1, :] = 40.\n rh[2, :] = 80.\n rh[3, :] = 100.\n relh = rh * units.percent\n isentlev = 296. * units.kelvin\n isentprs = isentropic_interpolation(isentlev, lev, tmpk, relh)\n truerh = 100. * units.percent\n assert_almost_equal(isentprs[1], truerh, 3)","def test_isentropic_interpolation_dataarray():\n temp = xr.DataArray([[[296.]], [[292.]], [[290.]], [[288.]]] * units.K,\n dims=('isobaric', 'y', 'x'),\n coords={'isobaric': (('isobaric',), [1000., 950., 900., 850.],\n {'units': 'hPa'}),\n 'time': '2020-01-01T00:00Z'})\n\n rh = xr.DataArray([[[100.]], [[80.]], [[40.]], [[20.]]] * units.percent,\n dims=('isobaric', 'y', 'x'), coords={\n 'isobaric': (('isobaric',), [1000., 950., 900., 850.], {'units': 'hPa'}),\n 'time': '2020-01-01T00:00Z'})\n\n isentlev = [296., 297.] * units.kelvin\n press, rh_interp = isentropic_interpolation(isentlev, temp.isobaric, temp, rh)\n\n assert_array_almost_equal(press, np.array([[[1000.]], [[936.213]]]) * units.hPa, 3)\n assert_array_almost_equal(rh_interp, np.array([[[100.]], [[69.19706]]]) * units.percent, 3)","def interpolate( h, x, y=None, z=None, outOfRangeValue=30 ):\n\n if x != x: return outOfRangeValue\n if x <= h.GetXaxis().GetBinCenter(1) or x >= h.GetXaxis().GetBinCenter(h.GetXaxis().GetNbins()): return outOfRangeValue\n \n if y != None:\n if y != y: return outOfRangeValue\n if y <= h.GetYaxis().GetBinCenter(1) or y >= h.GetYaxis().GetBinCenter(h.GetYaxis().GetNbins()): return outOfRangeValue\n if z != None:\n if z != z: return outOfRangeValue\n if z <= h.GetZaxis().GetBinCenter(1) or z >= h.GetZaxis().GetBinCenter(h.GetZaxis().GetNbins()): return outOfRangeValue\n \n if y != None and z != None: return h.Interpolate( x, y, z )\n if y != None: return h.Interpolate( x, y )\n return h.Interpolate( x )","def test_isentropic_pressure_tmp_out_interp():\n lev = [100000., 95000., 90000., 85000.] * units.Pa\n tmp = np.ones((4, 5, 5))\n tmp[0, :] = 296.\n tmp[1, :] = 292.\n tmp[2, :] = 290.\n tmp[3, :] = 288.\n tmpk = tmp * units.kelvin\n isentlev = [296., 297.] * units.kelvin\n isentprs = isentropic_interpolation(isentlev, lev, tmpk, temperature_out=True)\n truetmp = 291.4579 * units.kelvin\n assert_almost_equal(isentprs[1][1], truetmp, 3)","def interpolate(self, var, time, lat, lon):\n\n # Get the nearest four points in space\n # Check to see if lat/lons are 2d or 1d\n if len(self['lat'].shape) == 2:\n closey, closex, distances = self.nearest_points(lat, lon, npt=4)\n # Distances in km\n# distances = np.array([self.haversine(\n# (self['lat'][y,x].values, self['lon'][y,x].values),\n# (lat, lon)) for y,x in \n# zip(list(closey), list(closex))])\n else:\n closen = self.nearest_points(lat, lon, npt=4)\n closey = closen\n closex = closen\n # Distances in km\n distances = np.array([self.haversine(\n (self['lat'][n].values, self['lon'][n].values),\n (lat, lon)) for n in list(closen)])\n # Check for exact match (within some tolerance)\n spaceweights = np.zeros(distances.shape)\n if (distances < 1.0).sum() > 0:\n spaceweights[distances.argmin()] = 1\n else:\n # Here, inverse distance weighting (for simplicity)\n spaceweights = 1.0 / distances\n spaceweights /= spaceweights.sum()\n # Get weights in time\n #time64 = np.datetime64(time)\n #all the valid times in the ensemble\n valids = self['validtime'].values\n timeweights = np.zeros(valids.shape)\n # Check if we are outside the valid time range\n if (time < valids[0]) or (time > valids[-1]):\n print(\"Interpolation is outside of time range in state!\")\n return None\n # Find where we are in this list\n #index after the time of the observation\n lastdex = (valids >= time).argmax()\n # If we match a particular time value, then\n # this is just an identity\n if valids[lastdex] == time:\n # Just make a one at this time\n timeweights[lastdex] = 1\n else:\n # Linear interpolation\n #often going to be 6 hours, subtracts datetime objects I think\n diff = (valids[lastdex] - valids[lastdex-1])\n #print(valids[lastdex], valids[lastdex-1], diff)\n #often going to be 21600 seconds\n totsec = diff.seconds\n #totsec = np.abs(diff / np.timedelta64(1, 's'))\n #ST\n #calculate time difference between time after and time of observation\n #the abs will make this positive definite, which is okay since\n #the difference will always be negative\n thisdiff = abs(time - valids[lastdex])\n #thissec = np.abs(thisdiff / np.timedelta64(1,'s'))\n thissec = thisdiff.seconds\n # Put in appropriate weights\n #ST switched the -1 between the two lines to match up with the positive-\n #definite thisdiff\n timeweights[lastdex-1] = float(thissec) / totsec\n timeweights[lastdex] = 1.0 - (float(thissec)/totsec)\n # Now that we have the weights, do the interpolation\n #ST an ntimes x 4 x nens array\n interp = self.variables[var].values[:,closey,closex,:]\n # Do a dot product with the time weights\n # And with the space weights\n if len(interp.shape) == 3:\n interp = (timeweights[:,None,None] * interp).sum(axis=0)\n else:\n interp = (timeweights[:,None,None,None] * interp).sum(axis=0)\n \n if len(interp.shape) == 3:\n #ST Changed 2nd : to None\n interp = (spaceweights[:,None,None] * interp).sum(axis=1)\n else:\n interp = (spaceweights[:,None] * interp).sum(axis=0)\n # Return estimate from all ensemble members\n return interp","def linear_interpolate_release(mvi, j):\n set_system_state(mvi, 1)\n lam1 = mvi.system.lambda_()[j]\n set_system_state(mvi, 2)\n lam2 = mvi.system.lambda_()[j]\n\n # If either of the following loops are entered, there are likely going to\n # be problems.\n if (lam1 < 0) and (lam2 < 0):\n #add_constraints(mvi, mvi._state1_releases)\n #print mvi.lambda1c[j]\n #print mvi\n #raise Exception(\"Bad release interpolation.\")\n print 'WARNING: BAD INTERPOLANT'\n return mvi.t1, mvi.q1\n\n if lam1 < 0:\n return mvi.t1, mvi.q1\n\n tr = mvi.t1 - (lam1/(lam2-lam1))*(mvi.t2-mvi.t1)\n frac = (tr-mvi.t1)/(mvi.t2-mvi.t1)\n qr = frac*(mvi.q2-mvi.q1)+mvi.q1\n\n return tr, qr","def InterpolateSection(self, pointA, pointB, Resolution = 50):\n\t\tif type(pointA) != Point:\n\t\t\traise TypeError()\n\t\tif type(pointB) != Point:\n\t\t\traise TypeError()\n\n\t\tx0, y0, z0 = ToCartesian(pointA.Latitude, pointA.Longitude)\n\t\tx1, y1, z1 = ToCartesian(pointB.Latitude, pointB.Longitude)\n\n\t\tdistance = Distance_LatLongs(pointA.Latitude, pointA.Longitude, pointB.Latitude, pointB.Longitude)\n\n\t\t# distance = math.sqrt(math.pow(x1 - x0, 2) + math.pow(y1 - y0, 2) + math.pow(z1 - z0, 2))\n\n\t\tsegment_size = distance / Resolution\n\n\t\tsegments = []\n\n\t\tfor index in range(Resolution):\n\t\t\tsegment_distance = index * segment_size\n\t\t\tx, y, z = Interpolate_Linear_3Points(x0, y0, z0, x1, y1, z1, segment_distance)\n\n\t\t\tlat, lon = ToGeo(x, y, z)\n\n\t\t\tsegments.append(Point(Latitude = lat, Longitude = lon))\n\n\t\treturn segments","def filter_interpolated(self, ys, xs):\n return ys, xs","def interpolated_solution(self):\n # need to reverse the direction of the _solution array\n if self.model.assortativity == 'positive':\n traj = self._solution[::-1]\n else:\n traj = self._solution\n\n xi = np.linspace(traj[0, 0], traj[-1, 0], 10 * traj.shape[0])\n interp_soln = self.ivp.interpolate(traj, xi, k=5, ext=2)\n\n # convert to a data frame\n col_names = ['x', r'$\\hat{\\mu}(x)$', r'$\\hat{\\theta}(x)$', '$\\hat{w}(x)$', r'$\\hat{\\pi}(x)$']\n df = pd.DataFrame(interp_soln, columns=col_names)\n\n return df.set_index('x')","def computeNormalAndCurvature():\n radius = 50\n for i,j in pts:\n nb_pts = ti.cast(0, ti.f32)\n accu_0 = ti.cast(0, ti.f32)\n accu_1 = ti.cast(0, ti.f32)\n accu_2 = ti.cast(0, ti.f32)\n accu_3 = ti.cast(0, ti.f32)\n accu_4 = ti.cast(0, ti.f32)\n accu_5 = ti.cast(0, ti.f32)\n accu_6 = ti.cast(0, ti.f32)\n accu_7 = ti.cast(0, ti.f32)\n accu_8 = ti.cast(0, ti.f32)\n z = 0\n for x in range(i-radius, i+radius):\n for y in range(j-radius, j+radius):\n if ti.is_active(block1, [x,y]):\n accu_0 += x * x\n accu_1 += x * y\n accu_2 += x * z\n accu_3 += y * y\n accu_4 += y * z\n accu_5 += z * z\n accu_6 += x\n accu_7 += y\n accu_8 += z\n nb_pts += 1\n accu_0 /= nb_pts\n accu_1 /= nb_pts\n accu_2 /= nb_pts\n accu_3 /= nb_pts\n accu_4 /= nb_pts\n accu_5 /= nb_pts\n accu_6 /= nb_pts\n accu_7 /= nb_pts\n accu_8 /= nb_pts\n cov_mat_0 = accu_0 - accu_6 * accu_6\n cov_mat_1 = accu_1 - accu_6 * accu_7\n cov_mat_2 = accu_2 - accu_6 * accu_8\n cov_mat_4 = accu_3 - accu_7 * accu_7\n cov_mat_5 = accu_4 - accu_7 * accu_8\n cov_mat_8 = accu_5 - accu_8 * accu_8\n cov_mat_3 = cov_mat_1\n cov_mat_6 = cov_mat_2\n cov_mat_7 = cov_mat_5\n\n # Compute eigen value and eigen vector\n # Make sure in [-1, 1]\n scale = ti.max(1.0, ti.abs(cov_mat_0))\n scale = ti.max(scale, ti.abs(cov_mat_1))\n scale = ti.max(scale, ti.abs(cov_mat_2))\n scale = ti.max(scale, ti.abs(cov_mat_3))\n scale = ti.max(scale, ti.abs(cov_mat_4))\n scale = ti.max(scale, ti.abs(cov_mat_5))\n scale = ti.max(scale, ti.abs(cov_mat_6))\n scale = ti.max(scale, ti.abs(cov_mat_7))\n scale = ti.max(scale, ti.abs(cov_mat_8))\n if scale > 1.0:\n cov_mat_0 /= scale\n cov_mat_1 /= scale\n cov_mat_2 /= scale\n cov_mat_3 /= scale\n cov_mat_4 /= scale\n cov_mat_5 /= scale\n cov_mat_6 /= scale\n cov_mat_7 /= scale\n cov_mat_8 /= scale\n \n # Compute roots\n eigen_val_0 = ti.cast(0, ti.f32)\n eigen_val_1 = ti.cast(0, ti.f32)\n eigen_val_2 = ti.cast(0, ti.f32)\n \n c0 = cov_mat_0 * cov_mat_4 * cov_mat_8 \\\n + 2 * cov_mat_3 * cov_mat_6 * cov_mat_7 \\\n - cov_mat_0 * cov_mat_7 * cov_mat_7 \\\n - cov_mat_4 * cov_mat_6 * cov_mat_6 \\\n - cov_mat_8 * cov_mat_3 * cov_mat_3\n c1 = cov_mat_0 * cov_mat_4 \\\n - cov_mat_3 * cov_mat_3 \\\n + cov_mat_0 * cov_mat_8 \\\n - cov_mat_6 * cov_mat_6 \\\n + cov_mat_4 * cov_mat_8 \\\n - cov_mat_7 * cov_mat_7\n c2 = cov_mat_0 + cov_mat_4 + cov_mat_8\n \n if ti.abs(c0) < 0.00001:\n eigen_val_0 = 0\n d = c2 * c2 - 4.0 * c1\n if d < 0.0: # no real roots ! THIS SHOULD NOT HAPPEN!\n d = 0.0\n sd = ti.sqrt(d)\n eigen_val_2 = 0.5 * (c2 + sd)\n eigen_val_1 = 0.5 * (c2 - sd)\n else:\n s_inv3 = ti.cast(1.0 / 3.0, ti.f32)\n s_sqrt3 = ti.sqrt(3.0)\n c2_over_3 = c2 * s_inv3\n a_over_3 = (c1 - c2 * c2_over_3) * s_inv3\n if a_over_3 > 0:\n a_over_3 = 0\n \n half_b = 0.5 * (c0 + c2_over_3 * (2 * c2_over_3 * c2_over_3 - c1))\n q = half_b * half_b + a_over_3 * a_over_3 * a_over_3\n if q > 0:\n q = 0\n \n rho = ti.sqrt(-a_over_3)\n theta = ti.atan2(ti.sqrt(-q), half_b) * s_inv3\n cos_theta = ti.cos(theta)\n sin_theta = ti.sin(theta)\n eigen_val_0 = c2_over_3 + 2 * rho * cos_theta\n eigen_val_1 = c2_over_3 - rho * (cos_theta + s_sqrt3 * sin_theta)\n eigen_val_2 = c2_over_3 - rho * (cos_theta - s_sqrt3 * sin_theta)\n temp_swap = ti.cast(0, ti.f32)\n \n # Sort in increasing order.\n if eigen_val_0 >= eigen_val_1:\n temp_swap = eigen_val_1\n eigen_val_1 = eigen_val_0\n eigen_val_0 = temp_swap\n if eigen_val_1 >= eigen_val_2:\n temp_swap = eigen_val_2\n eigen_val_2 = eigen_val_1\n eigen_val_1 = temp_swap\n if eigen_val_0 >= eigen_val_1:\n temp_swap = eigen_val_1\n eigen_val_1 = eigen_val_0\n eigen_val_0 = temp_swap\n \n if eigen_val_0 <= 0:\n eigen_val_0 = 0\n d = c2 * c2 - 4.0 * c1\n if d < 0.0: # no real roots ! THIS SHOULD NOT HAPPEN!\n d = 0.0\n sd = ti.sqrt(d)\n eigen_val_2 = 0.5 * (c2 + sd)\n eigen_val_1 = 0.5 * (c2 - sd)\n # end of compute roots\n\n eigen_value = eigen_val_1 * scale # eigen value for 2D SDF\n # eigen value for 3D SDF\n #eigen_value = eigen_val_0 * scale\n\n #print(\"eigen_val_0 \", eigen_val_0)\n #print(\"eigen_val_1 \", eigen_val_1)\n #print(\"eigen_val_2 \", eigen_val_2)\n \n # TODO\n #scaledMat.diagonal ().array () -= eigenvalues (0)\n #eigenvector = detail::getLargest3x3Eigenvector (scaledMat).vector;\n\n # Compute normal vector (TODO)\n #visual_norm[i,j][0] = eigen_val_0 #eigen_vector[0]\n #visual_norm[i,j][1] = eigen_val_1 #eigen_vector[1]\n #visual_norm[i,j][2] = eigen_val_2 #eigen_vector[2]\n\n # Compute the curvature surface change\n eig_sum = cov_mat_0 + cov_mat_1 + cov_mat_2\n visual_curv[i,j][0] = 0\n if eig_sum != 0:\n visual_curv[i,j][0] = eigen_val_1 # true curvature is: ti.abs(eigen_value / eig_sum)","def segement_divide(pts,step=0.10, offset_x=0.01, offset_y=0.01):\n\n # Select the x and y of the points\n n = len(pts)\n \n z = 0.0\n \n points_plane = [] \n points_x = []\n paint_point = []\n\n for i in range(n):\n points_plane.append([pts[i][0], pts[i][1]])\n \n # Sorted the list according to x \n points_plane.sort(key=lambda x:x[0])\n\n # Segment the points according to x \n counter = 0 # Count the interval\n x_min = points_plane[0][0]\n x_max = points_plane[n-1][0]\n\n # The whole interval that needs to be divided\n upper = x_max + offset_x\n lower = x_min - offset_x\n lower_bound = lower\n \n # Set each segement's lower and upperbound\n while (lower_bound + step <= upper): \n # The break condition will be lower_bound > upper - step\n upper_bound = lower_bound + step\n\n # Find the index between lower bound and upper bound\n # First, find the index which x >= lower bound\n index = 0\n \n while (points_plane[index][0] < lower_bound): \n index = index + 1 # The index of the first point in the interval\n \n # If there is at least one point in the [lower_bound, upper_bound]\n if (points_plane[index][0] <= upper_bound): \n\n x_start = points_plane[index][0]\n y_max = points_plane[index][1]\n y_min = points_plane[index][1]\n \n while (points_plane[index][0] <= upper_bound): \n # The break condition will be x[index] > upper bound or index = n - 1\n # Compute the y max and y min in this interval\n \n if points_plane[index][1] > y_max: \n y_max = points_plane[index][1]\n\n if points_plane[index][1] < y_min:\n y_min = points_plane[index][1]\n \n if index < n - 1:\n index = index + 1\n else:\n break\n # The index of the last point in the interval, when index < n-1\n \n x_end = points_plane[index][0]\n\n paint_point.append([lower_bound,y_max+offset_y,z]) \n paint_point.append([lower_bound,y_min-offset_y,z])\n points_x.append([x_start, x_end])\n \n counter = counter + 1\n\n # Update interval\n lower_bound = upper_bound - offset_x\n \n # Deal with the last interval\n lower_bound_last = upper - step\n index_last = 0\n counter = counter + 1\n while ((index_last < n) and (points_plane[index_last][0] < lower_bound_last)): \n # The first point in the last interval\n index_last = index_last + 1\n \n if (index_last < n): \n # There is at least one point in the last interval\n x_start_last = points_plane[index_last][0]\n y_max_last = points_plane[index_last][1]\n y_min_last = points_plane[index_last][1]\n\n while ((index_last) y_max_last: \n y_max_last = points_plane[index_last][1]\n \n if points_plane[index_last][1] < y_min_last:\n y_min_last = points_plane[index_last][1]\n\n index_last = index_last + 1\n \n index_last = index_last - 1 # The index of the last point in the interval\n \n paint_point.append([lower_bound_last, y_max_last+offset_y, z])\n paint_point.append([lower_bound_last, y_min_last-offset_y, z])\n# paint_point.append([upper, y_max_last+offset_y, z])\n# paint_point.append([upper, y_min_last-offset_y, z])\n# return trans_to_end(paint_point)\n return paint_point","def different_quadratic_extrpolation_lower(x_interp, x_spline, y_spline):\n index_lower_1 = 0\n index_lower_2 = 1\n x1_lower = x_spline[index_lower_1]\n x2_lower = x_spline[index_lower_2]\n x3_lower = x_spline[index_lower_2 + 1]\n f1_lower = y_spline[index_lower_1]\n\n df1_dx_lower = calc_gradient(x_spline, y_spline, index_lower_1)/(x2_lower - x1_lower)\n df2_dx_lower = calc_gradient(x_spline, y_spline, index_lower_2)/(x3_lower - x2_lower)\n\n # Solve 2ax-b = df_dx for the gradient at point 1 and 2\n # Rearrange both equations to find 'a' and 'b' quadratic coefficients\n a_lower = (df2_dx_lower - df1_dx_lower)/(2.*(x2_lower - x1_lower))\n b_lower = df1_dx_lower - 2.*a_lower*x1_lower\n\n # Find c by solving at the fixed points (f = a x**2 + bx + c) at point 1 for the lower, and point 2 for the upper\n c_lower = f1_lower - a_lower*x1_lower**2 - b_lower*x1_lower\n return a_lower*x_interp**2 + b_lower*x_interp + c_lower","def interpolate1Image2D( iImage, iCoorX, iCoorY ):\n # pretvori vhodne spremenljivke v np polje\n iImage = np.asarray( iImage ) \n iCoorX = np.asarray( iCoorX )\n iCoorY = np.asarray( iCoorY ) \n # preberi velikost slike in jedra\n dy, dx = iImage.shape\n # ustvari 2d polje koordinat iz 1d vhodnih koordinat (!!!)\n if np.size(iCoorX) != np.size(iCoorY):\n print('Stevilo X in Y koordinat je razlicno!') \n iCoorX, iCoorY = np.meshgrid(iCoorX, iCoorY, sparse=False, indexing='xy')\n #------------------------------- za hitrost delovanja \n return interpn( (np.arange(dy),np.arange(dx)), iImage, \\\n np.dstack((iCoorY,iCoorX)),\\\n method='linear', bounds_error=False)\\\n .astype( iImage.dtype )"],"string":"[\n \"def __hinterpolate(self):\\n \\n # Temp. Data holders\\n upperint = []\\n lowerint = []\\n \\n # Dont like this, because here we insert points into the rawdata\\n # But it creates consisitent results in the interpolation results\\n if self.__upper[0][0] != 0: self.__upper.insert(0,(0.,0.))\\n if self.__lower[0][0] != 0: self.__lower.insert(0,(0.,0.))\\n \\n # Create points\\n if self.__interpolation_method == \\\"l\\\":\\n xpointsU = list(map(lambda x:x/float(self.__procPointsCount),range(0,self.__procPointsCount+1)))\\n xpointsL = list(map(lambda x:x/float(self.__procPointsCount),range(0,self.__procPointsCount+1)))\\n elif self.__interpolation_method == \\\"p\\\":\\n xpointsU = [x**2/float(self.__procPointsCount)**2 for x in range(self.__procPointsCount+1)]\\n xpointsL = [x**2/float(self.__procPointsCount)**2 for x in range(self.__procPointsCount+1)]\\n \\n # Calculate secants\\n uppersec = [(self.__upper[i+1][1]-self.__upper[i][1])/(self.__upper[i+1][0]-self.__upper[i][0]) for i in range(len(self.__upper)-1)]\\n lowersec = [(self.__lower[i+1][1]-self.__lower[i][1])/(self.__lower[i+1][0]-self.__lower[i][0]) for i in range(len(self.__lower)-1)]\\n \\n # Calculate tangents\\n uppertan = [(uppersec[k-1]+uppersec[k])/2 for k in range(1,len(uppersec))]\\n uppertan.insert(0,uppersec[0])\\n uppertan.append(uppersec[-1])\\n\\n lowertan = [(lowersec[k-1]+lowersec[k])/2 for k in range(1,len(lowersec))]\\n lowertan.insert(0,lowersec[0])\\n lowertan.append(lowersec[-1])\\n \\n # Hermite blending functions\\n p0 = lambda t: 2*t**3 - 3*t**2 + 1\\n m0 = lambda t: t**3 - 2*t**2 + t\\n p1 = lambda t: -2*t**3 + 3*t**2\\n m1 = lambda t: t**3 - t**2\\n \\n # Find matching points to improve accuarcy\\n matchU = [(i,j) for i in range(len(xpointsU)) for j in range(len(self.__upper)) if xpointsU[i] == self.__upper[j][0]]\\n matchL = [(i,j) for i in range(len(xpointsL)) for j in range(len(self.__lower)) if xpointsL[i] == self.__lower[j][0]]\\n \\n # Reverse match pairs to insure no index errors\\n matchU.reverse()\\n matchL.reverse()\\n\\n# print(self.__lower)\\n# print(xpointsL)\\n # Pop xpoints that dont require interpolation and append the point into the upperint list\\n for i in matchU:\\n xpointsU.pop(i[0])\\n upperint.append(self.__upper[i[1]])\\n \\n# print(matchL)\\n \\n # Same process as above but for lower airfoil\\n for i in matchL:\\n xpointsL.pop(i[0])\\n lowerint.append(self.__lower[i[1]])\\n \\n # Interpolate upper points\\n for xp in xpointsU:\\n for i in range(len(self.__upper)-1):\\n if self.__upper[i][0] < xp < self.__upper[i+1][0]:\\n h = self.__upper[i+1][0]-self.__upper[i][0]\\n t = (xp - self.__upper[i][0]) / h\\n solution = ( p0(t)*self.__upper[i][1] + h*m0(t)*uppertan[i] + p1(t)*self.__upper[i+1][1] + h*m1(t)*uppertan[i+1] )\\n upperint.append((xp,solution))\\n \\n # Interpolate lower points\\n for xp in xpointsL:\\n for i in range(len(self.__lower)-1):\\n if self.__lower[i][0] < xp < self.__lower[i+1][0]:\\n h = self.__lower[i+1][0]-self.__lower[i][0]\\n t = (xp - self.__lower[i][0]) / h\\n solution = ( p0(t)*self.__lower[i][1] + h*m0(t)*lowertan[i] + p1(t)*self.__lower[i+1][1] + h*m1(t)*lowertan[i+1] )\\n lowerint.append((xp,solution))\\n \\n # Sort the points to keep the correct sequence\\n upperint.sort(key=lambda x:x[0], reverse=True)\\n lowerint.sort(key=lambda x:x[0])\\n \\n # Do checks to insure no duplicates\\n if upperint[0][0] != 1.0: upperint.insert(0,(1.0,0.0))\\n if upperint[-1][0] != 0.0: upperint.append((0.0,0.0))\\n if lowerint[0][0] == 0.0: lowerint.pop(0)\\n if lowerint[-1][0] != 1.0: lowerint.append((1.0,0.0))\\n\\n self.__ProcPoints = upperint + lowerint\",\n \"def test_interpolation():\\n spiral_arm = survey.get_spiral_slice(track = \\\"perseus\\\", \\n interpolate = True)\\n spiral_arm2 = survey.get_spiral_slice(track = \\\"Per\\\", \\n interpolate = False)\\n\\n assert np.allclose(spiral_arm[\\\"INTEN\\\"], spiral_arm2[\\\"INTEN\\\"], equal_nan = True)\",\n \"def interpolate(self, distance, normalized=...): # -> BaseGeometry:\\n ...\",\n \"def test_interpolation(self):\\n\\n ndx1, ndx2 = self.find_partition()\\n tessellation = Delaunay(self.grid[ndx2,:])\\n\\n # initialisation\\n results = []\\n ndim = self.ndim+1\\n\\n for j in ndx1:\\n nmodels = len(self.tracks[j].models)\\n aResult = np.empty((nmodels,ndim+nglb+6),dtype=gtype)\\n pt = self.tracks[j].params + [0.0,]\\n\\n for i in range(nmodels):\\n aModel1 = self.tracks[j].models[i]\\n pt[-1] = aModel1.glb[iage]\\n aModel2 = interpolate_model(self,pt,tessellation,ndx2)\\n aResult[i,0:ndim] = pt\\n if (aModel2 is None):\\n aResult[i,ndim:ndim+nglb+6] = np.nan\\n else:\\n aResult[i,ndim:ndim+nglb+6] = compare_models(aModel1,aModel2)\\n\\n results.append(aResult)\\n\\n return results, ndx1, ndx2, tessellation\",\n \"def interpolate_none(self):\\n\\n # Reset processed data\\n self.u_processed_mps = np.copy(self.u_mps)\\n self.v_processed_mps = np.copy(self.v_mps)\\n self.u_processed_mps[self.valid_data[0, :] == False] = np.nan\\n self.v_processed_mps[self.valid_data[0, :] == False] = np.nan\",\n \"def _interpolate(self, kps1: List[List[kp]], kps2: List[List[kp]]) -> np.ndarray:\\n interpolated_kps = []\\n for i in range(len(kps1)):\\n # If one of the two points is empty -> Not interpolate\\n if len(kps1[i]) != 0 and len(kps2[i]) != 0:\\n interpolated_coords = np.linspace(np.array(kps1[i]), np.array(kps2[i]), num=3).tolist()\\n interpolated_kps.append(interpolated_coords[1])\\n else:\\n interpolated_kps.append([None, None, None])\\n return np.array(interpolated_kps)\",\n \"def interpolate_hold_9(self):\\n\\n # Initialize variables\\n n_ensembles = self.u_mps.shape[0]\\n\\n # Get data from object\\n self.u_processed_mps = np.copy(self.u_mps)\\n self.v_processed_mps = np.copy(self.v_mps)\\n self.u_processed_mps[self.valid_data[0, :] == False] = np.nan\\n self.v_processed_mps[self.valid_data[0, :] == False] = np.nan\\n\\n n_invalid = 0\\n # Process data by ensembles\\n for n in range(n_ensembles):\\n # Check if ensemble is invalid and number of consecutive invalids is less than 9\\n if self.valid_data[0, n] == False and n_invalid < 9:\\n self.u_processed_mps[n] = self.u_processed_mps[n - 1]\\n self.v_processed_mps[n] = self.v_processed_mps[n - 1]\\n n_invalid += 1\\n else:\\n n_invalid = 0\",\n \"def interpolate_nans(self):\\n\\n signal = self.signal\\n\\n # check for more than one nan in row\\n for i in range(len(signal)-1) :\\n if np.isnan(signal[i]) and np.isnan(signal[i+1]) :\\n raise Exception('There are two nans in a row ask moritz what to do !')\\n\\n if np.isnan(signal[0]) :\\n np.signal[0] = signal[1]\\n if np.isnan(signal[-1]) :\\n signal[-1] = signal[-2]\\n\\n for i in range(1,len(signal)-1) :\\n if np.isnan(signal[i]):\\n signal[i] = (signal[i-1] + signal[i+1])/2\",\n \"def linear_interpolation(self, pt1, pt2, unknown):\\n\\n #Write your code for linear interpolation here\\n pt1,intensity1=pt1\\n pt2,intensity2=pt2\\n newPoint=unknown\\n intensity_diff=pt2-pt1\\n if(intensity_diff<=0):\\n intensity_diff=1\\n\\n a1=pt2-newPoint\\n b1=a1/intensity_diff\\n x=intensity1*b1\\n a2=newPoint - pt1\\n b2=a2/intensity_diff\\n y=intensity2*b2\\n new_intensity=x+y\\n\\n return new_intensity\",\n \"def interpolate(self, *point, **kwargs):\\n\\n # Assume alpha enhancement of 0.4 if not given.\\n if len(point) == 3:\\n point = [] + list(point) + [0.4]\\n warnings.warn(\\n \\\"Assuming [alpha/Fe] = 0.4 composition unless \\\"\\n \\\"otherwise specified.\\\", StandardCompositionAssumed)\\n elif len(point) == 4:\\n point = list(point)\\n warnings.warn(\\n \\\"Fourth stellar param is [alpha/Fe] = {}\\\".format(point[3]))\\n\\n return super(self.__class__, self).interpolate(*point, **kwargs)\",\n \"def check_interp(self):\\n\\n points = np.loadtxt(\\\"skeleton_temp/\\\" + cell + \\\"_points.txt\\\", delimiter=',')\\n\\n self.initial_scatter = ax.scatter(points[:, 0],\\n points[:, 1],\\n points[:, 2], s=5, c='r')\\n self.cell_points = self.get_cell_xyz()\\n ax.scatter(self.cell_points[::5, 0],\\n self.cell_points[::5, 1],\\n self.cell_points[::5, 2], s=3, c='b', alpha=.03)\\n ax.set_xlabel('X (um)')\\n ax.set_ylabel('Y (um)')\\n ax.set_zlabel('Z (um)')\",\n \"def test_linear_interpolation_outside_domain(self):\\n\\n # Define pixel centers along each direction\\n x = [1.0, 2.0, 4.0]\\n y = [5.0, 9.0]\\n\\n # Define ny by nx array with corresponding values\\n A = numpy.zeros((len(x), len(y)))\\n\\n # Define values for each x, y pair as a linear function\\n for i in range(len(x)):\\n for j in range(len(y)):\\n A[i, j] = linear_function(x[i], y[j])\\n\\n # Simple example first for debugging\\n xis = numpy.linspace(0.9, 4.0, 4)\\n etas = numpy.linspace(5, 9.1, 3)\\n points = combine_coordinates(xis, etas)\\n refs = linear_function(points[:, 0], points[:, 1])\\n\\n vals = interpolate2d(x, y, A, points, mode='linear',\\n bounds_error=False)\\n msg = ('Length of interpolation points %i differs from length '\\n 'of interpolated values %i' % (len(points), len(vals)))\\n assert len(points) == len(vals), msg\\n for i, (xi, eta) in enumerate(points):\\n if xi < x[0] or xi > x[-1] or eta < y[0] or eta > y[-1]:\\n assert numpy.isnan(vals[i])\\n else:\\n msg = ('Got %.15f for (%f, %f), expected %.15f'\\n % (vals[i], xi, eta, refs[i]))\\n assert numpy.allclose(vals[i], refs[i],\\n rtol=1.0e-12, atol=1.0e-12), msg\\n\\n # Try a range of combinations of points outside domain\\n # with error_bounds True\\n print\\n for lox in [x[0], x[0] - 1]:\\n for hix in [x[-1], x[-1] + 1]:\\n for loy in [y[0], y[0] - 1]:\\n for hiy in [y[-1], y[-1] + 1]:\\n\\n # Then test that points outside domain can be handled\\n xis = numpy.linspace(lox, hix, 4)\\n etas = numpy.linspace(loy, hiy, 4)\\n points = combine_coordinates(xis, etas)\\n\\n if lox < x[0] or hix > x[-1] or \\\\\\n loy < y[0] or hiy > y[-1]:\\n try:\\n vals = interpolate2d(x, y, A, points,\\n mode='linear',\\n bounds_error=True)\\n except BoundsError, e:\\n assert 'bounds_error was requested' in str(e)\\n else:\\n msg = 'Should have raised bounds error'\\n raise Exception(msg)\\n\\n # Try a range of combinations of points outside domain with\\n # error_bounds False\\n for lox in [x[0], x[0] - 1, x[0] - 10]:\\n for hix in [x[-1], x[-1] + 1, x[-1] + 5]:\\n for loy in [y[0], y[0] - 1, y[0] - 10]:\\n for hiy in [y[-1], y[-1] + 1, y[-1] + 10]:\\n\\n # Then test that points outside domain can be handled\\n xis = numpy.linspace(lox, hix, 10)\\n etas = numpy.linspace(loy, hiy, 10)\\n points = combine_coordinates(xis, etas)\\n refs = linear_function(points[:, 0], points[:, 1])\\n vals = interpolate2d(x, y, A, points,\\n mode='linear', bounds_error=False)\\n\\n assert len(points) == len(vals), msg\\n for i, (xi, eta) in enumerate(points):\\n if xi < x[0] or xi > x[-1] or\\\\\\n eta < y[0] or eta > y[-1]:\\n msg = 'Expected NaN for %f, %f' % (xi, eta)\\n assert numpy.isnan(vals[i]), msg\\n else:\\n msg = ('Got %.15f for (%f, %f), expected '\\n '%.15f' % (vals[i], xi, eta, refs[i]))\\n assert numpy.allclose(vals[i], refs[i],\\n rtol=1.0e-12,\\n atol=1.0e-12), msg\",\n \"def _interpolation(self, video):\\n self.F_int = []\\n self.mgrid_0 = []\\n self.mgrid_1 = []\\n for p in range(video.points.shape[0]):\\n _m_0, _m_1 = np.meshgrid(self.extended_points_0[p], self.extended_points_1[p])\\n _F_int = interp2d(self.extended_points_0[p], self.extended_points_1[p], video.mraw[0, _m_0, _m_1], kind='cubic')\\n self.F_int.append(_F_int)\\n\\n m_0, m_1 = np.meshgrid(self.extended_points_0[p, self.pad:-self.pad], self.extended_points_1[p, self.pad:-self.pad])\\n self.mgrid_0.append(m_0)\\n self.mgrid_1.append(m_1)\",\n \"def InterpolateDerivs(self, , p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=...):\\n ...\",\n \"def interpolate(timepoint_defined, signal, interp_type, TR):\\n\\n timepoint_defined = np.array(timepoint_defined)\\n\\n true_inds = np.where(timepoint_defined == True)[0]\\n false_inds = np.where(timepoint_defined == False)[0]\\n\\n\\n signal_copy = np.array(signal)\\n\\n if interp_type == 'linear':\\n\\n #Still need to handle beginning/end cases\\n\\n for temp_timepoint in false_inds:\\n\\n\\n #past_timepoint = true_inds[np.sort(np.where(true_inds < temp_timepoint)[0])[-1]]\\n #future_timepoint = true_inds[np.sort(np.where(true_inds > temp_timepoint)[0])[0]]\\n\\n\\n #Be sure there is at least one future timepoint and one past timepoint.\\n #If there isn't, then grab either two past or two future timepoints and use those\\n #for interpolation. If there aren't even two total past + future timepoints, then\\n #just set the output to 0. Could also set the output to be unadjusted, but this\\n #is a way to make the issue more obvious.\\n temp_past_timepoint = np.sort(np.where(true_inds < temp_timepoint)[0])\\n temp_future_timepoint = np.sort(np.where(true_inds > temp_timepoint)[0])\\n\\n #If we don't have enough data to interpolate/extrapolate\\n if len(temp_past_timepoint) + len(temp_future_timepoint) < 2:\\n\\n signal_copy[temp_timepoint] = 0\\n\\n #If we do have enough data to interpolate/extrapolate\\n else:\\n\\n if len(temp_past_timepoint) == 0:\\n past_timepoint = true_inds[temp_future_timepoint[1]]\\n else:\\n past_timepoint = true_inds[temp_past_timepoint[-1]]\\n\\n if len(temp_future_timepoint) == 0:\\n future_timepoint = true_inds[temp_past_timepoint[-2]]\\n else:\\n future_timepoint = true_inds[temp_future_timepoint[0]]\\n\\n #Find the appopriate past/future values\\n past_value = signal_copy[int(past_timepoint)]\\n future_value = signal_copy[int(future_timepoint)]\\n\\n #Use the interp1d function for interpolation\\n interp_object = interp.interp1d([past_timepoint, future_timepoint], [past_value, future_value], bounds_error=False, fill_value='extrapolate')\\n signal_copy[temp_timepoint] = interp_object(temp_timepoint).item(0)\\n\\n return signal_copy\\n\\n\\n #For cubic spline interpolation, instead of taking the past/future timepoint\\n #we will just take the closest 5 timepoints. If there aren't 5 timepoints, we will\\n #set the output to 0\\n if interp_type == 'cubic_spline':\\n\\n sorted_good = np.sort(signal_copy[true_inds])\\n min_bound = sorted_good[0]\\n max_bound = sorted_good[-1]\\n\\n #Continue if there are at least 5 good inds\\n true_inds_needed = 5\\n if len(true_inds) >= true_inds_needed:\\n\\n for temp_timepoint in false_inds:\\n\\n closest_inds = true_inds[np.argsort(np.absolute(true_inds - temp_timepoint))]\\n closest_vals = signal_copy[closest_inds.astype(int)]\\n interp_object = interp.interp1d(closest_inds, closest_vals, kind = 'cubic', bounds_error=False, fill_value='extrapolate')\\n signal_copy[temp_timepoint.astype(int)] = interp_object(temp_timepoint).item(0)\\n\\n min_bound_exceded = np.where(signal_copy < min_bound)[0]\\n if len(min_bound_exceded) > 0:\\n\\n signal_copy[min_bound_exceded] = min_bound\\n\\n max_bound_exceded = np.where(signal_copy > max_bound)[0]\\n if len(max_bound_exceded) > 0:\\n\\n signal_copy[max_bound_exceded] = max_bound\\n\\n #If there aren't enough good timepoints, then set the bad timepoints = 0\\n else:\\n\\n signal_copy[false_inds.astype(int)] = 0\\n\\n\\n return signal_copy\\n\\n\\n if interp_type == 'spectral':\\n\\n signal_copy = spectral_interpolation(timepoint_defined, signal_copy, TR)\\n\\n return signal_copy\",\n \"def interpolate(self, interpolation=\\\"nearest\\\", **kwargs):\\n return podpac.interpolators.Interpolate(source=self, interpolation=interpolation, **kwargs)\",\n \"def InterpolationDerivs(self, , p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=..., p_float=...):\\n ...\",\n \"def test_linear_interpolation_nan_points(self):\\n\\n # Define pixel centers along each direction\\n x = [1.0, 2.0, 4.0]\\n y = [5.0, 9.0]\\n\\n # Define ny by nx array with corresponding values\\n A = numpy.zeros((len(x), len(y)))\\n\\n # Define values for each x, y pair as a linear function\\n for i in range(len(x)):\\n for j in range(len(y)):\\n A[i, j] = linear_function(x[i], y[j])\\n\\n # Then test that interpolated points can contain NaN\\n xis = numpy.linspace(x[0], x[-1], 10)\\n etas = numpy.linspace(y[0], y[-1], 10)\\n xis[6:7] = numpy.nan\\n etas[3] = numpy.nan\\n points = combine_coordinates(xis, etas)\\n\\n vals = interpolate2d(x, y, A, points, mode='linear')\\n refs = linear_function(points[:, 0], points[:, 1])\\n assert nanallclose(vals, refs, rtol=1e-12, atol=1e-12)\",\n \"def test_interpolation_corner_cases(self):\\n\\n # Define four pixel centers\\n x = [2.0, 4.0]\\n y = [5.0, 9.0]\\n\\n # Define ny by nx array with corresponding values\\n A = numpy.zeros((len(x), len(y)))\\n\\n # Define values for each x, y pair as a linear function\\n for i in range(len(x)):\\n for j in range(len(y)):\\n A[i, j] = linear_function(x[i], y[j])\\n\\n # Test that interpolated points are correct\\n xis = numpy.linspace(x[0], x[-1], 3)\\n etas = numpy.linspace(y[0], y[-1], 3)\\n points = combine_coordinates(xis, etas)\\n\\n # Interpolate to cropped grids\\n for xc, yc, Ac in [([x[0]], [y[0]], numpy.array([[A[0, 0]]])), # 1 x 1\\n ([x[0]], y, numpy.array([A[0, :]])), # 1 x 2\\n ]:\\n\\n vals = interpolate2d(xc, yc, Ac, points, mode='linear')\\n msg = 'Expected NaN when grid %s is incomplete' % str(Ac.shape)\\n assert numpy.all(numpy.isnan(vals)), msg\",\n \"def interpolate_linear(self, transect):\\n\\n u = np.copy(self.u_mps)\\n v = np.copy(self.v_mps)\\n\\n valid = np.isnan(u) == False\\n\\n # Check for valid data\\n if sum(valid) > 1 and sum(self.valid_data[0, :]) > 1:\\n\\n # Compute ens_time\\n ens_time = np.nancumsum(transect.date_time.ens_duration_sec)\\n\\n # Apply linear interpolation\\n self.u_processed_mps = np.interp(x=ens_time,\\n xp=ens_time[self.valid_data[0, :]],\\n fp=u[self.valid_data[0, :]],\\n left=np.nan,\\n right=np.nan)\\n # Apply linear interpolation\\n self.v_processed_mps = np.interp(x=ens_time,\\n xp=ens_time[self.valid_data[0, :]],\\n fp=v[self.valid_data[0, :]],\\n left=np.nan,\\n right=np.nan)\",\n \"def InterpolatePoint(self, p_int, vtkDataSetAttributes, vtkIdList, *float, **kwargs):\\n ...\",\n \"def interpolate(self):\\n print(\\\"Interpolating points...\\\")\\n interpolated_points = set()\\n if os.cpu_count():\\n processes = os.cpu_count()\\n print(f\\\"Running on all {processes} cores.\\\")\\n else:\\n processes = 1\\n length = len(self.main_cluster)\\n delta = math.ceil(length / processes)\\n manager = Manager()\\n result_map = manager.dict()\\n jobs = []\\n for index in range(processes):\\n start = index * delta\\n stop = (index + 1) * delta\\n if stop > length:\\n stop = length\\n p = Process(target=worker, args=(start, stop,\\n result_map, index,\\n self.distances,\\n self.interpolation_threshold,\\n self.main_cluster,\\n self.color_lookup_table_points))\\n jobs.append(p)\\n p.start()\\n\\n for proc in jobs:\\n proc.join()\\n\\n for index in result_map.keys():\\n print(index)\\n interpolated_points.update(result_map[index])\\n\\n main_points = [self.get_value_tuple(index) for index in self.main_cluster]\\n interpolated_points.update(main_points)\\n\\n print(\\\"Finished interpolation!\\\")\\n\\n self.interpolated_points = list(interpolated_points)\",\n \"def see_what_its_doing_1d():\\n all_points = create_points_with_random_pollution_1d(100, 100, 10)\\n picked_points = pick_uniform_random_points(all_points, 20)\\n interpolated_points = interpolate_unknown_points(picked_points, all_points)\\n\\n picked_x = []\\n picked_pollution = []\\n for label, point in picked_points.items():\\n picked_x.append(label)\\n picked_pollution.append(point.get_pollution_value())\\n\\n interp_x = []\\n inter_pollution = []\\n\\n for label, point in interpolated_points.items():\\n if not label in picked_x:\\n interp_x.append(label)\\n inter_pollution.append(point.get_pollution_value())\\n\\n plt.plot(picked_x, picked_pollution, \\\"ro\\\", interp_x, inter_pollution, \\\"go\\\")\\n plt.xlabel(\\\"Point Label\\\")\\n plt.ylabel(\\\"Pollution Value\\\")\\n plt.show()\",\n \"def see_what_its_doing_1d():\\n all_points = create_points_with_random_pollution_1d(100, 100, 10)\\n picked_points = pick_uniform_random_points(all_points, 20)\\n interpolated_points = interpolate_unknown_points(picked_points, all_points)\\n\\n picked_x = []\\n picked_pollution = []\\n for label, point in picked_points.items():\\n picked_x.append(label)\\n picked_pollution.append(point.get_pollution_value())\\n\\n interp_x = []\\n inter_pollution = []\\n\\n for label, point in interpolated_points.items():\\n if not label in picked_x:\\n interp_x.append(label)\\n inter_pollution.append(point.get_pollution_value())\\n\\n plt.plot(picked_x, picked_pollution, \\\"ro\\\", interp_x, inter_pollution, \\\"go\\\")\\n plt.xlabel(\\\"Point Label\\\")\\n plt.ylabel(\\\"Pollution Value\\\")\\n plt.show()\",\n \"def see_what_its_doing_1d():\\n all_points = create_points_with_random_pollution_1d(100, 100, 10)\\n picked_points = pick_uniform_random_points(all_points, 20)\\n interpolated_points = interpolate_unknown_points(picked_points, all_points)\\n\\n picked_x = []\\n picked_pollution = []\\n for label, point in picked_points.items():\\n picked_x.append(label)\\n picked_pollution.append(point.get_pollution_value())\\n\\n interp_x = []\\n inter_pollution = []\\n\\n for label, point in interpolated_points.items():\\n if not label in picked_x:\\n interp_x.append(label)\\n inter_pollution.append(point.get_pollution_value())\\n\\n plt.plot(picked_x, picked_pollution, \\\"ro\\\", interp_x, inter_pollution, \\\"go\\\")\\n plt.xlabel(\\\"Point Label\\\")\\n plt.ylabel(\\\"Pollution Value\\\")\\n plt.show()\",\n \"def test_isentropic_pressure_interp():\\n lev = [100000., 95000., 90000., 85000.] * units.Pa\\n tmp = np.ones((4, 5, 5))\\n tmp[0, :] = 296.\\n tmp[1, :] = 292.\\n tmp[2, :] = 290\\n tmp[3, :] = 288.\\n tmpk = tmp * units.kelvin\\n isentlev = [296., 297] * units.kelvin\\n isentprs = isentropic_interpolation(isentlev, lev, tmpk)\\n trueprs = 936.213 * units.hPa\\n assert_almost_equal(isentprs[0][1], trueprs, 3)\",\n \"def test_call_interpolate(self):\\r\\n # Verified with iNEXT (http://glimmer.rstudio.com/tchsieh/inext/).\\r\\n # SE estimates differ because they use a different technique. SE\\r\\n # estimates have been verified against values in Colwell 2012 instead\\r\\n # (in separate unit tests).\\r\\n\\r\\n # Just reference.\\r\\n obs = self.estimator1(start=15, stop=15, num_steps=1)\\r\\n self.assertEqual(obs.getSampleCount(), 1)\\r\\n assert_almost_equal(obs.getEstimates('S1'),\\r\\n [(15, 5, 0.674199862463, 3.67859255119, 6.32140744881)])\\r\\n\\r\\n # start=1 and reference.\\r\\n obs = self.estimator1(start=1, stop=1, num_steps=1)\\r\\n self.assertEqual(obs.getSampleCount(), 1)\\r\\n assert_almost_equal(obs.getEstimates('S1'),\\r\\n [(1, 1.0, 0.250252397843, 0.509514313183, 1.49048568682),\\r\\n (15, 5, 0.674199862463, 3.67859255119, 6.32140744881)])\\r\\n\\r\\n # Points in between start=1 and reference.\\r\\n obs = self.estimator1(start=1, stop=15, num_steps=3)\\r\\n self.assertEqual(obs.getSampleCount(), 1)\\r\\n assert_almost_equal(obs.getEstimates('S1'),\\r\\n [(1, 1.0, 0.250252397843, 0.509514313183, 1.49048568682),\\r\\n (5, 3.40326340326, 0.655024590447, 2.119438797,\\r\\n 4.68708800953),\\r\\n (9, 4.4001998002, 0.680106580075,\\r\\n 3.0672153976, 5.7331842028),\\r\\n (13, 4.85714285714, 0.665379090563, 3.55302380357,\\r\\n 6.16126191071),\\r\\n (15, 5, 0.674199862463, 3.67859255119, 6.32140744881)])\",\n \"def _larange_interpolate(x, points):\\n p = PRIME\\n k = len(points)\\n xs, ys = [], []\\n for pt in points:\\n xs.append(pt.X)\\n ys.append(pt.Y)\\n assert k == len(set(xs)), \\\"Points must be destinct.\\\"\\n nums = [] # numerators\\n dens = [] # denominators calculated individually to prevent float div errors\\n for i in range(k):\\n others = list(xs)\\n cur = others.pop(i) # current x value\\n nums.append(product(x - o for o in others))\\n dens.append(product(cur - o for o in others))\\n den = product(dens) # common denominator\\n num = sum([_divmod(nums[i] * den * ys[i] % p, dens[i], p) for i in range(k)])\\n return _divmod(num, den, p) % p\",\n \"def bilinear_interpolation(self, pt1, pt2, pt3, pt4, unknown):\\n\\n # Write your code for bilinear interpolation here\\n # May b you can reuse or call linear interpolatio method to compute this task\\n \\n X1,Y1, intensity1 = pt1\\n X2,Y2, intensity2 = pt2\\n X3,Y3, intensity3 = pt3\\n X4,Y4, intensity4 = pt4\\n newPointX1,newPointY1 = unknown\\n\\n newpt1=self.linear_interpolation((X1,intensity1),(X2,intensity2),newPointX1)\\n newpt2=self.linear_interpolation((X3,intensity3),(X4,intensity4),newPointX1)\\n newpt1=Y1,newpt1\\n newpt2=Y4,newpt2\\n intensity=self.linear_interpolation(newpt1,newpt2,newPointY1)\\n \\n \\n\\n return intensity\",\n \"def test_1d_linear_interpolation_basic(self):\\n\\n # Define pixel centers along each direction\\n x = [1.0, 2.0, 4.0]\\n\\n # Define array with corresponding values\\n A = numpy.zeros((len(x)))\\n\\n # Define values for each xas a linear function\\n for i in range(len(x)):\\n A[i] = linear_function(x[i], 0)\\n\\n # Test first that original points are reproduced correctly\\n for i, xi in enumerate(x):\\n val = interpolate1d(x, A, [xi], mode='linear')[0]\\n ref = linear_function(xi, 0)\\n assert numpy.allclose(val, ref, rtol=1e-12, atol=1e-12)\\n\\n # Then test that genuinly interpolated points are correct\\n xis = numpy.linspace(x[0], x[-1], 10)\\n points = xis\\n\\n vals = interpolate1d(x, A, points, mode='linear')\\n refs = linear_function(points, 0)\\n assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)\\n\\n # Exercise bounds_error flag\\n vals = interpolate1d(x, A, points, mode='linear',\\n bounds_error=True)\\n refs = linear_function(points, 0)\\n assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)\",\n \"def interpolate(self, xs):\\n tck = splrep(self._xs, self._ys)\\n new_ys = splev(xs, tck, der=0)\\n return new_ys\",\n \"def test_interpolation_random_array_and_nan(self):\\n\\n # Define pixel centers along each direction\\n x = numpy.arange(20) * 1.0\\n y = numpy.arange(25) * 1.0\\n\\n # Define ny by nx array with corresponding values\\n A = numpy.zeros((len(x), len(y)))\\n\\n # Define arbitrary values for each x, y pair\\n numpy.random.seed(17)\\n A = numpy.random.random((len(x), len(y))) * 10\\n\\n # Create islands of NaN\\n A[5, 13] = numpy.nan\\n A[6, 14] = A[6, 18] = numpy.nan\\n A[7, 14:18] = numpy.nan\\n A[8, 13:18] = numpy.nan\\n A[9, 12:19] = numpy.nan\\n A[10, 14:17] = numpy.nan\\n A[11, 15] = numpy.nan\\n\\n A[15, 5:6] = numpy.nan\\n\\n # Creat interpolation points\\n xis = numpy.linspace(x[0], x[-1], 39) # Hit all mid points\\n etas = numpy.linspace(y[0], y[-1], 73) # Hit thirds\\n points = combine_coordinates(xis, etas)\\n\\n for mode in ['linear', 'constant']:\\n vals = interpolate2d(x, y, A, points, mode=mode)\\n\\n # Calculate reference result with expected NaNs and compare\\n i = j = 0\\n for k, (xi, eta) in enumerate(points):\\n\\n # Find indices of nearest higher value in x and y\\n i = numpy.searchsorted(x, xi)\\n j = numpy.searchsorted(y, eta)\\n\\n if i > 0 and j > 0:\\n\\n # Get four neigbours\\n A00 = A[i - 1, j - 1]\\n A01 = A[i - 1, j]\\n A10 = A[i, j - 1]\\n A11 = A[i, j]\\n\\n if numpy.allclose(xi, x[i]):\\n alpha = 1.0\\n else:\\n alpha = 0.5\\n\\n if numpy.allclose(eta, y[j]):\\n beta = 1.0\\n else:\\n beta = eta - y[j - 1]\\n\\n if mode == 'linear':\\n if numpy.any(numpy.isnan([A00, A01, A10, A11])):\\n ref = numpy.nan\\n else:\\n ref = (A00 * (1 - alpha) * (1 - beta) +\\n A01 * (1 - alpha) * beta +\\n A10 * alpha * (1 - beta) +\\n A11 * alpha * beta)\\n elif mode == 'constant':\\n assert alpha >= 0.5 # Only case in this test\\n\\n if beta < 0.5:\\n ref = A10\\n else:\\n ref = A11\\n else:\\n msg = 'Unknown mode: %s' % mode\\n raise Exception(msg)\\n\\n #print i, j, xi, eta, alpha, beta, vals[k], ref\\n assert nanallclose(vals[k], ref, rtol=1e-12, atol=1e-12)\",\n \"def interpol(self,x,y,x1):\\n \\n N = len(x)\\n i = np.minimum(np.maximum(np.searchsorted(x,x1,side='right'),1),N-1)\\n xl = x[i-1]\\n xr = x[i]\\n yl = y[i-1]\\n yr = y[i]\\n y1 = yl + (yr-yl)/(xr-xl) * (x1-xl)\\n above = x1 > x[-1]\\n below = x1 < x[0]\\n y1 = np.where(above,y[-1] + (x1 - x[-1]) * (y[-1]-y[-2])/(x[-1]-x[-2]), y1)\\n y1 = np.where(below,y[0],y1)\\n \\n return y1, i\",\n \"def _interpolation(matrix):\\n try:\\n\\tok = ~np.isnan(matrix)\\n \\txp = ok.ravel().nonzero()[0]\\n \\tfp = matrix[~np.isnan(matrix)]\\n \\tx = np.isnan(matrix).ravel().nonzero()[0]\\n \\tmatrix[np.isnan(matrix)] = np.interp(x, xp, fp)\\n \\treturn matrix\\n except:\\n return matrix\",\n \"def interpolate(self, known_coords, known_values, interp_coords, groupname):\\n\\t\\t#Find which interpolation method is desired\\n\\t\\tif self.interp_method == \\\"Grid Linear\\\":\\n\\t\\t\\tinterp_values = self.grid_interpolation_linear(known_coords=known_coords, known_values=known_values, interp_coords=interp_coords, groupname=groupname)\\n\\t\\telif self.interp_method == \\\"Linear\\\":\\n\\t\\t\\tfrom scipy.interpolate import griddata\\n\\t\\t\\tinterp_values = self.interpolate_linear(known_coords=known_coords, known_values=known_values, interp_coords=interp_coords, groupname=groupname)\\n\\t\\telse:\\n\\t\\t\\t#Should raise error\\n\\t\\t\\tpass\\n\\t\\t\\n\\t\\treturn interp_values\",\n \"def interpolatePoints(pts, numBetween):\\n if numBetween <= 0:\\n return pts\\n #create new vector w/ original points distributed evenly\\n numPts = len(pts) + (len(pts)-1)*numBetween\\n densePts = np.zeros((numPts,3))\\n densePts[0::numBetween+1] = pts\\n \\n #create interpolated points\\n for idx in range(0, numPts-1, numBetween+1):\\n pt0 = densePts[idx]\\n pt1 = densePts[idx+numBetween+1]\\n dxyz = (pt1 - pt0)/float(numBetween+1)\\n for ii in range(1,numBetween+1):\\n densePts[idx+ii] = pt0 + dxyz*ii\\n return densePts\",\n \"def interpolate_point(xi, x, y):\\n num_pts = len(x)\\n if num_pts%2==0:\\n #Even\\n i_h2 = num_pts/2\\n i_h1 = num_pts/2 - 1\\n if x[i_h2] < xi:\\n return interpolate_point(xi, x[i_h2:], y[0:i_h2:])\\n elif x[i_h1] > xi:\\n return interpolate_point(xi, x[0:i_h1], y[0:i_h1])\\n else:\\n return ((xi-x[i_h1])*y[i_h2]+(x[i_h2]-xi)*y[i_h1])/(x[i_h2]-x[i_h1])\\n else:\\n #Odd\\n i_half = num_pts/2\\n if x[i_half] < xi:\\n return interpolate_point(xi, x[i_half:], y[i_half:])\\n elif x[i_half] > xi:\\n return interpolate_point(xi, x[0:i_half+1], y[0:i_half+1])\\n else:\\n return y[i_half]\",\n \"def interpol(newx, x, y, wrap=None, **kwargs):\\n if 'baddata' in kwargs:\\n y = np.ma.masked_equal(y, kwargs['baddata'])\\n x = np.ma.masked_array(x)\\n x.mask = y.mask\\n kwargs.__delitem__('baddata')\\n else:\\n tst = np.ma.core.MaskedArray\\n if type(x)!=tst or type(y)!=tst or type(newx)!=tst:\\n x = np.ma.masked_array(x)\\n y = np.ma.masked_array(y)\\n newx = np.ma.masked_array(newx)\\n\\n def wrap_interp(xout, xin, yin, sect):\\n dpsect=360/sect\\n yc = np.cos(np.deg2rad(y*dpsect))\\n ys = np.sin(np.deg2rad(y*dpsect))\\n new_yc = np.interp(newx, x.compressed(), yc.compressed(), **kwargs)\\n new_ys = np.interp(newx, x.compressed(), ys.compressed(), **kwargs)\\n try:\\n new_bad = np.interp(newx, x, y.mask)\\n except ValueError:\\n new_bad = np.zeros((len(newx)))\\n newy = np.rad2deg(np.arctan(new_ys/new_yc))/dpsect\\n #1st quadrant is O.K\\n #2nd quadrant\\n idx = [n for n in range(len(new_yc)) if new_yc[n]<0 and new_ys[n]>0]\\n newy[idx] = sect/2 + newy[idx]\\n #print('Sector 2 inds: %s' % idx)\\n #3rd quadrant\\n idx = [n for n in range(len(new_yc)) if new_yc[n]<0 and new_ys[n]<0]\\n newy[idx] = sect/2 + newy[idx]\\n #print('Sector 3 inds: %s' % idx)\\n #4th quadrant\\n idx = [n for n in range(len(new_yc)) if new_yc[n]>0 and new_ys[n]<0]\\n newy[idx] = sect + newy[idx]\\n #print('Sector 4 inds: %s' % idx)\\n new_bad = np.ma.make_mask(new_bad)\\n newy = np.ma.masked_array(newy, mask=new_bad)\\n return newy\\n\\n if wrap=='hour':\\n newy = wrap_interp(newx, x.compressed(), y.compressed(), 24)\\n elif wrap=='lon':\\n newy = wrap_interp(newx, x.compressed(), y.compressed(), 360)\\n elif isinstance(wrap, numbers.Real):\\n newy = wrap_interp(newx, x.compressed(), y.compressed(), wrap)\\n else:\\n newy = np.interp(newx, x.compressed(), y.compressed(), **kwargs)\\n return newy\",\n \"def interpolate(self, interp):\\n x = np.linspace(0, 29, len(self.ya))\\n f_ya = interpolate.interp1d(x, self.ya)\\n f_yv = interpolate.interp1d(x, self.yv)\\n f_pa = interpolate.interp1d(x, np.reshape(self.pa, [-1]))\\n f_pv = interpolate.interp1d(x, np.reshape(self.pv, [-1]))\\n\\n x_interp = np.linspace(0, 29, len(self.ya)*interp)\\n self.ya = list(f_ya(x_interp))\\n self.yv = list(f_yv(x_interp))\\n self.pa = list(f_pa(x_interp))\\n self.pv = list(f_pv(x_interp))\",\n \"def interpolate_smooth(self, transect):\\n\\n # Get data from object\\n\\n u = np.copy(self.u_mps)\\n v = np.copy(self.v_mps)\\n u[self.valid_data[0, :] == False] = np.nan\\n v[self.valid_data[0, :] == False] = np.nan\\n\\n # Compute ens_time\\n ens_time = np.nancumsum(transect.date_time.ens_duration_sec)\\n\\n # Apply smooth to each component\\n u_smooth = rloess(ens_time, u, 10)\\n v_smooth = rloess(ens_time, v, 10)\\n\\n # Save data in object\\n self.u_processed_mps = u\\n self.v_processed_mps = v\\n self.u_processed_mps[np.isnan(u)] = u_smooth[np.isnan(u)]\\n self.v_processed_mps[np.isnan(v)] = v_smooth[np.isnan(v)]\",\n \"def interpolate(i0, d0, i1, d1):\\n if i0 == i1:\\n return [d0]\\n values = []\\n a = (d1 - d0) / (i1 - i0)\\n d = d0\\n for i in range(i0,i1+1):\\n values.append(d)\\n d = d + a\\n return values\",\n \"def test_isentropic_pressure_addition_args_interp():\\n lev = [100000., 95000., 90000., 85000.] * units.Pa\\n tmp = np.ones((4, 5, 5))\\n tmp[0, :] = 296.\\n tmp[1, :] = 292.\\n tmp[2, :] = 290.\\n tmp[3, :] = 288.\\n rh = np.ones((4, 5, 5))\\n rh[0, :] = 100.\\n rh[1, :] = 80.\\n rh[2, :] = 40.\\n rh[3, :] = 20.\\n relh = rh * units.percent\\n tmpk = tmp * units.kelvin\\n isentlev = [296., 297.] * units.kelvin\\n isentprs = isentropic_interpolation(isentlev, lev, tmpk, relh)\\n truerh = 69.197 * units.percent\\n assert_almost_equal(isentprs[1][1], truerh, 3)\",\n \"def interpolate_timeseries(self, x, t, **kw):\\n v, t_v = self.timeseries(x, rmnans=True)\\n kw.update(dict(bounds_error=False))\\n interpolant = sp.interpolate.interp1d(t_v, v, **kw)\\n return interpolant(t)\",\n \"def linear_interpolate(x, x0, y0, x1, y1):\\n try:\\n return (y0 * (x1 - x) + y1 * (x - x0)) / (x1 - x0)\\n except ZeroDivisionError:\\n return 0.0\",\n \"def interpolate(self):\\n interp = (\\n self._get_ticks() - self._last_update\\n ) / self._tick_step / self.dilation\\n if interp > 1.0:\\n interp = 1.0\\n return interp\",\n \"def interpolate(self, distances):\\n cs = interp1d(self.distances, self.altitudes, fill_value='extrapolate')\\n return cs(distances)\",\n \"def test_isentropic_pressure_4d():\\n lev = [100000., 95000., 90000., 85000.] * units.Pa\\n tmp = np.ones((3, 4, 5, 5))\\n tmp[:, 0, :] = 296.\\n tmp[:, 1, :] = 292.\\n tmp[:, 2, :] = 290\\n tmp[:, 3, :] = 288.\\n tmpk = tmp * units.kelvin\\n rh = np.ones((3, 4, 5, 5))\\n rh[:, 0, :] = 100.\\n rh[:, 1, :] = 80.\\n rh[:, 2, :] = 40.\\n rh[:, 3, :] = 20.\\n relh = rh * units.percent\\n isentlev = [296., 297., 300.] * units.kelvin\\n isentprs = isentropic_interpolation(isentlev, lev, tmpk, relh, vertical_dim=1)\\n trueprs = 1000. * units.hPa\\n trueprs2 = 936.213 * units.hPa\\n trueprs3 = 879.50375588 * units.hPa\\n truerh = 69.19706 * units.percent\\n assert isentprs[0].shape == (3, 3, 5, 5)\\n assert_almost_equal(isentprs[0][:, 0, :], trueprs, 3)\\n assert_almost_equal(isentprs[0][:, 1, :], trueprs2, 3)\\n assert_almost_equal(isentprs[0][:, 2, :], trueprs3, 3)\\n assert_almost_equal(isentprs[1][:, 1, ], truerh, 3)\",\n \"def interp_flight(oflight, npts, timestep=55):\\n\\n # Let's start with a full copy of the original, and update it as we go\\n iflight = copy.deepcopy(oflight)\\n\\n rough_delta = iflight.flighttime.seconds/np.float(npts)\\n delta = np.around(rough_delta, decimals=0)\\n # i == number of legs\\n # j == total number of points in flight plan\\n i = 0\\n j = 0\\n for leg in iflight.legs:\\n if len(leg.utcdt) > 1:\\n # Construct our point timings, done poorly but quickly\\n filler = np.arange(leg.relative_time[0],\\n leg.relative_time[-1]+delta,\\n delta)\\n # If we popped over, just stop at the leg boundary regardless\\n if filler[-1] > leg.relative_time[-1]:\\n filler[-1] = leg.relative_time[-1]\\n\\n # Check if mhdg or thdg has a zero point crossing that will confuse\\n # the simple minded interpolation that's about to happen\\n\\n# print \\\"ORIG THDG:\\\", leg.mhdg\\n# print \\\"ORIG MHDG:\\\", leg.thdg\\n # This is some pretty dirty logic for right now. Needs cleaning up.\\n uprange = False\\n for k, hdg in enumerate(leg.mhdg):\\n if k != 0:\\n # Check the previous and the current; if it crosses zero,\\n # then add 360 to keep it monotonicly increasing\\n # Do this for both magnetic and true headings\\n if leg.mhdg[k-1] >= 350. and leg.mhdg[k] < 10:\\n uprange = True\\n if uprange is True:\\n leg.mhdg[k] += 360.\\n if leg.thdg[k-1] >= 350. and leg.thdg[k] < 10:\\n uprange = True\\n if uprange is True:\\n leg.thdg[k] += 360.\\n if uprange is True:\\n pass\\n\\n # Actually interpolate the points...add more in this style as need\\n latprimer = spi.interp1d(leg.relative_time,\\n leg.lat, kind='linear')\\n lonprimer = spi.interp1d(leg.relative_time,\\n leg.long, kind='linear')\\n thdgprimer = spi.interp1d(leg.relative_time,\\n leg.thdg, kind='linear')\\n mhdgprimer = spi.interp1d(leg.relative_time,\\n leg.mhdg, kind='linear')\\n\\n # Replacing the existing stuff with the interpolated values\\n leg.lat = latprimer(filler)\\n leg.long = lonprimer(filler)\\n leg.thdg = thdgprimer(filler) % 360.\\n leg.mhdg = mhdgprimer(filler) % 360.\\n\\n # Use a stubby little function instead of a loop. Better?\\n # Need to explicitly list() map() in Python3 to operate on it\\n # the same way as in Python2\\n filler = list(map(go_dt, filler))\\n leg.relative_time = filler\\n\\n # Recreate timestamps for the new interpolated set, both dt and iso\\n # formatted objects for easy interactions\\n leg.utcdt = leg.relative_time + np.repeat(iflight.takeoff,\\n len(filler))\\n leg.utc = list(map(go_iso, leg.utcdt))\\n\\n j += len(leg.long)\\n i += 1\\n\\n# print \\\"Interpolated %s to roughly fit %d points total,\\\" % \\\\\\n# (oflight.filename, npts)\\n# print \\\"with a delta_t of %06.1f; ended up with %d points total.\\\" % \\\\\\n# (delta, j)\\n\\n return iflight\",\n \"def extrapolate_nans(x, y, v):\\n if numpy.ma.is_masked(v):\\n nans = v.mask\\n else:\\n nans = numpy.isnan(v)\\n notnans = numpy.logical_not(nans)\\n v[nans] = scipy.interpolate.griddata((x[notnans], y[notnans]), v[notnans],\\n (x[nans], y[nans]),\\n method='nearest').ravel()\\n return v\",\n \"def fill_missing_data_points(data):\\n return data.interpolate()\",\n \"def interpolate(self, image):\\n return\",\n \"def test_linear_interpolation_basic(self):\\n\\n # Define pixel centers along each direction\\n x = [1.0, 2.0, 4.0]\\n y = [5.0, 9.0]\\n\\n # Define ny by nx array with corresponding values\\n A = numpy.zeros((len(x), len(y)))\\n\\n # Define values for each x, y pair as a linear function\\n for i in range(len(x)):\\n for j in range(len(y)):\\n A[i, j] = linear_function(x[i], y[j])\\n\\n # Test first that original points are reproduced correctly\\n for i, xi in enumerate(x):\\n for j, eta in enumerate(y):\\n val = interpolate2d(x, y, A, [(xi, eta)], mode='linear')[0]\\n ref = linear_function(xi, eta)\\n assert numpy.allclose(val, ref, rtol=1e-12, atol=1e-12)\\n\\n # Then test that genuinly interpolated points are correct\\n xis = numpy.linspace(x[0], x[-1], 10)\\n etas = numpy.linspace(y[0], y[-1], 10)\\n points = combine_coordinates(xis, etas)\\n\\n vals = interpolate2d(x, y, A, points, mode='linear')\\n refs = linear_function(points[:, 0], points[:, 1])\\n assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)\",\n \"def interpolate_missing(y):\\n if y.isna().any():\\n y = y.interpolate(method='linear', limit_direction='both')\\n return y\",\n \"def pad(input_data):\\n # source : https://stackoverflow.com/questions/6518811/interpolate-nan-values-in-a-numpy-array \\n data = input_data.copy()\\n bad_indexes = np.isnan(data)\\n good_indexes = np.logical_not(bad_indexes)\\n good_data = data[good_indexes]\\n interpolated = np.interp(bad_indexes.nonzero()[0], good_indexes.nonzero()[0], good_data)\\n data[bad_indexes] = interpolated\\n return data\",\n \"def interpolate_ephemeris(self):\\n #Compute the offsets into the lookup tables\\n startemiss, stopemiss = self.get_emissivity_offsets()\\n hourslice, starttime = self.get_hour_offsets()\\n latslice = self.get_lat_offsets()\\n \\n #Compute the start and stop dates\\n startdata = self.extract_season(self.startseason,startemiss,\\n hourslice, latslice)\\n stopdata = self.extract_season(self.stopseason,startemiss,\\n hourslice, latslice)\\n # Interpolate Season\\n seasons = [self.startseason, self.stopseason]\\n season_f = compute_interpolation_function(seasons, [startdata, stopdata], 'linear')\\n data = season_f(self.season)\\n #Interpolate time\\n self.data = self.interpolatehour(hourslice, starttime, data)\",\n \"def interpolate_linear(self, known_coords, known_values, interp_coords, groupname):\\n\\t\\t#First need to reshape known_coords and known_values\\n\\t\\tn_params = self.signal[groupname]['dimension']\\n\\t\\tknown_coords = np.reshape( known_coords, (-1,n_params) )\\n\\t\\tknown_values = np.reshape( known_values, (-1) )\\t\\t\\n\\t\\treturn griddata(known_coords, known_values, interp_coords, method='linear')\",\n \"def interpolate_loss_calculation(self, interpolates):\\n _, fake_scores = self.D(interpolates)\\n return fake_scores\",\n \"def profile_interp(var,z_orig,z_interp,method='linear',out_of_bounds='NaN'):\\n z_orig = z_orig[~isnan(z_orig)]\\n var= var[~isnan(var)]\\n #assert(all(diff(z_orig) > 0))\\n if len(z_orig) > len(var) or len(var) > len(z_orig): return NaN\\n if len(z_orig) <= 2 or len(var) <= 2: return NaN\\n \\n if out_of_bounds == 'NaN':\\n interpolant = interpolate.interp1d(z_orig,var,kind=method,bounds_error=False,fill_value=NaN)\\n elif out_of_bounds == 'nearest':\\n interpolant = interpolate.interp1d(z_orig,var,kind=method,bounds_error=False,fill_value=(var[0],var[-1]))\\n elif out_of_bounds == 'extrap':\\n interpolant = interpolate.interp1d(z_orig,var,kind=method,bounds_error=False,fill_value='extrapolate')\\n else:\\n raise ValueError('Extrapolation method must be NaN, nearest, or cubic.')\\n result = interpolant(z_interp)\\n\\n if result.size == 1: return result.item()\\n else: return result\",\n \"def interpolate(x0, y0, x1, y1, x):\\n y = (y0 * (x1 - x) + y1 * (x - x0)) / (x1 - x0)\\n\\n return y\",\n \"def test_isentropic_pressure_data_bounds_error():\\n lev = [100000., 95000., 90000., 85000.] * units.Pa\\n tmp = np.ones((4, 5, 5))\\n tmp[0, :] = 296.\\n tmp[1, :] = 292.\\n tmp[2, :] = 290.\\n tmp[3, :] = 288.\\n tmpk = tmp * units.kelvin\\n isentlev = [296., 350.] * units.kelvin\\n with pytest.raises(ValueError):\\n isentropic_interpolation(isentlev, lev, tmpk)\",\n \"def interp_spherical_data(x1, y1, x2, y2, lon, lat, J, m1, great_circle = False):\\n\\n background_x, background_y = m1(lon, lat)\\n\\n if great_circle == False:\\n interp_lons = np.linspace(x1, x2, 100)\\n interp_lats = np.linspace(y1, y2, 100)\\n interp_x, interp_y = m1(interp_lons, interp_lats)\\n\\n else:\\n great_circle = m1.drawgreatcircle(x1, y1, x2, y2, del_s = 50., alpha = 1.0, color = \\\"w\\\", zorder = 102)\\n interp_x = great_circle[0].get_data()[0] \\n interp_y = great_circle[0].get_data()[1]\\n\\n output_data = scipy.interpolate.griddata(list(zip(background_x, background_y)), jr1, list(zip(interp_x, interp_y)), method = 'cubic')\\n\\n output_lon, output_lat = m1(interp_x, interp_y, inverse = True)\\n return output_data, output_lon, output_lat\",\n \"def interpolate_composite(self, transect):\\n\\n u = np.copy(self.u_processed_mps)\\n v = np.copy(self.v_processed_mps)\\n\\n valid = np.isnan(u) == False\\n\\n # Check for valid data\\n if np.sum(valid) > 1:\\n\\n # Compute ensTime\\n ens_time = np.nancumsum(transect.date_time.ens_duration_sec)\\n\\n # Ensure monotonic input\\n diff_time = np.diff(ens_time[valid])\\n idx = np.where(diff_time == 0)[0]\\n mono_array = np.vstack([ens_time[valid], u[valid], v[valid]])\\n # Replace non-monotonic times with average values\\n for i in idx[::-1]:\\n mono_array[1, i] = np.nanmean(mono_array[1, i:i+2])\\n mono_array[2, i] = np.nanmean(mono_array[2, i:i + 2])\\n mono_array = np.delete(mono_array, i+1, 1)\\n # Apply linear interpolation\\n # Apply linear interpolation\\n self.u_processed_mps = np.interp(ens_time,\\n mono_array[0, :],\\n mono_array[1, :])\\n # Apply linear interpolation\\n self.v_processed_mps = np.interp(ens_time,\\n mono_array[0, :],\\n mono_array[2, :])\",\n \"def InterpolateSurfaceVectorsWithLine():\\r\\n # Load Surface Mesh Data and generate normals\\r\\n VTKString = OpenData('C:/Users/Tim/Documents/University/Year 4/Final Project/FinalYearProjectCode/TEH_Code/InputFiles','muscle_surface.vtk')\\r\\n header, PointData, PolygonData = CreateMatrixVTK(VTKString)\\r\\n Centroids1,Vectors1 = ElementNormal(PointData,PolygonData)\\r\\n # Load full volume centroid\\r\\n NCF_Str = OpenData(\\\"C:/Users/Tim/Documents/University/Year 4/Final Project/FinalYearProjectCode/TEH_Code/InputFiles\\\",\\\"new_centroids_file.dat\\\")\\r\\n HeaderNCF,Centroids2 = CreateMatrixDat(NCF_Str)\\r\\n print('Loading Finished \\\\n Inserting Centre Line...')\\r\\n # Create Plane of vectors through centreline.\\r\\n PlaneCentroids,PlaneVectors = InsertCentreLine(Centroids1,Vectors1,50)\\r\\n print('Centre Line Inserted \\\\n Interpolating Centroids...')\\r\\n # Interpolate Vectors\\r\\n Vectors2 = VectorInter(PlaneCentroids,PlaneVectors,Centroids2)\\r\\n # Make the data more sparse to display better.\\r\\n C1,V1 = SparseData(PlaneCentroids,PlaneVectors,0.1)\\r\\n C2,V2 = SparseData(Centroids2,Vectors2,0.1)\\r\\n print('Interpolation Finished \\\\n Plotting...')\\r\\n # Plot Data\\r\\n fig = plt.figure()\\r\\n\\r\\n ax1 = fig.add_subplot(121,projection = '3d')\\r\\n DisplaySliceVectors(C1,V1,ax1,5,10)\\r\\n\\r\\n ax2 = fig.add_subplot(122,projection = '3d')\\r\\n DisplaySliceVectors(C2,V2,ax2,5,10)\\r\\n\\r\\n plt.show()\\r\\n\\r\\n header = 'TITLE = \\\\\\\"Normal Surface Vectors With Central axis Line\\\\\\\"\\\\nVARIABLES = \\\\\\\"XV\\\\\\\", \\\\\\\"YV\\\\\\\", \\\\\\\"ZV\\\\\\\" \\\\nZONE T=\\\\\\\"Step 0 Incr 0\\\\\\\" \\\\nF = VECTORS'\\r\\n\\r\\n np.savetxt(\\\"C:/Users/Tim/Documents/University/Year 4/Final Project/FinalYearProjectCode/TEH_Code/OutputFiles/SurfaceLineVectorInterpolation.dat\\\",Vectors2,header = header,comments='')\",\n \"def interpolate_and_average(xs, ys, interop_points=None, confidence_interval=False):\\n # Get the xs of shortest curve\\n max_min_x = max(x.min() for x in xs)\\n min_max_x = min(x.max() for x in xs)\\n if interop_points is None:\\n # Interop points according to curve with \\\"least resolution\\\"\\n interop_points = min(x.shape[0] for x in xs)\\n\\n new_x = np.linspace(max_min_x, min_max_x, interop_points)\\n new_ys = []\\n\\n for old_x, old_y in zip(xs, ys):\\n new_ys.append(np.interp(new_x, old_x, old_y))\\n\\n # Average out\\n # atleast_2d for case when we only have one reptition\\n new_ys = np.atleast_2d(np.array(new_ys))\\n new_y = np.mean(new_ys, axis=0)\\n std_y = np.std(new_ys, axis=0)\\n\\n if confidence_interval:\\n interval = 1.96 * (std_y / np.sqrt(len(xs)))\\n lower_bound = new_y - interval\\n upper_bound = new_y + interval\\n return new_x, new_y, std_y, lower_bound, upper_bound\\n else:\\n return new_x, new_y, std_y\",\n \"def solve_i():\\r\\n x = np.array([ -2.1, -1.45, -1.3, -0.2, 0.1, 0.15, 0.8, 1.1, 1.5, 2.8, 3.8 ])\\r\\n y = np.array([0.012155, 0.122151, 0.184520, 0.960789, 0.990050, 0.977751,\\r\\n 0.527292, 0.298197, 0.105399, 3.936690E-4, 5.355348E-7])\\r\\n # find and plot both interpolations and the oiginal points\\r\\n plt.figure(1)\\r\\n cubic_interpol(x,y)\\r\\n lin_interpol(x,y)\\r\\n plt.plot(x, y, 'rx', ms = 10, label = 'Points')\\r\\n # plot settings\\r\\n plt.title('Cubic & Linear Interpolation Given Points')\\r\\n plt.xlabel('x',fontsize = 14)\\r\\n plt.ylabel('y',fontsize = 14)\\r\\n plt.legend()\",\n \"def Interpolate(self, ind, results):\\n return _gmat_py.Interpolator_Interpolate(self, ind, results)\",\n \"def test_isentropic_pressure_masked_column():\\n lev = [100000., 95000.] * units.Pa\\n tmp = np.ma.ones((len(lev), 5, 5))\\n tmp[0, :] = 296.\\n tmp[1, :] = 292.\\n tmp[:, :, -1] = np.ma.masked\\n tmp = units.Quantity(tmp, units.kelvin)\\n isentprs = isentropic_interpolation([296.] * units.kelvin, lev, tmp)\\n trueprs = np.ones((1, 5, 5)) * (1000. * units.hPa)\\n trueprs[:, :, -1] = np.nan\\n assert isentprs[0].shape == (1, 5, 5)\\n assert_almost_equal(isentprs[0], trueprs, 3)\",\n \"def test_1d_constant_interpolation_basic(self):\\n\\n # Define pixel centers along each direction\\n x = numpy.array([1.0, 2.0, 4.0])\\n\\n # Define ny by nx array with corresponding values\\n A = numpy.zeros((len(x)))\\n\\n # Define values for each x, y pair as a linear function\\n for i in range(len(x)):\\n A[i] = linear_function(x[i], 0)\\n\\n # Then test that interpolated points are always assigned value of\\n # closest neighbour\\n xis = numpy.linspace(x[0], x[-1], 10)\\n points = xis\\n\\n vals = interpolate1d(x, A, points, mode='constant')\\n\\n # Find upper neighbours for each interpolation point\\n xi = points[:]\\n idx = numpy.searchsorted(x, xi, side='left')\\n\\n # Get the neighbours for each interpolation point\\n x0 = x[idx - 1]\\n x1 = x[idx]\\n\\n z0 = A[idx - 1]\\n z1 = A[idx]\\n\\n # Location coefficients\\n alpha = (xi - x0) / (x1 - x0)\\n\\n refs = numpy.zeros(len(vals))\\n for i in range(len(refs)):\\n if alpha[i] < 0.5:\\n refs[i] = z0[i]\\n\\n if alpha[i] >= 0.5:\\n refs[i] = z1[i]\\n\\n assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)\",\n \"def interpolateSpline(x, y) :\\n n = len(x)\\n\\n dim = 4 * (n - 1)\\n b = np.zeros((dim, 1))\\n A = np.zeros((dim, dim))\\n\\n for i in range(n-1):\\n x1 = x[i]\\n x2 = x[i+1]\\n y1 = y[i]\\n y2 = y[i+1]\\n b[i*4:(i+1)*4, 0] = [y1, y2, 0, 0]\\n\\n A[i*4, i*4:(i+1)*4] = [pow(x1,3), pow(x1,2), x1, 1] \\n A[i*4+1, i*4:(i+1)*4] = [pow(x2,3), pow(x2,2), x2, 1]\\n if (i != n-2):\\n A[i*4+2, i*4:(i+2)*4] = [3*pow(x2,2), 2 * x2, 1, 0, -3*pow(x2,2), -2 * x2, -1, 0, ]\\n A[i*4+3, i*4:(i+2)*4] = [6*x2, 2, 0, 0, -6*x2, -2, 0, 0]\\n else: \\n A[i*4+2, 0:4] = [6*x[0], 2, 0, 0]\\n A[i*4+3, i*4:(i+1)*4] = [6*x2, 2, 0, 0]\\n \\n # solve linear system for the coefficients of the spline\\n coeffs = np.linalg.solve(A, b)\\n\\n # extract local pieces\\n spline = []\\n for k in range(n-1):\\n spline.append(np.poly1d(coeffs[k*4:(k+1)*4, 0]))\\n\\n return spline\",\n \"def interpolate_hold_last(self):\\n\\n # Initialize variables\\n n_ensembles = len(self.u_mps)\\n\\n # Get data from object\\n self.u_processed_mps = np.copy(self.u_mps)\\n self.v_processed_mps = np.copy(self.v_mps)\\n self.u_processed_mps[self.valid_data[0, :] == False] = np.nan\\n self.v_processed_mps[self.valid_data[0, :] == False] = np.nan\\n\\n n_invalid = 0\\n # Process data by ensembles\\n for n in range(1, n_ensembles):\\n # Check if ensemble is invalid and number of consecutive invalids is less than 9\\n if (self.valid_data[0, n] == False) and (n_invalid < 9):\\n self.u_processed_mps[n] = self.u_processed_mps[n - 1]\\n self.v_processed_mps[n] = self.v_processed_mps[n - 1]\",\n \"def trilinear_interpolate(point, atom_index, emap, emap_max, emap_min):\\n point1 = []\\n point0 = []\\n dif = []\\n for p in point:\\n if round(p) == p:\\n p += 1E-10\\n point0.append(math.floor(p))\\n point1.append(math.ceil(p))\\n dif.append((p - point0[-1]) / (point1[-1] - point0[-1]))\\n\\n i000 = energy_map_index(point0, emap_max, emap_min) # (0, 0, 0)\\n i100 = energy_map_index([point1[0], point0[1], point0[2]], emap_max, emap_min) # (1, 0, 0)\\n i001 = energy_map_index([point0[0], point0[1], point1[2]], emap_max, emap_min) # (0, 0, 1)\\n i101 = energy_map_index([point1[0], point0[1], point1[2]], emap_max, emap_min) # (1, 0, 1)\\n i010 = energy_map_index([point0[0], point1[1], point0[2]], emap_max, emap_min) # (0, 1, 0)\\n i110 = energy_map_index([point1[0], point1[1], point0[2]], emap_max, emap_min) # (1, 1, 0)\\n i011 = energy_map_index([point0[0], point1[1], point1[2]], emap_max, emap_min) # (0, 1, 1)\\n i111 = energy_map_index(point1, emap_max, emap_min) # (1, 1, 1)\\n\\n c00 = emap[i000][atom_index] * (1 - dif[0]) + emap[i100][atom_index] * dif[0]\\n c01 = emap[i001][atom_index] * (1 - dif[0]) + emap[i101][atom_index] * dif[0]\\n c10 = emap[i010][atom_index] * (1 - dif[0]) + emap[i110][atom_index] * dif[0]\\n c11 = emap[i011][atom_index] * (1 - dif[0]) + emap[i111][atom_index] * dif[0]\\n\\n c0 = c00 * (1 - dif[1]) + c10 * dif[1]\\n c1 = c01 * (1 - dif[1]) + c11 * dif[1]\\n\\n c = c0 * (1 - dif[2]) + c1 * dif[2]\\n\\n return c\",\n \"def interpolatePeriodicSpline(x, y) :\\n n = len(x)\\n\\n dim = 4 * (n - 1)\\n b = np.zeros((dim, 1))\\n A = np.zeros((dim, dim))\\n\\n for i in range(n-1):\\n x1 = x[i]\\n x2 = x[i+1]\\n y1 = y[i]\\n y2 = y[i+1]\\n b[i*4:(i+1)*4, 0] = [y1, y2, 0, 0]\\n\\n A[i*4, i*4:(i+1)*4] = [pow(x1,3), pow(x1,2), x1, 1] \\n A[i*4+1, i*4:(i+1)*4] = [pow(x2,3), pow(x2,2), x2, 1]\\n if (i != n-2):\\n A[i*4+2, i*4:(i+2)*4] = [3*pow(x2,2), 2 * x2, 1, 0, -3*pow(x2,2), -2 * x2, -1, 0, ]\\n A[i*4+3, i*4:(i+2)*4] = [6*x2, 2, 0, 0, -6*x2, -2, 0, 0]\\n else: \\n A[i*4+2, 0:4] = [3 * pow(x[0],2), 2 * x[0], 1, 0]\\n A[i*4+2, i*4:(i+1)*4] = [-3 * pow(x2,2), -2 * x2, -1, 0]\\n A[i*4+3, 0:4] = [6 * x[0], 2, 0, 0]\\n A[i*4+3, i*4:(i+1)*4] = [-6 * x2, -2, 0, 0]\\n # solve linear system for the coefficients of the spline\\n coeffs = np.linalg.solve(A, b)\\n\\n # extract local pieces\\n spline = []\\n for k in range(n-1):\\n spline.append(np.poly1d(coeffs[k*4:(k+1)*4, 0]))\\n\\n return spline\",\n \"def test_constant_interpolation_basic(self):\\n\\n # Define pixel centers along each direction\\n x = numpy.array([1.0, 2.0, 4.0])\\n y = numpy.array([5.0, 9.0])\\n\\n # Define ny by nx array with corresponding values\\n A = numpy.zeros((len(x), len(y)))\\n\\n # Define values for each x, y pair as a linear function\\n for i in range(len(x)):\\n for j in range(len(y)):\\n A[i, j] = linear_function(x[i], y[j])\\n\\n # Then test that interpolated points are always assigned value of\\n # closest neighbour\\n xis = numpy.linspace(x[0], x[-1], 10)\\n etas = numpy.linspace(y[0], y[-1], 10)\\n points = combine_coordinates(xis, etas)\\n\\n vals = interpolate2d(x, y, A, points, mode='constant')\\n\\n # Find upper neighbours for each interpolation point\\n xi = points[:, 0]\\n eta = points[:, 1]\\n idx = numpy.searchsorted(x, xi, side='left')\\n idy = numpy.searchsorted(y, eta, side='left')\\n\\n # Get the four neighbours for each interpolation point\\n x0 = x[idx - 1]\\n x1 = x[idx]\\n y0 = y[idy - 1]\\n y1 = y[idy]\\n\\n z00 = A[idx - 1, idy - 1]\\n z01 = A[idx - 1, idy]\\n z10 = A[idx, idy - 1]\\n z11 = A[idx, idy]\\n\\n # Location coefficients\\n alpha = (xi - x0) / (x1 - x0)\\n beta = (eta - y0) / (y1 - y0)\\n\\n refs = numpy.zeros(len(vals))\\n for i in range(len(refs)):\\n if alpha[i] < 0.5 and beta[i] < 0.5:\\n refs[i] = z00[i]\\n\\n if alpha[i] >= 0.5 and beta[i] < 0.5:\\n refs[i] = z10[i]\\n\\n if alpha[i] < 0.5 and beta[i] >= 0.5:\\n refs[i] = z01[i]\\n\\n if alpha[i] >= 0.5 and beta[i] >= 0.5:\\n refs[i] = z11[i]\\n\\n assert numpy.allclose(vals, refs, rtol=1e-12, atol=1e-12)\",\n \"def showAsPointsInterpolated(self, lToRRatio = 2.0):\\n MonkeyPatchMayaVi()\\n import enthought.mayavi.mlab as mlab\\n from mayavi import mlab\\n \\n @mlab.show\\n def _showSimple():\\n maxInterpolPts = 10\\n \\n def interpolateSection(section):\\n sStart = section.getDistalNPA4()\\n sEnd = section.getProximalNPA4()\\n length = section.getLength()\\n rad = min(section.d_r, section.p_r) \\n n = min( max( int( lToRRatio * length / rad ), 1 ), maxInterpolPts)\\n jVecSteps = ( sEnd-sStart ) / n\\n \\n intPts = [ sStart + k*jVecSteps for k in range(0,n) ]\\n return intPts \\n \\n lbs = []\\n for morph in self.morphs:\\n lb = Flatten( ListBuilderSectionVisitor(functor=interpolateSection, morph=morph ) () ) \\n lbs.extend( lb )\\n \\n \\n pts = numpy.array( lbs )\\n\\n x = pts[:, 0]\\n y = pts[:, 1]\\n z = pts[:, 2]\\n s = pts[:, 3]\\n \\n mlab.points3d(x, y, z, s, colormap=self.colormap, scale_factor=self.scale_factor)\\n mlab.outline()\\n _showSimple()\",\n \"def interpolate(self, x_pivot, f_pivot):\\n interpolation = interp1d(x_pivot, f_pivot,\\n kind=self.kind, bounds_error=False)\\n return interpolation\",\n \"def interpolate(series, indices):\\r\\n not_included = [t for t in indices if t not in series.index.values]\\r\\n new_indices_series = pd.Series(index=not_included, data=[np.nan] * len(not_included))\\r\\n with_new_indices = series.append(new_indices_series).sort_index()\\r\\n interpolated = with_new_indices.interpolate(method=\\\"linear\\\")\\r\\n\\r\\n # We want the values on the indices before the (originally) first index to be equal to the first value. Similarly,\\r\\n # we want the values after the (originally) last index to be equal to the last value.\\r\\n min_index = min(series.index.values)\\r\\n max_index = max(series.index.values)\\r\\n start_value = series.values[0]\\r\\n end_value = series.values[-1]\\r\\n\\r\\n new_values = []\\r\\n for t, p in interpolated.items():\\r\\n if t < min_index:\\r\\n new_values.append(start_value)\\r\\n elif t > max_index:\\r\\n new_values.append(end_value)\\r\\n else:\\r\\n new_values.append(p)\\r\\n\\r\\n new_series = pd.Series(data=new_values, index=interpolated.index)\\r\\n\\r\\n return new_series\",\n \"def interpolate_meridional(self, *interp1d_args, **interp1d_kwargs):\\n return self.interp1d_meridional(*interp1d_args, **interp1d_kwargs)(self.lat)\",\n \"def test_isentropic_pressure():\\n lev = [100000., 95000., 90000., 85000.] * units.Pa\\n tmp = np.ones((4, 5, 5))\\n tmp[0, :] = 296.\\n tmp[1, :] = 292.\\n tmp[2, :] = 290\\n tmp[3, :] = 288.\\n tmp[:, :, -1] = np.nan\\n tmpk = tmp * units.kelvin\\n isentlev = [296.] * units.kelvin\\n isentprs = isentropic_interpolation(isentlev, lev, tmpk)\\n trueprs = np.ones((1, 5, 5)) * (1000. * units.hPa)\\n trueprs[:, :, -1] = np.nan\\n assert isentprs[0].shape == (1, 5, 5)\\n assert_almost_equal(isentprs[0], trueprs, 3)\",\n \"def interpolate_matrix(matrix):\",\n \"def test_linear_interpolation_nan_array(self):\\n\\n # Define pixel centers along each direction\\n x = [0.0, 1.0, 2.0, 3.0, 4.0, 5.0]\\n y = [4.0, 5.0, 7.0, 9.0, 11.0, 13.0]\\n\\n # Define ny by nx array with corresponding values\\n A = numpy.zeros((len(x), len(y)))\\n\\n # Define values for each x, y pair as a linear function\\n for i in range(len(x)):\\n for j in range(len(y)):\\n A[i, j] = linear_function(x[i], y[j])\\n A[2, 3] = numpy.nan # (x=2.0, y=9.0): NaN\\n\\n # Then test that interpolated points can contain NaN\\n xis = numpy.linspace(x[0], x[-1], 12)\\n etas = numpy.linspace(y[0], y[-1], 10)\\n points = combine_coordinates(xis, etas)\\n\\n vals = interpolate2d(x, y, A, points, mode='linear')\\n refs = linear_function(points[:, 0], points[:, 1])\\n\\n # Set reference result with expected NaNs and compare\\n for i, (xi, eta) in enumerate(points):\\n if (1.0 < xi <= 3.0) and (7.0 < eta <= 11.0):\\n refs[i] = numpy.nan\\n\\n assert nanallclose(vals, refs, rtol=1e-12, atol=1e-12)\",\n \"def apply_interpolation(self, transect, interpolation_method=None):\\n\\n # Reset processed data\\n if self.u_mps is not None:\\n self.u_processed_mps = np.copy(self.u_mps)\\n self.v_processed_mps = np.copy(self.v_mps)\\n self.u_processed_mps[self.valid_data[0, :] == False] = np.nan\\n self.v_processed_mps[self.valid_data[0, :] == False] = np.nan\\n\\n # Determine interpolation methods to apply\\n if interpolation_method is None:\\n interpolation_method = self.interpolate\\n else:\\n self.interpolate = interpolation_method\\n\\n # Apply specified interpolation method\\n\\n if interpolation_method == 'None':\\n # Sets invalid data to nan with no interpolation\\n self.interpolate_none()\\n\\n elif interpolation_method == 'ExpandedT':\\n # Set interpolate to none as the interpolation done is in the QComp\\n self.interpolate_next()\\n\\n elif interpolation_method == 'Hold9':\\n # Interpolates using SonTek method of holding last valid for up to 9 samples\\n self.interpolate_hold_9()\\n\\n elif interpolation_method == 'HoldLast':\\n # Interpolates by holding last valid indefinitely\\n self.interpolate_hold_last()\\n\\n elif interpolation_method == 'Linear':\\n # Interpolates using linear interpolation\\n self.interpolate_linear(transect)\\n\\n elif interpolation_method == 'Smooth':\\n # Interpolates using smooth interpolation\\n self.interpolate_smooth(transect)\\n\\n elif interpolation_method == 'TRDI':\\n # TRDI interpolation is done in discharge.\\n # For TRDI the interpolation is done on discharge not on velocities\\n self.interpolate_none()\",\n \"def interpolate(m):\\n \\n x1 = m[0]\\n x2 = m[1]\\n x3 = m[2]\\n y1 = m[3]\\n y2 = m[4]\\n y3 = m[5]\\n denom = (x1 - x2)*(x1 - x3)*(x2 - x3)\\n A = (x3 * (y2 - y1) + x2 * (y1 - y3) + x1 * (y3 - y2)) / denom\\n B = (x3**2 * (y1 - y2) + x2**2 * (y3 - y1) + x1**2 * (y2 - y3)) / denom\\n C = (x2 * x3 * (x2 - x3) * y1 + x3 * x1 * (x3 - x1) * y2 + x1 * x2 * (x1 - x2) * y3) / denom\\n xext = -B/(2*A)\\n yext = A*xext**2 + B*xext + C\\n \\n return(np.array([xext,yext]))\",\n \"def interpolate_na(\\n self, method: str = \\\"nearest\\\", extrapolate: bool = False, **kwargs\\n ):\\n dim0 = self.dim0\\n kwargs.update(dict(method=method, extrapolate=extrapolate))\\n if dim0:\\n interp_data = np.empty(self._obj.shape, dtype=self._obj.dtype)\\n for i, (_, sub_xds) in enumerate(self._obj.groupby(dim0)):\\n interp_data[i, ...] = self._interpolate_na(\\n sub_xds.load().data, **kwargs\\n )\\n else:\\n interp_data = self._interpolate_na(self._obj.load().data, **kwargs)\\n interp_array = xr.DataArray(\\n name=self._obj.name,\\n dims=self._obj.dims,\\n coords=self._obj.coords,\\n data=interp_data,\\n attrs=self._obj.attrs,\\n )\\n interp_array.raster.set_nodata(self.nodata)\\n interp_array.raster.set_crs(self.crs)\\n return interp_array\",\n \"def _LinearInterpolate(x0, target, x1, y0, y1):\\n if x0 == x1:\\n return (y0 + y1) / 2\\n return (y1 - y0) * (target - x0) / (x1 - x0) + y0\",\n \"def splitting_intensity(self, **kwargs):\\n \\n if 'pol' not in kwargs:\\n raise Exception('pol must be specified')\\n \\n copy = self.data.copy()\\n copy.rotateto(kwargs['pol'])\\n copy.x = np.gradient(copy.x)\\n rdiff, trans = copy.chopdata()\\n s = -2 * np.trapz(trans * rdiff) / np.trapz(rdiff**2)\\n return s\",\n \"def section_coordinates():\\n \\n gh_width = 30.0 # in feet\\n gh_width_west = gh_width/2.0\\n N_x = 100\\n dx = gh_width_west/100.0\\n gh_length = 48 # in feet\\n \\n xvalues = np.linspace(0,(N_x)*dx,N_x+1) # array for width\\n yvalues = np.linspace(0,gh_length,num=gh_length+1) # array for height\\n zvalues_west = np.zeros(N_x+1) # array for height\\n \\n for i in range(0,len(xvalues)):\\n zvalues_west[i] = 7.29944696 + (1.27415518*xvalues[i]) + (-0.0680139854*xvalues[i]**2) + (0.00152035861*xvalues[i]**3)\\n i += 1\\n \\n roof_slopes_west = np.zeros(N_x+1)\\n roof_lengths = np.zeros(N_x+1)\\n\\n total_length_west = 0\\n\\n for i in range(1,len(xvalues)):\\n dz = zvalues_west[i] - zvalues_west[i-1]\\n roof_slopes_west[i] = dz/dx\\n roof_lengths[i] = (dz**2 + dx**2)**0.5\\n total_length_west += roof_lengths[i]\\n \\n zvalues_east = np.flip(zvalues_west, axis=0)\\n zvalues_west = zvalues_west[:-1]\\n zvalues = np.concatenate((zvalues_west, zvalues_east), axis=0)\\n \\n xx, yy = np.meshgrid(xvalues, yvalues) \\n \\n plt.plot(xx, yy, marker='.', color='k', linestyle='none')\\n plt.axis('equal')\\n plt.show() \\n\\n return roof_slopes_west\",\n \"def interpolate(self, lon, lat, egy=None):\\n raise NotImplementedError(\\\"MapBase.interpolate()\\\")\",\n \"def test_isentropic_pressure_p_increase_rh_out():\\n lev = [85000., 90000., 95000., 100000.] * units.Pa\\n tmp = np.ones((4, 5, 5))\\n tmp[0, :] = 288.\\n tmp[1, :] = 290.\\n tmp[2, :] = 292.\\n tmp[3, :] = 296.\\n tmpk = tmp * units.kelvin\\n rh = np.ones((4, 5, 5))\\n rh[0, :] = 20.\\n rh[1, :] = 40.\\n rh[2, :] = 80.\\n rh[3, :] = 100.\\n relh = rh * units.percent\\n isentlev = 296. * units.kelvin\\n isentprs = isentropic_interpolation(isentlev, lev, tmpk, relh)\\n truerh = 100. * units.percent\\n assert_almost_equal(isentprs[1], truerh, 3)\",\n \"def test_isentropic_interpolation_dataarray():\\n temp = xr.DataArray([[[296.]], [[292.]], [[290.]], [[288.]]] * units.K,\\n dims=('isobaric', 'y', 'x'),\\n coords={'isobaric': (('isobaric',), [1000., 950., 900., 850.],\\n {'units': 'hPa'}),\\n 'time': '2020-01-01T00:00Z'})\\n\\n rh = xr.DataArray([[[100.]], [[80.]], [[40.]], [[20.]]] * units.percent,\\n dims=('isobaric', 'y', 'x'), coords={\\n 'isobaric': (('isobaric',), [1000., 950., 900., 850.], {'units': 'hPa'}),\\n 'time': '2020-01-01T00:00Z'})\\n\\n isentlev = [296., 297.] * units.kelvin\\n press, rh_interp = isentropic_interpolation(isentlev, temp.isobaric, temp, rh)\\n\\n assert_array_almost_equal(press, np.array([[[1000.]], [[936.213]]]) * units.hPa, 3)\\n assert_array_almost_equal(rh_interp, np.array([[[100.]], [[69.19706]]]) * units.percent, 3)\",\n \"def interpolate( h, x, y=None, z=None, outOfRangeValue=30 ):\\n\\n if x != x: return outOfRangeValue\\n if x <= h.GetXaxis().GetBinCenter(1) or x >= h.GetXaxis().GetBinCenter(h.GetXaxis().GetNbins()): return outOfRangeValue\\n \\n if y != None:\\n if y != y: return outOfRangeValue\\n if y <= h.GetYaxis().GetBinCenter(1) or y >= h.GetYaxis().GetBinCenter(h.GetYaxis().GetNbins()): return outOfRangeValue\\n if z != None:\\n if z != z: return outOfRangeValue\\n if z <= h.GetZaxis().GetBinCenter(1) or z >= h.GetZaxis().GetBinCenter(h.GetZaxis().GetNbins()): return outOfRangeValue\\n \\n if y != None and z != None: return h.Interpolate( x, y, z )\\n if y != None: return h.Interpolate( x, y )\\n return h.Interpolate( x )\",\n \"def test_isentropic_pressure_tmp_out_interp():\\n lev = [100000., 95000., 90000., 85000.] * units.Pa\\n tmp = np.ones((4, 5, 5))\\n tmp[0, :] = 296.\\n tmp[1, :] = 292.\\n tmp[2, :] = 290.\\n tmp[3, :] = 288.\\n tmpk = tmp * units.kelvin\\n isentlev = [296., 297.] * units.kelvin\\n isentprs = isentropic_interpolation(isentlev, lev, tmpk, temperature_out=True)\\n truetmp = 291.4579 * units.kelvin\\n assert_almost_equal(isentprs[1][1], truetmp, 3)\",\n \"def interpolate(self, var, time, lat, lon):\\n\\n # Get the nearest four points in space\\n # Check to see if lat/lons are 2d or 1d\\n if len(self['lat'].shape) == 2:\\n closey, closex, distances = self.nearest_points(lat, lon, npt=4)\\n # Distances in km\\n# distances = np.array([self.haversine(\\n# (self['lat'][y,x].values, self['lon'][y,x].values),\\n# (lat, lon)) for y,x in \\n# zip(list(closey), list(closex))])\\n else:\\n closen = self.nearest_points(lat, lon, npt=4)\\n closey = closen\\n closex = closen\\n # Distances in km\\n distances = np.array([self.haversine(\\n (self['lat'][n].values, self['lon'][n].values),\\n (lat, lon)) for n in list(closen)])\\n # Check for exact match (within some tolerance)\\n spaceweights = np.zeros(distances.shape)\\n if (distances < 1.0).sum() > 0:\\n spaceweights[distances.argmin()] = 1\\n else:\\n # Here, inverse distance weighting (for simplicity)\\n spaceweights = 1.0 / distances\\n spaceweights /= spaceweights.sum()\\n # Get weights in time\\n #time64 = np.datetime64(time)\\n #all the valid times in the ensemble\\n valids = self['validtime'].values\\n timeweights = np.zeros(valids.shape)\\n # Check if we are outside the valid time range\\n if (time < valids[0]) or (time > valids[-1]):\\n print(\\\"Interpolation is outside of time range in state!\\\")\\n return None\\n # Find where we are in this list\\n #index after the time of the observation\\n lastdex = (valids >= time).argmax()\\n # If we match a particular time value, then\\n # this is just an identity\\n if valids[lastdex] == time:\\n # Just make a one at this time\\n timeweights[lastdex] = 1\\n else:\\n # Linear interpolation\\n #often going to be 6 hours, subtracts datetime objects I think\\n diff = (valids[lastdex] - valids[lastdex-1])\\n #print(valids[lastdex], valids[lastdex-1], diff)\\n #often going to be 21600 seconds\\n totsec = diff.seconds\\n #totsec = np.abs(diff / np.timedelta64(1, 's'))\\n #ST\\n #calculate time difference between time after and time of observation\\n #the abs will make this positive definite, which is okay since\\n #the difference will always be negative\\n thisdiff = abs(time - valids[lastdex])\\n #thissec = np.abs(thisdiff / np.timedelta64(1,'s'))\\n thissec = thisdiff.seconds\\n # Put in appropriate weights\\n #ST switched the -1 between the two lines to match up with the positive-\\n #definite thisdiff\\n timeweights[lastdex-1] = float(thissec) / totsec\\n timeweights[lastdex] = 1.0 - (float(thissec)/totsec)\\n # Now that we have the weights, do the interpolation\\n #ST an ntimes x 4 x nens array\\n interp = self.variables[var].values[:,closey,closex,:]\\n # Do a dot product with the time weights\\n # And with the space weights\\n if len(interp.shape) == 3:\\n interp = (timeweights[:,None,None] * interp).sum(axis=0)\\n else:\\n interp = (timeweights[:,None,None,None] * interp).sum(axis=0)\\n \\n if len(interp.shape) == 3:\\n #ST Changed 2nd : to None\\n interp = (spaceweights[:,None,None] * interp).sum(axis=1)\\n else:\\n interp = (spaceweights[:,None] * interp).sum(axis=0)\\n # Return estimate from all ensemble members\\n return interp\",\n \"def linear_interpolate_release(mvi, j):\\n set_system_state(mvi, 1)\\n lam1 = mvi.system.lambda_()[j]\\n set_system_state(mvi, 2)\\n lam2 = mvi.system.lambda_()[j]\\n\\n # If either of the following loops are entered, there are likely going to\\n # be problems.\\n if (lam1 < 0) and (lam2 < 0):\\n #add_constraints(mvi, mvi._state1_releases)\\n #print mvi.lambda1c[j]\\n #print mvi\\n #raise Exception(\\\"Bad release interpolation.\\\")\\n print 'WARNING: BAD INTERPOLANT'\\n return mvi.t1, mvi.q1\\n\\n if lam1 < 0:\\n return mvi.t1, mvi.q1\\n\\n tr = mvi.t1 - (lam1/(lam2-lam1))*(mvi.t2-mvi.t1)\\n frac = (tr-mvi.t1)/(mvi.t2-mvi.t1)\\n qr = frac*(mvi.q2-mvi.q1)+mvi.q1\\n\\n return tr, qr\",\n \"def InterpolateSection(self, pointA, pointB, Resolution = 50):\\n\\t\\tif type(pointA) != Point:\\n\\t\\t\\traise TypeError()\\n\\t\\tif type(pointB) != Point:\\n\\t\\t\\traise TypeError()\\n\\n\\t\\tx0, y0, z0 = ToCartesian(pointA.Latitude, pointA.Longitude)\\n\\t\\tx1, y1, z1 = ToCartesian(pointB.Latitude, pointB.Longitude)\\n\\n\\t\\tdistance = Distance_LatLongs(pointA.Latitude, pointA.Longitude, pointB.Latitude, pointB.Longitude)\\n\\n\\t\\t# distance = math.sqrt(math.pow(x1 - x0, 2) + math.pow(y1 - y0, 2) + math.pow(z1 - z0, 2))\\n\\n\\t\\tsegment_size = distance / Resolution\\n\\n\\t\\tsegments = []\\n\\n\\t\\tfor index in range(Resolution):\\n\\t\\t\\tsegment_distance = index * segment_size\\n\\t\\t\\tx, y, z = Interpolate_Linear_3Points(x0, y0, z0, x1, y1, z1, segment_distance)\\n\\n\\t\\t\\tlat, lon = ToGeo(x, y, z)\\n\\n\\t\\t\\tsegments.append(Point(Latitude = lat, Longitude = lon))\\n\\n\\t\\treturn segments\",\n \"def filter_interpolated(self, ys, xs):\\n return ys, xs\",\n \"def interpolated_solution(self):\\n # need to reverse the direction of the _solution array\\n if self.model.assortativity == 'positive':\\n traj = self._solution[::-1]\\n else:\\n traj = self._solution\\n\\n xi = np.linspace(traj[0, 0], traj[-1, 0], 10 * traj.shape[0])\\n interp_soln = self.ivp.interpolate(traj, xi, k=5, ext=2)\\n\\n # convert to a data frame\\n col_names = ['x', r'$\\\\hat{\\\\mu}(x)$', r'$\\\\hat{\\\\theta}(x)$', '$\\\\hat{w}(x)$', r'$\\\\hat{\\\\pi}(x)$']\\n df = pd.DataFrame(interp_soln, columns=col_names)\\n\\n return df.set_index('x')\",\n \"def computeNormalAndCurvature():\\n radius = 50\\n for i,j in pts:\\n nb_pts = ti.cast(0, ti.f32)\\n accu_0 = ti.cast(0, ti.f32)\\n accu_1 = ti.cast(0, ti.f32)\\n accu_2 = ti.cast(0, ti.f32)\\n accu_3 = ti.cast(0, ti.f32)\\n accu_4 = ti.cast(0, ti.f32)\\n accu_5 = ti.cast(0, ti.f32)\\n accu_6 = ti.cast(0, ti.f32)\\n accu_7 = ti.cast(0, ti.f32)\\n accu_8 = ti.cast(0, ti.f32)\\n z = 0\\n for x in range(i-radius, i+radius):\\n for y in range(j-radius, j+radius):\\n if ti.is_active(block1, [x,y]):\\n accu_0 += x * x\\n accu_1 += x * y\\n accu_2 += x * z\\n accu_3 += y * y\\n accu_4 += y * z\\n accu_5 += z * z\\n accu_6 += x\\n accu_7 += y\\n accu_8 += z\\n nb_pts += 1\\n accu_0 /= nb_pts\\n accu_1 /= nb_pts\\n accu_2 /= nb_pts\\n accu_3 /= nb_pts\\n accu_4 /= nb_pts\\n accu_5 /= nb_pts\\n accu_6 /= nb_pts\\n accu_7 /= nb_pts\\n accu_8 /= nb_pts\\n cov_mat_0 = accu_0 - accu_6 * accu_6\\n cov_mat_1 = accu_1 - accu_6 * accu_7\\n cov_mat_2 = accu_2 - accu_6 * accu_8\\n cov_mat_4 = accu_3 - accu_7 * accu_7\\n cov_mat_5 = accu_4 - accu_7 * accu_8\\n cov_mat_8 = accu_5 - accu_8 * accu_8\\n cov_mat_3 = cov_mat_1\\n cov_mat_6 = cov_mat_2\\n cov_mat_7 = cov_mat_5\\n\\n # Compute eigen value and eigen vector\\n # Make sure in [-1, 1]\\n scale = ti.max(1.0, ti.abs(cov_mat_0))\\n scale = ti.max(scale, ti.abs(cov_mat_1))\\n scale = ti.max(scale, ti.abs(cov_mat_2))\\n scale = ti.max(scale, ti.abs(cov_mat_3))\\n scale = ti.max(scale, ti.abs(cov_mat_4))\\n scale = ti.max(scale, ti.abs(cov_mat_5))\\n scale = ti.max(scale, ti.abs(cov_mat_6))\\n scale = ti.max(scale, ti.abs(cov_mat_7))\\n scale = ti.max(scale, ti.abs(cov_mat_8))\\n if scale > 1.0:\\n cov_mat_0 /= scale\\n cov_mat_1 /= scale\\n cov_mat_2 /= scale\\n cov_mat_3 /= scale\\n cov_mat_4 /= scale\\n cov_mat_5 /= scale\\n cov_mat_6 /= scale\\n cov_mat_7 /= scale\\n cov_mat_8 /= scale\\n \\n # Compute roots\\n eigen_val_0 = ti.cast(0, ti.f32)\\n eigen_val_1 = ti.cast(0, ti.f32)\\n eigen_val_2 = ti.cast(0, ti.f32)\\n \\n c0 = cov_mat_0 * cov_mat_4 * cov_mat_8 \\\\\\n + 2 * cov_mat_3 * cov_mat_6 * cov_mat_7 \\\\\\n - cov_mat_0 * cov_mat_7 * cov_mat_7 \\\\\\n - cov_mat_4 * cov_mat_6 * cov_mat_6 \\\\\\n - cov_mat_8 * cov_mat_3 * cov_mat_3\\n c1 = cov_mat_0 * cov_mat_4 \\\\\\n - cov_mat_3 * cov_mat_3 \\\\\\n + cov_mat_0 * cov_mat_8 \\\\\\n - cov_mat_6 * cov_mat_6 \\\\\\n + cov_mat_4 * cov_mat_8 \\\\\\n - cov_mat_7 * cov_mat_7\\n c2 = cov_mat_0 + cov_mat_4 + cov_mat_8\\n \\n if ti.abs(c0) < 0.00001:\\n eigen_val_0 = 0\\n d = c2 * c2 - 4.0 * c1\\n if d < 0.0: # no real roots ! THIS SHOULD NOT HAPPEN!\\n d = 0.0\\n sd = ti.sqrt(d)\\n eigen_val_2 = 0.5 * (c2 + sd)\\n eigen_val_1 = 0.5 * (c2 - sd)\\n else:\\n s_inv3 = ti.cast(1.0 / 3.0, ti.f32)\\n s_sqrt3 = ti.sqrt(3.0)\\n c2_over_3 = c2 * s_inv3\\n a_over_3 = (c1 - c2 * c2_over_3) * s_inv3\\n if a_over_3 > 0:\\n a_over_3 = 0\\n \\n half_b = 0.5 * (c0 + c2_over_3 * (2 * c2_over_3 * c2_over_3 - c1))\\n q = half_b * half_b + a_over_3 * a_over_3 * a_over_3\\n if q > 0:\\n q = 0\\n \\n rho = ti.sqrt(-a_over_3)\\n theta = ti.atan2(ti.sqrt(-q), half_b) * s_inv3\\n cos_theta = ti.cos(theta)\\n sin_theta = ti.sin(theta)\\n eigen_val_0 = c2_over_3 + 2 * rho * cos_theta\\n eigen_val_1 = c2_over_3 - rho * (cos_theta + s_sqrt3 * sin_theta)\\n eigen_val_2 = c2_over_3 - rho * (cos_theta - s_sqrt3 * sin_theta)\\n temp_swap = ti.cast(0, ti.f32)\\n \\n # Sort in increasing order.\\n if eigen_val_0 >= eigen_val_1:\\n temp_swap = eigen_val_1\\n eigen_val_1 = eigen_val_0\\n eigen_val_0 = temp_swap\\n if eigen_val_1 >= eigen_val_2:\\n temp_swap = eigen_val_2\\n eigen_val_2 = eigen_val_1\\n eigen_val_1 = temp_swap\\n if eigen_val_0 >= eigen_val_1:\\n temp_swap = eigen_val_1\\n eigen_val_1 = eigen_val_0\\n eigen_val_0 = temp_swap\\n \\n if eigen_val_0 <= 0:\\n eigen_val_0 = 0\\n d = c2 * c2 - 4.0 * c1\\n if d < 0.0: # no real roots ! THIS SHOULD NOT HAPPEN!\\n d = 0.0\\n sd = ti.sqrt(d)\\n eigen_val_2 = 0.5 * (c2 + sd)\\n eigen_val_1 = 0.5 * (c2 - sd)\\n # end of compute roots\\n\\n eigen_value = eigen_val_1 * scale # eigen value for 2D SDF\\n # eigen value for 3D SDF\\n #eigen_value = eigen_val_0 * scale\\n\\n #print(\\\"eigen_val_0 \\\", eigen_val_0)\\n #print(\\\"eigen_val_1 \\\", eigen_val_1)\\n #print(\\\"eigen_val_2 \\\", eigen_val_2)\\n \\n # TODO\\n #scaledMat.diagonal ().array () -= eigenvalues (0)\\n #eigenvector = detail::getLargest3x3Eigenvector (scaledMat).vector;\\n\\n # Compute normal vector (TODO)\\n #visual_norm[i,j][0] = eigen_val_0 #eigen_vector[0]\\n #visual_norm[i,j][1] = eigen_val_1 #eigen_vector[1]\\n #visual_norm[i,j][2] = eigen_val_2 #eigen_vector[2]\\n\\n # Compute the curvature surface change\\n eig_sum = cov_mat_0 + cov_mat_1 + cov_mat_2\\n visual_curv[i,j][0] = 0\\n if eig_sum != 0:\\n visual_curv[i,j][0] = eigen_val_1 # true curvature is: ti.abs(eigen_value / eig_sum)\",\n \"def segement_divide(pts,step=0.10, offset_x=0.01, offset_y=0.01):\\n\\n # Select the x and y of the points\\n n = len(pts)\\n \\n z = 0.0\\n \\n points_plane = [] \\n points_x = []\\n paint_point = []\\n\\n for i in range(n):\\n points_plane.append([pts[i][0], pts[i][1]])\\n \\n # Sorted the list according to x \\n points_plane.sort(key=lambda x:x[0])\\n\\n # Segment the points according to x \\n counter = 0 # Count the interval\\n x_min = points_plane[0][0]\\n x_max = points_plane[n-1][0]\\n\\n # The whole interval that needs to be divided\\n upper = x_max + offset_x\\n lower = x_min - offset_x\\n lower_bound = lower\\n \\n # Set each segement's lower and upperbound\\n while (lower_bound + step <= upper): \\n # The break condition will be lower_bound > upper - step\\n upper_bound = lower_bound + step\\n\\n # Find the index between lower bound and upper bound\\n # First, find the index which x >= lower bound\\n index = 0\\n \\n while (points_plane[index][0] < lower_bound): \\n index = index + 1 # The index of the first point in the interval\\n \\n # If there is at least one point in the [lower_bound, upper_bound]\\n if (points_plane[index][0] <= upper_bound): \\n\\n x_start = points_plane[index][0]\\n y_max = points_plane[index][1]\\n y_min = points_plane[index][1]\\n \\n while (points_plane[index][0] <= upper_bound): \\n # The break condition will be x[index] > upper bound or index = n - 1\\n # Compute the y max and y min in this interval\\n \\n if points_plane[index][1] > y_max: \\n y_max = points_plane[index][1]\\n\\n if points_plane[index][1] < y_min:\\n y_min = points_plane[index][1]\\n \\n if index < n - 1:\\n index = index + 1\\n else:\\n break\\n # The index of the last point in the interval, when index < n-1\\n \\n x_end = points_plane[index][0]\\n\\n paint_point.append([lower_bound,y_max+offset_y,z]) \\n paint_point.append([lower_bound,y_min-offset_y,z])\\n points_x.append([x_start, x_end])\\n \\n counter = counter + 1\\n\\n # Update interval\\n lower_bound = upper_bound - offset_x\\n \\n # Deal with the last interval\\n lower_bound_last = upper - step\\n index_last = 0\\n counter = counter + 1\\n while ((index_last < n) and (points_plane[index_last][0] < lower_bound_last)): \\n # The first point in the last interval\\n index_last = index_last + 1\\n \\n if (index_last < n): \\n # There is at least one point in the last interval\\n x_start_last = points_plane[index_last][0]\\n y_max_last = points_plane[index_last][1]\\n y_min_last = points_plane[index_last][1]\\n\\n while ((index_last) y_max_last: \\n y_max_last = points_plane[index_last][1]\\n \\n if points_plane[index_last][1] < y_min_last:\\n y_min_last = points_plane[index_last][1]\\n\\n index_last = index_last + 1\\n \\n index_last = index_last - 1 # The index of the last point in the interval\\n \\n paint_point.append([lower_bound_last, y_max_last+offset_y, z])\\n paint_point.append([lower_bound_last, y_min_last-offset_y, z])\\n# paint_point.append([upper, y_max_last+offset_y, z])\\n# paint_point.append([upper, y_min_last-offset_y, z])\\n# return trans_to_end(paint_point)\\n return paint_point\",\n \"def different_quadratic_extrpolation_lower(x_interp, x_spline, y_spline):\\n index_lower_1 = 0\\n index_lower_2 = 1\\n x1_lower = x_spline[index_lower_1]\\n x2_lower = x_spline[index_lower_2]\\n x3_lower = x_spline[index_lower_2 + 1]\\n f1_lower = y_spline[index_lower_1]\\n\\n df1_dx_lower = calc_gradient(x_spline, y_spline, index_lower_1)/(x2_lower - x1_lower)\\n df2_dx_lower = calc_gradient(x_spline, y_spline, index_lower_2)/(x3_lower - x2_lower)\\n\\n # Solve 2ax-b = df_dx for the gradient at point 1 and 2\\n # Rearrange both equations to find 'a' and 'b' quadratic coefficients\\n a_lower = (df2_dx_lower - df1_dx_lower)/(2.*(x2_lower - x1_lower))\\n b_lower = df1_dx_lower - 2.*a_lower*x1_lower\\n\\n # Find c by solving at the fixed points (f = a x**2 + bx + c) at point 1 for the lower, and point 2 for the upper\\n c_lower = f1_lower - a_lower*x1_lower**2 - b_lower*x1_lower\\n return a_lower*x_interp**2 + b_lower*x_interp + c_lower\",\n \"def interpolate1Image2D( iImage, iCoorX, iCoorY ):\\n # pretvori vhodne spremenljivke v np polje\\n iImage = np.asarray( iImage ) \\n iCoorX = np.asarray( iCoorX )\\n iCoorY = np.asarray( iCoorY ) \\n # preberi velikost slike in jedra\\n dy, dx = iImage.shape\\n # ustvari 2d polje koordinat iz 1d vhodnih koordinat (!!!)\\n if np.size(iCoorX) != np.size(iCoorY):\\n print('Stevilo X in Y koordinat je razlicno!') \\n iCoorX, iCoorY = np.meshgrid(iCoorX, iCoorY, sparse=False, indexing='xy')\\n #------------------------------- za hitrost delovanja \\n return interpn( (np.arange(dy),np.arange(dx)), iImage, \\\\\\n np.dstack((iCoorY,iCoorX)),\\\\\\n method='linear', bounds_error=False)\\\\\\n .astype( iImage.dtype )\"\n]"},"negative_scores":{"kind":"list like","value":["0.6352975","0.62675714","0.61275345","0.5952627","0.5907965","0.58464473","0.5796776","0.578933","0.57794523","0.57792443","0.5757177","0.5749844","0.57261205","0.5726011","0.56745857","0.5649165","0.56255597","0.5618809","0.5615824","0.55846244","0.5575734","0.55678564","0.5558076","0.5558076","0.5558076","0.55468947","0.55329084","0.5502345","0.55007267","0.54945827","0.5486501","0.5486107","0.5483363","0.54748726","0.5470862","0.54575795","0.54575104","0.5454245","0.5444075","0.5439287","0.5439023","0.54335827","0.54326206","0.5429286","0.5419967","0.5419636","0.5413704","0.5413231","0.54093695","0.5405765","0.5403048","0.5401799","0.5399949","0.53990865","0.5390334","0.5383853","0.5382359","0.53787386","0.53770256","0.5374631","0.5373034","0.5371954","0.536459","0.5363246","0.5359254","0.5355683","0.534502","0.5337399","0.53353155","0.53341794","0.5333126","0.532686","0.53198457","0.5315376","0.53144574","0.5301394","0.52952445","0.52941525","0.5260467","0.52507013","0.52471924","0.52338666","0.5231545","0.5225373","0.5220493","0.52130556","0.52061236","0.5206067","0.5205742","0.5202392","0.5201588","0.52007437","0.5195376","0.5191441","0.5181201","0.5175327","0.51715255","0.51670504","0.51669174","0.5166572"],"string":"[\n \"0.6352975\",\n \"0.62675714\",\n \"0.61275345\",\n \"0.5952627\",\n \"0.5907965\",\n \"0.58464473\",\n \"0.5796776\",\n \"0.578933\",\n \"0.57794523\",\n \"0.57792443\",\n \"0.5757177\",\n \"0.5749844\",\n \"0.57261205\",\n \"0.5726011\",\n \"0.56745857\",\n \"0.5649165\",\n \"0.56255597\",\n \"0.5618809\",\n \"0.5615824\",\n \"0.55846244\",\n \"0.5575734\",\n \"0.55678564\",\n \"0.5558076\",\n \"0.5558076\",\n \"0.5558076\",\n \"0.55468947\",\n \"0.55329084\",\n \"0.5502345\",\n \"0.55007267\",\n \"0.54945827\",\n \"0.5486501\",\n \"0.5486107\",\n \"0.5483363\",\n \"0.54748726\",\n \"0.5470862\",\n \"0.54575795\",\n \"0.54575104\",\n \"0.5454245\",\n \"0.5444075\",\n \"0.5439287\",\n \"0.5439023\",\n \"0.54335827\",\n \"0.54326206\",\n \"0.5429286\",\n \"0.5419967\",\n \"0.5419636\",\n \"0.5413704\",\n \"0.5413231\",\n \"0.54093695\",\n \"0.5405765\",\n \"0.5403048\",\n \"0.5401799\",\n \"0.5399949\",\n \"0.53990865\",\n \"0.5390334\",\n \"0.5383853\",\n \"0.5382359\",\n \"0.53787386\",\n \"0.53770256\",\n \"0.5374631\",\n \"0.5373034\",\n \"0.5371954\",\n \"0.536459\",\n \"0.5363246\",\n \"0.5359254\",\n \"0.5355683\",\n \"0.534502\",\n \"0.5337399\",\n \"0.53353155\",\n \"0.53341794\",\n \"0.5333126\",\n \"0.532686\",\n \"0.53198457\",\n \"0.5315376\",\n \"0.53144574\",\n \"0.5301394\",\n \"0.52952445\",\n \"0.52941525\",\n \"0.5260467\",\n \"0.52507013\",\n \"0.52471924\",\n \"0.52338666\",\n \"0.5231545\",\n \"0.5225373\",\n \"0.5220493\",\n \"0.52130556\",\n \"0.52061236\",\n \"0.5206067\",\n \"0.5205742\",\n \"0.5202392\",\n \"0.5201588\",\n \"0.52007437\",\n \"0.5195376\",\n \"0.5191441\",\n \"0.5181201\",\n \"0.5175327\",\n \"0.51715255\",\n \"0.51670504\",\n \"0.51669174\",\n \"0.5166572\"\n]"},"document_score":{"kind":"string","value":"0.6316739"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":8552,"cells":{"query":{"kind":"string","value":"Write a hoc file."},"document":{"kind":"string","value":"def writeHoc(self):\n print('Writing output file %s ...' % self.outFile)\n with open(self.outFile, 'w') as fOut:\n \n def createSection(secNum):\n fOut.write('create section_%i\\n' %secNum)\n fOut.write('section_%i {\\n' %secNum)\n fOut.write('pt3dclear()\\n')\n for node in xrange(len(self.sections[secNum])):\n fOut.write('pt3dadd(%.6f, %.6f, %.6f, %.6f)\\n' \\\n % (self.sections[secNum][node][0],\n self.sections[secNum][node][1],\n self.sections[secNum][node][2],\n self.secRads[secNum][node]))\n fOut.write('}\\n')\n \n def createConnection():\n for c in xrange(len(self.connections)):\n fOut.write('connect section_%i(1), section_%i(0)\\n' \\\n % (self.connections[c][0],self.connections[c][1]))\n \n \n for sec in self.sections.keys():\n createSection(sec)\n createConnection()\n \n \n return"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def write_to_file(self, filename: str) -> None:","def write(self, filename):\n pass","def write(self, filename):\n pass","def write(self, filename, data, hdr):\n pass","def write(self, fname):\n pass","def write_file(self):\n file = open(self.__file_path, 'w+')\n file.truncate(0)\n file.write(self.__content)\n file.close()","def write_file(file, content):\n with open(file, \"w\") as fid:\n fid.write(content)","def write_to_file(self, overwrite=True):\n t0 = time.time()\n self.hdus.verify()\n if BACKEND == 'astropy':\n self.hdus.writeto(self.filename, overwrite=overwrite)\n elif BACKEND == 'pyfits':\n self.hdus.writeto(self.filename, clobber=overwrite)\n self.logger.debug(\"Took {:.4f} seconds to write to disk\".format(time.time() - t0))","def openHFile():\r\n global file2write\r\n \r\n file2write=open(\"Core/Inc/songs.h\",'w')","def write(cls, file, data):\n file.write(data)","def write_to(self, filepath):\n output = self._generate_output()\n with open(filepath, 'wb') as out:\n out.write(output.encode('utf-8'))\n out.write(b'\\n')","def write_to_file(unit, fobj):\n\n _write_all_headers(unit, fobj)\n _write_all_sections(unit, fobj)","def write_file(path, data):\n with open_local_or_gcs(path, 'w') as h_dest:\n h_dest.write(data) # pylint: disable=no-member","def file_write(stuff, file_path):\n with open(file_path, \"wt\") as fo:\n fo.write(stuff)","def write(self, filename): # real signature unknown; restored from __doc__\n pass","def filewrite(self, filename):\n io.write(self, filename)","def write_file(*args, **kwargs): # real signature unknown\n pass","def writeHedr(self):\n path = os.path.join(self.dir,self.name)\n out = file(path,'r+b')\n out.seek(16) #--Skip to Hedr record data\n self.tes3.hedr.getSize()\n self.tes3.hedr.dump(out)\n out.close()\n #--Done\n self.getHeader()\n self.setMTime()","def write_data(fh, header, data):\r\n # fhw = open(filename, \"w\")\r\n fh.write(str(header))\r\n fh.write(str(data) + \"\\n\")","def write(self, file):\n #write header\n self.ID.write(file)\n if (self.write_size): \n self.size.write(file)\n for variable in self.variables:\n variable.write(file)\n for subchunk in self.subchunks:\n subchunk.write(file)","def write_file(self):\n if self._write_file == None:\n return\n\n try:\n out = file(self._write_file, \"w\")\n except IOError, e:\n print e\n sys.exit(1)\n out.writelines(\"A cases\") \n out.close()","def write_to_file(filename, content):\n with open(filename, 'w') as f:\n f.write(content)","def write(self, filename):\n bvh_string = self.generate_bvh_string()\n if filename[-4:] == '.bvh':\n filename = filename\n else:\n filename = filename + '.bvh'\n with open(filename, 'w') as outfile:\n outfile.write(bvh_string)","def write_file(filename, data):\n file = open(filename, \"a\")\n file.write(data)\n file.close()","def write(self, filename, data):\n owner_rw = 0600\n fd = os.open(filename, os.O_WRONLY | os.O_CREAT, owner_rw)\n # In case file existed already with wrong permissions, fix them.\n os.chmod(filename, owner_rw)\n os.write(fd, data)\n os.close(fd)","def write_to_file(data, filename):\n fimg = fits.HDUList()\n fimghdu = fits.PrimaryHDU()\n fimghdu.data = data\n fimg.append(fimghdu)\n fimg.writeto(filename, overwrite=True)\n print(' wrote output data to: ', filename)","def writefile(filename, content):\n with open(Path(os.path.expanduser(filename)), 'w') as outfile:\n outfile.write(content)","def write(self, filename, data):\n raise NotImplementedError","def file_writer(path, data):\n with open(path, \"a\") as file:\n file.write(data + \"\\n\")","def writeFile(self, filename):\n\n s = self.asString()\n if os.access(filename, os.F_OK):\n raise RuntimeError(\"file %s already exists -- not overwritten.\" % (filename))\n \n f = file(filename, \"w\")\n f.write(s)\n f.close()","def write_to_file(self, file, content):\n with open(file, 'a') as report_file:\n report_file.write('{}\\n'.format(content))","def write(self, instream: typ.BinaryIO, filepath: str,\r\n filename: str = None) -> None:\r\n if filename is not None:\r\n filename = path.basename(filename)\r\n if self.fs_type == 'FAT':\r\n allocator_metadata = self.fs.write(instream, filepath)\r\n self.metadata.add_file(filename, allocator_metadata)\r\n elif self.fs_type == 'NTFS':\r\n allocator_metadata = self.fs.write(instream, filepath)\r\n self.metadata.add_file(filename, allocator_metadata)\r\n else:\r\n raise NotImplementedError()","def put(self, filename, data, **kw):\n\n file_path = os.path.join(self.storage_path, filename)\n file_obj = open(file_path, \"w\")\n file_obj.write(data)","def write_file(self, filename, contents):\n blob = self.repo.create_blob(contents)\n self.index.add(pygit2.IndexEntry(filename, blob, pygit2.GIT_FILEMODE_BLOB))","def write_file(filename: str, content: str, mode: str = \"w\") -> IO:\n with open(filename, mode) as file:\n file.write(content)\n return file","def writefile():\n\n print(\"Writing to file...\")\n\n # Open the heartbeat file in append mode and save the current time.\n with open(settings.ROOT_DIR + \"/heartbeat\", \"a\") as f:\n f.write(str(time()))","def write (self, file):\n\t\tfile.write (self.pack ())","def write_file(file_path, contents):\n logger.debug(f'write to file:{file_path}')\n with open(file_path, 'w') as outfile:\n outfile.write(contents)","def write_file(path, data):\n # opens file\n try:\n os.makedirs(os.path.dirname(path), exist_ok=True)\n f = open(str(path), \"w\")\n f.write(data)\n f.close()\n except Exception as e:\n print(\"Error writing file: \", e)\n sys.exit(1)","def write_to_file(self):\n self.calibration_directory.mkdir(parents=True, exist_ok=True)\n with self.file_path.open(mode=\"w\") as file:\n \"\"\"\n ------------------\n Data virtual object\n ------------------\n \"\"\"\n file.write(\"Data received from the hololens:\\n\")\n file.write(f'{\"\".join(self.hololens_message)}\\n')\n file.write(\"Position and Rotation received from hololens \\n\")\n file.write(\"Pay attention: Left handed KOS and quaternion with scalar last\\n\")\n # for i in self.calibration_position:\n position = \" \".join([str(x) for x in self.calibration_position])\n file.write(position)\n file.write(\"\\n\")\n rotation = \" \".join([str(x) for x in self.calibration_rotation])\n file.write(rotation)\n file.write(\"\\n\")\n \"\"\"\n ------------------\n Holotracker\n ------------------\n \"\"\"\n file.write(f\"Holotracker Pose: Tracker->LH\\n\")\n file.write(\"x y z\\n\")\n position = \" \".join([str(x) for x in self.holo_tracker.position])\n file.write(f\"{position}\\n\")\n file.write(\"w i j k\\n\")\n rotation = \" \".join([str(x) for x in self.holo_tracker.rotation])\n file.write(f\"{rotation}\\n\")\n file.write(\"Homogenous matrix of Holo Tracker\\n\")\n np.savetxt(file, self.holo_tracker.get_pose_as_hom_matrix())\n file.write(\"\\n\")\n \"\"\"\n ------------------\n Calibrationtracker\n ------------------\n \"\"\"\n file.write(f\"Calibrationtracker Pose: Tracker->LH\\n\")\n file.write(\"x y z\\n\")\n position = \" \".join([str(x) for x in self.calibration_tracker.position])\n file.write(f\"{position}\\n\")\n file.write(\"w i j k\\n\")\n rotation = \" \".join([str(x) for x in self.calibration_tracker.rotation])\n file.write(f\"{rotation}\\n\")\n file.write(\"Homogenous matrix of Calibration Tracker\\n\")\n np.savetxt(file, self.calibration_tracker.get_pose_as_hom_matrix())\n file.write(\"\\n\")\n \"\"\"\n ------------------\n Calibration object used\n ------------------\n \"\"\"\n file.write(f\"CalibrationObject used : \\n{self.calibration_object}\")\n file.write(\"\\n\")\n \"\"\"\n ------------------\n Point registration service + reprojection error\n ------------------\n \"\"\"\n file.write(\"\\nMarix LH->Virtual\\n\")\n np.savetxt(file, self.hom_LH_to_virtual,)\n file.write(\"\\nReprojection error\\n\")\n file.write(f\"{self.reprojection_error}\")\n file.write(\"\\n\")\n \"\"\"\n ------------------\n Virtual center to Tracker\n ------------------\n \"\"\"\n file.write(\"\\nMatrix Virtual->Tracker\\n\")\n np.savetxt(file, self.hom_tracker_to_virtual)\n file.write(\"\\n\")\n \"\"\"\n ------------------\n Point Data which was used for matching\n ------------------\n \"\"\"\n file.write(\"POINTS THAT WERE MATCHED\\n\\n\")\n file.write(\"Virtual points. Already transformed into Right Hand KOS \\n\")\n np.savetxt(file, self.virtual_points)\n file.write(\"\\n\")\n file.write(\"Real points\\n\")\n np.savetxt(file, self.real_points)","def write_file(data, file_path):\n try:\n with open(file_path, \"w\") as file_obj:\n file_obj.write(data)\n\n except OSError:\n writer(f\"\\nwarning: Unable to write backup file {file_path}\\n\", FORMAT[\"WARNING\"])","def write_file(data, filename):\n file = open(filename, \"wb\")\n file.write(data)\n file.close()","def write_to_file(filepath, data):\n\n with open(filepath, 'w') as f:\n f.write(str(data))","def write(self, prefix, path=None):\n\n if path is None:\n path = os.getcwd()\n\n header, source = self.doprint(prefix=prefix)\n\n with open(os.path.join(path, prefix + '.h'), 'w') as f:\n f.write(header)\n\n with open(os.path.join(path, prefix + '.c'), 'w') as f:\n f.write(source)","def write(self, content):\n if content is None:\n self.hash = None\n else:\n try:\n self.hash = hashlib.sha1(content.encode('utf-8')).hexdigest()\n except AttributeError:\n self.hash = hashlib.sha1(content).hexdigest()\n\n if self._has_tmp_file_path():\n with open(self._get_tmp_file_path(), \"w\") as tmp_file:\n tmp_file.write(content)\n else:\n self._content = content","def write_file(filename):\r\n if Py3:\r\n return open(filename, \"w\", newline='')\r\n return open(filename, \"wb\")","def _write_file(output_path: str, file_content: Iterable[str]) -> None:\n with open(output_path, \"w+\", encoding=\"utf-8\") as f:\n f.writelines(file_content)\n\n logging.info(f\"wrote to '{output_path}'\")","def write(self, filename, data):\n\t\t# create the path if it doesn't exists\n\t\tdir = os.path.dirname(filename)\n\t\tif not os.path.isdir(dir):\n\t\t\tos.mkdir(dir)\n\t\t\n\t\t# write data\n\t\tfile = codecs.open(filename, 'w', 'utf8')\n\t\tfile.write(data)\n\t\tfile.close()","def write_file(self, contents):\n fd = open(os.path.join(os.path.dirname(__file__),\n 'data', 'test.html'), 'w')\n fd.write(contents)\n fd.close()","def saveOnFile(self, path, data):\n with open(path, \"w\") as f:\n f.write(data)","def _write_output_file(output: str, file_name: str):\n\tfile1 = open(file_name, 'w')\n\tfile1.write(output)\n\tfile1.close()","def write_file(path, contents, mode=\"w\"):\n with open(path, mode) as f:\n f.write(contents)","def write(self, path, content):\n this_file = open(path, 'w')\n this_file.write(content)\n this_file.close()","def create_file(self, content=\"\"):\n if (self.exists()):\n raise IOError(\"A file at '{}' already exists.\".format(self.location))\n with open(self.location, 'w') as f:\n f.write(content)","def write_to_file(entry, file):\n with open(file, \"a\") as f:\n f.write(entry)","def write(filename):\n print(uc.write(filename))","def write_file(filename, content):\n codecs.open(filename, \"w\", encoding='utf-8').writelines(content)","def write_to_file(filename, data):\n with open(filename, \"a\") as file:\n file.writelines(data)","def write_to_file(filename, data):\n with open(filename, \"a\") as file:\n file.writelines(data)","def write_to_file(file: Text, data: bytes):\n with open(file, \"wb\") as w:\n w.write(data)\n w.flush()","def fs_write(obj, file_path):\n try:\n with open(str(file_path), 'w') as f:\n f.write(obj)\n return obj\n except TypeError as e:\n raise e","def write(self,path,content):\n file_path = os.path.join( self.directory, path)\n with open(file_path, \"w\") as file:\n file.write( content )","def write_file(filename, content):\n dirname = os.path.dirname(filename)\n if not os.path.isdir(dirname):\n os.makedirs(dirname)\n\n with open(filename, 'wb') as f:\n f.write(content.encode('utf-8'))","def create_file(path):\n open(path, \"w\").close()","def write(self, file):\n #write header\n for variable in self.variables:\n variable.write(file)\n for subchunk in self.subchunks:\n subchunk.write(file)","def write(self, content, mode='wb'):\r\n self.localpath.write(content, mode)","def writable(path):","def write(self, file_path, content):\n self._set_extension(file_path)\n\n logger.debug(\"writing to %s\", self._file_path)\n\n self._content = content\n\n if self._file_ext == 'json':\n self._write_json()","def write_to_file(file_name, content):\n with open(file_name, \"w\") as text_file:\n text_file.write(str(content))","def file_write(filename, dic):\n d = dic \n f = open(filename, 'w') \n f.write(str(d))\n f.close()","def create_output_file(self):\n if self.options['storage_method'] == 'hdf5':\n try:\n fp = h5py.File(self.file_name, \"w\")\n except IOError:\n print \"Unable to open output file '%s'\" % self.file_name\n sys.exit(1)\n # remember file pointer\n self.file_pointer = fp\n print \"Creating file '%s'\" % self.file_name\n elif self.options['storage_method'] == 'none':\n # save command for later processing\n self.h5commands.append((\"create_file\", self.file_name))","def _write_file(self, filename, content, mode=None):\n with open(filename, 'w') as fp:\n fp.write(dedent(content).strip())\n fp.write('\\n')\n\n if mode is not None:\n os.chmod(filename, mode)","def write_file(content, file_path, mode='w', encoding='utf-8'):\n with codecs.open(file_path, mode, encoding=encoding) as fid:\n fid.write(content)","def WriteFile(path, content, mode='w', atomic=False, makedirs=False):\n write_path = path\n if atomic:\n write_path = path + '.tmp'\n\n if makedirs:\n SafeMakedirs(os.path.dirname(path))\n\n with open(write_path, mode) as f:\n f.writelines(cros_build_lib.iflatten_instance(content))\n\n if not atomic:\n return\n\n try:\n os.rename(write_path, path)\n except EnvironmentError:\n SafeUnlink(write_path)\n raise","def write_file ( file_name, contents ):\n vlog(4, 'Writing File: %s SIZE=%s' % (file_name, len(contents)))\n with open(file_name, 'w') as file:\n file.write(contents)","def write(self, data_to_write):\n self.single_file.write(data_to_write)\n self.single_file.flush()","def write_to_file(self, filepath, mode = \"a\"): \n if \"r\" in mode: \n print(\"Only accepts write and append modes\")\n return \n with open(filepath, mode) as f: \n f.write(\"{}\\n\".format(self.title))\n verified, seen, ratio = self.get_verified_ratio()\n f.write(\"Verified Names: {}\\n\".format(str(verified)))\n f.write(\"Names: {}\\n\".format(str(seen)))\n f.write(\"Ratio: {}\\n\".format(str(ratio)))","def WriteFile(fname, data):\n #self._out.Info(\"Write file '%s' size %d (%#0x)\" %\n #(fname, len(data), len(data)))\n with open(Filename(fname), 'wb') as fd:\n fd.write(data)","def write_configuration_file(self, content):\n with open(self.configuration_file_path, 'w') as configuration_file:\n configuration_file.write(content)","def write(self, file):\n pos = file.tell()\n pickle.dump((self.index, self.meta, self.info), file)\n file.seek(0)\n\n # update the header with the position of the content index.\n file.write(struct.pack(' None:\n self._original.write(output)\n self._handler.file_write(self._name, output)","def write(self, ext_file_action=ExtFileAction.copy_relative_paths):\n if self.simulation_data.auto_set_sizes:\n self._update_size_defs()\n\n # create any folders in path\n package_file_path = self.get_file_path()\n package_folder = os.path.split(package_file_path)[0]\n if package_folder and not os.path.isdir(package_folder):\n os.makedirs(os.path.split(package_file_path)[0])\n\n # open file\n fd = open(package_file_path, \"w\")\n\n # write flopy header\n if self.simulation_data.write_headers:\n dt = datetime.datetime.now()\n header = (\n \"# File generated by Flopy version {} on {} at {}.\"\n \"\\n\".format(\n __version__,\n dt.strftime(\"%m/%d/%Y\"),\n dt.strftime(\"%H:%M:%S\"),\n )\n )\n fd.write(header)\n\n # write blocks\n self._write_blocks(fd, ext_file_action)\n\n fd.close()","def write_file(self, directory, name, content):\n\n try:\n f = open(os.path.join(directory, name), 'w')\n f.write(content)\n f.close()\n except:\n print \"Content not written to file: %s\" % name","def save_to_file(self, file_name, format, properties=None,\n halo_properties=None):\n\n directory = '/'.join(file_name.split('/')[:-1])\n import os\n if not os.path.exists(directory):\n os.makedirs(directory)\n\n if format == \"hdf5\":\n import h5py\n\n f = h5py.File(file_name, \"a\")\n\n if properties is None: \n # save every property\n for quantity in self._quantities:\n f.create_dataset(quantity, data=self._quantities[quantity],\n compression=\"gzip\")\n else: \n # save specified properties\n for quantity in properties:\n f.create_dataset(quantity, data=self._quantities[quantity],\n compression=\"gzip\")\n\n if not halo_properties is None:\n # save specified halo properties\n for quantity in halo_properties:\n f.create_dataset(\"halo_\"+quantity, compression=\"gzip\",\n data=self.get_halo(quantity))\n f.close()\n\n elif format == \"fits\":\n from astropy.table import Table\n \n if properties is None:\n # save every property\n t = Table(list(self._quantities.values()), \n names=list(self._quantities.keys()))\n t.write(file_name, format=\"fits\")\n else:\n # save specified properties\n data = [None] * len(properties)\n for i, prop in enumerate(properties):\n data[i] = self._quantities[prop]\n t = Table(data, names=properties)\n t.write(file_name, format=\"fits\")\n\n if not halo_properties is None:\n # save specified halo properties\n data = [None] * len(halo_properties)\n for i, prop in enumerate(halo_properties):\n data[i] = self.get_halo(prop)\n halo_properties[i] = \"halo_\" + halo_properties[i]\n t = Table(data, names=halo_properties)\n t.write(file_name, format=\"fits\")\n\n # can add more file formats...\n\n else:\n raise ValueError(\"Invalid file format\")","def write(self, file, data):\n if not exists(dirname(file)):\n makedirs(dirname(file))\n\n with open(file + '.json', 'w') as file:\n file.write(dumps(data, indent=2, separators=(',', ': '), sort_keys=True))","def save_hdf_file(file_path, idata, key_path='entry', overwrite=True):\r\n if (\"\\\\\" in file_path):\r\n raise ValueError(\r\n \"Please use a file path following the Unix convention\")\r\n file_base, file_ext = os.path.splitext(file_path)\r\n if not ((file_ext == '.hdf') or (file_ext == '.h5')):\r\n file_ext = '.hdf'\r\n file_path = file_base + file_ext\r\n _create_folder(file_path)\r\n if not overwrite:\r\n file_path = _create_file_name(file_path)\r\n ofile = None\r\n try:\r\n ofile = h5py.File(file_path, 'w')\r\n except IOError:\r\n print((\"Couldn't write file: {}\").format(file_path))\r\n raise\r\n grp = ofile.create_group(key_path)\r\n grp.create_dataset(\"data\", data=idata)\r\n ofile.close()\r\n return file_path","def to_file(self, filename=None):\n name = None\n if filename is not None:\n name = filename\n elif self.name:\n name = self.name\n\n if name:\n #f = open(self.name, 'w')\n f = codecs.open(name, 'w', encoding='utf-8')\n self.seek(0)\n f.write(self.read())\n f.close()\n else:\n print \"No log_name for this log\"","def write_to_file(self,\n ofile=\"output.txt\",\n **kwargs):\n with open(file=ofile, mode='a') as ofile:\n for num_line, obj in self.items():\n ofile.write(str(self._construct_output_string(num_line=num_line,\n obj=obj,\n **kwargs)))","def write_data_2(fh, header, data):\r\n # fhw = open(filename, \"w\")\r\n if len(header) <= 0 or len(data) <= 0:\r\n return\r\n else:\r\n fh.write(str(header + \"\\n\"))\r\n fh.write(str(data) + \"\\n\")\r\n fh.write(\"\\n\")","def write(self, filename, header=None):\n\n origfile = self._filename\n\n try:\n with open(filename, 'w') as _file:\n self.writestream(_file, header)\n self._filename = filename\n return True\n\n except IOError:\n self._filename = origfile\n return False","def create_file(path: Path, content: str) -> None:\n path.touch()\n with path.open(\"w\") as f:\n f.write(content)"],"string":"[\n \"def write_to_file(self, filename: str) -> None:\",\n \"def write(self, filename):\\n pass\",\n \"def write(self, filename):\\n pass\",\n \"def write(self, filename, data, hdr):\\n pass\",\n \"def write(self, fname):\\n pass\",\n \"def write_file(self):\\n file = open(self.__file_path, 'w+')\\n file.truncate(0)\\n file.write(self.__content)\\n file.close()\",\n \"def write_file(file, content):\\n with open(file, \\\"w\\\") as fid:\\n fid.write(content)\",\n \"def write_to_file(self, overwrite=True):\\n t0 = time.time()\\n self.hdus.verify()\\n if BACKEND == 'astropy':\\n self.hdus.writeto(self.filename, overwrite=overwrite)\\n elif BACKEND == 'pyfits':\\n self.hdus.writeto(self.filename, clobber=overwrite)\\n self.logger.debug(\\\"Took {:.4f} seconds to write to disk\\\".format(time.time() - t0))\",\n \"def openHFile():\\r\\n global file2write\\r\\n \\r\\n file2write=open(\\\"Core/Inc/songs.h\\\",'w')\",\n \"def write(cls, file, data):\\n file.write(data)\",\n \"def write_to(self, filepath):\\n output = self._generate_output()\\n with open(filepath, 'wb') as out:\\n out.write(output.encode('utf-8'))\\n out.write(b'\\\\n')\",\n \"def write_to_file(unit, fobj):\\n\\n _write_all_headers(unit, fobj)\\n _write_all_sections(unit, fobj)\",\n \"def write_file(path, data):\\n with open_local_or_gcs(path, 'w') as h_dest:\\n h_dest.write(data) # pylint: disable=no-member\",\n \"def file_write(stuff, file_path):\\n with open(file_path, \\\"wt\\\") as fo:\\n fo.write(stuff)\",\n \"def write(self, filename): # real signature unknown; restored from __doc__\\n pass\",\n \"def filewrite(self, filename):\\n io.write(self, filename)\",\n \"def write_file(*args, **kwargs): # real signature unknown\\n pass\",\n \"def writeHedr(self):\\n path = os.path.join(self.dir,self.name)\\n out = file(path,'r+b')\\n out.seek(16) #--Skip to Hedr record data\\n self.tes3.hedr.getSize()\\n self.tes3.hedr.dump(out)\\n out.close()\\n #--Done\\n self.getHeader()\\n self.setMTime()\",\n \"def write_data(fh, header, data):\\r\\n # fhw = open(filename, \\\"w\\\")\\r\\n fh.write(str(header))\\r\\n fh.write(str(data) + \\\"\\\\n\\\")\",\n \"def write(self, file):\\n #write header\\n self.ID.write(file)\\n if (self.write_size): \\n self.size.write(file)\\n for variable in self.variables:\\n variable.write(file)\\n for subchunk in self.subchunks:\\n subchunk.write(file)\",\n \"def write_file(self):\\n if self._write_file == None:\\n return\\n\\n try:\\n out = file(self._write_file, \\\"w\\\")\\n except IOError, e:\\n print e\\n sys.exit(1)\\n out.writelines(\\\"A cases\\\") \\n out.close()\",\n \"def write_to_file(filename, content):\\n with open(filename, 'w') as f:\\n f.write(content)\",\n \"def write(self, filename):\\n bvh_string = self.generate_bvh_string()\\n if filename[-4:] == '.bvh':\\n filename = filename\\n else:\\n filename = filename + '.bvh'\\n with open(filename, 'w') as outfile:\\n outfile.write(bvh_string)\",\n \"def write_file(filename, data):\\n file = open(filename, \\\"a\\\")\\n file.write(data)\\n file.close()\",\n \"def write(self, filename, data):\\n owner_rw = 0600\\n fd = os.open(filename, os.O_WRONLY | os.O_CREAT, owner_rw)\\n # In case file existed already with wrong permissions, fix them.\\n os.chmod(filename, owner_rw)\\n os.write(fd, data)\\n os.close(fd)\",\n \"def write_to_file(data, filename):\\n fimg = fits.HDUList()\\n fimghdu = fits.PrimaryHDU()\\n fimghdu.data = data\\n fimg.append(fimghdu)\\n fimg.writeto(filename, overwrite=True)\\n print(' wrote output data to: ', filename)\",\n \"def writefile(filename, content):\\n with open(Path(os.path.expanduser(filename)), 'w') as outfile:\\n outfile.write(content)\",\n \"def write(self, filename, data):\\n raise NotImplementedError\",\n \"def file_writer(path, data):\\n with open(path, \\\"a\\\") as file:\\n file.write(data + \\\"\\\\n\\\")\",\n \"def writeFile(self, filename):\\n\\n s = self.asString()\\n if os.access(filename, os.F_OK):\\n raise RuntimeError(\\\"file %s already exists -- not overwritten.\\\" % (filename))\\n \\n f = file(filename, \\\"w\\\")\\n f.write(s)\\n f.close()\",\n \"def write_to_file(self, file, content):\\n with open(file, 'a') as report_file:\\n report_file.write('{}\\\\n'.format(content))\",\n \"def write(self, instream: typ.BinaryIO, filepath: str,\\r\\n filename: str = None) -> None:\\r\\n if filename is not None:\\r\\n filename = path.basename(filename)\\r\\n if self.fs_type == 'FAT':\\r\\n allocator_metadata = self.fs.write(instream, filepath)\\r\\n self.metadata.add_file(filename, allocator_metadata)\\r\\n elif self.fs_type == 'NTFS':\\r\\n allocator_metadata = self.fs.write(instream, filepath)\\r\\n self.metadata.add_file(filename, allocator_metadata)\\r\\n else:\\r\\n raise NotImplementedError()\",\n \"def put(self, filename, data, **kw):\\n\\n file_path = os.path.join(self.storage_path, filename)\\n file_obj = open(file_path, \\\"w\\\")\\n file_obj.write(data)\",\n \"def write_file(self, filename, contents):\\n blob = self.repo.create_blob(contents)\\n self.index.add(pygit2.IndexEntry(filename, blob, pygit2.GIT_FILEMODE_BLOB))\",\n \"def write_file(filename: str, content: str, mode: str = \\\"w\\\") -> IO:\\n with open(filename, mode) as file:\\n file.write(content)\\n return file\",\n \"def writefile():\\n\\n print(\\\"Writing to file...\\\")\\n\\n # Open the heartbeat file in append mode and save the current time.\\n with open(settings.ROOT_DIR + \\\"/heartbeat\\\", \\\"a\\\") as f:\\n f.write(str(time()))\",\n \"def write (self, file):\\n\\t\\tfile.write (self.pack ())\",\n \"def write_file(file_path, contents):\\n logger.debug(f'write to file:{file_path}')\\n with open(file_path, 'w') as outfile:\\n outfile.write(contents)\",\n \"def write_file(path, data):\\n # opens file\\n try:\\n os.makedirs(os.path.dirname(path), exist_ok=True)\\n f = open(str(path), \\\"w\\\")\\n f.write(data)\\n f.close()\\n except Exception as e:\\n print(\\\"Error writing file: \\\", e)\\n sys.exit(1)\",\n \"def write_to_file(self):\\n self.calibration_directory.mkdir(parents=True, exist_ok=True)\\n with self.file_path.open(mode=\\\"w\\\") as file:\\n \\\"\\\"\\\"\\n ------------------\\n Data virtual object\\n ------------------\\n \\\"\\\"\\\"\\n file.write(\\\"Data received from the hololens:\\\\n\\\")\\n file.write(f'{\\\"\\\".join(self.hololens_message)}\\\\n')\\n file.write(\\\"Position and Rotation received from hololens \\\\n\\\")\\n file.write(\\\"Pay attention: Left handed KOS and quaternion with scalar last\\\\n\\\")\\n # for i in self.calibration_position:\\n position = \\\" \\\".join([str(x) for x in self.calibration_position])\\n file.write(position)\\n file.write(\\\"\\\\n\\\")\\n rotation = \\\" \\\".join([str(x) for x in self.calibration_rotation])\\n file.write(rotation)\\n file.write(\\\"\\\\n\\\")\\n \\\"\\\"\\\"\\n ------------------\\n Holotracker\\n ------------------\\n \\\"\\\"\\\"\\n file.write(f\\\"Holotracker Pose: Tracker->LH\\\\n\\\")\\n file.write(\\\"x y z\\\\n\\\")\\n position = \\\" \\\".join([str(x) for x in self.holo_tracker.position])\\n file.write(f\\\"{position}\\\\n\\\")\\n file.write(\\\"w i j k\\\\n\\\")\\n rotation = \\\" \\\".join([str(x) for x in self.holo_tracker.rotation])\\n file.write(f\\\"{rotation}\\\\n\\\")\\n file.write(\\\"Homogenous matrix of Holo Tracker\\\\n\\\")\\n np.savetxt(file, self.holo_tracker.get_pose_as_hom_matrix())\\n file.write(\\\"\\\\n\\\")\\n \\\"\\\"\\\"\\n ------------------\\n Calibrationtracker\\n ------------------\\n \\\"\\\"\\\"\\n file.write(f\\\"Calibrationtracker Pose: Tracker->LH\\\\n\\\")\\n file.write(\\\"x y z\\\\n\\\")\\n position = \\\" \\\".join([str(x) for x in self.calibration_tracker.position])\\n file.write(f\\\"{position}\\\\n\\\")\\n file.write(\\\"w i j k\\\\n\\\")\\n rotation = \\\" \\\".join([str(x) for x in self.calibration_tracker.rotation])\\n file.write(f\\\"{rotation}\\\\n\\\")\\n file.write(\\\"Homogenous matrix of Calibration Tracker\\\\n\\\")\\n np.savetxt(file, self.calibration_tracker.get_pose_as_hom_matrix())\\n file.write(\\\"\\\\n\\\")\\n \\\"\\\"\\\"\\n ------------------\\n Calibration object used\\n ------------------\\n \\\"\\\"\\\"\\n file.write(f\\\"CalibrationObject used : \\\\n{self.calibration_object}\\\")\\n file.write(\\\"\\\\n\\\")\\n \\\"\\\"\\\"\\n ------------------\\n Point registration service + reprojection error\\n ------------------\\n \\\"\\\"\\\"\\n file.write(\\\"\\\\nMarix LH->Virtual\\\\n\\\")\\n np.savetxt(file, self.hom_LH_to_virtual,)\\n file.write(\\\"\\\\nReprojection error\\\\n\\\")\\n file.write(f\\\"{self.reprojection_error}\\\")\\n file.write(\\\"\\\\n\\\")\\n \\\"\\\"\\\"\\n ------------------\\n Virtual center to Tracker\\n ------------------\\n \\\"\\\"\\\"\\n file.write(\\\"\\\\nMatrix Virtual->Tracker\\\\n\\\")\\n np.savetxt(file, self.hom_tracker_to_virtual)\\n file.write(\\\"\\\\n\\\")\\n \\\"\\\"\\\"\\n ------------------\\n Point Data which was used for matching\\n ------------------\\n \\\"\\\"\\\"\\n file.write(\\\"POINTS THAT WERE MATCHED\\\\n\\\\n\\\")\\n file.write(\\\"Virtual points. Already transformed into Right Hand KOS \\\\n\\\")\\n np.savetxt(file, self.virtual_points)\\n file.write(\\\"\\\\n\\\")\\n file.write(\\\"Real points\\\\n\\\")\\n np.savetxt(file, self.real_points)\",\n \"def write_file(data, file_path):\\n try:\\n with open(file_path, \\\"w\\\") as file_obj:\\n file_obj.write(data)\\n\\n except OSError:\\n writer(f\\\"\\\\nwarning: Unable to write backup file {file_path}\\\\n\\\", FORMAT[\\\"WARNING\\\"])\",\n \"def write_file(data, filename):\\n file = open(filename, \\\"wb\\\")\\n file.write(data)\\n file.close()\",\n \"def write_to_file(filepath, data):\\n\\n with open(filepath, 'w') as f:\\n f.write(str(data))\",\n \"def write(self, prefix, path=None):\\n\\n if path is None:\\n path = os.getcwd()\\n\\n header, source = self.doprint(prefix=prefix)\\n\\n with open(os.path.join(path, prefix + '.h'), 'w') as f:\\n f.write(header)\\n\\n with open(os.path.join(path, prefix + '.c'), 'w') as f:\\n f.write(source)\",\n \"def write(self, content):\\n if content is None:\\n self.hash = None\\n else:\\n try:\\n self.hash = hashlib.sha1(content.encode('utf-8')).hexdigest()\\n except AttributeError:\\n self.hash = hashlib.sha1(content).hexdigest()\\n\\n if self._has_tmp_file_path():\\n with open(self._get_tmp_file_path(), \\\"w\\\") as tmp_file:\\n tmp_file.write(content)\\n else:\\n self._content = content\",\n \"def write_file(filename):\\r\\n if Py3:\\r\\n return open(filename, \\\"w\\\", newline='')\\r\\n return open(filename, \\\"wb\\\")\",\n \"def _write_file(output_path: str, file_content: Iterable[str]) -> None:\\n with open(output_path, \\\"w+\\\", encoding=\\\"utf-8\\\") as f:\\n f.writelines(file_content)\\n\\n logging.info(f\\\"wrote to '{output_path}'\\\")\",\n \"def write(self, filename, data):\\n\\t\\t# create the path if it doesn't exists\\n\\t\\tdir = os.path.dirname(filename)\\n\\t\\tif not os.path.isdir(dir):\\n\\t\\t\\tos.mkdir(dir)\\n\\t\\t\\n\\t\\t# write data\\n\\t\\tfile = codecs.open(filename, 'w', 'utf8')\\n\\t\\tfile.write(data)\\n\\t\\tfile.close()\",\n \"def write_file(self, contents):\\n fd = open(os.path.join(os.path.dirname(__file__),\\n 'data', 'test.html'), 'w')\\n fd.write(contents)\\n fd.close()\",\n \"def saveOnFile(self, path, data):\\n with open(path, \\\"w\\\") as f:\\n f.write(data)\",\n \"def _write_output_file(output: str, file_name: str):\\n\\tfile1 = open(file_name, 'w')\\n\\tfile1.write(output)\\n\\tfile1.close()\",\n \"def write_file(path, contents, mode=\\\"w\\\"):\\n with open(path, mode) as f:\\n f.write(contents)\",\n \"def write(self, path, content):\\n this_file = open(path, 'w')\\n this_file.write(content)\\n this_file.close()\",\n \"def create_file(self, content=\\\"\\\"):\\n if (self.exists()):\\n raise IOError(\\\"A file at '{}' already exists.\\\".format(self.location))\\n with open(self.location, 'w') as f:\\n f.write(content)\",\n \"def write_to_file(entry, file):\\n with open(file, \\\"a\\\") as f:\\n f.write(entry)\",\n \"def write(filename):\\n print(uc.write(filename))\",\n \"def write_file(filename, content):\\n codecs.open(filename, \\\"w\\\", encoding='utf-8').writelines(content)\",\n \"def write_to_file(filename, data):\\n with open(filename, \\\"a\\\") as file:\\n file.writelines(data)\",\n \"def write_to_file(filename, data):\\n with open(filename, \\\"a\\\") as file:\\n file.writelines(data)\",\n \"def write_to_file(file: Text, data: bytes):\\n with open(file, \\\"wb\\\") as w:\\n w.write(data)\\n w.flush()\",\n \"def fs_write(obj, file_path):\\n try:\\n with open(str(file_path), 'w') as f:\\n f.write(obj)\\n return obj\\n except TypeError as e:\\n raise e\",\n \"def write(self,path,content):\\n file_path = os.path.join( self.directory, path)\\n with open(file_path, \\\"w\\\") as file:\\n file.write( content )\",\n \"def write_file(filename, content):\\n dirname = os.path.dirname(filename)\\n if not os.path.isdir(dirname):\\n os.makedirs(dirname)\\n\\n with open(filename, 'wb') as f:\\n f.write(content.encode('utf-8'))\",\n \"def create_file(path):\\n open(path, \\\"w\\\").close()\",\n \"def write(self, file):\\n #write header\\n for variable in self.variables:\\n variable.write(file)\\n for subchunk in self.subchunks:\\n subchunk.write(file)\",\n \"def write(self, content, mode='wb'):\\r\\n self.localpath.write(content, mode)\",\n \"def writable(path):\",\n \"def write(self, file_path, content):\\n self._set_extension(file_path)\\n\\n logger.debug(\\\"writing to %s\\\", self._file_path)\\n\\n self._content = content\\n\\n if self._file_ext == 'json':\\n self._write_json()\",\n \"def write_to_file(file_name, content):\\n with open(file_name, \\\"w\\\") as text_file:\\n text_file.write(str(content))\",\n \"def file_write(filename, dic):\\n d = dic \\n f = open(filename, 'w') \\n f.write(str(d))\\n f.close()\",\n \"def create_output_file(self):\\n if self.options['storage_method'] == 'hdf5':\\n try:\\n fp = h5py.File(self.file_name, \\\"w\\\")\\n except IOError:\\n print \\\"Unable to open output file '%s'\\\" % self.file_name\\n sys.exit(1)\\n # remember file pointer\\n self.file_pointer = fp\\n print \\\"Creating file '%s'\\\" % self.file_name\\n elif self.options['storage_method'] == 'none':\\n # save command for later processing\\n self.h5commands.append((\\\"create_file\\\", self.file_name))\",\n \"def _write_file(self, filename, content, mode=None):\\n with open(filename, 'w') as fp:\\n fp.write(dedent(content).strip())\\n fp.write('\\\\n')\\n\\n if mode is not None:\\n os.chmod(filename, mode)\",\n \"def write_file(content, file_path, mode='w', encoding='utf-8'):\\n with codecs.open(file_path, mode, encoding=encoding) as fid:\\n fid.write(content)\",\n \"def WriteFile(path, content, mode='w', atomic=False, makedirs=False):\\n write_path = path\\n if atomic:\\n write_path = path + '.tmp'\\n\\n if makedirs:\\n SafeMakedirs(os.path.dirname(path))\\n\\n with open(write_path, mode) as f:\\n f.writelines(cros_build_lib.iflatten_instance(content))\\n\\n if not atomic:\\n return\\n\\n try:\\n os.rename(write_path, path)\\n except EnvironmentError:\\n SafeUnlink(write_path)\\n raise\",\n \"def write_file ( file_name, contents ):\\n vlog(4, 'Writing File: %s SIZE=%s' % (file_name, len(contents)))\\n with open(file_name, 'w') as file:\\n file.write(contents)\",\n \"def write(self, data_to_write):\\n self.single_file.write(data_to_write)\\n self.single_file.flush()\",\n \"def write_to_file(self, filepath, mode = \\\"a\\\"): \\n if \\\"r\\\" in mode: \\n print(\\\"Only accepts write and append modes\\\")\\n return \\n with open(filepath, mode) as f: \\n f.write(\\\"{}\\\\n\\\".format(self.title))\\n verified, seen, ratio = self.get_verified_ratio()\\n f.write(\\\"Verified Names: {}\\\\n\\\".format(str(verified)))\\n f.write(\\\"Names: {}\\\\n\\\".format(str(seen)))\\n f.write(\\\"Ratio: {}\\\\n\\\".format(str(ratio)))\",\n \"def WriteFile(fname, data):\\n #self._out.Info(\\\"Write file '%s' size %d (%#0x)\\\" %\\n #(fname, len(data), len(data)))\\n with open(Filename(fname), 'wb') as fd:\\n fd.write(data)\",\n \"def write_configuration_file(self, content):\\n with open(self.configuration_file_path, 'w') as configuration_file:\\n configuration_file.write(content)\",\n \"def write(self, file):\\n pos = file.tell()\\n pickle.dump((self.index, self.meta, self.info), file)\\n file.seek(0)\\n\\n # update the header with the position of the content index.\\n file.write(struct.pack(' None:\\n self._original.write(output)\\n self._handler.file_write(self._name, output)\",\n \"def write(self, ext_file_action=ExtFileAction.copy_relative_paths):\\n if self.simulation_data.auto_set_sizes:\\n self._update_size_defs()\\n\\n # create any folders in path\\n package_file_path = self.get_file_path()\\n package_folder = os.path.split(package_file_path)[0]\\n if package_folder and not os.path.isdir(package_folder):\\n os.makedirs(os.path.split(package_file_path)[0])\\n\\n # open file\\n fd = open(package_file_path, \\\"w\\\")\\n\\n # write flopy header\\n if self.simulation_data.write_headers:\\n dt = datetime.datetime.now()\\n header = (\\n \\\"# File generated by Flopy version {} on {} at {}.\\\"\\n \\\"\\\\n\\\".format(\\n __version__,\\n dt.strftime(\\\"%m/%d/%Y\\\"),\\n dt.strftime(\\\"%H:%M:%S\\\"),\\n )\\n )\\n fd.write(header)\\n\\n # write blocks\\n self._write_blocks(fd, ext_file_action)\\n\\n fd.close()\",\n \"def write_file(self, directory, name, content):\\n\\n try:\\n f = open(os.path.join(directory, name), 'w')\\n f.write(content)\\n f.close()\\n except:\\n print \\\"Content not written to file: %s\\\" % name\",\n \"def save_to_file(self, file_name, format, properties=None,\\n halo_properties=None):\\n\\n directory = '/'.join(file_name.split('/')[:-1])\\n import os\\n if not os.path.exists(directory):\\n os.makedirs(directory)\\n\\n if format == \\\"hdf5\\\":\\n import h5py\\n\\n f = h5py.File(file_name, \\\"a\\\")\\n\\n if properties is None: \\n # save every property\\n for quantity in self._quantities:\\n f.create_dataset(quantity, data=self._quantities[quantity],\\n compression=\\\"gzip\\\")\\n else: \\n # save specified properties\\n for quantity in properties:\\n f.create_dataset(quantity, data=self._quantities[quantity],\\n compression=\\\"gzip\\\")\\n\\n if not halo_properties is None:\\n # save specified halo properties\\n for quantity in halo_properties:\\n f.create_dataset(\\\"halo_\\\"+quantity, compression=\\\"gzip\\\",\\n data=self.get_halo(quantity))\\n f.close()\\n\\n elif format == \\\"fits\\\":\\n from astropy.table import Table\\n \\n if properties is None:\\n # save every property\\n t = Table(list(self._quantities.values()), \\n names=list(self._quantities.keys()))\\n t.write(file_name, format=\\\"fits\\\")\\n else:\\n # save specified properties\\n data = [None] * len(properties)\\n for i, prop in enumerate(properties):\\n data[i] = self._quantities[prop]\\n t = Table(data, names=properties)\\n t.write(file_name, format=\\\"fits\\\")\\n\\n if not halo_properties is None:\\n # save specified halo properties\\n data = [None] * len(halo_properties)\\n for i, prop in enumerate(halo_properties):\\n data[i] = self.get_halo(prop)\\n halo_properties[i] = \\\"halo_\\\" + halo_properties[i]\\n t = Table(data, names=halo_properties)\\n t.write(file_name, format=\\\"fits\\\")\\n\\n # can add more file formats...\\n\\n else:\\n raise ValueError(\\\"Invalid file format\\\")\",\n \"def write(self, file, data):\\n if not exists(dirname(file)):\\n makedirs(dirname(file))\\n\\n with open(file + '.json', 'w') as file:\\n file.write(dumps(data, indent=2, separators=(',', ': '), sort_keys=True))\",\n \"def save_hdf_file(file_path, idata, key_path='entry', overwrite=True):\\r\\n if (\\\"\\\\\\\\\\\" in file_path):\\r\\n raise ValueError(\\r\\n \\\"Please use a file path following the Unix convention\\\")\\r\\n file_base, file_ext = os.path.splitext(file_path)\\r\\n if not ((file_ext == '.hdf') or (file_ext == '.h5')):\\r\\n file_ext = '.hdf'\\r\\n file_path = file_base + file_ext\\r\\n _create_folder(file_path)\\r\\n if not overwrite:\\r\\n file_path = _create_file_name(file_path)\\r\\n ofile = None\\r\\n try:\\r\\n ofile = h5py.File(file_path, 'w')\\r\\n except IOError:\\r\\n print((\\\"Couldn't write file: {}\\\").format(file_path))\\r\\n raise\\r\\n grp = ofile.create_group(key_path)\\r\\n grp.create_dataset(\\\"data\\\", data=idata)\\r\\n ofile.close()\\r\\n return file_path\",\n \"def to_file(self, filename=None):\\n name = None\\n if filename is not None:\\n name = filename\\n elif self.name:\\n name = self.name\\n\\n if name:\\n #f = open(self.name, 'w')\\n f = codecs.open(name, 'w', encoding='utf-8')\\n self.seek(0)\\n f.write(self.read())\\n f.close()\\n else:\\n print \\\"No log_name for this log\\\"\",\n \"def write_to_file(self,\\n ofile=\\\"output.txt\\\",\\n **kwargs):\\n with open(file=ofile, mode='a') as ofile:\\n for num_line, obj in self.items():\\n ofile.write(str(self._construct_output_string(num_line=num_line,\\n obj=obj,\\n **kwargs)))\",\n \"def write_data_2(fh, header, data):\\r\\n # fhw = open(filename, \\\"w\\\")\\r\\n if len(header) <= 0 or len(data) <= 0:\\r\\n return\\r\\n else:\\r\\n fh.write(str(header + \\\"\\\\n\\\"))\\r\\n fh.write(str(data) + \\\"\\\\n\\\")\\r\\n fh.write(\\\"\\\\n\\\")\",\n \"def write(self, filename, header=None):\\n\\n origfile = self._filename\\n\\n try:\\n with open(filename, 'w') as _file:\\n self.writestream(_file, header)\\n self._filename = filename\\n return True\\n\\n except IOError:\\n self._filename = origfile\\n return False\",\n \"def create_file(path: Path, content: str) -> None:\\n path.touch()\\n with path.open(\\\"w\\\") as f:\\n f.write(content)\"\n]"},"negative_scores":{"kind":"list like","value":["0.68592376","0.674406","0.674406","0.656854","0.6566108","0.6498972","0.6464658","0.6464213","0.6418377","0.6384356","0.63767195","0.637185","0.63714814","0.63141376","0.6300945","0.63001466","0.6275614","0.62744516","0.6243898","0.6229664","0.62277204","0.61617565","0.61581826","0.6146818","0.612254","0.61209","0.6118378","0.6106481","0.6097403","0.6095508","0.6090492","0.60687876","0.60589784","0.6056844","0.6056712","0.6047705","0.60362005","0.60181713","0.60127056","0.6005693","0.59956783","0.5989833","0.5989538","0.5980762","0.5980057","0.5971517","0.59677005","0.59620833","0.5962006","0.59559435","0.5948734","0.5946951","0.5932892","0.5929774","0.5925201","0.5919731","0.59096605","0.59046036","0.5897821","0.58893883","0.5888516","0.5886751","0.58815306","0.5871647","0.5866589","0.5849164","0.58453715","0.5843467","0.58412105","0.58407396","0.5833554","0.5833362","0.58316284","0.5830037","0.5827301","0.582587","0.582022","0.5812739","0.5801791","0.57992864","0.57826763","0.57733524","0.57729423","0.57721883","0.5769498","0.5767416","0.5761557","0.5760997","0.5757384","0.57490283","0.5741134","0.5739183","0.5733576","0.57297724","0.57280165","0.5727656","0.5726971","0.57125527","0.5712195","0.5710507"],"string":"[\n \"0.68592376\",\n \"0.674406\",\n \"0.674406\",\n \"0.656854\",\n \"0.6566108\",\n \"0.6498972\",\n \"0.6464658\",\n \"0.6464213\",\n \"0.6418377\",\n \"0.6384356\",\n \"0.63767195\",\n \"0.637185\",\n \"0.63714814\",\n \"0.63141376\",\n \"0.6300945\",\n \"0.63001466\",\n \"0.6275614\",\n \"0.62744516\",\n \"0.6243898\",\n \"0.6229664\",\n \"0.62277204\",\n \"0.61617565\",\n \"0.61581826\",\n \"0.6146818\",\n \"0.612254\",\n \"0.61209\",\n \"0.6118378\",\n \"0.6106481\",\n \"0.6097403\",\n \"0.6095508\",\n \"0.6090492\",\n \"0.60687876\",\n \"0.60589784\",\n \"0.6056844\",\n \"0.6056712\",\n \"0.6047705\",\n \"0.60362005\",\n \"0.60181713\",\n \"0.60127056\",\n \"0.6005693\",\n \"0.59956783\",\n \"0.5989833\",\n \"0.5989538\",\n \"0.5980762\",\n \"0.5980057\",\n \"0.5971517\",\n \"0.59677005\",\n \"0.59620833\",\n \"0.5962006\",\n \"0.59559435\",\n \"0.5948734\",\n \"0.5946951\",\n \"0.5932892\",\n \"0.5929774\",\n \"0.5925201\",\n \"0.5919731\",\n \"0.59096605\",\n \"0.59046036\",\n \"0.5897821\",\n \"0.58893883\",\n \"0.5888516\",\n \"0.5886751\",\n \"0.58815306\",\n \"0.5871647\",\n \"0.5866589\",\n \"0.5849164\",\n \"0.58453715\",\n \"0.5843467\",\n \"0.58412105\",\n \"0.58407396\",\n \"0.5833554\",\n \"0.5833362\",\n \"0.58316284\",\n \"0.5830037\",\n \"0.5827301\",\n \"0.582587\",\n \"0.582022\",\n \"0.5812739\",\n \"0.5801791\",\n \"0.57992864\",\n \"0.57826763\",\n \"0.57733524\",\n \"0.57729423\",\n \"0.57721883\",\n \"0.5769498\",\n \"0.5767416\",\n \"0.5761557\",\n \"0.5760997\",\n \"0.5757384\",\n \"0.57490283\",\n \"0.5741134\",\n \"0.5739183\",\n \"0.5733576\",\n \"0.57297724\",\n \"0.57280165\",\n \"0.5727656\",\n \"0.5726971\",\n \"0.57125527\",\n \"0.5712195\",\n \"0.5710507\"\n]"},"document_score":{"kind":"string","value":"0.5741435"},"document_rank":{"kind":"string","value":"90"}}},{"rowIdx":8553,"cells":{"query":{"kind":"string","value":"Loads the data set provided in this repository and returns a list of Decks or FuzzyDecks. The deck list is sorted by archetype so the distance matrix is easier to visualize."},"document":{"kind":"string","value":"def load_data_set(hero_class: str, fuzzy: bool, filename: str = \"data/Decks.json\", debug: bool = False) \\\n -> Union[List[Deck], List[FuzzyDeck]]:\n if debug:\n print(\"### loading dataset...\")\n with open(filename) as f:\n data = json.load(f)\n\n hero_classes = list(data[\"series\"][\"metadata\"].keys())\n if hero_class not in hero_classes and hero_class != \"ALL\":\n raise Exception(\"hero class <\" + hero_class + \"> not available. \"\n \"Consider using one class out of: \" + \", \".join(hero_classes))\n\n if debug:\n for cl in hero_classes:\n print(\"\" + str(len(data[\"series\"][\"data\"][cl])) + \" played decks for hero class \" + cl)\n\n played_decks = []\n if hero_class == \"ALL\":\n for hero_class in hero_classes:\n for i, deck_data in enumerate(data[\"series\"][\"data\"][hero_class]):\n\n if fuzzy:\n played_decks.append(FuzzyDeck(deck_data))\n else:\n played_decks.append(Deck(deck_data))\n else:\n for i, deck_data in enumerate(data[\"series\"][\"data\"][hero_class]):\n\n if fuzzy:\n played_decks.append(FuzzyDeck(deck_data))\n else:\n played_decks.append(Deck(deck_data))\n\n # sort by cluster label for easier visualization of distance matrix\n played_decks = sorted(played_decks, key=lambda x: x.archetype[0])\n return played_decks"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_decks(**options):\n graph = bonobo.Graph()\n\n csv_in = bonobo.noop\n\n graph.add_chain(csv_in, in_use_cards, _input=None)\n\n for deck in listdir('decks'):\n deck_path = join('decks', deck)\n if deck == '.gitignore':\n continue\n\n if isfile(deck_path):\n graph.add_chain(bonobo.CsvReader(deck_path), _output=csv_in)\n\n return graph","def get_decks(self, include_cards=True):\n deck_previews = self.data_source.get_decks(self.user_id,\n not include_cards)\n\n return deck_previews","def get_deck_list(deckid):\n # Need to know if we're looking at a deckid or deckid tuple\n # TODO: Clean this up a bit (shouldn't need to support deckids or deck)\n # tuples now that I'm using Deck objects.)\n if isinstance(deckid, tuple):\n # The deckid is in deck[0]\n # Format is (deckid, deck_class)\n deckid = deckid[0]\n # http://www.hearthpwn.com/decks/listing/ + /neutral or /class\n url = 'http://www.hearthpwn.com/decks/listing/'\n css = '#cards > tbody > tr > td.col-name'\n\n cards = []\n\n # Class Cards\n pagetree = get_pagetree(url + str(deckid) + '/class')\n elements = get_elements_from_page(pagetree, css)\n for element in elements:\n card = html.tostring(element, method='text', encoding='UTF-8')\n cards.append(card)\n\n # Neutral Cards\n pagetree = get_pagetree(url + str(deckid) + '/neutral')\n elements = get_elements_from_page(pagetree, css)\n for element in elements:\n card = html.tostring(element, method='text', encoding='UTF-8')\n cards.append(card)\n\n regex = re.compile(b'^\\r\\n(.+)\\r\\n\\r\\n\\xc3\\x97 (\\d+)')\n deck = []\n for card in cards:\n match = re.search(regex, card)\n if match:\n cardname = match.group(1).decode('UTF-8')\n amount = int(match.group(2))\n deck.append(Card(cardname, amount))\n\n return deck","def get_decks(filtering=None, sorting=None, count=None,\n patch=None, classid=None):\n decks_metainfo = get_deck_metainfo(filtering, sorting, count,\n patch, classid)\n decks = [Deck(deck[0], deck[1], get_deck_list(deck[0]))\n for deck in decks_metainfo]\n return decks","def populatePokerDeck():\r\n #At some point, I may want this function, or a function like it, to read from a txt/json or dat file, \r\n #but for now this suffices.\r\n aDeck =\t[\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Ace\",\r\n \"Type\": \"Face\",\r\n \"Value\": 1\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Two\",\r\n \"Type\": \"Number\",\r\n \"Value\": 2\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Three\",\r\n \"Type\": \"Number\",\r\n \"Value\": 3\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Four\",\r\n \"Type\": \"Number\",\r\n \"Value\": 4\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Five\",\r\n \"Type\": \"Number\",\r\n \"Value\": 5\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Six\",\r\n \"Type\": \"Number\",\r\n \"Value\": 6\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Seven\",\r\n \"Type\": \"Number\",\r\n \"Value\": 7\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Eight\",\r\n \"Type\": \"Number\",\r\n \"Value\": 8\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Nine\",\r\n \"Type\": \"Number\",\r\n \"Value\": 9\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Ten\",\r\n \"Type\": \"Number\",\r\n \"Value\": 10\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Jack\",\r\n \"Type\": \"Face\",\r\n \"Value\": 2\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"Queen\",\r\n \"Type\": \"Face\",\r\n \"Value\": 3\r\n },\r\n {\r\n \"Suite\": \"Hearts\",\r\n \"Name\": \"King\",\r\n \"Type\": \"Face\",\r\n \"Value\": 4\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Ace\",\r\n \"Type\": \"Face\",\r\n \"Value\": 1\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Two\",\r\n \"Type\": \"Number\",\r\n \"Value\": 2\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Three\",\r\n \"Type\": \"Number\",\r\n \"Value\": 3\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Four\",\r\n \"Type\": \"Number\",\r\n \"Value\": 4\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Five\",\r\n \"Type\": \"Number\",\r\n \"Value\": 5\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Six\",\r\n \"Type\": \"Number\",\r\n \"Value\": 6\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Seven\",\r\n \"Type\": \"Number\",\r\n \"Value\": 7\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Eight\",\r\n \"Type\": \"Number\",\r\n \"Value\": 8\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Nine\",\r\n \"Type\": \"Number\",\r\n \"Value\": 9\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Ten\",\r\n \"Type\": \"Number\",\r\n \"Value\": 10\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Jack\",\r\n \"Type\": \"Face\",\r\n \"Value\": 2\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"Queen\",\r\n \"Type\": \"Face\",\r\n \"Value\": 3\r\n },\r\n {\r\n \"Suite\": \"Clubs\",\r\n \"Name\": \"King\",\r\n \"Type\": \"Face\",\r\n \"Value\": 4\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Ace\",\r\n \"Type\": \"Face\",\r\n \"Value\": 1\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Two\",\r\n \"Type\": \"Number\",\r\n \"Value\": 2\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Three\",\r\n \"Type\": \"Number\",\r\n \"Value\": 3\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Four\",\r\n \"Type\": \"Number\",\r\n \"Value\": 4\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Five\",\r\n \"Type\": \"Number\",\r\n \"Value\": 5\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Six\",\r\n \"Type\": \"Number\",\r\n \"Value\": 6\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Seven\",\r\n \"Type\": \"Number\",\r\n \"Value\": 7\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Eight\",\r\n \"Type\": \"Number\",\r\n \"Value\": 8\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Nine\",\r\n \"Type\": \"Number\",\r\n \"Value\": 9\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Ten\",\r\n \"Type\": \"Number\",\r\n \"Value\": 10\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Jack\",\r\n \"Type\": \"Face\",\r\n \"Value\": 2\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"Queen\",\r\n \"Type\": \"Face\",\r\n \"Value\": 3\r\n },\r\n {\r\n \"Suite\": \"Diamonds\",\r\n \"Name\": \"King\",\r\n \"Type\": \"Face\",\r\n \"Value\": 4\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Ace\",\r\n \"Type\": \"Face\",\r\n \"Value\": 1\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Two\",\r\n \"Type\": \"Number\",\r\n \"Value\": 2\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Three\",\r\n \"Type\": \"Number\",\r\n \"Value\": 3\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Four\",\r\n \"Type\": \"Number\",\r\n \"Value\": 4\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Five\",\r\n \"Type\": \"Number\",\r\n \"Value\": 5\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Six\",\r\n \"Type\": \"Number\",\r\n \"Value\": 6\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Seven\",\r\n \"Type\": \"Number\",\r\n \"Value\": 7\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Eight\",\r\n \"Type\": \"Number\",\r\n \"Value\": 8\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Nine\",\r\n \"Type\": \"Number\",\r\n \"Value\": 9\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Ten\",\r\n \"Type\": \"Number\",\r\n \"Value\": 10\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Jack\",\r\n \"Type\": \"Face\",\r\n \"Value\": 2\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"Queen\",\r\n \"Type\": \"Face\",\r\n \"Value\": 3\r\n },\r\n {\r\n \"Suite\": \"Spades\",\r\n \"Name\": \"King\",\r\n \"Type\": \"Face\",\r\n \"Value\": 4\r\n },\r\n {\r\n \"Suite\": \"Red\",\r\n \"Name\": \"Joker\",\r\n \"Type\": \"Face\",\r\n \"Value\": None\r\n },\r\n {\r\n \"Suite\": \"Black\",\r\n \"Name\": \"Joker\",\r\n \"Type\": \"Face\",\r\n \"Value\": None\r\n }]\r\n \r\n return aDeck","def get_deck():\n deck = []\n for suit in Suit:\n for rank in Rank:\n deck.append(Card(suit, rank))\n return deck","def deck(self) -> Iterable[CardIdentifier]:\n # for some reason cards are treated quite different by NS api currently\n # so we cant simply make a shards call. for now we make a direct call\n # to the requester shards_xml method, since it does not insert the\n # `nation=name` parameter\n # this request returns a structure,\n # so we immedietly retrieve the DECK node (which contains multiple CARD nodes)\n # with [0]\n deck = as_xml(\n self.requester.shard_request(\n shards=[\"cards\", \"deck\"], nationname=self.nationname\n ).text\n )[0]\n return [CardIdentifier.from_xml(node) for node in deck]","def prepare_decklists(deck_files, data_path):\n \n deck = {'deckname':[], 'cardname':[], 'card_count':[], 'sideboard':[]}\n for file_name in deck_files:\n companion = 0\n file = open(data_path+file_name, 'r')\n sideboard = False\n for line in file:\n\n items = line.split(\" \")\n if (items[0][:4] == 'Deck'):\n pass\n elif (items[0][:9] == 'Companion'):\n companion = 1\n elif '\\n' in items or items[0][:9] == 'Sideboard':\n if companion == 1:\n companion -= 1\n else:\n sideboard = True\n else:\n try:\n deck['deckname'].append(file_name)\n deck['cardname'].append(\" \".join(items[1:]).replace('\\n',''))\n deck['card_count'].append(int(items[0]))\n deck['sideboard'].append(sideboard)\n except (Exception, ValueError) as error:\n print(f'Unable to process: {error} ; file {filename}')\n return deck","def generate_deck(self):\n\t\tsuits = [\"hearts\", \"spades\",\"diamonds\",\"clubs\"]\n\t\tcards = []\n\n\t\tfor suit in suits:\n\t\t\tif self.ace_as_eleven:\n\t\t\t\tace = Card(\"Ace\", 11, suit)\n\t\t\telse:\n\t\t\t\tace = Card(\"Ace\", 1, suit)\n\t\t\tcards.append(ace)\n\n\t\t\ttwo = Card(\"Two\", 2, suit)\n\t\t\tcards.append(two)\n\t\t\t\n\t\t\tthree = Card(\"Three\", 3, suit)\n\t\t\tcards.append(three)\n\n\t\t\tfour = Card(\"Four\", 4, suit)\n\t\t\tcards.append(four)\n\n\t\t\tfive = Card(\"Five\", 5, suit)\n\t\t\tcards.append(five)\n\n\t\t\tsix = Card(\"Six\", 6, suit)\n\t\t\tcards.append(six)\n\n\t\t\tseven = Card(\"Seven\", 7, suit)\n\t\t\tcards.append(seven)\n\n\t\t\teight = Card(\"Eight\", 8, suit)\n\t\t\tcards.append(eight)\n\n\t\t\tnine = Card(\"Nine\", 9, suit)\n\t\t\tcards.append(nine)\n\n\t\t\tten = Card(\"Ten\", 10, suit)\n\t\t\tcards.append(ten)\n\n\t\t\tjack = Card(\"Jack\", 10, suit)\n\t\t\tcards.append(jack)\n\n\t\t\tqueen = Card(\"Queen\", 10, suit)\n\t\t\tcards.append(queen)\n\n\t\t\tking = Card(\"King\", 10, suit)\n\t\t\tcards.append(king)\n\n\t\treturn cards","def __init__(self):\n \n self.deck = [Card(suit,rank) for suit in SUITS for rank in RANKS]","def loadCardDB():\n with open(CARDS_JSON, 'r') as infofile:\n cards = json.load(infofile)\n with open(PILOT_TEXT_JSON, 'r') as infofile:\n pilotTexts = json.load(infofile)\n with open(UPGRADE_TEXT_JSON, 'r') as infofile:\n upgradeTexts = json.load(infofile)\n with open(MODIFICATION_TEXT_JSON, 'r') as infofile:\n modificationTexts = json.load(infofile)\n with open(TITLE_TEXT_JSON, 'r') as infofile:\n titleTexts = json.load(infofile)\n return _createCardDB(cards, pilotTexts, upgradeTexts, modificationTexts, titleTexts)","def sort(self):\n self.deckcards.sort()","def get_cards(self):\n return [card.view_model() for card in self._deck.loc]","def load():\n\n # Path for the cache-file.\n cache_path = os.path.join(data_dir, \"collisions.pkl\")\n\n # If the DataSet-object already exists in a cache-file\n # then load it, otherwise create a new object and save\n # it to the cache-file so it can be loaded the next time.\n dataset = load_cached(cache_path=cache_path,\n in_dir=data_dir)\n\n return dataset","def shuffle(self):\n\n if self.deck:\n self.deck = deque()\n\n max_decks = self.deck_count + 1 # +1 for range function\n\n for deck in range(1, max_decks):\n for suit in self.suits:\n for num, name in enumerate(self.names, start=1):\n card = PlayingCard()\n card.set_attributes(name, suit, num)\n self.deck.append(card)\n\n for deck_shuffle in range(self.shuffle_count):\n random.shuffle(self.deck)","def test_list(self):\n\n decks = []\n try:\n decks.extend(scrape_decks())\n except Exception as e:\n self.logger.exception(\n 'Scraper for site TappedOut raised an exception'\n )\n\n print(\"Collected {} decks:\".format(len(decks)))\n for deck in decks:\n print(\"#\", deck.deckType)\n print(\" commander =\", deck.commander)\n print(\" image =\", deck.commander_img)\n print(\" video =\", deck.video)\n if deck.decklist is not None:\n print(\" decklist =\", deck.decklist)\n print()\n\n if os.environ.get(\"JUMBO_WRITE_TO_DB\") is not None:\n self.insert_decks(decks)","def populate_deck_db(decks, cursor):\n cursor.execute('DROP TABLE IF EXISTS decks')\n cursor.execute('DROP TABLE IF EXISTS deck_lists')\n cursor.execute('''CREATE TABLE IF NOT EXISTS decks\n (deckid integer primary key, class text)\n WITHOUT ROWID''')\n\n cursor.execute('''CREATE TABLE IF NOT EXISTS deck_lists\n (deckid integer, cardname text, amount integer,\n PRIMARY KEY (deckid, cardname))''')\n for deck in decks:\n cursor.execute('INSERT INTO decks VALUES (?, ?)',\n (deck.deckid, deck.playerclass))\n for card in deck.decklist:\n cursor.execute('INSERT INTO deck_lists VALUES (?, ?, ?)',\n (deck.deckid, card.cardname, card.amount))\n return","def loadData(catalog):\n loadArtworks(catalog)\n loadArtists(catalog)\n loadAdquires(catalog)\n loadNacionalities(catalog)\n load2DArtworks(catalog)\n loadArtistMediumsTags(catalog)\n loadDptments(catalog)\n catalog['artists'] = sortArtists(catalog, 3)\n fillArtistMediums(catalog)\n fillMostUsedMediums(catalog)\n catalog['artists_tags'] = sortArtistTags(catalog, 3)\n sort_dptments(catalog)","def create_deck(self):\n\n deck = []\n\n # Suits and face values\n suits = ['Clubs', 'Diamonds', 'Hearts', 'Spades']\n face_values = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'J', 'Q', 'K']\n\n # Creating deck\n for suit in suits:\n for value in face_values:\n deck.append(Card(suit[0], value))\n\n # Adding jokers\n if self.jokers:\n deck.append(Card('Jk', 0))\n deck.append(Card('Jk', 0))\n\n return deck","def refresh(self):\n self.deck = []\n\n for _suit in Suit:\n for _face in Face:\n self.insert(Card(_suit, _face, self))","def load(self):\n\t\t# Initialize empty list\n\t\tdata_files = []\n\n\t\t# Append the Drusen files to the list\n\t\tfor single_file in os.listdir(self.data_dir):\n\t\t\tdata_files.append(single_file)\n\t\treturn data_files","def get_card_sets(self, name: str) -> List:","def fetch_data():\n for category in CHEATSHEETS.items():\n subprocess.call(f'curl -o {PATH}{category[0] + \".csv\"} {category[1]}', shell=True)\n\n index = -1\n for filename in os.listdir(PATH):\n for idx, row in pd.read_csv(PATH + filename, on_bad_lines='skip').replace(np.nan, '').iterrows():\n name = row['Model']\n url = REDIRECT_URL + name.lower()\n category = filename.split('.')[0]\n featurizers = row['Acceptable Featurizers'].split(' ') if row['Acceptable Featurizers'] != '' else []\n backends = ['PyTorch' if item in {\"PTorch\", \"Torch\", \"PyTorch \"} else item for item in row['Backend'].split('/')]\n types = row['Type'] if filename != 'general.csv' else row['Classifier/Regressor']\n types = types.split('/') if filename == 'material.csv' else types.split('/ ')\n index += 1\n\n backend_list.append(backends)\n type_list.append(types)\n featurizer_list.append(featurizers)\n model_list.append(Model(name, url, category, featurizers, backends, types, index))","def shuffle_deck(self):\n deck = [i for i in range(0, 52)]\n shuffle(deck)\n self.deck = [cards[c*2:c*2+2] for c in deck]","def load(self, source):\n try:\n inputdata = self.__inputmanager.read(source)\n self.__suitables = self.__inputmanager.map(inputdata)\n self.__data = inputdata\n except ValueError as e:\n print (\"Failed to load the dataset: %s\" % e)\n raise\n\n self.__modules = self.import_suitable_visualizations(self.__suitables)\n self.__has_datefields = self.__inputmanager.has_date_points()\n # Converting the datakeys into strings.\n self.__datakeys = [str(i) for i in list(self.__data[0].keys())]\n return self.__suitables","def parse_decklist(archidekt_id: str) -> tuple[Decklist, bool, list]:\r\n decklist = Decklist()\r\n warnings = []\r\n ok = True\r\n\r\n r = requests.get(f\"https://archidekt.com/api/decks/{archidekt_id}/\")\r\n if r.status_code != 200:\r\n raise (ValueError(f\"Archidekt returned statuscode {r.status_code}\"))\r\n\r\n data = r.json()\r\n\r\n in_deck = {cat[\"name\"] for cat in data[\"categories\"] if cat[\"includedInDeck\"]}\r\n\r\n for item in data[\"cards\"]:\r\n # Extract relevant data\r\n count = item[\"quantity\"]\r\n card_name = item[\"card\"][\"oracleCard\"][\"name\"]\r\n set_id = item[\"card\"][\"edition\"][\"editioncode\"]\r\n collector_number = item[\"card\"][\"collectorNumber\"]\r\n if len(item[\"categories\"]) > 0 and item[\"categories\"][0] not in in_deck:\r\n continue\r\n\r\n # Validate card name\r\n card_name, warnings_name = validate_card_name(card_name)\r\n if card_name is None:\r\n decklist.append_comment(card_name)\r\n warnings.extend([(decklist.entries[-1], level, msg) for level, msg in warnings_name])\r\n ok = False\r\n continue\r\n\r\n # Validate card print\r\n card, warnings_print = validate_print(card_name, set_id, collector_number)\r\n\r\n decklist.append_card(count, card)\r\n warnings.extend([(decklist.entries[-1], level, msg) for level, msg in warnings_name + warnings_print])\r\n\r\n decklist.name = data[\"name\"]\r\n\r\n return decklist, ok, warnings","def populate(cards_info, sets_file=None, session=Session):\n\n s = session()\n\n with sets_file or codecs.open(DEFAULT_SETS_FILE, encoding=\"utf-8\") as file:\n reader = unicode_csv_reader(file, reader=csv.DictReader)\n sets = {}\n for row in reader:\n row[\"released\"] = datetime.datetime.strptime(\n row[\"released\"], u\"%Y/%m/%d\"\n )\n sets[row[\"code\"]] = m.Set(**row)\n\n sts = itertools.chain.from_iterable(types.subtypes.itervalues())\n\n types_ = {type : m.Type(name=type) for type in types.all}\n supertypes = {st : m.Supertype(name=st) for st in types.supertypes}\n subtypes = {st : m.Subtype(name=st) for st in sts}\n\n s.add_all(\n itertools.chain.from_iterable(\n i.itervalues() for i in (sets, types_, supertypes, subtypes)\n )\n )\n\n for card in cards_info:\n # XXX: Split cards / Stupid multiple ability\n if \" // \" in card[u\"name\"] or card[u\"name\"] == u\"Seeds of Strength\":\n continue\n\n t, u, v = (card.pop(k) for k in [u\"supertypes\", u\"types\", u\"subtypes\"])\n\n card[u\"ability_objects\"] = [\n s.query(m.Ability).filter_by(description=d).first() or\n m.Ability(description=d) for d in card.pop(u\"abilities\")\n ]\n\n card[u\"supertype_objects\"] = {supertypes[st] for st in t}\n card[u\"type_objects\"] = {types_[type] for type in u}\n card[u\"subtype_objects\"] = {subtypes[st] for st in v}\n\n appearances = {\n m.SetAppearance(set=sets[set], rarity=rarity)\n for set, rarity in card.pop(u\"appearances\")\n }\n\n card = m.Card(**card)\n card.set_appearances.update(appearances)\n\n s.add(card)\n\n s.commit()","def build_data_set(self):\n if not self.assert_data_correct():\n self.download_all_data()\n self.unpack_rename_data()\n self.split_data_characters()\n self.clean_data_fragments()\n self.create_font_data()\n if not self.assert_train_augmented():\n self.augment_train_data()\n if not self.assert_style_data_correct():\n self.download_style_data()\n self.unpack_rename_data()","def shuffle(self):\r\n random.shuffle(self.deck_of_cards)\r\n return self.deck_of_cards","def shuffle(self):\n random.shuffle(self.deckcards)","def buildDeck(self, resources):\n for key,value in resources.deckData.items():\n self.deck.append(resources.cards[value[self.playerClass]])\n random.shuffle(self.deck)\n self.HP = self.getHP() # Set HP","def test_deck_contains_all_cards(self):\n\n # I'm using collections.Counter so that the order is ignored (as in a\n # set) but that multiples are accounted for.\n expected = collections.Counter([\n ('r', 'i'), ('r', 'i'), ('r', 'i'),\n ('r', 2), ('r', 3), ('r', 4), ('r', 5), ('r', 6), \n ('r', 7), ('r', 8), ('r', 9), ('r', 10),\n\n ('g', 'i'), ('g', 'i'), ('g', 'i'),\n ('g', 2), ('g', 3), ('g', 4), ('g', 5), ('g', 6),\n ('g', 7), ('g', 8), ('g', 9), ('g', 10),\n\n ('b', 'i'), ('b', 'i'), ('b', 'i'),\n ('b', 2), ('b', 3), ('b', 4), ('b', 5), ('b', 6),\n ('b', 7), ('b', 8), ('b', 9), ('b', 10),\n\n ('y', 'i'), ('y', 'i'), ('y', 'i'),\n ('y', 2), ('y', 3), ('y', 4), ('y', 5), ('y', 6),\n ('y', 7), ('y', 8), ('y', 9), ('y', 10),\n\n ('w', 'i'), ('w', 'i'), ('w', 'i'),\n ('w', 2), ('w', 3), ('w', 4), ('w', 5), ('w', 6),\n ('w', 7), ('w', 8), ('w', 9), ('w', 10), ])\n\n self.assertEqual(expected, collections.Counter(deck.deck_gen()))","def __init__(self):\n self.deck = []\n\n for i in SUITS:\n for j in RANKS:\n self.deck.append(Card(i, j))","def load_data(self):\n with open('data/fordTrain.csv') as f:\n data = csv.reader(f, delimiter=',')\n train = [x for i, x in enumerate(data) if i > 0] \n # Extract features and target variable separately\n trainx = [x[3:] for x in train]\n trainy = [x[2] for x in train]\n\n with open('data/fordTest.csv') as f:\n data = csv.reader(f, delimiter=',')\n testx = [x[3:] for i, x in enumerate(data) if i > 0] \n\n with open('data/Solution.csv') as f:\n data = csv.reader(f, delimiter=',')\n testy = [x[2] for i, x in enumerate(data) if i > 0] \n\n # Extract features and target variable, convert to numpy array\n trainx = np.asarray(trainx, dtype=np.float32)\n trainy = np.asarray(trainy, dtype=np.int8)\n testx = np.asarray(testx, dtype=np.float32)\n testy = np.asarray(testy, dtype=np.int8)\n\n # Return training and test sets\n trainSet = Dataset(trainx, trainy)\n testSet = Dataset(testx, testy)\n return trainSet, testSet","def load_dataset(self):\n # Get all the files in the directory\n file_list = self.get_file_list()\n\n # Concatenate the data corresponding to a list of files\n data = self.concatenate_file_data(file_list)\n\n # Shuffle the data and create the training and the validation datasets\n data = self.shuffle_data_dictionary(data)\n self.training_dataset, self.validation_dataset = self.split_data_into_training_and_validation(data)","def play():\n decks = make_decks()\n\n deck_pulls = {deck: [] for deck in decks}\n for i in range(100):\n deck = random.choice(decks)\n deck_pulls[deck].append(deck.pull())\n\n return decks, deck_pulls","def get_datasets() -> List[Dataset]:\n\n amzn = Dataset(\n id='amzn', name='Amazon Reviews', language='en',\n description=\"This dataset consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.\")\n\n cnn = Dataset(\n id='cnn_dailymail', name='CNN/ DailyMail', language='en',\n description='The well-known CNN/ DailyMail data set for text summarization (version 3.0.0). The data has been fetched via HuggingFace Datasets')\n\n swisstext = Dataset(\n id='swisstext', name='SwissText 2019', language='de',\n description='The dataset was published for the SwissText conference 2019. ')\n\n return [amzn, cnn, swisstext]","def load_data(self):\n if not os.path.isfile(\"{}/OFF_data.json\".format(settings.DIR_PATH)):\n self.request_constructor(settings.R_COLLECTION['category'], 'NULL', 'tags')\n self.crawl_data('category')\n i = 0\n for item in self.categories:\n i += 1\n cat = item.get(\"name\")\n self.request_constructor(settings.R_COLLECTION['product'], cat, 'products')\n self.crawl_data('product')\n\n self.data = {\"categories\": self.categories, \"products\": self.products}\n self.save_data('OFF_data.json')\n else:\n with open(\"{}/OFF_data.json\".format(settings.DIR_PATH), 'r') as f:\n self.data = json.load(f)\n self.categories = self.data[\"categories\"]\n self.products = self.data[\"products\"]\n return self.categories, self.products","def get_all_desserts():\n return get_data_from_category_name(\"Desserts\")","def _generate_datasets(self):\n datasets = list()\n for fname in sorted(os.listdir(self.base_dir)):\n if not self._filename_re.match(fname):\n continue\n\n file_path = os.path.join(self.base_dir, fname)\n try:\n fh = self._open_hdf5(file_path)\n\n except (IOError, OSError) as e:\n warnings.warn('Cannot access {}; skipped'.format(file_path))\n print(e)\n continue\n\n for key in fh:\n if self._groupname_re.match(key.lstrip('/')):\n datasets.append(ObjectTableWrapper(fh, key, self._schema))\n continue\n\n warn_msg = 'incorrect group name \"{}\" in {}; skipped this group'\n warnings.warn(warn_msg.format(os.path.basename(file_path), key))\n\n return datasets","def load_data_from_files(self):\n # separated method to allow mock easier\n logger.info(\"Loading data...\")\n parent = Path(__file__).parent\n path = parent / \"resources\" / \"scores.txt\"\n self.scorer.load_from_file(path)\n path = parent / \"resources\" / \"american-english-large.txt\"\n self.trie.load_from_file(path)\n path = parent / \"resources\" / \"reels.txt\"\n self.reels = Reel.get_from_file(path)\n logger.info(\"Data loaded!\")","def deckCreated(self):\n deck = self.deckLoader.loadDeck()\n self.assertTrue(all([item in deck for item in self.items]), \"Each item in the deck initializer should be in the deck\")","def _read_dataset(self):\n import pandas as pd\n\n freesolv_path = get_data_file_path(FREESOLV_PATH)\n\n freesolv_db = pd.read_csv(freesolv_path, delimiter=';',\n skipinitialspace=True,\n skiprows=[0, 1, 2], header=0,\n names=['compound id', 'SMILES',\n 'iupac name',\n 'experimental value',\n 'experimental uncertainty',\n 'calculated value (GAFF)',\n 'calculated uncertainty',\n 'experimental reference',\n 'calculated reference',\n 'notes'])\n\n compound_ids = freesolv_db['compound id'].to_list()\n smiles_tags = freesolv_db['SMILES'].to_list()\n experimental_v = freesolv_db['experimental value'].to_list()\n return compound_ids, smiles_tags, experimental_v","def get_deck(self, deck_id, include_cards=True):\n deck = self.data_source.get_deck(deck_id, self.user_id, include_cards)\n\n return deck","async def get_deck_definition(\n self,\n *,\n short_fixed_trash: bool = False,\n ) -> DeckDefinitionV2:\n deck_load_name = SHORT_TRASH_DECK if short_fixed_trash else STANDARD_DECK\n return load_deck(deck_load_name, 2)","def load_recipes_from_test_set(cls, args):\n cls._recipes = Dataset().load_test(\n use_full_test_set=args.use_full_test_set,\n use_english=args.use_english,\n use_english_intelligible=args.use_english_intelligible,\n use_gold=args.use_gold)\n cls._add_indices_to_recipes()\n cls._initialize_recipes_status()\n logging.info(\"Recipes loaded.\")","def get_card_list(self):\n return self.cards","def load_dataset():\n\n\n train_dd_loader = DailyDialogLoader(PATH_TO_TRAIN_DATA, load=False)\n train_dataloader = DataLoader(train_dd_loader, batch_size=16, shuffle=True, num_workers=0,\n collate_fn=PadCollate())\n\n test_dd_loader = DailyDialogLoader(PATH_TO_TEST_DATA, load=True)\n test_dataloader = DataLoader(test_dd_loader, batch_size=1, shuffle=False, num_workers=0,\n collate_fn=PadCollate())\n\n assert train_dd_loader.vocabulary.n_words == test_dd_loader.vocabulary.n_words\n\n return train_dd_loader, train_dataloader, test_dataloader","def shuffle(self):\r\n random.shuffle(self.deck)","def createDeck():\n deck = []\n my_file = open(current_file)\n all_the_lines = my_file.readlines()\n deck = []\n for i in all_the_lines:\n deck.append(i.strip())\n my_file.close()\n random.shuffle(deck)\n return deck","def make_soldier_objects(data_dir: str) -> List[Soldier]:\n soldier_list = []\n \n with open(data_dir, newline='') as csvfile:\n reader = csv.reader(csvfile, delimiter=',', quotechar='|')\n print(reader.__next__()) # print header\n for row in reader:\n ################################# YOUR CODE HERE #################################\n typecode, wp, armor, vitality = row\n if typecode not in [\"INF\", \"ARC\", \"CVL\"]:\n continue\n wp, armor, vitality = float(wp), float(armor), float(vitality)\n soldier = Soldier(typecode, wp, armor, vitality)\n soldier_list.append(soldier)\n ##################################################################################\n return soldier_list","def fill_standard_deck(self):\n for name in [\"ace\", \"two\", \"three\", \"four\", \"five\", \"six\", \"seven\", \"eight\", \"nine\", \"ten\", \"jack\",\n \"queen\", \"king\"]:\n for suit in [\"hearts\", \"diamonds\", \"spades\", \"clubs\"]:\n self.cards.append(card.Card(name, suit, self.card_values[name]))","def shuffle():\n deck = []\n # By Baccarat rules, there are 4 aces worth 1 point, 16 face cards and tens\n # worth 0 point, and 32 other cards worth their numerical value.\n # 8 decks are suffled together to create a shoe.\n for n in range(8):\n for i in range (32):\n deck.append((i % 8) + 2)\n \n for i in range (16):\n deck.append(0)\n \n for i in range (4):\n deck.append(1)\n \n random.shuffle(deck)\n\n return deck","async def test_get_deck_definition(\n deck_type: DeckType,\n expected_definition: DeckDefinitionV3,\n mock_labware_data_provider: LabwareDataProvider,\n) -> None:\n subject = DeckDataProvider(\n deck_type=deck_type, labware_data=mock_labware_data_provider\n )\n result = await subject.get_deck_definition()\n assert result == expected_definition","def load_data(data_links_list=(\n 'https://raw.githubusercontent.com/JanetMatsen/bacteriopop/master'\n '/raw_data/raw_data.csv',\n 'https://raw.githubusercontent.com/JanetMatsen/bacteriopop/master'\n '/raw_data/sample_meta_info.tsv')):\n\n # Reading data sets from the links provided.\n df1 = pd.read_csv(data_links_list[0],\n error_bad_lines=False)\n df2 = pd.read_csv(data_links_list[1],\n sep='\\t')\n df2 = df2.set_index(df2['project'])\n # fill the Nas id df1 as \". Makes the groupbys behave better.\n df1.fillna('', inplace=True)\n # repleace 'genus' = 'other' with an empty string to be consistent.\n df1.replace(to_replace='other', value='', inplace=True)\n # Removing duplicate columns.\n del df2['project']\n del df2['ID']\n df1 = df1.set_index(df1['project'])\n # Removing duplicate column.\n del df1['project']\n # Joining the two datasets.\n df = df1.join(df2)\n # Uniformity in non-capitalization of column names.\n df.rename(columns={'Kingdom': 'kingdom', 'Phylum': 'phylum',\n 'Class': 'class', 'Order': 'order',\n 'Family': 'family', 'Genus': 'genus',\n 'Length': 'length'}, inplace=True)\n df.index.names = ['sampleID']\n # Rearranging columns so that abundance is the last column.\n df = df[['kingdom',\t'phylum', 'class', 'order',\n 'family', 'genus', 'length', 'oxygen',\n 'replicate', 'week', 'abundance']]\n assert isinstance(df, pd.DataFrame)\n return df","def scrape_decklist(deck_url):\r\n soup = hot_soup(deck_url)\r\n card_re = re.compile(r\"(\\d+)\\s(.+)\")\r\n deck_table = soup.find_all(class_='Stable')[1]\r\n deck_headers = deck_table.previous_sibling.previous_sibling.find_all('td')\r\n archtype = deck_headers[2].text.replace('decks', '')\r\n cardlist = deck_table.table.find_all('table')\r\n mainboard, sideboard = [], []\r\n for row in cardlist.pop().find_all('span'):\r\n count, card = card_re.search(row.parent.text).groups()\r\n sideboard.append((int(count), card.strip()))\r\n\r\n for col in cardlist:\r\n for row in col.find_all('span'):\r\n count, card = card_re.search(row.parent.text).groups()\r\n mainboard.append((int(count), card.strip()))\r\n\r\n return mainboard, sideboard, archtype","def load_data(self, data_set):\n print(\"Started Loading the Data\")\n tagged_tokens = data_set.tagged_words()\n tokens = untag(tagged_tokens)\n\n # Get the list of words that appear less than 5 times in Corpus\n print(\"Get LT5's\")\n tokens = [token.lower() for token in tokens] # Convert to lower case\n freq_dist = FreqDist(tokens) # Compute the freq dist\n tokens_lt_5 = [word for word, count in freq_dist.items() if count < 5]\n\n # Delete words less than 5 and make the corpus insensitive\n print(\"Making data case insensitive\")\n token_range = range(len(tagged_tokens))\n indexed_tokens = OrderedDict(zip(token_range,tagged_tokens))\n updated_tagged_tokens = OrderedDict()\n for tagged_token_id, tagged_token in indexed_tokens.items():\n if tagged_token[0].lower() in tokens_lt_5:\n del indexed_tokens[tagged_token_id]\n else:\n temp = list()\n temp.append(tagged_token[0].lower())\n temp.append(tagged_token[1])\n temp = tuple(temp)\n updated_tagged_tokens[tagged_token_id] = temp\n tagged_tokens = list(updated_tagged_tokens.values())\n\n # Pickle the data for future purpose\n print(\"Pickling the Updated Corpus\")\n if data_set == brown:\n file_name = \"q5_brown_updated.pkl\"\n else:\n file_name = \"q5_treebank_updated.pkl\"\n pkl.dump((tagged_tokens, tokens_lt_5), open(file_name,'wb'))\n\n return tagged_tokens, tokens_lt_5","def test_list_datasets(self, tmp_path):\n assert qml.data.list_datasets() == {\n \"qspin\": {\"Heisenberg\": {\"closed\": {\"chain\": [\"1x4\"]}}},\n \"qchem\": {\"H2\": {\"6-31G\": [\"0.46\", \"1.0\", \"1.16\"]}},\n }","def __init__(self):\n self.deck = init_deck()\n self.shuffle()","def load_dataset(args, corpus_type, shuffle):\n assert corpus_type in [\"train\", \"valid\", \"test\"]\n\n def _lazy_dataset_loader(pt_file, corpus_type):\n dataset = torch.load(pt_file)\n logger.info('Loading %s dataset from %s, number of examples: %d' %\n (corpus_type, pt_file, len(dataset)))\n return dataset\n\n # Sort the glob output by file name (by increasing indexes).\n pts = sorted(glob.glob(args.data_path + '.' + corpus_type + '.[0-9]*.pt'))\n if pts:\n if (shuffle):\n random.shuffle(pts)\n\n for pt in pts:\n yield _lazy_dataset_loader(pt, corpus_type)\n else:\n # Only one inputters.*Dataset, simple!\n pt = args.data_path + '.' + corpus_type + '.pt'\n yield _lazy_dataset_loader(pt, corpus_type)","def main():\n\t\n\tDeck = []\n\tfor suite in range(suites):\n for typecard in range(1, typecard+1):\n cards.append(typecard)","def mock_data_loader(csv_path):\n file_path = KINGDOM_CSV_PATH\n\n kingdomArr = []\n\n with open(file_path, newline=\"\") as csv_file:\n reader = csv.reader(csv_file, delimiter=\",\")\n for row in reader:\n kingdomArr.append(Kingdom(row[0], row[1]))\n\n return kingdomArr","def reshuffle(self):\n self.cards = []\n self.fill_standard_deck()\n self.shuffle()","def load():\n global WHITE_CARDS\n global BLACK_CARDS\n\n with open('./cards.csv', 'r') as f:\n reader = csv.reader(f)\n for r in reader:\n black = r[0]\n white = r[1]\n if white:\n WHITE_CARDS.append(white)\n if black:\n BLACK_CARDS.append(black)","def get_datasets(sim_args):\n if len(sim_args.data_folders) == 1 and sim_args.data_folders[0] == 'all':\n data_tags = [\n 'Webscope_C14_Set1',\n 'Webscope_C14_Set2',\n 'MSLR-WEB10k',\n 'NP2003',\n 'NP2004',\n 'HP2003',\n 'HP2004',\n 'TD2003',\n 'TD2004',\n 'MQ2007',\n 'MQ2008',\n 'OHSUMED',\n ]\n elif len(sim_args.data_folders) == 1 and sim_args.data_folders[0] == 'CIKM2017':\n data_tags = [\n 'MSLR-WEB10k',\n 'NP2003',\n 'NP2004',\n 'HP2003',\n 'HP2004',\n 'TD2003',\n 'TD2004',\n 'MQ2007',\n 'MQ2008',\n 'OHSUMED',\n ]\n elif len(sim_args.data_folders) == 1 and sim_args.data_folders[0] == 'letor64':\n data_tags = [\n 'NP2003',\n 'NP2004',\n 'HP2003',\n 'HP2004',\n 'TD2003',\n 'TD2004',\n ]\n # random.shuffle(data_tags)\n else:\n data_tags = sim_args.data_folders\n for data_tag in data_tags:\n assert data_tag in DATASET_COLLECTION, 'Command line input is currently not supported.'\n yield DATASET_COLLECTION[data_tag]","def __init__(self):\n self.deck = []\n for n in range(1, 14):\n card1 = Card(n, \"diamond\")\n self.deck.append(card1)\n\n for n in range(1, 14):\n card1 = Card(n, \"spade\")\n self.deck.append(card1)\n\n for n in range(1, 14):\n card1 = Card(n, \"heart\")\n self.deck.append(card1)\n\n for n in range(1, 14):\n card1 = Card(n, \"club\")\n self.deck.append(card1)","def get_cards(self):\n return [Flashcard.from_word(word) for word in self.get_words()]","def choose_deck():\n deck_prompt = \"What deck would you like to play?\"\n choice = utils.choose_list(utils.DECKLIST, deck_prompt)\n deck = dicts.ALL_DECKS[choice]\n os.system('clear')\n return deck","def test_loadData():\n \n sys = LVsystem.Ecosystem()\n \n sys.loadSetup('2Prey1Predator')\n \n \n data = sys.create_data()\n \n assert data[0] == 3\n assert data[1] == ['rabbit', 'hen', 'fox']\n assert data[2] == [30,10,20]\n assert data[3] == [0.09,0.07,-0.06] \n assert data[4] == [10000,10000,1]\n assert data[5] == [400,500,250]\n assert data[6][1][2] == -data[6][2][1]\n assert data[6][2][2] == 0\n\n sys.removeSpecies('rabbit')\n sys.removeSpecies('fox')\n sys.removeSpecies('hen')","def __init__(self, num_decks=1):\r\n\t\tself.reshuffle = False\r\n\t\tself.stack = []\r\n\t\tfor i in range(num_decks):\r\n\t\t\tdeck = Deck()\r\n\t\t\tfor card in deck.cards:\r\n\t\t\t\tself.stack.append(card)\r\n\t\trandom.shuffle(self.stack)\r\n\t\tself.runningcount = 0\r\n\t\tself.decksremaining = num_decks\r\n\t\tself.truecount = 0","def list(self):\n return 'Decks available: \\n{}'.format(\"\\n\".join([\n 'Deck {}: {} ({} cards)'.format(deck['id'], deck['title'], len(deck['cards']))\n for key, deck in self.decks.items()\n ]))","def load_ck_data(openface_dir, emotion_dir, feature_type='AUs'):\n features = load_OpenFace_features(openface_dir, features=feature_type)\n labels = load_CK_emotions(emotion_dir)\n\n return train_utils.dicts2lists(features, labels)","def loadData(dataPath):\n\n if not os.path.isdir(dataPath):\n api = KaggleApi()\n api.authenticate()\n api.dataset_download_files(\n dataset='sumanthvrao/daily-climate-time-series-data',\n path=dataPath,\n quiet=True,\n unzip=True\n )\n\n filepath1 = os.path.join(dataPath, 'DailyDelhiClimateTrain.csv')\n df1 = DatasetUtility.sortByDate(pd.read_csv(filepath1, header='infer'))\n\n filepath2 = os.path.join(dataPath, 'DailyDelhiClimateTest.csv')\n df2 = DatasetUtility.sortByDate(pd.read_csv(filepath2, header='infer'))\n\n return pd.concat([df1, df2], axis=0, ignore_index=True)","def test_get_cards_by_card_types(model: BDF) -> None:\n # setup to remove hackish cards\n card_types = list(model.card_count.keys())\n removed_cards = []\n for card_type in ['ENDDATA', 'INCLUDE', 'JUNK']:\n if card_type in model.card_count:\n removed_cards.append(card_type)\n for removed_card in removed_cards:\n card_types.remove(removed_card)\n\n removed_cards = []\n for card_type in card_types:\n if card_type not in model.cards_to_read:\n try:\n removed_cards.append(card_type)\n #print('removed %s' % card_type)\n except ValueError:\n msg = 'card_type=%s cant be removed' % card_type\n raise ValueError(msg)\n for removed_card in removed_cards:\n card_types.remove(removed_card)\n\n # we now have a list of card types we would like to extract\n # we'll get the associated cards\n card_dict = model.get_cards_by_card_types(card_types,\n reset_type_to_slot_map=False)\n for card_type, cards in card_dict.items():\n for card in cards:\n msg = 'this should never crash here...card_type=%s card.type=%s' % (\n card_type, card.type)\n if card_type != card.type and card_type + '1' != card.type:\n raise RuntimeError(msg)","def test_should_return_correct_data(self, mocked_get_data_loader):\n\n mocked_get_data_loader.return_value = mock_data_loader\n\n correct_kingdoms = {\n 'SPACE': Kingdom('SPACE', 'Gorilla'),\n 'LAND': Kingdom('LAND', 'Panda'),\n 'WATER': Kingdom('WATER', 'Octopus'),\n 'ICE': Kingdom('ICE', 'Mammoth'),\n 'AIR': Kingdom('AIR', 'Owl'),\n 'FIRE': Kingdom('FIRE', 'Dragon')\n }\n\n result_kingdoms = KingdomRepositoryServiceCsvImpl().get_all_kingdoms()\n\n for i in correct_kingdoms:\n\n self.assertEqual(correct_kingdoms[i], result_kingdoms[i])","def load_data():\n\n # Load data from categories\n comp = fetch_20newsgroups(subset='all', categories=['comp.graphics', 'comp.sys.mac.hardware', 'comp.windows.x'], \\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\n science = fetch_20newsgroups(subset='all', categories=['sci.crypt', 'sci.electronics', 'sci.space'], \\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\n politics = fetch_20newsgroups(subset='all', categories=['talk.politics.guns', 'talk.politics.mideast'], \\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\n religion = fetch_20newsgroups(subset='all', categories=['alt.atheism', 'soc.religion.christian'], \\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\n recreation = fetch_20newsgroups(subset='all', categories=['rec.autos', 'rec.sport.baseball', 'rec.sport.hockey'], \\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\n\n # Print total number of documents\n data_len = [len(comp.data), len(science.data), len(politics.data), len(recreation.data), len(religion.data)]\n\n # Subsample classes to create a balanced dataset\n sub_k = min(data_len)\n comp.data, comp.target = [list(t) for t in zip(*random.sample(list(zip(comp.data, comp.target)), sub_k))]\n science.data, science.target = [list(t) for t in zip(*random.sample(list(zip(science.data, science.target)), sub_k))]\n politics.data, politics.target = [list(t) for t in zip(*random.sample(list(zip(politics.data, politics.target)), sub_k))]\n religion.data, religion.target = [list(t) for t in zip(*random.sample(list(zip(religion.data, religion.target)), sub_k))]\n recreation.data, recreation.target = [list(t) for t in zip(*random.sample(list(zip(recreation.data, recreation.target)), sub_k))]\n\n # Subcategories labels\n subcat_comp = np.array(comp.target)\n subcat_scien = np.array(science.target) + len(comp.target_names)\n subcat_polit = np.array(politics.target) + len(comp.target_names) + len(science.target_names)\n subcat_rel = np.array(religion.target) + len(comp.target_names) + len(science.target_names) + len(politics.target_names)\n subcat_rec = np.array(recreation.target) + len(comp.target_names) + len(science.target_names) + len(politics.target_names) + len(religion.target_names)\n\n # Assign labels to train data based on categories\n y_comp = np.ones(len(comp.data))\n y_scien = 2*np.ones(len(science.data))\n y_polit = 3*np.ones(len(politics.data))\n y_rel = 4*np.ones(len(religion.data))\n y_rec = 5*np.ones(len(recreation.data))\n labels = np.concatenate((y_comp,y_scien,y_polit,y_rel,y_rec), axis=None)\n\n # Computers\n train_comp, test_comp, y_train_comp, y_test_comp, subcat_comp_train, subcat_comp_test = train_test_split(comp.data, y_comp, subcat_comp, test_size=0.2, random_state=42)\n train_comp, val_comp, y_train_comp, y_val_comp, subcat_comp_train, subcat_comp_val = train_test_split(train_comp, y_train_comp, subcat_comp_train, test_size=0.25, random_state=42)\n\n # Sciences\n train_scien, test_scien, y_train_scien, y_test_scien, subcat_scien_train, subcat_scien_test = train_test_split(science.data, y_scien, subcat_scien, test_size=0.2, random_state=42)\n train_scien, val_scien, y_train_scien, y_val_scien, subcat_scien_train, subcat_scien_val = train_test_split(train_scien, y_train_scien, subcat_scien_train, test_size=0.25, random_state=42)\n\n # Politics\n train_polit, test_polit, y_train_polit, y_test_polit, subcat_polit_train, subcat_polit_test = train_test_split(politics.data, y_polit, subcat_polit, test_size=0.2, random_state=42)\n train_polit, val_polit, y_train_polit, y_val_polit, subcat_polit_train, subcat_polit_val = train_test_split(train_polit, y_train_polit, subcat_polit_train, test_size=0.25, random_state=42)\n\n # Religion\n train_rel, test_rel, y_train_rel, y_test_rel, subcat_rel_train, subcat_rel_test = train_test_split(religion.data, y_rel, subcat_rel, test_size=0.2, random_state=42)\n train_rel, val_rel, y_train_rel, y_val_rel, subcat_rel_train, subcat_rel_val = train_test_split(train_rel, y_train_rel, subcat_rel_train, test_size=0.25, random_state=42)\n\n # Recreation\n train_rec, test_rec, y_train_rec, y_test_rec, subcat_rec_train, subcat_rec_test = train_test_split(recreation.data, y_rec, subcat_rec, test_size=0.2, random_state=42)\n train_rec, val_rec, y_train_rec, y_val_rec, subcat_rec_train, subcat_rec_val = train_test_split(train_rec, y_train_rec, subcat_rec_train, test_size=0.25, random_state=42)\n\n # Corpus from all categories in train set\n newsgroups_train = train_comp + train_scien + train_polit + train_rel + train_rec\n #print(f\"Total number of documents in all categories in the train set is {len(newsgroups_train)}.\")\n train_labels = np.concatenate((y_train_comp,y_train_scien,y_train_polit,y_train_rel,y_train_rec), axis=None)\n #print(train_labels.shape)\n train_subcat = np.concatenate((subcat_comp_train,subcat_scien_train,subcat_polit_train,subcat_rel_train,subcat_rec_train), axis=None)\n #print(train_subcat.shape)\n\n # Corpus from all categories in test set\n newsgroups_test = test_comp + test_scien + test_polit + test_rel + test_rec\n test_labels = np.concatenate((y_test_comp,y_test_scien,y_test_polit,y_test_rel,y_test_rec), axis=None)\n test_subcat = np.concatenate((subcat_comp_test,subcat_scien_test,subcat_polit_test,subcat_rel_test,subcat_rec_test), axis=None)\n\n # Corpus from all categories in validation set\n newsgroups_val = val_comp + val_scien + val_polit + val_rel + val_rec\n val_labels = np.concatenate((y_val_comp,y_val_scien,y_val_polit,y_val_rel,y_val_rec), axis=None)\n val_subcat = np.concatenate((subcat_comp_val,subcat_scien_val,subcat_polit_val,subcat_rel_val,subcat_rec_val), axis=None)\n\n # Data Split\n total = len(test_labels) + len(val_labels) + len(train_labels)\n\n return newsgroups_train, train_labels, newsgroups_test, test_labels, newsgroups_val, val_labels, train_subcat, test_subcat, val_subcat","def _collect_quizzes():\n data_path = join(dirname(abspath(__file__)), 'data')\n for _, _, filenames in os.walk(data_path):\n for filename in filenames:\n if filename.endswith('.yml'):\n quiz_type = filename.replace('.yml', '').capitalize()\n QUIZ_DICT[quiz_type] = []\n with open(join(data_path, filename), encoding='utf-8') as f:\n data = yaml.load(f)\n for class_name, settings in data.items():\n Q = type(class_name, (Quiz, ), settings)\n QUIZ_DICT[quiz_type].append(Q)\n QUIZ_DICT_FLAT[class_name] = Q","def evalcards(cardA, cardB, cardC, cardD):\n array = []\n ranks = []\n spadessort = []\n cardsinsuit = 1\n # BASESUIT definitions\n if cardA[-3:] == \"SPA\":\n basesuit = suitspades\n if cardA[-3:] == \"HEA\":\n basesuit = suithearts\n if cardA[-3:] == \"DIA\":\n basesuit = suitdiamonds\n if cardA[-3:] == \"CLB\":\n basesuit = suitclubs\n if cardB in basesuit:\n cardsinsuit += 1\n if cardC in basesuit:\n cardsinsuit += 1\n if cardD in basesuit:\n cardsinsuit += 1\n #BEGIN SORTING CARDS\n cardBBB = cardB\n cardCCC = cardC\n cardDDD = cardD\n if cardB not in basesuit:\n cardBBB = basesuit[12]\n if cardC not in basesuit:\n cardCCC = basesuit[12]\n if cardD not in basesuit:\n cardDDD = basesuit[12]\n array += [str(basesuit.index(cardA))]\n if len(str(basesuit.index(cardA))) == 1:\n del array[0]\n array += [\"0\"+str(basesuit.index(cardA))]\n array += [str(basesuit.index(cardBBB))]\n if len(str(basesuit.index(cardBBB))) == 1:\n del array[1]\n array += [\"0\"+str(basesuit.index(cardBBB))]\n array += [str(basesuit.index(cardCCC))]\n if len(str(basesuit.index(cardCCC))) == 1:\n del array[2]\n array += [\"0\"+str(basesuit.index(cardCCC))]\n array += [str(basesuit.index(cardDDD))]\n if len(str(basesuit.index(cardDDD))) == 1:\n del array[3]\n array += [\"0\"+str(basesuit.index(cardDDD))]\n array.sort()\n for x in range(0,cardsinsuit):\n ranks += [basesuit[int(array[x])]]\n #CHECKING FOR NOT IN SUIT AND FOR SPADES\n if cardB not in basesuit:\n if cardB in spades:\n spadessort += [cardB]\n else:\n ranks += [cardB]\n if cardC not in basesuit:\n if cardC in spades:\n if (cardB in spades) and (spades.index(cardC) < spades.index(cardB)):\n spadessort = listinsert(spadessort, 0, cardC)\n elif (cardB in spades) and (spades.index(cardC) > spades.index(cardB)):\n spadessort += [cardC]\n else:\n spadessort += [cardC]\n else:\n ranks += [cardC]\n if cardD not in basesuit:\n if cardD in spades:\n if (cardB in spades) and (cardC in spades):\n if (spades.index(cardD) < spades.index(cardC)) and (spades.index(cardD) < spades.index(cardB)):\n spadessort = listinsert(spadessort, 0, cardD)\n elif ((spades.index(cardD) < spades.index(cardC)) and (spades.index(cardD) > spades.index(cardB))) or ((spades.index(cardD) > spades.index(cardC)) and (spades.index(cardD) < spades.index(cardB))):\n spadessort = listinsert(spadessort, 1, cardD)\n elif (spades.index(cardD) > spades.index(cardC)) and (spades.index(cardD) > spades.index(cardB)):\n spadessort += [cardD]\n elif (cardB in spades) and (cardC not in spades):\n if spades.index(cardD) < spades.index(cardB):\n spadessort = listinsert(spadessort, 0, cardD)\n if spades.index(cardD) > spades.index(cardB):\n spadessort += [cardD]\n elif (cardB not in spades) and (cardC in spades):\n if spades.index(cardD) < spades.index(cardC):\n spadessort = listinsert(spadessort, 0, cardD)\n if spades.index(cardD) > spades.index(cardC):\n spadessort += [cardD]\n else:\n spadessort += [cardD]\n else:\n ranks += [cardD]\n ranks = spadessort + ranks\n return(ranks)","def parse_decklist(manastack_id: str, zones: list[str] = [\"commander\", \"mainboard\"]):\r\n decklist = Decklist()\r\n warnings = []\r\n ok = True\r\n\r\n r = requests.get(f\"https://manastack.com/api/decklist?format=json&id={manastack_id}\")\r\n if r.status_code != 200:\r\n raise (ValueError(f\"Manastack returned statuscode {r.status_code}\"))\r\n\r\n data = r.json()\r\n for zone in zones:\r\n if len(data[\"list\"][zone]) > 0:\r\n decklist.append_comment(zone.capitalize())\r\n for item in data[\"list\"][zone]:\r\n # Extract relevant data\r\n count = item[\"count\"]\r\n card_name = item[\"card\"][\"name\"]\r\n set_id = item[\"card\"][\"set\"][\"slug\"]\r\n collector_number = item[\"card\"][\"num\"]\r\n\r\n # Validate card name\r\n card_name, warnings_name = validate_card_name(card_name)\r\n if card_name is None:\r\n decklist.append_comment(card_name)\r\n warnings.extend([(decklist.entries[-1], level, msg) for level, msg in warnings_name])\r\n ok = False\r\n continue\r\n\r\n # Validate card print\r\n card, warnings_print = validate_print(card_name, set_id, collector_number)\r\n\r\n decklist.append_card(count, card)\r\n warnings.extend([(decklist.entries[-1], level, msg) for level, msg in warnings_name + warnings_print])\r\n\r\n if zone != zones[-1]:\r\n decklist.append_comment(\"\")\r\n\r\n decklist.name = data[\"info\"][\"name\"]\r\n\r\n return decklist, ok, warnings","def get_data_loaders(opt):\n return find_dataloader_using_name(opt.dataloader)(opt).load_data()","def load_data(args, sample_idx):\n # The preference scores are not used for the MetFrag comparison (MetFrag uses LogP values as preference scores\n # and calculates those internally. However, due to the implementation of 'load_dataset_EA' we need to specify some\n # preference model.\n pref_model = {\"training_dataset\": \"MEOH_AND_CASMI_JOINT\", \"keep_test_molecules\": False,\n \"estimator\": \"ranksvm\", \"molecule_representation\": \"substructure_count\"}\n\n with sqlite3.connect(\"file:\" + args.database_fn + \"?mode=ro\", uri=True) as db:\n challenges, candidates = load_dataset_EA(\n db, participant=args.participant, prefmodel=pref_model, ion_mode=args.ion_mode,\n max_n_cand=args.max_n_cand, sort_candidates_by_ms2_score=args.sort_candidates_by_ms2_score,\n sample_idx=sample_idx)\n\n return challenges, candidates","def shuffled_deck(deck):\n random.shuffle(deck)\n return deck","def get_all_cards(self, filter='open'):\n print('Searching Trello cards..\\n')\n done_sources = []\n for list in self.my_lists:\n for card in list.list_cards(card_filter=filter):\n name = card.name.split()[0]\n done_sources.append(card)\n return done_sources","async def get_deck_fixed_labware(\n self,\n deck_definition: DeckDefinitionV2\n ) -> List[DeckFixedLabware]:\n labware = []\n\n for fixture in deck_definition[\"locations\"][\"fixtures\"]:\n labware_id = fixture[\"id\"]\n load_name = fixture.get(\"labware\") # type: ignore[misc]\n slot = fixture.get(\"slot\") # type: ignore[misc]\n\n if load_name is not None and slot is not None:\n location = DeckSlotLocation(slot=DeckSlotName.from_primitive(slot))\n definition = await self._labware_data.get_labware_definition(\n load_name=load_name,\n namespace=\"opentrons\",\n version=1,\n )\n\n labware.append(\n DeckFixedLabware(\n labware_id=labware_id,\n definition=definition,\n location=location,\n )\n )\n\n return labware","def deck_get_decks():\n log_request(request)\n\n data = request.json\n \n if not valid_params(['username', 'session_id'], data):\n logging.debug(\"Missing parameters\")\n return jsonify({'error' : 500})\n \n username = request.json['username']\n session_id = request.json['session_id']\n \n # verify session\n if not user.verify(username, session_id):\n logging.debug(\"Invalid username or session\")\n return jsonify({'error' : 101})\n \n uId = user.id_name(username)\n\n decks = deck.get_decks_by_uId(uId)\n ret = {'decks' : []}\n for d in decks:\n ret['decks'].append({'name' : d[0],\n 'deck_id' : d[1],\n 'description' : d[2]})\n\n ret['error'] = 0\n return jsonify(ret)","def getAllCards(self):\n return self._cards","def create_deck(self):\n\n id_already_use, deck, hand = [], [], []\n\n for _ in range(self.number_domino - self.hand_size):\n\n # We generate a domino and keep its id in id_alread_use\n # then we make sure to ony keep new id\n\n id = (randint(0, 6), randint(0, 6))\n while id in id_already_use:\n id = (randint(0, 6), randint(0, 6))\n deck.append(Domino(id[0], id[1]))\n id_already_use.append(id)\n\n for _ in range(self.hand_size):\n id = (randint(0, 6), randint(0, 6))\n while id in id_already_use:\n id = (randint(0, 6), randint(0, 6))\n hand.append(Domino(id[0], id[1]))\n id_already_use.append(id)\n\n return deck, hand","def load_deck_obj(deckFile, deckObj):\n\n deckObj = []\n\n # open up the deck file, and start adding lines to the deckObj\n with open(deckFile, 'r') as deckItem:\n for deckLine in deckItem:\n # print([deckLine])\n deckObj += [deckLine]\n\n # print the first 4 card names in the deck.\n # for card in deckObj[:4]:\n # print(card)\n\n # print the length of the json cards, and the deck's lines\n # print('deck item lines: {}'.format(len(deckObj)))\n \n return","def load_data():\n if _LOCATIONS_BY_ID:\n return _LOCATIONS_BY_NAME, _LOCATIONS_BY_ID\n\n # We need to read the locations in order of country -> admin level 1 -> admin level 2 -> city.\n # This is so that the higher resolution locations can look up the lower resolution locations\n # that they belong to, and compute the necessary fields.\n countries_by_code = _load_country_data(_DATA_FILES['country'])\n admin1_by_code = _load_admin1_data(_DATA_FILES['admin_1'], countries_by_code)\n admin2_by_code = _load_admin2_data(_DATA_FILES['admin_2'], countries_by_code, admin1_by_code)\n _load_city_data(_DATA_FILES['city'], countries_by_code, admin1_by_code, admin2_by_code)\n _add_alternate_names(_DATA_FILES['alt_wiki_names'])\n _add_estimated_importances(_DATA_FILES['estimated_importance'])\n\n return _LOCATIONS_BY_NAME, _LOCATIONS_BY_ID","def available_datasets(self) -> List[str]:\n return sorted(self.__by_name.keys())","def create_deck():\r\n deck = []\r\n faces = [2,3,4,5,6,7,8,9,10,\r\n 'Jack','Queen','King','Ace']\r\n suits = ['Spades', 'Diamonds', 'Clubs', 'Hearts']\r\n for face in faces:\r\n for suit in suits:\r\n # Creates a card-tuple and adds it to the deck.\r\n deck.append((face, suit))\r\n \r\n return deck","def generate_card_deck() -> [Card]:\n\n card_deck = []\n\n for card_color in CardColor:\n for card_value in CardValue:\n card_deck.append(Card(card_color, card_value))\n\n return Shuffle.__shuffle_card_deck(card_deck * Shuffle._CARD_DECK_MULTIPLIER)","def _load_raw_datashards(shard_num, nb_collaborators): \n train_obj = torchvision.datasets.CIFAR10('~/.CIFAR10', train=True, download=True) \n test_obj = torchvision.datasets.CIFAR10('~/.CIFAR10', train=False, download=True) \n x_train = train_obj.data\n y_train = np.asarray(train_obj.targets)\n x_test = test_obj.data\n y_test = np.asarray(test_obj.targets)\n # fix the label dimension to be (N,)\n y_train = y_train.reshape(-1)\n y_test = y_test.reshape(-1) \n \n # create the shards\n X_train_shards = x_train[shard_num::nb_collaborators]\n y_train_shards = y_train[shard_num::nb_collaborators]\n \n X_test_shards = x_test[shard_num::nb_collaborators]\n y_test_shards = y_test[shard_num::nb_collaborators]\n return (X_train_shards, y_train_shards), (X_test_shards, y_test_shards)","def fetch_cifar100_efficient_kd_dataloaders(args):\n\n loaders = {}\n for mode in [\"train\", \"test\"]:\n dataset = CachedKDDataset(mode=mode)\n loaders[mode] = \\\n torch.utils.data.DataLoader(\n dataset,\n batch_size=args.batch_size,\n shuffle=(mode == \"train\"),\n num_workers=4,\n collate_fn=dict_collate\n )\n\n return loaders[\"train\"], loaders[\"test\"]","def get_deck_as_str_list(self):\n\n ls = []\n for card in self.deck:\n ls.append(card.get_card())\n return ls","def get_faces_loaders(batch_size=128, test=True, data_path=\"./data/\"):\n\n dat = np.load(data_path + \"rotated_faces_data.npz\")\n train_images = torch.FloatTensor(dat['train_images'])\n train_targets = torch.FloatTensor(dat['train_angles'])\n\n traindata = torch.utils.data.TensorDataset(train_images, train_targets)\n trainloader = torch.utils.data.DataLoader(traindata, batch_size=batch_size,\n shuffle=True)\n\n if test:\n test_images = torch.FloatTensor(dat['test_images'])\n test_targets = torch.FloatTensor(dat['test_angles'])\n\n testdata = torch.utils.data.TensorDataset(test_images, test_targets)\n testloader = torch.utils.data.DataLoader(testdata, batch_size=batch_size)\n\n return trainloader, testloader\n\n return trainloader","def get_available_datasets():\n files = [file for file in glob.glob(os.path.join(MODULE_ROOT, \"datasets/*.json\"))]\n datasets = []\n for file in files:\n with open(file, \"r\") as f:\n dataset_info = json.load(f)\n datasets.append(dataset_info)\n return datasets","def get_datasets(FIELDS='all'):\n dsinfostr = fork_and_get_output(\"zfs list -H -o {0}\".format(FIELDS).split())\n header = get_zfs_ds_header()\n dsinfo = dsinfostr.splitlines()\n dsobjs = []\n for dsstr in dsinfo:\n dsobjs.append(DataZFS(dsstr, header, 'dataset'))\n return dsobjs","def fetch_review(self):\n c = self.db.cursor()\n c.execute(\"\"\"SELECT * FROM cards\n WHERE date_last_reviewed < (DATETIME('now', 'localtime', '-8 hours'))\n OR correct = 0\"\"\")\n rows = c.fetchall()\n cards = [\n Card(\n id=id,\n card_type=card_type,\n text=text,\n created=created,\n uri=uri,\n updated=updated,\n difficulty=difficulty,\n days_between=days_between,\n date_last_reviewed=date_last_reviewed,\n correct=correct,\n )\n for id, card_type, text, uri, created, updated, difficulty, days_between, date_last_reviewed, correct in rows\n ]\n cards = filter(lambda card: card.percent_overdue >= 1, cards)\n cards = sorted(cards, key=lambda card: card.percent_overdue)\n\n return cards[:20]","def get_results(path: str, threshold1: float, threshold2: float, quantiles: int, clear_cache: bool = True):\n create_cache_dirs()\n\n correlation_clustering = load_dataset(path, threshold1, threshold2, quantiles, clear_cache=clear_cache)\n print(\"DATA LOADED\")\n\n correlation_clustering.find_matches()"],"string":"[\n \"def get_decks(**options):\\n graph = bonobo.Graph()\\n\\n csv_in = bonobo.noop\\n\\n graph.add_chain(csv_in, in_use_cards, _input=None)\\n\\n for deck in listdir('decks'):\\n deck_path = join('decks', deck)\\n if deck == '.gitignore':\\n continue\\n\\n if isfile(deck_path):\\n graph.add_chain(bonobo.CsvReader(deck_path), _output=csv_in)\\n\\n return graph\",\n \"def get_decks(self, include_cards=True):\\n deck_previews = self.data_source.get_decks(self.user_id,\\n not include_cards)\\n\\n return deck_previews\",\n \"def get_deck_list(deckid):\\n # Need to know if we're looking at a deckid or deckid tuple\\n # TODO: Clean this up a bit (shouldn't need to support deckids or deck)\\n # tuples now that I'm using Deck objects.)\\n if isinstance(deckid, tuple):\\n # The deckid is in deck[0]\\n # Format is (deckid, deck_class)\\n deckid = deckid[0]\\n # http://www.hearthpwn.com/decks/listing/ + /neutral or /class\\n url = 'http://www.hearthpwn.com/decks/listing/'\\n css = '#cards > tbody > tr > td.col-name'\\n\\n cards = []\\n\\n # Class Cards\\n pagetree = get_pagetree(url + str(deckid) + '/class')\\n elements = get_elements_from_page(pagetree, css)\\n for element in elements:\\n card = html.tostring(element, method='text', encoding='UTF-8')\\n cards.append(card)\\n\\n # Neutral Cards\\n pagetree = get_pagetree(url + str(deckid) + '/neutral')\\n elements = get_elements_from_page(pagetree, css)\\n for element in elements:\\n card = html.tostring(element, method='text', encoding='UTF-8')\\n cards.append(card)\\n\\n regex = re.compile(b'^\\\\r\\\\n(.+)\\\\r\\\\n\\\\r\\\\n\\\\xc3\\\\x97 (\\\\d+)')\\n deck = []\\n for card in cards:\\n match = re.search(regex, card)\\n if match:\\n cardname = match.group(1).decode('UTF-8')\\n amount = int(match.group(2))\\n deck.append(Card(cardname, amount))\\n\\n return deck\",\n \"def get_decks(filtering=None, sorting=None, count=None,\\n patch=None, classid=None):\\n decks_metainfo = get_deck_metainfo(filtering, sorting, count,\\n patch, classid)\\n decks = [Deck(deck[0], deck[1], get_deck_list(deck[0]))\\n for deck in decks_metainfo]\\n return decks\",\n \"def populatePokerDeck():\\r\\n #At some point, I may want this function, or a function like it, to read from a txt/json or dat file, \\r\\n #but for now this suffices.\\r\\n aDeck =\\t[\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Ace\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 1\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Two\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 2\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Three\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 3\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Four\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 4\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Five\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 5\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Six\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 6\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Seven\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 7\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Eight\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 8\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Nine\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 9\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Ten\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 10\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Jack\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 2\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"Queen\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 3\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Hearts\\\",\\r\\n \\\"Name\\\": \\\"King\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 4\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Ace\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 1\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Two\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 2\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Three\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 3\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Four\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 4\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Five\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 5\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Six\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 6\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Seven\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 7\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Eight\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 8\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Nine\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 9\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Ten\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 10\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Jack\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 2\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"Queen\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 3\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Clubs\\\",\\r\\n \\\"Name\\\": \\\"King\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 4\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Ace\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 1\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Two\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 2\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Three\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 3\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Four\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 4\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Five\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 5\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Six\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 6\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Seven\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 7\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Eight\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 8\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Nine\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 9\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Ten\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 10\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Jack\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 2\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"Queen\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 3\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Diamonds\\\",\\r\\n \\\"Name\\\": \\\"King\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 4\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Ace\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 1\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Two\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 2\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Three\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 3\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Four\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 4\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Five\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 5\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Six\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 6\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Seven\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 7\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Eight\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 8\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Nine\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 9\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Ten\\\",\\r\\n \\\"Type\\\": \\\"Number\\\",\\r\\n \\\"Value\\\": 10\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Jack\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 2\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"Queen\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 3\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Spades\\\",\\r\\n \\\"Name\\\": \\\"King\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": 4\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Red\\\",\\r\\n \\\"Name\\\": \\\"Joker\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": None\\r\\n },\\r\\n {\\r\\n \\\"Suite\\\": \\\"Black\\\",\\r\\n \\\"Name\\\": \\\"Joker\\\",\\r\\n \\\"Type\\\": \\\"Face\\\",\\r\\n \\\"Value\\\": None\\r\\n }]\\r\\n \\r\\n return aDeck\",\n \"def get_deck():\\n deck = []\\n for suit in Suit:\\n for rank in Rank:\\n deck.append(Card(suit, rank))\\n return deck\",\n \"def deck(self) -> Iterable[CardIdentifier]:\\n # for some reason cards are treated quite different by NS api currently\\n # so we cant simply make a shards call. for now we make a direct call\\n # to the requester shards_xml method, since it does not insert the\\n # `nation=name` parameter\\n # this request returns a structure,\\n # so we immedietly retrieve the DECK node (which contains multiple CARD nodes)\\n # with [0]\\n deck = as_xml(\\n self.requester.shard_request(\\n shards=[\\\"cards\\\", \\\"deck\\\"], nationname=self.nationname\\n ).text\\n )[0]\\n return [CardIdentifier.from_xml(node) for node in deck]\",\n \"def prepare_decklists(deck_files, data_path):\\n \\n deck = {'deckname':[], 'cardname':[], 'card_count':[], 'sideboard':[]}\\n for file_name in deck_files:\\n companion = 0\\n file = open(data_path+file_name, 'r')\\n sideboard = False\\n for line in file:\\n\\n items = line.split(\\\" \\\")\\n if (items[0][:4] == 'Deck'):\\n pass\\n elif (items[0][:9] == 'Companion'):\\n companion = 1\\n elif '\\\\n' in items or items[0][:9] == 'Sideboard':\\n if companion == 1:\\n companion -= 1\\n else:\\n sideboard = True\\n else:\\n try:\\n deck['deckname'].append(file_name)\\n deck['cardname'].append(\\\" \\\".join(items[1:]).replace('\\\\n',''))\\n deck['card_count'].append(int(items[0]))\\n deck['sideboard'].append(sideboard)\\n except (Exception, ValueError) as error:\\n print(f'Unable to process: {error} ; file {filename}')\\n return deck\",\n \"def generate_deck(self):\\n\\t\\tsuits = [\\\"hearts\\\", \\\"spades\\\",\\\"diamonds\\\",\\\"clubs\\\"]\\n\\t\\tcards = []\\n\\n\\t\\tfor suit in suits:\\n\\t\\t\\tif self.ace_as_eleven:\\n\\t\\t\\t\\tace = Card(\\\"Ace\\\", 11, suit)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tace = Card(\\\"Ace\\\", 1, suit)\\n\\t\\t\\tcards.append(ace)\\n\\n\\t\\t\\ttwo = Card(\\\"Two\\\", 2, suit)\\n\\t\\t\\tcards.append(two)\\n\\t\\t\\t\\n\\t\\t\\tthree = Card(\\\"Three\\\", 3, suit)\\n\\t\\t\\tcards.append(three)\\n\\n\\t\\t\\tfour = Card(\\\"Four\\\", 4, suit)\\n\\t\\t\\tcards.append(four)\\n\\n\\t\\t\\tfive = Card(\\\"Five\\\", 5, suit)\\n\\t\\t\\tcards.append(five)\\n\\n\\t\\t\\tsix = Card(\\\"Six\\\", 6, suit)\\n\\t\\t\\tcards.append(six)\\n\\n\\t\\t\\tseven = Card(\\\"Seven\\\", 7, suit)\\n\\t\\t\\tcards.append(seven)\\n\\n\\t\\t\\teight = Card(\\\"Eight\\\", 8, suit)\\n\\t\\t\\tcards.append(eight)\\n\\n\\t\\t\\tnine = Card(\\\"Nine\\\", 9, suit)\\n\\t\\t\\tcards.append(nine)\\n\\n\\t\\t\\tten = Card(\\\"Ten\\\", 10, suit)\\n\\t\\t\\tcards.append(ten)\\n\\n\\t\\t\\tjack = Card(\\\"Jack\\\", 10, suit)\\n\\t\\t\\tcards.append(jack)\\n\\n\\t\\t\\tqueen = Card(\\\"Queen\\\", 10, suit)\\n\\t\\t\\tcards.append(queen)\\n\\n\\t\\t\\tking = Card(\\\"King\\\", 10, suit)\\n\\t\\t\\tcards.append(king)\\n\\n\\t\\treturn cards\",\n \"def __init__(self):\\n \\n self.deck = [Card(suit,rank) for suit in SUITS for rank in RANKS]\",\n \"def loadCardDB():\\n with open(CARDS_JSON, 'r') as infofile:\\n cards = json.load(infofile)\\n with open(PILOT_TEXT_JSON, 'r') as infofile:\\n pilotTexts = json.load(infofile)\\n with open(UPGRADE_TEXT_JSON, 'r') as infofile:\\n upgradeTexts = json.load(infofile)\\n with open(MODIFICATION_TEXT_JSON, 'r') as infofile:\\n modificationTexts = json.load(infofile)\\n with open(TITLE_TEXT_JSON, 'r') as infofile:\\n titleTexts = json.load(infofile)\\n return _createCardDB(cards, pilotTexts, upgradeTexts, modificationTexts, titleTexts)\",\n \"def sort(self):\\n self.deckcards.sort()\",\n \"def get_cards(self):\\n return [card.view_model() for card in self._deck.loc]\",\n \"def load():\\n\\n # Path for the cache-file.\\n cache_path = os.path.join(data_dir, \\\"collisions.pkl\\\")\\n\\n # If the DataSet-object already exists in a cache-file\\n # then load it, otherwise create a new object and save\\n # it to the cache-file so it can be loaded the next time.\\n dataset = load_cached(cache_path=cache_path,\\n in_dir=data_dir)\\n\\n return dataset\",\n \"def shuffle(self):\\n\\n if self.deck:\\n self.deck = deque()\\n\\n max_decks = self.deck_count + 1 # +1 for range function\\n\\n for deck in range(1, max_decks):\\n for suit in self.suits:\\n for num, name in enumerate(self.names, start=1):\\n card = PlayingCard()\\n card.set_attributes(name, suit, num)\\n self.deck.append(card)\\n\\n for deck_shuffle in range(self.shuffle_count):\\n random.shuffle(self.deck)\",\n \"def test_list(self):\\n\\n decks = []\\n try:\\n decks.extend(scrape_decks())\\n except Exception as e:\\n self.logger.exception(\\n 'Scraper for site TappedOut raised an exception'\\n )\\n\\n print(\\\"Collected {} decks:\\\".format(len(decks)))\\n for deck in decks:\\n print(\\\"#\\\", deck.deckType)\\n print(\\\" commander =\\\", deck.commander)\\n print(\\\" image =\\\", deck.commander_img)\\n print(\\\" video =\\\", deck.video)\\n if deck.decklist is not None:\\n print(\\\" decklist =\\\", deck.decklist)\\n print()\\n\\n if os.environ.get(\\\"JUMBO_WRITE_TO_DB\\\") is not None:\\n self.insert_decks(decks)\",\n \"def populate_deck_db(decks, cursor):\\n cursor.execute('DROP TABLE IF EXISTS decks')\\n cursor.execute('DROP TABLE IF EXISTS deck_lists')\\n cursor.execute('''CREATE TABLE IF NOT EXISTS decks\\n (deckid integer primary key, class text)\\n WITHOUT ROWID''')\\n\\n cursor.execute('''CREATE TABLE IF NOT EXISTS deck_lists\\n (deckid integer, cardname text, amount integer,\\n PRIMARY KEY (deckid, cardname))''')\\n for deck in decks:\\n cursor.execute('INSERT INTO decks VALUES (?, ?)',\\n (deck.deckid, deck.playerclass))\\n for card in deck.decklist:\\n cursor.execute('INSERT INTO deck_lists VALUES (?, ?, ?)',\\n (deck.deckid, card.cardname, card.amount))\\n return\",\n \"def loadData(catalog):\\n loadArtworks(catalog)\\n loadArtists(catalog)\\n loadAdquires(catalog)\\n loadNacionalities(catalog)\\n load2DArtworks(catalog)\\n loadArtistMediumsTags(catalog)\\n loadDptments(catalog)\\n catalog['artists'] = sortArtists(catalog, 3)\\n fillArtistMediums(catalog)\\n fillMostUsedMediums(catalog)\\n catalog['artists_tags'] = sortArtistTags(catalog, 3)\\n sort_dptments(catalog)\",\n \"def create_deck(self):\\n\\n deck = []\\n\\n # Suits and face values\\n suits = ['Clubs', 'Diamonds', 'Hearts', 'Spades']\\n face_values = ['1', '2', '3', '4', '5', '6', '7', '8', '9', '10', 'J', 'Q', 'K']\\n\\n # Creating deck\\n for suit in suits:\\n for value in face_values:\\n deck.append(Card(suit[0], value))\\n\\n # Adding jokers\\n if self.jokers:\\n deck.append(Card('Jk', 0))\\n deck.append(Card('Jk', 0))\\n\\n return deck\",\n \"def refresh(self):\\n self.deck = []\\n\\n for _suit in Suit:\\n for _face in Face:\\n self.insert(Card(_suit, _face, self))\",\n \"def load(self):\\n\\t\\t# Initialize empty list\\n\\t\\tdata_files = []\\n\\n\\t\\t# Append the Drusen files to the list\\n\\t\\tfor single_file in os.listdir(self.data_dir):\\n\\t\\t\\tdata_files.append(single_file)\\n\\t\\treturn data_files\",\n \"def get_card_sets(self, name: str) -> List:\",\n \"def fetch_data():\\n for category in CHEATSHEETS.items():\\n subprocess.call(f'curl -o {PATH}{category[0] + \\\".csv\\\"} {category[1]}', shell=True)\\n\\n index = -1\\n for filename in os.listdir(PATH):\\n for idx, row in pd.read_csv(PATH + filename, on_bad_lines='skip').replace(np.nan, '').iterrows():\\n name = row['Model']\\n url = REDIRECT_URL + name.lower()\\n category = filename.split('.')[0]\\n featurizers = row['Acceptable Featurizers'].split(' ') if row['Acceptable Featurizers'] != '' else []\\n backends = ['PyTorch' if item in {\\\"PTorch\\\", \\\"Torch\\\", \\\"PyTorch \\\"} else item for item in row['Backend'].split('/')]\\n types = row['Type'] if filename != 'general.csv' else row['Classifier/Regressor']\\n types = types.split('/') if filename == 'material.csv' else types.split('/ ')\\n index += 1\\n\\n backend_list.append(backends)\\n type_list.append(types)\\n featurizer_list.append(featurizers)\\n model_list.append(Model(name, url, category, featurizers, backends, types, index))\",\n \"def shuffle_deck(self):\\n deck = [i for i in range(0, 52)]\\n shuffle(deck)\\n self.deck = [cards[c*2:c*2+2] for c in deck]\",\n \"def load(self, source):\\n try:\\n inputdata = self.__inputmanager.read(source)\\n self.__suitables = self.__inputmanager.map(inputdata)\\n self.__data = inputdata\\n except ValueError as e:\\n print (\\\"Failed to load the dataset: %s\\\" % e)\\n raise\\n\\n self.__modules = self.import_suitable_visualizations(self.__suitables)\\n self.__has_datefields = self.__inputmanager.has_date_points()\\n # Converting the datakeys into strings.\\n self.__datakeys = [str(i) for i in list(self.__data[0].keys())]\\n return self.__suitables\",\n \"def parse_decklist(archidekt_id: str) -> tuple[Decklist, bool, list]:\\r\\n decklist = Decklist()\\r\\n warnings = []\\r\\n ok = True\\r\\n\\r\\n r = requests.get(f\\\"https://archidekt.com/api/decks/{archidekt_id}/\\\")\\r\\n if r.status_code != 200:\\r\\n raise (ValueError(f\\\"Archidekt returned statuscode {r.status_code}\\\"))\\r\\n\\r\\n data = r.json()\\r\\n\\r\\n in_deck = {cat[\\\"name\\\"] for cat in data[\\\"categories\\\"] if cat[\\\"includedInDeck\\\"]}\\r\\n\\r\\n for item in data[\\\"cards\\\"]:\\r\\n # Extract relevant data\\r\\n count = item[\\\"quantity\\\"]\\r\\n card_name = item[\\\"card\\\"][\\\"oracleCard\\\"][\\\"name\\\"]\\r\\n set_id = item[\\\"card\\\"][\\\"edition\\\"][\\\"editioncode\\\"]\\r\\n collector_number = item[\\\"card\\\"][\\\"collectorNumber\\\"]\\r\\n if len(item[\\\"categories\\\"]) > 0 and item[\\\"categories\\\"][0] not in in_deck:\\r\\n continue\\r\\n\\r\\n # Validate card name\\r\\n card_name, warnings_name = validate_card_name(card_name)\\r\\n if card_name is None:\\r\\n decklist.append_comment(card_name)\\r\\n warnings.extend([(decklist.entries[-1], level, msg) for level, msg in warnings_name])\\r\\n ok = False\\r\\n continue\\r\\n\\r\\n # Validate card print\\r\\n card, warnings_print = validate_print(card_name, set_id, collector_number)\\r\\n\\r\\n decklist.append_card(count, card)\\r\\n warnings.extend([(decklist.entries[-1], level, msg) for level, msg in warnings_name + warnings_print])\\r\\n\\r\\n decklist.name = data[\\\"name\\\"]\\r\\n\\r\\n return decklist, ok, warnings\",\n \"def populate(cards_info, sets_file=None, session=Session):\\n\\n s = session()\\n\\n with sets_file or codecs.open(DEFAULT_SETS_FILE, encoding=\\\"utf-8\\\") as file:\\n reader = unicode_csv_reader(file, reader=csv.DictReader)\\n sets = {}\\n for row in reader:\\n row[\\\"released\\\"] = datetime.datetime.strptime(\\n row[\\\"released\\\"], u\\\"%Y/%m/%d\\\"\\n )\\n sets[row[\\\"code\\\"]] = m.Set(**row)\\n\\n sts = itertools.chain.from_iterable(types.subtypes.itervalues())\\n\\n types_ = {type : m.Type(name=type) for type in types.all}\\n supertypes = {st : m.Supertype(name=st) for st in types.supertypes}\\n subtypes = {st : m.Subtype(name=st) for st in sts}\\n\\n s.add_all(\\n itertools.chain.from_iterable(\\n i.itervalues() for i in (sets, types_, supertypes, subtypes)\\n )\\n )\\n\\n for card in cards_info:\\n # XXX: Split cards / Stupid multiple ability\\n if \\\" // \\\" in card[u\\\"name\\\"] or card[u\\\"name\\\"] == u\\\"Seeds of Strength\\\":\\n continue\\n\\n t, u, v = (card.pop(k) for k in [u\\\"supertypes\\\", u\\\"types\\\", u\\\"subtypes\\\"])\\n\\n card[u\\\"ability_objects\\\"] = [\\n s.query(m.Ability).filter_by(description=d).first() or\\n m.Ability(description=d) for d in card.pop(u\\\"abilities\\\")\\n ]\\n\\n card[u\\\"supertype_objects\\\"] = {supertypes[st] for st in t}\\n card[u\\\"type_objects\\\"] = {types_[type] for type in u}\\n card[u\\\"subtype_objects\\\"] = {subtypes[st] for st in v}\\n\\n appearances = {\\n m.SetAppearance(set=sets[set], rarity=rarity)\\n for set, rarity in card.pop(u\\\"appearances\\\")\\n }\\n\\n card = m.Card(**card)\\n card.set_appearances.update(appearances)\\n\\n s.add(card)\\n\\n s.commit()\",\n \"def build_data_set(self):\\n if not self.assert_data_correct():\\n self.download_all_data()\\n self.unpack_rename_data()\\n self.split_data_characters()\\n self.clean_data_fragments()\\n self.create_font_data()\\n if not self.assert_train_augmented():\\n self.augment_train_data()\\n if not self.assert_style_data_correct():\\n self.download_style_data()\\n self.unpack_rename_data()\",\n \"def shuffle(self):\\r\\n random.shuffle(self.deck_of_cards)\\r\\n return self.deck_of_cards\",\n \"def shuffle(self):\\n random.shuffle(self.deckcards)\",\n \"def buildDeck(self, resources):\\n for key,value in resources.deckData.items():\\n self.deck.append(resources.cards[value[self.playerClass]])\\n random.shuffle(self.deck)\\n self.HP = self.getHP() # Set HP\",\n \"def test_deck_contains_all_cards(self):\\n\\n # I'm using collections.Counter so that the order is ignored (as in a\\n # set) but that multiples are accounted for.\\n expected = collections.Counter([\\n ('r', 'i'), ('r', 'i'), ('r', 'i'),\\n ('r', 2), ('r', 3), ('r', 4), ('r', 5), ('r', 6), \\n ('r', 7), ('r', 8), ('r', 9), ('r', 10),\\n\\n ('g', 'i'), ('g', 'i'), ('g', 'i'),\\n ('g', 2), ('g', 3), ('g', 4), ('g', 5), ('g', 6),\\n ('g', 7), ('g', 8), ('g', 9), ('g', 10),\\n\\n ('b', 'i'), ('b', 'i'), ('b', 'i'),\\n ('b', 2), ('b', 3), ('b', 4), ('b', 5), ('b', 6),\\n ('b', 7), ('b', 8), ('b', 9), ('b', 10),\\n\\n ('y', 'i'), ('y', 'i'), ('y', 'i'),\\n ('y', 2), ('y', 3), ('y', 4), ('y', 5), ('y', 6),\\n ('y', 7), ('y', 8), ('y', 9), ('y', 10),\\n\\n ('w', 'i'), ('w', 'i'), ('w', 'i'),\\n ('w', 2), ('w', 3), ('w', 4), ('w', 5), ('w', 6),\\n ('w', 7), ('w', 8), ('w', 9), ('w', 10), ])\\n\\n self.assertEqual(expected, collections.Counter(deck.deck_gen()))\",\n \"def __init__(self):\\n self.deck = []\\n\\n for i in SUITS:\\n for j in RANKS:\\n self.deck.append(Card(i, j))\",\n \"def load_data(self):\\n with open('data/fordTrain.csv') as f:\\n data = csv.reader(f, delimiter=',')\\n train = [x for i, x in enumerate(data) if i > 0] \\n # Extract features and target variable separately\\n trainx = [x[3:] for x in train]\\n trainy = [x[2] for x in train]\\n\\n with open('data/fordTest.csv') as f:\\n data = csv.reader(f, delimiter=',')\\n testx = [x[3:] for i, x in enumerate(data) if i > 0] \\n\\n with open('data/Solution.csv') as f:\\n data = csv.reader(f, delimiter=',')\\n testy = [x[2] for i, x in enumerate(data) if i > 0] \\n\\n # Extract features and target variable, convert to numpy array\\n trainx = np.asarray(trainx, dtype=np.float32)\\n trainy = np.asarray(trainy, dtype=np.int8)\\n testx = np.asarray(testx, dtype=np.float32)\\n testy = np.asarray(testy, dtype=np.int8)\\n\\n # Return training and test sets\\n trainSet = Dataset(trainx, trainy)\\n testSet = Dataset(testx, testy)\\n return trainSet, testSet\",\n \"def load_dataset(self):\\n # Get all the files in the directory\\n file_list = self.get_file_list()\\n\\n # Concatenate the data corresponding to a list of files\\n data = self.concatenate_file_data(file_list)\\n\\n # Shuffle the data and create the training and the validation datasets\\n data = self.shuffle_data_dictionary(data)\\n self.training_dataset, self.validation_dataset = self.split_data_into_training_and_validation(data)\",\n \"def play():\\n decks = make_decks()\\n\\n deck_pulls = {deck: [] for deck in decks}\\n for i in range(100):\\n deck = random.choice(decks)\\n deck_pulls[deck].append(deck.pull())\\n\\n return decks, deck_pulls\",\n \"def get_datasets() -> List[Dataset]:\\n\\n amzn = Dataset(\\n id='amzn', name='Amazon Reviews', language='en',\\n description=\\\"This dataset consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.\\\")\\n\\n cnn = Dataset(\\n id='cnn_dailymail', name='CNN/ DailyMail', language='en',\\n description='The well-known CNN/ DailyMail data set for text summarization (version 3.0.0). The data has been fetched via HuggingFace Datasets')\\n\\n swisstext = Dataset(\\n id='swisstext', name='SwissText 2019', language='de',\\n description='The dataset was published for the SwissText conference 2019. ')\\n\\n return [amzn, cnn, swisstext]\",\n \"def load_data(self):\\n if not os.path.isfile(\\\"{}/OFF_data.json\\\".format(settings.DIR_PATH)):\\n self.request_constructor(settings.R_COLLECTION['category'], 'NULL', 'tags')\\n self.crawl_data('category')\\n i = 0\\n for item in self.categories:\\n i += 1\\n cat = item.get(\\\"name\\\")\\n self.request_constructor(settings.R_COLLECTION['product'], cat, 'products')\\n self.crawl_data('product')\\n\\n self.data = {\\\"categories\\\": self.categories, \\\"products\\\": self.products}\\n self.save_data('OFF_data.json')\\n else:\\n with open(\\\"{}/OFF_data.json\\\".format(settings.DIR_PATH), 'r') as f:\\n self.data = json.load(f)\\n self.categories = self.data[\\\"categories\\\"]\\n self.products = self.data[\\\"products\\\"]\\n return self.categories, self.products\",\n \"def get_all_desserts():\\n return get_data_from_category_name(\\\"Desserts\\\")\",\n \"def _generate_datasets(self):\\n datasets = list()\\n for fname in sorted(os.listdir(self.base_dir)):\\n if not self._filename_re.match(fname):\\n continue\\n\\n file_path = os.path.join(self.base_dir, fname)\\n try:\\n fh = self._open_hdf5(file_path)\\n\\n except (IOError, OSError) as e:\\n warnings.warn('Cannot access {}; skipped'.format(file_path))\\n print(e)\\n continue\\n\\n for key in fh:\\n if self._groupname_re.match(key.lstrip('/')):\\n datasets.append(ObjectTableWrapper(fh, key, self._schema))\\n continue\\n\\n warn_msg = 'incorrect group name \\\"{}\\\" in {}; skipped this group'\\n warnings.warn(warn_msg.format(os.path.basename(file_path), key))\\n\\n return datasets\",\n \"def load_data_from_files(self):\\n # separated method to allow mock easier\\n logger.info(\\\"Loading data...\\\")\\n parent = Path(__file__).parent\\n path = parent / \\\"resources\\\" / \\\"scores.txt\\\"\\n self.scorer.load_from_file(path)\\n path = parent / \\\"resources\\\" / \\\"american-english-large.txt\\\"\\n self.trie.load_from_file(path)\\n path = parent / \\\"resources\\\" / \\\"reels.txt\\\"\\n self.reels = Reel.get_from_file(path)\\n logger.info(\\\"Data loaded!\\\")\",\n \"def deckCreated(self):\\n deck = self.deckLoader.loadDeck()\\n self.assertTrue(all([item in deck for item in self.items]), \\\"Each item in the deck initializer should be in the deck\\\")\",\n \"def _read_dataset(self):\\n import pandas as pd\\n\\n freesolv_path = get_data_file_path(FREESOLV_PATH)\\n\\n freesolv_db = pd.read_csv(freesolv_path, delimiter=';',\\n skipinitialspace=True,\\n skiprows=[0, 1, 2], header=0,\\n names=['compound id', 'SMILES',\\n 'iupac name',\\n 'experimental value',\\n 'experimental uncertainty',\\n 'calculated value (GAFF)',\\n 'calculated uncertainty',\\n 'experimental reference',\\n 'calculated reference',\\n 'notes'])\\n\\n compound_ids = freesolv_db['compound id'].to_list()\\n smiles_tags = freesolv_db['SMILES'].to_list()\\n experimental_v = freesolv_db['experimental value'].to_list()\\n return compound_ids, smiles_tags, experimental_v\",\n \"def get_deck(self, deck_id, include_cards=True):\\n deck = self.data_source.get_deck(deck_id, self.user_id, include_cards)\\n\\n return deck\",\n \"async def get_deck_definition(\\n self,\\n *,\\n short_fixed_trash: bool = False,\\n ) -> DeckDefinitionV2:\\n deck_load_name = SHORT_TRASH_DECK if short_fixed_trash else STANDARD_DECK\\n return load_deck(deck_load_name, 2)\",\n \"def load_recipes_from_test_set(cls, args):\\n cls._recipes = Dataset().load_test(\\n use_full_test_set=args.use_full_test_set,\\n use_english=args.use_english,\\n use_english_intelligible=args.use_english_intelligible,\\n use_gold=args.use_gold)\\n cls._add_indices_to_recipes()\\n cls._initialize_recipes_status()\\n logging.info(\\\"Recipes loaded.\\\")\",\n \"def get_card_list(self):\\n return self.cards\",\n \"def load_dataset():\\n\\n\\n train_dd_loader = DailyDialogLoader(PATH_TO_TRAIN_DATA, load=False)\\n train_dataloader = DataLoader(train_dd_loader, batch_size=16, shuffle=True, num_workers=0,\\n collate_fn=PadCollate())\\n\\n test_dd_loader = DailyDialogLoader(PATH_TO_TEST_DATA, load=True)\\n test_dataloader = DataLoader(test_dd_loader, batch_size=1, shuffle=False, num_workers=0,\\n collate_fn=PadCollate())\\n\\n assert train_dd_loader.vocabulary.n_words == test_dd_loader.vocabulary.n_words\\n\\n return train_dd_loader, train_dataloader, test_dataloader\",\n \"def shuffle(self):\\r\\n random.shuffle(self.deck)\",\n \"def createDeck():\\n deck = []\\n my_file = open(current_file)\\n all_the_lines = my_file.readlines()\\n deck = []\\n for i in all_the_lines:\\n deck.append(i.strip())\\n my_file.close()\\n random.shuffle(deck)\\n return deck\",\n \"def make_soldier_objects(data_dir: str) -> List[Soldier]:\\n soldier_list = []\\n \\n with open(data_dir, newline='') as csvfile:\\n reader = csv.reader(csvfile, delimiter=',', quotechar='|')\\n print(reader.__next__()) # print header\\n for row in reader:\\n ################################# YOUR CODE HERE #################################\\n typecode, wp, armor, vitality = row\\n if typecode not in [\\\"INF\\\", \\\"ARC\\\", \\\"CVL\\\"]:\\n continue\\n wp, armor, vitality = float(wp), float(armor), float(vitality)\\n soldier = Soldier(typecode, wp, armor, vitality)\\n soldier_list.append(soldier)\\n ##################################################################################\\n return soldier_list\",\n \"def fill_standard_deck(self):\\n for name in [\\\"ace\\\", \\\"two\\\", \\\"three\\\", \\\"four\\\", \\\"five\\\", \\\"six\\\", \\\"seven\\\", \\\"eight\\\", \\\"nine\\\", \\\"ten\\\", \\\"jack\\\",\\n \\\"queen\\\", \\\"king\\\"]:\\n for suit in [\\\"hearts\\\", \\\"diamonds\\\", \\\"spades\\\", \\\"clubs\\\"]:\\n self.cards.append(card.Card(name, suit, self.card_values[name]))\",\n \"def shuffle():\\n deck = []\\n # By Baccarat rules, there are 4 aces worth 1 point, 16 face cards and tens\\n # worth 0 point, and 32 other cards worth their numerical value.\\n # 8 decks are suffled together to create a shoe.\\n for n in range(8):\\n for i in range (32):\\n deck.append((i % 8) + 2)\\n \\n for i in range (16):\\n deck.append(0)\\n \\n for i in range (4):\\n deck.append(1)\\n \\n random.shuffle(deck)\\n\\n return deck\",\n \"async def test_get_deck_definition(\\n deck_type: DeckType,\\n expected_definition: DeckDefinitionV3,\\n mock_labware_data_provider: LabwareDataProvider,\\n) -> None:\\n subject = DeckDataProvider(\\n deck_type=deck_type, labware_data=mock_labware_data_provider\\n )\\n result = await subject.get_deck_definition()\\n assert result == expected_definition\",\n \"def load_data(data_links_list=(\\n 'https://raw.githubusercontent.com/JanetMatsen/bacteriopop/master'\\n '/raw_data/raw_data.csv',\\n 'https://raw.githubusercontent.com/JanetMatsen/bacteriopop/master'\\n '/raw_data/sample_meta_info.tsv')):\\n\\n # Reading data sets from the links provided.\\n df1 = pd.read_csv(data_links_list[0],\\n error_bad_lines=False)\\n df2 = pd.read_csv(data_links_list[1],\\n sep='\\\\t')\\n df2 = df2.set_index(df2['project'])\\n # fill the Nas id df1 as \\\". Makes the groupbys behave better.\\n df1.fillna('', inplace=True)\\n # repleace 'genus' = 'other' with an empty string to be consistent.\\n df1.replace(to_replace='other', value='', inplace=True)\\n # Removing duplicate columns.\\n del df2['project']\\n del df2['ID']\\n df1 = df1.set_index(df1['project'])\\n # Removing duplicate column.\\n del df1['project']\\n # Joining the two datasets.\\n df = df1.join(df2)\\n # Uniformity in non-capitalization of column names.\\n df.rename(columns={'Kingdom': 'kingdom', 'Phylum': 'phylum',\\n 'Class': 'class', 'Order': 'order',\\n 'Family': 'family', 'Genus': 'genus',\\n 'Length': 'length'}, inplace=True)\\n df.index.names = ['sampleID']\\n # Rearranging columns so that abundance is the last column.\\n df = df[['kingdom',\\t'phylum', 'class', 'order',\\n 'family', 'genus', 'length', 'oxygen',\\n 'replicate', 'week', 'abundance']]\\n assert isinstance(df, pd.DataFrame)\\n return df\",\n \"def scrape_decklist(deck_url):\\r\\n soup = hot_soup(deck_url)\\r\\n card_re = re.compile(r\\\"(\\\\d+)\\\\s(.+)\\\")\\r\\n deck_table = soup.find_all(class_='Stable')[1]\\r\\n deck_headers = deck_table.previous_sibling.previous_sibling.find_all('td')\\r\\n archtype = deck_headers[2].text.replace('decks', '')\\r\\n cardlist = deck_table.table.find_all('table')\\r\\n mainboard, sideboard = [], []\\r\\n for row in cardlist.pop().find_all('span'):\\r\\n count, card = card_re.search(row.parent.text).groups()\\r\\n sideboard.append((int(count), card.strip()))\\r\\n\\r\\n for col in cardlist:\\r\\n for row in col.find_all('span'):\\r\\n count, card = card_re.search(row.parent.text).groups()\\r\\n mainboard.append((int(count), card.strip()))\\r\\n\\r\\n return mainboard, sideboard, archtype\",\n \"def load_data(self, data_set):\\n print(\\\"Started Loading the Data\\\")\\n tagged_tokens = data_set.tagged_words()\\n tokens = untag(tagged_tokens)\\n\\n # Get the list of words that appear less than 5 times in Corpus\\n print(\\\"Get LT5's\\\")\\n tokens = [token.lower() for token in tokens] # Convert to lower case\\n freq_dist = FreqDist(tokens) # Compute the freq dist\\n tokens_lt_5 = [word for word, count in freq_dist.items() if count < 5]\\n\\n # Delete words less than 5 and make the corpus insensitive\\n print(\\\"Making data case insensitive\\\")\\n token_range = range(len(tagged_tokens))\\n indexed_tokens = OrderedDict(zip(token_range,tagged_tokens))\\n updated_tagged_tokens = OrderedDict()\\n for tagged_token_id, tagged_token in indexed_tokens.items():\\n if tagged_token[0].lower() in tokens_lt_5:\\n del indexed_tokens[tagged_token_id]\\n else:\\n temp = list()\\n temp.append(tagged_token[0].lower())\\n temp.append(tagged_token[1])\\n temp = tuple(temp)\\n updated_tagged_tokens[tagged_token_id] = temp\\n tagged_tokens = list(updated_tagged_tokens.values())\\n\\n # Pickle the data for future purpose\\n print(\\\"Pickling the Updated Corpus\\\")\\n if data_set == brown:\\n file_name = \\\"q5_brown_updated.pkl\\\"\\n else:\\n file_name = \\\"q5_treebank_updated.pkl\\\"\\n pkl.dump((tagged_tokens, tokens_lt_5), open(file_name,'wb'))\\n\\n return tagged_tokens, tokens_lt_5\",\n \"def test_list_datasets(self, tmp_path):\\n assert qml.data.list_datasets() == {\\n \\\"qspin\\\": {\\\"Heisenberg\\\": {\\\"closed\\\": {\\\"chain\\\": [\\\"1x4\\\"]}}},\\n \\\"qchem\\\": {\\\"H2\\\": {\\\"6-31G\\\": [\\\"0.46\\\", \\\"1.0\\\", \\\"1.16\\\"]}},\\n }\",\n \"def __init__(self):\\n self.deck = init_deck()\\n self.shuffle()\",\n \"def load_dataset(args, corpus_type, shuffle):\\n assert corpus_type in [\\\"train\\\", \\\"valid\\\", \\\"test\\\"]\\n\\n def _lazy_dataset_loader(pt_file, corpus_type):\\n dataset = torch.load(pt_file)\\n logger.info('Loading %s dataset from %s, number of examples: %d' %\\n (corpus_type, pt_file, len(dataset)))\\n return dataset\\n\\n # Sort the glob output by file name (by increasing indexes).\\n pts = sorted(glob.glob(args.data_path + '.' + corpus_type + '.[0-9]*.pt'))\\n if pts:\\n if (shuffle):\\n random.shuffle(pts)\\n\\n for pt in pts:\\n yield _lazy_dataset_loader(pt, corpus_type)\\n else:\\n # Only one inputters.*Dataset, simple!\\n pt = args.data_path + '.' + corpus_type + '.pt'\\n yield _lazy_dataset_loader(pt, corpus_type)\",\n \"def main():\\n\\t\\n\\tDeck = []\\n\\tfor suite in range(suites):\\n for typecard in range(1, typecard+1):\\n cards.append(typecard)\",\n \"def mock_data_loader(csv_path):\\n file_path = KINGDOM_CSV_PATH\\n\\n kingdomArr = []\\n\\n with open(file_path, newline=\\\"\\\") as csv_file:\\n reader = csv.reader(csv_file, delimiter=\\\",\\\")\\n for row in reader:\\n kingdomArr.append(Kingdom(row[0], row[1]))\\n\\n return kingdomArr\",\n \"def reshuffle(self):\\n self.cards = []\\n self.fill_standard_deck()\\n self.shuffle()\",\n \"def load():\\n global WHITE_CARDS\\n global BLACK_CARDS\\n\\n with open('./cards.csv', 'r') as f:\\n reader = csv.reader(f)\\n for r in reader:\\n black = r[0]\\n white = r[1]\\n if white:\\n WHITE_CARDS.append(white)\\n if black:\\n BLACK_CARDS.append(black)\",\n \"def get_datasets(sim_args):\\n if len(sim_args.data_folders) == 1 and sim_args.data_folders[0] == 'all':\\n data_tags = [\\n 'Webscope_C14_Set1',\\n 'Webscope_C14_Set2',\\n 'MSLR-WEB10k',\\n 'NP2003',\\n 'NP2004',\\n 'HP2003',\\n 'HP2004',\\n 'TD2003',\\n 'TD2004',\\n 'MQ2007',\\n 'MQ2008',\\n 'OHSUMED',\\n ]\\n elif len(sim_args.data_folders) == 1 and sim_args.data_folders[0] == 'CIKM2017':\\n data_tags = [\\n 'MSLR-WEB10k',\\n 'NP2003',\\n 'NP2004',\\n 'HP2003',\\n 'HP2004',\\n 'TD2003',\\n 'TD2004',\\n 'MQ2007',\\n 'MQ2008',\\n 'OHSUMED',\\n ]\\n elif len(sim_args.data_folders) == 1 and sim_args.data_folders[0] == 'letor64':\\n data_tags = [\\n 'NP2003',\\n 'NP2004',\\n 'HP2003',\\n 'HP2004',\\n 'TD2003',\\n 'TD2004',\\n ]\\n # random.shuffle(data_tags)\\n else:\\n data_tags = sim_args.data_folders\\n for data_tag in data_tags:\\n assert data_tag in DATASET_COLLECTION, 'Command line input is currently not supported.'\\n yield DATASET_COLLECTION[data_tag]\",\n \"def __init__(self):\\n self.deck = []\\n for n in range(1, 14):\\n card1 = Card(n, \\\"diamond\\\")\\n self.deck.append(card1)\\n\\n for n in range(1, 14):\\n card1 = Card(n, \\\"spade\\\")\\n self.deck.append(card1)\\n\\n for n in range(1, 14):\\n card1 = Card(n, \\\"heart\\\")\\n self.deck.append(card1)\\n\\n for n in range(1, 14):\\n card1 = Card(n, \\\"club\\\")\\n self.deck.append(card1)\",\n \"def get_cards(self):\\n return [Flashcard.from_word(word) for word in self.get_words()]\",\n \"def choose_deck():\\n deck_prompt = \\\"What deck would you like to play?\\\"\\n choice = utils.choose_list(utils.DECKLIST, deck_prompt)\\n deck = dicts.ALL_DECKS[choice]\\n os.system('clear')\\n return deck\",\n \"def test_loadData():\\n \\n sys = LVsystem.Ecosystem()\\n \\n sys.loadSetup('2Prey1Predator')\\n \\n \\n data = sys.create_data()\\n \\n assert data[0] == 3\\n assert data[1] == ['rabbit', 'hen', 'fox']\\n assert data[2] == [30,10,20]\\n assert data[3] == [0.09,0.07,-0.06] \\n assert data[4] == [10000,10000,1]\\n assert data[5] == [400,500,250]\\n assert data[6][1][2] == -data[6][2][1]\\n assert data[6][2][2] == 0\\n\\n sys.removeSpecies('rabbit')\\n sys.removeSpecies('fox')\\n sys.removeSpecies('hen')\",\n \"def __init__(self, num_decks=1):\\r\\n\\t\\tself.reshuffle = False\\r\\n\\t\\tself.stack = []\\r\\n\\t\\tfor i in range(num_decks):\\r\\n\\t\\t\\tdeck = Deck()\\r\\n\\t\\t\\tfor card in deck.cards:\\r\\n\\t\\t\\t\\tself.stack.append(card)\\r\\n\\t\\trandom.shuffle(self.stack)\\r\\n\\t\\tself.runningcount = 0\\r\\n\\t\\tself.decksremaining = num_decks\\r\\n\\t\\tself.truecount = 0\",\n \"def list(self):\\n return 'Decks available: \\\\n{}'.format(\\\"\\\\n\\\".join([\\n 'Deck {}: {} ({} cards)'.format(deck['id'], deck['title'], len(deck['cards']))\\n for key, deck in self.decks.items()\\n ]))\",\n \"def load_ck_data(openface_dir, emotion_dir, feature_type='AUs'):\\n features = load_OpenFace_features(openface_dir, features=feature_type)\\n labels = load_CK_emotions(emotion_dir)\\n\\n return train_utils.dicts2lists(features, labels)\",\n \"def loadData(dataPath):\\n\\n if not os.path.isdir(dataPath):\\n api = KaggleApi()\\n api.authenticate()\\n api.dataset_download_files(\\n dataset='sumanthvrao/daily-climate-time-series-data',\\n path=dataPath,\\n quiet=True,\\n unzip=True\\n )\\n\\n filepath1 = os.path.join(dataPath, 'DailyDelhiClimateTrain.csv')\\n df1 = DatasetUtility.sortByDate(pd.read_csv(filepath1, header='infer'))\\n\\n filepath2 = os.path.join(dataPath, 'DailyDelhiClimateTest.csv')\\n df2 = DatasetUtility.sortByDate(pd.read_csv(filepath2, header='infer'))\\n\\n return pd.concat([df1, df2], axis=0, ignore_index=True)\",\n \"def test_get_cards_by_card_types(model: BDF) -> None:\\n # setup to remove hackish cards\\n card_types = list(model.card_count.keys())\\n removed_cards = []\\n for card_type in ['ENDDATA', 'INCLUDE', 'JUNK']:\\n if card_type in model.card_count:\\n removed_cards.append(card_type)\\n for removed_card in removed_cards:\\n card_types.remove(removed_card)\\n\\n removed_cards = []\\n for card_type in card_types:\\n if card_type not in model.cards_to_read:\\n try:\\n removed_cards.append(card_type)\\n #print('removed %s' % card_type)\\n except ValueError:\\n msg = 'card_type=%s cant be removed' % card_type\\n raise ValueError(msg)\\n for removed_card in removed_cards:\\n card_types.remove(removed_card)\\n\\n # we now have a list of card types we would like to extract\\n # we'll get the associated cards\\n card_dict = model.get_cards_by_card_types(card_types,\\n reset_type_to_slot_map=False)\\n for card_type, cards in card_dict.items():\\n for card in cards:\\n msg = 'this should never crash here...card_type=%s card.type=%s' % (\\n card_type, card.type)\\n if card_type != card.type and card_type + '1' != card.type:\\n raise RuntimeError(msg)\",\n \"def test_should_return_correct_data(self, mocked_get_data_loader):\\n\\n mocked_get_data_loader.return_value = mock_data_loader\\n\\n correct_kingdoms = {\\n 'SPACE': Kingdom('SPACE', 'Gorilla'),\\n 'LAND': Kingdom('LAND', 'Panda'),\\n 'WATER': Kingdom('WATER', 'Octopus'),\\n 'ICE': Kingdom('ICE', 'Mammoth'),\\n 'AIR': Kingdom('AIR', 'Owl'),\\n 'FIRE': Kingdom('FIRE', 'Dragon')\\n }\\n\\n result_kingdoms = KingdomRepositoryServiceCsvImpl().get_all_kingdoms()\\n\\n for i in correct_kingdoms:\\n\\n self.assertEqual(correct_kingdoms[i], result_kingdoms[i])\",\n \"def load_data():\\n\\n # Load data from categories\\n comp = fetch_20newsgroups(subset='all', categories=['comp.graphics', 'comp.sys.mac.hardware', 'comp.windows.x'], \\\\\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\\n science = fetch_20newsgroups(subset='all', categories=['sci.crypt', 'sci.electronics', 'sci.space'], \\\\\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\\n politics = fetch_20newsgroups(subset='all', categories=['talk.politics.guns', 'talk.politics.mideast'], \\\\\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\\n religion = fetch_20newsgroups(subset='all', categories=['alt.atheism', 'soc.religion.christian'], \\\\\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\\n recreation = fetch_20newsgroups(subset='all', categories=['rec.autos', 'rec.sport.baseball', 'rec.sport.hockey'], \\\\\\n shuffle=True, random_state=1, remove=('headers', 'footers', 'quotes'))\\n\\n # Print total number of documents\\n data_len = [len(comp.data), len(science.data), len(politics.data), len(recreation.data), len(religion.data)]\\n\\n # Subsample classes to create a balanced dataset\\n sub_k = min(data_len)\\n comp.data, comp.target = [list(t) for t in zip(*random.sample(list(zip(comp.data, comp.target)), sub_k))]\\n science.data, science.target = [list(t) for t in zip(*random.sample(list(zip(science.data, science.target)), sub_k))]\\n politics.data, politics.target = [list(t) for t in zip(*random.sample(list(zip(politics.data, politics.target)), sub_k))]\\n religion.data, religion.target = [list(t) for t in zip(*random.sample(list(zip(religion.data, religion.target)), sub_k))]\\n recreation.data, recreation.target = [list(t) for t in zip(*random.sample(list(zip(recreation.data, recreation.target)), sub_k))]\\n\\n # Subcategories labels\\n subcat_comp = np.array(comp.target)\\n subcat_scien = np.array(science.target) + len(comp.target_names)\\n subcat_polit = np.array(politics.target) + len(comp.target_names) + len(science.target_names)\\n subcat_rel = np.array(religion.target) + len(comp.target_names) + len(science.target_names) + len(politics.target_names)\\n subcat_rec = np.array(recreation.target) + len(comp.target_names) + len(science.target_names) + len(politics.target_names) + len(religion.target_names)\\n\\n # Assign labels to train data based on categories\\n y_comp = np.ones(len(comp.data))\\n y_scien = 2*np.ones(len(science.data))\\n y_polit = 3*np.ones(len(politics.data))\\n y_rel = 4*np.ones(len(religion.data))\\n y_rec = 5*np.ones(len(recreation.data))\\n labels = np.concatenate((y_comp,y_scien,y_polit,y_rel,y_rec), axis=None)\\n\\n # Computers\\n train_comp, test_comp, y_train_comp, y_test_comp, subcat_comp_train, subcat_comp_test = train_test_split(comp.data, y_comp, subcat_comp, test_size=0.2, random_state=42)\\n train_comp, val_comp, y_train_comp, y_val_comp, subcat_comp_train, subcat_comp_val = train_test_split(train_comp, y_train_comp, subcat_comp_train, test_size=0.25, random_state=42)\\n\\n # Sciences\\n train_scien, test_scien, y_train_scien, y_test_scien, subcat_scien_train, subcat_scien_test = train_test_split(science.data, y_scien, subcat_scien, test_size=0.2, random_state=42)\\n train_scien, val_scien, y_train_scien, y_val_scien, subcat_scien_train, subcat_scien_val = train_test_split(train_scien, y_train_scien, subcat_scien_train, test_size=0.25, random_state=42)\\n\\n # Politics\\n train_polit, test_polit, y_train_polit, y_test_polit, subcat_polit_train, subcat_polit_test = train_test_split(politics.data, y_polit, subcat_polit, test_size=0.2, random_state=42)\\n train_polit, val_polit, y_train_polit, y_val_polit, subcat_polit_train, subcat_polit_val = train_test_split(train_polit, y_train_polit, subcat_polit_train, test_size=0.25, random_state=42)\\n\\n # Religion\\n train_rel, test_rel, y_train_rel, y_test_rel, subcat_rel_train, subcat_rel_test = train_test_split(religion.data, y_rel, subcat_rel, test_size=0.2, random_state=42)\\n train_rel, val_rel, y_train_rel, y_val_rel, subcat_rel_train, subcat_rel_val = train_test_split(train_rel, y_train_rel, subcat_rel_train, test_size=0.25, random_state=42)\\n\\n # Recreation\\n train_rec, test_rec, y_train_rec, y_test_rec, subcat_rec_train, subcat_rec_test = train_test_split(recreation.data, y_rec, subcat_rec, test_size=0.2, random_state=42)\\n train_rec, val_rec, y_train_rec, y_val_rec, subcat_rec_train, subcat_rec_val = train_test_split(train_rec, y_train_rec, subcat_rec_train, test_size=0.25, random_state=42)\\n\\n # Corpus from all categories in train set\\n newsgroups_train = train_comp + train_scien + train_polit + train_rel + train_rec\\n #print(f\\\"Total number of documents in all categories in the train set is {len(newsgroups_train)}.\\\")\\n train_labels = np.concatenate((y_train_comp,y_train_scien,y_train_polit,y_train_rel,y_train_rec), axis=None)\\n #print(train_labels.shape)\\n train_subcat = np.concatenate((subcat_comp_train,subcat_scien_train,subcat_polit_train,subcat_rel_train,subcat_rec_train), axis=None)\\n #print(train_subcat.shape)\\n\\n # Corpus from all categories in test set\\n newsgroups_test = test_comp + test_scien + test_polit + test_rel + test_rec\\n test_labels = np.concatenate((y_test_comp,y_test_scien,y_test_polit,y_test_rel,y_test_rec), axis=None)\\n test_subcat = np.concatenate((subcat_comp_test,subcat_scien_test,subcat_polit_test,subcat_rel_test,subcat_rec_test), axis=None)\\n\\n # Corpus from all categories in validation set\\n newsgroups_val = val_comp + val_scien + val_polit + val_rel + val_rec\\n val_labels = np.concatenate((y_val_comp,y_val_scien,y_val_polit,y_val_rel,y_val_rec), axis=None)\\n val_subcat = np.concatenate((subcat_comp_val,subcat_scien_val,subcat_polit_val,subcat_rel_val,subcat_rec_val), axis=None)\\n\\n # Data Split\\n total = len(test_labels) + len(val_labels) + len(train_labels)\\n\\n return newsgroups_train, train_labels, newsgroups_test, test_labels, newsgroups_val, val_labels, train_subcat, test_subcat, val_subcat\",\n \"def _collect_quizzes():\\n data_path = join(dirname(abspath(__file__)), 'data')\\n for _, _, filenames in os.walk(data_path):\\n for filename in filenames:\\n if filename.endswith('.yml'):\\n quiz_type = filename.replace('.yml', '').capitalize()\\n QUIZ_DICT[quiz_type] = []\\n with open(join(data_path, filename), encoding='utf-8') as f:\\n data = yaml.load(f)\\n for class_name, settings in data.items():\\n Q = type(class_name, (Quiz, ), settings)\\n QUIZ_DICT[quiz_type].append(Q)\\n QUIZ_DICT_FLAT[class_name] = Q\",\n \"def evalcards(cardA, cardB, cardC, cardD):\\n array = []\\n ranks = []\\n spadessort = []\\n cardsinsuit = 1\\n # BASESUIT definitions\\n if cardA[-3:] == \\\"SPA\\\":\\n basesuit = suitspades\\n if cardA[-3:] == \\\"HEA\\\":\\n basesuit = suithearts\\n if cardA[-3:] == \\\"DIA\\\":\\n basesuit = suitdiamonds\\n if cardA[-3:] == \\\"CLB\\\":\\n basesuit = suitclubs\\n if cardB in basesuit:\\n cardsinsuit += 1\\n if cardC in basesuit:\\n cardsinsuit += 1\\n if cardD in basesuit:\\n cardsinsuit += 1\\n #BEGIN SORTING CARDS\\n cardBBB = cardB\\n cardCCC = cardC\\n cardDDD = cardD\\n if cardB not in basesuit:\\n cardBBB = basesuit[12]\\n if cardC not in basesuit:\\n cardCCC = basesuit[12]\\n if cardD not in basesuit:\\n cardDDD = basesuit[12]\\n array += [str(basesuit.index(cardA))]\\n if len(str(basesuit.index(cardA))) == 1:\\n del array[0]\\n array += [\\\"0\\\"+str(basesuit.index(cardA))]\\n array += [str(basesuit.index(cardBBB))]\\n if len(str(basesuit.index(cardBBB))) == 1:\\n del array[1]\\n array += [\\\"0\\\"+str(basesuit.index(cardBBB))]\\n array += [str(basesuit.index(cardCCC))]\\n if len(str(basesuit.index(cardCCC))) == 1:\\n del array[2]\\n array += [\\\"0\\\"+str(basesuit.index(cardCCC))]\\n array += [str(basesuit.index(cardDDD))]\\n if len(str(basesuit.index(cardDDD))) == 1:\\n del array[3]\\n array += [\\\"0\\\"+str(basesuit.index(cardDDD))]\\n array.sort()\\n for x in range(0,cardsinsuit):\\n ranks += [basesuit[int(array[x])]]\\n #CHECKING FOR NOT IN SUIT AND FOR SPADES\\n if cardB not in basesuit:\\n if cardB in spades:\\n spadessort += [cardB]\\n else:\\n ranks += [cardB]\\n if cardC not in basesuit:\\n if cardC in spades:\\n if (cardB in spades) and (spades.index(cardC) < spades.index(cardB)):\\n spadessort = listinsert(spadessort, 0, cardC)\\n elif (cardB in spades) and (spades.index(cardC) > spades.index(cardB)):\\n spadessort += [cardC]\\n else:\\n spadessort += [cardC]\\n else:\\n ranks += [cardC]\\n if cardD not in basesuit:\\n if cardD in spades:\\n if (cardB in spades) and (cardC in spades):\\n if (spades.index(cardD) < spades.index(cardC)) and (spades.index(cardD) < spades.index(cardB)):\\n spadessort = listinsert(spadessort, 0, cardD)\\n elif ((spades.index(cardD) < spades.index(cardC)) and (spades.index(cardD) > spades.index(cardB))) or ((spades.index(cardD) > spades.index(cardC)) and (spades.index(cardD) < spades.index(cardB))):\\n spadessort = listinsert(spadessort, 1, cardD)\\n elif (spades.index(cardD) > spades.index(cardC)) and (spades.index(cardD) > spades.index(cardB)):\\n spadessort += [cardD]\\n elif (cardB in spades) and (cardC not in spades):\\n if spades.index(cardD) < spades.index(cardB):\\n spadessort = listinsert(spadessort, 0, cardD)\\n if spades.index(cardD) > spades.index(cardB):\\n spadessort += [cardD]\\n elif (cardB not in spades) and (cardC in spades):\\n if spades.index(cardD) < spades.index(cardC):\\n spadessort = listinsert(spadessort, 0, cardD)\\n if spades.index(cardD) > spades.index(cardC):\\n spadessort += [cardD]\\n else:\\n spadessort += [cardD]\\n else:\\n ranks += [cardD]\\n ranks = spadessort + ranks\\n return(ranks)\",\n \"def parse_decklist(manastack_id: str, zones: list[str] = [\\\"commander\\\", \\\"mainboard\\\"]):\\r\\n decklist = Decklist()\\r\\n warnings = []\\r\\n ok = True\\r\\n\\r\\n r = requests.get(f\\\"https://manastack.com/api/decklist?format=json&id={manastack_id}\\\")\\r\\n if r.status_code != 200:\\r\\n raise (ValueError(f\\\"Manastack returned statuscode {r.status_code}\\\"))\\r\\n\\r\\n data = r.json()\\r\\n for zone in zones:\\r\\n if len(data[\\\"list\\\"][zone]) > 0:\\r\\n decklist.append_comment(zone.capitalize())\\r\\n for item in data[\\\"list\\\"][zone]:\\r\\n # Extract relevant data\\r\\n count = item[\\\"count\\\"]\\r\\n card_name = item[\\\"card\\\"][\\\"name\\\"]\\r\\n set_id = item[\\\"card\\\"][\\\"set\\\"][\\\"slug\\\"]\\r\\n collector_number = item[\\\"card\\\"][\\\"num\\\"]\\r\\n\\r\\n # Validate card name\\r\\n card_name, warnings_name = validate_card_name(card_name)\\r\\n if card_name is None:\\r\\n decklist.append_comment(card_name)\\r\\n warnings.extend([(decklist.entries[-1], level, msg) for level, msg in warnings_name])\\r\\n ok = False\\r\\n continue\\r\\n\\r\\n # Validate card print\\r\\n card, warnings_print = validate_print(card_name, set_id, collector_number)\\r\\n\\r\\n decklist.append_card(count, card)\\r\\n warnings.extend([(decklist.entries[-1], level, msg) for level, msg in warnings_name + warnings_print])\\r\\n\\r\\n if zone != zones[-1]:\\r\\n decklist.append_comment(\\\"\\\")\\r\\n\\r\\n decklist.name = data[\\\"info\\\"][\\\"name\\\"]\\r\\n\\r\\n return decklist, ok, warnings\",\n \"def get_data_loaders(opt):\\n return find_dataloader_using_name(opt.dataloader)(opt).load_data()\",\n \"def load_data(args, sample_idx):\\n # The preference scores are not used for the MetFrag comparison (MetFrag uses LogP values as preference scores\\n # and calculates those internally. However, due to the implementation of 'load_dataset_EA' we need to specify some\\n # preference model.\\n pref_model = {\\\"training_dataset\\\": \\\"MEOH_AND_CASMI_JOINT\\\", \\\"keep_test_molecules\\\": False,\\n \\\"estimator\\\": \\\"ranksvm\\\", \\\"molecule_representation\\\": \\\"substructure_count\\\"}\\n\\n with sqlite3.connect(\\\"file:\\\" + args.database_fn + \\\"?mode=ro\\\", uri=True) as db:\\n challenges, candidates = load_dataset_EA(\\n db, participant=args.participant, prefmodel=pref_model, ion_mode=args.ion_mode,\\n max_n_cand=args.max_n_cand, sort_candidates_by_ms2_score=args.sort_candidates_by_ms2_score,\\n sample_idx=sample_idx)\\n\\n return challenges, candidates\",\n \"def shuffled_deck(deck):\\n random.shuffle(deck)\\n return deck\",\n \"def get_all_cards(self, filter='open'):\\n print('Searching Trello cards..\\\\n')\\n done_sources = []\\n for list in self.my_lists:\\n for card in list.list_cards(card_filter=filter):\\n name = card.name.split()[0]\\n done_sources.append(card)\\n return done_sources\",\n \"async def get_deck_fixed_labware(\\n self,\\n deck_definition: DeckDefinitionV2\\n ) -> List[DeckFixedLabware]:\\n labware = []\\n\\n for fixture in deck_definition[\\\"locations\\\"][\\\"fixtures\\\"]:\\n labware_id = fixture[\\\"id\\\"]\\n load_name = fixture.get(\\\"labware\\\") # type: ignore[misc]\\n slot = fixture.get(\\\"slot\\\") # type: ignore[misc]\\n\\n if load_name is not None and slot is not None:\\n location = DeckSlotLocation(slot=DeckSlotName.from_primitive(slot))\\n definition = await self._labware_data.get_labware_definition(\\n load_name=load_name,\\n namespace=\\\"opentrons\\\",\\n version=1,\\n )\\n\\n labware.append(\\n DeckFixedLabware(\\n labware_id=labware_id,\\n definition=definition,\\n location=location,\\n )\\n )\\n\\n return labware\",\n \"def deck_get_decks():\\n log_request(request)\\n\\n data = request.json\\n \\n if not valid_params(['username', 'session_id'], data):\\n logging.debug(\\\"Missing parameters\\\")\\n return jsonify({'error' : 500})\\n \\n username = request.json['username']\\n session_id = request.json['session_id']\\n \\n # verify session\\n if not user.verify(username, session_id):\\n logging.debug(\\\"Invalid username or session\\\")\\n return jsonify({'error' : 101})\\n \\n uId = user.id_name(username)\\n\\n decks = deck.get_decks_by_uId(uId)\\n ret = {'decks' : []}\\n for d in decks:\\n ret['decks'].append({'name' : d[0],\\n 'deck_id' : d[1],\\n 'description' : d[2]})\\n\\n ret['error'] = 0\\n return jsonify(ret)\",\n \"def getAllCards(self):\\n return self._cards\",\n \"def create_deck(self):\\n\\n id_already_use, deck, hand = [], [], []\\n\\n for _ in range(self.number_domino - self.hand_size):\\n\\n # We generate a domino and keep its id in id_alread_use\\n # then we make sure to ony keep new id\\n\\n id = (randint(0, 6), randint(0, 6))\\n while id in id_already_use:\\n id = (randint(0, 6), randint(0, 6))\\n deck.append(Domino(id[0], id[1]))\\n id_already_use.append(id)\\n\\n for _ in range(self.hand_size):\\n id = (randint(0, 6), randint(0, 6))\\n while id in id_already_use:\\n id = (randint(0, 6), randint(0, 6))\\n hand.append(Domino(id[0], id[1]))\\n id_already_use.append(id)\\n\\n return deck, hand\",\n \"def load_deck_obj(deckFile, deckObj):\\n\\n deckObj = []\\n\\n # open up the deck file, and start adding lines to the deckObj\\n with open(deckFile, 'r') as deckItem:\\n for deckLine in deckItem:\\n # print([deckLine])\\n deckObj += [deckLine]\\n\\n # print the first 4 card names in the deck.\\n # for card in deckObj[:4]:\\n # print(card)\\n\\n # print the length of the json cards, and the deck's lines\\n # print('deck item lines: {}'.format(len(deckObj)))\\n \\n return\",\n \"def load_data():\\n if _LOCATIONS_BY_ID:\\n return _LOCATIONS_BY_NAME, _LOCATIONS_BY_ID\\n\\n # We need to read the locations in order of country -> admin level 1 -> admin level 2 -> city.\\n # This is so that the higher resolution locations can look up the lower resolution locations\\n # that they belong to, and compute the necessary fields.\\n countries_by_code = _load_country_data(_DATA_FILES['country'])\\n admin1_by_code = _load_admin1_data(_DATA_FILES['admin_1'], countries_by_code)\\n admin2_by_code = _load_admin2_data(_DATA_FILES['admin_2'], countries_by_code, admin1_by_code)\\n _load_city_data(_DATA_FILES['city'], countries_by_code, admin1_by_code, admin2_by_code)\\n _add_alternate_names(_DATA_FILES['alt_wiki_names'])\\n _add_estimated_importances(_DATA_FILES['estimated_importance'])\\n\\n return _LOCATIONS_BY_NAME, _LOCATIONS_BY_ID\",\n \"def available_datasets(self) -> List[str]:\\n return sorted(self.__by_name.keys())\",\n \"def create_deck():\\r\\n deck = []\\r\\n faces = [2,3,4,5,6,7,8,9,10,\\r\\n 'Jack','Queen','King','Ace']\\r\\n suits = ['Spades', 'Diamonds', 'Clubs', 'Hearts']\\r\\n for face in faces:\\r\\n for suit in suits:\\r\\n # Creates a card-tuple and adds it to the deck.\\r\\n deck.append((face, suit))\\r\\n \\r\\n return deck\",\n \"def generate_card_deck() -> [Card]:\\n\\n card_deck = []\\n\\n for card_color in CardColor:\\n for card_value in CardValue:\\n card_deck.append(Card(card_color, card_value))\\n\\n return Shuffle.__shuffle_card_deck(card_deck * Shuffle._CARD_DECK_MULTIPLIER)\",\n \"def _load_raw_datashards(shard_num, nb_collaborators): \\n train_obj = torchvision.datasets.CIFAR10('~/.CIFAR10', train=True, download=True) \\n test_obj = torchvision.datasets.CIFAR10('~/.CIFAR10', train=False, download=True) \\n x_train = train_obj.data\\n y_train = np.asarray(train_obj.targets)\\n x_test = test_obj.data\\n y_test = np.asarray(test_obj.targets)\\n # fix the label dimension to be (N,)\\n y_train = y_train.reshape(-1)\\n y_test = y_test.reshape(-1) \\n \\n # create the shards\\n X_train_shards = x_train[shard_num::nb_collaborators]\\n y_train_shards = y_train[shard_num::nb_collaborators]\\n \\n X_test_shards = x_test[shard_num::nb_collaborators]\\n y_test_shards = y_test[shard_num::nb_collaborators]\\n return (X_train_shards, y_train_shards), (X_test_shards, y_test_shards)\",\n \"def fetch_cifar100_efficient_kd_dataloaders(args):\\n\\n loaders = {}\\n for mode in [\\\"train\\\", \\\"test\\\"]:\\n dataset = CachedKDDataset(mode=mode)\\n loaders[mode] = \\\\\\n torch.utils.data.DataLoader(\\n dataset,\\n batch_size=args.batch_size,\\n shuffle=(mode == \\\"train\\\"),\\n num_workers=4,\\n collate_fn=dict_collate\\n )\\n\\n return loaders[\\\"train\\\"], loaders[\\\"test\\\"]\",\n \"def get_deck_as_str_list(self):\\n\\n ls = []\\n for card in self.deck:\\n ls.append(card.get_card())\\n return ls\",\n \"def get_faces_loaders(batch_size=128, test=True, data_path=\\\"./data/\\\"):\\n\\n dat = np.load(data_path + \\\"rotated_faces_data.npz\\\")\\n train_images = torch.FloatTensor(dat['train_images'])\\n train_targets = torch.FloatTensor(dat['train_angles'])\\n\\n traindata = torch.utils.data.TensorDataset(train_images, train_targets)\\n trainloader = torch.utils.data.DataLoader(traindata, batch_size=batch_size,\\n shuffle=True)\\n\\n if test:\\n test_images = torch.FloatTensor(dat['test_images'])\\n test_targets = torch.FloatTensor(dat['test_angles'])\\n\\n testdata = torch.utils.data.TensorDataset(test_images, test_targets)\\n testloader = torch.utils.data.DataLoader(testdata, batch_size=batch_size)\\n\\n return trainloader, testloader\\n\\n return trainloader\",\n \"def get_available_datasets():\\n files = [file for file in glob.glob(os.path.join(MODULE_ROOT, \\\"datasets/*.json\\\"))]\\n datasets = []\\n for file in files:\\n with open(file, \\\"r\\\") as f:\\n dataset_info = json.load(f)\\n datasets.append(dataset_info)\\n return datasets\",\n \"def get_datasets(FIELDS='all'):\\n dsinfostr = fork_and_get_output(\\\"zfs list -H -o {0}\\\".format(FIELDS).split())\\n header = get_zfs_ds_header()\\n dsinfo = dsinfostr.splitlines()\\n dsobjs = []\\n for dsstr in dsinfo:\\n dsobjs.append(DataZFS(dsstr, header, 'dataset'))\\n return dsobjs\",\n \"def fetch_review(self):\\n c = self.db.cursor()\\n c.execute(\\\"\\\"\\\"SELECT * FROM cards\\n WHERE date_last_reviewed < (DATETIME('now', 'localtime', '-8 hours'))\\n OR correct = 0\\\"\\\"\\\")\\n rows = c.fetchall()\\n cards = [\\n Card(\\n id=id,\\n card_type=card_type,\\n text=text,\\n created=created,\\n uri=uri,\\n updated=updated,\\n difficulty=difficulty,\\n days_between=days_between,\\n date_last_reviewed=date_last_reviewed,\\n correct=correct,\\n )\\n for id, card_type, text, uri, created, updated, difficulty, days_between, date_last_reviewed, correct in rows\\n ]\\n cards = filter(lambda card: card.percent_overdue >= 1, cards)\\n cards = sorted(cards, key=lambda card: card.percent_overdue)\\n\\n return cards[:20]\",\n \"def get_results(path: str, threshold1: float, threshold2: float, quantiles: int, clear_cache: bool = True):\\n create_cache_dirs()\\n\\n correlation_clustering = load_dataset(path, threshold1, threshold2, quantiles, clear_cache=clear_cache)\\n print(\\\"DATA LOADED\\\")\\n\\n correlation_clustering.find_matches()\"\n]"},"negative_scores":{"kind":"list like","value":["0.5819562","0.5731613","0.544646","0.53726274","0.5366942","0.5298741","0.5272846","0.52254647","0.5140814","0.50974256","0.50899714","0.50865227","0.5069896","0.50649506","0.5054334","0.50400245","0.5027452","0.50256103","0.50096786","0.50049436","0.4990609","0.49646613","0.4954556","0.49482644","0.49426016","0.4938606","0.49299636","0.4926834","0.49254796","0.4924566","0.49029097","0.49005836","0.4890899","0.48813173","0.48632264","0.48506513","0.48446253","0.4842137","0.48375872","0.4825627","0.48236677","0.48153964","0.48141256","0.478497","0.47720465","0.47677535","0.47603887","0.4760373","0.4759246","0.4759064","0.47521466","0.47501683","0.47412425","0.47400504","0.47339097","0.47301137","0.47273877","0.47133395","0.47133297","0.47117725","0.4707252","0.46988466","0.46984452","0.46865392","0.46790886","0.46712542","0.46705425","0.4667598","0.4657107","0.4652513","0.46463388","0.46448675","0.46294528","0.46276632","0.4627134","0.46239272","0.46235293","0.46221435","0.46193847","0.46141276","0.4612455","0.46118468","0.46118212","0.46020073","0.46011117","0.4600475","0.45985457","0.45974976","0.4595586","0.45931476","0.45914948","0.45896","0.45870155","0.4584769","0.45845485","0.4584389","0.45843363","0.45831826","0.45785546","0.4576486"],"string":"[\n \"0.5819562\",\n \"0.5731613\",\n \"0.544646\",\n \"0.53726274\",\n \"0.5366942\",\n \"0.5298741\",\n \"0.5272846\",\n \"0.52254647\",\n \"0.5140814\",\n \"0.50974256\",\n \"0.50899714\",\n \"0.50865227\",\n \"0.5069896\",\n \"0.50649506\",\n \"0.5054334\",\n \"0.50400245\",\n \"0.5027452\",\n \"0.50256103\",\n \"0.50096786\",\n \"0.50049436\",\n \"0.4990609\",\n \"0.49646613\",\n \"0.4954556\",\n \"0.49482644\",\n \"0.49426016\",\n \"0.4938606\",\n \"0.49299636\",\n \"0.4926834\",\n \"0.49254796\",\n \"0.4924566\",\n \"0.49029097\",\n \"0.49005836\",\n \"0.4890899\",\n \"0.48813173\",\n \"0.48632264\",\n \"0.48506513\",\n \"0.48446253\",\n \"0.4842137\",\n \"0.48375872\",\n \"0.4825627\",\n \"0.48236677\",\n \"0.48153964\",\n \"0.48141256\",\n \"0.478497\",\n \"0.47720465\",\n \"0.47677535\",\n \"0.47603887\",\n \"0.4760373\",\n \"0.4759246\",\n \"0.4759064\",\n \"0.47521466\",\n \"0.47501683\",\n \"0.47412425\",\n \"0.47400504\",\n \"0.47339097\",\n \"0.47301137\",\n \"0.47273877\",\n \"0.47133395\",\n \"0.47133297\",\n \"0.47117725\",\n \"0.4707252\",\n \"0.46988466\",\n \"0.46984452\",\n \"0.46865392\",\n \"0.46790886\",\n \"0.46712542\",\n \"0.46705425\",\n \"0.4667598\",\n \"0.4657107\",\n \"0.4652513\",\n \"0.46463388\",\n \"0.46448675\",\n \"0.46294528\",\n \"0.46276632\",\n \"0.4627134\",\n \"0.46239272\",\n \"0.46235293\",\n \"0.46221435\",\n \"0.46193847\",\n \"0.46141276\",\n \"0.4612455\",\n \"0.46118468\",\n \"0.46118212\",\n \"0.46020073\",\n \"0.46011117\",\n \"0.4600475\",\n \"0.45985457\",\n \"0.45974976\",\n \"0.4595586\",\n \"0.45931476\",\n \"0.45914948\",\n \"0.45896\",\n \"0.45870155\",\n \"0.4584769\",\n \"0.45845485\",\n \"0.4584389\",\n \"0.45843363\",\n \"0.45831826\",\n \"0.45785546\",\n \"0.4576486\"\n]"},"document_score":{"kind":"string","value":"0.648076"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8554,"cells":{"query":{"kind":"string","value":"Calculates the distance matrix of a list of Deck or FuzzyDeck objects. Returns the vectorform distance vector."},"document":{"kind":"string","value":"def calculate_distance_matrix(played_decks: Union[List[FuzzyDeck], List[Deck]], measure: str):\n deck_data = np.array(played_decks).reshape(len(played_decks), 1)\n if measure == \"jaccard\":\n dist = pdist(deck_data, lambda u, v: u[0].jaccard_distance(v[0]))\n elif measure == \"euclidean\":\n dist = pdist(deck_data, lambda u, v: u[0].euclidean_distance(v[0]))\n else:\n raise ValueError(\"Unknown distance measure {}. \".format(measure) +\n \"Please choose one of the following distance measures ['euclidean','jaccard']\")\n\n return dist"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def getDistanceMatrix(self):\n v = self.getVectors()\n vLis = v.keys()\n N = len(v.keys())\n D = np.zeros([N, N], dtype=np.float32)\n print(N)\n for i in range(N):\n print(\"%d/%d\" %(i, N))\n D[i, i] = 1\n for j in range(i + 1, N):\n dist = self.cosin_sim_pairs(v[vLis[i]], v[vLis[j]])\n D[i, j] = dist\n D[j, i] = dist\n return D","def cal_distances(embeddings):\n # calculate\n dist = np.zeros([len(embeddings), len(embeddings)], dtype=float)\n for ii in xrange(len(embeddings)):\n for jj in xrange(ii + 1, len(embeddings)):\n dist[ii, jj] = np.linalg.norm(embeddings[ii] - embeddings[jj])\n dist[jj, ii] = dist[ii, jj] \n \n # return\n return dist","def _compute_distances(self, atoms: List[CellAtom]):\n muon = self._cell_atoms[self._muon_index]\n\n for atom in atoms:\n atom.distance_from_muon = np.linalg.norm(muon.position - atom.position)","def calculate_distance_matrix(atomlist):\n distlist = []\n for atom in atomlist:\n atomdict = {}\n for partner in atomlist:\n if not str(int(partner[0][1])) in atomdict.keys():\n atomdict[str(int(partner[0][1]))] = []\n atomdict[str(int(partner[0][1]))].append(np.linalg.norm(atom[1] - partner[1]))\n else:\n atomdict[str(int(partner[0][1]))].append(np.linalg.norm(atom[1] - partner[1]))\n atomdict[str(int(partner[0][1]))].sort()\n\n distlist.append(atomdict)\n\n return distlist","def _distance_matrix(self):\n\n # Log the type of metric being used in Sequencing\n logger.info('Using {} Distance'.format(self.measure))\n\n # Convert the nodal coordinate tuples to a np.array\n coords = np.vstack(map(np.array, self.coords.values()))\n \n if self.measure == 'haversine':\n # Partially applied haversine function that takes a coord and computes the vector distances for all coords\n haversine = lambda coord: get_hav_distance(coords[:, 0], coords[:, 1], *coord) \n # Map the partially applied function over all coordinates, and stack to a matrix\n return np.vstack(map(haversine, coords))\n\n # Partially applied haversine function that takes a coord and computes the vector distances for all coords\n euclidean = lambda coord: get_euclidean_dist(coords, coord)\n # Map the partially applied function over all coordinates, and stack to a matrix\n return np.vstack(map(euclidean, coords))","def DistanceMatrices(self):\r\n return self._dms","def compute_distances(Ls):\n if not isinstance(Ls, list):\n Ls = [Ls]\n\n dists = []\n for L in Ls:\n N,D = L.shape\n # 1xNxD - Nx1xD (L1 distance)\n dist = (np.abs(L[None,:,:] - L[:,None,:])).sum(axis=2)\n dists.append(dist)\n\n return dists","def __build_distance_matrix(self):\n for i in range(0, len(self.__corpus)):\n doc_i = self.__corpus[i]\n for j in range(i + 1, len(self.__corpus)):\n doc_j = self.__corpus[j]\n distance = doc_i.calc_distance(doc_j)\n self.__distance_matrix.append(distance)","def distance(self, features, targets):\n cost_matrix = np.zeros((len(targets), len(features)))\n for i, target in enumerate(targets):\n cost_matrix[i, :] = self._metric(self.samples[target], features)\n return cost_matrix","def distance(self, features, targets):\n cost_matrix = np.zeros((len(targets), len(features)))\n for i, target in enumerate(targets):\n cost_matrix[i, :] = self._metric(self.samples[target], features)\n return cost_matrix","def get_distances(self):\n N = len(self.cells) # Number of cells\n distances = np.zeros([N, N]) # distances between cells\n positions = self.position_matrix() # positions of cells \n \n # get distances between cells (exploit symmetry between upper and lower triangular form)\n for i, position in enumerate(positions[:-1, :]): # Iterate matrix except the last one\n directions = positions[i+1:, :] - position # direction from i to j > i\n distances[i, i+1:] = np.linalg.norm(directions, axis=1) # length of directions\n \n return distances + distances.T # Add lower triangle of matrix to upper ","def compute_distances(self, X):\n #print(X.shape, self.Xtr.shape)\n dists = np.zeros((X.shape[0], self.Xtr.shape[0]))\n for i in range(X.shape[0]):\n X_r = np.tile(X[i], (self.Xtr.shape[0], 1))\n dists[i] = np.sqrt(np.sum(np.square(self.Xtr - X_r), axis = 1))\n #print(dists.shape)\n return dists","def calcDistance(self):\n # Initialize the distance matrix\n arr = np.repeat(0, self.num_col)\n result_mat = np.repeat(arr, self.num_col)\n result_mat = np.reshape(result_mat, (self.num_col, self.num_col))\n trinary_mat = self.df_trinary.values\n for left_val in TRINARY_VALUES:\n left_func = lambda v: 1 if v==left_val else 0\n left_mat = np.transpose(np.vectorize(left_func)(trinary_mat))\n for right_val in TRINARY_VALUES:\n if left_val == right_val:\n continue\n right_func = lambda v: 1 if v==right_val else 0\n right_mat = np.vectorize(right_func)(trinary_mat)\n # Count the number of occurrences of this combination of values\n # by doing a matrix multiply\n new_mat = np.matmul(left_mat, right_mat)\n # Multiply by the squared distance between the values\n squared_distance = (left_val - right_val)**2\n new_mat = new_mat*squared_distance\n # Accumulate the result\n result_mat = result_mat + new_mat\n # Convert to dataframe\n result_mat = np.vectorize(lambda v: np.sqrt(v)) (result_mat)\n self.df_distance = pd.DataFrame(result_mat, columns=self.columns,\n index=self.columns)","def distance_matrix(data):\n D = numpy.zeros( (data.shape[0], data.shape[0]) )\n for i in xrange(data.shape[0]):\n for j in xrange(i):\n D[i,j] = numpy.linalg.norm(data[i,:]-data[j,:])\n D[j,i] = D[i,j]\n\n return D","def _calculate_distances(self):\n all_dists = []\n for ref in range(len(self.atoms)):\n if self.atoms[ref].symbol in self.exclude:\n continue\n indices = list(range(ref+1, len(self.atoms)))\n indices = self._filter_excluded(indices)\n if len(indices) == 0:\n continue\n dists = self.atoms.get_distances(ref, indices, mic=True)\n all_dists += list(dists)\n \n # Normalize by the mean distance\n return np.array(all_dists)/np.mean(all_dists)","def _calc_distance(self, X):\n distances = np.zeros((X.shape[0], self.n_clusters))\n print(distances.shape)\n for i, centroid in enumerate(self.centroids):\n distances[:, i] = np.linalg.norm(X - centroid, axis=1)\n return distances","def getDistancesWithNames(twoDList):\n matrix = []\n for i in range(0,len(twoDList)):\n for j in range(len(twoDList) - len(twoDList) + i):\n SD = determineIdenticalBases(data[i][1], data[j][1])\n temp = []\n if SD[1] != 0:\n p = calculateP(SD[0]+SD[1], SD[1])\n temp.append(data[i][0])\n temp.append(data[j][0]) \n temp.append(estimateMutationsPerSite(p))\n matrix.append(temp)\n return matrix","def getDistanceMatrix(self):\n return self.pointcloud.distmat","def _calc_distance_features(self):\n d = ()\n for dx, dy in DIRECTIONS:\n if dx and dy:\n d += (list(self.__calc_distance(direction_x=dx, direction_y=dy)), )\n elif dx:\n tmp, _, _ = self.__calc_distance(direction_x=dx, direction_y=dy)\n d += (tmp, )\n elif dy:\n _, tmp, _ = self.__calc_distance(direction_x=dx, direction_y=dy)\n d += (tmp, )\n\n self.dist_features = d\n\n self.direc_dist = self.__calc_direc_distance()","def compute_distance(self, transpose=False):\n\n # Calculate distance matrix\n if transpose:\n distance_matrix = pdist(self.matrix.T, self.distance)\n else:\n distance_matrix = pdist(self.matrix, self.distance)\n\n # Remove NaNs\n distance_matrix[np.isnan(distance_matrix)] = 1.0\n\n return distance_matrix","def get_distance_matrix(self, points):\n return points[:, :, np.newaxis, :]-points[:, np.newaxis, :, :]","def test_distances_with_vector_input(self):\n input_vector = self.vectors['dog.n.01']\n distances = self.vectors.distances(input_vector, ['mammal.n.01', 'dog.n.01'])\n self.assertTrue(np.allclose(distances, [4.5278745, 0]))\n\n distances = self.vectors.distances(input_vector)\n self.assertEqual(len(distances), len(self.vectors.vocab))\n self.assertTrue(np.allclose(distances[-1], 10.04756))","def norm_dist(face_vectors, f_vector):\n if len(face_vectors) == 0:\n return np.empty((0))\n return np.linalg.norm(face_vectors - f_vector, axis=1)","def distance_matrix(d1, d2=None):\n if d2 is None:\n dists = np.zeros(shape=(d1.shape[0], d1.shape[0]))\n for i in range(dists.shape[0]):\n dists[i] = (((d1 - d1[i]) ** 2).sum(axis=1)) ** 0.5\n else:\n dists = np.zeros(shape=(d1.shape[0], d2.shape[0]))\n for i in range(d1.shape[0]):\n dists[i] = (((d2 - d1[i]) ** 2).sum(axis=1)) ** 0.5\n return dists","def distances(self):\n self._sort_measurements()\n return self._distances","def calcDistanceList(work_list):\n distance_list = []\n for swap in work_list: # for every work item find distance\n distance_list.append(Cluster.calcDistance(*swap))\n return distance_list","def distances(self):","def nm_dist_mat(self):\n mat = np.zeros([self.N, self.M])\n for n in range(self.N):\n for m in range(self.M):\n mat[n, m] = distance(self.N_coords[n], self.M_coords[m])\n return mat","def distance_matrix(sunspots1, sunspots2):\n \n N1 = len(sunspots1)\n N2 = len(sunspots2)\n\n distance_matrix = np.zeros((N1, N2))\n\n for i in list(range(N1)):\n for j in list(range(N2)):\n\n distance_matrix[i, j] = euclidean_dist(sunspots1[i], sunspots2[j])\n\n return distance_matrix","def DistanceMatrices(self, dms):\r\n if not isinstance(dms, ListType):\r\n raise TypeError(\"The item passed in as the new list was not a \"\r\n \"list data type.\")\r\n if self._num_dms >= 0 and len(dms) != self._num_dms:\r\n raise ValueError(\"Cannot set %d distance matrices. Must provide \"\r\n \"exactly %d distance matrices.\" % (len(dms),\r\n self._num_dms))\r\n for dm in dms:\r\n if not isinstance(dm, DistanceMatrix):\r\n raise TypeError(\r\n 'Invalid type (%s); expected DistanceMatrix' %\r\n dm.__class__.__name__)\r\n if self._min_dm_size >= 0 and dm.shape[0] < self._min_dm_size:\r\n raise ValueError(\"Distance matrix of size %dx%d is smaller \"\r\n \"than the minimum allowable distance matrix \"\r\n \"size of %dx%d for this analysis.\" %\r\n (dm.shape[0], dm.shape[0], self._min_dm_size,\r\n self._min_dm_size))\r\n self._dms = dms","def getDistanceMatrix(self):\n return self.distmat.as_matrix()","def _derive_euclidean_dm(self, cat_mat, dim):\r\n res_mat = []\r\n\r\n for i in range(dim):\r\n res_mat.append([0 for k in range(dim)])\r\n for j in range(i):\r\n res_mat[i][j] = self._vector_dist(cat_mat[i], cat_mat[j])\r\n res_mat[j][i] = res_mat[i][j]\r\n\r\n return DistanceMatrix(res_mat, self.DistanceMatrices[0].ids)","def test_distance(self):\n self.assertTrue(np.allclose(self.vectors.distance('dog.n.01', 'mammal.n.01'), 4.5278745))\n self.assertEqual(self.vectors.distance('dog.n.01', 'dog.n.01'), 0)","def Dvec(self):\n return vec(-self.distance)","def distance_unsafe(self, *mass_functions):\n #Submethod to get distance between self and one mass function:\n def distance_one_mass(mass_function):\n #Get the jaccard index matrix:\n difference = self.difference_unsafe(mass_function)\n matrix = {}\n for e1 in difference:\n matrix[e1] = {}\n for e2 in difference:\n if (not e1.is_empty()) or (not e2.is_empty()):\n matrix[e1][e2] = e1.conjunction_unsafe(e2).cardinal / e1.disjunction_unsafe(e2).cardinal\n else:\n matrix[e1][e2] = 1\n \n #Compute the distance as sqtr(0.5 * diffT * matrix * diff):\n distance = 0\n temp = {}\n for e1 in difference:\n temp[e1] = 0\n for e2 in difference:\n temp[e1] += difference[e2] * matrix[e1][e2]\n for e1 in difference:\n distance += temp[e1] * difference[e1]\n return math.sqrt(0.5 * distance)\n\n #Get the distance between self and the provided set of mass functions:\n distance = 0\n for mass_function in mass_functions:\n distance += distance_one_mass(mass_function)\n return round(distance / len(mass_functions), 6)","def compute_distances(self, X):\n num_test = X.shape[0]\n num_train = self.X_train.shape[0]\n dists = np.zeros((num_test, num_train))\n \n sum_test_square = np.sum(np.square(X), axis=1).reshape(-1, 1)\n sum_train_square = np.sum(np.square(self.X_train), axis=1).reshape(-1, 1)\n product_test_train = X @ self.X_train.T\n \n sum_test_square = np.repeat(sum_test_square, num_train, axis=1)\n sum_train_square = np.repeat(sum_train_square, num_test, axis=1).T\n \n dists_square = sum_test_square - 2 * product_test_train + sum_train_square\n \n dists = np.sqrt(dists_square)\n \n return dists","def test_distances(self):\n distances = self.vectors.distances('dog.n.01', ['mammal.n.01', 'dog.n.01'])\n self.assertTrue(np.allclose(distances, [4.5278745, 0]))\n\n distances = self.vectors.distances('dog.n.01')\n self.assertEqual(len(distances), len(self.vectors.vocab))\n self.assertTrue(np.allclose(distances[-1], 10.04756))","def distance_matrix(dnas: Collection[str], metric=hamming_distance, relative=True, as_ndarray=False):\n n = len(dnas)\n result = [[0] * n for _ in range(n)]\n for pair in itertools.combinations(zip(range(n), dnas), r=2):\n (idx1, dna1), (idx2, dna2) = pair\n distance = metric(dna1, dna2)\n distance = distance / max(len(dna1), len(dna2)) if relative else distance\n result[idx1][idx2] = distance\n result[idx2][idx1] = distance\n if as_ndarray:\n result = np.asarray(result)\n return result","def calc_dist_matrix(self,verbose=False):\n\n print(\"Calculating distance matrix.\"); sys.stdout.flush()\n\n nrow = self.data_vector.shape[0]\n self.dist_matrix = np.zeros((nrow, nrow),dtype=float)\n for i in range(nrow):\n if verbose:\n if i % 1000 == 0:\n print(\"Row\",i,\"of\",nrow)\n sys.stdout.flush()\n\n for j in range(i + 1, nrow):\n self.dist_matrix[i,j] = self._pairwise_dist(self.data_vector[i],self.data_vector[j])\n self.dist_matrix[j,i] = self.dist_matrix[i,j]\n \n self.dist_frame = pd.DataFrame(self.dist_matrix,\n index = self.seq_strings,\n columns = self.seq_strings)","def calc_dist_matrix(self):\n\n self.dist_matrix = spatial.distance.squareform(spatial.distance.pdist(self.data_vector,metric=\"hamming\"))\n\n self.dist_frame = pd.DataFrame(self.dist_matrix,\n index = self.seq_strings,\n columns = self.seq_strings)","def distance_matrix(cities):\n\n return [[city1.distance(city2) for city2 in cities]\n for city1 in cities]","def distance(self, *mass_functions):\n #Submethod to get distance between self and one mass function:\n def distance_one_mass(mass_function):\n #Get the jaccard index matrix:\n difference = self.difference(mass_function)\n matrix = {}\n for e1 in difference:\n matrix[e1] = {}\n for e2 in difference:\n if (not e1.is_empty()) or (not e2.is_empty()):\n matrix[e1][e2] = e1.conjunction(e2).cardinal / e1.disjunction(e2).cardinal\n else:\n matrix[e1][e2] = 1\n \n #Compute the distance as sqtr(0.5 * diffT * matrix * diff):\n distance = 0\n temp = {}\n for e1 in difference:\n temp[e1] = 0\n for e2 in difference:\n temp[e1] += difference[e2] * matrix[e1][e2]\n for e1 in difference:\n distance += temp[e1] * difference[e1]\n return math.sqrt(0.5 * distance)\n\n #Get the distance between self and the provided set of mass functions:\n distance = 0\n for mass_function in mass_functions:\n distance += distance_one_mass(mass_function)\n return round(distance / len(mass_functions), 6)","def get_distance(list1, list2):\n import math\n distance_result = (list1[0] - list2[0]) ** 2 + (list1[1] - list2[1]) ** 2 + (list1[2] - list2[2]) ** 2\n return math.sqrt(abs(distance_result))","def __surface_distances(result, reference, voxelspacing=None, connectivity=1):\n result = np.atleast_1d(result.astype(np.bool))\n reference = np.atleast_1d(reference.astype(np.bool))\n if voxelspacing is not None:\n voxelspacing = _ni_support._normalize_sequence(voxelspacing, result.ndim)\n voxelspacing = np.asarray(voxelspacing, dtype=np.float64)\n if not voxelspacing.flags.contiguous:\n voxelspacing = voxelspacing.copy()\n \n # binary structure\n footprint = generate_binary_structure(result.ndim, connectivity)\n \n # test for emptiness\n if 0 == np.count_nonzero(result): \n raise RuntimeError('The first supplied array does not contain any binary object.')\n if 0 == np.count_nonzero(reference): \n raise RuntimeError('The second supplied array does not contain any binary object.') \n \n # extract only 1-pixel border line of objects\n result_border = result ^ binary_erosion(result, structure=footprint, iterations=1)\n\n reference_border = reference ^ binary_erosion(reference, structure=footprint, iterations=1)\n\n dt = distance_transform_edt(~reference_border, sampling=voxelspacing)\n # print(dt)\n reference_border = (reference_border + 0).astype(np.float32)\n\n sds = dt[result_border]\n \n return sds","def test_vector_distance(self):\n\n # Example 1.2\n vector_p = np.array([0.5, 0.0, 0.5])\n vector_q = np.array([0.5, 0.5, 0.0])\n crystal = crystal_system.Tetragonal(0.5, 1.0)\n d_ref_nm = np.sqrt(5.0)/4.0\n\n g_ij_nm2 = crystal.gij_nm2\n\n vector_d = vector_p - vector_q\n d_nm = vector.distance(crystal, vector_d, vector_d)\n\n self.assertAlmostEqual(d_ref_nm, d_nm, 5)\n\n #self.fail(\"Test if the testcase is working.\")","def distance(self, X, Mu):\r\n # Reshape X to N x 1 x D to enable broadcasting\r\n X_reshaped = tf.reshape(X, (-1, 1, X.shape[-1]))\r\n\r\n # subtraction is performed on the last two dimensions of X_reshaped\r\n # X_reshaped(N stack, 1 x D) - Mu(K x D) => (N stack, K x D)\r\n # norm(N stack, K x D) => (N stack, K)\r\n return tf.reduce_sum(tf.square(X_reshaped - Mu), axis=-1)","def distance_dmc(distances, Ks, points):\n doors = []\n for d in distances:\n dmc = []\n for k in Ks:\n print \"==========================\", k, \"==========================\"\n clusters = create_clusters(25, k)\n\n kmeans(points, clusters)\n # print \"Finished creating kmeans algorithm\"\n\n create_backbone_network(GRAPH, clusters, d)\n # print \"Finished creating backbone network\"\n\n find_all_shortest_paths(clusters, SP_TABLE, GRAPH)\n # print \"Finished finding all shortest paths\"\n\n for clst in clusters:\n clst.inter_cost = inter_cost(clst)\n clst.intra_cost = intra_cost(points, clst)\n clst.dm_cost = door_matt_cost(clusters, clst, SP_TABLE)\n\n ret = total_cost(clusters)\n dmc.append(ret[2])\n doors.append(sum(dmc))\n draw_door_matts(map(lambda d: float(format(d, \".4g\")), distances), doors)","def distances(self) -> ndarray:\n return self._distances","def compute_distances_one_loop(self, X):\n num_test = X.shape[0]\n num_train = self.X_train.shape[0]\n dists = np.zeros((num_test, num_train))\n for i in range(num_test):\n dists[i, :] = np.sqrt(np.sum(np.square(X[i, :] - self.X_train), axis=1)).transpose()\n return dists","def _calculate_distance(self, ordered_list):\r\n\r\n total_distance = 0\r\n previous_point = None\r\n for point in ordered_list:\r\n if previous_point is not None:\r\n angle, distance = previous_point.angleAndDistanceTo(point) # geodesic distance in meters\r\n total_distance += distance\r\n previous_point = point\r\n\r\n return total_distance","def compute_distance(self):\n loc = np.extend_dims(self.state[:, :, Boids.Attr.LOC], axis=-1)\n m = np.tile(loc, (1, 1, self.num_boids))\n pos_diff = m-m.transpose(0, 2, 1)\n self.distance = np.linalg.norm(pos_diff, axis=0)","def compute_derivs_matrices(vecs, adv_vecs, dt):\n return (adv_vecs - vecs)/(1.*dt)","def dist_matrix(self):\n return self.__dist_matrix","def get_distances(self, crds):\n self.all_dist = np.zeros((self.natom, self.natom))\n # Loop over upper triangle of atom pairs\n for iat in range(self.natom-1):\n # Get the atom indices\n at_inds = np.arange(len(crds))\n\n # Calc distances between atoms (only upper triangle though)\n at_msk = at_inds > iat\n all_ut_dist = crds[at_msk] - crds[iat]\n all_ut_dist = np.linalg.norm(all_ut_dist, axis=1)\n\n self.all_dist[iat, iat+1:] = all_ut_dist\n\n # Get lower triangle indices\n self.all_dist = self.all_dist + self.all_dist.T","def _get_distances(self):\n for molecule in self.values():\n molecule.get_distances()\n\n # for atom in self.atoms:\n # atom.get_distances()","def get_distance_matrix(self):\n names = self.get_named_leaves()\n num_names = len(names)\n dist_mat = np.zeros((num_names, num_names), dtype='float')\n for i, j in itertools.combinations(range(num_names), 2):\n node1, node2 = self.node_names[names[i]], self.node_names[names[j]]\n dist = self.node_distance(node1, node2)\n dist_mat[i,j] = dist\n dist_mat[j,i] = dist\n return names, dist_mat","def get_correct_distance_matrix(L):\n n = len(L)\n D = np.zeros((n,n))\n for i in range(n):\n for j in range(n):\n if i != j:\n D[i][j] = get_minor(L, [i, j], [i, j]) / get_minor(L, [i], [i])\n return D","def test_poincare_distances_batch(self):\n vector_1 = self.vectors['dog.n.01']\n vectors_2 = self.vectors[['mammal.n.01', 'dog.n.01']]\n distances = self.vectors.vector_distance_batch(vector_1, vectors_2)\n self.assertTrue(np.allclose(distances, [4.5278745, 0]))","def distancematrix(vec1, vec2):\n v1, v2 = np.meshgrid(vec1, vec2)\n return np.abs(v1 - v2)","def measure_distance(self, mat):\n if len(mat) == 1:\n print(\"chain has only one CAatom\")\n return\n self.dists = []\n for num in range(0, len(mat)):\n if num + 1 <= len(mat) - 1:\n c1 = mat[num]\n c2 = mat[num + 1]\n d = c2 - c1\n self.dists.append(math.sqrt(np.sum(d * d)))\n return self.dists","def calculateDistances(df):\n return","def getDistanceMatrix(self, alignedSequences):\n\t\tif not alignedSequences:\n\t\t\traise ValueError(\"alignedSequences must not be empty\")\n\t\tdominantAlignedSequence = alignedSequences[0]\n\t\tsubdominantAlignedSequences = alignedSequences[1:]\n\t\tdistanceMatrix = []\n\t\tfor seq in subdominantAlignedSequences:\n\t\t\tdistanceMatrix.append(len(seq) - self._getNumberOfSpaces(seq) - self._getNumberOfAlignedNucleotides(dominantAlignedSequence, seq))\n\t\treturn distanceMatrix","def _calc_distances(preds, targets, mask, normalize):\n N, K, _ = preds.shape\n _mask = mask.copy()\n _mask[np.where((normalize == 0).sum(1))[0], :] = False\n distances = np.full((N, K), -1, dtype=np.float32)\n normalize[np.where(normalize <= 0)] = 1000000.0\n distances[_mask] = np.linalg.norm(((preds - targets) / normalize[:, None, :])[_mask], axis=-1)\n return distances.T","def calcEuclideanDistance(d1, d2):\n #initiate empty list\n result = []\n #for each index in the list, each position in both list minus each other\n #and to the power of two. Add this in the result list\n for idx in range(len(d1)):\n result.append((d1[idx]-d2[idx])**2)\n\n #Return the square of the sum of all values in the result list\n return math.sqrt(sum(result))","def get_distance_metrics():\n\n return [HausdorffDistance(),\n AverageDistance(),\n MahalanobisDistance(),\n VariationOfInformation(),\n GlobalConsistencyError(),\n ProbabilisticDistance()]","def calculate_distances(train_data, test_datum):\n n = train_data.shape[0]\n dist = []\n for i in range(n):\n distance = np.sqrt(np.sum(np.square(train_data[i]-test_datum)))\n dist.append(distance)\n dist = np.asarray(dist)\n return dist","def build_homes_matrix(self, homes_list):\n\n # Matrix that contains every home and the duration it takes to get to every other home in the list\n homes_matrix = []\n\n # Loop through every home in the list\n # And create a list of the times between this home and the other homes\n for home in homes_list:\n home_distances = []\n\n # Only let them do driving\n commute_type = CommuteType.objects.get_or_create(commute_type=CommuteType.DRIVING)[0]\n\n # Depending on the accuracy either get the exact commute or the approximate\n if self.commute_accuracy == CommuteAccuracy.EXACT:\n result_distance_wrapper = retrieve_exact_commute_client_scheduler(homes_list, [home], commute_type)\n for commute in result_distance_wrapper:\n time_seconds = commute[0][0]\n distance_meters = commute[0][1]\n if time_seconds is not None and distance_meters is not None:\n home_distances.append(time_seconds)\n else:\n home_distances.append(math.inf)\n else:\n update_commutes_cache_client_scheduler(homes_list,\n home,\n accuracy=CommuteAccuracy.APPROXIMATE,\n commute_type=CommuteType.DRIVING)\n home_distances = retrieve_approximate_commute_client_scheduler(homes_list,\n home,\n commute_type=CommuteType.DRIVING)\n\n homes_matrix.append(home_distances)\n\n return homes_matrix","def DM(self, masses=None):\n N = len(self.diameters)\n rs = self.rs\n d = self.ndim\n M = np.zeros((d * N, d * N))\n\n for i in range(N):\n sigi = self.diameters[i]\n for j in range(i):\n rijvec = rs[i, :] - rs[j, :]\n rijvec = rijvec - np.around(rijvec)\n rijsq = np.sum(rijvec**2)\n dij = (sigi + self.diameters[j]) / 2\n dijsq = dij**2\n if rijsq < dijsq:\n rij = np.sqrt(rijsq)\n rijouter = np.outer(rijvec, rijvec)\n # U(r) = ½(1 - r/d)²\n # d²U/dxdy = (dr/dx)(dr/dy)/d² - (1 - r/d)(d²r/dxdy)/d\n # dr/dx = x/r\n # d²r/dxdy = -(x y) / r³\n # d²U/dxdy = -(x y)/(r² d²) + (1 - r/d)((x y)/r²)/(d r)\n # d²U/dx² = (dr/dx)²/d² - (1 - r/d)(d²r/dx²)/d\n # d²r/dx² = -x² / r³ + 1/r\n # d²U/dxᵢdxⱼ = -(xᵢ xⱼ)/(r² d²) + (1 - r/d)((xᵢ xⱼ)/r² -\n # δᵢⱼ)/(d r)\n\n Mij1 = -rijouter / rijsq / dijsq\n Mij2 = (1 - rij / dij) * \\\n (rijouter / rijsq - np.eye(d)) / rij / dij\n Mij = Mij1 + Mij2\n\n M[d * i:d * i + d, d * j:d * j + d] = Mij\n M[d * j:d * j + d, d * i:d * i + d] = Mij\n M[d * i:d * i + d, d * i:d * i + d] -= Mij\n M[d * j:d * j + d, d * j:d * j + d] -= Mij\n\n np.divide(M, self.L**2, out=M)\n if masses is None:\n return M\n\n # TODO: is the mass part of this really part of this?\n marr = np.array(masses)\n assert np.shape(masses) == np.shape(self.diameters)\n marr = np.array([masses] * d)\n marr = marr.T.flatten()\n # marr is now [m1,m1,m2,m2,...] (in 2D)\n mm = np.eye(d * N)\n np.multiply(mm, marr**-.5, out=mm)\n # mm is now M^-½, where M is the mass matrix\n\n mm.dot(M, out=M)\n M.dot(mm, out=M)\n return M","def distancePairs(self):\n return spsd.squareform(spsd.pdist(self.coordinates()))","def face_distance(face_encodings, face_to_compare):\n if len(face_encodings) == 0:\n return np.empty((0))\n\n #return 1/np.linalg.norm(face_encodings - face_to_compare, axis=1)\n return np.sum(face_encodings*face_to_compare,axis=1)","def compute_distance(X, K_clusters):\n dis = np.linalg.norm((X-K_clusters),2,axis=1)**2\n return dis","def compute_pairwise_distances(input_vecs: types.Tensor) -> types.Tensor:\n r = tf.reduce_sum(input_vecs * input_vecs, axis=1, keepdims=True)\n pdistance_matrix = (\n r\n - 2 * tf.matmul(input_vecs, input_vecs, transpose_b=True)\n + tf.transpose(r)\n )\n return tf.cast(pdistance_matrix, dtype=tf.float32)","def F(self, distances):\n return np.sum(self.F_mat(distances), 1)","def get_distance_vector(catchpoints, closest):\n\n deg_rad = math.pi / 180\n \n dphis = catchpoints[:, 1] - closest[:, 1]\n phims = 0.5 * (catchpoints[:, 1] + closest[:, 1])\n dlams = catchpoints[:,0] - closest[:,0]\n\n k1s = (111.13209 - 0.56605 * numpy.cos(2 * phims * deg_rad) + \n 0.00120 * numpy.cos(4 * phims * deg_rad))\n k2s = (111.41513 * numpy.cos(phims * deg_rad) - 0.09455 * \n numpy.cos(3 * phims * deg_rad) + 0.0012 * \n numpy.cos(5 * phims * deg_rad))\n \n return numpy.sqrt(k1s**2 * dphis**2 + k2s**2 * dlams**2)","def _location_distances(self, positions) -> torch.Tensor:\n diff = positions[..., None, :, :] - positions[..., None, :]\n distances = torch.norm(diff, dim=3)\n return distances","def calculate_vectors(self, spectrum_list: List[Spectrum]) -> np.ndarray:\n n_rows = len(spectrum_list)\n reference_vectors = np.empty(\n (n_rows, self.output_vector_dim), dtype=\"float\")\n binned_spectrums = self.model.spectrum_binner.transform(spectrum_list, progress_bar=self.progress_bar)\n for index_reference, reference in enumerate(\n tqdm(binned_spectrums,\n desc='Calculating vectors of reference spectrums',\n disable=(not self.progress_bar))):\n reference_vectors[index_reference, 0:self.output_vector_dim] = \\\n self.model.base.predict(self._create_input_vector(reference), verbose=0)\n return reference_vectors","def test_euclidean_distance_Ndimension(self):\n\n self.assertEqual(15, euclidean_distance([0, 0, 0], [10, 10, 5]))\n self.assertEqual(15, euclidean_distance([0, 0, 0], [-10, -10, -5]))\n\n self.assertEqual(17, euclidean_distance([0, 0, 0, 0], [10, 10, 8, 5]))\n self.assertEqual(17, euclidean_distance([0, 0, 0, 0], [-10, -10, -8, -5]))\n\n self.assertEqual(8, euclidean_distance([0, 0, 0, 0, 0], [5, 1, 1, 1, 6]))\n self.assertEqual(8, euclidean_distance([0, 0, 0, 0, 0], [-5, -1, -1, -1, -6]))","def test_distances(self):\n sf = make_classifier_data(n=10, d=2, seed=37)\n sf.remove_column(\"class\", inplace=True)\n\n numeric_features = [\"int0\", \"int1\", \"float0\", \"float1\"]\n array_features = [\"array0\"]\n string_features = [\"str0\"]\n dict_features = [\"dict0\"]\n\n ## Numeric standard distances should work for numeric columns\n for d in [\n \"euclidean\",\n \"squared_euclidean\",\n \"manhattan\",\n \"cosine\",\n \"transformed_dot_product\",\n ]:\n try:\n m = tc.dbscan.create(\n sf,\n features=numeric_features,\n distance=d,\n radius=1,\n min_core_neighbors=3,\n verbose=False,\n )\n except:\n assert False, \"Standard distance {} failed.\".format(d)\n\n ## Numeric standard distances should work for array columns\n for d in [\n \"euclidean\",\n \"squared_euclidean\",\n \"manhattan\",\n \"cosine\",\n \"transformed_dot_product\",\n ]:\n try:\n m = tc.dbscan.create(\n sf,\n features=array_features,\n distance=d,\n radius=1,\n min_core_neighbors=3,\n verbose=False,\n )\n except:\n assert False, \"Standard distance {} failed.\".format(d)\n\n ## String standard distances should work.\n for d in [\"levenshtein\"]:\n try:\n m = tc.dbscan.create(\n sf,\n features=string_features,\n distance=d,\n radius=1,\n min_core_neighbors=3,\n verbose=False,\n )\n except:\n assert False, \"Standard distance {} failed.\".format(d)\n\n ## Dictionary standard distances should work.\n for d in [\"jaccard\", \"weighted_jaccard\", \"cosine\", \"transformed_dot_product\"]:\n try:\n m = tc.dbscan.create(\n sf,\n features=dict_features,\n distance=d,\n radius=1,\n min_core_neighbors=3,\n verbose=False,\n )\n except:\n assert False, \"Standard distance {} failed.\".format(d)\n\n # Nonsensical combinations of feature types and distances should fail.\n with self.assertRaises(ValueError):\n m = tc.dbscan.create(\n sf,\n features=numeric_features,\n distance=\"levenshtein\",\n radius=1,\n min_core_neighbors=3,\n verbose=False,\n )\n\n with self.assertRaises(ToolkitError):\n m = tc.dbscan.create(\n sf,\n features=dict_features,\n distance=\"levenshtein\",\n radius=1,\n min_core_neighbors=3,\n verbose=False,\n )\n\n with self.assertRaises(ToolkitError):\n m = tc.dbscan.create(\n sf,\n features=string_features,\n distance=\"euclidean\",\n radius=1,\n min_core_neighbors=3,\n verbose=False,\n )\n\n # If no distance is specified, the automatic distance construction\n # should kick in and be correct.\n correct_dist = [\n [[\"str0\"], \"levenshtein\", 1],\n [[\"str1\"], \"levenshtein\", 1],\n [[\"dict0\"], \"jaccard\", 1],\n [[\"int0\", \"int1\", \"float0\", \"float1\"], \"euclidean\", 1],\n [[\"array0\"], \"euclidean\", 1],\n ]\n\n m = tc.dbscan.create(\n sf, radius=1, distance=None, min_core_neighbors=3, verbose=False\n )\n\n self.assertItemsEqual(m.distance, correct_dist)\n\n m = tc.dbscan.create(\n sf, radius=1, distance=\"auto\", min_core_neighbors=3, verbose=False\n )\n self.assertItemsEqual(m.distance, correct_dist)","def compute_distance (uVector, uOther):\n ## since each element can be either 0 or 1,\n ## no need for square roots and pow\n d = 0\n for i in range (len(uVector)):\n d = d + math.pow((int(uVector [i]) - int(uOther [i])), 2)\n\n return d","def distance(self,m,n):\n if type(m) == np.ndarray:\n return np.linalg.norm( self.positions[m] - self.positions[n] , axis = 1)\n \n return np.linalg.norm(self.positions[m]-self.positions[n])","def getDistanceM(self, test, train):\n p = 2 # TUNE currently euclidian distance\n distanceM = pd.DataFrame(index=test.index.values, columns=train.index.values)\n for testrow, testing in test.iterrows():\n for trainrow, training in train.iterrows():\n tot = 0\n for indexc, column in test.iteritems():\n #print(indexc)\n if indexc in self.discrete: # need to reference VDM\n datapoint = self.VDMdict.get(indexc)\n dif = datapoint[testing[indexc]][training[indexc]]\n elif indexc != \"class\": #get distance beween 2 points\n dif = abs(float(testing[indexc]) - float(training[indexc]))\n\n tot += dif ** p\n distance = tot ** (1 / p) #distance is calculated\n distanceM.at[testrow, trainrow] = distance #put in distance matrix\n return(distanceM)","def get_dist_mat(self):\n n_site = self.status.give(keyword=\"n_site\")\n sites = self.status.give(keyword=\"sites\")\n dist_mat = [[0.0 for j in xrange(n_site)] for i in xrange(n_site)]\n for i in xrange(n_site):\n for j in xrange(n_site):\n ri = sites[i].pos\n rj = sites[j].pos\n dist_mat[i][j] = np.linalg.norm(ri-rj)\n # print ri, rj\n return dist_mat","def get_distance(positions: np.ndarray, position: np.ndarray, unit_factor: np.ndarray = None):\n\n if unit_factor is None:\n unit_factor = np.array([1, 1, 1])\n\n distances = np.sqrt(np.sum(((positions - position) * unit_factor.reshape(1, 3)) ** 2, axis=1))\n\n return distances","def face_distance(face_encodings, face_to_compare):\n if len(face_encodings) == 0:\n return np.empty((0))\n\n return np.linalg.norm(face_encodings - face_to_compare, axis=1)","def squared_distance_matrix(X, augmented=False):\n XX = np.dot(X,X.T)\n D = np.outer(np.diag(XX), np.ones(len(X)))-2*XX+np.outer(np.ones(len(X)),\n np.diag(XX))\n if augmented == True:\n n = len(D)\n zeros_v = np.zeros((n,1))\n zeros_h = np.zeros((1,n+1))\n D = np.bmat('D zeros_v; zeros_h')\n return D","def F_mat(self, distances):\n distances_norm2 = norm2(distances)\n distances_norm = np.sqrt(distances_norm2)\n isColliding = self.isColliding(distances_norm)[:, :, :, None]\n\n # Repulsion force when a collision happens\n f_colliding = (2/self.d_coll**2)*isColliding\n \n # Interaction force\n ident = np.identity(np.shape(distances)[1])[None, :, :]\n d = (ident+distances_norm)\n dn = (d**self.n)[:, :, :, None]\n d2 = (ident+distances_norm2)\n d2n = (d2**(self.n+1))[:, :, :, None]\n\n f_interact = self.n*self.d_attr**self.n*(self.d_attr**self.n-dn)/(d2n + 10e-50)*(1-isColliding)\n\n # Total Force\n f = (f_colliding + f_interact)*distances\n\n # Remove self-interaction\n diag = np.einsum('ijj->ij', f[:, :, :, 0])\n diag[:, :] = 0\n\n diag2 = np.einsum('ijj->ij', f[:, :, :, 1])\n diag2[:, :] = 0\n\n return f","def test_cmatrix_list(self):\n\n test_dtraj = [np.array([0, 1, 1, 0, 0, 0, 1, 1, 1, 1]), \\\n np.array([0,1,1,1,0])]\n\n cmatrix_compare = np.array([[2., 3.], [2., 6.]])\n cmatrix_computed = cmatrix(test_dtraj)\n self.assertTrue(np.allclose(cmatrix_compare, cmatrix_computed))","def cal_dis(data,Cen,dis=\"Euclidean\"):\n dis = []\n for i in range(len(data)):\n dis.append([])\n for j in range(len(Cen)):\n dd = math.sqrt(sum(map(lambda x:x**2,data[i]-Cen[j])))\n dis[i].append(dd)\n \n return dis","def _computeDistances(self) -> None:\n length = len(self.data)\n for i, sequenceOne in enumerate(self.data):\n print(f\"[SeqCluBaselineOffline] Computing distances is at iteration {i} of {length}.\")\n for j, sequenceTwo in enumerate(self.data):\n if i == j:\n self.distances[i][j] = 0\n continue\n distance = self.distanceMeasure.calculateDistance(sequenceOne, sequenceTwo)\n self.distances[i][j] = distance\n self.distances[j][i] = distance","def _object_distance(self, object1, object2):\n return np.linalg.norm(np.array(object1) - np.array(object2))","def test_distance(self):\n for emb_vals, point, dist_gt in self.DISTANCE_EXAMPLES:\n print(emb_vals, point, dist_gt)\n emb = to_emb(emb_vals)\n dist = emb.distance(point)\n assert np.allclose(dist, dist_gt), \\\n (\"Wrong distance for point {}: expected {} but was {};\"\n \"\\nembedding:\\n{}\").format(point, dist_gt, dist, str(emb))","def compute_distance(df):\n pass","def get_distance ( self, X: np.ndarray, x0: np.ndarray ):\n \n # Apply distance_function across rows of X\n return [ self.distance_function ( row, x0 ) for row in X ]\n # End get_distance()","def distance(self, vector1, vector2):\n\t\tsum_sq = 0\n\t\tfor i in range(28):\n\t\t\tfor j in range(28):\n\t\t\t\tsum_sq += (vector1[i][j] - vector2[i][j])**2\n\t\treturn math.sqrt(sum_sq)","def return_energy_mat(grid, objects_list, choice_parallelization):\n assert len(grid.shape) == 1, \"energy distance can only be applied on 1D objects\"\n\n n_obj = len(objects_list)\n n_pix = len(grid)\n distance_matrix = numpy.zeros((n_obj, n_obj))\n\n if choice_parallelization == True:\n master_index_list = []\n for i in range(n_obj):\n for j in range(i+1, n_obj):\n master_index_list.append([i, j])\n\n num_cores = multiprocessing.cpu_count()\n results = Parallel(n_jobs=num_cores)(delayed(energy_simple_1D)(grid, objects_list, i) for i in master_index_list)\n\n for i_pair in range(len(results)):\n i = master_index_list[i_pair][0]\n j = master_index_list[i_pair][1]\n distance_matrix[i, j] = results[i_pair]\n distance_matrix[j, i] = results[i_pair]\n\n if choice_parallelization == False:\n for i in range(n_obj):\n for j in range(i+1, n_obj):\n obj_i = objects_list[i]\n obj_j = objects_list[j]\n energy_val = energy_distance(grid, grid, u_weights=obj_i, v_weights=obj_j)\n distance_matrix[i, j] = energy_val\n distance_matrix[j, i] = energy_val\n\n return distance_matrix","def calculate_distances(drives):\n for d in drives:\n d.set_distance()","def eval_mean_distance(played_decks, clustering_data: List, fuzzy: bool, debug: bool = False):\n\n for alg_dict in clustering_data:\n decks = np.array(played_decks)\n clusters = []\n for label in set(alg_dict[\"labels\"]):\n indices = np.where(alg_dict[\"labels\"] == label)\n if fuzzy:\n clusters.append(FuzzyDeckCluster(decks[indices]))\n else:\n clusters.append(DeckCluster(decks[indices]))\n\n if fuzzy:\n clustering = FuzzyDeckClustering(clusters)\n else:\n clustering = DeckClustering(clusters)\n\n sum_of_squared_distances_centroid = 0\n sum_of_squared_distances_core = 0\n\n for cluster in clustering.deck_clusters:\n centroid = cluster.centroid()\n core = cluster.core()\n for deck in cluster.decks:\n sum_of_squared_distances_centroid += (deck.jaccard_distance(centroid))**2\n sum_of_squared_distances_core += (deck.jaccard_distance(core))**2\n alg_dict[\"sse_centroid\"] = sum_of_squared_distances_centroid\n alg_dict[\"sse_core\"] = sum_of_squared_distances_core\n\n if debug:\n print(\"Alg: \" + alg_dict[\"name\"] + \"; \\t sse = \" + str(alg_dict[\"sse_centroid\"]))\n print(\"Alg: \" + alg_dict[\"name\"] + \"; \\t sse = \" + str(alg_dict[\"sse_core\"]))","def compute_distances_two_loops(self, X):\n num_test = X.shape[0]\n num_train = self.X_train.shape[0]\n dists = np.zeros((num_test, num_train))\n for i in range(num_test):\n for j in range(num_train):\n dists[i, j] = np.sqrt(np.sum(np.square(X[i] - self.X_train[j])))\n return dists","def transform(self, samples):\n check_is_fitted(self, [\"cluster_centers\"])\n\n distance_mat = self.get_distance(samples, self.cluster_centers)\n return distance_mat","def getDistances(trainingSet, testInstance, distances):\n # Empty list to store distances of between testInstance and each trainSet item\n # Number of dimensions to check\n length=len(testInstance) - 1\n # Iterate through all items in trainingSet and compute the distance, then append to the distances list\n for x in range(len(trainingSet)):\n dist=calculateDistance(testInstance, trainingSet[x], length)\n distances.append((trainingSet[x], dist))\n return distances"],"string":"[\n \"def getDistanceMatrix(self):\\n v = self.getVectors()\\n vLis = v.keys()\\n N = len(v.keys())\\n D = np.zeros([N, N], dtype=np.float32)\\n print(N)\\n for i in range(N):\\n print(\\\"%d/%d\\\" %(i, N))\\n D[i, i] = 1\\n for j in range(i + 1, N):\\n dist = self.cosin_sim_pairs(v[vLis[i]], v[vLis[j]])\\n D[i, j] = dist\\n D[j, i] = dist\\n return D\",\n \"def cal_distances(embeddings):\\n # calculate\\n dist = np.zeros([len(embeddings), len(embeddings)], dtype=float)\\n for ii in xrange(len(embeddings)):\\n for jj in xrange(ii + 1, len(embeddings)):\\n dist[ii, jj] = np.linalg.norm(embeddings[ii] - embeddings[jj])\\n dist[jj, ii] = dist[ii, jj] \\n \\n # return\\n return dist\",\n \"def _compute_distances(self, atoms: List[CellAtom]):\\n muon = self._cell_atoms[self._muon_index]\\n\\n for atom in atoms:\\n atom.distance_from_muon = np.linalg.norm(muon.position - atom.position)\",\n \"def calculate_distance_matrix(atomlist):\\n distlist = []\\n for atom in atomlist:\\n atomdict = {}\\n for partner in atomlist:\\n if not str(int(partner[0][1])) in atomdict.keys():\\n atomdict[str(int(partner[0][1]))] = []\\n atomdict[str(int(partner[0][1]))].append(np.linalg.norm(atom[1] - partner[1]))\\n else:\\n atomdict[str(int(partner[0][1]))].append(np.linalg.norm(atom[1] - partner[1]))\\n atomdict[str(int(partner[0][1]))].sort()\\n\\n distlist.append(atomdict)\\n\\n return distlist\",\n \"def _distance_matrix(self):\\n\\n # Log the type of metric being used in Sequencing\\n logger.info('Using {} Distance'.format(self.measure))\\n\\n # Convert the nodal coordinate tuples to a np.array\\n coords = np.vstack(map(np.array, self.coords.values()))\\n \\n if self.measure == 'haversine':\\n # Partially applied haversine function that takes a coord and computes the vector distances for all coords\\n haversine = lambda coord: get_hav_distance(coords[:, 0], coords[:, 1], *coord) \\n # Map the partially applied function over all coordinates, and stack to a matrix\\n return np.vstack(map(haversine, coords))\\n\\n # Partially applied haversine function that takes a coord and computes the vector distances for all coords\\n euclidean = lambda coord: get_euclidean_dist(coords, coord)\\n # Map the partially applied function over all coordinates, and stack to a matrix\\n return np.vstack(map(euclidean, coords))\",\n \"def DistanceMatrices(self):\\r\\n return self._dms\",\n \"def compute_distances(Ls):\\n if not isinstance(Ls, list):\\n Ls = [Ls]\\n\\n dists = []\\n for L in Ls:\\n N,D = L.shape\\n # 1xNxD - Nx1xD (L1 distance)\\n dist = (np.abs(L[None,:,:] - L[:,None,:])).sum(axis=2)\\n dists.append(dist)\\n\\n return dists\",\n \"def __build_distance_matrix(self):\\n for i in range(0, len(self.__corpus)):\\n doc_i = self.__corpus[i]\\n for j in range(i + 1, len(self.__corpus)):\\n doc_j = self.__corpus[j]\\n distance = doc_i.calc_distance(doc_j)\\n self.__distance_matrix.append(distance)\",\n \"def distance(self, features, targets):\\n cost_matrix = np.zeros((len(targets), len(features)))\\n for i, target in enumerate(targets):\\n cost_matrix[i, :] = self._metric(self.samples[target], features)\\n return cost_matrix\",\n \"def distance(self, features, targets):\\n cost_matrix = np.zeros((len(targets), len(features)))\\n for i, target in enumerate(targets):\\n cost_matrix[i, :] = self._metric(self.samples[target], features)\\n return cost_matrix\",\n \"def get_distances(self):\\n N = len(self.cells) # Number of cells\\n distances = np.zeros([N, N]) # distances between cells\\n positions = self.position_matrix() # positions of cells \\n \\n # get distances between cells (exploit symmetry between upper and lower triangular form)\\n for i, position in enumerate(positions[:-1, :]): # Iterate matrix except the last one\\n directions = positions[i+1:, :] - position # direction from i to j > i\\n distances[i, i+1:] = np.linalg.norm(directions, axis=1) # length of directions\\n \\n return distances + distances.T # Add lower triangle of matrix to upper \",\n \"def compute_distances(self, X):\\n #print(X.shape, self.Xtr.shape)\\n dists = np.zeros((X.shape[0], self.Xtr.shape[0]))\\n for i in range(X.shape[0]):\\n X_r = np.tile(X[i], (self.Xtr.shape[0], 1))\\n dists[i] = np.sqrt(np.sum(np.square(self.Xtr - X_r), axis = 1))\\n #print(dists.shape)\\n return dists\",\n \"def calcDistance(self):\\n # Initialize the distance matrix\\n arr = np.repeat(0, self.num_col)\\n result_mat = np.repeat(arr, self.num_col)\\n result_mat = np.reshape(result_mat, (self.num_col, self.num_col))\\n trinary_mat = self.df_trinary.values\\n for left_val in TRINARY_VALUES:\\n left_func = lambda v: 1 if v==left_val else 0\\n left_mat = np.transpose(np.vectorize(left_func)(trinary_mat))\\n for right_val in TRINARY_VALUES:\\n if left_val == right_val:\\n continue\\n right_func = lambda v: 1 if v==right_val else 0\\n right_mat = np.vectorize(right_func)(trinary_mat)\\n # Count the number of occurrences of this combination of values\\n # by doing a matrix multiply\\n new_mat = np.matmul(left_mat, right_mat)\\n # Multiply by the squared distance between the values\\n squared_distance = (left_val - right_val)**2\\n new_mat = new_mat*squared_distance\\n # Accumulate the result\\n result_mat = result_mat + new_mat\\n # Convert to dataframe\\n result_mat = np.vectorize(lambda v: np.sqrt(v)) (result_mat)\\n self.df_distance = pd.DataFrame(result_mat, columns=self.columns,\\n index=self.columns)\",\n \"def distance_matrix(data):\\n D = numpy.zeros( (data.shape[0], data.shape[0]) )\\n for i in xrange(data.shape[0]):\\n for j in xrange(i):\\n D[i,j] = numpy.linalg.norm(data[i,:]-data[j,:])\\n D[j,i] = D[i,j]\\n\\n return D\",\n \"def _calculate_distances(self):\\n all_dists = []\\n for ref in range(len(self.atoms)):\\n if self.atoms[ref].symbol in self.exclude:\\n continue\\n indices = list(range(ref+1, len(self.atoms)))\\n indices = self._filter_excluded(indices)\\n if len(indices) == 0:\\n continue\\n dists = self.atoms.get_distances(ref, indices, mic=True)\\n all_dists += list(dists)\\n \\n # Normalize by the mean distance\\n return np.array(all_dists)/np.mean(all_dists)\",\n \"def _calc_distance(self, X):\\n distances = np.zeros((X.shape[0], self.n_clusters))\\n print(distances.shape)\\n for i, centroid in enumerate(self.centroids):\\n distances[:, i] = np.linalg.norm(X - centroid, axis=1)\\n return distances\",\n \"def getDistancesWithNames(twoDList):\\n matrix = []\\n for i in range(0,len(twoDList)):\\n for j in range(len(twoDList) - len(twoDList) + i):\\n SD = determineIdenticalBases(data[i][1], data[j][1])\\n temp = []\\n if SD[1] != 0:\\n p = calculateP(SD[0]+SD[1], SD[1])\\n temp.append(data[i][0])\\n temp.append(data[j][0]) \\n temp.append(estimateMutationsPerSite(p))\\n matrix.append(temp)\\n return matrix\",\n \"def getDistanceMatrix(self):\\n return self.pointcloud.distmat\",\n \"def _calc_distance_features(self):\\n d = ()\\n for dx, dy in DIRECTIONS:\\n if dx and dy:\\n d += (list(self.__calc_distance(direction_x=dx, direction_y=dy)), )\\n elif dx:\\n tmp, _, _ = self.__calc_distance(direction_x=dx, direction_y=dy)\\n d += (tmp, )\\n elif dy:\\n _, tmp, _ = self.__calc_distance(direction_x=dx, direction_y=dy)\\n d += (tmp, )\\n\\n self.dist_features = d\\n\\n self.direc_dist = self.__calc_direc_distance()\",\n \"def compute_distance(self, transpose=False):\\n\\n # Calculate distance matrix\\n if transpose:\\n distance_matrix = pdist(self.matrix.T, self.distance)\\n else:\\n distance_matrix = pdist(self.matrix, self.distance)\\n\\n # Remove NaNs\\n distance_matrix[np.isnan(distance_matrix)] = 1.0\\n\\n return distance_matrix\",\n \"def get_distance_matrix(self, points):\\n return points[:, :, np.newaxis, :]-points[:, np.newaxis, :, :]\",\n \"def test_distances_with_vector_input(self):\\n input_vector = self.vectors['dog.n.01']\\n distances = self.vectors.distances(input_vector, ['mammal.n.01', 'dog.n.01'])\\n self.assertTrue(np.allclose(distances, [4.5278745, 0]))\\n\\n distances = self.vectors.distances(input_vector)\\n self.assertEqual(len(distances), len(self.vectors.vocab))\\n self.assertTrue(np.allclose(distances[-1], 10.04756))\",\n \"def norm_dist(face_vectors, f_vector):\\n if len(face_vectors) == 0:\\n return np.empty((0))\\n return np.linalg.norm(face_vectors - f_vector, axis=1)\",\n \"def distance_matrix(d1, d2=None):\\n if d2 is None:\\n dists = np.zeros(shape=(d1.shape[0], d1.shape[0]))\\n for i in range(dists.shape[0]):\\n dists[i] = (((d1 - d1[i]) ** 2).sum(axis=1)) ** 0.5\\n else:\\n dists = np.zeros(shape=(d1.shape[0], d2.shape[0]))\\n for i in range(d1.shape[0]):\\n dists[i] = (((d2 - d1[i]) ** 2).sum(axis=1)) ** 0.5\\n return dists\",\n \"def distances(self):\\n self._sort_measurements()\\n return self._distances\",\n \"def calcDistanceList(work_list):\\n distance_list = []\\n for swap in work_list: # for every work item find distance\\n distance_list.append(Cluster.calcDistance(*swap))\\n return distance_list\",\n \"def distances(self):\",\n \"def nm_dist_mat(self):\\n mat = np.zeros([self.N, self.M])\\n for n in range(self.N):\\n for m in range(self.M):\\n mat[n, m] = distance(self.N_coords[n], self.M_coords[m])\\n return mat\",\n \"def distance_matrix(sunspots1, sunspots2):\\n \\n N1 = len(sunspots1)\\n N2 = len(sunspots2)\\n\\n distance_matrix = np.zeros((N1, N2))\\n\\n for i in list(range(N1)):\\n for j in list(range(N2)):\\n\\n distance_matrix[i, j] = euclidean_dist(sunspots1[i], sunspots2[j])\\n\\n return distance_matrix\",\n \"def DistanceMatrices(self, dms):\\r\\n if not isinstance(dms, ListType):\\r\\n raise TypeError(\\\"The item passed in as the new list was not a \\\"\\r\\n \\\"list data type.\\\")\\r\\n if self._num_dms >= 0 and len(dms) != self._num_dms:\\r\\n raise ValueError(\\\"Cannot set %d distance matrices. Must provide \\\"\\r\\n \\\"exactly %d distance matrices.\\\" % (len(dms),\\r\\n self._num_dms))\\r\\n for dm in dms:\\r\\n if not isinstance(dm, DistanceMatrix):\\r\\n raise TypeError(\\r\\n 'Invalid type (%s); expected DistanceMatrix' %\\r\\n dm.__class__.__name__)\\r\\n if self._min_dm_size >= 0 and dm.shape[0] < self._min_dm_size:\\r\\n raise ValueError(\\\"Distance matrix of size %dx%d is smaller \\\"\\r\\n \\\"than the minimum allowable distance matrix \\\"\\r\\n \\\"size of %dx%d for this analysis.\\\" %\\r\\n (dm.shape[0], dm.shape[0], self._min_dm_size,\\r\\n self._min_dm_size))\\r\\n self._dms = dms\",\n \"def getDistanceMatrix(self):\\n return self.distmat.as_matrix()\",\n \"def _derive_euclidean_dm(self, cat_mat, dim):\\r\\n res_mat = []\\r\\n\\r\\n for i in range(dim):\\r\\n res_mat.append([0 for k in range(dim)])\\r\\n for j in range(i):\\r\\n res_mat[i][j] = self._vector_dist(cat_mat[i], cat_mat[j])\\r\\n res_mat[j][i] = res_mat[i][j]\\r\\n\\r\\n return DistanceMatrix(res_mat, self.DistanceMatrices[0].ids)\",\n \"def test_distance(self):\\n self.assertTrue(np.allclose(self.vectors.distance('dog.n.01', 'mammal.n.01'), 4.5278745))\\n self.assertEqual(self.vectors.distance('dog.n.01', 'dog.n.01'), 0)\",\n \"def Dvec(self):\\n return vec(-self.distance)\",\n \"def distance_unsafe(self, *mass_functions):\\n #Submethod to get distance between self and one mass function:\\n def distance_one_mass(mass_function):\\n #Get the jaccard index matrix:\\n difference = self.difference_unsafe(mass_function)\\n matrix = {}\\n for e1 in difference:\\n matrix[e1] = {}\\n for e2 in difference:\\n if (not e1.is_empty()) or (not e2.is_empty()):\\n matrix[e1][e2] = e1.conjunction_unsafe(e2).cardinal / e1.disjunction_unsafe(e2).cardinal\\n else:\\n matrix[e1][e2] = 1\\n \\n #Compute the distance as sqtr(0.5 * diffT * matrix * diff):\\n distance = 0\\n temp = {}\\n for e1 in difference:\\n temp[e1] = 0\\n for e2 in difference:\\n temp[e1] += difference[e2] * matrix[e1][e2]\\n for e1 in difference:\\n distance += temp[e1] * difference[e1]\\n return math.sqrt(0.5 * distance)\\n\\n #Get the distance between self and the provided set of mass functions:\\n distance = 0\\n for mass_function in mass_functions:\\n distance += distance_one_mass(mass_function)\\n return round(distance / len(mass_functions), 6)\",\n \"def compute_distances(self, X):\\n num_test = X.shape[0]\\n num_train = self.X_train.shape[0]\\n dists = np.zeros((num_test, num_train))\\n \\n sum_test_square = np.sum(np.square(X), axis=1).reshape(-1, 1)\\n sum_train_square = np.sum(np.square(self.X_train), axis=1).reshape(-1, 1)\\n product_test_train = X @ self.X_train.T\\n \\n sum_test_square = np.repeat(sum_test_square, num_train, axis=1)\\n sum_train_square = np.repeat(sum_train_square, num_test, axis=1).T\\n \\n dists_square = sum_test_square - 2 * product_test_train + sum_train_square\\n \\n dists = np.sqrt(dists_square)\\n \\n return dists\",\n \"def test_distances(self):\\n distances = self.vectors.distances('dog.n.01', ['mammal.n.01', 'dog.n.01'])\\n self.assertTrue(np.allclose(distances, [4.5278745, 0]))\\n\\n distances = self.vectors.distances('dog.n.01')\\n self.assertEqual(len(distances), len(self.vectors.vocab))\\n self.assertTrue(np.allclose(distances[-1], 10.04756))\",\n \"def distance_matrix(dnas: Collection[str], metric=hamming_distance, relative=True, as_ndarray=False):\\n n = len(dnas)\\n result = [[0] * n for _ in range(n)]\\n for pair in itertools.combinations(zip(range(n), dnas), r=2):\\n (idx1, dna1), (idx2, dna2) = pair\\n distance = metric(dna1, dna2)\\n distance = distance / max(len(dna1), len(dna2)) if relative else distance\\n result[idx1][idx2] = distance\\n result[idx2][idx1] = distance\\n if as_ndarray:\\n result = np.asarray(result)\\n return result\",\n \"def calc_dist_matrix(self,verbose=False):\\n\\n print(\\\"Calculating distance matrix.\\\"); sys.stdout.flush()\\n\\n nrow = self.data_vector.shape[0]\\n self.dist_matrix = np.zeros((nrow, nrow),dtype=float)\\n for i in range(nrow):\\n if verbose:\\n if i % 1000 == 0:\\n print(\\\"Row\\\",i,\\\"of\\\",nrow)\\n sys.stdout.flush()\\n\\n for j in range(i + 1, nrow):\\n self.dist_matrix[i,j] = self._pairwise_dist(self.data_vector[i],self.data_vector[j])\\n self.dist_matrix[j,i] = self.dist_matrix[i,j]\\n \\n self.dist_frame = pd.DataFrame(self.dist_matrix,\\n index = self.seq_strings,\\n columns = self.seq_strings)\",\n \"def calc_dist_matrix(self):\\n\\n self.dist_matrix = spatial.distance.squareform(spatial.distance.pdist(self.data_vector,metric=\\\"hamming\\\"))\\n\\n self.dist_frame = pd.DataFrame(self.dist_matrix,\\n index = self.seq_strings,\\n columns = self.seq_strings)\",\n \"def distance_matrix(cities):\\n\\n return [[city1.distance(city2) for city2 in cities]\\n for city1 in cities]\",\n \"def distance(self, *mass_functions):\\n #Submethod to get distance between self and one mass function:\\n def distance_one_mass(mass_function):\\n #Get the jaccard index matrix:\\n difference = self.difference(mass_function)\\n matrix = {}\\n for e1 in difference:\\n matrix[e1] = {}\\n for e2 in difference:\\n if (not e1.is_empty()) or (not e2.is_empty()):\\n matrix[e1][e2] = e1.conjunction(e2).cardinal / e1.disjunction(e2).cardinal\\n else:\\n matrix[e1][e2] = 1\\n \\n #Compute the distance as sqtr(0.5 * diffT * matrix * diff):\\n distance = 0\\n temp = {}\\n for e1 in difference:\\n temp[e1] = 0\\n for e2 in difference:\\n temp[e1] += difference[e2] * matrix[e1][e2]\\n for e1 in difference:\\n distance += temp[e1] * difference[e1]\\n return math.sqrt(0.5 * distance)\\n\\n #Get the distance between self and the provided set of mass functions:\\n distance = 0\\n for mass_function in mass_functions:\\n distance += distance_one_mass(mass_function)\\n return round(distance / len(mass_functions), 6)\",\n \"def get_distance(list1, list2):\\n import math\\n distance_result = (list1[0] - list2[0]) ** 2 + (list1[1] - list2[1]) ** 2 + (list1[2] - list2[2]) ** 2\\n return math.sqrt(abs(distance_result))\",\n \"def __surface_distances(result, reference, voxelspacing=None, connectivity=1):\\n result = np.atleast_1d(result.astype(np.bool))\\n reference = np.atleast_1d(reference.astype(np.bool))\\n if voxelspacing is not None:\\n voxelspacing = _ni_support._normalize_sequence(voxelspacing, result.ndim)\\n voxelspacing = np.asarray(voxelspacing, dtype=np.float64)\\n if not voxelspacing.flags.contiguous:\\n voxelspacing = voxelspacing.copy()\\n \\n # binary structure\\n footprint = generate_binary_structure(result.ndim, connectivity)\\n \\n # test for emptiness\\n if 0 == np.count_nonzero(result): \\n raise RuntimeError('The first supplied array does not contain any binary object.')\\n if 0 == np.count_nonzero(reference): \\n raise RuntimeError('The second supplied array does not contain any binary object.') \\n \\n # extract only 1-pixel border line of objects\\n result_border = result ^ binary_erosion(result, structure=footprint, iterations=1)\\n\\n reference_border = reference ^ binary_erosion(reference, structure=footprint, iterations=1)\\n\\n dt = distance_transform_edt(~reference_border, sampling=voxelspacing)\\n # print(dt)\\n reference_border = (reference_border + 0).astype(np.float32)\\n\\n sds = dt[result_border]\\n \\n return sds\",\n \"def test_vector_distance(self):\\n\\n # Example 1.2\\n vector_p = np.array([0.5, 0.0, 0.5])\\n vector_q = np.array([0.5, 0.5, 0.0])\\n crystal = crystal_system.Tetragonal(0.5, 1.0)\\n d_ref_nm = np.sqrt(5.0)/4.0\\n\\n g_ij_nm2 = crystal.gij_nm2\\n\\n vector_d = vector_p - vector_q\\n d_nm = vector.distance(crystal, vector_d, vector_d)\\n\\n self.assertAlmostEqual(d_ref_nm, d_nm, 5)\\n\\n #self.fail(\\\"Test if the testcase is working.\\\")\",\n \"def distance(self, X, Mu):\\r\\n # Reshape X to N x 1 x D to enable broadcasting\\r\\n X_reshaped = tf.reshape(X, (-1, 1, X.shape[-1]))\\r\\n\\r\\n # subtraction is performed on the last two dimensions of X_reshaped\\r\\n # X_reshaped(N stack, 1 x D) - Mu(K x D) => (N stack, K x D)\\r\\n # norm(N stack, K x D) => (N stack, K)\\r\\n return tf.reduce_sum(tf.square(X_reshaped - Mu), axis=-1)\",\n \"def distance_dmc(distances, Ks, points):\\n doors = []\\n for d in distances:\\n dmc = []\\n for k in Ks:\\n print \\\"==========================\\\", k, \\\"==========================\\\"\\n clusters = create_clusters(25, k)\\n\\n kmeans(points, clusters)\\n # print \\\"Finished creating kmeans algorithm\\\"\\n\\n create_backbone_network(GRAPH, clusters, d)\\n # print \\\"Finished creating backbone network\\\"\\n\\n find_all_shortest_paths(clusters, SP_TABLE, GRAPH)\\n # print \\\"Finished finding all shortest paths\\\"\\n\\n for clst in clusters:\\n clst.inter_cost = inter_cost(clst)\\n clst.intra_cost = intra_cost(points, clst)\\n clst.dm_cost = door_matt_cost(clusters, clst, SP_TABLE)\\n\\n ret = total_cost(clusters)\\n dmc.append(ret[2])\\n doors.append(sum(dmc))\\n draw_door_matts(map(lambda d: float(format(d, \\\".4g\\\")), distances), doors)\",\n \"def distances(self) -> ndarray:\\n return self._distances\",\n \"def compute_distances_one_loop(self, X):\\n num_test = X.shape[0]\\n num_train = self.X_train.shape[0]\\n dists = np.zeros((num_test, num_train))\\n for i in range(num_test):\\n dists[i, :] = np.sqrt(np.sum(np.square(X[i, :] - self.X_train), axis=1)).transpose()\\n return dists\",\n \"def _calculate_distance(self, ordered_list):\\r\\n\\r\\n total_distance = 0\\r\\n previous_point = None\\r\\n for point in ordered_list:\\r\\n if previous_point is not None:\\r\\n angle, distance = previous_point.angleAndDistanceTo(point) # geodesic distance in meters\\r\\n total_distance += distance\\r\\n previous_point = point\\r\\n\\r\\n return total_distance\",\n \"def compute_distance(self):\\n loc = np.extend_dims(self.state[:, :, Boids.Attr.LOC], axis=-1)\\n m = np.tile(loc, (1, 1, self.num_boids))\\n pos_diff = m-m.transpose(0, 2, 1)\\n self.distance = np.linalg.norm(pos_diff, axis=0)\",\n \"def compute_derivs_matrices(vecs, adv_vecs, dt):\\n return (adv_vecs - vecs)/(1.*dt)\",\n \"def dist_matrix(self):\\n return self.__dist_matrix\",\n \"def get_distances(self, crds):\\n self.all_dist = np.zeros((self.natom, self.natom))\\n # Loop over upper triangle of atom pairs\\n for iat in range(self.natom-1):\\n # Get the atom indices\\n at_inds = np.arange(len(crds))\\n\\n # Calc distances between atoms (only upper triangle though)\\n at_msk = at_inds > iat\\n all_ut_dist = crds[at_msk] - crds[iat]\\n all_ut_dist = np.linalg.norm(all_ut_dist, axis=1)\\n\\n self.all_dist[iat, iat+1:] = all_ut_dist\\n\\n # Get lower triangle indices\\n self.all_dist = self.all_dist + self.all_dist.T\",\n \"def _get_distances(self):\\n for molecule in self.values():\\n molecule.get_distances()\\n\\n # for atom in self.atoms:\\n # atom.get_distances()\",\n \"def get_distance_matrix(self):\\n names = self.get_named_leaves()\\n num_names = len(names)\\n dist_mat = np.zeros((num_names, num_names), dtype='float')\\n for i, j in itertools.combinations(range(num_names), 2):\\n node1, node2 = self.node_names[names[i]], self.node_names[names[j]]\\n dist = self.node_distance(node1, node2)\\n dist_mat[i,j] = dist\\n dist_mat[j,i] = dist\\n return names, dist_mat\",\n \"def get_correct_distance_matrix(L):\\n n = len(L)\\n D = np.zeros((n,n))\\n for i in range(n):\\n for j in range(n):\\n if i != j:\\n D[i][j] = get_minor(L, [i, j], [i, j]) / get_minor(L, [i], [i])\\n return D\",\n \"def test_poincare_distances_batch(self):\\n vector_1 = self.vectors['dog.n.01']\\n vectors_2 = self.vectors[['mammal.n.01', 'dog.n.01']]\\n distances = self.vectors.vector_distance_batch(vector_1, vectors_2)\\n self.assertTrue(np.allclose(distances, [4.5278745, 0]))\",\n \"def distancematrix(vec1, vec2):\\n v1, v2 = np.meshgrid(vec1, vec2)\\n return np.abs(v1 - v2)\",\n \"def measure_distance(self, mat):\\n if len(mat) == 1:\\n print(\\\"chain has only one CAatom\\\")\\n return\\n self.dists = []\\n for num in range(0, len(mat)):\\n if num + 1 <= len(mat) - 1:\\n c1 = mat[num]\\n c2 = mat[num + 1]\\n d = c2 - c1\\n self.dists.append(math.sqrt(np.sum(d * d)))\\n return self.dists\",\n \"def calculateDistances(df):\\n return\",\n \"def getDistanceMatrix(self, alignedSequences):\\n\\t\\tif not alignedSequences:\\n\\t\\t\\traise ValueError(\\\"alignedSequences must not be empty\\\")\\n\\t\\tdominantAlignedSequence = alignedSequences[0]\\n\\t\\tsubdominantAlignedSequences = alignedSequences[1:]\\n\\t\\tdistanceMatrix = []\\n\\t\\tfor seq in subdominantAlignedSequences:\\n\\t\\t\\tdistanceMatrix.append(len(seq) - self._getNumberOfSpaces(seq) - self._getNumberOfAlignedNucleotides(dominantAlignedSequence, seq))\\n\\t\\treturn distanceMatrix\",\n \"def _calc_distances(preds, targets, mask, normalize):\\n N, K, _ = preds.shape\\n _mask = mask.copy()\\n _mask[np.where((normalize == 0).sum(1))[0], :] = False\\n distances = np.full((N, K), -1, dtype=np.float32)\\n normalize[np.where(normalize <= 0)] = 1000000.0\\n distances[_mask] = np.linalg.norm(((preds - targets) / normalize[:, None, :])[_mask], axis=-1)\\n return distances.T\",\n \"def calcEuclideanDistance(d1, d2):\\n #initiate empty list\\n result = []\\n #for each index in the list, each position in both list minus each other\\n #and to the power of two. Add this in the result list\\n for idx in range(len(d1)):\\n result.append((d1[idx]-d2[idx])**2)\\n\\n #Return the square of the sum of all values in the result list\\n return math.sqrt(sum(result))\",\n \"def get_distance_metrics():\\n\\n return [HausdorffDistance(),\\n AverageDistance(),\\n MahalanobisDistance(),\\n VariationOfInformation(),\\n GlobalConsistencyError(),\\n ProbabilisticDistance()]\",\n \"def calculate_distances(train_data, test_datum):\\n n = train_data.shape[0]\\n dist = []\\n for i in range(n):\\n distance = np.sqrt(np.sum(np.square(train_data[i]-test_datum)))\\n dist.append(distance)\\n dist = np.asarray(dist)\\n return dist\",\n \"def build_homes_matrix(self, homes_list):\\n\\n # Matrix that contains every home and the duration it takes to get to every other home in the list\\n homes_matrix = []\\n\\n # Loop through every home in the list\\n # And create a list of the times between this home and the other homes\\n for home in homes_list:\\n home_distances = []\\n\\n # Only let them do driving\\n commute_type = CommuteType.objects.get_or_create(commute_type=CommuteType.DRIVING)[0]\\n\\n # Depending on the accuracy either get the exact commute or the approximate\\n if self.commute_accuracy == CommuteAccuracy.EXACT:\\n result_distance_wrapper = retrieve_exact_commute_client_scheduler(homes_list, [home], commute_type)\\n for commute in result_distance_wrapper:\\n time_seconds = commute[0][0]\\n distance_meters = commute[0][1]\\n if time_seconds is not None and distance_meters is not None:\\n home_distances.append(time_seconds)\\n else:\\n home_distances.append(math.inf)\\n else:\\n update_commutes_cache_client_scheduler(homes_list,\\n home,\\n accuracy=CommuteAccuracy.APPROXIMATE,\\n commute_type=CommuteType.DRIVING)\\n home_distances = retrieve_approximate_commute_client_scheduler(homes_list,\\n home,\\n commute_type=CommuteType.DRIVING)\\n\\n homes_matrix.append(home_distances)\\n\\n return homes_matrix\",\n \"def DM(self, masses=None):\\n N = len(self.diameters)\\n rs = self.rs\\n d = self.ndim\\n M = np.zeros((d * N, d * N))\\n\\n for i in range(N):\\n sigi = self.diameters[i]\\n for j in range(i):\\n rijvec = rs[i, :] - rs[j, :]\\n rijvec = rijvec - np.around(rijvec)\\n rijsq = np.sum(rijvec**2)\\n dij = (sigi + self.diameters[j]) / 2\\n dijsq = dij**2\\n if rijsq < dijsq:\\n rij = np.sqrt(rijsq)\\n rijouter = np.outer(rijvec, rijvec)\\n # U(r) = ½(1 - r/d)²\\n # d²U/dxdy = (dr/dx)(dr/dy)/d² - (1 - r/d)(d²r/dxdy)/d\\n # dr/dx = x/r\\n # d²r/dxdy = -(x y) / r³\\n # d²U/dxdy = -(x y)/(r² d²) + (1 - r/d)((x y)/r²)/(d r)\\n # d²U/dx² = (dr/dx)²/d² - (1 - r/d)(d²r/dx²)/d\\n # d²r/dx² = -x² / r³ + 1/r\\n # d²U/dxᵢdxⱼ = -(xᵢ xⱼ)/(r² d²) + (1 - r/d)((xᵢ xⱼ)/r² -\\n # δᵢⱼ)/(d r)\\n\\n Mij1 = -rijouter / rijsq / dijsq\\n Mij2 = (1 - rij / dij) * \\\\\\n (rijouter / rijsq - np.eye(d)) / rij / dij\\n Mij = Mij1 + Mij2\\n\\n M[d * i:d * i + d, d * j:d * j + d] = Mij\\n M[d * j:d * j + d, d * i:d * i + d] = Mij\\n M[d * i:d * i + d, d * i:d * i + d] -= Mij\\n M[d * j:d * j + d, d * j:d * j + d] -= Mij\\n\\n np.divide(M, self.L**2, out=M)\\n if masses is None:\\n return M\\n\\n # TODO: is the mass part of this really part of this?\\n marr = np.array(masses)\\n assert np.shape(masses) == np.shape(self.diameters)\\n marr = np.array([masses] * d)\\n marr = marr.T.flatten()\\n # marr is now [m1,m1,m2,m2,...] (in 2D)\\n mm = np.eye(d * N)\\n np.multiply(mm, marr**-.5, out=mm)\\n # mm is now M^-½, where M is the mass matrix\\n\\n mm.dot(M, out=M)\\n M.dot(mm, out=M)\\n return M\",\n \"def distancePairs(self):\\n return spsd.squareform(spsd.pdist(self.coordinates()))\",\n \"def face_distance(face_encodings, face_to_compare):\\n if len(face_encodings) == 0:\\n return np.empty((0))\\n\\n #return 1/np.linalg.norm(face_encodings - face_to_compare, axis=1)\\n return np.sum(face_encodings*face_to_compare,axis=1)\",\n \"def compute_distance(X, K_clusters):\\n dis = np.linalg.norm((X-K_clusters),2,axis=1)**2\\n return dis\",\n \"def compute_pairwise_distances(input_vecs: types.Tensor) -> types.Tensor:\\n r = tf.reduce_sum(input_vecs * input_vecs, axis=1, keepdims=True)\\n pdistance_matrix = (\\n r\\n - 2 * tf.matmul(input_vecs, input_vecs, transpose_b=True)\\n + tf.transpose(r)\\n )\\n return tf.cast(pdistance_matrix, dtype=tf.float32)\",\n \"def F(self, distances):\\n return np.sum(self.F_mat(distances), 1)\",\n \"def get_distance_vector(catchpoints, closest):\\n\\n deg_rad = math.pi / 180\\n \\n dphis = catchpoints[:, 1] - closest[:, 1]\\n phims = 0.5 * (catchpoints[:, 1] + closest[:, 1])\\n dlams = catchpoints[:,0] - closest[:,0]\\n\\n k1s = (111.13209 - 0.56605 * numpy.cos(2 * phims * deg_rad) + \\n 0.00120 * numpy.cos(4 * phims * deg_rad))\\n k2s = (111.41513 * numpy.cos(phims * deg_rad) - 0.09455 * \\n numpy.cos(3 * phims * deg_rad) + 0.0012 * \\n numpy.cos(5 * phims * deg_rad))\\n \\n return numpy.sqrt(k1s**2 * dphis**2 + k2s**2 * dlams**2)\",\n \"def _location_distances(self, positions) -> torch.Tensor:\\n diff = positions[..., None, :, :] - positions[..., None, :]\\n distances = torch.norm(diff, dim=3)\\n return distances\",\n \"def calculate_vectors(self, spectrum_list: List[Spectrum]) -> np.ndarray:\\n n_rows = len(spectrum_list)\\n reference_vectors = np.empty(\\n (n_rows, self.output_vector_dim), dtype=\\\"float\\\")\\n binned_spectrums = self.model.spectrum_binner.transform(spectrum_list, progress_bar=self.progress_bar)\\n for index_reference, reference in enumerate(\\n tqdm(binned_spectrums,\\n desc='Calculating vectors of reference spectrums',\\n disable=(not self.progress_bar))):\\n reference_vectors[index_reference, 0:self.output_vector_dim] = \\\\\\n self.model.base.predict(self._create_input_vector(reference), verbose=0)\\n return reference_vectors\",\n \"def test_euclidean_distance_Ndimension(self):\\n\\n self.assertEqual(15, euclidean_distance([0, 0, 0], [10, 10, 5]))\\n self.assertEqual(15, euclidean_distance([0, 0, 0], [-10, -10, -5]))\\n\\n self.assertEqual(17, euclidean_distance([0, 0, 0, 0], [10, 10, 8, 5]))\\n self.assertEqual(17, euclidean_distance([0, 0, 0, 0], [-10, -10, -8, -5]))\\n\\n self.assertEqual(8, euclidean_distance([0, 0, 0, 0, 0], [5, 1, 1, 1, 6]))\\n self.assertEqual(8, euclidean_distance([0, 0, 0, 0, 0], [-5, -1, -1, -1, -6]))\",\n \"def test_distances(self):\\n sf = make_classifier_data(n=10, d=2, seed=37)\\n sf.remove_column(\\\"class\\\", inplace=True)\\n\\n numeric_features = [\\\"int0\\\", \\\"int1\\\", \\\"float0\\\", \\\"float1\\\"]\\n array_features = [\\\"array0\\\"]\\n string_features = [\\\"str0\\\"]\\n dict_features = [\\\"dict0\\\"]\\n\\n ## Numeric standard distances should work for numeric columns\\n for d in [\\n \\\"euclidean\\\",\\n \\\"squared_euclidean\\\",\\n \\\"manhattan\\\",\\n \\\"cosine\\\",\\n \\\"transformed_dot_product\\\",\\n ]:\\n try:\\n m = tc.dbscan.create(\\n sf,\\n features=numeric_features,\\n distance=d,\\n radius=1,\\n min_core_neighbors=3,\\n verbose=False,\\n )\\n except:\\n assert False, \\\"Standard distance {} failed.\\\".format(d)\\n\\n ## Numeric standard distances should work for array columns\\n for d in [\\n \\\"euclidean\\\",\\n \\\"squared_euclidean\\\",\\n \\\"manhattan\\\",\\n \\\"cosine\\\",\\n \\\"transformed_dot_product\\\",\\n ]:\\n try:\\n m = tc.dbscan.create(\\n sf,\\n features=array_features,\\n distance=d,\\n radius=1,\\n min_core_neighbors=3,\\n verbose=False,\\n )\\n except:\\n assert False, \\\"Standard distance {} failed.\\\".format(d)\\n\\n ## String standard distances should work.\\n for d in [\\\"levenshtein\\\"]:\\n try:\\n m = tc.dbscan.create(\\n sf,\\n features=string_features,\\n distance=d,\\n radius=1,\\n min_core_neighbors=3,\\n verbose=False,\\n )\\n except:\\n assert False, \\\"Standard distance {} failed.\\\".format(d)\\n\\n ## Dictionary standard distances should work.\\n for d in [\\\"jaccard\\\", \\\"weighted_jaccard\\\", \\\"cosine\\\", \\\"transformed_dot_product\\\"]:\\n try:\\n m = tc.dbscan.create(\\n sf,\\n features=dict_features,\\n distance=d,\\n radius=1,\\n min_core_neighbors=3,\\n verbose=False,\\n )\\n except:\\n assert False, \\\"Standard distance {} failed.\\\".format(d)\\n\\n # Nonsensical combinations of feature types and distances should fail.\\n with self.assertRaises(ValueError):\\n m = tc.dbscan.create(\\n sf,\\n features=numeric_features,\\n distance=\\\"levenshtein\\\",\\n radius=1,\\n min_core_neighbors=3,\\n verbose=False,\\n )\\n\\n with self.assertRaises(ToolkitError):\\n m = tc.dbscan.create(\\n sf,\\n features=dict_features,\\n distance=\\\"levenshtein\\\",\\n radius=1,\\n min_core_neighbors=3,\\n verbose=False,\\n )\\n\\n with self.assertRaises(ToolkitError):\\n m = tc.dbscan.create(\\n sf,\\n features=string_features,\\n distance=\\\"euclidean\\\",\\n radius=1,\\n min_core_neighbors=3,\\n verbose=False,\\n )\\n\\n # If no distance is specified, the automatic distance construction\\n # should kick in and be correct.\\n correct_dist = [\\n [[\\\"str0\\\"], \\\"levenshtein\\\", 1],\\n [[\\\"str1\\\"], \\\"levenshtein\\\", 1],\\n [[\\\"dict0\\\"], \\\"jaccard\\\", 1],\\n [[\\\"int0\\\", \\\"int1\\\", \\\"float0\\\", \\\"float1\\\"], \\\"euclidean\\\", 1],\\n [[\\\"array0\\\"], \\\"euclidean\\\", 1],\\n ]\\n\\n m = tc.dbscan.create(\\n sf, radius=1, distance=None, min_core_neighbors=3, verbose=False\\n )\\n\\n self.assertItemsEqual(m.distance, correct_dist)\\n\\n m = tc.dbscan.create(\\n sf, radius=1, distance=\\\"auto\\\", min_core_neighbors=3, verbose=False\\n )\\n self.assertItemsEqual(m.distance, correct_dist)\",\n \"def compute_distance (uVector, uOther):\\n ## since each element can be either 0 or 1,\\n ## no need for square roots and pow\\n d = 0\\n for i in range (len(uVector)):\\n d = d + math.pow((int(uVector [i]) - int(uOther [i])), 2)\\n\\n return d\",\n \"def distance(self,m,n):\\n if type(m) == np.ndarray:\\n return np.linalg.norm( self.positions[m] - self.positions[n] , axis = 1)\\n \\n return np.linalg.norm(self.positions[m]-self.positions[n])\",\n \"def getDistanceM(self, test, train):\\n p = 2 # TUNE currently euclidian distance\\n distanceM = pd.DataFrame(index=test.index.values, columns=train.index.values)\\n for testrow, testing in test.iterrows():\\n for trainrow, training in train.iterrows():\\n tot = 0\\n for indexc, column in test.iteritems():\\n #print(indexc)\\n if indexc in self.discrete: # need to reference VDM\\n datapoint = self.VDMdict.get(indexc)\\n dif = datapoint[testing[indexc]][training[indexc]]\\n elif indexc != \\\"class\\\": #get distance beween 2 points\\n dif = abs(float(testing[indexc]) - float(training[indexc]))\\n\\n tot += dif ** p\\n distance = tot ** (1 / p) #distance is calculated\\n distanceM.at[testrow, trainrow] = distance #put in distance matrix\\n return(distanceM)\",\n \"def get_dist_mat(self):\\n n_site = self.status.give(keyword=\\\"n_site\\\")\\n sites = self.status.give(keyword=\\\"sites\\\")\\n dist_mat = [[0.0 for j in xrange(n_site)] for i in xrange(n_site)]\\n for i in xrange(n_site):\\n for j in xrange(n_site):\\n ri = sites[i].pos\\n rj = sites[j].pos\\n dist_mat[i][j] = np.linalg.norm(ri-rj)\\n # print ri, rj\\n return dist_mat\",\n \"def get_distance(positions: np.ndarray, position: np.ndarray, unit_factor: np.ndarray = None):\\n\\n if unit_factor is None:\\n unit_factor = np.array([1, 1, 1])\\n\\n distances = np.sqrt(np.sum(((positions - position) * unit_factor.reshape(1, 3)) ** 2, axis=1))\\n\\n return distances\",\n \"def face_distance(face_encodings, face_to_compare):\\n if len(face_encodings) == 0:\\n return np.empty((0))\\n\\n return np.linalg.norm(face_encodings - face_to_compare, axis=1)\",\n \"def squared_distance_matrix(X, augmented=False):\\n XX = np.dot(X,X.T)\\n D = np.outer(np.diag(XX), np.ones(len(X)))-2*XX+np.outer(np.ones(len(X)),\\n np.diag(XX))\\n if augmented == True:\\n n = len(D)\\n zeros_v = np.zeros((n,1))\\n zeros_h = np.zeros((1,n+1))\\n D = np.bmat('D zeros_v; zeros_h')\\n return D\",\n \"def F_mat(self, distances):\\n distances_norm2 = norm2(distances)\\n distances_norm = np.sqrt(distances_norm2)\\n isColliding = self.isColliding(distances_norm)[:, :, :, None]\\n\\n # Repulsion force when a collision happens\\n f_colliding = (2/self.d_coll**2)*isColliding\\n \\n # Interaction force\\n ident = np.identity(np.shape(distances)[1])[None, :, :]\\n d = (ident+distances_norm)\\n dn = (d**self.n)[:, :, :, None]\\n d2 = (ident+distances_norm2)\\n d2n = (d2**(self.n+1))[:, :, :, None]\\n\\n f_interact = self.n*self.d_attr**self.n*(self.d_attr**self.n-dn)/(d2n + 10e-50)*(1-isColliding)\\n\\n # Total Force\\n f = (f_colliding + f_interact)*distances\\n\\n # Remove self-interaction\\n diag = np.einsum('ijj->ij', f[:, :, :, 0])\\n diag[:, :] = 0\\n\\n diag2 = np.einsum('ijj->ij', f[:, :, :, 1])\\n diag2[:, :] = 0\\n\\n return f\",\n \"def test_cmatrix_list(self):\\n\\n test_dtraj = [np.array([0, 1, 1, 0, 0, 0, 1, 1, 1, 1]), \\\\\\n np.array([0,1,1,1,0])]\\n\\n cmatrix_compare = np.array([[2., 3.], [2., 6.]])\\n cmatrix_computed = cmatrix(test_dtraj)\\n self.assertTrue(np.allclose(cmatrix_compare, cmatrix_computed))\",\n \"def cal_dis(data,Cen,dis=\\\"Euclidean\\\"):\\n dis = []\\n for i in range(len(data)):\\n dis.append([])\\n for j in range(len(Cen)):\\n dd = math.sqrt(sum(map(lambda x:x**2,data[i]-Cen[j])))\\n dis[i].append(dd)\\n \\n return dis\",\n \"def _computeDistances(self) -> None:\\n length = len(self.data)\\n for i, sequenceOne in enumerate(self.data):\\n print(f\\\"[SeqCluBaselineOffline] Computing distances is at iteration {i} of {length}.\\\")\\n for j, sequenceTwo in enumerate(self.data):\\n if i == j:\\n self.distances[i][j] = 0\\n continue\\n distance = self.distanceMeasure.calculateDistance(sequenceOne, sequenceTwo)\\n self.distances[i][j] = distance\\n self.distances[j][i] = distance\",\n \"def _object_distance(self, object1, object2):\\n return np.linalg.norm(np.array(object1) - np.array(object2))\",\n \"def test_distance(self):\\n for emb_vals, point, dist_gt in self.DISTANCE_EXAMPLES:\\n print(emb_vals, point, dist_gt)\\n emb = to_emb(emb_vals)\\n dist = emb.distance(point)\\n assert np.allclose(dist, dist_gt), \\\\\\n (\\\"Wrong distance for point {}: expected {} but was {};\\\"\\n \\\"\\\\nembedding:\\\\n{}\\\").format(point, dist_gt, dist, str(emb))\",\n \"def compute_distance(df):\\n pass\",\n \"def get_distance ( self, X: np.ndarray, x0: np.ndarray ):\\n \\n # Apply distance_function across rows of X\\n return [ self.distance_function ( row, x0 ) for row in X ]\\n # End get_distance()\",\n \"def distance(self, vector1, vector2):\\n\\t\\tsum_sq = 0\\n\\t\\tfor i in range(28):\\n\\t\\t\\tfor j in range(28):\\n\\t\\t\\t\\tsum_sq += (vector1[i][j] - vector2[i][j])**2\\n\\t\\treturn math.sqrt(sum_sq)\",\n \"def return_energy_mat(grid, objects_list, choice_parallelization):\\n assert len(grid.shape) == 1, \\\"energy distance can only be applied on 1D objects\\\"\\n\\n n_obj = len(objects_list)\\n n_pix = len(grid)\\n distance_matrix = numpy.zeros((n_obj, n_obj))\\n\\n if choice_parallelization == True:\\n master_index_list = []\\n for i in range(n_obj):\\n for j in range(i+1, n_obj):\\n master_index_list.append([i, j])\\n\\n num_cores = multiprocessing.cpu_count()\\n results = Parallel(n_jobs=num_cores)(delayed(energy_simple_1D)(grid, objects_list, i) for i in master_index_list)\\n\\n for i_pair in range(len(results)):\\n i = master_index_list[i_pair][0]\\n j = master_index_list[i_pair][1]\\n distance_matrix[i, j] = results[i_pair]\\n distance_matrix[j, i] = results[i_pair]\\n\\n if choice_parallelization == False:\\n for i in range(n_obj):\\n for j in range(i+1, n_obj):\\n obj_i = objects_list[i]\\n obj_j = objects_list[j]\\n energy_val = energy_distance(grid, grid, u_weights=obj_i, v_weights=obj_j)\\n distance_matrix[i, j] = energy_val\\n distance_matrix[j, i] = energy_val\\n\\n return distance_matrix\",\n \"def calculate_distances(drives):\\n for d in drives:\\n d.set_distance()\",\n \"def eval_mean_distance(played_decks, clustering_data: List, fuzzy: bool, debug: bool = False):\\n\\n for alg_dict in clustering_data:\\n decks = np.array(played_decks)\\n clusters = []\\n for label in set(alg_dict[\\\"labels\\\"]):\\n indices = np.where(alg_dict[\\\"labels\\\"] == label)\\n if fuzzy:\\n clusters.append(FuzzyDeckCluster(decks[indices]))\\n else:\\n clusters.append(DeckCluster(decks[indices]))\\n\\n if fuzzy:\\n clustering = FuzzyDeckClustering(clusters)\\n else:\\n clustering = DeckClustering(clusters)\\n\\n sum_of_squared_distances_centroid = 0\\n sum_of_squared_distances_core = 0\\n\\n for cluster in clustering.deck_clusters:\\n centroid = cluster.centroid()\\n core = cluster.core()\\n for deck in cluster.decks:\\n sum_of_squared_distances_centroid += (deck.jaccard_distance(centroid))**2\\n sum_of_squared_distances_core += (deck.jaccard_distance(core))**2\\n alg_dict[\\\"sse_centroid\\\"] = sum_of_squared_distances_centroid\\n alg_dict[\\\"sse_core\\\"] = sum_of_squared_distances_core\\n\\n if debug:\\n print(\\\"Alg: \\\" + alg_dict[\\\"name\\\"] + \\\"; \\\\t sse = \\\" + str(alg_dict[\\\"sse_centroid\\\"]))\\n print(\\\"Alg: \\\" + alg_dict[\\\"name\\\"] + \\\"; \\\\t sse = \\\" + str(alg_dict[\\\"sse_core\\\"]))\",\n \"def compute_distances_two_loops(self, X):\\n num_test = X.shape[0]\\n num_train = self.X_train.shape[0]\\n dists = np.zeros((num_test, num_train))\\n for i in range(num_test):\\n for j in range(num_train):\\n dists[i, j] = np.sqrt(np.sum(np.square(X[i] - self.X_train[j])))\\n return dists\",\n \"def transform(self, samples):\\n check_is_fitted(self, [\\\"cluster_centers\\\"])\\n\\n distance_mat = self.get_distance(samples, self.cluster_centers)\\n return distance_mat\",\n \"def getDistances(trainingSet, testInstance, distances):\\n # Empty list to store distances of between testInstance and each trainSet item\\n # Number of dimensions to check\\n length=len(testInstance) - 1\\n # Iterate through all items in trainingSet and compute the distance, then append to the distances list\\n for x in range(len(trainingSet)):\\n dist=calculateDistance(testInstance, trainingSet[x], length)\\n distances.append((trainingSet[x], dist))\\n return distances\"\n]"},"negative_scores":{"kind":"list like","value":["0.6267775","0.60056895","0.59760046","0.5957225","0.5952635","0.5888199","0.5881407","0.5870848","0.58344764","0.58344764","0.5777284","0.5726229","0.5702075","0.5700626","0.5683218","0.5678633","0.56485","0.55838466","0.5582898","0.55652297","0.5557965","0.5538048","0.5524559","0.5520437","0.55093014","0.5492023","0.5476906","0.54740274","0.5468652","0.54592836","0.5457917","0.5448652","0.54400367","0.5436454","0.54340523","0.5427078","0.54269075","0.5416064","0.54154843","0.5410674","0.540545","0.53949946","0.53861356","0.5383494","0.53687376","0.5355188","0.53515697","0.533828","0.533723","0.53245854","0.5311616","0.52939904","0.52919304","0.52798796","0.5272237","0.52686805","0.524248","0.5241534","0.52353513","0.52337164","0.5231434","0.5225982","0.5225211","0.5213618","0.5211022","0.51966524","0.5191735","0.5175747","0.51739544","0.5166391","0.51469094","0.51397663","0.51294327","0.5124239","0.51191765","0.50992894","0.5096712","0.50916415","0.50812113","0.50792336","0.5076106","0.50724345","0.50662065","0.5057851","0.5038595","0.50378203","0.50354904","0.5029184","0.5028512","0.5026596","0.5024021","0.5016911","0.5014636","0.50143015","0.5012521","0.5010736","0.49971828","0.49853188","0.49781188","0.49730885"],"string":"[\n \"0.6267775\",\n \"0.60056895\",\n \"0.59760046\",\n \"0.5957225\",\n \"0.5952635\",\n \"0.5888199\",\n \"0.5881407\",\n \"0.5870848\",\n \"0.58344764\",\n \"0.58344764\",\n \"0.5777284\",\n \"0.5726229\",\n \"0.5702075\",\n \"0.5700626\",\n \"0.5683218\",\n \"0.5678633\",\n \"0.56485\",\n \"0.55838466\",\n \"0.5582898\",\n \"0.55652297\",\n \"0.5557965\",\n \"0.5538048\",\n \"0.5524559\",\n \"0.5520437\",\n \"0.55093014\",\n \"0.5492023\",\n \"0.5476906\",\n \"0.54740274\",\n \"0.5468652\",\n \"0.54592836\",\n \"0.5457917\",\n \"0.5448652\",\n \"0.54400367\",\n \"0.5436454\",\n \"0.54340523\",\n \"0.5427078\",\n \"0.54269075\",\n \"0.5416064\",\n \"0.54154843\",\n \"0.5410674\",\n \"0.540545\",\n \"0.53949946\",\n \"0.53861356\",\n \"0.5383494\",\n \"0.53687376\",\n \"0.5355188\",\n \"0.53515697\",\n \"0.533828\",\n \"0.533723\",\n \"0.53245854\",\n \"0.5311616\",\n \"0.52939904\",\n \"0.52919304\",\n \"0.52798796\",\n \"0.5272237\",\n \"0.52686805\",\n \"0.524248\",\n \"0.5241534\",\n \"0.52353513\",\n \"0.52337164\",\n \"0.5231434\",\n \"0.5225982\",\n \"0.5225211\",\n \"0.5213618\",\n \"0.5211022\",\n \"0.51966524\",\n \"0.5191735\",\n \"0.5175747\",\n \"0.51739544\",\n \"0.5166391\",\n \"0.51469094\",\n \"0.51397663\",\n \"0.51294327\",\n \"0.5124239\",\n \"0.51191765\",\n \"0.50992894\",\n \"0.5096712\",\n \"0.50916415\",\n \"0.50812113\",\n \"0.50792336\",\n \"0.5076106\",\n \"0.50724345\",\n \"0.50662065\",\n \"0.5057851\",\n \"0.5038595\",\n \"0.50378203\",\n \"0.50354904\",\n \"0.5029184\",\n \"0.5028512\",\n \"0.5026596\",\n \"0.5024021\",\n \"0.5016911\",\n \"0.5014636\",\n \"0.50143015\",\n \"0.5012521\",\n \"0.5010736\",\n \"0.49971828\",\n \"0.49853188\",\n \"0.49781188\",\n \"0.49730885\"\n]"},"document_score":{"kind":"string","value":"0.68410903"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8555,"cells":{"query":{"kind":"string","value":"Calculates vmeasure, homogeneity, and completeness for each clustering algorithm stored in clustering_alg and adds it to each algorithms dictionary."},"document":{"kind":"string","value":"def eval_v_measure_homogeneity_completeness(clustering_alg: List, sdist_euclidean, sdist_jaccard,\n labels_true, debug: bool = False):\n for i, alg_dict in enumerate(clustering_alg):\n if \"alg\" in alg_dict:\n if alg_dict[\"distance\"] == \"euclidean\":\n clustering = alg_dict[\"alg\"].fit(sdist_euclidean)\n elif alg_dict[\"distance\"] == \"jaccard\":\n clustering = alg_dict[\"alg\"].fit(sdist_jaccard)\n else:\n raise ValueError(\"Unknown distance measure {}. \".format(alg_dict[\"distance\"]) +\n \"Please choose one of the following distance measures ['euclidean','jaccard']\")\n labels_predicted = clustering.labels_\n alg_dict[\"labels\"] = labels_predicted\n else:\n labels_predicted = alg_dict[\"labels\"]\n\n alg_dict[\"homogeneity\"], alg_dict[\"completeness\"], alg_dict[\"v-measure\"] = \\\n homogeneity_completeness_v_measure(labels_true, labels_predicted)\n\n if debug:\n print(\"Alg: \" + alg_dict[\"name\"] + \"; \\t v-measure = \" + str(alg_dict[\"v-measure\"]))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def evaluate_clustering_methods(methods):\r\n results = {}\r\n for m in methods:\r\n res = results[m['name']] = {}\r\n prec = 3\r\n res['Adjusted Rand Score'] = round(sklearn.metrics.adjusted_rand_score(m['target'], m['clustering']),prec)\r\n res['Normalized Mutual Information'] = round(sklearn.metrics.normalized_mutual_info_score(m['target'], m['clustering']),prec)\r\n res['Adjusted Mutual Information'] = round(sklearn.metrics.adjusted_mutual_info_score(m['target'], m['clustering']),prec)\r\n return np.transpose(results)","def __init__(self, dictAlg):\n\n # values of dict dictAlg are DataSetList which should have only one\n # element which will be assigned as values in the following lines.\n d = set()\n f = set()\n for i in dictAlg.values():\n d |= set(j.dim for j in i)\n f |= set(j.funcId for j in i)\n\n if len(f) > 1 or len(d) > 1:\n Usage('Expect the data of algorithms for only one function and '\n 'one dimension.')\n\n f = f.pop()\n d = d.pop()\n\n dictMaxEvals = {}\n dictFinalFunVals = {}\n tmpdictAlg = {}\n for alg, i in dictAlg.iteritems():\n if len(i) == 0:\n warnings.warn('Algorithm %s was not tested on f%d %d-D.'\n % (alg, f, d))\n continue\n elif len(i) > 1:\n warnings.warn('Algorithm %s has a problem on f%d %d-D.'\n % (alg, f, d))\n continue\n\n tmpdictAlg[alg] = i[0] # Assign ONLY the first element as value\n dictMaxEvals[alg] = i[0].maxevals\n dictFinalFunVals[alg] = i[0].finalfunvals\n\n dictAlg = tmpdictAlg\n\n sortedAlgs = dictAlg.keys()\n # algorithms will be sorted along sortedAlgs which is now a fixed list\n\n # Align ERT\n erts = list(np.transpose(np.vstack([dictAlg[i].target, dictAlg[i].ert]))\n for i in sortedAlgs)\n res = readalign.alignArrayData(readalign.HArrayMultiReader(erts))\n\n resalgs = []\n reserts = []\n # For each function value\n for i in res:\n # Find best algorithm\n curerts = i[1:]\n assert len((np.isnan(curerts) == False)) > 0\n currentbestert = np.inf\n currentbestalg = ''\n for j, tmpert in enumerate(curerts):\n if np.isnan(tmpert):\n continue # TODO: don't disregard these entries\n if tmpert == currentbestert:\n # TODO: what do we do in case of ties?\n # look at function values corresponding to the ERT?\n # Look at the function evaluations? the success ratio?\n pass\n elif tmpert < currentbestert:\n currentbestert = tmpert\n currentbestalg = sortedAlgs[j]\n reserts.append(currentbestert)\n resalgs.append(currentbestalg)\n\n dictiter = {}\n dictcurLine = {}\n resDataSet = []\n\n # write down the #fevals to reach the function value.\n for funval, alg in zip(res[:, 0], resalgs):\n it = dictiter.setdefault(alg, iter(dictAlg[alg].evals))\n curLine = dictcurLine.setdefault(alg, np.array([np.inf, 0]))\n while curLine[0] > funval:\n try:\n curLine = it.next()\n except StopIteration:\n break\n dictcurLine[alg] = curLine.copy()\n tmp = curLine.copy()\n tmp[0] = funval\n resDataSet.append(tmp)\n\n setalgs = set(resalgs)\n dictFunValsNoFail = {}\n for alg in setalgs:\n for curline in dictAlg[alg].funvals:\n if (curline[1:] == dictAlg[alg].finalfunvals).any():\n # only works because the funvals are monotonous\n break\n dictFunValsNoFail[alg] = curline.copy()\n\n self.evals = resDataSet\n # evals is not a np array but a list of arrays because they may not\n # all be of the same size.\n self.maxevals = dict((i, dictMaxEvals[i]) for i in setalgs)\n self.finalfunvals = dict((i, dictFinalFunVals[i]) for i in setalgs)\n self.funvalsnofail = dictFunValsNoFail\n self.dim = d\n self.funcId = f\n self.algs = resalgs\n self.algId = 'Virtual Best Algorithm'\n self.comment = 'Combination of ' + ', '.join(sortedAlgs)\n self.ert = np.array(reserts)\n self.target = res[:, 0]\n\n bestfinalfunvals = np.array([np.inf])\n for alg in sortedAlgs:\n if np.median(dictAlg[alg].finalfunvals) < np.median(bestfinalfunvals):\n bestfinalfunvals = dictAlg[alg].finalfunvals\n algbestfinalfunvals = alg\n self.bestfinalfunvals = bestfinalfunvals\n self.algbestfinalfunvals = algbestfinalfunvals","def get_clustering_algorithm_class(cls):\n return {\n \"spectral\": SpectralClusteringAlgorithm,\n \"dbscan\": DBSCANAlgorithm,\n \"gromos\": GromosAlgorithm,\n \"kmedoids\": KMedoidsAlgorithm,\n \"random\": RandomClusteringAlgorithm,\n \"hierarchical\": HierarchicalClusteringAlgorithm\n }","def cluster_analysis(\n clusterers: list,\n hyperparameter_grids: list,\n eval_metrics_grid: list,\n eval_metrics_params: dict,\n word_embeddings: np.ndarray,\n words_vocabulary: list,\n word_to_int: dict,\n word_embeddings_normalized: np.ndarray = None,\n compute_pairwise_word_distances: bool = False,\n compute_pairwise_word_distances_normalized: bool = False,\n return_word_vectors: bool = False,\n save_result_to_disk: bool = False,\n output_dir: Optional[str] = None,\n model_name: Optional[str] = None,\n dataset_name: Optional[str] = None,\n output_filepath_suffix: Optional[str] = None,\n) -> Union[dict, tuple]:\n # Create word vectors from given words/vocabulary\n word_vectors = words_to_vectors(\n words_vocabulary=words_vocabulary,\n word_to_int=word_to_int,\n word_embeddings=word_embeddings,\n )\n\n # Create normalized word vectors from given words/vocabulary if specified.\n word_vectors_normalized = None\n if word_embeddings_normalized is not None:\n word_vectors_normalized = words_to_vectors(\n words_vocabulary=words_vocabulary,\n word_to_int=word_to_int,\n word_embeddings=word_embeddings_normalized,\n )\n\n if compute_pairwise_word_distances:\n word_vectors_pairwise_distances = pairwise_cosine_distances(word_vectors)\n if (\n compute_pairwise_word_distances_normalized\n and word_vectors_normalized is not None\n ):\n normalized_word_vectors_pairwise_distances = euclidean_distances(\n word_vectors_normalized\n )\n\n # Perform cluster analysis\n clusterers_result = {}\n unique_cluster_metrics = set()\n for clusterer_tuple, hyperparameter_grid, eval_metrics in zip(\n clusterers, hyperparameter_grids, eval_metrics_grid\n ):\n if len(clusterer_tuple) == 3:\n (clusterer_name, clusterer_cls, clusterer_use_normalized) = clusterer_tuple\n else:\n clusterer_use_normalized = False\n (clusterer_name, clusterer_cls) = clusterer_tuple\n print(f\"-- Clustering using {clusterer_name} --\")\n clusterers_result[clusterer_name] = {\n \"cluster_labels\": [],\n \"cluster_params\": [],\n \"cluster_metrics\": {},\n }\n\n # Do clustering for each set of hyperparameters\n param_grid = ParameterGrid(hyperparameter_grid)\n for params_idx, params in enumerate(tqdm(param_grid)):\n clusterers_result[clusterer_name][\"cluster_params\"].append(params)\n\n # Add exception for ward linkage clustering.\n if (\n clusterer_cls is AgglomerativeClustering\n and params.get(\"linkage\") == \"ward\"\n and word_vectors_normalized is not None\n ):\n params = {**params, \"affinity\": \"euclidean\"}\n clusterer_instance = clusterer_cls(**params)\n fit_predict_X = word_vectors_normalized\n else:\n clusterer_instance = clusterer_cls(**params)\n if (\n params.get(\"affinity\") == \"precomputed\"\n or params.get(\"metric\") == \"precomputed\"\n ):\n if (\n clusterer_use_normalized\n and compute_pairwise_word_distances_normalized\n ):\n fit_predict_X = normalized_word_vectors_pairwise_distances\n elif compute_pairwise_word_distances:\n fit_predict_X = word_vectors_pairwise_distances\n else:\n if clusterer_use_normalized and word_vectors_normalized is not None:\n fit_predict_X = word_vectors_normalized\n else:\n fit_predict_X = word_vectors\n\n # Use fit_predict if it is available.\n if getattr(clusterer_instance, \"fit_predict\", None) is not None:\n predicted_labels = clusterer_instance.fit_predict(fit_predict_X)\n else:\n clusterer_instance.fit(fit_predict_X)\n predicted_labels = clusterer_instance.predict(fit_predict_X)\n\n # Separate noise labels into clusters\n if clusterer_cls is HDBSCAN:\n predicted_labels = separate_noise_labels_into_clusters(predicted_labels)\n\n clusterers_result[clusterer_name][\"cluster_labels\"].append(predicted_labels)\n\n # Evaluate predicted cluster labels using internal evaluation metrics\n for eval_metric_tuple in eval_metrics:\n if len(eval_metric_tuple) == 3:\n (\n eval_metric_key,\n eval_metric,\n eval_metric_use_normalized,\n ) = eval_metric_tuple\n else:\n eval_metric_use_normalized = False\n (eval_metric_key, eval_metric) = eval_metric_tuple\n eval_metric_params = eval_metrics_params.get(eval_metric_key, {})\n if (\n compute_pairwise_word_distances\n and eval_metric_params.get(\"metric\") == \"precomputed\"\n ):\n if (\n eval_metric_use_normalized\n and compute_pairwise_word_distances_normalized\n ):\n metric_name, metric_score, metric_obj_max = eval_metric(\n word_embeddings=normalized_word_vectors_pairwise_distances,\n cluster_labels=predicted_labels,\n clusterer=clusterer_instance,\n **eval_metric_params,\n )\n else:\n metric_name, metric_score, metric_obj_max = eval_metric(\n word_embeddings=word_vectors_pairwise_distances,\n cluster_labels=predicted_labels,\n clusterer=clusterer_instance,\n **eval_metric_params,\n )\n else:\n if (\n eval_metric_use_normalized\n and word_vectors_normalized is not None\n ):\n metric_name, metric_score, metric_obj_max = eval_metric(\n word_embeddings=word_vectors_normalized,\n cluster_labels=predicted_labels,\n clusterer=clusterer_instance,\n **eval_metric_params,\n )\n else:\n metric_name, metric_score, metric_obj_max = eval_metric(\n word_embeddings=word_vectors,\n cluster_labels=predicted_labels,\n clusterer=clusterer_instance,\n **eval_metric_params,\n )\n unique_cluster_metrics.add(metric_name)\n\n # Initialize metric result\n if (\n metric_name\n not in clusterers_result[clusterer_name][\"cluster_metrics\"]\n ):\n clusterers_result[clusterer_name][\"cluster_metrics\"][\n metric_name\n ] = {\n \"metric_scores\": [],\n \"metric_obj_max\": metric_obj_max,\n \"best_metric_score_indices\": [],\n }\n\n clusterers_result[clusterer_name][\"cluster_metrics\"][metric_name][\n \"metric_scores\"\n ].append(metric_score)\n\n # Set best metric score indices\n if params_idx == len(param_grid) - 1:\n best_metric_score_indices = np.argsort(\n clusterers_result[clusterer_name][\"cluster_metrics\"][\n metric_name\n ][\"metric_scores\"]\n )\n if metric_obj_max:\n best_metric_score_indices = best_metric_score_indices[::-1]\n clusterers_result[clusterer_name][\"cluster_metrics\"][metric_name][\n \"best_metric_score_indices\"\n ] = best_metric_score_indices\n\n # Find preferred clusterers for each cluster metric (from best to worst)\n metric_preferred_clusterers = {}\n for cluster_metric_name in unique_cluster_metrics:\n metric_obj_max = None\n metric_best_scores = []\n clusterer_names = []\n for clusterer_name, clusterer_result in clusterers_result.items():\n if cluster_metric_name in clusterer_result[\"cluster_metrics\"]:\n clusterer_names.append(clusterer_name)\n metric_result = clusterer_result[\"cluster_metrics\"][cluster_metric_name]\n if metric_obj_max is None:\n metric_obj_max = metric_result[\"metric_obj_max\"]\n best_metric_score = metric_result[\"metric_scores\"][\n metric_result[\"best_metric_score_indices\"][0]\n ]\n metric_best_scores.append(best_metric_score)\n clusterer_names = np.array(clusterer_names)\n metric_best_scores = np.array(metric_best_scores)\n\n metric_best_scores_sorted_indices = np.argsort(metric_best_scores)\n if metric_obj_max:\n metric_best_scores_sorted_indices = metric_best_scores_sorted_indices[::-1]\n metric_preferred_clusterers[cluster_metric_name] = {\n \"clusterer_names\": clusterer_names[metric_best_scores_sorted_indices],\n \"best_metric_scores\": metric_best_scores[metric_best_scores_sorted_indices],\n }\n\n # Return result as dictionary\n cluster_analysis_result = {\n \"clusterers\": clusterers_result,\n \"metric_preferred_clusterers\": metric_preferred_clusterers,\n }\n\n if return_word_vectors:\n if compute_pairwise_word_distances:\n cluster_analysis_result = (\n cluster_analysis_result,\n word_vectors,\n word_vectors_pairwise_distances,\n )\n else:\n cluster_analysis_result = (cluster_analysis_result, word_vectors)\n\n # Save result to disk\n if save_result_to_disk:\n save_cluster_result_to_disk(\n cluster_result=cluster_analysis_result,\n output_dir=output_dir,\n model_name=model_name,\n dataset_name=dataset_name,\n output_filepath_suffix=output_filepath_suffix,\n )\n\n return cluster_analysis_result","def eval_cluster_contingency(clustering_alg: List, labels_true, sdist):\n for (alg_name, alg_dict) in clustering_alg:\n if \"alg\" in alg_dict:\n clustering = alg_dict[\"alg\"].fit(sdist)\n labels_pred = clustering.labels_\n alg_dict[\"labels\"] = labels_pred\n else:\n labels_pred = alg_dict[\"labels\"]\n\n pred_label_dict, new_labels = normalize_labels(labels_pred)\n\n alg_dict[\"cm\"] = contingency_matrix(labels_true, new_labels)","def _eval_clustering(self, gen_reviews, clusters, embedding_model, clustering):\n result = []\n preds = self.predict_gen(gen_reviews, embedding_model, clustering)\n\n acc = accuracy_score(np.array(clusters), np.array(preds))\n conf = confusion_matrix(np.array(clusters), np.array(preds))\n\n return acc, conf","def generate_clustering_info(self, algorithm_type, clustering_parameters, clusterings = []):\n clustering_info = {}\n for i, running_parameters in enumerate(clustering_parameters):\n\n clustering_id = \"clustering_%04d\"%(self.current_clustering_id)\n self.current_clustering_id += 1\n clustering_info[clustering_id] = {\n \"type\":algorithm_type,\n \"clustering\": None,\n \"parameters\": running_parameters\n }\n\n if clusterings != []:\n clustering_info[clustering_id][\"clustering\"] = clusterings[i]\n\n return clustering_info","def run_algorithm(algorithm, algorithm_kwargs, clustering_id):\n clustering = algorithm.perform_clustering(algorithm_kwargs)\n return (clustering_id, clustering)","def main(argv=None):\n\n if argv is None:\n argv = sys.argv\n\n # setup command line parser\n parser = E.OptionParser(version=\"%prog version: $Id$\",\n usage=globals()[\"__doc__\"])\n\n parser.add_option(\"-t\", \"--test\", dest=\"test\", type=\"string\",\n help=\"supply help\")\n\n parser.add_option(\"--method\", dest=\"method\", type=\"choice\",\n choices=(\"metrics\", \"summary\", \"module_summary\"),\n help=\"method to summarise clustering\")\n\n parser.add_option(\"--ref-gtf-files\", dest=\"ref_gtf\", type=\"string\",\n help=\"comma separated list of reference gtf files\")\n\n # add common options (-h/--help, ...) and parse command line\n (options, args) = E.Start(parser, argv=argv)\n\n if options.method == \"metrics\":\n infile = argv[-1]\n E.info(\"loading input file: %s\" % infile)\n assert infile\n\n df = pd.read_table(infile,\n sep=\"\\t\",\n header=None,\n index_col=0)\n\n df = df.ix[:, :50]\n cluster_combs = (x for x in itertools.combinations(df.columns,\n 2))\n genes = df.index\n results_dict = {}\n all_clusts = {}\n\n E.info(\"setting up cluster containers\")\n for i in df.columns:\n clusters = set(df[i].values.tolist())\n cluster_dict = {}\n for clust in clusters:\n cluster_dict[clust] = []\n for gene in genes:\n cluster_dict[df[i][gene]].append(gene)\n\n for col in clusters:\n col_set = set()\n clust_col = cluster_dict[col]\n gene_members = itertools.combinations(clust_col,\n 2)\n col_set.update(gene_members)\n cluster_dict[col] = col_set\n all_clusts[i] = cluster_dict\n E.info(\"generating all pair-wise cluster comparisons\")\n E.info(\"calculating adjusted mutual information\")\n for k in cluster_combs:\n clusters1 = all_clusts[k[0]]\n clusters2 = all_clusts[k[1]]\n metric_dict = {}\n metric_dict['AMI'] = TS.adjustedMutualInformation(clusters1,\n clusters2)\n results_dict[k] = metric_dict\n\n res_frame = pd.DataFrame(results_dict).T\n res_frame = res_frame.reset_index()\n res_frame.drop(['level_0'], inplace=True, axis=1)\n res_frame.drop(['level_1'], inplace=True, axis=1)\n\n # flatten rand indices and add to output dataframe\n rand_arrays = TS.randIndexes(df)\n flat_adj_rand = TS.unravel_arrays(rand_arrays[0])\n flat_rand = TS.unravel_arrays(rand_arrays[1])\n res_frame['Rand_Index'] = flat_rand\n res_frame['Adjusted_Rand_Index'] = flat_adj_rand\n E.info(\"aggregating results\")\n\n res_frame.to_csv(options.stdout,\n sep=\"\\t\",\n index_label='idx')\n\n elif options.method == \"summary\":\n infiles = argv[-1]\n list_of_files = infiles.split(\",\")\n\n file_dict = {}\n for fle in list_of_files:\n fname = fle.split(\"/\")[-1]\n condition = fname.split(\"-\")[0]\n ref = fname.split(\"-\")[1]\n df_ = pd.read_table(fle,\n sep=\"\\t\",\n header=0,\n index_col=0)\n df_.columns = ['gene_id', 'cluster']\n clust_dict = {}\n for idx in df_.index:\n cluster = df_.loc[idx]['cluster']\n gene = df_.loc[idx]['gene_id']\n try:\n clust_dict[cluster] += 1\n except KeyError:\n clust_dict[cluster] = 1\n med_size = np.median(clust_dict.values())\n file_dict[fname] = {'condition': condition,\n 'reference': ref,\n 'median_cluster_size': med_size}\n\n outframe = pd.DataFrame(file_dict).T\n outframe.to_csv(options.stdout,\n sep=\"\\t\",\n index_label='idx')\n\n elif options.method == \"module_summary\":\n # get lncRNA/gene lengths from reference gtfs\n ref_gtfs = options.ref_gtf.split(\",\")\n length_dict = {}\n for ref in ref_gtfs:\n oref = IOTools.openFile(ref, \"rb\")\n git = GTF.transcript_iterator(GTF.iterator(oref))\n for gene in git:\n for trans in gene:\n length = trans.end - trans.start\n try:\n length_dict[trans.gene_id] += length\n except KeyError:\n length_dict[trans.gene_id] = length\n oref.close()\n\n infiles = argv[-1]\n list_of_files = infiles.split(\",\")\n\n fdfs = []\n for fle in list_of_files:\n cond = fle.split(\"/\")[-1].split(\"-\")[0]\n refer = fle.split(\"/\")[-1].split(\"-\")[1]\n _df = pd.read_table(fle, sep=\"\\t\",\n header=0, index_col=0)\n _df.columns = ['gene_id', 'cluster']\n clusters = set(_df['cluster'])\n c_dict = {}\n # summarize over each cluster\n for clust in clusters:\n lengths = []\n c_df = _df[_df['cluster'] == clust]\n for lid in c_df['gene_id']:\n lengths.append(length_dict[lid])\n c_dict[clust] = {'cluster_size': len(c_df['gene_id']),\n 'mean_length': np.mean(lengths),\n 'index': (cond, refer),\n 'module': clust}\n cdf = pd.DataFrame(c_dict).T\n # use a multindex for hierarchical indexing\n midx = pd.MultiIndex.from_tuples(cdf['index'])\n cdf.index = midx\n cdf.drop(['index'], inplace=True, axis=1)\n fdfs.append(cdf)\n\n # generate a single output df\n s_df = fdfs[0]\n fdfs.pop(0)\n for df in fdfs:\n s_df = s_df.append(df)\n\n s_df.to_csv(options.stdout,\n index_label=(\"condition\", \"reference\"),\n sep=\"\\t\")\n\n # write footer and output benchmark information.\n E.Stop()","def interpret_clusters(self, split=0.7, all_demos=None, num_clusters=None, \n max_depth=CLUSTER_DEPTH, data=None, labels=None, verbose=True):\n all_demos = self.all_data if all_demos is None else all_demos\n clusters = self.get_ordered_clusters(labels, num_clusters)\n data = self.demos if data is None else data\n labels = self.labels if labels is None else labels\n\n cluster_formulas = []\n counter = 0\n sep = \"\\n \"\n for c in clusters:\n counter += 1\n res = self.sample_from_clusters(num_samples=split,\n all_data=all_demos,\n pos_validation=True, \n neg_validation=True,\n which_cluster=counter)\n positive_samples, val_positive_samples = res[0], res[1]\n negative_samples, val_negative_samples = res[2], res[3]\n z = 0\n for d in positive_samples:\n if d[1] == 0: z += 1\n\n cluster_data = {'pos': positive_samples,\n 'neg': negative_samples}\n val_cluster_data = {'pos': val_positive_samples,\n 'neg': val_negative_samples}\n\n if verbose: print(sep +\"Checking formulas \" + \\\n \"with max depth {}\\n\".format(max_depth))\n\n cluster_formula, value_formula = wrapper_train(max_depth,\n cluster_data, \n val_cluster_data,\n verbose=verbose,\n pred_data=[self.pipeline_X,\n self.pipeline_y])\n if cluster_formula is not None:\n print(cluster_formula)\n\n cluster_formulas.append((c, cluster_formula, value_formula))\n self.reset_pipeline()\n\n return cluster_formulas","def run_evaluation(self, n_runs=1, n_points=1000, n_iterations=1, min_n_components=2, max_n_components=25,\n\t\t\t\t\t n_splits=3, save_data=False, file_label='',n_microstates=None, all_methods=True,\n\t\t\t\t\t assign_transition_points=True):\n\n\t\tif self.presampled_data is not None:\n\t\t\tsampled_data = self.presampled_data[0]\n\t\t\ttrue_clustering = self.presampled_data[1]\n\t\t\tn_runs = sampled_data.shape[0]\n\n\t\tself.cluster_score_ami_kmeans_ = np.zeros(n_runs)\n\t\tself.cluster_score_ami_AW_ = np.zeros(n_runs)\n\t\tself.cluster_score_ami_spectral_ = np.zeros(n_runs)\n\t\tself.cluster_score_ami_density_peaks_ = np.zeros(n_runs)\n\t\tself.cluster_score_ami_GMM_ = np.zeros(n_runs)\n\t\tself.cluster_score_ami_GMM_FE_min_ = np.zeros(n_runs)\n\n\t\tself.cluster_score_fm_kmeans_ = np.zeros(n_runs)\n\t\tself.cluster_score_fm_AW_ = np.zeros(n_runs)\n\t\tself.cluster_score_fm_spectral_ = np.zeros(n_runs)\n\t\tself.cluster_score_fm_density_peaks_ = np.zeros(n_runs)\n\t\tself.cluster_score_fm_GMM_ = np.zeros(n_runs)\n\t\tself.cluster_score_fm_GMM_FE_min_ = np.zeros(n_runs)\n\n\t\tself.cluster_score_vm_kmeans_ = np.zeros(n_runs)\n\t\tself.cluster_score_vm_AW_ = np.zeros(n_runs)\n\t\tself.cluster_score_vm_spectral_ = np.zeros(n_runs)\n\t\tself.cluster_score_vm_density_peaks_ = np.zeros(n_runs)\n\t\tself.cluster_score_vm_GMM_ = np.zeros(n_runs)\n\t\tself.cluster_score_vm_GMM_FE_min_ = np.zeros(n_runs)\n\n\t\tdata = self.toy_model_.sample(3)\n\n\t\t# Create free energy estimators\n\t\tgmm_FE = GMM_FE.FreeEnergyClustering(data, min_n_components=min_n_components, max_n_components=max_n_components,\n\t\t\t\t\t\t\t\t\t x_lims=self.x_lims_, n_grids=self.n_grids_, stack_landscapes=False,\n\t\t\t\t\t\t\t\t\t n_splits=n_splits, n_iterations=n_iterations,convergence_tol=self.convergence_tol_,\n\t\t\t\t\t\t\t\t\t verbose=self.verbose_)\n\n\t\tkm = kmc.KMeansCluster(min_n_components, max_n_components)\n\t\taw = awc.AWCluster(min_n_components, max_n_components)\n\t\tspectral = sc.SpectralCluster(min_n_components, max_n_components)\n\n\t\tall_data = []\n\t\tfor i_run in range(n_runs):\n\t\t\tprint(\"Run: \"+str(i_run+1)+'/'+str(n_runs))\n\n\t\t\tif self.presampled_data is None:\n\t\t\t\t# Sample data\n\t\t\t\tdata = self.toy_model_.sample(n_points)\n\t\t\telse:\n\t\t\t\tdata = sampled_data[i_run]\n\t\t\t\n\t\t\tall_data.append(data)\n\n\t\t\tprint('Shape data: ' + str(data.shape))\n\n\t\t\t# Set data in model and estimate GMM density\n\t\t\tgmm_FE.data_ = data\n\t\t\tcoords, est_FE_landsc, FE_points = gmm_FE.landscape()\n\n\t\t\t# Get true cluster labels\n\t\t\tif self.presampled_data is None:\n\t\t\t\tif hasattr(self.toy_model_, \"assign_cluster_labels\"):\n\t\t\t\t\tself.true_labels_ = self.toy_model_.assign_cluster_labels(data)\n\t\t\t\telse:\n\t\t\t\t\tprint('Setting true labels.')\n\t\t\t\t\tself.true_labels_, _ = self.true_FE_.cluster(data, np.zeros(data.shape[0]))\n\t\t\telse:\n\t\t\t\tself.true_labels_ = true_clustering[i_run]\n\t\t\t\n\t\t\t# Cluster data with different methods\n\t\t\tif n_microstates is None:\n\t\t\t\tself.FE_min_labels, _ = gmm_FE.cluster(data, FE_points, assign_transition_points=assign_transition_points)\n\t\t\telse:\n\t\t\t\tkmea = KMeans(n_clusters=n_microstates).fit(data[::2])\n\t\t\t\tmicrostate_centers = kmea.cluster_centers_\n\t\t\t\tself.FE_min_labels, _ = gmm_FE.cluster(microstate_centers, FE_points, data, assign_transition_points=assign_transition_points, unravel_grid=False)\n\n\t\t\tif all_methods:\n\t\t\t\tself.km_labels = km.cluster(data)\n\t\t\t\tself.aw_labels = aw.cluster(data)\n\t\t\t\tself.spectral_labels = spectral.cluster(data)\n\n\t\t\t# Score clustering using different scoring metrics\n\t\t\t# V-measure score\n\t\t\tself.cluster_score_vm_GMM_FE_min_[i_run] = self._score_clustering(self.FE_min_labels,'vm')\n\t\t\tprint(self.cluster_score_vm_GMM_FE_min_[i_run])\n\t\t\tif all_methods:\n\t\t\t\tself.cluster_score_vm_GMM_[i_run] = self._score_clustering(gmm_FE.density_est_.predict(data),'vm')\n\t\t\t\tself.cluster_score_vm_kmeans_[i_run] = self._score_clustering(self.km_labels,'vm')\n\t\t\t\tself.cluster_score_vm_AW_[i_run] = self._score_clustering(self.aw_labels,'vm')\n\t\t\t\tself.cluster_score_vm_spectral_[i_run] = self._score_clustering(self.spectral_labels,'vm')\n\n\t\t\t\t# Adjusted MI\n\t\t\t\tself.cluster_score_ami_GMM_FE_min_[i_run] = self._score_clustering(self.FE_min_labels,'ami')\n\t\t\t\tself.cluster_score_ami_GMM_[i_run] = self._score_clustering(gmm_FE.density_est_.predict(data),'ami')\n\t\t\t\tself.cluster_score_ami_kmeans_[i_run] = self._score_clustering(self.km_labels,'ami')\n\t\t\t\tself.cluster_score_ami_AW_[i_run] = self._score_clustering(self.aw_labels,'ami')\n\t\t\t\tself.cluster_score_ami_spectral_[i_run] = self._score_clustering(self.spectral_labels,'ami')\n\n\t\t\t\t# Fowlkes Mallows\n\t\t\t\tself.cluster_score_fm_GMM_FE_min_[i_run] = self._score_clustering(self.FE_min_labels,'fm')\n\t\t\t\tself.cluster_score_fm_GMM_[i_run] = self._score_clustering(gmm_FE.density_est_.predict(data),'fm')\n\t\t\t\tself.cluster_score_fm_kmeans_[i_run] = self._score_clustering(self.km_labels,'fm')\n\t\t\t\tself.cluster_score_fm_AW_[i_run] = self._score_clustering(self.aw_labels,'fm')\n\t\t\t\tself.cluster_score_fm_spectral_[i_run] = self._score_clustering(self.spectral_labels,'fm')\n\t\t\n\t\tif save_data:\n\t\t\tif self.presampled_data is None:\n\t\t\t\tnp.save('data_out/sampled_data_'+self.toy_model_.name+file_label+'.npy',all_data)\n\n\t\t\tif False:\n\t\t\t\tnp.save('data_out/cluster_score_fm_FE_min_'+self.toy_model_.name+file_label+'.npy',self.cluster_score_fm_GMM_FE_min_)\n\t\t\t\tnp.save('data_out/cluster_score_fm_GMM_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_fm_GMM_)\n\t\t\t\tnp.save('data_out/cluster_score_fm_kmeans_' + self.toy_model_.name +file_label +'.npy', self.cluster_score_fm_kmeans_)\n\t\t\t\tnp.save('data_out/cluster_score_fm_AW_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_fm_AW_)\n\t\t\t\tnp.save('data_out/cluster_score_fm_spectral_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_fm_spectral_)\n\n\t\t\t\tnp.save('data_out/cluster_score_ami_FE_min_'+self.toy_model_.name+file_label+'.npy',self.cluster_score_ami_GMM_FE_min_)\n\t\t\t\tnp.save('data_out/cluster_score_ami_GMM_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_ami_GMM_)\n\t\t\t\tnp.save('data_out/cluster_score_ami_kmeans_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_ami_kmeans_)\n\t\t\t\tnp.save('data_out/cluster_score_ami_AW_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_ami_AW_)\n\t\t\t\tnp.save('data_out/cluster_score_ami_spectral_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_ami_spectral_)\n\n\t\t\tnp.save('data_out/cluster_score_vm_FE_min_'+self.toy_model_.name+file_label+'.npy',self.cluster_score_vm_GMM_FE_min_)\n\t\t\tif all_methods:\n\t\t\t\tnp.save('data_out/cluster_score_vm_GMM_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_vm_GMM_)\n\t\t\t\tnp.save('data_out/cluster_score_vm_kmeans_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_vm_kmeans_)\n\t\t\t\tnp.save('data_out/cluster_score_vm_AW_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_vm_AW_)\n\t\t\t\tnp.save('data_out/cluster_score_vm_spectral_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_vm_spectral_)\n\t\treturn","def fit(self):\n self.cluseter_agglomerative(n_clusters=20, linkage='average', iterate=5)\n self.sub_clustering(n_clusters=3, index_cluster=[79], linkage='complete')\n self.merge_clusters([[0,9,53],[1,83],[46,35,67],[88,23],[6,68]])\n self.merge_clusters([[6,33,52],[17,14]])\n self.sub_clustering(n_clusters=2, index_cluster=[0], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[2], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[85], linkage='average')\n self.sub_clustering(n_clusters=2, index_cluster=[14], linkage='complete')\n self.sub_clustering(n_clusters=2, index_cluster=[16], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[22], linkage='average')\n self.sub_clustering(n_clusters=2, index_cluster=[24], linkage='complete')\n self.sub_clustering(n_clusters=2, index_cluster=[26], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[28], linkage='ward')\n self.merge_clusters([[6,98,99]])\n self.merge_clusters([[35,80]])\n self.sub_clustering(n_clusters=4, index_cluster=[35], linkage='complete')\n self.merge_clusters([[76,98]])\n self.sub_clustering(n_clusters=3, index_cluster=[35], linkage='complete')\n self.merge_clusters([[39,42]])\n self.sub_clustering(n_clusters=3, index_cluster=[47], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='average')\n self.merge_clusters([[70,101]])\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[61], linkage='ward')\n self.merge_clusters()\n return","def getAllContributingAlgorithmsToBest(algnamelist, target_lb=1e-8, \n target_ub=1e2):\n \n print \"Generating best algorithm data from given algorithm list...\\n\", \n customgenerate(algnamelist)\n \n bestalgfilepath = 'bestCustomAlg'\n picklefilename = os.path.join(bestalgfilepath, 'bestalg.pickle')\n fid = open(picklefilename, 'r')\n bestalgentries = pickle.load(fid)\n fid.close()\n print 'loading of best algorithm data done.'\n \n countsperalgorithm = {}\n for (d, f) in bestalgentries:\n print 'dimension:', d, ', function:', f\n print f\n setofalgs = set(bestalgentries[d,f].algs)\n # pre-processing data to only look at targets >= target_lb:\n correctedbestalgentries = []\n for i in range(0,len(bestalgentries[d,f].target)):\n if ((bestalgentries[d,f].target[i] >= target_lb) and\n (bestalgentries[d,f].target[i] <= target_ub)):\n \n correctedbestalgentries.append(bestalgentries[d,f].algs[i])\n print len(correctedbestalgentries)\n # now count how often algorithm a is best for the extracted targets\n for a in setofalgs:\n # use setdefault to initialize with zero if a entry not existant:\n countsperalgorithm.setdefault((d, a), 0) \n countsperalgorithm[(d,a)] += correctedbestalgentries.count(a)\n \n selectedalgsperdimension = {}\n for (d,a) in sorted(countsperalgorithm):\n if not selectedalgsperdimension.has_key(d):\n selectedalgsperdimension[d] = []\n selectedalgsperdimension[d].append((countsperalgorithm[(d,a)], a))\n \n for d in sorted(selectedalgsperdimension):\n print d, 'D:'\n for (count, alg) in sorted(selectedalgsperdimension[d], reverse=True):\n print count, alg\n print '\\n'\n \n \n print \" done.\"","def gen_cluster_accuracies():\n accuracies = {}\n with Parallel(n_jobs=morphs.parallel.N_JOBS) as parallel:\n for block_path in morphs.paths.blocks():\n print(block_path)\n spikes = morphs.load.ephys_data(block_path, collapse_endpoints=True)\n\n if len(spikes[\"recording\"].unique()) >= 1:\n template_spikes = spikes[spikes[\"stim_id\"].isin(list(\"abcdefgh\"))]\n assert len(template_spikes) > 0\n cluster_groups = template_spikes.groupby(\"cluster\")\n\n morph_dims = spikes.morph_dim.unique()\n morph_dims = morph_dims[~pd.isnull(morph_dims)]\n morph_dims.sort()\n\n max_num_reps = np.max(\n [\n len(stim_group.groupby(by=[\"recording\", \"stim_presentation\"]))\n for stim_id, stim_group in template_spikes.groupby(\"stim_id\")\n ]\n )\n\n accuracies_list = parallel(\n delayed(cluster_accuracy)(\n cluster, cluster_group, morph_dims, max_num_reps\n )\n for (cluster, cluster_group) in cluster_groups\n )\n\n accuracies[block_path] = pd.concat(accuracies_list)\n\n morphs.paths.PROCESSED_DIR.mkdir(parents=True, exist_ok=True)\n with open(morphs.paths.ACCURACIES_PKL.as_posix(), \"wb\") as f:\n pickle.dump(accuracies, f)","def calculate_all_metrcis(self):\n self.calculate_gc_metrcis()\n self.calculate_sam_metrics()\n self.calculate_classification_metrics()\n self.calculate_losses()","def run(\n self,\n number_of_clusters=None,\n max_K=8,\n method_clustering=\"pam\",\n init_clustering=\"random\",\n max_iter_clustering=100,\n discart_value_JI=0.6,\n bootstraps_JI=100,\n bootstraps_p_value=100,\n n_jobs=1,\n verbose=1,\n ):\n\n if number_of_clusters is None:\n self.k = optimizer.optimizeK(\n self.distance_matrix,\n self.y.to_numpy(),\n self.model_type,\n max_K,\n method_clustering,\n init_clustering,\n max_iter_clustering,\n discart_value_JI,\n bootstraps_JI,\n self.random_state,\n n_jobs,\n verbose,\n )\n\n if self.k == 1:\n warnings.warn(\"No stable clusters were found!\")\n return\n\n print(f\"Optimal number of cluster is: {self.k}\")\n\n else:\n self.k = number_of_clusters\n print(f\"Use {self.k} as number of cluster\")\n\n self.cluster_labels = (\n kmedoids.KMedoids(\n n_clusters=self.k,\n method=method_clustering,\n init=init_clustering,\n metric=\"precomputed\",\n max_iter=max_iter_clustering,\n random_state=self.random_state,\n )\n .fit(self.distance_matrix)\n .labels_\n )\n\n (\n self._data_clustering_ranked,\n self.p_value_of_features,\n ) = stats.calculate_global_feature_importance(\n self.X, self.y, self.cluster_labels, self.model_type\n )\n self._p_value_of_features_per_cluster = (\n stats.calculate_local_feature_importance(\n self._data_clustering_ranked, bootstraps_p_value\n )\n )","def get_sklearn_algorithms(verbose=False):\n from collections import defaultdict\n import importlib\n import sklearn\n algos = defaultdict(list)\n if verbose: print(dir(sklearn))\n for nom_module in dir(sklearn):\n if verbose: print(nom_module)\n try:\n to_import = \"sklearn.%s\" % nom_module\n module = importlib.import_module(to_import)\n for nom_fonction in dir(module):\n fonction = getattr(module, nom_fonction)\n if hasattr(fonction, \"fit\"):\n if verbose: print(\" nom algorithme = \", nom_fonction)\n algos[nom_module].append(fonction)\n except Exception as e:\n if verbose: print(e)\n if verbose: print(\"=\" * 30)\n return algos","def build_algorithm(self, algorithm_type):\n distance_matrix = self.matrix_handler.distance_matrix\n algorithm_execution_parameters = {}\n if algorithm_type == \"spectral\":\n # We need to set number of clusters for performance and we get sigma if defined\n algorithm_execution_parameters[\"max_clusters\"] = self.evaluation_parameters[\"maximum_clusters\"]\n if \"sigma\" in self.clustering_parameters[\"algorithms\"][\"spectral\"]:\n algorithm_execution_parameters[\"sigma_sq\"] = self.clustering_parameters[\"algorithms\"][\"spectral\"][\"sigma\"]\n # else it calculates its own sigma\n\n if algorithm_type in [\"spectral\",\"dbscan\",\"gromos\",\"kmedoids\",\"random\",\"hierarchical\"] :\n return ClusteringExplorer.get_clustering_algorithm_class()[algorithm_type](distance_matrix, **algorithm_execution_parameters)\n else:\n print \"[ERROR][ClusteringExplorer::build_algorithms] Not known algorithm type ( %s )\"%(algorithm_type)\n self.notify(\"SHUTDOWN\", \"Not known algorithm type ( %s )\"%(algorithm_type))\n exit()","def calculate_all_scores(best_phenotype, clustering_algorithm, dataset, y):\n samples_dist_matrix = distance.squareform(distance.pdist(dataset.values))\n allowed_fitness = list(DICT_ALLOWED_FITNESSES.keys())\n scores = [(fitness_name, fitness_value) for fitness_name, fitness_value in\n zip(allowed_fitness,\n eval_multiple(dataset.values, clustering_algorithm, allowed_fitness, samples_dist_matrix, y,\n best_phenotype))]\n scores = dict(scores)\n return scores","def measureAll(authors_texts,sectorialized_agents):\n authors_texts=P.text.aux.textFromAuthors(authors_texts,self.topm_dict[\"sectorialized_agents\"])\n authors_measures={}\n # análise de cada mensagem e de cada autor\n for author in authors_texts:\n authors_measures[author]={}\n texts=authors_texts[author]\n authors_measures[author][\"raw_strings\"]=P.text.raw.analyseAll(texts)\n authors_measures[author][\"pos\"]= P.text.pos.analyseAll(authors_analysis[author][\"raw_analysis\"])\n authors_measures[author][ \"wordnet\" ]=P.text.wordnet.analyseAll(authors_analysis[author][\"pos_analysis\"])\n authors_measures[author][\"tfIdf\"]=P.text.tfIdf.analyseAll(texts) # tfIdf de cada texto e do autor, numeric: mean e std das distancias\n # análise de cada setor e da estrutura toda\n# sectors_texts=P.text.aux.textFromSectors(authors_text,sectorialized_agents)\n sectors_measures={}\n for sector in sectorialized_agents:\n sectors_measures[sector][\"raw_strings\"]=P.text.raw.sectorsAnalyseAll(authors_analysis,sectorialized_agents[sector])\n sectors_measures[sector][\"pos\"]= P.text.pos.sectorsAnalyseAll(authors_analysis,sectorialized_agents[sector])\n sectors_measures[sector][\"wordnet\"]= P.text.wordnet.sectorsAnalyseAll(authors_analysis,sectorialized_agents[sector])\n # tfIdf de cada texto e de cada autor, numeric: mean e std das distancias por texto e por autor, e media e etd dos autores\n sectors_measures[sector][\"tfIdf\"]= P.text.tfIdf.sectorsAnalyseAll(authors_analysis,sectorialized_agents[sector])\n\n# texts=[sectors_texts[i] for i in (\"peripherals\",\"intermediaries\",\"hubs\")]\n# sectors_analysis[\"raw_strings\"]=P.text.raw.analyseAll(texts)\n# sectors_analysis[\"pos\"]= P.text.pos.analyseAll(sectors_analysis[\"raw_analysis\"])\n# sectors_analysis[ \"wordnet\" ]=P.text.wordnet.analyseAll(sectors_analysis[\"pos_analysis\"])\n# sectors_analysis[\"tfIdf\"]=P.text.tfIdf.tfIdf(texts)\n\n overall_measures[\"raw_strings\"]=P.text.raw.systemAnalysis(sectors_analysis) # medias de toda a rede por mensagem, por autor e por setor\n overall_measures[\"pos\"]=P.text.raw.systemAnalysis(sectors_analysis) # medias de toda a rede por mensagem, por autor e por setor\n overall_measures[\"wordnet\"]=P.text.raw.systemAnalysis(sectors_analysis) # medias de toda a rede por mensagem, por autor e por setor\n # tfIdf measurespor texto, autor e setor, numeric: media e desvio das distancias por cada grupo, media e desvio dos setores e dos autores\n overall_measures[\"tfIdf\"]=P.text.tfIdf.systemAnalysis(sectors_analysis) # medias de toda a rede por mensagem, por autor e por setor\n\n del authors_texts,sectorialized_agents,author, sector\n return locals()","def evaluate(self, clustering):\n # Pca for each one of the clusters\n pca_mean_val = 0.;\n MAX_ELEMENTS = 1000\n for c in clustering.clusters:\n # Pick the coordinates (ensuring that we are copying them)\n element_indexes = c.all_elements\n ###################\n # Performance hack\n ###################\n # As it can be very slow for big clusters (i.e. > 3k elements) we'll compress this clusters \n # before calculating PCA. It should increase variance but will allow calculations.\n # It should use the kmedoids compressor\n if len(c.all_elements) > MAX_ELEMENTS:\n element_indexes = c.get_random_sample(MAX_ELEMENTS)\n print \"[PCA] Random sampling too big cluster to improve performance (%d elements -> %d elements).\"%(len(c.all_elements),MAX_ELEMENTS)\n ###################\n \n fitting_coordinates_of_this_cluster = self.fitting_coordinates[element_indexes]\n \n calculator = RMSDCalculator(calculatorType = \"QTRFIT_SERIAL_CALCULATOR\",\n fittingCoordsets = fitting_coordinates_of_this_cluster)\n \n if self.calculation_coordinates is not None:\n calculation_coordinates_of_this_cluster = self.calculation_coordinates[element_indexes]\n calculator = RMSDCalculator(calculatorType = \"QTRFIT_SERIAL_CALCULATOR\",\n fittingCoordsets = fitting_coordinates_of_this_cluster,\n calculationCoordsets = calculation_coordinates_of_this_cluster)\n \n # Make an iterative superposition (to get the minimum RMSD of all with respect to a mean conformation)\n calculator.iterativeSuperposition()\n\n # Calculate the covariance matrix\n if self.calculation_coordinates is None:\n covariance_matrix = PCAMetric.create_covariance_matrix(fitting_coordinates_of_this_cluster)\n else:\n covariance_matrix = PCAMetric.create_covariance_matrix(calculation_coordinates_of_this_cluster)\n \n # And then the eigenvalue we are interested in\n pca_mean_val += PCAMetric.calculate_biggest_eigenvalue(covariance_matrix)\n print \"PCA finished\"\n return pca_mean_val /clustering.total_number_of_elements","def _compute_util_data(self):\n\n print(\"Computing PCA of document vectors.\")\n self.pca = PCA(n_components = 3)\n\n print(\"Computing document clusters in PCA basis.\")\n inferred_vecs = np.array([self.model.infer_vector(doc.words) for doc in self.tagged_docs])\n self.pca_reduced_vecs = self.pca.fit_transform(inferred_vecs)\n n_clusters = 25 # TODO find way to determine approx cluster size\n self.kmeans = KMeans(init = 'k-means++', n_clusters = n_clusters, random_state = 0)\n self.kmeans_preds = self.kmeans.fit_predict(self.pca_reduced_vecs)","def compute_feature_properties(self):\n\n self.valuecounts = {}\n self.unique_values = {}\n self.missing_ratios = {}\n self.counts = {}\n self.codemaps = {}\n for f in self.features:\n # Compute various things\n all_values = [self.data[l].get(f,\"?\") for l in self.data]\n missing_data_ratio = all_values.count(\"?\") / (1.0*len(all_values))\n non_q_values = [v for v in all_values if v != \"?\"]\n counts = {}\n for v in non_q_values:\n counts[v] = non_q_values.count(v)\n unique_values = list(set(non_q_values))\n # Sort unique_values carefully.\n # Possibly all feature values are numeric strings, e.g. \"1\", \"2\", \"3\".\n # If we sort these as strings then we get weird things like \"10\" < \"2\".\n # This can actually matter for things like ordinal models.\n # So convert these to ints first...\n if all([v.isdigit() for v in unique_values]):\n unique_values = list(map(int, unique_values))\n unique_values.sort()\n unique_values = list(map(str, unique_values))\n # ...otherwise, just sort normally\n else:\n unique_values.sort()\n self.unique_values[f] = unique_values\n\n N = len(unique_values)\n self.valuecounts[f] = N\n self.missing_ratios[f] = missing_data_ratio\n self.counts[f] = counts\n self.codemaps[f] = self.build_codemap(unique_values)","def compute_statistics(self):\n for i in range(len(self.wine_matrix[0, :])):\n feature = self.wine_matrix[:, i]\n self.wine_stats['feature ' + str(i)] = {}\n if i == 11: # results column\n self.wine_stats['feature ' + str(i)]['positive_class_ratio'] = (feature == 1).sum() / len(feature)\n null, self.wine_stats['feature ' + str(i)]['pvalue'] = stats.normaltest(feature)\n\n # plot\n # pyplot.hist(feature, bins=50)\n # pyplot.show()\n\n for i in range(len(self.cancer_matrix[0, :])):\n feature = self.cancer_matrix[:, i]\n self.cancer_stats['feature ' + str(i)] = {}\n if i == 10: # results column\n self.cancer_stats['feature ' + str(i)]['positive_class_ratio'] = (feature == 1).sum() / len(feature)\n null, self.cancer_stats['feature ' + str(i)]['pvalue'] = stats.normaltest(feature)\n\n # plot\n # pyplot.hist(feature, bins=50)\n # pyplot.show()","def aggregate_results(results):\n\n for (config,con,dec),folds in results.iteritems():\n m = MODEL_PATTERN.match(config)\n if m:\n mode = m.groupdict()['mode'] # mle, rl, mrt, ...\n model = m.groupdict()['model'] # haem, hacm, hard, ...\n align = m.groupdict()['align'] # crp, cls ...\n else:\n mode, model, align = '', '', ''\n # mean accuracies across seeds for each fold\n foldaccuracies = []\n # we count number of models over folds and seeds\n num_individual_models = 0\n\n for foldname,fold in folds.items():\n if 'Q' in options.mode:\n seedaccurracies = fold.values()[:1] if fold.values() else [] # pick one\n# SUPPORT_STATISTICS[(config,con,dec,model,align,mode,foldname)] += 1\n else:\n seedaccurracies = []\n for seed_acc in fold.values():\n seedaccurracies.append(seed_acc)\n SUPPORT_STATISTICS[(config,con,dec,model,align,mode,foldname)] += 1\n # aggregate on fold level\n fold['__MEAN__'] = float(np.mean(seedaccurracies))\n fold['__SD__'] = float(np.std(seedaccurracies))\n l = len(seedaccurracies)\n num_individual_models += l\n SUPPORT_STATISTICS[(config,con,dec,model,align,mode,'__MEAN__')] += l\n SUPPORT_STATISTICS[(config,con,dec,model,align,mode,'__SD__')] += l\n\n # statistics over seeds for this fold\n fold['__STATS__'] = fold['__MEAN__'], fold['__SD__'], l\n foldaccuracies.append(fold['__MEAN__'])\n # aggregate on (config, condition, decoding) level\n folds['__MEAN__'] = float(np.mean(foldaccuracies))\n folds['__SD__'] = float(np.std(foldaccuracies))\n # statistics over folds for this (config, condition, decoding)\n folds['__STATS__'] = folds['__MEAN__'], folds['__SD__'], num_individual_models","def compute_metrics(\n Phi, optimal_subspace\n):\n feature_norm = jnp.linalg.norm(Phi) / Phi.shape[0]\n cosine_similarity = compute_cosine_similarity(Phi, optimal_subspace)\n\n metrics = {\n 'cosine_similarity': cosine_similarity,\n 'feature_norm': feature_norm,\n 'eigengame_subspace_distance': eigengame_subspace_distance(\n Phi, optimal_subspace\n ),\n }\n\n _, d = Phi.shape\n if d > 1:\n grassman_distance = compute_grassman_distance(Phi, optimal_subspace)\n metrics |= {'grassman_distance': grassman_distance}\n elif d == 1:\n dot_product = compute_normalized_dot_product(Phi, optimal_subspace)\n metrics |= {'dot_product': dot_product}\n\n return metrics","def extractBestAlgorithms(args = algs2009, f_factor=2,\n target_lb=1e-8, target_ub=1e22):\n\n # TODO: use pproc.TargetValues class as input target values\n # default target values:\n targets = pproc.TargetValues(\n 10**np.arange(np.log10(max((1e-8, target_lb))),\n np.log10(target_ub) + 1e-9, 0.2))\n # there should be a simpler way to express this to become the\n # interface of this function\n\n print 'Loading algorithm data from given algorithm list...\\n' \n\n verbose = True\n dsList, sortedAlgs, dictAlg = pproc.processInputArgs(args, verbose=verbose)\n\n print 'This may take a while (depending on the number of algorithms)'\n\n selectedAlgsPerProblem = {}\n for f, i in pproc.dictAlgByFun(dictAlg).iteritems():\n for d, j in pproc.dictAlgByDim(i).iteritems():\n selectedAlgsPerProblemDF = []\n best = BestAlgSet(j)\n \n for i in range(0, len(best.target)):\n t = best.target[i]\n # if ((t <= target_ub) and (t >= target_lb)):\n if toolsstats.in_approximately(t,\n targets((f, d), discretize=True)):\n # add best for this target:\n selectedAlgsPerProblemDF.append(best.algs[i])\n \n # add second best or all algorithms that have an ERT\n # within a factor of f_factor of the best:\n secondbest_ERT = np.infty\n secondbest_str = ''\n secondbest_included = False \n for astring in j:\n currdictalg = dictAlg[astring].dictByDim()\n if currdictalg.has_key(d):\n curralgdata = currdictalg[d][f-1] \n currERT = curralgdata.detERT([t])[0]\n if (astring != best.algs[i]):\n if (currERT < secondbest_ERT):\n secondbest_ERT = currERT\n secondbest_str = astring\n if (currERT <= best.detERT([t])[0] * f_factor):\n selectedAlgsPerProblemDF.append(astring)\n secondbest_included = True\n if not (secondbest_included) and (secondbest_str != ''):\n selectedAlgsPerProblemDF.append(secondbest_str)\n \n if len(selectedAlgsPerProblemDF) > 0:\n selectedAlgsPerProblem[(d, f)] = selectedAlgsPerProblemDF\n \n print 'pre-processing of function', f, 'done.' \n \n print 'loading of best algorithm(s) data done.'\n \n countsperalgorithm = {}\n for (d, f) in selectedAlgsPerProblem:\n print 'dimension:', d, ', function:', f\n setofalgs = set(selectedAlgsPerProblem[d,f])\n \n # now count how often algorithm a is best for the extracted targets\n for a in setofalgs:\n # use setdefault to initialize with zero if a entry not existant:\n countsperalgorithm.setdefault((d, a), 0) \n countsperalgorithm[(d,a)] += selectedAlgsPerProblem[d,f].count(a)\n \n selectedalgsperdimension = {}\n for (d,a) in sorted(countsperalgorithm):\n if not selectedalgsperdimension.has_key(d):\n selectedalgsperdimension[d] = []\n selectedalgsperdimension[d].append((countsperalgorithm[(d,a)], a))\n \n for d in sorted(selectedalgsperdimension):\n print d, 'D:'\n for (count, alg) in sorted(selectedalgsperdimension[d], reverse=True):\n print count, alg\n print '\\n'\n \n \n print \" done.\"\n \n return selectedalgsperdimension","def get_clusters(ensemble, grouping, clustering):\n\n\t# Prevent SQL injected since column names cannot be parameterized.\n\tif \";\" in ensemble or \";\" in grouping or \";\" in clustering:\n\t\treturn None\n\n\tensemble = ensemble.replace('EnsEns','Ens')\n\tdf = None;\n\n\tif grouping in ['annotation','cluster']:\n\t\tgroupingu = ensemble+\".\"+grouping+\"_\"+clustering\n\telif grouping in ['NeuN']:\n\t\tgroupingu = \"CONCAT('NeuN',cells.\"+grouping+\")\"\n\telse:\n\t\tgroupingu = \"cells.\"+grouping\n\n\t# Get methylation info\n\tquery = \"SELECT count(cells.cell_id) ncells, 'snmC' as modality, \\\n\t\t%(groupingu)s as groups \\\n\t\tFROM cells \\\n\t\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\n\t\tGROUP BY groups \" % {'ensemble': ensemble,\n\t\t\t\t\t'groupingu': groupingu,\n\t\t\t\t\t'clustering': clustering}\n\ttry:\n\t\tdf = pd.read_sql(query, db.get_engine(current_app, 'methylation_data'))\n\texcept exc.ProgrammingError as e:\n\t\tnow = datetime.datetime.now()\n\t\tprint(\"[{}] ERROR in app(get_clusters): {}\".format(str(now), e))\n\t\tsys.stdout.flush()\n\t\t# return None\n\n\t# Get snATAC info\n\tquery = \"SELECT count(cells.cell_id) ncells, 'snATAC' AS modality, %(ensemble)s.cluster_ATAC groups \\\n\t\tFROM cells \\\n\t\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\n\t\tGROUP BY groups \" % {'ensemble': ensemble,\n\t\t\t\t\t'grouping': grouping,\n\t\t\t\t\t'clustering': clustering}\n\n\ttry:\n\t\tdf_atac = pd.read_sql(query, db.get_engine(current_app, 'snATAC_data'))\n\t\tdf=df.append(df_atac)\n\texcept exc.ProgrammingError as e:\n\t\tnow = datetime.datetime.now()\n\t\tprint(\"[{}] ERROR in app(get_clusters): {}\".format(str(now), e))\n\t\tsys.stdout.flush()\n\n\n\t# Get snRNA info\n\tquery = \"SELECT count(cells.cell_id) ncells, 'RNA' AS modality, %(ensemble)s.cluster_RNA groups \\\n\t\tFROM cells \\\n\t\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\n\t\tGROUP BY groups \" % {'ensemble': ensemble,\n\t\t\t\t\t'grouping': grouping,\n\t\t\t\t\t'clustering': clustering}\n\n\ttry:\n\t\tdf_rna = pd.read_sql(query, db.get_engine(current_app, 'RNA_data'))\n\t\tdf=df.append(df_rna)\n\texcept exc.ProgrammingError as e:\n\t\tnow = datetime.datetime.now()\n\t\tprint(\"[{}] ERROR in app(get_clusters): {}\".format(str(now), e))\n\t\tsys.stdout.flush()\n\n\treturn df","def clustering_and_visulization(self):\n centroids, _ = kmeans(self.data_mat, self.k)\n idx, _ = vq(self.data_mat, centroids)\n for i in range(self.k):\n\n self.plot_list.append(self.data_mat[idx == i, 0])\n self.plot_list1.append(self.data_mat[idx == i, 1])\n\n for j in range(self.k):\n plot(self.plot_list[j], self.plot_list1[j], self.color_code[j])\n plot(centroids[:, 0], centroids[:, 1], 'sg', markersize=8)\n show()\n for i in range(self.k):\n self.cluster = self.data_mat[idx == i]\n self.clusterlist.append(self.cluster)\n\n for i in range(len(self.clusterlist)):\n self.clusterdict[i] = self.clusterlist[i]\n print(self.clusterdict)\n\n\n self.indexdict = {}\n for i in self.clusterdict:\n self.indexdict[i] = []\n print(len(self.clusterdict))\n for i in range(len(idx)):\n for j in range(len(self.clusterdict)):\n if (self.clusterdict[j][:] == self.data_mat[i]).any():\n self.indexdict[j].append(i)\n print(\"cluster dict of packs\",self.indexdict)\n\n self.drugdict = {}\n for i in self.clusterdict:\n self.drugdict[i] = []\n self.drug=[]\n for i in range(len(self.indexdict.keys())):\n for j in range(len(self.indexdict[i])):\n self.drugdict[i].append(self.df.iloc[self.indexdict[i][j]].to_dict())\n print(\"drugs dict with their frequencies\",self.drugdict)\n clusterdict_from_df_as_drug_non_O_frequency = {}\n clusterdict_from_as_drugs_only_as_list = {}\n clusterdict_of_non_repeated_drugs ={}\n for i in self.drugdict:\n clusterdict_from_df_as_drug_non_O_frequency[i] = []\n for i in self.drugdict:\n for j in self.drugdict[i]:\n clusterdict_from_df_as_drug_non_O_frequency[i].append({x: y for x, y in j.items() if y != 0})\n print(\"clusterdict_from_df_as_drug_non_O_frequency\", clusterdict_from_df_as_drug_non_O_frequency)\n print('\\n')\n\n for i in self.drugdict:\n clusterdict_from_as_drugs_only_as_list[i] = []\n\n for i in self.drugdict:\n for j in clusterdict_from_df_as_drug_non_O_frequency[i]:\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\n\n print(\"only keys drugs with drugs name\", clusterdict_from_as_drugs_only_as_list)\n print('\\n')\n\n\n for i in self.drugdict:\n clusterdict_of_non_repeated_drugs[i]=list(more_itertools.collapse([list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\n\n\n print(\"only drugs only\", clusterdict_of_non_repeated_drugs)\n\n########################################################################################################################\n try:\n common_drug_list = [x for x in clusterdict_of_non_repeated_drugs[0] if x in clusterdict_of_non_repeated_drugs[1]]\n print('\\n')\n print(\"common drug list\", common_drug_list)\n total_frequency_of_drugs_dict = {}\n for i in self.drugdict:\n total_frequency_of_drugs_dict[i] = []\n\n for drug in common_drug_list:\n\n for cluster_keys in clusterdict_from_df_as_drug_non_O_frequency.keys():\n temp_list = []\n for cluster_values_as_list in clusterdict_from_df_as_drug_non_O_frequency[cluster_keys]:\n try:\n temp_list.append(cluster_values_as_list[str(drug)])\n except KeyError:\n print(\"\\t\")\n total_frequency_of_drugs_dict[cluster_keys].append(np.sum(temp_list))\n print(\"total drugs frequency\",total_frequency_of_drugs_dict)\n total_frequency_of_drugs_dict_with_drugs = {}\n for i in self.drugdict:\n total_frequency_of_drugs_dict_with_drugs[i] = []\n temp_list1 = []\n temp_list2 = []\n for keys in self.drugdict.keys():\n temp_list1.append(clusterdict_of_non_repeated_drugs[keys])\n for keys in self.drugdict.keys():\n temp_list2.append(total_frequency_of_drugs_dict[keys])\n temp_list3 = []\n for i in temp_list1:\n for j in temp_list2:\n temp_list3.append(dict(zip(i,j)))\n temp_list4 = temp_list3[:2]\n print('\\n')\n for keys in self.drugdict:\n total_frequency_of_drugs_dict_with_drugs[keys].append(temp_list4[keys])\n print(\"total frequency with drugs dict\",total_frequency_of_drugs_dict_with_drugs)\n\n final_drugs_in_clusters_dict = {}\n for i in self.drugdict:\n final_drugs_in_clusters_dict[i] = []\n compare_list = []\n for drug in common_drug_list:\n compare_list.append(min(total_frequency_of_drugs_dict_with_drugs[0][0][drug], total_frequency_of_drugs_dict_with_drugs[1][0][drug]))\n print(\"compare list\",compare_list)\n for values in total_frequency_of_drugs_dict_with_drugs.values():\n for key1, value1 in values[0].items():\n if value1 in compare_list:\n\n key2 =values[0].keys()[values[0].values().index(value1)]\n values[0].pop(key2, None)\n\n\n print('final dict with deleted keys', total_frequency_of_drugs_dict_with_drugs)\n\n clusterdict_from_as_drugs_only_as_list = {}\n clusterdict_of_non_repeated_drugs = {}\n\n for i in self.drugdict:\n clusterdict_from_as_drugs_only_as_list[i] = []\n\n for i in self.drugdict:\n for j in total_frequency_of_drugs_dict_with_drugs[i]:\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\n print(\"only keys drugs with drugs name\", clusterdict_from_as_drugs_only_as_list)\n print('\\n')\n\n for i in self.drugdict:\n clusterdict_of_non_repeated_drugs[i] = list(more_itertools.collapse([list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\n print(\"only drugs\",clusterdict_of_non_repeated_drugs)\n\n final_robot_packs_dict = {}\n for i in self.drugdict:\n final_robot_packs_dict[i] = []\n\n winner_drug_dict = {}\n for i in common_drug_list:\n winner_drug_dict[i] = []\n for drug in common_drug_list:\n if drug in clusterdict_of_non_repeated_drugs[0]:\n winner_drug_dict[str(drug)].append(0)\n if drug in clusterdict_of_non_repeated_drugs[1]:\n winner_drug_dict[str(drug)].append(1)\n print(\"winner drug dict\",winner_drug_dict)\n\n for i in self.indexdict:\n print(i)\n for pack in self.indexdict[i]:\n packdict = self.df.iloc[pack].to_dict()\n packdict_non_0 = {x: y for x, y in packdict.items() if y != 0}\n packdict_non_0_key = packdict_non_0.keys()\n for drug in packdict_non_0_key:\n if drug in clusterdict_of_non_repeated_drugs[0]:\n final_robot_packs_dict[0].append(pack)\n elif drug in clusterdict_of_non_repeated_drugs[1]:\n final_robot_packs_dict[1].append(pack)\n\n final_robot_packs_dict[i].append(pack)\n for commondrugs in winner_drug_dict:\n for winnercluster in winner_drug_dict[commondrugs]:\n if winnercluster==0:\n loosercluster =1\n if winnercluster == 1:\n loosercluster = 0\n if commondrugs in packdict_non_0_key and i==loosercluster:\n try:\n final_robot_packs_dict[i].remove(pack)\n final_robot_packs_dict[winnercluster].append(pack)\n except ValueError:\n print('\\t')\n\n for i in self.indexdict:\n final_robot_packs_dict[i] = set(final_robot_packs_dict[i])\n\n print(\"final which pack which robot dict\",final_robot_packs_dict)\n\n except IndexError:\n print(\"No common drugs\")","def clustering_metrics(clusts, node_assn, node_pred):\n pred_vox = cluster_to_voxel_label(clusts, node_pred)\n true_vox = cluster_to_voxel_label(clusts, node_assn)\n ari = ARI(pred_vox, true_vox)\n ami = AMI(pred_vox, true_vox)\n sbd = SBD(pred_vox, true_vox)\n pur, eff = purity_efficiency(pred_vox, true_vox)\n return ari, ami, sbd, pur, eff","def get_combinations(classes_folder='./data/CASIA1_classes_by_unbalanced_kmeans/', \n originals='./data/CASIA1_originals', fakes_ela='./data/CASIA1_fakes_ela'):\n classes_ = []\n for i in range(20):\n classes_.append('{}{}' .format(classes_folder, i+1))\n\n medians_ = [0,3,5,7,9,11,13,15,17,19]\n\n iterations_ = []\n for i in range(21):\n iterations_.append(i)\n\n threshold_ = []\n for i in range(40):\n threshold_.append(i)\n\n for i, item in enumerate(classes_):\n fakes_list = os.listdir(item)\n fakes = load_fakes(fakes_list, item, originals)\n\n best = 0\n best_median_filter_size = 0\n best_number_of_iterations = 0\n best_thresh = 0\n for x, median_filter_size in enumerate(medians_):\n for y, number_of_iterations in enumerate(iterations_):\n for t, thresh in enumerate(threshold_):\n whole_score = 0\n for e, elem in enumerate(fakes):\n image = cv2.imread(os.path.join(fakes_ela, elem.path.split('\\\\')[-1]))\n\n if thresh > 0:\n image_ = pywt.threshold(image, thresh, 'soft')\n image = cv2.normalize(image_, image, 0, 1, cv2.NORM_MINMAX)\n image = 255 * image\n image = image.astype(np.uint8)\n\n image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)\n \n image = cv2.inRange(image, np.array([0,0,0]), np.array([180,255,60]))\n image = cv2.bitwise_not(image)\n\n if median_filter_size > 0:\n image = cv2.medianBlur(image, median_filter_size)\n\n kernel = np.ones((3, 3), np.uint8)\n image = cv2.morphologyEx(image, cv2.MORPH_GRADIENT, kernel, iterations=number_of_iterations)\n\n cnts = cv2.findContours(image.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n cnts = imutils.grab_contours(cnts)\n\n max_idx = 0\n max_pnts = 0\n for u, ulem in enumerate(cnts):\n if cv2.contourArea(ulem) < max_pnts:\n continue\n else:\n max_idx = u\n max_pnts = cv2.contourArea(ulem)\n\n if len(cnts) > 0:\n (x, y, w, h) = cv2.boundingRect(cnts[max_idx])\n pred = {\n \"x\": x,\n \"y\": y,\n \"w\": w,\n \"h\": h\n }\n else:\n pred = None\n\n whole_score += evaluate_augmentation_fit(pred, elem)\n if best < whole_score:\n best = whole_score\n best_median_filter_size = median_filter_size\n best_number_of_iterations = number_of_iterations\n best_thresh = thresh\n print(\"Class: {}; MedianFilterSize: {}; Iterations: {}; Thresh: {}; Score: {}\" .format(item, median_filter_size, number_of_iterations, thresh, round(whole_score, 2)))\n print(\"###########\")\n print(\"Best: {} -> {} % ({}, {}, {})\" .format(round(best, 2), round((best/len(fakes)), 2), best_median_filter_size, best_number_of_iterations, best_thresh))\n print(\"###########\")","def calculate_clusters(study_id):\n\n with current_app.app_context():\n cur = conn.cursor()\n\n cur.execute(\"\"\"SELECT * FROM STATS WHERE STUDY_ID=%s\"\"\", (str(study_id),))\n study = fetchoneClean(cur)\n clusters_calculating = study[4]\n clusters_changed = study[5]\n if clusters_changed:\n if clusters_calculating:\n return {'message': 'calculating'}\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CALCULATING = TRUE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n conn.commit()\n\n distance = study[7]['matrix']\n card_names = study[7]['cardNames']\n cur.execute(\"\"\"SELECT COUNT(ID) FROM PARTICIPANT WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n total_participants = fetchoneClean(cur)[0]\n\n distance_matrix = calculate_square_form(distance, total_participants)\n distArray = ssd.squareform(distance_matrix)\n\n try:\n clusters = hierarchy.linkage(distArray, method='average')\n except ValueError:\n return {'message': 'not enough data'}\n\n tree = hierarchy.to_tree(clusters, rd=False)\n # TODO Distance 0 on root\n dendro = dict(children=[], hierarchy=0, distance=100)\n add_node(tree, dendro, card_names)\n\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS = %s WHERE STUDY_ID = %s\"\"\", (json.dumps(dendro), str(study_id),))\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CALCULATING = FALSE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CHANGED = FALSE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n conn.commit()\n else:\n dendro = study[6]\n\n return dendro","def apply_algorithms(x: np.ndarray, label_true, params, components, database_name):\n names = ['Original dataset', 'Our PCA results', 'KMeans with previous our PCA reduction',\n 'KMeans without previous reduction (PCA)', 'KMeans without previous reduction (T-SNE)']\n\n datasets = []\n labels = []\n reduct = []\n\n # get the representation of the original matrix splitted to be plotted\n partial_x = split_db_original(x, components)\n datasets.append(partial_x)\n labels.append(label_true)\n reduct.append(None)\n\n # get our PCA\n pca = OPCA(n_components=params['n_components'])\n our_pca = pca.fit_transform(x)\n datasets.append(our_pca)\n labels.append(label_true)\n reduct.append(None)\n\n # get PCA and IPCA from sklearn\n sk_pca = pca_sklearn(x, params['db_name'], params['n_components'])\n sk_ipca = ipca_sklearn(x, params['db_name'], params['n_components'])\n\n # compare the three PCA algorithms\n name = ['Our PCA', 'SK_PCA', 'SK_IPCA', 'original_data']\n pca_data = [our_pca, sk_pca['db'], sk_ipca['db'], x]\n apply_evaluation(pca_data, label_true, params, name, database_name)\n\n # KMeans with PCA reduction\n algorithm = KMeans(k=params['k'], seed=params['seed'], max_it=params['max_it'], tol=params['tol'])\n labels_kmeans = algorithm.fit_predict(our_pca)\n datasets.append(our_pca)\n labels.append(labels_kmeans)\n reduct.append(None)\n\n # KMeans without PCA reduction\n algorithm = KMeans(k=params['k'], seed=params['seed'], max_it=params['max_it'], tol=params['tol'])\n labels_kmeans = algorithm.fit_predict(x)\n datasets.append(x)\n labels.append(labels_kmeans)\n reduct.append('pca')\n datasets.append(x)\n labels.append(labels_kmeans)\n reduct.append('tsne')\n\n # selection number of dimensions of plot\n if type(params['n_components']) == int:\n if params['n_components'] == 2:\n nd = 2\n if params['n_components'] > 2:\n nd = 3\n elif type(params['n_components']) == float:\n if our_pca.shape[1] == 2:\n nd = 2\n if our_pca.shape[1] > 2:\n nd = 3\n else:\n nd = 3\n\n if nd == 2:\n pca_names = ['PCA Component 1', 'PCA Component 2']\n plot_names = [components[0], pca_names, pca_names, pca_names, ['TSNE 1', 'T-SNE 2']]\n plot2d(datasets, labels, names, plot_names, reduct)\n elif nd == 3:\n pca_names = ['PCA Component 1', 'PCA Component 2', 'PCA Component 3']\n plot_names = [components[0], pca_names, pca_names, pca_names, ['TSNE 1', 'T-SNE 2', 'T-SNE 3']]\n plot3d(datasets, labels, names, plot_names, reduct)","def evaluate(self):\n results = dict()\n for metric in self.metrics:\n print('Evaluating clustering with metric %s' % metric)\n if metric in LABEL_METRICS.keys():\n results[metric] = LABEL_METRICS[metric](self.X, self.model.labels_)\n results['adjusted_rand_score'] = SCORE_METRICS['adjusted_rand_score'](self.Y[:, 0], self.model.labels_)\n self.results = results\n return results","def __tool_classification__(self,task_id,shape,aggregations):\n\n print \"tool classification - more than one tool could create \" +str(shape) + \"s in task \" + str(task_id)\n\n if aggregations == {}:\n print \"warning - empty classifications\"\n return {}\n\n # only go through the \"uncertain\" shapes\n tool_classifications = {}\n\n for subject_id in aggregations:\n # look at the individual points in the cluster\n\n for cluster_index,cluster in aggregations[subject_id][task_id][shape+ \" clusters\"].items():\n # all_users just gives us a list of all of the users who have seen this subject\n # not relevant here\n if cluster_index == \"all_users\":\n continue\n\n # which users marked this cluster\n users = cluster[\"users\"]\n # which tool each individual user used\n tools = cluster[\"tools\"]\n assert len(tools) == len(users)\n\n # in this case, we want to \"vote\" on the tools\n ballots = zip(users,tools)\n\n tool_classifications[(subject_id,cluster_index)] = ballots\n\n # classify\n print \"tool results classification\"\n tool_results = self.__task_aggregation__(tool_classifications,task_id,{})\n assert isinstance(tool_results,dict)\n\n for subject_id,cluster_index in tool_results:\n\n new_results = tool_results[(subject_id,cluster_index)][task_id]\n # the clustering results already exist so we are just adding more data to it\n aggregations[subject_id][task_id][shape + \" clusters\"][cluster_index][\"tool_classification\"] = new_results\n\n return aggregations","def algorithm_parameters(alg):\n if alg in list(SEM_TYPE.keys()):\n return simulate_parameters(alg)\n\n param_dict = dict()\n\n param = getfullargspec(INLINE_ALGORITHMS[alg.upper()].__init__)\n if param is not None:\n param_len = len(param.args)\n if param.defaults:\n if 'input_dim' in param.args:\n param_dict.update({'input_dim': None})\n for index, value in enumerate(reversed(param.defaults)):\n if not isfunction(value) and (value is not None):\n param_dict.update(\n {param.args[param_len - index - 1]: value})\n param = getfullargspec(INLINE_ALGORITHMS[alg.upper()].learn)\n if param is not None:\n param_len = len(param.args)\n if param_len > 2:\n if 'rank' in param.args:\n param_dict.update({'rank': None})\n return param_dict","def clustering_and_visulization(self):\n try:\n centroids, _ = kmeans(self.data_mat, self.k)\n except ValueError:\n print(\"The number of clusters is more than the data points\")\n self.idx, _ = vq(self.data_mat, centroids)\n for i in range(self.k):\n\n self.plot_list.append(self.data_mat[self.idx == i, 0])\n self.plot_list1.append(self.data_mat[self.idx == i, 1])\n\n for j in range(self.k):\n plot(self.plot_list[j], self.plot_list1[j], self.color_code[j])\n plot(centroids[:, 0], centroids[:, 1], 'sg', markersize=8)\n show()\n\n for i in range(self.k):\n self.cluster = self.data_mat[self.idx == i]\n self.clusterlist.append(self.cluster)\n print(self.clusterlist)\n for i in range(len(self.clusterlist)):\n self.clusterdict[i] = self.clusterlist[i]\n print(self.clusterdict)\n\n index_dict ={}\n for i in self.clusterdict:\n index_dict[i] = []\n for i in range(len(self.data_mat)):\n for j in range(len(self.clusterdict)):\n if (self.clusterdict[j][:] == self.data_mat[i]).any():\n index_dict[j].append(i)\n print(\"drugs cluster dict\", index_dict)\n\n self.drugsdict = {}\n for i in index_dict:\n self.drugsdict[i] = []\n drugslist = list(self.df.columns.values)\n print(\"drugs list from dataframe\", drugslist)\n\n for i in index_dict:\n self.drugsdict[i] = [drugslist[index] for index in index_dict[i]]\n\n print(\"drugs cluster dict\", self.drugsdict)\n########################################################################################################################\n clusterdict_from_df_as_drug_frequency = {}\n clusterdict_from_df_as_drug_non_O_frequency = {}\n\n print('\\n')\n\n for i in range(len(self.df)):\n clusterdict_from_df_as_drug_frequency[i] = []\n\n for i in range(len(self.df)):\n clusterdict_from_df_as_drug_frequency[i].append(self.df.iloc[i].to_dict()) #\n print(\"packs in dict form of drugs frequency\", clusterdict_from_df_as_drug_frequency)\n\n for i in range(len(self.df)):\n clusterdict_from_df_as_drug_non_O_frequency[i] = []\n\n for i in range(len(self.df)):\n for j in clusterdict_from_df_as_drug_frequency[i]:\n clusterdict_from_df_as_drug_non_O_frequency[i].append({x: y for x, y in j.items() if y != 0})\n print(\"clusterdict_from_df_as_drug_non_O_frequency\", clusterdict_from_df_as_drug_non_O_frequency)\n print('\\n')\n clusterdict_from_as_drugs_only_as_list = {}\n clusterdict_of_non_repeated_drugs = {}\n for i in range(len(self.df)):\n clusterdict_from_as_drugs_only_as_list[i] = []\n\n for i in range(len(self.df)):\n for j in clusterdict_from_df_as_drug_non_O_frequency[i]:\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\n\n print(\"only keys drugs with drugs name\", clusterdict_from_as_drugs_only_as_list)\n print('\\n')\n\n for i in range(len(self.df)):\n clusterdict_of_non_repeated_drugs[i] = list(more_itertools.collapse(\n [list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\n\n print(\"only drugs only\", clusterdict_of_non_repeated_drugs)\n\n########################################################################################################################\n robot_for_packs_dict = {}\n for i in range(len(self.df)):\n robot_for_packs_dict[i] = []\n\n # for i in range(len(self.df)):\n for i in range(len(self.df)):\n for j in clusterdict_of_non_repeated_drugs[i]:\n if j in self.drugsdict[0]:\n robot_for_packs_dict[i].append(0)\n elif j in self.drugsdict[1]:\n robot_for_packs_dict[i].append(1)\n for i in range(len(self.df)):\n robot_for_packs_dict[i] = set(robot_for_packs_dict[i])\n\n for i in range(len(self.df)):\n robot_for_packs_dict[i] = list(more_itertools.collapse(robot_for_packs_dict[i]))\n print('\\n')\n print(\"clusterdict_of_non_repeated_drugs\", robot_for_packs_dict)","def compute_cluster_similarities(emb_clusters1, emb_clusters2, compare, order, clmethod, plot):\n def compute_sim(e, e1, cls, cls1):\n sims = np.empty((20, 20))\n xticks, yticks = [], []\n for i, c in enumerate(cls):\n yticks.append(', '.join(c[1]) + (f' {round(c[3], 5)}' if order == 'avgfreq' else ''))\n for j, c1 in enumerate(cls1):\n if len(xticks) < 20:\n xticks.append(', '.join(c1[1]) + (f' {round(c1[3], 5)}' if order == 'avgfreq' else ''))\n sims[i, j] = jaccard_similarity_score(c[2], c1[2])\n jaccard_similarities[f'{e}-{e1}'] = sims\n\n if plot:\n if order == 'clustermap':\n similarity_clustermap(sims, xticks, yticks, f'{e}-{e1}_{clmethod}')\n elif order == 'default' or order == 'avgfreq':\n similarity_heatmap(sims, xticks, yticks, f'{e}-{e1}_{clmethod}', order)\n else:\n pass\n\n jaccard_similarities = {}\n if compare == 'cross':\n for ie, (e, cls) in enumerate(emb_clusters1.items()):\n for ie1, (e1, cls1) in enumerate(emb_clusters2.items()):\n if ie < ie1:\n compute_sim(e, e1, cls, cls1)\n elif compare == 'dot':\n for (e, cls), (e1, cls1) in zip(emb_clusters1.items(), emb_clusters2.items()):\n compute_sim(e, e1, cls, cls1)\n\n return jaccard_similarities","def integrated_clustering(t_all,y_all,num_of_days=500,period = 1440,trim=10,min_n_clusters = 4, max_n_clusters=10,hierarchical=0):\n\n\n\n all_seg_april = initial_disaggregate(t_all,y_all,num_of_days,period = period)\n \n ''' '''\n all_seg_april_normalized = [np.array(x[0])-np.mean(x[1]) for x in all_seg_april if len(x[1])==3]\n \n ''' filter the empty segments'''\n all_seg_april_normalized = [x for x in all_seg_april_normalized if len(x)>0]\n \n ''' clustering in different ranges will probably have a better result'''\n if hierarchical == 0:\n pass\n elif hierarchical ==1:\n all_seg_april_normalized = [x for x in all_seg_april_normalized if x.mean()>1000]\n else:\n all_seg_april_normalized = [x for x in all_seg_april_normalized if x.mean()<1000]\n \n ''' filter out the positive segments'''\n all_positive_seg_april_normalized = [x for x in all_seg_april_normalized if x.min()>0]\n \n \n all_seg_april_normalized_trim50 = extract_first_n(all_positive_seg_april_normalized, trim)\n cluster_average = []\n \n # find optimal clustering number using silhouette score\n \n optimal_dict = {}\n \n for n_clusters in range(min_n_clusters,max_n_clusters):\n \n y_pred = KMeans(n_clusters=n_clusters).fit_predict(all_seg_april_normalized_trim50)\n\n cluster_average = []\n for i_cluster in range(n_clusters):\n cluster_average.append(\n np.mean([np.mean(x) for i, x in enumerate(all_seg_april_normalized_trim50) if y_pred[i]==i_cluster])\n ) \n\n # sihouette score\n cluster_labels = y_pred\n sample_silhouette_values = silhouette_samples(all_seg_april_normalized_trim50, cluster_labels)\n \n silhouette_avg = silhouette_score(pd.DataFrame(all_seg_april_normalized_trim50), cluster_labels)\n\n optimal_dict[n_clusters] = silhouette_avg +(sample_silhouette_values.min()+sample_silhouette_values.max())/2\n \n # n_clusters will give us the optimal number of clusters\n n_clusters = max(optimal_dict.iteritems(), key=operator.itemgetter(1))[0]\n\n #print n_clusters\n \n y_pred = KMeans(n_clusters=n_clusters).fit_predict(all_seg_april_normalized_trim50)\n\n cluster_average = []\n \n for i_cluster in range(n_clusters):\n cluster_average.append(\n np.mean([np.mean(x) for i, x in enumerate(all_seg_april_normalized_trim50) if y_pred[i]==i_cluster])\n ) \n cluster_average_rank = np.argsort(cluster_average)[::-1]\n rank_map = {cluster_average_rank[i_cluster]:i_cluster for i_cluster in range(n_clusters)} # old index:new index\n\n y_pred_old = y_pred\n y_pred = [rank_map[x] for x in y_pred]\n all_seg_per_cluster = [[] for i in range(n_clusters) ]\n for i_seg in range(len(all_seg_april_normalized_trim50)):\n all_seg_per_cluster[y_pred[i_seg]].append(all_seg_april_normalized_trim50[i_seg])\n \n cluster_mean = [[] for i in range(n_clusters) ]\n cluster_std = [[] for i in range(n_clusters) ]\n for i_cluster in range(n_clusters):\n cluster_mean[ i_cluster ] = np.mean(np.array(all_seg_per_cluster[i_cluster]), axis=0)\n cluster_std[ i_cluster ] = np.std(np.array(all_seg_per_cluster[i_cluster]), axis=0)\n \n \n \n \n #cluster_mean_2 = cluster_mean[5:6]\n \n return cluster_mean,cluster_std,n_clusters,all_seg_per_cluster","def __existence_classification__(self,task_id,shape,aggregations):\n\n # aggregations = {}\n\n # raw_classifications and clustering_results have different hierarchy orderings- raw_classifications\n # is better for processing data and clustering_results is better for showing the end result\n # technically we only need to look at the data from clustering_results right now but its\n # hierarchy is really inefficient so use raw_classifications to help\n\n # each shape is done independently\n\n # set - so if multiple tools create the same shape - we only do that shape once\n # for shape in set(marking_tasks[task_id]):\n\n\n # pretentious name but basically whether each person who has seen a subject thinks it is a true\n # positive or not\n existence_classification = {\"param\":\"subject_id\"}\n\n global_cluster_index = 0\n # clusters_per_subject = []\n\n # look at the individual points in the cluster\n for subject_id in aggregations.keys():\n if subject_id == \"param\":\n continue\n\n # gold standard pts may not match up perfectly with the given clusters -\n # for example, we could have a gold penguin at 10,10 but the users' cluster\n # is centered at 10.1,9.8 - same penguin though\n # so as we go through the clusters, we need to see which ones match up more closely\n # with the gold standard\n # if subject_id in gold_standard_clustering[0]:\n # # closest cluster and distance\n # gold_to_cluster = {pt:(None,float(\"inf\")) for pt in gold_standard_clustering[0][subject_id]}\n # else:\n # gold_to_cluster = None\n\n\n # clusters_per_subject.append([])\n\n # # in either case probably an empty image\n # if subject_id not in clustering_results:\n # continue\n # if task_id not in clustering_results[subject_id]:\n # continue\n\n if (shape+ \" clusters\") not in aggregations[subject_id][task_id]:\n # if none of the relevant markings were made on this subject, skip it\n continue\n\n all_users = aggregations[subject_id][task_id][shape+ \" clusters\"][\"all_users\"]\n\n for local_cluster_index in aggregations[subject_id][task_id][shape+ \" clusters\"]:\n if local_cluster_index == \"all_users\":\n continue\n\n # extract the users who marked this cluster\n cluster = aggregations[subject_id][task_id][shape+ \" clusters\"][local_cluster_index]\n\n # todo - put this back when we support gold standard clustering\n # # is this user cluster close to any gold standard pt?\n # if subject_id in gold_standard_clustering[0]:\n # x,y = cluster[\"center\"]\n # for (gold_x,gold_y) in gold_to_cluster:\n # dist = math.sqrt((x-gold_x)**2+(y-gold_y)**2)\n # if dist < gold_to_cluster[(gold_x,gold_y)][1]:\n # gold_to_cluster[(gold_x,gold_y)] = local_cluster_index,dist\n #\n # # now repeat for negative gold standards\n # if subject_id in gold_standard_clustering[1]:\n # x,y = cluster[\"center\"]\n # min_dist = float(\"inf\")\n # closest= None\n # for x2,y2 in gold_standard_clustering[1][subject_id]:\n # dist = math.sqrt((x-x2)**2+(y-y2)**2)\n # if dist < min_dist:\n # min_dist = min(dist,min_dist)\n # closest = (x2,y2)\n # if min_dist == 0.:\n # assert (x,y) == closest\n # mapped_gold_standard[(subject_id,local_cluster_index)] = 0\n\n users = cluster[\"users\"]\n\n ballots = []\n\n # todo - the 15 hard coded value - might want to change that at some point\n for u in all_users:\n if u in users:\n ballots.append((u,1))\n else:\n ballots.append((u,0))\n\n existence_classification[(subject_id,local_cluster_index)] = ballots\n # clusters_per_subject[-1].append(global_cluster_index)\n # global_cluster_index += 1\n\n # # note we don't care about why a cluster corresponds to a gold standard pt - that is\n # # it could be really close to given gold standards - the point is that it is close\n # # to at least one of them\n # if gold_to_cluster is not None:\n # for (local_cluster_index,dist) in gold_to_cluster.values():\n # # arbitrary threshold but seems reasonable\n # if dist < 1:\n # mapped_gold_standard[(subject_id,local_cluster_index)] = 1\n\n existence_results = self.__task_aggregation__(existence_classification,task_id,{})#,mapped_gold_standard)\n assert isinstance(existence_results,dict)\n\n for subject_id,cluster_index in existence_results:\n new_results = existence_results[(subject_id,cluster_index)][task_id]\n # new_agg = {subject_id: {task_id: {shape + \" clusters\": {cluster_index: {\"existence\": new_results}}}}}\n # aggregations = self.__merge_results__(aggregations,new_agg)\n aggregations[subject_id][task_id][shape + \" clusters\"][cluster_index][\"existence\"] = new_results\n # if subject_id not in aggregations:\n # aggregations[subject_id] = {}\n # if task_id not in aggregations[subject_id]:\n # aggregations[subject_id][task_id] = {}\n # if (shape + \" clusters\") not in aggregations[subject_id][task_id]:\n # aggregations[subject_id][task_id][shape+ \" clusters\"] = {}\n # # this part is probably redundant\n # if cluster_index not in aggregations[subject_id][task_id][shape+ \" clusters\"]:\n # aggregations[subject_id][task_id][shape+ \" clusters\"][cluster_index] = {}\n #\n # aggregations[subject_id][task_id][shape+ \" clusters\"][cluster_index][\"existence\"] = existence_results[(subject_id,cluster_index)]\n\n return aggregations","def clustering(self): \n clusterOfFiles=self.getClusters()\n \n #group files based on the hash of their contents\n self.keyingMethod=md5Hash\n [self.addFile(afile) for acluster in clusterOfFiles for afile in acluster]\n clusterOfFiles=self.getClusters()\n self.showClusters(clusterOfFiles)","def test(dist_param, picker_param, iters):\n orig = '/home/zby/MAGISTERKA/MGR/results/oryginal.clustered.t'\n cl_orig = read_clustered(orig)\n name_tag = ''\n ndist = dist_param[1:]\n npick = picker_param[1:]\n for index in drange(4, 20, 0.5):\n name_tag = \"{}_{}_{}\".format(index, npick, ndist)\n tf_conf = configs.TfidfConfig(\n root_name('all_merged.txt', None),\n tfidf_name('merged.stem{}.stop', name_tag),\n tfidf_name('merged.stem{}.stop.txt', name_tag),\n None,\n tfidf_name('merged.stem{}.tfidf', name_tag),\n 10,\n 0,\n None)\n execute(tf_conf)\n tf_conf = configs.TfidfConfig(\n root_name('all_merged.txt', None),\n None,\n tfidf_name('merged.stem{}.stop.txt', name_tag),\n tfidf_name('merged.stem{}.stop', name_tag),\n tfidf_name('merged.stem{}.stop.tfidf', name_tag),\n None,\n None,\n None)\n execute(tf_conf)\n #input, out, picker, distance, iterations,\n clust_cfg = configs.ClusteringConfig(\n tfidf_name('merged.stem{}.stop.tfidf', name_tag),\n tfidf_name('merged.stem{}.stop.clustered.t', name_tag),\n picker_param,\n dist_param,\n iters,\n None\n )\n execute(clust_cfg)\n clust2 = read_clustered(tfidf_name('merged.stem{}.stop.clustered.t', name_tag))\n var, norm = variation_of_information(cl_orig, clust2)\n print(\"**** FOR var {} VOI is {}\".format(name_tag, norm))","def get_feature(glcm, featurelist=['contrast']):\n measure_list = dict(max_prob=0, contrast=0, dissimilarity=0, homogeneity=0, ASM=0, energy=0, entropy=0,\n correlation=0, cluster_shade=0, variance_i=0, variance_j=0, mean_i=0, mean_j=0)\n\n M, N = glcm.shape\n\n np.seterr(divide='ignore', invalid='ignore')\n\n flat_glcm = glcm.flatten()\n index_i = np.arange(0, M) # row index\n index_j = np.arange(0, N) # column index = row\n\n sum_v = np.sum(glcm, axis=0) # sum column[] , vertical\n sum_h = np.sum(glcm, axis=1) # sum row[] , horizontal\n\n max_prob = np.max(flat_glcm)\n mean_i = np.dot(index_i, sum_h.flatten())\n mean_j = np.dot(index_j, sum_v.flatten())\n var_i = np.dot((index_i - mean_i) ** 2, sum_h.flatten())\n var_j = np.dot((index_j - mean_j) ** 2, sum_v.flatten())\n\n measure_list['max_prob'] = max_prob\n measure_list['variance_i'] = var_i\n measure_list['variance_j'] = var_j\n measure_list['mean_i'] = mean_i\n measure_list['mean_j'] = mean_j\n\n for name in featurelist:\n if name in measure_list.keys():\n if name is 'max_prob':\n measure_list[name] = np.max(flat_glcm)\n elif name is 'ASM':\n measure_list[name] = np.dot(flat_glcm, flat_glcm)\n elif name is 'energy':\n ASM = np.dot(flat_glcm, flat_glcm)\n measure_list[name] = np.sqrt(ASM)\n elif name is 'cluster_shade':\n cluster_weights = np.zeros([M, N])\n for i in range(M):\n for j in range(N):\n cluster_weights[i, j] = (i + j - mean_i - mean_j) ** 3\n measure_list[name] = np.dot(flat_glcm, cluster_weights.flatten())\n elif name is 'correlation':\n stdev_i = np.sqrt(var_i)\n stdev_j = np.sqrt(var_j)\n correl_weights = np.outer((index_i - mean_i), (index_j - mean_j)) / (stdev_i * stdev_j)\n measure_list[name] = np.dot(flat_glcm, correl_weights.flatten())\n elif name is 'contrast':\n contrast_weights = np.zeros([M, N])\n for i in range(M):\n for j in range(N):\n contrast_weights[i, j] = (i - j) ** 2\n measure_list[name] = np.dot(flat_glcm, contrast_weights.flatten())\n elif name is 'entropy':\n # ln = np.log(flat_glcm) here, log(0) = -inf, will have some problem, using np.ma.log instead\n # np.ma.log(0) = -- : not -inf. ? can pass\n ln = np.ma.log(flat_glcm)\n measure_list[name] = -np.dot(flat_glcm, ln)\n elif name is 'dissimilarity':\n dissi_weights = np.zeros([M, N])\n for i in range(M):\n for j in range(N):\n dissi_weights[i, j] = abs(i - j)\n measure_list[name] = np.dot(flat_glcm, dissi_weights.flatten())\n elif name is 'homogeneity':\n homo_weights = np.zeros([M, N])\n for i in range(M):\n for j in range(N):\n homo_weights[i, j] = 1 / (1 + (i - j) ** 2)\n measure_list[name] = np.dot(flat_glcm, homo_weights.flatten())\n\n return measure_list","def perform_calculations(collector):\n result = {}\n try:\n radius, mass = Calculator.calculate_radius_mass(collector)\n result['radius'] = radius\n result['mass'] = mass\n average_density = Calculator.calculate_average_density(radius,\n mass)\n result['average_density'] = average_density\n escape_velocity = Calculator.calculate_escape_velocity(radius,\n mass)\n result['escape_velocity'] = escape_velocity\n earth_similarity_index = Calculator.calculate_esi_index(\n radius, mass, collector.get_average_temperature())\n result['earth_similarity_index'] = earth_similarity_index\n except NoDataError:\n pass\n\n try:\n avg_atm_molar_mass = Calculator.calculate_molar_mass(collector)\n except NoDataError:\n avg_atm_molar_mass = None\n if avg_atm_molar_mass is not None and avg_atm_molar_mass <= 0:\n logging.getLogger('Analyzer').debug('Molar mass <= 0: %d',\n avg_atm_molar_mass)\n avg_atm_molar_mass = None\n\n if avg_atm_molar_mass is not None:\n result['avg_atm_molar_mass'] = avg_atm_molar_mass\n avg_molecule_mass = avg_atm_molar_mass / Calculator.A\n result['avg_molecule_mass'] = avg_molecule_mass\n specific_gas_const = Calculator.R / avg_atm_molar_mass\n result['specific_gas_const'] = specific_gas_const\n\n try:\n speed_of_sound = Kundt.speed_of_sound(collector.kundt)\n result['speed_of_sound'] = speed_of_sound\n\n if avg_atm_molar_mass is None:\n # All further calculations require valid molar mass\n return result\n\n # Since calculate_molar_mass already uses get_average_temperature\n # and get_ground_pressure, it's safe to use these functions here\n # without worrying about NoDataError\n adiabatic_index = Calculator.calculate_adiabatic_index(\n collector, speed_of_sound, avg_atm_molar_mass)\n result['adiabatic_index'] = adiabatic_index\n\n atmosphere_density = (adiabatic_index *\n collector.get_ground_pressure() /\n speed_of_sound ** 2)\n result['atmosphere_density'] = atmosphere_density\n\n refractive_index = (3 * avg_atm_molar_mass *\n collector.get_ground_pressure() /\n atmosphere_density / Calculator.R /\n collector.get_average_temperature() - 2) ** 0.5\n result['refractive_index'] = refractive_index\n\n molar_refractivity = (avg_atm_molar_mass /\n atmosphere_density *\n (refractive_index ** 2 - 1) /\n (refractive_index ** 2 + 2))\n result['molar_refractivity'] = molar_refractivity\n\n atm_speed_of_light = Calculator.C / refractive_index\n result['atm_speed_of_light'] = atm_speed_of_light\n except NoDataError:\n pass\n\n return result","def calculate3(pred_ccm, pred_ad, truth_ccm, truth_ad, method=\"sym_pseudoV\", weights=None, verbose=False, pseudo_counts=True, full_matrix=True, in_mat=2):\n larger_is_worse_methods = ['sym_pseudoV_nc', 'sym_pseudoV', 'pseudoV_nc', 'pseudoV', \"simpleKL_nc\", 'simpleKL'] # methods where a larger score is worse\n\n \n pc_pred_ccm, pc_pred_ad, pc_truth_ccm, pc_truth_ad = pred_ccm, pred_ad, truth_ccm, truth_ad\n y = np.array(pc_pred_ad.shape)[1]\n nssms = int(np.ceil(0.5 * (2*y + 1) - 0.5 * np.sqrt(4*y + 1)))\n\n if isinstance(method, list):\n res = [calculate3_onemetric(pc_pred_ccm, pc_pred_ad, pc_truth_ccm, pc_truth_ad,\n method=m, verbose=verbose, in_mat=in_mat) for m in method] # calculate the score for each method\n\n # normalize the scores to be between (worst of NCluster score and OneCluster score) and (Truth score)\n ncluster_ccm, ncluster_ad = add_pseudo_counts(mb.get_ccm('NClusterOneLineage', nssms=nssms), mb.get_ad('NClusterOneLineage', nssms=nssms))\n ncluster_score = [calculate3_onemetric(ncluster_ccm, ncluster_ad, pc_truth_ccm, pc_truth_ad,\n method=m, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat) for m in method]\n del ncluster_ccm, ncluster_ad\n onecluster_ccm, onecluster_ad = add_pseudo_counts(mb.get_ccm('OneCluster', nssms=nssms), mb.get_ad('OneCluster', nssms=nssms))\n onecluster_score = [calculate3_onemetric(onecluster_ccm, onecluster_ad, pc_truth_ccm, pc_truth_ad,\n method=m, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat) for m in method]\n del onecluster_ccm, onecluster_ad\n for i in range(len(method)):\n if method[i] in larger_is_worse_methods: # normalization for methods where a larger score is worse\n worst_score = max(ncluster_score[i], onecluster_score[i]) # worst of NCluster and OneCluster scores\n res[i] = 1 - (res[i] / worst_score) # normalize the score\n else: # normalization for methods where a smaller score is worse\n worst_score = min(ncluster_score[i], onecluster_score[i])\n res[i] = (res[i] - worst_score) / (1 - worst_score)\n\n\n if weights is None: # if weights are not specified or if they cannot be normalized then default to equal weights\n weights = [1] * len(method)\n elif sum(weights) == 0:\n Warning('Weights sum to zero so they are invalid, defaulting to equal weights')\n weights = [1] * len(method)\n\n weights = np.array(weights) / float(sum(weights)) # normalize the weights\n score = sum(np.multiply(res, weights))\n else:\n \n score = calculate3_onemetric(pc_pred_ccm, pc_pred_ad, pc_truth_ccm, pc_truth_ad,\n method=method, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat)\n del pc_pred_ccm\n del pc_pred_ad\n # normalize the score to be between (worst of NCluster score and OneCluster score) and (Truth score) - similar to above\n ncluster_ccm, ncluster_ad = add_pseudo_counts(mb.get_ccm('NClusterOneLineage', nssms=nssms), mb.get_ad('NClusterOneLineage', nssms=nssms))\n ncluster_score = calculate3_onemetric(ncluster_ccm, ncluster_ad, pc_truth_ccm, pc_truth_ad,\n method=method, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat)\n del ncluster_ccm, ncluster_ad\n onecluster_ccm, onecluster_ad = add_pseudo_counts(mb.get_ccm('OneCluster', nssms=nssms), mb.get_ad('OneCluster', nssms=nssms))\n \n onecluster_score = calculate3_onemetric(onecluster_ccm, onecluster_ad, pc_truth_ccm, pc_truth_ad,\n method=method, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat)\n del onecluster_ccm, onecluster_ad\n\n #print score, ncluster_score, onecluster_score\n if method in larger_is_worse_methods:\n worst_score = max(ncluster_score, onecluster_score)\n score = 1 - (score / worst_score)\n else:\n worst_score = min(ncluster_score, onecluster_score)\n score = (score - worst_score) / (1 - worst_score)\n return score","def algorithms():\n algorith_paradigms = ['Divide-and-conquer', 'Backtrackig', 'Greedy-Algorithms', 'Dynamic-programming']\n return algorith_paradigms","def main():\r\n algos = [merge_sort, quick_sort, heap_sort, radix_sort, bucket_sort_general]\r\n array_sizes = [5000, 10000, 15000, 20000, 50000, 75000, 100000, 150000]\r\n results = {algo.__name__: [] for algo in algos}\r\n for algo in algos:\r\n result = []\r\n for size in array_sizes:\r\n time = test(algo, size)\r\n result.append(time)\r\n results[algo.__name__] = result\r\n\r\n display_results(results, array_sizes)","def __all_Algs_ ( self ) :\n _algs = self.algorithms()\n\n algs = []\n for _a in _algs :\n algs += [ self.algorithm ( _a ) ]\n return algs","def __all_Algs_ ( self ) :\n _algs = self.algorithms()\n\n algs = []\n for _a in _algs :\n algs += [ self.algorithm ( _a ) ]\n return algs","def all_means(runtimes):\n tmp = {}\n for name in runtimes:\n tmp[name] = compute_means(runtimes[name])\n return tmp","def generate(dictalg):\n\n # dsList, sortedAlgs, dictAlg = processInputArgs(args, verbose=verbose)\n res = {}\n for f, i in pproc.dictAlgByFun(dictalg).iteritems():\n for d, j in pproc.dictAlgByDim(i).iteritems():\n tmp = BestAlgSet(j)\n res[(d, f)] = tmp\n return res","def compute_statistics(self):","def _calculate_cluster_measures(\n arr4d,\n threshold,\n bin_struct,\n two_sided_test=False,\n):\n n_regressors = arr4d.shape[3]\n\n max_sizes = np.zeros(n_regressors, int)\n max_masses = np.zeros(n_regressors, float)\n\n for i_regressor in range(n_regressors):\n arr3d = arr4d[..., i_regressor].copy()\n\n if two_sided_test:\n arr3d[np.abs(arr3d) <= threshold] = 0\n else:\n arr3d[arr3d <= threshold] = 0\n\n labeled_arr3d, _ = label(arr3d > 0, bin_struct)\n\n if two_sided_test:\n # Label positive and negative clusters separately\n n_positive_clusters = np.max(labeled_arr3d)\n temp_labeled_arr3d, _ = label(\n arr3d < 0,\n bin_struct,\n )\n temp_labeled_arr3d[temp_labeled_arr3d > 0] += n_positive_clusters\n labeled_arr3d = labeled_arr3d + temp_labeled_arr3d\n del temp_labeled_arr3d\n\n clust_vals, clust_sizes = np.unique(labeled_arr3d, return_counts=True)\n assert clust_vals[0] == 0\n\n clust_vals = clust_vals[1:] # First cluster is zeros in matrix\n clust_sizes = clust_sizes[1:]\n\n # Cluster mass-based inference\n max_mass = 0\n for unique_val in clust_vals:\n ss_vals = np.abs(arr3d[labeled_arr3d == unique_val]) - threshold\n max_mass = np.maximum(max_mass, np.sum(ss_vals))\n\n # Cluster size-based inference\n max_size = 0\n if clust_sizes.size:\n max_size = np.max(clust_sizes)\n\n max_sizes[i_regressor], max_masses[i_regressor] = max_size, max_mass\n\n return max_sizes, max_masses","def _calculate_metrics(self):\n metrics = {}\n precision, recall = self.calc_precision_recall()\n metrics[\"precision\"] = precision\n metrics[\"recall\"] = recall\n metrics[\"entropy\"] = self.calc_entropy()\n metrics[\"component_entropy\"] = self.calc_component_entropy()\n metrics[\"num_comps\"] = len(self.get_components())\n metrics[\"num_diagnoses\"] = len(self.diagnoses)\n metrics[\"distinct_diagnoses_scores\"] = len(Counter(list(map(lambda x: x.probability, self.diagnoses))))\n metrics[\"num_tests\"] = len(self.get_tests())\n metrics[\"num_distinct_traces\"] = len(self.get_distinct_traces())\n metrics[\"num_failed_tests\"] = len(self._get_tests_by_error(1))\n metrics[\"num_passed_tests\"] = len(self._get_tests_by_error(0))\n passed_comps = set(self._get_components_by_error(0))\n failed_comps = set(self.get_components_in_failed_tests())\n metrics[\"num_failed_comps\"] = len(failed_comps)\n metrics[\"only_failed_comps\"] = len(failed_comps - passed_comps)\n metrics[\"only_passed_comps\"] = len(passed_comps - failed_comps)\n metrics[\"num_bugs\"] = len(self.get_bugs())\n metrics[\"wasted\"] = self.calc_wasted_components()\n metrics[\"top_k\"] = self.calc_top_k()\n metrics[\"num_comps_in_diagnoses\"] = len(self._get_comps_in_diagnoses())\n metrics[\"bugs_cover_ratio\"] = self._get_bugs_cover_ratio()\n metrics[\"average_trace_size\"] = self._get_average_trace_size()\n metrics[\"average_component_activity\"] = self._get_average_component_activity()\n metrics[\"average_diagnosis_size\"] = self._get_average_diagnosis_size()\n metrics[\"bugs_scores_average\"], metrics[\"bugs_scores_std\"], metrics[\"bugs_scores_entropy\"] = self._get_bugs_scores()\n metrics[\"non_bugs_scores_average\"], metrics[\"non_bugs_scores_std\"], metrics[\"non_bugs_scores_entropy\"] = self._get_non_bugs_scores()\n metrics.update(self.cardinality())\n # metrics[\"ochiai\"] = self.calc_ochiai_values()\n return metrics","def compute_metrics(self):\n overall_ret = OrderedDict()\n for ap_iou_thresh in self.ap_iou_thresh:\n ret_dict = OrderedDict()\n rec, prec, ap = eval_det_multiprocessing(self.pred_map_cls, self.gt_map_cls, ovthresh=ap_iou_thresh)\n for key in sorted(ap.keys()):\n clsname = self.class2type_map[key] if self.class2type_map else str(key)\n ret_dict[\"%s Average Precision\" % (clsname)] = ap[key]\n ap_vals = np.array(list(ap.values()), dtype=np.float32)\n ap_vals[np.isnan(ap_vals)] = 0\n ret_dict[\"mAP\"] = ap_vals.mean()\n rec_list = []\n for key in sorted(ap.keys()):\n clsname = self.class2type_map[key] if self.class2type_map else str(key)\n try:\n ret_dict[\"%s Recall\" % (clsname)] = rec[key][-1]\n rec_list.append(rec[key][-1])\n except:\n ret_dict[\"%s Recall\" % (clsname)] = 0\n rec_list.append(0)\n ret_dict[\"AR\"] = np.mean(rec_list)\n overall_ret[ap_iou_thresh] = ret_dict\n return overall_ret","def eval_mean_distance(played_decks, clustering_data: List, fuzzy: bool, debug: bool = False):\n\n for alg_dict in clustering_data:\n decks = np.array(played_decks)\n clusters = []\n for label in set(alg_dict[\"labels\"]):\n indices = np.where(alg_dict[\"labels\"] == label)\n if fuzzy:\n clusters.append(FuzzyDeckCluster(decks[indices]))\n else:\n clusters.append(DeckCluster(decks[indices]))\n\n if fuzzy:\n clustering = FuzzyDeckClustering(clusters)\n else:\n clustering = DeckClustering(clusters)\n\n sum_of_squared_distances_centroid = 0\n sum_of_squared_distances_core = 0\n\n for cluster in clustering.deck_clusters:\n centroid = cluster.centroid()\n core = cluster.core()\n for deck in cluster.decks:\n sum_of_squared_distances_centroid += (deck.jaccard_distance(centroid))**2\n sum_of_squared_distances_core += (deck.jaccard_distance(core))**2\n alg_dict[\"sse_centroid\"] = sum_of_squared_distances_centroid\n alg_dict[\"sse_core\"] = sum_of_squared_distances_core\n\n if debug:\n print(\"Alg: \" + alg_dict[\"name\"] + \"; \\t sse = \" + str(alg_dict[\"sse_centroid\"]))\n print(\"Alg: \" + alg_dict[\"name\"] + \"; \\t sse = \" + str(alg_dict[\"sse_core\"]))","def __init__(self, conn, args, data, split_type, num_clusters):\n\n self.conn = conn\n self.args = args\n self.data = data\n self.split_type = split_type\n\n self.pca_model = None\n self.cluster_model = None\n self.algorithm = args['cluster_algorithm']\n\n # http://scikit-learn.org/stable/auto_examples/cluster/plot_cluster_comparison.html\n hdbsc = hdbscan.HDBSCAN(min_cluster_size=10)\n affinity_propagation = cluster.AffinityPropagation()\n ms = cluster.MeanShift(bin_seeding=True)\n spectral = cluster.SpectralClustering(n_clusters=num_clusters, \n eigen_solver='arpack',\n affinity=\"nearest_neighbors\", \n random_state=self.args['seed'])\n ward = cluster.AgglomerativeClustering(n_clusters=num_clusters, \n linkage='ward')\n birch = cluster.Birch(n_clusters=num_clusters)\n two_means = cluster.MiniBatchKMeans(n_clusters=num_clusters,\n random_state=self.args['seed'])\n average_linkage = cluster.AgglomerativeClustering(linkage=\"average\", \n n_clusters=num_clusters)\n hdbsc = hdbscan.HDBSCAN(min_cluster_size=10)\n kmeans = cluster.KMeans(n_clusters=num_clusters, random_state=self.args['seed'])\n dbscan = cluster.DBSCAN()\n \n self.clustering_algorithms = {\n 'MiniBatchKMeans': two_means,\n 'AffinityPropagation': affinity_propagation,\n 'MeanShift': ms,\n 'SpectralClustering': spectral,\n 'Ward': ward,\n 'AgglomerativeClustering': average_linkage,\n 'DBSCAN': dbscan,\n 'Birch': birch,\n 'HDBSCAN': hdbsc,\n 'KMeans': kmeans\n }","def Clustering(typeVector, behaviour, sampleType):\r\n ProduceVector.produceVector(typeVector, behaviour, sampleType)\r\n vector = ProduceVector.getVector()\r\n\r\n if sampleType == \"\":\r\n sampleType2 = \"ransomware\"\r\n if sampleType == \"2\":\r\n sampleType2 = \"backdoor\"\r\n if sampleType == \"3\":\r\n sampleType2 = \"trojan\"\r\n\r\n if (behaviour == \"f\") or (behaviour == \"fc\"): \r\n\r\n calculateStandardisation(vector)\r\n vector = getStandardisation()\r\n\r\n typeOfVector = typeVector + \" \" + behaviour\r\n\r\n nGram, syscallRep = typeOfVector.split()\r\n\r\n if syscallRep == \"b\":\r\n nGram += \"Full Representation Bit Vector\"\r\n if syscallRep == \"f\":\r\n nGram += \"Full Representation Frequency Vector\"\r\n if syscallRep == \"bc\":\r\n nGram += \"Category Bit Vector\"\r\n if syscallRep == \"fc\":\r\n nGram += \"Category Frequency Vector\"\r\n\r\n\r\n fileName = sampleType2 + \" \" + syscallRep + \" standardisation \" + nGram + \".txt\"\r\n\r\n file = open(fileName, \"w\")\r\n file.write(str(vector.tolist()))\r\n file.close()\r\n\r\n calculateEuclideanDistance(vector) \r\n\r\n typeOfVector = typeVector + \" \" + behaviour\r\n\r\n nGram, syscallRep = typeOfVector.split()\r\n\r\n if syscallRep == \"b\":\r\n nGram += \"Full Representation Bit Vector\"\r\n if syscallRep == \"f\":\r\n nGram += \"Full Representation Frequency Vector\"\r\n if syscallRep == \"bc\":\r\n nGram += \"Category Bit Vector\"\r\n if syscallRep == \"fc\":\r\n nGram += \"Category Frequency Vector\" \r\n\r\n fileName = sampleType2 + \" \" + syscallRep + \" matrix \" + nGram + \".txt\"\r\n\r\n file = open(fileName, \"w\")\r\n file.write(str(getEuclideanDistance().tolist()))\r\n file.close()\r\n\r\n print(\"Producing a dendrogram\")\r\n\r\n\r\n typeOfVector = typeVector + \" \" + behaviour\r\n\r\n setBestCluster(Validation.evaluate(getEuclideanDistance(), vector, typeOfVector, sampleType))","def parse_clustering(key, content):\n if inspect.isclass(key):\n cl = key(**content)\n key = cl.__class__.__name__.lower()\n\n elif 'auto' in (content.get('n_clusters', ''),\n content.get('preference', '')) \\\n and key.lower() != 'hierarchical':\n # Wrapper class that automatically detects the best number of clusters\n # via 10-Fold CV\n content.pop('n_clusters', '')\n content.pop('preference', '')\n\n kwargs = {'param_grid': [], 'n_jobs': -1,\n 'scoring': silhouette_score, 'cv': 10}\n\n if key.lower() == 'kmeans':\n content.setdefault('init', 'k-means++')\n content.setdefault('n_jobs', 1)\n kwargs['estimator'] = KMeans(**content)\n elif key.lower() == 'ap':\n kwargs['estimator'] = AffinityPropagation(**content)\n kwargs['affinity'] = kwargs['estimator'].affinity\n else:\n logging.error(\"n_clusters = 'auto' specified outside kmeans or \"\n \"ap. Trying to create GridSearchCV pipeline anyway \"\n \" ...\")\n cl = GridSearchCV(**kwargs)\n elif 'auto' in (content.get('n_clusters', ''),\n content.get('preference', '')) \\\n and key.lower() == 'hierarchical':\n # TODO implement this\n # from adenine.utils.extensions import AgglomerativeClustering\n cl = AgglomerativeClustering(**content)\n else:\n if key.lower() == 'kmeans':\n content.setdefault('n_jobs', -1)\n cl = KMeans(**content)\n elif key.lower() == 'ap':\n content.setdefault('preference', 1)\n cl = AffinityPropagation(**content)\n elif key.lower() == 'ms':\n cl = MeanShift(**content)\n elif key.lower() == 'spectral':\n cl = SpectralClustering(**content)\n elif key.lower() == 'hierarchical':\n cl = AgglomerativeClustering(**content)\n else:\n cl = DummyNone()\n return (key, cl, 'clustering')","def calculate_distances(self, iterations=[1]):\n for i in iterations:\n saved_policies = self.memory[i]\n # Load relevant saved experiences\n trajectories = []\n policies = []\n kdes = []\n\n for p in saved_policies:\n trajectories.extend(p['trajectory'])\n policies.append(p['policy'])\n kdes.append(p['kde'])\n\n num_policies = len(policies)\n\n kde_all = self.calculate_KDE(trajectories)\n samples = self.sample_kde(kde_all, 100)\n\n self.KDEs[i] = kde_all\n self.meta_samples[i] = samples\n\n sample_divergences = []\n\n for sample_ix, sample in enumerate(samples):\n probs_n = []\n sample_divergence = np.zeros([num_policies, num_policies])\n for ix in range(num_policies):\n occupancy_measure = self.calculate_occupancy(\n kdes[ix], policies[ix], sample)\n probs_n.append(occupancy_measure)\n # Save occupancy measures for comparison later\n key = sample_ix\n\n try:\n self.meta_occupancies[i][ix][key] = occupancy_measure\n except:\n try:\n self.meta_occupancies[i][ix] = {\n key: occupancy_measure}\n except:\n self.meta_occupancies[i] = {\n ix: {key: occupancy_measure}}\n\n for a in range(num_policies):\n for b in range(num_policies):\n sample_divergence[a][b] = self.calculate_JSD(\n probs_n[a].squeeze(), probs_n[b].squeeze())\n\n sample_prob = np.exp(kde_all.score(sample.reshape(1, -1)))\n sample_divergences.append(sample_divergence * sample_prob)\n # Compute average divergence over entirety\n divergence = np.sum(sample_divergences, axis=0) # or sum?\n self.meta_divergences[i] = divergence","def answer_q10():\n data_sources = [viz.DATA_111_URL, viz.DATA_290_URL, viz.DATA_896_URL]\n x_vals = range(6, 21)\n y_vals_hier = {}\n y_vals_kmean = {}\n for idx in range(len(data_sources)):\n # 0. Generate data_field & cluster_list\n clust_list, data_table = closest_pair.create_cluster_list(\n data_sources[idx])\n y_vals_hier[idx] = []\n # 1. calculate values for hierarchical - decreasing order\n for clust_size in reversed(x_vals):\n clust_list = closest_pair.hierarchical_clustering(clust_list,\n clust_size)\n clust_error = closest_pair.compute_distortions(clust_list,\n data_table)\n y_vals_hier[idx].insert(0, clust_error)\n # 2. calculate values for kmeans - decreasing order\n y_vals_kmean[idx] = []\n for clust_size in x_vals:\n clust_list, data_table = closest_pair.create_cluster_list(\n data_sources[idx])\n clust_list = closest_pair.kmeans_clustering(clust_list,\n clust_size, 5)\n clust_error = closest_pair.compute_distortions(clust_list,\n data_table)\n y_vals_kmean[idx].append(clust_error)\n return x_vals, y_vals_hier, y_vals_kmean","def calculate_metric(self, embeddings, fingerprints, properties, estimator, param_dict):\n\n metric_array = []\n for col in properties.columns:\n props = properties[col].astype(cupy.float32).to_array()\n embedding_error = self.gpu_gridsearch_cv(estimator, param_dict, embeddings, props)\n fingerprint_error = self.gpu_gridsearch_cv(estimator, param_dict, fingerprints, props)\n ratio = fingerprint_error / embedding_error # If ratio > 1.0 --> embedding error is smaller --> embedding model is better\n metric_array.append(ratio)\n return cupy.array(metric_array)","def analysis_function_details(self,clustering):\n return clustering.details","def selectedComparisons(samples_dict):\n sectors=\"peripherals\",\"intermediaries\",\"hubs\"\n ks_measures={}\n for analyses_type in samples_dict[sectors[0]]:\n ks_measures[analyses_type]={}\n for analysis_grouping in samples_dict[sectors[0]][analyses_type]:\n ks_measures[analyses_type][analysis_grouping]={}\n if samples_dict[sectors[0]][analyses_type][analysis_grouping]==dict:\n ks_measures[analyses_type][analysis_grouping]={}\n for analysis in samples_dict[sectors[0]][analyses_type][analysis_grouping]:\n for var in samples_dict[sectors[0]][analyses_type][analysis_grouping][analysis]:\n samples_peripherals=samples_dict[sectors[0]][analyses_type][analysis_grouping][analysis]\n samples_intermediaries=samples_dict[sectors[1]][analyses_type][analysis_grouping][analysis]\n samples_hubs=samples_dict[sectors[2]][analyses_type][analysis_grouping][analysis]\n ks_measures[analysis][\"peripherals_intermediaries\"]=P.kolmogorovSmirnovTest(samples_peripherals,samples_intermediaries)\n ks_measures[analysis][\"peripherals_hubs\"]=P.kolmogorovSmirnovTest(samples_peripherals,samples_hubs)\n ks_measures[analysis][\"hubs_intermediaries\"]=P.kolmogorovSmirnovTest(samples_hubs,samples_intermediaries)\n else:\n for var in samples_dict[sectors[0]][analyses_type][analysis_grouping]:\n samples_peripherals=samples_dict[sectors[0]][analyses_type][analysis_grouping]\n samples_intermediaries=samples_dict[sectors[1]][analyses_type][analysis_grouping]\n samples_hubs=samples_dict[sectors[2]][analyses_type][analysis_grouping]\n\n\n\n samples[sector][analyses][analysis_grouping]=updateDict(samples[sector][analyses][analysis_grouping],getSamples(authors_analysis[analyses][author][analysis_grouping]))","def analyzeClusterPerformance(self, cluster):\n def calcOverlap(playlist, group):\n urls = set(group[\"uri\"].values)\n playlist = set(playlist)\n return len(urls & playlist)\n\n groupedDF = self.audioDF.groupby(cluster)\n playlists = list(self.playlists)\n\n clusters = [group for _, group in groupedDF]\n numSongs = sum([len(p) for p in playlists])\n\n numOverlap, maxOverlap = 0, 1\n while len(playlists) > 0 and len(clusters) > 0 and maxOverlap > 0:\n maxOverlap, pIDX, gIDX = 0, None, None\n for i, playlist in enumerate(playlists):\n for j, c in enumerate(clusters):\n overlap = calcOverlap(playlist, c)\n if overlap > maxOverlap:\n maxOverlap, pIDX, gIDX = overlap, i, j\n \n if maxOverlap > 0:\n playlists.pop(pIDX)\n clusters.pop(gIDX)\n numOverlap += maxOverlap\n\n performance = float(numOverlap) / float(numSongs)\n performancePercentage = round(performance, 4) * 100\n\n return {\n \"Clustering Algorithm\": cluster,\n \"Performance\": performance\n }","def _compute_experiment_statistics(self):\n pass","def test(referrer, tester, test_word, algorithm, algo_params={}, visualize_results=False, apply_PCA=False, clear_referrer_with_algo=False, clean_algo_parameters={\"name\": 'EllipticEnvelope', \"contamination\": 0.1, \"visualize_results\": False}):\n\n # Split the test_word to digraphs\n test_digraphs = [('Key' + c[0].upper() if c[0] != ' ' else 'Space') + ('Key' + c[1].upper() if c[1] != ' ' else 'Space')\n for c in [z[0] + z[1] for z in zip(test_word, test_word[1:])]]\n\n # Test each digraph data of tester against referrer\n count_insufficient_ref_samples = 0.\n # `score` Represents number of inliers if algo != 'GMM' else represents score for each GMM component\n score = 0. if algorithm != 'GMM' else []\n count_global = 0.\n for test_digraph in test_digraphs:\n\n # Find the digraph data of referrer\n ref_di_points = ret_digraph_points(\n referrer, test_digraph).astype(float)\n # print ref_di_points\n if len(ref_di_points) >= 10:\n\n # If tester and referrer sample\n if referrer['_subject'] == tester['_subject'] and referrer['_track_code'] == tester['_track_code']:\n _tmp = ref_di_points\n np.random.shuffle(_tmp)\n perc = int(np.floor(0.8 * len(_tmp)))\n ref_di_points = _tmp[0:perc, :]\n test_di_points = _tmp[perc:, :]\n else:\n # Sample some data for the particular digraph in tester\n _test_di_points = ret_digraph_points(tester, test_digraph)\n test_di_points = _test_di_points[np.random.choice(\n _test_di_points.shape[0], size=randint(10, 12), replace=False), :]\n\n # Transform ref and tester data with standard scaler\n sscaler = StandardScaler(with_mean=True, with_std=True).fit(\n np.append(ref_di_points, test_di_points, axis=0))\n train_points = sscaler.transform(ref_di_points)\n test_points = sscaler.transform(test_di_points)\n\n # Apply PCA if needed\n if apply_PCA is True:\n pca_model = PCA().fit(\n np.append(train_points, test_points, axis=0))\n train_points = pca_model.transform(train_points)[:, 0:2]\n test_points = pca_model.transform(test_points)[:, 0:2]\n\n # Clean referrer points from noise if needed\n if clear_referrer_with_algo is True:\n train_points = general_purpose.clean_with_algo(\n train_points, algorithm=clean_algo_parameters['name'], contamination=clean_algo_parameters['contamination'])\n\n # Anomaly-Test the digraph and get the count_global of inliers\n if algorithm != 'GMM':\n score += digraph_test(train_points,\n test_points, algorithm, algo_params, visualize_results=visualize_results,\n plt_title_info={\"referrer\": referrer['_subject'],\n \"tester\": tester['_subject'], \"digraph\": test_digraph})\n else:\n # Special procedure for GMM\n _sc = digraph_test_GMM(train_points,\n test_points, algo_params, visualize_results=visualize_results,\n plt_title_info={\"referrer\": referrer['_subject'],\n \"tester\": tester['_subject'], \"digraph\": test_digraph})\n score.append(_sc)\n\n else:\n\n count_insufficient_ref_samples += len(test_points)\n\n count_global += len(test_points)\n\n # Find eventually the total score\n if algorithm != 'GMM':\n total_score = score / \\\n (count_global - count_insufficient_ref_samples)\n else:\n total_score = 0.\n for s in score:\n total_score += sum(s)\n total_score = total_score / \\\n (count_global - count_insufficient_ref_samples)\n\n # print '\\n'\n # print 'Digraph passed: ' + str(total_score) + '%, ' + str(int(score)) + ' out of ' + str(int(count_global - count_insufficient_ref_samples))\n # print 'Insufissient digraph samples: ' + str(count_insufficient_ref_samples) + ' out of ' + str(int(count_global))\n # print total_score\n if count_insufficient_ref_samples > 0:\n print 'Insuffisient samples: %d' % (count_insufficient_ref_samples)\n print 'For word: ' + test_word\n return total_score","def multiClusterAlgorithm(values):\n clusterMap = dict()\n # Lowest unixtime in the values list\n startUnixtime = values[0][0]\n # Separate values into separate clusters in the map, clusterMap\n for value in values:\n if value[2] not in clusterMap.keys():\n clusterMap[value[2]] = []\n clusterMap[value[2]].append(value)\n \n # An array of the predicted values per cluster\n clusterPredicted = []\n # An array of unixtime averages per cluster\n unixtimeAverage = []\n \n # Generate predicted value for each cluster using a weighted average\n # Adds predicted value for each cluster to clusterPredicted and adds\n # the unixtime average for each cluster to unixtimeAverage\n for key in clusterMap.keys():\n clusterLength = len(clusterMap[key]) \n totalUnixtime = sum([elem[0] for elem in clusterMap[key]])\n unixtimeAverage.append(float(totalUnixtime) / float(clusterLength))\n \n clusterLight = [elem[1] for elem in clusterMap[key]]\n\n totalDistanceFromStart = sum([elem[0] - startUnixtime for elem in clusterMap[key]])\n clusterWeightValues = [float(elem[0] - startUnixtime) / float(totalDistanceFromStart) for elem in clusterMap[key]]\n \n predicted = np.average(clusterLight, weights = clusterWeightValues)\n clusterPredicted.append(predicted)\n \n print clusterPredicted\n total = sum([elem - startUnixtime for elem in unixtimeAverage])\n # Create weighted values based on unixtime average per cluster\n weightValues = [float(elem - startUnixtime) / float(total) for elem in unixtimeAverage]\n print weightValues\n # Return a weighted average across clusters\n return np.average(clusterPredicted, weights = weightValues)","def get_metrics(cfg, model, X_anchor, y_anchor, X_gal, y_gal, annoy_index, vec_dim):\n rank10_acc = 0\n rank5_acc = 0\n rank1_acc = 0\n avg_acc = 0\n vote_res = 0\n\n l2 = []\n for anchor in range(0, len(X_anchor)):\n res = get_result(get_image_features(cfg, model, X_anchor[anchor]), annoy_index)\n vote = defaultdict(int)\n # Accuracy\n correct = 0\n for i in res[:10]:\n vote[y_gal[i]] += 1\n\n max_key = max(vote, key=vote.get)\n if max_key == y_anchor[anchor]:\n vote_res += 1\n \n\n for recomm in res[:10]:\n if y_gal[recomm] == y_anchor[anchor]:\n correct += 1 \n\n avg_acc += correct/len(res)\n\n # Mean Average Precision\n l1 = []\n for recomm in res[:10]:\n if y_gal[recomm] == y_anchor[anchor]:\n correct += 1\n l1.append(1)\n else:\n l1.append(0)\n l2.append(l1) \n\n # Rank10 Accuracy\n for each_val in res[:10]:\n if y_gal[each_val] == y_anchor[anchor]:\n rank10_acc += 1\n break\n \n # Rank5 Accuracy\n for each_val in res[:5]:\n if y_gal[each_val] == y_anchor[anchor]:\n rank5_acc += 1\n break\n\n # Rank1 Accuracy\n for each_val in res[:1]:\n if y_gal[each_val] == y_anchor[anchor]:\n rank1_acc += 1\n break\n\n print(\"Avg acc is :: {avg_acc}\".format(avg_acc = avg_acc/len(X_anchor)))\n print(\"Rank 10 acc is :: {rank10_acc}\".format(rank10_acc = rank10_acc/len(X_anchor)))\n print(\"Rank 5 acc is :: {rank5_acc}\".format(rank5_acc = rank5_acc/len(X_anchor)))\n print(\"Rank 1 acc is :: {rank1_acc}\".format(rank1_acc = rank1_acc/len(X_anchor)))\n print(\"Mean Avg Precision is :: {mAP}\".format(mAP=mean_average_precision(l2)))\n print(\"Vote res :: \", vote_res/len(X_anchor))\n\n return rank1_acc/len(X_anchor), mean_average_precision(l2)","def enumerate_clusterings(self):\n\n # Initialize an empty list of clusterings. Each element of the list\n # is a dictionary mapping NOEs to the signatures they are clustered to\n # in a solution. Each clustering is initialize with all uniquely\n # clusterable NOEs as keys mapping to their unique clusters\n\n clusterings = []\n\n while True:\n\n # Run the solver and get a solution back\n\n solution = self.solve()\n\n # If UNSAT, then flush aux clauses from the formula and return\n # all the clusterings we found so far\n\n if not solution:\n self.flush()\n return clusterings\n\n # Iterate over the clustering variables set to true by in the\n # discovered solution. Forbid this clustering from reoccuring and\n # add it to the list of found clusterings\n\n clause = []\n clustering = {}\n for node in self.clustering_variables.keys():\n if len(node.clusters) == 1:\n clustering[node] = list(node.clusters)[0]\n\n for vtype, node, cluster in solution:\n if vtype == Formula.CST_VAR:\n clustering[node] = cluster\n clause.append(-self.clustering_variables[node][cluster])\n\n self.add_clause(clause)\n clusterings.append(clustering)","def compute_means(self):\n ###TODO\n vector_means = []\n for doc in self.fin_clust.values():\n vec = defaultdict(float)\n for d_id in doc:\n doc_keys = self.docs[d_id].keys()\n for key in self.docs[d_id]:\n vec[key] = vec[key] + self.docs[d_id][key]\n tot = len(doc)\n x = defaultdict(float)\n for k,v in vec.items():\n x[k] = float(v)/tot\n vec = Counter(x)\n vector_means.append(vec)\n return vector_means","def evaluation_cc(self, property='clustering-coeff'):\n\n if property == 'clustering-coeff':\n rw_cc = [np.mean(clustering_coef_wu(self.rw_data[t])) for t in range(0, self.T)]\n smth_cc = [np.mean(clustering_coef_wu(self.smth_data[t])) for t in range(0, self.T)]\n elif property == 'transitivity':\n rw_cc = [np.mean(transitivity_wu(self.rw_data[t])) for t in range(0, self.T)]\n smth_cc = [np.mean(transitivity_wu(self.smth_data[t])) for t in range(0, self.T)]\n elif property == 'coreness':\n rw_cc = [np.mean(core.core_periphery_dir(self.rw_data[t])) for t in range(0, self.T)]\n smth_cc = [np.mean(core.core_periphery_dir(self.smth_data[t])) for t in range(0, self.T)]\n elif property == 'assortativity':\n rw_cc = [np.mean(core.assortativity_wei(self.rw_data[t], 0)) for t in range(0, self.T)]\n smth_cc = [np.mean(core.assortativity_wei(self.smth_data[t], 0)) for t in range(0, self.T)]\n elif property == 'modularity':\n rw_cc, _ = get_number_of_components(self.rw_data)\n smth_cc, _ = get_number_of_components(self.smth_data)\n elif property == 'path_length':\n rw_cc = [charpath(rw)[0] for rw in self.rw_data]\n smth_cc = [charpath(sm)[0] for sm in self.smth_data]\n\n # rw_cc_ent = get_entropy_list(rw_cc)\n # smth_cc_ent = get_entropy_list(smth_cc)\n\n return rw_cc, smth_cc","def ehost_iaa_compute(folder1, folder2, no_context=False):\n annotator1 = read_ehost_annotated_result(folder1, no_context=no_context)\n annotator2 = read_ehost_annotated_result(folder2, no_context=no_context)\n merged_keys = list(set(annotator1.keys()) | set(annotator2.keys()))\n y1 = []\n y2 = []\n for key in merged_keys:\n if key in annotator1 and key in annotator2:\n y1.append(annotator1[key])\n y2.append(annotator2[key])\n else:\n print('%s not matched in all' % key)\n iaa = sklearn.metrics.cohen_kappa_score(y1, y2)\n print('IAA is %s on %s' % (iaa, len(annotator1)))\n return iaa","def clustering(self):\n ret_concepts = []\n clusters = []\n for word in self.words:\n clusters.append(WordCluster(None, word))\n while len(clusters) > 1:\n maxi = -1\n maxj = -1\n max = -1\n m = -1\n for i in range(len(clusters)):\n for j in range(len(clusters)):\n if i == j:\n continue\n # print(\"%d cluster compare with %d cluster\" % (i, j))\n # 1: join 21: i absorb j 22: j absorb i 3: collapse\n # l1: join L(Tm) value l21: A absorb B L(Tm)value\n l1, newtags = self.__calculate_ltm(clusters[i], clusters[j], 1)\n if l1 > max:\n m = 1\n maxi = i\n maxj = j\n max = l1\n print(\"max L(Tm) for clustering in current loop: %lf\" % max)\n if max < ClusterAlgorithm.P_threshold:\n return\n Tm = clusters[maxi].join(clusters[maxj])\n Tm_concepts = self.__select_concepts(self.__getword(Tm))\n for tmp_concept in Tm_concepts.items():\n ret_concepts.append(tmp_concept)\n rm1 = clusters[maxi]\n rm2 = clusters[maxj]\n clusters.remove(rm1)\n clusters.remove(rm2)\n if Tm is not None:\n print(\"merged cluster's words:\")\n print(self.__getword(Tm))\n return ret_concepts","def main():\n parser = argparse.ArgumentParser(description=\"Wrapper of the scikit-learn AgglomerativeClustering method. \", formatter_class=lambda prog: argparse.RawTextHelpFormatter(prog, width=99999))\n parser.add_argument('--config', required=False, help='Configuration file')\n\n # Specific args of each building block\n required_args = parser.add_argument_group('required arguments')\n required_args.add_argument('--input_dataset_path', required=True, help='Path to the input dataset. Accepted formats: csv.')\n required_args.add_argument('--output_results_path', required=True, help='Path to the clustered dataset. Accepted formats: csv.')\n parser.add_argument('--output_plot_path', required=False, help='Path to the clustering plot. Accepted formats: png.')\n\n args = parser.parse_args()\n args.config = args.config or \"{}\"\n properties = settings.ConfReader(config=args.config).get_prop_dic()\n\n # Specific call of each building block\n agglomerative_clustering(input_dataset_path=args.input_dataset_path,\n output_results_path=args.output_results_path,\n output_plot_path=args.output_plot_path,\n properties=properties)","def compute_metrics(self):\n self.finalize_output_dict()\n self.metric_dict = {\n key: value(self.output_dict[\"labels\"], self.output_dict[\"pred_probs\"])\n for key, value in self.metric_fns.items()\n }","def _cluster(self):\n # , distance_function=spearman_squared_distance, max_iter=1000, tol=0.0001):\n if self.cluster_method is None:\n clusters = KMedoids(\n self.k,\n self.batchsize,\n dist_func=self.distance_function,\n max_iter=self.max_iter,\n tol=self.tol,\n init_medoids=self.init_medoids,\n swap_medoids=self.swap_medoids,\n )\n clusters.fit(self.clustering_attributions, verbose=self.verbose)\n\n self.subpopulations = clusters.members\n self.subpopulation_sizes = GAM.get_subpopulation_sizes(clusters.members)\n self.explanations = self._get_explanations(clusters.centers)\n # Making explanations return numerical values instead of dask arrays\n if isinstance(self.explanations[0][0][1], da.Array):\n explanations = []\n for explanation in self.explanations:\n explanations.append([(x[0], x[1].compute()) for x in explanation])\n self.explanations = explanations\n else:\n self.cluster_method(self)","def prepare_statistics(self):\n\n # statistics of clustering files\n len0 = len(self.cluster_lists[0])\n len1 = len(self.cluster_lists[1])\n longer_index = 0 if len0 >= len1 else 1\n shorter_index = 1 if len1 <= len0 else 0\n\n percentage_stars = \"%.2f\" % (100.0 * float(self.shared_spec_num)/float(self.cluster_spectra_num[shorter_index]))\n percentage_starlets = \"%.2f\" % (100.0 * float(self.shared_spec_num)/float(self.cluster_spectra_num[longer_index]))\n\n head = \"{0:<25}{1:<20}{2:<20}\\n\".format(\"name\", \"number\", \"description\")\n rows = \"\"\n rows += \"{0:<25}{1:<20}{2:<20}\\n\".format(\"stars No.\", self.stars_length, \"in file with less(or equal) clusters: file\" + str(shorter_index))\n rows += \"{0:<25}{1:<20}{2:<20}\\n\".format(\"starlets No.\", self.starlets_length, \"in file with more(or equal) clusters: file\" + str(longer_index))\n rows += \"{0:<25}{1:<20}{2:<20}\\n\".format(\"identical cluster No.\", self.similarity_dist[10], \"between them\")\n rows += \"{0:<25}{1:<20}{2:<20}\\n\".format(\"spectrum No\", self.cluster_spectra_num[shorter_index], \"in stars\")\n rows += \"{0:<25}{1:<20}{2:<20}\\n\".format(\"spectrum No\", self.cluster_spectra_num[longer_index], \"in starlets \")\n rows += \"{0:<25}{1:<20}{2:<20}\\n\".format(\"shared spectrum No\", self.shared_spec_num, \"between them\")\n rows += \"{0:<25}{1:<20}{2:<20}\\n\".format(\"shared spectrum percent\", percentage_stars, \"in stars\")\n rows += \"{0:<25}{1:<20}{2:<20}\\n\".format(\"shared spectrum percent\", percentage_starlets, \"in starlets\")\n self.tables.append(('statistics of files', head, rows))\n\n # distribution of cluster size in stars\n head = '{0:<20}{1:<20}{2:<20}{3:<20}\\n'.format(\"cluster size\",\"No.\", \"percentage\", \"accumulate pecentage\")\n rows = \"\"\n rows += \"{0:<20}{1:<20}\\n\".format(\"%.2f\" % (self.ave_star_size), \"average\")\n accumulate_num = 0\n for key in sorted(self.cluster_size_dist[shorter_index].keys()):\n value = self.cluster_size_dist[shorter_index][key]\n accumulate_num += value\n percent = \"%.2f\" % (100 * value/self.stars_length)\n accum_percent = \"%.2f\" % (100 * accumulate_num/self.stars_length)\n rows += '{0:<20}{1:<20}{2:<20}{3:<20}\\n'.format(key, value, percent, accum_percent)\n self.tables.append(('distribution of cluster size in stars', head, rows))\n \n head = '{0:<20}{1:<20}{2:<20}{3:<20}\\n'.format(\"cluster size\",\"No.\", \"percentage\", \"accumulate pecentage\")\n rows = \"\"\n rows += \"{0:<20}{1:<20}\\n\".format(\"%.2f\" % (self.ave_starlet_size), \"average\")\n accumulate_num = 0\n for key in sorted(self.cluster_size_dist[longer_index].keys()):\n value = self.cluster_size_dist[longer_index][key]\n accumulate_num += value\n percent = \"%.2f\" % (100 * value/self.starlets_length)\n accum_percent = \"%.2f\" % (100 * accumulate_num/self.starlets_length)\n rows += '{0:<20}{1:<20}{2:<20}{3:<20}\\n'.format(key, value, percent, accum_percent)\n self.tables.append(('distribution of cluster size in starlets', head, rows))\n\n # distribution of similarity\n head = \"{0:<20}{1:<20}{2:<20}{3:<20}\\n\".format(\"similarity score\", \"pairs of clusters\", \"percentage(stars)\", \"percentage(starlets)\")\n rows = \"\"\n for key in reversed(sorted(self.similarity_dist.keys())):\n value = self.similarity_dist[key]\n percent_star = \"%.2f\" % (100.0*value/self.stars_length)\n percent_starlet = \"%.2f\" % (100.0*value/self.starlets_length)\n rows += '{0:<20}{1:<20}{2:<20}{3:<20}\\n'.format(key, value, percent_star, percent_starlet)\n self.tables.append(('distribution of similarity (identical = 10)', head, rows))\n\n # distribution of star divide factors\n head = '{0:<20}{1:<20}{2:<20}\\n'.format(\"divide factor\",\"No.\",\"percentage\")\n rows = \"\"\n rows += \"{0:<20}{1:<20}\\n\".format(\"%.2f\" % (self.ave_divide_factor_star), \"average\")\n for key in sorted(self.star_divide_factor_dist.keys()):\n value = self.star_divide_factor_dist[key]\n percent_star = \"%.2f\" % (100.0*value/self.stars_length)\n rows += '{0:<20}{1:<20}{2:<20}\\n'.format(key, value, percent_star)\n self.tables.append(('distribution of star divide factors', head, rows))\n\n # distribution of starlet divide factors\n head = '{0:<20}{1:<20}{2:<20}\\n'.format(\"divide factor\",\"No.\",\"percentage\")\n rows = \"\"\n rows += \"{0:<20}{1:<20}\\n\".format(\"%.2f\" % (self.ave_divide_factor_starlet), \"average\")\n for key in sorted(self.starlet_divide_factor_dist.keys()):\n value = self.starlet_divide_factor_dist[key]\n percent_starlet = \"%.2f\" % (100.0*value/self.starlets_length)\n rows += '{0:<20}{1:<20}{2:<20}\\n'.format(key, value, percent_starlet)\n self.tables.append(('distribution of starlet divide factors', head, rows))","def cluster_membership_occupancy(data):\n \n \n \n n_clusters = len(set(data['clusters'])-{-1}) # since -1 element denotes noice\n\n if n_clusters == 0:\n membership=[Cluster_Membership_Features()]\n membership = pd.DataFrame([o.__dict__ for o in membership])\n areas=[Cluster_Area_Features()]\n areas = pd.DataFrame([o.__dict__ for o in areas])\n density=[Cluster_Density_Features()]\n density = pd.DataFrame([o.__dict__ for o in density])\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\n density], axis=1)\n \n elif n_clusters ==1:\n #obtain_total_cluster_areas_set_everything_else_to_default\n membership=[Cluster_Membership_Features()]\n membership = pd.DataFrame([o.__dict__ for o in membership])\n d = dict(tuple(data.groupby('clusters')))\n d.pop(-1, None)\n \n try:\n cluster_chull_areas=[ss.ConvexHull(np.column_stack([d[i]['X'].array,d[i]['Y'].array])).volume for i in d.keys()]\n except:\n cluster_chull_areas=[0,0,0]\n \n Total_cluster_area=np.sum(cluster_chull_areas)\n areas=[Cluster_Area_Features([Total_cluster_area,0,0,0,0,0,0,0,0])]\n areas = pd.DataFrame([o.__dict__ for o in areas])\n density=[Cluster_Density_Features()]\n density = pd.DataFrame([o.__dict__ for o in density])\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\n density], axis=1)\n \n elif n_clusters >1:\n #Summarizing the cluster membership distribution characteristics\n cluster_size_nums=np.delete(np.array(data.groupby(['clusters']).size()),0)\n (cluster_size_nums_avg,cluster_size_nums_min,cluster_size_nums_max,\n cluster_size_nums_std,cluster_size_nums_cv,cluster_size_nums_cd,\n cluster_size_nums_IQR,cluster_size_nums_Quartile_CD)= distribution_statistics(cluster_size_nums)\n\n #For each cluster calculate the area by calculating the area of the convex hull of cluster members\n # Note: concavehull implementation here might be a good addition as it will provide more imformative values. \n\n d = dict(tuple(data.groupby('clusters')))\n d.pop(-1, None)\n try:\n cluster_chull_areas=[ss.ConvexHull(np.column_stack([d[i]['X'].array,d[i]['Y'].array])).volume for i in d.keys()]\n except:\n cluster_chull_areas=[0,0,0,0,0]\n \n\n (avg_cluster_area,min_cluster_area,max_cluster_area,\n std_cluster_area,CV_cluster_area,CD_cluster_area,\n IQR_cluster_area,Quartile_CD_cluster_area)= distribution_statistics(cluster_chull_areas)\n Total_cluster_area=np.sum(cluster_chull_areas)\n\n #Calculate cluster density: number of nuclei/ convex area of cluster\n cluster_density=np.divide(cluster_size_nums,cluster_chull_areas)\n (avg_cluster_density,min_cluster_density,max_cluster_density,\n std_cluster_density,CV_cluster_density,CD_cluster_density,\n IQR_cluster_density,Quartile_CD_cluster_density)= distribution_statistics(cluster_density)\n\n #return dataframe of features\n membership=[Cluster_Membership_Features([cluster_size_nums_avg,cluster_size_nums_min,cluster_size_nums_max,\n cluster_size_nums_std,cluster_size_nums_cv,cluster_size_nums_cd,\n cluster_size_nums_IQR,cluster_size_nums_Quartile_CD])]\n membership = pd.DataFrame([o.__dict__ for o in membership])\n areas=[Cluster_Area_Features([Total_cluster_area,\n avg_cluster_area,min_cluster_area,max_cluster_area,\n std_cluster_area,CV_cluster_area,CD_cluster_area,\n IQR_cluster_area,Quartile_CD_cluster_area])]\n areas = pd.DataFrame([o.__dict__ for o in areas])\n density=[Cluster_Density_Features([avg_cluster_density,min_cluster_density,max_cluster_density,\n std_cluster_density,CV_cluster_density,CD_cluster_density,\n IQR_cluster_density,Quartile_CD_cluster_density])]\n density = pd.DataFrame([o.__dict__ for o in density])\n\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\n density], axis=1)\n return all_features","def convergence_measure_all(filename,index,mean_subtract,smoothing_scale=None):\n\n\tlogging.info(\"Processing {0}\".format(filename))\n\n\t#Load the map\n\tconv_map = ConvergenceMap.load(filename)\n\n\tif mean_subtract:\n\t\tconv_map.data -= conv_map.mean()\n\n\t#Smooth the map maybe\n\tif smoothing_scale is not None:\n\t\tlogging.info(\"Smoothing {0} on {1}\".format(filename,smoothing_scale))\n\t\tconv_map.smooth(smoothing_scale,kind=\"gaussianFFT\",inplace=True)\n\n\t#Allocate memory for observables\n\tdescriptors = index\n\tobservables = np.zeros(descriptors.size)\n\n\t#Measure descriptors as directed by input\n\tfor n in range(descriptors.num_descriptors):\n\t\t\n\t\tif type(descriptors[n]) == PowerSpectrum:\n\t\t\tl,observables[descriptors[n].first:descriptors[n].last] = conv_map.powerSpectrum(descriptors[n].l_edges)\n\t\t\t\n\t\telif type(descriptors[n]) == Moments:\n\t\t\tobservables[descriptors[n].first:descriptors[n].last] = conv_map.moments(connected=descriptors[n].connected)\n\t\t\t\n\t\telif type(descriptors[n]) == Peaks:\n\t\t\tv,observables[descriptors[n].first:descriptors[n].last] = conv_map.peakCount(descriptors[n].thresholds,norm=descriptors[n].norm)\n\n\t\telif type(descriptors[n]) == PDF:\n\t\t\tv,observables[descriptors[n].first:descriptors[n].last] = conv_map.pdf(descriptors[n].thresholds,norm=descriptors[n].norm)\n\t\t\n\t\telif type(descriptors[n]) == MinkowskiAll:\n\t\t\tv,V0,V1,V2 = conv_map.minkowskiFunctionals(descriptors[n].thresholds,norm=descriptors[n].norm)\n\t\t\tobservables[descriptors[n].first:descriptors[n].last] = np.hstack((V0,V1,V2))\n\t\t\n\t\telif type(descriptors[n]) == MinkowskiSingle:\n\t\t\traise ValueError(\"Due to computational performance you have to measure all Minkowski functionals at once!\")\n\t\t\n\t\telse:\n\t\t\t\n\t\t\traise ValueError(\"Measurement of this descriptor not implemented!!!\")\n\n\t#Return\n\treturn observables","def cal_topology_feature(self):\n self.NPL()\n self.topo_efficiency_cal()\n self.efficiency_cal()\n self.cluster_cal()\n self.topo_diameter()\n self.spatial_diameter()","def main(seed, numpoints, dimensions, num_centres, fragments, mode, iterations,\n epsilon, arity, use_storage):\n start_time = time.time()\n\n # Generate the data\n fragment_list = []\n # Prevent infinite loops in case of not-so-smart users\n points_per_fragment = max(1, numpoints // fragments)\n\n for l in range(0, numpoints, points_per_fragment):\n # Note that the seed is different for each fragment.\n # This is done to avoid having repeated data.\n r = min(numpoints, l + points_per_fragment)\n\n fragment_list.append(\n generate_fragment(r - l, dimensions, mode, seed + l, use_storage)\n )\n\n compss_barrier()\n print(\"Generation/Load done\")\n initialization_time = time.time()\n print(\"Starting kmeans\")\n\n # Run kmeans\n centres = kmeans_frag(fragments=fragment_list,\n dimensions=dimensions,\n num_centres=num_centres,\n iterations=iterations,\n seed=seed,\n epsilon=epsilon,\n arity=arity)\n compss_barrier()\n print(\"Ending kmeans\")\n kmeans_time = time.time()\n\n # Run again kmeans (system cache will be filled)\n print(\"Second kmeans\")\n centres = kmeans_frag(fragments=fragment_list,\n dimensions=dimensions,\n num_centres=num_centres,\n iterations=iterations,\n seed=seed,\n epsilon=epsilon,\n arity=arity)\n compss_barrier()\n print(\"Ending second kmeans\")\n kmeans_2nd = time.time()\n\n print(\"-----------------------------------------\")\n print(\"-------------- RESULTS ------------------\")\n print(\"-----------------------------------------\")\n print(\"Initialization time: %f\" % (initialization_time - start_time))\n print(\"Kmeans time: %f\" % (kmeans_time - initialization_time))\n print(\"Kmeans 2nd round time: %f\" % (kmeans_2nd - kmeans_time))\n print(\"Total time: %f\" % (kmeans_2nd - start_time))\n print(\"-----------------------------------------\")\n centres = compss_wait_on(centres)\n print(\"CENTRES:\")\n print(centres)\n print(\"-----------------------------------------\")","def evaluate():\n global dictionary, wv\n count = 0\n # To save the scores by distance and similarity\n scores = np.zeros(6)\n similar = np.zeros(6)\n itr = len(dictionary)\n logging.info('running evaluation for {0} samples'.format(itr))\n for key in dictionary:\n progress = (count / itr) * 100\n d = dictionary[key].split('resource/')\n d = [idx.split()[0].translate(table).lower() for idx in d[1:]]\n try:\n r = np.array(list(map(lambda x: wv.get_vector(x), d)),\n dtype=np.float32)\n except KeyError:\n itr -= 1\n continue\n if np.any(np.isnan(r)):\n itr -= 1\n continue\n else:\n if r.ndim == 2:\n try:\n # Mean of vector containing all word vectors\n # obtained from abstract.\n r = r.mean(axis=0).reshape(1, -1)\n \n # Obtain the vectors for the entity\n mean_vec = mean_encoder(dictionary[key])\n mean_vec = mean_vec.reshape(1, -1) / norm(mean_vec)\n mean_dist_vec = distance_encoder(dictionary[key])\n mean_dist_vec = mean_dist_vec.reshape(1, -1)\n mean_dist_vec = mean_dist_vec / norm(mean_dist_vec)\n title_vec = title_mean(key)\n title_vec = title_vec.reshape(1, -1) / norm(title_vec)\n abstract_vec = abstract_encoder(key)\n abstract_vec = abstract_vec.reshape(1, -1)\n abstract_vec = abstract_vec / norm(abstract_vec)\n random_vec = np.random.randn(100).reshape(1, -1)\n zero_vec = np.zeros(100).reshape(1, -1)\n \n # Score the entity vectors\n scores[0] += norm(r - mean_vec)\n scores[1] += norm(r - mean_dist_vec)\n scores[2] += norm(r - title_vec)\n scores[3] += norm(r - abstract_vec)\n scores[4] += norm(r - random_vec)\n scores[5] += norm(r - zero_vec)\n similar[0] += cosine_similarity(r, mean_vec)\n similar[1] += cosine_similarity(r, mean_dist_vec)\n similar[2] += cosine_similarity(r, title_vec)\n similar[3] += cosine_similarity(r, abstract_vec)\n similar[4] += cosine_similarity(r, random_vec)\n similar[5] += cosine_similarity(r, zero_vec)\n count += 1\n print(count, end='\\r')\n except (ValueError, KeyError) as _:\n itr -= 1\n continue\n else:\n itr -= 1\n continue\n # Normalize the scores to get a better\n # comparison against the baselines.\n scores = scores / norm(scores)\n similar = similar / norm(similar)\n print_summary(scores, similar)","def evaluate_clusters(self, cluster_formulas, value='weighted_sum'):\n num_elems = len(self.labels)\n total_val = {}\n num_cl = len(cluster_formulas)\n clustered_points_num = 0\n print(\"\\n\\n\")\n print(\"Sufficiently big clusters: {}\".format(num_cl))\n for c, formula, val in cluster_formulas:\n c_size = len([l for l in self.labels if l == c])\n clustered_points_num += c_size\n\n if value == 'weighted_sum':\n total_val[c] = val * c_size / num_elems\n elif value == 'sum':\n total_val[c] = val * 1\n\n clust_val = sum(total_val.values())\n self.clustering_value = total_val\n print(\"Value of clustering: {}\".format(clust_val))\n return clust_val","def cluster_life_expectancy() -> Dict:\n return dict(model=None, score=None, clusters=None)","def _prepare_algorithms(\n self, initial_model: TModel, initial_graph: NNCFGraph, combinations: Dict[CombinationKey, Combination]\n ) -> None:\n for combination_key, combination in combinations.items():\n kwargs = apply_combination(self._init_params, combination)\n self._algorithms[combination_key] = self._algorithm_cls(**kwargs)\n\n # Collect required statistics for created algorithms\n stats_aggregator = StatisticsAggregatorFactory.create(initial_model, self._calibration_dataset)\n for algorithm in self._algorithms.values():\n statistic_points = algorithm.get_statistic_points(initial_model, initial_graph)\n stats_aggregator.register_statistic_points(statistic_points)\n stats_aggregator.collect_statistics(initial_model, initial_graph)\n self._statistic_points = stats_aggregator.statistic_points","def _compute_cluster_averages(self, key=\"_scvi_labels\"):\n # find cell label column\n label_col = self.adata.uns[\"_scvi\"][\"categorical_mappings\"][key][\"original_key\"]\n\n # find data slot\n x_dict = self.adata.uns[\"_scvi\"][\"data_registry\"][\"X\"]\n if x_dict[\"attr_name\"] == \"X\":\n use_raw = False\n else:\n use_raw = True\n if x_dict[\"attr_name\"] == \"layers\":\n layer = x_dict[\"attr_key\"]\n else:\n layer = None\n\n # compute mean expression of each gene in each cluster/batch\n aver = compute_cluster_averages(self.adata, labels=label_col, use_raw=use_raw, layer=layer)\n\n return aver","def load_cluster_accuracies():\n accuracies = morphs.utils.load._pickle(morphs.paths.ACCURACIES_PKL)\n cluster_accuracies = {\n block_path: accuracies[block_path]\n .groupby(\"cluster\")\n .agg(np.mean)\n .sort_values(\"accuracy\")\n for block_path in accuracies\n }\n return accuracies, cluster_accuracies","def schedule_algorithm(self, algorithm_type):\n\n algorithm_data = self.clustering_parameters[\"algorithms\"][algorithm_type]\n\n # The algorithm we are going to use\n algorithm = self.build_algorithm(algorithm_type)\n\n # If not parameters were given we have to get the better ones\n clusterings = []\n\n auto_parameter_generation = True if not \"parameters\" in algorithm_data else False\n\n if auto_parameter_generation:\n print \"Generating params for\", algorithm_type\n algorithm_run_params, clusterings = self.parameters_generator.get_parameters_for_type(algorithm_type)\n else:\n # A list with all the parameters for diverse runs\n algorithm_run_params = algorithm_data[\"parameters\"]\n\n clusterings_info = self.generate_clustering_info(algorithm_type, algorithm_run_params, clusterings)\n\n # Sometimes getting the best parameters imply getting the clusterings themselves\n if clusterings == []:\n for clustering_id in clusterings_info:\n one_clustering_info = clusterings_info[clustering_id]\n self.scheduler.add_task( task_name = clustering_id,\n description = \"Generation of clustering with %s algorithm and id %s\"%(\n one_clustering_info[\"type\"],\n clustering_id\n ),\n target_function = run_algorithm,\n function_kwargs = {\n \"algorithm\":algorithm,\n \"clustering_id\":clustering_id,\n \"algorithm_kwargs\":one_clustering_info[\"parameters\"]\n },\n dependencies = {})\n return clusterings_info","def compute_performance_analysis(self, G, I, thresholds=0.01):\r\n FAR = self.compute_FAR(I, thresholds)\r\n FRR = self.compute_FRR(G, thresholds)\r\n CRR = self.compute_CRR(FAR)\r\n CAR = self.compute_CAR(FRR)\r\n EER = self.compute_EER(FAR, FRR)\r\n AUC = self.compute_AUC(FAR, CAR)\r\n return FAR, FRR, CRR, CAR, EER, AUC","def compute_metrics(self, results: list) -> dict:","def test_optimalk(parallel_backend, n_jobs, n_clusters):\n import numpy as np\n from sklearn.datasets.samples_generator import make_blobs\n from gap_statistic import OptimalK\n\n # Create data\n X, y = make_blobs(n_samples=int(1e3), n_features=2, centers=3)\n\n for algo in ['kmeans', 'kmeans2', 'skl-kmeans', 'sph-kmeans']:\n # Create optimalK instance\n optimalK = OptimalK(parallel_backend=parallel_backend, n_jobs=n_jobs, algo=algo)\n\n suggested_clusters = optimalK(X, n_refs=3, cluster_array=np.arange(1, 10))\n\n assert np.allclose(suggested_clusters, n_clusters, 2), \\\n ('Correct clusters is {}, OptimalK suggested {}'.format(n_clusters, suggested_clusters))","def benchmark(self):\n nsites = []\n for m in self.methods:\n for name, structure in self.test_structures.items():\n cns = []\n if self.unique_sites:\n es = SpacegroupAnalyzer(structure).get_symmetrized_structure().equivalent_sites\n sites = [structure.index(x[0]) for x in es]\n else:\n sites = range(len(structure))\n\n for key, val in self.hi.items():\n if name == key:\n for j in sites:\n if isinstance(m, NearNeighbors):\n tmpcn = m.get_cn_dict(structure, j, self.use_weights)\n else:\n tmpcn = m.compute(structure, j)\n if tmpcn == \"null\":\n continue\n if self.nround:\n self._roundcns(tmpcn, self.nround)\n cns.append((structure[j].species_string, tmpcn))\n if self.cation_anion:\n for mat, cat in self.cations.items():\n if (name == mat) and cat:\n cns = self._popel(cns, cat)\n elif self.anion_cation:\n for mat, an in self.anions.items():\n if name == mat:\n cns = self._popel(cns, an)\n m._cns[name] = cns\n nsites.append(len(cns))\n self.nsites = max(nsites)","def plot_metric_results():\n from run_metric_comparison_experiments import (\n PIVECTOR_TEMPLATE,\n PIVECTOR_DISTANCE_MATRIX_TEMPLATE,\n DISCRIMINATOR_DISTANCE_MATRIX_TEMPLATE,\n GAUSSIAN_DISTANCE_MATRIX_TEMPLATE,\n ENCODER_DISTANCE_MATRIX_TEMPLATE,\n DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE,\n NUM_TRAJECTORIES,\n NUM_COMPONENTS,\n NUM_REPETITIONS,\n REWARD_SCALES,\n ENVS\n )\n\n # Path-templates to each distance matrix to compare\n # BC = Behavioural Characteristication\n BC_DISTANCE_MATRIX_TEMPLATES = [\n PIVECTOR_DISTANCE_MATRIX_TEMPLATE,\n GAUSSIAN_DISTANCE_MATRIX_TEMPLATE,\n DISCRIMINATOR_DISTANCE_MATRIX_TEMPLATE,\n ENCODER_DISTANCE_MATRIX_TEMPLATE,\n DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE\n ]\n\n BC_LEGEND_NAMES = [\n \"Supervector\",\n \"Gaussian\",\n \"Discriminator\",\n \"Encoder\",\n \"Discretization\"\n ]\n\n BC_PLOT_COLORS = [\n \"C0\",\n \"C1\",\n \"C2\",\n \"C3\",\n \"C4\"\n ]\n\n fig, axs = pyplot.subplots(\n figsize=[4.8 * 3 * 0.75, 4.8 * 0.75],\n nrows=1,\n ncols=3,\n )\n\n def get_policy_names(env):\n policy_names = glob(PIVECTOR_TEMPLATE.format(env=env, num_traj=\"*\", num_components=\"*\", policy_name=\"*\", repetition_num=\"*\"))\n policy_names = [\"_\".join(os.path.basename(x).split(\"_\")[-4:-2]) for x in policy_names]\n policy_names = sorted(list(set(policy_names)))\n return policy_names\n\n # For each different distance measurement\n for distance_matrix_template, plot_legend_name, plot_color in zip(BC_DISTANCE_MATRIX_TEMPLATES, BC_LEGEND_NAMES, BC_PLOT_COLORS):\n # These will be NUM_TRAJECTORY length lists\n average_scores = np.ones((len(NUM_TRAJECTORIES),))\n std_scores = np.ones((len(NUM_TRAJECTORIES),))\n for num_traj_idx, num_traj in enumerate(NUM_TRAJECTORIES):\n # Average over environments, policies and repetitions\n scores = []\n for env_i, env in enumerate(ENVS):\n if \"Bipedal\" in env and distance_matrix_template == DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE:\n print(\"[Note] Skipping env {} for discretization distances (OOM)\".format(env))\n continue\n min_reward, max_reward = REWARD_SCALES[env]\n policy_names = get_policy_names(env)\n\n for policy_name in policy_names:\n for repetition in range(1, NUM_REPETITIONS + 1):\n # Ugh bit of messing around because I did not think this through...\n if distance_matrix_template == PIVECTOR_DISTANCE_MATRIX_TEMPLATE:\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, num_components=NUM_COMPONENTS, policy_name=policy_name, repetition_num=repetition)\n else:\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, policy_name=policy_name, repetition_num=repetition)\n\n data = np.load(file_path)\n distance_matrix = data[\"distance_matrix\"]\n rewards = data[\"average_episodic_rewards\"]\n\n raveled_reward_distances = np.abs(rewards - rewards[:, None])\n # Take upper diagonal, skip diagonal\n raveled_reward_distances = raveled_reward_distances[np.triu_indices(raveled_reward_distances.shape[0], 1)]\n raveled_distances = distance_matrix[np.triu_indices(distance_matrix.shape[0], 1)]\n\n # Score is correlation between the two\n correlation = np.corrcoef(raveled_distances, raveled_reward_distances)[0, 1]\n scores.append(correlation)\n\n scores = np.array(scores)\n average_score = np.mean(scores)\n std_score = np.std(scores)\n average_scores[num_traj_idx] = average_score\n std_scores[num_traj_idx] = std_score\n ax = axs[0]\n ax.plot(NUM_TRAJECTORIES, average_scores, c=plot_color, label=plot_legend_name)\n ax.scatter(NUM_TRAJECTORIES, average_scores, c=plot_color)\n #ax.fill_between(\n # NUM_TRAJECTORIES,\n # average_scores - std_scores,\n # average_scores + std_scores,\n # alpha=0.2,\n # color=plot_color,\n # edgecolor=\"none\",\n # linewidth=0.0\n #)\n ax.set_xticks(NUM_TRAJECTORIES)\n ax.tick_params(axis='both', which='both', labelsize=\"x-large\")\n ax.set_ylabel(\"Correlation with return-distances\", fontsize=\"x-large\")\n ax.set_xlabel(\"Number of trajectories\", fontsize=\"x-large\")\n ax.grid(alpha=0.2)\n\n # Amount of error to \"ground truth\" result,\n # where \"ground truth\" is one of the results with 100 trajectories of data.\n # Because of wonkyness of this, store list [#num-traj] of lists,\n # each storing results for that num-traj run\n per_trajectory_relative_errors = [[] for i in NUM_TRAJECTORIES]\n for env in ENVS:\n if \"Bipedal\" in env and distance_matrix_template == DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE:\n print(\"[Note] Skipping env {} for discretization distances (OOM)\".format(env))\n continue\n policy_names = get_policy_names(env)\n for policy_name in policy_names:\n # The \"ground truth\" distances, will be filled with first\n # result with 100 trajectories.\n anchor_distance = None\n for traj_i, num_traj in enumerate(NUM_TRAJECTORIES):\n for repetition in range(1, NUM_REPETITIONS + 1):\n if distance_matrix_template == PIVECTOR_DISTANCE_MATRIX_TEMPLATE:\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, num_components=NUM_COMPONENTS, policy_name=policy_name, repetition_num=repetition)\n else:\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, policy_name=policy_name, repetition_num=repetition)\n distance_matrix = np.load(file_path)[\"distance_matrix\"]\n # Normalize to [0, 1]\n distance_matrix = (distance_matrix - distance_matrix.min()) / (distance_matrix.max() - distance_matrix.min())\n # Get only upper triangle as distance matrix is symmetric. Exlude diagonal\n raveled_distances = distance_matrix[np.triu_indices(distance_matrix.shape[0], 1)]\n # Check if we use this as the zero-point or compute relative error to\n if anchor_distance is None:\n assert num_traj == 100\n anchor_distance = raveled_distances\n else:\n per_trajectory_relative_errors[traj_i].append(\n np.mean(np.abs(raveled_distances - anchor_distance) / np.abs(anchor_distance))\n )\n # Lists are not of equal length, so can not just change into an array\n mean_average_errors = np.array([np.mean(np.array(results) * 100) for results in per_trajectory_relative_errors])\n std_average_errors = np.array([np.std(np.array(results) * 100) for results in per_trajectory_relative_errors])\n ax = axs[1]\n ax.plot(NUM_TRAJECTORIES, mean_average_errors, c=plot_color, label=plot_legend_name)\n ax.scatter(NUM_TRAJECTORIES, mean_average_errors, c=plot_color)\n #ax.fill_between(\n # NUM_TRAJECTORIES,\n # mean_average_errors - std_average_errors,\n # mean_average_errors + std_average_errors,\n # alpha=0.2,\n # color=plot_color,\n # edgecolor=\"none\",\n # linewidth=0.0\n #)\n ax.set_xticks(NUM_TRAJECTORIES)\n ax.tick_params(axis='both', which='both', labelsize=\"x-large\")\n ax.set_ylabel(\"Relative error to ground truth (%)\", fontsize=\"x-large\")\n ax.set_xlabel(\"Number of trajectories\", fontsize=\"x-large\")\n ax.grid(alpha=0.2)\n\n # Variation between results\n cv_means = np.ones((len(NUM_TRAJECTORIES,)))\n cv_stds = np.ones((len(NUM_TRAJECTORIES,)))\n for traj_i, num_traj in enumerate(NUM_TRAJECTORIES):\n traj_averaged_cvs = []\n for env in ENVS:\n if \"Bipedal\" in env and distance_matrix_template == DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE:\n print(\"[Note] Skipping env {} for discretization distances (OOM)\".format(env))\n continue\n policy_names = get_policy_names(env)\n for policy_name in policy_names:\n # Compute std over repetitions\n distances = []\n for repetition in range(1, NUM_REPETITIONS + 1):\n if distance_matrix_template == PIVECTOR_DISTANCE_MATRIX_TEMPLATE:\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, num_components=NUM_COMPONENTS, policy_name=policy_name, repetition_num=repetition)\n else:\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, policy_name=policy_name, repetition_num=repetition)\n\n distance_matrix = np.load(file_path)[\"distance_matrix\"]\n # Normalize to [0, 1]\n distance_matrix = (distance_matrix - distance_matrix.min()) / (distance_matrix.max() - distance_matrix.min())\n # Get only upper triangle as distance matrix is symmetric. Exlude diagonal\n raveled_distances = distance_matrix[np.triu_indices(distance_matrix.shape[0], 1)]\n distances.append(raveled_distances)\n distances = np.stack(distances)\n # Coefficient of variance (std / mean)\n average_cv = np.mean(np.std(distances, axis=0) / np.mean(distances, axis=0))\n traj_averaged_cvs.append(average_cv)\n traj_averaged_cvs = np.array(traj_averaged_cvs)\n cv_means[traj_i] = np.mean(traj_averaged_cvs)\n cv_stds[traj_i] = np.std(traj_averaged_cvs)\n\n ax = axs[2]\n ax.plot(NUM_TRAJECTORIES, cv_means, c=plot_color, label=plot_legend_name)\n ax.scatter(NUM_TRAJECTORIES, cv_means, c=plot_color)\n #ax.fill_between(\n # NUM_TRAJECTORIES,\n # cv_means - cv_stds,\n # cv_means + cv_stds,\n # alpha=0.2,\n # color=plot_color,\n # edgecolor=\"none\",\n # linewidth=0.0\n #)\n ax.set_xticks(NUM_TRAJECTORIES)\n ax.tick_params(axis='both', which='both', labelsize=\"x-large\")\n ax.set_ylabel(\"Coefficient of variance $\\\\sigma/\\\\mu$\", fontsize=\"x-large\")\n ax.set_xlabel(\"Number of trajectories\", fontsize=\"x-large\")\n ax.grid(alpha=0.2)\n\n axs[1].legend(prop={\"size\": \"large\"})\n pyplot.tight_layout()\n pyplot.savefig(\"figures/metric_comparison.pdf\", bbox_inches=\"tight\", pad_inches=0.0)","def run(self):\n # load_data\n layers = self.load_all_data() # list of tuples (file_name, feature_matrix)\n\n # check variable types\n if len(self.method) == 1:\n self.method = [self.method[0]] * len(layers)\n elif len(layers) != len(self.method):\n raise ValueError(\"Number of matrices extracted from input files and number of similarity methods \" +\n \"does not correspond\")\n\n # check missing value parameter\n if len(self.missing) == 1:\n self.logger.info(\"#Setting all 'missing' parameters to {}\".format(self.missing[0]))\n self.missing = [self.missing[0]] * len(layers)\n elif len(layers) != len(self.missing):\n raise ValueError(\"Number of matrices extracted from input files and number of given missing parameters \" +\n \"does not correspond\")\n\n # extract sample names\n all_samples = set()\n for layer_data in layers:\n all_samples = all_samples.union({name for name in layer_data[1].columns})\n self.logger.info(\"#Total number of unique samples: {}\".format(len(all_samples)))\n\n out_arrays = {}\n adj_matrices = []\n\n # create adjacency matrices\n for i in range(len(layers)):\n self.logger.info(\"#Layer: {}\".format(i))\n layer_data = layers[i][1]\n\n # add missing samples layer\n samples = {name for name in layer_data.columns}\n for name in all_samples - samples:\n layer_data[name] = np.nan\n\n # sort data frame by sample names\n layer_data.sort_index(axis=1, inplace=True)\n\n # extract feature matrices\n f = layer_data.values.T\n self.logger.info(\"Feature matrix: ({} samples x {} features)\".format(f.shape[0], f.shape[1]))\n\n # check if feature matrix values are correct\n ncat = check_categories(f)\n if ncat != [0, 1]:\n standardized = is_standardized(f, axis=0, atol=self.atol)\n if not standardized[0]:\n raise ValueError(\"Incorrect values in feature matrix. Mean of features in \" +\n \"({},{}) \".format(round(standardized[1][0], 3), round(standardized[1][1], 3)) +\n \"range. Standard deviation of features in \" +\n \"({}, {}) \".format(round(standardized[2][0], 3), round(standardized[2][1], 3)) +\n \"range. Please, supply either binary dataset \" +\n \"(0 or 1 feature values) or continuous values standardized feature-wise. \" +\n \"Alternatively for almost standardized continuous data, \" +\n \"increase '-atol' parameter value (currently {}).\".format(self.atol))\n else:\n self.logger.debug(\"Data is correctly standardized\")\n else:\n self.logger.debug(\"Found two unique categories in data: [0, 1]\")\n if self.method[i] != 'cosine':\n self.logger.info(\"Using '{}' similarity for [0, 1] data. \".format(self.method[i]) +\n \"Suggested better measure: cosine similarity.\")\n\n # create adjacency matrix\n a = feature_to_adjacency(f, missing=self.missing[i], method=self.method[i], n=self.k, alpha=self.alpha)\n self.logger.info('Adjacency matrix {} created [similarity method: {}]'.format(a.shape, self.method[i]))\n\n # plot adjacency matrix\n plot_path = self.plot_base + \"_\" + str(i) + \".png\" if self.plot else self.plot_base\n plot_heatmap_seaborn(a, title=\"Layer {} (source:{})\".format(i, layers[i][0]), file_path=plot_path)\n if self.plot:\n self.logger.info(\"Adjacency matrix plot saved to {}\".format(plot_path))\n\n # add matrices to output arrays\n out_arrays[str(i)] = a\n adj_matrices.append(a)\n out_arrays[\"f\" + str(i)] = f\n\n # check if there are samples not accessible in any layer\n missing_samples = []\n for a in adj_matrices:\n missing_samples += [i for i in range(a.shape[1]) if np.all(np.isnan(a[:, i]))]\n\n samples_to_drop = [sample for sample, val in Counter(missing_samples).items() if val == len(adj_matrices)]\n if samples_to_drop:\n # drop inaccessible samples\n self.logger.info(\"Found samples inaccessible in every layer of graph. \" +\n \"Try changing '-missing' parameter or inspect your data \")\n sample_names = np.array(sorted(list(all_samples)))[np.array(samples_to_drop)]\n self.logger.info(\"Dropped samples: {}\".format(list(sample_names)))\n updated_out_arrays = {}\n selector = np.array([x for x in range(len(all_samples)) if x not in samples_to_drop])\n for i in range(len(out_arrays.keys())):\n if str(i) not in out_arrays.keys():\n break\n updated_out_arrays[str(i)] = out_arrays[str(i)][selector[:, None], selector]\n updated_out_arrays[\"f\" + str(i)] = out_arrays[\"f\" + str(i)][selector, :]\n\n # create output file\n updated_out_arrays[\"samples\"] = np.array(sorted(list(all_samples)))[selector]\n save_arrays_to_npz(data=updated_out_arrays, file_path=self.outfile)\n\n else:\n # create output file\n out_arrays[\"samples\"] = np.array(sorted(list(all_samples)))\n save_arrays_to_npz(data=out_arrays, file_path=self.outfile)\n\n self.logger.info(\"#Output file {} created\".format(self.outfile))","def get_feature_statistics(results):\n to_be_deleted = []\n\n for result in results:\n if len(result.subset) != 6:\n to_be_deleted.append(result)\n\n length = len(results)\n feature_labels = datapoint_features\n statistics = {}\n\n for label in feature_labels:\n result_with = metrics.filter_results(results, features=[label])\n result_without = metrics.filter_results(results, without_features=[label])\n\n with_length = len(result_with)\n without_length = len(result_without)\n prevalence = with_length / length\n\n if prevalence != 0:\n avg_f1_dos = math.fsum([result.metrics['dos'].f1 for result in result_with]) / with_length\n avg_f1_fuzzy = math.fsum([result.metrics['fuzzy'].f1 for result in result_with]) / with_length\n avg_f1_imp = math.fsum([result.metrics['impersonation'].f1 for result in result_with]) / with_length\n else:\n avg_f1_dos = 0\n avg_f1_fuzzy = 0\n avg_f1_imp = 0\n\n avg_f1_without_dos = math.fsum([result.metrics['dos'].f1 for result in result_without]) / without_length\n avg_f1_without_fuzzy = math.fsum([result.metrics['fuzzy'].f1 for result in result_without]) / without_length\n avg_f1_without_imp = math.fsum([result.metrics['impersonation'].f1 for result in result_without]) / without_length\n avg_f1_diff_dos = avg_f1_without_dos - avg_f1_dos\n avg_f1_diff_fuzzy = avg_f1_without_fuzzy - avg_f1_fuzzy\n avg_f1_diff_imp = avg_f1_without_imp - avg_f1_imp\n\n statistics[label] = [prevalence, avg_f1_diff_dos, avg_f1_diff_fuzzy, avg_f1_diff_imp]\n\n return statistics","def analyse_algorithms(R, u_t, inverse_transform, true_weight_vect, algo_list, equation, preconditioner):\n\n # Generate the model list for each sparse regression algorithm\n algo_model_list_list = []\n for algo_index, algo in enumerate(algo_list):\n model_list = generate_models(R, u_t, inverse_transform, algo)\n algo_model_list_list.append(model_list)\n\n # set up plot\n symbol_list = ['v', 's', 'o', '+', '*', 'D']\n color_list = [(162 / 256., 173 / 256., 0., 0.9), (156 / 256., 157 / 256., 159 / 256., 0.8),\n (0., 101 / 256., 189 / 256., 1.), (227 / 256., 114 / 256., 34 / 256., 0.9)]\n fig, ax = plt.subplots(figsize=(1.8 * 2.6, 1.8 * 1.95))\n\n # iterate all models of all algorithms and plot the summaries\n for algo_index, algo in enumerate(algo_list):\n model_list = algo_model_list_list[algo_index]\n for i_model, model in enumerate(model_list):\n set_model_correctness_and_error(model, true_weight_vect) # calculate absolute and relative error\n # plot model properties\n ax.semilogy(model.terms, model.mean_rel_err, marker=symbol_list[algo_index], markerfacecolor='none',\n linestyle='None', color=color_list[algo_index], label=algo if i_model == 0 else \"\")\n\n # finish plot\n ax.plot((-1., 10.), (1.5, 1.5), color='k')\n # xlim needs to be adjusted with respect to the maximum number of correct term in the model\n ax.set(ylim=[1.e-9, 75.], xlim=[0.5, 6.5], xlabel='Number of Terms', ylabel='MRE')\n ax.legend(loc=4)\n ax.set_yticks(ax.get_yticks()[:-3])\n ax.set_xticks(np.arange(1, 7, 1))\n plt.savefig('Regression_accuracy_comparison_' + str(equation) + '_' + preconditioner + '_test.png')\n plt.savefig('Regression_accuracy_comparison_' + str(equation) + '_' + preconditioner + '_test.pgf')","def test_query_algorithms_101Algorithms_(self):\n right_list = []\n create_test_algorithm_list(right_list, 101)\n documents = []\n create_test_documents_list(right_list, documents, 101)\n index = search.Index(name=search_algorithm._INDEX_STRING)\n index.put(documents)\n result = search_algorithm.query_algorithms(index)\n self.assertEqual(101, len(result), msg='Wrong number of algorithms')\n self.assertItemsEqual(right_list, result, msg='Discrepancy in returned algorithms')","def main():\n\n file_name_base = \"./lab-record/result/fairness/\"\n scenarios = ['lan', 'wan1', 'wan2']\n scenario = scenarios[2]\n\n algorithms = [\"bbr\", \"scalable\", \"bic\", \"highspeed\", \"htcp\", \"hybla\",\n \"illinois\", \"vegas\", \"yeah\"]\n names = [\"BBR\", \"Scalable\", \"BIC\", \"High Speed\",\n \"H-TCP\", \"Hybla\", \"Illinois\", \"Vegas\", \"YeAH\"]\n\n test_types = [\"vs_reno\", \"vs_cubic\", \"vs_itself\"]\n\n fsize = 36\n \n index_reno = []\n index_cubic = []\n index_itself = []\n\n data = []\n \n print 'Loadint statistics for ' + file_name_base + '/' + scenario\n\n for algorithm in algorithms:\n for test in test_types:\n path_base = file_name_base + \"/\" + scenario + \"/\" + test + \"/\" + \\\n algorithm + \"/\"\n if test == \"vs_itself\":\n exp_name = names[algorithms.index(algorithm)] + \"_1\"\n con_name = names[algorithms.index(algorithm)] + \"_2\"\n print path_base + exp_name\n print path_base + con_name\n exp_filename = \"/\" + algorithm + \"_1.log\"\n con_filename = \"/\" + algorithm + \"_2.log\"\n process(path_base, exp_filename, con_filename, index_itself)\n if test == \"vs_reno\":\n exp_name = names[algorithms.index(algorithm)]\n con_name = \"Reno\"\n print path_base + exp_name\n print path_base + con_name\n exp_filename = \"/\" + algorithm + \".log\"\n con_filename = \"/reno.log\"\n process(path_base, exp_filename, con_filename, index_reno)\n if test == \"vs_cubic\":\n con_name = \"CUBIC\"\n exp_name = names[algorithms.index(algorithm)]\n print path_base + exp_name\n print path_base + con_name\n exp_filename = \"/\" + algorithm + \".log\"\n con_filename = \"/cubic.log\"\n process(path_base, exp_filename, con_filename, index_cubic)\n\n size = 9\n x = numpy.arange(size)\n\n total_width, n = 1.2, 2.5\n width = 1.0 / n\n x = x - (total_width - width) / 2\n\n for i in range(0, len(x)):\n x[i] += 0.5 * i\n\n # Exp\n fig = plt.figure()\n\n # Con\n con_reno = plt.bar(x + 0 * width - 1.2,\n index_reno,\n width=width,\n label='Against Reno',\n alpha=0.5,\n color=\"darkorange\")\n\n con_cubic = plt.bar(x + 1 * width - 1.2,\n index_cubic,\n width=width,\n label='Against CUBIC',\n alpha=0.5,\n color=\"lawngreen\")\n\n con_itself = plt.bar(x + 2 * width - 1.2,\n index_itself,\n width=width,\n label='Against Another Same CCA',\n alpha=0.5,\n color=\"dodgerblue\")\n\n # Index\n plt.xticks(x + 1.5 * width - 1.2, [\"BBR\", \"Scalable\", \"BIC\", \"High Speed\",\n \"H-TCP\", \"Hybla\", \"Illinois\", \"Vegas\",\n \"YeAH\"],\n fontsize=fsize,\n rotation=\"45\")\n plt.ylabel(\"Jain`s Fairness Index\", fontsize=fsize)\n plt.yticks(fontsize=fsize)\n plt.ylim(0.5, 1.1)\n\n ax = plt.subplot(111)\n ax.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3,\n ncol=3, mode=\"expand\", borderaxespad=0., fontsize=fsize)\n\n plt.subplots_adjust(left=0.07, right=0.98, top=0.9, bottom=0.2)\n\n plt.show()","def set_algorithm(self, algorithm):\n self._data_dict[self.ALGO_INFO] = {'module' : algorithm.algo_group.module,\n 'class' : algorithm.algo_group.classname,\n 'init_param' : algorithm.algo_group.init_parameter,\n 'identifier' : algorithm.identifier}"],"string":"[\n \"def evaluate_clustering_methods(methods):\\r\\n results = {}\\r\\n for m in methods:\\r\\n res = results[m['name']] = {}\\r\\n prec = 3\\r\\n res['Adjusted Rand Score'] = round(sklearn.metrics.adjusted_rand_score(m['target'], m['clustering']),prec)\\r\\n res['Normalized Mutual Information'] = round(sklearn.metrics.normalized_mutual_info_score(m['target'], m['clustering']),prec)\\r\\n res['Adjusted Mutual Information'] = round(sklearn.metrics.adjusted_mutual_info_score(m['target'], m['clustering']),prec)\\r\\n return np.transpose(results)\",\n \"def __init__(self, dictAlg):\\n\\n # values of dict dictAlg are DataSetList which should have only one\\n # element which will be assigned as values in the following lines.\\n d = set()\\n f = set()\\n for i in dictAlg.values():\\n d |= set(j.dim for j in i)\\n f |= set(j.funcId for j in i)\\n\\n if len(f) > 1 or len(d) > 1:\\n Usage('Expect the data of algorithms for only one function and '\\n 'one dimension.')\\n\\n f = f.pop()\\n d = d.pop()\\n\\n dictMaxEvals = {}\\n dictFinalFunVals = {}\\n tmpdictAlg = {}\\n for alg, i in dictAlg.iteritems():\\n if len(i) == 0:\\n warnings.warn('Algorithm %s was not tested on f%d %d-D.'\\n % (alg, f, d))\\n continue\\n elif len(i) > 1:\\n warnings.warn('Algorithm %s has a problem on f%d %d-D.'\\n % (alg, f, d))\\n continue\\n\\n tmpdictAlg[alg] = i[0] # Assign ONLY the first element as value\\n dictMaxEvals[alg] = i[0].maxevals\\n dictFinalFunVals[alg] = i[0].finalfunvals\\n\\n dictAlg = tmpdictAlg\\n\\n sortedAlgs = dictAlg.keys()\\n # algorithms will be sorted along sortedAlgs which is now a fixed list\\n\\n # Align ERT\\n erts = list(np.transpose(np.vstack([dictAlg[i].target, dictAlg[i].ert]))\\n for i in sortedAlgs)\\n res = readalign.alignArrayData(readalign.HArrayMultiReader(erts))\\n\\n resalgs = []\\n reserts = []\\n # For each function value\\n for i in res:\\n # Find best algorithm\\n curerts = i[1:]\\n assert len((np.isnan(curerts) == False)) > 0\\n currentbestert = np.inf\\n currentbestalg = ''\\n for j, tmpert in enumerate(curerts):\\n if np.isnan(tmpert):\\n continue # TODO: don't disregard these entries\\n if tmpert == currentbestert:\\n # TODO: what do we do in case of ties?\\n # look at function values corresponding to the ERT?\\n # Look at the function evaluations? the success ratio?\\n pass\\n elif tmpert < currentbestert:\\n currentbestert = tmpert\\n currentbestalg = sortedAlgs[j]\\n reserts.append(currentbestert)\\n resalgs.append(currentbestalg)\\n\\n dictiter = {}\\n dictcurLine = {}\\n resDataSet = []\\n\\n # write down the #fevals to reach the function value.\\n for funval, alg in zip(res[:, 0], resalgs):\\n it = dictiter.setdefault(alg, iter(dictAlg[alg].evals))\\n curLine = dictcurLine.setdefault(alg, np.array([np.inf, 0]))\\n while curLine[0] > funval:\\n try:\\n curLine = it.next()\\n except StopIteration:\\n break\\n dictcurLine[alg] = curLine.copy()\\n tmp = curLine.copy()\\n tmp[0] = funval\\n resDataSet.append(tmp)\\n\\n setalgs = set(resalgs)\\n dictFunValsNoFail = {}\\n for alg in setalgs:\\n for curline in dictAlg[alg].funvals:\\n if (curline[1:] == dictAlg[alg].finalfunvals).any():\\n # only works because the funvals are monotonous\\n break\\n dictFunValsNoFail[alg] = curline.copy()\\n\\n self.evals = resDataSet\\n # evals is not a np array but a list of arrays because they may not\\n # all be of the same size.\\n self.maxevals = dict((i, dictMaxEvals[i]) for i in setalgs)\\n self.finalfunvals = dict((i, dictFinalFunVals[i]) for i in setalgs)\\n self.funvalsnofail = dictFunValsNoFail\\n self.dim = d\\n self.funcId = f\\n self.algs = resalgs\\n self.algId = 'Virtual Best Algorithm'\\n self.comment = 'Combination of ' + ', '.join(sortedAlgs)\\n self.ert = np.array(reserts)\\n self.target = res[:, 0]\\n\\n bestfinalfunvals = np.array([np.inf])\\n for alg in sortedAlgs:\\n if np.median(dictAlg[alg].finalfunvals) < np.median(bestfinalfunvals):\\n bestfinalfunvals = dictAlg[alg].finalfunvals\\n algbestfinalfunvals = alg\\n self.bestfinalfunvals = bestfinalfunvals\\n self.algbestfinalfunvals = algbestfinalfunvals\",\n \"def get_clustering_algorithm_class(cls):\\n return {\\n \\\"spectral\\\": SpectralClusteringAlgorithm,\\n \\\"dbscan\\\": DBSCANAlgorithm,\\n \\\"gromos\\\": GromosAlgorithm,\\n \\\"kmedoids\\\": KMedoidsAlgorithm,\\n \\\"random\\\": RandomClusteringAlgorithm,\\n \\\"hierarchical\\\": HierarchicalClusteringAlgorithm\\n }\",\n \"def cluster_analysis(\\n clusterers: list,\\n hyperparameter_grids: list,\\n eval_metrics_grid: list,\\n eval_metrics_params: dict,\\n word_embeddings: np.ndarray,\\n words_vocabulary: list,\\n word_to_int: dict,\\n word_embeddings_normalized: np.ndarray = None,\\n compute_pairwise_word_distances: bool = False,\\n compute_pairwise_word_distances_normalized: bool = False,\\n return_word_vectors: bool = False,\\n save_result_to_disk: bool = False,\\n output_dir: Optional[str] = None,\\n model_name: Optional[str] = None,\\n dataset_name: Optional[str] = None,\\n output_filepath_suffix: Optional[str] = None,\\n) -> Union[dict, tuple]:\\n # Create word vectors from given words/vocabulary\\n word_vectors = words_to_vectors(\\n words_vocabulary=words_vocabulary,\\n word_to_int=word_to_int,\\n word_embeddings=word_embeddings,\\n )\\n\\n # Create normalized word vectors from given words/vocabulary if specified.\\n word_vectors_normalized = None\\n if word_embeddings_normalized is not None:\\n word_vectors_normalized = words_to_vectors(\\n words_vocabulary=words_vocabulary,\\n word_to_int=word_to_int,\\n word_embeddings=word_embeddings_normalized,\\n )\\n\\n if compute_pairwise_word_distances:\\n word_vectors_pairwise_distances = pairwise_cosine_distances(word_vectors)\\n if (\\n compute_pairwise_word_distances_normalized\\n and word_vectors_normalized is not None\\n ):\\n normalized_word_vectors_pairwise_distances = euclidean_distances(\\n word_vectors_normalized\\n )\\n\\n # Perform cluster analysis\\n clusterers_result = {}\\n unique_cluster_metrics = set()\\n for clusterer_tuple, hyperparameter_grid, eval_metrics in zip(\\n clusterers, hyperparameter_grids, eval_metrics_grid\\n ):\\n if len(clusterer_tuple) == 3:\\n (clusterer_name, clusterer_cls, clusterer_use_normalized) = clusterer_tuple\\n else:\\n clusterer_use_normalized = False\\n (clusterer_name, clusterer_cls) = clusterer_tuple\\n print(f\\\"-- Clustering using {clusterer_name} --\\\")\\n clusterers_result[clusterer_name] = {\\n \\\"cluster_labels\\\": [],\\n \\\"cluster_params\\\": [],\\n \\\"cluster_metrics\\\": {},\\n }\\n\\n # Do clustering for each set of hyperparameters\\n param_grid = ParameterGrid(hyperparameter_grid)\\n for params_idx, params in enumerate(tqdm(param_grid)):\\n clusterers_result[clusterer_name][\\\"cluster_params\\\"].append(params)\\n\\n # Add exception for ward linkage clustering.\\n if (\\n clusterer_cls is AgglomerativeClustering\\n and params.get(\\\"linkage\\\") == \\\"ward\\\"\\n and word_vectors_normalized is not None\\n ):\\n params = {**params, \\\"affinity\\\": \\\"euclidean\\\"}\\n clusterer_instance = clusterer_cls(**params)\\n fit_predict_X = word_vectors_normalized\\n else:\\n clusterer_instance = clusterer_cls(**params)\\n if (\\n params.get(\\\"affinity\\\") == \\\"precomputed\\\"\\n or params.get(\\\"metric\\\") == \\\"precomputed\\\"\\n ):\\n if (\\n clusterer_use_normalized\\n and compute_pairwise_word_distances_normalized\\n ):\\n fit_predict_X = normalized_word_vectors_pairwise_distances\\n elif compute_pairwise_word_distances:\\n fit_predict_X = word_vectors_pairwise_distances\\n else:\\n if clusterer_use_normalized and word_vectors_normalized is not None:\\n fit_predict_X = word_vectors_normalized\\n else:\\n fit_predict_X = word_vectors\\n\\n # Use fit_predict if it is available.\\n if getattr(clusterer_instance, \\\"fit_predict\\\", None) is not None:\\n predicted_labels = clusterer_instance.fit_predict(fit_predict_X)\\n else:\\n clusterer_instance.fit(fit_predict_X)\\n predicted_labels = clusterer_instance.predict(fit_predict_X)\\n\\n # Separate noise labels into clusters\\n if clusterer_cls is HDBSCAN:\\n predicted_labels = separate_noise_labels_into_clusters(predicted_labels)\\n\\n clusterers_result[clusterer_name][\\\"cluster_labels\\\"].append(predicted_labels)\\n\\n # Evaluate predicted cluster labels using internal evaluation metrics\\n for eval_metric_tuple in eval_metrics:\\n if len(eval_metric_tuple) == 3:\\n (\\n eval_metric_key,\\n eval_metric,\\n eval_metric_use_normalized,\\n ) = eval_metric_tuple\\n else:\\n eval_metric_use_normalized = False\\n (eval_metric_key, eval_metric) = eval_metric_tuple\\n eval_metric_params = eval_metrics_params.get(eval_metric_key, {})\\n if (\\n compute_pairwise_word_distances\\n and eval_metric_params.get(\\\"metric\\\") == \\\"precomputed\\\"\\n ):\\n if (\\n eval_metric_use_normalized\\n and compute_pairwise_word_distances_normalized\\n ):\\n metric_name, metric_score, metric_obj_max = eval_metric(\\n word_embeddings=normalized_word_vectors_pairwise_distances,\\n cluster_labels=predicted_labels,\\n clusterer=clusterer_instance,\\n **eval_metric_params,\\n )\\n else:\\n metric_name, metric_score, metric_obj_max = eval_metric(\\n word_embeddings=word_vectors_pairwise_distances,\\n cluster_labels=predicted_labels,\\n clusterer=clusterer_instance,\\n **eval_metric_params,\\n )\\n else:\\n if (\\n eval_metric_use_normalized\\n and word_vectors_normalized is not None\\n ):\\n metric_name, metric_score, metric_obj_max = eval_metric(\\n word_embeddings=word_vectors_normalized,\\n cluster_labels=predicted_labels,\\n clusterer=clusterer_instance,\\n **eval_metric_params,\\n )\\n else:\\n metric_name, metric_score, metric_obj_max = eval_metric(\\n word_embeddings=word_vectors,\\n cluster_labels=predicted_labels,\\n clusterer=clusterer_instance,\\n **eval_metric_params,\\n )\\n unique_cluster_metrics.add(metric_name)\\n\\n # Initialize metric result\\n if (\\n metric_name\\n not in clusterers_result[clusterer_name][\\\"cluster_metrics\\\"]\\n ):\\n clusterers_result[clusterer_name][\\\"cluster_metrics\\\"][\\n metric_name\\n ] = {\\n \\\"metric_scores\\\": [],\\n \\\"metric_obj_max\\\": metric_obj_max,\\n \\\"best_metric_score_indices\\\": [],\\n }\\n\\n clusterers_result[clusterer_name][\\\"cluster_metrics\\\"][metric_name][\\n \\\"metric_scores\\\"\\n ].append(metric_score)\\n\\n # Set best metric score indices\\n if params_idx == len(param_grid) - 1:\\n best_metric_score_indices = np.argsort(\\n clusterers_result[clusterer_name][\\\"cluster_metrics\\\"][\\n metric_name\\n ][\\\"metric_scores\\\"]\\n )\\n if metric_obj_max:\\n best_metric_score_indices = best_metric_score_indices[::-1]\\n clusterers_result[clusterer_name][\\\"cluster_metrics\\\"][metric_name][\\n \\\"best_metric_score_indices\\\"\\n ] = best_metric_score_indices\\n\\n # Find preferred clusterers for each cluster metric (from best to worst)\\n metric_preferred_clusterers = {}\\n for cluster_metric_name in unique_cluster_metrics:\\n metric_obj_max = None\\n metric_best_scores = []\\n clusterer_names = []\\n for clusterer_name, clusterer_result in clusterers_result.items():\\n if cluster_metric_name in clusterer_result[\\\"cluster_metrics\\\"]:\\n clusterer_names.append(clusterer_name)\\n metric_result = clusterer_result[\\\"cluster_metrics\\\"][cluster_metric_name]\\n if metric_obj_max is None:\\n metric_obj_max = metric_result[\\\"metric_obj_max\\\"]\\n best_metric_score = metric_result[\\\"metric_scores\\\"][\\n metric_result[\\\"best_metric_score_indices\\\"][0]\\n ]\\n metric_best_scores.append(best_metric_score)\\n clusterer_names = np.array(clusterer_names)\\n metric_best_scores = np.array(metric_best_scores)\\n\\n metric_best_scores_sorted_indices = np.argsort(metric_best_scores)\\n if metric_obj_max:\\n metric_best_scores_sorted_indices = metric_best_scores_sorted_indices[::-1]\\n metric_preferred_clusterers[cluster_metric_name] = {\\n \\\"clusterer_names\\\": clusterer_names[metric_best_scores_sorted_indices],\\n \\\"best_metric_scores\\\": metric_best_scores[metric_best_scores_sorted_indices],\\n }\\n\\n # Return result as dictionary\\n cluster_analysis_result = {\\n \\\"clusterers\\\": clusterers_result,\\n \\\"metric_preferred_clusterers\\\": metric_preferred_clusterers,\\n }\\n\\n if return_word_vectors:\\n if compute_pairwise_word_distances:\\n cluster_analysis_result = (\\n cluster_analysis_result,\\n word_vectors,\\n word_vectors_pairwise_distances,\\n )\\n else:\\n cluster_analysis_result = (cluster_analysis_result, word_vectors)\\n\\n # Save result to disk\\n if save_result_to_disk:\\n save_cluster_result_to_disk(\\n cluster_result=cluster_analysis_result,\\n output_dir=output_dir,\\n model_name=model_name,\\n dataset_name=dataset_name,\\n output_filepath_suffix=output_filepath_suffix,\\n )\\n\\n return cluster_analysis_result\",\n \"def eval_cluster_contingency(clustering_alg: List, labels_true, sdist):\\n for (alg_name, alg_dict) in clustering_alg:\\n if \\\"alg\\\" in alg_dict:\\n clustering = alg_dict[\\\"alg\\\"].fit(sdist)\\n labels_pred = clustering.labels_\\n alg_dict[\\\"labels\\\"] = labels_pred\\n else:\\n labels_pred = alg_dict[\\\"labels\\\"]\\n\\n pred_label_dict, new_labels = normalize_labels(labels_pred)\\n\\n alg_dict[\\\"cm\\\"] = contingency_matrix(labels_true, new_labels)\",\n \"def _eval_clustering(self, gen_reviews, clusters, embedding_model, clustering):\\n result = []\\n preds = self.predict_gen(gen_reviews, embedding_model, clustering)\\n\\n acc = accuracy_score(np.array(clusters), np.array(preds))\\n conf = confusion_matrix(np.array(clusters), np.array(preds))\\n\\n return acc, conf\",\n \"def generate_clustering_info(self, algorithm_type, clustering_parameters, clusterings = []):\\n clustering_info = {}\\n for i, running_parameters in enumerate(clustering_parameters):\\n\\n clustering_id = \\\"clustering_%04d\\\"%(self.current_clustering_id)\\n self.current_clustering_id += 1\\n clustering_info[clustering_id] = {\\n \\\"type\\\":algorithm_type,\\n \\\"clustering\\\": None,\\n \\\"parameters\\\": running_parameters\\n }\\n\\n if clusterings != []:\\n clustering_info[clustering_id][\\\"clustering\\\"] = clusterings[i]\\n\\n return clustering_info\",\n \"def run_algorithm(algorithm, algorithm_kwargs, clustering_id):\\n clustering = algorithm.perform_clustering(algorithm_kwargs)\\n return (clustering_id, clustering)\",\n \"def main(argv=None):\\n\\n if argv is None:\\n argv = sys.argv\\n\\n # setup command line parser\\n parser = E.OptionParser(version=\\\"%prog version: $Id$\\\",\\n usage=globals()[\\\"__doc__\\\"])\\n\\n parser.add_option(\\\"-t\\\", \\\"--test\\\", dest=\\\"test\\\", type=\\\"string\\\",\\n help=\\\"supply help\\\")\\n\\n parser.add_option(\\\"--method\\\", dest=\\\"method\\\", type=\\\"choice\\\",\\n choices=(\\\"metrics\\\", \\\"summary\\\", \\\"module_summary\\\"),\\n help=\\\"method to summarise clustering\\\")\\n\\n parser.add_option(\\\"--ref-gtf-files\\\", dest=\\\"ref_gtf\\\", type=\\\"string\\\",\\n help=\\\"comma separated list of reference gtf files\\\")\\n\\n # add common options (-h/--help, ...) and parse command line\\n (options, args) = E.Start(parser, argv=argv)\\n\\n if options.method == \\\"metrics\\\":\\n infile = argv[-1]\\n E.info(\\\"loading input file: %s\\\" % infile)\\n assert infile\\n\\n df = pd.read_table(infile,\\n sep=\\\"\\\\t\\\",\\n header=None,\\n index_col=0)\\n\\n df = df.ix[:, :50]\\n cluster_combs = (x for x in itertools.combinations(df.columns,\\n 2))\\n genes = df.index\\n results_dict = {}\\n all_clusts = {}\\n\\n E.info(\\\"setting up cluster containers\\\")\\n for i in df.columns:\\n clusters = set(df[i].values.tolist())\\n cluster_dict = {}\\n for clust in clusters:\\n cluster_dict[clust] = []\\n for gene in genes:\\n cluster_dict[df[i][gene]].append(gene)\\n\\n for col in clusters:\\n col_set = set()\\n clust_col = cluster_dict[col]\\n gene_members = itertools.combinations(clust_col,\\n 2)\\n col_set.update(gene_members)\\n cluster_dict[col] = col_set\\n all_clusts[i] = cluster_dict\\n E.info(\\\"generating all pair-wise cluster comparisons\\\")\\n E.info(\\\"calculating adjusted mutual information\\\")\\n for k in cluster_combs:\\n clusters1 = all_clusts[k[0]]\\n clusters2 = all_clusts[k[1]]\\n metric_dict = {}\\n metric_dict['AMI'] = TS.adjustedMutualInformation(clusters1,\\n clusters2)\\n results_dict[k] = metric_dict\\n\\n res_frame = pd.DataFrame(results_dict).T\\n res_frame = res_frame.reset_index()\\n res_frame.drop(['level_0'], inplace=True, axis=1)\\n res_frame.drop(['level_1'], inplace=True, axis=1)\\n\\n # flatten rand indices and add to output dataframe\\n rand_arrays = TS.randIndexes(df)\\n flat_adj_rand = TS.unravel_arrays(rand_arrays[0])\\n flat_rand = TS.unravel_arrays(rand_arrays[1])\\n res_frame['Rand_Index'] = flat_rand\\n res_frame['Adjusted_Rand_Index'] = flat_adj_rand\\n E.info(\\\"aggregating results\\\")\\n\\n res_frame.to_csv(options.stdout,\\n sep=\\\"\\\\t\\\",\\n index_label='idx')\\n\\n elif options.method == \\\"summary\\\":\\n infiles = argv[-1]\\n list_of_files = infiles.split(\\\",\\\")\\n\\n file_dict = {}\\n for fle in list_of_files:\\n fname = fle.split(\\\"/\\\")[-1]\\n condition = fname.split(\\\"-\\\")[0]\\n ref = fname.split(\\\"-\\\")[1]\\n df_ = pd.read_table(fle,\\n sep=\\\"\\\\t\\\",\\n header=0,\\n index_col=0)\\n df_.columns = ['gene_id', 'cluster']\\n clust_dict = {}\\n for idx in df_.index:\\n cluster = df_.loc[idx]['cluster']\\n gene = df_.loc[idx]['gene_id']\\n try:\\n clust_dict[cluster] += 1\\n except KeyError:\\n clust_dict[cluster] = 1\\n med_size = np.median(clust_dict.values())\\n file_dict[fname] = {'condition': condition,\\n 'reference': ref,\\n 'median_cluster_size': med_size}\\n\\n outframe = pd.DataFrame(file_dict).T\\n outframe.to_csv(options.stdout,\\n sep=\\\"\\\\t\\\",\\n index_label='idx')\\n\\n elif options.method == \\\"module_summary\\\":\\n # get lncRNA/gene lengths from reference gtfs\\n ref_gtfs = options.ref_gtf.split(\\\",\\\")\\n length_dict = {}\\n for ref in ref_gtfs:\\n oref = IOTools.openFile(ref, \\\"rb\\\")\\n git = GTF.transcript_iterator(GTF.iterator(oref))\\n for gene in git:\\n for trans in gene:\\n length = trans.end - trans.start\\n try:\\n length_dict[trans.gene_id] += length\\n except KeyError:\\n length_dict[trans.gene_id] = length\\n oref.close()\\n\\n infiles = argv[-1]\\n list_of_files = infiles.split(\\\",\\\")\\n\\n fdfs = []\\n for fle in list_of_files:\\n cond = fle.split(\\\"/\\\")[-1].split(\\\"-\\\")[0]\\n refer = fle.split(\\\"/\\\")[-1].split(\\\"-\\\")[1]\\n _df = pd.read_table(fle, sep=\\\"\\\\t\\\",\\n header=0, index_col=0)\\n _df.columns = ['gene_id', 'cluster']\\n clusters = set(_df['cluster'])\\n c_dict = {}\\n # summarize over each cluster\\n for clust in clusters:\\n lengths = []\\n c_df = _df[_df['cluster'] == clust]\\n for lid in c_df['gene_id']:\\n lengths.append(length_dict[lid])\\n c_dict[clust] = {'cluster_size': len(c_df['gene_id']),\\n 'mean_length': np.mean(lengths),\\n 'index': (cond, refer),\\n 'module': clust}\\n cdf = pd.DataFrame(c_dict).T\\n # use a multindex for hierarchical indexing\\n midx = pd.MultiIndex.from_tuples(cdf['index'])\\n cdf.index = midx\\n cdf.drop(['index'], inplace=True, axis=1)\\n fdfs.append(cdf)\\n\\n # generate a single output df\\n s_df = fdfs[0]\\n fdfs.pop(0)\\n for df in fdfs:\\n s_df = s_df.append(df)\\n\\n s_df.to_csv(options.stdout,\\n index_label=(\\\"condition\\\", \\\"reference\\\"),\\n sep=\\\"\\\\t\\\")\\n\\n # write footer and output benchmark information.\\n E.Stop()\",\n \"def interpret_clusters(self, split=0.7, all_demos=None, num_clusters=None, \\n max_depth=CLUSTER_DEPTH, data=None, labels=None, verbose=True):\\n all_demos = self.all_data if all_demos is None else all_demos\\n clusters = self.get_ordered_clusters(labels, num_clusters)\\n data = self.demos if data is None else data\\n labels = self.labels if labels is None else labels\\n\\n cluster_formulas = []\\n counter = 0\\n sep = \\\"\\\\n \\\"\\n for c in clusters:\\n counter += 1\\n res = self.sample_from_clusters(num_samples=split,\\n all_data=all_demos,\\n pos_validation=True, \\n neg_validation=True,\\n which_cluster=counter)\\n positive_samples, val_positive_samples = res[0], res[1]\\n negative_samples, val_negative_samples = res[2], res[3]\\n z = 0\\n for d in positive_samples:\\n if d[1] == 0: z += 1\\n\\n cluster_data = {'pos': positive_samples,\\n 'neg': negative_samples}\\n val_cluster_data = {'pos': val_positive_samples,\\n 'neg': val_negative_samples}\\n\\n if verbose: print(sep +\\\"Checking formulas \\\" + \\\\\\n \\\"with max depth {}\\\\n\\\".format(max_depth))\\n\\n cluster_formula, value_formula = wrapper_train(max_depth,\\n cluster_data, \\n val_cluster_data,\\n verbose=verbose,\\n pred_data=[self.pipeline_X,\\n self.pipeline_y])\\n if cluster_formula is not None:\\n print(cluster_formula)\\n\\n cluster_formulas.append((c, cluster_formula, value_formula))\\n self.reset_pipeline()\\n\\n return cluster_formulas\",\n \"def run_evaluation(self, n_runs=1, n_points=1000, n_iterations=1, min_n_components=2, max_n_components=25,\\n\\t\\t\\t\\t\\t n_splits=3, save_data=False, file_label='',n_microstates=None, all_methods=True,\\n\\t\\t\\t\\t\\t assign_transition_points=True):\\n\\n\\t\\tif self.presampled_data is not None:\\n\\t\\t\\tsampled_data = self.presampled_data[0]\\n\\t\\t\\ttrue_clustering = self.presampled_data[1]\\n\\t\\t\\tn_runs = sampled_data.shape[0]\\n\\n\\t\\tself.cluster_score_ami_kmeans_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_ami_AW_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_ami_spectral_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_ami_density_peaks_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_ami_GMM_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_ami_GMM_FE_min_ = np.zeros(n_runs)\\n\\n\\t\\tself.cluster_score_fm_kmeans_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_fm_AW_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_fm_spectral_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_fm_density_peaks_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_fm_GMM_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_fm_GMM_FE_min_ = np.zeros(n_runs)\\n\\n\\t\\tself.cluster_score_vm_kmeans_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_vm_AW_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_vm_spectral_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_vm_density_peaks_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_vm_GMM_ = np.zeros(n_runs)\\n\\t\\tself.cluster_score_vm_GMM_FE_min_ = np.zeros(n_runs)\\n\\n\\t\\tdata = self.toy_model_.sample(3)\\n\\n\\t\\t# Create free energy estimators\\n\\t\\tgmm_FE = GMM_FE.FreeEnergyClustering(data, min_n_components=min_n_components, max_n_components=max_n_components,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t x_lims=self.x_lims_, n_grids=self.n_grids_, stack_landscapes=False,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t n_splits=n_splits, n_iterations=n_iterations,convergence_tol=self.convergence_tol_,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t verbose=self.verbose_)\\n\\n\\t\\tkm = kmc.KMeansCluster(min_n_components, max_n_components)\\n\\t\\taw = awc.AWCluster(min_n_components, max_n_components)\\n\\t\\tspectral = sc.SpectralCluster(min_n_components, max_n_components)\\n\\n\\t\\tall_data = []\\n\\t\\tfor i_run in range(n_runs):\\n\\t\\t\\tprint(\\\"Run: \\\"+str(i_run+1)+'/'+str(n_runs))\\n\\n\\t\\t\\tif self.presampled_data is None:\\n\\t\\t\\t\\t# Sample data\\n\\t\\t\\t\\tdata = self.toy_model_.sample(n_points)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tdata = sampled_data[i_run]\\n\\t\\t\\t\\n\\t\\t\\tall_data.append(data)\\n\\n\\t\\t\\tprint('Shape data: ' + str(data.shape))\\n\\n\\t\\t\\t# Set data in model and estimate GMM density\\n\\t\\t\\tgmm_FE.data_ = data\\n\\t\\t\\tcoords, est_FE_landsc, FE_points = gmm_FE.landscape()\\n\\n\\t\\t\\t# Get true cluster labels\\n\\t\\t\\tif self.presampled_data is None:\\n\\t\\t\\t\\tif hasattr(self.toy_model_, \\\"assign_cluster_labels\\\"):\\n\\t\\t\\t\\t\\tself.true_labels_ = self.toy_model_.assign_cluster_labels(data)\\n\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\tprint('Setting true labels.')\\n\\t\\t\\t\\t\\tself.true_labels_, _ = self.true_FE_.cluster(data, np.zeros(data.shape[0]))\\n\\t\\t\\telse:\\n\\t\\t\\t\\tself.true_labels_ = true_clustering[i_run]\\n\\t\\t\\t\\n\\t\\t\\t# Cluster data with different methods\\n\\t\\t\\tif n_microstates is None:\\n\\t\\t\\t\\tself.FE_min_labels, _ = gmm_FE.cluster(data, FE_points, assign_transition_points=assign_transition_points)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tkmea = KMeans(n_clusters=n_microstates).fit(data[::2])\\n\\t\\t\\t\\tmicrostate_centers = kmea.cluster_centers_\\n\\t\\t\\t\\tself.FE_min_labels, _ = gmm_FE.cluster(microstate_centers, FE_points, data, assign_transition_points=assign_transition_points, unravel_grid=False)\\n\\n\\t\\t\\tif all_methods:\\n\\t\\t\\t\\tself.km_labels = km.cluster(data)\\n\\t\\t\\t\\tself.aw_labels = aw.cluster(data)\\n\\t\\t\\t\\tself.spectral_labels = spectral.cluster(data)\\n\\n\\t\\t\\t# Score clustering using different scoring metrics\\n\\t\\t\\t# V-measure score\\n\\t\\t\\tself.cluster_score_vm_GMM_FE_min_[i_run] = self._score_clustering(self.FE_min_labels,'vm')\\n\\t\\t\\tprint(self.cluster_score_vm_GMM_FE_min_[i_run])\\n\\t\\t\\tif all_methods:\\n\\t\\t\\t\\tself.cluster_score_vm_GMM_[i_run] = self._score_clustering(gmm_FE.density_est_.predict(data),'vm')\\n\\t\\t\\t\\tself.cluster_score_vm_kmeans_[i_run] = self._score_clustering(self.km_labels,'vm')\\n\\t\\t\\t\\tself.cluster_score_vm_AW_[i_run] = self._score_clustering(self.aw_labels,'vm')\\n\\t\\t\\t\\tself.cluster_score_vm_spectral_[i_run] = self._score_clustering(self.spectral_labels,'vm')\\n\\n\\t\\t\\t\\t# Adjusted MI\\n\\t\\t\\t\\tself.cluster_score_ami_GMM_FE_min_[i_run] = self._score_clustering(self.FE_min_labels,'ami')\\n\\t\\t\\t\\tself.cluster_score_ami_GMM_[i_run] = self._score_clustering(gmm_FE.density_est_.predict(data),'ami')\\n\\t\\t\\t\\tself.cluster_score_ami_kmeans_[i_run] = self._score_clustering(self.km_labels,'ami')\\n\\t\\t\\t\\tself.cluster_score_ami_AW_[i_run] = self._score_clustering(self.aw_labels,'ami')\\n\\t\\t\\t\\tself.cluster_score_ami_spectral_[i_run] = self._score_clustering(self.spectral_labels,'ami')\\n\\n\\t\\t\\t\\t# Fowlkes Mallows\\n\\t\\t\\t\\tself.cluster_score_fm_GMM_FE_min_[i_run] = self._score_clustering(self.FE_min_labels,'fm')\\n\\t\\t\\t\\tself.cluster_score_fm_GMM_[i_run] = self._score_clustering(gmm_FE.density_est_.predict(data),'fm')\\n\\t\\t\\t\\tself.cluster_score_fm_kmeans_[i_run] = self._score_clustering(self.km_labels,'fm')\\n\\t\\t\\t\\tself.cluster_score_fm_AW_[i_run] = self._score_clustering(self.aw_labels,'fm')\\n\\t\\t\\t\\tself.cluster_score_fm_spectral_[i_run] = self._score_clustering(self.spectral_labels,'fm')\\n\\t\\t\\n\\t\\tif save_data:\\n\\t\\t\\tif self.presampled_data is None:\\n\\t\\t\\t\\tnp.save('data_out/sampled_data_'+self.toy_model_.name+file_label+'.npy',all_data)\\n\\n\\t\\t\\tif False:\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_fm_FE_min_'+self.toy_model_.name+file_label+'.npy',self.cluster_score_fm_GMM_FE_min_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_fm_GMM_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_fm_GMM_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_fm_kmeans_' + self.toy_model_.name +file_label +'.npy', self.cluster_score_fm_kmeans_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_fm_AW_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_fm_AW_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_fm_spectral_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_fm_spectral_)\\n\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_ami_FE_min_'+self.toy_model_.name+file_label+'.npy',self.cluster_score_ami_GMM_FE_min_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_ami_GMM_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_ami_GMM_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_ami_kmeans_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_ami_kmeans_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_ami_AW_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_ami_AW_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_ami_spectral_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_ami_spectral_)\\n\\n\\t\\t\\tnp.save('data_out/cluster_score_vm_FE_min_'+self.toy_model_.name+file_label+'.npy',self.cluster_score_vm_GMM_FE_min_)\\n\\t\\t\\tif all_methods:\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_vm_GMM_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_vm_GMM_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_vm_kmeans_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_vm_kmeans_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_vm_AW_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_vm_AW_)\\n\\t\\t\\t\\tnp.save('data_out/cluster_score_vm_spectral_' + self.toy_model_.name + file_label+'.npy', self.cluster_score_vm_spectral_)\\n\\t\\treturn\",\n \"def fit(self):\\n self.cluseter_agglomerative(n_clusters=20, linkage='average', iterate=5)\\n self.sub_clustering(n_clusters=3, index_cluster=[79], linkage='complete')\\n self.merge_clusters([[0,9,53],[1,83],[46,35,67],[88,23],[6,68]])\\n self.merge_clusters([[6,33,52],[17,14]])\\n self.sub_clustering(n_clusters=2, index_cluster=[0], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[2], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[85], linkage='average')\\n self.sub_clustering(n_clusters=2, index_cluster=[14], linkage='complete')\\n self.sub_clustering(n_clusters=2, index_cluster=[16], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[22], linkage='average')\\n self.sub_clustering(n_clusters=2, index_cluster=[24], linkage='complete')\\n self.sub_clustering(n_clusters=2, index_cluster=[26], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[28], linkage='ward')\\n self.merge_clusters([[6,98,99]])\\n self.merge_clusters([[35,80]])\\n self.sub_clustering(n_clusters=4, index_cluster=[35], linkage='complete')\\n self.merge_clusters([[76,98]])\\n self.sub_clustering(n_clusters=3, index_cluster=[35], linkage='complete')\\n self.merge_clusters([[39,42]])\\n self.sub_clustering(n_clusters=3, index_cluster=[47], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='average')\\n self.merge_clusters([[70,101]])\\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[61], linkage='ward')\\n self.merge_clusters()\\n return\",\n \"def getAllContributingAlgorithmsToBest(algnamelist, target_lb=1e-8, \\n target_ub=1e2):\\n \\n print \\\"Generating best algorithm data from given algorithm list...\\\\n\\\", \\n customgenerate(algnamelist)\\n \\n bestalgfilepath = 'bestCustomAlg'\\n picklefilename = os.path.join(bestalgfilepath, 'bestalg.pickle')\\n fid = open(picklefilename, 'r')\\n bestalgentries = pickle.load(fid)\\n fid.close()\\n print 'loading of best algorithm data done.'\\n \\n countsperalgorithm = {}\\n for (d, f) in bestalgentries:\\n print 'dimension:', d, ', function:', f\\n print f\\n setofalgs = set(bestalgentries[d,f].algs)\\n # pre-processing data to only look at targets >= target_lb:\\n correctedbestalgentries = []\\n for i in range(0,len(bestalgentries[d,f].target)):\\n if ((bestalgentries[d,f].target[i] >= target_lb) and\\n (bestalgentries[d,f].target[i] <= target_ub)):\\n \\n correctedbestalgentries.append(bestalgentries[d,f].algs[i])\\n print len(correctedbestalgentries)\\n # now count how often algorithm a is best for the extracted targets\\n for a in setofalgs:\\n # use setdefault to initialize with zero if a entry not existant:\\n countsperalgorithm.setdefault((d, a), 0) \\n countsperalgorithm[(d,a)] += correctedbestalgentries.count(a)\\n \\n selectedalgsperdimension = {}\\n for (d,a) in sorted(countsperalgorithm):\\n if not selectedalgsperdimension.has_key(d):\\n selectedalgsperdimension[d] = []\\n selectedalgsperdimension[d].append((countsperalgorithm[(d,a)], a))\\n \\n for d in sorted(selectedalgsperdimension):\\n print d, 'D:'\\n for (count, alg) in sorted(selectedalgsperdimension[d], reverse=True):\\n print count, alg\\n print '\\\\n'\\n \\n \\n print \\\" done.\\\"\",\n \"def gen_cluster_accuracies():\\n accuracies = {}\\n with Parallel(n_jobs=morphs.parallel.N_JOBS) as parallel:\\n for block_path in morphs.paths.blocks():\\n print(block_path)\\n spikes = morphs.load.ephys_data(block_path, collapse_endpoints=True)\\n\\n if len(spikes[\\\"recording\\\"].unique()) >= 1:\\n template_spikes = spikes[spikes[\\\"stim_id\\\"].isin(list(\\\"abcdefgh\\\"))]\\n assert len(template_spikes) > 0\\n cluster_groups = template_spikes.groupby(\\\"cluster\\\")\\n\\n morph_dims = spikes.morph_dim.unique()\\n morph_dims = morph_dims[~pd.isnull(morph_dims)]\\n morph_dims.sort()\\n\\n max_num_reps = np.max(\\n [\\n len(stim_group.groupby(by=[\\\"recording\\\", \\\"stim_presentation\\\"]))\\n for stim_id, stim_group in template_spikes.groupby(\\\"stim_id\\\")\\n ]\\n )\\n\\n accuracies_list = parallel(\\n delayed(cluster_accuracy)(\\n cluster, cluster_group, morph_dims, max_num_reps\\n )\\n for (cluster, cluster_group) in cluster_groups\\n )\\n\\n accuracies[block_path] = pd.concat(accuracies_list)\\n\\n morphs.paths.PROCESSED_DIR.mkdir(parents=True, exist_ok=True)\\n with open(morphs.paths.ACCURACIES_PKL.as_posix(), \\\"wb\\\") as f:\\n pickle.dump(accuracies, f)\",\n \"def calculate_all_metrcis(self):\\n self.calculate_gc_metrcis()\\n self.calculate_sam_metrics()\\n self.calculate_classification_metrics()\\n self.calculate_losses()\",\n \"def run(\\n self,\\n number_of_clusters=None,\\n max_K=8,\\n method_clustering=\\\"pam\\\",\\n init_clustering=\\\"random\\\",\\n max_iter_clustering=100,\\n discart_value_JI=0.6,\\n bootstraps_JI=100,\\n bootstraps_p_value=100,\\n n_jobs=1,\\n verbose=1,\\n ):\\n\\n if number_of_clusters is None:\\n self.k = optimizer.optimizeK(\\n self.distance_matrix,\\n self.y.to_numpy(),\\n self.model_type,\\n max_K,\\n method_clustering,\\n init_clustering,\\n max_iter_clustering,\\n discart_value_JI,\\n bootstraps_JI,\\n self.random_state,\\n n_jobs,\\n verbose,\\n )\\n\\n if self.k == 1:\\n warnings.warn(\\\"No stable clusters were found!\\\")\\n return\\n\\n print(f\\\"Optimal number of cluster is: {self.k}\\\")\\n\\n else:\\n self.k = number_of_clusters\\n print(f\\\"Use {self.k} as number of cluster\\\")\\n\\n self.cluster_labels = (\\n kmedoids.KMedoids(\\n n_clusters=self.k,\\n method=method_clustering,\\n init=init_clustering,\\n metric=\\\"precomputed\\\",\\n max_iter=max_iter_clustering,\\n random_state=self.random_state,\\n )\\n .fit(self.distance_matrix)\\n .labels_\\n )\\n\\n (\\n self._data_clustering_ranked,\\n self.p_value_of_features,\\n ) = stats.calculate_global_feature_importance(\\n self.X, self.y, self.cluster_labels, self.model_type\\n )\\n self._p_value_of_features_per_cluster = (\\n stats.calculate_local_feature_importance(\\n self._data_clustering_ranked, bootstraps_p_value\\n )\\n )\",\n \"def get_sklearn_algorithms(verbose=False):\\n from collections import defaultdict\\n import importlib\\n import sklearn\\n algos = defaultdict(list)\\n if verbose: print(dir(sklearn))\\n for nom_module in dir(sklearn):\\n if verbose: print(nom_module)\\n try:\\n to_import = \\\"sklearn.%s\\\" % nom_module\\n module = importlib.import_module(to_import)\\n for nom_fonction in dir(module):\\n fonction = getattr(module, nom_fonction)\\n if hasattr(fonction, \\\"fit\\\"):\\n if verbose: print(\\\" nom algorithme = \\\", nom_fonction)\\n algos[nom_module].append(fonction)\\n except Exception as e:\\n if verbose: print(e)\\n if verbose: print(\\\"=\\\" * 30)\\n return algos\",\n \"def build_algorithm(self, algorithm_type):\\n distance_matrix = self.matrix_handler.distance_matrix\\n algorithm_execution_parameters = {}\\n if algorithm_type == \\\"spectral\\\":\\n # We need to set number of clusters for performance and we get sigma if defined\\n algorithm_execution_parameters[\\\"max_clusters\\\"] = self.evaluation_parameters[\\\"maximum_clusters\\\"]\\n if \\\"sigma\\\" in self.clustering_parameters[\\\"algorithms\\\"][\\\"spectral\\\"]:\\n algorithm_execution_parameters[\\\"sigma_sq\\\"] = self.clustering_parameters[\\\"algorithms\\\"][\\\"spectral\\\"][\\\"sigma\\\"]\\n # else it calculates its own sigma\\n\\n if algorithm_type in [\\\"spectral\\\",\\\"dbscan\\\",\\\"gromos\\\",\\\"kmedoids\\\",\\\"random\\\",\\\"hierarchical\\\"] :\\n return ClusteringExplorer.get_clustering_algorithm_class()[algorithm_type](distance_matrix, **algorithm_execution_parameters)\\n else:\\n print \\\"[ERROR][ClusteringExplorer::build_algorithms] Not known algorithm type ( %s )\\\"%(algorithm_type)\\n self.notify(\\\"SHUTDOWN\\\", \\\"Not known algorithm type ( %s )\\\"%(algorithm_type))\\n exit()\",\n \"def calculate_all_scores(best_phenotype, clustering_algorithm, dataset, y):\\n samples_dist_matrix = distance.squareform(distance.pdist(dataset.values))\\n allowed_fitness = list(DICT_ALLOWED_FITNESSES.keys())\\n scores = [(fitness_name, fitness_value) for fitness_name, fitness_value in\\n zip(allowed_fitness,\\n eval_multiple(dataset.values, clustering_algorithm, allowed_fitness, samples_dist_matrix, y,\\n best_phenotype))]\\n scores = dict(scores)\\n return scores\",\n \"def measureAll(authors_texts,sectorialized_agents):\\n authors_texts=P.text.aux.textFromAuthors(authors_texts,self.topm_dict[\\\"sectorialized_agents\\\"])\\n authors_measures={}\\n # análise de cada mensagem e de cada autor\\n for author in authors_texts:\\n authors_measures[author]={}\\n texts=authors_texts[author]\\n authors_measures[author][\\\"raw_strings\\\"]=P.text.raw.analyseAll(texts)\\n authors_measures[author][\\\"pos\\\"]= P.text.pos.analyseAll(authors_analysis[author][\\\"raw_analysis\\\"])\\n authors_measures[author][ \\\"wordnet\\\" ]=P.text.wordnet.analyseAll(authors_analysis[author][\\\"pos_analysis\\\"])\\n authors_measures[author][\\\"tfIdf\\\"]=P.text.tfIdf.analyseAll(texts) # tfIdf de cada texto e do autor, numeric: mean e std das distancias\\n # análise de cada setor e da estrutura toda\\n# sectors_texts=P.text.aux.textFromSectors(authors_text,sectorialized_agents)\\n sectors_measures={}\\n for sector in sectorialized_agents:\\n sectors_measures[sector][\\\"raw_strings\\\"]=P.text.raw.sectorsAnalyseAll(authors_analysis,sectorialized_agents[sector])\\n sectors_measures[sector][\\\"pos\\\"]= P.text.pos.sectorsAnalyseAll(authors_analysis,sectorialized_agents[sector])\\n sectors_measures[sector][\\\"wordnet\\\"]= P.text.wordnet.sectorsAnalyseAll(authors_analysis,sectorialized_agents[sector])\\n # tfIdf de cada texto e de cada autor, numeric: mean e std das distancias por texto e por autor, e media e etd dos autores\\n sectors_measures[sector][\\\"tfIdf\\\"]= P.text.tfIdf.sectorsAnalyseAll(authors_analysis,sectorialized_agents[sector])\\n\\n# texts=[sectors_texts[i] for i in (\\\"peripherals\\\",\\\"intermediaries\\\",\\\"hubs\\\")]\\n# sectors_analysis[\\\"raw_strings\\\"]=P.text.raw.analyseAll(texts)\\n# sectors_analysis[\\\"pos\\\"]= P.text.pos.analyseAll(sectors_analysis[\\\"raw_analysis\\\"])\\n# sectors_analysis[ \\\"wordnet\\\" ]=P.text.wordnet.analyseAll(sectors_analysis[\\\"pos_analysis\\\"])\\n# sectors_analysis[\\\"tfIdf\\\"]=P.text.tfIdf.tfIdf(texts)\\n\\n overall_measures[\\\"raw_strings\\\"]=P.text.raw.systemAnalysis(sectors_analysis) # medias de toda a rede por mensagem, por autor e por setor\\n overall_measures[\\\"pos\\\"]=P.text.raw.systemAnalysis(sectors_analysis) # medias de toda a rede por mensagem, por autor e por setor\\n overall_measures[\\\"wordnet\\\"]=P.text.raw.systemAnalysis(sectors_analysis) # medias de toda a rede por mensagem, por autor e por setor\\n # tfIdf measurespor texto, autor e setor, numeric: media e desvio das distancias por cada grupo, media e desvio dos setores e dos autores\\n overall_measures[\\\"tfIdf\\\"]=P.text.tfIdf.systemAnalysis(sectors_analysis) # medias de toda a rede por mensagem, por autor e por setor\\n\\n del authors_texts,sectorialized_agents,author, sector\\n return locals()\",\n \"def evaluate(self, clustering):\\n # Pca for each one of the clusters\\n pca_mean_val = 0.;\\n MAX_ELEMENTS = 1000\\n for c in clustering.clusters:\\n # Pick the coordinates (ensuring that we are copying them)\\n element_indexes = c.all_elements\\n ###################\\n # Performance hack\\n ###################\\n # As it can be very slow for big clusters (i.e. > 3k elements) we'll compress this clusters \\n # before calculating PCA. It should increase variance but will allow calculations.\\n # It should use the kmedoids compressor\\n if len(c.all_elements) > MAX_ELEMENTS:\\n element_indexes = c.get_random_sample(MAX_ELEMENTS)\\n print \\\"[PCA] Random sampling too big cluster to improve performance (%d elements -> %d elements).\\\"%(len(c.all_elements),MAX_ELEMENTS)\\n ###################\\n \\n fitting_coordinates_of_this_cluster = self.fitting_coordinates[element_indexes]\\n \\n calculator = RMSDCalculator(calculatorType = \\\"QTRFIT_SERIAL_CALCULATOR\\\",\\n fittingCoordsets = fitting_coordinates_of_this_cluster)\\n \\n if self.calculation_coordinates is not None:\\n calculation_coordinates_of_this_cluster = self.calculation_coordinates[element_indexes]\\n calculator = RMSDCalculator(calculatorType = \\\"QTRFIT_SERIAL_CALCULATOR\\\",\\n fittingCoordsets = fitting_coordinates_of_this_cluster,\\n calculationCoordsets = calculation_coordinates_of_this_cluster)\\n \\n # Make an iterative superposition (to get the minimum RMSD of all with respect to a mean conformation)\\n calculator.iterativeSuperposition()\\n\\n # Calculate the covariance matrix\\n if self.calculation_coordinates is None:\\n covariance_matrix = PCAMetric.create_covariance_matrix(fitting_coordinates_of_this_cluster)\\n else:\\n covariance_matrix = PCAMetric.create_covariance_matrix(calculation_coordinates_of_this_cluster)\\n \\n # And then the eigenvalue we are interested in\\n pca_mean_val += PCAMetric.calculate_biggest_eigenvalue(covariance_matrix)\\n print \\\"PCA finished\\\"\\n return pca_mean_val /clustering.total_number_of_elements\",\n \"def _compute_util_data(self):\\n\\n print(\\\"Computing PCA of document vectors.\\\")\\n self.pca = PCA(n_components = 3)\\n\\n print(\\\"Computing document clusters in PCA basis.\\\")\\n inferred_vecs = np.array([self.model.infer_vector(doc.words) for doc in self.tagged_docs])\\n self.pca_reduced_vecs = self.pca.fit_transform(inferred_vecs)\\n n_clusters = 25 # TODO find way to determine approx cluster size\\n self.kmeans = KMeans(init = 'k-means++', n_clusters = n_clusters, random_state = 0)\\n self.kmeans_preds = self.kmeans.fit_predict(self.pca_reduced_vecs)\",\n \"def compute_feature_properties(self):\\n\\n self.valuecounts = {}\\n self.unique_values = {}\\n self.missing_ratios = {}\\n self.counts = {}\\n self.codemaps = {}\\n for f in self.features:\\n # Compute various things\\n all_values = [self.data[l].get(f,\\\"?\\\") for l in self.data]\\n missing_data_ratio = all_values.count(\\\"?\\\") / (1.0*len(all_values))\\n non_q_values = [v for v in all_values if v != \\\"?\\\"]\\n counts = {}\\n for v in non_q_values:\\n counts[v] = non_q_values.count(v)\\n unique_values = list(set(non_q_values))\\n # Sort unique_values carefully.\\n # Possibly all feature values are numeric strings, e.g. \\\"1\\\", \\\"2\\\", \\\"3\\\".\\n # If we sort these as strings then we get weird things like \\\"10\\\" < \\\"2\\\".\\n # This can actually matter for things like ordinal models.\\n # So convert these to ints first...\\n if all([v.isdigit() for v in unique_values]):\\n unique_values = list(map(int, unique_values))\\n unique_values.sort()\\n unique_values = list(map(str, unique_values))\\n # ...otherwise, just sort normally\\n else:\\n unique_values.sort()\\n self.unique_values[f] = unique_values\\n\\n N = len(unique_values)\\n self.valuecounts[f] = N\\n self.missing_ratios[f] = missing_data_ratio\\n self.counts[f] = counts\\n self.codemaps[f] = self.build_codemap(unique_values)\",\n \"def compute_statistics(self):\\n for i in range(len(self.wine_matrix[0, :])):\\n feature = self.wine_matrix[:, i]\\n self.wine_stats['feature ' + str(i)] = {}\\n if i == 11: # results column\\n self.wine_stats['feature ' + str(i)]['positive_class_ratio'] = (feature == 1).sum() / len(feature)\\n null, self.wine_stats['feature ' + str(i)]['pvalue'] = stats.normaltest(feature)\\n\\n # plot\\n # pyplot.hist(feature, bins=50)\\n # pyplot.show()\\n\\n for i in range(len(self.cancer_matrix[0, :])):\\n feature = self.cancer_matrix[:, i]\\n self.cancer_stats['feature ' + str(i)] = {}\\n if i == 10: # results column\\n self.cancer_stats['feature ' + str(i)]['positive_class_ratio'] = (feature == 1).sum() / len(feature)\\n null, self.cancer_stats['feature ' + str(i)]['pvalue'] = stats.normaltest(feature)\\n\\n # plot\\n # pyplot.hist(feature, bins=50)\\n # pyplot.show()\",\n \"def aggregate_results(results):\\n\\n for (config,con,dec),folds in results.iteritems():\\n m = MODEL_PATTERN.match(config)\\n if m:\\n mode = m.groupdict()['mode'] # mle, rl, mrt, ...\\n model = m.groupdict()['model'] # haem, hacm, hard, ...\\n align = m.groupdict()['align'] # crp, cls ...\\n else:\\n mode, model, align = '', '', ''\\n # mean accuracies across seeds for each fold\\n foldaccuracies = []\\n # we count number of models over folds and seeds\\n num_individual_models = 0\\n\\n for foldname,fold in folds.items():\\n if 'Q' in options.mode:\\n seedaccurracies = fold.values()[:1] if fold.values() else [] # pick one\\n# SUPPORT_STATISTICS[(config,con,dec,model,align,mode,foldname)] += 1\\n else:\\n seedaccurracies = []\\n for seed_acc in fold.values():\\n seedaccurracies.append(seed_acc)\\n SUPPORT_STATISTICS[(config,con,dec,model,align,mode,foldname)] += 1\\n # aggregate on fold level\\n fold['__MEAN__'] = float(np.mean(seedaccurracies))\\n fold['__SD__'] = float(np.std(seedaccurracies))\\n l = len(seedaccurracies)\\n num_individual_models += l\\n SUPPORT_STATISTICS[(config,con,dec,model,align,mode,'__MEAN__')] += l\\n SUPPORT_STATISTICS[(config,con,dec,model,align,mode,'__SD__')] += l\\n\\n # statistics over seeds for this fold\\n fold['__STATS__'] = fold['__MEAN__'], fold['__SD__'], l\\n foldaccuracies.append(fold['__MEAN__'])\\n # aggregate on (config, condition, decoding) level\\n folds['__MEAN__'] = float(np.mean(foldaccuracies))\\n folds['__SD__'] = float(np.std(foldaccuracies))\\n # statistics over folds for this (config, condition, decoding)\\n folds['__STATS__'] = folds['__MEAN__'], folds['__SD__'], num_individual_models\",\n \"def compute_metrics(\\n Phi, optimal_subspace\\n):\\n feature_norm = jnp.linalg.norm(Phi) / Phi.shape[0]\\n cosine_similarity = compute_cosine_similarity(Phi, optimal_subspace)\\n\\n metrics = {\\n 'cosine_similarity': cosine_similarity,\\n 'feature_norm': feature_norm,\\n 'eigengame_subspace_distance': eigengame_subspace_distance(\\n Phi, optimal_subspace\\n ),\\n }\\n\\n _, d = Phi.shape\\n if d > 1:\\n grassman_distance = compute_grassman_distance(Phi, optimal_subspace)\\n metrics |= {'grassman_distance': grassman_distance}\\n elif d == 1:\\n dot_product = compute_normalized_dot_product(Phi, optimal_subspace)\\n metrics |= {'dot_product': dot_product}\\n\\n return metrics\",\n \"def extractBestAlgorithms(args = algs2009, f_factor=2,\\n target_lb=1e-8, target_ub=1e22):\\n\\n # TODO: use pproc.TargetValues class as input target values\\n # default target values:\\n targets = pproc.TargetValues(\\n 10**np.arange(np.log10(max((1e-8, target_lb))),\\n np.log10(target_ub) + 1e-9, 0.2))\\n # there should be a simpler way to express this to become the\\n # interface of this function\\n\\n print 'Loading algorithm data from given algorithm list...\\\\n' \\n\\n verbose = True\\n dsList, sortedAlgs, dictAlg = pproc.processInputArgs(args, verbose=verbose)\\n\\n print 'This may take a while (depending on the number of algorithms)'\\n\\n selectedAlgsPerProblem = {}\\n for f, i in pproc.dictAlgByFun(dictAlg).iteritems():\\n for d, j in pproc.dictAlgByDim(i).iteritems():\\n selectedAlgsPerProblemDF = []\\n best = BestAlgSet(j)\\n \\n for i in range(0, len(best.target)):\\n t = best.target[i]\\n # if ((t <= target_ub) and (t >= target_lb)):\\n if toolsstats.in_approximately(t,\\n targets((f, d), discretize=True)):\\n # add best for this target:\\n selectedAlgsPerProblemDF.append(best.algs[i])\\n \\n # add second best or all algorithms that have an ERT\\n # within a factor of f_factor of the best:\\n secondbest_ERT = np.infty\\n secondbest_str = ''\\n secondbest_included = False \\n for astring in j:\\n currdictalg = dictAlg[astring].dictByDim()\\n if currdictalg.has_key(d):\\n curralgdata = currdictalg[d][f-1] \\n currERT = curralgdata.detERT([t])[0]\\n if (astring != best.algs[i]):\\n if (currERT < secondbest_ERT):\\n secondbest_ERT = currERT\\n secondbest_str = astring\\n if (currERT <= best.detERT([t])[0] * f_factor):\\n selectedAlgsPerProblemDF.append(astring)\\n secondbest_included = True\\n if not (secondbest_included) and (secondbest_str != ''):\\n selectedAlgsPerProblemDF.append(secondbest_str)\\n \\n if len(selectedAlgsPerProblemDF) > 0:\\n selectedAlgsPerProblem[(d, f)] = selectedAlgsPerProblemDF\\n \\n print 'pre-processing of function', f, 'done.' \\n \\n print 'loading of best algorithm(s) data done.'\\n \\n countsperalgorithm = {}\\n for (d, f) in selectedAlgsPerProblem:\\n print 'dimension:', d, ', function:', f\\n setofalgs = set(selectedAlgsPerProblem[d,f])\\n \\n # now count how often algorithm a is best for the extracted targets\\n for a in setofalgs:\\n # use setdefault to initialize with zero if a entry not existant:\\n countsperalgorithm.setdefault((d, a), 0) \\n countsperalgorithm[(d,a)] += selectedAlgsPerProblem[d,f].count(a)\\n \\n selectedalgsperdimension = {}\\n for (d,a) in sorted(countsperalgorithm):\\n if not selectedalgsperdimension.has_key(d):\\n selectedalgsperdimension[d] = []\\n selectedalgsperdimension[d].append((countsperalgorithm[(d,a)], a))\\n \\n for d in sorted(selectedalgsperdimension):\\n print d, 'D:'\\n for (count, alg) in sorted(selectedalgsperdimension[d], reverse=True):\\n print count, alg\\n print '\\\\n'\\n \\n \\n print \\\" done.\\\"\\n \\n return selectedalgsperdimension\",\n \"def get_clusters(ensemble, grouping, clustering):\\n\\n\\t# Prevent SQL injected since column names cannot be parameterized.\\n\\tif \\\";\\\" in ensemble or \\\";\\\" in grouping or \\\";\\\" in clustering:\\n\\t\\treturn None\\n\\n\\tensemble = ensemble.replace('EnsEns','Ens')\\n\\tdf = None;\\n\\n\\tif grouping in ['annotation','cluster']:\\n\\t\\tgroupingu = ensemble+\\\".\\\"+grouping+\\\"_\\\"+clustering\\n\\telif grouping in ['NeuN']:\\n\\t\\tgroupingu = \\\"CONCAT('NeuN',cells.\\\"+grouping+\\\")\\\"\\n\\telse:\\n\\t\\tgroupingu = \\\"cells.\\\"+grouping\\n\\n\\t# Get methylation info\\n\\tquery = \\\"SELECT count(cells.cell_id) ncells, 'snmC' as modality, \\\\\\n\\t\\t%(groupingu)s as groups \\\\\\n\\t\\tFROM cells \\\\\\n\\t\\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\\\\n\\t\\tGROUP BY groups \\\" % {'ensemble': ensemble,\\n\\t\\t\\t\\t\\t'groupingu': groupingu,\\n\\t\\t\\t\\t\\t'clustering': clustering}\\n\\ttry:\\n\\t\\tdf = pd.read_sql(query, db.get_engine(current_app, 'methylation_data'))\\n\\texcept exc.ProgrammingError as e:\\n\\t\\tnow = datetime.datetime.now()\\n\\t\\tprint(\\\"[{}] ERROR in app(get_clusters): {}\\\".format(str(now), e))\\n\\t\\tsys.stdout.flush()\\n\\t\\t# return None\\n\\n\\t# Get snATAC info\\n\\tquery = \\\"SELECT count(cells.cell_id) ncells, 'snATAC' AS modality, %(ensemble)s.cluster_ATAC groups \\\\\\n\\t\\tFROM cells \\\\\\n\\t\\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\\\\n\\t\\tGROUP BY groups \\\" % {'ensemble': ensemble,\\n\\t\\t\\t\\t\\t'grouping': grouping,\\n\\t\\t\\t\\t\\t'clustering': clustering}\\n\\n\\ttry:\\n\\t\\tdf_atac = pd.read_sql(query, db.get_engine(current_app, 'snATAC_data'))\\n\\t\\tdf=df.append(df_atac)\\n\\texcept exc.ProgrammingError as e:\\n\\t\\tnow = datetime.datetime.now()\\n\\t\\tprint(\\\"[{}] ERROR in app(get_clusters): {}\\\".format(str(now), e))\\n\\t\\tsys.stdout.flush()\\n\\n\\n\\t# Get snRNA info\\n\\tquery = \\\"SELECT count(cells.cell_id) ncells, 'RNA' AS modality, %(ensemble)s.cluster_RNA groups \\\\\\n\\t\\tFROM cells \\\\\\n\\t\\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\\\\n\\t\\tGROUP BY groups \\\" % {'ensemble': ensemble,\\n\\t\\t\\t\\t\\t'grouping': grouping,\\n\\t\\t\\t\\t\\t'clustering': clustering}\\n\\n\\ttry:\\n\\t\\tdf_rna = pd.read_sql(query, db.get_engine(current_app, 'RNA_data'))\\n\\t\\tdf=df.append(df_rna)\\n\\texcept exc.ProgrammingError as e:\\n\\t\\tnow = datetime.datetime.now()\\n\\t\\tprint(\\\"[{}] ERROR in app(get_clusters): {}\\\".format(str(now), e))\\n\\t\\tsys.stdout.flush()\\n\\n\\treturn df\",\n \"def clustering_and_visulization(self):\\n centroids, _ = kmeans(self.data_mat, self.k)\\n idx, _ = vq(self.data_mat, centroids)\\n for i in range(self.k):\\n\\n self.plot_list.append(self.data_mat[idx == i, 0])\\n self.plot_list1.append(self.data_mat[idx == i, 1])\\n\\n for j in range(self.k):\\n plot(self.plot_list[j], self.plot_list1[j], self.color_code[j])\\n plot(centroids[:, 0], centroids[:, 1], 'sg', markersize=8)\\n show()\\n for i in range(self.k):\\n self.cluster = self.data_mat[idx == i]\\n self.clusterlist.append(self.cluster)\\n\\n for i in range(len(self.clusterlist)):\\n self.clusterdict[i] = self.clusterlist[i]\\n print(self.clusterdict)\\n\\n\\n self.indexdict = {}\\n for i in self.clusterdict:\\n self.indexdict[i] = []\\n print(len(self.clusterdict))\\n for i in range(len(idx)):\\n for j in range(len(self.clusterdict)):\\n if (self.clusterdict[j][:] == self.data_mat[i]).any():\\n self.indexdict[j].append(i)\\n print(\\\"cluster dict of packs\\\",self.indexdict)\\n\\n self.drugdict = {}\\n for i in self.clusterdict:\\n self.drugdict[i] = []\\n self.drug=[]\\n for i in range(len(self.indexdict.keys())):\\n for j in range(len(self.indexdict[i])):\\n self.drugdict[i].append(self.df.iloc[self.indexdict[i][j]].to_dict())\\n print(\\\"drugs dict with their frequencies\\\",self.drugdict)\\n clusterdict_from_df_as_drug_non_O_frequency = {}\\n clusterdict_from_as_drugs_only_as_list = {}\\n clusterdict_of_non_repeated_drugs ={}\\n for i in self.drugdict:\\n clusterdict_from_df_as_drug_non_O_frequency[i] = []\\n for i in self.drugdict:\\n for j in self.drugdict[i]:\\n clusterdict_from_df_as_drug_non_O_frequency[i].append({x: y for x, y in j.items() if y != 0})\\n print(\\\"clusterdict_from_df_as_drug_non_O_frequency\\\", clusterdict_from_df_as_drug_non_O_frequency)\\n print('\\\\n')\\n\\n for i in self.drugdict:\\n clusterdict_from_as_drugs_only_as_list[i] = []\\n\\n for i in self.drugdict:\\n for j in clusterdict_from_df_as_drug_non_O_frequency[i]:\\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\\n\\n print(\\\"only keys drugs with drugs name\\\", clusterdict_from_as_drugs_only_as_list)\\n print('\\\\n')\\n\\n\\n for i in self.drugdict:\\n clusterdict_of_non_repeated_drugs[i]=list(more_itertools.collapse([list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\\n\\n\\n print(\\\"only drugs only\\\", clusterdict_of_non_repeated_drugs)\\n\\n########################################################################################################################\\n try:\\n common_drug_list = [x for x in clusterdict_of_non_repeated_drugs[0] if x in clusterdict_of_non_repeated_drugs[1]]\\n print('\\\\n')\\n print(\\\"common drug list\\\", common_drug_list)\\n total_frequency_of_drugs_dict = {}\\n for i in self.drugdict:\\n total_frequency_of_drugs_dict[i] = []\\n\\n for drug in common_drug_list:\\n\\n for cluster_keys in clusterdict_from_df_as_drug_non_O_frequency.keys():\\n temp_list = []\\n for cluster_values_as_list in clusterdict_from_df_as_drug_non_O_frequency[cluster_keys]:\\n try:\\n temp_list.append(cluster_values_as_list[str(drug)])\\n except KeyError:\\n print(\\\"\\\\t\\\")\\n total_frequency_of_drugs_dict[cluster_keys].append(np.sum(temp_list))\\n print(\\\"total drugs frequency\\\",total_frequency_of_drugs_dict)\\n total_frequency_of_drugs_dict_with_drugs = {}\\n for i in self.drugdict:\\n total_frequency_of_drugs_dict_with_drugs[i] = []\\n temp_list1 = []\\n temp_list2 = []\\n for keys in self.drugdict.keys():\\n temp_list1.append(clusterdict_of_non_repeated_drugs[keys])\\n for keys in self.drugdict.keys():\\n temp_list2.append(total_frequency_of_drugs_dict[keys])\\n temp_list3 = []\\n for i in temp_list1:\\n for j in temp_list2:\\n temp_list3.append(dict(zip(i,j)))\\n temp_list4 = temp_list3[:2]\\n print('\\\\n')\\n for keys in self.drugdict:\\n total_frequency_of_drugs_dict_with_drugs[keys].append(temp_list4[keys])\\n print(\\\"total frequency with drugs dict\\\",total_frequency_of_drugs_dict_with_drugs)\\n\\n final_drugs_in_clusters_dict = {}\\n for i in self.drugdict:\\n final_drugs_in_clusters_dict[i] = []\\n compare_list = []\\n for drug in common_drug_list:\\n compare_list.append(min(total_frequency_of_drugs_dict_with_drugs[0][0][drug], total_frequency_of_drugs_dict_with_drugs[1][0][drug]))\\n print(\\\"compare list\\\",compare_list)\\n for values in total_frequency_of_drugs_dict_with_drugs.values():\\n for key1, value1 in values[0].items():\\n if value1 in compare_list:\\n\\n key2 =values[0].keys()[values[0].values().index(value1)]\\n values[0].pop(key2, None)\\n\\n\\n print('final dict with deleted keys', total_frequency_of_drugs_dict_with_drugs)\\n\\n clusterdict_from_as_drugs_only_as_list = {}\\n clusterdict_of_non_repeated_drugs = {}\\n\\n for i in self.drugdict:\\n clusterdict_from_as_drugs_only_as_list[i] = []\\n\\n for i in self.drugdict:\\n for j in total_frequency_of_drugs_dict_with_drugs[i]:\\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\\n print(\\\"only keys drugs with drugs name\\\", clusterdict_from_as_drugs_only_as_list)\\n print('\\\\n')\\n\\n for i in self.drugdict:\\n clusterdict_of_non_repeated_drugs[i] = list(more_itertools.collapse([list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\\n print(\\\"only drugs\\\",clusterdict_of_non_repeated_drugs)\\n\\n final_robot_packs_dict = {}\\n for i in self.drugdict:\\n final_robot_packs_dict[i] = []\\n\\n winner_drug_dict = {}\\n for i in common_drug_list:\\n winner_drug_dict[i] = []\\n for drug in common_drug_list:\\n if drug in clusterdict_of_non_repeated_drugs[0]:\\n winner_drug_dict[str(drug)].append(0)\\n if drug in clusterdict_of_non_repeated_drugs[1]:\\n winner_drug_dict[str(drug)].append(1)\\n print(\\\"winner drug dict\\\",winner_drug_dict)\\n\\n for i in self.indexdict:\\n print(i)\\n for pack in self.indexdict[i]:\\n packdict = self.df.iloc[pack].to_dict()\\n packdict_non_0 = {x: y for x, y in packdict.items() if y != 0}\\n packdict_non_0_key = packdict_non_0.keys()\\n for drug in packdict_non_0_key:\\n if drug in clusterdict_of_non_repeated_drugs[0]:\\n final_robot_packs_dict[0].append(pack)\\n elif drug in clusterdict_of_non_repeated_drugs[1]:\\n final_robot_packs_dict[1].append(pack)\\n\\n final_robot_packs_dict[i].append(pack)\\n for commondrugs in winner_drug_dict:\\n for winnercluster in winner_drug_dict[commondrugs]:\\n if winnercluster==0:\\n loosercluster =1\\n if winnercluster == 1:\\n loosercluster = 0\\n if commondrugs in packdict_non_0_key and i==loosercluster:\\n try:\\n final_robot_packs_dict[i].remove(pack)\\n final_robot_packs_dict[winnercluster].append(pack)\\n except ValueError:\\n print('\\\\t')\\n\\n for i in self.indexdict:\\n final_robot_packs_dict[i] = set(final_robot_packs_dict[i])\\n\\n print(\\\"final which pack which robot dict\\\",final_robot_packs_dict)\\n\\n except IndexError:\\n print(\\\"No common drugs\\\")\",\n \"def clustering_metrics(clusts, node_assn, node_pred):\\n pred_vox = cluster_to_voxel_label(clusts, node_pred)\\n true_vox = cluster_to_voxel_label(clusts, node_assn)\\n ari = ARI(pred_vox, true_vox)\\n ami = AMI(pred_vox, true_vox)\\n sbd = SBD(pred_vox, true_vox)\\n pur, eff = purity_efficiency(pred_vox, true_vox)\\n return ari, ami, sbd, pur, eff\",\n \"def get_combinations(classes_folder='./data/CASIA1_classes_by_unbalanced_kmeans/', \\n originals='./data/CASIA1_originals', fakes_ela='./data/CASIA1_fakes_ela'):\\n classes_ = []\\n for i in range(20):\\n classes_.append('{}{}' .format(classes_folder, i+1))\\n\\n medians_ = [0,3,5,7,9,11,13,15,17,19]\\n\\n iterations_ = []\\n for i in range(21):\\n iterations_.append(i)\\n\\n threshold_ = []\\n for i in range(40):\\n threshold_.append(i)\\n\\n for i, item in enumerate(classes_):\\n fakes_list = os.listdir(item)\\n fakes = load_fakes(fakes_list, item, originals)\\n\\n best = 0\\n best_median_filter_size = 0\\n best_number_of_iterations = 0\\n best_thresh = 0\\n for x, median_filter_size in enumerate(medians_):\\n for y, number_of_iterations in enumerate(iterations_):\\n for t, thresh in enumerate(threshold_):\\n whole_score = 0\\n for e, elem in enumerate(fakes):\\n image = cv2.imread(os.path.join(fakes_ela, elem.path.split('\\\\\\\\')[-1]))\\n\\n if thresh > 0:\\n image_ = pywt.threshold(image, thresh, 'soft')\\n image = cv2.normalize(image_, image, 0, 1, cv2.NORM_MINMAX)\\n image = 255 * image\\n image = image.astype(np.uint8)\\n\\n image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)\\n \\n image = cv2.inRange(image, np.array([0,0,0]), np.array([180,255,60]))\\n image = cv2.bitwise_not(image)\\n\\n if median_filter_size > 0:\\n image = cv2.medianBlur(image, median_filter_size)\\n\\n kernel = np.ones((3, 3), np.uint8)\\n image = cv2.morphologyEx(image, cv2.MORPH_GRADIENT, kernel, iterations=number_of_iterations)\\n\\n cnts = cv2.findContours(image.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\\n cnts = imutils.grab_contours(cnts)\\n\\n max_idx = 0\\n max_pnts = 0\\n for u, ulem in enumerate(cnts):\\n if cv2.contourArea(ulem) < max_pnts:\\n continue\\n else:\\n max_idx = u\\n max_pnts = cv2.contourArea(ulem)\\n\\n if len(cnts) > 0:\\n (x, y, w, h) = cv2.boundingRect(cnts[max_idx])\\n pred = {\\n \\\"x\\\": x,\\n \\\"y\\\": y,\\n \\\"w\\\": w,\\n \\\"h\\\": h\\n }\\n else:\\n pred = None\\n\\n whole_score += evaluate_augmentation_fit(pred, elem)\\n if best < whole_score:\\n best = whole_score\\n best_median_filter_size = median_filter_size\\n best_number_of_iterations = number_of_iterations\\n best_thresh = thresh\\n print(\\\"Class: {}; MedianFilterSize: {}; Iterations: {}; Thresh: {}; Score: {}\\\" .format(item, median_filter_size, number_of_iterations, thresh, round(whole_score, 2)))\\n print(\\\"###########\\\")\\n print(\\\"Best: {} -> {} % ({}, {}, {})\\\" .format(round(best, 2), round((best/len(fakes)), 2), best_median_filter_size, best_number_of_iterations, best_thresh))\\n print(\\\"###########\\\")\",\n \"def calculate_clusters(study_id):\\n\\n with current_app.app_context():\\n cur = conn.cursor()\\n\\n cur.execute(\\\"\\\"\\\"SELECT * FROM STATS WHERE STUDY_ID=%s\\\"\\\"\\\", (str(study_id),))\\n study = fetchoneClean(cur)\\n clusters_calculating = study[4]\\n clusters_changed = study[5]\\n if clusters_changed:\\n if clusters_calculating:\\n return {'message': 'calculating'}\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CALCULATING = TRUE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n conn.commit()\\n\\n distance = study[7]['matrix']\\n card_names = study[7]['cardNames']\\n cur.execute(\\\"\\\"\\\"SELECT COUNT(ID) FROM PARTICIPANT WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n total_participants = fetchoneClean(cur)[0]\\n\\n distance_matrix = calculate_square_form(distance, total_participants)\\n distArray = ssd.squareform(distance_matrix)\\n\\n try:\\n clusters = hierarchy.linkage(distArray, method='average')\\n except ValueError:\\n return {'message': 'not enough data'}\\n\\n tree = hierarchy.to_tree(clusters, rd=False)\\n # TODO Distance 0 on root\\n dendro = dict(children=[], hierarchy=0, distance=100)\\n add_node(tree, dendro, card_names)\\n\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS = %s WHERE STUDY_ID = %s\\\"\\\"\\\", (json.dumps(dendro), str(study_id),))\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CALCULATING = FALSE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CHANGED = FALSE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n conn.commit()\\n else:\\n dendro = study[6]\\n\\n return dendro\",\n \"def apply_algorithms(x: np.ndarray, label_true, params, components, database_name):\\n names = ['Original dataset', 'Our PCA results', 'KMeans with previous our PCA reduction',\\n 'KMeans without previous reduction (PCA)', 'KMeans without previous reduction (T-SNE)']\\n\\n datasets = []\\n labels = []\\n reduct = []\\n\\n # get the representation of the original matrix splitted to be plotted\\n partial_x = split_db_original(x, components)\\n datasets.append(partial_x)\\n labels.append(label_true)\\n reduct.append(None)\\n\\n # get our PCA\\n pca = OPCA(n_components=params['n_components'])\\n our_pca = pca.fit_transform(x)\\n datasets.append(our_pca)\\n labels.append(label_true)\\n reduct.append(None)\\n\\n # get PCA and IPCA from sklearn\\n sk_pca = pca_sklearn(x, params['db_name'], params['n_components'])\\n sk_ipca = ipca_sklearn(x, params['db_name'], params['n_components'])\\n\\n # compare the three PCA algorithms\\n name = ['Our PCA', 'SK_PCA', 'SK_IPCA', 'original_data']\\n pca_data = [our_pca, sk_pca['db'], sk_ipca['db'], x]\\n apply_evaluation(pca_data, label_true, params, name, database_name)\\n\\n # KMeans with PCA reduction\\n algorithm = KMeans(k=params['k'], seed=params['seed'], max_it=params['max_it'], tol=params['tol'])\\n labels_kmeans = algorithm.fit_predict(our_pca)\\n datasets.append(our_pca)\\n labels.append(labels_kmeans)\\n reduct.append(None)\\n\\n # KMeans without PCA reduction\\n algorithm = KMeans(k=params['k'], seed=params['seed'], max_it=params['max_it'], tol=params['tol'])\\n labels_kmeans = algorithm.fit_predict(x)\\n datasets.append(x)\\n labels.append(labels_kmeans)\\n reduct.append('pca')\\n datasets.append(x)\\n labels.append(labels_kmeans)\\n reduct.append('tsne')\\n\\n # selection number of dimensions of plot\\n if type(params['n_components']) == int:\\n if params['n_components'] == 2:\\n nd = 2\\n if params['n_components'] > 2:\\n nd = 3\\n elif type(params['n_components']) == float:\\n if our_pca.shape[1] == 2:\\n nd = 2\\n if our_pca.shape[1] > 2:\\n nd = 3\\n else:\\n nd = 3\\n\\n if nd == 2:\\n pca_names = ['PCA Component 1', 'PCA Component 2']\\n plot_names = [components[0], pca_names, pca_names, pca_names, ['TSNE 1', 'T-SNE 2']]\\n plot2d(datasets, labels, names, plot_names, reduct)\\n elif nd == 3:\\n pca_names = ['PCA Component 1', 'PCA Component 2', 'PCA Component 3']\\n plot_names = [components[0], pca_names, pca_names, pca_names, ['TSNE 1', 'T-SNE 2', 'T-SNE 3']]\\n plot3d(datasets, labels, names, plot_names, reduct)\",\n \"def evaluate(self):\\n results = dict()\\n for metric in self.metrics:\\n print('Evaluating clustering with metric %s' % metric)\\n if metric in LABEL_METRICS.keys():\\n results[metric] = LABEL_METRICS[metric](self.X, self.model.labels_)\\n results['adjusted_rand_score'] = SCORE_METRICS['adjusted_rand_score'](self.Y[:, 0], self.model.labels_)\\n self.results = results\\n return results\",\n \"def __tool_classification__(self,task_id,shape,aggregations):\\n\\n print \\\"tool classification - more than one tool could create \\\" +str(shape) + \\\"s in task \\\" + str(task_id)\\n\\n if aggregations == {}:\\n print \\\"warning - empty classifications\\\"\\n return {}\\n\\n # only go through the \\\"uncertain\\\" shapes\\n tool_classifications = {}\\n\\n for subject_id in aggregations:\\n # look at the individual points in the cluster\\n\\n for cluster_index,cluster in aggregations[subject_id][task_id][shape+ \\\" clusters\\\"].items():\\n # all_users just gives us a list of all of the users who have seen this subject\\n # not relevant here\\n if cluster_index == \\\"all_users\\\":\\n continue\\n\\n # which users marked this cluster\\n users = cluster[\\\"users\\\"]\\n # which tool each individual user used\\n tools = cluster[\\\"tools\\\"]\\n assert len(tools) == len(users)\\n\\n # in this case, we want to \\\"vote\\\" on the tools\\n ballots = zip(users,tools)\\n\\n tool_classifications[(subject_id,cluster_index)] = ballots\\n\\n # classify\\n print \\\"tool results classification\\\"\\n tool_results = self.__task_aggregation__(tool_classifications,task_id,{})\\n assert isinstance(tool_results,dict)\\n\\n for subject_id,cluster_index in tool_results:\\n\\n new_results = tool_results[(subject_id,cluster_index)][task_id]\\n # the clustering results already exist so we are just adding more data to it\\n aggregations[subject_id][task_id][shape + \\\" clusters\\\"][cluster_index][\\\"tool_classification\\\"] = new_results\\n\\n return aggregations\",\n \"def algorithm_parameters(alg):\\n if alg in list(SEM_TYPE.keys()):\\n return simulate_parameters(alg)\\n\\n param_dict = dict()\\n\\n param = getfullargspec(INLINE_ALGORITHMS[alg.upper()].__init__)\\n if param is not None:\\n param_len = len(param.args)\\n if param.defaults:\\n if 'input_dim' in param.args:\\n param_dict.update({'input_dim': None})\\n for index, value in enumerate(reversed(param.defaults)):\\n if not isfunction(value) and (value is not None):\\n param_dict.update(\\n {param.args[param_len - index - 1]: value})\\n param = getfullargspec(INLINE_ALGORITHMS[alg.upper()].learn)\\n if param is not None:\\n param_len = len(param.args)\\n if param_len > 2:\\n if 'rank' in param.args:\\n param_dict.update({'rank': None})\\n return param_dict\",\n \"def clustering_and_visulization(self):\\n try:\\n centroids, _ = kmeans(self.data_mat, self.k)\\n except ValueError:\\n print(\\\"The number of clusters is more than the data points\\\")\\n self.idx, _ = vq(self.data_mat, centroids)\\n for i in range(self.k):\\n\\n self.plot_list.append(self.data_mat[self.idx == i, 0])\\n self.plot_list1.append(self.data_mat[self.idx == i, 1])\\n\\n for j in range(self.k):\\n plot(self.plot_list[j], self.plot_list1[j], self.color_code[j])\\n plot(centroids[:, 0], centroids[:, 1], 'sg', markersize=8)\\n show()\\n\\n for i in range(self.k):\\n self.cluster = self.data_mat[self.idx == i]\\n self.clusterlist.append(self.cluster)\\n print(self.clusterlist)\\n for i in range(len(self.clusterlist)):\\n self.clusterdict[i] = self.clusterlist[i]\\n print(self.clusterdict)\\n\\n index_dict ={}\\n for i in self.clusterdict:\\n index_dict[i] = []\\n for i in range(len(self.data_mat)):\\n for j in range(len(self.clusterdict)):\\n if (self.clusterdict[j][:] == self.data_mat[i]).any():\\n index_dict[j].append(i)\\n print(\\\"drugs cluster dict\\\", index_dict)\\n\\n self.drugsdict = {}\\n for i in index_dict:\\n self.drugsdict[i] = []\\n drugslist = list(self.df.columns.values)\\n print(\\\"drugs list from dataframe\\\", drugslist)\\n\\n for i in index_dict:\\n self.drugsdict[i] = [drugslist[index] for index in index_dict[i]]\\n\\n print(\\\"drugs cluster dict\\\", self.drugsdict)\\n########################################################################################################################\\n clusterdict_from_df_as_drug_frequency = {}\\n clusterdict_from_df_as_drug_non_O_frequency = {}\\n\\n print('\\\\n')\\n\\n for i in range(len(self.df)):\\n clusterdict_from_df_as_drug_frequency[i] = []\\n\\n for i in range(len(self.df)):\\n clusterdict_from_df_as_drug_frequency[i].append(self.df.iloc[i].to_dict()) #\\n print(\\\"packs in dict form of drugs frequency\\\", clusterdict_from_df_as_drug_frequency)\\n\\n for i in range(len(self.df)):\\n clusterdict_from_df_as_drug_non_O_frequency[i] = []\\n\\n for i in range(len(self.df)):\\n for j in clusterdict_from_df_as_drug_frequency[i]:\\n clusterdict_from_df_as_drug_non_O_frequency[i].append({x: y for x, y in j.items() if y != 0})\\n print(\\\"clusterdict_from_df_as_drug_non_O_frequency\\\", clusterdict_from_df_as_drug_non_O_frequency)\\n print('\\\\n')\\n clusterdict_from_as_drugs_only_as_list = {}\\n clusterdict_of_non_repeated_drugs = {}\\n for i in range(len(self.df)):\\n clusterdict_from_as_drugs_only_as_list[i] = []\\n\\n for i in range(len(self.df)):\\n for j in clusterdict_from_df_as_drug_non_O_frequency[i]:\\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\\n\\n print(\\\"only keys drugs with drugs name\\\", clusterdict_from_as_drugs_only_as_list)\\n print('\\\\n')\\n\\n for i in range(len(self.df)):\\n clusterdict_of_non_repeated_drugs[i] = list(more_itertools.collapse(\\n [list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\\n\\n print(\\\"only drugs only\\\", clusterdict_of_non_repeated_drugs)\\n\\n########################################################################################################################\\n robot_for_packs_dict = {}\\n for i in range(len(self.df)):\\n robot_for_packs_dict[i] = []\\n\\n # for i in range(len(self.df)):\\n for i in range(len(self.df)):\\n for j in clusterdict_of_non_repeated_drugs[i]:\\n if j in self.drugsdict[0]:\\n robot_for_packs_dict[i].append(0)\\n elif j in self.drugsdict[1]:\\n robot_for_packs_dict[i].append(1)\\n for i in range(len(self.df)):\\n robot_for_packs_dict[i] = set(robot_for_packs_dict[i])\\n\\n for i in range(len(self.df)):\\n robot_for_packs_dict[i] = list(more_itertools.collapse(robot_for_packs_dict[i]))\\n print('\\\\n')\\n print(\\\"clusterdict_of_non_repeated_drugs\\\", robot_for_packs_dict)\",\n \"def compute_cluster_similarities(emb_clusters1, emb_clusters2, compare, order, clmethod, plot):\\n def compute_sim(e, e1, cls, cls1):\\n sims = np.empty((20, 20))\\n xticks, yticks = [], []\\n for i, c in enumerate(cls):\\n yticks.append(', '.join(c[1]) + (f' {round(c[3], 5)}' if order == 'avgfreq' else ''))\\n for j, c1 in enumerate(cls1):\\n if len(xticks) < 20:\\n xticks.append(', '.join(c1[1]) + (f' {round(c1[3], 5)}' if order == 'avgfreq' else ''))\\n sims[i, j] = jaccard_similarity_score(c[2], c1[2])\\n jaccard_similarities[f'{e}-{e1}'] = sims\\n\\n if plot:\\n if order == 'clustermap':\\n similarity_clustermap(sims, xticks, yticks, f'{e}-{e1}_{clmethod}')\\n elif order == 'default' or order == 'avgfreq':\\n similarity_heatmap(sims, xticks, yticks, f'{e}-{e1}_{clmethod}', order)\\n else:\\n pass\\n\\n jaccard_similarities = {}\\n if compare == 'cross':\\n for ie, (e, cls) in enumerate(emb_clusters1.items()):\\n for ie1, (e1, cls1) in enumerate(emb_clusters2.items()):\\n if ie < ie1:\\n compute_sim(e, e1, cls, cls1)\\n elif compare == 'dot':\\n for (e, cls), (e1, cls1) in zip(emb_clusters1.items(), emb_clusters2.items()):\\n compute_sim(e, e1, cls, cls1)\\n\\n return jaccard_similarities\",\n \"def integrated_clustering(t_all,y_all,num_of_days=500,period = 1440,trim=10,min_n_clusters = 4, max_n_clusters=10,hierarchical=0):\\n\\n\\n\\n all_seg_april = initial_disaggregate(t_all,y_all,num_of_days,period = period)\\n \\n ''' '''\\n all_seg_april_normalized = [np.array(x[0])-np.mean(x[1]) for x in all_seg_april if len(x[1])==3]\\n \\n ''' filter the empty segments'''\\n all_seg_april_normalized = [x for x in all_seg_april_normalized if len(x)>0]\\n \\n ''' clustering in different ranges will probably have a better result'''\\n if hierarchical == 0:\\n pass\\n elif hierarchical ==1:\\n all_seg_april_normalized = [x for x in all_seg_april_normalized if x.mean()>1000]\\n else:\\n all_seg_april_normalized = [x for x in all_seg_april_normalized if x.mean()<1000]\\n \\n ''' filter out the positive segments'''\\n all_positive_seg_april_normalized = [x for x in all_seg_april_normalized if x.min()>0]\\n \\n \\n all_seg_april_normalized_trim50 = extract_first_n(all_positive_seg_april_normalized, trim)\\n cluster_average = []\\n \\n # find optimal clustering number using silhouette score\\n \\n optimal_dict = {}\\n \\n for n_clusters in range(min_n_clusters,max_n_clusters):\\n \\n y_pred = KMeans(n_clusters=n_clusters).fit_predict(all_seg_april_normalized_trim50)\\n\\n cluster_average = []\\n for i_cluster in range(n_clusters):\\n cluster_average.append(\\n np.mean([np.mean(x) for i, x in enumerate(all_seg_april_normalized_trim50) if y_pred[i]==i_cluster])\\n ) \\n\\n # sihouette score\\n cluster_labels = y_pred\\n sample_silhouette_values = silhouette_samples(all_seg_april_normalized_trim50, cluster_labels)\\n \\n silhouette_avg = silhouette_score(pd.DataFrame(all_seg_april_normalized_trim50), cluster_labels)\\n\\n optimal_dict[n_clusters] = silhouette_avg +(sample_silhouette_values.min()+sample_silhouette_values.max())/2\\n \\n # n_clusters will give us the optimal number of clusters\\n n_clusters = max(optimal_dict.iteritems(), key=operator.itemgetter(1))[0]\\n\\n #print n_clusters\\n \\n y_pred = KMeans(n_clusters=n_clusters).fit_predict(all_seg_april_normalized_trim50)\\n\\n cluster_average = []\\n \\n for i_cluster in range(n_clusters):\\n cluster_average.append(\\n np.mean([np.mean(x) for i, x in enumerate(all_seg_april_normalized_trim50) if y_pred[i]==i_cluster])\\n ) \\n cluster_average_rank = np.argsort(cluster_average)[::-1]\\n rank_map = {cluster_average_rank[i_cluster]:i_cluster for i_cluster in range(n_clusters)} # old index:new index\\n\\n y_pred_old = y_pred\\n y_pred = [rank_map[x] for x in y_pred]\\n all_seg_per_cluster = [[] for i in range(n_clusters) ]\\n for i_seg in range(len(all_seg_april_normalized_trim50)):\\n all_seg_per_cluster[y_pred[i_seg]].append(all_seg_april_normalized_trim50[i_seg])\\n \\n cluster_mean = [[] for i in range(n_clusters) ]\\n cluster_std = [[] for i in range(n_clusters) ]\\n for i_cluster in range(n_clusters):\\n cluster_mean[ i_cluster ] = np.mean(np.array(all_seg_per_cluster[i_cluster]), axis=0)\\n cluster_std[ i_cluster ] = np.std(np.array(all_seg_per_cluster[i_cluster]), axis=0)\\n \\n \\n \\n \\n #cluster_mean_2 = cluster_mean[5:6]\\n \\n return cluster_mean,cluster_std,n_clusters,all_seg_per_cluster\",\n \"def __existence_classification__(self,task_id,shape,aggregations):\\n\\n # aggregations = {}\\n\\n # raw_classifications and clustering_results have different hierarchy orderings- raw_classifications\\n # is better for processing data and clustering_results is better for showing the end result\\n # technically we only need to look at the data from clustering_results right now but its\\n # hierarchy is really inefficient so use raw_classifications to help\\n\\n # each shape is done independently\\n\\n # set - so if multiple tools create the same shape - we only do that shape once\\n # for shape in set(marking_tasks[task_id]):\\n\\n\\n # pretentious name but basically whether each person who has seen a subject thinks it is a true\\n # positive or not\\n existence_classification = {\\\"param\\\":\\\"subject_id\\\"}\\n\\n global_cluster_index = 0\\n # clusters_per_subject = []\\n\\n # look at the individual points in the cluster\\n for subject_id in aggregations.keys():\\n if subject_id == \\\"param\\\":\\n continue\\n\\n # gold standard pts may not match up perfectly with the given clusters -\\n # for example, we could have a gold penguin at 10,10 but the users' cluster\\n # is centered at 10.1,9.8 - same penguin though\\n # so as we go through the clusters, we need to see which ones match up more closely\\n # with the gold standard\\n # if subject_id in gold_standard_clustering[0]:\\n # # closest cluster and distance\\n # gold_to_cluster = {pt:(None,float(\\\"inf\\\")) for pt in gold_standard_clustering[0][subject_id]}\\n # else:\\n # gold_to_cluster = None\\n\\n\\n # clusters_per_subject.append([])\\n\\n # # in either case probably an empty image\\n # if subject_id not in clustering_results:\\n # continue\\n # if task_id not in clustering_results[subject_id]:\\n # continue\\n\\n if (shape+ \\\" clusters\\\") not in aggregations[subject_id][task_id]:\\n # if none of the relevant markings were made on this subject, skip it\\n continue\\n\\n all_users = aggregations[subject_id][task_id][shape+ \\\" clusters\\\"][\\\"all_users\\\"]\\n\\n for local_cluster_index in aggregations[subject_id][task_id][shape+ \\\" clusters\\\"]:\\n if local_cluster_index == \\\"all_users\\\":\\n continue\\n\\n # extract the users who marked this cluster\\n cluster = aggregations[subject_id][task_id][shape+ \\\" clusters\\\"][local_cluster_index]\\n\\n # todo - put this back when we support gold standard clustering\\n # # is this user cluster close to any gold standard pt?\\n # if subject_id in gold_standard_clustering[0]:\\n # x,y = cluster[\\\"center\\\"]\\n # for (gold_x,gold_y) in gold_to_cluster:\\n # dist = math.sqrt((x-gold_x)**2+(y-gold_y)**2)\\n # if dist < gold_to_cluster[(gold_x,gold_y)][1]:\\n # gold_to_cluster[(gold_x,gold_y)] = local_cluster_index,dist\\n #\\n # # now repeat for negative gold standards\\n # if subject_id in gold_standard_clustering[1]:\\n # x,y = cluster[\\\"center\\\"]\\n # min_dist = float(\\\"inf\\\")\\n # closest= None\\n # for x2,y2 in gold_standard_clustering[1][subject_id]:\\n # dist = math.sqrt((x-x2)**2+(y-y2)**2)\\n # if dist < min_dist:\\n # min_dist = min(dist,min_dist)\\n # closest = (x2,y2)\\n # if min_dist == 0.:\\n # assert (x,y) == closest\\n # mapped_gold_standard[(subject_id,local_cluster_index)] = 0\\n\\n users = cluster[\\\"users\\\"]\\n\\n ballots = []\\n\\n # todo - the 15 hard coded value - might want to change that at some point\\n for u in all_users:\\n if u in users:\\n ballots.append((u,1))\\n else:\\n ballots.append((u,0))\\n\\n existence_classification[(subject_id,local_cluster_index)] = ballots\\n # clusters_per_subject[-1].append(global_cluster_index)\\n # global_cluster_index += 1\\n\\n # # note we don't care about why a cluster corresponds to a gold standard pt - that is\\n # # it could be really close to given gold standards - the point is that it is close\\n # # to at least one of them\\n # if gold_to_cluster is not None:\\n # for (local_cluster_index,dist) in gold_to_cluster.values():\\n # # arbitrary threshold but seems reasonable\\n # if dist < 1:\\n # mapped_gold_standard[(subject_id,local_cluster_index)] = 1\\n\\n existence_results = self.__task_aggregation__(existence_classification,task_id,{})#,mapped_gold_standard)\\n assert isinstance(existence_results,dict)\\n\\n for subject_id,cluster_index in existence_results:\\n new_results = existence_results[(subject_id,cluster_index)][task_id]\\n # new_agg = {subject_id: {task_id: {shape + \\\" clusters\\\": {cluster_index: {\\\"existence\\\": new_results}}}}}\\n # aggregations = self.__merge_results__(aggregations,new_agg)\\n aggregations[subject_id][task_id][shape + \\\" clusters\\\"][cluster_index][\\\"existence\\\"] = new_results\\n # if subject_id not in aggregations:\\n # aggregations[subject_id] = {}\\n # if task_id not in aggregations[subject_id]:\\n # aggregations[subject_id][task_id] = {}\\n # if (shape + \\\" clusters\\\") not in aggregations[subject_id][task_id]:\\n # aggregations[subject_id][task_id][shape+ \\\" clusters\\\"] = {}\\n # # this part is probably redundant\\n # if cluster_index not in aggregations[subject_id][task_id][shape+ \\\" clusters\\\"]:\\n # aggregations[subject_id][task_id][shape+ \\\" clusters\\\"][cluster_index] = {}\\n #\\n # aggregations[subject_id][task_id][shape+ \\\" clusters\\\"][cluster_index][\\\"existence\\\"] = existence_results[(subject_id,cluster_index)]\\n\\n return aggregations\",\n \"def clustering(self): \\n clusterOfFiles=self.getClusters()\\n \\n #group files based on the hash of their contents\\n self.keyingMethod=md5Hash\\n [self.addFile(afile) for acluster in clusterOfFiles for afile in acluster]\\n clusterOfFiles=self.getClusters()\\n self.showClusters(clusterOfFiles)\",\n \"def test(dist_param, picker_param, iters):\\n orig = '/home/zby/MAGISTERKA/MGR/results/oryginal.clustered.t'\\n cl_orig = read_clustered(orig)\\n name_tag = ''\\n ndist = dist_param[1:]\\n npick = picker_param[1:]\\n for index in drange(4, 20, 0.5):\\n name_tag = \\\"{}_{}_{}\\\".format(index, npick, ndist)\\n tf_conf = configs.TfidfConfig(\\n root_name('all_merged.txt', None),\\n tfidf_name('merged.stem{}.stop', name_tag),\\n tfidf_name('merged.stem{}.stop.txt', name_tag),\\n None,\\n tfidf_name('merged.stem{}.tfidf', name_tag),\\n 10,\\n 0,\\n None)\\n execute(tf_conf)\\n tf_conf = configs.TfidfConfig(\\n root_name('all_merged.txt', None),\\n None,\\n tfidf_name('merged.stem{}.stop.txt', name_tag),\\n tfidf_name('merged.stem{}.stop', name_tag),\\n tfidf_name('merged.stem{}.stop.tfidf', name_tag),\\n None,\\n None,\\n None)\\n execute(tf_conf)\\n #input, out, picker, distance, iterations,\\n clust_cfg = configs.ClusteringConfig(\\n tfidf_name('merged.stem{}.stop.tfidf', name_tag),\\n tfidf_name('merged.stem{}.stop.clustered.t', name_tag),\\n picker_param,\\n dist_param,\\n iters,\\n None\\n )\\n execute(clust_cfg)\\n clust2 = read_clustered(tfidf_name('merged.stem{}.stop.clustered.t', name_tag))\\n var, norm = variation_of_information(cl_orig, clust2)\\n print(\\\"**** FOR var {} VOI is {}\\\".format(name_tag, norm))\",\n \"def get_feature(glcm, featurelist=['contrast']):\\n measure_list = dict(max_prob=0, contrast=0, dissimilarity=0, homogeneity=0, ASM=0, energy=0, entropy=0,\\n correlation=0, cluster_shade=0, variance_i=0, variance_j=0, mean_i=0, mean_j=0)\\n\\n M, N = glcm.shape\\n\\n np.seterr(divide='ignore', invalid='ignore')\\n\\n flat_glcm = glcm.flatten()\\n index_i = np.arange(0, M) # row index\\n index_j = np.arange(0, N) # column index = row\\n\\n sum_v = np.sum(glcm, axis=0) # sum column[] , vertical\\n sum_h = np.sum(glcm, axis=1) # sum row[] , horizontal\\n\\n max_prob = np.max(flat_glcm)\\n mean_i = np.dot(index_i, sum_h.flatten())\\n mean_j = np.dot(index_j, sum_v.flatten())\\n var_i = np.dot((index_i - mean_i) ** 2, sum_h.flatten())\\n var_j = np.dot((index_j - mean_j) ** 2, sum_v.flatten())\\n\\n measure_list['max_prob'] = max_prob\\n measure_list['variance_i'] = var_i\\n measure_list['variance_j'] = var_j\\n measure_list['mean_i'] = mean_i\\n measure_list['mean_j'] = mean_j\\n\\n for name in featurelist:\\n if name in measure_list.keys():\\n if name is 'max_prob':\\n measure_list[name] = np.max(flat_glcm)\\n elif name is 'ASM':\\n measure_list[name] = np.dot(flat_glcm, flat_glcm)\\n elif name is 'energy':\\n ASM = np.dot(flat_glcm, flat_glcm)\\n measure_list[name] = np.sqrt(ASM)\\n elif name is 'cluster_shade':\\n cluster_weights = np.zeros([M, N])\\n for i in range(M):\\n for j in range(N):\\n cluster_weights[i, j] = (i + j - mean_i - mean_j) ** 3\\n measure_list[name] = np.dot(flat_glcm, cluster_weights.flatten())\\n elif name is 'correlation':\\n stdev_i = np.sqrt(var_i)\\n stdev_j = np.sqrt(var_j)\\n correl_weights = np.outer((index_i - mean_i), (index_j - mean_j)) / (stdev_i * stdev_j)\\n measure_list[name] = np.dot(flat_glcm, correl_weights.flatten())\\n elif name is 'contrast':\\n contrast_weights = np.zeros([M, N])\\n for i in range(M):\\n for j in range(N):\\n contrast_weights[i, j] = (i - j) ** 2\\n measure_list[name] = np.dot(flat_glcm, contrast_weights.flatten())\\n elif name is 'entropy':\\n # ln = np.log(flat_glcm) here, log(0) = -inf, will have some problem, using np.ma.log instead\\n # np.ma.log(0) = -- : not -inf. ? can pass\\n ln = np.ma.log(flat_glcm)\\n measure_list[name] = -np.dot(flat_glcm, ln)\\n elif name is 'dissimilarity':\\n dissi_weights = np.zeros([M, N])\\n for i in range(M):\\n for j in range(N):\\n dissi_weights[i, j] = abs(i - j)\\n measure_list[name] = np.dot(flat_glcm, dissi_weights.flatten())\\n elif name is 'homogeneity':\\n homo_weights = np.zeros([M, N])\\n for i in range(M):\\n for j in range(N):\\n homo_weights[i, j] = 1 / (1 + (i - j) ** 2)\\n measure_list[name] = np.dot(flat_glcm, homo_weights.flatten())\\n\\n return measure_list\",\n \"def perform_calculations(collector):\\n result = {}\\n try:\\n radius, mass = Calculator.calculate_radius_mass(collector)\\n result['radius'] = radius\\n result['mass'] = mass\\n average_density = Calculator.calculate_average_density(radius,\\n mass)\\n result['average_density'] = average_density\\n escape_velocity = Calculator.calculate_escape_velocity(radius,\\n mass)\\n result['escape_velocity'] = escape_velocity\\n earth_similarity_index = Calculator.calculate_esi_index(\\n radius, mass, collector.get_average_temperature())\\n result['earth_similarity_index'] = earth_similarity_index\\n except NoDataError:\\n pass\\n\\n try:\\n avg_atm_molar_mass = Calculator.calculate_molar_mass(collector)\\n except NoDataError:\\n avg_atm_molar_mass = None\\n if avg_atm_molar_mass is not None and avg_atm_molar_mass <= 0:\\n logging.getLogger('Analyzer').debug('Molar mass <= 0: %d',\\n avg_atm_molar_mass)\\n avg_atm_molar_mass = None\\n\\n if avg_atm_molar_mass is not None:\\n result['avg_atm_molar_mass'] = avg_atm_molar_mass\\n avg_molecule_mass = avg_atm_molar_mass / Calculator.A\\n result['avg_molecule_mass'] = avg_molecule_mass\\n specific_gas_const = Calculator.R / avg_atm_molar_mass\\n result['specific_gas_const'] = specific_gas_const\\n\\n try:\\n speed_of_sound = Kundt.speed_of_sound(collector.kundt)\\n result['speed_of_sound'] = speed_of_sound\\n\\n if avg_atm_molar_mass is None:\\n # All further calculations require valid molar mass\\n return result\\n\\n # Since calculate_molar_mass already uses get_average_temperature\\n # and get_ground_pressure, it's safe to use these functions here\\n # without worrying about NoDataError\\n adiabatic_index = Calculator.calculate_adiabatic_index(\\n collector, speed_of_sound, avg_atm_molar_mass)\\n result['adiabatic_index'] = adiabatic_index\\n\\n atmosphere_density = (adiabatic_index *\\n collector.get_ground_pressure() /\\n speed_of_sound ** 2)\\n result['atmosphere_density'] = atmosphere_density\\n\\n refractive_index = (3 * avg_atm_molar_mass *\\n collector.get_ground_pressure() /\\n atmosphere_density / Calculator.R /\\n collector.get_average_temperature() - 2) ** 0.5\\n result['refractive_index'] = refractive_index\\n\\n molar_refractivity = (avg_atm_molar_mass /\\n atmosphere_density *\\n (refractive_index ** 2 - 1) /\\n (refractive_index ** 2 + 2))\\n result['molar_refractivity'] = molar_refractivity\\n\\n atm_speed_of_light = Calculator.C / refractive_index\\n result['atm_speed_of_light'] = atm_speed_of_light\\n except NoDataError:\\n pass\\n\\n return result\",\n \"def calculate3(pred_ccm, pred_ad, truth_ccm, truth_ad, method=\\\"sym_pseudoV\\\", weights=None, verbose=False, pseudo_counts=True, full_matrix=True, in_mat=2):\\n larger_is_worse_methods = ['sym_pseudoV_nc', 'sym_pseudoV', 'pseudoV_nc', 'pseudoV', \\\"simpleKL_nc\\\", 'simpleKL'] # methods where a larger score is worse\\n\\n \\n pc_pred_ccm, pc_pred_ad, pc_truth_ccm, pc_truth_ad = pred_ccm, pred_ad, truth_ccm, truth_ad\\n y = np.array(pc_pred_ad.shape)[1]\\n nssms = int(np.ceil(0.5 * (2*y + 1) - 0.5 * np.sqrt(4*y + 1)))\\n\\n if isinstance(method, list):\\n res = [calculate3_onemetric(pc_pred_ccm, pc_pred_ad, pc_truth_ccm, pc_truth_ad,\\n method=m, verbose=verbose, in_mat=in_mat) for m in method] # calculate the score for each method\\n\\n # normalize the scores to be between (worst of NCluster score and OneCluster score) and (Truth score)\\n ncluster_ccm, ncluster_ad = add_pseudo_counts(mb.get_ccm('NClusterOneLineage', nssms=nssms), mb.get_ad('NClusterOneLineage', nssms=nssms))\\n ncluster_score = [calculate3_onemetric(ncluster_ccm, ncluster_ad, pc_truth_ccm, pc_truth_ad,\\n method=m, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat) for m in method]\\n del ncluster_ccm, ncluster_ad\\n onecluster_ccm, onecluster_ad = add_pseudo_counts(mb.get_ccm('OneCluster', nssms=nssms), mb.get_ad('OneCluster', nssms=nssms))\\n onecluster_score = [calculate3_onemetric(onecluster_ccm, onecluster_ad, pc_truth_ccm, pc_truth_ad,\\n method=m, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat) for m in method]\\n del onecluster_ccm, onecluster_ad\\n for i in range(len(method)):\\n if method[i] in larger_is_worse_methods: # normalization for methods where a larger score is worse\\n worst_score = max(ncluster_score[i], onecluster_score[i]) # worst of NCluster and OneCluster scores\\n res[i] = 1 - (res[i] / worst_score) # normalize the score\\n else: # normalization for methods where a smaller score is worse\\n worst_score = min(ncluster_score[i], onecluster_score[i])\\n res[i] = (res[i] - worst_score) / (1 - worst_score)\\n\\n\\n if weights is None: # if weights are not specified or if they cannot be normalized then default to equal weights\\n weights = [1] * len(method)\\n elif sum(weights) == 0:\\n Warning('Weights sum to zero so they are invalid, defaulting to equal weights')\\n weights = [1] * len(method)\\n\\n weights = np.array(weights) / float(sum(weights)) # normalize the weights\\n score = sum(np.multiply(res, weights))\\n else:\\n \\n score = calculate3_onemetric(pc_pred_ccm, pc_pred_ad, pc_truth_ccm, pc_truth_ad,\\n method=method, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat)\\n del pc_pred_ccm\\n del pc_pred_ad\\n # normalize the score to be between (worst of NCluster score and OneCluster score) and (Truth score) - similar to above\\n ncluster_ccm, ncluster_ad = add_pseudo_counts(mb.get_ccm('NClusterOneLineage', nssms=nssms), mb.get_ad('NClusterOneLineage', nssms=nssms))\\n ncluster_score = calculate3_onemetric(ncluster_ccm, ncluster_ad, pc_truth_ccm, pc_truth_ad,\\n method=method, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat)\\n del ncluster_ccm, ncluster_ad\\n onecluster_ccm, onecluster_ad = add_pseudo_counts(mb.get_ccm('OneCluster', nssms=nssms), mb.get_ad('OneCluster', nssms=nssms))\\n \\n onecluster_score = calculate3_onemetric(onecluster_ccm, onecluster_ad, pc_truth_ccm, pc_truth_ad,\\n method=method, verbose=verbose, full_matrix=full_matrix, in_mat=in_mat)\\n del onecluster_ccm, onecluster_ad\\n\\n #print score, ncluster_score, onecluster_score\\n if method in larger_is_worse_methods:\\n worst_score = max(ncluster_score, onecluster_score)\\n score = 1 - (score / worst_score)\\n else:\\n worst_score = min(ncluster_score, onecluster_score)\\n score = (score - worst_score) / (1 - worst_score)\\n return score\",\n \"def algorithms():\\n algorith_paradigms = ['Divide-and-conquer', 'Backtrackig', 'Greedy-Algorithms', 'Dynamic-programming']\\n return algorith_paradigms\",\n \"def main():\\r\\n algos = [merge_sort, quick_sort, heap_sort, radix_sort, bucket_sort_general]\\r\\n array_sizes = [5000, 10000, 15000, 20000, 50000, 75000, 100000, 150000]\\r\\n results = {algo.__name__: [] for algo in algos}\\r\\n for algo in algos:\\r\\n result = []\\r\\n for size in array_sizes:\\r\\n time = test(algo, size)\\r\\n result.append(time)\\r\\n results[algo.__name__] = result\\r\\n\\r\\n display_results(results, array_sizes)\",\n \"def __all_Algs_ ( self ) :\\n _algs = self.algorithms()\\n\\n algs = []\\n for _a in _algs :\\n algs += [ self.algorithm ( _a ) ]\\n return algs\",\n \"def __all_Algs_ ( self ) :\\n _algs = self.algorithms()\\n\\n algs = []\\n for _a in _algs :\\n algs += [ self.algorithm ( _a ) ]\\n return algs\",\n \"def all_means(runtimes):\\n tmp = {}\\n for name in runtimes:\\n tmp[name] = compute_means(runtimes[name])\\n return tmp\",\n \"def generate(dictalg):\\n\\n # dsList, sortedAlgs, dictAlg = processInputArgs(args, verbose=verbose)\\n res = {}\\n for f, i in pproc.dictAlgByFun(dictalg).iteritems():\\n for d, j in pproc.dictAlgByDim(i).iteritems():\\n tmp = BestAlgSet(j)\\n res[(d, f)] = tmp\\n return res\",\n \"def compute_statistics(self):\",\n \"def _calculate_cluster_measures(\\n arr4d,\\n threshold,\\n bin_struct,\\n two_sided_test=False,\\n):\\n n_regressors = arr4d.shape[3]\\n\\n max_sizes = np.zeros(n_regressors, int)\\n max_masses = np.zeros(n_regressors, float)\\n\\n for i_regressor in range(n_regressors):\\n arr3d = arr4d[..., i_regressor].copy()\\n\\n if two_sided_test:\\n arr3d[np.abs(arr3d) <= threshold] = 0\\n else:\\n arr3d[arr3d <= threshold] = 0\\n\\n labeled_arr3d, _ = label(arr3d > 0, bin_struct)\\n\\n if two_sided_test:\\n # Label positive and negative clusters separately\\n n_positive_clusters = np.max(labeled_arr3d)\\n temp_labeled_arr3d, _ = label(\\n arr3d < 0,\\n bin_struct,\\n )\\n temp_labeled_arr3d[temp_labeled_arr3d > 0] += n_positive_clusters\\n labeled_arr3d = labeled_arr3d + temp_labeled_arr3d\\n del temp_labeled_arr3d\\n\\n clust_vals, clust_sizes = np.unique(labeled_arr3d, return_counts=True)\\n assert clust_vals[0] == 0\\n\\n clust_vals = clust_vals[1:] # First cluster is zeros in matrix\\n clust_sizes = clust_sizes[1:]\\n\\n # Cluster mass-based inference\\n max_mass = 0\\n for unique_val in clust_vals:\\n ss_vals = np.abs(arr3d[labeled_arr3d == unique_val]) - threshold\\n max_mass = np.maximum(max_mass, np.sum(ss_vals))\\n\\n # Cluster size-based inference\\n max_size = 0\\n if clust_sizes.size:\\n max_size = np.max(clust_sizes)\\n\\n max_sizes[i_regressor], max_masses[i_regressor] = max_size, max_mass\\n\\n return max_sizes, max_masses\",\n \"def _calculate_metrics(self):\\n metrics = {}\\n precision, recall = self.calc_precision_recall()\\n metrics[\\\"precision\\\"] = precision\\n metrics[\\\"recall\\\"] = recall\\n metrics[\\\"entropy\\\"] = self.calc_entropy()\\n metrics[\\\"component_entropy\\\"] = self.calc_component_entropy()\\n metrics[\\\"num_comps\\\"] = len(self.get_components())\\n metrics[\\\"num_diagnoses\\\"] = len(self.diagnoses)\\n metrics[\\\"distinct_diagnoses_scores\\\"] = len(Counter(list(map(lambda x: x.probability, self.diagnoses))))\\n metrics[\\\"num_tests\\\"] = len(self.get_tests())\\n metrics[\\\"num_distinct_traces\\\"] = len(self.get_distinct_traces())\\n metrics[\\\"num_failed_tests\\\"] = len(self._get_tests_by_error(1))\\n metrics[\\\"num_passed_tests\\\"] = len(self._get_tests_by_error(0))\\n passed_comps = set(self._get_components_by_error(0))\\n failed_comps = set(self.get_components_in_failed_tests())\\n metrics[\\\"num_failed_comps\\\"] = len(failed_comps)\\n metrics[\\\"only_failed_comps\\\"] = len(failed_comps - passed_comps)\\n metrics[\\\"only_passed_comps\\\"] = len(passed_comps - failed_comps)\\n metrics[\\\"num_bugs\\\"] = len(self.get_bugs())\\n metrics[\\\"wasted\\\"] = self.calc_wasted_components()\\n metrics[\\\"top_k\\\"] = self.calc_top_k()\\n metrics[\\\"num_comps_in_diagnoses\\\"] = len(self._get_comps_in_diagnoses())\\n metrics[\\\"bugs_cover_ratio\\\"] = self._get_bugs_cover_ratio()\\n metrics[\\\"average_trace_size\\\"] = self._get_average_trace_size()\\n metrics[\\\"average_component_activity\\\"] = self._get_average_component_activity()\\n metrics[\\\"average_diagnosis_size\\\"] = self._get_average_diagnosis_size()\\n metrics[\\\"bugs_scores_average\\\"], metrics[\\\"bugs_scores_std\\\"], metrics[\\\"bugs_scores_entropy\\\"] = self._get_bugs_scores()\\n metrics[\\\"non_bugs_scores_average\\\"], metrics[\\\"non_bugs_scores_std\\\"], metrics[\\\"non_bugs_scores_entropy\\\"] = self._get_non_bugs_scores()\\n metrics.update(self.cardinality())\\n # metrics[\\\"ochiai\\\"] = self.calc_ochiai_values()\\n return metrics\",\n \"def compute_metrics(self):\\n overall_ret = OrderedDict()\\n for ap_iou_thresh in self.ap_iou_thresh:\\n ret_dict = OrderedDict()\\n rec, prec, ap = eval_det_multiprocessing(self.pred_map_cls, self.gt_map_cls, ovthresh=ap_iou_thresh)\\n for key in sorted(ap.keys()):\\n clsname = self.class2type_map[key] if self.class2type_map else str(key)\\n ret_dict[\\\"%s Average Precision\\\" % (clsname)] = ap[key]\\n ap_vals = np.array(list(ap.values()), dtype=np.float32)\\n ap_vals[np.isnan(ap_vals)] = 0\\n ret_dict[\\\"mAP\\\"] = ap_vals.mean()\\n rec_list = []\\n for key in sorted(ap.keys()):\\n clsname = self.class2type_map[key] if self.class2type_map else str(key)\\n try:\\n ret_dict[\\\"%s Recall\\\" % (clsname)] = rec[key][-1]\\n rec_list.append(rec[key][-1])\\n except:\\n ret_dict[\\\"%s Recall\\\" % (clsname)] = 0\\n rec_list.append(0)\\n ret_dict[\\\"AR\\\"] = np.mean(rec_list)\\n overall_ret[ap_iou_thresh] = ret_dict\\n return overall_ret\",\n \"def eval_mean_distance(played_decks, clustering_data: List, fuzzy: bool, debug: bool = False):\\n\\n for alg_dict in clustering_data:\\n decks = np.array(played_decks)\\n clusters = []\\n for label in set(alg_dict[\\\"labels\\\"]):\\n indices = np.where(alg_dict[\\\"labels\\\"] == label)\\n if fuzzy:\\n clusters.append(FuzzyDeckCluster(decks[indices]))\\n else:\\n clusters.append(DeckCluster(decks[indices]))\\n\\n if fuzzy:\\n clustering = FuzzyDeckClustering(clusters)\\n else:\\n clustering = DeckClustering(clusters)\\n\\n sum_of_squared_distances_centroid = 0\\n sum_of_squared_distances_core = 0\\n\\n for cluster in clustering.deck_clusters:\\n centroid = cluster.centroid()\\n core = cluster.core()\\n for deck in cluster.decks:\\n sum_of_squared_distances_centroid += (deck.jaccard_distance(centroid))**2\\n sum_of_squared_distances_core += (deck.jaccard_distance(core))**2\\n alg_dict[\\\"sse_centroid\\\"] = sum_of_squared_distances_centroid\\n alg_dict[\\\"sse_core\\\"] = sum_of_squared_distances_core\\n\\n if debug:\\n print(\\\"Alg: \\\" + alg_dict[\\\"name\\\"] + \\\"; \\\\t sse = \\\" + str(alg_dict[\\\"sse_centroid\\\"]))\\n print(\\\"Alg: \\\" + alg_dict[\\\"name\\\"] + \\\"; \\\\t sse = \\\" + str(alg_dict[\\\"sse_core\\\"]))\",\n \"def __init__(self, conn, args, data, split_type, num_clusters):\\n\\n self.conn = conn\\n self.args = args\\n self.data = data\\n self.split_type = split_type\\n\\n self.pca_model = None\\n self.cluster_model = None\\n self.algorithm = args['cluster_algorithm']\\n\\n # http://scikit-learn.org/stable/auto_examples/cluster/plot_cluster_comparison.html\\n hdbsc = hdbscan.HDBSCAN(min_cluster_size=10)\\n affinity_propagation = cluster.AffinityPropagation()\\n ms = cluster.MeanShift(bin_seeding=True)\\n spectral = cluster.SpectralClustering(n_clusters=num_clusters, \\n eigen_solver='arpack',\\n affinity=\\\"nearest_neighbors\\\", \\n random_state=self.args['seed'])\\n ward = cluster.AgglomerativeClustering(n_clusters=num_clusters, \\n linkage='ward')\\n birch = cluster.Birch(n_clusters=num_clusters)\\n two_means = cluster.MiniBatchKMeans(n_clusters=num_clusters,\\n random_state=self.args['seed'])\\n average_linkage = cluster.AgglomerativeClustering(linkage=\\\"average\\\", \\n n_clusters=num_clusters)\\n hdbsc = hdbscan.HDBSCAN(min_cluster_size=10)\\n kmeans = cluster.KMeans(n_clusters=num_clusters, random_state=self.args['seed'])\\n dbscan = cluster.DBSCAN()\\n \\n self.clustering_algorithms = {\\n 'MiniBatchKMeans': two_means,\\n 'AffinityPropagation': affinity_propagation,\\n 'MeanShift': ms,\\n 'SpectralClustering': spectral,\\n 'Ward': ward,\\n 'AgglomerativeClustering': average_linkage,\\n 'DBSCAN': dbscan,\\n 'Birch': birch,\\n 'HDBSCAN': hdbsc,\\n 'KMeans': kmeans\\n }\",\n \"def Clustering(typeVector, behaviour, sampleType):\\r\\n ProduceVector.produceVector(typeVector, behaviour, sampleType)\\r\\n vector = ProduceVector.getVector()\\r\\n\\r\\n if sampleType == \\\"\\\":\\r\\n sampleType2 = \\\"ransomware\\\"\\r\\n if sampleType == \\\"2\\\":\\r\\n sampleType2 = \\\"backdoor\\\"\\r\\n if sampleType == \\\"3\\\":\\r\\n sampleType2 = \\\"trojan\\\"\\r\\n\\r\\n if (behaviour == \\\"f\\\") or (behaviour == \\\"fc\\\"): \\r\\n\\r\\n calculateStandardisation(vector)\\r\\n vector = getStandardisation()\\r\\n\\r\\n typeOfVector = typeVector + \\\" \\\" + behaviour\\r\\n\\r\\n nGram, syscallRep = typeOfVector.split()\\r\\n\\r\\n if syscallRep == \\\"b\\\":\\r\\n nGram += \\\"Full Representation Bit Vector\\\"\\r\\n if syscallRep == \\\"f\\\":\\r\\n nGram += \\\"Full Representation Frequency Vector\\\"\\r\\n if syscallRep == \\\"bc\\\":\\r\\n nGram += \\\"Category Bit Vector\\\"\\r\\n if syscallRep == \\\"fc\\\":\\r\\n nGram += \\\"Category Frequency Vector\\\"\\r\\n\\r\\n\\r\\n fileName = sampleType2 + \\\" \\\" + syscallRep + \\\" standardisation \\\" + nGram + \\\".txt\\\"\\r\\n\\r\\n file = open(fileName, \\\"w\\\")\\r\\n file.write(str(vector.tolist()))\\r\\n file.close()\\r\\n\\r\\n calculateEuclideanDistance(vector) \\r\\n\\r\\n typeOfVector = typeVector + \\\" \\\" + behaviour\\r\\n\\r\\n nGram, syscallRep = typeOfVector.split()\\r\\n\\r\\n if syscallRep == \\\"b\\\":\\r\\n nGram += \\\"Full Representation Bit Vector\\\"\\r\\n if syscallRep == \\\"f\\\":\\r\\n nGram += \\\"Full Representation Frequency Vector\\\"\\r\\n if syscallRep == \\\"bc\\\":\\r\\n nGram += \\\"Category Bit Vector\\\"\\r\\n if syscallRep == \\\"fc\\\":\\r\\n nGram += \\\"Category Frequency Vector\\\" \\r\\n\\r\\n fileName = sampleType2 + \\\" \\\" + syscallRep + \\\" matrix \\\" + nGram + \\\".txt\\\"\\r\\n\\r\\n file = open(fileName, \\\"w\\\")\\r\\n file.write(str(getEuclideanDistance().tolist()))\\r\\n file.close()\\r\\n\\r\\n print(\\\"Producing a dendrogram\\\")\\r\\n\\r\\n\\r\\n typeOfVector = typeVector + \\\" \\\" + behaviour\\r\\n\\r\\n setBestCluster(Validation.evaluate(getEuclideanDistance(), vector, typeOfVector, sampleType))\",\n \"def parse_clustering(key, content):\\n if inspect.isclass(key):\\n cl = key(**content)\\n key = cl.__class__.__name__.lower()\\n\\n elif 'auto' in (content.get('n_clusters', ''),\\n content.get('preference', '')) \\\\\\n and key.lower() != 'hierarchical':\\n # Wrapper class that automatically detects the best number of clusters\\n # via 10-Fold CV\\n content.pop('n_clusters', '')\\n content.pop('preference', '')\\n\\n kwargs = {'param_grid': [], 'n_jobs': -1,\\n 'scoring': silhouette_score, 'cv': 10}\\n\\n if key.lower() == 'kmeans':\\n content.setdefault('init', 'k-means++')\\n content.setdefault('n_jobs', 1)\\n kwargs['estimator'] = KMeans(**content)\\n elif key.lower() == 'ap':\\n kwargs['estimator'] = AffinityPropagation(**content)\\n kwargs['affinity'] = kwargs['estimator'].affinity\\n else:\\n logging.error(\\\"n_clusters = 'auto' specified outside kmeans or \\\"\\n \\\"ap. Trying to create GridSearchCV pipeline anyway \\\"\\n \\\" ...\\\")\\n cl = GridSearchCV(**kwargs)\\n elif 'auto' in (content.get('n_clusters', ''),\\n content.get('preference', '')) \\\\\\n and key.lower() == 'hierarchical':\\n # TODO implement this\\n # from adenine.utils.extensions import AgglomerativeClustering\\n cl = AgglomerativeClustering(**content)\\n else:\\n if key.lower() == 'kmeans':\\n content.setdefault('n_jobs', -1)\\n cl = KMeans(**content)\\n elif key.lower() == 'ap':\\n content.setdefault('preference', 1)\\n cl = AffinityPropagation(**content)\\n elif key.lower() == 'ms':\\n cl = MeanShift(**content)\\n elif key.lower() == 'spectral':\\n cl = SpectralClustering(**content)\\n elif key.lower() == 'hierarchical':\\n cl = AgglomerativeClustering(**content)\\n else:\\n cl = DummyNone()\\n return (key, cl, 'clustering')\",\n \"def calculate_distances(self, iterations=[1]):\\n for i in iterations:\\n saved_policies = self.memory[i]\\n # Load relevant saved experiences\\n trajectories = []\\n policies = []\\n kdes = []\\n\\n for p in saved_policies:\\n trajectories.extend(p['trajectory'])\\n policies.append(p['policy'])\\n kdes.append(p['kde'])\\n\\n num_policies = len(policies)\\n\\n kde_all = self.calculate_KDE(trajectories)\\n samples = self.sample_kde(kde_all, 100)\\n\\n self.KDEs[i] = kde_all\\n self.meta_samples[i] = samples\\n\\n sample_divergences = []\\n\\n for sample_ix, sample in enumerate(samples):\\n probs_n = []\\n sample_divergence = np.zeros([num_policies, num_policies])\\n for ix in range(num_policies):\\n occupancy_measure = self.calculate_occupancy(\\n kdes[ix], policies[ix], sample)\\n probs_n.append(occupancy_measure)\\n # Save occupancy measures for comparison later\\n key = sample_ix\\n\\n try:\\n self.meta_occupancies[i][ix][key] = occupancy_measure\\n except:\\n try:\\n self.meta_occupancies[i][ix] = {\\n key: occupancy_measure}\\n except:\\n self.meta_occupancies[i] = {\\n ix: {key: occupancy_measure}}\\n\\n for a in range(num_policies):\\n for b in range(num_policies):\\n sample_divergence[a][b] = self.calculate_JSD(\\n probs_n[a].squeeze(), probs_n[b].squeeze())\\n\\n sample_prob = np.exp(kde_all.score(sample.reshape(1, -1)))\\n sample_divergences.append(sample_divergence * sample_prob)\\n # Compute average divergence over entirety\\n divergence = np.sum(sample_divergences, axis=0) # or sum?\\n self.meta_divergences[i] = divergence\",\n \"def answer_q10():\\n data_sources = [viz.DATA_111_URL, viz.DATA_290_URL, viz.DATA_896_URL]\\n x_vals = range(6, 21)\\n y_vals_hier = {}\\n y_vals_kmean = {}\\n for idx in range(len(data_sources)):\\n # 0. Generate data_field & cluster_list\\n clust_list, data_table = closest_pair.create_cluster_list(\\n data_sources[idx])\\n y_vals_hier[idx] = []\\n # 1. calculate values for hierarchical - decreasing order\\n for clust_size in reversed(x_vals):\\n clust_list = closest_pair.hierarchical_clustering(clust_list,\\n clust_size)\\n clust_error = closest_pair.compute_distortions(clust_list,\\n data_table)\\n y_vals_hier[idx].insert(0, clust_error)\\n # 2. calculate values for kmeans - decreasing order\\n y_vals_kmean[idx] = []\\n for clust_size in x_vals:\\n clust_list, data_table = closest_pair.create_cluster_list(\\n data_sources[idx])\\n clust_list = closest_pair.kmeans_clustering(clust_list,\\n clust_size, 5)\\n clust_error = closest_pair.compute_distortions(clust_list,\\n data_table)\\n y_vals_kmean[idx].append(clust_error)\\n return x_vals, y_vals_hier, y_vals_kmean\",\n \"def calculate_metric(self, embeddings, fingerprints, properties, estimator, param_dict):\\n\\n metric_array = []\\n for col in properties.columns:\\n props = properties[col].astype(cupy.float32).to_array()\\n embedding_error = self.gpu_gridsearch_cv(estimator, param_dict, embeddings, props)\\n fingerprint_error = self.gpu_gridsearch_cv(estimator, param_dict, fingerprints, props)\\n ratio = fingerprint_error / embedding_error # If ratio > 1.0 --> embedding error is smaller --> embedding model is better\\n metric_array.append(ratio)\\n return cupy.array(metric_array)\",\n \"def analysis_function_details(self,clustering):\\n return clustering.details\",\n \"def selectedComparisons(samples_dict):\\n sectors=\\\"peripherals\\\",\\\"intermediaries\\\",\\\"hubs\\\"\\n ks_measures={}\\n for analyses_type in samples_dict[sectors[0]]:\\n ks_measures[analyses_type]={}\\n for analysis_grouping in samples_dict[sectors[0]][analyses_type]:\\n ks_measures[analyses_type][analysis_grouping]={}\\n if samples_dict[sectors[0]][analyses_type][analysis_grouping]==dict:\\n ks_measures[analyses_type][analysis_grouping]={}\\n for analysis in samples_dict[sectors[0]][analyses_type][analysis_grouping]:\\n for var in samples_dict[sectors[0]][analyses_type][analysis_grouping][analysis]:\\n samples_peripherals=samples_dict[sectors[0]][analyses_type][analysis_grouping][analysis]\\n samples_intermediaries=samples_dict[sectors[1]][analyses_type][analysis_grouping][analysis]\\n samples_hubs=samples_dict[sectors[2]][analyses_type][analysis_grouping][analysis]\\n ks_measures[analysis][\\\"peripherals_intermediaries\\\"]=P.kolmogorovSmirnovTest(samples_peripherals,samples_intermediaries)\\n ks_measures[analysis][\\\"peripherals_hubs\\\"]=P.kolmogorovSmirnovTest(samples_peripherals,samples_hubs)\\n ks_measures[analysis][\\\"hubs_intermediaries\\\"]=P.kolmogorovSmirnovTest(samples_hubs,samples_intermediaries)\\n else:\\n for var in samples_dict[sectors[0]][analyses_type][analysis_grouping]:\\n samples_peripherals=samples_dict[sectors[0]][analyses_type][analysis_grouping]\\n samples_intermediaries=samples_dict[sectors[1]][analyses_type][analysis_grouping]\\n samples_hubs=samples_dict[sectors[2]][analyses_type][analysis_grouping]\\n\\n\\n\\n samples[sector][analyses][analysis_grouping]=updateDict(samples[sector][analyses][analysis_grouping],getSamples(authors_analysis[analyses][author][analysis_grouping]))\",\n \"def analyzeClusterPerformance(self, cluster):\\n def calcOverlap(playlist, group):\\n urls = set(group[\\\"uri\\\"].values)\\n playlist = set(playlist)\\n return len(urls & playlist)\\n\\n groupedDF = self.audioDF.groupby(cluster)\\n playlists = list(self.playlists)\\n\\n clusters = [group for _, group in groupedDF]\\n numSongs = sum([len(p) for p in playlists])\\n\\n numOverlap, maxOverlap = 0, 1\\n while len(playlists) > 0 and len(clusters) > 0 and maxOverlap > 0:\\n maxOverlap, pIDX, gIDX = 0, None, None\\n for i, playlist in enumerate(playlists):\\n for j, c in enumerate(clusters):\\n overlap = calcOverlap(playlist, c)\\n if overlap > maxOverlap:\\n maxOverlap, pIDX, gIDX = overlap, i, j\\n \\n if maxOverlap > 0:\\n playlists.pop(pIDX)\\n clusters.pop(gIDX)\\n numOverlap += maxOverlap\\n\\n performance = float(numOverlap) / float(numSongs)\\n performancePercentage = round(performance, 4) * 100\\n\\n return {\\n \\\"Clustering Algorithm\\\": cluster,\\n \\\"Performance\\\": performance\\n }\",\n \"def _compute_experiment_statistics(self):\\n pass\",\n \"def test(referrer, tester, test_word, algorithm, algo_params={}, visualize_results=False, apply_PCA=False, clear_referrer_with_algo=False, clean_algo_parameters={\\\"name\\\": 'EllipticEnvelope', \\\"contamination\\\": 0.1, \\\"visualize_results\\\": False}):\\n\\n # Split the test_word to digraphs\\n test_digraphs = [('Key' + c[0].upper() if c[0] != ' ' else 'Space') + ('Key' + c[1].upper() if c[1] != ' ' else 'Space')\\n for c in [z[0] + z[1] for z in zip(test_word, test_word[1:])]]\\n\\n # Test each digraph data of tester against referrer\\n count_insufficient_ref_samples = 0.\\n # `score` Represents number of inliers if algo != 'GMM' else represents score for each GMM component\\n score = 0. if algorithm != 'GMM' else []\\n count_global = 0.\\n for test_digraph in test_digraphs:\\n\\n # Find the digraph data of referrer\\n ref_di_points = ret_digraph_points(\\n referrer, test_digraph).astype(float)\\n # print ref_di_points\\n if len(ref_di_points) >= 10:\\n\\n # If tester and referrer sample\\n if referrer['_subject'] == tester['_subject'] and referrer['_track_code'] == tester['_track_code']:\\n _tmp = ref_di_points\\n np.random.shuffle(_tmp)\\n perc = int(np.floor(0.8 * len(_tmp)))\\n ref_di_points = _tmp[0:perc, :]\\n test_di_points = _tmp[perc:, :]\\n else:\\n # Sample some data for the particular digraph in tester\\n _test_di_points = ret_digraph_points(tester, test_digraph)\\n test_di_points = _test_di_points[np.random.choice(\\n _test_di_points.shape[0], size=randint(10, 12), replace=False), :]\\n\\n # Transform ref and tester data with standard scaler\\n sscaler = StandardScaler(with_mean=True, with_std=True).fit(\\n np.append(ref_di_points, test_di_points, axis=0))\\n train_points = sscaler.transform(ref_di_points)\\n test_points = sscaler.transform(test_di_points)\\n\\n # Apply PCA if needed\\n if apply_PCA is True:\\n pca_model = PCA().fit(\\n np.append(train_points, test_points, axis=0))\\n train_points = pca_model.transform(train_points)[:, 0:2]\\n test_points = pca_model.transform(test_points)[:, 0:2]\\n\\n # Clean referrer points from noise if needed\\n if clear_referrer_with_algo is True:\\n train_points = general_purpose.clean_with_algo(\\n train_points, algorithm=clean_algo_parameters['name'], contamination=clean_algo_parameters['contamination'])\\n\\n # Anomaly-Test the digraph and get the count_global of inliers\\n if algorithm != 'GMM':\\n score += digraph_test(train_points,\\n test_points, algorithm, algo_params, visualize_results=visualize_results,\\n plt_title_info={\\\"referrer\\\": referrer['_subject'],\\n \\\"tester\\\": tester['_subject'], \\\"digraph\\\": test_digraph})\\n else:\\n # Special procedure for GMM\\n _sc = digraph_test_GMM(train_points,\\n test_points, algo_params, visualize_results=visualize_results,\\n plt_title_info={\\\"referrer\\\": referrer['_subject'],\\n \\\"tester\\\": tester['_subject'], \\\"digraph\\\": test_digraph})\\n score.append(_sc)\\n\\n else:\\n\\n count_insufficient_ref_samples += len(test_points)\\n\\n count_global += len(test_points)\\n\\n # Find eventually the total score\\n if algorithm != 'GMM':\\n total_score = score / \\\\\\n (count_global - count_insufficient_ref_samples)\\n else:\\n total_score = 0.\\n for s in score:\\n total_score += sum(s)\\n total_score = total_score / \\\\\\n (count_global - count_insufficient_ref_samples)\\n\\n # print '\\\\n'\\n # print 'Digraph passed: ' + str(total_score) + '%, ' + str(int(score)) + ' out of ' + str(int(count_global - count_insufficient_ref_samples))\\n # print 'Insufissient digraph samples: ' + str(count_insufficient_ref_samples) + ' out of ' + str(int(count_global))\\n # print total_score\\n if count_insufficient_ref_samples > 0:\\n print 'Insuffisient samples: %d' % (count_insufficient_ref_samples)\\n print 'For word: ' + test_word\\n return total_score\",\n \"def multiClusterAlgorithm(values):\\n clusterMap = dict()\\n # Lowest unixtime in the values list\\n startUnixtime = values[0][0]\\n # Separate values into separate clusters in the map, clusterMap\\n for value in values:\\n if value[2] not in clusterMap.keys():\\n clusterMap[value[2]] = []\\n clusterMap[value[2]].append(value)\\n \\n # An array of the predicted values per cluster\\n clusterPredicted = []\\n # An array of unixtime averages per cluster\\n unixtimeAverage = []\\n \\n # Generate predicted value for each cluster using a weighted average\\n # Adds predicted value for each cluster to clusterPredicted and adds\\n # the unixtime average for each cluster to unixtimeAverage\\n for key in clusterMap.keys():\\n clusterLength = len(clusterMap[key]) \\n totalUnixtime = sum([elem[0] for elem in clusterMap[key]])\\n unixtimeAverage.append(float(totalUnixtime) / float(clusterLength))\\n \\n clusterLight = [elem[1] for elem in clusterMap[key]]\\n\\n totalDistanceFromStart = sum([elem[0] - startUnixtime for elem in clusterMap[key]])\\n clusterWeightValues = [float(elem[0] - startUnixtime) / float(totalDistanceFromStart) for elem in clusterMap[key]]\\n \\n predicted = np.average(clusterLight, weights = clusterWeightValues)\\n clusterPredicted.append(predicted)\\n \\n print clusterPredicted\\n total = sum([elem - startUnixtime for elem in unixtimeAverage])\\n # Create weighted values based on unixtime average per cluster\\n weightValues = [float(elem - startUnixtime) / float(total) for elem in unixtimeAverage]\\n print weightValues\\n # Return a weighted average across clusters\\n return np.average(clusterPredicted, weights = weightValues)\",\n \"def get_metrics(cfg, model, X_anchor, y_anchor, X_gal, y_gal, annoy_index, vec_dim):\\n rank10_acc = 0\\n rank5_acc = 0\\n rank1_acc = 0\\n avg_acc = 0\\n vote_res = 0\\n\\n l2 = []\\n for anchor in range(0, len(X_anchor)):\\n res = get_result(get_image_features(cfg, model, X_anchor[anchor]), annoy_index)\\n vote = defaultdict(int)\\n # Accuracy\\n correct = 0\\n for i in res[:10]:\\n vote[y_gal[i]] += 1\\n\\n max_key = max(vote, key=vote.get)\\n if max_key == y_anchor[anchor]:\\n vote_res += 1\\n \\n\\n for recomm in res[:10]:\\n if y_gal[recomm] == y_anchor[anchor]:\\n correct += 1 \\n\\n avg_acc += correct/len(res)\\n\\n # Mean Average Precision\\n l1 = []\\n for recomm in res[:10]:\\n if y_gal[recomm] == y_anchor[anchor]:\\n correct += 1\\n l1.append(1)\\n else:\\n l1.append(0)\\n l2.append(l1) \\n\\n # Rank10 Accuracy\\n for each_val in res[:10]:\\n if y_gal[each_val] == y_anchor[anchor]:\\n rank10_acc += 1\\n break\\n \\n # Rank5 Accuracy\\n for each_val in res[:5]:\\n if y_gal[each_val] == y_anchor[anchor]:\\n rank5_acc += 1\\n break\\n\\n # Rank1 Accuracy\\n for each_val in res[:1]:\\n if y_gal[each_val] == y_anchor[anchor]:\\n rank1_acc += 1\\n break\\n\\n print(\\\"Avg acc is :: {avg_acc}\\\".format(avg_acc = avg_acc/len(X_anchor)))\\n print(\\\"Rank 10 acc is :: {rank10_acc}\\\".format(rank10_acc = rank10_acc/len(X_anchor)))\\n print(\\\"Rank 5 acc is :: {rank5_acc}\\\".format(rank5_acc = rank5_acc/len(X_anchor)))\\n print(\\\"Rank 1 acc is :: {rank1_acc}\\\".format(rank1_acc = rank1_acc/len(X_anchor)))\\n print(\\\"Mean Avg Precision is :: {mAP}\\\".format(mAP=mean_average_precision(l2)))\\n print(\\\"Vote res :: \\\", vote_res/len(X_anchor))\\n\\n return rank1_acc/len(X_anchor), mean_average_precision(l2)\",\n \"def enumerate_clusterings(self):\\n\\n # Initialize an empty list of clusterings. Each element of the list\\n # is a dictionary mapping NOEs to the signatures they are clustered to\\n # in a solution. Each clustering is initialize with all uniquely\\n # clusterable NOEs as keys mapping to their unique clusters\\n\\n clusterings = []\\n\\n while True:\\n\\n # Run the solver and get a solution back\\n\\n solution = self.solve()\\n\\n # If UNSAT, then flush aux clauses from the formula and return\\n # all the clusterings we found so far\\n\\n if not solution:\\n self.flush()\\n return clusterings\\n\\n # Iterate over the clustering variables set to true by in the\\n # discovered solution. Forbid this clustering from reoccuring and\\n # add it to the list of found clusterings\\n\\n clause = []\\n clustering = {}\\n for node in self.clustering_variables.keys():\\n if len(node.clusters) == 1:\\n clustering[node] = list(node.clusters)[0]\\n\\n for vtype, node, cluster in solution:\\n if vtype == Formula.CST_VAR:\\n clustering[node] = cluster\\n clause.append(-self.clustering_variables[node][cluster])\\n\\n self.add_clause(clause)\\n clusterings.append(clustering)\",\n \"def compute_means(self):\\n ###TODO\\n vector_means = []\\n for doc in self.fin_clust.values():\\n vec = defaultdict(float)\\n for d_id in doc:\\n doc_keys = self.docs[d_id].keys()\\n for key in self.docs[d_id]:\\n vec[key] = vec[key] + self.docs[d_id][key]\\n tot = len(doc)\\n x = defaultdict(float)\\n for k,v in vec.items():\\n x[k] = float(v)/tot\\n vec = Counter(x)\\n vector_means.append(vec)\\n return vector_means\",\n \"def evaluation_cc(self, property='clustering-coeff'):\\n\\n if property == 'clustering-coeff':\\n rw_cc = [np.mean(clustering_coef_wu(self.rw_data[t])) for t in range(0, self.T)]\\n smth_cc = [np.mean(clustering_coef_wu(self.smth_data[t])) for t in range(0, self.T)]\\n elif property == 'transitivity':\\n rw_cc = [np.mean(transitivity_wu(self.rw_data[t])) for t in range(0, self.T)]\\n smth_cc = [np.mean(transitivity_wu(self.smth_data[t])) for t in range(0, self.T)]\\n elif property == 'coreness':\\n rw_cc = [np.mean(core.core_periphery_dir(self.rw_data[t])) for t in range(0, self.T)]\\n smth_cc = [np.mean(core.core_periphery_dir(self.smth_data[t])) for t in range(0, self.T)]\\n elif property == 'assortativity':\\n rw_cc = [np.mean(core.assortativity_wei(self.rw_data[t], 0)) for t in range(0, self.T)]\\n smth_cc = [np.mean(core.assortativity_wei(self.smth_data[t], 0)) for t in range(0, self.T)]\\n elif property == 'modularity':\\n rw_cc, _ = get_number_of_components(self.rw_data)\\n smth_cc, _ = get_number_of_components(self.smth_data)\\n elif property == 'path_length':\\n rw_cc = [charpath(rw)[0] for rw in self.rw_data]\\n smth_cc = [charpath(sm)[0] for sm in self.smth_data]\\n\\n # rw_cc_ent = get_entropy_list(rw_cc)\\n # smth_cc_ent = get_entropy_list(smth_cc)\\n\\n return rw_cc, smth_cc\",\n \"def ehost_iaa_compute(folder1, folder2, no_context=False):\\n annotator1 = read_ehost_annotated_result(folder1, no_context=no_context)\\n annotator2 = read_ehost_annotated_result(folder2, no_context=no_context)\\n merged_keys = list(set(annotator1.keys()) | set(annotator2.keys()))\\n y1 = []\\n y2 = []\\n for key in merged_keys:\\n if key in annotator1 and key in annotator2:\\n y1.append(annotator1[key])\\n y2.append(annotator2[key])\\n else:\\n print('%s not matched in all' % key)\\n iaa = sklearn.metrics.cohen_kappa_score(y1, y2)\\n print('IAA is %s on %s' % (iaa, len(annotator1)))\\n return iaa\",\n \"def clustering(self):\\n ret_concepts = []\\n clusters = []\\n for word in self.words:\\n clusters.append(WordCluster(None, word))\\n while len(clusters) > 1:\\n maxi = -1\\n maxj = -1\\n max = -1\\n m = -1\\n for i in range(len(clusters)):\\n for j in range(len(clusters)):\\n if i == j:\\n continue\\n # print(\\\"%d cluster compare with %d cluster\\\" % (i, j))\\n # 1: join 21: i absorb j 22: j absorb i 3: collapse\\n # l1: join L(Tm) value l21: A absorb B L(Tm)value\\n l1, newtags = self.__calculate_ltm(clusters[i], clusters[j], 1)\\n if l1 > max:\\n m = 1\\n maxi = i\\n maxj = j\\n max = l1\\n print(\\\"max L(Tm) for clustering in current loop: %lf\\\" % max)\\n if max < ClusterAlgorithm.P_threshold:\\n return\\n Tm = clusters[maxi].join(clusters[maxj])\\n Tm_concepts = self.__select_concepts(self.__getword(Tm))\\n for tmp_concept in Tm_concepts.items():\\n ret_concepts.append(tmp_concept)\\n rm1 = clusters[maxi]\\n rm2 = clusters[maxj]\\n clusters.remove(rm1)\\n clusters.remove(rm2)\\n if Tm is not None:\\n print(\\\"merged cluster's words:\\\")\\n print(self.__getword(Tm))\\n return ret_concepts\",\n \"def main():\\n parser = argparse.ArgumentParser(description=\\\"Wrapper of the scikit-learn AgglomerativeClustering method. \\\", formatter_class=lambda prog: argparse.RawTextHelpFormatter(prog, width=99999))\\n parser.add_argument('--config', required=False, help='Configuration file')\\n\\n # Specific args of each building block\\n required_args = parser.add_argument_group('required arguments')\\n required_args.add_argument('--input_dataset_path', required=True, help='Path to the input dataset. Accepted formats: csv.')\\n required_args.add_argument('--output_results_path', required=True, help='Path to the clustered dataset. Accepted formats: csv.')\\n parser.add_argument('--output_plot_path', required=False, help='Path to the clustering plot. Accepted formats: png.')\\n\\n args = parser.parse_args()\\n args.config = args.config or \\\"{}\\\"\\n properties = settings.ConfReader(config=args.config).get_prop_dic()\\n\\n # Specific call of each building block\\n agglomerative_clustering(input_dataset_path=args.input_dataset_path,\\n output_results_path=args.output_results_path,\\n output_plot_path=args.output_plot_path,\\n properties=properties)\",\n \"def compute_metrics(self):\\n self.finalize_output_dict()\\n self.metric_dict = {\\n key: value(self.output_dict[\\\"labels\\\"], self.output_dict[\\\"pred_probs\\\"])\\n for key, value in self.metric_fns.items()\\n }\",\n \"def _cluster(self):\\n # , distance_function=spearman_squared_distance, max_iter=1000, tol=0.0001):\\n if self.cluster_method is None:\\n clusters = KMedoids(\\n self.k,\\n self.batchsize,\\n dist_func=self.distance_function,\\n max_iter=self.max_iter,\\n tol=self.tol,\\n init_medoids=self.init_medoids,\\n swap_medoids=self.swap_medoids,\\n )\\n clusters.fit(self.clustering_attributions, verbose=self.verbose)\\n\\n self.subpopulations = clusters.members\\n self.subpopulation_sizes = GAM.get_subpopulation_sizes(clusters.members)\\n self.explanations = self._get_explanations(clusters.centers)\\n # Making explanations return numerical values instead of dask arrays\\n if isinstance(self.explanations[0][0][1], da.Array):\\n explanations = []\\n for explanation in self.explanations:\\n explanations.append([(x[0], x[1].compute()) for x in explanation])\\n self.explanations = explanations\\n else:\\n self.cluster_method(self)\",\n \"def prepare_statistics(self):\\n\\n # statistics of clustering files\\n len0 = len(self.cluster_lists[0])\\n len1 = len(self.cluster_lists[1])\\n longer_index = 0 if len0 >= len1 else 1\\n shorter_index = 1 if len1 <= len0 else 0\\n\\n percentage_stars = \\\"%.2f\\\" % (100.0 * float(self.shared_spec_num)/float(self.cluster_spectra_num[shorter_index]))\\n percentage_starlets = \\\"%.2f\\\" % (100.0 * float(self.shared_spec_num)/float(self.cluster_spectra_num[longer_index]))\\n\\n head = \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"name\\\", \\\"number\\\", \\\"description\\\")\\n rows = \\\"\\\"\\n rows += \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"stars No.\\\", self.stars_length, \\\"in file with less(or equal) clusters: file\\\" + str(shorter_index))\\n rows += \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"starlets No.\\\", self.starlets_length, \\\"in file with more(or equal) clusters: file\\\" + str(longer_index))\\n rows += \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"identical cluster No.\\\", self.similarity_dist[10], \\\"between them\\\")\\n rows += \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"spectrum No\\\", self.cluster_spectra_num[shorter_index], \\\"in stars\\\")\\n rows += \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"spectrum No\\\", self.cluster_spectra_num[longer_index], \\\"in starlets \\\")\\n rows += \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"shared spectrum No\\\", self.shared_spec_num, \\\"between them\\\")\\n rows += \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"shared spectrum percent\\\", percentage_stars, \\\"in stars\\\")\\n rows += \\\"{0:<25}{1:<20}{2:<20}\\\\n\\\".format(\\\"shared spectrum percent\\\", percentage_starlets, \\\"in starlets\\\")\\n self.tables.append(('statistics of files', head, rows))\\n\\n # distribution of cluster size in stars\\n head = '{0:<20}{1:<20}{2:<20}{3:<20}\\\\n'.format(\\\"cluster size\\\",\\\"No.\\\", \\\"percentage\\\", \\\"accumulate pecentage\\\")\\n rows = \\\"\\\"\\n rows += \\\"{0:<20}{1:<20}\\\\n\\\".format(\\\"%.2f\\\" % (self.ave_star_size), \\\"average\\\")\\n accumulate_num = 0\\n for key in sorted(self.cluster_size_dist[shorter_index].keys()):\\n value = self.cluster_size_dist[shorter_index][key]\\n accumulate_num += value\\n percent = \\\"%.2f\\\" % (100 * value/self.stars_length)\\n accum_percent = \\\"%.2f\\\" % (100 * accumulate_num/self.stars_length)\\n rows += '{0:<20}{1:<20}{2:<20}{3:<20}\\\\n'.format(key, value, percent, accum_percent)\\n self.tables.append(('distribution of cluster size in stars', head, rows))\\n \\n head = '{0:<20}{1:<20}{2:<20}{3:<20}\\\\n'.format(\\\"cluster size\\\",\\\"No.\\\", \\\"percentage\\\", \\\"accumulate pecentage\\\")\\n rows = \\\"\\\"\\n rows += \\\"{0:<20}{1:<20}\\\\n\\\".format(\\\"%.2f\\\" % (self.ave_starlet_size), \\\"average\\\")\\n accumulate_num = 0\\n for key in sorted(self.cluster_size_dist[longer_index].keys()):\\n value = self.cluster_size_dist[longer_index][key]\\n accumulate_num += value\\n percent = \\\"%.2f\\\" % (100 * value/self.starlets_length)\\n accum_percent = \\\"%.2f\\\" % (100 * accumulate_num/self.starlets_length)\\n rows += '{0:<20}{1:<20}{2:<20}{3:<20}\\\\n'.format(key, value, percent, accum_percent)\\n self.tables.append(('distribution of cluster size in starlets', head, rows))\\n\\n # distribution of similarity\\n head = \\\"{0:<20}{1:<20}{2:<20}{3:<20}\\\\n\\\".format(\\\"similarity score\\\", \\\"pairs of clusters\\\", \\\"percentage(stars)\\\", \\\"percentage(starlets)\\\")\\n rows = \\\"\\\"\\n for key in reversed(sorted(self.similarity_dist.keys())):\\n value = self.similarity_dist[key]\\n percent_star = \\\"%.2f\\\" % (100.0*value/self.stars_length)\\n percent_starlet = \\\"%.2f\\\" % (100.0*value/self.starlets_length)\\n rows += '{0:<20}{1:<20}{2:<20}{3:<20}\\\\n'.format(key, value, percent_star, percent_starlet)\\n self.tables.append(('distribution of similarity (identical = 10)', head, rows))\\n\\n # distribution of star divide factors\\n head = '{0:<20}{1:<20}{2:<20}\\\\n'.format(\\\"divide factor\\\",\\\"No.\\\",\\\"percentage\\\")\\n rows = \\\"\\\"\\n rows += \\\"{0:<20}{1:<20}\\\\n\\\".format(\\\"%.2f\\\" % (self.ave_divide_factor_star), \\\"average\\\")\\n for key in sorted(self.star_divide_factor_dist.keys()):\\n value = self.star_divide_factor_dist[key]\\n percent_star = \\\"%.2f\\\" % (100.0*value/self.stars_length)\\n rows += '{0:<20}{1:<20}{2:<20}\\\\n'.format(key, value, percent_star)\\n self.tables.append(('distribution of star divide factors', head, rows))\\n\\n # distribution of starlet divide factors\\n head = '{0:<20}{1:<20}{2:<20}\\\\n'.format(\\\"divide factor\\\",\\\"No.\\\",\\\"percentage\\\")\\n rows = \\\"\\\"\\n rows += \\\"{0:<20}{1:<20}\\\\n\\\".format(\\\"%.2f\\\" % (self.ave_divide_factor_starlet), \\\"average\\\")\\n for key in sorted(self.starlet_divide_factor_dist.keys()):\\n value = self.starlet_divide_factor_dist[key]\\n percent_starlet = \\\"%.2f\\\" % (100.0*value/self.starlets_length)\\n rows += '{0:<20}{1:<20}{2:<20}\\\\n'.format(key, value, percent_starlet)\\n self.tables.append(('distribution of starlet divide factors', head, rows))\",\n \"def cluster_membership_occupancy(data):\\n \\n \\n \\n n_clusters = len(set(data['clusters'])-{-1}) # since -1 element denotes noice\\n\\n if n_clusters == 0:\\n membership=[Cluster_Membership_Features()]\\n membership = pd.DataFrame([o.__dict__ for o in membership])\\n areas=[Cluster_Area_Features()]\\n areas = pd.DataFrame([o.__dict__ for o in areas])\\n density=[Cluster_Density_Features()]\\n density = pd.DataFrame([o.__dict__ for o in density])\\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\\n density], axis=1)\\n \\n elif n_clusters ==1:\\n #obtain_total_cluster_areas_set_everything_else_to_default\\n membership=[Cluster_Membership_Features()]\\n membership = pd.DataFrame([o.__dict__ for o in membership])\\n d = dict(tuple(data.groupby('clusters')))\\n d.pop(-1, None)\\n \\n try:\\n cluster_chull_areas=[ss.ConvexHull(np.column_stack([d[i]['X'].array,d[i]['Y'].array])).volume for i in d.keys()]\\n except:\\n cluster_chull_areas=[0,0,0]\\n \\n Total_cluster_area=np.sum(cluster_chull_areas)\\n areas=[Cluster_Area_Features([Total_cluster_area,0,0,0,0,0,0,0,0])]\\n areas = pd.DataFrame([o.__dict__ for o in areas])\\n density=[Cluster_Density_Features()]\\n density = pd.DataFrame([o.__dict__ for o in density])\\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\\n density], axis=1)\\n \\n elif n_clusters >1:\\n #Summarizing the cluster membership distribution characteristics\\n cluster_size_nums=np.delete(np.array(data.groupby(['clusters']).size()),0)\\n (cluster_size_nums_avg,cluster_size_nums_min,cluster_size_nums_max,\\n cluster_size_nums_std,cluster_size_nums_cv,cluster_size_nums_cd,\\n cluster_size_nums_IQR,cluster_size_nums_Quartile_CD)= distribution_statistics(cluster_size_nums)\\n\\n #For each cluster calculate the area by calculating the area of the convex hull of cluster members\\n # Note: concavehull implementation here might be a good addition as it will provide more imformative values. \\n\\n d = dict(tuple(data.groupby('clusters')))\\n d.pop(-1, None)\\n try:\\n cluster_chull_areas=[ss.ConvexHull(np.column_stack([d[i]['X'].array,d[i]['Y'].array])).volume for i in d.keys()]\\n except:\\n cluster_chull_areas=[0,0,0,0,0]\\n \\n\\n (avg_cluster_area,min_cluster_area,max_cluster_area,\\n std_cluster_area,CV_cluster_area,CD_cluster_area,\\n IQR_cluster_area,Quartile_CD_cluster_area)= distribution_statistics(cluster_chull_areas)\\n Total_cluster_area=np.sum(cluster_chull_areas)\\n\\n #Calculate cluster density: number of nuclei/ convex area of cluster\\n cluster_density=np.divide(cluster_size_nums,cluster_chull_areas)\\n (avg_cluster_density,min_cluster_density,max_cluster_density,\\n std_cluster_density,CV_cluster_density,CD_cluster_density,\\n IQR_cluster_density,Quartile_CD_cluster_density)= distribution_statistics(cluster_density)\\n\\n #return dataframe of features\\n membership=[Cluster_Membership_Features([cluster_size_nums_avg,cluster_size_nums_min,cluster_size_nums_max,\\n cluster_size_nums_std,cluster_size_nums_cv,cluster_size_nums_cd,\\n cluster_size_nums_IQR,cluster_size_nums_Quartile_CD])]\\n membership = pd.DataFrame([o.__dict__ for o in membership])\\n areas=[Cluster_Area_Features([Total_cluster_area,\\n avg_cluster_area,min_cluster_area,max_cluster_area,\\n std_cluster_area,CV_cluster_area,CD_cluster_area,\\n IQR_cluster_area,Quartile_CD_cluster_area])]\\n areas = pd.DataFrame([o.__dict__ for o in areas])\\n density=[Cluster_Density_Features([avg_cluster_density,min_cluster_density,max_cluster_density,\\n std_cluster_density,CV_cluster_density,CD_cluster_density,\\n IQR_cluster_density,Quartile_CD_cluster_density])]\\n density = pd.DataFrame([o.__dict__ for o in density])\\n\\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\\n density], axis=1)\\n return all_features\",\n \"def convergence_measure_all(filename,index,mean_subtract,smoothing_scale=None):\\n\\n\\tlogging.info(\\\"Processing {0}\\\".format(filename))\\n\\n\\t#Load the map\\n\\tconv_map = ConvergenceMap.load(filename)\\n\\n\\tif mean_subtract:\\n\\t\\tconv_map.data -= conv_map.mean()\\n\\n\\t#Smooth the map maybe\\n\\tif smoothing_scale is not None:\\n\\t\\tlogging.info(\\\"Smoothing {0} on {1}\\\".format(filename,smoothing_scale))\\n\\t\\tconv_map.smooth(smoothing_scale,kind=\\\"gaussianFFT\\\",inplace=True)\\n\\n\\t#Allocate memory for observables\\n\\tdescriptors = index\\n\\tobservables = np.zeros(descriptors.size)\\n\\n\\t#Measure descriptors as directed by input\\n\\tfor n in range(descriptors.num_descriptors):\\n\\t\\t\\n\\t\\tif type(descriptors[n]) == PowerSpectrum:\\n\\t\\t\\tl,observables[descriptors[n].first:descriptors[n].last] = conv_map.powerSpectrum(descriptors[n].l_edges)\\n\\t\\t\\t\\n\\t\\telif type(descriptors[n]) == Moments:\\n\\t\\t\\tobservables[descriptors[n].first:descriptors[n].last] = conv_map.moments(connected=descriptors[n].connected)\\n\\t\\t\\t\\n\\t\\telif type(descriptors[n]) == Peaks:\\n\\t\\t\\tv,observables[descriptors[n].first:descriptors[n].last] = conv_map.peakCount(descriptors[n].thresholds,norm=descriptors[n].norm)\\n\\n\\t\\telif type(descriptors[n]) == PDF:\\n\\t\\t\\tv,observables[descriptors[n].first:descriptors[n].last] = conv_map.pdf(descriptors[n].thresholds,norm=descriptors[n].norm)\\n\\t\\t\\n\\t\\telif type(descriptors[n]) == MinkowskiAll:\\n\\t\\t\\tv,V0,V1,V2 = conv_map.minkowskiFunctionals(descriptors[n].thresholds,norm=descriptors[n].norm)\\n\\t\\t\\tobservables[descriptors[n].first:descriptors[n].last] = np.hstack((V0,V1,V2))\\n\\t\\t\\n\\t\\telif type(descriptors[n]) == MinkowskiSingle:\\n\\t\\t\\traise ValueError(\\\"Due to computational performance you have to measure all Minkowski functionals at once!\\\")\\n\\t\\t\\n\\t\\telse:\\n\\t\\t\\t\\n\\t\\t\\traise ValueError(\\\"Measurement of this descriptor not implemented!!!\\\")\\n\\n\\t#Return\\n\\treturn observables\",\n \"def cal_topology_feature(self):\\n self.NPL()\\n self.topo_efficiency_cal()\\n self.efficiency_cal()\\n self.cluster_cal()\\n self.topo_diameter()\\n self.spatial_diameter()\",\n \"def main(seed, numpoints, dimensions, num_centres, fragments, mode, iterations,\\n epsilon, arity, use_storage):\\n start_time = time.time()\\n\\n # Generate the data\\n fragment_list = []\\n # Prevent infinite loops in case of not-so-smart users\\n points_per_fragment = max(1, numpoints // fragments)\\n\\n for l in range(0, numpoints, points_per_fragment):\\n # Note that the seed is different for each fragment.\\n # This is done to avoid having repeated data.\\n r = min(numpoints, l + points_per_fragment)\\n\\n fragment_list.append(\\n generate_fragment(r - l, dimensions, mode, seed + l, use_storage)\\n )\\n\\n compss_barrier()\\n print(\\\"Generation/Load done\\\")\\n initialization_time = time.time()\\n print(\\\"Starting kmeans\\\")\\n\\n # Run kmeans\\n centres = kmeans_frag(fragments=fragment_list,\\n dimensions=dimensions,\\n num_centres=num_centres,\\n iterations=iterations,\\n seed=seed,\\n epsilon=epsilon,\\n arity=arity)\\n compss_barrier()\\n print(\\\"Ending kmeans\\\")\\n kmeans_time = time.time()\\n\\n # Run again kmeans (system cache will be filled)\\n print(\\\"Second kmeans\\\")\\n centres = kmeans_frag(fragments=fragment_list,\\n dimensions=dimensions,\\n num_centres=num_centres,\\n iterations=iterations,\\n seed=seed,\\n epsilon=epsilon,\\n arity=arity)\\n compss_barrier()\\n print(\\\"Ending second kmeans\\\")\\n kmeans_2nd = time.time()\\n\\n print(\\\"-----------------------------------------\\\")\\n print(\\\"-------------- RESULTS ------------------\\\")\\n print(\\\"-----------------------------------------\\\")\\n print(\\\"Initialization time: %f\\\" % (initialization_time - start_time))\\n print(\\\"Kmeans time: %f\\\" % (kmeans_time - initialization_time))\\n print(\\\"Kmeans 2nd round time: %f\\\" % (kmeans_2nd - kmeans_time))\\n print(\\\"Total time: %f\\\" % (kmeans_2nd - start_time))\\n print(\\\"-----------------------------------------\\\")\\n centres = compss_wait_on(centres)\\n print(\\\"CENTRES:\\\")\\n print(centres)\\n print(\\\"-----------------------------------------\\\")\",\n \"def evaluate():\\n global dictionary, wv\\n count = 0\\n # To save the scores by distance and similarity\\n scores = np.zeros(6)\\n similar = np.zeros(6)\\n itr = len(dictionary)\\n logging.info('running evaluation for {0} samples'.format(itr))\\n for key in dictionary:\\n progress = (count / itr) * 100\\n d = dictionary[key].split('resource/')\\n d = [idx.split()[0].translate(table).lower() for idx in d[1:]]\\n try:\\n r = np.array(list(map(lambda x: wv.get_vector(x), d)),\\n dtype=np.float32)\\n except KeyError:\\n itr -= 1\\n continue\\n if np.any(np.isnan(r)):\\n itr -= 1\\n continue\\n else:\\n if r.ndim == 2:\\n try:\\n # Mean of vector containing all word vectors\\n # obtained from abstract.\\n r = r.mean(axis=0).reshape(1, -1)\\n \\n # Obtain the vectors for the entity\\n mean_vec = mean_encoder(dictionary[key])\\n mean_vec = mean_vec.reshape(1, -1) / norm(mean_vec)\\n mean_dist_vec = distance_encoder(dictionary[key])\\n mean_dist_vec = mean_dist_vec.reshape(1, -1)\\n mean_dist_vec = mean_dist_vec / norm(mean_dist_vec)\\n title_vec = title_mean(key)\\n title_vec = title_vec.reshape(1, -1) / norm(title_vec)\\n abstract_vec = abstract_encoder(key)\\n abstract_vec = abstract_vec.reshape(1, -1)\\n abstract_vec = abstract_vec / norm(abstract_vec)\\n random_vec = np.random.randn(100).reshape(1, -1)\\n zero_vec = np.zeros(100).reshape(1, -1)\\n \\n # Score the entity vectors\\n scores[0] += norm(r - mean_vec)\\n scores[1] += norm(r - mean_dist_vec)\\n scores[2] += norm(r - title_vec)\\n scores[3] += norm(r - abstract_vec)\\n scores[4] += norm(r - random_vec)\\n scores[5] += norm(r - zero_vec)\\n similar[0] += cosine_similarity(r, mean_vec)\\n similar[1] += cosine_similarity(r, mean_dist_vec)\\n similar[2] += cosine_similarity(r, title_vec)\\n similar[3] += cosine_similarity(r, abstract_vec)\\n similar[4] += cosine_similarity(r, random_vec)\\n similar[5] += cosine_similarity(r, zero_vec)\\n count += 1\\n print(count, end='\\\\r')\\n except (ValueError, KeyError) as _:\\n itr -= 1\\n continue\\n else:\\n itr -= 1\\n continue\\n # Normalize the scores to get a better\\n # comparison against the baselines.\\n scores = scores / norm(scores)\\n similar = similar / norm(similar)\\n print_summary(scores, similar)\",\n \"def evaluate_clusters(self, cluster_formulas, value='weighted_sum'):\\n num_elems = len(self.labels)\\n total_val = {}\\n num_cl = len(cluster_formulas)\\n clustered_points_num = 0\\n print(\\\"\\\\n\\\\n\\\")\\n print(\\\"Sufficiently big clusters: {}\\\".format(num_cl))\\n for c, formula, val in cluster_formulas:\\n c_size = len([l for l in self.labels if l == c])\\n clustered_points_num += c_size\\n\\n if value == 'weighted_sum':\\n total_val[c] = val * c_size / num_elems\\n elif value == 'sum':\\n total_val[c] = val * 1\\n\\n clust_val = sum(total_val.values())\\n self.clustering_value = total_val\\n print(\\\"Value of clustering: {}\\\".format(clust_val))\\n return clust_val\",\n \"def cluster_life_expectancy() -> Dict:\\n return dict(model=None, score=None, clusters=None)\",\n \"def _prepare_algorithms(\\n self, initial_model: TModel, initial_graph: NNCFGraph, combinations: Dict[CombinationKey, Combination]\\n ) -> None:\\n for combination_key, combination in combinations.items():\\n kwargs = apply_combination(self._init_params, combination)\\n self._algorithms[combination_key] = self._algorithm_cls(**kwargs)\\n\\n # Collect required statistics for created algorithms\\n stats_aggregator = StatisticsAggregatorFactory.create(initial_model, self._calibration_dataset)\\n for algorithm in self._algorithms.values():\\n statistic_points = algorithm.get_statistic_points(initial_model, initial_graph)\\n stats_aggregator.register_statistic_points(statistic_points)\\n stats_aggregator.collect_statistics(initial_model, initial_graph)\\n self._statistic_points = stats_aggregator.statistic_points\",\n \"def _compute_cluster_averages(self, key=\\\"_scvi_labels\\\"):\\n # find cell label column\\n label_col = self.adata.uns[\\\"_scvi\\\"][\\\"categorical_mappings\\\"][key][\\\"original_key\\\"]\\n\\n # find data slot\\n x_dict = self.adata.uns[\\\"_scvi\\\"][\\\"data_registry\\\"][\\\"X\\\"]\\n if x_dict[\\\"attr_name\\\"] == \\\"X\\\":\\n use_raw = False\\n else:\\n use_raw = True\\n if x_dict[\\\"attr_name\\\"] == \\\"layers\\\":\\n layer = x_dict[\\\"attr_key\\\"]\\n else:\\n layer = None\\n\\n # compute mean expression of each gene in each cluster/batch\\n aver = compute_cluster_averages(self.adata, labels=label_col, use_raw=use_raw, layer=layer)\\n\\n return aver\",\n \"def load_cluster_accuracies():\\n accuracies = morphs.utils.load._pickle(morphs.paths.ACCURACIES_PKL)\\n cluster_accuracies = {\\n block_path: accuracies[block_path]\\n .groupby(\\\"cluster\\\")\\n .agg(np.mean)\\n .sort_values(\\\"accuracy\\\")\\n for block_path in accuracies\\n }\\n return accuracies, cluster_accuracies\",\n \"def schedule_algorithm(self, algorithm_type):\\n\\n algorithm_data = self.clustering_parameters[\\\"algorithms\\\"][algorithm_type]\\n\\n # The algorithm we are going to use\\n algorithm = self.build_algorithm(algorithm_type)\\n\\n # If not parameters were given we have to get the better ones\\n clusterings = []\\n\\n auto_parameter_generation = True if not \\\"parameters\\\" in algorithm_data else False\\n\\n if auto_parameter_generation:\\n print \\\"Generating params for\\\", algorithm_type\\n algorithm_run_params, clusterings = self.parameters_generator.get_parameters_for_type(algorithm_type)\\n else:\\n # A list with all the parameters for diverse runs\\n algorithm_run_params = algorithm_data[\\\"parameters\\\"]\\n\\n clusterings_info = self.generate_clustering_info(algorithm_type, algorithm_run_params, clusterings)\\n\\n # Sometimes getting the best parameters imply getting the clusterings themselves\\n if clusterings == []:\\n for clustering_id in clusterings_info:\\n one_clustering_info = clusterings_info[clustering_id]\\n self.scheduler.add_task( task_name = clustering_id,\\n description = \\\"Generation of clustering with %s algorithm and id %s\\\"%(\\n one_clustering_info[\\\"type\\\"],\\n clustering_id\\n ),\\n target_function = run_algorithm,\\n function_kwargs = {\\n \\\"algorithm\\\":algorithm,\\n \\\"clustering_id\\\":clustering_id,\\n \\\"algorithm_kwargs\\\":one_clustering_info[\\\"parameters\\\"]\\n },\\n dependencies = {})\\n return clusterings_info\",\n \"def compute_performance_analysis(self, G, I, thresholds=0.01):\\r\\n FAR = self.compute_FAR(I, thresholds)\\r\\n FRR = self.compute_FRR(G, thresholds)\\r\\n CRR = self.compute_CRR(FAR)\\r\\n CAR = self.compute_CAR(FRR)\\r\\n EER = self.compute_EER(FAR, FRR)\\r\\n AUC = self.compute_AUC(FAR, CAR)\\r\\n return FAR, FRR, CRR, CAR, EER, AUC\",\n \"def compute_metrics(self, results: list) -> dict:\",\n \"def test_optimalk(parallel_backend, n_jobs, n_clusters):\\n import numpy as np\\n from sklearn.datasets.samples_generator import make_blobs\\n from gap_statistic import OptimalK\\n\\n # Create data\\n X, y = make_blobs(n_samples=int(1e3), n_features=2, centers=3)\\n\\n for algo in ['kmeans', 'kmeans2', 'skl-kmeans', 'sph-kmeans']:\\n # Create optimalK instance\\n optimalK = OptimalK(parallel_backend=parallel_backend, n_jobs=n_jobs, algo=algo)\\n\\n suggested_clusters = optimalK(X, n_refs=3, cluster_array=np.arange(1, 10))\\n\\n assert np.allclose(suggested_clusters, n_clusters, 2), \\\\\\n ('Correct clusters is {}, OptimalK suggested {}'.format(n_clusters, suggested_clusters))\",\n \"def benchmark(self):\\n nsites = []\\n for m in self.methods:\\n for name, structure in self.test_structures.items():\\n cns = []\\n if self.unique_sites:\\n es = SpacegroupAnalyzer(structure).get_symmetrized_structure().equivalent_sites\\n sites = [structure.index(x[0]) for x in es]\\n else:\\n sites = range(len(structure))\\n\\n for key, val in self.hi.items():\\n if name == key:\\n for j in sites:\\n if isinstance(m, NearNeighbors):\\n tmpcn = m.get_cn_dict(structure, j, self.use_weights)\\n else:\\n tmpcn = m.compute(structure, j)\\n if tmpcn == \\\"null\\\":\\n continue\\n if self.nround:\\n self._roundcns(tmpcn, self.nround)\\n cns.append((structure[j].species_string, tmpcn))\\n if self.cation_anion:\\n for mat, cat in self.cations.items():\\n if (name == mat) and cat:\\n cns = self._popel(cns, cat)\\n elif self.anion_cation:\\n for mat, an in self.anions.items():\\n if name == mat:\\n cns = self._popel(cns, an)\\n m._cns[name] = cns\\n nsites.append(len(cns))\\n self.nsites = max(nsites)\",\n \"def plot_metric_results():\\n from run_metric_comparison_experiments import (\\n PIVECTOR_TEMPLATE,\\n PIVECTOR_DISTANCE_MATRIX_TEMPLATE,\\n DISCRIMINATOR_DISTANCE_MATRIX_TEMPLATE,\\n GAUSSIAN_DISTANCE_MATRIX_TEMPLATE,\\n ENCODER_DISTANCE_MATRIX_TEMPLATE,\\n DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE,\\n NUM_TRAJECTORIES,\\n NUM_COMPONENTS,\\n NUM_REPETITIONS,\\n REWARD_SCALES,\\n ENVS\\n )\\n\\n # Path-templates to each distance matrix to compare\\n # BC = Behavioural Characteristication\\n BC_DISTANCE_MATRIX_TEMPLATES = [\\n PIVECTOR_DISTANCE_MATRIX_TEMPLATE,\\n GAUSSIAN_DISTANCE_MATRIX_TEMPLATE,\\n DISCRIMINATOR_DISTANCE_MATRIX_TEMPLATE,\\n ENCODER_DISTANCE_MATRIX_TEMPLATE,\\n DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE\\n ]\\n\\n BC_LEGEND_NAMES = [\\n \\\"Supervector\\\",\\n \\\"Gaussian\\\",\\n \\\"Discriminator\\\",\\n \\\"Encoder\\\",\\n \\\"Discretization\\\"\\n ]\\n\\n BC_PLOT_COLORS = [\\n \\\"C0\\\",\\n \\\"C1\\\",\\n \\\"C2\\\",\\n \\\"C3\\\",\\n \\\"C4\\\"\\n ]\\n\\n fig, axs = pyplot.subplots(\\n figsize=[4.8 * 3 * 0.75, 4.8 * 0.75],\\n nrows=1,\\n ncols=3,\\n )\\n\\n def get_policy_names(env):\\n policy_names = glob(PIVECTOR_TEMPLATE.format(env=env, num_traj=\\\"*\\\", num_components=\\\"*\\\", policy_name=\\\"*\\\", repetition_num=\\\"*\\\"))\\n policy_names = [\\\"_\\\".join(os.path.basename(x).split(\\\"_\\\")[-4:-2]) for x in policy_names]\\n policy_names = sorted(list(set(policy_names)))\\n return policy_names\\n\\n # For each different distance measurement\\n for distance_matrix_template, plot_legend_name, plot_color in zip(BC_DISTANCE_MATRIX_TEMPLATES, BC_LEGEND_NAMES, BC_PLOT_COLORS):\\n # These will be NUM_TRAJECTORY length lists\\n average_scores = np.ones((len(NUM_TRAJECTORIES),))\\n std_scores = np.ones((len(NUM_TRAJECTORIES),))\\n for num_traj_idx, num_traj in enumerate(NUM_TRAJECTORIES):\\n # Average over environments, policies and repetitions\\n scores = []\\n for env_i, env in enumerate(ENVS):\\n if \\\"Bipedal\\\" in env and distance_matrix_template == DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE:\\n print(\\\"[Note] Skipping env {} for discretization distances (OOM)\\\".format(env))\\n continue\\n min_reward, max_reward = REWARD_SCALES[env]\\n policy_names = get_policy_names(env)\\n\\n for policy_name in policy_names:\\n for repetition in range(1, NUM_REPETITIONS + 1):\\n # Ugh bit of messing around because I did not think this through...\\n if distance_matrix_template == PIVECTOR_DISTANCE_MATRIX_TEMPLATE:\\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, num_components=NUM_COMPONENTS, policy_name=policy_name, repetition_num=repetition)\\n else:\\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, policy_name=policy_name, repetition_num=repetition)\\n\\n data = np.load(file_path)\\n distance_matrix = data[\\\"distance_matrix\\\"]\\n rewards = data[\\\"average_episodic_rewards\\\"]\\n\\n raveled_reward_distances = np.abs(rewards - rewards[:, None])\\n # Take upper diagonal, skip diagonal\\n raveled_reward_distances = raveled_reward_distances[np.triu_indices(raveled_reward_distances.shape[0], 1)]\\n raveled_distances = distance_matrix[np.triu_indices(distance_matrix.shape[0], 1)]\\n\\n # Score is correlation between the two\\n correlation = np.corrcoef(raveled_distances, raveled_reward_distances)[0, 1]\\n scores.append(correlation)\\n\\n scores = np.array(scores)\\n average_score = np.mean(scores)\\n std_score = np.std(scores)\\n average_scores[num_traj_idx] = average_score\\n std_scores[num_traj_idx] = std_score\\n ax = axs[0]\\n ax.plot(NUM_TRAJECTORIES, average_scores, c=plot_color, label=plot_legend_name)\\n ax.scatter(NUM_TRAJECTORIES, average_scores, c=plot_color)\\n #ax.fill_between(\\n # NUM_TRAJECTORIES,\\n # average_scores - std_scores,\\n # average_scores + std_scores,\\n # alpha=0.2,\\n # color=plot_color,\\n # edgecolor=\\\"none\\\",\\n # linewidth=0.0\\n #)\\n ax.set_xticks(NUM_TRAJECTORIES)\\n ax.tick_params(axis='both', which='both', labelsize=\\\"x-large\\\")\\n ax.set_ylabel(\\\"Correlation with return-distances\\\", fontsize=\\\"x-large\\\")\\n ax.set_xlabel(\\\"Number of trajectories\\\", fontsize=\\\"x-large\\\")\\n ax.grid(alpha=0.2)\\n\\n # Amount of error to \\\"ground truth\\\" result,\\n # where \\\"ground truth\\\" is one of the results with 100 trajectories of data.\\n # Because of wonkyness of this, store list [#num-traj] of lists,\\n # each storing results for that num-traj run\\n per_trajectory_relative_errors = [[] for i in NUM_TRAJECTORIES]\\n for env in ENVS:\\n if \\\"Bipedal\\\" in env and distance_matrix_template == DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE:\\n print(\\\"[Note] Skipping env {} for discretization distances (OOM)\\\".format(env))\\n continue\\n policy_names = get_policy_names(env)\\n for policy_name in policy_names:\\n # The \\\"ground truth\\\" distances, will be filled with first\\n # result with 100 trajectories.\\n anchor_distance = None\\n for traj_i, num_traj in enumerate(NUM_TRAJECTORIES):\\n for repetition in range(1, NUM_REPETITIONS + 1):\\n if distance_matrix_template == PIVECTOR_DISTANCE_MATRIX_TEMPLATE:\\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, num_components=NUM_COMPONENTS, policy_name=policy_name, repetition_num=repetition)\\n else:\\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, policy_name=policy_name, repetition_num=repetition)\\n distance_matrix = np.load(file_path)[\\\"distance_matrix\\\"]\\n # Normalize to [0, 1]\\n distance_matrix = (distance_matrix - distance_matrix.min()) / (distance_matrix.max() - distance_matrix.min())\\n # Get only upper triangle as distance matrix is symmetric. Exlude diagonal\\n raveled_distances = distance_matrix[np.triu_indices(distance_matrix.shape[0], 1)]\\n # Check if we use this as the zero-point or compute relative error to\\n if anchor_distance is None:\\n assert num_traj == 100\\n anchor_distance = raveled_distances\\n else:\\n per_trajectory_relative_errors[traj_i].append(\\n np.mean(np.abs(raveled_distances - anchor_distance) / np.abs(anchor_distance))\\n )\\n # Lists are not of equal length, so can not just change into an array\\n mean_average_errors = np.array([np.mean(np.array(results) * 100) for results in per_trajectory_relative_errors])\\n std_average_errors = np.array([np.std(np.array(results) * 100) for results in per_trajectory_relative_errors])\\n ax = axs[1]\\n ax.plot(NUM_TRAJECTORIES, mean_average_errors, c=plot_color, label=plot_legend_name)\\n ax.scatter(NUM_TRAJECTORIES, mean_average_errors, c=plot_color)\\n #ax.fill_between(\\n # NUM_TRAJECTORIES,\\n # mean_average_errors - std_average_errors,\\n # mean_average_errors + std_average_errors,\\n # alpha=0.2,\\n # color=plot_color,\\n # edgecolor=\\\"none\\\",\\n # linewidth=0.0\\n #)\\n ax.set_xticks(NUM_TRAJECTORIES)\\n ax.tick_params(axis='both', which='both', labelsize=\\\"x-large\\\")\\n ax.set_ylabel(\\\"Relative error to ground truth (%)\\\", fontsize=\\\"x-large\\\")\\n ax.set_xlabel(\\\"Number of trajectories\\\", fontsize=\\\"x-large\\\")\\n ax.grid(alpha=0.2)\\n\\n # Variation between results\\n cv_means = np.ones((len(NUM_TRAJECTORIES,)))\\n cv_stds = np.ones((len(NUM_TRAJECTORIES,)))\\n for traj_i, num_traj in enumerate(NUM_TRAJECTORIES):\\n traj_averaged_cvs = []\\n for env in ENVS:\\n if \\\"Bipedal\\\" in env and distance_matrix_template == DISCRETIZATION_DISTANCE_MATRIX_TEMPLATE:\\n print(\\\"[Note] Skipping env {} for discretization distances (OOM)\\\".format(env))\\n continue\\n policy_names = get_policy_names(env)\\n for policy_name in policy_names:\\n # Compute std over repetitions\\n distances = []\\n for repetition in range(1, NUM_REPETITIONS + 1):\\n if distance_matrix_template == PIVECTOR_DISTANCE_MATRIX_TEMPLATE:\\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, num_components=NUM_COMPONENTS, policy_name=policy_name, repetition_num=repetition)\\n else:\\n file_path = distance_matrix_template.format(env=env, num_traj=num_traj, policy_name=policy_name, repetition_num=repetition)\\n\\n distance_matrix = np.load(file_path)[\\\"distance_matrix\\\"]\\n # Normalize to [0, 1]\\n distance_matrix = (distance_matrix - distance_matrix.min()) / (distance_matrix.max() - distance_matrix.min())\\n # Get only upper triangle as distance matrix is symmetric. Exlude diagonal\\n raveled_distances = distance_matrix[np.triu_indices(distance_matrix.shape[0], 1)]\\n distances.append(raveled_distances)\\n distances = np.stack(distances)\\n # Coefficient of variance (std / mean)\\n average_cv = np.mean(np.std(distances, axis=0) / np.mean(distances, axis=0))\\n traj_averaged_cvs.append(average_cv)\\n traj_averaged_cvs = np.array(traj_averaged_cvs)\\n cv_means[traj_i] = np.mean(traj_averaged_cvs)\\n cv_stds[traj_i] = np.std(traj_averaged_cvs)\\n\\n ax = axs[2]\\n ax.plot(NUM_TRAJECTORIES, cv_means, c=plot_color, label=plot_legend_name)\\n ax.scatter(NUM_TRAJECTORIES, cv_means, c=plot_color)\\n #ax.fill_between(\\n # NUM_TRAJECTORIES,\\n # cv_means - cv_stds,\\n # cv_means + cv_stds,\\n # alpha=0.2,\\n # color=plot_color,\\n # edgecolor=\\\"none\\\",\\n # linewidth=0.0\\n #)\\n ax.set_xticks(NUM_TRAJECTORIES)\\n ax.tick_params(axis='both', which='both', labelsize=\\\"x-large\\\")\\n ax.set_ylabel(\\\"Coefficient of variance $\\\\\\\\sigma/\\\\\\\\mu$\\\", fontsize=\\\"x-large\\\")\\n ax.set_xlabel(\\\"Number of trajectories\\\", fontsize=\\\"x-large\\\")\\n ax.grid(alpha=0.2)\\n\\n axs[1].legend(prop={\\\"size\\\": \\\"large\\\"})\\n pyplot.tight_layout()\\n pyplot.savefig(\\\"figures/metric_comparison.pdf\\\", bbox_inches=\\\"tight\\\", pad_inches=0.0)\",\n \"def run(self):\\n # load_data\\n layers = self.load_all_data() # list of tuples (file_name, feature_matrix)\\n\\n # check variable types\\n if len(self.method) == 1:\\n self.method = [self.method[0]] * len(layers)\\n elif len(layers) != len(self.method):\\n raise ValueError(\\\"Number of matrices extracted from input files and number of similarity methods \\\" +\\n \\\"does not correspond\\\")\\n\\n # check missing value parameter\\n if len(self.missing) == 1:\\n self.logger.info(\\\"#Setting all 'missing' parameters to {}\\\".format(self.missing[0]))\\n self.missing = [self.missing[0]] * len(layers)\\n elif len(layers) != len(self.missing):\\n raise ValueError(\\\"Number of matrices extracted from input files and number of given missing parameters \\\" +\\n \\\"does not correspond\\\")\\n\\n # extract sample names\\n all_samples = set()\\n for layer_data in layers:\\n all_samples = all_samples.union({name for name in layer_data[1].columns})\\n self.logger.info(\\\"#Total number of unique samples: {}\\\".format(len(all_samples)))\\n\\n out_arrays = {}\\n adj_matrices = []\\n\\n # create adjacency matrices\\n for i in range(len(layers)):\\n self.logger.info(\\\"#Layer: {}\\\".format(i))\\n layer_data = layers[i][1]\\n\\n # add missing samples layer\\n samples = {name for name in layer_data.columns}\\n for name in all_samples - samples:\\n layer_data[name] = np.nan\\n\\n # sort data frame by sample names\\n layer_data.sort_index(axis=1, inplace=True)\\n\\n # extract feature matrices\\n f = layer_data.values.T\\n self.logger.info(\\\"Feature matrix: ({} samples x {} features)\\\".format(f.shape[0], f.shape[1]))\\n\\n # check if feature matrix values are correct\\n ncat = check_categories(f)\\n if ncat != [0, 1]:\\n standardized = is_standardized(f, axis=0, atol=self.atol)\\n if not standardized[0]:\\n raise ValueError(\\\"Incorrect values in feature matrix. Mean of features in \\\" +\\n \\\"({},{}) \\\".format(round(standardized[1][0], 3), round(standardized[1][1], 3)) +\\n \\\"range. Standard deviation of features in \\\" +\\n \\\"({}, {}) \\\".format(round(standardized[2][0], 3), round(standardized[2][1], 3)) +\\n \\\"range. Please, supply either binary dataset \\\" +\\n \\\"(0 or 1 feature values) or continuous values standardized feature-wise. \\\" +\\n \\\"Alternatively for almost standardized continuous data, \\\" +\\n \\\"increase '-atol' parameter value (currently {}).\\\".format(self.atol))\\n else:\\n self.logger.debug(\\\"Data is correctly standardized\\\")\\n else:\\n self.logger.debug(\\\"Found two unique categories in data: [0, 1]\\\")\\n if self.method[i] != 'cosine':\\n self.logger.info(\\\"Using '{}' similarity for [0, 1] data. \\\".format(self.method[i]) +\\n \\\"Suggested better measure: cosine similarity.\\\")\\n\\n # create adjacency matrix\\n a = feature_to_adjacency(f, missing=self.missing[i], method=self.method[i], n=self.k, alpha=self.alpha)\\n self.logger.info('Adjacency matrix {} created [similarity method: {}]'.format(a.shape, self.method[i]))\\n\\n # plot adjacency matrix\\n plot_path = self.plot_base + \\\"_\\\" + str(i) + \\\".png\\\" if self.plot else self.plot_base\\n plot_heatmap_seaborn(a, title=\\\"Layer {} (source:{})\\\".format(i, layers[i][0]), file_path=plot_path)\\n if self.plot:\\n self.logger.info(\\\"Adjacency matrix plot saved to {}\\\".format(plot_path))\\n\\n # add matrices to output arrays\\n out_arrays[str(i)] = a\\n adj_matrices.append(a)\\n out_arrays[\\\"f\\\" + str(i)] = f\\n\\n # check if there are samples not accessible in any layer\\n missing_samples = []\\n for a in adj_matrices:\\n missing_samples += [i for i in range(a.shape[1]) if np.all(np.isnan(a[:, i]))]\\n\\n samples_to_drop = [sample for sample, val in Counter(missing_samples).items() if val == len(adj_matrices)]\\n if samples_to_drop:\\n # drop inaccessible samples\\n self.logger.info(\\\"Found samples inaccessible in every layer of graph. \\\" +\\n \\\"Try changing '-missing' parameter or inspect your data \\\")\\n sample_names = np.array(sorted(list(all_samples)))[np.array(samples_to_drop)]\\n self.logger.info(\\\"Dropped samples: {}\\\".format(list(sample_names)))\\n updated_out_arrays = {}\\n selector = np.array([x for x in range(len(all_samples)) if x not in samples_to_drop])\\n for i in range(len(out_arrays.keys())):\\n if str(i) not in out_arrays.keys():\\n break\\n updated_out_arrays[str(i)] = out_arrays[str(i)][selector[:, None], selector]\\n updated_out_arrays[\\\"f\\\" + str(i)] = out_arrays[\\\"f\\\" + str(i)][selector, :]\\n\\n # create output file\\n updated_out_arrays[\\\"samples\\\"] = np.array(sorted(list(all_samples)))[selector]\\n save_arrays_to_npz(data=updated_out_arrays, file_path=self.outfile)\\n\\n else:\\n # create output file\\n out_arrays[\\\"samples\\\"] = np.array(sorted(list(all_samples)))\\n save_arrays_to_npz(data=out_arrays, file_path=self.outfile)\\n\\n self.logger.info(\\\"#Output file {} created\\\".format(self.outfile))\",\n \"def get_feature_statistics(results):\\n to_be_deleted = []\\n\\n for result in results:\\n if len(result.subset) != 6:\\n to_be_deleted.append(result)\\n\\n length = len(results)\\n feature_labels = datapoint_features\\n statistics = {}\\n\\n for label in feature_labels:\\n result_with = metrics.filter_results(results, features=[label])\\n result_without = metrics.filter_results(results, without_features=[label])\\n\\n with_length = len(result_with)\\n without_length = len(result_without)\\n prevalence = with_length / length\\n\\n if prevalence != 0:\\n avg_f1_dos = math.fsum([result.metrics['dos'].f1 for result in result_with]) / with_length\\n avg_f1_fuzzy = math.fsum([result.metrics['fuzzy'].f1 for result in result_with]) / with_length\\n avg_f1_imp = math.fsum([result.metrics['impersonation'].f1 for result in result_with]) / with_length\\n else:\\n avg_f1_dos = 0\\n avg_f1_fuzzy = 0\\n avg_f1_imp = 0\\n\\n avg_f1_without_dos = math.fsum([result.metrics['dos'].f1 for result in result_without]) / without_length\\n avg_f1_without_fuzzy = math.fsum([result.metrics['fuzzy'].f1 for result in result_without]) / without_length\\n avg_f1_without_imp = math.fsum([result.metrics['impersonation'].f1 for result in result_without]) / without_length\\n avg_f1_diff_dos = avg_f1_without_dos - avg_f1_dos\\n avg_f1_diff_fuzzy = avg_f1_without_fuzzy - avg_f1_fuzzy\\n avg_f1_diff_imp = avg_f1_without_imp - avg_f1_imp\\n\\n statistics[label] = [prevalence, avg_f1_diff_dos, avg_f1_diff_fuzzy, avg_f1_diff_imp]\\n\\n return statistics\",\n \"def analyse_algorithms(R, u_t, inverse_transform, true_weight_vect, algo_list, equation, preconditioner):\\n\\n # Generate the model list for each sparse regression algorithm\\n algo_model_list_list = []\\n for algo_index, algo in enumerate(algo_list):\\n model_list = generate_models(R, u_t, inverse_transform, algo)\\n algo_model_list_list.append(model_list)\\n\\n # set up plot\\n symbol_list = ['v', 's', 'o', '+', '*', 'D']\\n color_list = [(162 / 256., 173 / 256., 0., 0.9), (156 / 256., 157 / 256., 159 / 256., 0.8),\\n (0., 101 / 256., 189 / 256., 1.), (227 / 256., 114 / 256., 34 / 256., 0.9)]\\n fig, ax = plt.subplots(figsize=(1.8 * 2.6, 1.8 * 1.95))\\n\\n # iterate all models of all algorithms and plot the summaries\\n for algo_index, algo in enumerate(algo_list):\\n model_list = algo_model_list_list[algo_index]\\n for i_model, model in enumerate(model_list):\\n set_model_correctness_and_error(model, true_weight_vect) # calculate absolute and relative error\\n # plot model properties\\n ax.semilogy(model.terms, model.mean_rel_err, marker=symbol_list[algo_index], markerfacecolor='none',\\n linestyle='None', color=color_list[algo_index], label=algo if i_model == 0 else \\\"\\\")\\n\\n # finish plot\\n ax.plot((-1., 10.), (1.5, 1.5), color='k')\\n # xlim needs to be adjusted with respect to the maximum number of correct term in the model\\n ax.set(ylim=[1.e-9, 75.], xlim=[0.5, 6.5], xlabel='Number of Terms', ylabel='MRE')\\n ax.legend(loc=4)\\n ax.set_yticks(ax.get_yticks()[:-3])\\n ax.set_xticks(np.arange(1, 7, 1))\\n plt.savefig('Regression_accuracy_comparison_' + str(equation) + '_' + preconditioner + '_test.png')\\n plt.savefig('Regression_accuracy_comparison_' + str(equation) + '_' + preconditioner + '_test.pgf')\",\n \"def test_query_algorithms_101Algorithms_(self):\\n right_list = []\\n create_test_algorithm_list(right_list, 101)\\n documents = []\\n create_test_documents_list(right_list, documents, 101)\\n index = search.Index(name=search_algorithm._INDEX_STRING)\\n index.put(documents)\\n result = search_algorithm.query_algorithms(index)\\n self.assertEqual(101, len(result), msg='Wrong number of algorithms')\\n self.assertItemsEqual(right_list, result, msg='Discrepancy in returned algorithms')\",\n \"def main():\\n\\n file_name_base = \\\"./lab-record/result/fairness/\\\"\\n scenarios = ['lan', 'wan1', 'wan2']\\n scenario = scenarios[2]\\n\\n algorithms = [\\\"bbr\\\", \\\"scalable\\\", \\\"bic\\\", \\\"highspeed\\\", \\\"htcp\\\", \\\"hybla\\\",\\n \\\"illinois\\\", \\\"vegas\\\", \\\"yeah\\\"]\\n names = [\\\"BBR\\\", \\\"Scalable\\\", \\\"BIC\\\", \\\"High Speed\\\",\\n \\\"H-TCP\\\", \\\"Hybla\\\", \\\"Illinois\\\", \\\"Vegas\\\", \\\"YeAH\\\"]\\n\\n test_types = [\\\"vs_reno\\\", \\\"vs_cubic\\\", \\\"vs_itself\\\"]\\n\\n fsize = 36\\n \\n index_reno = []\\n index_cubic = []\\n index_itself = []\\n\\n data = []\\n \\n print 'Loadint statistics for ' + file_name_base + '/' + scenario\\n\\n for algorithm in algorithms:\\n for test in test_types:\\n path_base = file_name_base + \\\"/\\\" + scenario + \\\"/\\\" + test + \\\"/\\\" + \\\\\\n algorithm + \\\"/\\\"\\n if test == \\\"vs_itself\\\":\\n exp_name = names[algorithms.index(algorithm)] + \\\"_1\\\"\\n con_name = names[algorithms.index(algorithm)] + \\\"_2\\\"\\n print path_base + exp_name\\n print path_base + con_name\\n exp_filename = \\\"/\\\" + algorithm + \\\"_1.log\\\"\\n con_filename = \\\"/\\\" + algorithm + \\\"_2.log\\\"\\n process(path_base, exp_filename, con_filename, index_itself)\\n if test == \\\"vs_reno\\\":\\n exp_name = names[algorithms.index(algorithm)]\\n con_name = \\\"Reno\\\"\\n print path_base + exp_name\\n print path_base + con_name\\n exp_filename = \\\"/\\\" + algorithm + \\\".log\\\"\\n con_filename = \\\"/reno.log\\\"\\n process(path_base, exp_filename, con_filename, index_reno)\\n if test == \\\"vs_cubic\\\":\\n con_name = \\\"CUBIC\\\"\\n exp_name = names[algorithms.index(algorithm)]\\n print path_base + exp_name\\n print path_base + con_name\\n exp_filename = \\\"/\\\" + algorithm + \\\".log\\\"\\n con_filename = \\\"/cubic.log\\\"\\n process(path_base, exp_filename, con_filename, index_cubic)\\n\\n size = 9\\n x = numpy.arange(size)\\n\\n total_width, n = 1.2, 2.5\\n width = 1.0 / n\\n x = x - (total_width - width) / 2\\n\\n for i in range(0, len(x)):\\n x[i] += 0.5 * i\\n\\n # Exp\\n fig = plt.figure()\\n\\n # Con\\n con_reno = plt.bar(x + 0 * width - 1.2,\\n index_reno,\\n width=width,\\n label='Against Reno',\\n alpha=0.5,\\n color=\\\"darkorange\\\")\\n\\n con_cubic = plt.bar(x + 1 * width - 1.2,\\n index_cubic,\\n width=width,\\n label='Against CUBIC',\\n alpha=0.5,\\n color=\\\"lawngreen\\\")\\n\\n con_itself = plt.bar(x + 2 * width - 1.2,\\n index_itself,\\n width=width,\\n label='Against Another Same CCA',\\n alpha=0.5,\\n color=\\\"dodgerblue\\\")\\n\\n # Index\\n plt.xticks(x + 1.5 * width - 1.2, [\\\"BBR\\\", \\\"Scalable\\\", \\\"BIC\\\", \\\"High Speed\\\",\\n \\\"H-TCP\\\", \\\"Hybla\\\", \\\"Illinois\\\", \\\"Vegas\\\",\\n \\\"YeAH\\\"],\\n fontsize=fsize,\\n rotation=\\\"45\\\")\\n plt.ylabel(\\\"Jain`s Fairness Index\\\", fontsize=fsize)\\n plt.yticks(fontsize=fsize)\\n plt.ylim(0.5, 1.1)\\n\\n ax = plt.subplot(111)\\n ax.legend(bbox_to_anchor=(0., 1.02, 1., .102), loc=3,\\n ncol=3, mode=\\\"expand\\\", borderaxespad=0., fontsize=fsize)\\n\\n plt.subplots_adjust(left=0.07, right=0.98, top=0.9, bottom=0.2)\\n\\n plt.show()\",\n \"def set_algorithm(self, algorithm):\\n self._data_dict[self.ALGO_INFO] = {'module' : algorithm.algo_group.module,\\n 'class' : algorithm.algo_group.classname,\\n 'init_param' : algorithm.algo_group.init_parameter,\\n 'identifier' : algorithm.identifier}\"\n]"},"negative_scores":{"kind":"list like","value":["0.6315484","0.61245906","0.5925279","0.5822709","0.57913584","0.57853943","0.57158273","0.56992424","0.5629585","0.56262213","0.55483156","0.5493547","0.5488877","0.54682064","0.5456372","0.5410733","0.5409758","0.54085684","0.53946304","0.53820395","0.5365618","0.5353488","0.53240466","0.5320415","0.5304393","0.5303199","0.52986354","0.5283749","0.5268433","0.52369326","0.5180255","0.5175428","0.5164062","0.515936","0.51485467","0.5147816","0.5142116","0.5135826","0.51307833","0.51235807","0.5123402","0.5120338","0.51176727","0.5116642","0.5108093","0.51047105","0.50972265","0.5096663","0.5096663","0.50897586","0.5089474","0.5086195","0.5073285","0.5069407","0.5045897","0.50371","0.5032525","0.5024298","0.50012976","0.49893403","0.49816048","0.496002","0.49576274","0.4942733","0.4941863","0.49375358","0.49359924","0.49280685","0.49258095","0.49247968","0.4923402","0.4920409","0.4914313","0.49006045","0.4899087","0.48885742","0.48871896","0.48808146","0.48771632","0.48620665","0.48606378","0.485639","0.4851699","0.48480994","0.48418057","0.4839492","0.48355648","0.48308","0.48281068","0.4818679","0.48169157","0.48157486","0.48147896","0.4811808","0.4810023","0.4807312","0.48026064","0.47996712","0.4797637","0.47930786"],"string":"[\n \"0.6315484\",\n \"0.61245906\",\n \"0.5925279\",\n \"0.5822709\",\n \"0.57913584\",\n \"0.57853943\",\n \"0.57158273\",\n \"0.56992424\",\n \"0.5629585\",\n \"0.56262213\",\n \"0.55483156\",\n \"0.5493547\",\n \"0.5488877\",\n \"0.54682064\",\n \"0.5456372\",\n \"0.5410733\",\n \"0.5409758\",\n \"0.54085684\",\n \"0.53946304\",\n \"0.53820395\",\n \"0.5365618\",\n \"0.5353488\",\n \"0.53240466\",\n \"0.5320415\",\n \"0.5304393\",\n \"0.5303199\",\n \"0.52986354\",\n \"0.5283749\",\n \"0.5268433\",\n \"0.52369326\",\n \"0.5180255\",\n \"0.5175428\",\n \"0.5164062\",\n \"0.515936\",\n \"0.51485467\",\n \"0.5147816\",\n \"0.5142116\",\n \"0.5135826\",\n \"0.51307833\",\n \"0.51235807\",\n \"0.5123402\",\n \"0.5120338\",\n \"0.51176727\",\n \"0.5116642\",\n \"0.5108093\",\n \"0.51047105\",\n \"0.50972265\",\n \"0.5096663\",\n \"0.5096663\",\n \"0.50897586\",\n \"0.5089474\",\n \"0.5086195\",\n \"0.5073285\",\n \"0.5069407\",\n \"0.5045897\",\n \"0.50371\",\n \"0.5032525\",\n \"0.5024298\",\n \"0.50012976\",\n \"0.49893403\",\n \"0.49816048\",\n \"0.496002\",\n \"0.49576274\",\n \"0.4942733\",\n \"0.4941863\",\n \"0.49375358\",\n \"0.49359924\",\n \"0.49280685\",\n \"0.49258095\",\n \"0.49247968\",\n \"0.4923402\",\n \"0.4920409\",\n \"0.4914313\",\n \"0.49006045\",\n \"0.4899087\",\n \"0.48885742\",\n \"0.48871896\",\n \"0.48808146\",\n \"0.48771632\",\n \"0.48620665\",\n \"0.48606378\",\n \"0.485639\",\n \"0.4851699\",\n \"0.48480994\",\n \"0.48418057\",\n \"0.4839492\",\n \"0.48355648\",\n \"0.48308\",\n \"0.48281068\",\n \"0.4818679\",\n \"0.48169157\",\n \"0.48157486\",\n \"0.48147896\",\n \"0.4811808\",\n \"0.4810023\",\n \"0.4807312\",\n \"0.48026064\",\n \"0.47996712\",\n \"0.4797637\",\n \"0.47930786\"\n]"},"document_score":{"kind":"string","value":"0.69420356"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8556,"cells":{"query":{"kind":"string","value":"Calculates a clustering's contingency matrix for each clustering algorithm stored in the list clustering_alg and adds it to the dict."},"document":{"kind":"string","value":"def eval_cluster_contingency(clustering_alg: List, labels_true, sdist):\n for (alg_name, alg_dict) in clustering_alg:\n if \"alg\" in alg_dict:\n clustering = alg_dict[\"alg\"].fit(sdist)\n labels_pred = clustering.labels_\n alg_dict[\"labels\"] = labels_pred\n else:\n labels_pred = alg_dict[\"labels\"]\n\n pred_label_dict, new_labels = normalize_labels(labels_pred)\n\n alg_dict[\"cm\"] = contingency_matrix(labels_true, new_labels)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def generate_clustering_info(self, algorithm_type, clustering_parameters, clusterings = []):\n clustering_info = {}\n for i, running_parameters in enumerate(clustering_parameters):\n\n clustering_id = \"clustering_%04d\"%(self.current_clustering_id)\n self.current_clustering_id += 1\n clustering_info[clustering_id] = {\n \"type\":algorithm_type,\n \"clustering\": None,\n \"parameters\": running_parameters\n }\n\n if clusterings != []:\n clustering_info[clustering_id][\"clustering\"] = clusterings[i]\n\n return clustering_info","def enumerate_clusterings(self):\n\n # Initialize an empty list of clusterings. Each element of the list\n # is a dictionary mapping NOEs to the signatures they are clustered to\n # in a solution. Each clustering is initialize with all uniquely\n # clusterable NOEs as keys mapping to their unique clusters\n\n clusterings = []\n\n while True:\n\n # Run the solver and get a solution back\n\n solution = self.solve()\n\n # If UNSAT, then flush aux clauses from the formula and return\n # all the clusterings we found so far\n\n if not solution:\n self.flush()\n return clusterings\n\n # Iterate over the clustering variables set to true by in the\n # discovered solution. Forbid this clustering from reoccuring and\n # add it to the list of found clusterings\n\n clause = []\n clustering = {}\n for node in self.clustering_variables.keys():\n if len(node.clusters) == 1:\n clustering[node] = list(node.clusters)[0]\n\n for vtype, node, cluster in solution:\n if vtype == Formula.CST_VAR:\n clustering[node] = cluster\n clause.append(-self.clustering_variables[node][cluster])\n\n self.add_clause(clause)\n clusterings.append(clustering)","def matrix_dist(self):\n matrix_dic = {}\n for clus in self.clusters:\n for other_clus in self.clusters:\n if clus.samples[0].s_id > other_clus.samples[0].s_id: # avoid duplicates\n matrix_dic[(clus.samples[0].s_id, other_clus.samples[0].s_id)] = clus.samples[0]\\\n .compute_euclidean_distance(other_clus.samples[0])\n return matrix_dic","def _eval_clustering(self, gen_reviews, clusters, embedding_model, clustering):\n result = []\n preds = self.predict_gen(gen_reviews, embedding_model, clustering)\n\n acc = accuracy_score(np.array(clusters), np.array(preds))\n conf = confusion_matrix(np.array(clusters), np.array(preds))\n\n return acc, conf","def clustering_and_visulization(self):\n centroids, _ = kmeans(self.data_mat, self.k)\n idx, _ = vq(self.data_mat, centroids)\n for i in range(self.k):\n\n self.plot_list.append(self.data_mat[idx == i, 0])\n self.plot_list1.append(self.data_mat[idx == i, 1])\n\n for j in range(self.k):\n plot(self.plot_list[j], self.plot_list1[j], self.color_code[j])\n plot(centroids[:, 0], centroids[:, 1], 'sg', markersize=8)\n show()\n for i in range(self.k):\n self.cluster = self.data_mat[idx == i]\n self.clusterlist.append(self.cluster)\n\n for i in range(len(self.clusterlist)):\n self.clusterdict[i] = self.clusterlist[i]\n print(self.clusterdict)\n\n\n self.indexdict = {}\n for i in self.clusterdict:\n self.indexdict[i] = []\n print(len(self.clusterdict))\n for i in range(len(idx)):\n for j in range(len(self.clusterdict)):\n if (self.clusterdict[j][:] == self.data_mat[i]).any():\n self.indexdict[j].append(i)\n print(\"cluster dict of packs\",self.indexdict)\n\n self.drugdict = {}\n for i in self.clusterdict:\n self.drugdict[i] = []\n self.drug=[]\n for i in range(len(self.indexdict.keys())):\n for j in range(len(self.indexdict[i])):\n self.drugdict[i].append(self.df.iloc[self.indexdict[i][j]].to_dict())\n print(\"drugs dict with their frequencies\",self.drugdict)\n clusterdict_from_df_as_drug_non_O_frequency = {}\n clusterdict_from_as_drugs_only_as_list = {}\n clusterdict_of_non_repeated_drugs ={}\n for i in self.drugdict:\n clusterdict_from_df_as_drug_non_O_frequency[i] = []\n for i in self.drugdict:\n for j in self.drugdict[i]:\n clusterdict_from_df_as_drug_non_O_frequency[i].append({x: y for x, y in j.items() if y != 0})\n print(\"clusterdict_from_df_as_drug_non_O_frequency\", clusterdict_from_df_as_drug_non_O_frequency)\n print('\\n')\n\n for i in self.drugdict:\n clusterdict_from_as_drugs_only_as_list[i] = []\n\n for i in self.drugdict:\n for j in clusterdict_from_df_as_drug_non_O_frequency[i]:\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\n\n print(\"only keys drugs with drugs name\", clusterdict_from_as_drugs_only_as_list)\n print('\\n')\n\n\n for i in self.drugdict:\n clusterdict_of_non_repeated_drugs[i]=list(more_itertools.collapse([list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\n\n\n print(\"only drugs only\", clusterdict_of_non_repeated_drugs)\n\n########################################################################################################################\n try:\n common_drug_list = [x for x in clusterdict_of_non_repeated_drugs[0] if x in clusterdict_of_non_repeated_drugs[1]]\n print('\\n')\n print(\"common drug list\", common_drug_list)\n total_frequency_of_drugs_dict = {}\n for i in self.drugdict:\n total_frequency_of_drugs_dict[i] = []\n\n for drug in common_drug_list:\n\n for cluster_keys in clusterdict_from_df_as_drug_non_O_frequency.keys():\n temp_list = []\n for cluster_values_as_list in clusterdict_from_df_as_drug_non_O_frequency[cluster_keys]:\n try:\n temp_list.append(cluster_values_as_list[str(drug)])\n except KeyError:\n print(\"\\t\")\n total_frequency_of_drugs_dict[cluster_keys].append(np.sum(temp_list))\n print(\"total drugs frequency\",total_frequency_of_drugs_dict)\n total_frequency_of_drugs_dict_with_drugs = {}\n for i in self.drugdict:\n total_frequency_of_drugs_dict_with_drugs[i] = []\n temp_list1 = []\n temp_list2 = []\n for keys in self.drugdict.keys():\n temp_list1.append(clusterdict_of_non_repeated_drugs[keys])\n for keys in self.drugdict.keys():\n temp_list2.append(total_frequency_of_drugs_dict[keys])\n temp_list3 = []\n for i in temp_list1:\n for j in temp_list2:\n temp_list3.append(dict(zip(i,j)))\n temp_list4 = temp_list3[:2]\n print('\\n')\n for keys in self.drugdict:\n total_frequency_of_drugs_dict_with_drugs[keys].append(temp_list4[keys])\n print(\"total frequency with drugs dict\",total_frequency_of_drugs_dict_with_drugs)\n\n final_drugs_in_clusters_dict = {}\n for i in self.drugdict:\n final_drugs_in_clusters_dict[i] = []\n compare_list = []\n for drug in common_drug_list:\n compare_list.append(min(total_frequency_of_drugs_dict_with_drugs[0][0][drug], total_frequency_of_drugs_dict_with_drugs[1][0][drug]))\n print(\"compare list\",compare_list)\n for values in total_frequency_of_drugs_dict_with_drugs.values():\n for key1, value1 in values[0].items():\n if value1 in compare_list:\n\n key2 =values[0].keys()[values[0].values().index(value1)]\n values[0].pop(key2, None)\n\n\n print('final dict with deleted keys', total_frequency_of_drugs_dict_with_drugs)\n\n clusterdict_from_as_drugs_only_as_list = {}\n clusterdict_of_non_repeated_drugs = {}\n\n for i in self.drugdict:\n clusterdict_from_as_drugs_only_as_list[i] = []\n\n for i in self.drugdict:\n for j in total_frequency_of_drugs_dict_with_drugs[i]:\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\n print(\"only keys drugs with drugs name\", clusterdict_from_as_drugs_only_as_list)\n print('\\n')\n\n for i in self.drugdict:\n clusterdict_of_non_repeated_drugs[i] = list(more_itertools.collapse([list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\n print(\"only drugs\",clusterdict_of_non_repeated_drugs)\n\n final_robot_packs_dict = {}\n for i in self.drugdict:\n final_robot_packs_dict[i] = []\n\n winner_drug_dict = {}\n for i in common_drug_list:\n winner_drug_dict[i] = []\n for drug in common_drug_list:\n if drug in clusterdict_of_non_repeated_drugs[0]:\n winner_drug_dict[str(drug)].append(0)\n if drug in clusterdict_of_non_repeated_drugs[1]:\n winner_drug_dict[str(drug)].append(1)\n print(\"winner drug dict\",winner_drug_dict)\n\n for i in self.indexdict:\n print(i)\n for pack in self.indexdict[i]:\n packdict = self.df.iloc[pack].to_dict()\n packdict_non_0 = {x: y for x, y in packdict.items() if y != 0}\n packdict_non_0_key = packdict_non_0.keys()\n for drug in packdict_non_0_key:\n if drug in clusterdict_of_non_repeated_drugs[0]:\n final_robot_packs_dict[0].append(pack)\n elif drug in clusterdict_of_non_repeated_drugs[1]:\n final_robot_packs_dict[1].append(pack)\n\n final_robot_packs_dict[i].append(pack)\n for commondrugs in winner_drug_dict:\n for winnercluster in winner_drug_dict[commondrugs]:\n if winnercluster==0:\n loosercluster =1\n if winnercluster == 1:\n loosercluster = 0\n if commondrugs in packdict_non_0_key and i==loosercluster:\n try:\n final_robot_packs_dict[i].remove(pack)\n final_robot_packs_dict[winnercluster].append(pack)\n except ValueError:\n print('\\t')\n\n for i in self.indexdict:\n final_robot_packs_dict[i] = set(final_robot_packs_dict[i])\n\n print(\"final which pack which robot dict\",final_robot_packs_dict)\n\n except IndexError:\n print(\"No common drugs\")","def cluster(self):\n\t\tself.index[\"cluster\"] = {}\n\n\t\tfor item in self.index[\"items\"]:\n\t\t\tself.index[\"cluster\"][item] = [{\"weight\" : float(len(set(self.index[\"items\"][item]).intersection( set(self.index[\"items\"][id]))))/float(len(self.index[\"items\"][item])) , \"name\" : id, \"authority\" : set(self.index[\"items\"][item]).intersection( set(self.index[\"items\"][id])) } for id in self.index[\"items\"] if id != item and len(set(self.index[\"items\"][item]).intersection( set(self.index[\"items\"][id]))) >= 1]\n\n\t\treturn self.index","def evaluate_clustering_methods(methods):\r\n results = {}\r\n for m in methods:\r\n res = results[m['name']] = {}\r\n prec = 3\r\n res['Adjusted Rand Score'] = round(sklearn.metrics.adjusted_rand_score(m['target'], m['clustering']),prec)\r\n res['Normalized Mutual Information'] = round(sklearn.metrics.normalized_mutual_info_score(m['target'], m['clustering']),prec)\r\n res['Adjusted Mutual Information'] = round(sklearn.metrics.adjusted_mutual_info_score(m['target'], m['clustering']),prec)\r\n return np.transpose(results)","def clustering(distribution, areal_units, classes=None):\n\n # Regroup into classes if specified. Otherwise return categories indicated\n # in the data\n if not classes:\n classes = return_categories(distribution) \n \n ## Get the number of neighbourhoods\n neigh = mb.neighbourhoods(distribution, areal_units, classes)\n num_neigh = {cl: len(neigh[cl]) for cl in classes}\n num_units = {cl: len([a for ne in neigh[cl] for a in ne])\n for cl in classes}\n\n ## Compute clustering values\n clustering = {}\n for cl in classes:\n if num_units[cl] == 0:\n clustering[cl] = float('nan')\n elif num_units[cl] == 1:\n clustering[cl] = 1\n else:\n clustering[cl] = _single_clustering(num_units[cl],\n num_neigh[cl])\n\n clustering[cl] = ((num_neigh[cl] - num_units[cl]) /\n (1 - num_units[cl]))\n return clustering","def get_clustering_algorithm_class(cls):\n return {\n \"spectral\": SpectralClusteringAlgorithm,\n \"dbscan\": DBSCANAlgorithm,\n \"gromos\": GromosAlgorithm,\n \"kmedoids\": KMedoidsAlgorithm,\n \"random\": RandomClusteringAlgorithm,\n \"hierarchical\": HierarchicalClusteringAlgorithm\n }","def cluster_all_features(feature_mat):\n n_dims = feature_mat.shape[1]\n whitened = whiten(feature_mat.transpose())\n all_codebooks = dict()\n for k in range(n_dims, 0, -1):\n centroids, distortion = kmeans(whitened, k)\n all_codebooks[k] = (distortion, centroids)\n\n return all_codebooks","def create_clusters(self):\n ex = 0\n print 'Iter - Purity Gini Index'\n while ex < self.MAX_ITERATION:\n new_clusters = np.zeros(self.centroids.shape)\n distances = euclidean_distances(self.vectors, self.centroids).argmin(axis=1)\n for i in range(self.K):\n indexes = np.argwhere(distances == i)\n data = self.vectors[indexes.transpose()[0]]\n if data.shape[0] > 1:\n new_clusters[i] = (np.sum(data, axis=0) / data.shape[0])\n else:\n new_clusters[i] = np.sum(data, axis=0)\n print ex, '----', self.cal_purity()\n ex += 1\n if np.allclose(self.centroids, new_clusters, atol=self.TOLERANCE):\n break\n self.centroids = new_clusters","def update(self, clusters):\n centroids = {}\n for cluster, coordinates in clusters.iteritems():\n sumLat = 0\n sumLong = 0\n for coordinate in coordinates:\n sumLat += float(coordinate[0])\n sumLong += float(coordinate[1])\n centroids[cluster] = (sumLat/float(len(coordinates)), sumLong/float(len(coordinates)))\n return centroids","def evaulate_clusters(self, pred_dict, model_dir):\n\t\tclustering_dict = {\"Topic\":[], \"Text\":[], \"Keywords\": []}\n\t\tfor cluster_num, sents_list in pred_dict.items():\n\t\t\tprint(\"\\n cluster number : \", cluster_num)\n\t\t\tprint(\"\\n number of sents : \", len(sents_list))\n\t\t\ttfidf_vec = TfidfVectorizer(use_idf=True, sublinear_tf=True, max_df=0.8, max_features=20, ngram_range=(1,5), min_df=1)\n\t\t\tX_tfidf = tfidf_vec.fit_transform(sents_list).toarray()\n\t\t\ttotal_tfidf = tfidf_vec.get_feature_names()\n\t\t\tfor sent in sents_list:\n\t\t\t\tclustering_dict[\"Topic\"].append(cluster_num)\n\t\t\t\tclustering_dict[\"Text\"].append(sent)\n\t\t\t\tclustering_dict[\"Keywords\"].append(\",\".join(total_tfidf))\n\t\t\"\"\" save the clusters to csv file \"\"\"\n\t\tdf_dominant_topic = defaultdict(list) \n\t\tdf_dominant_topic[\"Topic\"] = clustering_dict[\"Topic\"]\n\t\tdf_dominant_topic[\"Text\"] = clustering_dict[\"Text\"]\n\t\tdf_dominant_topic[\"Keywords\"] = clustering_dict[\"Keywords\"]\n\t\tdf_dominant_topic = pd.DataFrame(df_dominant_topic)\n\t\tdf_dominant_topic.to_csv(os.path.join(model_dir, \"cluster_sentence_topic_mapping.csv\"))\n\t\treturn df_dominant_topic","def calc_cc(graph):\n\tclustering_coeffs = {}\n\tfor node in graph.nodes():\n\t\tclustering_coeffs[node] = { \"cc\" : nx.clustering(graph, node)}\n\tnx.set_node_attributes(graph, clustering_coeffs)","def gen_cluster_accuracies():\n accuracies = {}\n with Parallel(n_jobs=morphs.parallel.N_JOBS) as parallel:\n for block_path in morphs.paths.blocks():\n print(block_path)\n spikes = morphs.load.ephys_data(block_path, collapse_endpoints=True)\n\n if len(spikes[\"recording\"].unique()) >= 1:\n template_spikes = spikes[spikes[\"stim_id\"].isin(list(\"abcdefgh\"))]\n assert len(template_spikes) > 0\n cluster_groups = template_spikes.groupby(\"cluster\")\n\n morph_dims = spikes.morph_dim.unique()\n morph_dims = morph_dims[~pd.isnull(morph_dims)]\n morph_dims.sort()\n\n max_num_reps = np.max(\n [\n len(stim_group.groupby(by=[\"recording\", \"stim_presentation\"]))\n for stim_id, stim_group in template_spikes.groupby(\"stim_id\")\n ]\n )\n\n accuracies_list = parallel(\n delayed(cluster_accuracy)(\n cluster, cluster_group, morph_dims, max_num_reps\n )\n for (cluster, cluster_group) in cluster_groups\n )\n\n accuracies[block_path] = pd.concat(accuracies_list)\n\n morphs.paths.PROCESSED_DIR.mkdir(parents=True, exist_ok=True)\n with open(morphs.paths.ACCURACIES_PKL.as_posix(), \"wb\") as f:\n pickle.dump(accuracies, f)","def clustering_and_visulization(self):\n try:\n centroids, _ = kmeans(self.data_mat, self.k)\n except ValueError:\n print(\"The number of clusters is more than the data points\")\n self.idx, _ = vq(self.data_mat, centroids)\n for i in range(self.k):\n\n self.plot_list.append(self.data_mat[self.idx == i, 0])\n self.plot_list1.append(self.data_mat[self.idx == i, 1])\n\n for j in range(self.k):\n plot(self.plot_list[j], self.plot_list1[j], self.color_code[j])\n plot(centroids[:, 0], centroids[:, 1], 'sg', markersize=8)\n show()\n\n for i in range(self.k):\n self.cluster = self.data_mat[self.idx == i]\n self.clusterlist.append(self.cluster)\n print(self.clusterlist)\n for i in range(len(self.clusterlist)):\n self.clusterdict[i] = self.clusterlist[i]\n print(self.clusterdict)\n\n index_dict ={}\n for i in self.clusterdict:\n index_dict[i] = []\n for i in range(len(self.data_mat)):\n for j in range(len(self.clusterdict)):\n if (self.clusterdict[j][:] == self.data_mat[i]).any():\n index_dict[j].append(i)\n print(\"drugs cluster dict\", index_dict)\n\n self.drugsdict = {}\n for i in index_dict:\n self.drugsdict[i] = []\n drugslist = list(self.df.columns.values)\n print(\"drugs list from dataframe\", drugslist)\n\n for i in index_dict:\n self.drugsdict[i] = [drugslist[index] for index in index_dict[i]]\n\n print(\"drugs cluster dict\", self.drugsdict)\n########################################################################################################################\n clusterdict_from_df_as_drug_frequency = {}\n clusterdict_from_df_as_drug_non_O_frequency = {}\n\n print('\\n')\n\n for i in range(len(self.df)):\n clusterdict_from_df_as_drug_frequency[i] = []\n\n for i in range(len(self.df)):\n clusterdict_from_df_as_drug_frequency[i].append(self.df.iloc[i].to_dict()) #\n print(\"packs in dict form of drugs frequency\", clusterdict_from_df_as_drug_frequency)\n\n for i in range(len(self.df)):\n clusterdict_from_df_as_drug_non_O_frequency[i] = []\n\n for i in range(len(self.df)):\n for j in clusterdict_from_df_as_drug_frequency[i]:\n clusterdict_from_df_as_drug_non_O_frequency[i].append({x: y for x, y in j.items() if y != 0})\n print(\"clusterdict_from_df_as_drug_non_O_frequency\", clusterdict_from_df_as_drug_non_O_frequency)\n print('\\n')\n clusterdict_from_as_drugs_only_as_list = {}\n clusterdict_of_non_repeated_drugs = {}\n for i in range(len(self.df)):\n clusterdict_from_as_drugs_only_as_list[i] = []\n\n for i in range(len(self.df)):\n for j in clusterdict_from_df_as_drug_non_O_frequency[i]:\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\n\n print(\"only keys drugs with drugs name\", clusterdict_from_as_drugs_only_as_list)\n print('\\n')\n\n for i in range(len(self.df)):\n clusterdict_of_non_repeated_drugs[i] = list(more_itertools.collapse(\n [list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\n\n print(\"only drugs only\", clusterdict_of_non_repeated_drugs)\n\n########################################################################################################################\n robot_for_packs_dict = {}\n for i in range(len(self.df)):\n robot_for_packs_dict[i] = []\n\n # for i in range(len(self.df)):\n for i in range(len(self.df)):\n for j in clusterdict_of_non_repeated_drugs[i]:\n if j in self.drugsdict[0]:\n robot_for_packs_dict[i].append(0)\n elif j in self.drugsdict[1]:\n robot_for_packs_dict[i].append(1)\n for i in range(len(self.df)):\n robot_for_packs_dict[i] = set(robot_for_packs_dict[i])\n\n for i in range(len(self.df)):\n robot_for_packs_dict[i] = list(more_itertools.collapse(robot_for_packs_dict[i]))\n print('\\n')\n print(\"clusterdict_of_non_repeated_drugs\", robot_for_packs_dict)","def cluster_classification(weblog,classification_column_transaction,\\\n classification_column_diversity, session_data_threshold, cluster_type, classification_wanted_transaction, verbose = False):\n if verbose== True:\n start_time = timelib.time()\n print(\"\\n * Computing cluster matrices ...\") \n browsing_matrix = {}\n diversifying_matrix = {}\n # Selecting sessions from each cluster\n for cluster_id in session_data_threshold[cluster_type].unique():\n sessions_cluster = session_data_threshold[session_data_threshold[cluster_type]==cluster_id].session_id\n divpat_log = weblog[weblog.session_id.isin(sessions_cluster)]\n # Filtering some requests\n divpat_log=divpat_log[divpat_log['requested_'+classification_column_transaction].isin(classification_wanted_transaction)]\n divpat_log=divpat_log[divpat_log['referrer_'+classification_column_transaction].isin(classification_wanted_transaction)]\n \n # Defining matrices\n diversity_columns=('referrer_'+classification_column_diversity,'requested_'+classification_column_diversity)\n browsing_matrix[cluster_id],_ = compute_browsing_matrix(divpat_log,'referrer_'+classification_column_transaction,'requested_'+classification_column_transaction,labels=classification_wanted_transaction)\n diversifying_matrix[cluster_id],_ = compute_diversifying_matrix(divpat_log,'referrer_'+classification_column_transaction,'requested_'+classification_column_transaction,\\\n diversity_columns,labels = classification_wanted_transaction)\n if verbose == True:\n print(\" Cluster matrices computed in %.1f seconds.\"%(timelib.time() - start_time))\n \n return browsing_matrix, diversifying_matrix;","def _granger_causality(self):\r\n gc = dict(frequencies={}, gc_xy={}, gc_yx={}, gc_sim={},\r\n spectral_density={})\r\n for i, j in self.ij:\r\n w, f_x2y, f_y2x, f_xy, Sw = \\\r\n alg.granger_causality_xy(self.model_coef[i, j],\r\n self.error_cov[i, j],\r\n n_freqs=self._n_freqs)\r\n\r\n # All other measures are dependent on i, j:\r\n gc['gc_xy'][i, j] = f_x2y\r\n gc['gc_yx'][i, j] = f_y2x\r\n gc['gc_sim'][i, j] = f_xy\r\n gc['spectral_density'][i, j] = Sw\r\n\r\n return gc","def compute_clusters(self, documents):\n ###TODO\n for d in range(0, len(documents)):\n maxi = 999999999\n for cid in range(0, len(self.means)):\n dist = self.distance(documents[d], self.means[cid], self.norms[cid])\n if dist < maxi:\n maxi = dist\n clust = cid \n self.cluster[d] = clust","def kmode_calculation(self, data):\n col_dict = {}\n\n for col in data.columns:\n data[col] = data[col].astype('category')\n col_dict.update({col: dict(enumerate(data[col].cat.categories))})\n\n # Get all the cols in the DataFrame\n cols = [col for col in data.columns]\n\n # Transform all values into categorical and numerical values\n for col in cols:\n data[col] = data[col].astype('category')\n data[col] = data[col].cat.codes\n\n # Run k-modes using the algorithm\n kmodes_method = KModes(n_clusters=self.n_cluster, init=self.init_method, n_init=self.n_iter, verbose=1)\n kmode_result = kmodes_method.fit_predict(data[cols])\n\n # Attach the output label for each data point\n data['classification'] = pd.Series(kmode_result, index=data.index)\n\n return col_dict, kmodes_method.cluster_centroids_, data","def _compute_centroids(self, encodings, labels):\n counts = {}\n centroids = {}\n\n # Copy encodings to avoid ref modification when computing centroid.\n encodings = encodings.copy()\n\n for i, encoding in enumerate(encodings):\n key = int(labels[i])\n if key in centroids:\n centroids[key] += encoding\n counts[key] += 1\n else:\n centroids[key] = encoding\n counts[key] = 1\n for key in centroids:\n centroids[key] /= counts[key]\n self.centroids = centroids","def get_clusters_adjacencies(adjacency, clusters: list):\n clusters.sort(key=lambda t: len(t), reverse=True)\n id_to_cluster = get_id_to_cluster(clusters, adjacency.shape[0])\n num_clusters = len(clusters)\n mat = np.zeros((num_clusters, num_clusters))\n rows, cols = adjacency.nonzero()\n for i, j in zip(rows, cols):\n weight = adjacency[i, j]\n src_cluster = id_to_cluster[i]\n dest_cluster = id_to_cluster[j]\n mat[src_cluster, dest_cluster] += weight\n return mat","def compute_confusion_matrix(num_clusters, clustered_points_algo, sorted_indices_algo):\r\n seg_len = 400\r\n true_confusion_matrix = np.zeros([num_clusters, num_clusters])\r\n for point in range(len(clustered_points_algo)):\r\n cluster = clustered_points_algo[point]\r\n num = (int(sorted_indices_algo[point]/seg_len) % num_clusters)\r\n true_confusion_matrix[int(num), int(cluster)] += 1\r\n return true_confusion_matrix","def clustering_metrics(clusts, node_assn, node_pred):\n pred_vox = cluster_to_voxel_label(clusts, node_pred)\n true_vox = cluster_to_voxel_label(clusts, node_assn)\n ari = ARI(pred_vox, true_vox)\n ami = AMI(pred_vox, true_vox)\n sbd = SBD(pred_vox, true_vox)\n pur, eff = purity_efficiency(pred_vox, true_vox)\n return ari, ami, sbd, pur, eff","def get_clusters(ensemble, grouping, clustering):\n\n\t# Prevent SQL injected since column names cannot be parameterized.\n\tif \";\" in ensemble or \";\" in grouping or \";\" in clustering:\n\t\treturn None\n\n\tensemble = ensemble.replace('EnsEns','Ens')\n\tdf = None;\n\n\tif grouping in ['annotation','cluster']:\n\t\tgroupingu = ensemble+\".\"+grouping+\"_\"+clustering\n\telif grouping in ['NeuN']:\n\t\tgroupingu = \"CONCAT('NeuN',cells.\"+grouping+\")\"\n\telse:\n\t\tgroupingu = \"cells.\"+grouping\n\n\t# Get methylation info\n\tquery = \"SELECT count(cells.cell_id) ncells, 'snmC' as modality, \\\n\t\t%(groupingu)s as groups \\\n\t\tFROM cells \\\n\t\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\n\t\tGROUP BY groups \" % {'ensemble': ensemble,\n\t\t\t\t\t'groupingu': groupingu,\n\t\t\t\t\t'clustering': clustering}\n\ttry:\n\t\tdf = pd.read_sql(query, db.get_engine(current_app, 'methylation_data'))\n\texcept exc.ProgrammingError as e:\n\t\tnow = datetime.datetime.now()\n\t\tprint(\"[{}] ERROR in app(get_clusters): {}\".format(str(now), e))\n\t\tsys.stdout.flush()\n\t\t# return None\n\n\t# Get snATAC info\n\tquery = \"SELECT count(cells.cell_id) ncells, 'snATAC' AS modality, %(ensemble)s.cluster_ATAC groups \\\n\t\tFROM cells \\\n\t\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\n\t\tGROUP BY groups \" % {'ensemble': ensemble,\n\t\t\t\t\t'grouping': grouping,\n\t\t\t\t\t'clustering': clustering}\n\n\ttry:\n\t\tdf_atac = pd.read_sql(query, db.get_engine(current_app, 'snATAC_data'))\n\t\tdf=df.append(df_atac)\n\texcept exc.ProgrammingError as e:\n\t\tnow = datetime.datetime.now()\n\t\tprint(\"[{}] ERROR in app(get_clusters): {}\".format(str(now), e))\n\t\tsys.stdout.flush()\n\n\n\t# Get snRNA info\n\tquery = \"SELECT count(cells.cell_id) ncells, 'RNA' AS modality, %(ensemble)s.cluster_RNA groups \\\n\t\tFROM cells \\\n\t\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\n\t\tGROUP BY groups \" % {'ensemble': ensemble,\n\t\t\t\t\t'grouping': grouping,\n\t\t\t\t\t'clustering': clustering}\n\n\ttry:\n\t\tdf_rna = pd.read_sql(query, db.get_engine(current_app, 'RNA_data'))\n\t\tdf=df.append(df_rna)\n\texcept exc.ProgrammingError as e:\n\t\tnow = datetime.datetime.now()\n\t\tprint(\"[{}] ERROR in app(get_clusters): {}\".format(str(now), e))\n\t\tsys.stdout.flush()\n\n\treturn df","def index_nodes(self):\n out = {}\n\n #avg = np.mean(list(self.rtype_vectors.values()),axis=0)\n\n\n #for name, node in self.nodes.items():\n # tmp1 = [self.rtype_vectors[rtype]\n # for rtype, dest in node.outgoing_relations] or [NULL_VEC()]\n # tmp2 = [permute_rtype_vector(self.rtype_vectors[rtype])\n # for rtype, prev in node.incoming_relations] or [NULL_VEC()]\n\n # net = tmp1 + tmp2\n\n # #out[name] = np.asarray(net).mean(axis=0)\n # #out[name] = np.asarray(net).sum(axis=0)\n # v = np.asarray(net).sum(axis=0)\n # if v.any():\n # out[name] = v/max(v)#softmax(v/max(v))\n # else:\n # out[name] = v\n\n\n #avg = np.mean(list(out.values()),axis=0)\n\n #maxm = np.max(list(out.values()),axis=0)\n\n ####normalize everything\n #for r,v in out.items():\n # if v.any():\n # #out[r] = v / sqrt(v.dot(v))\n # out[r] = softmax((v-avg)/maxm)\n\n\n\n # PCA method 0001701\n rmap = self.rtype_vectors\n data = np.zeros((len(self.nodes), JACCARD_DIMENSIONS), dtype=np.float)\n ix = 0\n for node in self.nodes.values():\n\n #compute weighted average of each relation type\n tmp = [rmap[rtype] for \n rtype, dest in node.outgoing_relations] + \\\n [permute_rtype_vector(rmap[rtype]) for \n rtype, prev in node.incoming_relations]\n\n v = np.asarray(tmp).mean(axis=0) if tmp else NULL_VEC()\n\n #normalize\n if v.any():\n data[ix] = v / sqrt(v.dot(v))\n else:\n data[ix] = v\n ix += 1\n\n #eliminate projection onto first 7 principal components\n d2 = data - PCA(data, 7)\n\n #order of nodes is preserved\n for i,v in enumerate(self.nodes):\n out[v] = softmax(d2[i])\n\n return out","def evaluate(self):\n results = dict()\n for metric in self.metrics:\n print('Evaluating clustering with metric %s' % metric)\n if metric in LABEL_METRICS.keys():\n results[metric] = LABEL_METRICS[metric](self.X, self.model.labels_)\n results['adjusted_rand_score'] = SCORE_METRICS['adjusted_rand_score'](self.Y[:, 0], self.model.labels_)\n self.results = results\n return results","def cluster_cal(self):\n self.Cluster = []\n for i in range(self.nodenum):\n neighborhood_node = self.neighbor_node(i)\n Node_num = len(neighborhood_node)\n Count = self.neighbor_edge(neighborhood_node)\n if(Node_num == 0 or Node_num == 1):\n self.Cluster.append(0.5)\n else:\n self.Cluster.append(Count/(Node_num*(Node_num - 1)))\n \n self.cluster_coeff = np.average(self.Cluster)","def _generate_adjacency_matrices(self):\n self.adj_matrices = dict()\n mes = []\n args = []\n for metaedge in self.metaedges:\n mes.append(metaedge)\n args.append(self._prepare_parallel_adj_matrix_args(self.edge_df.query('abbrev == @metaedge')))\n res = parallel_process(array=args, function=mt.get_adj_matrix, use_kwargs=True, n_jobs=self.n_jobs,\n front_num=0)\n for metaedge, matrix in zip(mes, res):\n self.adj_matrices[metaedge] = matrix","def clustering(self):\n ret_concepts = []\n clusters = []\n for word in self.words:\n clusters.append(WordCluster(None, word))\n while len(clusters) > 1:\n maxi = -1\n maxj = -1\n max = -1\n m = -1\n for i in range(len(clusters)):\n for j in range(len(clusters)):\n if i == j:\n continue\n # print(\"%d cluster compare with %d cluster\" % (i, j))\n # 1: join 21: i absorb j 22: j absorb i 3: collapse\n # l1: join L(Tm) value l21: A absorb B L(Tm)value\n l1, newtags = self.__calculate_ltm(clusters[i], clusters[j], 1)\n if l1 > max:\n m = 1\n maxi = i\n maxj = j\n max = l1\n print(\"max L(Tm) for clustering in current loop: %lf\" % max)\n if max < ClusterAlgorithm.P_threshold:\n return\n Tm = clusters[maxi].join(clusters[maxj])\n Tm_concepts = self.__select_concepts(self.__getword(Tm))\n for tmp_concept in Tm_concepts.items():\n ret_concepts.append(tmp_concept)\n rm1 = clusters[maxi]\n rm2 = clusters[maxj]\n clusters.remove(rm1)\n clusters.remove(rm2)\n if Tm is not None:\n print(\"merged cluster's words:\")\n print(self.__getword(Tm))\n return ret_concepts","def clusterAlgorithm(values):\n clusterMap = dict()\n for value in values:\n if value[2] not in clusterMap.keys():\n clusterMap[value[2]] = []\n clusterMap[value[2]].append(value)\n frequency = [float(len(clusterMap[value[2]])) for value in values]\n total = sum(frequency)\n weightValues = [freq / total for freq in frequency]\n print sum(weightValues)\n lightValues = [value[1] for value in values]\n return np.average(lightValues, weights = weightValues)","def make_contingency_tables(\n y: np.ndarray, flagged_A: np.ndarray, flagged_B: np.ndarray\n) -> Dict[int, np.ndarray]:\n\n y = np.array(y).astype(np.int64).flatten()\n flagged_A = np.array(flagged_A).astype(np.bool_).flatten()\n flagged_B = np.array(flagged_B).astype(np.bool_).flatten()\n\n if len(flagged_A) != len(y) or len(flagged_B) != len(y):\n raise ValueError(\n f\"Expected arrays y, flagged_A, and flagged_B of the same length: \\\n got {len(y)}, {len(flagged_A)}, and {len(flagged_B)}.\"\n )\n\n contingency_tables = {}\n for class_id in np.unique(y):\n\n items_flagged_A = flagged_A[y == class_id]\n items_flagged_B = flagged_B[y == class_id]\n\n a = (~items_flagged_A & ~items_flagged_B).sum()\n b = (~items_flagged_A & items_flagged_B).sum()\n c = (items_flagged_A & ~items_flagged_B).sum()\n d = (items_flagged_A & items_flagged_B).sum()\n\n table = np.array([[a, b], [c, d]])\n contingency_tables[class_id] = table\n\n return contingency_tables","def cluster_life_expectancy() -> Dict:\n return dict(model=None, score=None, clusters=None)","def _cluster(self):\n # , distance_function=spearman_squared_distance, max_iter=1000, tol=0.0001):\n if self.cluster_method is None:\n clusters = KMedoids(\n self.k,\n self.batchsize,\n dist_func=self.distance_function,\n max_iter=self.max_iter,\n tol=self.tol,\n init_medoids=self.init_medoids,\n swap_medoids=self.swap_medoids,\n )\n clusters.fit(self.clustering_attributions, verbose=self.verbose)\n\n self.subpopulations = clusters.members\n self.subpopulation_sizes = GAM.get_subpopulation_sizes(clusters.members)\n self.explanations = self._get_explanations(clusters.centers)\n # Making explanations return numerical values instead of dask arrays\n if isinstance(self.explanations[0][0][1], da.Array):\n explanations = []\n for explanation in self.explanations:\n explanations.append([(x[0], x[1].compute()) for x in explanation])\n self.explanations = explanations\n else:\n self.cluster_method(self)","def eval_v_measure_homogeneity_completeness(clustering_alg: List, sdist_euclidean, sdist_jaccard,\n labels_true, debug: bool = False):\n for i, alg_dict in enumerate(clustering_alg):\n if \"alg\" in alg_dict:\n if alg_dict[\"distance\"] == \"euclidean\":\n clustering = alg_dict[\"alg\"].fit(sdist_euclidean)\n elif alg_dict[\"distance\"] == \"jaccard\":\n clustering = alg_dict[\"alg\"].fit(sdist_jaccard)\n else:\n raise ValueError(\"Unknown distance measure {}. \".format(alg_dict[\"distance\"]) +\n \"Please choose one of the following distance measures ['euclidean','jaccard']\")\n labels_predicted = clustering.labels_\n alg_dict[\"labels\"] = labels_predicted\n else:\n labels_predicted = alg_dict[\"labels\"]\n\n alg_dict[\"homogeneity\"], alg_dict[\"completeness\"], alg_dict[\"v-measure\"] = \\\n homogeneity_completeness_v_measure(labels_true, labels_predicted)\n\n if debug:\n print(\"Alg: \" + alg_dict[\"name\"] + \"; \\t v-measure = \" + str(alg_dict[\"v-measure\"]))","def predict_clustering_pairs(args, **kwargs):\n # We first compute the exponential and uniform likelihoods for all genomes\n # in the dataset, individually\n organisms_uniform_probabilities, n_pairs = \\\n clustering_probs.compute_organisms_probabilities(\n args, **kwargs)\n\n # Finds all the probabilities files for single organisms\n probabilities_files_list = file_utilities.get_file_list(\n args[\"individual_probabilities_dir\"],\n args[\"probabilities_filename_suffix\"])\n\n if args[\"weight\"] is True or args[\"subclades\"] is True:\n logger.info(\"Importing phylogenetic tree %s\", args[\"tree_file\"])\n tree = ete3.Tree(args[\"tree_file\"])\n logger.info(\"Phylogenetic tree %s imported\", args[\"tree_file\"])\n if args[\"weight\"] is True:\n if not os.path.exists(args[\"weights_file\"]) or args[\n \"force\"] is True:\n GSC.save_weights(None, args[\"weights_file\"], None, \"w\")\n else:\n tree = None\n\n # Conserved clustering analysis in each subclade:\n if args[\"subclades\"] is True:\n logger.info(\n \"Started computing subclade-specific conserved\"\n \" clustering probabilities\")\n subclade_analysis.partition_tree(probabilities_files_list,\n organisms_uniform_probabilities,\n n_pairs,\n tree,\n args,\n **kwargs)\n logger.info(\n \"Parsing subclade-specific conserved clustering probabilities, \"\n \"this will take a while\")\n find_last_subclade.parse_and_clean_tree(n_pairs, args)\n logger.info(\n \"Parsing subclade-specific conserved clustering probabilities done\")\n logger.info(\n \"Subclade-specific conserved clustering probabilities computed\")\n\n\n # Clustering analysis just in the root:\n else:\n if not os.path.exists(args[\"final_probabilities_filename\"]) \\\n or probabilities_files.is_table_empty(\n args[\"final_probabilities_filename\"]) \\\n or args[\"force\"] is True:\n logger.info(\n \"Started computing root-only conserved clustering probabilities\")\n final_probs.compute_conserved_probabilities(\n probabilities_files_list,\n organisms_uniform_probabilities,\n n_pairs,\n tree,\n 0,\n args[\"final_probabilities_filename\"],\n args)\n\n logger.info(\"Root conserved clustering probabilities saved in file %s\",\n args[\"final_probabilities_filename\"])\n\n if args[\"weight\"] is True:\n logger.info(\"Phylogenetic weights saved in file %s\",\n args[\"weights_file\"])\n\n\n return 0","def _calculate_cluster_measures(\n arr4d,\n threshold,\n bin_struct,\n two_sided_test=False,\n):\n n_regressors = arr4d.shape[3]\n\n max_sizes = np.zeros(n_regressors, int)\n max_masses = np.zeros(n_regressors, float)\n\n for i_regressor in range(n_regressors):\n arr3d = arr4d[..., i_regressor].copy()\n\n if two_sided_test:\n arr3d[np.abs(arr3d) <= threshold] = 0\n else:\n arr3d[arr3d <= threshold] = 0\n\n labeled_arr3d, _ = label(arr3d > 0, bin_struct)\n\n if two_sided_test:\n # Label positive and negative clusters separately\n n_positive_clusters = np.max(labeled_arr3d)\n temp_labeled_arr3d, _ = label(\n arr3d < 0,\n bin_struct,\n )\n temp_labeled_arr3d[temp_labeled_arr3d > 0] += n_positive_clusters\n labeled_arr3d = labeled_arr3d + temp_labeled_arr3d\n del temp_labeled_arr3d\n\n clust_vals, clust_sizes = np.unique(labeled_arr3d, return_counts=True)\n assert clust_vals[0] == 0\n\n clust_vals = clust_vals[1:] # First cluster is zeros in matrix\n clust_sizes = clust_sizes[1:]\n\n # Cluster mass-based inference\n max_mass = 0\n for unique_val in clust_vals:\n ss_vals = np.abs(arr3d[labeled_arr3d == unique_val]) - threshold\n max_mass = np.maximum(max_mass, np.sum(ss_vals))\n\n # Cluster size-based inference\n max_size = 0\n if clust_sizes.size:\n max_size = np.max(clust_sizes)\n\n max_sizes[i_regressor], max_masses[i_regressor] = max_size, max_mass\n\n return max_sizes, max_masses","def cluster(self):\n logger.debug(\"Beginning feature based clustering on %d clusters.\" % len(self.c2b))\n # Merge the two nearest clusters until we can't.\n #\n while self.mergeNearestClusters():\n pass\n logger.debug(\"After clustering, there are now %d clusters remaining.\" % len(self.c2b))\n return self.c2b.values()","def __generate_dict_of_keys_to_classification__(self):\n dict_of_assigned_citations = {}\n # duplicating citation dataset to filter as matches go on meaning\n # it should result in quicker allocation\n # can be removed to reduce memory load at expense of speed\n list_of_unassigned = []\n for key in self.dict_of_keywords:\n list_of_current_key = []\n for citation_instance in self.array_of_citations:\n if key == citation_instance.get_classification():\n list_of_current_key.append(citation_instance)\n if \"Unassigned\" == citation_instance.get_classification():\n list_of_unassigned.append(citation_instance)\n dict_of_assigned_citations[key] = list_of_current_key\n dict_of_assigned_citations[\"Unassigned\"] = list_of_unassigned\n return dict_of_assigned_citations","def calculate_conductivities(self, vertices, gm_label):\r\n self.gm_label = gm_label\r\n data = pd.read_csv(vertices, sep=' ', header=None)\r\n\r\n self.__calculate_gm_bounds(data)\r\n self.dmri_handler.handle() #counts evals and evecs\r\n shape = self.dmri_handler.get_shape()\r\n\r\n self.xscale_coef = (self.gm_box.get_max_x() - self.gm_box.get_min_x()) / shape[0]\r\n self.yscale_coef = (self.gm_box.get_max_y() - self.gm_box.get_min_y()) / shape[1]\r\n self.zscale_coef = (self.gm_box.get_max_z() - self.gm_box.get_min_z()) / shape[2]\r\n\r\n self.__calculate_conductivities(data)\r\n data.to_csv(self.output_file, sep=' ')","def evaluation_cc(self, property='clustering-coeff'):\n\n if property == 'clustering-coeff':\n rw_cc = [np.mean(clustering_coef_wu(self.rw_data[t])) for t in range(0, self.T)]\n smth_cc = [np.mean(clustering_coef_wu(self.smth_data[t])) for t in range(0, self.T)]\n elif property == 'transitivity':\n rw_cc = [np.mean(transitivity_wu(self.rw_data[t])) for t in range(0, self.T)]\n smth_cc = [np.mean(transitivity_wu(self.smth_data[t])) for t in range(0, self.T)]\n elif property == 'coreness':\n rw_cc = [np.mean(core.core_periphery_dir(self.rw_data[t])) for t in range(0, self.T)]\n smth_cc = [np.mean(core.core_periphery_dir(self.smth_data[t])) for t in range(0, self.T)]\n elif property == 'assortativity':\n rw_cc = [np.mean(core.assortativity_wei(self.rw_data[t], 0)) for t in range(0, self.T)]\n smth_cc = [np.mean(core.assortativity_wei(self.smth_data[t], 0)) for t in range(0, self.T)]\n elif property == 'modularity':\n rw_cc, _ = get_number_of_components(self.rw_data)\n smth_cc, _ = get_number_of_components(self.smth_data)\n elif property == 'path_length':\n rw_cc = [charpath(rw)[0] for rw in self.rw_data]\n smth_cc = [charpath(sm)[0] for sm in self.smth_data]\n\n # rw_cc_ent = get_entropy_list(rw_cc)\n # smth_cc_ent = get_entropy_list(smth_cc)\n\n return rw_cc, smth_cc","def multiClusterAlgorithm(values):\n clusterMap = dict()\n # Lowest unixtime in the values list\n startUnixtime = values[0][0]\n # Separate values into separate clusters in the map, clusterMap\n for value in values:\n if value[2] not in clusterMap.keys():\n clusterMap[value[2]] = []\n clusterMap[value[2]].append(value)\n \n # An array of the predicted values per cluster\n clusterPredicted = []\n # An array of unixtime averages per cluster\n unixtimeAverage = []\n \n # Generate predicted value for each cluster using a weighted average\n # Adds predicted value for each cluster to clusterPredicted and adds\n # the unixtime average for each cluster to unixtimeAverage\n for key in clusterMap.keys():\n clusterLength = len(clusterMap[key]) \n totalUnixtime = sum([elem[0] for elem in clusterMap[key]])\n unixtimeAverage.append(float(totalUnixtime) / float(clusterLength))\n \n clusterLight = [elem[1] for elem in clusterMap[key]]\n\n totalDistanceFromStart = sum([elem[0] - startUnixtime for elem in clusterMap[key]])\n clusterWeightValues = [float(elem[0] - startUnixtime) / float(totalDistanceFromStart) for elem in clusterMap[key]]\n \n predicted = np.average(clusterLight, weights = clusterWeightValues)\n clusterPredicted.append(predicted)\n \n print clusterPredicted\n total = sum([elem - startUnixtime for elem in unixtimeAverage])\n # Create weighted values based on unixtime average per cluster\n weightValues = [float(elem - startUnixtime) / float(total) for elem in unixtimeAverage]\n print weightValues\n # Return a weighted average across clusters\n return np.average(clusterPredicted, weights = weightValues)","def dictionary(descriptors, n_clusters):\n # TODO\n print(descriptors.shape)\n dummy=MiniBatchKMeans(n_clusters=n_clusters, batch_size=3000, random_state=9).fit(descriptors)\n clusters=dummy.cluster_centers_\n return clusters","def _compute_util_data(self):\n\n print(\"Computing PCA of document vectors.\")\n self.pca = PCA(n_components = 3)\n\n print(\"Computing document clusters in PCA basis.\")\n inferred_vecs = np.array([self.model.infer_vector(doc.words) for doc in self.tagged_docs])\n self.pca_reduced_vecs = self.pca.fit_transform(inferred_vecs)\n n_clusters = 25 # TODO find way to determine approx cluster size\n self.kmeans = KMeans(init = 'k-means++', n_clusters = n_clusters, random_state = 0)\n self.kmeans_preds = self.kmeans.fit_predict(self.pca_reduced_vecs)","def clustering(clusters, dend_matrix, labels, linkagefun):\n Z = linkagefun(dend_matrix)\n color_threshold = Z[-1*clusters][2]+0.0000000001 #Cut slightly above the tree node\n \n # Defining to which cluster belongs to each simulation\n T = fcluster(Z, t=clusters, criterion='maxclust')\n clustdict = { \"cluster\" + str(clust) : [] for clust in T }\n for sim,clust in zip(labels,T):\n clustdict[\"cluster\" + str(clust)].append(sim)\n\n return(color_threshold, clustdict)","def prepare_data_matrix():\n # create matrix X and list of languages\n\n lds = {}\n for fn in listdir(\"clustering\"):\n if fn.lower().endswith(\".txt\"):\n with open(join(\"clustering\", fn), encoding=\"utf8\") as f:\n text = f.read()\n nter = terke(text, n=3)\n lds[fn] = nter\n #print(lds.keys())\n \n #lds is a dictionary of dictionaries: {\"slovenian.txt\": {\"abc\":3,\"efg\":4...}, \"macedonian.txt\":{\"efg\":6...},...}\n l=listOfTuples(lds) #list of strings\n #print(l[:100])\n languages = list(lds.keys()) # ['Slo', 'Mac', ]\n # which language represents row number i: languages[i]\n # which row does language s represent: languagues.index(s)\n X=np.zeros([len(languages),100])\n for i in range(len(languages)):\n #print(languages[i])\n count = 0\n for j in range(100):\n if l[j] in lds[languages[i]]:\n X[i,j]=lds[languages[i]][l[j]]\n count += 1\n # print(count)\n\n #print([sum(x) for x in X])\n \n return X, languages\n # X, languages = prepare_data_matrix()","def fit(self):\n self.cluseter_agglomerative(n_clusters=20, linkage='average', iterate=5)\n self.sub_clustering(n_clusters=3, index_cluster=[79], linkage='complete')\n self.merge_clusters([[0,9,53],[1,83],[46,35,67],[88,23],[6,68]])\n self.merge_clusters([[6,33,52],[17,14]])\n self.sub_clustering(n_clusters=2, index_cluster=[0], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[2], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[85], linkage='average')\n self.sub_clustering(n_clusters=2, index_cluster=[14], linkage='complete')\n self.sub_clustering(n_clusters=2, index_cluster=[16], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[22], linkage='average')\n self.sub_clustering(n_clusters=2, index_cluster=[24], linkage='complete')\n self.sub_clustering(n_clusters=2, index_cluster=[26], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[28], linkage='ward')\n self.merge_clusters([[6,98,99]])\n self.merge_clusters([[35,80]])\n self.sub_clustering(n_clusters=4, index_cluster=[35], linkage='complete')\n self.merge_clusters([[76,98]])\n self.sub_clustering(n_clusters=3, index_cluster=[35], linkage='complete')\n self.merge_clusters([[39,42]])\n self.sub_clustering(n_clusters=3, index_cluster=[47], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='average')\n self.merge_clusters([[70,101]])\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[61], linkage='ward')\n self.merge_clusters()\n return","def evaluate(self, clustering):\n # Pca for each one of the clusters\n pca_mean_val = 0.;\n MAX_ELEMENTS = 1000\n for c in clustering.clusters:\n # Pick the coordinates (ensuring that we are copying them)\n element_indexes = c.all_elements\n ###################\n # Performance hack\n ###################\n # As it can be very slow for big clusters (i.e. > 3k elements) we'll compress this clusters \n # before calculating PCA. It should increase variance but will allow calculations.\n # It should use the kmedoids compressor\n if len(c.all_elements) > MAX_ELEMENTS:\n element_indexes = c.get_random_sample(MAX_ELEMENTS)\n print \"[PCA] Random sampling too big cluster to improve performance (%d elements -> %d elements).\"%(len(c.all_elements),MAX_ELEMENTS)\n ###################\n \n fitting_coordinates_of_this_cluster = self.fitting_coordinates[element_indexes]\n \n calculator = RMSDCalculator(calculatorType = \"QTRFIT_SERIAL_CALCULATOR\",\n fittingCoordsets = fitting_coordinates_of_this_cluster)\n \n if self.calculation_coordinates is not None:\n calculation_coordinates_of_this_cluster = self.calculation_coordinates[element_indexes]\n calculator = RMSDCalculator(calculatorType = \"QTRFIT_SERIAL_CALCULATOR\",\n fittingCoordsets = fitting_coordinates_of_this_cluster,\n calculationCoordsets = calculation_coordinates_of_this_cluster)\n \n # Make an iterative superposition (to get the minimum RMSD of all with respect to a mean conformation)\n calculator.iterativeSuperposition()\n\n # Calculate the covariance matrix\n if self.calculation_coordinates is None:\n covariance_matrix = PCAMetric.create_covariance_matrix(fitting_coordinates_of_this_cluster)\n else:\n covariance_matrix = PCAMetric.create_covariance_matrix(calculation_coordinates_of_this_cluster)\n \n # And then the eigenvalue we are interested in\n pca_mean_val += PCAMetric.calculate_biggest_eigenvalue(covariance_matrix)\n print \"PCA finished\"\n return pca_mean_val /clustering.total_number_of_elements","def cluster_classification_tex(f,browsing_matrix,diversifying_matrix, weblog,session_data_threshold,cluster_type,classification_column_diversity,classification_wanted_transaction):\n divpat_classification_wanted_transaction = classification_wanted_transaction\n divpat_N_classification_wanted_transaction=len(divpat_classification_wanted_transaction)\n f.write(\"\\n% 6. Cluster Classification\")\n columns_latex = '|'+'c|'*len(session_data_threshold[cluster_type].unique())\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('DivColumnsLatex',columns_latex)) \n columns_blank = ' ' + '& '*(len(session_data_threshold[cluster_type].unique()) -1)\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('DivColumnsBlank',columns_blank)) \n cluster_list = []\n ieuc_clusters = []\n star_chain_like_clusters = []\n length_clusters = []\n browsing_pattern_1 = []\n browsing_pattern_2 = []\n browsing_pattern_3 = []\n diversifying_pattern_1 = []\n diversifying_pattern_2 = []\n diversifying_pattern_3 = []\n cluster_ids = session_data_threshold[cluster_type].unique()\n cluster_ids.sort()\n for cluster_id in cluster_ids:\n cluster_list.append(str(cluster_id))\n \n cluster_session_list=session_data_threshold[session_data_threshold[cluster_type]==cluster_id].session_id.values\n temp_cluster_weblog=weblog[weblog.session_id.isin(cluster_session_list)]\n pa,pa_names = proportional_abundance(temp_cluster_weblog,'requested_'+classification_column_diversity)\n cluster_entropy=ShannonEntropy(pa,normalize=True)\n \n ieuc_clusters.append(str(round(np.power(2.0,cluster_entropy),2)))\n star_chain_like_clusters.append(star_chain_str(session_data_threshold[session_data_threshold[cluster_type]==cluster_id].star_chain_like.mean()))\n length_clusters.append(length(session_data_threshold[session_data_threshold[cluster_type]==cluster_id].requests.mean()))\n # Browsing patterns\n r,c=np.unravel_index(browsing_matrix[cluster_id][:-1,:-1].argsort(axis=None)[::-1][:3],dims=(divpat_N_classification_wanted_transaction,divpat_N_classification_wanted_transaction))\n browsing_pattern_1.append('%.1f\\%%: %s$\\\\rightarrow$%s'%(100.0*browsing_matrix[cluster_id][r[0],c[0]],divpat_classification_wanted_transaction[r[0]],divpat_classification_wanted_transaction[c[0]]))\n browsing_pattern_2.append('%.1f\\%%: %s$\\\\rightarrow$%s'%(100.0*browsing_matrix[cluster_id][r[1],c[1]],divpat_classification_wanted_transaction[r[1]],divpat_classification_wanted_transaction[c[1]]))\n browsing_pattern_3.append('%.1f\\%%: %s$\\\\rightarrow$%s'%(100.0*browsing_matrix[cluster_id][r[2],c[2]],divpat_classification_wanted_transaction[r[2]],divpat_classification_wanted_transaction[c[2]]))\n \n # Diversifying patterns\n r,c=np.unravel_index(np.nan_to_num(diversifying_matrix[cluster_id])[:-1,:-1].argsort(axis=None)[::-1][:3],dims=(divpat_N_classification_wanted_transaction,divpat_N_classification_wanted_transaction))\n diversifying_pattern_1.append('%.1f\\%%: %s$\\\\rightarrow$%s'%(100.0*diversifying_matrix[cluster_id][r[0],c[0]],divpat_classification_wanted_transaction[r[0]],divpat_classification_wanted_transaction[c[0]]))\n diversifying_pattern_2.append('%.1f\\%%: %s$\\\\rightarrow$%s'%(100.0*diversifying_matrix[cluster_id][r[1],c[1]],divpat_classification_wanted_transaction[r[1]],divpat_classification_wanted_transaction[c[1]]))\n diversifying_pattern_3.append('%.1f\\%%: %s$\\\\rightarrow$%s'%(100.0*diversifying_matrix[cluster_id][r[2],c[2]],divpat_classification_wanted_transaction[r[2]],divpat_classification_wanted_transaction[c[2]]))\n\n del temp_cluster_weblog\n \n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('DivClusterList',' & '.join(cluster_list)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('DivIEUCClusters',' & '.join(ieuc_clusters)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('StarChainClusters',' & '.join(star_chain_like_clusters)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('LengthClusters',' & '.join(length_clusters)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('BrowsingPatternClustersOne',' & '.join(browsing_pattern_1)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('BrowsingPatternClustersTwo',' & '.join(browsing_pattern_2)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('BrowsingPatternClustersThree',' & '.join(browsing_pattern_3)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('DiversifyingPatternClustersOne',' & '.join(diversifying_pattern_1)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('DiversifyingPatternClustersTwo',' & '.join(diversifying_pattern_2)))\n f.write(\"\\n\\\\newcommand{\\\\%s}{%s}\"%('DiversifyingPatternClustersThree',' & '.join(diversifying_pattern_3)))\n\n return f;","def generate(dictalg):\n\n # dsList, sortedAlgs, dictAlg = processInputArgs(args, verbose=verbose)\n res = {}\n for f, i in pproc.dictAlgByFun(dictalg).iteritems():\n for d, j in pproc.dictAlgByDim(i).iteritems():\n tmp = BestAlgSet(j)\n res[(d, f)] = tmp\n return res","def calculate_clusters(study_id):\n\n with current_app.app_context():\n cur = conn.cursor()\n\n cur.execute(\"\"\"SELECT * FROM STATS WHERE STUDY_ID=%s\"\"\", (str(study_id),))\n study = fetchoneClean(cur)\n clusters_calculating = study[4]\n clusters_changed = study[5]\n if clusters_changed:\n if clusters_calculating:\n return {'message': 'calculating'}\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CALCULATING = TRUE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n conn.commit()\n\n distance = study[7]['matrix']\n card_names = study[7]['cardNames']\n cur.execute(\"\"\"SELECT COUNT(ID) FROM PARTICIPANT WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n total_participants = fetchoneClean(cur)[0]\n\n distance_matrix = calculate_square_form(distance, total_participants)\n distArray = ssd.squareform(distance_matrix)\n\n try:\n clusters = hierarchy.linkage(distArray, method='average')\n except ValueError:\n return {'message': 'not enough data'}\n\n tree = hierarchy.to_tree(clusters, rd=False)\n # TODO Distance 0 on root\n dendro = dict(children=[], hierarchy=0, distance=100)\n add_node(tree, dendro, card_names)\n\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS = %s WHERE STUDY_ID = %s\"\"\", (json.dumps(dendro), str(study_id),))\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CALCULATING = FALSE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CHANGED = FALSE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n conn.commit()\n else:\n dendro = study[6]\n\n return dendro","def kmeans_clustering(cluster_list, num_clusters, num_iterations):\n points = cluster_list[:]\n \n # n <-- |p|;\n len_points_list = len(points)\n\n # position initial clusters at the location of clusters with largest populations (i.e., cluster[3] which is population) \n cluster_centers = []\n temp_cl = points[:]\n \n temp_cl.sort(key=lambda cluster: cluster.total_population())\n for cluster in reversed(temp_cl):\n if len(cluster_centers) < num_clusters:\n cluster_centers.append(alg_cluster.Cluster(set([]), cluster.horiz_center(), cluster.vert_center(), 0, 0))\n\n # For number of iterations\n for dummy_var in range(num_iterations):\n # initialize k (num_clusters) empty sets C1, ... Ck;\n cluster_groupings = []\n for index in range(len(cluster_centers)):\n cluster_groupings.append(alg_cluster.Cluster(set(), 0, 0, 0, 0))\n # # For each county\n # for j = 0 to n - 1 do\n for index in range(len_points_list):\n # Find the old cluster center that is closest \n # L <-- argminsub(1<=f<=k) (dsub(psubj), musubf); \n min_dist = float('inf')\n nearest_cluster_index = None\n\n for idx, cluster in enumerate(cluster_centers):\n if points[index].distance(cluster) < min_dist:\n min_dist = points[index].distance(cluster)\n nearest_cluster_index = idx\n\n # Add the county to the corresponding new cluster\n # Handled with Cluster class merge_clusters method, which will automatically update the cluster centers to correct locations.\n cluster_groupings[nearest_cluster_index].merge_clusters(points[index])\n # Set old clusters equal to new clusters \n # for f = 1 to k do\n for index in range(len(cluster_centers)):\n # muf = center (Cf) // handled with Cluster class built-in method(s)\n cluster_centers[index] = cluster_groupings[index].copy()\n\n # return {C1, C2, ..., Ck}; \n return cluster_groupings","def cluster_membership_occupancy(data):\n \n \n \n n_clusters = len(set(data['clusters'])-{-1}) # since -1 element denotes noice\n\n if n_clusters == 0:\n membership=[Cluster_Membership_Features()]\n membership = pd.DataFrame([o.__dict__ for o in membership])\n areas=[Cluster_Area_Features()]\n areas = pd.DataFrame([o.__dict__ for o in areas])\n density=[Cluster_Density_Features()]\n density = pd.DataFrame([o.__dict__ for o in density])\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\n density], axis=1)\n \n elif n_clusters ==1:\n #obtain_total_cluster_areas_set_everything_else_to_default\n membership=[Cluster_Membership_Features()]\n membership = pd.DataFrame([o.__dict__ for o in membership])\n d = dict(tuple(data.groupby('clusters')))\n d.pop(-1, None)\n \n try:\n cluster_chull_areas=[ss.ConvexHull(np.column_stack([d[i]['X'].array,d[i]['Y'].array])).volume for i in d.keys()]\n except:\n cluster_chull_areas=[0,0,0]\n \n Total_cluster_area=np.sum(cluster_chull_areas)\n areas=[Cluster_Area_Features([Total_cluster_area,0,0,0,0,0,0,0,0])]\n areas = pd.DataFrame([o.__dict__ for o in areas])\n density=[Cluster_Density_Features()]\n density = pd.DataFrame([o.__dict__ for o in density])\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\n density], axis=1)\n \n elif n_clusters >1:\n #Summarizing the cluster membership distribution characteristics\n cluster_size_nums=np.delete(np.array(data.groupby(['clusters']).size()),0)\n (cluster_size_nums_avg,cluster_size_nums_min,cluster_size_nums_max,\n cluster_size_nums_std,cluster_size_nums_cv,cluster_size_nums_cd,\n cluster_size_nums_IQR,cluster_size_nums_Quartile_CD)= distribution_statistics(cluster_size_nums)\n\n #For each cluster calculate the area by calculating the area of the convex hull of cluster members\n # Note: concavehull implementation here might be a good addition as it will provide more imformative values. \n\n d = dict(tuple(data.groupby('clusters')))\n d.pop(-1, None)\n try:\n cluster_chull_areas=[ss.ConvexHull(np.column_stack([d[i]['X'].array,d[i]['Y'].array])).volume for i in d.keys()]\n except:\n cluster_chull_areas=[0,0,0,0,0]\n \n\n (avg_cluster_area,min_cluster_area,max_cluster_area,\n std_cluster_area,CV_cluster_area,CD_cluster_area,\n IQR_cluster_area,Quartile_CD_cluster_area)= distribution_statistics(cluster_chull_areas)\n Total_cluster_area=np.sum(cluster_chull_areas)\n\n #Calculate cluster density: number of nuclei/ convex area of cluster\n cluster_density=np.divide(cluster_size_nums,cluster_chull_areas)\n (avg_cluster_density,min_cluster_density,max_cluster_density,\n std_cluster_density,CV_cluster_density,CD_cluster_density,\n IQR_cluster_density,Quartile_CD_cluster_density)= distribution_statistics(cluster_density)\n\n #return dataframe of features\n membership=[Cluster_Membership_Features([cluster_size_nums_avg,cluster_size_nums_min,cluster_size_nums_max,\n cluster_size_nums_std,cluster_size_nums_cv,cluster_size_nums_cd,\n cluster_size_nums_IQR,cluster_size_nums_Quartile_CD])]\n membership = pd.DataFrame([o.__dict__ for o in membership])\n areas=[Cluster_Area_Features([Total_cluster_area,\n avg_cluster_area,min_cluster_area,max_cluster_area,\n std_cluster_area,CV_cluster_area,CD_cluster_area,\n IQR_cluster_area,Quartile_CD_cluster_area])]\n areas = pd.DataFrame([o.__dict__ for o in areas])\n density=[Cluster_Density_Features([avg_cluster_density,min_cluster_density,max_cluster_density,\n std_cluster_density,CV_cluster_density,CD_cluster_density,\n IQR_cluster_density,Quartile_CD_cluster_density])]\n density = pd.DataFrame([o.__dict__ for o in density])\n\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\n density], axis=1)\n return all_features","def cluster_bal_iter(self):\n # moving\n for j,cluster in enumerate(self.clusters):\n cluster.move()\n self.clusters_allocate_cells()\n for j,cluster in enumerate(self.clusters):\n cluster.calc()\n #print j, '\\t', cluster.center, '\\t', cluster.np, '\\t', cluster.size\n \n # resizing\n for j,cluster in enumerate(self.clusters):\n cluster.resize()\n self.clusters_allocate_cells()\n for j,cluster in enumerate(self.clusters):\n cluster.calc()\n #print j, '\\t', cluster.center, '\\t', cluster.np, '\\t', cluster.size\n \n self.calc()","def get_all_clusters(self) -> Dict[str, List[str]]:\n result = {}\n for c_id in set(self._clusters.values()):\n result[c_id] = self.get_cluster_by_id(c_id)\n return result","def _create_adjacency_matrix(layer_edges):\n A = defaultdict(int)\n for l, edges in list(layer_edges.items()):\n for edge in edges:\n A[(edge[0], edge[1], l)] += 1\n A[(edge[1], edge[0], l)] += 1 \n return A","def calculate_all_metrcis(self):\n self.calculate_gc_metrcis()\n self.calculate_sam_metrics()\n self.calculate_classification_metrics()\n self.calculate_losses()","def assign_clusters(self):\n running_perts = {}\n for name in self.tensor_info:\n item = self.tensor_info[name]\n pert_list = item[1]\n pert_names = []\n prob_list = []\n if pert_list is not None:\n for pert in pert_list:\n pert_names.append(pert.__class__.__name__)\n prob_list.append(pert.p)\n pert_names = '_'.join(pert_names)\n if pert_names not in running_perts:\n running_perts[pert_names] = [(name, prob_list)]\n else:\n running_perts[pert_names].append((name, prob_list))\n\n running_perts.pop('')\n\n assert len(running_perts) <= len(self.clusters), \"More different perturbations than clusters available, cannot assign tensors to clusters\"\n\n # ONLY BITWISEPERT FOR THE TIME BEING\n bitwises = running_perts['BitwisePert']\n bitwise_probs = [item[1][0] for item in bitwises]\n centers, _ = kmeans(bitwise_probs, len(self.clusters))\n groups, _ = vq(bitwise_probs, centers)\n\n for tensor, cluster in zip(bitwises, groups):\n name = tensor[0]\n tensor_ref = self.tensor_info[name][0]\n repr = self.tensor_info[name][2]\n self.clusters[cluster].add_tensor(tensor_ref, repr)\n\n for cluster, rate in zip(self.clusters, centers):\n pert_dict = {\n \"name\": \"BitwisePert\",\n \"p\": rate}\n pert = P.construct_pert(pert_dict)\n cluster.set_perturb([pert])","def cluster_analysis(\n clusterers: list,\n hyperparameter_grids: list,\n eval_metrics_grid: list,\n eval_metrics_params: dict,\n word_embeddings: np.ndarray,\n words_vocabulary: list,\n word_to_int: dict,\n word_embeddings_normalized: np.ndarray = None,\n compute_pairwise_word_distances: bool = False,\n compute_pairwise_word_distances_normalized: bool = False,\n return_word_vectors: bool = False,\n save_result_to_disk: bool = False,\n output_dir: Optional[str] = None,\n model_name: Optional[str] = None,\n dataset_name: Optional[str] = None,\n output_filepath_suffix: Optional[str] = None,\n) -> Union[dict, tuple]:\n # Create word vectors from given words/vocabulary\n word_vectors = words_to_vectors(\n words_vocabulary=words_vocabulary,\n word_to_int=word_to_int,\n word_embeddings=word_embeddings,\n )\n\n # Create normalized word vectors from given words/vocabulary if specified.\n word_vectors_normalized = None\n if word_embeddings_normalized is not None:\n word_vectors_normalized = words_to_vectors(\n words_vocabulary=words_vocabulary,\n word_to_int=word_to_int,\n word_embeddings=word_embeddings_normalized,\n )\n\n if compute_pairwise_word_distances:\n word_vectors_pairwise_distances = pairwise_cosine_distances(word_vectors)\n if (\n compute_pairwise_word_distances_normalized\n and word_vectors_normalized is not None\n ):\n normalized_word_vectors_pairwise_distances = euclidean_distances(\n word_vectors_normalized\n )\n\n # Perform cluster analysis\n clusterers_result = {}\n unique_cluster_metrics = set()\n for clusterer_tuple, hyperparameter_grid, eval_metrics in zip(\n clusterers, hyperparameter_grids, eval_metrics_grid\n ):\n if len(clusterer_tuple) == 3:\n (clusterer_name, clusterer_cls, clusterer_use_normalized) = clusterer_tuple\n else:\n clusterer_use_normalized = False\n (clusterer_name, clusterer_cls) = clusterer_tuple\n print(f\"-- Clustering using {clusterer_name} --\")\n clusterers_result[clusterer_name] = {\n \"cluster_labels\": [],\n \"cluster_params\": [],\n \"cluster_metrics\": {},\n }\n\n # Do clustering for each set of hyperparameters\n param_grid = ParameterGrid(hyperparameter_grid)\n for params_idx, params in enumerate(tqdm(param_grid)):\n clusterers_result[clusterer_name][\"cluster_params\"].append(params)\n\n # Add exception for ward linkage clustering.\n if (\n clusterer_cls is AgglomerativeClustering\n and params.get(\"linkage\") == \"ward\"\n and word_vectors_normalized is not None\n ):\n params = {**params, \"affinity\": \"euclidean\"}\n clusterer_instance = clusterer_cls(**params)\n fit_predict_X = word_vectors_normalized\n else:\n clusterer_instance = clusterer_cls(**params)\n if (\n params.get(\"affinity\") == \"precomputed\"\n or params.get(\"metric\") == \"precomputed\"\n ):\n if (\n clusterer_use_normalized\n and compute_pairwise_word_distances_normalized\n ):\n fit_predict_X = normalized_word_vectors_pairwise_distances\n elif compute_pairwise_word_distances:\n fit_predict_X = word_vectors_pairwise_distances\n else:\n if clusterer_use_normalized and word_vectors_normalized is not None:\n fit_predict_X = word_vectors_normalized\n else:\n fit_predict_X = word_vectors\n\n # Use fit_predict if it is available.\n if getattr(clusterer_instance, \"fit_predict\", None) is not None:\n predicted_labels = clusterer_instance.fit_predict(fit_predict_X)\n else:\n clusterer_instance.fit(fit_predict_X)\n predicted_labels = clusterer_instance.predict(fit_predict_X)\n\n # Separate noise labels into clusters\n if clusterer_cls is HDBSCAN:\n predicted_labels = separate_noise_labels_into_clusters(predicted_labels)\n\n clusterers_result[clusterer_name][\"cluster_labels\"].append(predicted_labels)\n\n # Evaluate predicted cluster labels using internal evaluation metrics\n for eval_metric_tuple in eval_metrics:\n if len(eval_metric_tuple) == 3:\n (\n eval_metric_key,\n eval_metric,\n eval_metric_use_normalized,\n ) = eval_metric_tuple\n else:\n eval_metric_use_normalized = False\n (eval_metric_key, eval_metric) = eval_metric_tuple\n eval_metric_params = eval_metrics_params.get(eval_metric_key, {})\n if (\n compute_pairwise_word_distances\n and eval_metric_params.get(\"metric\") == \"precomputed\"\n ):\n if (\n eval_metric_use_normalized\n and compute_pairwise_word_distances_normalized\n ):\n metric_name, metric_score, metric_obj_max = eval_metric(\n word_embeddings=normalized_word_vectors_pairwise_distances,\n cluster_labels=predicted_labels,\n clusterer=clusterer_instance,\n **eval_metric_params,\n )\n else:\n metric_name, metric_score, metric_obj_max = eval_metric(\n word_embeddings=word_vectors_pairwise_distances,\n cluster_labels=predicted_labels,\n clusterer=clusterer_instance,\n **eval_metric_params,\n )\n else:\n if (\n eval_metric_use_normalized\n and word_vectors_normalized is not None\n ):\n metric_name, metric_score, metric_obj_max = eval_metric(\n word_embeddings=word_vectors_normalized,\n cluster_labels=predicted_labels,\n clusterer=clusterer_instance,\n **eval_metric_params,\n )\n else:\n metric_name, metric_score, metric_obj_max = eval_metric(\n word_embeddings=word_vectors,\n cluster_labels=predicted_labels,\n clusterer=clusterer_instance,\n **eval_metric_params,\n )\n unique_cluster_metrics.add(metric_name)\n\n # Initialize metric result\n if (\n metric_name\n not in clusterers_result[clusterer_name][\"cluster_metrics\"]\n ):\n clusterers_result[clusterer_name][\"cluster_metrics\"][\n metric_name\n ] = {\n \"metric_scores\": [],\n \"metric_obj_max\": metric_obj_max,\n \"best_metric_score_indices\": [],\n }\n\n clusterers_result[clusterer_name][\"cluster_metrics\"][metric_name][\n \"metric_scores\"\n ].append(metric_score)\n\n # Set best metric score indices\n if params_idx == len(param_grid) - 1:\n best_metric_score_indices = np.argsort(\n clusterers_result[clusterer_name][\"cluster_metrics\"][\n metric_name\n ][\"metric_scores\"]\n )\n if metric_obj_max:\n best_metric_score_indices = best_metric_score_indices[::-1]\n clusterers_result[clusterer_name][\"cluster_metrics\"][metric_name][\n \"best_metric_score_indices\"\n ] = best_metric_score_indices\n\n # Find preferred clusterers for each cluster metric (from best to worst)\n metric_preferred_clusterers = {}\n for cluster_metric_name in unique_cluster_metrics:\n metric_obj_max = None\n metric_best_scores = []\n clusterer_names = []\n for clusterer_name, clusterer_result in clusterers_result.items():\n if cluster_metric_name in clusterer_result[\"cluster_metrics\"]:\n clusterer_names.append(clusterer_name)\n metric_result = clusterer_result[\"cluster_metrics\"][cluster_metric_name]\n if metric_obj_max is None:\n metric_obj_max = metric_result[\"metric_obj_max\"]\n best_metric_score = metric_result[\"metric_scores\"][\n metric_result[\"best_metric_score_indices\"][0]\n ]\n metric_best_scores.append(best_metric_score)\n clusterer_names = np.array(clusterer_names)\n metric_best_scores = np.array(metric_best_scores)\n\n metric_best_scores_sorted_indices = np.argsort(metric_best_scores)\n if metric_obj_max:\n metric_best_scores_sorted_indices = metric_best_scores_sorted_indices[::-1]\n metric_preferred_clusterers[cluster_metric_name] = {\n \"clusterer_names\": clusterer_names[metric_best_scores_sorted_indices],\n \"best_metric_scores\": metric_best_scores[metric_best_scores_sorted_indices],\n }\n\n # Return result as dictionary\n cluster_analysis_result = {\n \"clusterers\": clusterers_result,\n \"metric_preferred_clusterers\": metric_preferred_clusterers,\n }\n\n if return_word_vectors:\n if compute_pairwise_word_distances:\n cluster_analysis_result = (\n cluster_analysis_result,\n word_vectors,\n word_vectors_pairwise_distances,\n )\n else:\n cluster_analysis_result = (cluster_analysis_result, word_vectors)\n\n # Save result to disk\n if save_result_to_disk:\n save_cluster_result_to_disk(\n cluster_result=cluster_analysis_result,\n output_dir=output_dir,\n model_name=model_name,\n dataset_name=dataset_name,\n output_filepath_suffix=output_filepath_suffix,\n )\n\n return cluster_analysis_result","def compute_cluster_similarities(emb_clusters1, emb_clusters2, compare, order, clmethod, plot):\n def compute_sim(e, e1, cls, cls1):\n sims = np.empty((20, 20))\n xticks, yticks = [], []\n for i, c in enumerate(cls):\n yticks.append(', '.join(c[1]) + (f' {round(c[3], 5)}' if order == 'avgfreq' else ''))\n for j, c1 in enumerate(cls1):\n if len(xticks) < 20:\n xticks.append(', '.join(c1[1]) + (f' {round(c1[3], 5)}' if order == 'avgfreq' else ''))\n sims[i, j] = jaccard_similarity_score(c[2], c1[2])\n jaccard_similarities[f'{e}-{e1}'] = sims\n\n if plot:\n if order == 'clustermap':\n similarity_clustermap(sims, xticks, yticks, f'{e}-{e1}_{clmethod}')\n elif order == 'default' or order == 'avgfreq':\n similarity_heatmap(sims, xticks, yticks, f'{e}-{e1}_{clmethod}', order)\n else:\n pass\n\n jaccard_similarities = {}\n if compare == 'cross':\n for ie, (e, cls) in enumerate(emb_clusters1.items()):\n for ie1, (e1, cls1) in enumerate(emb_clusters2.items()):\n if ie < ie1:\n compute_sim(e, e1, cls, cls1)\n elif compare == 'dot':\n for (e, cls), (e1, cls1) in zip(emb_clusters1.items(), emb_clusters2.items()):\n compute_sim(e, e1, cls, cls1)\n\n return jaccard_similarities","def get_all_local_clustering_coef(g):\n local_cc = {}\n\n for n in nx.nodes(g):\n local_cc[n] = get_local_clustering_coef(g, n)\n\n return local_cc","def evaluate_clusters(self, cluster_formulas, value='weighted_sum'):\n num_elems = len(self.labels)\n total_val = {}\n num_cl = len(cluster_formulas)\n clustered_points_num = 0\n print(\"\\n\\n\")\n print(\"Sufficiently big clusters: {}\".format(num_cl))\n for c, formula, val in cluster_formulas:\n c_size = len([l for l in self.labels if l == c])\n clustered_points_num += c_size\n\n if value == 'weighted_sum':\n total_val[c] = val * c_size / num_elems\n elif value == 'sum':\n total_val[c] = val * 1\n\n clust_val = sum(total_val.values())\n self.clustering_value = total_val\n print(\"Value of clustering: {}\".format(clust_val))\n return clust_val","def load_cluster_accuracies():\n accuracies = morphs.utils.load._pickle(morphs.paths.ACCURACIES_PKL)\n cluster_accuracies = {\n block_path: accuracies[block_path]\n .groupby(\"cluster\")\n .agg(np.mean)\n .sort_values(\"accuracy\")\n for block_path in accuracies\n }\n return accuracies, cluster_accuracies","def match_cluster_sets(cs1, cs2):\n\n matr = [[len(cl1.bibs & cl2.bibs) for cl2 in cs2.clusters] for cl1 in cs1.clusters]\n mapping = maximized_mapping(matr)\n return dict((cs1.clusters[mappy[0]], cs2.clusters[mappy[1]]) for mappy in mapping)","def run(\n self,\n number_of_clusters=None,\n max_K=8,\n method_clustering=\"pam\",\n init_clustering=\"random\",\n max_iter_clustering=100,\n discart_value_JI=0.6,\n bootstraps_JI=100,\n bootstraps_p_value=100,\n n_jobs=1,\n verbose=1,\n ):\n\n if number_of_clusters is None:\n self.k = optimizer.optimizeK(\n self.distance_matrix,\n self.y.to_numpy(),\n self.model_type,\n max_K,\n method_clustering,\n init_clustering,\n max_iter_clustering,\n discart_value_JI,\n bootstraps_JI,\n self.random_state,\n n_jobs,\n verbose,\n )\n\n if self.k == 1:\n warnings.warn(\"No stable clusters were found!\")\n return\n\n print(f\"Optimal number of cluster is: {self.k}\")\n\n else:\n self.k = number_of_clusters\n print(f\"Use {self.k} as number of cluster\")\n\n self.cluster_labels = (\n kmedoids.KMedoids(\n n_clusters=self.k,\n method=method_clustering,\n init=init_clustering,\n metric=\"precomputed\",\n max_iter=max_iter_clustering,\n random_state=self.random_state,\n )\n .fit(self.distance_matrix)\n .labels_\n )\n\n (\n self._data_clustering_ranked,\n self.p_value_of_features,\n ) = stats.calculate_global_feature_importance(\n self.X, self.y, self.cluster_labels, self.model_type\n )\n self._p_value_of_features_per_cluster = (\n stats.calculate_local_feature_importance(\n self._data_clustering_ranked, bootstraps_p_value\n )\n )","def clustering(self): \n clusterOfFiles=self.getClusters()\n \n #group files based on the hash of their contents\n self.keyingMethod=md5Hash\n [self.addFile(afile) for acluster in clusterOfFiles for afile in acluster]\n clusterOfFiles=self.getClusters()\n self.showClusters(clusterOfFiles)","def matching_clusterization(self):\n result = []\n self.reclustering(self.groups.copy(deep=True), result)\n self.result = pd.DataFrame(result)\n return self.result.sort_values(by=['cluster_size'], ascending=False)","def censuses(self, *scales: int) -> Mapping[int, Census]:\n return {\n # Map id to the whole census object\n census.id: census\n # The dict is created from a generating parsing the nodes\n for census in (\n Census.from_xml(node)\n # an XML node can be used as an iterator, where it yields children\n for node in self.shards_xml(\n \"census\",\n # we want to grab all the values, since a Census requires them\n mode=joined_parameter(\"score\", \"rank\", \"rrank\", \"prank\", \"prrank\"),\n # gets all the different stats for us\n scale=joined_parameter(*(str(scale) for scale in scales))\n if scales\n else \"all\",\n )[\"census\"]\n )\n }","def get_cluster_info(self) -> Dict[str, Any]:\n pass","def return_factorized_dict(ls):\r\n factos = pd.unique(pd.factorize(ls)[0])\r\n categs = pd.unique(pd.factorize(ls)[1])\r\n if -1 in factos:\r\n categs = np.insert(categs,np.where(factos==-1)[0][0],np.nan)\r\n return dict(zip(categs,factos))","def cluster(X=None, datalabels=None, nc=2):\n from sklearn.cluster import KMeans\n from sklearn.cluster import AffinityPropagation\n\n C = KMeans(n_clusters=nc,n_init=10,init='random')\n C.fit(X[:,:1])\n\n #C = AffinityPropagation(preference=-80,damping=0.5).fit(X)\n #cluster_centers_indices = C.cluster_centers_indices_\n\n clust = {}\n for (i, label) in enumerate(C.labels_):\n key = C.cluster_centers_[label][0]\n #print label,key, datalabels[i],X[i][1]\n if not clust.has_key(key):\n clust[key]=[]\n clust[key].append(datalabels[i])\n #print clust\n return C, clust","def _generate_weighted_matrices(self):\n self.degree_weighted_matrices = dict()\n mes = []\n args = []\n for metaedge, matrix in self.adj_matrices.items():\n mes.append(metaedge)\n args.append({'matrix': matrix, 'w': self.w, 'degree_fwd': self.out_degree[metaedge],\n 'degree_rev': self.in_degree[metaedge]})\n res = parallel_process(array=args, function=mt.weight_by_degree, use_kwargs=True, n_jobs=self.n_jobs,\n front_num=0)\n for metaedge, matrix in zip(mes, res):\n self.degree_weighted_matrices[metaedge] = matrix","def dimension_homology_sc(self):\r\n vec_dic = {}\r\n for k in range(self.dimension()+1):\r\n p = k \r\n A = self.matrix_simmetric_representate(p)\r\n dn = 0\r\n dc = 0\r\n if (p == 0):\r\n dn = A.shape[1]\r\n if (p > 0 and (p <= self.dimension())):\r\n null = null_space(A)\r\n if (null.size != 0):\r\n dn = len(null[0])\r\n if (all(elem == 0 for elem in null[0])):\r\n dn = 0 \r\n p = k + 1\r\n if (p>0 and (p <= self.dimension())):\r\n A1=self.matrix_simmetric_representate(p)\r\n col = orth(A1)\r\n if (col.size != 0):\r\n dc = len(col[0])\r\n else: \r\n dc = 0\r\n vec_dic[k] = dn - dc\r\n return vec_dic","def get_results_for_init(self):\n return dict(init=self.centroids, n_clusters=self.centroids.shape[0])","def compute_feature_properties(self):\n\n self.valuecounts = {}\n self.unique_values = {}\n self.missing_ratios = {}\n self.counts = {}\n self.codemaps = {}\n for f in self.features:\n # Compute various things\n all_values = [self.data[l].get(f,\"?\") for l in self.data]\n missing_data_ratio = all_values.count(\"?\") / (1.0*len(all_values))\n non_q_values = [v for v in all_values if v != \"?\"]\n counts = {}\n for v in non_q_values:\n counts[v] = non_q_values.count(v)\n unique_values = list(set(non_q_values))\n # Sort unique_values carefully.\n # Possibly all feature values are numeric strings, e.g. \"1\", \"2\", \"3\".\n # If we sort these as strings then we get weird things like \"10\" < \"2\".\n # This can actually matter for things like ordinal models.\n # So convert these to ints first...\n if all([v.isdigit() for v in unique_values]):\n unique_values = list(map(int, unique_values))\n unique_values.sort()\n unique_values = list(map(str, unique_values))\n # ...otherwise, just sort normally\n else:\n unique_values.sort()\n self.unique_values[f] = unique_values\n\n N = len(unique_values)\n self.valuecounts[f] = N\n self.missing_ratios[f] = missing_data_ratio\n self.counts[f] = counts\n self.codemaps[f] = self.build_codemap(unique_values)","def katz_for_pairs(self, pairs, adj_prefix, max_length=6, beta=0.1):\n filenames = [adj_prefix + str(i) + '.npz' for i in range(2, max_length + 1)]\n n = 1\n self.katz = {}\n bs = [1.500, .891, .631, .543, .413, .420] # output from Mohler method\n for u, v in pairs:\n if u not in self.katz:\n self.katz[u] = defaultdict(float)\n for f in filenames:\n a = scipy.sparse.load_npz(f)\n # b = beta ** n\n b = bs[n-1]\n for u, v in pairs:\n self.katz[u][v] += b * a[u-1, v-1]\n n += 1\n print(\"Loaded %s\" % f)","def _gen_cg_dict(maxdim, existing_keys=None):\n cg_dict = {}\n # print(\"gen_cg_dict called with maxdim =\", maxdim)\n\n fastcgmat = memoize(clebschSU2mat)\n\n for k1, n1, k2, n2 in itertools.product(range(maxdim), repeat=4):\n if ((k1, n1), (k2, n2)) in existing_keys:\n continue\n cg_dict.setdefault(((k1, n1), (k2, n2)), {})\n kmin, kmax = abs(k1 - k2), k1 + k2\n nmin, nmax = abs(n1 - n2), n1 + n2\n # dim1, dim2 = (k1 + 1) * (n1 + 1), (k2 + 1) * (n2 + 1)\n for k, n in itertools.product(\n range(kmin, kmax + 1, 2), range(nmin, nmax + 1, 2)\n ):\n cg_dict[((k1, n1), (k2, n2))][(k, n)] = torch.tensor(\n clebschmat((k1, n1), (k2, n2), (k, n), fastcgmat=fastcgmat)\n )\n\n return cg_dict","def compute_statistics(self):\n for i in range(len(self.wine_matrix[0, :])):\n feature = self.wine_matrix[:, i]\n self.wine_stats['feature ' + str(i)] = {}\n if i == 11: # results column\n self.wine_stats['feature ' + str(i)]['positive_class_ratio'] = (feature == 1).sum() / len(feature)\n null, self.wine_stats['feature ' + str(i)]['pvalue'] = stats.normaltest(feature)\n\n # plot\n # pyplot.hist(feature, bins=50)\n # pyplot.show()\n\n for i in range(len(self.cancer_matrix[0, :])):\n feature = self.cancer_matrix[:, i]\n self.cancer_stats['feature ' + str(i)] = {}\n if i == 10: # results column\n self.cancer_stats['feature ' + str(i)]['positive_class_ratio'] = (feature == 1).sum() / len(feature)\n null, self.cancer_stats['feature ' + str(i)]['pvalue'] = stats.normaltest(feature)\n\n # plot\n # pyplot.hist(feature, bins=50)\n # pyplot.show()","def cluster(self, documents, iters=10):\n ###TODO\n self.means = documents[0:self.k]\n self.cluster = defaultdict(lambda : int)\n self.docs = documents\n \n for val in range(iters):\n self.norms = []\n for x in self.means:\n self.norms.append(self.sqnorm(x))\n \n self.compute_clusters(documents)\n \n self.fin_clust = defaultdict(lambda:[])\n for z in self.cluster:\n self.fin_clust[self.cluster[z]].append(z)\n \n self.means = self.compute_means()\n \n to_print_array = []\n for k in self.fin_clust:\n to_print_array.append(len(self.fin_clust[k]))\n \n print (to_print_array)\n print (self.error(documents))","def clustering(df, mode):\n # split into list of dfs containing only one reference node\n df_list = [df.loc[i : i + 8 - 1, :] for i in range(0, len(df), 8)]\n\n df_coefficient = pd.DataFrame()\n\n # loop over every single node\n for df_single in df_list:\n df_single = df_single.reset_index()\n total_value = 0\n\n # loop over the weights of all connected nodes\n for j in range(len(df_single) - 1):\n if mode == \"geometric\":\n # geometric\n total_value = total_value + math.sqrt(df_single.chi_sq[j] * df_single.chi_sq[j + 1])\n if mode == \"arithmetic\": \n # arithmetic\n total_value = total_value + ((df_single.chi_sq[j] * df_single.chi_sq[j + 1]) / 2)\n if mode == \"argmax\": \n # max\n total_value = total_value + max(df_single.chi_sq[j], df_single.chi_sq[j + 1])\n if mode == \"argmin\":\n # min\n total_value = total_value + min(df_single.chi_sq[j], df_single.chi_sq[j + 1])\n\n for i in range(len(df_single) - 1):\n if mode == \"geometric\":\n # geometric\n triplet_value = math.sqrt(df_single.chi_sq[i] * df_single.chi_sq[i + 1])\n if mode == \"arithmetic\":\n # arithmetic\n triplet_value = (df_single.chi_sq[i] * df_single.chi_sq[i + 1]) / 2\n if mode == \"argmax\":\n # max\n triplet_value = max(df_single.chi_sq[i], df_single.chi_sq[i + 1])\n if mode == \"argmin\": \n # min\n triplet_value = min(df_single.chi_sq[i], df_single.chi_sq[i + 1])\n\n cluster_coefficient = triplet_value / total_value\n buffer = [\n [\n df_single.reference[i],\n df_single.comparison[i],\n df_single.comparison[i + 1],\n triplet_value,\n cluster_coefficient,\n ]\n ]\n df_coefficient = df_coefficient.append(buffer)\n\n df_coefficient = df_coefficient.reset_index()\n\n print(\"\\n\\n threshold 0.5*c_omega\")\n check_list = []\n # print out triangles that have a cluster coefficient bigger, than X\n for i in range(len(df_coefficient)):\n if df_coefficient[4][i] >= ((0.5) * df_coefficient[4].max()):\n print(list(df_coefficient.loc[i][1:4]))\n check_list.append(list(df_coefficient.loc[i][1:4]))\n else:\n continue\n\n print(\"\\n\\n threshold 0.75*c_omega\")\n check_list = []\n for i in range(len(df_coefficient)):\n if df_coefficient[4][i] >= ((0.75) * df_coefficient[4].max()):\n print(list(df_coefficient.loc[i][1:4]))\n check_list.append(list(df_coefficient.loc[i][1:4]))\n else:\n continue\n\n print(\"\\n\\n threshold 0.8*c_omega\")\n check_list = []\n for i in range(len(df_coefficient)):\n if df_coefficient[4][i] >= ((0.9) * df_coefficient[4].max()):\n print(list(df_coefficient.loc[i][1:4]))\n check_list.append(list(df_coefficient.loc[i][1:4]))\n else:\n continue\n\n\n print(\"\\n\\n threshold 0.9*c_omega\")\n check_list = []\n for i in range(len(df_coefficient)):\n if df_coefficient[4][i] >= ((0.9) * df_coefficient[4].max()):\n print(list(df_coefficient.loc[i][1:4]))\n check_list.append(list(df_coefficient.loc[i][1:4]))\n else:\n continue\n\n return","def _assign_clusters(self):\n\n dist = np.zeros((self.k, ))\n distortion = 0\n\n for index in range(0, self.data.shape[0]):\n for i in range(0, self.k):\n dist[i] = np.linalg.norm(self.data[index] - self.centroids[i])\n\n self.assigned_clusters[index] = np.argmin(dist)\n distortion += np.min(dist)\n\n return distortion","def interpret_clusters(self, split=0.7, all_demos=None, num_clusters=None, \n max_depth=CLUSTER_DEPTH, data=None, labels=None, verbose=True):\n all_demos = self.all_data if all_demos is None else all_demos\n clusters = self.get_ordered_clusters(labels, num_clusters)\n data = self.demos if data is None else data\n labels = self.labels if labels is None else labels\n\n cluster_formulas = []\n counter = 0\n sep = \"\\n \"\n for c in clusters:\n counter += 1\n res = self.sample_from_clusters(num_samples=split,\n all_data=all_demos,\n pos_validation=True, \n neg_validation=True,\n which_cluster=counter)\n positive_samples, val_positive_samples = res[0], res[1]\n negative_samples, val_negative_samples = res[2], res[3]\n z = 0\n for d in positive_samples:\n if d[1] == 0: z += 1\n\n cluster_data = {'pos': positive_samples,\n 'neg': negative_samples}\n val_cluster_data = {'pos': val_positive_samples,\n 'neg': val_negative_samples}\n\n if verbose: print(sep +\"Checking formulas \" + \\\n \"with max depth {}\\n\".format(max_depth))\n\n cluster_formula, value_formula = wrapper_train(max_depth,\n cluster_data, \n val_cluster_data,\n verbose=verbose,\n pred_data=[self.pipeline_X,\n self.pipeline_y])\n if cluster_formula is not None:\n print(cluster_formula)\n\n cluster_formulas.append((c, cluster_formula, value_formula))\n self.reset_pipeline()\n\n return cluster_formulas","def _recalculate_centroids(self):\n\n self._prev_centroids = dict(self.centroids)\n for cluster in self.clusters:\n self.centroids[cluster] = np.average(self.clusters[cluster], axis=0)","def calcClusters(dataset, medoids, number_of_clusters, verbosity=0, class_header=\"Class\"):\n clusters = [pandas.DataFrame(columns=dataset.columns)] * number_of_clusters # create array of clusters\n multiprocess_count = multiprocessing.cpu_count() # Find processor count\n pool = multiprocessing.Pool(processes=multiprocess_count) # create multiprocessing pool\n\n set_list = []\n partition_size = math.ceil(len(dataset) / multiprocess_count)\n for i in range(multiprocess_count - 1): # repeat for every subset\n sample = dataset.iloc[i * partition_size: (i + 1) * partition_size] # take a sample of data\n set_list.append((sample, medoids, number_of_clusters, verbosity, class_header)) # fill work list\n set_list.append(\n (dataset.iloc[(multiprocess_count - 1) * partition_size:], medoids, number_of_clusters, verbosity, class_header))\n\n # find list of clustering for each subset\n clusters_subsets = pool.starmap(Cluster.calcClustersMultiprocess, set_list)\n pool.close()\n pool.join()\n # Transpose 2d list of dataframes so each lower level list is of the same cluster\n cluster_lists = [[i for i in element if i is not None] for element in list(zip_longest(*clusters_subsets))]\n\n for i in range(number_of_clusters): # concat together each list of cluster subsets.\n clusters[i] = pandas.concat(cluster_lists[i])\n return clusters","def compute_means(self):\n ###TODO\n vector_means = []\n for doc in self.fin_clust.values():\n vec = defaultdict(float)\n for d_id in doc:\n doc_keys = self.docs[d_id].keys()\n for key in self.docs[d_id]:\n vec[key] = vec[key] + self.docs[d_id][key]\n tot = len(doc)\n x = defaultdict(float)\n for k,v in vec.items():\n x[k] = float(v)/tot\n vec = Counter(x)\n vector_means.append(vec)\n return vector_means","def _generate_weighted_adj_matrices(self):\n self.weighted_adj_matrices = dict()\n mes = []\n args = []\n for metaedge in self.metaedges:\n mes.append(metaedge)\n args.append(self._prepare_parallel_weighted_adj_matrix_args(self.edge_df.query('abbrev == @metaedge')))\n res = parallel_process(array=args, function=mt.get_adj_matrix, use_kwargs=True, n_jobs=self.n_jobs,\n front_num=0)\n for metaedge, matrix in zip(mes, res):\n self.weighted_adj_matrices[metaedge] = matrix","def adj_dict(self):\n adj_dict = {i: [] for i in self.indices}\n for coeff in self.interactions[1:]:\n for _inds, value in coeff.items():\n for i in _inds:\n _inds_list = list(_inds)\n _inds_list.remove(i)\n adj_dict[i].append([_inds_list, value])\n return adj_dict","def scores(self):\n\t\tseqLengths = []\n\t\tfor x in self.contigsInfo.keys():\n\t\t\tseq = self.contigsInfo[x]\n\t\t\tseqLengths.append(len(seq))\n\n\t\tseqLengths = sorted(seqLengths)\t\n\t\tmax_length = max(seqLengths)\n\t\tmin_length = min(seqLengths)\n\t\tmean_length = np.mean(seqLengths)\t\n\n\n\t\tmidLength = sum(seqLengths)/2\n\n\t\tcomputedMidLength = 0\n\t\tl50 = 0\n\t\tn50 = 0\n\t\tfor i,x in enumerate(seqLengths):\n\t\t\tif (midLength < computedMidLength):\n\t\t\t\tn50 = i\n\t\t\t\tl50 = x \n\t\t\t\tbreak\n\t\t\tcomputedMidLength += x\n\n\t\tscoresDict = {'number_of_contigs':len(seqLengths), 'smallestContig':min_length, 'meanContig':mean_length, \n\t\t'n50':n50, 'l50':l50, 'largestContig':max_length, 'lengthOfAssembly':sum(seqLengths)}\n\t\treturn scoresDict","def clustering(dataset, logger):\n all_instances = dataset\n meta_dataset = collections.defaultdict(list)\n for instance in all_instances:\n meta_dataset[instance['label']].append(instance['coordinate'])\n\n tasklist = map(\n lambda item, meta_dataset=meta_dataset, logger=logger: (\n item[0],\n clustering_by_label,\n (item[1], item[0], meta_dataset, logger)), meta_dataset.items())\n\n # pool = multiprocessing.pool.Pool(PROCESS_COUNT)\n # clusters = dict(pool.map(map_generate_tuple, tasklist))\n clusters = dict(map(map_generate_tuple, tasklist))\n # pool.close()\n # pool.join()\n\n return clusters","def get_composition(self) -> Dict[KappaAgent, int]:\n agent_types = self.get_agent_types_present()\n composition = dict(zip(agent_types, [0] * len(agent_types)))\n for agent_type in agent_types:\n for kappa_complex, abundance in self.get_all_complexes_and_abundances():\n complex_composition = kappa_complex.get_complex_composition()\n local_abundance = complex_composition[agent_type] if agent_type in complex_composition else 0\n composition[agent_type] += abundance * local_abundance\n return composition","def analysis_function_num_clusters(self,clustering):\n return len(clustering.clusters)","def collectInitialeccnStatistics(self, folder, databaseFilename, multiplicityFactor = 1.0, deformedNuclei = False):\n typeCollections = ((1, 'sn'), (2,'en'))\n for ecc_id, ecc_type_name in typeCollections:\n db = SqliteDB(path.join(folder, databaseFilename % ecc_type_name))\n # first write the ecc_id_lookup table, makes sure there is only one such table\n if db.createTableIfNotExists(\"ecc_id_lookup\", ((\"ecc_id\",\"integer\"), (\"ecc_type_name\",\"text\"))):\n db.insertIntoTable(\"ecc_id_lookup\", (ecc_id, ecc_type_name))\n\n # next create the eccentricities and collisionParameters table\n db.createTableIfNotExists(\"eccentricities\", ((\"event_id\",\"integer\"), (\"ecc_id\", \"integer\"), (\"n\",\"integer\"), (\"ecc_real\",\"real\"), (\"ecc_imag\",\"real\")))\n db.createTableIfNotExists(\"collisionParameters\", ((\"event_id\",\"integer\"), (\"Npart\", \"integer\"), (\"Ncoll\",\"integer\"), (\"b\",\"real\"), (\"total_entropy\",\"real\")))\n if(deformedNuclei):\n db.createTableIfNotExists(\"deformationParameters\", ((\"event_id\",\"integer\"), (\"cosTheta1\", \"real\"), (\"phi1\",\"real\"), (\"cosTheta2\",\"real\"), (\"phi2\",\"real\")))\n\n # the big loop\n for iorder in range(1,10):\n data = loadtxt(path.join(folder, '%s_ecc_eccp_%d.dat' %(ecc_type_name, iorder)))\n if iorder == 1:\n Npart = data[:,4]\n Ncoll = data[:,5]\n dSdy = data[:,6]/multiplicityFactor #scale out the multiplicity factor used in superMC\n b = data[:,7]\n for event_id in range(len(Npart)):\n db.insertIntoTable(\"collisionParameters\", (event_id, int(Npart[event_id]), int(Ncoll[event_id]), float(b[event_id]), float(dSdy[event_id])))\n if(deformedNuclei):\n cosTheta1 = data[:,8]\n phi1 = data[:,9]\n cosTheta2 = data[:,10]\n phi2 = data[:,11]\n for event_id in range(len(Npart)):\n db.insertIntoTable(\"deformationParameters\", (event_id, float(cosTheta1[event_id]), float(phi1[event_id]), float(cosTheta2[event_id]), float(phi2[event_id])))\n eccReal = data[:,2]\n eccImag = data[:,3]\n for event_id in range(len(eccReal)):\n db.insertIntoTable(\"eccentricities\",(event_id, ecc_id, iorder, float(eccReal[event_id]), float(eccImag[event_id])))\n\n # close connection to commit changes\n db.closeConnection()","def effective_cluster_weights(self):\n weights = np.array(\n [\n np.sum(\n self._subspace.function_ordering_multiplicities[\n self._subspace.function_orbit_ids == i\n ]\n * self.eci[self.eci_orbit_ids == i] ** 2\n )\n for i in range(len(self._subspace.orbits) + 1)\n ]\n )\n return weights","def formAdjacencyMatrix(self):\n self.adjacencyMatrix = dict()\n for i in self.node:\n self.adjacencyMatrix[i] = dict()\n for j in self.node:\n self.adjacencyMatrix[i][j] = 0\n \n for ij in self.link:\n self.adjacencyMatrix[self.link[ij].tail][self.link[ij].head] = 1","def __init__(self, dictAlg):\n\n # values of dict dictAlg are DataSetList which should have only one\n # element which will be assigned as values in the following lines.\n d = set()\n f = set()\n for i in dictAlg.values():\n d |= set(j.dim for j in i)\n f |= set(j.funcId for j in i)\n\n if len(f) > 1 or len(d) > 1:\n Usage('Expect the data of algorithms for only one function and '\n 'one dimension.')\n\n f = f.pop()\n d = d.pop()\n\n dictMaxEvals = {}\n dictFinalFunVals = {}\n tmpdictAlg = {}\n for alg, i in dictAlg.iteritems():\n if len(i) == 0:\n warnings.warn('Algorithm %s was not tested on f%d %d-D.'\n % (alg, f, d))\n continue\n elif len(i) > 1:\n warnings.warn('Algorithm %s has a problem on f%d %d-D.'\n % (alg, f, d))\n continue\n\n tmpdictAlg[alg] = i[0] # Assign ONLY the first element as value\n dictMaxEvals[alg] = i[0].maxevals\n dictFinalFunVals[alg] = i[0].finalfunvals\n\n dictAlg = tmpdictAlg\n\n sortedAlgs = dictAlg.keys()\n # algorithms will be sorted along sortedAlgs which is now a fixed list\n\n # Align ERT\n erts = list(np.transpose(np.vstack([dictAlg[i].target, dictAlg[i].ert]))\n for i in sortedAlgs)\n res = readalign.alignArrayData(readalign.HArrayMultiReader(erts))\n\n resalgs = []\n reserts = []\n # For each function value\n for i in res:\n # Find best algorithm\n curerts = i[1:]\n assert len((np.isnan(curerts) == False)) > 0\n currentbestert = np.inf\n currentbestalg = ''\n for j, tmpert in enumerate(curerts):\n if np.isnan(tmpert):\n continue # TODO: don't disregard these entries\n if tmpert == currentbestert:\n # TODO: what do we do in case of ties?\n # look at function values corresponding to the ERT?\n # Look at the function evaluations? the success ratio?\n pass\n elif tmpert < currentbestert:\n currentbestert = tmpert\n currentbestalg = sortedAlgs[j]\n reserts.append(currentbestert)\n resalgs.append(currentbestalg)\n\n dictiter = {}\n dictcurLine = {}\n resDataSet = []\n\n # write down the #fevals to reach the function value.\n for funval, alg in zip(res[:, 0], resalgs):\n it = dictiter.setdefault(alg, iter(dictAlg[alg].evals))\n curLine = dictcurLine.setdefault(alg, np.array([np.inf, 0]))\n while curLine[0] > funval:\n try:\n curLine = it.next()\n except StopIteration:\n break\n dictcurLine[alg] = curLine.copy()\n tmp = curLine.copy()\n tmp[0] = funval\n resDataSet.append(tmp)\n\n setalgs = set(resalgs)\n dictFunValsNoFail = {}\n for alg in setalgs:\n for curline in dictAlg[alg].funvals:\n if (curline[1:] == dictAlg[alg].finalfunvals).any():\n # only works because the funvals are monotonous\n break\n dictFunValsNoFail[alg] = curline.copy()\n\n self.evals = resDataSet\n # evals is not a np array but a list of arrays because they may not\n # all be of the same size.\n self.maxevals = dict((i, dictMaxEvals[i]) for i in setalgs)\n self.finalfunvals = dict((i, dictFinalFunVals[i]) for i in setalgs)\n self.funvalsnofail = dictFunValsNoFail\n self.dim = d\n self.funcId = f\n self.algs = resalgs\n self.algId = 'Virtual Best Algorithm'\n self.comment = 'Combination of ' + ', '.join(sortedAlgs)\n self.ert = np.array(reserts)\n self.target = res[:, 0]\n\n bestfinalfunvals = np.array([np.inf])\n for alg in sortedAlgs:\n if np.median(dictAlg[alg].finalfunvals) < np.median(bestfinalfunvals):\n bestfinalfunvals = dictAlg[alg].finalfunvals\n algbestfinalfunvals = alg\n self.bestfinalfunvals = bestfinalfunvals\n self.algbestfinalfunvals = algbestfinalfunvals","def _estimate_assignments(self, graph: GraphRepresentation) -> None:\n embed_graph = augment_diagonal(graph)\n latent = AdjacencySpectralEmbed(\n n_components=self.n_components, **self.embed_kws\n ).fit_transform(embed_graph)\n if isinstance(latent, tuple):\n latent = np.concatenate(latent, axis=1)\n gc = GaussianCluster(\n min_components=self.min_comm,\n max_components=self.max_comm,\n **self.cluster_kws\n )\n vertex_assignments = gc.fit_predict(latent) # type: ignore\n self.vertex_assignments_ = vertex_assignments","def add_clusterings(self, clustering):\n self.clustering.append(clustering)","def bases(layout, mvClass=MultiVector, grades=None):\n\n dict = {}\n for i in range(layout.gaDims):\n grade = layout.gradeList[i]\n if grade != 0:\n if grades is not None and grade not in grades:\n continue\n v = np.zeros((layout.gaDims,), dtype=int)\n v[i] = 1\n dict[layout.names[i]] = mvClass(layout, v)\n return dict","def calculate_components(self, parts):\n target = {}\n for part in parts:\n rank = part[0]\n\n try:\n face = part[1]\n except IndexError:\n face = '*'\n\n try:\n target[rank][face] += 1\n except KeyError:\n if rank not in target:\n target[rank] = {}\n target[rank][face] = 1\n\n return target","def kl_divergence(self):\r\n\r\n target_columns = list(self.origdst.columns[11:-3])\r\n target_columns.append(self.origdst.columns[1]) # channel\r\n target_columns.append(self.origdst.columns[2]) # program_title\r\n target_columns.append(self.origdst.columns[3]) # genre\r\n\r\n kl_dict = {}\r\n\r\n for col in target_columns:\r\n\r\n try:\r\n\r\n col_counts_orig = self.origdst[col].value_counts(normalize=True).sort_index(ascending=True)\r\n col_counts_synth = self.synthdst[col].value_counts(normalize=True).sort_index(ascending=True)\r\n\r\n kl = sum(rel_entr(col_counts_orig.tolist(), col_counts_synth.tolist()))\r\n\r\n kl_dict[col] = kl\r\n\r\n except:\r\n\r\n print('For the column ', col, ' you must generate the same unique values as the real dataset.')\r\n print('The number of unique values than you should generate for column ', col, 'is ',\r\n len(self.origdst[col].unique()))\r\n\r\n return kl_dict"],"string":"[\n \"def generate_clustering_info(self, algorithm_type, clustering_parameters, clusterings = []):\\n clustering_info = {}\\n for i, running_parameters in enumerate(clustering_parameters):\\n\\n clustering_id = \\\"clustering_%04d\\\"%(self.current_clustering_id)\\n self.current_clustering_id += 1\\n clustering_info[clustering_id] = {\\n \\\"type\\\":algorithm_type,\\n \\\"clustering\\\": None,\\n \\\"parameters\\\": running_parameters\\n }\\n\\n if clusterings != []:\\n clustering_info[clustering_id][\\\"clustering\\\"] = clusterings[i]\\n\\n return clustering_info\",\n \"def enumerate_clusterings(self):\\n\\n # Initialize an empty list of clusterings. Each element of the list\\n # is a dictionary mapping NOEs to the signatures they are clustered to\\n # in a solution. Each clustering is initialize with all uniquely\\n # clusterable NOEs as keys mapping to their unique clusters\\n\\n clusterings = []\\n\\n while True:\\n\\n # Run the solver and get a solution back\\n\\n solution = self.solve()\\n\\n # If UNSAT, then flush aux clauses from the formula and return\\n # all the clusterings we found so far\\n\\n if not solution:\\n self.flush()\\n return clusterings\\n\\n # Iterate over the clustering variables set to true by in the\\n # discovered solution. Forbid this clustering from reoccuring and\\n # add it to the list of found clusterings\\n\\n clause = []\\n clustering = {}\\n for node in self.clustering_variables.keys():\\n if len(node.clusters) == 1:\\n clustering[node] = list(node.clusters)[0]\\n\\n for vtype, node, cluster in solution:\\n if vtype == Formula.CST_VAR:\\n clustering[node] = cluster\\n clause.append(-self.clustering_variables[node][cluster])\\n\\n self.add_clause(clause)\\n clusterings.append(clustering)\",\n \"def matrix_dist(self):\\n matrix_dic = {}\\n for clus in self.clusters:\\n for other_clus in self.clusters:\\n if clus.samples[0].s_id > other_clus.samples[0].s_id: # avoid duplicates\\n matrix_dic[(clus.samples[0].s_id, other_clus.samples[0].s_id)] = clus.samples[0]\\\\\\n .compute_euclidean_distance(other_clus.samples[0])\\n return matrix_dic\",\n \"def _eval_clustering(self, gen_reviews, clusters, embedding_model, clustering):\\n result = []\\n preds = self.predict_gen(gen_reviews, embedding_model, clustering)\\n\\n acc = accuracy_score(np.array(clusters), np.array(preds))\\n conf = confusion_matrix(np.array(clusters), np.array(preds))\\n\\n return acc, conf\",\n \"def clustering_and_visulization(self):\\n centroids, _ = kmeans(self.data_mat, self.k)\\n idx, _ = vq(self.data_mat, centroids)\\n for i in range(self.k):\\n\\n self.plot_list.append(self.data_mat[idx == i, 0])\\n self.plot_list1.append(self.data_mat[idx == i, 1])\\n\\n for j in range(self.k):\\n plot(self.plot_list[j], self.plot_list1[j], self.color_code[j])\\n plot(centroids[:, 0], centroids[:, 1], 'sg', markersize=8)\\n show()\\n for i in range(self.k):\\n self.cluster = self.data_mat[idx == i]\\n self.clusterlist.append(self.cluster)\\n\\n for i in range(len(self.clusterlist)):\\n self.clusterdict[i] = self.clusterlist[i]\\n print(self.clusterdict)\\n\\n\\n self.indexdict = {}\\n for i in self.clusterdict:\\n self.indexdict[i] = []\\n print(len(self.clusterdict))\\n for i in range(len(idx)):\\n for j in range(len(self.clusterdict)):\\n if (self.clusterdict[j][:] == self.data_mat[i]).any():\\n self.indexdict[j].append(i)\\n print(\\\"cluster dict of packs\\\",self.indexdict)\\n\\n self.drugdict = {}\\n for i in self.clusterdict:\\n self.drugdict[i] = []\\n self.drug=[]\\n for i in range(len(self.indexdict.keys())):\\n for j in range(len(self.indexdict[i])):\\n self.drugdict[i].append(self.df.iloc[self.indexdict[i][j]].to_dict())\\n print(\\\"drugs dict with their frequencies\\\",self.drugdict)\\n clusterdict_from_df_as_drug_non_O_frequency = {}\\n clusterdict_from_as_drugs_only_as_list = {}\\n clusterdict_of_non_repeated_drugs ={}\\n for i in self.drugdict:\\n clusterdict_from_df_as_drug_non_O_frequency[i] = []\\n for i in self.drugdict:\\n for j in self.drugdict[i]:\\n clusterdict_from_df_as_drug_non_O_frequency[i].append({x: y for x, y in j.items() if y != 0})\\n print(\\\"clusterdict_from_df_as_drug_non_O_frequency\\\", clusterdict_from_df_as_drug_non_O_frequency)\\n print('\\\\n')\\n\\n for i in self.drugdict:\\n clusterdict_from_as_drugs_only_as_list[i] = []\\n\\n for i in self.drugdict:\\n for j in clusterdict_from_df_as_drug_non_O_frequency[i]:\\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\\n\\n print(\\\"only keys drugs with drugs name\\\", clusterdict_from_as_drugs_only_as_list)\\n print('\\\\n')\\n\\n\\n for i in self.drugdict:\\n clusterdict_of_non_repeated_drugs[i]=list(more_itertools.collapse([list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\\n\\n\\n print(\\\"only drugs only\\\", clusterdict_of_non_repeated_drugs)\\n\\n########################################################################################################################\\n try:\\n common_drug_list = [x for x in clusterdict_of_non_repeated_drugs[0] if x in clusterdict_of_non_repeated_drugs[1]]\\n print('\\\\n')\\n print(\\\"common drug list\\\", common_drug_list)\\n total_frequency_of_drugs_dict = {}\\n for i in self.drugdict:\\n total_frequency_of_drugs_dict[i] = []\\n\\n for drug in common_drug_list:\\n\\n for cluster_keys in clusterdict_from_df_as_drug_non_O_frequency.keys():\\n temp_list = []\\n for cluster_values_as_list in clusterdict_from_df_as_drug_non_O_frequency[cluster_keys]:\\n try:\\n temp_list.append(cluster_values_as_list[str(drug)])\\n except KeyError:\\n print(\\\"\\\\t\\\")\\n total_frequency_of_drugs_dict[cluster_keys].append(np.sum(temp_list))\\n print(\\\"total drugs frequency\\\",total_frequency_of_drugs_dict)\\n total_frequency_of_drugs_dict_with_drugs = {}\\n for i in self.drugdict:\\n total_frequency_of_drugs_dict_with_drugs[i] = []\\n temp_list1 = []\\n temp_list2 = []\\n for keys in self.drugdict.keys():\\n temp_list1.append(clusterdict_of_non_repeated_drugs[keys])\\n for keys in self.drugdict.keys():\\n temp_list2.append(total_frequency_of_drugs_dict[keys])\\n temp_list3 = []\\n for i in temp_list1:\\n for j in temp_list2:\\n temp_list3.append(dict(zip(i,j)))\\n temp_list4 = temp_list3[:2]\\n print('\\\\n')\\n for keys in self.drugdict:\\n total_frequency_of_drugs_dict_with_drugs[keys].append(temp_list4[keys])\\n print(\\\"total frequency with drugs dict\\\",total_frequency_of_drugs_dict_with_drugs)\\n\\n final_drugs_in_clusters_dict = {}\\n for i in self.drugdict:\\n final_drugs_in_clusters_dict[i] = []\\n compare_list = []\\n for drug in common_drug_list:\\n compare_list.append(min(total_frequency_of_drugs_dict_with_drugs[0][0][drug], total_frequency_of_drugs_dict_with_drugs[1][0][drug]))\\n print(\\\"compare list\\\",compare_list)\\n for values in total_frequency_of_drugs_dict_with_drugs.values():\\n for key1, value1 in values[0].items():\\n if value1 in compare_list:\\n\\n key2 =values[0].keys()[values[0].values().index(value1)]\\n values[0].pop(key2, None)\\n\\n\\n print('final dict with deleted keys', total_frequency_of_drugs_dict_with_drugs)\\n\\n clusterdict_from_as_drugs_only_as_list = {}\\n clusterdict_of_non_repeated_drugs = {}\\n\\n for i in self.drugdict:\\n clusterdict_from_as_drugs_only_as_list[i] = []\\n\\n for i in self.drugdict:\\n for j in total_frequency_of_drugs_dict_with_drugs[i]:\\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\\n print(\\\"only keys drugs with drugs name\\\", clusterdict_from_as_drugs_only_as_list)\\n print('\\\\n')\\n\\n for i in self.drugdict:\\n clusterdict_of_non_repeated_drugs[i] = list(more_itertools.collapse([list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\\n print(\\\"only drugs\\\",clusterdict_of_non_repeated_drugs)\\n\\n final_robot_packs_dict = {}\\n for i in self.drugdict:\\n final_robot_packs_dict[i] = []\\n\\n winner_drug_dict = {}\\n for i in common_drug_list:\\n winner_drug_dict[i] = []\\n for drug in common_drug_list:\\n if drug in clusterdict_of_non_repeated_drugs[0]:\\n winner_drug_dict[str(drug)].append(0)\\n if drug in clusterdict_of_non_repeated_drugs[1]:\\n winner_drug_dict[str(drug)].append(1)\\n print(\\\"winner drug dict\\\",winner_drug_dict)\\n\\n for i in self.indexdict:\\n print(i)\\n for pack in self.indexdict[i]:\\n packdict = self.df.iloc[pack].to_dict()\\n packdict_non_0 = {x: y for x, y in packdict.items() if y != 0}\\n packdict_non_0_key = packdict_non_0.keys()\\n for drug in packdict_non_0_key:\\n if drug in clusterdict_of_non_repeated_drugs[0]:\\n final_robot_packs_dict[0].append(pack)\\n elif drug in clusterdict_of_non_repeated_drugs[1]:\\n final_robot_packs_dict[1].append(pack)\\n\\n final_robot_packs_dict[i].append(pack)\\n for commondrugs in winner_drug_dict:\\n for winnercluster in winner_drug_dict[commondrugs]:\\n if winnercluster==0:\\n loosercluster =1\\n if winnercluster == 1:\\n loosercluster = 0\\n if commondrugs in packdict_non_0_key and i==loosercluster:\\n try:\\n final_robot_packs_dict[i].remove(pack)\\n final_robot_packs_dict[winnercluster].append(pack)\\n except ValueError:\\n print('\\\\t')\\n\\n for i in self.indexdict:\\n final_robot_packs_dict[i] = set(final_robot_packs_dict[i])\\n\\n print(\\\"final which pack which robot dict\\\",final_robot_packs_dict)\\n\\n except IndexError:\\n print(\\\"No common drugs\\\")\",\n \"def cluster(self):\\n\\t\\tself.index[\\\"cluster\\\"] = {}\\n\\n\\t\\tfor item in self.index[\\\"items\\\"]:\\n\\t\\t\\tself.index[\\\"cluster\\\"][item] = [{\\\"weight\\\" : float(len(set(self.index[\\\"items\\\"][item]).intersection( set(self.index[\\\"items\\\"][id]))))/float(len(self.index[\\\"items\\\"][item])) , \\\"name\\\" : id, \\\"authority\\\" : set(self.index[\\\"items\\\"][item]).intersection( set(self.index[\\\"items\\\"][id])) } for id in self.index[\\\"items\\\"] if id != item and len(set(self.index[\\\"items\\\"][item]).intersection( set(self.index[\\\"items\\\"][id]))) >= 1]\\n\\n\\t\\treturn self.index\",\n \"def evaluate_clustering_methods(methods):\\r\\n results = {}\\r\\n for m in methods:\\r\\n res = results[m['name']] = {}\\r\\n prec = 3\\r\\n res['Adjusted Rand Score'] = round(sklearn.metrics.adjusted_rand_score(m['target'], m['clustering']),prec)\\r\\n res['Normalized Mutual Information'] = round(sklearn.metrics.normalized_mutual_info_score(m['target'], m['clustering']),prec)\\r\\n res['Adjusted Mutual Information'] = round(sklearn.metrics.adjusted_mutual_info_score(m['target'], m['clustering']),prec)\\r\\n return np.transpose(results)\",\n \"def clustering(distribution, areal_units, classes=None):\\n\\n # Regroup into classes if specified. Otherwise return categories indicated\\n # in the data\\n if not classes:\\n classes = return_categories(distribution) \\n \\n ## Get the number of neighbourhoods\\n neigh = mb.neighbourhoods(distribution, areal_units, classes)\\n num_neigh = {cl: len(neigh[cl]) for cl in classes}\\n num_units = {cl: len([a for ne in neigh[cl] for a in ne])\\n for cl in classes}\\n\\n ## Compute clustering values\\n clustering = {}\\n for cl in classes:\\n if num_units[cl] == 0:\\n clustering[cl] = float('nan')\\n elif num_units[cl] == 1:\\n clustering[cl] = 1\\n else:\\n clustering[cl] = _single_clustering(num_units[cl],\\n num_neigh[cl])\\n\\n clustering[cl] = ((num_neigh[cl] - num_units[cl]) /\\n (1 - num_units[cl]))\\n return clustering\",\n \"def get_clustering_algorithm_class(cls):\\n return {\\n \\\"spectral\\\": SpectralClusteringAlgorithm,\\n \\\"dbscan\\\": DBSCANAlgorithm,\\n \\\"gromos\\\": GromosAlgorithm,\\n \\\"kmedoids\\\": KMedoidsAlgorithm,\\n \\\"random\\\": RandomClusteringAlgorithm,\\n \\\"hierarchical\\\": HierarchicalClusteringAlgorithm\\n }\",\n \"def cluster_all_features(feature_mat):\\n n_dims = feature_mat.shape[1]\\n whitened = whiten(feature_mat.transpose())\\n all_codebooks = dict()\\n for k in range(n_dims, 0, -1):\\n centroids, distortion = kmeans(whitened, k)\\n all_codebooks[k] = (distortion, centroids)\\n\\n return all_codebooks\",\n \"def create_clusters(self):\\n ex = 0\\n print 'Iter - Purity Gini Index'\\n while ex < self.MAX_ITERATION:\\n new_clusters = np.zeros(self.centroids.shape)\\n distances = euclidean_distances(self.vectors, self.centroids).argmin(axis=1)\\n for i in range(self.K):\\n indexes = np.argwhere(distances == i)\\n data = self.vectors[indexes.transpose()[0]]\\n if data.shape[0] > 1:\\n new_clusters[i] = (np.sum(data, axis=0) / data.shape[0])\\n else:\\n new_clusters[i] = np.sum(data, axis=0)\\n print ex, '----', self.cal_purity()\\n ex += 1\\n if np.allclose(self.centroids, new_clusters, atol=self.TOLERANCE):\\n break\\n self.centroids = new_clusters\",\n \"def update(self, clusters):\\n centroids = {}\\n for cluster, coordinates in clusters.iteritems():\\n sumLat = 0\\n sumLong = 0\\n for coordinate in coordinates:\\n sumLat += float(coordinate[0])\\n sumLong += float(coordinate[1])\\n centroids[cluster] = (sumLat/float(len(coordinates)), sumLong/float(len(coordinates)))\\n return centroids\",\n \"def evaulate_clusters(self, pred_dict, model_dir):\\n\\t\\tclustering_dict = {\\\"Topic\\\":[], \\\"Text\\\":[], \\\"Keywords\\\": []}\\n\\t\\tfor cluster_num, sents_list in pred_dict.items():\\n\\t\\t\\tprint(\\\"\\\\n cluster number : \\\", cluster_num)\\n\\t\\t\\tprint(\\\"\\\\n number of sents : \\\", len(sents_list))\\n\\t\\t\\ttfidf_vec = TfidfVectorizer(use_idf=True, sublinear_tf=True, max_df=0.8, max_features=20, ngram_range=(1,5), min_df=1)\\n\\t\\t\\tX_tfidf = tfidf_vec.fit_transform(sents_list).toarray()\\n\\t\\t\\ttotal_tfidf = tfidf_vec.get_feature_names()\\n\\t\\t\\tfor sent in sents_list:\\n\\t\\t\\t\\tclustering_dict[\\\"Topic\\\"].append(cluster_num)\\n\\t\\t\\t\\tclustering_dict[\\\"Text\\\"].append(sent)\\n\\t\\t\\t\\tclustering_dict[\\\"Keywords\\\"].append(\\\",\\\".join(total_tfidf))\\n\\t\\t\\\"\\\"\\\" save the clusters to csv file \\\"\\\"\\\"\\n\\t\\tdf_dominant_topic = defaultdict(list) \\n\\t\\tdf_dominant_topic[\\\"Topic\\\"] = clustering_dict[\\\"Topic\\\"]\\n\\t\\tdf_dominant_topic[\\\"Text\\\"] = clustering_dict[\\\"Text\\\"]\\n\\t\\tdf_dominant_topic[\\\"Keywords\\\"] = clustering_dict[\\\"Keywords\\\"]\\n\\t\\tdf_dominant_topic = pd.DataFrame(df_dominant_topic)\\n\\t\\tdf_dominant_topic.to_csv(os.path.join(model_dir, \\\"cluster_sentence_topic_mapping.csv\\\"))\\n\\t\\treturn df_dominant_topic\",\n \"def calc_cc(graph):\\n\\tclustering_coeffs = {}\\n\\tfor node in graph.nodes():\\n\\t\\tclustering_coeffs[node] = { \\\"cc\\\" : nx.clustering(graph, node)}\\n\\tnx.set_node_attributes(graph, clustering_coeffs)\",\n \"def gen_cluster_accuracies():\\n accuracies = {}\\n with Parallel(n_jobs=morphs.parallel.N_JOBS) as parallel:\\n for block_path in morphs.paths.blocks():\\n print(block_path)\\n spikes = morphs.load.ephys_data(block_path, collapse_endpoints=True)\\n\\n if len(spikes[\\\"recording\\\"].unique()) >= 1:\\n template_spikes = spikes[spikes[\\\"stim_id\\\"].isin(list(\\\"abcdefgh\\\"))]\\n assert len(template_spikes) > 0\\n cluster_groups = template_spikes.groupby(\\\"cluster\\\")\\n\\n morph_dims = spikes.morph_dim.unique()\\n morph_dims = morph_dims[~pd.isnull(morph_dims)]\\n morph_dims.sort()\\n\\n max_num_reps = np.max(\\n [\\n len(stim_group.groupby(by=[\\\"recording\\\", \\\"stim_presentation\\\"]))\\n for stim_id, stim_group in template_spikes.groupby(\\\"stim_id\\\")\\n ]\\n )\\n\\n accuracies_list = parallel(\\n delayed(cluster_accuracy)(\\n cluster, cluster_group, morph_dims, max_num_reps\\n )\\n for (cluster, cluster_group) in cluster_groups\\n )\\n\\n accuracies[block_path] = pd.concat(accuracies_list)\\n\\n morphs.paths.PROCESSED_DIR.mkdir(parents=True, exist_ok=True)\\n with open(morphs.paths.ACCURACIES_PKL.as_posix(), \\\"wb\\\") as f:\\n pickle.dump(accuracies, f)\",\n \"def clustering_and_visulization(self):\\n try:\\n centroids, _ = kmeans(self.data_mat, self.k)\\n except ValueError:\\n print(\\\"The number of clusters is more than the data points\\\")\\n self.idx, _ = vq(self.data_mat, centroids)\\n for i in range(self.k):\\n\\n self.plot_list.append(self.data_mat[self.idx == i, 0])\\n self.plot_list1.append(self.data_mat[self.idx == i, 1])\\n\\n for j in range(self.k):\\n plot(self.plot_list[j], self.plot_list1[j], self.color_code[j])\\n plot(centroids[:, 0], centroids[:, 1], 'sg', markersize=8)\\n show()\\n\\n for i in range(self.k):\\n self.cluster = self.data_mat[self.idx == i]\\n self.clusterlist.append(self.cluster)\\n print(self.clusterlist)\\n for i in range(len(self.clusterlist)):\\n self.clusterdict[i] = self.clusterlist[i]\\n print(self.clusterdict)\\n\\n index_dict ={}\\n for i in self.clusterdict:\\n index_dict[i] = []\\n for i in range(len(self.data_mat)):\\n for j in range(len(self.clusterdict)):\\n if (self.clusterdict[j][:] == self.data_mat[i]).any():\\n index_dict[j].append(i)\\n print(\\\"drugs cluster dict\\\", index_dict)\\n\\n self.drugsdict = {}\\n for i in index_dict:\\n self.drugsdict[i] = []\\n drugslist = list(self.df.columns.values)\\n print(\\\"drugs list from dataframe\\\", drugslist)\\n\\n for i in index_dict:\\n self.drugsdict[i] = [drugslist[index] for index in index_dict[i]]\\n\\n print(\\\"drugs cluster dict\\\", self.drugsdict)\\n########################################################################################################################\\n clusterdict_from_df_as_drug_frequency = {}\\n clusterdict_from_df_as_drug_non_O_frequency = {}\\n\\n print('\\\\n')\\n\\n for i in range(len(self.df)):\\n clusterdict_from_df_as_drug_frequency[i] = []\\n\\n for i in range(len(self.df)):\\n clusterdict_from_df_as_drug_frequency[i].append(self.df.iloc[i].to_dict()) #\\n print(\\\"packs in dict form of drugs frequency\\\", clusterdict_from_df_as_drug_frequency)\\n\\n for i in range(len(self.df)):\\n clusterdict_from_df_as_drug_non_O_frequency[i] = []\\n\\n for i in range(len(self.df)):\\n for j in clusterdict_from_df_as_drug_frequency[i]:\\n clusterdict_from_df_as_drug_non_O_frequency[i].append({x: y for x, y in j.items() if y != 0})\\n print(\\\"clusterdict_from_df_as_drug_non_O_frequency\\\", clusterdict_from_df_as_drug_non_O_frequency)\\n print('\\\\n')\\n clusterdict_from_as_drugs_only_as_list = {}\\n clusterdict_of_non_repeated_drugs = {}\\n for i in range(len(self.df)):\\n clusterdict_from_as_drugs_only_as_list[i] = []\\n\\n for i in range(len(self.df)):\\n for j in clusterdict_from_df_as_drug_non_O_frequency[i]:\\n clusterdict_from_as_drugs_only_as_list[i].append(j.keys())\\n\\n print(\\\"only keys drugs with drugs name\\\", clusterdict_from_as_drugs_only_as_list)\\n print('\\\\n')\\n\\n for i in range(len(self.df)):\\n clusterdict_of_non_repeated_drugs[i] = list(more_itertools.collapse(\\n [list(x) for x in set([tuple(x) for x in clusterdict_from_as_drugs_only_as_list[i]])]))\\n\\n print(\\\"only drugs only\\\", clusterdict_of_non_repeated_drugs)\\n\\n########################################################################################################################\\n robot_for_packs_dict = {}\\n for i in range(len(self.df)):\\n robot_for_packs_dict[i] = []\\n\\n # for i in range(len(self.df)):\\n for i in range(len(self.df)):\\n for j in clusterdict_of_non_repeated_drugs[i]:\\n if j in self.drugsdict[0]:\\n robot_for_packs_dict[i].append(0)\\n elif j in self.drugsdict[1]:\\n robot_for_packs_dict[i].append(1)\\n for i in range(len(self.df)):\\n robot_for_packs_dict[i] = set(robot_for_packs_dict[i])\\n\\n for i in range(len(self.df)):\\n robot_for_packs_dict[i] = list(more_itertools.collapse(robot_for_packs_dict[i]))\\n print('\\\\n')\\n print(\\\"clusterdict_of_non_repeated_drugs\\\", robot_for_packs_dict)\",\n \"def cluster_classification(weblog,classification_column_transaction,\\\\\\n classification_column_diversity, session_data_threshold, cluster_type, classification_wanted_transaction, verbose = False):\\n if verbose== True:\\n start_time = timelib.time()\\n print(\\\"\\\\n * Computing cluster matrices ...\\\") \\n browsing_matrix = {}\\n diversifying_matrix = {}\\n # Selecting sessions from each cluster\\n for cluster_id in session_data_threshold[cluster_type].unique():\\n sessions_cluster = session_data_threshold[session_data_threshold[cluster_type]==cluster_id].session_id\\n divpat_log = weblog[weblog.session_id.isin(sessions_cluster)]\\n # Filtering some requests\\n divpat_log=divpat_log[divpat_log['requested_'+classification_column_transaction].isin(classification_wanted_transaction)]\\n divpat_log=divpat_log[divpat_log['referrer_'+classification_column_transaction].isin(classification_wanted_transaction)]\\n \\n # Defining matrices\\n diversity_columns=('referrer_'+classification_column_diversity,'requested_'+classification_column_diversity)\\n browsing_matrix[cluster_id],_ = compute_browsing_matrix(divpat_log,'referrer_'+classification_column_transaction,'requested_'+classification_column_transaction,labels=classification_wanted_transaction)\\n diversifying_matrix[cluster_id],_ = compute_diversifying_matrix(divpat_log,'referrer_'+classification_column_transaction,'requested_'+classification_column_transaction,\\\\\\n diversity_columns,labels = classification_wanted_transaction)\\n if verbose == True:\\n print(\\\" Cluster matrices computed in %.1f seconds.\\\"%(timelib.time() - start_time))\\n \\n return browsing_matrix, diversifying_matrix;\",\n \"def _granger_causality(self):\\r\\n gc = dict(frequencies={}, gc_xy={}, gc_yx={}, gc_sim={},\\r\\n spectral_density={})\\r\\n for i, j in self.ij:\\r\\n w, f_x2y, f_y2x, f_xy, Sw = \\\\\\r\\n alg.granger_causality_xy(self.model_coef[i, j],\\r\\n self.error_cov[i, j],\\r\\n n_freqs=self._n_freqs)\\r\\n\\r\\n # All other measures are dependent on i, j:\\r\\n gc['gc_xy'][i, j] = f_x2y\\r\\n gc['gc_yx'][i, j] = f_y2x\\r\\n gc['gc_sim'][i, j] = f_xy\\r\\n gc['spectral_density'][i, j] = Sw\\r\\n\\r\\n return gc\",\n \"def compute_clusters(self, documents):\\n ###TODO\\n for d in range(0, len(documents)):\\n maxi = 999999999\\n for cid in range(0, len(self.means)):\\n dist = self.distance(documents[d], self.means[cid], self.norms[cid])\\n if dist < maxi:\\n maxi = dist\\n clust = cid \\n self.cluster[d] = clust\",\n \"def kmode_calculation(self, data):\\n col_dict = {}\\n\\n for col in data.columns:\\n data[col] = data[col].astype('category')\\n col_dict.update({col: dict(enumerate(data[col].cat.categories))})\\n\\n # Get all the cols in the DataFrame\\n cols = [col for col in data.columns]\\n\\n # Transform all values into categorical and numerical values\\n for col in cols:\\n data[col] = data[col].astype('category')\\n data[col] = data[col].cat.codes\\n\\n # Run k-modes using the algorithm\\n kmodes_method = KModes(n_clusters=self.n_cluster, init=self.init_method, n_init=self.n_iter, verbose=1)\\n kmode_result = kmodes_method.fit_predict(data[cols])\\n\\n # Attach the output label for each data point\\n data['classification'] = pd.Series(kmode_result, index=data.index)\\n\\n return col_dict, kmodes_method.cluster_centroids_, data\",\n \"def _compute_centroids(self, encodings, labels):\\n counts = {}\\n centroids = {}\\n\\n # Copy encodings to avoid ref modification when computing centroid.\\n encodings = encodings.copy()\\n\\n for i, encoding in enumerate(encodings):\\n key = int(labels[i])\\n if key in centroids:\\n centroids[key] += encoding\\n counts[key] += 1\\n else:\\n centroids[key] = encoding\\n counts[key] = 1\\n for key in centroids:\\n centroids[key] /= counts[key]\\n self.centroids = centroids\",\n \"def get_clusters_adjacencies(adjacency, clusters: list):\\n clusters.sort(key=lambda t: len(t), reverse=True)\\n id_to_cluster = get_id_to_cluster(clusters, adjacency.shape[0])\\n num_clusters = len(clusters)\\n mat = np.zeros((num_clusters, num_clusters))\\n rows, cols = adjacency.nonzero()\\n for i, j in zip(rows, cols):\\n weight = adjacency[i, j]\\n src_cluster = id_to_cluster[i]\\n dest_cluster = id_to_cluster[j]\\n mat[src_cluster, dest_cluster] += weight\\n return mat\",\n \"def compute_confusion_matrix(num_clusters, clustered_points_algo, sorted_indices_algo):\\r\\n seg_len = 400\\r\\n true_confusion_matrix = np.zeros([num_clusters, num_clusters])\\r\\n for point in range(len(clustered_points_algo)):\\r\\n cluster = clustered_points_algo[point]\\r\\n num = (int(sorted_indices_algo[point]/seg_len) % num_clusters)\\r\\n true_confusion_matrix[int(num), int(cluster)] += 1\\r\\n return true_confusion_matrix\",\n \"def clustering_metrics(clusts, node_assn, node_pred):\\n pred_vox = cluster_to_voxel_label(clusts, node_pred)\\n true_vox = cluster_to_voxel_label(clusts, node_assn)\\n ari = ARI(pred_vox, true_vox)\\n ami = AMI(pred_vox, true_vox)\\n sbd = SBD(pred_vox, true_vox)\\n pur, eff = purity_efficiency(pred_vox, true_vox)\\n return ari, ami, sbd, pur, eff\",\n \"def get_clusters(ensemble, grouping, clustering):\\n\\n\\t# Prevent SQL injected since column names cannot be parameterized.\\n\\tif \\\";\\\" in ensemble or \\\";\\\" in grouping or \\\";\\\" in clustering:\\n\\t\\treturn None\\n\\n\\tensemble = ensemble.replace('EnsEns','Ens')\\n\\tdf = None;\\n\\n\\tif grouping in ['annotation','cluster']:\\n\\t\\tgroupingu = ensemble+\\\".\\\"+grouping+\\\"_\\\"+clustering\\n\\telif grouping in ['NeuN']:\\n\\t\\tgroupingu = \\\"CONCAT('NeuN',cells.\\\"+grouping+\\\")\\\"\\n\\telse:\\n\\t\\tgroupingu = \\\"cells.\\\"+grouping\\n\\n\\t# Get methylation info\\n\\tquery = \\\"SELECT count(cells.cell_id) ncells, 'snmC' as modality, \\\\\\n\\t\\t%(groupingu)s as groups \\\\\\n\\t\\tFROM cells \\\\\\n\\t\\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\\\\n\\t\\tGROUP BY groups \\\" % {'ensemble': ensemble,\\n\\t\\t\\t\\t\\t'groupingu': groupingu,\\n\\t\\t\\t\\t\\t'clustering': clustering}\\n\\ttry:\\n\\t\\tdf = pd.read_sql(query, db.get_engine(current_app, 'methylation_data'))\\n\\texcept exc.ProgrammingError as e:\\n\\t\\tnow = datetime.datetime.now()\\n\\t\\tprint(\\\"[{}] ERROR in app(get_clusters): {}\\\".format(str(now), e))\\n\\t\\tsys.stdout.flush()\\n\\t\\t# return None\\n\\n\\t# Get snATAC info\\n\\tquery = \\\"SELECT count(cells.cell_id) ncells, 'snATAC' AS modality, %(ensemble)s.cluster_ATAC groups \\\\\\n\\t\\tFROM cells \\\\\\n\\t\\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\\\\n\\t\\tGROUP BY groups \\\" % {'ensemble': ensemble,\\n\\t\\t\\t\\t\\t'grouping': grouping,\\n\\t\\t\\t\\t\\t'clustering': clustering}\\n\\n\\ttry:\\n\\t\\tdf_atac = pd.read_sql(query, db.get_engine(current_app, 'snATAC_data'))\\n\\t\\tdf=df.append(df_atac)\\n\\texcept exc.ProgrammingError as e:\\n\\t\\tnow = datetime.datetime.now()\\n\\t\\tprint(\\\"[{}] ERROR in app(get_clusters): {}\\\".format(str(now), e))\\n\\t\\tsys.stdout.flush()\\n\\n\\n\\t# Get snRNA info\\n\\tquery = \\\"SELECT count(cells.cell_id) ncells, 'RNA' AS modality, %(ensemble)s.cluster_RNA groups \\\\\\n\\t\\tFROM cells \\\\\\n\\t\\tINNER JOIN %(ensemble)s ON cells.cell_id = %(ensemble)s.cell_id \\\\\\n\\t\\tGROUP BY groups \\\" % {'ensemble': ensemble,\\n\\t\\t\\t\\t\\t'grouping': grouping,\\n\\t\\t\\t\\t\\t'clustering': clustering}\\n\\n\\ttry:\\n\\t\\tdf_rna = pd.read_sql(query, db.get_engine(current_app, 'RNA_data'))\\n\\t\\tdf=df.append(df_rna)\\n\\texcept exc.ProgrammingError as e:\\n\\t\\tnow = datetime.datetime.now()\\n\\t\\tprint(\\\"[{}] ERROR in app(get_clusters): {}\\\".format(str(now), e))\\n\\t\\tsys.stdout.flush()\\n\\n\\treturn df\",\n \"def index_nodes(self):\\n out = {}\\n\\n #avg = np.mean(list(self.rtype_vectors.values()),axis=0)\\n\\n\\n #for name, node in self.nodes.items():\\n # tmp1 = [self.rtype_vectors[rtype]\\n # for rtype, dest in node.outgoing_relations] or [NULL_VEC()]\\n # tmp2 = [permute_rtype_vector(self.rtype_vectors[rtype])\\n # for rtype, prev in node.incoming_relations] or [NULL_VEC()]\\n\\n # net = tmp1 + tmp2\\n\\n # #out[name] = np.asarray(net).mean(axis=0)\\n # #out[name] = np.asarray(net).sum(axis=0)\\n # v = np.asarray(net).sum(axis=0)\\n # if v.any():\\n # out[name] = v/max(v)#softmax(v/max(v))\\n # else:\\n # out[name] = v\\n\\n\\n #avg = np.mean(list(out.values()),axis=0)\\n\\n #maxm = np.max(list(out.values()),axis=0)\\n\\n ####normalize everything\\n #for r,v in out.items():\\n # if v.any():\\n # #out[r] = v / sqrt(v.dot(v))\\n # out[r] = softmax((v-avg)/maxm)\\n\\n\\n\\n # PCA method 0001701\\n rmap = self.rtype_vectors\\n data = np.zeros((len(self.nodes), JACCARD_DIMENSIONS), dtype=np.float)\\n ix = 0\\n for node in self.nodes.values():\\n\\n #compute weighted average of each relation type\\n tmp = [rmap[rtype] for \\n rtype, dest in node.outgoing_relations] + \\\\\\n [permute_rtype_vector(rmap[rtype]) for \\n rtype, prev in node.incoming_relations]\\n\\n v = np.asarray(tmp).mean(axis=0) if tmp else NULL_VEC()\\n\\n #normalize\\n if v.any():\\n data[ix] = v / sqrt(v.dot(v))\\n else:\\n data[ix] = v\\n ix += 1\\n\\n #eliminate projection onto first 7 principal components\\n d2 = data - PCA(data, 7)\\n\\n #order of nodes is preserved\\n for i,v in enumerate(self.nodes):\\n out[v] = softmax(d2[i])\\n\\n return out\",\n \"def evaluate(self):\\n results = dict()\\n for metric in self.metrics:\\n print('Evaluating clustering with metric %s' % metric)\\n if metric in LABEL_METRICS.keys():\\n results[metric] = LABEL_METRICS[metric](self.X, self.model.labels_)\\n results['adjusted_rand_score'] = SCORE_METRICS['adjusted_rand_score'](self.Y[:, 0], self.model.labels_)\\n self.results = results\\n return results\",\n \"def cluster_cal(self):\\n self.Cluster = []\\n for i in range(self.nodenum):\\n neighborhood_node = self.neighbor_node(i)\\n Node_num = len(neighborhood_node)\\n Count = self.neighbor_edge(neighborhood_node)\\n if(Node_num == 0 or Node_num == 1):\\n self.Cluster.append(0.5)\\n else:\\n self.Cluster.append(Count/(Node_num*(Node_num - 1)))\\n \\n self.cluster_coeff = np.average(self.Cluster)\",\n \"def _generate_adjacency_matrices(self):\\n self.adj_matrices = dict()\\n mes = []\\n args = []\\n for metaedge in self.metaedges:\\n mes.append(metaedge)\\n args.append(self._prepare_parallel_adj_matrix_args(self.edge_df.query('abbrev == @metaedge')))\\n res = parallel_process(array=args, function=mt.get_adj_matrix, use_kwargs=True, n_jobs=self.n_jobs,\\n front_num=0)\\n for metaedge, matrix in zip(mes, res):\\n self.adj_matrices[metaedge] = matrix\",\n \"def clustering(self):\\n ret_concepts = []\\n clusters = []\\n for word in self.words:\\n clusters.append(WordCluster(None, word))\\n while len(clusters) > 1:\\n maxi = -1\\n maxj = -1\\n max = -1\\n m = -1\\n for i in range(len(clusters)):\\n for j in range(len(clusters)):\\n if i == j:\\n continue\\n # print(\\\"%d cluster compare with %d cluster\\\" % (i, j))\\n # 1: join 21: i absorb j 22: j absorb i 3: collapse\\n # l1: join L(Tm) value l21: A absorb B L(Tm)value\\n l1, newtags = self.__calculate_ltm(clusters[i], clusters[j], 1)\\n if l1 > max:\\n m = 1\\n maxi = i\\n maxj = j\\n max = l1\\n print(\\\"max L(Tm) for clustering in current loop: %lf\\\" % max)\\n if max < ClusterAlgorithm.P_threshold:\\n return\\n Tm = clusters[maxi].join(clusters[maxj])\\n Tm_concepts = self.__select_concepts(self.__getword(Tm))\\n for tmp_concept in Tm_concepts.items():\\n ret_concepts.append(tmp_concept)\\n rm1 = clusters[maxi]\\n rm2 = clusters[maxj]\\n clusters.remove(rm1)\\n clusters.remove(rm2)\\n if Tm is not None:\\n print(\\\"merged cluster's words:\\\")\\n print(self.__getword(Tm))\\n return ret_concepts\",\n \"def clusterAlgorithm(values):\\n clusterMap = dict()\\n for value in values:\\n if value[2] not in clusterMap.keys():\\n clusterMap[value[2]] = []\\n clusterMap[value[2]].append(value)\\n frequency = [float(len(clusterMap[value[2]])) for value in values]\\n total = sum(frequency)\\n weightValues = [freq / total for freq in frequency]\\n print sum(weightValues)\\n lightValues = [value[1] for value in values]\\n return np.average(lightValues, weights = weightValues)\",\n \"def make_contingency_tables(\\n y: np.ndarray, flagged_A: np.ndarray, flagged_B: np.ndarray\\n) -> Dict[int, np.ndarray]:\\n\\n y = np.array(y).astype(np.int64).flatten()\\n flagged_A = np.array(flagged_A).astype(np.bool_).flatten()\\n flagged_B = np.array(flagged_B).astype(np.bool_).flatten()\\n\\n if len(flagged_A) != len(y) or len(flagged_B) != len(y):\\n raise ValueError(\\n f\\\"Expected arrays y, flagged_A, and flagged_B of the same length: \\\\\\n got {len(y)}, {len(flagged_A)}, and {len(flagged_B)}.\\\"\\n )\\n\\n contingency_tables = {}\\n for class_id in np.unique(y):\\n\\n items_flagged_A = flagged_A[y == class_id]\\n items_flagged_B = flagged_B[y == class_id]\\n\\n a = (~items_flagged_A & ~items_flagged_B).sum()\\n b = (~items_flagged_A & items_flagged_B).sum()\\n c = (items_flagged_A & ~items_flagged_B).sum()\\n d = (items_flagged_A & items_flagged_B).sum()\\n\\n table = np.array([[a, b], [c, d]])\\n contingency_tables[class_id] = table\\n\\n return contingency_tables\",\n \"def cluster_life_expectancy() -> Dict:\\n return dict(model=None, score=None, clusters=None)\",\n \"def _cluster(self):\\n # , distance_function=spearman_squared_distance, max_iter=1000, tol=0.0001):\\n if self.cluster_method is None:\\n clusters = KMedoids(\\n self.k,\\n self.batchsize,\\n dist_func=self.distance_function,\\n max_iter=self.max_iter,\\n tol=self.tol,\\n init_medoids=self.init_medoids,\\n swap_medoids=self.swap_medoids,\\n )\\n clusters.fit(self.clustering_attributions, verbose=self.verbose)\\n\\n self.subpopulations = clusters.members\\n self.subpopulation_sizes = GAM.get_subpopulation_sizes(clusters.members)\\n self.explanations = self._get_explanations(clusters.centers)\\n # Making explanations return numerical values instead of dask arrays\\n if isinstance(self.explanations[0][0][1], da.Array):\\n explanations = []\\n for explanation in self.explanations:\\n explanations.append([(x[0], x[1].compute()) for x in explanation])\\n self.explanations = explanations\\n else:\\n self.cluster_method(self)\",\n \"def eval_v_measure_homogeneity_completeness(clustering_alg: List, sdist_euclidean, sdist_jaccard,\\n labels_true, debug: bool = False):\\n for i, alg_dict in enumerate(clustering_alg):\\n if \\\"alg\\\" in alg_dict:\\n if alg_dict[\\\"distance\\\"] == \\\"euclidean\\\":\\n clustering = alg_dict[\\\"alg\\\"].fit(sdist_euclidean)\\n elif alg_dict[\\\"distance\\\"] == \\\"jaccard\\\":\\n clustering = alg_dict[\\\"alg\\\"].fit(sdist_jaccard)\\n else:\\n raise ValueError(\\\"Unknown distance measure {}. \\\".format(alg_dict[\\\"distance\\\"]) +\\n \\\"Please choose one of the following distance measures ['euclidean','jaccard']\\\")\\n labels_predicted = clustering.labels_\\n alg_dict[\\\"labels\\\"] = labels_predicted\\n else:\\n labels_predicted = alg_dict[\\\"labels\\\"]\\n\\n alg_dict[\\\"homogeneity\\\"], alg_dict[\\\"completeness\\\"], alg_dict[\\\"v-measure\\\"] = \\\\\\n homogeneity_completeness_v_measure(labels_true, labels_predicted)\\n\\n if debug:\\n print(\\\"Alg: \\\" + alg_dict[\\\"name\\\"] + \\\"; \\\\t v-measure = \\\" + str(alg_dict[\\\"v-measure\\\"]))\",\n \"def predict_clustering_pairs(args, **kwargs):\\n # We first compute the exponential and uniform likelihoods for all genomes\\n # in the dataset, individually\\n organisms_uniform_probabilities, n_pairs = \\\\\\n clustering_probs.compute_organisms_probabilities(\\n args, **kwargs)\\n\\n # Finds all the probabilities files for single organisms\\n probabilities_files_list = file_utilities.get_file_list(\\n args[\\\"individual_probabilities_dir\\\"],\\n args[\\\"probabilities_filename_suffix\\\"])\\n\\n if args[\\\"weight\\\"] is True or args[\\\"subclades\\\"] is True:\\n logger.info(\\\"Importing phylogenetic tree %s\\\", args[\\\"tree_file\\\"])\\n tree = ete3.Tree(args[\\\"tree_file\\\"])\\n logger.info(\\\"Phylogenetic tree %s imported\\\", args[\\\"tree_file\\\"])\\n if args[\\\"weight\\\"] is True:\\n if not os.path.exists(args[\\\"weights_file\\\"]) or args[\\n \\\"force\\\"] is True:\\n GSC.save_weights(None, args[\\\"weights_file\\\"], None, \\\"w\\\")\\n else:\\n tree = None\\n\\n # Conserved clustering analysis in each subclade:\\n if args[\\\"subclades\\\"] is True:\\n logger.info(\\n \\\"Started computing subclade-specific conserved\\\"\\n \\\" clustering probabilities\\\")\\n subclade_analysis.partition_tree(probabilities_files_list,\\n organisms_uniform_probabilities,\\n n_pairs,\\n tree,\\n args,\\n **kwargs)\\n logger.info(\\n \\\"Parsing subclade-specific conserved clustering probabilities, \\\"\\n \\\"this will take a while\\\")\\n find_last_subclade.parse_and_clean_tree(n_pairs, args)\\n logger.info(\\n \\\"Parsing subclade-specific conserved clustering probabilities done\\\")\\n logger.info(\\n \\\"Subclade-specific conserved clustering probabilities computed\\\")\\n\\n\\n # Clustering analysis just in the root:\\n else:\\n if not os.path.exists(args[\\\"final_probabilities_filename\\\"]) \\\\\\n or probabilities_files.is_table_empty(\\n args[\\\"final_probabilities_filename\\\"]) \\\\\\n or args[\\\"force\\\"] is True:\\n logger.info(\\n \\\"Started computing root-only conserved clustering probabilities\\\")\\n final_probs.compute_conserved_probabilities(\\n probabilities_files_list,\\n organisms_uniform_probabilities,\\n n_pairs,\\n tree,\\n 0,\\n args[\\\"final_probabilities_filename\\\"],\\n args)\\n\\n logger.info(\\\"Root conserved clustering probabilities saved in file %s\\\",\\n args[\\\"final_probabilities_filename\\\"])\\n\\n if args[\\\"weight\\\"] is True:\\n logger.info(\\\"Phylogenetic weights saved in file %s\\\",\\n args[\\\"weights_file\\\"])\\n\\n\\n return 0\",\n \"def _calculate_cluster_measures(\\n arr4d,\\n threshold,\\n bin_struct,\\n two_sided_test=False,\\n):\\n n_regressors = arr4d.shape[3]\\n\\n max_sizes = np.zeros(n_regressors, int)\\n max_masses = np.zeros(n_regressors, float)\\n\\n for i_regressor in range(n_regressors):\\n arr3d = arr4d[..., i_regressor].copy()\\n\\n if two_sided_test:\\n arr3d[np.abs(arr3d) <= threshold] = 0\\n else:\\n arr3d[arr3d <= threshold] = 0\\n\\n labeled_arr3d, _ = label(arr3d > 0, bin_struct)\\n\\n if two_sided_test:\\n # Label positive and negative clusters separately\\n n_positive_clusters = np.max(labeled_arr3d)\\n temp_labeled_arr3d, _ = label(\\n arr3d < 0,\\n bin_struct,\\n )\\n temp_labeled_arr3d[temp_labeled_arr3d > 0] += n_positive_clusters\\n labeled_arr3d = labeled_arr3d + temp_labeled_arr3d\\n del temp_labeled_arr3d\\n\\n clust_vals, clust_sizes = np.unique(labeled_arr3d, return_counts=True)\\n assert clust_vals[0] == 0\\n\\n clust_vals = clust_vals[1:] # First cluster is zeros in matrix\\n clust_sizes = clust_sizes[1:]\\n\\n # Cluster mass-based inference\\n max_mass = 0\\n for unique_val in clust_vals:\\n ss_vals = np.abs(arr3d[labeled_arr3d == unique_val]) - threshold\\n max_mass = np.maximum(max_mass, np.sum(ss_vals))\\n\\n # Cluster size-based inference\\n max_size = 0\\n if clust_sizes.size:\\n max_size = np.max(clust_sizes)\\n\\n max_sizes[i_regressor], max_masses[i_regressor] = max_size, max_mass\\n\\n return max_sizes, max_masses\",\n \"def cluster(self):\\n logger.debug(\\\"Beginning feature based clustering on %d clusters.\\\" % len(self.c2b))\\n # Merge the two nearest clusters until we can't.\\n #\\n while self.mergeNearestClusters():\\n pass\\n logger.debug(\\\"After clustering, there are now %d clusters remaining.\\\" % len(self.c2b))\\n return self.c2b.values()\",\n \"def __generate_dict_of_keys_to_classification__(self):\\n dict_of_assigned_citations = {}\\n # duplicating citation dataset to filter as matches go on meaning\\n # it should result in quicker allocation\\n # can be removed to reduce memory load at expense of speed\\n list_of_unassigned = []\\n for key in self.dict_of_keywords:\\n list_of_current_key = []\\n for citation_instance in self.array_of_citations:\\n if key == citation_instance.get_classification():\\n list_of_current_key.append(citation_instance)\\n if \\\"Unassigned\\\" == citation_instance.get_classification():\\n list_of_unassigned.append(citation_instance)\\n dict_of_assigned_citations[key] = list_of_current_key\\n dict_of_assigned_citations[\\\"Unassigned\\\"] = list_of_unassigned\\n return dict_of_assigned_citations\",\n \"def calculate_conductivities(self, vertices, gm_label):\\r\\n self.gm_label = gm_label\\r\\n data = pd.read_csv(vertices, sep=' ', header=None)\\r\\n\\r\\n self.__calculate_gm_bounds(data)\\r\\n self.dmri_handler.handle() #counts evals and evecs\\r\\n shape = self.dmri_handler.get_shape()\\r\\n\\r\\n self.xscale_coef = (self.gm_box.get_max_x() - self.gm_box.get_min_x()) / shape[0]\\r\\n self.yscale_coef = (self.gm_box.get_max_y() - self.gm_box.get_min_y()) / shape[1]\\r\\n self.zscale_coef = (self.gm_box.get_max_z() - self.gm_box.get_min_z()) / shape[2]\\r\\n\\r\\n self.__calculate_conductivities(data)\\r\\n data.to_csv(self.output_file, sep=' ')\",\n \"def evaluation_cc(self, property='clustering-coeff'):\\n\\n if property == 'clustering-coeff':\\n rw_cc = [np.mean(clustering_coef_wu(self.rw_data[t])) for t in range(0, self.T)]\\n smth_cc = [np.mean(clustering_coef_wu(self.smth_data[t])) for t in range(0, self.T)]\\n elif property == 'transitivity':\\n rw_cc = [np.mean(transitivity_wu(self.rw_data[t])) for t in range(0, self.T)]\\n smth_cc = [np.mean(transitivity_wu(self.smth_data[t])) for t in range(0, self.T)]\\n elif property == 'coreness':\\n rw_cc = [np.mean(core.core_periphery_dir(self.rw_data[t])) for t in range(0, self.T)]\\n smth_cc = [np.mean(core.core_periphery_dir(self.smth_data[t])) for t in range(0, self.T)]\\n elif property == 'assortativity':\\n rw_cc = [np.mean(core.assortativity_wei(self.rw_data[t], 0)) for t in range(0, self.T)]\\n smth_cc = [np.mean(core.assortativity_wei(self.smth_data[t], 0)) for t in range(0, self.T)]\\n elif property == 'modularity':\\n rw_cc, _ = get_number_of_components(self.rw_data)\\n smth_cc, _ = get_number_of_components(self.smth_data)\\n elif property == 'path_length':\\n rw_cc = [charpath(rw)[0] for rw in self.rw_data]\\n smth_cc = [charpath(sm)[0] for sm in self.smth_data]\\n\\n # rw_cc_ent = get_entropy_list(rw_cc)\\n # smth_cc_ent = get_entropy_list(smth_cc)\\n\\n return rw_cc, smth_cc\",\n \"def multiClusterAlgorithm(values):\\n clusterMap = dict()\\n # Lowest unixtime in the values list\\n startUnixtime = values[0][0]\\n # Separate values into separate clusters in the map, clusterMap\\n for value in values:\\n if value[2] not in clusterMap.keys():\\n clusterMap[value[2]] = []\\n clusterMap[value[2]].append(value)\\n \\n # An array of the predicted values per cluster\\n clusterPredicted = []\\n # An array of unixtime averages per cluster\\n unixtimeAverage = []\\n \\n # Generate predicted value for each cluster using a weighted average\\n # Adds predicted value for each cluster to clusterPredicted and adds\\n # the unixtime average for each cluster to unixtimeAverage\\n for key in clusterMap.keys():\\n clusterLength = len(clusterMap[key]) \\n totalUnixtime = sum([elem[0] for elem in clusterMap[key]])\\n unixtimeAverage.append(float(totalUnixtime) / float(clusterLength))\\n \\n clusterLight = [elem[1] for elem in clusterMap[key]]\\n\\n totalDistanceFromStart = sum([elem[0] - startUnixtime for elem in clusterMap[key]])\\n clusterWeightValues = [float(elem[0] - startUnixtime) / float(totalDistanceFromStart) for elem in clusterMap[key]]\\n \\n predicted = np.average(clusterLight, weights = clusterWeightValues)\\n clusterPredicted.append(predicted)\\n \\n print clusterPredicted\\n total = sum([elem - startUnixtime for elem in unixtimeAverage])\\n # Create weighted values based on unixtime average per cluster\\n weightValues = [float(elem - startUnixtime) / float(total) for elem in unixtimeAverage]\\n print weightValues\\n # Return a weighted average across clusters\\n return np.average(clusterPredicted, weights = weightValues)\",\n \"def dictionary(descriptors, n_clusters):\\n # TODO\\n print(descriptors.shape)\\n dummy=MiniBatchKMeans(n_clusters=n_clusters, batch_size=3000, random_state=9).fit(descriptors)\\n clusters=dummy.cluster_centers_\\n return clusters\",\n \"def _compute_util_data(self):\\n\\n print(\\\"Computing PCA of document vectors.\\\")\\n self.pca = PCA(n_components = 3)\\n\\n print(\\\"Computing document clusters in PCA basis.\\\")\\n inferred_vecs = np.array([self.model.infer_vector(doc.words) for doc in self.tagged_docs])\\n self.pca_reduced_vecs = self.pca.fit_transform(inferred_vecs)\\n n_clusters = 25 # TODO find way to determine approx cluster size\\n self.kmeans = KMeans(init = 'k-means++', n_clusters = n_clusters, random_state = 0)\\n self.kmeans_preds = self.kmeans.fit_predict(self.pca_reduced_vecs)\",\n \"def clustering(clusters, dend_matrix, labels, linkagefun):\\n Z = linkagefun(dend_matrix)\\n color_threshold = Z[-1*clusters][2]+0.0000000001 #Cut slightly above the tree node\\n \\n # Defining to which cluster belongs to each simulation\\n T = fcluster(Z, t=clusters, criterion='maxclust')\\n clustdict = { \\\"cluster\\\" + str(clust) : [] for clust in T }\\n for sim,clust in zip(labels,T):\\n clustdict[\\\"cluster\\\" + str(clust)].append(sim)\\n\\n return(color_threshold, clustdict)\",\n \"def prepare_data_matrix():\\n # create matrix X and list of languages\\n\\n lds = {}\\n for fn in listdir(\\\"clustering\\\"):\\n if fn.lower().endswith(\\\".txt\\\"):\\n with open(join(\\\"clustering\\\", fn), encoding=\\\"utf8\\\") as f:\\n text = f.read()\\n nter = terke(text, n=3)\\n lds[fn] = nter\\n #print(lds.keys())\\n \\n #lds is a dictionary of dictionaries: {\\\"slovenian.txt\\\": {\\\"abc\\\":3,\\\"efg\\\":4...}, \\\"macedonian.txt\\\":{\\\"efg\\\":6...},...}\\n l=listOfTuples(lds) #list of strings\\n #print(l[:100])\\n languages = list(lds.keys()) # ['Slo', 'Mac', ]\\n # which language represents row number i: languages[i]\\n # which row does language s represent: languagues.index(s)\\n X=np.zeros([len(languages),100])\\n for i in range(len(languages)):\\n #print(languages[i])\\n count = 0\\n for j in range(100):\\n if l[j] in lds[languages[i]]:\\n X[i,j]=lds[languages[i]][l[j]]\\n count += 1\\n # print(count)\\n\\n #print([sum(x) for x in X])\\n \\n return X, languages\\n # X, languages = prepare_data_matrix()\",\n \"def fit(self):\\n self.cluseter_agglomerative(n_clusters=20, linkage='average', iterate=5)\\n self.sub_clustering(n_clusters=3, index_cluster=[79], linkage='complete')\\n self.merge_clusters([[0,9,53],[1,83],[46,35,67],[88,23],[6,68]])\\n self.merge_clusters([[6,33,52],[17,14]])\\n self.sub_clustering(n_clusters=2, index_cluster=[0], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[2], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[85], linkage='average')\\n self.sub_clustering(n_clusters=2, index_cluster=[14], linkage='complete')\\n self.sub_clustering(n_clusters=2, index_cluster=[16], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[22], linkage='average')\\n self.sub_clustering(n_clusters=2, index_cluster=[24], linkage='complete')\\n self.sub_clustering(n_clusters=2, index_cluster=[26], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[28], linkage='ward')\\n self.merge_clusters([[6,98,99]])\\n self.merge_clusters([[35,80]])\\n self.sub_clustering(n_clusters=4, index_cluster=[35], linkage='complete')\\n self.merge_clusters([[76,98]])\\n self.sub_clustering(n_clusters=3, index_cluster=[35], linkage='complete')\\n self.merge_clusters([[39,42]])\\n self.sub_clustering(n_clusters=3, index_cluster=[47], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='average')\\n self.merge_clusters([[70,101]])\\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[61], linkage='ward')\\n self.merge_clusters()\\n return\",\n \"def evaluate(self, clustering):\\n # Pca for each one of the clusters\\n pca_mean_val = 0.;\\n MAX_ELEMENTS = 1000\\n for c in clustering.clusters:\\n # Pick the coordinates (ensuring that we are copying them)\\n element_indexes = c.all_elements\\n ###################\\n # Performance hack\\n ###################\\n # As it can be very slow for big clusters (i.e. > 3k elements) we'll compress this clusters \\n # before calculating PCA. It should increase variance but will allow calculations.\\n # It should use the kmedoids compressor\\n if len(c.all_elements) > MAX_ELEMENTS:\\n element_indexes = c.get_random_sample(MAX_ELEMENTS)\\n print \\\"[PCA] Random sampling too big cluster to improve performance (%d elements -> %d elements).\\\"%(len(c.all_elements),MAX_ELEMENTS)\\n ###################\\n \\n fitting_coordinates_of_this_cluster = self.fitting_coordinates[element_indexes]\\n \\n calculator = RMSDCalculator(calculatorType = \\\"QTRFIT_SERIAL_CALCULATOR\\\",\\n fittingCoordsets = fitting_coordinates_of_this_cluster)\\n \\n if self.calculation_coordinates is not None:\\n calculation_coordinates_of_this_cluster = self.calculation_coordinates[element_indexes]\\n calculator = RMSDCalculator(calculatorType = \\\"QTRFIT_SERIAL_CALCULATOR\\\",\\n fittingCoordsets = fitting_coordinates_of_this_cluster,\\n calculationCoordsets = calculation_coordinates_of_this_cluster)\\n \\n # Make an iterative superposition (to get the minimum RMSD of all with respect to a mean conformation)\\n calculator.iterativeSuperposition()\\n\\n # Calculate the covariance matrix\\n if self.calculation_coordinates is None:\\n covariance_matrix = PCAMetric.create_covariance_matrix(fitting_coordinates_of_this_cluster)\\n else:\\n covariance_matrix = PCAMetric.create_covariance_matrix(calculation_coordinates_of_this_cluster)\\n \\n # And then the eigenvalue we are interested in\\n pca_mean_val += PCAMetric.calculate_biggest_eigenvalue(covariance_matrix)\\n print \\\"PCA finished\\\"\\n return pca_mean_val /clustering.total_number_of_elements\",\n \"def cluster_classification_tex(f,browsing_matrix,diversifying_matrix, weblog,session_data_threshold,cluster_type,classification_column_diversity,classification_wanted_transaction):\\n divpat_classification_wanted_transaction = classification_wanted_transaction\\n divpat_N_classification_wanted_transaction=len(divpat_classification_wanted_transaction)\\n f.write(\\\"\\\\n% 6. Cluster Classification\\\")\\n columns_latex = '|'+'c|'*len(session_data_threshold[cluster_type].unique())\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('DivColumnsLatex',columns_latex)) \\n columns_blank = ' ' + '& '*(len(session_data_threshold[cluster_type].unique()) -1)\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('DivColumnsBlank',columns_blank)) \\n cluster_list = []\\n ieuc_clusters = []\\n star_chain_like_clusters = []\\n length_clusters = []\\n browsing_pattern_1 = []\\n browsing_pattern_2 = []\\n browsing_pattern_3 = []\\n diversifying_pattern_1 = []\\n diversifying_pattern_2 = []\\n diversifying_pattern_3 = []\\n cluster_ids = session_data_threshold[cluster_type].unique()\\n cluster_ids.sort()\\n for cluster_id in cluster_ids:\\n cluster_list.append(str(cluster_id))\\n \\n cluster_session_list=session_data_threshold[session_data_threshold[cluster_type]==cluster_id].session_id.values\\n temp_cluster_weblog=weblog[weblog.session_id.isin(cluster_session_list)]\\n pa,pa_names = proportional_abundance(temp_cluster_weblog,'requested_'+classification_column_diversity)\\n cluster_entropy=ShannonEntropy(pa,normalize=True)\\n \\n ieuc_clusters.append(str(round(np.power(2.0,cluster_entropy),2)))\\n star_chain_like_clusters.append(star_chain_str(session_data_threshold[session_data_threshold[cluster_type]==cluster_id].star_chain_like.mean()))\\n length_clusters.append(length(session_data_threshold[session_data_threshold[cluster_type]==cluster_id].requests.mean()))\\n # Browsing patterns\\n r,c=np.unravel_index(browsing_matrix[cluster_id][:-1,:-1].argsort(axis=None)[::-1][:3],dims=(divpat_N_classification_wanted_transaction,divpat_N_classification_wanted_transaction))\\n browsing_pattern_1.append('%.1f\\\\%%: %s$\\\\\\\\rightarrow$%s'%(100.0*browsing_matrix[cluster_id][r[0],c[0]],divpat_classification_wanted_transaction[r[0]],divpat_classification_wanted_transaction[c[0]]))\\n browsing_pattern_2.append('%.1f\\\\%%: %s$\\\\\\\\rightarrow$%s'%(100.0*browsing_matrix[cluster_id][r[1],c[1]],divpat_classification_wanted_transaction[r[1]],divpat_classification_wanted_transaction[c[1]]))\\n browsing_pattern_3.append('%.1f\\\\%%: %s$\\\\\\\\rightarrow$%s'%(100.0*browsing_matrix[cluster_id][r[2],c[2]],divpat_classification_wanted_transaction[r[2]],divpat_classification_wanted_transaction[c[2]]))\\n \\n # Diversifying patterns\\n r,c=np.unravel_index(np.nan_to_num(diversifying_matrix[cluster_id])[:-1,:-1].argsort(axis=None)[::-1][:3],dims=(divpat_N_classification_wanted_transaction,divpat_N_classification_wanted_transaction))\\n diversifying_pattern_1.append('%.1f\\\\%%: %s$\\\\\\\\rightarrow$%s'%(100.0*diversifying_matrix[cluster_id][r[0],c[0]],divpat_classification_wanted_transaction[r[0]],divpat_classification_wanted_transaction[c[0]]))\\n diversifying_pattern_2.append('%.1f\\\\%%: %s$\\\\\\\\rightarrow$%s'%(100.0*diversifying_matrix[cluster_id][r[1],c[1]],divpat_classification_wanted_transaction[r[1]],divpat_classification_wanted_transaction[c[1]]))\\n diversifying_pattern_3.append('%.1f\\\\%%: %s$\\\\\\\\rightarrow$%s'%(100.0*diversifying_matrix[cluster_id][r[2],c[2]],divpat_classification_wanted_transaction[r[2]],divpat_classification_wanted_transaction[c[2]]))\\n\\n del temp_cluster_weblog\\n \\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('DivClusterList',' & '.join(cluster_list)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('DivIEUCClusters',' & '.join(ieuc_clusters)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('StarChainClusters',' & '.join(star_chain_like_clusters)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('LengthClusters',' & '.join(length_clusters)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('BrowsingPatternClustersOne',' & '.join(browsing_pattern_1)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('BrowsingPatternClustersTwo',' & '.join(browsing_pattern_2)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('BrowsingPatternClustersThree',' & '.join(browsing_pattern_3)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('DiversifyingPatternClustersOne',' & '.join(diversifying_pattern_1)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('DiversifyingPatternClustersTwo',' & '.join(diversifying_pattern_2)))\\n f.write(\\\"\\\\n\\\\\\\\newcommand{\\\\\\\\%s}{%s}\\\"%('DiversifyingPatternClustersThree',' & '.join(diversifying_pattern_3)))\\n\\n return f;\",\n \"def generate(dictalg):\\n\\n # dsList, sortedAlgs, dictAlg = processInputArgs(args, verbose=verbose)\\n res = {}\\n for f, i in pproc.dictAlgByFun(dictalg).iteritems():\\n for d, j in pproc.dictAlgByDim(i).iteritems():\\n tmp = BestAlgSet(j)\\n res[(d, f)] = tmp\\n return res\",\n \"def calculate_clusters(study_id):\\n\\n with current_app.app_context():\\n cur = conn.cursor()\\n\\n cur.execute(\\\"\\\"\\\"SELECT * FROM STATS WHERE STUDY_ID=%s\\\"\\\"\\\", (str(study_id),))\\n study = fetchoneClean(cur)\\n clusters_calculating = study[4]\\n clusters_changed = study[5]\\n if clusters_changed:\\n if clusters_calculating:\\n return {'message': 'calculating'}\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CALCULATING = TRUE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n conn.commit()\\n\\n distance = study[7]['matrix']\\n card_names = study[7]['cardNames']\\n cur.execute(\\\"\\\"\\\"SELECT COUNT(ID) FROM PARTICIPANT WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n total_participants = fetchoneClean(cur)[0]\\n\\n distance_matrix = calculate_square_form(distance, total_participants)\\n distArray = ssd.squareform(distance_matrix)\\n\\n try:\\n clusters = hierarchy.linkage(distArray, method='average')\\n except ValueError:\\n return {'message': 'not enough data'}\\n\\n tree = hierarchy.to_tree(clusters, rd=False)\\n # TODO Distance 0 on root\\n dendro = dict(children=[], hierarchy=0, distance=100)\\n add_node(tree, dendro, card_names)\\n\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS = %s WHERE STUDY_ID = %s\\\"\\\"\\\", (json.dumps(dendro), str(study_id),))\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CALCULATING = FALSE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CHANGED = FALSE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n conn.commit()\\n else:\\n dendro = study[6]\\n\\n return dendro\",\n \"def kmeans_clustering(cluster_list, num_clusters, num_iterations):\\n points = cluster_list[:]\\n \\n # n <-- |p|;\\n len_points_list = len(points)\\n\\n # position initial clusters at the location of clusters with largest populations (i.e., cluster[3] which is population) \\n cluster_centers = []\\n temp_cl = points[:]\\n \\n temp_cl.sort(key=lambda cluster: cluster.total_population())\\n for cluster in reversed(temp_cl):\\n if len(cluster_centers) < num_clusters:\\n cluster_centers.append(alg_cluster.Cluster(set([]), cluster.horiz_center(), cluster.vert_center(), 0, 0))\\n\\n # For number of iterations\\n for dummy_var in range(num_iterations):\\n # initialize k (num_clusters) empty sets C1, ... Ck;\\n cluster_groupings = []\\n for index in range(len(cluster_centers)):\\n cluster_groupings.append(alg_cluster.Cluster(set(), 0, 0, 0, 0))\\n # # For each county\\n # for j = 0 to n - 1 do\\n for index in range(len_points_list):\\n # Find the old cluster center that is closest \\n # L <-- argminsub(1<=f<=k) (dsub(psubj), musubf); \\n min_dist = float('inf')\\n nearest_cluster_index = None\\n\\n for idx, cluster in enumerate(cluster_centers):\\n if points[index].distance(cluster) < min_dist:\\n min_dist = points[index].distance(cluster)\\n nearest_cluster_index = idx\\n\\n # Add the county to the corresponding new cluster\\n # Handled with Cluster class merge_clusters method, which will automatically update the cluster centers to correct locations.\\n cluster_groupings[nearest_cluster_index].merge_clusters(points[index])\\n # Set old clusters equal to new clusters \\n # for f = 1 to k do\\n for index in range(len(cluster_centers)):\\n # muf = center (Cf) // handled with Cluster class built-in method(s)\\n cluster_centers[index] = cluster_groupings[index].copy()\\n\\n # return {C1, C2, ..., Ck}; \\n return cluster_groupings\",\n \"def cluster_membership_occupancy(data):\\n \\n \\n \\n n_clusters = len(set(data['clusters'])-{-1}) # since -1 element denotes noice\\n\\n if n_clusters == 0:\\n membership=[Cluster_Membership_Features()]\\n membership = pd.DataFrame([o.__dict__ for o in membership])\\n areas=[Cluster_Area_Features()]\\n areas = pd.DataFrame([o.__dict__ for o in areas])\\n density=[Cluster_Density_Features()]\\n density = pd.DataFrame([o.__dict__ for o in density])\\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\\n density], axis=1)\\n \\n elif n_clusters ==1:\\n #obtain_total_cluster_areas_set_everything_else_to_default\\n membership=[Cluster_Membership_Features()]\\n membership = pd.DataFrame([o.__dict__ for o in membership])\\n d = dict(tuple(data.groupby('clusters')))\\n d.pop(-1, None)\\n \\n try:\\n cluster_chull_areas=[ss.ConvexHull(np.column_stack([d[i]['X'].array,d[i]['Y'].array])).volume for i in d.keys()]\\n except:\\n cluster_chull_areas=[0,0,0]\\n \\n Total_cluster_area=np.sum(cluster_chull_areas)\\n areas=[Cluster_Area_Features([Total_cluster_area,0,0,0,0,0,0,0,0])]\\n areas = pd.DataFrame([o.__dict__ for o in areas])\\n density=[Cluster_Density_Features()]\\n density = pd.DataFrame([o.__dict__ for o in density])\\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\\n density], axis=1)\\n \\n elif n_clusters >1:\\n #Summarizing the cluster membership distribution characteristics\\n cluster_size_nums=np.delete(np.array(data.groupby(['clusters']).size()),0)\\n (cluster_size_nums_avg,cluster_size_nums_min,cluster_size_nums_max,\\n cluster_size_nums_std,cluster_size_nums_cv,cluster_size_nums_cd,\\n cluster_size_nums_IQR,cluster_size_nums_Quartile_CD)= distribution_statistics(cluster_size_nums)\\n\\n #For each cluster calculate the area by calculating the area of the convex hull of cluster members\\n # Note: concavehull implementation here might be a good addition as it will provide more imformative values. \\n\\n d = dict(tuple(data.groupby('clusters')))\\n d.pop(-1, None)\\n try:\\n cluster_chull_areas=[ss.ConvexHull(np.column_stack([d[i]['X'].array,d[i]['Y'].array])).volume for i in d.keys()]\\n except:\\n cluster_chull_areas=[0,0,0,0,0]\\n \\n\\n (avg_cluster_area,min_cluster_area,max_cluster_area,\\n std_cluster_area,CV_cluster_area,CD_cluster_area,\\n IQR_cluster_area,Quartile_CD_cluster_area)= distribution_statistics(cluster_chull_areas)\\n Total_cluster_area=np.sum(cluster_chull_areas)\\n\\n #Calculate cluster density: number of nuclei/ convex area of cluster\\n cluster_density=np.divide(cluster_size_nums,cluster_chull_areas)\\n (avg_cluster_density,min_cluster_density,max_cluster_density,\\n std_cluster_density,CV_cluster_density,CD_cluster_density,\\n IQR_cluster_density,Quartile_CD_cluster_density)= distribution_statistics(cluster_density)\\n\\n #return dataframe of features\\n membership=[Cluster_Membership_Features([cluster_size_nums_avg,cluster_size_nums_min,cluster_size_nums_max,\\n cluster_size_nums_std,cluster_size_nums_cv,cluster_size_nums_cd,\\n cluster_size_nums_IQR,cluster_size_nums_Quartile_CD])]\\n membership = pd.DataFrame([o.__dict__ for o in membership])\\n areas=[Cluster_Area_Features([Total_cluster_area,\\n avg_cluster_area,min_cluster_area,max_cluster_area,\\n std_cluster_area,CV_cluster_area,CD_cluster_area,\\n IQR_cluster_area,Quartile_CD_cluster_area])]\\n areas = pd.DataFrame([o.__dict__ for o in areas])\\n density=[Cluster_Density_Features([avg_cluster_density,min_cluster_density,max_cluster_density,\\n std_cluster_density,CV_cluster_density,CD_cluster_density,\\n IQR_cluster_density,Quartile_CD_cluster_density])]\\n density = pd.DataFrame([o.__dict__ for o in density])\\n\\n all_features = pd.concat([membership.reset_index(drop=True), areas.reset_index(drop=True),\\n density], axis=1)\\n return all_features\",\n \"def cluster_bal_iter(self):\\n # moving\\n for j,cluster in enumerate(self.clusters):\\n cluster.move()\\n self.clusters_allocate_cells()\\n for j,cluster in enumerate(self.clusters):\\n cluster.calc()\\n #print j, '\\\\t', cluster.center, '\\\\t', cluster.np, '\\\\t', cluster.size\\n \\n # resizing\\n for j,cluster in enumerate(self.clusters):\\n cluster.resize()\\n self.clusters_allocate_cells()\\n for j,cluster in enumerate(self.clusters):\\n cluster.calc()\\n #print j, '\\\\t', cluster.center, '\\\\t', cluster.np, '\\\\t', cluster.size\\n \\n self.calc()\",\n \"def get_all_clusters(self) -> Dict[str, List[str]]:\\n result = {}\\n for c_id in set(self._clusters.values()):\\n result[c_id] = self.get_cluster_by_id(c_id)\\n return result\",\n \"def _create_adjacency_matrix(layer_edges):\\n A = defaultdict(int)\\n for l, edges in list(layer_edges.items()):\\n for edge in edges:\\n A[(edge[0], edge[1], l)] += 1\\n A[(edge[1], edge[0], l)] += 1 \\n return A\",\n \"def calculate_all_metrcis(self):\\n self.calculate_gc_metrcis()\\n self.calculate_sam_metrics()\\n self.calculate_classification_metrics()\\n self.calculate_losses()\",\n \"def assign_clusters(self):\\n running_perts = {}\\n for name in self.tensor_info:\\n item = self.tensor_info[name]\\n pert_list = item[1]\\n pert_names = []\\n prob_list = []\\n if pert_list is not None:\\n for pert in pert_list:\\n pert_names.append(pert.__class__.__name__)\\n prob_list.append(pert.p)\\n pert_names = '_'.join(pert_names)\\n if pert_names not in running_perts:\\n running_perts[pert_names] = [(name, prob_list)]\\n else:\\n running_perts[pert_names].append((name, prob_list))\\n\\n running_perts.pop('')\\n\\n assert len(running_perts) <= len(self.clusters), \\\"More different perturbations than clusters available, cannot assign tensors to clusters\\\"\\n\\n # ONLY BITWISEPERT FOR THE TIME BEING\\n bitwises = running_perts['BitwisePert']\\n bitwise_probs = [item[1][0] for item in bitwises]\\n centers, _ = kmeans(bitwise_probs, len(self.clusters))\\n groups, _ = vq(bitwise_probs, centers)\\n\\n for tensor, cluster in zip(bitwises, groups):\\n name = tensor[0]\\n tensor_ref = self.tensor_info[name][0]\\n repr = self.tensor_info[name][2]\\n self.clusters[cluster].add_tensor(tensor_ref, repr)\\n\\n for cluster, rate in zip(self.clusters, centers):\\n pert_dict = {\\n \\\"name\\\": \\\"BitwisePert\\\",\\n \\\"p\\\": rate}\\n pert = P.construct_pert(pert_dict)\\n cluster.set_perturb([pert])\",\n \"def cluster_analysis(\\n clusterers: list,\\n hyperparameter_grids: list,\\n eval_metrics_grid: list,\\n eval_metrics_params: dict,\\n word_embeddings: np.ndarray,\\n words_vocabulary: list,\\n word_to_int: dict,\\n word_embeddings_normalized: np.ndarray = None,\\n compute_pairwise_word_distances: bool = False,\\n compute_pairwise_word_distances_normalized: bool = False,\\n return_word_vectors: bool = False,\\n save_result_to_disk: bool = False,\\n output_dir: Optional[str] = None,\\n model_name: Optional[str] = None,\\n dataset_name: Optional[str] = None,\\n output_filepath_suffix: Optional[str] = None,\\n) -> Union[dict, tuple]:\\n # Create word vectors from given words/vocabulary\\n word_vectors = words_to_vectors(\\n words_vocabulary=words_vocabulary,\\n word_to_int=word_to_int,\\n word_embeddings=word_embeddings,\\n )\\n\\n # Create normalized word vectors from given words/vocabulary if specified.\\n word_vectors_normalized = None\\n if word_embeddings_normalized is not None:\\n word_vectors_normalized = words_to_vectors(\\n words_vocabulary=words_vocabulary,\\n word_to_int=word_to_int,\\n word_embeddings=word_embeddings_normalized,\\n )\\n\\n if compute_pairwise_word_distances:\\n word_vectors_pairwise_distances = pairwise_cosine_distances(word_vectors)\\n if (\\n compute_pairwise_word_distances_normalized\\n and word_vectors_normalized is not None\\n ):\\n normalized_word_vectors_pairwise_distances = euclidean_distances(\\n word_vectors_normalized\\n )\\n\\n # Perform cluster analysis\\n clusterers_result = {}\\n unique_cluster_metrics = set()\\n for clusterer_tuple, hyperparameter_grid, eval_metrics in zip(\\n clusterers, hyperparameter_grids, eval_metrics_grid\\n ):\\n if len(clusterer_tuple) == 3:\\n (clusterer_name, clusterer_cls, clusterer_use_normalized) = clusterer_tuple\\n else:\\n clusterer_use_normalized = False\\n (clusterer_name, clusterer_cls) = clusterer_tuple\\n print(f\\\"-- Clustering using {clusterer_name} --\\\")\\n clusterers_result[clusterer_name] = {\\n \\\"cluster_labels\\\": [],\\n \\\"cluster_params\\\": [],\\n \\\"cluster_metrics\\\": {},\\n }\\n\\n # Do clustering for each set of hyperparameters\\n param_grid = ParameterGrid(hyperparameter_grid)\\n for params_idx, params in enumerate(tqdm(param_grid)):\\n clusterers_result[clusterer_name][\\\"cluster_params\\\"].append(params)\\n\\n # Add exception for ward linkage clustering.\\n if (\\n clusterer_cls is AgglomerativeClustering\\n and params.get(\\\"linkage\\\") == \\\"ward\\\"\\n and word_vectors_normalized is not None\\n ):\\n params = {**params, \\\"affinity\\\": \\\"euclidean\\\"}\\n clusterer_instance = clusterer_cls(**params)\\n fit_predict_X = word_vectors_normalized\\n else:\\n clusterer_instance = clusterer_cls(**params)\\n if (\\n params.get(\\\"affinity\\\") == \\\"precomputed\\\"\\n or params.get(\\\"metric\\\") == \\\"precomputed\\\"\\n ):\\n if (\\n clusterer_use_normalized\\n and compute_pairwise_word_distances_normalized\\n ):\\n fit_predict_X = normalized_word_vectors_pairwise_distances\\n elif compute_pairwise_word_distances:\\n fit_predict_X = word_vectors_pairwise_distances\\n else:\\n if clusterer_use_normalized and word_vectors_normalized is not None:\\n fit_predict_X = word_vectors_normalized\\n else:\\n fit_predict_X = word_vectors\\n\\n # Use fit_predict if it is available.\\n if getattr(clusterer_instance, \\\"fit_predict\\\", None) is not None:\\n predicted_labels = clusterer_instance.fit_predict(fit_predict_X)\\n else:\\n clusterer_instance.fit(fit_predict_X)\\n predicted_labels = clusterer_instance.predict(fit_predict_X)\\n\\n # Separate noise labels into clusters\\n if clusterer_cls is HDBSCAN:\\n predicted_labels = separate_noise_labels_into_clusters(predicted_labels)\\n\\n clusterers_result[clusterer_name][\\\"cluster_labels\\\"].append(predicted_labels)\\n\\n # Evaluate predicted cluster labels using internal evaluation metrics\\n for eval_metric_tuple in eval_metrics:\\n if len(eval_metric_tuple) == 3:\\n (\\n eval_metric_key,\\n eval_metric,\\n eval_metric_use_normalized,\\n ) = eval_metric_tuple\\n else:\\n eval_metric_use_normalized = False\\n (eval_metric_key, eval_metric) = eval_metric_tuple\\n eval_metric_params = eval_metrics_params.get(eval_metric_key, {})\\n if (\\n compute_pairwise_word_distances\\n and eval_metric_params.get(\\\"metric\\\") == \\\"precomputed\\\"\\n ):\\n if (\\n eval_metric_use_normalized\\n and compute_pairwise_word_distances_normalized\\n ):\\n metric_name, metric_score, metric_obj_max = eval_metric(\\n word_embeddings=normalized_word_vectors_pairwise_distances,\\n cluster_labels=predicted_labels,\\n clusterer=clusterer_instance,\\n **eval_metric_params,\\n )\\n else:\\n metric_name, metric_score, metric_obj_max = eval_metric(\\n word_embeddings=word_vectors_pairwise_distances,\\n cluster_labels=predicted_labels,\\n clusterer=clusterer_instance,\\n **eval_metric_params,\\n )\\n else:\\n if (\\n eval_metric_use_normalized\\n and word_vectors_normalized is not None\\n ):\\n metric_name, metric_score, metric_obj_max = eval_metric(\\n word_embeddings=word_vectors_normalized,\\n cluster_labels=predicted_labels,\\n clusterer=clusterer_instance,\\n **eval_metric_params,\\n )\\n else:\\n metric_name, metric_score, metric_obj_max = eval_metric(\\n word_embeddings=word_vectors,\\n cluster_labels=predicted_labels,\\n clusterer=clusterer_instance,\\n **eval_metric_params,\\n )\\n unique_cluster_metrics.add(metric_name)\\n\\n # Initialize metric result\\n if (\\n metric_name\\n not in clusterers_result[clusterer_name][\\\"cluster_metrics\\\"]\\n ):\\n clusterers_result[clusterer_name][\\\"cluster_metrics\\\"][\\n metric_name\\n ] = {\\n \\\"metric_scores\\\": [],\\n \\\"metric_obj_max\\\": metric_obj_max,\\n \\\"best_metric_score_indices\\\": [],\\n }\\n\\n clusterers_result[clusterer_name][\\\"cluster_metrics\\\"][metric_name][\\n \\\"metric_scores\\\"\\n ].append(metric_score)\\n\\n # Set best metric score indices\\n if params_idx == len(param_grid) - 1:\\n best_metric_score_indices = np.argsort(\\n clusterers_result[clusterer_name][\\\"cluster_metrics\\\"][\\n metric_name\\n ][\\\"metric_scores\\\"]\\n )\\n if metric_obj_max:\\n best_metric_score_indices = best_metric_score_indices[::-1]\\n clusterers_result[clusterer_name][\\\"cluster_metrics\\\"][metric_name][\\n \\\"best_metric_score_indices\\\"\\n ] = best_metric_score_indices\\n\\n # Find preferred clusterers for each cluster metric (from best to worst)\\n metric_preferred_clusterers = {}\\n for cluster_metric_name in unique_cluster_metrics:\\n metric_obj_max = None\\n metric_best_scores = []\\n clusterer_names = []\\n for clusterer_name, clusterer_result in clusterers_result.items():\\n if cluster_metric_name in clusterer_result[\\\"cluster_metrics\\\"]:\\n clusterer_names.append(clusterer_name)\\n metric_result = clusterer_result[\\\"cluster_metrics\\\"][cluster_metric_name]\\n if metric_obj_max is None:\\n metric_obj_max = metric_result[\\\"metric_obj_max\\\"]\\n best_metric_score = metric_result[\\\"metric_scores\\\"][\\n metric_result[\\\"best_metric_score_indices\\\"][0]\\n ]\\n metric_best_scores.append(best_metric_score)\\n clusterer_names = np.array(clusterer_names)\\n metric_best_scores = np.array(metric_best_scores)\\n\\n metric_best_scores_sorted_indices = np.argsort(metric_best_scores)\\n if metric_obj_max:\\n metric_best_scores_sorted_indices = metric_best_scores_sorted_indices[::-1]\\n metric_preferred_clusterers[cluster_metric_name] = {\\n \\\"clusterer_names\\\": clusterer_names[metric_best_scores_sorted_indices],\\n \\\"best_metric_scores\\\": metric_best_scores[metric_best_scores_sorted_indices],\\n }\\n\\n # Return result as dictionary\\n cluster_analysis_result = {\\n \\\"clusterers\\\": clusterers_result,\\n \\\"metric_preferred_clusterers\\\": metric_preferred_clusterers,\\n }\\n\\n if return_word_vectors:\\n if compute_pairwise_word_distances:\\n cluster_analysis_result = (\\n cluster_analysis_result,\\n word_vectors,\\n word_vectors_pairwise_distances,\\n )\\n else:\\n cluster_analysis_result = (cluster_analysis_result, word_vectors)\\n\\n # Save result to disk\\n if save_result_to_disk:\\n save_cluster_result_to_disk(\\n cluster_result=cluster_analysis_result,\\n output_dir=output_dir,\\n model_name=model_name,\\n dataset_name=dataset_name,\\n output_filepath_suffix=output_filepath_suffix,\\n )\\n\\n return cluster_analysis_result\",\n \"def compute_cluster_similarities(emb_clusters1, emb_clusters2, compare, order, clmethod, plot):\\n def compute_sim(e, e1, cls, cls1):\\n sims = np.empty((20, 20))\\n xticks, yticks = [], []\\n for i, c in enumerate(cls):\\n yticks.append(', '.join(c[1]) + (f' {round(c[3], 5)}' if order == 'avgfreq' else ''))\\n for j, c1 in enumerate(cls1):\\n if len(xticks) < 20:\\n xticks.append(', '.join(c1[1]) + (f' {round(c1[3], 5)}' if order == 'avgfreq' else ''))\\n sims[i, j] = jaccard_similarity_score(c[2], c1[2])\\n jaccard_similarities[f'{e}-{e1}'] = sims\\n\\n if plot:\\n if order == 'clustermap':\\n similarity_clustermap(sims, xticks, yticks, f'{e}-{e1}_{clmethod}')\\n elif order == 'default' or order == 'avgfreq':\\n similarity_heatmap(sims, xticks, yticks, f'{e}-{e1}_{clmethod}', order)\\n else:\\n pass\\n\\n jaccard_similarities = {}\\n if compare == 'cross':\\n for ie, (e, cls) in enumerate(emb_clusters1.items()):\\n for ie1, (e1, cls1) in enumerate(emb_clusters2.items()):\\n if ie < ie1:\\n compute_sim(e, e1, cls, cls1)\\n elif compare == 'dot':\\n for (e, cls), (e1, cls1) in zip(emb_clusters1.items(), emb_clusters2.items()):\\n compute_sim(e, e1, cls, cls1)\\n\\n return jaccard_similarities\",\n \"def get_all_local_clustering_coef(g):\\n local_cc = {}\\n\\n for n in nx.nodes(g):\\n local_cc[n] = get_local_clustering_coef(g, n)\\n\\n return local_cc\",\n \"def evaluate_clusters(self, cluster_formulas, value='weighted_sum'):\\n num_elems = len(self.labels)\\n total_val = {}\\n num_cl = len(cluster_formulas)\\n clustered_points_num = 0\\n print(\\\"\\\\n\\\\n\\\")\\n print(\\\"Sufficiently big clusters: {}\\\".format(num_cl))\\n for c, formula, val in cluster_formulas:\\n c_size = len([l for l in self.labels if l == c])\\n clustered_points_num += c_size\\n\\n if value == 'weighted_sum':\\n total_val[c] = val * c_size / num_elems\\n elif value == 'sum':\\n total_val[c] = val * 1\\n\\n clust_val = sum(total_val.values())\\n self.clustering_value = total_val\\n print(\\\"Value of clustering: {}\\\".format(clust_val))\\n return clust_val\",\n \"def load_cluster_accuracies():\\n accuracies = morphs.utils.load._pickle(morphs.paths.ACCURACIES_PKL)\\n cluster_accuracies = {\\n block_path: accuracies[block_path]\\n .groupby(\\\"cluster\\\")\\n .agg(np.mean)\\n .sort_values(\\\"accuracy\\\")\\n for block_path in accuracies\\n }\\n return accuracies, cluster_accuracies\",\n \"def match_cluster_sets(cs1, cs2):\\n\\n matr = [[len(cl1.bibs & cl2.bibs) for cl2 in cs2.clusters] for cl1 in cs1.clusters]\\n mapping = maximized_mapping(matr)\\n return dict((cs1.clusters[mappy[0]], cs2.clusters[mappy[1]]) for mappy in mapping)\",\n \"def run(\\n self,\\n number_of_clusters=None,\\n max_K=8,\\n method_clustering=\\\"pam\\\",\\n init_clustering=\\\"random\\\",\\n max_iter_clustering=100,\\n discart_value_JI=0.6,\\n bootstraps_JI=100,\\n bootstraps_p_value=100,\\n n_jobs=1,\\n verbose=1,\\n ):\\n\\n if number_of_clusters is None:\\n self.k = optimizer.optimizeK(\\n self.distance_matrix,\\n self.y.to_numpy(),\\n self.model_type,\\n max_K,\\n method_clustering,\\n init_clustering,\\n max_iter_clustering,\\n discart_value_JI,\\n bootstraps_JI,\\n self.random_state,\\n n_jobs,\\n verbose,\\n )\\n\\n if self.k == 1:\\n warnings.warn(\\\"No stable clusters were found!\\\")\\n return\\n\\n print(f\\\"Optimal number of cluster is: {self.k}\\\")\\n\\n else:\\n self.k = number_of_clusters\\n print(f\\\"Use {self.k} as number of cluster\\\")\\n\\n self.cluster_labels = (\\n kmedoids.KMedoids(\\n n_clusters=self.k,\\n method=method_clustering,\\n init=init_clustering,\\n metric=\\\"precomputed\\\",\\n max_iter=max_iter_clustering,\\n random_state=self.random_state,\\n )\\n .fit(self.distance_matrix)\\n .labels_\\n )\\n\\n (\\n self._data_clustering_ranked,\\n self.p_value_of_features,\\n ) = stats.calculate_global_feature_importance(\\n self.X, self.y, self.cluster_labels, self.model_type\\n )\\n self._p_value_of_features_per_cluster = (\\n stats.calculate_local_feature_importance(\\n self._data_clustering_ranked, bootstraps_p_value\\n )\\n )\",\n \"def clustering(self): \\n clusterOfFiles=self.getClusters()\\n \\n #group files based on the hash of their contents\\n self.keyingMethod=md5Hash\\n [self.addFile(afile) for acluster in clusterOfFiles for afile in acluster]\\n clusterOfFiles=self.getClusters()\\n self.showClusters(clusterOfFiles)\",\n \"def matching_clusterization(self):\\n result = []\\n self.reclustering(self.groups.copy(deep=True), result)\\n self.result = pd.DataFrame(result)\\n return self.result.sort_values(by=['cluster_size'], ascending=False)\",\n \"def censuses(self, *scales: int) -> Mapping[int, Census]:\\n return {\\n # Map id to the whole census object\\n census.id: census\\n # The dict is created from a generating parsing the nodes\\n for census in (\\n Census.from_xml(node)\\n # an XML node can be used as an iterator, where it yields children\\n for node in self.shards_xml(\\n \\\"census\\\",\\n # we want to grab all the values, since a Census requires them\\n mode=joined_parameter(\\\"score\\\", \\\"rank\\\", \\\"rrank\\\", \\\"prank\\\", \\\"prrank\\\"),\\n # gets all the different stats for us\\n scale=joined_parameter(*(str(scale) for scale in scales))\\n if scales\\n else \\\"all\\\",\\n )[\\\"census\\\"]\\n )\\n }\",\n \"def get_cluster_info(self) -> Dict[str, Any]:\\n pass\",\n \"def return_factorized_dict(ls):\\r\\n factos = pd.unique(pd.factorize(ls)[0])\\r\\n categs = pd.unique(pd.factorize(ls)[1])\\r\\n if -1 in factos:\\r\\n categs = np.insert(categs,np.where(factos==-1)[0][0],np.nan)\\r\\n return dict(zip(categs,factos))\",\n \"def cluster(X=None, datalabels=None, nc=2):\\n from sklearn.cluster import KMeans\\n from sklearn.cluster import AffinityPropagation\\n\\n C = KMeans(n_clusters=nc,n_init=10,init='random')\\n C.fit(X[:,:1])\\n\\n #C = AffinityPropagation(preference=-80,damping=0.5).fit(X)\\n #cluster_centers_indices = C.cluster_centers_indices_\\n\\n clust = {}\\n for (i, label) in enumerate(C.labels_):\\n key = C.cluster_centers_[label][0]\\n #print label,key, datalabels[i],X[i][1]\\n if not clust.has_key(key):\\n clust[key]=[]\\n clust[key].append(datalabels[i])\\n #print clust\\n return C, clust\",\n \"def _generate_weighted_matrices(self):\\n self.degree_weighted_matrices = dict()\\n mes = []\\n args = []\\n for metaedge, matrix in self.adj_matrices.items():\\n mes.append(metaedge)\\n args.append({'matrix': matrix, 'w': self.w, 'degree_fwd': self.out_degree[metaedge],\\n 'degree_rev': self.in_degree[metaedge]})\\n res = parallel_process(array=args, function=mt.weight_by_degree, use_kwargs=True, n_jobs=self.n_jobs,\\n front_num=0)\\n for metaedge, matrix in zip(mes, res):\\n self.degree_weighted_matrices[metaedge] = matrix\",\n \"def dimension_homology_sc(self):\\r\\n vec_dic = {}\\r\\n for k in range(self.dimension()+1):\\r\\n p = k \\r\\n A = self.matrix_simmetric_representate(p)\\r\\n dn = 0\\r\\n dc = 0\\r\\n if (p == 0):\\r\\n dn = A.shape[1]\\r\\n if (p > 0 and (p <= self.dimension())):\\r\\n null = null_space(A)\\r\\n if (null.size != 0):\\r\\n dn = len(null[0])\\r\\n if (all(elem == 0 for elem in null[0])):\\r\\n dn = 0 \\r\\n p = k + 1\\r\\n if (p>0 and (p <= self.dimension())):\\r\\n A1=self.matrix_simmetric_representate(p)\\r\\n col = orth(A1)\\r\\n if (col.size != 0):\\r\\n dc = len(col[0])\\r\\n else: \\r\\n dc = 0\\r\\n vec_dic[k] = dn - dc\\r\\n return vec_dic\",\n \"def get_results_for_init(self):\\n return dict(init=self.centroids, n_clusters=self.centroids.shape[0])\",\n \"def compute_feature_properties(self):\\n\\n self.valuecounts = {}\\n self.unique_values = {}\\n self.missing_ratios = {}\\n self.counts = {}\\n self.codemaps = {}\\n for f in self.features:\\n # Compute various things\\n all_values = [self.data[l].get(f,\\\"?\\\") for l in self.data]\\n missing_data_ratio = all_values.count(\\\"?\\\") / (1.0*len(all_values))\\n non_q_values = [v for v in all_values if v != \\\"?\\\"]\\n counts = {}\\n for v in non_q_values:\\n counts[v] = non_q_values.count(v)\\n unique_values = list(set(non_q_values))\\n # Sort unique_values carefully.\\n # Possibly all feature values are numeric strings, e.g. \\\"1\\\", \\\"2\\\", \\\"3\\\".\\n # If we sort these as strings then we get weird things like \\\"10\\\" < \\\"2\\\".\\n # This can actually matter for things like ordinal models.\\n # So convert these to ints first...\\n if all([v.isdigit() for v in unique_values]):\\n unique_values = list(map(int, unique_values))\\n unique_values.sort()\\n unique_values = list(map(str, unique_values))\\n # ...otherwise, just sort normally\\n else:\\n unique_values.sort()\\n self.unique_values[f] = unique_values\\n\\n N = len(unique_values)\\n self.valuecounts[f] = N\\n self.missing_ratios[f] = missing_data_ratio\\n self.counts[f] = counts\\n self.codemaps[f] = self.build_codemap(unique_values)\",\n \"def katz_for_pairs(self, pairs, adj_prefix, max_length=6, beta=0.1):\\n filenames = [adj_prefix + str(i) + '.npz' for i in range(2, max_length + 1)]\\n n = 1\\n self.katz = {}\\n bs = [1.500, .891, .631, .543, .413, .420] # output from Mohler method\\n for u, v in pairs:\\n if u not in self.katz:\\n self.katz[u] = defaultdict(float)\\n for f in filenames:\\n a = scipy.sparse.load_npz(f)\\n # b = beta ** n\\n b = bs[n-1]\\n for u, v in pairs:\\n self.katz[u][v] += b * a[u-1, v-1]\\n n += 1\\n print(\\\"Loaded %s\\\" % f)\",\n \"def _gen_cg_dict(maxdim, existing_keys=None):\\n cg_dict = {}\\n # print(\\\"gen_cg_dict called with maxdim =\\\", maxdim)\\n\\n fastcgmat = memoize(clebschSU2mat)\\n\\n for k1, n1, k2, n2 in itertools.product(range(maxdim), repeat=4):\\n if ((k1, n1), (k2, n2)) in existing_keys:\\n continue\\n cg_dict.setdefault(((k1, n1), (k2, n2)), {})\\n kmin, kmax = abs(k1 - k2), k1 + k2\\n nmin, nmax = abs(n1 - n2), n1 + n2\\n # dim1, dim2 = (k1 + 1) * (n1 + 1), (k2 + 1) * (n2 + 1)\\n for k, n in itertools.product(\\n range(kmin, kmax + 1, 2), range(nmin, nmax + 1, 2)\\n ):\\n cg_dict[((k1, n1), (k2, n2))][(k, n)] = torch.tensor(\\n clebschmat((k1, n1), (k2, n2), (k, n), fastcgmat=fastcgmat)\\n )\\n\\n return cg_dict\",\n \"def compute_statistics(self):\\n for i in range(len(self.wine_matrix[0, :])):\\n feature = self.wine_matrix[:, i]\\n self.wine_stats['feature ' + str(i)] = {}\\n if i == 11: # results column\\n self.wine_stats['feature ' + str(i)]['positive_class_ratio'] = (feature == 1).sum() / len(feature)\\n null, self.wine_stats['feature ' + str(i)]['pvalue'] = stats.normaltest(feature)\\n\\n # plot\\n # pyplot.hist(feature, bins=50)\\n # pyplot.show()\\n\\n for i in range(len(self.cancer_matrix[0, :])):\\n feature = self.cancer_matrix[:, i]\\n self.cancer_stats['feature ' + str(i)] = {}\\n if i == 10: # results column\\n self.cancer_stats['feature ' + str(i)]['positive_class_ratio'] = (feature == 1).sum() / len(feature)\\n null, self.cancer_stats['feature ' + str(i)]['pvalue'] = stats.normaltest(feature)\\n\\n # plot\\n # pyplot.hist(feature, bins=50)\\n # pyplot.show()\",\n \"def cluster(self, documents, iters=10):\\n ###TODO\\n self.means = documents[0:self.k]\\n self.cluster = defaultdict(lambda : int)\\n self.docs = documents\\n \\n for val in range(iters):\\n self.norms = []\\n for x in self.means:\\n self.norms.append(self.sqnorm(x))\\n \\n self.compute_clusters(documents)\\n \\n self.fin_clust = defaultdict(lambda:[])\\n for z in self.cluster:\\n self.fin_clust[self.cluster[z]].append(z)\\n \\n self.means = self.compute_means()\\n \\n to_print_array = []\\n for k in self.fin_clust:\\n to_print_array.append(len(self.fin_clust[k]))\\n \\n print (to_print_array)\\n print (self.error(documents))\",\n \"def clustering(df, mode):\\n # split into list of dfs containing only one reference node\\n df_list = [df.loc[i : i + 8 - 1, :] for i in range(0, len(df), 8)]\\n\\n df_coefficient = pd.DataFrame()\\n\\n # loop over every single node\\n for df_single in df_list:\\n df_single = df_single.reset_index()\\n total_value = 0\\n\\n # loop over the weights of all connected nodes\\n for j in range(len(df_single) - 1):\\n if mode == \\\"geometric\\\":\\n # geometric\\n total_value = total_value + math.sqrt(df_single.chi_sq[j] * df_single.chi_sq[j + 1])\\n if mode == \\\"arithmetic\\\": \\n # arithmetic\\n total_value = total_value + ((df_single.chi_sq[j] * df_single.chi_sq[j + 1]) / 2)\\n if mode == \\\"argmax\\\": \\n # max\\n total_value = total_value + max(df_single.chi_sq[j], df_single.chi_sq[j + 1])\\n if mode == \\\"argmin\\\":\\n # min\\n total_value = total_value + min(df_single.chi_sq[j], df_single.chi_sq[j + 1])\\n\\n for i in range(len(df_single) - 1):\\n if mode == \\\"geometric\\\":\\n # geometric\\n triplet_value = math.sqrt(df_single.chi_sq[i] * df_single.chi_sq[i + 1])\\n if mode == \\\"arithmetic\\\":\\n # arithmetic\\n triplet_value = (df_single.chi_sq[i] * df_single.chi_sq[i + 1]) / 2\\n if mode == \\\"argmax\\\":\\n # max\\n triplet_value = max(df_single.chi_sq[i], df_single.chi_sq[i + 1])\\n if mode == \\\"argmin\\\": \\n # min\\n triplet_value = min(df_single.chi_sq[i], df_single.chi_sq[i + 1])\\n\\n cluster_coefficient = triplet_value / total_value\\n buffer = [\\n [\\n df_single.reference[i],\\n df_single.comparison[i],\\n df_single.comparison[i + 1],\\n triplet_value,\\n cluster_coefficient,\\n ]\\n ]\\n df_coefficient = df_coefficient.append(buffer)\\n\\n df_coefficient = df_coefficient.reset_index()\\n\\n print(\\\"\\\\n\\\\n threshold 0.5*c_omega\\\")\\n check_list = []\\n # print out triangles that have a cluster coefficient bigger, than X\\n for i in range(len(df_coefficient)):\\n if df_coefficient[4][i] >= ((0.5) * df_coefficient[4].max()):\\n print(list(df_coefficient.loc[i][1:4]))\\n check_list.append(list(df_coefficient.loc[i][1:4]))\\n else:\\n continue\\n\\n print(\\\"\\\\n\\\\n threshold 0.75*c_omega\\\")\\n check_list = []\\n for i in range(len(df_coefficient)):\\n if df_coefficient[4][i] >= ((0.75) * df_coefficient[4].max()):\\n print(list(df_coefficient.loc[i][1:4]))\\n check_list.append(list(df_coefficient.loc[i][1:4]))\\n else:\\n continue\\n\\n print(\\\"\\\\n\\\\n threshold 0.8*c_omega\\\")\\n check_list = []\\n for i in range(len(df_coefficient)):\\n if df_coefficient[4][i] >= ((0.9) * df_coefficient[4].max()):\\n print(list(df_coefficient.loc[i][1:4]))\\n check_list.append(list(df_coefficient.loc[i][1:4]))\\n else:\\n continue\\n\\n\\n print(\\\"\\\\n\\\\n threshold 0.9*c_omega\\\")\\n check_list = []\\n for i in range(len(df_coefficient)):\\n if df_coefficient[4][i] >= ((0.9) * df_coefficient[4].max()):\\n print(list(df_coefficient.loc[i][1:4]))\\n check_list.append(list(df_coefficient.loc[i][1:4]))\\n else:\\n continue\\n\\n return\",\n \"def _assign_clusters(self):\\n\\n dist = np.zeros((self.k, ))\\n distortion = 0\\n\\n for index in range(0, self.data.shape[0]):\\n for i in range(0, self.k):\\n dist[i] = np.linalg.norm(self.data[index] - self.centroids[i])\\n\\n self.assigned_clusters[index] = np.argmin(dist)\\n distortion += np.min(dist)\\n\\n return distortion\",\n \"def interpret_clusters(self, split=0.7, all_demos=None, num_clusters=None, \\n max_depth=CLUSTER_DEPTH, data=None, labels=None, verbose=True):\\n all_demos = self.all_data if all_demos is None else all_demos\\n clusters = self.get_ordered_clusters(labels, num_clusters)\\n data = self.demos if data is None else data\\n labels = self.labels if labels is None else labels\\n\\n cluster_formulas = []\\n counter = 0\\n sep = \\\"\\\\n \\\"\\n for c in clusters:\\n counter += 1\\n res = self.sample_from_clusters(num_samples=split,\\n all_data=all_demos,\\n pos_validation=True, \\n neg_validation=True,\\n which_cluster=counter)\\n positive_samples, val_positive_samples = res[0], res[1]\\n negative_samples, val_negative_samples = res[2], res[3]\\n z = 0\\n for d in positive_samples:\\n if d[1] == 0: z += 1\\n\\n cluster_data = {'pos': positive_samples,\\n 'neg': negative_samples}\\n val_cluster_data = {'pos': val_positive_samples,\\n 'neg': val_negative_samples}\\n\\n if verbose: print(sep +\\\"Checking formulas \\\" + \\\\\\n \\\"with max depth {}\\\\n\\\".format(max_depth))\\n\\n cluster_formula, value_formula = wrapper_train(max_depth,\\n cluster_data, \\n val_cluster_data,\\n verbose=verbose,\\n pred_data=[self.pipeline_X,\\n self.pipeline_y])\\n if cluster_formula is not None:\\n print(cluster_formula)\\n\\n cluster_formulas.append((c, cluster_formula, value_formula))\\n self.reset_pipeline()\\n\\n return cluster_formulas\",\n \"def _recalculate_centroids(self):\\n\\n self._prev_centroids = dict(self.centroids)\\n for cluster in self.clusters:\\n self.centroids[cluster] = np.average(self.clusters[cluster], axis=0)\",\n \"def calcClusters(dataset, medoids, number_of_clusters, verbosity=0, class_header=\\\"Class\\\"):\\n clusters = [pandas.DataFrame(columns=dataset.columns)] * number_of_clusters # create array of clusters\\n multiprocess_count = multiprocessing.cpu_count() # Find processor count\\n pool = multiprocessing.Pool(processes=multiprocess_count) # create multiprocessing pool\\n\\n set_list = []\\n partition_size = math.ceil(len(dataset) / multiprocess_count)\\n for i in range(multiprocess_count - 1): # repeat for every subset\\n sample = dataset.iloc[i * partition_size: (i + 1) * partition_size] # take a sample of data\\n set_list.append((sample, medoids, number_of_clusters, verbosity, class_header)) # fill work list\\n set_list.append(\\n (dataset.iloc[(multiprocess_count - 1) * partition_size:], medoids, number_of_clusters, verbosity, class_header))\\n\\n # find list of clustering for each subset\\n clusters_subsets = pool.starmap(Cluster.calcClustersMultiprocess, set_list)\\n pool.close()\\n pool.join()\\n # Transpose 2d list of dataframes so each lower level list is of the same cluster\\n cluster_lists = [[i for i in element if i is not None] for element in list(zip_longest(*clusters_subsets))]\\n\\n for i in range(number_of_clusters): # concat together each list of cluster subsets.\\n clusters[i] = pandas.concat(cluster_lists[i])\\n return clusters\",\n \"def compute_means(self):\\n ###TODO\\n vector_means = []\\n for doc in self.fin_clust.values():\\n vec = defaultdict(float)\\n for d_id in doc:\\n doc_keys = self.docs[d_id].keys()\\n for key in self.docs[d_id]:\\n vec[key] = vec[key] + self.docs[d_id][key]\\n tot = len(doc)\\n x = defaultdict(float)\\n for k,v in vec.items():\\n x[k] = float(v)/tot\\n vec = Counter(x)\\n vector_means.append(vec)\\n return vector_means\",\n \"def _generate_weighted_adj_matrices(self):\\n self.weighted_adj_matrices = dict()\\n mes = []\\n args = []\\n for metaedge in self.metaedges:\\n mes.append(metaedge)\\n args.append(self._prepare_parallel_weighted_adj_matrix_args(self.edge_df.query('abbrev == @metaedge')))\\n res = parallel_process(array=args, function=mt.get_adj_matrix, use_kwargs=True, n_jobs=self.n_jobs,\\n front_num=0)\\n for metaedge, matrix in zip(mes, res):\\n self.weighted_adj_matrices[metaedge] = matrix\",\n \"def adj_dict(self):\\n adj_dict = {i: [] for i in self.indices}\\n for coeff in self.interactions[1:]:\\n for _inds, value in coeff.items():\\n for i in _inds:\\n _inds_list = list(_inds)\\n _inds_list.remove(i)\\n adj_dict[i].append([_inds_list, value])\\n return adj_dict\",\n \"def scores(self):\\n\\t\\tseqLengths = []\\n\\t\\tfor x in self.contigsInfo.keys():\\n\\t\\t\\tseq = self.contigsInfo[x]\\n\\t\\t\\tseqLengths.append(len(seq))\\n\\n\\t\\tseqLengths = sorted(seqLengths)\\t\\n\\t\\tmax_length = max(seqLengths)\\n\\t\\tmin_length = min(seqLengths)\\n\\t\\tmean_length = np.mean(seqLengths)\\t\\n\\n\\n\\t\\tmidLength = sum(seqLengths)/2\\n\\n\\t\\tcomputedMidLength = 0\\n\\t\\tl50 = 0\\n\\t\\tn50 = 0\\n\\t\\tfor i,x in enumerate(seqLengths):\\n\\t\\t\\tif (midLength < computedMidLength):\\n\\t\\t\\t\\tn50 = i\\n\\t\\t\\t\\tl50 = x \\n\\t\\t\\t\\tbreak\\n\\t\\t\\tcomputedMidLength += x\\n\\n\\t\\tscoresDict = {'number_of_contigs':len(seqLengths), 'smallestContig':min_length, 'meanContig':mean_length, \\n\\t\\t'n50':n50, 'l50':l50, 'largestContig':max_length, 'lengthOfAssembly':sum(seqLengths)}\\n\\t\\treturn scoresDict\",\n \"def clustering(dataset, logger):\\n all_instances = dataset\\n meta_dataset = collections.defaultdict(list)\\n for instance in all_instances:\\n meta_dataset[instance['label']].append(instance['coordinate'])\\n\\n tasklist = map(\\n lambda item, meta_dataset=meta_dataset, logger=logger: (\\n item[0],\\n clustering_by_label,\\n (item[1], item[0], meta_dataset, logger)), meta_dataset.items())\\n\\n # pool = multiprocessing.pool.Pool(PROCESS_COUNT)\\n # clusters = dict(pool.map(map_generate_tuple, tasklist))\\n clusters = dict(map(map_generate_tuple, tasklist))\\n # pool.close()\\n # pool.join()\\n\\n return clusters\",\n \"def get_composition(self) -> Dict[KappaAgent, int]:\\n agent_types = self.get_agent_types_present()\\n composition = dict(zip(agent_types, [0] * len(agent_types)))\\n for agent_type in agent_types:\\n for kappa_complex, abundance in self.get_all_complexes_and_abundances():\\n complex_composition = kappa_complex.get_complex_composition()\\n local_abundance = complex_composition[agent_type] if agent_type in complex_composition else 0\\n composition[agent_type] += abundance * local_abundance\\n return composition\",\n \"def analysis_function_num_clusters(self,clustering):\\n return len(clustering.clusters)\",\n \"def collectInitialeccnStatistics(self, folder, databaseFilename, multiplicityFactor = 1.0, deformedNuclei = False):\\n typeCollections = ((1, 'sn'), (2,'en'))\\n for ecc_id, ecc_type_name in typeCollections:\\n db = SqliteDB(path.join(folder, databaseFilename % ecc_type_name))\\n # first write the ecc_id_lookup table, makes sure there is only one such table\\n if db.createTableIfNotExists(\\\"ecc_id_lookup\\\", ((\\\"ecc_id\\\",\\\"integer\\\"), (\\\"ecc_type_name\\\",\\\"text\\\"))):\\n db.insertIntoTable(\\\"ecc_id_lookup\\\", (ecc_id, ecc_type_name))\\n\\n # next create the eccentricities and collisionParameters table\\n db.createTableIfNotExists(\\\"eccentricities\\\", ((\\\"event_id\\\",\\\"integer\\\"), (\\\"ecc_id\\\", \\\"integer\\\"), (\\\"n\\\",\\\"integer\\\"), (\\\"ecc_real\\\",\\\"real\\\"), (\\\"ecc_imag\\\",\\\"real\\\")))\\n db.createTableIfNotExists(\\\"collisionParameters\\\", ((\\\"event_id\\\",\\\"integer\\\"), (\\\"Npart\\\", \\\"integer\\\"), (\\\"Ncoll\\\",\\\"integer\\\"), (\\\"b\\\",\\\"real\\\"), (\\\"total_entropy\\\",\\\"real\\\")))\\n if(deformedNuclei):\\n db.createTableIfNotExists(\\\"deformationParameters\\\", ((\\\"event_id\\\",\\\"integer\\\"), (\\\"cosTheta1\\\", \\\"real\\\"), (\\\"phi1\\\",\\\"real\\\"), (\\\"cosTheta2\\\",\\\"real\\\"), (\\\"phi2\\\",\\\"real\\\")))\\n\\n # the big loop\\n for iorder in range(1,10):\\n data = loadtxt(path.join(folder, '%s_ecc_eccp_%d.dat' %(ecc_type_name, iorder)))\\n if iorder == 1:\\n Npart = data[:,4]\\n Ncoll = data[:,5]\\n dSdy = data[:,6]/multiplicityFactor #scale out the multiplicity factor used in superMC\\n b = data[:,7]\\n for event_id in range(len(Npart)):\\n db.insertIntoTable(\\\"collisionParameters\\\", (event_id, int(Npart[event_id]), int(Ncoll[event_id]), float(b[event_id]), float(dSdy[event_id])))\\n if(deformedNuclei):\\n cosTheta1 = data[:,8]\\n phi1 = data[:,9]\\n cosTheta2 = data[:,10]\\n phi2 = data[:,11]\\n for event_id in range(len(Npart)):\\n db.insertIntoTable(\\\"deformationParameters\\\", (event_id, float(cosTheta1[event_id]), float(phi1[event_id]), float(cosTheta2[event_id]), float(phi2[event_id])))\\n eccReal = data[:,2]\\n eccImag = data[:,3]\\n for event_id in range(len(eccReal)):\\n db.insertIntoTable(\\\"eccentricities\\\",(event_id, ecc_id, iorder, float(eccReal[event_id]), float(eccImag[event_id])))\\n\\n # close connection to commit changes\\n db.closeConnection()\",\n \"def effective_cluster_weights(self):\\n weights = np.array(\\n [\\n np.sum(\\n self._subspace.function_ordering_multiplicities[\\n self._subspace.function_orbit_ids == i\\n ]\\n * self.eci[self.eci_orbit_ids == i] ** 2\\n )\\n for i in range(len(self._subspace.orbits) + 1)\\n ]\\n )\\n return weights\",\n \"def formAdjacencyMatrix(self):\\n self.adjacencyMatrix = dict()\\n for i in self.node:\\n self.adjacencyMatrix[i] = dict()\\n for j in self.node:\\n self.adjacencyMatrix[i][j] = 0\\n \\n for ij in self.link:\\n self.adjacencyMatrix[self.link[ij].tail][self.link[ij].head] = 1\",\n \"def __init__(self, dictAlg):\\n\\n # values of dict dictAlg are DataSetList which should have only one\\n # element which will be assigned as values in the following lines.\\n d = set()\\n f = set()\\n for i in dictAlg.values():\\n d |= set(j.dim for j in i)\\n f |= set(j.funcId for j in i)\\n\\n if len(f) > 1 or len(d) > 1:\\n Usage('Expect the data of algorithms for only one function and '\\n 'one dimension.')\\n\\n f = f.pop()\\n d = d.pop()\\n\\n dictMaxEvals = {}\\n dictFinalFunVals = {}\\n tmpdictAlg = {}\\n for alg, i in dictAlg.iteritems():\\n if len(i) == 0:\\n warnings.warn('Algorithm %s was not tested on f%d %d-D.'\\n % (alg, f, d))\\n continue\\n elif len(i) > 1:\\n warnings.warn('Algorithm %s has a problem on f%d %d-D.'\\n % (alg, f, d))\\n continue\\n\\n tmpdictAlg[alg] = i[0] # Assign ONLY the first element as value\\n dictMaxEvals[alg] = i[0].maxevals\\n dictFinalFunVals[alg] = i[0].finalfunvals\\n\\n dictAlg = tmpdictAlg\\n\\n sortedAlgs = dictAlg.keys()\\n # algorithms will be sorted along sortedAlgs which is now a fixed list\\n\\n # Align ERT\\n erts = list(np.transpose(np.vstack([dictAlg[i].target, dictAlg[i].ert]))\\n for i in sortedAlgs)\\n res = readalign.alignArrayData(readalign.HArrayMultiReader(erts))\\n\\n resalgs = []\\n reserts = []\\n # For each function value\\n for i in res:\\n # Find best algorithm\\n curerts = i[1:]\\n assert len((np.isnan(curerts) == False)) > 0\\n currentbestert = np.inf\\n currentbestalg = ''\\n for j, tmpert in enumerate(curerts):\\n if np.isnan(tmpert):\\n continue # TODO: don't disregard these entries\\n if tmpert == currentbestert:\\n # TODO: what do we do in case of ties?\\n # look at function values corresponding to the ERT?\\n # Look at the function evaluations? the success ratio?\\n pass\\n elif tmpert < currentbestert:\\n currentbestert = tmpert\\n currentbestalg = sortedAlgs[j]\\n reserts.append(currentbestert)\\n resalgs.append(currentbestalg)\\n\\n dictiter = {}\\n dictcurLine = {}\\n resDataSet = []\\n\\n # write down the #fevals to reach the function value.\\n for funval, alg in zip(res[:, 0], resalgs):\\n it = dictiter.setdefault(alg, iter(dictAlg[alg].evals))\\n curLine = dictcurLine.setdefault(alg, np.array([np.inf, 0]))\\n while curLine[0] > funval:\\n try:\\n curLine = it.next()\\n except StopIteration:\\n break\\n dictcurLine[alg] = curLine.copy()\\n tmp = curLine.copy()\\n tmp[0] = funval\\n resDataSet.append(tmp)\\n\\n setalgs = set(resalgs)\\n dictFunValsNoFail = {}\\n for alg in setalgs:\\n for curline in dictAlg[alg].funvals:\\n if (curline[1:] == dictAlg[alg].finalfunvals).any():\\n # only works because the funvals are monotonous\\n break\\n dictFunValsNoFail[alg] = curline.copy()\\n\\n self.evals = resDataSet\\n # evals is not a np array but a list of arrays because they may not\\n # all be of the same size.\\n self.maxevals = dict((i, dictMaxEvals[i]) for i in setalgs)\\n self.finalfunvals = dict((i, dictFinalFunVals[i]) for i in setalgs)\\n self.funvalsnofail = dictFunValsNoFail\\n self.dim = d\\n self.funcId = f\\n self.algs = resalgs\\n self.algId = 'Virtual Best Algorithm'\\n self.comment = 'Combination of ' + ', '.join(sortedAlgs)\\n self.ert = np.array(reserts)\\n self.target = res[:, 0]\\n\\n bestfinalfunvals = np.array([np.inf])\\n for alg in sortedAlgs:\\n if np.median(dictAlg[alg].finalfunvals) < np.median(bestfinalfunvals):\\n bestfinalfunvals = dictAlg[alg].finalfunvals\\n algbestfinalfunvals = alg\\n self.bestfinalfunvals = bestfinalfunvals\\n self.algbestfinalfunvals = algbestfinalfunvals\",\n \"def _estimate_assignments(self, graph: GraphRepresentation) -> None:\\n embed_graph = augment_diagonal(graph)\\n latent = AdjacencySpectralEmbed(\\n n_components=self.n_components, **self.embed_kws\\n ).fit_transform(embed_graph)\\n if isinstance(latent, tuple):\\n latent = np.concatenate(latent, axis=1)\\n gc = GaussianCluster(\\n min_components=self.min_comm,\\n max_components=self.max_comm,\\n **self.cluster_kws\\n )\\n vertex_assignments = gc.fit_predict(latent) # type: ignore\\n self.vertex_assignments_ = vertex_assignments\",\n \"def add_clusterings(self, clustering):\\n self.clustering.append(clustering)\",\n \"def bases(layout, mvClass=MultiVector, grades=None):\\n\\n dict = {}\\n for i in range(layout.gaDims):\\n grade = layout.gradeList[i]\\n if grade != 0:\\n if grades is not None and grade not in grades:\\n continue\\n v = np.zeros((layout.gaDims,), dtype=int)\\n v[i] = 1\\n dict[layout.names[i]] = mvClass(layout, v)\\n return dict\",\n \"def calculate_components(self, parts):\\n target = {}\\n for part in parts:\\n rank = part[0]\\n\\n try:\\n face = part[1]\\n except IndexError:\\n face = '*'\\n\\n try:\\n target[rank][face] += 1\\n except KeyError:\\n if rank not in target:\\n target[rank] = {}\\n target[rank][face] = 1\\n\\n return target\",\n \"def kl_divergence(self):\\r\\n\\r\\n target_columns = list(self.origdst.columns[11:-3])\\r\\n target_columns.append(self.origdst.columns[1]) # channel\\r\\n target_columns.append(self.origdst.columns[2]) # program_title\\r\\n target_columns.append(self.origdst.columns[3]) # genre\\r\\n\\r\\n kl_dict = {}\\r\\n\\r\\n for col in target_columns:\\r\\n\\r\\n try:\\r\\n\\r\\n col_counts_orig = self.origdst[col].value_counts(normalize=True).sort_index(ascending=True)\\r\\n col_counts_synth = self.synthdst[col].value_counts(normalize=True).sort_index(ascending=True)\\r\\n\\r\\n kl = sum(rel_entr(col_counts_orig.tolist(), col_counts_synth.tolist()))\\r\\n\\r\\n kl_dict[col] = kl\\r\\n\\r\\n except:\\r\\n\\r\\n print('For the column ', col, ' you must generate the same unique values as the real dataset.')\\r\\n print('The number of unique values than you should generate for column ', col, 'is ',\\r\\n len(self.origdst[col].unique()))\\r\\n\\r\\n return kl_dict\"\n]"},"negative_scores":{"kind":"list like","value":["0.60130954","0.5818192","0.57543993","0.5732739","0.56639177","0.56580245","0.56447226","0.560482","0.552206","0.551928","0.54748267","0.5463208","0.5428008","0.54264724","0.5389764","0.535151","0.5327543","0.53244734","0.5321029","0.5317272","0.5313567","0.52784014","0.5268973","0.52574134","0.5225924","0.52034247","0.5200481","0.5199405","0.5187148","0.51740474","0.5168689","0.5168088","0.5161099","0.51606315","0.5141321","0.51361215","0.5130891","0.5123838","0.51188105","0.5114492","0.5114134","0.50952685","0.5076774","0.50671357","0.5054872","0.5054367","0.50508374","0.5020113","0.50168306","0.5013794","0.50130177","0.5012417","0.5008053","0.500698","0.50005645","0.49908346","0.4988226","0.49863073","0.49841753","0.49804747","0.49748373","0.4973168","0.49665457","0.4958062","0.4954808","0.4954743","0.49452704","0.493537","0.49351147","0.4931998","0.49319458","0.49191707","0.4912733","0.49119478","0.4907791","0.49076417","0.49066368","0.48908702","0.48797494","0.48775354","0.48688793","0.48541453","0.48537183","0.4853347","0.4850343","0.48494658","0.4848352","0.48341274","0.48337764","0.48269358","0.48258853","0.482428","0.48193154","0.48180807","0.48172462","0.4809217","0.48090717","0.48082712","0.47957844","0.47931737"],"string":"[\n \"0.60130954\",\n \"0.5818192\",\n \"0.57543993\",\n \"0.5732739\",\n \"0.56639177\",\n \"0.56580245\",\n \"0.56447226\",\n \"0.560482\",\n \"0.552206\",\n \"0.551928\",\n \"0.54748267\",\n \"0.5463208\",\n \"0.5428008\",\n \"0.54264724\",\n \"0.5389764\",\n \"0.535151\",\n \"0.5327543\",\n \"0.53244734\",\n \"0.5321029\",\n \"0.5317272\",\n \"0.5313567\",\n \"0.52784014\",\n \"0.5268973\",\n \"0.52574134\",\n \"0.5225924\",\n \"0.52034247\",\n \"0.5200481\",\n \"0.5199405\",\n \"0.5187148\",\n \"0.51740474\",\n \"0.5168689\",\n \"0.5168088\",\n \"0.5161099\",\n \"0.51606315\",\n \"0.5141321\",\n \"0.51361215\",\n \"0.5130891\",\n \"0.5123838\",\n \"0.51188105\",\n \"0.5114492\",\n \"0.5114134\",\n \"0.50952685\",\n \"0.5076774\",\n \"0.50671357\",\n \"0.5054872\",\n \"0.5054367\",\n \"0.50508374\",\n \"0.5020113\",\n \"0.50168306\",\n \"0.5013794\",\n \"0.50130177\",\n \"0.5012417\",\n \"0.5008053\",\n \"0.500698\",\n \"0.50005645\",\n \"0.49908346\",\n \"0.4988226\",\n 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and its related core and centroid. Always uses Jaccard distance."},"document":{"kind":"string","value":"def eval_mean_distance(played_decks, clustering_data: List, fuzzy: bool, debug: bool = False):\n\n for alg_dict in clustering_data:\n decks = np.array(played_decks)\n clusters = []\n for label in set(alg_dict[\"labels\"]):\n indices = np.where(alg_dict[\"labels\"] == label)\n if fuzzy:\n clusters.append(FuzzyDeckCluster(decks[indices]))\n else:\n clusters.append(DeckCluster(decks[indices]))\n\n if fuzzy:\n clustering = FuzzyDeckClustering(clusters)\n else:\n clustering = DeckClustering(clusters)\n\n sum_of_squared_distances_centroid = 0\n sum_of_squared_distances_core = 0\n\n for cluster in clustering.deck_clusters:\n centroid = cluster.centroid()\n core = cluster.core()\n for deck in cluster.decks:\n sum_of_squared_distances_centroid += (deck.jaccard_distance(centroid))**2\n sum_of_squared_distances_core += (deck.jaccard_distance(core))**2\n alg_dict[\"sse_centroid\"] = sum_of_squared_distances_centroid\n alg_dict[\"sse_core\"] = sum_of_squared_distances_core\n\n if debug:\n print(\"Alg: \" + alg_dict[\"name\"] + \"; \\t sse = \" + str(alg_dict[\"sse_centroid\"]))\n print(\"Alg: \" + alg_dict[\"name\"] + \"; \\t sse = \" + str(alg_dict[\"sse_core\"]))"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def calcAvgDistances(centroids, clusters, class_header=\"Class\"):\n avg_distances = [0] * len(centroids)\n multiprocess_count = multiprocessing.cpu_count() # Find processor count\n for centroid_row_index, centroid_tuple in enumerate(centroids.iterrows()): # For each cluster\n work_list = [] # initialize multiprocessing structures\n set_list = []\n for _, datum in clusters[centroid_row_index].iterrows(): # For each point in the medoid cluster\n work_list.append((centroid_tuple[1], datum, class_header)) # add calculation to work list\n\n partition_size = math.ceil(len(work_list) / multiprocess_count) # find size of each work subeset\n for i in range(multiprocess_count - 1): # repeat for every subset\n sample = work_list[i * partition_size: (i + 1) * partition_size] # break work list into fair subsets\n set_list.append(sample)\n set_list.append((work_list[(multiprocess_count - 1) * partition_size:]))\n pool = multiprocessing.Pool(processes=multiprocess_count) # create multiprocessing pool\n # calculate sum of list of all distances from work list tasks\n avg_distances[centroid_row_index] = sum(sum(pool.map(Cluster.calcDistanceList, set_list), []))\n pool.close()\n pool.join()\n\n if avg_distances[centroid_row_index] is not 0: # make sure we do not divide by 0\n # calculate average of distance list\n avg_distances[centroid_row_index] = avg_distances[centroid_row_index] / len(clusters[centroid_row_index])\n return avg_distances","def _calc_distance(self, X):\n distances = np.zeros((X.shape[0], self.n_clusters))\n print(distances.shape)\n for i, centroid in enumerate(self.centroids):\n distances[:, i] = np.linalg.norm(X - centroid, axis=1)\n return distances","def calculate_cost(self, medoids, clusters):\n cost = 0.0\n for i in range(0, len(medoids)):\n for j in range(0, len(clusters[i])):\n cost += distance.sqeuclidean(medoids[i], clusters[i][j])\n return cost\n pass","def _compute_centroids(self):\n\n for i in range(0, self.k):\n cluster = np.argwhere(self.assigned_clusters == i)\n cluster_points = self.data[cluster].squeeze()\n self.centroids[i] = np.mean(cluster_points, axis=0)","def clustering_error(examples):\n\n cluster_examples = partition(examples)\n cluster_averages = [\n class_average(cluster_examples[class_id])\n for class_id in range(0, cluster_count)\n ]\n\n # accumulate the distances between each example and its cluster's average\n # into an error value\n error = 0\n for example in examples:\n error += dist(cluster_averages[example.type], example)\n\n return (error, cluster_averages)","def get_distance(self, samples, clusters):\n n_samples = samples.shape[0]\n n_features = samples.shape[1]\n n_centroids = clusters.shape[0]\n dist = np.zeros(shape=(n_samples, n_centroids))\n\n # computing squared euclidian distance for each sample-cluster pair\n for i in range(n_samples):\n for j in range(n_centroids):\n for k in range(n_features):\n dist[i, j] += (samples[i, k] - clusters[j, k])**2\n # dist[i, j] = D[i, j]**(1/2)\n\n return np.sqrt(dist)","def test_sum_of_distances(self):\n N = 10\n centers = [[0, 0], [1, 0], [0.5, np.sqrt(0.75)]]\n cluster_std = [0.3, 0.3, 0.3]\n n_samples = int(0.75 * N)\n data, labels_true = \\\n sklearn.datasets.make_blobs(n_samples=n_samples,\n centers=centers,\n cluster_std=cluster_std)\n centers = [[0.5, np.sqrt(0.75)]]\n cluster_std = [0.3]\n extra, labels_true = \\\n sklearn.datasets.make_blobs(n_samples=int(0.25 * N),\n centers=centers,\n cluster_std=cluster_std)\n X = np.concatenate((data, extra), axis=0)\n N = X.shape[0]\n\n # Pick some random floats for the counts/weights:\n counts = np.random.random_sample((N,)) * 10\n\n # SciPy:\n Y = pdist(X, metric=cdist)\n weights = [counts[i] * counts[j]\n for i in xrange(N - 1) for j in xrange(i + 1, N)]\n scipy_sum = np.sum(weights * Y)\n N = counts.sum()\n N_unique_pairs = N * (N - 1.0) / 2.0\n scipy_mean = scipy_sum / N_unique_pairs\n\n # C & Cython:\n c_mean = c_mean_dist(X, counts)\n\n # There is minor rounding error, but check for equality:\n self.assertTrue(np.isclose(c_mean, scipy_mean))\n # Even though above is comparing the means, it is actually checking the\n # sums are correct as the means are calculated in the same way, i.e.,\n # by dividing by the same number, N_unique_pairs.","def cluster(self, verbose=0, sum_ess=False):\n ## if sum_ess and self.linkage.__name__ != \"ward_link\":\n ## raise ValueError(\n ## \"Summing for method other than Ward makes no sense...\")\n clusters = copy.copy(self._dist_matrix)\n #clusters = self._dist_matrix\n summed_ess = 0.0\n\n while len(clusters) > max(self._num_clusters, 1):\n if verbose >= 1:\n print('k=%s' % len(clusters))\n if verbose == 2:\n print(clusters)\n\n best, i, j = self.smallest_distance(clusters)\n # In Ward (1963) ess is summed at each iteration\n # in R's hclust and Python's hcluster and some text books it is not.\n # Here it is optional...\n if sum_ess:\n summed_ess += best\n else:\n summed_ess = best\n clusters = self.update_distmatrix(i, j, clusters)\n self._dendrogram.merge(i,j)\n self._dendrogram[i].distance = summed_ess\n indices = numpy.arange(clusters.shape[0])\n indices = indices[indices!=j]\n clusters = clusters.take(indices, axis=0).take(indices, axis=1)","def _calculate_distances(self):\n all_dists = []\n for ref in range(len(self.atoms)):\n if self.atoms[ref].symbol in self.exclude:\n continue\n indices = list(range(ref+1, len(self.atoms)))\n indices = self._filter_excluded(indices)\n if len(indices) == 0:\n continue\n dists = self.atoms.get_distances(ref, indices, mic=True)\n all_dists += list(dists)\n \n # Normalize by the mean distance\n return np.array(all_dists)/np.mean(all_dists)","def cluster_spatial_positioning(data):\n \n n_clusters = len(set(data['clusters'])-{-1}) # since -1 element denotes noice\n if n_clusters <2:\n #Setting cluster angluar features to default\n cdist=[Cluster_Relative_Distances()]\n cdist = pd.DataFrame([o.__dict__ for o in cdist])\n\n elif n_clusters >=2:\n # Here we implement two approaches for measuring distances between clustes:\n # (1) border-boder distances and (2) centroid-centroid distances. \n # We compute dispersion measures for the distances obtained. \n \n d = dict(tuple(data.groupby('clusters')))\n d.pop(-1, None)\n\n min_dist_between_clusters=np.row_stack([[np.amin(ss.distance_matrix(np.column_stack([d[i]['X'].array,d[i]['Y'].array]), \n np.column_stack([d[j]['X'].array,d[j]['Y'].array]))) for j in d.keys()] for i in d.keys()])\n min_dist_between_clusters=np.delete(list(set(np.frombuffer(min_dist_between_clusters))) ,0)\n\n cen_dist_between_clusters=ss.distance_matrix(np.row_stack([(np.mean(d[i]['X'].array),np.mean(d[i]['Y'].array)) for i in d.keys()]),\n np.row_stack([(np.mean(d[i]['X'].array),np.mean(d[i]['Y'].array)) for i in d.keys()]))\n cen_dist_between_clusters=np.delete(list(set(np.frombuffer(cen_dist_between_clusters))) ,0)\n\n (avg_bor_bor_dist_cluster,min_bor_bor_dist_cluster,max_bor_bor_dist_cluster,\n std_bor_bor_dist_cluster,CV_bor_bor_dist_cluster,CD_bor_bor_dist_cluster,\n IQR_bor_bor_dist_cluster,Quartile_CD_bor_bor_dist_cluster)= distribution_statistics(min_dist_between_clusters)\n\n (avg_cen_cen_dist_cluster,min_cen_cen_dist_cluster,max_cen_cen_dist_cluster,\n std_cen_cen_dist_cluster,CV_cen_cen_dist_cluster,CD_cen_cen_dist_cluster,\n IQR_cen_cen_dist_cluster,Quartile_CD_cen_cen_dist_cluster)= distribution_statistics(cen_dist_between_clusters)\n\n cdist = [Cluster_Relative_Distances([avg_bor_bor_dist_cluster,min_bor_bor_dist_cluster,max_bor_bor_dist_cluster,\n std_bor_bor_dist_cluster,CV_bor_bor_dist_cluster,CD_bor_bor_dist_cluster,\n IQR_bor_bor_dist_cluster,Quartile_CD_bor_bor_dist_cluster,\n avg_cen_cen_dist_cluster,min_cen_cen_dist_cluster,max_cen_cen_dist_cluster,\n std_cen_cen_dist_cluster,CV_cen_cen_dist_cluster,CD_cen_cen_dist_cluster,\n IQR_cen_cen_dist_cluster,Quartile_CD_cen_cen_dist_cluster])]\n \n cdist = pd.DataFrame([o.__dict__ for o in cdist])\n\n \n return cdist","def __calculate_estimation(self):\r\n estimation = 0.0\r\n for index_cluster in range(0, len(self.__clusters)):\r\n cluster = self.__clusters[index_cluster]\r\n index_medoid = self.__current[index_cluster]\r\n for index_point in cluster:\r\n estimation += euclidean_distance_square(self.__pointer_data[index_point], self.__pointer_data[index_medoid])\r\n\r\n return estimation","def train_KMean(data: np.array, labels: np.array, n_clusters: int)->None:\n n_examples = np.size(data, 0)\n n_features = np.size(data, 1)\n\n # Scale the data so that Euclidian distance makes sense\n means = np.mean(data, axis = 0)\n stddevs = np.std(data, axis = 0, ddof = 1)\n\n #print(means)\n #print(stddevs)\n\n data_scaled = np.zeros((n_examples, n_features))\n\n for i in range(n_features):\n data_scaled[:, i] = (data[:,i] - means[i]) / stddevs[i]\n\n study_correlation(data_scaled)\n\n # Initialize the centroids\n idx = np.random.randint(n_examples, size = n_clusters)\n centroids = data_scaled[idx, :]\n\n counter = 0\n\n while True:\n\n distances = np.array([[np.sqrt(np.sum(np.square(example-centroid))) for centroid in centroids] for example in data_scaled])\n centroid_idx = np.argmin(distances, axis = 1)\n old_centroids = centroids\n centroids = update_centroids(data_scaled, centroid_idx, n_examples)\n #displacement = get_displacement(old_centroids, centroids)\n displacement = np.linalg.norm(np.array([old - new for old, new in zip(old_centroids, centroids)]))\n\n #assert np.linalg.norm(np.array([old - new for old, new in zip([1, 2, 3, 4], [5, 6, 7, 8])])) == 8\n\n if counter == 0:\n# print(\"Initial displacement = {}\".format(displacement))\n initial_displacement = displacement\n\n counter += 1\n\n if displacement < (initial_displacement / 10000): break\n\n #print(\"Total number of loops before ending : {}\".format(counter))\n converted_predictions = convert_predictions(centroid_idx)\n accuracy = np.mean([p == l for p, l in zip(converted_predictions, labels)])\n print(\"Accuracy = {}\".format(accuracy))\n\n pass","def calcCentroid(self):\n size = len(self.vectors)\n # zip all features together\n zipped = zip(*self.vectors)\n # Calculate the mean for each feature/column\n centroid = [math.fsum(column)/size for column in zipped]\n \n return centroid","def compute_distance(X, K_clusters):\n dis = np.linalg.norm((X-K_clusters),2,axis=1)**2\n return dis","def cluster_cal(self):\n self.Cluster = []\n for i in range(self.nodenum):\n neighborhood_node = self.neighbor_node(i)\n Node_num = len(neighborhood_node)\n Count = self.neighbor_edge(neighborhood_node)\n if(Node_num == 0 or Node_num == 1):\n self.Cluster.append(0.5)\n else:\n self.Cluster.append(Count/(Node_num*(Node_num - 1)))\n \n self.cluster_coeff = np.average(self.Cluster)","def computeLoss(self):\n return sum(np.arccosh(-minkowskiArrayDot(self.examples, self.centroid)) ** 2)[0] / np.shape(self.examples)[0]","def __compute_distance(self, x, centroid):\n \n diff = x - centroid\n return np.sqrt(np.dot(diff.T, diff))","def __calculate_estimation(self):\n estimation = 0.0\n for index_cluster in range(0, len(self.__clusters)):\n cluster = self.__clusters[index_cluster]\n index_medoid = self.__current[index_cluster]\n for index_point in cluster:\n estimation += euclidean_distance_square(\n self.__pointer_data[index_point],\n self.__pointer_data[index_medoid],\n )\n\n return estimation","def clustering(df, mode):\n # split into list of dfs containing only one reference node\n df_list = [df.loc[i : i + 8 - 1, :] for i in range(0, len(df), 8)]\n\n df_coefficient = pd.DataFrame()\n\n # loop over every single node\n for df_single in df_list:\n df_single = df_single.reset_index()\n total_value = 0\n\n # loop over the weights of all connected nodes\n for j in range(len(df_single) - 1):\n if mode == \"geometric\":\n # geometric\n total_value = total_value + math.sqrt(df_single.chi_sq[j] * df_single.chi_sq[j + 1])\n if mode == \"arithmetic\": \n # arithmetic\n total_value = total_value + ((df_single.chi_sq[j] * df_single.chi_sq[j + 1]) / 2)\n if mode == \"argmax\": \n # max\n total_value = total_value + max(df_single.chi_sq[j], df_single.chi_sq[j + 1])\n if mode == \"argmin\":\n # min\n total_value = total_value + min(df_single.chi_sq[j], df_single.chi_sq[j + 1])\n\n for i in range(len(df_single) - 1):\n if mode == \"geometric\":\n # geometric\n triplet_value = math.sqrt(df_single.chi_sq[i] * df_single.chi_sq[i + 1])\n if mode == \"arithmetic\":\n # arithmetic\n triplet_value = (df_single.chi_sq[i] * df_single.chi_sq[i + 1]) / 2\n if mode == \"argmax\":\n # max\n triplet_value = max(df_single.chi_sq[i], df_single.chi_sq[i + 1])\n if mode == \"argmin\": \n # min\n triplet_value = min(df_single.chi_sq[i], df_single.chi_sq[i + 1])\n\n cluster_coefficient = triplet_value / total_value\n buffer = [\n [\n df_single.reference[i],\n df_single.comparison[i],\n df_single.comparison[i + 1],\n triplet_value,\n cluster_coefficient,\n ]\n ]\n df_coefficient = df_coefficient.append(buffer)\n\n df_coefficient = df_coefficient.reset_index()\n\n print(\"\\n\\n threshold 0.5*c_omega\")\n check_list = []\n # print out triangles that have a cluster coefficient bigger, than X\n for i in range(len(df_coefficient)):\n if df_coefficient[4][i] >= ((0.5) * df_coefficient[4].max()):\n print(list(df_coefficient.loc[i][1:4]))\n check_list.append(list(df_coefficient.loc[i][1:4]))\n else:\n continue\n\n print(\"\\n\\n threshold 0.75*c_omega\")\n check_list = []\n for i in range(len(df_coefficient)):\n if df_coefficient[4][i] >= ((0.75) * df_coefficient[4].max()):\n print(list(df_coefficient.loc[i][1:4]))\n check_list.append(list(df_coefficient.loc[i][1:4]))\n else:\n continue\n\n print(\"\\n\\n threshold 0.8*c_omega\")\n check_list = []\n for i in range(len(df_coefficient)):\n if df_coefficient[4][i] >= ((0.9) * df_coefficient[4].max()):\n print(list(df_coefficient.loc[i][1:4]))\n check_list.append(list(df_coefficient.loc[i][1:4]))\n else:\n continue\n\n\n print(\"\\n\\n threshold 0.9*c_omega\")\n check_list = []\n for i in range(len(df_coefficient)):\n if df_coefficient[4][i] >= ((0.9) * df_coefficient[4].max()):\n print(list(df_coefficient.loc[i][1:4]))\n check_list.append(list(df_coefficient.loc[i][1:4]))\n else:\n continue\n\n return","def compute_distortion(cluster_list, data_table):\r\n distortion = 0\r\n \r\n for cluster in cluster_list:\r\n distortion += cluster.cluster_error(data_table)\r\n\r\n return distortion","def _recalculate_centroids(self):\n\n self._prev_centroids = dict(self.centroids)\n for cluster in self.clusters:\n self.centroids[cluster] = np.average(self.clusters[cluster], axis=0)","def calculate_all_distances_to_center(self):\n all_distances = pd.DataFrame()\n for label in np.unique(self.embedding_df['cluster']): \n distance_df = self.calculate_distances_for_cluster(label)\n all_distances = pd.concat([all_distances, distance_df])\n \n self.embedding_df = self.embedding_df.merge(all_distances, left_index=True, right_index=True)","def compute_distortion(cluster_list, data_table):\n\tdistortion = 0\n\tfor cluster in cluster_list:\n\t\tdistortion += cluster.cluster_error(data_table)\n\treturn distortion","def cluster_index_2(X):\n \n global_mean = X.mean(axis=0)\n\n sum_squared_distances = (((X - global_mean)**2).sum(axis = 1)).sum()\n #Sum of squared distances of each sample from the global mean\n \n centroids, labels, inertia = k_means(X, 2)\n\n ci = inertia / sum_squared_distances\n\n return ci , labels","def _assign_clusters(self):\n\n dist = np.zeros((self.k, ))\n distortion = 0\n\n for index in range(0, self.data.shape[0]):\n for i in range(0, self.k):\n dist[i] = np.linalg.norm(self.data[index] - self.centroids[i])\n\n self.assigned_clusters[index] = np.argmin(dist)\n distortion += np.min(dist)\n\n return distortion","def error(self, documents):\n ###TODO\n sum_1 = 0.0\n for c_id,clust in self.fin_clust.items():\n n = self.sqnorm(self.means[c_id]) \n sum_1 = sum_1 + sum([self.distance(self.docs[dc],self.means[c_id],n) for dc in clust]) \n return round(sum_1,2)","def wca_mean(X, k, df):\n\t\n\n\t# Intializing the clusters\t\n\tC = dict()\n\tfor cluster in range(k):\n\t C[cluster] = pd.DataFrame()\n\n\t# Calculating the mean vector\n\tmean_vector = X.mean()\n\n\t# Choosing the seed points based on the minimum distance from the mean vector\n\tX['dist_mean'] = X.apply(lambda x: np.linalg.norm(np.asarray(x)- np.asarray(mean_vector)), axis=1)\n\tdist_means = X.sort_values(by='dist_mean')\n\t\n\t# Dropping the the datapoints which have already been assigned as seed\n\tidx_to_drop = dist_means.index[:k]\n\tdist_means.reset_index(drop=True,inplace=True)\n\tX.drop('dist_mean',axis=1,inplace=True)\n\tX.drop(idx_to_drop, inplace=True)\n\n\t# Assigning seed points to the clusters\n\tmu = list()\n\tfor cluster in range(k):\n\t C[cluster] = C[cluster].append(dist_means.iloc[cluster].drop('dist_mean'))\n\t mu.append(C[cluster].mean())\n\t\n\t# Running the algorithm\t\n\t\n\t# Initializing the p-value list which would be used for plotting\n\tpval = dict()\n\n\tfor cluster in range(k):\n\t pval[cluster] = dict()\n\t for i in C[0].columns:\n\t pval[cluster][i] = list()\n\n\t# Algorithm\n\tfor i in tqdm(range(int(len(X)/k)), desc='Iterations: '):\n\t for cluster in range(k):\n\n\t # Calculating the distances from the mean vector of eaimportch cluster (in Descending order)\n\t X['dist_mean'] = X.apply(lambda x: np.linalg.norm(np.asarray(x)- np.asarray(mu[cluster])), axis=1)\n\t dist_means = X.sort_values(by='dist_mean', ascending=False)\n\t idx_to_drop = dist_means.index[0]\n\t dist_means.reset_index(drop=True,inplace=True)\n\t X.drop('dist_mean',axis=1,inplace=True)\n\n\t # Assigning the top value to the cluster\n\t C[cluster] = C[cluster].append(dist_means.iloc[0].drop('dist_mean'))\n\t C[cluster] = C[cluster].reset_index(drop=True)\n\t \n\t # Updating means of each cluster\n\t mu[cluster] = C[cluster].mean()\n\n\t # Remove datapoint from X?\n\t X.drop(idx_to_drop,inplace=True)\n\t \n\t for i in C[0].columns:\n\t pval[cluster][i].append(sc.ks_2samp(C[cluster][i],df.drop('target',axis=1)[i])[1])\n\n\treturn(C,pval)","def find_avg(centroids, short_cut=False, sim_scores=None):\n \n total_sim = 0.0\n total_comparisons = 0\n \n if short_cut:\n total_comparisons = len(sim_scores)\n \n for score in sim_scores:\n total_sim += score\n \n return (total_sim / total_comparisons)\n\n length = len(centroids)\n\n for i in xrange(0, length):\n for j in xrange(i + 1, length):\n total_sim += similarity(centroids[i], centroids[j])\n total_comparisons += 1\n\n return (total_sim / total_comparisons)","def avg_dists(self):\n \n d = self.descriptors\n # make an empty array to fill b/c it is a touch faster\n averages = np.empty([1, self.d_length])\n for i, u in enumerate(d):\n s = 0\n for j, v in enumerate(d):\n if i != j:\n s += self.jaccard(u, v)\n averages[0, i] = (s / (self.d_length-1))\n return averages[0]","def compute_means(self):\n ###TODO\n vector_means = []\n for doc in self.fin_clust.values():\n vec = defaultdict(float)\n for d_id in doc:\n doc_keys = self.docs[d_id].keys()\n for key in self.docs[d_id]:\n vec[key] = vec[key] + self.docs[d_id][key]\n tot = len(doc)\n x = defaultdict(float)\n for k,v in vec.items():\n x[k] = float(v)/tot\n vec = Counter(x)\n vector_means.append(vec)\n return vector_means","def compute_distances(self, X):\n num_test = X.shape[0]\n num_train = self.X_train.shape[0]\n dists = np.zeros((num_test, num_train))\n \n sum_test_square = np.sum(np.square(X), axis=1).reshape(-1, 1)\n sum_train_square = np.sum(np.square(self.X_train), axis=1).reshape(-1, 1)\n product_test_train = X @ self.X_train.T\n \n sum_test_square = np.repeat(sum_test_square, num_train, axis=1)\n sum_train_square = np.repeat(sum_train_square, num_test, axis=1).T\n \n dists_square = sum_test_square - 2 * product_test_train + sum_train_square\n \n dists = np.sqrt(dists_square)\n \n return dists","def fit(self, train_data, metric=None):\n \n if metric==None:\n self.metric=self.euclidean_sqr\n\n if self.centroids_.shape[0]==0:\n centroids=self.random_init(train_data)\n else:\n centroids=self.centroids_\n\n # remove mean from data\n #train_data_mean=np.mean(train_data,axis=0)\n #train_data=train_data-train_data_mean\n # row norms??\n #train_data_sqr_norms = np.einsum('ij,ij->i', train_data, train_data)\n\n\n old_centroids=np.zeros(centroids.shape)\n\n # iterate until no change in cluster centers or defined number of iterations is reached\n n_iterations=self.n_iterations_\n while n_iterations>0 and np.array_equal(centroids,old_centroids)==False:\n n_iterations-=1\n old_centroids=centroids\n centroids=self.fit_iteration(train_data, centroids)\n \n self.centroids_=centroids\n return centroids","def get_cluster_average(cls, indices, dist_mat):\n distances = cls.get_all_distances(indices, dist_mat)\n return np.mean(distances)","def centroids(self):\n return self.mdm_.covmeans_","def euclidean_dist(self):\r\n\r\n real_cat, synth_cat = self.to_cat(self.origdst, self.synthdst)\r\n\r\n real_cat_dem = self.get_demographics(real_cat)\r\n synth_cat_dem = self.get_demographics(synth_cat)\r\n\r\n corr_real_obj = associations(real_cat_dem, theil_u=True, bias_correction=False, plot=False)\r\n corr_synth_obj = associations(synth_cat_dem, theil_u=True, bias_correction=False, plot=False)\r\n\r\n corr_real = corr_real_obj['corr']\r\n corr_rand = corr_synth_obj['corr']\r\n\r\n eucl_matr = distance.cdist(corr_real, corr_rand, 'euclidean')\r\n\r\n eucl = LA.norm(eucl_matr)\r\n\r\n return eucl, eucl_matr","def calculate_cost(data, centers, clusters):\n total = 0\n for i in range(len(centers)):\n total = total + np.sum(data[centers[i]][clusters[i]]) \n return total","def calcCentroids(data_points, clusters):\n #initiate empty list for the new centroids\n newCentroids = []\n\n #For position in each cluster, calculate the average for each position\n #The lists are zipped so each position can have an average\n for c in clusters:\n newCentroids.append(map(calcAverage, zip(*c)))\n\n #This is the check that a centroid is not empty. If a centroid is empty,\n #delete it, the filled centroids are added to the new list\n correctCentroid = []\n for centroid in newCentroids:\n #If centroid is not empty\n if centroid:\n correctCentroid.append(centroid)\n\n return len(correctCentroid), correctCentroid","def SquareClusteringCoefficient(graph):\n coef = np.mean(list(nx.square_clustering(graph).values()))\n return coef","def test_mean_of_distances(self):\n X = np.array([[0.3, 0.4],\n [0.1, 4.0],\n [2.0, 1.0],\n [0.0, 0.5]])\n counts = np.array([3, 2, 1, 2])\n scipy_X = []\n for c, count in enumerate(counts):\n for i in range(count):\n scipy_X.append(X[c])\n\n # SciPy:\n Y = pdist(scipy_X, metric=cdist)\n scipy_N = np.sum(counts)\n N_unique_pairs = scipy_N * (scipy_N - 1.0) / 2.0\n scipy_mean = Y.mean()\n self.assertTrue(Y.shape[0] == N_unique_pairs)\n self.assertTrue(scipy_mean == (np.sum(Y) / N_unique_pairs))\n\n # C & Cython:\n c_mean = c_mean_dist(X, counts)\n self.assertTrue(np.isclose(c_mean, scipy_mean))","def calculate_error(k_means_matrix):\n return sum([min(dist) for dist in k_means_matrix])","def assign_to_current_mean(img: np.ndarray, clustermask: np.ndarray) -> float:\n\n rows, cols = img.shape[:2]\n distances = np.zeros((numclusters, 1))\n overall_dist = 0\n\n for i in range(rows):\n for j in range(cols):\n distances = distance(img[i, j, :]) # returned shape: (numclusters, 1)\n \n k = np.argmin(distances) # closest cluster\n clustermask.itemset((i, j), k) # update cluster mask\n overall_dist += distances[k, 0] # sum distance\n\n return overall_dist","def _evaluate_centroids(self):\n\n for c in self.centroids:\n _prev_cent = self._prev_centroids[c]\n _curr_cent = self.centroids[c]\n\n if self._euclidean_distance(_prev_cent, _curr_cent) > self.tol:\n return\n self._optimized = True","def calculate_metric(self, distance_matrix):\n ap_scores = []\n for node_id in range(len(distance_matrix)):\n sorted_nodes = np.argsort(distance_matrix[node_id]).tolist()\n neighs = self.neighbors[node_id]\n n_correct = 0.0\n precisions = []\n for i in range(1, len(sorted_nodes)):\n if sorted_nodes[i] in neighs:\n n_correct += 1\n precisions.append(n_correct / i)\n if n_correct == len(neighs):\n break\n\n ap_scores.append(np.mean(precisions))\n\n return np.mean(ap_scores)","def compute_clusters(self, documents):\n ###TODO\n for d in range(0, len(documents)):\n maxi = 999999999\n for cid in range(0, len(self.means)):\n dist = self.distance(documents[d], self.means[cid], self.norms[cid])\n if dist < maxi:\n maxi = dist\n clust = cid \n self.cluster[d] = clust","def run(self, points, K):\n # Get size\n D, N = points.shape\n\n # DxK array initialiezd with random points\n centroids = points[:, np.random.permutation(N)[:K]]\n\n # Assigments 1xN array\n labels = np.zeros(N)\n\n for it in np.arange(self.niter):\n # 1. Compute distance to all cluster\n #v1 dirty\n distances = np.zeros([K, N])\n for n in np.arange(N):\n for k in np.arange(K):\n distances[k, n] = np.sqrt( (points[:, n] - centroids[:, k])**2 ).sum()\n #distances = np.sqrt(((points - centroids[:, np.newaxis, 0])**2)).sum(axis=0) \n\n # 2. Update assigments\n # v1 dirty\n for n in np.arange(N):\n kmin = 0\n for k in np.arange(1, K):\n if distances[k, n] <= distances[kmin, n]:\n kmin = k\n labels[n] = kmin\n # v2 quicker\n #labels = np.argmin(distances, axis=1)\n\n # 3. Update mean\n for k in np.arange(K):\n centroids[:, k] = np.mean(points[:, labels == k], axis=1)\n #np.array([points[closest==k].mean(axis=0) for k in range(centroids.shape[0])])\n\n return centroids, labels","def average_distance(c1, c2):\n return sum(sum(symmetric_distances[p1][p2] for p1 in c1) for p2 in c2) \\\n / (len(c1) * len(c2))","def calculate_centroids(self, data, clusters):\n centroids = []\n for i in range(self.n_clusters):\n mask = clusters == i \n centroids.append(np.mean(data[mask, :], axis = 0)) \n return centroids","def kmean(X,initial_centroids,max_iters):\n m = np.size(X,0)\n K = np.size(initial_centroids,0)\n centroids = initial_centroids\n idx = np.zeros((m,1))\n for i in range(1,max_iters):\n idx = nearest_cluster(X,centroids)\n centroids = update_centroids(X,idx,K)\n return centroids,idx","def k_means_clustering(rows, distance=pearson_distance, k=4):\n # Determine the min and max values for each point\n ranges = [(min(row[i] for row in rows), max([row[i] for row in rows])) for i in range(len(rows[0]))]\n\n # Create k RANDOMLY placed centroids\n clusters = [[random() * (ranges[i][1] - ranges[i][0]) + ranges[i][0] for i in range(len(rows[0]))] for j in\n range(k)]\n distances_from_centroids = {}\n last_matches = None\n best_matches = None\n for t in range(100):\n print ('Iteration {}'.format(t))\n best_matches = [[] for i in range(k)]\n\n # Find the centroid that is the closest for each row\n for j in range(len(rows)):\n row = rows[j]\n best_match = 0\n for i in range(k):\n d = distance(clusters[i], row)\n if d < distance(clusters[best_match], row):\n best_match = i\n best_matches[best_match].append(j)\n\n # if the results are the same as last time, then this is complete\n if best_matches == last_matches:\n break\n last_matches = best_matches\n\n # Move the centroids to the average of their members\n for i in range(k):\n avgs = [0.0] * len(rows[0])\n if len(best_matches[i]) > 0:\n for row_id in best_matches[i]:\n for m in range(len(rows[row_id])):\n avgs[m] += rows[row_id][m]\n for j in range(len(avgs)):\n avgs[j] /= len(best_matches[i])\n clusters[i] = avgs\n\n # Chapter 3 Exercise 5: Return along with the cluster results the total distance between all items\n # and their respective centroids\n for i in range(k):\n for j in range(len(best_matches[i])):\n distances_from_centroids[best_matches[i][j]] = distance(clusters[i],rows[best_matches[i][j]])\n return best_matches, distances_from_centroids","def update(self, clusters):\n centroids = {}\n for cluster, coordinates in clusters.iteritems():\n sumLat = 0\n sumLong = 0\n for coordinate in coordinates:\n sumLat += float(coordinate[0])\n sumLong += float(coordinate[1])\n centroids[cluster] = (sumLat/float(len(coordinates)), sumLong/float(len(coordinates)))\n return centroids","def centroid_link(clusters, i, j, dendrogram):\n n_i, n_j = len(dendrogram[i]), len(dendrogram[j])\n a_i = n_i / (n_i + n_j)\n a_j = n_j / (n_i + n_j)\n b = -(n_i * n_j) / (n_i + n_j)**2\n update_fn = lambda d_ik,d_jk: a_i*d_ik + a_j*d_jk + b*clusters[i,j]\n return _general_link(clusters, i, j, update_fn)","def _distorted_distance(self):\n distance = 0\n for i, pixel in enumerate(self.training_set):\n distance += self._euclid_distance(\n pixel, self.clusters[self.labels[i]], axis=0)\n return distance","def calc_centroid(self):\n num = 0\n centroid = numpy.zeros(3, float)\n for atm in self:\n if atm.position is not None:\n centroid += atm.position\n num += 1\n return centroid / num","def calculate(self):\n\n gt_n = np.count_nonzero(self.ground_truth)\n gt_indices = np.flip(np.where(self.ground_truth == 1), axis=0)\n gt_mean = gt_indices.mean(axis=1)\n gt_cov = np.cov(gt_indices)\n\n seg_n = np.count_nonzero(self.segmentation)\n seg_indices = np.flip(np.where(self.segmentation == 1), axis=0)\n seg_mean = seg_indices.mean(axis=1)\n seg_cov = np.cov(seg_indices)\n\n # calculate common covariance matrix\n common_cov = (gt_n * gt_cov + seg_n * seg_cov) / (gt_n + seg_n)\n common_cov_inv = np.linalg.inv(common_cov)\n\n mean = np.matrix(np.array(gt_mean) - np.array(seg_mean))\n\n return math.sqrt(mean * np.matrix(common_cov_inv) * mean.T)","def calcDistortion(medoids, clusters, class_header=\"Class\"):\n distortion = 0\n for medoid_row_index, medoid_tuple in enumerate(medoids.iterrows()): # For every Medoid\n for _, datum in clusters[medoid_row_index].iterrows(): # For each point in the medoid cluster\n # Add the distance between medoid and data point squared to total distortion\n distortion += (Cluster.calcDistance(medoid_tuple[1], datum, class_header=class_header)) ** 2\n return distortion","def _compute_mean(self, C, mag, rjb, rake):\n mean = (C['a1'] +\n self._compute_linear_magnitude_term(C, mag) +\n self._compute_quadratic_magnitude_term(C, mag) +\n self._compute_logarithmic_distance_term(C, mag, rjb) +\n self._compute_faulting_style_term(C, rake))\n\n return mean","def findK_centroids_average(self, features, clusters):\n\n class InnerFeatures:\n def __init__(self, kps, des, pos):\n self.kps = kps\n self.des = des\n self.pos = pos\n\n kmeans = KMeans(n_clusters=clusters)\n\n pts = np.array(features.pos)\n kps = np.array(features.kps)\n des = np.array(features.des)\n\n kmeans.fit(pts)\n m_clusters = np.array(kmeans.labels_.tolist())\n centers = np.array(kmeans.cluster_centers_)\n\n # KeyPoint(x,y,size) -required\n\n final_kps = []\n final_des = []\n final_pts = []\n\n for cluster in range(clusters):\n indices = np.where(m_clusters == cluster)\n cluster_kps_size = np.mean(np.array([x.size for x in kps[indices]]))\n cluster_des = des[indices]\n\n average_des = np.mean(cluster_des, axis=0)\n cluster_kps = cv2.KeyPoint(x=centers[cluster][0], y=centers[cluster][1], _size=cluster_kps_size)\n\n final_kps.append(cluster_kps)\n final_des.append(average_des)\n final_pts.append([centers[cluster][0], centers[cluster][1]])\n\n final_pts = np.array(final_pts)\n final_des = np.array(final_des)\n final_kps = np.array(final_kps)\n\n result = InnerFeatures(kps=final_kps, des=final_des, pos=final_pts)\n return result","def fit(self):\n self.cluseter_agglomerative(n_clusters=20, linkage='average', iterate=5)\n self.sub_clustering(n_clusters=3, index_cluster=[79], linkage='complete')\n self.merge_clusters([[0,9,53],[1,83],[46,35,67],[88,23],[6,68]])\n self.merge_clusters([[6,33,52],[17,14]])\n self.sub_clustering(n_clusters=2, index_cluster=[0], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[2], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[85], linkage='average')\n self.sub_clustering(n_clusters=2, index_cluster=[14], linkage='complete')\n self.sub_clustering(n_clusters=2, index_cluster=[16], linkage='average')\n self.sub_clustering(n_clusters=3, index_cluster=[22], linkage='average')\n self.sub_clustering(n_clusters=2, index_cluster=[24], linkage='complete')\n self.sub_clustering(n_clusters=2, index_cluster=[26], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[28], linkage='ward')\n self.merge_clusters([[6,98,99]])\n self.merge_clusters([[35,80]])\n self.sub_clustering(n_clusters=4, index_cluster=[35], linkage='complete')\n self.merge_clusters([[76,98]])\n self.sub_clustering(n_clusters=3, index_cluster=[35], linkage='complete')\n self.merge_clusters([[39,42]])\n self.sub_clustering(n_clusters=3, index_cluster=[47], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='average')\n self.merge_clusters([[70,101]])\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='complete')\n self.sub_clustering(n_clusters=3, index_cluster=[61], linkage='ward')\n self.merge_clusters()\n return","def _compute_distances(self, atoms: List[CellAtom]):\n muon = self._cell_atoms[self._muon_index]\n\n for atom in atoms:\n atom.distance_from_muon = np.linalg.norm(muon.position - atom.position)","def run_k_means(self):\r\n centroids = self.centroids\r\n\r\n for i in range(self.max_iters):\r\n self.closestcentroids()\r\n self.newcentroids()\r\n\r\n J = 0\r\n X = self.x\r\n m = len(X)\r\n idx = self.index\r\n K = self.K\r\n dim = X.shape[1]\r\n\r\n for num in range(K):\r\n # find the index of all entries where idx==n\r\n indexentries = np.nonzero(idx == num)[0]\r\n # the values in X that have the index in indesxentries\r\n values = X[indexentries]\r\n # using one of the K centroids to do the calculation. K<=2 doesn't\r\n # work here for some reason.\r\n centroid = centroids[num, 0]\r\n J += np.sum((values - centroid) ** 2)\r\n\r\n return [centroids.reshape((1, K, dim)), [X[idx == k].size for k in range(K)], J / m]","def _eval_clustering(self, gen_reviews, clusters, embedding_model, clustering):\n result = []\n preds = self.predict_gen(gen_reviews, embedding_model, clustering)\n\n acc = accuracy_score(np.array(clusters), np.array(preds))\n conf = confusion_matrix(np.array(clusters), np.array(preds))\n\n return acc, conf","def calculate_all_metrcis(self):\n self.calculate_gc_metrcis()\n self.calculate_sam_metrics()\n self.calculate_classification_metrics()\n self.calculate_losses()","def _cluster(self):\n # , distance_function=spearman_squared_distance, max_iter=1000, tol=0.0001):\n if self.cluster_method is None:\n clusters = KMedoids(\n self.k,\n self.batchsize,\n dist_func=self.distance_function,\n max_iter=self.max_iter,\n tol=self.tol,\n init_medoids=self.init_medoids,\n swap_medoids=self.swap_medoids,\n )\n clusters.fit(self.clustering_attributions, verbose=self.verbose)\n\n self.subpopulations = clusters.members\n self.subpopulation_sizes = GAM.get_subpopulation_sizes(clusters.members)\n self.explanations = self._get_explanations(clusters.centers)\n # Making explanations return numerical values instead of dask arrays\n if isinstance(self.explanations[0][0][1], da.Array):\n explanations = []\n for explanation in self.explanations:\n explanations.append([(x[0], x[1].compute()) for x in explanation])\n self.explanations = explanations\n else:\n self.cluster_method(self)","def kmeans(X, k, iterations=1000):\n\n # Initialize the cluster centroids (C <- centroid \"means\")\n C = initialize(X, k)\n\n if C is None:\n return None, None\n if not isinstance(iterations, int) or iterations <= 0:\n return None, None\n\n # n: number of dada points\n # d: dimension of each data point\n n, d = X.shape\n\n # # Initialize the cost/distortion function;\n # # defined as J = sum/n(sum/k(r(ij)*||x(i) - c(j)||**2))\n # J = np.inf\n\n # Iterate over iterations\n for iteration in range(iterations):\n # print(\"iteration:\", iteration)\n\n # Maintain a deep copy of C\n # C_prev = np.array([x for x in C])\n # Another alternative (removes for loop):\n C_prev = np.copy(C)\n\n # OPTION 1: FOR LOOPS\n\n # Initialize the array of pairwise data point-centroid\n # distances with zeros\n # dist = np.zeros((n, k))\n\n # for i in range(n):\n # for j in range(k):\n # dist[i, j] = np.linalg.norm(X[i, ...] - C[j, ...])\n # Note: squared distances can alternatively be inferred\n # directtly from the inner product of (X - C) with itself\n # dist[i, j] = np.inner(X[i,:]-C[j,:], X[i,:]-C[j,:])\n # print(\"dist:\", dist)\n # Squared distances from \"dist\":\n # print(\"dist ** 2:\", dist ** 2)\n\n # OPTION 2: VECTORIZATION\n\n # Convert X into an array suitable for vectorization\n Xv = np.repeat(X, k, axis=0)\n # print(\"Xv:\", Xv)\n # print(\"Xv.shape:\", Xv.shape)\n Xv = Xv.reshape(n, k, d)\n # print(\"Xv:\", Xv)\n # print(\"Xv.shape:\", Xv.shape)\n\n # Convert C into an array suitable for vectorization\n Cv = np.tile(C, (n, 1))\n # print(\"Cv:\", Cv)\n # print(\"Cv.shape:\", Cv.shape)\n Cv = Cv.reshape(n, k, d)\n # print(\"Cv:\", Cv)\n # print(\"Cv.shape:\", Cv.shape)\n\n # Compute the \"dist\" matrix of euclidean distances between\n # data points and centroids; shape (n, k)\n dist = np.linalg.norm(Xv - Cv, axis=2)\n\n # Assign each point of the dataset to a centroid:\n # Evaluate argmin(dist**2) for comparison with k\n # r(ij) = 1 if argmin(dist**2) == j\n # -> point i assigned to centroid k\n # otherwise r(ij) = 0 -> ignore point i wrt centroid k\n clss = np.argmin(dist ** 2, axis=1)\n # print(\"centroid indices:\", clss)\n # print(\"clss.shape:\", clss.shape)\n # Note: here, clss is a 1D array of the unique centroid index\n # to which each point in the dataset as been assigned (closest to);\n # the indices array is used in place of r(ij) in J evaluations\n\n # OPTION 1: EXIT CONDITION BASED ON J_prev == J\n\n # # Make a copy of the previous J value & reinitialize J\n # J_prev = J\n # # J = 0\n\n # # Update J (summing over the n data points),\n # # based on the (shortest) distances inferred from \"indices\"\n # # From \"for\" loop:\n # # for i in range(n):\n # # J += (dist[i, clss[i]] ** 2)\n # # From vectorization:\n # J = np.sum(dist[..., clss] ** 2)\n # # Normalize J to the number of data points to\n # # reduce the computational cost (optional)\n # J /= n\n # # print(\"J:\", J)\n\n # if J == J_prev:\n # # print(\"last iteration:\", iteration)\n # return C, clss\n\n # Move the cluster centroids to the center (mean) of\n # the refined cluster by updating C (centroid coordinates)\n for j in range(k):\n # Infer the array of data point indices that correspond\n # to each assigned cluster centroid\n indices = np.where(clss == j)[0]\n # print(\"indices:\", indices)\n if len(indices) == 0:\n C[j] = initialize(X, 1)\n else:\n C[j] = np.mean(X[indices], axis=0)\n\n # OPTION 2: EXIT CONDITION BASED ON C == C_prev\n\n if (C == C_prev).all():\n # print(\"last iteration:\", iteration)\n return C, clss\n\n # Update clss before returning C, clss\n Cv = np.tile(C, (n, 1))\n Cv = Cv.reshape(n, k, d)\n dist = np.linalg.norm(Xv - Cv, axis=2)\n clss = np.argmin(dist ** 2, axis=1)\n\n return C, clss","def evaluate_clusters(self, cluster_formulas, value='weighted_sum'):\n num_elems = len(self.labels)\n total_val = {}\n num_cl = len(cluster_formulas)\n clustered_points_num = 0\n print(\"\\n\\n\")\n print(\"Sufficiently big clusters: {}\".format(num_cl))\n for c, formula, val in cluster_formulas:\n c_size = len([l for l in self.labels if l == c])\n clustered_points_num += c_size\n\n if value == 'weighted_sum':\n total_val[c] = val * c_size / num_elems\n elif value == 'sum':\n total_val[c] = val * 1\n\n clust_val = sum(total_val.values())\n self.clustering_value = total_val\n print(\"Value of clustering: {}\".format(clust_val))\n return clust_val","def _calculate_analysis_values(predicted_clusters, true_cluster, times):\n logger = get_logger('analysis', logging.INFO)\n logger.info('Calculate scores')\n\n # Initialize output\n metric_results = [None] * len(metric_names)\n for m, min_value in enumerate(metric_min_values):\n if min_value == 1:\n metric_results[m] = np.ones(len(true_cluster))\n else:\n metric_results[m] = np.zeros((len(true_cluster)))\n\n # Loop over all possible clustering\n for i, predicted_cluster in enumerate(predicted_clusters):\n logger.info('Calculated Scores for {}/{} predicted clusters'.format(i, len(predicted_clusters)))\n # Calculate different analysis's\n metric_results[0][i] = misclassification_rate(true_cluster, predicted_cluster)\n metric_results[1][i] = average_cluster_purity(true_cluster, predicted_cluster)\n metric_results[2][i] = adjusted_rand_index(true_cluster, predicted_cluster)\n metric_results[3][i] = diarization_error_rate(true_cluster, predicted_cluster, times)\n\n return metric_results","def find_centroid_for_each(self):","def calc_error_dist(self):\n pass","def train(self, train_X, max_iterations=1000):\n assert len(train_X.shape) == 2 and train_X.shape[1] == self.D, f\"train_X should be a NxD matrix. Got: {train_X.shape}\"\n assert max_iterations > 0, f\"max_iterations must be positive. Got: {max_iterations}\"\n N = train_X.shape[0]\n\n labels = np.empty(shape=(N, 1), dtype=np.long)\n distances = np.empty(shape=(N, self.K))\n for _ in range(max_iterations):\n old_labels = labels\n\n # ====================================================\n for index, center in enumerate(self.centers): # build the distances matrix\n # K iterations\n newDistanceCol = np.square(np.linalg.norm(train_X - center, axis=1))\n distances[:, index] = newDistanceCol\n\n labels = np.argmin(distances, axis=1).reshape((N, 1))# update labels based on distances\n\n cluster_child_count = np.zeros((1, self.K))\n self.centers = np.zeros(self.centers.shape) # replace with zeros\n\n\n for x_index, center_index in enumerate(labels): #update centers value\n # N iterations\n self.centers[center_index] += train_X[x_index, :] # increment centers\n cluster_child_count[:, center_index] += 1 # inc number of children in that center\n\n self.centers /= cluster_child_count.T # divide by number of children in each center to get avg\n # ====================================================\n\n # Check convergence\n if np.allclose(old_labels, labels):\n break\n\n return labels","def k_clusters(old_ops, max_outputs, mut):\n \n # DM construction\n matrix = starting_centroids(old_ops, max_outputs, mut)\n\n\n # Clustering\n seed = []\n for i in matrix.OPs:\n seed.append(i)\n centroids = cluster(old_ops, seed, mut)\n disto = distortion(centroids, old_ops, mut)\n\n return centroids, disto","def mean_cluster(self, labelled_cluster):\n sum_of_points = self.sum_cluster(labelled_cluster)\n size_cluster = len(labelled_cluster)\n if self.sigma_cl1:\n size_cluster += np.sqrt(2)*self.sigma_cl1*np.random.randn()\n mean_of_points = sum_of_points * (1.0 / size_cluster)\n return mean_of_points","def clusterAndDistance(self, data):\n\t\treturn closestClusterAndDistance(data, self.centers)","def _compute_dist(self, K, dist, within_distances, update_within):\r\n\r\n sw = self.sample_weight_\r\n\r\n for j in xrange(self.n_clusters):\r\n mask = self.labels_ == j\r\n if np.sum(mask) == 0:\r\n raise ValueError(\"Empty cluster found, try smaller n_cluster.\")\r\n\r\n denom = sw[mask].sum()\r\n denomsq = denom * denom\r\n if update_within:\r\n KK = K[mask][:, mask] \r\n dist_j = np.sum(np.outer(sw[mask], sw[mask]) * KK / denomsq)\r\n within_distances[j] = dist_j\r\n dist[:, j] += dist_j\r\n else:\r\n dist[:, j] += within_distances[j]\r\n\r\n dist[:, j] -= 2 * np.sum(sw[mask] * K[:, mask], axis=1) / denom #calculating distance of each point from centroid of cluster j by finding \r\n #diff. b/w centroid of cluster j & similarity of it with points in cluster j\r","def cluster_means(self):\n if self.evaluate_by is not None:\n return(self.merged_data.groupby(\n 'labels').mean().sort_values(self.evaluate_by).transpose())\n else:\n return(self.merged_data.groupby('labels').mean().transpose())","def _transform(self, X):\r\n return euclidean_distances(X, self.cluster_centers_)","def compute_cost(X, groups, K_clusters):\n m = X.shape[0]\n dis = np.empty(m)\n for i in range(m):\n dis[i] = compute_distance(X[i,:].reshape(1,X.shape[1]), K_clusters[groups[i],:].reshape(1,X.shape[1]))\n cost = (1/m)*np.sum(dis)\n return cost","def computeKMeans(self, points, k):\n centroids = self.init_centroids(points,k)\n \n for i in range(5):\n closest = self.closestCentroids(points,centroids)\n centroids = self.updateCentroids(points, closest ,centroids)\n\n return centroids","def calculateEuclideanDistance(vector):\r\n global euclideanDistance\r\n # create linkage matrix with the distance metric as euclidean distance\r\n # calculate the distances of the clusters by starting as singletons\r\n # and in each iteration will merge the two clusters which have the smallest distance\r\n # returns array of length n - 1\r\n # Z[i] will tell us which clusters were merged in the i-th iteration\r\n # each row has format [cluster1, cluster1, dist, sample_count].\r\n euclideanDistance = linkage(vector, metric='euclidean')","def ex7():\n\n \"\"\"\n ================= Part 1: Find Closest Centroids ====================\n To help you implement K-Means, we have divided the learning algorithm\n into two functions -- find_closest_centroids and computeCentroids. In this\n part, you shoudl complete the code in the find_closest_centroids function.\n \"\"\"\n print('Finding closest centroids.\\n\\n')\n\n # Load an example dataset that we will be using\n with open('ex7/data/ex7data2.pkl', 'rb') as fin:\n X = pickle.load(fin)\n\n # Select an initial set of centroids\n K = 3 # 3 Centroids\n initial_centroids = np.array([[3, 3], [6, 2], [8, 5]])\n\n # Find the closest centroids for the examples using the\n # initial_centroids\n idx = find_closest_centroids(X, initial_centroids)\n\n print('Closest centroids for the first 3 examples: \\n')\n print(idx[0:3])\n print('\\n(the closest centroids should be 0, 2, 1 respectively)\\n')\n\n \"\"\"\n ===================== Part 2: Compute Means =========================\n After implementing the closest centroids function, you should now\n complete the computeCentroids function.\n \n \"\"\"\n print('\\nComputing centroids means.\\n\\n')\n\n # Compute means based on the closest centroids found in the previous part.\n centroids = compute_centroids(X, idx, K)\n\n print('Centroids computed after initial finding of closest centroids: \\n')\n print(centroids)\n print('\\n(the centroids should be\\n')\n print(' [ 2.428301 3.157924 ]\\n')\n print(' [ 5.813503 2.633656 ]\\n')\n print(' [ 7.119387 3.616684 ]\\n)\\n')\n\n \"\"\"\n =================== Part 3: K-Means Clustering ======================\n After you have completed the two functions computeCentroids and\n find_closest_centroids, you have all the necessary pieces to run the\n kMeans algorithm. In this part, you will run the K-Means algorithm on\n the example dataset we have provided.\n \"\"\"\n print('\\nRunning K-Means clustering on example dataset.\\n\\n')\n\n # Load an example dataset\n with open('ex7/data/ex7data2.pkl', 'rb') as fin:\n X = pickle.load(fin)\n\n # Settings for running K-Means\n K = 3\n max_iters = 10\n\n \"\"\"\n For consistency, here we set centroids to specific values\n but in practice you want to generate them automatically, such as by\n settings them to be random examples (as can be seen in\n kmeans_init_centroids).\n \"\"\"\n initial_centroids = np.array([[3, 3], [6, 2], [8, 5]])\n\n # Run K-Means algorithm. The 'true' at the end tells our function to plot\n # the progress of K-Means\n centroids, idx = run_kmeans(X, initial_centroids, max_iters, True)\n print('\\nK-Means Done.\\n\\n')\n\n \"\"\"\n ============= Part 4: K-Means Clustering on Pixels ===============\n In this exercise, you will use K-Means to compress an image. To do this,\n you will first run K-Means on the colors of the pixels in the image and\n then you will map each pixel on to it's closest centroid.\n \n You should now complete the code in kmeans_init_centroids.py\n \"\"\"\n\n print('\\nRunning K-Means clustering on pixels from an image.\\n\\n')\n\n # Load an image of a bird\n A = plt.imread('ex7/data/bird_small.png')\n # A = A / 255; # Divide by 255 so that all values are in the range 0 - 1\n\n # Size of the image\n img_size = A.shape\n\n # Reshape the image into an Nx3 matrix where N = number of pixels.\n # Each row will contain the Red, Green and Blue pixel values\n # This gives us our dataset matrix X that we will use K-Means on.\n X = np.reshape(A, (img_size[0] * img_size[1], 3))\n\n # Run your K-Means algorithm on this data\n # You should try different values of K and max_iters here\n K = 16\n max_iters = 10\n\n # When using K-Means, it is important the initialize the centroids\n # randomly.\n # You should complete the code in kmeans_init_centroids.py before proceeding\n initial_centroids = kmeans_init_centroids(X, K)\n\n # Run K-Means\n [centroids, idx] = run_kmeans(X, initial_centroids, max_iters)\n\n \"\"\"\n ================= Part 5: Image Compression ======================\n In this part of the exercise, you will use the clusters of K-Means to\n compress an image. To do this, we first find the closest clusters for\n each example. After that, we \n \"\"\"\n print('\\nApplying K-Means to compress an image.\\n\\n')\n\n # Find closest cluster members\n idx = find_closest_centroids(X, centroids)\n\n # Essentially, now we have represented the image X as in terms of the\n # indices in idx.\n\n # We can now recover the image from the indices (idx) by mapping each pixel\n # (specified by it's index in idx) to the centroid value\n X_recovered = centroids[idx, :]\n\n # Reshape the recovered image into proper dimensions\n X_recovered = np.reshape(X_recovered, (img_size[0], img_size[1], 3))\n\n # Display the original image\n plt.close()\n fig, (ax1, ax2) = plt.subplots(1, 2)\n ax1.imshow(A)\n ax1.set_title('Original')\n\n # Display compressed image side by side\n ax2.imshow(X_recovered)\n ax2.set_title('Compressed, with {:d} colors.'.format(K))\n plt.show()","def get_cluster_accuracy(self, curs, p_gene_table, mcl_id_list, p_value_cut_off=0.01):\n\t\taccuracy2cluster = []\n\t\tfor mcl_id in mcl_id_list:\n\t\t\tcurs.execute(\"select is_correct_lca from %s where mcl_id=%s and p_value_cut_off<=%s\"%(p_gene_table,\\\n\t\t\t\tmcl_id, p_value_cut_off))\n\t\t\trows = curs.fetchall()\n\t\t\tif rows:\n\t\t\t\tis_correct_lca_array = array(rows)\n\t\t\t\tcorrect_array = greater(is_correct_lca_array[:,0],0)\n\t\t\t\tknown_array = greater_equal(is_correct_lca_array[:,0],0)\n\t\t\t\taccuracy = float(sum(correct_array))/float(sum(known_array))\n\t\t\t\taccuracy2cluster.append([accuracy, sum(correct_array), sum(known_array), len(correct_array), mcl_id]) \n\t\treturn accuracy2cluster","def __move_centroids(self, data):\n \n for i in range(len(self.centroids)):\n members_cluster = data[self.clusters == i]\n self.centroids[i] = np.sum(members_cluster, axis=0) / (len(members_cluster) + self.epsilon)","def calculate_euclidean_distance(self, matrix, input, output_neuron):\n result = 0\n\n # Loop over all input data.\n diff = input - matrix[output_neuron]\n return np.sqrt(sum(diff*diff))","def evaluate(self, clustering):\n # Pca for each one of the clusters\n pca_mean_val = 0.;\n MAX_ELEMENTS = 1000\n for c in clustering.clusters:\n # Pick the coordinates (ensuring that we are copying them)\n element_indexes = c.all_elements\n ###################\n # Performance hack\n ###################\n # As it can be very slow for big clusters (i.e. > 3k elements) we'll compress this clusters \n # before calculating PCA. It should increase variance but will allow calculations.\n # It should use the kmedoids compressor\n if len(c.all_elements) > MAX_ELEMENTS:\n element_indexes = c.get_random_sample(MAX_ELEMENTS)\n print \"[PCA] Random sampling too big cluster to improve performance (%d elements -> %d elements).\"%(len(c.all_elements),MAX_ELEMENTS)\n ###################\n \n fitting_coordinates_of_this_cluster = self.fitting_coordinates[element_indexes]\n \n calculator = RMSDCalculator(calculatorType = \"QTRFIT_SERIAL_CALCULATOR\",\n fittingCoordsets = fitting_coordinates_of_this_cluster)\n \n if self.calculation_coordinates is not None:\n calculation_coordinates_of_this_cluster = self.calculation_coordinates[element_indexes]\n calculator = RMSDCalculator(calculatorType = \"QTRFIT_SERIAL_CALCULATOR\",\n fittingCoordsets = fitting_coordinates_of_this_cluster,\n calculationCoordsets = calculation_coordinates_of_this_cluster)\n \n # Make an iterative superposition (to get the minimum RMSD of all with respect to a mean conformation)\n calculator.iterativeSuperposition()\n\n # Calculate the covariance matrix\n if self.calculation_coordinates is None:\n covariance_matrix = PCAMetric.create_covariance_matrix(fitting_coordinates_of_this_cluster)\n else:\n covariance_matrix = PCAMetric.create_covariance_matrix(calculation_coordinates_of_this_cluster)\n \n # And then the eigenvalue we are interested in\n pca_mean_val += PCAMetric.calculate_biggest_eigenvalue(covariance_matrix)\n print \"PCA finished\"\n return pca_mean_val /clustering.total_number_of_elements","def rms(trained_data, dist):\n sum = 0\n for i in trained_data:\n point = i[:-2]\n centroid = i[-1]\n distance = (calculate_distance(point,centroid, dist)**2)\n sum +=distance\n return sum","def calc_distances_from_central(cluster, embedding):\n\n return calc_distances_in_embedding(cluster, embedding)","def Dist_clust(data):\n mask = np.loadtxt('/net/tarea/scratch/Rafael/phd/apogee/python/comb_SkyTel_mask.dat')\n masked = np.where(mask == 1)[0]\n spectra_list = data['fullset']\n clusters = data['clusters']\n clusters = clusters.transpose()\n distance = np.zeros((len(spectra_list), 2))\n min_dist_cl = np.zeros((data['nc'], 2))\n for j_cluster in range(data['nc']):\n dist_cluster= np.zeros((data['nc']))\n for i_cluster in range(data['nc']):\n dist_cluster[i_cluster] = np.nansum((clusters[j_cluster][masked] - clusters[i_cluster][masked])**2)**0.5\n min_dist_cl[j_cluster,0] = np.argmin(dist_cluster)\n dist_cluster[np.argmin(dist_cluster)] = dist_cluster[np.argmax(dist_cluster)]\n if (len(np.where(dist_cluster != 0)[0]) > 0):\n min_dist_cl[j_cluster,1] = np.argmin(dist_cluster[(dist_cluster != 0)])\n for i_spec, name in enumerate(spectra_list):\n vec_temp = np.load(name)\n for i_cluster, j_cluster in enumerate(min_dist_cl[data['assign'][i_spec]]):\n distance[i_spec,i_cluster] = np.nansum((clusters[j_cluster][masked] - vec_temp['norm'][masked])**2)**0.5\n vec_temp.close()\n return distance, min_dist_cl","def k_means(x_input, n_cluster=3, n_iter=100, n_tries=10):\n results = []\n for _ in range(n_tries):\n error_value = 0\n rand.seed(None)\n centers = sorted([rand.uniform(0.0, 100.0) for i in range(n_cluster)])\n min_dist_idx = [0] * len(x_input)\n i = 0\n while i < n_iter:\n failed = False\n dist_mat = l2_pairwise_distance(x_input, centers)\n error_value = calculate_error(dist_mat)\n min_dist_idx = [dist.index(min(dist)) for dist in dist_mat]\n centers = [0] * n_cluster\n count = [0] * n_cluster\n for j in range(len(x_input)):\n centers[min_dist_idx[j]] += x_input[j]\n count[min_dist_idx[j]] += 1\n\n for j in range(n_cluster):\n if count[j] == 0:\n centers = sorted(\n [rand.uniform(0.0, 100.0) for i in range(n_cluster)])\n failed = True\n break\n\n if failed:\n i = 0\n continue\n\n for j in range(n_cluster):\n centers[j] = centers[j] / count[j]\n i += 1\n\n results.append((centers, min_dist_idx, error_value))\n\n return min(results, key=lambda x: x[2])","def get_distances(centroid, points):\r\n return np.linalg.norm(points - centroid, axis=1)","def compute(self): \r\n hist = self.confusion_matrix\r\n iu = np.diag(hist) / (hist.sum(axis=1) + hist.sum(axis=0) - np.diag(hist))\r\n mean_iu = np.nanmean(iu)\r\n return mean_iu","def k_mean_cluster(num_anchors, boxes, convergence_threshold=1e-9):\n # Randomly pick 5 boxes as centroids\n centroids = np.array(random.sample(boxes, k=num_anchors))\n # Clustering until reaching loss_convergence threshold\n centroids, prev_errors = k_mean(boxes, centroids)\n while True:\n centroids, errors = k_mean(boxes, centroids)\n if abs(errors - prev_errors) <= convergence_threshold:\n break\n else:\n prev_errors = errors\n\n avg_iou = np.mean(np.max(compute_iou(boxes, centroids), axis=-1))\n return centroids, avg_iou","def updateCentroids(self, points, closest, centroids):\n return numpy.array([points[closest==k].mean(axis=0) for k in range(centroids.shape[0])])","def computeStats(self, absList, statOut, errorOut):\n \n nMentions = 0\n pSum = 0\n rSum = 0\n for abstract in absList:\n # build hash of annotated clusters/chains keyed by ID\n errorOut.write('\\n---- '+abstract.id+' ----\\n')\n trueChainLengths = {}\n entityList = abstract.annotatedEntities.getList(self.entityTypes[0])\n errorOut.write('True chains:\\n')\n for entityTemplate in entityList:\n if len(entityTemplate.getAnnotatedId()) > 0:\n trueChain = entityTemplate.getMentionChain()\n trueChainLengths[entityTemplate.getAnnotatedId(checkEntireCluster=False)] = len(trueChain)\n for m in trueChain:\n# errorOut.write(m.name+':'+m.getAnnotatedId(checkEntireCluster=False) +'\\n')\n errorOut.write('%s %s:%s, matchedMention=%s \\n'%(m.name, m.mention, m.getAnnotatedId(checkEntireCluster=False), m.mention.matchedMention))\n\n errorOut.write('----\\n')\n else:\n print abstract.id, entityTemplate.name, 'is missing an ID'\n \n # compute Recall and precision for each detected chain/cluster\n entityList = abstract.entities.getList(self.entityTypes[0])\n errorOut.write('\\nHypothesis chains:\\n')\n for entityTemplate in entityList:\n detectedChain = entityTemplate.getMentionChain()\n \n rootMention = entityTemplate.rootMention()\n errorOut.write('[Canonical name: '+rootMention.getCanonicalName()+']\\n')\n \n for m in detectedChain:\n errorOut.write('%s %s:%s, matchedMention=%s \\n'%(m.name, m.mention, m.getAnnotatedId(checkEntireCluster=False), m.mention.matchedMention))\n# errorOut.write(m.name+':'+m.getAnnotatedId(checkEntireCluster=False) +'\\n')\n errorOut.write('----\\n')\n\n nMentionsInChain = len(detectedChain)\n for mTemplate in detectedChain:\n nMentions += 1\n if len(mTemplate.getAnnotatedId(checkEntireCluster=False)) == 0:\n # mention is a false positive, it does not belong to any chain\n pSum += 1.0/nMentionsInChain\n rSum += 1\n else:\n if mTemplate.getAnnotatedId(checkEntireCluster=False) not in trueChainLengths:\n print abstract.id, 'template with id =',mTemplate.getAnnotatedId(checkEntireCluster=False), 'not in a true chain'\n break\n nMentionsInTrueChain = trueChainLengths[mTemplate.getAnnotatedId(checkEntireCluster=False)]\n nCorrectInDetectedChain = 0\n annotatedMatches = set([])\n # count the number of mentions in the detected chain that\n # should be in the same chain as this mention\n for m in detectedChain:\n if mTemplate.getAnnotatedId(checkEntireCluster=False) == m.getAnnotatedId(checkEntireCluster=False) \\\n and m.mention.matchedMention not in annotatedMatches:\n nCorrectInDetectedChain += 1\n annotatedMatches.add(m.mention.matchedMention)\n# else:\n# print abstract.id, 'Two mentions do not belong in same chain',\n# print mTemplate, m.getAnnotatedId()\n \n if nCorrectInDetectedChain > nMentionsInTrueChain:\n print abstract.id, 'id=',mTemplate.getAnnotatedId(checkEntireCluster=False), \n print 'detected chain=', nCorrectInDetectedChain,\n print 'true chain=', nMentionsInTrueChain\n nCorrectInDetectedChain = nMentionsInTrueChain\n \n# if nCorrectInDetectedChain != nMentionsInChain:\n# print abstract.id, 'id=',mTemplate.getAnnotatedId(), \n# print 'detected chain=', nCorrectInDetectedChain,\n# print 'true chain=', nMentionsInTrueChain\n \n pSum += float(nCorrectInDetectedChain) / nMentionsInChain\n rSum += float(nCorrectInDetectedChain) / nMentionsInTrueChain\n \n if nMentions == 0:\n print 'No mentions???'\n return \n \n precision = pSum/nMentions\n recall = rSum/nMentions \n fscore = 2*(recall*precision)/(recall + precision)\n \n sys.stdout.write('Recall\\tPrecision\\tF-score\\n')\n sys.stdout.write('%.3f\\t ' % recall + '%.3f\\t ' % precision + '%.3f' % fscore+'\\n')\n# statOut.write(self.entityTypesString+'\\n')\n# statOut.write('Recall\\tPrecision\\tF-score\\n')\n# statOut.write('%.3f\\t ' % recall + '%.3f\\t ' % precision + '%.3f' % fscore+'\\n')\n statOut.addStats('MC - '+self.entityTypesString, [['R', recall], ['P', precision], ['F',fscore]])","def euclidean_sqr(self, instance, centroid):\n return np.linalg.norm(instance-centroid)**2","def k_means(data, k = 2, centroids = None, max_iters = 100) :\r\n if centroids == None :\r\n centroids = get_random_centroids(data, k)\r\n \r\n elif len(centroids) != k :\r\n AssertionError(\"Número de centroides no equivale a k\")\r\n \r\n for i in range(max_iters) :\r\n old_centroids = centroids\r\n \r\n assigned_centroids = assign_centroids(data, centroids)\r\n \r\n # Sum the data by cluster\r\n centroids = [[0]*data.shape[1]] * k\r\n values_in_centroid = [0] * k\r\n\r\n for i in range(k) :\r\n assigned_centroids_aux = np.column_stack([assigned_centroids]*data.shape[1])==i\r\n centroids[i] = np.sum(np.multiply(data, assigned_centroids_aux), axis = 0)\r\n values_in_centroid[i] = np.sum(assigned_centroids == i)\r\n\r\n # Mean\r\n for i in range(k) :\r\n if values_in_centroid[i] > 0 :\r\n centroids[i] = centroids[i]/values_in_centroid[i]\r\n\r\n centroids = np.stack(centroids, axis=0)\r\n\r\n error = sum([np.linalg.norm(centroids[i] - old_centroids[i]) for i in range(k)])\r\n if(error < 1e-5) : break\r\n \r\n \r\n return centroids","def run(self, max_clusters):\n sample_dist_matrix = self.matrix_dist()\n self.link.print_link()\n first_clus = self.clusters[0] # initialize first cluster to merge into\n second_clus = self.clusters[0] # initialize second cluster to merge\n max_samples_dist = max(sample_dist_matrix.values())\n # initialize minimun distance between two samples\n min_dist = max_samples_dist\n while len(self.clusters) > max_clusters: # clustering loop\n for clus in self.clusters: # iterate over every cluster\n for other_clus in self.clusters: # iterate over other clusters\n if clus.c_id > other_clus.c_id: # avoid duplicates and make sure to pass correct key to dictionary\n # compute distance between two clusters according to current link\n clus_dist = self.link.compute(clus, other_clus, sample_dist_matrix)\n if clus_dist < min_dist: # keep the minimum distance and its clusters\n min_dist = clus_dist\n first_clus = other_clus\n second_clus = clus\n self.clusters.remove(second_clus) # remove the cluster that's getting merged from clusters list\n first_clus.merge(second_clus) # merge the cluster with higher id into the other\n min_dist = max_samples_dist # restore high distance in order to start the search again\n\n sum_sil = self.compute_summery_silhouette(sample_dist_matrix)\n # print results\n for clus in self.clusters:\n clus.print_details(sum_sil[clus.c_id])\n print(f'Whole data: silhouette = {sum_sil[0]}, RI = {self.compute_rand_index()}')","def calculate_clusters(study_id):\n\n with current_app.app_context():\n cur = conn.cursor()\n\n cur.execute(\"\"\"SELECT * FROM STATS WHERE STUDY_ID=%s\"\"\", (str(study_id),))\n study = fetchoneClean(cur)\n clusters_calculating = study[4]\n clusters_changed = study[5]\n if clusters_changed:\n if clusters_calculating:\n return {'message': 'calculating'}\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CALCULATING = TRUE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n conn.commit()\n\n distance = study[7]['matrix']\n card_names = study[7]['cardNames']\n cur.execute(\"\"\"SELECT COUNT(ID) FROM PARTICIPANT WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n total_participants = fetchoneClean(cur)[0]\n\n distance_matrix = calculate_square_form(distance, total_participants)\n distArray = ssd.squareform(distance_matrix)\n\n try:\n clusters = hierarchy.linkage(distArray, method='average')\n except ValueError:\n return {'message': 'not enough data'}\n\n tree = hierarchy.to_tree(clusters, rd=False)\n # TODO Distance 0 on root\n dendro = dict(children=[], hierarchy=0, distance=100)\n add_node(tree, dendro, card_names)\n\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS = %s WHERE STUDY_ID = %s\"\"\", (json.dumps(dendro), str(study_id),))\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CALCULATING = FALSE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n cur.execute(\"\"\"UPDATE STATS SET CLUSTERS_CHANGED = FALSE WHERE STUDY_ID = %s\"\"\", (str(study_id),))\n conn.commit()\n else:\n dendro = study[6]\n\n return dendro","def __call__(self, embeddings: np.ndarray) -> List[Optional[str]]:\n assert self._centroids != {} # Centroids must be set in advance\n \n # Setup known database\n cluster_ids, cluster_embs = zip(*self._centroids.items())\n cluster_embs = np.vstack(cluster_embs)\n \n # Calculate similarity with cluster centroids\n similarity = cosine_similarity(embeddings, cluster_embs)\n \n # Fetch the best-matching clusters\n results = []\n for i, idx in enumerate(similarity.argmax(axis=1)):\n results.append(cluster_ids[idx] if similarity[i, idx] >= self._sim_thr else None)\n return results","def __find_nearest_centroids(self, data):\n \n self.clusters = np.array([]) \n for i, d in enumerate(data):\n min_dist = np.inf\n self.clusters = np.concatenate((self.clusters, np.array([-1])))\n for j, c in enumerate(self.centroids):\n dist = self.__compute_distance(d, c)\n if min_dist > dist:\n min_dist = dist\n self.clusters[i] = j","def __get_cluster_centroid_distance(self, single_training: np.ndarray, cluster_center: np.ndarray) -> (int, float):\n training_label, training_distance = None, float('inf')\n # Check the distance of this point from all the cluster point.\n # This training point belongs to a cluster, which ever cluster centroid have the lowest distance from this point\n for cluster_label, single_cluster in enumerate(cluster_center):\n # Distance from the this training point to this cluster centroid\n this_distance = self.__get_distance(single_cluster, single_training)\n if this_distance < training_distance:\n training_label = cluster_label\n training_distance = this_distance\n return training_label, training_distance","def kmeans_clustering(all_features, vocab_size, epsilon, max_iter):\n\n # Your code here. You should also change the return value.\n\n def _initiate_random_centroids(all_features, vocab_size):\n \"\"\"\n Initiate random centroids in the range of input\n\n :param all_features:\n :param vocab_size:\n :return:\n \"\"\"\n centroids = []\n # 1) Genereate points for initial centroids\n\n min_feat = np.ones(all_features[0].size)*np.inf\n max_feat = np.zeros(all_features[0].size)\n\n for a in all_features:\n for p in range(len(a)):\n if a[p] < min_feat[p]:\n min_feat[p] = a[p]\n else:\n if a[p] > max_feat[p]:\n max_feat[p] = a[p]\n\n\n for _ in range(vocab_size):\n random_vector = np.multiply(np.random.rand(1, all_features[0].size),\n max_feat-min_feat) + min_feat\n centroids.append(random_vector.flatten())\n\n return np.array(centroids)\n\n def _assign_vectors_to_nearest_centroid(all_features, centroid):\n \"\"\"\n Assign vectors to nearest centroids\n\n :param all_features:\n :param centroid:\n :return:\n \"\"\"\n #TODO: sprawdz co lepiej dziala\n new_centroid_coor = np.zeros([len(centroid), all_features[0].size])\n #new_centroid_coor = centroid\n new_centroid_counter = np.zeros(len(centroid))\n\n dist = pdist(centroid, all_features)\n #min_dist = dist.min(axis=0)\n min_dist_index = dist.argmin(axis=0)\n\n for x in range(len(min_dist_index)):\n id = min_dist_index[x]\n new_centroid_coor[id] = np.add(new_centroid_coor[id],\n all_features[x])\n new_centroid_counter[id] += 1\n\n new_centroid_coor_out = []\n for i in range(len(new_centroid_coor)):\n if new_centroid_counter[i] == 0:\n new_centroid_coor_out.append(centroid[i])\n else:\n new_centroid_coor_out.append(np.divide(new_centroid_coor[i],new_centroid_counter[i]))\n\n return np.array(new_centroid_coor_out), new_centroid_counter\n\n\n def _check_convergence_condition(old_centroids, new_centroids, epsilon):\n \"\"\"\n Check convergence confition\n\n :param old_centroids:\n :param new_centroids:\n :param epsilon: if every centroid is moved by dist < epsilon KMeans terminates\n :return:\n \"\"\"\n for i in range(len(old_centroids)):\n dist = euclidean(old_centroids[i], new_centroids[i])\n if dist > epsilon:\n return False\n\n return True\n\n def delete_small_clusters(new_centroids, centroid_counter, threshold):\n \"\"\"\n Potential extension of the algorithm -> if there is not any point in the cluster, delete this cluste\n\n :param new_centroids:\n :param centroid_counter:\n :param threshold:\n :return:\n \"\"\"\n\n out_centroids = []\n for n in range(len(new_centroids)):\n if centroid_counter[n] > threshold:\n out_centroids.append(new_centroids[n])\n out_centroids = np.array(out_centroids)\n return out_centroids\n\n #MAIN\n old_centroids = _initiate_random_centroids(all_features, vocab_size)\n\n for _ in range(max_iter):\n new_centroids, centroid_counter = _assign_vectors_to_nearest_centroid(all_features, old_centroids)\n if_convergenced = _check_convergence_condition(new_centroids, old_centroids, epsilon)\n\n if if_convergenced == True:\n # return centroids if algorithm is converged\n # return delete_small_clusters(new_centroids, centroid_counter, 0)\n return new_centroids\n old_centroids = new_centroids\n\n # return centroids if reached max_iter\n # return delete_small_clusters(new_centroids, centroid_counter, 0)\n return new_centroids"],"string":"[\n \"def calcAvgDistances(centroids, clusters, class_header=\\\"Class\\\"):\\n avg_distances = [0] * len(centroids)\\n multiprocess_count = multiprocessing.cpu_count() # Find processor count\\n for centroid_row_index, centroid_tuple in enumerate(centroids.iterrows()): # For each cluster\\n work_list = [] # initialize multiprocessing structures\\n set_list = []\\n for _, datum in clusters[centroid_row_index].iterrows(): # For each point in the medoid cluster\\n work_list.append((centroid_tuple[1], datum, class_header)) # add calculation to work list\\n\\n partition_size = math.ceil(len(work_list) / multiprocess_count) # find size of each work subeset\\n for i in range(multiprocess_count - 1): # repeat for every subset\\n sample = work_list[i * partition_size: (i + 1) * partition_size] # break work list into fair subsets\\n set_list.append(sample)\\n set_list.append((work_list[(multiprocess_count - 1) * partition_size:]))\\n pool = multiprocessing.Pool(processes=multiprocess_count) # create multiprocessing pool\\n # calculate sum of list of all distances from work list tasks\\n avg_distances[centroid_row_index] = sum(sum(pool.map(Cluster.calcDistanceList, set_list), []))\\n pool.close()\\n pool.join()\\n\\n if avg_distances[centroid_row_index] is not 0: # make sure we do not divide by 0\\n # calculate average of distance list\\n avg_distances[centroid_row_index] = avg_distances[centroid_row_index] / len(clusters[centroid_row_index])\\n return avg_distances\",\n \"def _calc_distance(self, X):\\n distances = np.zeros((X.shape[0], self.n_clusters))\\n print(distances.shape)\\n for i, centroid in enumerate(self.centroids):\\n distances[:, i] = np.linalg.norm(X - centroid, axis=1)\\n return distances\",\n \"def calculate_cost(self, medoids, clusters):\\n cost = 0.0\\n for i in range(0, len(medoids)):\\n for j in range(0, len(clusters[i])):\\n cost += distance.sqeuclidean(medoids[i], clusters[i][j])\\n return cost\\n pass\",\n \"def _compute_centroids(self):\\n\\n for i in range(0, self.k):\\n cluster = np.argwhere(self.assigned_clusters == i)\\n cluster_points = self.data[cluster].squeeze()\\n self.centroids[i] = np.mean(cluster_points, axis=0)\",\n \"def clustering_error(examples):\\n\\n cluster_examples = partition(examples)\\n cluster_averages = [\\n class_average(cluster_examples[class_id])\\n for class_id in range(0, cluster_count)\\n ]\\n\\n # accumulate the distances between each example and its cluster's average\\n # into an error value\\n error = 0\\n for example in examples:\\n error += dist(cluster_averages[example.type], example)\\n\\n return (error, cluster_averages)\",\n \"def get_distance(self, samples, clusters):\\n n_samples = samples.shape[0]\\n n_features = samples.shape[1]\\n n_centroids = clusters.shape[0]\\n dist = np.zeros(shape=(n_samples, n_centroids))\\n\\n # computing squared euclidian distance for each sample-cluster pair\\n for i in range(n_samples):\\n for j in range(n_centroids):\\n for k in range(n_features):\\n dist[i, j] += (samples[i, k] - clusters[j, k])**2\\n # dist[i, j] = D[i, j]**(1/2)\\n\\n return np.sqrt(dist)\",\n \"def test_sum_of_distances(self):\\n N = 10\\n centers = [[0, 0], [1, 0], [0.5, np.sqrt(0.75)]]\\n cluster_std = [0.3, 0.3, 0.3]\\n n_samples = int(0.75 * N)\\n data, labels_true = \\\\\\n sklearn.datasets.make_blobs(n_samples=n_samples,\\n centers=centers,\\n cluster_std=cluster_std)\\n centers = [[0.5, np.sqrt(0.75)]]\\n cluster_std = [0.3]\\n extra, labels_true = \\\\\\n sklearn.datasets.make_blobs(n_samples=int(0.25 * N),\\n centers=centers,\\n cluster_std=cluster_std)\\n X = np.concatenate((data, extra), axis=0)\\n N = X.shape[0]\\n\\n # Pick some random floats for the counts/weights:\\n counts = np.random.random_sample((N,)) * 10\\n\\n # SciPy:\\n Y = pdist(X, metric=cdist)\\n weights = [counts[i] * counts[j]\\n for i in xrange(N - 1) for j in xrange(i + 1, N)]\\n scipy_sum = np.sum(weights * Y)\\n N = counts.sum()\\n N_unique_pairs = N * (N - 1.0) / 2.0\\n scipy_mean = scipy_sum / N_unique_pairs\\n\\n # C & Cython:\\n c_mean = c_mean_dist(X, counts)\\n\\n # There is minor rounding error, but check for equality:\\n self.assertTrue(np.isclose(c_mean, scipy_mean))\\n # Even though above is comparing the means, it is actually checking the\\n # sums are correct as the means are calculated in the same way, i.e.,\\n # by dividing by the same number, N_unique_pairs.\",\n \"def cluster(self, verbose=0, sum_ess=False):\\n ## if sum_ess and self.linkage.__name__ != \\\"ward_link\\\":\\n ## raise ValueError(\\n ## \\\"Summing for method other than Ward makes no sense...\\\")\\n clusters = copy.copy(self._dist_matrix)\\n #clusters = self._dist_matrix\\n summed_ess = 0.0\\n\\n while len(clusters) > max(self._num_clusters, 1):\\n if verbose >= 1:\\n print('k=%s' % len(clusters))\\n if verbose == 2:\\n print(clusters)\\n\\n best, i, j = self.smallest_distance(clusters)\\n # In Ward (1963) ess is summed at each iteration\\n # in R's hclust and Python's hcluster and some text books it is not.\\n # Here it is optional...\\n if sum_ess:\\n summed_ess += best\\n else:\\n summed_ess = best\\n clusters = self.update_distmatrix(i, j, clusters)\\n self._dendrogram.merge(i,j)\\n self._dendrogram[i].distance = summed_ess\\n indices = numpy.arange(clusters.shape[0])\\n indices = indices[indices!=j]\\n clusters = clusters.take(indices, axis=0).take(indices, axis=1)\",\n \"def _calculate_distances(self):\\n all_dists = []\\n for ref in range(len(self.atoms)):\\n if self.atoms[ref].symbol in self.exclude:\\n continue\\n indices = list(range(ref+1, len(self.atoms)))\\n indices = self._filter_excluded(indices)\\n if len(indices) == 0:\\n continue\\n dists = self.atoms.get_distances(ref, indices, mic=True)\\n all_dists += list(dists)\\n \\n # Normalize by the mean distance\\n return np.array(all_dists)/np.mean(all_dists)\",\n \"def cluster_spatial_positioning(data):\\n \\n n_clusters = len(set(data['clusters'])-{-1}) # since -1 element denotes noice\\n if n_clusters <2:\\n #Setting cluster angluar features to default\\n cdist=[Cluster_Relative_Distances()]\\n cdist = pd.DataFrame([o.__dict__ for o in cdist])\\n\\n elif n_clusters >=2:\\n # Here we implement two approaches for measuring distances between clustes:\\n # (1) border-boder distances and (2) centroid-centroid distances. \\n # We compute dispersion measures for the distances obtained. \\n \\n d = dict(tuple(data.groupby('clusters')))\\n d.pop(-1, None)\\n\\n min_dist_between_clusters=np.row_stack([[np.amin(ss.distance_matrix(np.column_stack([d[i]['X'].array,d[i]['Y'].array]), \\n np.column_stack([d[j]['X'].array,d[j]['Y'].array]))) for j in d.keys()] for i in d.keys()])\\n min_dist_between_clusters=np.delete(list(set(np.frombuffer(min_dist_between_clusters))) ,0)\\n\\n cen_dist_between_clusters=ss.distance_matrix(np.row_stack([(np.mean(d[i]['X'].array),np.mean(d[i]['Y'].array)) for i in d.keys()]),\\n np.row_stack([(np.mean(d[i]['X'].array),np.mean(d[i]['Y'].array)) for i in d.keys()]))\\n cen_dist_between_clusters=np.delete(list(set(np.frombuffer(cen_dist_between_clusters))) ,0)\\n\\n (avg_bor_bor_dist_cluster,min_bor_bor_dist_cluster,max_bor_bor_dist_cluster,\\n std_bor_bor_dist_cluster,CV_bor_bor_dist_cluster,CD_bor_bor_dist_cluster,\\n IQR_bor_bor_dist_cluster,Quartile_CD_bor_bor_dist_cluster)= distribution_statistics(min_dist_between_clusters)\\n\\n (avg_cen_cen_dist_cluster,min_cen_cen_dist_cluster,max_cen_cen_dist_cluster,\\n std_cen_cen_dist_cluster,CV_cen_cen_dist_cluster,CD_cen_cen_dist_cluster,\\n IQR_cen_cen_dist_cluster,Quartile_CD_cen_cen_dist_cluster)= distribution_statistics(cen_dist_between_clusters)\\n\\n cdist = [Cluster_Relative_Distances([avg_bor_bor_dist_cluster,min_bor_bor_dist_cluster,max_bor_bor_dist_cluster,\\n std_bor_bor_dist_cluster,CV_bor_bor_dist_cluster,CD_bor_bor_dist_cluster,\\n IQR_bor_bor_dist_cluster,Quartile_CD_bor_bor_dist_cluster,\\n avg_cen_cen_dist_cluster,min_cen_cen_dist_cluster,max_cen_cen_dist_cluster,\\n std_cen_cen_dist_cluster,CV_cen_cen_dist_cluster,CD_cen_cen_dist_cluster,\\n IQR_cen_cen_dist_cluster,Quartile_CD_cen_cen_dist_cluster])]\\n \\n cdist = pd.DataFrame([o.__dict__ for o in cdist])\\n\\n \\n return cdist\",\n \"def __calculate_estimation(self):\\r\\n estimation = 0.0\\r\\n for index_cluster in range(0, len(self.__clusters)):\\r\\n cluster = self.__clusters[index_cluster]\\r\\n index_medoid = self.__current[index_cluster]\\r\\n for index_point in cluster:\\r\\n estimation += euclidean_distance_square(self.__pointer_data[index_point], self.__pointer_data[index_medoid])\\r\\n\\r\\n return estimation\",\n \"def train_KMean(data: np.array, labels: np.array, n_clusters: int)->None:\\n n_examples = np.size(data, 0)\\n n_features = np.size(data, 1)\\n\\n # Scale the data so that Euclidian distance makes sense\\n means = np.mean(data, axis = 0)\\n stddevs = np.std(data, axis = 0, ddof = 1)\\n\\n #print(means)\\n #print(stddevs)\\n\\n data_scaled = np.zeros((n_examples, n_features))\\n\\n for i in range(n_features):\\n data_scaled[:, i] = (data[:,i] - means[i]) / stddevs[i]\\n\\n study_correlation(data_scaled)\\n\\n # Initialize the centroids\\n idx = np.random.randint(n_examples, size = n_clusters)\\n centroids = data_scaled[idx, :]\\n\\n counter = 0\\n\\n while True:\\n\\n distances = np.array([[np.sqrt(np.sum(np.square(example-centroid))) for centroid in centroids] for example in data_scaled])\\n centroid_idx = np.argmin(distances, axis = 1)\\n old_centroids = centroids\\n centroids = update_centroids(data_scaled, centroid_idx, n_examples)\\n #displacement = get_displacement(old_centroids, centroids)\\n displacement = np.linalg.norm(np.array([old - new for old, new in zip(old_centroids, centroids)]))\\n\\n #assert np.linalg.norm(np.array([old - new for old, new in zip([1, 2, 3, 4], [5, 6, 7, 8])])) == 8\\n\\n if counter == 0:\\n# print(\\\"Initial displacement = {}\\\".format(displacement))\\n initial_displacement = displacement\\n\\n counter += 1\\n\\n if displacement < (initial_displacement / 10000): break\\n\\n #print(\\\"Total number of loops before ending : {}\\\".format(counter))\\n converted_predictions = convert_predictions(centroid_idx)\\n accuracy = np.mean([p == l for p, l in zip(converted_predictions, labels)])\\n print(\\\"Accuracy = {}\\\".format(accuracy))\\n\\n pass\",\n \"def calcCentroid(self):\\n size = len(self.vectors)\\n # zip all features together\\n zipped = zip(*self.vectors)\\n # Calculate the mean for each feature/column\\n centroid = [math.fsum(column)/size for column in zipped]\\n \\n return centroid\",\n \"def compute_distance(X, K_clusters):\\n dis = np.linalg.norm((X-K_clusters),2,axis=1)**2\\n return dis\",\n \"def cluster_cal(self):\\n self.Cluster = []\\n for i in range(self.nodenum):\\n neighborhood_node = self.neighbor_node(i)\\n Node_num = len(neighborhood_node)\\n Count = self.neighbor_edge(neighborhood_node)\\n if(Node_num == 0 or Node_num == 1):\\n self.Cluster.append(0.5)\\n else:\\n self.Cluster.append(Count/(Node_num*(Node_num - 1)))\\n \\n self.cluster_coeff = np.average(self.Cluster)\",\n \"def computeLoss(self):\\n return sum(np.arccosh(-minkowskiArrayDot(self.examples, self.centroid)) ** 2)[0] / np.shape(self.examples)[0]\",\n \"def __compute_distance(self, x, centroid):\\n \\n diff = x - centroid\\n return np.sqrt(np.dot(diff.T, diff))\",\n \"def __calculate_estimation(self):\\n estimation = 0.0\\n for index_cluster in range(0, len(self.__clusters)):\\n cluster = self.__clusters[index_cluster]\\n index_medoid = self.__current[index_cluster]\\n for index_point in cluster:\\n estimation += euclidean_distance_square(\\n self.__pointer_data[index_point],\\n self.__pointer_data[index_medoid],\\n )\\n\\n return estimation\",\n \"def clustering(df, mode):\\n # split into list of dfs containing only one reference node\\n df_list = [df.loc[i : i + 8 - 1, :] for i in range(0, len(df), 8)]\\n\\n df_coefficient = pd.DataFrame()\\n\\n # loop over every single node\\n for df_single in df_list:\\n df_single = df_single.reset_index()\\n total_value = 0\\n\\n # loop over the weights of all connected nodes\\n for j in range(len(df_single) - 1):\\n if mode == \\\"geometric\\\":\\n # geometric\\n total_value = total_value + math.sqrt(df_single.chi_sq[j] * df_single.chi_sq[j + 1])\\n if mode == \\\"arithmetic\\\": \\n # arithmetic\\n total_value = total_value + ((df_single.chi_sq[j] * df_single.chi_sq[j + 1]) / 2)\\n if mode == \\\"argmax\\\": \\n # max\\n total_value = total_value + max(df_single.chi_sq[j], df_single.chi_sq[j + 1])\\n if mode == \\\"argmin\\\":\\n # min\\n total_value = total_value + min(df_single.chi_sq[j], df_single.chi_sq[j + 1])\\n\\n for i in range(len(df_single) - 1):\\n if mode == \\\"geometric\\\":\\n # geometric\\n triplet_value = math.sqrt(df_single.chi_sq[i] * df_single.chi_sq[i + 1])\\n if mode == \\\"arithmetic\\\":\\n # arithmetic\\n triplet_value = (df_single.chi_sq[i] * df_single.chi_sq[i + 1]) / 2\\n if mode == \\\"argmax\\\":\\n # max\\n triplet_value = max(df_single.chi_sq[i], df_single.chi_sq[i + 1])\\n if mode == \\\"argmin\\\": \\n # min\\n triplet_value = min(df_single.chi_sq[i], df_single.chi_sq[i + 1])\\n\\n cluster_coefficient = triplet_value / total_value\\n buffer = [\\n [\\n df_single.reference[i],\\n df_single.comparison[i],\\n df_single.comparison[i + 1],\\n triplet_value,\\n cluster_coefficient,\\n ]\\n ]\\n df_coefficient = df_coefficient.append(buffer)\\n\\n df_coefficient = df_coefficient.reset_index()\\n\\n print(\\\"\\\\n\\\\n threshold 0.5*c_omega\\\")\\n check_list = []\\n # print out triangles that have a cluster coefficient bigger, than X\\n for i in range(len(df_coefficient)):\\n if df_coefficient[4][i] >= ((0.5) * df_coefficient[4].max()):\\n print(list(df_coefficient.loc[i][1:4]))\\n check_list.append(list(df_coefficient.loc[i][1:4]))\\n else:\\n continue\\n\\n print(\\\"\\\\n\\\\n threshold 0.75*c_omega\\\")\\n check_list = []\\n for i in range(len(df_coefficient)):\\n if df_coefficient[4][i] >= ((0.75) * df_coefficient[4].max()):\\n print(list(df_coefficient.loc[i][1:4]))\\n check_list.append(list(df_coefficient.loc[i][1:4]))\\n else:\\n continue\\n\\n print(\\\"\\\\n\\\\n threshold 0.8*c_omega\\\")\\n check_list = []\\n for i in range(len(df_coefficient)):\\n if df_coefficient[4][i] >= ((0.9) * df_coefficient[4].max()):\\n print(list(df_coefficient.loc[i][1:4]))\\n check_list.append(list(df_coefficient.loc[i][1:4]))\\n else:\\n continue\\n\\n\\n print(\\\"\\\\n\\\\n threshold 0.9*c_omega\\\")\\n check_list = []\\n for i in range(len(df_coefficient)):\\n if df_coefficient[4][i] >= ((0.9) * df_coefficient[4].max()):\\n print(list(df_coefficient.loc[i][1:4]))\\n check_list.append(list(df_coefficient.loc[i][1:4]))\\n else:\\n continue\\n\\n return\",\n \"def compute_distortion(cluster_list, data_table):\\r\\n distortion = 0\\r\\n \\r\\n for cluster in cluster_list:\\r\\n distortion += cluster.cluster_error(data_table)\\r\\n\\r\\n return distortion\",\n \"def _recalculate_centroids(self):\\n\\n self._prev_centroids = dict(self.centroids)\\n for cluster in self.clusters:\\n self.centroids[cluster] = np.average(self.clusters[cluster], axis=0)\",\n \"def calculate_all_distances_to_center(self):\\n all_distances = pd.DataFrame()\\n for label in np.unique(self.embedding_df['cluster']): \\n distance_df = self.calculate_distances_for_cluster(label)\\n all_distances = pd.concat([all_distances, distance_df])\\n \\n self.embedding_df = self.embedding_df.merge(all_distances, left_index=True, right_index=True)\",\n \"def compute_distortion(cluster_list, data_table):\\n\\tdistortion = 0\\n\\tfor cluster in cluster_list:\\n\\t\\tdistortion += cluster.cluster_error(data_table)\\n\\treturn distortion\",\n \"def cluster_index_2(X):\\n \\n global_mean = X.mean(axis=0)\\n\\n sum_squared_distances = (((X - global_mean)**2).sum(axis = 1)).sum()\\n #Sum of squared distances of each sample from the global mean\\n \\n centroids, labels, inertia = k_means(X, 2)\\n\\n ci = inertia / sum_squared_distances\\n\\n return ci , labels\",\n \"def _assign_clusters(self):\\n\\n dist = np.zeros((self.k, ))\\n distortion = 0\\n\\n for index in range(0, self.data.shape[0]):\\n for i in range(0, self.k):\\n dist[i] = np.linalg.norm(self.data[index] - self.centroids[i])\\n\\n self.assigned_clusters[index] = np.argmin(dist)\\n distortion += np.min(dist)\\n\\n return distortion\",\n \"def error(self, documents):\\n ###TODO\\n sum_1 = 0.0\\n for c_id,clust in self.fin_clust.items():\\n n = self.sqnorm(self.means[c_id]) \\n sum_1 = sum_1 + sum([self.distance(self.docs[dc],self.means[c_id],n) for dc in clust]) \\n return round(sum_1,2)\",\n \"def wca_mean(X, k, df):\\n\\t\\n\\n\\t# Intializing the clusters\\t\\n\\tC = dict()\\n\\tfor cluster in range(k):\\n\\t C[cluster] = pd.DataFrame()\\n\\n\\t# Calculating the mean vector\\n\\tmean_vector = X.mean()\\n\\n\\t# Choosing the seed points based on the minimum distance from the mean vector\\n\\tX['dist_mean'] = X.apply(lambda x: np.linalg.norm(np.asarray(x)- np.asarray(mean_vector)), axis=1)\\n\\tdist_means = X.sort_values(by='dist_mean')\\n\\t\\n\\t# Dropping the the datapoints which have already been assigned as seed\\n\\tidx_to_drop = dist_means.index[:k]\\n\\tdist_means.reset_index(drop=True,inplace=True)\\n\\tX.drop('dist_mean',axis=1,inplace=True)\\n\\tX.drop(idx_to_drop, inplace=True)\\n\\n\\t# Assigning seed points to the clusters\\n\\tmu = list()\\n\\tfor cluster in range(k):\\n\\t C[cluster] = C[cluster].append(dist_means.iloc[cluster].drop('dist_mean'))\\n\\t mu.append(C[cluster].mean())\\n\\t\\n\\t# Running the algorithm\\t\\n\\t\\n\\t# Initializing the p-value list which would be used for plotting\\n\\tpval = dict()\\n\\n\\tfor cluster in range(k):\\n\\t pval[cluster] = dict()\\n\\t for i in C[0].columns:\\n\\t pval[cluster][i] = list()\\n\\n\\t# Algorithm\\n\\tfor i in tqdm(range(int(len(X)/k)), desc='Iterations: '):\\n\\t for cluster in range(k):\\n\\n\\t # Calculating the distances from the mean vector of eaimportch cluster (in Descending order)\\n\\t X['dist_mean'] = X.apply(lambda x: np.linalg.norm(np.asarray(x)- np.asarray(mu[cluster])), axis=1)\\n\\t dist_means = X.sort_values(by='dist_mean', ascending=False)\\n\\t idx_to_drop = dist_means.index[0]\\n\\t dist_means.reset_index(drop=True,inplace=True)\\n\\t X.drop('dist_mean',axis=1,inplace=True)\\n\\n\\t # Assigning the top value to the cluster\\n\\t C[cluster] = C[cluster].append(dist_means.iloc[0].drop('dist_mean'))\\n\\t C[cluster] = C[cluster].reset_index(drop=True)\\n\\t \\n\\t # Updating means of each cluster\\n\\t mu[cluster] = C[cluster].mean()\\n\\n\\t # Remove datapoint from X?\\n\\t X.drop(idx_to_drop,inplace=True)\\n\\t \\n\\t for i in C[0].columns:\\n\\t pval[cluster][i].append(sc.ks_2samp(C[cluster][i],df.drop('target',axis=1)[i])[1])\\n\\n\\treturn(C,pval)\",\n \"def find_avg(centroids, short_cut=False, sim_scores=None):\\n \\n total_sim = 0.0\\n total_comparisons = 0\\n \\n if short_cut:\\n total_comparisons = len(sim_scores)\\n \\n for score in sim_scores:\\n total_sim += score\\n \\n return (total_sim / total_comparisons)\\n\\n length = len(centroids)\\n\\n for i in xrange(0, length):\\n for j in xrange(i + 1, length):\\n total_sim += similarity(centroids[i], centroids[j])\\n total_comparisons += 1\\n\\n return (total_sim / total_comparisons)\",\n \"def avg_dists(self):\\n \\n d = self.descriptors\\n # make an empty array to fill b/c it is a touch faster\\n averages = np.empty([1, self.d_length])\\n for i, u in enumerate(d):\\n s = 0\\n for j, v in enumerate(d):\\n if i != j:\\n s += self.jaccard(u, v)\\n averages[0, i] = (s / (self.d_length-1))\\n return averages[0]\",\n \"def compute_means(self):\\n ###TODO\\n vector_means = []\\n for doc in self.fin_clust.values():\\n vec = defaultdict(float)\\n for d_id in doc:\\n doc_keys = self.docs[d_id].keys()\\n for key in self.docs[d_id]:\\n vec[key] = vec[key] + self.docs[d_id][key]\\n tot = len(doc)\\n x = defaultdict(float)\\n for k,v in vec.items():\\n x[k] = float(v)/tot\\n vec = Counter(x)\\n vector_means.append(vec)\\n return vector_means\",\n \"def compute_distances(self, X):\\n num_test = X.shape[0]\\n num_train = self.X_train.shape[0]\\n dists = np.zeros((num_test, num_train))\\n \\n sum_test_square = np.sum(np.square(X), axis=1).reshape(-1, 1)\\n sum_train_square = np.sum(np.square(self.X_train), axis=1).reshape(-1, 1)\\n product_test_train = X @ self.X_train.T\\n \\n sum_test_square = np.repeat(sum_test_square, num_train, axis=1)\\n sum_train_square = np.repeat(sum_train_square, num_test, axis=1).T\\n \\n dists_square = sum_test_square - 2 * product_test_train + sum_train_square\\n \\n dists = np.sqrt(dists_square)\\n \\n return dists\",\n \"def fit(self, train_data, metric=None):\\n \\n if metric==None:\\n self.metric=self.euclidean_sqr\\n\\n if self.centroids_.shape[0]==0:\\n centroids=self.random_init(train_data)\\n else:\\n centroids=self.centroids_\\n\\n # remove mean from data\\n #train_data_mean=np.mean(train_data,axis=0)\\n #train_data=train_data-train_data_mean\\n # row norms??\\n #train_data_sqr_norms = np.einsum('ij,ij->i', train_data, train_data)\\n\\n\\n old_centroids=np.zeros(centroids.shape)\\n\\n # iterate until no change in cluster centers or defined number of iterations is reached\\n n_iterations=self.n_iterations_\\n while n_iterations>0 and np.array_equal(centroids,old_centroids)==False:\\n n_iterations-=1\\n old_centroids=centroids\\n centroids=self.fit_iteration(train_data, centroids)\\n \\n self.centroids_=centroids\\n return centroids\",\n \"def get_cluster_average(cls, indices, dist_mat):\\n distances = cls.get_all_distances(indices, dist_mat)\\n return np.mean(distances)\",\n \"def centroids(self):\\n return self.mdm_.covmeans_\",\n \"def euclidean_dist(self):\\r\\n\\r\\n real_cat, synth_cat = self.to_cat(self.origdst, self.synthdst)\\r\\n\\r\\n real_cat_dem = self.get_demographics(real_cat)\\r\\n synth_cat_dem = self.get_demographics(synth_cat)\\r\\n\\r\\n corr_real_obj = associations(real_cat_dem, theil_u=True, bias_correction=False, plot=False)\\r\\n corr_synth_obj = associations(synth_cat_dem, theil_u=True, bias_correction=False, plot=False)\\r\\n\\r\\n corr_real = corr_real_obj['corr']\\r\\n corr_rand = corr_synth_obj['corr']\\r\\n\\r\\n eucl_matr = distance.cdist(corr_real, corr_rand, 'euclidean')\\r\\n\\r\\n eucl = LA.norm(eucl_matr)\\r\\n\\r\\n return eucl, eucl_matr\",\n \"def calculate_cost(data, centers, clusters):\\n total = 0\\n for i in range(len(centers)):\\n total = total + np.sum(data[centers[i]][clusters[i]]) \\n return total\",\n \"def calcCentroids(data_points, clusters):\\n #initiate empty list for the new centroids\\n newCentroids = []\\n\\n #For position in each cluster, calculate the average for each position\\n #The lists are zipped so each position can have an average\\n for c in clusters:\\n newCentroids.append(map(calcAverage, zip(*c)))\\n\\n #This is the check that a centroid is not empty. If a centroid is empty,\\n #delete it, the filled centroids are added to the new list\\n correctCentroid = []\\n for centroid in newCentroids:\\n #If centroid is not empty\\n if centroid:\\n correctCentroid.append(centroid)\\n\\n return len(correctCentroid), correctCentroid\",\n \"def SquareClusteringCoefficient(graph):\\n coef = np.mean(list(nx.square_clustering(graph).values()))\\n return coef\",\n \"def test_mean_of_distances(self):\\n X = np.array([[0.3, 0.4],\\n [0.1, 4.0],\\n [2.0, 1.0],\\n [0.0, 0.5]])\\n counts = np.array([3, 2, 1, 2])\\n scipy_X = []\\n for c, count in enumerate(counts):\\n for i in range(count):\\n scipy_X.append(X[c])\\n\\n # SciPy:\\n Y = pdist(scipy_X, metric=cdist)\\n scipy_N = np.sum(counts)\\n N_unique_pairs = scipy_N * (scipy_N - 1.0) / 2.0\\n scipy_mean = Y.mean()\\n self.assertTrue(Y.shape[0] == N_unique_pairs)\\n self.assertTrue(scipy_mean == (np.sum(Y) / N_unique_pairs))\\n\\n # C & Cython:\\n c_mean = c_mean_dist(X, counts)\\n self.assertTrue(np.isclose(c_mean, scipy_mean))\",\n \"def calculate_error(k_means_matrix):\\n return sum([min(dist) for dist in k_means_matrix])\",\n \"def assign_to_current_mean(img: np.ndarray, clustermask: np.ndarray) -> float:\\n\\n rows, cols = img.shape[:2]\\n distances = np.zeros((numclusters, 1))\\n overall_dist = 0\\n\\n for i in range(rows):\\n for j in range(cols):\\n distances = distance(img[i, j, :]) # returned shape: (numclusters, 1)\\n \\n k = np.argmin(distances) # closest cluster\\n clustermask.itemset((i, j), k) # update cluster mask\\n overall_dist += distances[k, 0] # sum distance\\n\\n return overall_dist\",\n \"def _evaluate_centroids(self):\\n\\n for c in self.centroids:\\n _prev_cent = self._prev_centroids[c]\\n _curr_cent = self.centroids[c]\\n\\n if self._euclidean_distance(_prev_cent, _curr_cent) > self.tol:\\n return\\n self._optimized = True\",\n \"def calculate_metric(self, distance_matrix):\\n ap_scores = []\\n for node_id in range(len(distance_matrix)):\\n sorted_nodes = np.argsort(distance_matrix[node_id]).tolist()\\n neighs = self.neighbors[node_id]\\n n_correct = 0.0\\n precisions = []\\n for i in range(1, len(sorted_nodes)):\\n if sorted_nodes[i] in neighs:\\n n_correct += 1\\n precisions.append(n_correct / i)\\n if n_correct == len(neighs):\\n break\\n\\n ap_scores.append(np.mean(precisions))\\n\\n return np.mean(ap_scores)\",\n \"def compute_clusters(self, documents):\\n ###TODO\\n for d in range(0, len(documents)):\\n maxi = 999999999\\n for cid in range(0, len(self.means)):\\n dist = self.distance(documents[d], self.means[cid], self.norms[cid])\\n if dist < maxi:\\n maxi = dist\\n clust = cid \\n self.cluster[d] = clust\",\n \"def run(self, points, K):\\n # Get size\\n D, N = points.shape\\n\\n # DxK array initialiezd with random points\\n centroids = points[:, np.random.permutation(N)[:K]]\\n\\n # Assigments 1xN array\\n labels = np.zeros(N)\\n\\n for it in np.arange(self.niter):\\n # 1. Compute distance to all cluster\\n #v1 dirty\\n distances = np.zeros([K, N])\\n for n in np.arange(N):\\n for k in np.arange(K):\\n distances[k, n] = np.sqrt( (points[:, n] - centroids[:, k])**2 ).sum()\\n #distances = np.sqrt(((points - centroids[:, np.newaxis, 0])**2)).sum(axis=0) \\n\\n # 2. Update assigments\\n # v1 dirty\\n for n in np.arange(N):\\n kmin = 0\\n for k in np.arange(1, K):\\n if distances[k, n] <= distances[kmin, n]:\\n kmin = k\\n labels[n] = kmin\\n # v2 quicker\\n #labels = np.argmin(distances, axis=1)\\n\\n # 3. Update mean\\n for k in np.arange(K):\\n centroids[:, k] = np.mean(points[:, labels == k], axis=1)\\n #np.array([points[closest==k].mean(axis=0) for k in range(centroids.shape[0])])\\n\\n return centroids, labels\",\n \"def average_distance(c1, c2):\\n return sum(sum(symmetric_distances[p1][p2] for p1 in c1) for p2 in c2) \\\\\\n / (len(c1) * len(c2))\",\n \"def calculate_centroids(self, data, clusters):\\n centroids = []\\n for i in range(self.n_clusters):\\n mask = clusters == i \\n centroids.append(np.mean(data[mask, :], axis = 0)) \\n return centroids\",\n \"def kmean(X,initial_centroids,max_iters):\\n m = np.size(X,0)\\n K = np.size(initial_centroids,0)\\n centroids = initial_centroids\\n idx = np.zeros((m,1))\\n for i in range(1,max_iters):\\n idx = nearest_cluster(X,centroids)\\n centroids = update_centroids(X,idx,K)\\n return centroids,idx\",\n \"def k_means_clustering(rows, distance=pearson_distance, k=4):\\n # Determine the min and max values for each point\\n ranges = [(min(row[i] for row in rows), max([row[i] for row in rows])) for i in range(len(rows[0]))]\\n\\n # Create k RANDOMLY placed centroids\\n clusters = [[random() * (ranges[i][1] - ranges[i][0]) + ranges[i][0] for i in range(len(rows[0]))] for j in\\n range(k)]\\n distances_from_centroids = {}\\n last_matches = None\\n best_matches = None\\n for t in range(100):\\n print ('Iteration {}'.format(t))\\n best_matches = [[] for i in range(k)]\\n\\n # Find the centroid that is the closest for each row\\n for j in range(len(rows)):\\n row = rows[j]\\n best_match = 0\\n for i in range(k):\\n d = distance(clusters[i], row)\\n if d < distance(clusters[best_match], row):\\n best_match = i\\n best_matches[best_match].append(j)\\n\\n # if the results are the same as last time, then this is complete\\n if best_matches == last_matches:\\n break\\n last_matches = best_matches\\n\\n # Move the centroids to the average of their members\\n for i in range(k):\\n avgs = [0.0] * len(rows[0])\\n if len(best_matches[i]) > 0:\\n for row_id in best_matches[i]:\\n for m in range(len(rows[row_id])):\\n avgs[m] += rows[row_id][m]\\n for j in range(len(avgs)):\\n avgs[j] /= len(best_matches[i])\\n clusters[i] = avgs\\n\\n # Chapter 3 Exercise 5: Return along with the cluster results the total distance between all items\\n # and their respective centroids\\n for i in range(k):\\n for j in range(len(best_matches[i])):\\n distances_from_centroids[best_matches[i][j]] = distance(clusters[i],rows[best_matches[i][j]])\\n return best_matches, distances_from_centroids\",\n \"def update(self, clusters):\\n centroids = {}\\n for cluster, coordinates in clusters.iteritems():\\n sumLat = 0\\n sumLong = 0\\n for coordinate in coordinates:\\n sumLat += float(coordinate[0])\\n sumLong += float(coordinate[1])\\n centroids[cluster] = (sumLat/float(len(coordinates)), sumLong/float(len(coordinates)))\\n return centroids\",\n \"def centroid_link(clusters, i, j, dendrogram):\\n n_i, n_j = len(dendrogram[i]), len(dendrogram[j])\\n a_i = n_i / (n_i + n_j)\\n a_j = n_j / (n_i + n_j)\\n b = -(n_i * n_j) / (n_i + n_j)**2\\n update_fn = lambda d_ik,d_jk: a_i*d_ik + a_j*d_jk + b*clusters[i,j]\\n return _general_link(clusters, i, j, update_fn)\",\n \"def _distorted_distance(self):\\n distance = 0\\n for i, pixel in enumerate(self.training_set):\\n distance += self._euclid_distance(\\n pixel, self.clusters[self.labels[i]], axis=0)\\n return distance\",\n \"def calc_centroid(self):\\n num = 0\\n centroid = numpy.zeros(3, float)\\n for atm in self:\\n if atm.position is not None:\\n centroid += atm.position\\n num += 1\\n return centroid / num\",\n \"def calculate(self):\\n\\n gt_n = np.count_nonzero(self.ground_truth)\\n gt_indices = np.flip(np.where(self.ground_truth == 1), axis=0)\\n gt_mean = gt_indices.mean(axis=1)\\n gt_cov = np.cov(gt_indices)\\n\\n seg_n = np.count_nonzero(self.segmentation)\\n seg_indices = np.flip(np.where(self.segmentation == 1), axis=0)\\n seg_mean = seg_indices.mean(axis=1)\\n seg_cov = np.cov(seg_indices)\\n\\n # calculate common covariance matrix\\n common_cov = (gt_n * gt_cov + seg_n * seg_cov) / (gt_n + seg_n)\\n common_cov_inv = np.linalg.inv(common_cov)\\n\\n mean = np.matrix(np.array(gt_mean) - np.array(seg_mean))\\n\\n return math.sqrt(mean * np.matrix(common_cov_inv) * mean.T)\",\n \"def calcDistortion(medoids, clusters, class_header=\\\"Class\\\"):\\n distortion = 0\\n for medoid_row_index, medoid_tuple in enumerate(medoids.iterrows()): # For every Medoid\\n for _, datum in clusters[medoid_row_index].iterrows(): # For each point in the medoid cluster\\n # Add the distance between medoid and data point squared to total distortion\\n distortion += (Cluster.calcDistance(medoid_tuple[1], datum, class_header=class_header)) ** 2\\n return distortion\",\n \"def _compute_mean(self, C, mag, rjb, rake):\\n mean = (C['a1'] +\\n self._compute_linear_magnitude_term(C, mag) +\\n self._compute_quadratic_magnitude_term(C, mag) +\\n self._compute_logarithmic_distance_term(C, mag, rjb) +\\n self._compute_faulting_style_term(C, rake))\\n\\n return mean\",\n \"def findK_centroids_average(self, features, clusters):\\n\\n class InnerFeatures:\\n def __init__(self, kps, des, pos):\\n self.kps = kps\\n self.des = des\\n self.pos = pos\\n\\n kmeans = KMeans(n_clusters=clusters)\\n\\n pts = np.array(features.pos)\\n kps = np.array(features.kps)\\n des = np.array(features.des)\\n\\n kmeans.fit(pts)\\n m_clusters = np.array(kmeans.labels_.tolist())\\n centers = np.array(kmeans.cluster_centers_)\\n\\n # KeyPoint(x,y,size) -required\\n\\n final_kps = []\\n final_des = []\\n final_pts = []\\n\\n for cluster in range(clusters):\\n indices = np.where(m_clusters == cluster)\\n cluster_kps_size = np.mean(np.array([x.size for x in kps[indices]]))\\n cluster_des = des[indices]\\n\\n average_des = np.mean(cluster_des, axis=0)\\n cluster_kps = cv2.KeyPoint(x=centers[cluster][0], y=centers[cluster][1], _size=cluster_kps_size)\\n\\n final_kps.append(cluster_kps)\\n final_des.append(average_des)\\n final_pts.append([centers[cluster][0], centers[cluster][1]])\\n\\n final_pts = np.array(final_pts)\\n final_des = np.array(final_des)\\n final_kps = np.array(final_kps)\\n\\n result = InnerFeatures(kps=final_kps, des=final_des, pos=final_pts)\\n return result\",\n \"def fit(self):\\n self.cluseter_agglomerative(n_clusters=20, linkage='average', iterate=5)\\n self.sub_clustering(n_clusters=3, index_cluster=[79], linkage='complete')\\n self.merge_clusters([[0,9,53],[1,83],[46,35,67],[88,23],[6,68]])\\n self.merge_clusters([[6,33,52],[17,14]])\\n self.sub_clustering(n_clusters=2, index_cluster=[0], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[2], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[85], linkage='average')\\n self.sub_clustering(n_clusters=2, index_cluster=[14], linkage='complete')\\n self.sub_clustering(n_clusters=2, index_cluster=[16], linkage='average')\\n self.sub_clustering(n_clusters=3, index_cluster=[22], linkage='average')\\n self.sub_clustering(n_clusters=2, index_cluster=[24], linkage='complete')\\n self.sub_clustering(n_clusters=2, index_cluster=[26], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[28], linkage='ward')\\n self.merge_clusters([[6,98,99]])\\n self.merge_clusters([[35,80]])\\n self.sub_clustering(n_clusters=4, index_cluster=[35], linkage='complete')\\n self.merge_clusters([[76,98]])\\n self.sub_clustering(n_clusters=3, index_cluster=[35], linkage='complete')\\n self.merge_clusters([[39,42]])\\n self.sub_clustering(n_clusters=3, index_cluster=[47], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='average')\\n self.merge_clusters([[70,101]])\\n self.sub_clustering(n_clusters=3, index_cluster=[51], linkage='complete')\\n self.sub_clustering(n_clusters=3, index_cluster=[61], linkage='ward')\\n self.merge_clusters()\\n return\",\n \"def _compute_distances(self, atoms: List[CellAtom]):\\n muon = self._cell_atoms[self._muon_index]\\n\\n for atom in atoms:\\n atom.distance_from_muon = np.linalg.norm(muon.position - atom.position)\",\n \"def run_k_means(self):\\r\\n centroids = self.centroids\\r\\n\\r\\n for i in range(self.max_iters):\\r\\n self.closestcentroids()\\r\\n self.newcentroids()\\r\\n\\r\\n J = 0\\r\\n X = self.x\\r\\n m = len(X)\\r\\n idx = self.index\\r\\n K = self.K\\r\\n dim = X.shape[1]\\r\\n\\r\\n for num in range(K):\\r\\n # find the index of all entries where idx==n\\r\\n indexentries = np.nonzero(idx == num)[0]\\r\\n # the values in X that have the index in indesxentries\\r\\n values = X[indexentries]\\r\\n # using one of the K centroids to do the calculation. K<=2 doesn't\\r\\n # work here for some reason.\\r\\n centroid = centroids[num, 0]\\r\\n J += np.sum((values - centroid) ** 2)\\r\\n\\r\\n return [centroids.reshape((1, K, dim)), [X[idx == k].size for k in range(K)], J / m]\",\n \"def _eval_clustering(self, gen_reviews, clusters, embedding_model, clustering):\\n result = []\\n preds = self.predict_gen(gen_reviews, embedding_model, clustering)\\n\\n acc = accuracy_score(np.array(clusters), np.array(preds))\\n conf = confusion_matrix(np.array(clusters), np.array(preds))\\n\\n return acc, conf\",\n \"def calculate_all_metrcis(self):\\n self.calculate_gc_metrcis()\\n self.calculate_sam_metrics()\\n self.calculate_classification_metrics()\\n self.calculate_losses()\",\n \"def _cluster(self):\\n # , distance_function=spearman_squared_distance, max_iter=1000, tol=0.0001):\\n if self.cluster_method is None:\\n clusters = KMedoids(\\n self.k,\\n self.batchsize,\\n dist_func=self.distance_function,\\n max_iter=self.max_iter,\\n tol=self.tol,\\n init_medoids=self.init_medoids,\\n swap_medoids=self.swap_medoids,\\n )\\n clusters.fit(self.clustering_attributions, verbose=self.verbose)\\n\\n self.subpopulations = clusters.members\\n self.subpopulation_sizes = GAM.get_subpopulation_sizes(clusters.members)\\n self.explanations = self._get_explanations(clusters.centers)\\n # Making explanations return numerical values instead of dask arrays\\n if isinstance(self.explanations[0][0][1], da.Array):\\n explanations = []\\n for explanation in self.explanations:\\n explanations.append([(x[0], x[1].compute()) for x in explanation])\\n self.explanations = explanations\\n else:\\n self.cluster_method(self)\",\n \"def kmeans(X, k, iterations=1000):\\n\\n # Initialize the cluster centroids (C <- centroid \\\"means\\\")\\n C = initialize(X, k)\\n\\n if C is None:\\n return None, None\\n if not isinstance(iterations, int) or iterations <= 0:\\n return None, None\\n\\n # n: number of dada points\\n # d: dimension of each data point\\n n, d = X.shape\\n\\n # # Initialize the cost/distortion function;\\n # # defined as J = sum/n(sum/k(r(ij)*||x(i) - c(j)||**2))\\n # J = np.inf\\n\\n # Iterate over iterations\\n for iteration in range(iterations):\\n # print(\\\"iteration:\\\", iteration)\\n\\n # Maintain a deep copy of C\\n # C_prev = np.array([x for x in C])\\n # Another alternative (removes for loop):\\n C_prev = np.copy(C)\\n\\n # OPTION 1: FOR LOOPS\\n\\n # Initialize the array of pairwise data point-centroid\\n # distances with zeros\\n # dist = np.zeros((n, k))\\n\\n # for i in range(n):\\n # for j in range(k):\\n # dist[i, j] = np.linalg.norm(X[i, ...] - C[j, ...])\\n # Note: squared distances can alternatively be inferred\\n # directtly from the inner product of (X - C) with itself\\n # dist[i, j] = np.inner(X[i,:]-C[j,:], X[i,:]-C[j,:])\\n # print(\\\"dist:\\\", dist)\\n # Squared distances from \\\"dist\\\":\\n # print(\\\"dist ** 2:\\\", dist ** 2)\\n\\n # OPTION 2: VECTORIZATION\\n\\n # Convert X into an array suitable for vectorization\\n Xv = np.repeat(X, k, axis=0)\\n # print(\\\"Xv:\\\", Xv)\\n # print(\\\"Xv.shape:\\\", Xv.shape)\\n Xv = Xv.reshape(n, k, d)\\n # print(\\\"Xv:\\\", Xv)\\n # print(\\\"Xv.shape:\\\", Xv.shape)\\n\\n # Convert C into an array suitable for vectorization\\n Cv = np.tile(C, (n, 1))\\n # print(\\\"Cv:\\\", Cv)\\n # print(\\\"Cv.shape:\\\", Cv.shape)\\n Cv = Cv.reshape(n, k, d)\\n # print(\\\"Cv:\\\", Cv)\\n # print(\\\"Cv.shape:\\\", Cv.shape)\\n\\n # Compute the \\\"dist\\\" matrix of euclidean distances between\\n # data points and centroids; shape (n, k)\\n dist = np.linalg.norm(Xv - Cv, axis=2)\\n\\n # Assign each point of the dataset to a centroid:\\n # Evaluate argmin(dist**2) for comparison with k\\n # r(ij) = 1 if argmin(dist**2) == j\\n # -> point i assigned to centroid k\\n # otherwise r(ij) = 0 -> ignore point i wrt centroid k\\n clss = np.argmin(dist ** 2, axis=1)\\n # print(\\\"centroid indices:\\\", clss)\\n # print(\\\"clss.shape:\\\", clss.shape)\\n # Note: here, clss is a 1D array of the unique centroid index\\n # to which each point in the dataset as been assigned (closest to);\\n # the indices array is used in place of r(ij) in J evaluations\\n\\n # OPTION 1: EXIT CONDITION BASED ON J_prev == J\\n\\n # # Make a copy of the previous J value & reinitialize J\\n # J_prev = J\\n # # J = 0\\n\\n # # Update J (summing over the n data points),\\n # # based on the (shortest) distances inferred from \\\"indices\\\"\\n # # From \\\"for\\\" loop:\\n # # for i in range(n):\\n # # J += (dist[i, clss[i]] ** 2)\\n # # From vectorization:\\n # J = np.sum(dist[..., clss] ** 2)\\n # # Normalize J to the number of data points to\\n # # reduce the computational cost (optional)\\n # J /= n\\n # # print(\\\"J:\\\", J)\\n\\n # if J == J_prev:\\n # # print(\\\"last iteration:\\\", iteration)\\n # return C, clss\\n\\n # Move the cluster centroids to the center (mean) of\\n # the refined cluster by updating C (centroid coordinates)\\n for j in range(k):\\n # Infer the array of data point indices that correspond\\n # to each assigned cluster centroid\\n indices = np.where(clss == j)[0]\\n # print(\\\"indices:\\\", indices)\\n if len(indices) == 0:\\n C[j] = initialize(X, 1)\\n else:\\n C[j] = np.mean(X[indices], axis=0)\\n\\n # OPTION 2: EXIT CONDITION BASED ON C == C_prev\\n\\n if (C == C_prev).all():\\n # print(\\\"last iteration:\\\", iteration)\\n return C, clss\\n\\n # Update clss before returning C, clss\\n Cv = np.tile(C, (n, 1))\\n Cv = Cv.reshape(n, k, d)\\n dist = np.linalg.norm(Xv - Cv, axis=2)\\n clss = np.argmin(dist ** 2, axis=1)\\n\\n return C, clss\",\n \"def evaluate_clusters(self, cluster_formulas, value='weighted_sum'):\\n num_elems = len(self.labels)\\n total_val = {}\\n num_cl = len(cluster_formulas)\\n clustered_points_num = 0\\n print(\\\"\\\\n\\\\n\\\")\\n print(\\\"Sufficiently big clusters: {}\\\".format(num_cl))\\n for c, formula, val in cluster_formulas:\\n c_size = len([l for l in self.labels if l == c])\\n clustered_points_num += c_size\\n\\n if value == 'weighted_sum':\\n total_val[c] = val * c_size / num_elems\\n elif value == 'sum':\\n total_val[c] = val * 1\\n\\n clust_val = sum(total_val.values())\\n self.clustering_value = total_val\\n print(\\\"Value of clustering: {}\\\".format(clust_val))\\n return clust_val\",\n \"def _calculate_analysis_values(predicted_clusters, true_cluster, times):\\n logger = get_logger('analysis', logging.INFO)\\n logger.info('Calculate scores')\\n\\n # Initialize output\\n metric_results = [None] * len(metric_names)\\n for m, min_value in enumerate(metric_min_values):\\n if min_value == 1:\\n metric_results[m] = np.ones(len(true_cluster))\\n else:\\n metric_results[m] = np.zeros((len(true_cluster)))\\n\\n # Loop over all possible clustering\\n for i, predicted_cluster in enumerate(predicted_clusters):\\n logger.info('Calculated Scores for {}/{} predicted clusters'.format(i, len(predicted_clusters)))\\n # Calculate different analysis's\\n metric_results[0][i] = misclassification_rate(true_cluster, predicted_cluster)\\n metric_results[1][i] = average_cluster_purity(true_cluster, predicted_cluster)\\n metric_results[2][i] = adjusted_rand_index(true_cluster, predicted_cluster)\\n metric_results[3][i] = diarization_error_rate(true_cluster, predicted_cluster, times)\\n\\n return metric_results\",\n \"def find_centroid_for_each(self):\",\n \"def calc_error_dist(self):\\n pass\",\n \"def train(self, train_X, max_iterations=1000):\\n assert len(train_X.shape) == 2 and train_X.shape[1] == self.D, f\\\"train_X should be a NxD matrix. Got: {train_X.shape}\\\"\\n assert max_iterations > 0, f\\\"max_iterations must be positive. Got: {max_iterations}\\\"\\n N = train_X.shape[0]\\n\\n labels = np.empty(shape=(N, 1), dtype=np.long)\\n distances = np.empty(shape=(N, self.K))\\n for _ in range(max_iterations):\\n old_labels = labels\\n\\n # ====================================================\\n for index, center in enumerate(self.centers): # build the distances matrix\\n # K iterations\\n newDistanceCol = np.square(np.linalg.norm(train_X - center, axis=1))\\n distances[:, index] = newDistanceCol\\n\\n labels = np.argmin(distances, axis=1).reshape((N, 1))# update labels based on distances\\n\\n cluster_child_count = np.zeros((1, self.K))\\n self.centers = np.zeros(self.centers.shape) # replace with zeros\\n\\n\\n for x_index, center_index in enumerate(labels): #update centers value\\n # N iterations\\n self.centers[center_index] += train_X[x_index, :] # increment centers\\n cluster_child_count[:, center_index] += 1 # inc number of children in that center\\n\\n self.centers /= cluster_child_count.T # divide by number of children in each center to get avg\\n # ====================================================\\n\\n # Check convergence\\n if np.allclose(old_labels, labels):\\n break\\n\\n return labels\",\n \"def k_clusters(old_ops, max_outputs, mut):\\n \\n # DM construction\\n matrix = starting_centroids(old_ops, max_outputs, mut)\\n\\n\\n # Clustering\\n seed = []\\n for i in matrix.OPs:\\n seed.append(i)\\n centroids = cluster(old_ops, seed, mut)\\n disto = distortion(centroids, old_ops, mut)\\n\\n return centroids, disto\",\n \"def mean_cluster(self, labelled_cluster):\\n sum_of_points = self.sum_cluster(labelled_cluster)\\n size_cluster = len(labelled_cluster)\\n if self.sigma_cl1:\\n size_cluster += np.sqrt(2)*self.sigma_cl1*np.random.randn()\\n mean_of_points = sum_of_points * (1.0 / size_cluster)\\n return mean_of_points\",\n \"def clusterAndDistance(self, data):\\n\\t\\treturn closestClusterAndDistance(data, self.centers)\",\n \"def _compute_dist(self, K, dist, within_distances, update_within):\\r\\n\\r\\n sw = self.sample_weight_\\r\\n\\r\\n for j in xrange(self.n_clusters):\\r\\n mask = self.labels_ == j\\r\\n if np.sum(mask) == 0:\\r\\n raise ValueError(\\\"Empty cluster found, try smaller n_cluster.\\\")\\r\\n\\r\\n denom = sw[mask].sum()\\r\\n denomsq = denom * denom\\r\\n if update_within:\\r\\n KK = K[mask][:, mask] \\r\\n dist_j = np.sum(np.outer(sw[mask], sw[mask]) * KK / denomsq)\\r\\n within_distances[j] = dist_j\\r\\n dist[:, j] += dist_j\\r\\n else:\\r\\n dist[:, j] += within_distances[j]\\r\\n\\r\\n dist[:, j] -= 2 * np.sum(sw[mask] * K[:, mask], axis=1) / denom #calculating distance of each point from centroid of cluster j by finding \\r\\n #diff. b/w centroid of cluster j & similarity of it with points in cluster j\\r\",\n \"def cluster_means(self):\\n if self.evaluate_by is not None:\\n return(self.merged_data.groupby(\\n 'labels').mean().sort_values(self.evaluate_by).transpose())\\n else:\\n return(self.merged_data.groupby('labels').mean().transpose())\",\n \"def _transform(self, X):\\r\\n return euclidean_distances(X, self.cluster_centers_)\",\n \"def compute_cost(X, groups, K_clusters):\\n m = X.shape[0]\\n dis = np.empty(m)\\n for i in range(m):\\n dis[i] = compute_distance(X[i,:].reshape(1,X.shape[1]), K_clusters[groups[i],:].reshape(1,X.shape[1]))\\n cost = (1/m)*np.sum(dis)\\n return cost\",\n \"def computeKMeans(self, points, k):\\n centroids = self.init_centroids(points,k)\\n \\n for i in range(5):\\n closest = self.closestCentroids(points,centroids)\\n centroids = self.updateCentroids(points, closest ,centroids)\\n\\n return centroids\",\n \"def calculateEuclideanDistance(vector):\\r\\n global euclideanDistance\\r\\n # create linkage matrix with the distance metric as euclidean distance\\r\\n # calculate the distances of the clusters by starting as singletons\\r\\n # and in each iteration will merge the two clusters which have the smallest distance\\r\\n # returns array of length n - 1\\r\\n # Z[i] will tell us which clusters were merged in the i-th iteration\\r\\n # each row has format [cluster1, cluster1, dist, sample_count].\\r\\n euclideanDistance = linkage(vector, metric='euclidean')\",\n \"def ex7():\\n\\n \\\"\\\"\\\"\\n ================= Part 1: Find Closest Centroids ====================\\n To help you implement K-Means, we have divided the learning algorithm\\n into two functions -- find_closest_centroids and computeCentroids. In this\\n part, you shoudl complete the code in the find_closest_centroids function.\\n \\\"\\\"\\\"\\n print('Finding closest centroids.\\\\n\\\\n')\\n\\n # Load an example dataset that we will be using\\n with open('ex7/data/ex7data2.pkl', 'rb') as fin:\\n X = pickle.load(fin)\\n\\n # Select an initial set of centroids\\n K = 3 # 3 Centroids\\n initial_centroids = np.array([[3, 3], [6, 2], [8, 5]])\\n\\n # Find the closest centroids for the examples using the\\n # initial_centroids\\n idx = find_closest_centroids(X, initial_centroids)\\n\\n print('Closest centroids for the first 3 examples: \\\\n')\\n print(idx[0:3])\\n print('\\\\n(the closest centroids should be 0, 2, 1 respectively)\\\\n')\\n\\n \\\"\\\"\\\"\\n ===================== Part 2: Compute Means =========================\\n After implementing the closest centroids function, you should now\\n complete the computeCentroids function.\\n \\n \\\"\\\"\\\"\\n print('\\\\nComputing centroids means.\\\\n\\\\n')\\n\\n # Compute means based on the closest centroids found in the previous part.\\n centroids = compute_centroids(X, idx, K)\\n\\n print('Centroids computed after initial finding of closest centroids: \\\\n')\\n print(centroids)\\n print('\\\\n(the centroids should be\\\\n')\\n print(' [ 2.428301 3.157924 ]\\\\n')\\n print(' [ 5.813503 2.633656 ]\\\\n')\\n print(' [ 7.119387 3.616684 ]\\\\n)\\\\n')\\n\\n \\\"\\\"\\\"\\n =================== Part 3: K-Means Clustering ======================\\n After you have completed the two functions computeCentroids and\\n find_closest_centroids, you have all the necessary pieces to run the\\n kMeans algorithm. In this part, you will run the K-Means algorithm on\\n the example dataset we have provided.\\n \\\"\\\"\\\"\\n print('\\\\nRunning K-Means clustering on example dataset.\\\\n\\\\n')\\n\\n # Load an example dataset\\n with open('ex7/data/ex7data2.pkl', 'rb') as fin:\\n X = pickle.load(fin)\\n\\n # Settings for running K-Means\\n K = 3\\n max_iters = 10\\n\\n \\\"\\\"\\\"\\n For consistency, here we set centroids to specific values\\n but in practice you want to generate them automatically, such as by\\n settings them to be random examples (as can be seen in\\n kmeans_init_centroids).\\n \\\"\\\"\\\"\\n initial_centroids = np.array([[3, 3], [6, 2], [8, 5]])\\n\\n # Run K-Means algorithm. The 'true' at the end tells our function to plot\\n # the progress of K-Means\\n centroids, idx = run_kmeans(X, initial_centroids, max_iters, True)\\n print('\\\\nK-Means Done.\\\\n\\\\n')\\n\\n \\\"\\\"\\\"\\n ============= Part 4: K-Means Clustering on Pixels ===============\\n In this exercise, you will use K-Means to compress an image. To do this,\\n you will first run K-Means on the colors of the pixels in the image and\\n then you will map each pixel on to it's closest centroid.\\n \\n You should now complete the code in kmeans_init_centroids.py\\n \\\"\\\"\\\"\\n\\n print('\\\\nRunning K-Means clustering on pixels from an image.\\\\n\\\\n')\\n\\n # Load an image of a bird\\n A = plt.imread('ex7/data/bird_small.png')\\n # A = A / 255; # Divide by 255 so that all values are in the range 0 - 1\\n\\n # Size of the image\\n img_size = A.shape\\n\\n # Reshape the image into an Nx3 matrix where N = number of pixels.\\n # Each row will contain the Red, Green and Blue pixel values\\n # This gives us our dataset matrix X that we will use K-Means on.\\n X = np.reshape(A, (img_size[0] * img_size[1], 3))\\n\\n # Run your K-Means algorithm on this data\\n # You should try different values of K and max_iters here\\n K = 16\\n max_iters = 10\\n\\n # When using K-Means, it is important the initialize the centroids\\n # randomly.\\n # You should complete the code in kmeans_init_centroids.py before proceeding\\n initial_centroids = kmeans_init_centroids(X, K)\\n\\n # Run K-Means\\n [centroids, idx] = run_kmeans(X, initial_centroids, max_iters)\\n\\n \\\"\\\"\\\"\\n ================= Part 5: Image Compression ======================\\n In this part of the exercise, you will use the clusters of K-Means to\\n compress an image. To do this, we first find the closest clusters for\\n each example. After that, we \\n \\\"\\\"\\\"\\n print('\\\\nApplying K-Means to compress an image.\\\\n\\\\n')\\n\\n # Find closest cluster members\\n idx = find_closest_centroids(X, centroids)\\n\\n # Essentially, now we have represented the image X as in terms of the\\n # indices in idx.\\n\\n # We can now recover the image from the indices (idx) by mapping each pixel\\n # (specified by it's index in idx) to the centroid value\\n X_recovered = centroids[idx, :]\\n\\n # Reshape the recovered image into proper dimensions\\n X_recovered = np.reshape(X_recovered, (img_size[0], img_size[1], 3))\\n\\n # Display the original image\\n plt.close()\\n fig, (ax1, ax2) = plt.subplots(1, 2)\\n ax1.imshow(A)\\n ax1.set_title('Original')\\n\\n # Display compressed image side by side\\n ax2.imshow(X_recovered)\\n ax2.set_title('Compressed, with {:d} colors.'.format(K))\\n plt.show()\",\n \"def get_cluster_accuracy(self, curs, p_gene_table, mcl_id_list, p_value_cut_off=0.01):\\n\\t\\taccuracy2cluster = []\\n\\t\\tfor mcl_id in mcl_id_list:\\n\\t\\t\\tcurs.execute(\\\"select is_correct_lca from %s where mcl_id=%s and p_value_cut_off<=%s\\\"%(p_gene_table,\\\\\\n\\t\\t\\t\\tmcl_id, p_value_cut_off))\\n\\t\\t\\trows = curs.fetchall()\\n\\t\\t\\tif rows:\\n\\t\\t\\t\\tis_correct_lca_array = array(rows)\\n\\t\\t\\t\\tcorrect_array = greater(is_correct_lca_array[:,0],0)\\n\\t\\t\\t\\tknown_array = greater_equal(is_correct_lca_array[:,0],0)\\n\\t\\t\\t\\taccuracy = float(sum(correct_array))/float(sum(known_array))\\n\\t\\t\\t\\taccuracy2cluster.append([accuracy, sum(correct_array), sum(known_array), len(correct_array), mcl_id]) \\n\\t\\treturn accuracy2cluster\",\n \"def __move_centroids(self, data):\\n \\n for i in range(len(self.centroids)):\\n members_cluster = data[self.clusters == i]\\n self.centroids[i] = np.sum(members_cluster, axis=0) / (len(members_cluster) + self.epsilon)\",\n \"def calculate_euclidean_distance(self, matrix, input, output_neuron):\\n result = 0\\n\\n # Loop over all input data.\\n diff = input - matrix[output_neuron]\\n return np.sqrt(sum(diff*diff))\",\n \"def evaluate(self, clustering):\\n # Pca for each one of the clusters\\n pca_mean_val = 0.;\\n MAX_ELEMENTS = 1000\\n for c in clustering.clusters:\\n # Pick the coordinates (ensuring that we are copying them)\\n element_indexes = c.all_elements\\n ###################\\n # Performance hack\\n ###################\\n # As it can be very slow for big clusters (i.e. > 3k elements) we'll compress this clusters \\n # before calculating PCA. It should increase variance but will allow calculations.\\n # It should use the kmedoids compressor\\n if len(c.all_elements) > MAX_ELEMENTS:\\n element_indexes = c.get_random_sample(MAX_ELEMENTS)\\n print \\\"[PCA] Random sampling too big cluster to improve performance (%d elements -> %d elements).\\\"%(len(c.all_elements),MAX_ELEMENTS)\\n ###################\\n \\n fitting_coordinates_of_this_cluster = self.fitting_coordinates[element_indexes]\\n \\n calculator = RMSDCalculator(calculatorType = \\\"QTRFIT_SERIAL_CALCULATOR\\\",\\n fittingCoordsets = fitting_coordinates_of_this_cluster)\\n \\n if self.calculation_coordinates is not None:\\n calculation_coordinates_of_this_cluster = self.calculation_coordinates[element_indexes]\\n calculator = RMSDCalculator(calculatorType = \\\"QTRFIT_SERIAL_CALCULATOR\\\",\\n fittingCoordsets = fitting_coordinates_of_this_cluster,\\n calculationCoordsets = calculation_coordinates_of_this_cluster)\\n \\n # Make an iterative superposition (to get the minimum RMSD of all with respect to a mean conformation)\\n calculator.iterativeSuperposition()\\n\\n # Calculate the covariance matrix\\n if self.calculation_coordinates is None:\\n covariance_matrix = PCAMetric.create_covariance_matrix(fitting_coordinates_of_this_cluster)\\n else:\\n covariance_matrix = PCAMetric.create_covariance_matrix(calculation_coordinates_of_this_cluster)\\n \\n # And then the eigenvalue we are interested in\\n pca_mean_val += PCAMetric.calculate_biggest_eigenvalue(covariance_matrix)\\n print \\\"PCA finished\\\"\\n return pca_mean_val /clustering.total_number_of_elements\",\n \"def rms(trained_data, dist):\\n sum = 0\\n for i in trained_data:\\n point = i[:-2]\\n centroid = i[-1]\\n distance = (calculate_distance(point,centroid, dist)**2)\\n sum +=distance\\n return sum\",\n \"def calc_distances_from_central(cluster, embedding):\\n\\n return calc_distances_in_embedding(cluster, embedding)\",\n \"def Dist_clust(data):\\n mask = np.loadtxt('/net/tarea/scratch/Rafael/phd/apogee/python/comb_SkyTel_mask.dat')\\n masked = np.where(mask == 1)[0]\\n spectra_list = data['fullset']\\n clusters = data['clusters']\\n clusters = clusters.transpose()\\n distance = np.zeros((len(spectra_list), 2))\\n min_dist_cl = np.zeros((data['nc'], 2))\\n for j_cluster in range(data['nc']):\\n dist_cluster= np.zeros((data['nc']))\\n for i_cluster in range(data['nc']):\\n dist_cluster[i_cluster] = np.nansum((clusters[j_cluster][masked] - clusters[i_cluster][masked])**2)**0.5\\n min_dist_cl[j_cluster,0] = np.argmin(dist_cluster)\\n dist_cluster[np.argmin(dist_cluster)] = dist_cluster[np.argmax(dist_cluster)]\\n if (len(np.where(dist_cluster != 0)[0]) > 0):\\n min_dist_cl[j_cluster,1] = np.argmin(dist_cluster[(dist_cluster != 0)])\\n for i_spec, name in enumerate(spectra_list):\\n vec_temp = np.load(name)\\n for i_cluster, j_cluster in enumerate(min_dist_cl[data['assign'][i_spec]]):\\n distance[i_spec,i_cluster] = np.nansum((clusters[j_cluster][masked] - vec_temp['norm'][masked])**2)**0.5\\n vec_temp.close()\\n return distance, min_dist_cl\",\n \"def k_means(x_input, n_cluster=3, n_iter=100, n_tries=10):\\n results = []\\n for _ in range(n_tries):\\n error_value = 0\\n rand.seed(None)\\n centers = sorted([rand.uniform(0.0, 100.0) for i in range(n_cluster)])\\n min_dist_idx = [0] * len(x_input)\\n i = 0\\n while i < n_iter:\\n failed = False\\n dist_mat = l2_pairwise_distance(x_input, centers)\\n error_value = calculate_error(dist_mat)\\n min_dist_idx = [dist.index(min(dist)) for dist in dist_mat]\\n centers = [0] * n_cluster\\n count = [0] * n_cluster\\n for j in range(len(x_input)):\\n centers[min_dist_idx[j]] += x_input[j]\\n count[min_dist_idx[j]] += 1\\n\\n for j in range(n_cluster):\\n if count[j] == 0:\\n centers = sorted(\\n [rand.uniform(0.0, 100.0) for i in range(n_cluster)])\\n failed = True\\n break\\n\\n if failed:\\n i = 0\\n continue\\n\\n for j in range(n_cluster):\\n centers[j] = centers[j] / count[j]\\n i += 1\\n\\n results.append((centers, min_dist_idx, error_value))\\n\\n return min(results, key=lambda x: x[2])\",\n \"def get_distances(centroid, points):\\r\\n return np.linalg.norm(points - centroid, axis=1)\",\n \"def compute(self): \\r\\n hist = self.confusion_matrix\\r\\n iu = np.diag(hist) / (hist.sum(axis=1) + hist.sum(axis=0) - np.diag(hist))\\r\\n mean_iu = np.nanmean(iu)\\r\\n return mean_iu\",\n \"def k_mean_cluster(num_anchors, boxes, convergence_threshold=1e-9):\\n # Randomly pick 5 boxes as centroids\\n centroids = np.array(random.sample(boxes, k=num_anchors))\\n # Clustering until reaching loss_convergence threshold\\n centroids, prev_errors = k_mean(boxes, centroids)\\n while True:\\n centroids, errors = k_mean(boxes, centroids)\\n if abs(errors - prev_errors) <= convergence_threshold:\\n break\\n else:\\n prev_errors = errors\\n\\n avg_iou = np.mean(np.max(compute_iou(boxes, centroids), axis=-1))\\n return centroids, avg_iou\",\n \"def updateCentroids(self, points, closest, centroids):\\n return numpy.array([points[closest==k].mean(axis=0) for k in range(centroids.shape[0])])\",\n \"def computeStats(self, absList, statOut, errorOut):\\n \\n nMentions = 0\\n pSum = 0\\n rSum = 0\\n for abstract in absList:\\n # build hash of annotated clusters/chains keyed by ID\\n errorOut.write('\\\\n---- '+abstract.id+' ----\\\\n')\\n trueChainLengths = {}\\n entityList = abstract.annotatedEntities.getList(self.entityTypes[0])\\n errorOut.write('True chains:\\\\n')\\n for entityTemplate in entityList:\\n if len(entityTemplate.getAnnotatedId()) > 0:\\n trueChain = entityTemplate.getMentionChain()\\n trueChainLengths[entityTemplate.getAnnotatedId(checkEntireCluster=False)] = len(trueChain)\\n for m in trueChain:\\n# errorOut.write(m.name+':'+m.getAnnotatedId(checkEntireCluster=False) +'\\\\n')\\n errorOut.write('%s %s:%s, matchedMention=%s \\\\n'%(m.name, m.mention, m.getAnnotatedId(checkEntireCluster=False), m.mention.matchedMention))\\n\\n errorOut.write('----\\\\n')\\n else:\\n print abstract.id, entityTemplate.name, 'is missing an ID'\\n \\n # compute Recall and precision for each detected chain/cluster\\n entityList = abstract.entities.getList(self.entityTypes[0])\\n errorOut.write('\\\\nHypothesis chains:\\\\n')\\n for entityTemplate in entityList:\\n detectedChain = entityTemplate.getMentionChain()\\n \\n rootMention = entityTemplate.rootMention()\\n errorOut.write('[Canonical name: '+rootMention.getCanonicalName()+']\\\\n')\\n \\n for m in detectedChain:\\n errorOut.write('%s %s:%s, matchedMention=%s \\\\n'%(m.name, m.mention, m.getAnnotatedId(checkEntireCluster=False), m.mention.matchedMention))\\n# errorOut.write(m.name+':'+m.getAnnotatedId(checkEntireCluster=False) +'\\\\n')\\n errorOut.write('----\\\\n')\\n\\n nMentionsInChain = len(detectedChain)\\n for mTemplate in detectedChain:\\n nMentions += 1\\n if len(mTemplate.getAnnotatedId(checkEntireCluster=False)) == 0:\\n # mention is a false positive, it does not belong to any chain\\n pSum += 1.0/nMentionsInChain\\n rSum += 1\\n else:\\n if mTemplate.getAnnotatedId(checkEntireCluster=False) not in trueChainLengths:\\n print abstract.id, 'template with id =',mTemplate.getAnnotatedId(checkEntireCluster=False), 'not in a true chain'\\n break\\n nMentionsInTrueChain = trueChainLengths[mTemplate.getAnnotatedId(checkEntireCluster=False)]\\n nCorrectInDetectedChain = 0\\n annotatedMatches = set([])\\n # count the number of mentions in the detected chain that\\n # should be in the same chain as this mention\\n for m in detectedChain:\\n if mTemplate.getAnnotatedId(checkEntireCluster=False) == m.getAnnotatedId(checkEntireCluster=False) \\\\\\n and m.mention.matchedMention not in annotatedMatches:\\n nCorrectInDetectedChain += 1\\n annotatedMatches.add(m.mention.matchedMention)\\n# else:\\n# print abstract.id, 'Two mentions do not belong in same chain',\\n# print mTemplate, m.getAnnotatedId()\\n \\n if nCorrectInDetectedChain > nMentionsInTrueChain:\\n print abstract.id, 'id=',mTemplate.getAnnotatedId(checkEntireCluster=False), \\n print 'detected chain=', nCorrectInDetectedChain,\\n print 'true chain=', nMentionsInTrueChain\\n nCorrectInDetectedChain = nMentionsInTrueChain\\n \\n# if nCorrectInDetectedChain != nMentionsInChain:\\n# print abstract.id, 'id=',mTemplate.getAnnotatedId(), \\n# print 'detected chain=', nCorrectInDetectedChain,\\n# print 'true chain=', nMentionsInTrueChain\\n \\n pSum += float(nCorrectInDetectedChain) / nMentionsInChain\\n rSum += float(nCorrectInDetectedChain) / nMentionsInTrueChain\\n \\n if nMentions == 0:\\n print 'No mentions???'\\n return \\n \\n precision = pSum/nMentions\\n recall = rSum/nMentions \\n fscore = 2*(recall*precision)/(recall + precision)\\n \\n sys.stdout.write('Recall\\\\tPrecision\\\\tF-score\\\\n')\\n sys.stdout.write('%.3f\\\\t ' % recall + '%.3f\\\\t ' % precision + '%.3f' % fscore+'\\\\n')\\n# statOut.write(self.entityTypesString+'\\\\n')\\n# statOut.write('Recall\\\\tPrecision\\\\tF-score\\\\n')\\n# statOut.write('%.3f\\\\t ' % recall + '%.3f\\\\t ' % precision + '%.3f' % fscore+'\\\\n')\\n statOut.addStats('MC - '+self.entityTypesString, [['R', recall], ['P', precision], ['F',fscore]])\",\n \"def euclidean_sqr(self, instance, centroid):\\n return np.linalg.norm(instance-centroid)**2\",\n \"def k_means(data, k = 2, centroids = None, max_iters = 100) :\\r\\n if centroids == None :\\r\\n centroids = get_random_centroids(data, k)\\r\\n \\r\\n elif len(centroids) != k :\\r\\n AssertionError(\\\"Número de centroides no equivale a k\\\")\\r\\n \\r\\n for i in range(max_iters) :\\r\\n old_centroids = centroids\\r\\n \\r\\n assigned_centroids = assign_centroids(data, centroids)\\r\\n \\r\\n # Sum the data by cluster\\r\\n centroids = [[0]*data.shape[1]] * k\\r\\n values_in_centroid = [0] * k\\r\\n\\r\\n for i in range(k) :\\r\\n assigned_centroids_aux = np.column_stack([assigned_centroids]*data.shape[1])==i\\r\\n centroids[i] = np.sum(np.multiply(data, assigned_centroids_aux), axis = 0)\\r\\n values_in_centroid[i] = np.sum(assigned_centroids == i)\\r\\n\\r\\n # Mean\\r\\n for i in range(k) :\\r\\n if values_in_centroid[i] > 0 :\\r\\n centroids[i] = centroids[i]/values_in_centroid[i]\\r\\n\\r\\n centroids = np.stack(centroids, axis=0)\\r\\n\\r\\n error = sum([np.linalg.norm(centroids[i] - old_centroids[i]) for i in range(k)])\\r\\n if(error < 1e-5) : break\\r\\n \\r\\n \\r\\n return centroids\",\n \"def run(self, max_clusters):\\n sample_dist_matrix = self.matrix_dist()\\n self.link.print_link()\\n first_clus = self.clusters[0] # initialize first cluster to merge into\\n second_clus = self.clusters[0] # initialize second cluster to merge\\n max_samples_dist = max(sample_dist_matrix.values())\\n # initialize minimun distance between two samples\\n min_dist = max_samples_dist\\n while len(self.clusters) > max_clusters: # clustering loop\\n for clus in self.clusters: # iterate over every cluster\\n for other_clus in self.clusters: # iterate over other clusters\\n if clus.c_id > other_clus.c_id: # avoid duplicates and make sure to pass correct key to dictionary\\n # compute distance between two clusters according to current link\\n clus_dist = self.link.compute(clus, other_clus, sample_dist_matrix)\\n if clus_dist < min_dist: # keep the minimum distance and its clusters\\n min_dist = clus_dist\\n first_clus = other_clus\\n second_clus = clus\\n self.clusters.remove(second_clus) # remove the cluster that's getting merged from clusters list\\n first_clus.merge(second_clus) # merge the cluster with higher id into the other\\n min_dist = max_samples_dist # restore high distance in order to start the search again\\n\\n sum_sil = self.compute_summery_silhouette(sample_dist_matrix)\\n # print results\\n for clus in self.clusters:\\n clus.print_details(sum_sil[clus.c_id])\\n print(f'Whole data: silhouette = {sum_sil[0]}, RI = {self.compute_rand_index()}')\",\n \"def calculate_clusters(study_id):\\n\\n with current_app.app_context():\\n cur = conn.cursor()\\n\\n cur.execute(\\\"\\\"\\\"SELECT * FROM STATS WHERE STUDY_ID=%s\\\"\\\"\\\", (str(study_id),))\\n study = fetchoneClean(cur)\\n clusters_calculating = study[4]\\n clusters_changed = study[5]\\n if clusters_changed:\\n if clusters_calculating:\\n return {'message': 'calculating'}\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CALCULATING = TRUE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n conn.commit()\\n\\n distance = study[7]['matrix']\\n card_names = study[7]['cardNames']\\n cur.execute(\\\"\\\"\\\"SELECT COUNT(ID) FROM PARTICIPANT WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n total_participants = fetchoneClean(cur)[0]\\n\\n distance_matrix = calculate_square_form(distance, total_participants)\\n distArray = ssd.squareform(distance_matrix)\\n\\n try:\\n clusters = hierarchy.linkage(distArray, method='average')\\n except ValueError:\\n return {'message': 'not enough data'}\\n\\n tree = hierarchy.to_tree(clusters, rd=False)\\n # TODO Distance 0 on root\\n dendro = dict(children=[], hierarchy=0, distance=100)\\n add_node(tree, dendro, card_names)\\n\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS = %s WHERE STUDY_ID = %s\\\"\\\"\\\", (json.dumps(dendro), str(study_id),))\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CALCULATING = FALSE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n cur.execute(\\\"\\\"\\\"UPDATE STATS SET CLUSTERS_CHANGED = FALSE WHERE STUDY_ID = %s\\\"\\\"\\\", (str(study_id),))\\n conn.commit()\\n else:\\n dendro = study[6]\\n\\n return dendro\",\n \"def __call__(self, embeddings: np.ndarray) -> List[Optional[str]]:\\n assert self._centroids != {} # Centroids must be set in advance\\n \\n # Setup known database\\n cluster_ids, cluster_embs = zip(*self._centroids.items())\\n cluster_embs = np.vstack(cluster_embs)\\n \\n # Calculate similarity with cluster centroids\\n similarity = cosine_similarity(embeddings, cluster_embs)\\n \\n # Fetch the best-matching clusters\\n results = []\\n for i, idx in enumerate(similarity.argmax(axis=1)):\\n results.append(cluster_ids[idx] if similarity[i, idx] >= self._sim_thr else None)\\n return results\",\n \"def __find_nearest_centroids(self, data):\\n \\n self.clusters = np.array([]) \\n for i, d in enumerate(data):\\n min_dist = np.inf\\n self.clusters = np.concatenate((self.clusters, np.array([-1])))\\n for j, c in enumerate(self.centroids):\\n dist = self.__compute_distance(d, c)\\n if min_dist > dist:\\n min_dist = dist\\n self.clusters[i] = j\",\n \"def __get_cluster_centroid_distance(self, single_training: np.ndarray, cluster_center: np.ndarray) -> (int, float):\\n training_label, training_distance = None, float('inf')\\n # Check the distance of this point from all the cluster point.\\n # This training point belongs to a cluster, which ever cluster centroid have the lowest distance from this point\\n for cluster_label, single_cluster in enumerate(cluster_center):\\n # Distance from the this training point to this cluster centroid\\n this_distance = self.__get_distance(single_cluster, single_training)\\n if this_distance < training_distance:\\n training_label = cluster_label\\n training_distance = this_distance\\n return training_label, training_distance\",\n \"def kmeans_clustering(all_features, vocab_size, epsilon, max_iter):\\n\\n # Your code here. You should also change the return value.\\n\\n def _initiate_random_centroids(all_features, vocab_size):\\n \\\"\\\"\\\"\\n Initiate random centroids in the range of input\\n\\n :param all_features:\\n :param vocab_size:\\n :return:\\n \\\"\\\"\\\"\\n centroids = []\\n # 1) Genereate points for initial centroids\\n\\n min_feat = np.ones(all_features[0].size)*np.inf\\n max_feat = np.zeros(all_features[0].size)\\n\\n for a in all_features:\\n for p in range(len(a)):\\n if a[p] < min_feat[p]:\\n min_feat[p] = a[p]\\n else:\\n if a[p] > max_feat[p]:\\n max_feat[p] = a[p]\\n\\n\\n for _ in range(vocab_size):\\n random_vector = np.multiply(np.random.rand(1, all_features[0].size),\\n max_feat-min_feat) + min_feat\\n centroids.append(random_vector.flatten())\\n\\n return np.array(centroids)\\n\\n def _assign_vectors_to_nearest_centroid(all_features, centroid):\\n \\\"\\\"\\\"\\n Assign vectors to nearest centroids\\n\\n :param all_features:\\n :param centroid:\\n :return:\\n \\\"\\\"\\\"\\n #TODO: sprawdz co lepiej dziala\\n new_centroid_coor = np.zeros([len(centroid), all_features[0].size])\\n #new_centroid_coor = centroid\\n new_centroid_counter = np.zeros(len(centroid))\\n\\n dist = pdist(centroid, all_features)\\n #min_dist = dist.min(axis=0)\\n min_dist_index = dist.argmin(axis=0)\\n\\n for x in range(len(min_dist_index)):\\n id = min_dist_index[x]\\n new_centroid_coor[id] = np.add(new_centroid_coor[id],\\n all_features[x])\\n new_centroid_counter[id] += 1\\n\\n new_centroid_coor_out = []\\n for i in range(len(new_centroid_coor)):\\n if new_centroid_counter[i] == 0:\\n new_centroid_coor_out.append(centroid[i])\\n else:\\n new_centroid_coor_out.append(np.divide(new_centroid_coor[i],new_centroid_counter[i]))\\n\\n return np.array(new_centroid_coor_out), new_centroid_counter\\n\\n\\n def _check_convergence_condition(old_centroids, new_centroids, epsilon):\\n \\\"\\\"\\\"\\n Check convergence confition\\n\\n :param old_centroids:\\n :param new_centroids:\\n :param epsilon: if every centroid is moved by dist < epsilon KMeans terminates\\n :return:\\n \\\"\\\"\\\"\\n for i in range(len(old_centroids)):\\n dist = euclidean(old_centroids[i], new_centroids[i])\\n if dist > epsilon:\\n return False\\n\\n return True\\n\\n def delete_small_clusters(new_centroids, centroid_counter, threshold):\\n \\\"\\\"\\\"\\n Potential extension of the algorithm -> if there is not any point in the cluster, delete this cluste\\n\\n :param new_centroids:\\n :param centroid_counter:\\n :param threshold:\\n :return:\\n \\\"\\\"\\\"\\n\\n out_centroids = []\\n for n in range(len(new_centroids)):\\n if centroid_counter[n] > threshold:\\n out_centroids.append(new_centroids[n])\\n out_centroids = np.array(out_centroids)\\n return out_centroids\\n\\n #MAIN\\n old_centroids = _initiate_random_centroids(all_features, vocab_size)\\n\\n for _ in range(max_iter):\\n new_centroids, centroid_counter = _assign_vectors_to_nearest_centroid(all_features, old_centroids)\\n if_convergenced = _check_convergence_condition(new_centroids, old_centroids, epsilon)\\n\\n if if_convergenced == True:\\n # return centroids if algorithm is converged\\n # return delete_small_clusters(new_centroids, centroid_counter, 0)\\n return new_centroids\\n old_centroids = new_centroids\\n\\n # return centroids if reached max_iter\\n # return delete_small_clusters(new_centroids, centroid_counter, 0)\\n return new_centroids\"\n]"},"negative_scores":{"kind":"list like","value":["0.67511815","0.667103","0.65723747","0.6478668","0.62807804","0.6273955","0.622381","0.6105332","0.60754263","0.6067694","0.6046383","0.603666","0.60061574","0.59977764","0.5997736","0.59847236","0.5973263","0.5969204","0.5959918","0.59587914","0.59409744","0.5935671","0.59233385","0.5913697","0.5912067","0.5898303","0.5897077","0.5891139","0.58898133","0.58638555","0.5845367","0.5830787","0.5826753","0.58232653","0.58089817","0.58002794","0.579822","0.5798033","0.57907546","0.5788285","0.57841915","0.5735069","0.5728007","0.57186556","0.57140136","0.56801116","0.56733304","0.5672067","0.56673783","0.5662086","0.5661992","0.56618965","0.5655326","0.5648323","0.56384504","0.5634903","0.56336486","0.563165","0.5624158","0.56166404","0.5612015","0.560881","0.56073177","0.5601574","0.5595551","0.55879253","0.5585332","0.55839145","0.5571036","0.55707157","0.5567687","0.5547009","0.5536406","0.5533442","0.5532877","0.5526473","0.55253524","0.5522286","0.5520693","0.5517294","0.5515676","0.5511529","0.5509922","0.54956645","0.5489253","0.5488356","0.54664946","0.5451735","0.5450782","0.54491097","0.5447916","0.5445619","0.54417783","0.54321754","0.5424051","0.5421796","0.5419851","0.54151356","0.541286","0.5403115"],"string":"[\n \"0.67511815\",\n \"0.667103\",\n \"0.65723747\",\n \"0.6478668\",\n \"0.62807804\",\n \"0.6273955\",\n \"0.622381\",\n \"0.6105332\",\n \"0.60754263\",\n \"0.6067694\",\n \"0.6046383\",\n \"0.603666\",\n \"0.60061574\",\n \"0.59977764\",\n \"0.5997736\",\n \"0.59847236\",\n \"0.5973263\",\n \"0.5969204\",\n \"0.5959918\",\n \"0.59587914\",\n \"0.59409744\",\n \"0.5935671\",\n \"0.59233385\",\n \"0.5913697\",\n \"0.5912067\",\n \"0.5898303\",\n \"0.5897077\",\n \"0.5891139\",\n \"0.58898133\",\n \"0.58638555\",\n \"0.5845367\",\n \"0.5830787\",\n \"0.5826753\",\n \"0.58232653\",\n \"0.58089817\",\n \"0.58002794\",\n \"0.579822\",\n \"0.5798033\",\n \"0.57907546\",\n \"0.5788285\",\n \"0.57841915\",\n \"0.5735069\",\n \"0.5728007\",\n \"0.57186556\",\n \"0.57140136\",\n \"0.56801116\",\n \"0.56733304\",\n \"0.5672067\",\n \"0.56673783\",\n \"0.5662086\",\n \"0.5661992\",\n \"0.56618965\",\n \"0.5655326\",\n \"0.5648323\",\n \"0.56384504\",\n \"0.5634903\",\n \"0.56336486\",\n \"0.563165\",\n \"0.5624158\",\n \"0.56166404\",\n \"0.5612015\",\n \"0.560881\",\n \"0.56073177\",\n \"0.5601574\",\n \"0.5595551\",\n \"0.55879253\",\n \"0.5585332\",\n \"0.55839145\",\n \"0.5571036\",\n \"0.55707157\",\n \"0.5567687\",\n \"0.5547009\",\n \"0.5536406\",\n \"0.5533442\",\n \"0.5532877\",\n \"0.5526473\",\n \"0.55253524\",\n \"0.5522286\",\n \"0.5520693\",\n \"0.5517294\",\n \"0.5515676\",\n \"0.5511529\",\n \"0.5509922\",\n \"0.54956645\",\n \"0.5489253\",\n \"0.5488356\",\n \"0.54664946\",\n \"0.5451735\",\n \"0.5450782\",\n \"0.54491097\",\n \"0.5447916\",\n \"0.5445619\",\n \"0.54417783\",\n \"0.54321754\",\n \"0.5424051\",\n \"0.5421796\",\n \"0.5419851\",\n \"0.54151356\",\n \"0.541286\",\n \"0.5403115\"\n]"},"document_score":{"kind":"string","value":"0.66500586"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":8558,"cells":{"query":{"kind":"string","value":"Change the labels from arbitrary numbers to the range [0, len(set(labels))]. Points that are in the same cluster will stay in the same cluster. Points from different clusters will remain in different clusters."},"document":{"kind":"string","value":"def normalize_labels(labels):\n new_labels = np.array([-1] * len(labels))\n labels = np.array(labels)\n label_dict = dict()\n for i, label in enumerate(set(labels)):\n new_labels[np.where(labels == label)] = i\n label_dict[i] = label\n return label_dict, new_labels"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _relocate_clusters(self, cluster_labels):\n for cluster_label in range(self.k):\n if cluster_labels[cluster_label] is not None:\n # mean of the pixels assigned to cluster\n p_sum, p_count = np.asarray(\n cluster_labels[\n cluster_label\n ]).sum(axis=0), len(cluster_labels[cluster_label])\n self._clusters[cluster_label] = p_sum / p_count","def clean_labels(labels):\n\n llabels, slabels = list(labels), set(labels)\n \n for l in slabels:\n if llabels.count(l) <2 and l != max(slabels):\n llabels[llabels.index(l)] = l+1\n return clean_labels(llabels)\n elif llabels.count(l) <2 and l == max(slabels):\n llabels[llabels.index(l)] = l-1\n return clean_labels(llabels)\n else:\n return np.array(llabels)","def assign_labels_to_centroids(self):\n labelled_centroids = []\n for i in range(len(self.final_clusters)):\n labels = map(lambda x: x[0], self.final_clusters[i])\n # pick the most common label\n most_common = Counter(labels).most_common(1)[0][0]\n c = np.round(len([item for item in self.final_clusters[i] if item[0]==1])/len(self.final_clusters[i]),2)\n if c>=0.46:\n most_common = 1.0\n centroid = (most_common, self.final_centroids[i])\n labelled_centroids.append(centroid)\n\n self.labelled_centroids = labelled_centroids\n print(\"cluster_0: \", np.round(len([item for item in self.final_clusters[0] if item[0]==1])/len(self.final_clusters[0]),2), \"size_0: \", len(self.final_clusters[0]))\n print(\"cluster_1: \", np.round(len([item for item in self.final_clusters[1] if item[0]==1])/len(self.final_clusters[1]),2), \"size_1: \", len(self.final_clusters[1]))\n #print(\"cluster_2: \", np.round(len([item for item in self.final_clusters[2] if item[0]==1])/len(self.final_clusters[2]),2), \"size_2: \", len(self.final_clusters[2]))\n #print(\"cluster_3: \", np.round(len([item for item in self.final_clusters[3] if item[0]==1])/len(self.final_clusters[3]),2), \"size_2: \", len(self.final_clusters[3]))","def _relabel(labels, minval=0, bgval=None):\n\n labels = np.unique(labels, return_inverse=True)[-1] + minval\n if bgval is not None:\n labels[labels == minval] = bgval\n return labels","def change_labels(labels, cluster_name, idx_to_change, target_labels):\n assert(type(idx_to_change) == list)\n assert(type(target_labels) == list)\n assert(len(idx_to_change) == len(target_labels))\n\n sub_list = labels[labels == cluster_name]\n\n for idx, target in zip(idx_to_change, target_labels):\n sub_list[idx] = target\n\n labels[labels == cluster_name] = sub_list\n\n return labels","def separate_noise_labels_into_clusters(\n labels: np.ndarray, noise_label: int = -1\n) -> np.ndarray:\n new_labels = labels.copy()\n max_label = np.max(new_labels)\n j = max_label + 1\n for i in range(len(new_labels)):\n if new_labels[i] == noise_label:\n new_labels[i] = j\n j += 1\n return new_labels","def repair_labels(labels):\n ret = np.copy(labels)\n ret[:, 0] = 10 # overwrite length to be stop seq\n ret = np.roll(ret, -1, axis=1) # move first to last\n return ret","def _rename_clusters(self):\n all_clusters = []\n temp_clusters = self._clusters.copy()\n for clu in temp_clusters:\n all_clusters.append(self._clusters.pop(clu))\n idx = 0\n for clu in all_clusters:\n label = 'S' + str(idx)\n clu.rename(label)\n self._clusters[label] = clu\n idx += 1","def cluster_labels(kmeans,actual_labels):\r\n infered_label={}\r\n for i in range(kmeans.n_clusters):\r\n # Find Index of points in cluster\r\n labels = []\r\n index = np.where(kmeans.labels_ == i)\r\n \r\n #Append actual labels for each point\r\n labels.append(actual_labels[index])\r\n \r\n #Determine the most common label\r\n if len(labels[0])==1:\r\n counts=np.bincount(labels[0])\r\n else:\r\n counts=np.bincount(np.squeeze(labels))\r\n #Assign cluster to a value in the dictionary\r\n if np.argmax(counts) in infered_label:\r\n # append the new number to the existing array at this slot\r\n infered_label[np.argmax(counts)].append(i)\r\n else:\r\n # create a new array in this slot\r\n infered_label[np.argmax(counts)]=[i]\r\n return infered_label","def _calculate_nearest_cluster(self, pixels, cluster_labels):\n\n # assign pixel (RGB) to nearest cluster label (index)\n for index, rgb in pixels:\n rgb_vector = np.tile(rgb, (self.k, 1))\n self._labels[index] = np.argmin(\n self._euclid_distance(rgb_vector, self._clusters), axis=0)\n\n if cluster_labels[self._labels[index]] is None:\n cluster_labels[self._labels[index]] = list()\n\n cluster_labels[self._labels[index]].append(rgb)\n\n return cluster_labels","def anonymize(labels, unique_ordered_labels):\n index_dict = dict((val, idx) for idx, val in enumerate(unique_ordered_labels))\n return [index_dict[x] for x in labels]","def normalize_labels(labels):\n number_of_labels = len(labels)\n number_of_species = get_number_of_species()\n labels_norm = np.zeros(shape=(number_of_labels, number_of_species))\n for i in range(number_of_labels):\n for label in labels[i]:\n labels_norm[i][label] = 1\n return labels_norm","def updateClusterInfo(self):\n self.nPoints = len(self.labels)\n self.n = len(np.unique(self.labels))\n self.centers = [ [0.0 for j in range(3)] for i in range(self.n)]","def _relabel(self, a):\n\n labels = list(np.unique(a))\n if 0 in labels:\n labels.remove(0)\n\n if len(labels) == 0:\n return a.copy()\n old_values = np.asarray(labels)\n new_values = np.arange(1, len(labels) + 1, dtype=old_values.dtype)\n\n try:\n values_map = np.arange(int(a.max() + 1), dtype=new_values.dtype)\n except ValueError as e:\n raise ValueError(f\"{e}, arange length: {int(a.max() + 1)}\")\n values_map[old_values] = new_values\n\n return values_map[a.copy()]","def rename_labels_by_count(labels):\n new_labels, label_counts = _count_labels(labels)\n\n return new_labels","def cluster_assign(images_lists, dataset):\n assert images_lists is not None\n pseudolabels = []\n image_indexes = []\n for cluster, images in enumerate(images_lists):\n image_indexes.extend(images)\n pseudolabels.extend([cluster] * len(images))\n print(image_indexes)\n print(pseudolabels)\n \n normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],\n std=[0.229, 0.224, 0.225])\n t = transforms.Compose([transforms.RandomResizedCrop(224),\n transforms.RandomHorizontalFlip(),\n transforms.ToTensor(),\n normalize])\n\n return ReassignedDataset(image_indexes, pseudolabels, dataset, t)","def process_label(self, foreground_labels):\n # Find the unique (nonnegative) foreground_labels, map them to {0, ..., K-1}\n unique_nonnegative_indices = np.unique(foreground_labels)\n mapped_labels = foreground_labels.copy()\n for k in range(unique_nonnegative_indices.shape[0]):\n mapped_labels[foreground_labels == unique_nonnegative_indices[k]] = k\n foreground_labels = mapped_labels\n return foreground_labels","def setLabels(self, labels: List[Shape]):\n self.labels = labels\n self.update()","def cluster_to_voxel_label(clusts: nb.types.List(nb.int64[:]),\n node_label: nb.int64[:]) -> nb.int64[:]:\n nvoxels = np.sum([len(c) for c in clusts])\n vlabel = np.empty(nvoxels, dtype=np.int64)\n stptr = 0\n for i, c in enumerate(clusts):\n endptr = stptr + len(c)\n vlabel[stptr:endptr] = node_label[i]\n stptr = endptr\n\n return vlabel","def labels(self, labels: MutableMapping[str, str]):\n self._labels = labels","def consolidate_labels(labels):\n return map(RNN_model.consolidate_label , labels)","def classify_k_cluster(labels, datas):\n classify_k_cluster_to_redis(labels=labels, texts=datas)","def _remove_and_relabel_blobs(labeled, wanted_blobs):\n labeled = labeled.copy()\n wanted_blobs = np.array(wanted_blobs)\n no_blobs = len(wanted_blobs)\n unwanted_blobs = np.arange(1, no_blobs+1)[np.logical_not(wanted_blobs)]\n wanted_blobs = np.arange(1, no_blobs+1)[wanted_blobs]\n\n for unwanted_blob in unwanted_blobs:\n labeled[labeled == unwanted_blob] = 0\n\n for new_label, wanted_blob in enumerate(wanted_blobs):\n new_label += 1\n labeled[labeled == wanted_blob] = -new_label\n\n return -labeled","def change_class_labels(classes):\n u,indices=np.unique(classes,return_inverse=True)\n return u,indices","def move_centroids(self, labelled_clusters):\n new_centroids = []\n # print(\"Cluster size\", end=\"\\t\")\n for cluster in labelled_clusters:\n new_centroids.append(self.mean_cluster(cluster))\n # print(len(cluster), end=\"\\t\" )\n # print(\"\\n\")\n return new_centroids","def regroup_dataset(labels):\r\n batch_y = labels.copy()\r\n for i, label in enumerate(labels):\r\n if label in [0, 15, 19]:\r\n batch_y[i]=0\r\n if label in [1, 2, 3, 4, 5,]:\r\n batch_y[i]=1\r\n if label in [6]:\r\n batch_y[i]=2\r\n if label in [7,8,9,10]:\r\n batch_y[i]=3\r\n if label in [11,12,13,14]:\r\n batch_y[i]=4\r\n if label in [16,17,18]:\r\n batch_y[i]=5\r\n \r\n print('regrouped label', batch_y.shape)\r\n return batch_y","def assignLabels(self):\n clusters = np.arange(0, len(self.V))[self.V < self.V1] #indexes self.V, volumes_sorted, and oldOrder\n self.clusterV = self.volumes_sorted[clusters]\n clusters = self.oldOrder[clusters] #indexes volumes\n self.clusters = self.nonBI[clusters] #indexes self.vor and self.data\n self.easyLabel = np.zeros(len(self.data))\n self.easyLabel[self.clusters] = 1\n print('Out of ' + str(len(self.data)) + ' particles, ' + str(len(self.clusters)) + ' (' + str(round(len(self.clusters)*100/len(self.data), 3)) +' %) are labelled as cluster particles.')","def labels(self, labels):\n self._labels = labels","def get_cluster_elements_labels(self):\n \n copy = deepcopy(self.cluster_elements_labels)\n return copy","def get_cluster_to_label_mapping_safe(y, y_pred, n_classes, n_clusters, toprint=True):\n one_hot_encoded = np_utils.to_categorical(y, n_classes)\n\n cluster_to_label_mapping = []\n n_assigned_list = []\n majority_class_fractions = []\n majority_class_pred = np.zeros(y.shape)\n for cluster in range(n_clusters):\n cluster_indices = np.where(y_pred == cluster)[0]\n n_assigned_examples = cluster_indices.shape[0]\n n_assigned_list.append(n_assigned_examples)\n cluster_labels = one_hot_encoded[cluster_indices]\n cluster_label_fractions = np.mean(cluster_labels, axis=0)\n majority_cluster_class = np.argmax(cluster_label_fractions)\n cluster_to_label_mapping.append(majority_cluster_class)\n majority_class_pred[cluster_indices] += majority_cluster_class\n majority_class_fractions.append(cluster_label_fractions[majority_cluster_class])\n if toprint:\n print(cluster, n_assigned_examples, majority_cluster_class, cluster_label_fractions[majority_cluster_class])\n #print(cluster_to_label_mapping)\n if toprint:\n print(np.unique(y), np.unique(cluster_to_label_mapping))\n try:\n # make sure there is at least 1 cluster representing each class\n assert np.all(np.unique(y) == np.unique(cluster_to_label_mapping))\n except AssertionError:\n # if there is no cluster for a class then we will assign a cluster to that\n # class\n \n # find which class it is\n # ASSUMPTION - this task is binary\n \n diff = list(set(np.unique(y)) - set(np.unique(cluster_to_label_mapping)))[0]\n # we choose the cluster that contains the most examples of the class with no cluster\n \n one_hot = np_utils.to_categorical(y_pred[np.where(y==diff)[0]], \\\n len(cluster_to_label_mapping))\n \n cluster_to_label_mapping[np.argmax(np.sum(one_hot, axis=0))] = int(diff)\n if toprint:\n print(cluster_to_label_mapping)\n return cluster_to_label_mapping, n_assigned_list, majority_class_fractions","def consolidate_labels(labels):\n return list(map(RNNOIE_model.consolidate_label , labels))","def set_labels(self, new_labels=None):\n self.labels = new_labels","def mask_labels(labels):\n def do_one_row(row):\n erase = False\n for i, _ in enumerate(row):\n if erase:\n row[i] = 0\n else:\n if row[i] == 10:\n erase = True\n row[i] = 1\n return row\n\n ret = np.copy(labels)\n return np.apply_along_axis(do_one_row, axis=1, arr=ret)","def recluster(dataList, labelConverter, clusterSeedList, eps, minPts):\n # print(\"starting reclustering\")\n for pt in dataList:\n pt.isVisited = False\n\n # Expand existing clusters from the seed pt.\n for seed in clusterSeedList:\n if labelConverter[seed.label] == -1:\n continue\n seed.isVisited = True\n neighborhood = findNeighbor(seed, dataList, eps)\n # Cluster is expanded iff neighbor's label is same as seed's label,\n # or label is extra cluster.(x.label != -1 and labelConverter[x.label] == -1)\n neighborhood = [x for x in neighborhood\n if (x.label != -1 and labelConverter[x.label] == -1) or x.label == seed.label]\n idx = -1\n while (idx < len(neighborhood) - 1):\n idx += 1\n if (neighborhood[idx].isVisited):\n continue\n neighborhood[idx].isVisited = True\n nextNeighbor = findNeighbor(neighborhood[idx], dataList, eps)\n nextNeighbor = [x for x in nextNeighbor\n if (x.label != -1 and labelConverter[x.label] == -1) or x.label == seed.label]\n neighborhood = neighborhood \\\n + [x for x in nextNeighbor if x not in neighborhood and not x.isVisited]\n if (labelConverter[neighborhood[idx].label] == -1):\n # print(str(neighborhood[idx].id) + \" changed to \" + str(seed.label))\n neighborhood[idx].label = seed.label","def createSetsFromLabels(self):\n \n self.tots = [0]*self.n\n for i in range(self.n):\n self.sets.append([])\n for i in range(self.nPoints):\n self.sets[self.labels[i]].append(i)\n self.tots[self.labels[i]] += 1","def relabel_labelmask(labelmask, preserve_order=True):\n mask = np.copy(labelmask)\n # Get all object labels and their counts.\n labels, counts = np.unique(mask, return_counts=True)\n # Get the indexes of sorted counts, descending.\n ordered_indexes = np.argsort(counts)[::-1]\n # Set largest object as background (ID=0).\n background_label = labels[ordered_indexes[0]]\n mask[mask == background_label] = 0\n # Renumber the rest of the objects 1..n.\n obj_num=1\n if (preserve_order):\n oldlabels = labels\n else:\n oldlabels = labels[ordered_indexes]\n for old_label in oldlabels:\n if (old_label != background_label):\n mask[labelmask == old_label] = obj_num\n obj_num = obj_num + 1\n return mask","def setCSLabels(self, labels):\n\n if isinstance(labels, list):\n if len(labels) == self._n_csets:\n if all((lbl is None or isinstance(lbl, str))\n for lbl in labels):\n self._cslabels = list(labels)\n else:\n raise ValueError('all items of labels must be strings')\n else:\n raise ValueError('length of labels must be equal to the '\n 'number of coordinate sets')\n else:\n raise TypeError('labels must be a list')","def truncate_labels(labels):\n def do_one_row(row):\n erase = False\n for i, _ in enumerate(row):\n if erase:\n row[i] = -1\n else:\n if row[i] == 10:\n erase = True\n return row\n\n ret = np.copy(labels)\n ret = repair_labels(ret)\n return np.apply_along_axis(do_one_row, axis=1, arr=ret)","def labels(self, labels):\n\n self._labels = labels","def labels(self, labels):\n\n self._labels = labels","def labels(self, labels):\n\n self._labels = labels","def labels(self, labels):\n\n self._labels = labels","def labels(self, labels):\n\n self._labels = labels","def convertLabels(self, labels):\n counter = 0\n numericLabels = []\n for label in labels:\n if label not in self.labelDict:\n self.labelDict[label] = counter\n self.backwards_conversion[counter] = label\n counter += 1\n numericLabels += [self.labelDict[label]]\n return np.array(numericLabels)","def classify_clusters_sk(cloud: object, labels: np.ndarray) -> list:\n \"\"\"\n indices = list(dict.fromkeys(labels))\n if (-1 in indices):\n indices.remove(-1)\n clusters = [[] for i in indices]\n for (i, point) in enumerate(cloud, start=0):\n if (labels[i] != -1):\n clusters[labels[i]].append(point) \n return (clusters, indices)\n \"\"\"\n indices = list(dict.fromkeys(labels))\n if (-1 in indices):\n indices.remove(-1)\n clusters = []\n for i in indices:\n clusters.append([])\n for (idx, point) in enumerate(cloud, start=0):\n label = labels[idx]\n if (label != -1):\n clusters[label].append(point)\n for el in clusters:\n el = np.vstack(el)\n radar_clusters = [Cluster(np.asarray(el), sensor='radar') for el in clusters]\n return (radar_clusters, indices)","def update_labels(self, nidxs, y):\n\n y = np.array(y, dtype=bool)\n for n, yi in zip(nidxs, y):\n self.node_labels[n] = [self.labels[i] for i, j in enumerate(yi) if j]\n\n return self","def set_label(self, labels_set=None):\n for pos in labels_set:\n self._q_bnn_circ.x(self.outputs[int(pos)])","def infer_data_labels(X_labels, cluster_labels):\r\n #Empty array of len(X)\r\n predicted_labels = np.zeros(len(X_labels)).astype(np.uint8)\r\n \r\n for i, cluster in enumerate(X_labels):\r\n for key, value in cluster_labels.items():\r\n if cluster in value:\r\n predicted_labels[i] = key\r\n \r\n return predicted_labels","def rectifyClusteringLabels( labels, rectificationWidth=5):\r\n\r\n\tfor l in range( len(labels) - rectificationWidth):\r\n\t\tfirstLabelIndex = l\r\n\t\tmedianLabelIndex = l + ( rectificationWidth//2)\r\n\t\tlastLabelIndex = l + rectificationWidth -1\r\n\t\tfirstLabel = labels[firstLabelIndex]\r\n\t\tmedianLabel = labels[ medianLabelIndex]\r\n\t\tlastLabel = labels[lastLabelIndex]\r\n\t\tleftLabels = labels[firstLabelIndex +1 : medianLabelIndex]\r\n\t\trightLabels = labels[ medianLabelIndex +1 : lastLabelIndex]\r\n\t\tif medianLabel != firstLabel and medianLabel != lastLabel:\r\n\t\t\tfor label in leftLabels:\r\n\t\t\t\tif label != firstLabel: continue\r\n\t\t\tfor label in rightLabels:\r\n\t\t\t\tif label != lastLabel: continue\r\n\t\t\tlabels[medianLabelIndex] = labels[medianLabelIndex - 1]\r\n\treturn labels","def labels(self, points):\n\n assert(self.final_clusters is not None)\n\n labels = np.array([self.classify_point(point) for point in points])\n \n return labels","def change_class_labels_back(classes,given):\n classes=np.asarray(classes)\n classes_new=np.zeros(classes.shape,dtype=object)\n for i in range(len(given)):\n classes_new[classes==i]=given[i]\n return classes_new","def flip_random_labels(labels, percent):\n\n assert percent <= 1.0 and percent >= 0.0\n \n num_labels = len(labels)\n indices = np.random.permutation(num_labels)[:int(num_labels * percent)]\n labels[indices] = -labels[indices]\n return labels","def reformat_labels(label, bin_limits=[2]):\n# num_labels = y_batch.max() + 1\n label = np.array([label], dtype=np.float32)\n num_labels = 2\n label = np.digitize(label, bins=[2])\n label = (np.arange(num_labels) == label[:, None]).astype(np.float32)[0]\n return label","def initClusters(self):\n if len(self.labelList) != len(self.pointList):\n \traise ValueError(\"Label List and Point List not the same length!\")\n for i in range(len(self.labelList)):\n self.centroids[self.labelList[i]] = self.pointList[i]\n self.pointcounts[self.labelList[i]] = 1","def propagate_labels_simple(regions,labels):\n rlabels,_ = label(regions)\n cors = correspondences(rlabels,labels,False)\n outputs = zeros(amax(rlabels)+1,'i')\n for o,i in cors.T: outputs[o] = i\n outputs[0] = 0\n return outputs[rlabels]","def update_plot_clusters(cluster_handles, data_points, cluster_ids):\n for handle, cluster_id in zip(cluster_handles, np.unique(cluster_ids)):\n loc = cluster_id == cluster_ids\n handle.set_data(data_points[loc, 0], data_points[loc, 1])","def ConfigureCluster(messages, args, cluster):\n cluster.labels = labels_util.ParseCreateArgs(args,\n messages.Cluster.LabelsValue)","def form_clusters(self, labelled_data, unlabelled_centroids):\n # enumerate because centroids are arrays which are unhashable,\n centroids_indices = range(len(unlabelled_centroids))\n # initialize an empty list for each centroid. The list will contain\n # all the datapoints that are closer to that centroid than to any other.\n # That list is the cluster of that centroid.\n clusters = {c: [] for c in centroids_indices}\n \n for (label, Xi) in labelled_data:\n # for each datapoint, pick the closest centroid.\n smallest_distance = float(\"inf\")\n for cj_index in centroids_indices:\n cj = unlabelled_centroids[cj_index]\n distance = np.linalg.norm(Xi - cj)\n if distance < smallest_distance:\n closest_centroid_index = cj_index\n smallest_distance = distance\n # allocate that datapoint to the cluster of that centroid.\n clusters[closest_centroid_index].append((label,Xi))\n return list(clusters.values())","def deletemessageslabels(self, uidlist, labels):\n\n labels = labels - self.ignorelabels\n result = self._messagelabels_aux('-X-GM-LABELS', uidlist, labels)\n if result:\n for uid in uidlist:\n self.messagelist[uid]['labels'] = self.messagelist[uid]['labels'] - labels","def cfilter(centers, labels, t=5, position_likes=None, labels_likes=None):\n if position_likes is None:\n position_likes = []\n \n if labels_likes is None:\n labels_likes = []\n \n # backup the labels and the clusters\n centers, labels = deepcopy(centers), deepcopy(labels)\n unique_labels = np.unique(labels)\n \n # Create lists for each cluster contaning the related nodes\n components = []\n node_labels = [None for _ in range(len(labels))]\n \n for label in np.sort(unique_labels):\n component = np.argwhere(label == labels).T\n assert len(component) == 1\n\n for node in component[0]:\n node_labels[node] = label\n\n components.append(component[0].tolist())\n \n # Find the cluster indices of the to small clusters\n removal = []\n for idx, component in enumerate(components):\n if len(component) < t:\n removal.append(idx)\n \n # delete the too small centers\n new_centers = np.delete(centers, removal)\n \n # remove the old labels from the labels array\n position_removal = []\n labels_np = np.array(labels)\n \n for label in removal:\n position_removal += np.argwhere(label==labels_np).T[0].tolist()\n \n new_labels = np.delete(labels, position_removal)\n \n \n # adjust the position arrays\n new_position_likes = []\n for pos_like in position_likes:\n new_position_likes.append(np.delete(pos_like, position_removal, axis=0))\n \n # adjust the labels arrays\n new_labels_likes = []\n for lab_like in labels_likes:\n new_labels_likes.append(np.delete(lab_like, position_removal))\n \n \n # remove te gaps in the labels array (They sholud be the indices of the clusters array...):\n difference = [0 for i in range(len(unique_labels))]\n last_difference = 0\n \n for label in np.sort(unique_labels):\n if label in removal:\n last_difference += 1\n \n difference[label] = last_difference\n \n for idx, label in enumerate(new_labels):\n new_labels[idx] -= difference[label]\n \n \n # adjust the cluster centers to the fact, that the position array changed (they are the indices of it...): \n pos_difference = [0 for i in range(len(labels))]\n last_difference = 0\n \n for idx in range(len(labels)):\n if idx in position_removal:\n last_difference += 1\n \n \n pos_difference[idx] = last_difference\n \n for idx, center in enumerate(new_centers):\n new_centers[idx] -= pos_difference[center]\n \n \n \n # Adjust the output to the input\n if len(new_position_likes) != 0:\n if len(new_labels_likes) != 0:\n return new_centers, new_labels, new_position_likes, new_labels_likes\n \n else:\n return new_centers, new_labels, new_position_likes\n \n elif len(new_labels_likes) != 0:\n return new_centers, new_labels, new_labels_likes\n \n return new_centers, new_labels","def _alter(self, label):\n altered = np.full(self.n, -1)\n altered[np.where(self.y_train == label)] = +1\n return altered","def reassign_noise(labels: np.ndarray, mask):\n ret = labels.copy()\n ret[mask] = np.arange(np.sum(mask)) + np.max(ret) + 1\n return ret","def prepare_labels(labels, class_mask):\n mask = [1 if elt else -1 for elt in class_mask]\n mask = np.array(mask)\n return labels.dot(mask)","def update_pivot_labels(l, maxn):\n tmp = maxn+1\n tmps = []\n for i in range(0, len(l)):\n if l[i] > MAX_NODES-1 or l[i] in tmps:\n l[i] = tmp\n tmp += 1\n tmps.append(l[i])\n return l","def assign_labels(self, data):\n data[self.label] = self.labeler(data.index.values)","def transform_labels(self, labels):\n # Fallback:\n # return self.encoder.transform(labels)\n classes = list(self.classes_())\n return [classes.index(label) for label in labels]","def transform_labels(self, labels):\n # Fallback:\n # return self.encoder.transform(labels)\n classes = list(self.classes_())\n return [classes.index(label) for label in labels]","def replace_image_point_labels(image, labels):\n img = image.copy()\n for label, point in labels:\n row, col = point\n # Find the existing label at the point\n index = img[int(row), int(col)]\n # Replace the existing label with new, excluding background\n if index > 0:\n img[img == index] = label\n\n return img","def associate_clusters(self, labels_1, labels_2):\n if not torch.is_tensor(labels_1):\n labels_1 = torch.cat(labels_1).cuda()\n\n if not torch.is_tensor(labels_2):\n labels_2 = torch.cat(labels_2).cuda()\n\n assert labels_1.shape == labels_2.shape, \"Shape mismatch: {}, {}\".format(labels_1.shape, labels_2.shape)\n\n # do not associate the outlier ID with anything\n unique_labels_1 = list(set(labels_1.unique().tolist()) - {self.OUTLIER_LABEL})\n unique_labels_2 = list(set(labels_2.unique().tolist()) - {self.OUTLIER_LABEL})\n\n assert not set(unique_labels_1).intersection(set(unique_labels_2)), \\\n \"Labels overlap: {}, {}\".format(unique_labels_1, unique_labels_2)\n\n association_costs = np.zeros((len(unique_labels_1), len(unique_labels_2)), np.float32)\n recall_12 = np.zeros((len(unique_labels_1), len(unique_labels_2)), np.float32)\n\n # iterate over pairs of labels\n for i1, i2 in [(i1, i2) for i1 in range(len(unique_labels_1)) for i2 in range(len(unique_labels_2))]:\n l1, l2 = unique_labels_1[i1], unique_labels_2[i2]\n l1_active_pts = labels_1 == l1\n l2_active_pts = labels_2 == l2\n\n intersection = (l1_active_pts & l2_active_pts).float().sum()\n union = (l1_active_pts | l2_active_pts).float().sum()\n iou = intersection / union\n\n # print(\"IoU ({}, {}) = {}\".format(l1, l2, iou.item()))\n association_costs[i1, i2] = 1. - iou.item()\n recall_12[i1, i2] = intersection / l1_active_pts.sum(dtype=torch.float32)\n\n idxes_1, idxes_2 = linear_sum_assignment(association_costs)\n\n associations = []\n unassigned_labels_1 = set(unique_labels_1)\n unassigned_labels_2 = set(unique_labels_2)\n\n for i1, i2 in zip(idxes_1, idxes_2):\n l1, l2 = unique_labels_1[i1], unique_labels_2[i2]\n associations.append((l1, l2))\n unassigned_labels_1.remove(l1)\n unassigned_labels_2.remove(l2)\n\n return associations, unassigned_labels_1, unassigned_labels_2, association_costs[idxes_1, idxes_2], \\\n (recall_12, unique_labels_1, unique_labels_2)","def class2color(self, labels, clean_up_clusters=0, mode=None):\n clean_up_clusters *= clean_up_clusters # create an area\n colored_labels = np.zeros(labels.shape[:2] + (3,)).astype(np.uint8)\n labels = np.squeeze(labels)\n if clean_up_clusters > 0:\n labels = DropClusters.drop(labels, min_size=clean_up_clusters)\n ys, xs = np.where(labels)\n colored_labels[ys, xs, :] = self.label_color\n return colored_labels","def _remove_duplicates(labels):\n to_delete = []\n for i in range(len(labels)):\n for j in range(i + 1, len(labels)):\n if intersection_ratio(labels[i], labels[j]) >= 0.5:\n to_delete.append(j)\n to_delete = np.unique(np.array(to_delete))\n return np.delete(labels, to_delete, 0)","def _merge_clusters(self, cl1, cl2):\n label = ''\n to_delete = ''\n if cl1 < cl2:\n label = cl1\n to_delete = cl2\n else:\n label = cl2\n to_delete = cl1\n to_keep = self.get_cluster(label)\n to_remove = self._clusters.pop(to_delete)\n to_keep.merge(to_remove)","def add_label_to_unique_species_labels(self, label: str) -> str:\n unique_label, i = label, 0\n while unique_label in self.unique_species_labels:\n unique_label = f'{label}_{i}'\n i += 1\n self.unique_species_labels.append(unique_label)\n return unique_label","def label_centroids_heuristically(self, centroids: np.ndarray):\n\n cluster_centroids_labels = [(\"\", {}) for c in centroids]\n\n centre_point = centroids[0]\n heuristic_centroids = np.array(\n [\n centre_point + [-30, 30],\n centre_point + [30, 30],\n centre_point + [0, -48.125],\n ]\n )\n heuristic_centroid_labels = [\n ConstJoint.LEFT_EYE,\n ConstJoint.RIGHT_EYE,\n ConstJoint.MOUTH,\n ]\n labeled = [False for c in centroids]\n used_label = [False for c in heuristic_centroids]\n while self.__are_labels_matched_with_centroids(cluster_centroids_labels, \"\"):\n min_dist_square = math.inf\n min_centroid = 0\n min_cluster = 0\n current_cluster = {}\n for i, c in enumerate(centroids):\n if labeled[i]:\n continue\n for j, cl in enumerate(heuristic_centroids):\n if used_label[j]:\n continue\n diff = c - cl\n dist_square = diff.dot(diff)\n\n if dist_square < min_dist_square:\n min_centroid = i\n current_cluster = c\n min_cluster = j\n min_dist_square = dist_square\n\n cluster_centroids_labels[min_centroid] = (\n heuristic_centroid_labels[min_cluster],\n current_cluster,\n )\n labeled[min_centroid] = True\n used_label[min_cluster] = True\n\n return cluster_centroids_labels","def assign_labels_to_longer_segs(self, uniq_id, base_scale_clus_label):\n per_scale_clus_label = []\n self.scale_n = len(self.multiscale_timestamp_dict[uniq_id]['scale_dict'])\n uniq_scale_mapping = get_scale_mapping_list(self.multiscale_timestamp_dict[uniq_id])\n for scale_index in range(self.scale_n):\n new_clus_label = []\n scale_seq_len = len(self.multiscale_timestamp_dict[uniq_id][\"scale_dict\"][scale_index][\"time_stamps\"])\n for seg_idx in range(scale_seq_len):\n if seg_idx in uniq_scale_mapping[scale_index]:\n seg_clus_label = mode(base_scale_clus_label[uniq_scale_mapping[scale_index] == seg_idx])\n else:\n seg_clus_label = 0 if len(new_clus_label) == 0 else new_clus_label[-1]\n new_clus_label.append(seg_clus_label)\n per_scale_clus_label.extend(new_clus_label)\n per_scale_clus_label = torch.tensor(per_scale_clus_label)\n return per_scale_clus_label, uniq_scale_mapping","def normalize_label(labels):\n max_val = torch.max(labels)\n min_val = torch.min(labels)\n norm_labels = (labels - min_val)/(max_val - min_val)\n return norm_labels","def map_clusters(labels, rows):\r\n counts = Counter(labels)\r\n mappings = {c + 1: ((counts[c] / rows) * 100) for c in sorted(counts)}\r\n\r\n return mappings","def AddLabelsFromString(self, labels):\n if self.labels is None:\n self.labels = set()\n\n self.labels = self.labels.union([x.strip() for x in labels.split(',')])","def propagate_labels(image,labels,conflict=0):\n rlabels,_ = label(image)\n cors = correspondences(rlabels,labels,False)\n outputs = zeros(amax(rlabels)+1,'i')\n oops = -(1<<30)\n for o,i in cors.T:\n if outputs[o]!=0: outputs[o] = oops\n else: outputs[o] = i\n outputs[outputs==oops] = conflict\n outputs[0] = 0\n return outputs[rlabels]","def apply_remap_values(labels: np.ndarray, label_map: Dict[int, int]) -> np.ndarray:\n for l1, l2 in label_map.items():\n labels[labels == l1] = l2","def clustering_by_label(instances, label, meta_dataset, logger):\n clusters = []\n impurities = {\n item[0]: item[1]\n for item in meta_dataset.items() if item[0] != label}\n impurities = list(itertools.chain(*impurities.values()))\n\n while instances:\n # List is not empty\n cluster = gift_wrapping(instances, impurities, logger)\n\n found = cluster['dimension'] < len(cluster['vertices'])\n _dataset = []\n vertices = []\n points = []\n for vertex in instances:\n if vertex in cluster['vertices']:\n vertices.append(vertex)\n else:\n if found and check_inside_hull(cluster['faces'], vertex):\n points.append(vertex)\n else:\n _dataset.append(vertex)\n\n if found:\n volume = round(calculate_volume(cluster['faces']), 15)\n elif len(cluster['faces'][0]) > 1:\n volume = round(numpy.exp(squared_area(cluster['faces'][0])), 15)\n else:\n volume = 0.0\n\n instances = _dataset\n clusters.append({'vertices': vertices,\n 'points': points,\n 'size': len(vertices) + len(points),\n 'volume': volume})\n\n logger.info(\n 'Clustering: %d clusters found, '\n '%d/%d instance processed for label %r',\n len(clusters), len(meta_dataset[label]) - len(instances),\n len(impurities) + len(meta_dataset[label]), label)\n\n return clusters","def convert_labels_to_int(labels): \n if not len(labels):\n raise ValueError(\"Nothing to convert!\")\n\n if isinstance(labels[0], basestring) or isinstance(labels[0], int):\n label_legend = list(set(labels))\n converted_labels = [ label_legend.index(l) for l in labels ]\n elif is_iterable(labels[0]): # Multiple labels, handle each one individually\n num_labels = len(labels[0])\n label_legend = []\n converted_labels = []\n \n # Get the unique sets of labels for each index\n for i in xrange(num_labels):\n temp_labels = [l[i] for l in labels]\n label_legend.append(list(set(temp_labels)))\n\n # Apply mapping to each label\n for label in labels:\n converted_label = [ leg.index(l) for leg, l in \n zip(label_legend, label) ]\n converted_labels.append(converted_label)\n else: # Not a string/int, not a list... hmmm\n raise ValueError('Unexpected label type!')\n\n return label_legend, array(converted_labels)","def get_partition_from_labels(self, labels):\n partition = defaultdict(list)\n for ind, label in enumerate(labels):\n partition[label].append(ind)\n self.clean_partition(partition)\n return partition","def spread_labels(labels,maxdist=9999999):\n #distances,features = morphology.distance_transform_edt(labels==0,return_distances=1,return_indices=1)\n #indexes = features[0]*labels.shape[1]+features[1]\n #spread = labels.ravel()[indexes.ravel()].reshape(*labels.shape)\n if not labels.any():\n return labels\n distances,indexes = cv2.distanceTransformWithLabels(array(labels==0,uint8),cv2.DIST_L2,cv2.DIST_MASK_PRECISE,labelType=cv2.DIST_LABEL_PIXEL)\n spread = labels[where(labels>0)][indexes-1]\n if maxdist is None:\n return spread, distances\n spread *= (distances0)\n\t\t\t\tself.bool_train_unlabelled=(self.train_labels___0_unlab__neg1_exclud==0)\n\t\t\t\tself.bool_train_excluded=(self.train_labels___0_unlab__neg1_exclud<0)\n\t\t\t\tself.num_train_labelled=sum(self.bool_train_labelled)\n\t\t\t\tself.num_train_unlabelled=sum(self.bool_train_unlabelled)\n\t\t\t\tself.num_train_excluded=sum(self.bool_train_excluded)","def _labels_to_ordinals(self, labels, mask):\n one_to_n = tf.range(1, self._ordinal_size + 1, dtype=tf.float32)\n unsqueezed = tf.repeat(\n tf.expand_dims(labels, axis=2), self._ordinal_size, axis=-1)\n ordinals = tf.where(unsqueezed >= one_to_n, tf.ones_like(unsqueezed), 0.0)\n if self._use_fraction_label:\n fractions = unsqueezed - one_to_n + 1.0\n fractions = tf.where(\n tf.logical_and(fractions > 0.0, fractions < 1.0), fractions, 0.0)\n ordinals += fractions\n return tf.where(tf.expand_dims(mask, axis=-1), ordinals, 0.0)","def from_labels_map(cls, labels_map):\n mask_index = cls()\n for index, value in iteritems(labels_map):\n mask_index[index] = CategoricalAttribute(\"label\", value)\n\n return mask_index","def undo_uniform_list_length(labels):\n for label in labels:\n while \" \" in label:\n label.remove(\" \")\n return labels","def make_fixed_labels(self):\n fixed_labels = []\n for dim in range(self.opt.c_dim):\n t = [0] * self.opt.c_dim\n t[dim] = 1\n t = torch.FloatTensor(t).expand([self.opt.batch_size, self.opt.c_dim])\n fixed_labels.append(t)\n return fixed_labels","def labels_to_scores(labels):\n device = sp.get_device(labels)\n xp = device.xp\n with device:\n num_classes = labels.max() + 1\n scores = xp.zeros([len(labels), num_classes], dtype=np.float32)\n scores[xp.arange(len(labels)), labels] = 1\n\n return scores","def getLabel(labels):\r\n elems = {}\r\n for l in labels:\r\n if l not in elems.keys():\r\n elems[l] = 1\r\n else:\r\n elems[l] += 1\r\n counts = sorted(elems.values(), reverse=True)\r\n if len(counts) > 1 and counts[0] == counts[1]:\r\n return choice(list(elems.keys()))\r\n return sorted(elems, key=elems.get, reverse=True)[0]","def change_class_labels_to_given(classes,given):\n classes=np.asarray(classes)\n classes_new=np.zeros(classes.shape,dtype=object)\n for i in given:\n classes_new[classes==i]=given[i]\n return classes_new","def fix_label_names():\n\n assert trace.cpu.trace_done\n binary_addr = memorymanager.BinaryAddr(0)\n while binary_addr < len(classifications):\n c = classifications[binary_addr]\n if c is not None:\n dummy = [str(x) for x in c.as_string_list(binary_addr, None)]\n binary_addr += c.length()\n else:\n binary_addr += 1","def _empty_clusters(clusters):\n for clst in clusters:\n clst.points = []","def inlabel_shuffle(data):\n num_zero_data = np.sum(data[:,-1]==0)\n label_zero_data = data[:num_zero_data,:]\n label_one_data = data[num_zero_data:,:]\n np.random.shuffle(label_zero_data)\n np.random.shuffle(label_one_data)\n return data","def relabeled(self, memo=None, labels=None):\n from copy import deepcopy\n\n self._deepcopy_relabel_ = True\n self._deepcopy_labels_ = labels\n new = deepcopy(self, memo)\n del self._deepcopy_relabel_\n del self._deepcopy_labels_\n return new","def annotate(self, ignore=(-1,), shuffle=True, chunk_size=10):\n\n self.chunk_size = chunk_size\n\n self.new_clusters = OrderedDict.fromkeys(self.clusters)\n\n try:\n self.new_clusters.pop(ignore, None)\n except TypeError:\n for value in ignore:\n self.new_clusters.pop(value, None)\n\n self.new_labels = self.cluster_labels.copy().astype(float)\n self.new_labels[:] = np.nan\n\n self._label_queue = deque(self.new_clusters.keys())\n self._already_labelled = deque([])\n if shuffle:\n np.random.shuffle(self._label_queue)\n\n self._annotation_loop = self._annotation_iterator()\n # reset the progress bar\n self.progressbar.max = len(self._label_queue)\n self.progressbar.value = 0\n\n # start the iteration cycle\n return next(self._annotation_loop)","def overlay_labels(labels):\n labels_scaled = rescaled(labels,0,256)\n labels_colored = plt.get_cmap(\"jet\")(labels_scaled)\n border_mask = region_borders(labels) & (labels > 0)\n labels_colored[~border_mask,:,3] = 0 # set alpha to zero\n return labels_colored","def binarize_labels(labels):\n labels = np.where(labels == 0, labels, 1)\n\n return labels"],"string":"[\n \"def _relocate_clusters(self, cluster_labels):\\n for cluster_label in range(self.k):\\n if cluster_labels[cluster_label] is not None:\\n # mean of the pixels assigned to cluster\\n p_sum, p_count = np.asarray(\\n cluster_labels[\\n cluster_label\\n ]).sum(axis=0), len(cluster_labels[cluster_label])\\n self._clusters[cluster_label] = p_sum / p_count\",\n \"def clean_labels(labels):\\n\\n llabels, slabels = list(labels), set(labels)\\n \\n for l in slabels:\\n if llabels.count(l) <2 and l != max(slabels):\\n llabels[llabels.index(l)] = l+1\\n return clean_labels(llabels)\\n elif llabels.count(l) <2 and l == max(slabels):\\n llabels[llabels.index(l)] = l-1\\n return clean_labels(llabels)\\n else:\\n return np.array(llabels)\",\n \"def assign_labels_to_centroids(self):\\n labelled_centroids = []\\n for i in range(len(self.final_clusters)):\\n labels = map(lambda x: x[0], self.final_clusters[i])\\n # pick the most common label\\n most_common = Counter(labels).most_common(1)[0][0]\\n c = np.round(len([item for item in self.final_clusters[i] if item[0]==1])/len(self.final_clusters[i]),2)\\n if c>=0.46:\\n most_common = 1.0\\n centroid = (most_common, self.final_centroids[i])\\n labelled_centroids.append(centroid)\\n\\n self.labelled_centroids = labelled_centroids\\n print(\\\"cluster_0: \\\", np.round(len([item for item in self.final_clusters[0] if item[0]==1])/len(self.final_clusters[0]),2), \\\"size_0: \\\", len(self.final_clusters[0]))\\n print(\\\"cluster_1: \\\", np.round(len([item for item in self.final_clusters[1] if item[0]==1])/len(self.final_clusters[1]),2), \\\"size_1: \\\", len(self.final_clusters[1]))\\n #print(\\\"cluster_2: \\\", np.round(len([item for item in self.final_clusters[2] if item[0]==1])/len(self.final_clusters[2]),2), \\\"size_2: \\\", len(self.final_clusters[2]))\\n #print(\\\"cluster_3: \\\", np.round(len([item for item in self.final_clusters[3] if item[0]==1])/len(self.final_clusters[3]),2), \\\"size_2: \\\", len(self.final_clusters[3]))\",\n \"def _relabel(labels, minval=0, bgval=None):\\n\\n labels = np.unique(labels, return_inverse=True)[-1] + minval\\n if bgval is not None:\\n labels[labels == minval] = bgval\\n return labels\",\n \"def change_labels(labels, cluster_name, idx_to_change, target_labels):\\n assert(type(idx_to_change) == list)\\n assert(type(target_labels) == list)\\n assert(len(idx_to_change) == len(target_labels))\\n\\n sub_list = labels[labels == cluster_name]\\n\\n for idx, target in zip(idx_to_change, target_labels):\\n sub_list[idx] = target\\n\\n labels[labels == cluster_name] = sub_list\\n\\n return labels\",\n \"def separate_noise_labels_into_clusters(\\n labels: np.ndarray, noise_label: int = -1\\n) -> np.ndarray:\\n new_labels = labels.copy()\\n max_label = np.max(new_labels)\\n j = max_label + 1\\n for i in range(len(new_labels)):\\n if new_labels[i] == noise_label:\\n new_labels[i] = j\\n j += 1\\n return new_labels\",\n \"def repair_labels(labels):\\n ret = np.copy(labels)\\n ret[:, 0] = 10 # overwrite length to be stop seq\\n ret = np.roll(ret, -1, axis=1) # move first to last\\n return ret\",\n \"def _rename_clusters(self):\\n all_clusters = []\\n temp_clusters = self._clusters.copy()\\n for clu in temp_clusters:\\n all_clusters.append(self._clusters.pop(clu))\\n idx = 0\\n for clu in all_clusters:\\n label = 'S' + str(idx)\\n clu.rename(label)\\n self._clusters[label] = clu\\n idx += 1\",\n \"def cluster_labels(kmeans,actual_labels):\\r\\n infered_label={}\\r\\n for i in range(kmeans.n_clusters):\\r\\n # Find Index of points in cluster\\r\\n labels = []\\r\\n index = np.where(kmeans.labels_ == i)\\r\\n \\r\\n #Append actual labels for each point\\r\\n labels.append(actual_labels[index])\\r\\n \\r\\n #Determine the most common label\\r\\n if len(labels[0])==1:\\r\\n counts=np.bincount(labels[0])\\r\\n else:\\r\\n counts=np.bincount(np.squeeze(labels))\\r\\n #Assign cluster to a value in the dictionary\\r\\n if np.argmax(counts) in infered_label:\\r\\n # append the new number to the existing array at this slot\\r\\n infered_label[np.argmax(counts)].append(i)\\r\\n else:\\r\\n # create a new array in this slot\\r\\n infered_label[np.argmax(counts)]=[i]\\r\\n return infered_label\",\n \"def _calculate_nearest_cluster(self, pixels, cluster_labels):\\n\\n # assign pixel (RGB) to nearest cluster label (index)\\n for index, rgb in pixels:\\n rgb_vector = np.tile(rgb, (self.k, 1))\\n self._labels[index] = np.argmin(\\n self._euclid_distance(rgb_vector, self._clusters), axis=0)\\n\\n if cluster_labels[self._labels[index]] is None:\\n cluster_labels[self._labels[index]] = list()\\n\\n cluster_labels[self._labels[index]].append(rgb)\\n\\n return cluster_labels\",\n \"def anonymize(labels, unique_ordered_labels):\\n index_dict = dict((val, idx) for idx, val in enumerate(unique_ordered_labels))\\n return [index_dict[x] for x in labels]\",\n \"def normalize_labels(labels):\\n number_of_labels = len(labels)\\n number_of_species = get_number_of_species()\\n labels_norm = np.zeros(shape=(number_of_labels, number_of_species))\\n for i in range(number_of_labels):\\n for label in labels[i]:\\n labels_norm[i][label] = 1\\n return labels_norm\",\n \"def updateClusterInfo(self):\\n self.nPoints = len(self.labels)\\n self.n = len(np.unique(self.labels))\\n self.centers = [ [0.0 for j in range(3)] for i in range(self.n)]\",\n \"def _relabel(self, a):\\n\\n labels = list(np.unique(a))\\n if 0 in labels:\\n labels.remove(0)\\n\\n if len(labels) == 0:\\n return a.copy()\\n old_values = np.asarray(labels)\\n new_values = np.arange(1, len(labels) + 1, dtype=old_values.dtype)\\n\\n try:\\n values_map = np.arange(int(a.max() + 1), dtype=new_values.dtype)\\n except ValueError as e:\\n raise ValueError(f\\\"{e}, arange length: {int(a.max() + 1)}\\\")\\n values_map[old_values] = new_values\\n\\n return values_map[a.copy()]\",\n \"def rename_labels_by_count(labels):\\n new_labels, label_counts = _count_labels(labels)\\n\\n return new_labels\",\n \"def cluster_assign(images_lists, dataset):\\n assert images_lists is not None\\n pseudolabels = []\\n image_indexes = []\\n for cluster, images in enumerate(images_lists):\\n image_indexes.extend(images)\\n pseudolabels.extend([cluster] * len(images))\\n print(image_indexes)\\n print(pseudolabels)\\n \\n normalize = transforms.Normalize(mean=[0.485, 0.456, 0.406],\\n std=[0.229, 0.224, 0.225])\\n t = transforms.Compose([transforms.RandomResizedCrop(224),\\n transforms.RandomHorizontalFlip(),\\n transforms.ToTensor(),\\n normalize])\\n\\n return ReassignedDataset(image_indexes, pseudolabels, dataset, t)\",\n \"def process_label(self, foreground_labels):\\n # Find the unique (nonnegative) foreground_labels, map them to {0, ..., K-1}\\n unique_nonnegative_indices = np.unique(foreground_labels)\\n mapped_labels = foreground_labels.copy()\\n for k in range(unique_nonnegative_indices.shape[0]):\\n mapped_labels[foreground_labels == unique_nonnegative_indices[k]] = k\\n foreground_labels = mapped_labels\\n return foreground_labels\",\n \"def setLabels(self, labels: List[Shape]):\\n self.labels = labels\\n self.update()\",\n \"def cluster_to_voxel_label(clusts: nb.types.List(nb.int64[:]),\\n node_label: nb.int64[:]) -> nb.int64[:]:\\n nvoxels = np.sum([len(c) for c in clusts])\\n vlabel = np.empty(nvoxels, dtype=np.int64)\\n stptr = 0\\n for i, c in enumerate(clusts):\\n endptr = stptr + len(c)\\n vlabel[stptr:endptr] = node_label[i]\\n stptr = endptr\\n\\n return vlabel\",\n \"def labels(self, labels: MutableMapping[str, str]):\\n self._labels = labels\",\n \"def consolidate_labels(labels):\\n return map(RNN_model.consolidate_label , labels)\",\n \"def classify_k_cluster(labels, datas):\\n classify_k_cluster_to_redis(labels=labels, texts=datas)\",\n \"def _remove_and_relabel_blobs(labeled, wanted_blobs):\\n labeled = labeled.copy()\\n wanted_blobs = np.array(wanted_blobs)\\n no_blobs = len(wanted_blobs)\\n unwanted_blobs = np.arange(1, no_blobs+1)[np.logical_not(wanted_blobs)]\\n wanted_blobs = np.arange(1, no_blobs+1)[wanted_blobs]\\n\\n for unwanted_blob in unwanted_blobs:\\n labeled[labeled == unwanted_blob] = 0\\n\\n for new_label, wanted_blob in enumerate(wanted_blobs):\\n new_label += 1\\n labeled[labeled == wanted_blob] = -new_label\\n\\n return -labeled\",\n \"def change_class_labels(classes):\\n u,indices=np.unique(classes,return_inverse=True)\\n return u,indices\",\n \"def move_centroids(self, labelled_clusters):\\n new_centroids = []\\n # print(\\\"Cluster size\\\", end=\\\"\\\\t\\\")\\n for cluster in labelled_clusters:\\n new_centroids.append(self.mean_cluster(cluster))\\n # print(len(cluster), end=\\\"\\\\t\\\" )\\n # print(\\\"\\\\n\\\")\\n return new_centroids\",\n \"def regroup_dataset(labels):\\r\\n batch_y = labels.copy()\\r\\n for i, label in enumerate(labels):\\r\\n if label in [0, 15, 19]:\\r\\n batch_y[i]=0\\r\\n if label in [1, 2, 3, 4, 5,]:\\r\\n batch_y[i]=1\\r\\n if label in [6]:\\r\\n batch_y[i]=2\\r\\n if label in [7,8,9,10]:\\r\\n batch_y[i]=3\\r\\n if label in [11,12,13,14]:\\r\\n batch_y[i]=4\\r\\n if label in [16,17,18]:\\r\\n batch_y[i]=5\\r\\n \\r\\n print('regrouped label', batch_y.shape)\\r\\n return batch_y\",\n \"def assignLabels(self):\\n clusters = np.arange(0, len(self.V))[self.V < self.V1] #indexes self.V, volumes_sorted, and oldOrder\\n self.clusterV = self.volumes_sorted[clusters]\\n clusters = self.oldOrder[clusters] #indexes volumes\\n self.clusters = self.nonBI[clusters] #indexes self.vor and self.data\\n self.easyLabel = np.zeros(len(self.data))\\n self.easyLabel[self.clusters] = 1\\n print('Out of ' + str(len(self.data)) + ' particles, ' + str(len(self.clusters)) + ' (' + str(round(len(self.clusters)*100/len(self.data), 3)) +' %) are labelled as cluster particles.')\",\n \"def labels(self, labels):\\n self._labels = labels\",\n \"def get_cluster_elements_labels(self):\\n \\n copy = deepcopy(self.cluster_elements_labels)\\n return copy\",\n \"def get_cluster_to_label_mapping_safe(y, y_pred, n_classes, n_clusters, toprint=True):\\n one_hot_encoded = np_utils.to_categorical(y, n_classes)\\n\\n cluster_to_label_mapping = []\\n n_assigned_list = []\\n majority_class_fractions = []\\n majority_class_pred = np.zeros(y.shape)\\n for cluster in range(n_clusters):\\n cluster_indices = np.where(y_pred == cluster)[0]\\n n_assigned_examples = cluster_indices.shape[0]\\n n_assigned_list.append(n_assigned_examples)\\n cluster_labels = one_hot_encoded[cluster_indices]\\n cluster_label_fractions = np.mean(cluster_labels, axis=0)\\n majority_cluster_class = np.argmax(cluster_label_fractions)\\n cluster_to_label_mapping.append(majority_cluster_class)\\n majority_class_pred[cluster_indices] += majority_cluster_class\\n majority_class_fractions.append(cluster_label_fractions[majority_cluster_class])\\n if toprint:\\n print(cluster, n_assigned_examples, majority_cluster_class, cluster_label_fractions[majority_cluster_class])\\n #print(cluster_to_label_mapping)\\n if toprint:\\n print(np.unique(y), np.unique(cluster_to_label_mapping))\\n try:\\n # make sure there is at least 1 cluster representing each class\\n assert np.all(np.unique(y) == np.unique(cluster_to_label_mapping))\\n except AssertionError:\\n # if there is no cluster for a class then we will assign a cluster to that\\n # class\\n \\n # find which class it is\\n # ASSUMPTION - this task is binary\\n \\n diff = list(set(np.unique(y)) - set(np.unique(cluster_to_label_mapping)))[0]\\n # we choose the cluster that contains the most examples of the class with no cluster\\n \\n one_hot = np_utils.to_categorical(y_pred[np.where(y==diff)[0]], \\\\\\n len(cluster_to_label_mapping))\\n \\n cluster_to_label_mapping[np.argmax(np.sum(one_hot, axis=0))] = int(diff)\\n if toprint:\\n print(cluster_to_label_mapping)\\n return cluster_to_label_mapping, n_assigned_list, majority_class_fractions\",\n \"def consolidate_labels(labels):\\n return list(map(RNNOIE_model.consolidate_label , labels))\",\n \"def set_labels(self, new_labels=None):\\n self.labels = new_labels\",\n \"def mask_labels(labels):\\n def do_one_row(row):\\n erase = False\\n for i, _ in enumerate(row):\\n if erase:\\n row[i] = 0\\n else:\\n if row[i] == 10:\\n erase = True\\n row[i] = 1\\n return row\\n\\n ret = np.copy(labels)\\n return np.apply_along_axis(do_one_row, axis=1, arr=ret)\",\n \"def recluster(dataList, labelConverter, clusterSeedList, eps, minPts):\\n # print(\\\"starting reclustering\\\")\\n for pt in dataList:\\n pt.isVisited = False\\n\\n # Expand existing clusters from the seed pt.\\n for seed in clusterSeedList:\\n if labelConverter[seed.label] == -1:\\n continue\\n seed.isVisited = True\\n neighborhood = findNeighbor(seed, dataList, eps)\\n # Cluster is expanded iff neighbor's label is same as seed's label,\\n # or label is extra cluster.(x.label != -1 and labelConverter[x.label] == -1)\\n neighborhood = [x for x in neighborhood\\n if (x.label != -1 and labelConverter[x.label] == -1) or x.label == seed.label]\\n idx = -1\\n while (idx < len(neighborhood) - 1):\\n idx += 1\\n if (neighborhood[idx].isVisited):\\n continue\\n neighborhood[idx].isVisited = True\\n nextNeighbor = findNeighbor(neighborhood[idx], dataList, eps)\\n nextNeighbor = [x for x in nextNeighbor\\n if (x.label != -1 and labelConverter[x.label] == -1) or x.label == seed.label]\\n neighborhood = neighborhood \\\\\\n + [x for x in nextNeighbor if x not in neighborhood and not x.isVisited]\\n if (labelConverter[neighborhood[idx].label] == -1):\\n # print(str(neighborhood[idx].id) + \\\" changed to \\\" + str(seed.label))\\n neighborhood[idx].label = seed.label\",\n \"def createSetsFromLabels(self):\\n \\n self.tots = [0]*self.n\\n for i in range(self.n):\\n self.sets.append([])\\n for i in range(self.nPoints):\\n self.sets[self.labels[i]].append(i)\\n self.tots[self.labels[i]] += 1\",\n \"def relabel_labelmask(labelmask, preserve_order=True):\\n mask = np.copy(labelmask)\\n # Get all object labels and their counts.\\n labels, counts = np.unique(mask, return_counts=True)\\n # Get the indexes of sorted counts, descending.\\n ordered_indexes = np.argsort(counts)[::-1]\\n # Set largest object as background (ID=0).\\n background_label = labels[ordered_indexes[0]]\\n mask[mask == background_label] = 0\\n # Renumber the rest of the objects 1..n.\\n obj_num=1\\n if (preserve_order):\\n oldlabels = labels\\n else:\\n oldlabels = labels[ordered_indexes]\\n for old_label in oldlabels:\\n if (old_label != background_label):\\n mask[labelmask == old_label] = obj_num\\n obj_num = obj_num + 1\\n return mask\",\n \"def setCSLabels(self, labels):\\n\\n if isinstance(labels, list):\\n if len(labels) == self._n_csets:\\n if all((lbl is None or isinstance(lbl, str))\\n for lbl in labels):\\n self._cslabels = list(labels)\\n else:\\n raise ValueError('all items of labels must be strings')\\n else:\\n raise ValueError('length of labels must be equal to the '\\n 'number of coordinate sets')\\n else:\\n raise TypeError('labels must be a list')\",\n \"def truncate_labels(labels):\\n def do_one_row(row):\\n erase = False\\n for i, _ in enumerate(row):\\n if erase:\\n row[i] = -1\\n else:\\n if row[i] == 10:\\n erase = True\\n return row\\n\\n ret = np.copy(labels)\\n ret = repair_labels(ret)\\n return np.apply_along_axis(do_one_row, axis=1, arr=ret)\",\n \"def labels(self, labels):\\n\\n self._labels = labels\",\n \"def labels(self, labels):\\n\\n self._labels = labels\",\n \"def labels(self, labels):\\n\\n self._labels = labels\",\n \"def labels(self, labels):\\n\\n self._labels = labels\",\n \"def labels(self, labels):\\n\\n self._labels = labels\",\n \"def convertLabels(self, labels):\\n counter = 0\\n numericLabels = []\\n for label in labels:\\n if label not in self.labelDict:\\n self.labelDict[label] = counter\\n self.backwards_conversion[counter] = label\\n counter += 1\\n numericLabels += [self.labelDict[label]]\\n return np.array(numericLabels)\",\n \"def classify_clusters_sk(cloud: object, labels: np.ndarray) -> list:\\n \\\"\\\"\\\"\\n indices = list(dict.fromkeys(labels))\\n if (-1 in indices):\\n indices.remove(-1)\\n clusters = [[] for i in indices]\\n for (i, point) in enumerate(cloud, start=0):\\n if (labels[i] != -1):\\n clusters[labels[i]].append(point) \\n return (clusters, indices)\\n \\\"\\\"\\\"\\n indices = list(dict.fromkeys(labels))\\n if (-1 in indices):\\n indices.remove(-1)\\n clusters = []\\n for i in indices:\\n clusters.append([])\\n for (idx, point) in enumerate(cloud, start=0):\\n label = labels[idx]\\n if (label != -1):\\n clusters[label].append(point)\\n for el in clusters:\\n el = np.vstack(el)\\n radar_clusters = [Cluster(np.asarray(el), sensor='radar') for el in clusters]\\n return (radar_clusters, indices)\",\n \"def update_labels(self, nidxs, y):\\n\\n y = np.array(y, dtype=bool)\\n for n, yi in zip(nidxs, y):\\n self.node_labels[n] = [self.labels[i] for i, j in enumerate(yi) if j]\\n\\n return self\",\n \"def set_label(self, labels_set=None):\\n for pos in labels_set:\\n self._q_bnn_circ.x(self.outputs[int(pos)])\",\n \"def infer_data_labels(X_labels, cluster_labels):\\r\\n #Empty array of len(X)\\r\\n predicted_labels = np.zeros(len(X_labels)).astype(np.uint8)\\r\\n \\r\\n for i, cluster in enumerate(X_labels):\\r\\n for key, value in cluster_labels.items():\\r\\n if cluster in value:\\r\\n predicted_labels[i] = key\\r\\n \\r\\n return predicted_labels\",\n \"def rectifyClusteringLabels( labels, rectificationWidth=5):\\r\\n\\r\\n\\tfor l in range( len(labels) - rectificationWidth):\\r\\n\\t\\tfirstLabelIndex = l\\r\\n\\t\\tmedianLabelIndex = l + ( rectificationWidth//2)\\r\\n\\t\\tlastLabelIndex = l + rectificationWidth -1\\r\\n\\t\\tfirstLabel = labels[firstLabelIndex]\\r\\n\\t\\tmedianLabel = labels[ medianLabelIndex]\\r\\n\\t\\tlastLabel = labels[lastLabelIndex]\\r\\n\\t\\tleftLabels = labels[firstLabelIndex +1 : medianLabelIndex]\\r\\n\\t\\trightLabels = labels[ medianLabelIndex +1 : lastLabelIndex]\\r\\n\\t\\tif medianLabel != firstLabel and medianLabel != lastLabel:\\r\\n\\t\\t\\tfor label in leftLabels:\\r\\n\\t\\t\\t\\tif label != firstLabel: continue\\r\\n\\t\\t\\tfor label in rightLabels:\\r\\n\\t\\t\\t\\tif label != lastLabel: continue\\r\\n\\t\\t\\tlabels[medianLabelIndex] = labels[medianLabelIndex - 1]\\r\\n\\treturn labels\",\n \"def labels(self, points):\\n\\n assert(self.final_clusters is not None)\\n\\n labels = np.array([self.classify_point(point) for point in points])\\n \\n return labels\",\n \"def change_class_labels_back(classes,given):\\n classes=np.asarray(classes)\\n classes_new=np.zeros(classes.shape,dtype=object)\\n for i in range(len(given)):\\n classes_new[classes==i]=given[i]\\n return classes_new\",\n \"def flip_random_labels(labels, percent):\\n\\n assert percent <= 1.0 and percent >= 0.0\\n \\n num_labels = len(labels)\\n indices = np.random.permutation(num_labels)[:int(num_labels * percent)]\\n labels[indices] = -labels[indices]\\n return labels\",\n \"def reformat_labels(label, bin_limits=[2]):\\n# num_labels = y_batch.max() + 1\\n label = np.array([label], dtype=np.float32)\\n num_labels = 2\\n label = np.digitize(label, bins=[2])\\n label = (np.arange(num_labels) == label[:, None]).astype(np.float32)[0]\\n return label\",\n \"def initClusters(self):\\n if len(self.labelList) != len(self.pointList):\\n \\traise ValueError(\\\"Label List and Point List not the same length!\\\")\\n for i in range(len(self.labelList)):\\n self.centroids[self.labelList[i]] = self.pointList[i]\\n self.pointcounts[self.labelList[i]] = 1\",\n \"def propagate_labels_simple(regions,labels):\\n rlabels,_ = label(regions)\\n cors = correspondences(rlabels,labels,False)\\n outputs = zeros(amax(rlabels)+1,'i')\\n for o,i in cors.T: outputs[o] = i\\n outputs[0] = 0\\n return outputs[rlabels]\",\n \"def update_plot_clusters(cluster_handles, data_points, cluster_ids):\\n for handle, cluster_id in zip(cluster_handles, np.unique(cluster_ids)):\\n loc = cluster_id == cluster_ids\\n handle.set_data(data_points[loc, 0], data_points[loc, 1])\",\n \"def ConfigureCluster(messages, args, cluster):\\n cluster.labels = labels_util.ParseCreateArgs(args,\\n messages.Cluster.LabelsValue)\",\n \"def form_clusters(self, labelled_data, unlabelled_centroids):\\n # enumerate because centroids are arrays which are unhashable,\\n centroids_indices = range(len(unlabelled_centroids))\\n # initialize an empty list for each centroid. The list will contain\\n # all the datapoints that are closer to that centroid than to any other.\\n # That list is the cluster of that centroid.\\n clusters = {c: [] for c in centroids_indices}\\n \\n for (label, Xi) in labelled_data:\\n # for each datapoint, pick the closest centroid.\\n smallest_distance = float(\\\"inf\\\")\\n for cj_index in centroids_indices:\\n cj = unlabelled_centroids[cj_index]\\n distance = np.linalg.norm(Xi - cj)\\n if distance < smallest_distance:\\n closest_centroid_index = cj_index\\n smallest_distance = distance\\n # allocate that datapoint to the cluster of that centroid.\\n clusters[closest_centroid_index].append((label,Xi))\\n return list(clusters.values())\",\n \"def deletemessageslabels(self, uidlist, labels):\\n\\n labels = labels - self.ignorelabels\\n result = self._messagelabels_aux('-X-GM-LABELS', uidlist, labels)\\n if result:\\n for uid in uidlist:\\n self.messagelist[uid]['labels'] = self.messagelist[uid]['labels'] - labels\",\n \"def cfilter(centers, labels, t=5, position_likes=None, labels_likes=None):\\n if position_likes is None:\\n position_likes = []\\n \\n if labels_likes is None:\\n labels_likes = []\\n \\n # backup the labels and the clusters\\n centers, labels = deepcopy(centers), deepcopy(labels)\\n unique_labels = np.unique(labels)\\n \\n # Create lists for each cluster contaning the related nodes\\n components = []\\n node_labels = [None for _ in range(len(labels))]\\n \\n for label in np.sort(unique_labels):\\n component = np.argwhere(label == labels).T\\n assert len(component) == 1\\n\\n for node in component[0]:\\n node_labels[node] = label\\n\\n components.append(component[0].tolist())\\n \\n # Find the cluster indices of the to small clusters\\n removal = []\\n for idx, component in enumerate(components):\\n if len(component) < t:\\n removal.append(idx)\\n \\n # delete the too small centers\\n new_centers = np.delete(centers, removal)\\n \\n # remove the old labels from the labels array\\n position_removal = []\\n labels_np = np.array(labels)\\n \\n for label in removal:\\n position_removal += np.argwhere(label==labels_np).T[0].tolist()\\n \\n new_labels = np.delete(labels, position_removal)\\n \\n \\n # adjust the position arrays\\n new_position_likes = []\\n for pos_like in position_likes:\\n new_position_likes.append(np.delete(pos_like, position_removal, axis=0))\\n \\n # adjust the labels arrays\\n new_labels_likes = []\\n for lab_like in labels_likes:\\n new_labels_likes.append(np.delete(lab_like, position_removal))\\n \\n \\n # remove te gaps in the labels array (They sholud be the indices of the clusters array...):\\n difference = [0 for i in range(len(unique_labels))]\\n last_difference = 0\\n \\n for label in np.sort(unique_labels):\\n if label in removal:\\n last_difference += 1\\n \\n difference[label] = last_difference\\n \\n for idx, label in enumerate(new_labels):\\n new_labels[idx] -= difference[label]\\n \\n \\n # adjust the cluster centers to the fact, that the position array changed (they are the indices of it...): \\n pos_difference = [0 for i in range(len(labels))]\\n last_difference = 0\\n \\n for idx in range(len(labels)):\\n if idx in position_removal:\\n last_difference += 1\\n \\n \\n pos_difference[idx] = last_difference\\n \\n for idx, center in enumerate(new_centers):\\n new_centers[idx] -= pos_difference[center]\\n \\n \\n \\n # Adjust the output to the input\\n if len(new_position_likes) != 0:\\n if len(new_labels_likes) != 0:\\n return new_centers, new_labels, new_position_likes, new_labels_likes\\n \\n else:\\n return new_centers, new_labels, new_position_likes\\n \\n elif len(new_labels_likes) != 0:\\n return new_centers, new_labels, new_labels_likes\\n \\n return new_centers, new_labels\",\n \"def _alter(self, label):\\n altered = np.full(self.n, -1)\\n altered[np.where(self.y_train == label)] = +1\\n return altered\",\n \"def reassign_noise(labels: np.ndarray, mask):\\n ret = labels.copy()\\n ret[mask] = np.arange(np.sum(mask)) + np.max(ret) + 1\\n return ret\",\n \"def prepare_labels(labels, class_mask):\\n mask = [1 if elt else -1 for elt in class_mask]\\n mask = np.array(mask)\\n return labels.dot(mask)\",\n \"def update_pivot_labels(l, maxn):\\n tmp = maxn+1\\n tmps = []\\n for i in range(0, len(l)):\\n if l[i] > MAX_NODES-1 or l[i] in tmps:\\n l[i] = tmp\\n tmp += 1\\n tmps.append(l[i])\\n return l\",\n \"def assign_labels(self, data):\\n data[self.label] = self.labeler(data.index.values)\",\n \"def transform_labels(self, labels):\\n # Fallback:\\n # return self.encoder.transform(labels)\\n classes = list(self.classes_())\\n return [classes.index(label) for label in labels]\",\n \"def transform_labels(self, labels):\\n # Fallback:\\n # return self.encoder.transform(labels)\\n classes = list(self.classes_())\\n return [classes.index(label) for label in labels]\",\n \"def replace_image_point_labels(image, labels):\\n img = image.copy()\\n for label, point in labels:\\n row, col = point\\n # Find the existing label at the point\\n index = img[int(row), int(col)]\\n # Replace the existing label with new, excluding background\\n if index > 0:\\n img[img == index] = label\\n\\n return img\",\n \"def associate_clusters(self, labels_1, labels_2):\\n if not torch.is_tensor(labels_1):\\n labels_1 = torch.cat(labels_1).cuda()\\n\\n if not torch.is_tensor(labels_2):\\n labels_2 = torch.cat(labels_2).cuda()\\n\\n assert labels_1.shape == labels_2.shape, \\\"Shape mismatch: {}, {}\\\".format(labels_1.shape, labels_2.shape)\\n\\n # do not associate the outlier ID with anything\\n unique_labels_1 = list(set(labels_1.unique().tolist()) - {self.OUTLIER_LABEL})\\n unique_labels_2 = list(set(labels_2.unique().tolist()) - {self.OUTLIER_LABEL})\\n\\n assert not set(unique_labels_1).intersection(set(unique_labels_2)), \\\\\\n \\\"Labels overlap: {}, {}\\\".format(unique_labels_1, unique_labels_2)\\n\\n association_costs = np.zeros((len(unique_labels_1), len(unique_labels_2)), np.float32)\\n recall_12 = np.zeros((len(unique_labels_1), len(unique_labels_2)), np.float32)\\n\\n # iterate over pairs of labels\\n for i1, i2 in [(i1, i2) for i1 in range(len(unique_labels_1)) for i2 in range(len(unique_labels_2))]:\\n l1, l2 = unique_labels_1[i1], unique_labels_2[i2]\\n l1_active_pts = labels_1 == l1\\n l2_active_pts = labels_2 == l2\\n\\n intersection = (l1_active_pts & l2_active_pts).float().sum()\\n union = (l1_active_pts | l2_active_pts).float().sum()\\n iou = intersection / union\\n\\n # print(\\\"IoU ({}, {}) = {}\\\".format(l1, l2, iou.item()))\\n association_costs[i1, i2] = 1. - iou.item()\\n recall_12[i1, i2] = intersection / l1_active_pts.sum(dtype=torch.float32)\\n\\n idxes_1, idxes_2 = linear_sum_assignment(association_costs)\\n\\n associations = []\\n unassigned_labels_1 = set(unique_labels_1)\\n unassigned_labels_2 = set(unique_labels_2)\\n\\n for i1, i2 in zip(idxes_1, idxes_2):\\n l1, l2 = unique_labels_1[i1], unique_labels_2[i2]\\n associations.append((l1, l2))\\n unassigned_labels_1.remove(l1)\\n unassigned_labels_2.remove(l2)\\n\\n return associations, unassigned_labels_1, unassigned_labels_2, association_costs[idxes_1, idxes_2], \\\\\\n (recall_12, unique_labels_1, unique_labels_2)\",\n \"def class2color(self, labels, clean_up_clusters=0, mode=None):\\n clean_up_clusters *= clean_up_clusters # create an area\\n colored_labels = np.zeros(labels.shape[:2] + (3,)).astype(np.uint8)\\n labels = np.squeeze(labels)\\n if clean_up_clusters > 0:\\n labels = DropClusters.drop(labels, min_size=clean_up_clusters)\\n ys, xs = np.where(labels)\\n colored_labels[ys, xs, :] = self.label_color\\n return colored_labels\",\n \"def _remove_duplicates(labels):\\n to_delete = []\\n for i in range(len(labels)):\\n for j in range(i + 1, len(labels)):\\n if intersection_ratio(labels[i], labels[j]) >= 0.5:\\n to_delete.append(j)\\n to_delete = np.unique(np.array(to_delete))\\n return np.delete(labels, to_delete, 0)\",\n \"def _merge_clusters(self, cl1, cl2):\\n label = ''\\n to_delete = ''\\n if cl1 < cl2:\\n label = cl1\\n to_delete = cl2\\n else:\\n label = cl2\\n to_delete = cl1\\n to_keep = self.get_cluster(label)\\n to_remove = self._clusters.pop(to_delete)\\n to_keep.merge(to_remove)\",\n \"def add_label_to_unique_species_labels(self, label: str) -> str:\\n unique_label, i = label, 0\\n while unique_label in self.unique_species_labels:\\n unique_label = f'{label}_{i}'\\n i += 1\\n self.unique_species_labels.append(unique_label)\\n return unique_label\",\n \"def label_centroids_heuristically(self, centroids: np.ndarray):\\n\\n cluster_centroids_labels = [(\\\"\\\", {}) for c in centroids]\\n\\n centre_point = centroids[0]\\n heuristic_centroids = np.array(\\n [\\n centre_point + [-30, 30],\\n centre_point + [30, 30],\\n centre_point + [0, -48.125],\\n ]\\n )\\n heuristic_centroid_labels = [\\n ConstJoint.LEFT_EYE,\\n ConstJoint.RIGHT_EYE,\\n ConstJoint.MOUTH,\\n ]\\n labeled = [False for c in centroids]\\n used_label = [False for c in heuristic_centroids]\\n while self.__are_labels_matched_with_centroids(cluster_centroids_labels, \\\"\\\"):\\n min_dist_square = math.inf\\n min_centroid = 0\\n min_cluster = 0\\n current_cluster = {}\\n for i, c in enumerate(centroids):\\n if labeled[i]:\\n continue\\n for j, cl in enumerate(heuristic_centroids):\\n if used_label[j]:\\n continue\\n diff = c - cl\\n dist_square = diff.dot(diff)\\n\\n if dist_square < min_dist_square:\\n min_centroid = i\\n current_cluster = c\\n min_cluster = j\\n min_dist_square = dist_square\\n\\n cluster_centroids_labels[min_centroid] = (\\n heuristic_centroid_labels[min_cluster],\\n current_cluster,\\n )\\n labeled[min_centroid] = True\\n used_label[min_cluster] = True\\n\\n return cluster_centroids_labels\",\n \"def assign_labels_to_longer_segs(self, uniq_id, base_scale_clus_label):\\n per_scale_clus_label = []\\n self.scale_n = len(self.multiscale_timestamp_dict[uniq_id]['scale_dict'])\\n uniq_scale_mapping = get_scale_mapping_list(self.multiscale_timestamp_dict[uniq_id])\\n for scale_index in range(self.scale_n):\\n new_clus_label = []\\n scale_seq_len = len(self.multiscale_timestamp_dict[uniq_id][\\\"scale_dict\\\"][scale_index][\\\"time_stamps\\\"])\\n for seg_idx in range(scale_seq_len):\\n if seg_idx in uniq_scale_mapping[scale_index]:\\n seg_clus_label = mode(base_scale_clus_label[uniq_scale_mapping[scale_index] == seg_idx])\\n else:\\n seg_clus_label = 0 if len(new_clus_label) == 0 else new_clus_label[-1]\\n new_clus_label.append(seg_clus_label)\\n per_scale_clus_label.extend(new_clus_label)\\n per_scale_clus_label = torch.tensor(per_scale_clus_label)\\n return per_scale_clus_label, uniq_scale_mapping\",\n \"def normalize_label(labels):\\n max_val = torch.max(labels)\\n min_val = torch.min(labels)\\n norm_labels = (labels - min_val)/(max_val - min_val)\\n return norm_labels\",\n \"def map_clusters(labels, rows):\\r\\n counts = Counter(labels)\\r\\n mappings = {c + 1: ((counts[c] / rows) * 100) for c in sorted(counts)}\\r\\n\\r\\n return mappings\",\n \"def AddLabelsFromString(self, labels):\\n if self.labels is None:\\n self.labels = set()\\n\\n self.labels = self.labels.union([x.strip() for x in labels.split(',')])\",\n \"def propagate_labels(image,labels,conflict=0):\\n rlabels,_ = label(image)\\n cors = correspondences(rlabels,labels,False)\\n outputs = zeros(amax(rlabels)+1,'i')\\n oops = -(1<<30)\\n for o,i in cors.T:\\n if outputs[o]!=0: outputs[o] = oops\\n else: outputs[o] = i\\n outputs[outputs==oops] = conflict\\n outputs[0] = 0\\n return outputs[rlabels]\",\n \"def apply_remap_values(labels: np.ndarray, label_map: Dict[int, int]) -> np.ndarray:\\n for l1, l2 in label_map.items():\\n labels[labels == l1] = l2\",\n \"def clustering_by_label(instances, label, meta_dataset, logger):\\n clusters = []\\n impurities = {\\n item[0]: item[1]\\n for item in meta_dataset.items() if item[0] != label}\\n impurities = list(itertools.chain(*impurities.values()))\\n\\n while instances:\\n # List is not empty\\n cluster = gift_wrapping(instances, impurities, logger)\\n\\n found = cluster['dimension'] < len(cluster['vertices'])\\n _dataset = []\\n vertices = []\\n points = []\\n for vertex in instances:\\n if vertex in cluster['vertices']:\\n vertices.append(vertex)\\n else:\\n if found and check_inside_hull(cluster['faces'], vertex):\\n points.append(vertex)\\n else:\\n _dataset.append(vertex)\\n\\n if found:\\n volume = round(calculate_volume(cluster['faces']), 15)\\n elif len(cluster['faces'][0]) > 1:\\n volume = round(numpy.exp(squared_area(cluster['faces'][0])), 15)\\n else:\\n volume = 0.0\\n\\n instances = _dataset\\n clusters.append({'vertices': vertices,\\n 'points': points,\\n 'size': len(vertices) + len(points),\\n 'volume': volume})\\n\\n logger.info(\\n 'Clustering: %d clusters found, '\\n '%d/%d instance processed for label %r',\\n len(clusters), len(meta_dataset[label]) - len(instances),\\n len(impurities) + len(meta_dataset[label]), label)\\n\\n return clusters\",\n \"def convert_labels_to_int(labels): \\n if not len(labels):\\n raise ValueError(\\\"Nothing to convert!\\\")\\n\\n if isinstance(labels[0], basestring) or isinstance(labels[0], int):\\n label_legend = list(set(labels))\\n converted_labels = [ label_legend.index(l) for l in labels ]\\n elif is_iterable(labels[0]): # Multiple labels, handle each one individually\\n num_labels = len(labels[0])\\n label_legend = []\\n converted_labels = []\\n \\n # Get the unique sets of labels for each index\\n for i in xrange(num_labels):\\n temp_labels = [l[i] for l in labels]\\n label_legend.append(list(set(temp_labels)))\\n\\n # Apply mapping to each label\\n for label in labels:\\n converted_label = [ leg.index(l) for leg, l in \\n zip(label_legend, label) ]\\n converted_labels.append(converted_label)\\n else: # Not a string/int, not a list... hmmm\\n raise ValueError('Unexpected label type!')\\n\\n return label_legend, array(converted_labels)\",\n \"def get_partition_from_labels(self, labels):\\n partition = defaultdict(list)\\n for ind, label in enumerate(labels):\\n partition[label].append(ind)\\n self.clean_partition(partition)\\n return partition\",\n \"def spread_labels(labels,maxdist=9999999):\\n #distances,features = morphology.distance_transform_edt(labels==0,return_distances=1,return_indices=1)\\n #indexes = features[0]*labels.shape[1]+features[1]\\n #spread = labels.ravel()[indexes.ravel()].reshape(*labels.shape)\\n if not labels.any():\\n return labels\\n distances,indexes = cv2.distanceTransformWithLabels(array(labels==0,uint8),cv2.DIST_L2,cv2.DIST_MASK_PRECISE,labelType=cv2.DIST_LABEL_PIXEL)\\n spread = labels[where(labels>0)][indexes-1]\\n if maxdist is None:\\n return spread, distances\\n spread *= (distances0)\\n\\t\\t\\t\\tself.bool_train_unlabelled=(self.train_labels___0_unlab__neg1_exclud==0)\\n\\t\\t\\t\\tself.bool_train_excluded=(self.train_labels___0_unlab__neg1_exclud<0)\\n\\t\\t\\t\\tself.num_train_labelled=sum(self.bool_train_labelled)\\n\\t\\t\\t\\tself.num_train_unlabelled=sum(self.bool_train_unlabelled)\\n\\t\\t\\t\\tself.num_train_excluded=sum(self.bool_train_excluded)\",\n \"def _labels_to_ordinals(self, labels, mask):\\n one_to_n = tf.range(1, self._ordinal_size + 1, dtype=tf.float32)\\n unsqueezed = tf.repeat(\\n tf.expand_dims(labels, axis=2), self._ordinal_size, axis=-1)\\n ordinals = tf.where(unsqueezed >= one_to_n, tf.ones_like(unsqueezed), 0.0)\\n if self._use_fraction_label:\\n fractions = unsqueezed - one_to_n + 1.0\\n fractions = tf.where(\\n tf.logical_and(fractions > 0.0, fractions < 1.0), fractions, 0.0)\\n ordinals += fractions\\n return tf.where(tf.expand_dims(mask, axis=-1), ordinals, 0.0)\",\n \"def from_labels_map(cls, labels_map):\\n mask_index = cls()\\n for index, value in iteritems(labels_map):\\n mask_index[index] = CategoricalAttribute(\\\"label\\\", value)\\n\\n return mask_index\",\n \"def undo_uniform_list_length(labels):\\n for label in labels:\\n while \\\" \\\" in label:\\n label.remove(\\\" \\\")\\n return labels\",\n \"def make_fixed_labels(self):\\n fixed_labels = []\\n for dim in range(self.opt.c_dim):\\n t = [0] * self.opt.c_dim\\n t[dim] = 1\\n t = torch.FloatTensor(t).expand([self.opt.batch_size, self.opt.c_dim])\\n fixed_labels.append(t)\\n return fixed_labels\",\n \"def labels_to_scores(labels):\\n device = sp.get_device(labels)\\n xp = device.xp\\n with device:\\n num_classes = labels.max() + 1\\n scores = xp.zeros([len(labels), num_classes], dtype=np.float32)\\n scores[xp.arange(len(labels)), labels] = 1\\n\\n return scores\",\n \"def getLabel(labels):\\r\\n elems = {}\\r\\n for l in labels:\\r\\n if l not in elems.keys():\\r\\n elems[l] = 1\\r\\n else:\\r\\n elems[l] += 1\\r\\n counts = sorted(elems.values(), reverse=True)\\r\\n if len(counts) > 1 and counts[0] == counts[1]:\\r\\n return choice(list(elems.keys()))\\r\\n return sorted(elems, key=elems.get, reverse=True)[0]\",\n \"def change_class_labels_to_given(classes,given):\\n classes=np.asarray(classes)\\n classes_new=np.zeros(classes.shape,dtype=object)\\n for i in given:\\n classes_new[classes==i]=given[i]\\n return classes_new\",\n \"def fix_label_names():\\n\\n assert trace.cpu.trace_done\\n binary_addr = memorymanager.BinaryAddr(0)\\n while binary_addr < len(classifications):\\n c = classifications[binary_addr]\\n if c is not None:\\n dummy = [str(x) for x in c.as_string_list(binary_addr, None)]\\n binary_addr += c.length()\\n else:\\n binary_addr += 1\",\n \"def _empty_clusters(clusters):\\n for clst in clusters:\\n clst.points = []\",\n \"def inlabel_shuffle(data):\\n num_zero_data = np.sum(data[:,-1]==0)\\n label_zero_data = data[:num_zero_data,:]\\n label_one_data = data[num_zero_data:,:]\\n np.random.shuffle(label_zero_data)\\n np.random.shuffle(label_one_data)\\n return data\",\n \"def relabeled(self, memo=None, labels=None):\\n from copy import deepcopy\\n\\n self._deepcopy_relabel_ = True\\n self._deepcopy_labels_ = labels\\n new = deepcopy(self, memo)\\n del self._deepcopy_relabel_\\n del self._deepcopy_labels_\\n return new\",\n \"def annotate(self, ignore=(-1,), shuffle=True, chunk_size=10):\\n\\n self.chunk_size = chunk_size\\n\\n self.new_clusters = OrderedDict.fromkeys(self.clusters)\\n\\n try:\\n self.new_clusters.pop(ignore, None)\\n except TypeError:\\n for value in ignore:\\n self.new_clusters.pop(value, None)\\n\\n self.new_labels = self.cluster_labels.copy().astype(float)\\n self.new_labels[:] = np.nan\\n\\n self._label_queue = deque(self.new_clusters.keys())\\n self._already_labelled = deque([])\\n if shuffle:\\n np.random.shuffle(self._label_queue)\\n\\n self._annotation_loop = self._annotation_iterator()\\n # reset the progress bar\\n self.progressbar.max = len(self._label_queue)\\n self.progressbar.value = 0\\n\\n # start the iteration cycle\\n return next(self._annotation_loop)\",\n \"def overlay_labels(labels):\\n labels_scaled = rescaled(labels,0,256)\\n labels_colored = plt.get_cmap(\\\"jet\\\")(labels_scaled)\\n border_mask = region_borders(labels) & (labels > 0)\\n labels_colored[~border_mask,:,3] = 0 # set alpha to zero\\n return labels_colored\",\n \"def binarize_labels(labels):\\n labels = np.where(labels == 0, labels, 1)\\n\\n return labels\"\n]"},"negative_scores":{"kind":"list like","value":["0.68851614","0.6850147","0.6721148","0.6478987","0.643922","0.6345853","0.6343787","0.6329328","0.62441224","0.6120226","0.6087101","0.60843414","0.60319865","0.5999183","0.59800136","0.5965767","0.5940681","0.59308654","0.592457","0.5924074","0.5922587","0.59185356","0.5911539","0.59012073","0.5877225","0.5865721","0.58591425","0.5842034","0.5841271","0.583055","0.58052087","0.57852286","0.57824177","0.5774432","0.5773876","0.57583994","0.57548106","0.5750352","0.5749712","0.5749712","0.5749712","0.5749712","0.5749712","0.5726109","0.57021797","0.56795007","0.5652587","0.56458086","0.563204","0.5627547","0.5619535","0.5607772","0.55898774","0.5588308","0.5584888","0.5572411","0.5559481","0.55373293","0.5535396","0.5533","0.5522069","0.55180997","0.55126876","0.55126005","0.5509811","0.5505415","0.5505415","0.550264","0.55001694","0.5483458","0.54727143","0.5470554","0.54704493","0.54658973","0.5455896","0.5445543","0.54352915","0.5432285","0.54200834","0.5417614","0.54157406","0.54087716","0.54015917","0.53999066","0.5382394","0.538059","0.53634214","0.5358435","0.5354307","0.53521377","0.5351596","0.5348534","0.5342153","0.5340996","0.5340373","0.5325329","0.53194404","0.53154236","0.53067553","0.530533"],"string":"[\n \"0.68851614\",\n \"0.6850147\",\n \"0.6721148\",\n \"0.6478987\",\n \"0.643922\",\n \"0.6345853\",\n \"0.6343787\",\n \"0.6329328\",\n \"0.62441224\",\n \"0.6120226\",\n \"0.6087101\",\n \"0.60843414\",\n \"0.60319865\",\n \"0.5999183\",\n \"0.59800136\",\n \"0.5965767\",\n \"0.5940681\",\n \"0.59308654\",\n \"0.592457\",\n \"0.5924074\",\n \"0.5922587\",\n \"0.59185356\",\n \"0.5911539\",\n \"0.59012073\",\n \"0.5877225\",\n \"0.5865721\",\n \"0.58591425\",\n \"0.5842034\",\n \"0.5841271\",\n \"0.583055\",\n \"0.58052087\",\n \"0.57852286\",\n \"0.57824177\",\n \"0.5774432\",\n \"0.5773876\",\n \"0.57583994\",\n \"0.57548106\",\n \"0.5750352\",\n \"0.5749712\",\n \"0.5749712\",\n \"0.5749712\",\n \"0.5749712\",\n \"0.5749712\",\n \"0.5726109\",\n \"0.57021797\",\n \"0.56795007\",\n \"0.5652587\",\n \"0.56458086\",\n \"0.563204\",\n \"0.5627547\",\n \"0.5619535\",\n \"0.5607772\",\n \"0.55898774\",\n \"0.5588308\",\n \"0.5584888\",\n \"0.5572411\",\n \"0.5559481\",\n \"0.55373293\",\n \"0.5535396\",\n \"0.5533\",\n \"0.5522069\",\n \"0.55180997\",\n \"0.55126876\",\n \"0.55126005\",\n \"0.5509811\",\n \"0.5505415\",\n \"0.5505415\",\n \"0.550264\",\n \"0.55001694\",\n \"0.5483458\",\n \"0.54727143\",\n \"0.5470554\",\n \"0.54704493\",\n \"0.54658973\",\n \"0.5455896\",\n \"0.5445543\",\n \"0.54352915\",\n \"0.5432285\",\n \"0.54200834\",\n \"0.5417614\",\n \"0.54157406\",\n \"0.54087716\",\n \"0.54015917\",\n \"0.53999066\",\n \"0.5382394\",\n \"0.538059\",\n \"0.53634214\",\n \"0.5358435\",\n \"0.5354307\",\n \"0.53521377\",\n \"0.5351596\",\n \"0.5348534\",\n \"0.5342153\",\n \"0.5340996\",\n \"0.5340373\",\n \"0.5325329\",\n \"0.53194404\",\n \"0.53154236\",\n \"0.53067553\",\n \"0.530533\"\n]"},"document_score":{"kind":"string","value":"0.6535897"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":8559,"cells":{"query":{"kind":"string","value":"Modify the column name to make it Pythoncompatible as a field name"},"document":{"kind":"string","value":"def normalize_col_name(col_name, used_column_names, is_relation):\n field_params = {}\n field_notes = []\n\n new_name = col_name.lower()\n if new_name != col_name:\n field_notes.append('Field name made lowercase.')\n\n if is_relation:\n if new_name.endswith('_id'):\n new_name = new_name[:-3]\n else:\n field_params['db_column'] = col_name\n\n new_name, num_repl = re.subn(r'\\W', '_', new_name)\n if num_repl > 0:\n field_notes.append('Field renamed to remove unsuitable characters.')\n\n if new_name.find(LOOKUP_SEP) >= 0:\n while new_name.find(LOOKUP_SEP) >= 0:\n new_name = new_name.replace(LOOKUP_SEP, '_')\n if col_name.lower().find(LOOKUP_SEP) >= 0:\n # Only add the comment if the double underscore was in the original\n # name\n field_notes.append(\n \"Field renamed because it contained more than one '_' in a row.\"\n )\n\n if new_name.startswith('_'):\n new_name = 'field%s' % new_name\n field_notes.append(\"Field renamed because it started with '_'.\")\n\n if new_name.endswith('_'):\n new_name = '%sfield' % new_name\n field_notes.append(\"Field renamed because it ended with '_'.\")\n\n if keyword.iskeyword(new_name):\n new_name += '_field'\n field_notes.append(\n 'Field renamed because it was a Python reserved word.')\n\n if new_name[0].isdigit():\n new_name = 'number_%s' % new_name\n field_notes.append(\n \"Field renamed because it wasn't a valid Python identifier.\")\n\n if new_name in used_column_names:\n num = 0\n while '%s_%d' % (new_name, num) in used_column_names:\n num += 1\n new_name = '%s_%d' % (new_name, num)\n field_notes.append('Field renamed because of name conflict.')\n\n if col_name != new_name and field_notes:\n field_params['db_column'] = col_name\n\n return new_name, field_params, field_notes"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _update_column_name(self, column, idx, old_name, name):\n dtype = self.dtype\n # Updating the names on the dtype should suffice\n dtype.names = dtype.names[:idx] + (name,) + dtype.names[idx + 1 :]","def py_field_name(self, field):\n name = field.name\n name = as_identifier(name)\n if self.options(field).convert_case:\n name = from_camel_case(name)\n name = self._mangle_name(name)\n return name","def col_name(col):\n\n if isinstance(col, str):\n return col\n return col.__name__","def encodeColumnName(self, column):\r\n return '\"{}\"'.format(column)","def column_name(name):\n # Only needs exceptions to standard token cleanup\n column_map = {\n \"line#\" : \"ignore\",\n \"date\" : \"timestamp\",\n \"rh\" : \"humidity\",\n \"par\" : \"par_ue\"\n }\n\n if name in column_map:\n return column_map[name]\n \n return name","def set_column_name(self, name):\r\n self.column_name = name","def set_column_name(self, name):\r\n self.column_name = name","def _column_original_name(name):\n if ':' in name:\n return name.split(':')[-1]\n else:\n return name","def name(self):\n if self.table:\n return \"{}.{}\".format(self.table, self.field_name)\n return self.field_name","def wrap_columns_name(self, format_string):\n self._data_frame = self._data_frame.rename(\n columns=lambda column: format_string.format(column)\n )","def rename_columns(self, col):\n try:\n self.cleaned_data.columns = col\n except Exception as e:\n raise e","def db_field_name(self):\r\n return self.db_field or self.column_name","def db_field_name(self):\r\n return self.db_field or self.column_name","def short_column(name : str) -> str:\n return name.split(\"-\")[1]","def get_name(self):\n return self.col_name","def capnp_field_name(self, field):\n name = field.name\n return as_identifier(name)","def _valid_column(column_name):\n return str(column_name)","def namehack(field):\n if field.endswith((\"attribute\", \"views\")):\n return field + \"__name\"\n else:\n return field","def column_name(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"column_name\")","def column_name(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"column_name\")","def _validate_column_name(col_name : str) -> str:\n\n if col_name[0].isdigit():\n return f'\"{col_name}\"'\n return col_name","def typed_column(self) -> str:\n\n return \"{}:{}\".format(self.name, self.dtype)","def rename(self, newname):\n # set the new column name\n self.colname = newname","def __getitem__(self, item):\n if isinstance(item, str):\n name_dict = {n.lower():n for n in self.colnames}\n item = item.lower()\n item = ','.join([name_dict[i] for i in item.split(',')])\n out = APtable.__getitem__(self, item)\n return out","def as_field(identifier: str) -> str:\n return identifier.lower()","def _remap_column_names(self, frame):\n\n frame[TransactionColumns.BANK.name] = self.INSTITUTION\n frame[TransactionColumns.ACCOUNT.name] = self.account\n frame.rename(columns=self._FIELD_2_TRANSACTION, inplace=True)\n frame[TransactionColumns.CHECK_NO.name] = None\n return frame","def column_name(self) -> Optional[str]:\n return pulumi.get(self, \"column_name\")","def test_column_name(self):\n field = self.base_field\n sch = SchemaField(field)\n self.assertEqual(sch.name, sch.column_name)\n self.assertNotEqual(sch.column_name, sch.title)","def getColName(self, col):\n try:\n return chr(ord('a') + col)\n except:\n return col","def getColName(self, col):\n try:\n return chr(ord('a') + col)\n except:\n return col","def generate_field_name(container, field):\n if \"standard_name\" in container.fields[field]:\n field_name = container.fields[field][\"standard_name\"]\n elif \"long_name\" in container.fields[field]:\n field_name = container.fields[field][\"long_name\"]\n else:\n field_name = str(field)\n field_name = field_name.replace(\"_\", \" \")\n field_name = field_name[0].upper() + field_name[1:]\n return field_name","def __set_name(self):\n table_name = self.get_table_name()\n record, timestamp = self.__get_max_timestamp()\n self.name = \"%s_%s_%s\" % (table_name, record, timestamp)","def new_index_name(self, column, unique=False):\n table_name = self.name.lstrip('migrate_')\n column = column.replace(', ', '')\n return '{}_{}_{}{}'.format(table_name, column, self._random_string(6), '_unique' if unique else '')","def format_column(self, column, use_table=False, name=None, table_name=None):\n if name is None:\n name = column.name\n if not getattr(column, 'is_literal', False):\n if use_table:\n return self.format_table(column.table, use_schema=False, name=table_name) + \".\" + self.__generic_obj_format(column, name)\n else:\n return self.__generic_obj_format(column, name)\n else:\n # literal textual elements get stuck into ColumnClause alot, which shouldnt get quoted\n if use_table:\n return self.format_table(column.table, use_schema=False, name=table_name) + \".\" + name\n else:\n return name","def test_dummydb_add_data_to_table_wrong_column_name(self):\n db = DummyDB()\n columns = {\n \"one\": int,\n \"two\": str,\n \"three\": bool,\n }\n db.create_table(\"new_table\", columns)\n result = db.select(\"new_table\", four=1)","def _field_name(self) -> str:\n name = self._resolve_field_name()\n if name is None:\n # pylint: disable=consider-using-f-string\n raise FieldNameError(\n \"No field name found among: explicit name = {}, inferred name = {}\".format(\n self.__name_explicit, self.__name_contextual\n )\n )\n return name","def safe_column_name(string):\n string = unidecode(string.replace(' ', '_').lower())\n return re.sub(r'[^0-9a-z_]','', string)","def alter_column(self, table_name, name, field, explicit_name=True):\r\n # Get the column's SQL\r\n field.set_attributes_from_name(name)\r\n if not explicit_name:\r\n name = field.column\r\n sql = self.column_sql(table_name, name, field)\r\n # Remake the table correctly\r\n self._remake_table(table_name, altered={name: sql})","def new_constraint_name(self, column, type):\n name = self.name.lstrip('migrate_')[:30]\n if type == 'UNIQUE':\n return '{}_{}_{}_uniq'.format(name, column[:15], self._random_string(8))\n elif type == 'PRIMARY KEY':\n return '{}_{}_pkey'.format(name, self._random_string(4))\n else:\n raise NotImplementedError('Name not implemented for type {}'.format(type))","def name_field(self):\r\n return 'name'","def __getitem__(self, field_name: str) -> ColumnField:\n return ColumnField(self, field_name=field_name)","def undo_format_field_name(field_name):\n if json_api_settings.FORMAT_FIELD_NAMES:\n return format_value(field_name, \"underscore\")\n\n return field_name","def update_column_title(col):\n col_type = self.features_bucket_mapping_.get(col).type\n return [f\"Feature '{col}'\"], [col_type]","def __tablename__(self):\n return sub(r\"(? str:\n\n return re.sub(r\"_[^_]+$\", \"\", field_name).replace(\"human_readable_\", \"\")","def update_column_format(self):\n pass","def columnName(self):\n return self.__column","def _get_column_name(df, name='agg'):\n while name in df.columns:\n name += '_'\n return name","def get_column_name(self) -> str:\n if self.is_shared():\n assert self._shared_id is not None\n return self._shared_id\n else:\n return str(id(self))","def get_column_def(self):\r\n return '{} {}'.format(self.cql, self.db_type)","def _clean_up_table_column_names(loop_dict):\n \n # Make the column names all lowercase\n # and remove any underscores from the beginning\n for key in loop_dict.keys():\n rename_dict = { x:re.sub(r\"\"\"^_\"\"\", '', x.lower()) for x in loop_dict[key].columns }\n loop_dict[key].rename(columns=rename_dict, inplace=True)\n \n return loop_dict","def change_type(self, col_name, str_type):\n if self[col_name] is not None:\n self[col_name] = self[col_name].astype(str_type)","def _str_colnames(self):\n return ', '.join(self.galcat.colnames)","def substitute_names(df):\n\n masking_tag = '_sql'\n duplicated_names = ['SwitchName', 'Fabric_Name', 'SwitchMode', 'Memory_Usage', 'Flash_Usage', 'Speed']\n replace_dct = {orig_name + masking_tag: orig_name for orig_name in duplicated_names}\n df.rename(columns=replace_dct, inplace=True)","def _get_custom_attribute_field_name(self, attribute):\n return 'attribute_{0}'.format(attribute.id)","def namingConvention(columnName):\n words = columnName.lower().split(\"_\")\n\n def cap(word):\n if word.lower() == \"id\":\n return word.upper()\n else:\n return word.capitalize()\n\n return words[0] + \"\".join(map(cap, words[1:]))","def colNames_string(self):\n # SELECT column_name FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = 'some_table';\n return \"SELECT column_name FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = \"","def fix_name(row, index, name_map):\n # print(\"Input row: {}\".format(row))\n name = row[index].strip()\n # print(\"Name entry is {}\".format(name))\n if name.endswith(\" (yourself)\"):\n name = name[:-len(\" (yourself)\")]\n # print(\"Shortening to |{}|\".format(name))\n if name not in name_map:\n name_map[name] = name # Initially the identity transform\n row[index] = name_map[name]","def give_field(self, name):\n return self.field(name).toPyObject()","def get_ast_field_name(ast):\n replacements = {\n # We always rewrite the following field names into their proper underlying counterparts.\n TYPENAME_META_FIELD_NAME: '@class'\n }\n base_field_name = ast.name.value\n normalized_name = replacements.get(base_field_name, base_field_name)\n return normalized_name","def _table_name(self, name: AnyStr) -> bytes:\n name = ensure_bytes(name)\n if self.table_prefix is None:\n return name\n return self.table_prefix + self.table_prefix_separator + name","def name(self) -> str:\n return self.fqtable.replace(\".\", \"_\")","def _str_colnames(self):\n return ', '.join(self.colnames)","def to_sql(self, model_cls, field_name, value):\n raise NotImplementedError # pragma: no cover","def NAME(self) -> str:\n return self._field_name","async def set_db_name_field(self, db_name_field):\n self.db_name_field = db_name_field","def new_fk_index_name(self, column, fk_column):\n return '{}_refs_{}_{}'.format(column, fk_column, self._random_string(8))","def rename(self, old_column, new_column, data_type):\n self.table.rename_column(old_column, new_column, data_type)\n return self","def __tablename__(cls) -> str:\n return inflection.underscore(cls.__name__)","def _label(self, column):\n # XXX\n return column","def undo_format_field_names(obj):\n if json_api_settings.FORMAT_FIELD_NAMES:\n return format_field_names(obj, \"underscore\")\n\n return obj","def rename_columns(self):\n self.data.rename(columns={\n 'DealerID': 'd_id',\n 'DealerName': 'd_name',\n 'Type': 'stock_type', # Needs capitalization\n 'Stock': 'stock_id',\n 'VIN': 'vin',\n 'Year': 'year',\n 'Make': 'make',\n 'Model': 'model',\n 'Body': 'trim', # Needs parsing\n 'Trim': 'body_style',\n 'Doors': 'doors',\n 'ExtColor': 'exterior_colour',\n 'IntColor': 'interior_colour',\n 'EngCylinders': 'cylinders',\n 'EngDisplacement': 'displacement', # Needs parsing\n 'Transmission': 'transmission_description', # Needs parsing and split\n 'Odometer': 'odometer',\n 'Price': 'price',\n 'MSRP': 'msrp',\n 'Description': 'description',\n 'EngType': 'configuration',\n 'EngFuel': 'fuel_type',\n 'Drivetrain': 'drivetrain',\n 'ExtColorGeneric': 'exterior_colour_generic', # Needs parsing\n 'IntColorGeneric': 'interior_colour_generic', # Needs parsing\n 'PassengerCount': 'passengers'\n }, inplace=True)\n\n return None","def get_field(cls, name):\n if name not in cls.get_field_names():\n # - check field name first, next: column name -\n name = cls.get_field_name(name)\n return getattr(cls, name, None)","def setFieldNames(self, model, lyr): \n #get the fields\n fields = lyr.pendingFields()\n position = 0\n \n #set column names\n for field in fields:\n model.setHorizontalHeaderItem(position, QStandardItem(field.name()))\n position+=1","def _transformed_name(key: Text) -> Text:\n return key + \"_xf\"","def make_column(options, name, column):\n # (ElasticsearchFDWOptions, str, multicorn.ColumnDefinition) -> Column\n assert name not in {\n options.rowid_column,\n options.score_column,\n options.query_column,\n }, \"Programmer error: bad name passed to make_column {name}\".format(name=name)\n\n if column.base_type_name.upper() in {\"JSON\", \"JSONB\"}:\n return JsonColumn(name=name)\n return BasicColumn(name=name)","def __init__(self, column_type, name):\n self.column_type = column_type\n self.name = name","def autoname(self):\n ret = \"%(table)s_%(reftable)s_fkey\"%dict(\n table=self.table.name,\n reftable=self.reftable.name,\n )\n return ret","def act_on_column_name(self, *, arg, value):\n assert arg is None\n assert isinstance(value, str)","def translate_db_fields(cls, data):\r\n dst_data = data.copy()\r\n for name, col in cls._columns.items():\r\n key = col.db_field or name\r\n if key in dst_data:\r\n dst_data[name] = dst_data.pop(key)\r\n\r\n return dst_data","def del_column(self, fieldname):\n ...","def _sanitize_field_name(self, field_name):\n field_name = field_name.replace(self._field_prefix, '')\n return field_name.replace('.', '_')","def camel_case_to_mysql(name: str) -> str:\n\n view_name = name\n\n # Convert to MySQL view name\n idx_prefix = 'Ix'\n if view_name.startswith(idx_prefix):\n view_name = view_name.replace(idx_prefix, '', 1)\n return CobolDefinition.name_to_snake_case(view_name) + '_view'\n\n return CobolDefinition.name_to_snake_case(view_name)","def rename_id_col(df: pd.DataFrame):\r\n for col in df.columns:\r\n if \"id\" in col:\r\n df.rename(columns={col: col.replace(\"-\", \"_\")}, inplace=True)\r\n return df","def test_rename_column(self):\n name_column = Varchar()\n name_column._meta.name = \"name\"\n\n title_column = Varchar()\n title_column._meta.name = \"title\"\n\n schema: t.List[DiffableTable] = [\n DiffableTable(\n class_name=\"Band\",\n tablename=\"band\",\n columns=[name_column],\n )\n ]\n schema_snapshot: t.List[DiffableTable] = [\n DiffableTable(\n class_name=\"Band\",\n tablename=\"band\",\n columns=[title_column],\n )\n ]\n\n schema_differ = SchemaDiffer(\n schema=schema, schema_snapshot=schema_snapshot, auto_input=\"y\"\n )\n\n self.assertTrue(len(schema_differ.rename_columns.statements) == 1)\n self.assertEqual(\n schema_differ.rename_columns.statements[0],\n \"manager.rename_column(table_class_name='Band', tablename='band', old_column_name='title', new_column_name='name', old_db_column_name='title', new_db_column_name='name')\", # noqa\n )","def update_column_title():\n\n column_id = request.get_json()['column_id']\n column_title = request.get_json()['column_title']\n\n return sql_manager.update_column_title(column_id, column_title)","def __to_key(name: str) -> str:\n return name.replace(\" \", \"-\")","def get_column_def(self):\r\n db_type = self.db_type.format(self.value_type.db_type)\r\n return '{} {}'.format(self.cql, db_type)","def _normalize_column(column):\n if not isinstance(column, str):\n msg = \"expected column of type 'str', got {0!r} instead\"\n raise TypeError(msg.format(column.__class__.__name__))\n column = column.strip()\n column = column.replace('\"', '\"\"') # Escape quotes.\n if column == '':\n column = '_empty_'\n return '\"' + column + '\"'","def _normalize_column(column):\n if not isinstance(column, str):\n msg = \"expected column of type 'str', got {0!r} instead\"\n raise TypeError(msg.format(column.__class__.__name__))\n column = column.strip()\n column = column.replace('\"', '\"\"') # Escape quotes.\n if column == '':\n column = '_empty_'\n return '\"' + column + '\"'","def get_field_class_name(field):\n return field.capitalize() + \"Field\"","def _resolve_ref(self, name):\n if name not in self.fields:\n raise RuntimeError(\"No field with name `{}`\".format(name))\n\n field = self.fields.get(name)\n field.set_attributes_from_name(name)\n return Col(self.name, field, output_field=field)","def sql_for_columns(self, data, qn, connection):\n table_alias, _name, db_type = data\n\n fun = connection.ops.field_cast_sql\n\n if table_alias:\n lhs = [fun(f.db_type(connection)) % '%s.%s' % (qn(table_alias), qn(f.column)) for f in self.fields]\n else:\n lhs = [fun(f.db_type(connection)) % qn(f.column) for f in self.fields]\n return Atoms(self.fields, lhs)","def field_names(self):\n ...","def format_colname(name):\n colnames = [\n \"AV\",\n \"RV\",\n \"EBV\",\n \"CAV1\",\n \"CAV2\",\n \"CAV3\",\n \"CAV4\",\n \"C1\",\n \"C2\",\n \"C3\",\n \"C4\",\n \"x_o\",\n \"gamma\",\n \"bump_area\",\n \"fh2\",\n \"nhtot\",\n \"nh2\",\n \"nhi\",\n \"NH_AV\",\n \"NH_EBV\",\n ]\n plotnames = [\n \"$A(V)$\",\n \"$R(V)$\",\n \"$E(B-V)$\",\n \"$C^{A(V)}_1$\",\n \"$C^{A(V)}_2$\",\n \"$C^{A(V)}_3$\",\n \"$C^{A(V)}_4$\",\n \"$C_1$\",\n \"$C_2$\",\n \"$C_3$\",\n \"$C_4$\",\n \"$x_o$\",\n r\"$\\gamma$\",\n r\"$\\pi C^{A(V)}_3 / 2 \\gamma$\",\n \"$f(H_2)$\",\n \"$N(H)$\",\n \"$N(H_2)$\",\n \"$N(HI)$\",\n \"$N(H)/A(V)$\",\n \"$N(H)/E(B-V)$\",\n ]\n dic_pairs = dict(zip(colnames, plotnames))\n\n out_name = name\n if name[:3] == \"log\":\n out_name = r\"$\\log (\" + name[3:].upper() + \")$\"\n elif name in dic_pairs.keys():\n out_name = dic_pairs[name]\n\n return out_name","def _field_prefix(self):\n if self.layer_name == 'geninfo':\n return ''\n return self.layer_name + '.'","def _make_alias(self, agg_func, code, col):\n\t\treturn DELIMITER.join([agg_func.prefix(), code, self.name(), col])","def _field_name_flag(field: _d.Field):\r\n return f\"--{field.name.rstrip('_').replace('_', '-')}\""],"string":"[\n \"def _update_column_name(self, column, idx, old_name, name):\\n dtype = self.dtype\\n # Updating the names on the dtype should suffice\\n dtype.names = dtype.names[:idx] + (name,) + dtype.names[idx + 1 :]\",\n \"def py_field_name(self, field):\\n name = field.name\\n name = as_identifier(name)\\n if self.options(field).convert_case:\\n name = from_camel_case(name)\\n name = self._mangle_name(name)\\n return name\",\n \"def col_name(col):\\n\\n if isinstance(col, str):\\n return col\\n return col.__name__\",\n \"def encodeColumnName(self, column):\\r\\n return '\\\"{}\\\"'.format(column)\",\n \"def column_name(name):\\n # Only needs exceptions to standard token cleanup\\n column_map = {\\n \\\"line#\\\" : \\\"ignore\\\",\\n \\\"date\\\" : \\\"timestamp\\\",\\n \\\"rh\\\" : \\\"humidity\\\",\\n \\\"par\\\" : \\\"par_ue\\\"\\n }\\n\\n if name in column_map:\\n return column_map[name]\\n \\n return name\",\n \"def set_column_name(self, name):\\r\\n self.column_name = name\",\n \"def set_column_name(self, name):\\r\\n self.column_name = name\",\n \"def _column_original_name(name):\\n if ':' in name:\\n return name.split(':')[-1]\\n else:\\n return name\",\n \"def name(self):\\n if self.table:\\n return \\\"{}.{}\\\".format(self.table, self.field_name)\\n return self.field_name\",\n \"def wrap_columns_name(self, format_string):\\n self._data_frame = self._data_frame.rename(\\n columns=lambda column: format_string.format(column)\\n )\",\n \"def rename_columns(self, col):\\n try:\\n self.cleaned_data.columns = col\\n except Exception as e:\\n raise e\",\n \"def db_field_name(self):\\r\\n return self.db_field or self.column_name\",\n \"def db_field_name(self):\\r\\n return self.db_field or self.column_name\",\n \"def short_column(name : str) -> str:\\n return name.split(\\\"-\\\")[1]\",\n \"def get_name(self):\\n return self.col_name\",\n \"def capnp_field_name(self, field):\\n name = field.name\\n return as_identifier(name)\",\n \"def _valid_column(column_name):\\n return str(column_name)\",\n \"def namehack(field):\\n if field.endswith((\\\"attribute\\\", \\\"views\\\")):\\n return field + \\\"__name\\\"\\n else:\\n return field\",\n \"def column_name(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"column_name\\\")\",\n \"def column_name(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"column_name\\\")\",\n \"def _validate_column_name(col_name : str) -> str:\\n\\n if col_name[0].isdigit():\\n return f'\\\"{col_name}\\\"'\\n return col_name\",\n \"def typed_column(self) -> str:\\n\\n return \\\"{}:{}\\\".format(self.name, self.dtype)\",\n \"def rename(self, newname):\\n # set the new column name\\n self.colname = newname\",\n \"def __getitem__(self, item):\\n if isinstance(item, str):\\n name_dict = {n.lower():n for n in self.colnames}\\n item = item.lower()\\n item = ','.join([name_dict[i] for i in item.split(',')])\\n out = APtable.__getitem__(self, item)\\n return out\",\n \"def as_field(identifier: str) -> str:\\n return identifier.lower()\",\n \"def _remap_column_names(self, frame):\\n\\n frame[TransactionColumns.BANK.name] = self.INSTITUTION\\n frame[TransactionColumns.ACCOUNT.name] = self.account\\n frame.rename(columns=self._FIELD_2_TRANSACTION, inplace=True)\\n frame[TransactionColumns.CHECK_NO.name] = None\\n return frame\",\n \"def column_name(self) -> Optional[str]:\\n return pulumi.get(self, \\\"column_name\\\")\",\n \"def test_column_name(self):\\n field = self.base_field\\n sch = SchemaField(field)\\n self.assertEqual(sch.name, sch.column_name)\\n self.assertNotEqual(sch.column_name, sch.title)\",\n \"def getColName(self, col):\\n try:\\n return chr(ord('a') + col)\\n except:\\n return col\",\n \"def getColName(self, col):\\n try:\\n return chr(ord('a') + col)\\n except:\\n return col\",\n \"def generate_field_name(container, field):\\n if \\\"standard_name\\\" in container.fields[field]:\\n field_name = container.fields[field][\\\"standard_name\\\"]\\n elif \\\"long_name\\\" in container.fields[field]:\\n field_name = container.fields[field][\\\"long_name\\\"]\\n else:\\n field_name = str(field)\\n field_name = field_name.replace(\\\"_\\\", \\\" \\\")\\n field_name = field_name[0].upper() + field_name[1:]\\n return field_name\",\n \"def __set_name(self):\\n table_name = self.get_table_name()\\n record, timestamp = self.__get_max_timestamp()\\n self.name = \\\"%s_%s_%s\\\" % (table_name, record, timestamp)\",\n \"def new_index_name(self, column, unique=False):\\n table_name = self.name.lstrip('migrate_')\\n column = column.replace(', ', '')\\n return '{}_{}_{}{}'.format(table_name, column, self._random_string(6), '_unique' if unique else '')\",\n \"def format_column(self, column, use_table=False, name=None, table_name=None):\\n if name is None:\\n name = column.name\\n if not getattr(column, 'is_literal', False):\\n if use_table:\\n return self.format_table(column.table, use_schema=False, name=table_name) + \\\".\\\" + self.__generic_obj_format(column, name)\\n else:\\n return self.__generic_obj_format(column, name)\\n else:\\n # literal textual elements get stuck into ColumnClause alot, which shouldnt get quoted\\n if use_table:\\n return self.format_table(column.table, use_schema=False, name=table_name) + \\\".\\\" + name\\n else:\\n return name\",\n \"def test_dummydb_add_data_to_table_wrong_column_name(self):\\n db = DummyDB()\\n columns = {\\n \\\"one\\\": int,\\n \\\"two\\\": str,\\n \\\"three\\\": bool,\\n }\\n db.create_table(\\\"new_table\\\", columns)\\n result = db.select(\\\"new_table\\\", four=1)\",\n \"def _field_name(self) -> str:\\n name = self._resolve_field_name()\\n if name is None:\\n # pylint: disable=consider-using-f-string\\n raise FieldNameError(\\n \\\"No field name found among: explicit name = {}, inferred name = {}\\\".format(\\n self.__name_explicit, self.__name_contextual\\n )\\n )\\n return name\",\n \"def safe_column_name(string):\\n string = unidecode(string.replace(' ', '_').lower())\\n return re.sub(r'[^0-9a-z_]','', string)\",\n \"def alter_column(self, table_name, name, field, explicit_name=True):\\r\\n # Get the column's SQL\\r\\n field.set_attributes_from_name(name)\\r\\n if not explicit_name:\\r\\n name = field.column\\r\\n sql = self.column_sql(table_name, name, field)\\r\\n # Remake the table correctly\\r\\n self._remake_table(table_name, altered={name: sql})\",\n \"def new_constraint_name(self, column, type):\\n name = self.name.lstrip('migrate_')[:30]\\n if type == 'UNIQUE':\\n return '{}_{}_{}_uniq'.format(name, column[:15], self._random_string(8))\\n elif type == 'PRIMARY KEY':\\n return '{}_{}_pkey'.format(name, self._random_string(4))\\n else:\\n raise NotImplementedError('Name not implemented for type {}'.format(type))\",\n \"def name_field(self):\\r\\n return 'name'\",\n \"def __getitem__(self, field_name: str) -> ColumnField:\\n return ColumnField(self, field_name=field_name)\",\n \"def undo_format_field_name(field_name):\\n if json_api_settings.FORMAT_FIELD_NAMES:\\n return format_value(field_name, \\\"underscore\\\")\\n\\n return field_name\",\n \"def update_column_title(col):\\n col_type = self.features_bucket_mapping_.get(col).type\\n return [f\\\"Feature '{col}'\\\"], [col_type]\",\n \"def __tablename__(self):\\n return sub(r\\\"(? str:\\n\\n return re.sub(r\\\"_[^_]+$\\\", \\\"\\\", field_name).replace(\\\"human_readable_\\\", \\\"\\\")\",\n \"def update_column_format(self):\\n pass\",\n \"def columnName(self):\\n return self.__column\",\n \"def _get_column_name(df, name='agg'):\\n while name in df.columns:\\n name += '_'\\n return name\",\n \"def get_column_name(self) -> str:\\n if self.is_shared():\\n assert self._shared_id is not None\\n return self._shared_id\\n else:\\n return str(id(self))\",\n \"def get_column_def(self):\\r\\n return '{} {}'.format(self.cql, self.db_type)\",\n \"def _clean_up_table_column_names(loop_dict):\\n \\n # Make the column names all lowercase\\n # and remove any underscores from the beginning\\n for key in loop_dict.keys():\\n rename_dict = { x:re.sub(r\\\"\\\"\\\"^_\\\"\\\"\\\", '', x.lower()) for x in loop_dict[key].columns }\\n loop_dict[key].rename(columns=rename_dict, inplace=True)\\n \\n return loop_dict\",\n \"def change_type(self, col_name, str_type):\\n if self[col_name] is not None:\\n self[col_name] = self[col_name].astype(str_type)\",\n \"def _str_colnames(self):\\n return ', '.join(self.galcat.colnames)\",\n \"def substitute_names(df):\\n\\n masking_tag = '_sql'\\n duplicated_names = ['SwitchName', 'Fabric_Name', 'SwitchMode', 'Memory_Usage', 'Flash_Usage', 'Speed']\\n replace_dct = {orig_name + masking_tag: orig_name for orig_name in duplicated_names}\\n df.rename(columns=replace_dct, inplace=True)\",\n \"def _get_custom_attribute_field_name(self, attribute):\\n return 'attribute_{0}'.format(attribute.id)\",\n \"def namingConvention(columnName):\\n words = columnName.lower().split(\\\"_\\\")\\n\\n def cap(word):\\n if word.lower() == \\\"id\\\":\\n return word.upper()\\n else:\\n return word.capitalize()\\n\\n return words[0] + \\\"\\\".join(map(cap, words[1:]))\",\n \"def colNames_string(self):\\n # SELECT column_name FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = 'some_table';\\n return \\\"SELECT column_name FROM INFORMATION_SCHEMA.COLUMNS WHERE TABLE_NAME = \\\"\",\n \"def fix_name(row, index, name_map):\\n # print(\\\"Input row: {}\\\".format(row))\\n name = row[index].strip()\\n # print(\\\"Name entry is {}\\\".format(name))\\n if name.endswith(\\\" (yourself)\\\"):\\n name = name[:-len(\\\" (yourself)\\\")]\\n # print(\\\"Shortening to |{}|\\\".format(name))\\n if name not in name_map:\\n name_map[name] = name # Initially the identity transform\\n row[index] = name_map[name]\",\n \"def give_field(self, name):\\n return self.field(name).toPyObject()\",\n \"def get_ast_field_name(ast):\\n replacements = {\\n # We always rewrite the following field names into their proper underlying counterparts.\\n TYPENAME_META_FIELD_NAME: '@class'\\n }\\n base_field_name = ast.name.value\\n normalized_name = replacements.get(base_field_name, base_field_name)\\n return normalized_name\",\n \"def _table_name(self, name: AnyStr) -> bytes:\\n name = ensure_bytes(name)\\n if self.table_prefix is None:\\n return name\\n return self.table_prefix + self.table_prefix_separator + name\",\n \"def name(self) -> str:\\n return self.fqtable.replace(\\\".\\\", \\\"_\\\")\",\n \"def _str_colnames(self):\\n return ', '.join(self.colnames)\",\n \"def to_sql(self, model_cls, field_name, value):\\n raise NotImplementedError # pragma: no cover\",\n \"def NAME(self) -> str:\\n return self._field_name\",\n \"async def set_db_name_field(self, db_name_field):\\n self.db_name_field = db_name_field\",\n \"def new_fk_index_name(self, column, fk_column):\\n return '{}_refs_{}_{}'.format(column, fk_column, self._random_string(8))\",\n \"def rename(self, old_column, new_column, data_type):\\n self.table.rename_column(old_column, new_column, data_type)\\n return self\",\n \"def __tablename__(cls) -> str:\\n return inflection.underscore(cls.__name__)\",\n \"def _label(self, column):\\n # XXX\\n return column\",\n \"def undo_format_field_names(obj):\\n if json_api_settings.FORMAT_FIELD_NAMES:\\n return format_field_names(obj, \\\"underscore\\\")\\n\\n return obj\",\n \"def rename_columns(self):\\n self.data.rename(columns={\\n 'DealerID': 'd_id',\\n 'DealerName': 'd_name',\\n 'Type': 'stock_type', # Needs capitalization\\n 'Stock': 'stock_id',\\n 'VIN': 'vin',\\n 'Year': 'year',\\n 'Make': 'make',\\n 'Model': 'model',\\n 'Body': 'trim', # Needs parsing\\n 'Trim': 'body_style',\\n 'Doors': 'doors',\\n 'ExtColor': 'exterior_colour',\\n 'IntColor': 'interior_colour',\\n 'EngCylinders': 'cylinders',\\n 'EngDisplacement': 'displacement', # Needs parsing\\n 'Transmission': 'transmission_description', # Needs parsing and split\\n 'Odometer': 'odometer',\\n 'Price': 'price',\\n 'MSRP': 'msrp',\\n 'Description': 'description',\\n 'EngType': 'configuration',\\n 'EngFuel': 'fuel_type',\\n 'Drivetrain': 'drivetrain',\\n 'ExtColorGeneric': 'exterior_colour_generic', # Needs parsing\\n 'IntColorGeneric': 'interior_colour_generic', # Needs parsing\\n 'PassengerCount': 'passengers'\\n }, inplace=True)\\n\\n return None\",\n \"def get_field(cls, name):\\n if name not in cls.get_field_names():\\n # - check field name first, next: column name -\\n name = cls.get_field_name(name)\\n return getattr(cls, name, None)\",\n \"def setFieldNames(self, model, lyr): \\n #get the fields\\n fields = lyr.pendingFields()\\n position = 0\\n \\n #set column names\\n for field in fields:\\n model.setHorizontalHeaderItem(position, QStandardItem(field.name()))\\n position+=1\",\n \"def _transformed_name(key: Text) -> Text:\\n return key + \\\"_xf\\\"\",\n \"def make_column(options, name, column):\\n # (ElasticsearchFDWOptions, str, multicorn.ColumnDefinition) -> Column\\n assert name not in {\\n options.rowid_column,\\n options.score_column,\\n options.query_column,\\n }, \\\"Programmer error: bad name passed to make_column {name}\\\".format(name=name)\\n\\n if column.base_type_name.upper() in {\\\"JSON\\\", \\\"JSONB\\\"}:\\n return JsonColumn(name=name)\\n return BasicColumn(name=name)\",\n \"def __init__(self, column_type, name):\\n self.column_type = column_type\\n self.name = name\",\n \"def autoname(self):\\n ret = \\\"%(table)s_%(reftable)s_fkey\\\"%dict(\\n table=self.table.name,\\n reftable=self.reftable.name,\\n )\\n return ret\",\n \"def act_on_column_name(self, *, arg, value):\\n assert arg is None\\n assert isinstance(value, str)\",\n \"def translate_db_fields(cls, data):\\r\\n dst_data = data.copy()\\r\\n for name, col in cls._columns.items():\\r\\n key = col.db_field or name\\r\\n if key in dst_data:\\r\\n dst_data[name] = dst_data.pop(key)\\r\\n\\r\\n return dst_data\",\n \"def del_column(self, fieldname):\\n ...\",\n \"def _sanitize_field_name(self, field_name):\\n field_name = field_name.replace(self._field_prefix, '')\\n return field_name.replace('.', '_')\",\n \"def camel_case_to_mysql(name: str) -> str:\\n\\n view_name = name\\n\\n # Convert to MySQL view name\\n idx_prefix = 'Ix'\\n if view_name.startswith(idx_prefix):\\n view_name = view_name.replace(idx_prefix, '', 1)\\n return CobolDefinition.name_to_snake_case(view_name) + '_view'\\n\\n return CobolDefinition.name_to_snake_case(view_name)\",\n \"def rename_id_col(df: pd.DataFrame):\\r\\n for col in df.columns:\\r\\n if \\\"id\\\" in col:\\r\\n df.rename(columns={col: col.replace(\\\"-\\\", \\\"_\\\")}, inplace=True)\\r\\n return df\",\n \"def test_rename_column(self):\\n name_column = Varchar()\\n name_column._meta.name = \\\"name\\\"\\n\\n title_column = Varchar()\\n title_column._meta.name = \\\"title\\\"\\n\\n schema: t.List[DiffableTable] = [\\n DiffableTable(\\n class_name=\\\"Band\\\",\\n tablename=\\\"band\\\",\\n columns=[name_column],\\n )\\n ]\\n schema_snapshot: t.List[DiffableTable] = [\\n DiffableTable(\\n class_name=\\\"Band\\\",\\n tablename=\\\"band\\\",\\n columns=[title_column],\\n )\\n ]\\n\\n schema_differ = SchemaDiffer(\\n schema=schema, schema_snapshot=schema_snapshot, auto_input=\\\"y\\\"\\n )\\n\\n self.assertTrue(len(schema_differ.rename_columns.statements) == 1)\\n self.assertEqual(\\n schema_differ.rename_columns.statements[0],\\n \\\"manager.rename_column(table_class_name='Band', tablename='band', old_column_name='title', new_column_name='name', old_db_column_name='title', new_db_column_name='name')\\\", # noqa\\n )\",\n \"def update_column_title():\\n\\n column_id = request.get_json()['column_id']\\n column_title = request.get_json()['column_title']\\n\\n return sql_manager.update_column_title(column_id, column_title)\",\n \"def __to_key(name: str) -> str:\\n return name.replace(\\\" \\\", \\\"-\\\")\",\n \"def get_column_def(self):\\r\\n db_type = self.db_type.format(self.value_type.db_type)\\r\\n return '{} {}'.format(self.cql, db_type)\",\n \"def _normalize_column(column):\\n if not isinstance(column, str):\\n msg = \\\"expected column of type 'str', got {0!r} instead\\\"\\n raise TypeError(msg.format(column.__class__.__name__))\\n column = column.strip()\\n column = column.replace('\\\"', '\\\"\\\"') # Escape quotes.\\n if column == '':\\n column = '_empty_'\\n return '\\\"' + column + '\\\"'\",\n \"def _normalize_column(column):\\n if not isinstance(column, str):\\n msg = \\\"expected column of type 'str', got {0!r} instead\\\"\\n raise TypeError(msg.format(column.__class__.__name__))\\n column = column.strip()\\n column = column.replace('\\\"', '\\\"\\\"') # Escape quotes.\\n if column == '':\\n column = '_empty_'\\n return '\\\"' + column + '\\\"'\",\n \"def get_field_class_name(field):\\n return field.capitalize() + \\\"Field\\\"\",\n \"def _resolve_ref(self, name):\\n if name not in self.fields:\\n raise RuntimeError(\\\"No field with name `{}`\\\".format(name))\\n\\n field = self.fields.get(name)\\n field.set_attributes_from_name(name)\\n return Col(self.name, field, output_field=field)\",\n \"def sql_for_columns(self, data, qn, connection):\\n table_alias, _name, db_type = data\\n\\n fun = connection.ops.field_cast_sql\\n\\n if table_alias:\\n lhs = [fun(f.db_type(connection)) % '%s.%s' % (qn(table_alias), qn(f.column)) for f in self.fields]\\n else:\\n lhs = [fun(f.db_type(connection)) % qn(f.column) for f in self.fields]\\n return Atoms(self.fields, lhs)\",\n \"def field_names(self):\\n ...\",\n \"def format_colname(name):\\n colnames = [\\n \\\"AV\\\",\\n \\\"RV\\\",\\n \\\"EBV\\\",\\n \\\"CAV1\\\",\\n \\\"CAV2\\\",\\n \\\"CAV3\\\",\\n \\\"CAV4\\\",\\n \\\"C1\\\",\\n \\\"C2\\\",\\n \\\"C3\\\",\\n \\\"C4\\\",\\n \\\"x_o\\\",\\n \\\"gamma\\\",\\n \\\"bump_area\\\",\\n \\\"fh2\\\",\\n \\\"nhtot\\\",\\n \\\"nh2\\\",\\n \\\"nhi\\\",\\n \\\"NH_AV\\\",\\n \\\"NH_EBV\\\",\\n ]\\n plotnames = [\\n \\\"$A(V)$\\\",\\n \\\"$R(V)$\\\",\\n \\\"$E(B-V)$\\\",\\n \\\"$C^{A(V)}_1$\\\",\\n \\\"$C^{A(V)}_2$\\\",\\n \\\"$C^{A(V)}_3$\\\",\\n \\\"$C^{A(V)}_4$\\\",\\n \\\"$C_1$\\\",\\n \\\"$C_2$\\\",\\n \\\"$C_3$\\\",\\n \\\"$C_4$\\\",\\n \\\"$x_o$\\\",\\n r\\\"$\\\\gamma$\\\",\\n r\\\"$\\\\pi C^{A(V)}_3 / 2 \\\\gamma$\\\",\\n \\\"$f(H_2)$\\\",\\n \\\"$N(H)$\\\",\\n \\\"$N(H_2)$\\\",\\n \\\"$N(HI)$\\\",\\n \\\"$N(H)/A(V)$\\\",\\n \\\"$N(H)/E(B-V)$\\\",\\n ]\\n dic_pairs = dict(zip(colnames, plotnames))\\n\\n out_name = name\\n if name[:3] == \\\"log\\\":\\n out_name = r\\\"$\\\\log (\\\" + name[3:].upper() + \\\")$\\\"\\n elif name in dic_pairs.keys():\\n out_name = dic_pairs[name]\\n\\n return out_name\",\n \"def _field_prefix(self):\\n if self.layer_name == 'geninfo':\\n return ''\\n return self.layer_name + '.'\",\n \"def _make_alias(self, agg_func, code, col):\\n\\t\\treturn DELIMITER.join([agg_func.prefix(), code, self.name(), col])\",\n \"def _field_name_flag(field: _d.Field):\\r\\n return f\\\"--{field.name.rstrip('_').replace('_', '-')}\\\"\"\n]"},"negative_scores":{"kind":"list like","value":["0.7072573","0.7007338","0.6994978","0.69579434","0.68072045","0.6802428","0.6802428","0.67907166","0.6732477","0.6600031","0.65641886","0.64931035","0.64931035","0.64816284","0.6459289","0.64281356","0.63902634","0.6334104","0.6324554","0.6324554","0.62862897","0.6277314","0.62329","0.6204517","0.6178222","0.61457276","0.6116452","0.61137515","0.6037867","0.6037867","0.6021725","0.60192513","0.59939206","0.5990731","0.59853417","0.59742796","0.59728163","0.5941572","0.59278464","0.5924766","0.59223235","0.5900049","0.5889538","0.5882949","0.58741105","0.5867748","0.5842101","0.5841567","0.5837694","0.5822072","0.57839173","0.5775221","0.5773551","0.5761088","0.575862","0.57581127","0.57547784","0.5732902","0.5731511","0.5722033","0.5713239","0.57056814","0.57017636","0.5689161","0.56811345","0.5664873","0.56612074","0.56606156","0.56585294","0.5655326","0.56533086","0.5653031","0.56509554","0.5647386","0.5626526","0.559765","0.55964524","0.5589174","0.55836254","0.5583242","0.5581165","0.5576898","0.5574576","0.5564658","0.5562101","0.55595887","0.55535525","0.55443704","0.5535675","0.55331427","0.5527466","0.5527466","0.55250585","0.55134696","0.55020696","0.5501646","0.54988164","0.5492232","0.5490315","0.54811484"],"string":"[\n \"0.7072573\",\n \"0.7007338\",\n \"0.6994978\",\n \"0.69579434\",\n \"0.68072045\",\n \"0.6802428\",\n \"0.6802428\",\n \"0.67907166\",\n \"0.6732477\",\n \"0.6600031\",\n \"0.65641886\",\n \"0.64931035\",\n \"0.64931035\",\n \"0.64816284\",\n \"0.6459289\",\n \"0.64281356\",\n \"0.63902634\",\n \"0.6334104\",\n \"0.6324554\",\n \"0.6324554\",\n \"0.62862897\",\n \"0.6277314\",\n \"0.62329\",\n \"0.6204517\",\n \"0.6178222\",\n \"0.61457276\",\n \"0.6116452\",\n \"0.61137515\",\n \"0.6037867\",\n \"0.6037867\",\n \"0.6021725\",\n \"0.60192513\",\n \"0.59939206\",\n \"0.5990731\",\n \"0.59853417\",\n \"0.59742796\",\n \"0.59728163\",\n \"0.5941572\",\n \"0.59278464\",\n \"0.5924766\",\n \"0.59223235\",\n \"0.5900049\",\n \"0.5889538\",\n \"0.5882949\",\n \"0.58741105\",\n \"0.5867748\",\n \"0.5842101\",\n \"0.5841567\",\n \"0.5837694\",\n \"0.5822072\",\n \"0.57839173\",\n \"0.5775221\",\n \"0.5773551\",\n \"0.5761088\",\n \"0.575862\",\n \"0.57581127\",\n \"0.57547784\",\n \"0.5732902\",\n \"0.5731511\",\n \"0.5722033\",\n \"0.5713239\",\n \"0.57056814\",\n \"0.57017636\",\n \"0.5689161\",\n \"0.56811345\",\n \"0.5664873\",\n \"0.56612074\",\n \"0.56606156\",\n \"0.56585294\",\n \"0.5655326\",\n \"0.56533086\",\n \"0.5653031\",\n \"0.56509554\",\n \"0.5647386\",\n \"0.5626526\",\n \"0.559765\",\n \"0.55964524\",\n \"0.5589174\",\n \"0.55836254\",\n \"0.5583242\",\n \"0.5581165\",\n \"0.5576898\",\n \"0.5574576\",\n \"0.5564658\",\n \"0.5562101\",\n \"0.55595887\",\n \"0.55535525\",\n \"0.55443704\",\n \"0.5535675\",\n \"0.55331427\",\n \"0.5527466\",\n \"0.5527466\",\n \"0.55250585\",\n \"0.55134696\",\n \"0.55020696\",\n \"0.5501646\",\n \"0.54988164\",\n \"0.5492232\",\n \"0.5490315\",\n \"0.54811484\"\n]"},"document_score":{"kind":"string","value":"0.7277575"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8560,"cells":{"query":{"kind":"string","value":"Given the database connection, the table name, and the cursor row description, this routine will return the given field type name, as well as any additional keyword parameters and notes for the field."},"document":{"kind":"string","value":"def get_field_type(connection, table_name, row):\n field_params = OrderedDict()\n field_notes = []\n is_geometry = False\n try:\n field_type = connection.introspection.get_field_type(row[1], row)\n except KeyError:\n field_type = 'TextField'\n field_notes.append('This field type is a guess.')\n\n # This is a hook for data_types_reverse to return a tuple of\n # (field_type, field_params_dict).\n if type(field_type) is tuple:\n field_type, new_params = field_type\n field_params.update(new_params)\n\n # Add max_length for all CharFields.\n if field_type == 'CharField' and row[3]:\n field_params['max_length'] = int(row[3])\n\n if field_type == 'DecimalField':\n if row[4] is None or row[5] is None:\n field_notes.append(\n 'max_digits and decimal_places have been guessed, as this '\n 'database handles decimal fields as float')\n field_params['max_digits'] = row[4] if row[4] is not None else 10\n field_params['decimal_places'] = row[\n 5] if row[5] is not None else 5\n else:\n field_params['max_digits'] = row[4]\n field_params['decimal_places'] = row[5]\n\n if field_type == 'GeometryField':\n geo_col = row[0]\n # Getting a more specific field type and any additional parameters\n # from the `get_geometry_type` routine for the spatial backend.\n field_type, geo_params = connection.introspection.get_geometry_type(\n table_name, geo_col)\n field_params.update(geo_params)\n is_geometry = True\n\n return field_type, field_params, is_geometry\n # return getattr(models.fields, field_type), field_params"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _get_fields(self):\n if not self._cursor.description:\n return {}\n\n results = {}\n column = 0\n\n for des in self._cursor.description:\n fieldname = des[0]\n results[column] = fieldname\n column = column + 1\n\n return results","def get_field_type(self, table_name, field_name):\n \n dtype = self.field_types[(self.field_types.TABNAME == table_name) & (self.field_types.FIELDNAME == field_name)]['DATATYPE'].values[0] \n return dtype","def getFieldDetails(self, field_name):\n try:\n value_list = []\n con = self.getMetadataDatabaseConnection()\n results = con.cursor()\n con.cursor().callproc('qiime_assets.get_field_details', [field_name, results])\n\n for row in results:\n # column_name, data_type, desc_or_value, definition, active\n value_list.append((row[0], row[1], row[2], row[3], row[4]))\n \n if len(value_list) == 0:\n # If not found in the dictionary, assume this is a user-created column\n value_list.append((field_name, 'text', '', ''))\n \n return value_list[0]\n except Exception, e:\n print 'Exception caught: %s.\\nThe error is: %s' % (type(e), e)\n return False","def get_geometry_type(self, table_name, description):\n with self.connection.cursor() as cursor:\n cursor.execute(\n \"\"\"\n SELECT t.coord_dimension, t.srid, t.type FROM (\n SELECT * FROM geometry_columns\n UNION ALL\n SELECT * FROM geography_columns\n ) AS t WHERE t.f_table_name = %s AND t.f_geometry_column = %s\n \"\"\",\n (table_name, description.name),\n )\n row = cursor.fetchone()\n if not row:\n raise Exception(\n 'Could not find a geometry or geography column for \"%s\".\"%s\"'\n % (table_name, description.name)\n )\n dim, srid, field_type = row\n # OGRGeomType does not require GDAL and makes it easy to convert\n # from OGC geom type name to Django field.\n field_type = OGRGeomType(field_type).django\n # Getting any GeometryField keyword arguments that are not the default.\n field_params = {}\n if self.postgis_oid_lookup.get(description.type_code) == \"geography\":\n field_params[\"geography\"] = True\n if srid != 4326:\n field_params[\"srid\"] = srid\n if dim != 2:\n field_params[\"dim\"] = dim\n return field_type, field_params","def _convert_field_type(row):\n return row","def get_column_def(self):\r\n return '{} {}'.format(self.cql, self.db_type)","def parse_description(_descriptions, _db_type):\n _field_names = []\n _field_types = []\n\n \"\"\"name, type_code, display_size, internal_size, precision, scale, null_ok\"\"\"\n\n for _column in _descriptions:\n _field_names.append(_column[0])\n if _db_type == DB_MYSQL:\n _field_types.append(mysql_type_to_sql_type(_column[1]))\n else:\n _field_types.append(_column[1])\n\n return _field_names, _field_types","def test_get_field_type_text_field(self):\n db_introspection = DatabaseIntrospection(self.connection)\n self.assertEqual(\n db_introspection.get_field_type(\n TypeCode.STRING,\n description=ColumnInfo(\n name=\"name\",\n type_code=TypeCode.STRING,\n internal_size=\"MAX\",\n ),\n ),\n \"TextField\",\n )","def field_type(self):\n return \"\"","def field_type(name):\n if name not in field_types:\n field_types[name] = records.fields_get([name], attributes=['type'])[name]['type']\n return field_types.get(name)","def findMetadataTable(self, field_name, field_type, log, study_id, lock):\n \n # log passed in from writeMetadataValue() - it's a list. At end of function, \n # exception handler will output contents of log to web for viewing if error\n # occurrs.\n \n try:\n table = ''\n field_name = field_name.upper()\n field_name.replace('\"', '')\n\n # Fill out the field list if it's the first call\n log.append('Length of fields is: {0}'.format(str(len(self.fields))))\n if len(self.fields) == 0:\n log.append('Filling out field list for table lookup. Current field is \"{0}\"'.format(field_name))\n lock.acquire()\n con = self.getMetadataDatabaseConnection()\n results = con.cursor()\n con.cursor().callproc('qiime_assets.find_metadata_table', [results])\n for tab_name, col_name in results:\n if col_name not in self.fields:\n self.fields[col_name] = []\n self.fields[col_name].append(tab_name)\n lock.release()\n \n log.append('field{} successfully filled out')\n \n if field_name in self.fields:\n # If there's only one hit we can assign it\n tables = self.fields[field_name]\n log.append('Type of variable is: %s' % str(tables))\n if len(self.fields[field_name]) == 1:\n table = self.fields[field_name][0]\n log.append('Field only in one table: %s' % table)\n \n # More than one table was found with this column name. Find the correct one\n # based on the study id\n else:\n log.append('Field in multiple tables(%s): %s' % (len(self.fields[field_name]), str(self.fields[field_name])))\n log.append('Study is is: %s' % study_id)\n for table_name in self.fields[field_name]:\n if str(study_id) in table_name:\n table = table_name\n \n # If table is not found, assume user-defined column\n else:\n \"\"\" Code may look bizarre... but here's why:\n 1. To streamline access and prevent blocking, we first check to see if the field\n does exist in the field list. If it does, we do not have to lock and can simply\n look up the table name.\n \n 2. If field is not in list, it must be a new column. In this case we must lock the \n code that handles new column creation. The catch is that if two threads both hit the lock\n with the same field name, one will get in and the other will block. Once the initial thread \n exists, it will have handled the new column, gotten the appropriate table name, and returned. \n The 2nd thread will now enter the critical section, however if we don't again check to see \n if the field is now in the field list, it will attempt to create the same column again and \n fail. Thus we check a 2nd time to see if the field exists and if so, simply read it from the \n field list. \n \"\"\"\n lock.acquire() \n if field_name in self.fields:\n log.append('Field now exists. Pulling from local list.')\n table = self.fields[field_name][0]\n log.append('Table name exists. Using \"%s\".' % table)\n else:\n log.append('Entities do not exist. Creating...')\n table = self.handleExtraData(study_id, field_name, field_type, log)\n log.append('Entities created. Table name is \"%s\"' % table)\n if field_name not in self.fields:\n self.fields[field_name] = [table]\n else:\n self.fields[field_name].append(table)\n lock.release()\n \n log.append('Returning from findMetadataTable with value: %s' % str(table))\n return table\n\n except Exception, e:\n lock.release()\n log.append('Exception caught: %s' % str(e))\n print 'Exception caught: %s.\\nThe error is: %s' % (type(e), e)\n raise Exception('\\n'.join(log))","def get_column_def(self):\r\n db_type = self.db_type.format(self.value_type.db_type)\r\n return '{} {}'.format(self.cql, db_type)","def get_unique_name(self, cursor, field_name=None):\n if cursor.kind in [CursorKind.UNEXPOSED_DECL]:\n return ''\n # covers most cases\n name = cursor.spelling\n if cursor.kind == CursorKind.CXX_BASE_SPECIFIER:\n name = cursor.type.spelling\n # if it's a record decl or field decl and its type is anonymous\n if name == '':\n # if cursor.is_anonymous():\n # a unnamed object at the root TU\n if (cursor.semantic_parent\n and cursor.semantic_parent.kind == CursorKind.TRANSLATION_UNIT):\n name = self.make_python_name(cursor.get_usr())\n log.debug('get_unique_name: root unnamed type kind %s',cursor.kind)\n elif cursor.kind in [CursorKind.STRUCT_DECL,CursorKind.UNION_DECL,\n CursorKind.CLASS_DECL,CursorKind.FIELD_DECL]:\n name = self._make_unknown_name(cursor, field_name)\n log.debug('Unnamed cursor type, got name %s',name)\n else:\n log.debug('Unnamed cursor, No idea what to do')\n #import code\n #code.interact(local=locals())\n return ''\n if cursor.kind in [CursorKind.STRUCT_DECL,CursorKind.UNION_DECL,\n CursorKind.CLASS_DECL, CursorKind.CXX_BASE_SPECIFIER]:\n names= {CursorKind.STRUCT_DECL: 'struct',\n CursorKind.UNION_DECL: 'union',\n CursorKind.CLASS_DECL: 'class',\n CursorKind.TYPE_REF: '',\n CursorKind.CXX_BASE_SPECIFIER: 'class'\n }\n name = '%s_%s'%(names[cursor.kind],name)\n log.debug('get_unique_name: name \"%s\"',name)\n return name","def get_column_def(self):\r\n db_type = self.db_type.format(\r\n self.key_type.db_type,\r\n self.value_type.db_type\r\n )\r\n return '{} {}'.format(self.cql, db_type)","def get_eltype_from_sbmfielddesc(hgf_field):\n\tq = \"\"\"SELECT type FROM sbmFIELDDESC where name='%s'\"\"\" %(hgf_field)\n\treturn run_sql(q)[0][0]","def getdocfield(fieldname):\t\t\n\tl = [d for d in doctype_dl if d.doctype=='DocField' and d.fieldname==fieldname]\n\treturn l and l[0] or None","def test_row_description(cursor: pyodbc.Cursor):\n cursor.execute(\"create table t1(a int, b char(3))\")\n cursor.execute(\"insert into t1 values(1, 'abc')\")\n row = cursor.execute(\"select * from t1\").fetchone()\n assert cursor.description == row.cursor_description","def get_field_from_sbmfielddesc(hgf_field):\n\tq = \"\"\"SELECT * FROM sbmFIELDDESC where name='%s'\"\"\" %(hgf_field)\n\treturn run_sql(q)[0]","def get_type(self) -> str:\n return self.row_dict['type']","def _read_metadata(self, conn, tbl_name): \n # Split table name in libname and actual table name\n name, schema = tuple(tbl_name.split('.'))\n # Query the Vertica dictionary to get types and formats\n query = \"\"\"\n SELECT column_name as NAME, data_type as TYPE, data_type_length AS LENGTH \n FROM v_catalog.columns \n WHERE table_schema = '{}' AND table_name = '{}'\n \"\"\".format(name, schema)\n \n md = conn.fetch(query)\n if not len(md):\n raise ValueError('No metadata for table {}'.format(tbl_name))\n\n md = (md\n # Use variable names as row names, then remove the NAME column\n .set_index('NAME', inplace=False)\n # Compute the number of bytes for each variable It is given by the LENGTH variable\n .rename({'LENGTH': 'NUM_BYTES'}, axis=1))\n\n # Identify data types\n type_upper = md['TYPE'].str.upper()\n md['IS_TEXT'] = type_upper.str.startswith('VARCHAR')\n md['IS_BOOLEAN'] = type_upper == 'BOOLEAN'\n md['IS_INTEGER'] = type_upper.isin(['INT', 'INTEGER'])\n md['IS_FLOAT'] = (type_upper == 'FLOAT') | type_upper.str.startswith('NUMERIC')\n md['IS_DATE'] = type_upper == 'DATE'\n md['IS_TIMESTAMP'] = type_upper == 'TIMESTAMP'\n md['IS_TIME'] = type_upper == 'TIME'\n # Determine datetime formats for date and time data\n md['DATETIME_FORMAT'] = np.nan\n md.loc[md['IS_DATE'], 'DATETIME_FORMAT'] = 'yyyy-MM-dd'\n md.loc[md['IS_TIME'], 'DATETIME_FORMAT'] = 'HH:mm:ss'\n # Determine datetime formats for timestamp data\n # For timestamp data, the right format is:\n # - yyyy-MM-dd HH:mm:ss.0 with a JDBC connection <-- python default\n # - yyyy-MM-dd HH:mm:ss with an ODBC connection\n md.loc[md['IS_TIMESTAMP'], 'DATETIME_FORMAT'] = 'yyyy-MM-dd HH:mm:ss.0'\n\n # Original type\n md.rename({'TYPE': 'TYPE_IN_SOURCE'}, axis=1, inplace=True)\n # Create the metadata catalog\n md = MetadataCatalog(md, is_case_sensitive=False)\n # Check that all formats have been correctly processed\n format_check = md.check_metadata_completeness()\n if not all(format_check):\n unsupported_format = md.get_type_in_source()\n unsupported_format = unsupported_format[~format_check].unique()\n raise ValueError('Unsupported Vertica format: {}'.format(unsupported_format))\n return md","def columns_type(self,table):\n with self.conn.cursor() as cur:\n #_logger.debug('Columns Query. sql: %r', self.table_columns_query)\n cur.execute(self.columns_info_query % (self.dbname,table))\n for row in cur:\n yield row","def _get_tabletype(cls) -> str:\n raise NotImplementedError","def field_type(self) -> Optional[NameObject]:\n return self.get(\"/FT\")","def get_field_type(field):\n if (field < len(Field.FIELD_TYPES)):\n return Field.FIELD_TYPES[field][1]\n return 'unknown'","def db_field_name(self):\r\n return self.db_field or self.column_name","def db_field_name(self):\r\n return self.db_field or self.column_name","def get_column_type(type_name: str) -> object:\n raise NotImplementedError","def _get_fields(self, table):\n fields = list()\n for column in table.columns:\n fields.append({'id': column.name, 'type': str(column.type)})\n return fields","def db_fields(self):","def dict_factory(self, cursor, row):\n results = {}\n for index, col_name in enumerate(cursor.description):\n results[col_name[0]] = row[index]\n\n return results","def get_field(cls, name):\n if name not in cls.get_field_names():\n # - check field name first, next: column name -\n name = cls.get_field_name(name)\n return getattr(cls, name, None)","def cursor_data(c):\r\n\r\n # pull column description\r\n d = []\r\n for i in range(len(c.description)):\r\n d.append(c.description[i][0])\r\n\r\n # fetch column entries\r\n c = c.fetchall()\r\n\r\n # compile list\r\n info = []\r\n for i in range(len(c)):\r\n # compile dictionary entry\r\n entry = {}\r\n for j in range(len(d)):\r\n entry[d[j]] = c[i][j]\r\n info.append(entry)\t\r\n\r\n # success\r\n return info","def getfield(value, arg):\n #import pdb; pdb.set_trace()\n if hasattr(value, \"fields\"):\n fields = getattr(value, \"fields\")\n if str(arg) in fields:\n return str(fields[str(arg)])","def _update_desc(self):\n if not self.connection:\n self.close()\n cname = CREATE_BUFFER_U(1024)\n ctype_code = C_SHORT()\n csize = ctypes.c_size_t()\n cdisp_size = C_SSIZE_T(0)\n c_decimal_digits = C_SHORT()\n cnull_ok = C_SHORT()\n col_descr = []\n self._col_type_code_list = []\n for col in range(1, self._num_of_cols() + 1):\n ret = ODBC_API.SQLColAttribute(self.stmt_h, col, 6, ADDR(CREATE_BUFFER(10)), 10, ADDR(C_SHORT()), ADDR(cdisp_size))\n if ret != SQL_SUCCESS:\n check_success(self, ret)\n ret = ODBC_API.SQLDescribeColW(self.stmt_h, col, cname, len(cname), ADDR(C_SHORT()), ADDR(ctype_code), ADDR(csize), ADDR(c_decimal_digits), ADDR(cnull_ok))\n if ret != SQL_SUCCESS:\n check_success(self, ret)\n # (name, type_code, display_size,\n col_descr.append((from_buffer_u(cname), SQL_DATA_TYPE_DICT.get(ctype_code.value, (ctype_code.value,))[0], cdisp_size.value, csize.value, csize.value, c_decimal_digits.value, cnull_ok.value == 1 and True or False))\n self._col_type_code_list.append(ctype_code.value)\n if len(col_descr) > 0:\n self.description = col_descr\n # Create the row type before fetching.\n self._row_type = self.row_type_callable(self)\n else:\n self.description = None\n self._create_col_buf()","def _get_fields(self):\n tables = [self.sell_table, self.buy_table, self.pending_table]\n for table in tables:\n sql = f'SHOW COLUMNS in {table}'\n self.fields[table] = list(tb.Database().read(sql).Field)","def get_field_def(schema, parent_type, field_ast):\n name = field_ast.name.value\n if name == SchemaMetaFieldDef.name and schema.get_query_type() == parent_type:\n return SchemaMetaFieldDef\n\n elif name == TypeMetaFieldDef.name and schema.get_query_type() == parent_type:\n return TypeMetaFieldDef\n\n elif name == TypeNameMetaFieldDef.name and \\\n isinstance(parent_type, (\n GraphQLObjectType,\n GraphQLInterfaceType,\n GraphQLUnionType,\n )):\n return TypeNameMetaFieldDef\n\n elif isinstance(parent_type, (GraphQLObjectType, GraphQLInterfaceType)):\n return parent_type.get_fields().get(name)","def type(self):\n return self._field.type","def _to_known_field(cls, field_name: str, value) -> (Column, dict):\n field_names = field_name.split(\".\", maxsplit=1)\n if len(field_names) == 2:\n for field in cls.__fields__:\n if field.name == field_names[0] and field.field_type == dict:\n return field, {field_names[1]: value}\n return None, None","def dict_factory(cursor, row):\r\n\td = {}\r\n\tfor idx, col in enumerate(cursor.description):\r\n\t\td[col[0]] = row[idx]\r\n\treturn d","def dict_factory(cursor, row):\n fields = [column[0] for column in cursor.description]\n return {key: value for key, value in zip(fields, row)}","def __parse_field(self, field, tuple_descriptor, alias_on_complex_types, make_visible):\r\n alias = None\r\n field_type = None\r\n return_type = None\r\n underlying_fields = None\r\n aggregate_factory = None\r\n literal_value = None\r\n func_factory = None\r\n fields_to_verify = []\r\n parsed_fds = []\r\n field_backup = list(field)\r\n self.__clean_list(field)\r\n \r\n # parse aliases if they exist\r\n if (len(field) >= 4) and (field[-2] == QueryTokens.AS):\r\n alias = field[-1]\r\n field = field[:-2]\r\n if (field[0] == QueryTokens.STRING_LITERAL) or \\\r\n (field[0] == QueryTokens.INTEGER_LITERAL) or \\\r\n (field[0] == QueryTokens.FLOAT_LITERAL): \r\n alias = self.unnamed_operator_name()\r\n underlying_fields = []\r\n field_type = FieldType.LITERAL\r\n literal_value = field[1]\r\n if field[0] == QueryTokens.STRING_LITERAL:\r\n return_type = ReturnType.STRING\r\n elif field[0] == QueryTokens.INTEGER_LITERAL:\r\n return_type = ReturnType.INTEGER\r\n literal_value = int(literal_value)\r\n elif field[0] == QueryTokens.FLOAT_LITERAL:\r\n return_type = ReturnType.FLOAT\r\n literal_value = float(literal_value)\r\n elif field[0] == QueryTokens.COLUMN_NAME: # field or alias\r\n if alias == None:\r\n alias = field[1]\r\n field_descriptor = tuple_descriptor.get_descriptor(field[1])\r\n if field_descriptor == None: # underlying field not yet defined. mark to check later\r\n field_type = FieldType.UNDEFINED\r\n underlying_fields = [field[1]]\r\n # check alias and underlying once this process is done to\r\n # find yet-undefined fields\r\n fields_to_verify.append(field[1])\r\n fields_to_verify.append(alias)\r\n else: # field found, copy information\r\n field_type = field_descriptor.field_type\r\n return_type = field_descriptor.return_type\r\n underlying_fields = field_descriptor.underlying_fields\r\n aggregate_factory = field_descriptor.aggregate_factory\r\n func_factory = field_descriptor.func_factory\r\n elif field[0] == QueryTokens.FUNCTION_OR_AGGREGATE: # function or aggregate \r\n if alias == None:\r\n if alias_on_complex_types:\r\n raise QueryException(\"Must specify alias (AS clause) for '%s'\" % (field[1]))\r\n else:\r\n alias = self.unnamed_operator_name()\r\n underlying_field_list = field[2:]\r\n underlying_fields = []\r\n for underlying in underlying_field_list:\r\n (parsed_fd_list, parsed_verify) = self.__parse_field(underlying, tuple_descriptor, False, False)\r\n for parsed_fd in parsed_fd_list:\r\n parsed_fd.visible = False\r\n fields_to_verify.extend(parsed_verify)\r\n parsed_fds.extend(parsed_fd_list)\r\n underlying_fields.append(parsed_fd_list[0].alias)\r\n aggregate_factory = get_aggregate_factory(field[1])\r\n if aggregate_factory != None: # found an aggregate function\r\n field_type = FieldType.AGGREGATE\r\n return_type = ReturnType.FLOAT\r\n else:\r\n function_information = self.function_registry.get_function(field[1])\r\n if function_information != None:\r\n field_type = FieldType.FUNCTION\r\n func_factory = function_information.func_factory\r\n return_type = function_information.return_type\r\n else:\r\n raise QueryException(\"'%s' is neither an aggregate or a registered function\" % (field[1]))\r\n else:\r\n raise QueryException(\"Empty field clause found: %s\" % (\"\".join(field_backup)))\r\n fd = FieldDescriptor(alias, underlying_fields, field_type, return_type, aggregate_factory, func_factory, literal_value)\r\n fd.visible = make_visible\r\n parsed_fds.insert(0, fd)\r\n return (parsed_fds, fields_to_verify)","def get_field_type(field, table):\n for i in settings.GTFS_SPEC['resources']:\n print(i['name'])\n if i['name'] == table:\n for j in i['schema']['fields']:\n print(j['name'])\n if j['name'] == field:\n return j['gtfs_type']\n raise ValueError(\"Field not found in GTFS spec.\")","def dict_factory(cursor, row):\n dic = {}\n for idx, col in enumerate(cursor.description):\n if isinstance(row[idx], unicode):\n dic[col[0]] = u.unicode_to_string(row[idx])\n else:\n dic[col[0]] = row[idx]\n return dic","def datetime_type_field_name(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"datetime_type_field_name\")","def __getitem__(self, field_name):\n\n if field_name in self._module._fields.keys():\n try:\n return self._fields[field_name]\n except KeyError:\n if self['id'] == '':\n # If this is a new entry, the 'id' field is yet undefined.\n return ''\n else:\n # Retrieve the field from the SugarCRM connection.\n \n q_str = \"%s.id='%s'\" % (self._module._table, self['id'])\n res = self._module._connection.get_entry_list(\n self._module._name, q_str,\n '', 0, [field_name], 1, 0)\n\n nvl = res['entry_list'][0]['name_value_list']\n for attribute in nvl:\n if attribute == field_name:\n value = nvl[attribute]['value']\n if value:\n self._fields[attribute] = \\\n HTMLParser().unescape(\n nvl[attribute]['value'])\n else:\n self._fields[attribute] = ''\n\n return self._fields[attribute]\n\n else:\n raise AttributeError","def find_type(line):\n type_string = line.split(':')[-1].strip(\";\\n \")\n isOptional = False\n if \"|\" in type_string:\n isOptional = True\n type_string = type_string.split(' | ')[0].strip()\n\n column_type = type_mapping[type_string]\n\n register_imports(column_type, isOptional)\n\n return (column_type, isOptional)","def writeMetadataValue(self, field_type, key_field, field_name, field_value, \\\n study_id, host_key_field, row_num, lock):\n \n # This is a mess and it's slow right now. In need of serious speed improvements and cleanup.\n \n statement = ''\n log = []\n pk_name = ''\n\n try:\n #lock.acquire()\n \n # Get our database connection\n con = self.getMetadataDatabaseConnection()\n \n # Set the timeout\n #con.cursor().execute('alter session set ddl_lock_timeout=100') \n \n # Find the table name\n log.append('Locating table name...')\n table_name = None\n table_name = self.findMetadataTable(field_name, field_type, log, study_id, lock)\n log.append('Successfully found table name. Table name is \"%s\"' % str(table_name))\n \n #if field_name == 'dw1':\n # raise Exception('asdf')\n\n # Double-quote for database safety\n log.append('Adding quotes to table name...')\n table_name = '\"' + table_name + '\"' \n log.append('Quoted table name is %s' % table_name)\n log.append('Table name found: %s' % (table_name))\n \n # Store the field name in the database. These are the field names which will\n # be used later to generate a mapping file. We collect the names here because\n # it's an expensive operation to determine post-commit which fields were\n # actually submitted to the database.\n log.append('Attempting to store values in study_actual_columns: %s, %s, %s'\\\n % (study_id, field_name, table_name))\n self.addStudyActualColumn(study_id, field_name, table_name);\n \n # Get extended field info from the database\n log.append('Loading field details...')\n field_details = self.getFieldDetails(field_name)\n log.append(str(field_details))\n if field_details == None:\n log.append('Could not obtain detailed field information. Skipping.')\n raise Exception\n else:\n database_data_type = field_details[1]\n log.append('Read field database data type as \"%s\"' % database_data_type)\n \n # If the field value is 'unknown', switch to 'null' (empty string is the same as null)\n #pass_values = \n if str(field_value).upper() == 'UNKNOWN':\n field_value = ''\n # Figure out if this needs to be an integer ID instead of a text value\n elif database_data_type == 'list':\n log.append('Field is of type list. Looking up integer value...')\n named_params = {'field_value':field_value.upper()}\n statement = 'select vocab_value_id from controlled_vocab_values where upper(term) = :field_value'\n statement = str(statement)\n log.append(statement)\n results = con.cursor().execute(statement, named_params).fetchone()\n if results != None:\n # If found, set the field_value to its numeric identifier for storage\n log.append('Value found in controlled_vocab_values. Old field value: \"%s\", new field value: \"%s\".'\\\n % (field_value, results[0]))\n field_value = results[0]\n else:\n log.append('Could not determine inteteger value for list term \"%s\" with value \"%s\". Skipping.'\\\n % (field_name, field_value))\n raise Exception\n \n # Set the field_name to it's quoted upper-case name to avoid key-work issues with Oracle\n field_name = '\"%s\"' % field_name.upper()\n \n ########################################\n ### For STUDY\n ########################################\n \n # Study is special - handle separately since row is guaranteed to exist and there can only be one row\n if table_name == '\"STUDY\"' or 'EXTRA_STUDY_' in table_name:\n log.append('Updating study field...')\n named_params = {'field_value':field_value, 'study_id':study_id}\n statement = 'update %s set %s = :field_value where study_id = :study_id' % (table_name, field_name)\n statement = str(statement)\n log.append(statement)\n log.append('field_value = \"%s\", study_id = \"%s\"' % (field_value, study_id))\n results = con.cursor().execute(statement, named_params)\n con.cursor().execute('commit')\n log.append('Study updated.')\n #raise Exception\n return\n \n ########################################\n ### For other tables\n ########################################\n \n if table_name in ['\"AIR\"', '\"COMMON_FIELDS\"', '\"MICROBIAL_MAT_BIOFILM\"', '\"OTHER_ENVIRONMENT\"', \\\n '\"SAMPLE\"', '\"SEDIMENT\"', '\"SOIL\"', '\"WASTEWATER_SLUDGE\"', '\"WATER\"', '\"SEQUENCE_PREP\"', \\\n '\"HOST_ASSOC_VERTIBRATE\"', '\"HOST_ASSOCIATED_PLANT\"', '\"HOST_SAMPLE\"', '\"HUMAN_ASSOCIATED\"',\n '\"COMMON_EXTRA_SAMPLE\"', '\"COMMON_EXTRA_SAMPLE_2\"', '\"COMMON_EXTRA_PREP\"'] \\\n or 'EXTRA_SAMPLE_' in table_name or 'EXTRA_PREP_' in table_name:\n named_params = {'key_field':key_field, 'study_id':study_id}\n statement = 'select sample_id from \"SAMPLE\" where sample_name = :key_field and study_id = :study_id'\n statement = str(statement)\n key_column = 'sample_id'\n key_table = '\"SAMPLE\"'\n elif table_name in ['\"HOST\"']:\n named_params = {'key_field':'{0}:{1}'.format(str(study_id), host_key_field)}\n statement = 'select host_id from \"HOST\" where host_subject_id = :key_field'\n statement = str(statement)\n key_column = 'host_id'\n key_table = '\"HOST\"'\n else:\n return 'Unknown table found - no action taken. Table name was: \"%s\". Column name was: \"%s\"'\\\n % (table_name, field_name)\n \n # Find the assocaited key column\n log.append('Determining if required key row exists...')\n log.append(statement + '\", key_field is ' + key_field + ', study_id is ' + str(study_id))\n results = con.cursor().execute(statement, named_params).fetchone()\n if results != None:\n key_column_value = results[0]\n log.append('Found key_column_value: %s' % str(key_column_value))\n else:\n log.append('Could not determine key. Skipping write for field %s with value \"%s\".'\\\n % (field_name, field_value))\n raise Exception\n\n\n\n\n\n\n\n\n\n\n\n ####### to speed up access, create local storage for all items already seen\n\n\n\n # If it ain't there, create it\n log.append('Checking if row already exists...')\n \n # Must append row_num if sequence table\n if table_name == '\"SEQUENCE_PREP\"' or table_name == '\"COMMON_EXTRA_PREP\"' or 'EXTRA_PREP_' in table_name:\n named_params = {'key_column_value':key_column_value, 'row_number':row_num}\n statement = 'select 1 from %s where %s = :key_column_value and row_number = :row_number'\\\n % (table_name, key_column)\n else:\n named_params = {'key_column_value':key_column_value}\n statement = 'select 1 from %s where %s = :key_column_value' % (table_name, key_column)\n statement = str(statement)\n log.append(statement)\n results = con.cursor().execute(statement, named_params).fetchone()\n \n if results == None:\n log.append('No row found, inserting new row')\n if table_name == '\"SEQUENCE_PREP\"' or table_name == '\"COMMON_EXTRA_PREP\"' or 'EXTRA_PREP_' in table_name:\n log.append('Row number is %s' % (str(row_num)))\n named_params = {'key_column_value':key_column_value, 'row_number':row_num}\n statement = 'insert into %s (%s, row_number) values (:key_column_value, :row_number)'\\\n % (table_name, key_column)\n else:\n named_params = {'key_column_value':key_column_value}\n statement = 'insert into %s (%s) values (:key_column_value)' % (table_name, key_column)\n statement = str(statement)\n log.append(statement)\n con.cursor().execute(statement, named_params)\n\n\n\n\n\n\n \n # Attempt to write the metadata field\n log.append('Writing metadata value...')\n \n # If it's a date, must not put quotes around the oracle to_date function.\n if database_data_type == 'date':\n field_value = self.convertToOracleHappyName(field_value)\n if table_name == '\"SEQUENCE_PREP\"' or table_name == '\"COMMON_EXTRA_PREP\"' or 'EXTRA_PREP_' in table_name:\n statement = 'update %s set %s = %s where %s = %s and row_number = %s'\\\n % (table_name, field_name, field_value, key_column, key_column_value, row_num)\n else: \n statement = 'update %s set %s = %s where %s = %s'\\\n % (table_name, field_name, field_value, key_column, key_column_value) \n else: \n if table_name == '\"SEQUENCE_PREP\"' or table_name == '\"COMMON_EXTRA_PREP\"' or 'EXTRA_PREP_' in table_name:\n statement = 'update %s set %s = \\'%s\\' where %s = %s and row_number = %s'\\\n % (table_name, field_name, field_value, key_column, key_column_value, row_num)\n else: \n statement = 'update %s set %s = \\'%s\\' where %s = %s'\\\n % (table_name, field_name, field_value, key_column, key_column_value)\n statement = str(statement)\n log.append(statement)\n results = con.cursor().execute(statement)\n \n # Finally, commit the changes\n results = con.cursor().execute('commit')\n\n #if field_name == '\"DW1\"':\n # raise Exception('Found DW1: Dumping log')\n \n except Exception, e:\n call_string = 'writeMetadataValue(\"%s\", \"%s\", \"%s\", \"%s\", \"%s\")'\\\n % (field_type, key_field, field_name, field_value, study_id)\n log_string = '
'.join(log)\n error_msg = 'Exception caught attempting to store field \"%s\" with value \"%s\" into \\\n table \"%s\".
Method signature: %s
Full error log:
%s
Oracle says: %s' % \\\n (field_name, field_value, table_name, call_string, log_string, str(e))\n raise Exception(error_msg)\n finally:\n # Release the lock\n #lock.release()\n log.append('Lock released')","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def get_pymongo_type_string(\n self, field_type: Union[Type, str], collection_name: str\n ) -> str:\n try:\n type_string = PYMONGO_TYPE_TO_MONGO_TYPE[field_type]\n except KeyError:\n self.report.report_warning(\n collection_name, f\"unable to map type {field_type} to metadata schema\"\n )\n PYMONGO_TYPE_TO_MONGO_TYPE[field_type] = \"unknown\"\n type_string = \"unknown\"\n\n return type_string","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def db_type(self, field):\r\n if self.connection.settings_dict.get('STORE_RELATIONS_AS_DB_KEYS'):\r\n if field.primary_key or field.rel is not None:\r\n return 'key'\r\n\r\n # Primary keys were processed as db.Keys; for related fields\r\n # the db_type of primary key of the referenced model was used,\r\n # but RelatedAutoField type was not defined and resulted in\r\n # \"integer\" being used for relations to models with AutoFields.\r\n # TODO: Check with Positive/SmallIntegerField primary keys.\r\n else:\r\n if field.primary_key:\r\n return 'key'\r\n if field.rel is not None:\r\n related_field = field.rel.get_related_field()\r\n if related_field.get_internal_type() == 'AutoField':\r\n return 'integer'\r\n else:\r\n return related_field.db_type(connection=self.connection)\r\n\r\n db_type = field.db_type(connection=self.connection)\r\n\r\n # Override db_type of \"string\" fields according to indexing.\r\n if db_type in ('string', 'text'):\r\n indexes = get_model_indexes(field.model)\r\n if field.attname in indexes['indexed']:\r\n return 'string'\r\n elif field.attname in indexes['unindexed']:\r\n return 'text'\r\n\r\n return db_type","def dict_factory(cursor, row):\n rowdict = {}\n for idx, col in enumerate(cursor.description):\n rowdict[col[0]] = row[idx]\n return rowdict","def type_fields(self, res, op_item):\n result = []\n cast_func = {}\n header = res[0]\n for heading in header:\n cast_func[heading] = DataType.str\n\n if \"field_type\" in op_item:\n for f, p in findall(FIELD_TYPE_RE, op_item[\"field_type\"]):\n cast_func[p] = self.dt.get_func(f)\n first = True\n for row in res[1:]:\n new_row = []\n for idx in range(len(header)):\n\n heading = header[idx]\n cur_value = row[idx]\n if type(cur_value) is tuple:\n cur_value = cur_value[1]\n if heading == \"timespan\" and first:\n first = False\n new_row.append((cast_func[heading](cur_value), cur_value))\n\n result.append(new_row)\n\n return [header] + result","def get_column_type(cls, **kwargs: Any) -> Any: # pragma no cover\n return None","def extract_generic_credit_type(self, course_row):\n course_id = row[0]\n credit_type_res = {re.compile(\"Communication\"):\"CS\",\n re.compile(\"Natural Science\"):\"NS\",\n re.compile(\"Humanities\"):\"H\",\n re.compile(\"Performance\"):\"HP\",\n re.compile(\"Social\"):\"SS\",\n re.compile(\"Lab\"):\"NSL\",\n re.compile(\"Quant\"):\"QS\",\n re.compile(\"Elective\"):\"E\",\n re.compile(\"Diversity\"):\"DC\",\n re.compile(\"Prereq\"):\"PR\"}\n for credit_type_re in credit_type_res:\n if credit_type_re.search(course_id):\n type_string = credit_type_res[credit_type_re]\n credit_type = models.CreditType.objects.get(label_short=type_string)\n return credit_type","def specific(self):\n field_attr = field_registry.field_map[self.type]\n return getattr(self, field_attr, None)","def _fields(self, doclet):\n FIELD_TYPES = OrderedDict([('params', _params_formatter),\n ('properties', _params_formatter),\n ('exceptions', _exceptions_formatter),\n ('returns', _returns_formatter)])\n for field_name, callback in iteritems(FIELD_TYPES):\n for field in doclet.get(field_name, []):\n description = field.get('description', '')\n unwrapped = sub(r'[ \\t]*[\\r\\n]+[ \\t]*', ' ', description)\n yield callback(field, unwrapped)","def get_model_details(refobject):\n typename = type(refobject).__name__\n\n if typename in TYPES_TABLE:\n\n details = TYPES_TABLE[typename]\n\n elif isinstance(refobject, type):\n clrtype = clr.GetClrType(refobject)\n\n if clrtype.IsEnum:\n details = TYPES_TABLE['enumtype']\n\n elif clrtype.IsClass:\n if clrtype.FullName.startswith('Autodesk.Revit.DB'):\n details = TYPES_TABLE['revitclass']\n\n else:\n details = TYPES_TABLE['classtype']\n\n elif clrtype.IsInterface:\n details = TYPES_TABLE['interface']\n\n elif clrtype.FullName in SYS_TYPES:\n details = TYPES_TABLE['systype']\n\n elif clrtype.FullName in WIN_TYPES:\n details = TYPES_TABLE['wintype']\n\n else:\n details = TYPES_TABLE['unknown']\n logger.debug('TODO get_model_details for CLR/type: {} ({})'.format(\n typename, refobject))\n\n # match all list/collection types\n elif is_iterable(refobject):\n details = TYPES_TABLE['listtype']\n\n # match sub enum types\n elif clr.GetClrType(type(refobject)).IsEnum:\n details = TYPES_TABLE['subenumtype']\n\n # match sub class types\n elif clr.GetClrType(type(refobject)).IsClass:\n\n if clr.GetClrType(type(refobject)).FullName == 'Autodesk.Revit.DB.Parameter':\n details = TYPES_TABLE['revitparameter']\n\n elif clr.GetClrType(type(refobject)).FullName.startswith('Autodesk.Revit.DB'):\n details = TYPES_TABLE['revitclass']\n else:\n details = TYPES_TABLE['subclasstype']\n\n elif clr.GetClrType(type(refobject)).IsInterface:\n details = TYPES_TABLE['interface']\n\n elif clr.GetClrType(type(refobject)).FullName in SYS_TYPES:\n details = TYPES_TABLE['systype']\n\n elif clr.GetClrType(type(refobject)).FullName in WIN_TYPES:\n details = TYPES_TABLE['wintype']\n\n else:\n details = TYPES_TABLE['unknown']\n logger.debug('TODO get_model_details for : {} ({})'.format(\n typename, refobject))\n\n return details","def init_fields(self):\n result = self.connection.execute('pragma table_info(files)')\n rows = result.fetchall()\n self.fields = [Field(row) for row in rows[4:]]\n result = self.connection.execute('select _keyword from keywords')\n rows = result.fetchall()\n self.keywords = [row[0] for row in rows]","def field(self) -> 'outputs.PreventionStoredInfoTypeLargeCustomDictionaryBigQueryFieldField':\n return pulumi.get(self, \"field\")","def south_field_triple(self):\n # We'll just introspect ourselves, since we inherit.\n from south.modelsinspector import introspector\n field_class = \"django.db.models.fields.TextField\"\n args, kwargs = introspector(self)\n # That's our definition!\n return (field_class, args, kwargs)","async def get_schema_info(self, collection):\n await self.ensure_collection(collection)\n try:\n # Luke handler is not supported in API v2 yet.\n # /v2/collections//schema/fields doesn't show dynamically\n # created fields.\n # So using old API (/solr/...).\n response = await self.get(\n '/solr/{}/admin/luke?numTerms=0'.format(collection)\n )\n return json.loads(response.body.decode('utf-8'))\n except SolrError:\n logger.warning('Failed to fetch fields list for collection {}'\n .format(collection))\n raise","def sql_type(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"sql_type\")","def sql_type(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"sql_type\")","def _init_fields(self):\n if self._fields is None:\n M.mset('U', \"^\") # DBS Calls Require this\n f = self._fields = {}\n attrs = self.fieldnames = {}\n fieldid = \"0\"\n while 1:\n # Subscript 0 is field description, .1 is the title, 3 is help\n fieldid, info, title, fieldhelp = M.ddwalk(self._fileid, fieldid)\n #fieldid, info, title, fieldhelp = M.mexec(\n # \"\"\"set s0=$order(^DD(s2,s0)) Q:s0'=+s0 s s1=$G(^DD(s2,s0,0)),s3=$G(^DD(s2,s0,.1)),s4=$G(^DD(s2,s0,3))\"\"\",\n # M.INOUT(str(fieldid)), M.INOUT(\"\"), str(self._fileid), M.INOUT(\"\"), M.INOUT(\"\"))\n if fieldid == \"\" or fieldid[0] not in \"0123456789.\":\n break\n\n info = info.split(\"^\", 4) \n label = self._clean_label(info[0])\n try:\n ftype = info[1]\n except:\n ftype = None\n if ftype:\n finst = None\n for klass in FIELD_TYPES:\n if klass.isa(ftype):\n finst = f[fieldid] = klass(fieldid, label, info)\n finst.fileid = self.fileid\n finst.ownerdd = self\n attrs[label] = fieldid\n break\n if finst is None:\n print finst, \"FIELD [%s], spec [%s] was not identified\" % (label, ftype)\n continue\n finst.title = title\n finst.fieldhelp = fieldhelp\n else:\n assert finst, \"FIELD [%s] %s has no fieldspec\" % (label, info)\n\n return self._fields","def describe(self):\r\n return dict((field.name, dict(\r\n id=field.name,\r\n name=field.label,\r\n validators=ValidatorSerializer(\r\n field.requires if isSequenceType(field.requires) else [field.requires])(),\r\n comment=field.comment,\r\n readable=field.readable,\r\n writable=field.writable,\r\n type=getattr(field, 'wtype',\r\n field.type.type if isinstance(field.type, SQLCustomType) else field.type.split('(')[0]),\r\n # w2pwidget=field.widget,\r\n )) for field in self.descibe_columns)","def table_description(classname, nclassname, shape=()):\n classdict = {}\n colpos = append_columns(classdict, shape)\n\n ndescr = nested_description(nclassname, colpos, shape=shape)\n classdict['c_nested'] = ndescr\n colpos += 1\n\n extracol = tb.IntCol(shape=shape, pos=colpos)\n classdict['c_extra'] = extracol\n colpos += 1\n\n idxextracol = tb.IntCol(shape=shape, pos=colpos)\n classdict['c_idxextra'] = idxextracol\n colpos += 1\n\n return type(classname, (tb.IsDescription,), classdict)","def retrievebeamparamproptype(self, cursor, bpptname, bpptunit=None):\n sql = \"\"\"\n SELECT\n beam_param_prop_type_id,\n beam_param_prop_type_name,\n beam_param_prop_type_desc,\n beam_param_prop_type_unit\n FROM\n beam_param_prop_type\n WHERE\n \"\"\"\n sql += \"beam_param_prop_type_name = '%s'\" % (bpptname,)\n if bpptunit is None:\n sql += \" AND beam_param_prop_type_unit IS NULL\"\n else:\n sql += \" AND beam_param_prop_type_unit = '%s'\" % (bpptunit,)\n cursor.execute(sql)\n return cursor.fetchone()","def _getfield(self, block, name):\n\n # First, get the field from the class, if defined\n block_field = getattr(block.__class__, name, None)\n if block_field is not None and isinstance(block_field, Field):\n return block_field\n\n # Not in the class, so name\n # really doesn't name a field\n raise KeyError(name)","def add_field(self, field_name, field_type):\n field_name = field_name.replace('\"','')\n if field_type == 'keyword':\n query = \"\"\"insert or ignore into keywords\n (_keyword) values (\"%s\")\"\"\" % field_name\n else:\n query = 'alter table files add column \"%s\" %s' % (\n field_name, field_type)\n self.connection.execute(query)\n self.connection.commit()\n self.init_fields()","def column_reflection_fallback(self):\n col_info_dict_list: List[Dict]\n if self.sql_engine_dialect.name.lower() == \"mssql\":\n type_module = self._get_dialect_type_module()\n # Get column names and types from the database\n # StackOverflow to the rescue: https://stackoverflow.com/a/38634368\n col_info_query: TextClause = sa.text(\n f\"\"\"\nSELECT\n cols.NAME, ty.NAME\nFROM\n tempdb.sys.columns AS cols\nJOIN\n sys.types AS ty\nON\n cols.user_type_id = ty.user_type_id\nWHERE\n object_id = OBJECT_ID('tempdb..{self._table}')\n \"\"\"\n )\n col_info_tuples_list = self.engine.execute(col_info_query).fetchall()\n col_info_dict_list = [\n {\"name\": col_name, \"type\": getattr(type_module, col_type.upper())()}\n for col_name, col_type in col_info_tuples_list\n ]\n else:\n query: Select = sa.select([sa.text(\"*\")]).select_from(self._table).limit(1)\n col_names: list = self.engine.execute(query).keys()\n col_info_dict_list = [{\"name\": col_name} for col_name in col_names]\n return col_info_dict_list","def get_field_type(db_code):\n try:\n field_type = connection.introspection.get_field_type(\n db_code, 'django_musicbrainz tests')\n except KeyError:\n # if the db_code is not listed in\n # django.db.backens.postgresql_psycopg2.introspection.\\\n # DatabaseIntrospection.data_types_reverse we guess that\n # the db type is a TextField\n field_type = 'TextField'\n return field_type","def get_table_info(line):\n\n COMMENT_EXPR = '-- Name: '\n TYPE_EXPR = '; Type: '\n SCHEMA_EXPR = '; Schema: '\n OWNER_EXPR = '; Owner: '\n TABLESPACE_EXPR = '; Tablespace: '\n\n temp = line.strip('\\n')\n type_start = get_all_occurrences(TYPE_EXPR, temp)\n schema_start = get_all_occurrences(SCHEMA_EXPR, temp)\n owner_start = get_all_occurrences(OWNER_EXPR, temp)\n tblspace_start = get_all_occurrences(TABLESPACE_EXPR, temp)\n if len(type_start) != 1 or len(schema_start) != 1 or len(owner_start) != 1:\n return (None, None, None, None)\n name = temp[len(COMMENT_EXPR) : type_start[0]]\n type = temp[type_start[0] + len(TYPE_EXPR) : schema_start[0]]\n schema = temp[schema_start[0] + len(SCHEMA_EXPR) : owner_start[0]]\n if not tblspace_start:\n tblspace_start.append(None)\n owner = temp[owner_start[0] + len(OWNER_EXPR) : tblspace_start[0]]\n return (name, type, schema, owner)","def test_get_table_description(self):\n db_introspection = DatabaseIntrospection(self.connection)\n cursor = mock.MagicMock()\n\n def description(*args, **kwargs):\n return [[\"name\", TypeCode.STRING], [\"age\", TypeCode.INT64]]\n\n def get_table_column_schema(*args, **kwargs):\n column_details = {}\n column_details[\"name\"] = ColumnDetails(\n null_ok=False, spanner_type=\"STRING(10)\"\n )\n column_details[\"age\"] = ColumnDetails(\n null_ok=True, spanner_type=\"INT64\"\n )\n return column_details\n\n cursor.get_table_column_schema = get_table_column_schema\n cursor.description = description()\n table_description = db_introspection.get_table_description(\n cursor=cursor, table_name=\"Table_1\"\n )\n if USING_DJANGO_3:\n self.assertEqual(\n table_description,\n [\n FieldInfo(\n name=\"name\",\n type_code=TypeCode.STRING,\n display_size=None,\n internal_size=10,\n precision=None,\n scale=None,\n null_ok=False,\n default=None,\n collation=None,\n ),\n FieldInfo(\n name=\"age\",\n type_code=TypeCode.INT64,\n display_size=None,\n internal_size=None,\n precision=None,\n scale=None,\n null_ok=True,\n default=None,\n collation=None,\n ),\n ],\n )\n else:\n self.assertEqual(\n table_description,\n [\n FieldInfo(\n name=\"name\",\n type_code=TypeCode.STRING,\n display_size=None,\n internal_size=10,\n precision=None,\n scale=None,\n null_ok=False,\n default=None,\n ),\n FieldInfo(\n name=\"age\",\n type_code=TypeCode.INT64,\n display_size=None,\n internal_size=None,\n precision=None,\n scale=None,\n null_ok=True,\n default=None,\n ),\n ],\n )","def _get_field_details(self, data, fields):\n fields_metadata = dict()\n for field in fields:\n dtype = data[field].dtype\n field_template = self._FIELD_TEMPLATES.get(dtype.kind)\n if not field_template:\n raise ValueError('Unsupported dtype {} in column {}'.format(dtype, field))\n\n field_details = copy.deepcopy(field_template)\n fields_metadata[field] = field_details\n\n return fields_metadata","def get_description_from_row(row):\n return [\n (\n name, # name\n get_type(value), # type_code\n None, # [display_size]\n None, # [internal_size]\n None, # [precision]\n None, # [scale]\n get_type(value) == Type.STRING, # [null_ok]\n )\n for name, value in row.items()\n ]","def get_fields(dgid, metadata=None, computed_columns=None):\n # NOTE: metadata does not contain computed_columns yet\n if metadata is None:\n conn = get_database_connection(dgid)\n metadata = get_metadata(conn)\n\n # Used to evaluate computed columns\n unify_computed_columns(computed_columns)\n columns = list(metadata.keys())\n select_expr_as = [get_field_name(column, metadata) for column in columns]\n databases = [\"datagrid\"]\n\n if computed_columns:\n # Only passed in when calling from endpoint\n update_state(computed_columns, metadata, databases, columns, select_expr_as)\n # Now metadata has computed columns\n\n fields = {}\n for column in metadata:\n datatype = metadata[column][\"type\"]\n field_name = get_field_name(column, metadata)\n qbtype = datatype_to_qbtype(datatype)\n if qbtype is None:\n continue\n\n if datatype in [\"FLOAT\", \"INTEGER\", \"ROW_ID\"]:\n fields[field_name] = {\n \"label\": column,\n \"field\": field_name,\n \"type\": qbtype,\n \"tooltip\": \"The '%s' column (type '%s') from the data grid\"\n % (column, qbtype),\n }\n # name, datatype, min, max, avg, variance, total, stddev, other\n if (metadata[column][\"minimum\"] is not None) and (\n metadata[column][\"minimum\"] is not None\n ):\n min_value = metadata[column][\"minimum\"]\n max_value = metadata[column][\"maximum\"]\n fields[field_name][\"fieldSettings\"] = {\n \"min\": min_value,\n \"max\": max_value,\n }\n fields[field_name][\"valueSources\"] = [\"value\", \"field\"]\n\n elif datatype == \"DATETIME\":\n field_exp = \"datetime(%s, 'unixepoch')\" % field_name\n fields[field_exp] = {\n \"label\": column,\n \"field\": field_name,\n \"type\": qbtype,\n \"tooltip\": \"The '%s' column (type '%s') from the data grid\"\n % (column, qbtype),\n }\n if (metadata[column][\"minimum\"] is not None) and (\n metadata[column][\"minimum\"] is not None\n ):\n min_value = metadata[column][\"minimum\"]\n max_value = metadata[column][\"maximum\"]\n fields[field_exp][\"fieldSettings\"] = {\n \"min\": min_value,\n \"max\": max_value,\n # \"dateFormat\": \"DD-MM-YYYY\",\n # \"timeFormat\":\n # \"valueFormat\":\n }\n fields[field_exp][\"valueSources\"] = [\n \"value\",\n \"field\",\n \"func\",\n ] # adds Now, and Relative\n\n elif datatype == \"BOOLEAN\":\n fields[field_name] = {\n \"label\": column,\n \"field\": field_name,\n \"type\": qbtype,\n \"tooltip\": \"The '%s' column (type '%s') from the data grid\"\n % (column, qbtype),\n }\n fields[field_name][\"fieldSettings\"] = {\n \"labelYes\": \"True\",\n \"labelNo\": \"False\",\n }\n fields[field_name][\"valueSources\"] = [\"value\", \"field\"]\n\n elif datatype == \"TEXT\":\n fields[field_name] = {\n \"label\": column,\n \"field\": field_name,\n \"type\": qbtype,\n \"tooltip\": \"The '%s' column (type '%s') from the data grid\"\n % (column, qbtype),\n }\n fields[field_name][\"valueSources\"] = [\"value\", \"field\"]\n\n elif datatype == \"JSON\":\n # Asset metadata columns are named\n # 'COLUMN_NAME.metadata' or 'COLUMN_NAME--metadata'\n fields[field_name] = {\n \"label\": column.replace(\".metadata\", \"\").replace(\"--metadata\", \"\"),\n \"field\": field_name,\n \"tooltip\": \"The '%s' column (type 'JSON') from the data grid\"\n % (column,),\n \"type\": \"!struct\",\n \"subfields\": {},\n }\n subfields = ast.literal_eval(metadata[column][\"other\"])\n # Only filterable keys are in subfields\n for key in subfields:\n # Query Builder filter types: \"text\", \"number\", \"boolean\", or \"list-of-text\"\n qbtype = subfields[key][\"type\"]\n if qbtype == \"list-of-text\":\n field_exp = \"json_extract(%s, '$.%s')\" % (field_name, key)\n fields[field_name][\"subfields\"][field_exp] = {\n \"type\": \"text\",\n \"label\": key,\n \"field\": field_name,\n \"tableName\": \"1\", # special signal for JSON queries in our QueryBuilder\n \"operators\": [\"like\"],\n }\n else:\n field_exp = \"json_extract(%s, '$.%s')\" % (field_name, key)\n fields[field_name][\"subfields\"][field_exp] = {\n \"type\": qbtype,\n \"label\": key,\n \"field\": field_name,\n \"tableName\": \"1\", # special signal for JSON queries in our QueryBuilder\n }\n if \"values\" in subfields[key]:\n fields[field_name][\"subfields\"][field_exp][\"type\"] = \"select\"\n fields[field_name][\"subfields\"][field_exp][\"fieldSettings\"] = {\n \"listValues\": sorted(subfields[key][\"values\"])\n }\n\n return fields","def getFieldDescr(fieldName, descr):\n i = getIter(descr)\n if not i:\n return\n\n try:\n sw = ''\n item = i.next()\n while item:\n if fieldName == item[0]:\n yield item\n break\n if isinstance(item[1], list):\n if fieldName.startswith('%s/' %item[0]):\n sw = item[0]\n else:\n item = i.next()\n continue\n [trash, newField] = fieldName.split(sw + '/')\n for c in getFieldDescr(newField, item[1]):\n sw = '%s/%s' % (sw, c[0])\n yield (sw, c[1])\n item = i.next()\n except StopIteration:\n pass","def createField(schemaName, field):\n# print(field.domain)\n# print(field.name, field.domain if isinstance(field.domain, str) else field.domain.type)\n# print(field.__dict__)\n return \"\\\"{name}\\\" {type_}\".format(\n name = field.name,\n type_ = '\"' + schemaName + '\".\"' + field.domain + '\"' if isinstance(field.domain, str) else getType(field.domain)\n )","def _savebeamparamproptype(self, cursor, bpptname, bpptunit=None, bpptdesc=None):\n sql = \"\"\"\n INSERT INTO beam_param_prop_type (\n beam_param_prop_type_name,\n beam_param_prop_type_desc,\n beam_param_prop_type_unit\n ) VALUES (\n '%s', %s, %s\n )\n \"\"\"\n if bpptunit is None:\n bpptunit = \"NULL\"\n else:\n bpptunit = \"'%s'\" % (bpptunit,)\n\n if bpptdesc is None:\n bpptdesc = \"NULL\"\n else:\n bpptdesc = \"'%s'\" % (bpptdesc,)\n\n cursor.execute(sql % (bpptname, bpptdesc, bpptunit))\n return cursor.lastrowid","def _make_unknown_name(self, cursor, field_name):\n parent = cursor.lexical_parent\n pname = self.get_unique_name(parent)\n log.debug('_make_unknown_name: Got parent get_unique_name %s',pname)\n # we only look at types declarations\n _cursor_decl = cursor.type.get_declaration()\n # we had the field index from the parent record, as to differenciate\n # between unnamed siblings of a same struct\n _i = 0\n found = False\n # Look at the parent fields to find myself\n for m in parent.get_children():\n # FIXME: make the good indices for fields\n log.debug('_make_unknown_name child %d %s %s %s',_i,m.kind, m.type.kind,m.location)\n if m.kind not in [CursorKind.STRUCT_DECL,CursorKind.UNION_DECL,\n CursorKind.CLASS_DECL]:#,\n #CursorKind.FIELD_DECL]:\n continue\n if m == _cursor_decl:\n found = True\n break\n _i+=1\n if not found:\n raise NotImplementedError(\"_make_unknown_name BUG %s\" % cursor.location)\n # truncate parent name to remove the first part (union or struct)\n _premainer = '_'.join(pname.split('_')[1:])\n # name the anonymous record with the field name if it has one\n if field_name:\n name = '%s_%s' % (_premainer, field_name)\n else:\n name = '%s_%d' % (_premainer, _i)\n return name","def get_field(self, field_name):\n all_fields = self._fields.items(self._fields.root)\n print(\"all_fields\", all_fields)\n for name, field in all_fields:\n print(name, field_name)\n if name == field_name:\n return field","def get_fields(self, table_name):\n return self.get_table_meta(table_name)['fields']","def GetFieldDef(fielddef, fields=\"format_, addrdef, baseaddr, bits, bitshift, strindex, datadef, arraydef, validate, cmd, group, tasmotacmnd, converter, readconverter, writeconverter\"):\n format_ = addrdef = baseaddr = datadef = arraydef = validate = cmd = group = tasmotacmnd = converter = readconverter = writeconverter = strindex = None\n bits = bitshift = 0\n\n # calling with nothing is wrong\n if fielddef is None:\n print(' is None', file=sys.stderr)\n raise SyntaxError(' error')\n\n # get top level items\n if len(fielddef) == 3:\n # converter not present\n format_, addrdef, datadef = fielddef\n elif len(fielddef) == 4:\n # converter present\n format_, addrdef, datadef, converter = fielddef\n else:\n print('wrong {} length ({}) in setting'.format(fielddef, len(fielddef)), file=sys.stderr)\n raise SyntaxError(' error')\n\n # ignore calls with 'root' setting\n if isinstance(format_, dict) and baseaddr is None and datadef is None:\n return eval(fields)\n\n if not isinstance(format_, (str,dict)):\n print('wrong {} type {} in {}'.format(format_, type(format_), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n\n # extract addrdef items\n baseaddr = addrdef\n if isinstance(baseaddr, (list,tuple)):\n if len(baseaddr) == 3:\n # baseaddr bit definition\n baseaddr, bits, bitshift = baseaddr\n if not isinstance(bits, int):\n print(' must be defined as integer in {}'.format(fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n if not isinstance(bitshift, int):\n print(' must be defined as integer in {}'.format(fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n elif len(baseaddr) == 2:\n # baseaddr string definition\n baseaddr, strindex = baseaddr\n if not isinstance(strindex, int):\n print(' must be defined as integer in {}'.format(fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n if strindex >= SettingsTextIndex.index('SET_MAX'):\n print(' out of range [0,{}] in {}'.format(SettingsTextIndex.index('SET_MAX'), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n else:\n print('wrong {} length ({}) in {}'.format(addrdef, len(addrdef), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n if not isinstance(baseaddr, int):\n print(' {} must be defined as integer in {}'.format(baseaddr, fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n\n # extract datadef items\n arraydef = datadef\n if isinstance(datadef, (tuple)):\n if len(datadef) == 2:\n # datadef has a validator\n arraydef, validate = datadef\n elif len(datadef) == 3:\n # datadef has a validator and cmd set\n arraydef, validate, cmd = datadef\n # cmd must be a tuple with 2 objects\n if isinstance(cmd, tuple) and len(cmd) == 2:\n group, tasmotacmnd = cmd\n if group is not None and not isinstance(group, str):\n print('wrong {} in {}'.format(group, fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n if isinstance(tasmotacmnd, tuple):\n for tcmnd in tasmotacmnd:\n if tcmnd is not None and not callable(tcmnd) and not isinstance(tcmnd, str):\n print('wrong {} in {}'.format(tcmnd, fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n else:\n if tasmotacmnd is not None and not callable(tasmotacmnd) and not isinstance(tasmotacmnd, str):\n print('wrong {} in {}'.format(tasmotacmnd, fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n else:\n print('wrong {} length ({}) in {}'.format(cmd, len(cmd), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n else:\n print('wrong {} length ({}) in {}'.format(datadef, len(datadef), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n\n if validate is not None and (not isinstance(validate, str) and not callable(validate)):\n print('wrong {} type {} in {}'.format(validate, type(validate), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n\n # convert single int into one-dimensional list\n if isinstance(arraydef, int):\n arraydef = [arraydef]\n\n if arraydef is not None and not isinstance(arraydef, (list)):\n print('wrong {} type {} in {}'.format(arraydef, type(arraydef), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n\n # get read/write converter items\n readconverter = converter\n if isinstance(converter, (tuple)):\n if len(converter) == 2:\n # converter has read/write converter\n readconverter, writeconverter = converter\n if readconverter is not None and not isinstance(readconverter, str) and not callable(readconverter):\n print('wrong {} type {} in {}'.format(readconverter, type(readconverter), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n if writeconverter is not None and (not isinstance(writeconverter, (bool,str)) and not callable(writeconverter)):\n print('wrong {} type {} in {}'.format(writeconverter, type(writeconverter), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n else:\n print('wrong {} length ({}) in {}'.format(converter, len(converter), fielddef), file=sys.stderr)\n raise SyntaxError(' error')\n\n\n return eval(fields)","def getDocObjects(row, field):\n\n doc = nlp_larg(str(row[field]).lower())\n\n return doc","def typeString(self):\n return Parameter.string_dict[self._field.type]","def test_parse_fields(pawprint_default_tracker_db):\n\n tracker = pawprint_default_tracker_db\n\n # SELECT * FROM table\n args = ()\n assert tracker._parse_fields(*args) == \"*\"\n\n # SELECT event FROM table\n args = (\"event\",)\n assert tracker._parse_fields(*args) == \"event\"\n\n # SELECT user_id, timestamp FROM table\n args = (\"user_id\", \"timestamp\")\n assert tracker._parse_fields(*args) == \"user_id, timestamp\"\n\n # SELECT metadata #>> '{a, b}' FROM table\n args = (\"metadata__a__b\",)\n assert tracker._parse_fields(*args) == \"metadata #> '{a, b}' AS json_field\"","def get_column_information(self, column_name, table, verbose=True): \n \n assert(self.connected)\n try: \n assert(self.check_table(table, verbose=False)) \n except AssertionError: \n raise TableNotFoundError\n \n if (not self.check_column(column_name, table, verbose=False)):\n return\n \n GET_COLUMN_INFO_COMMAND = (\"SELECT COLUMN_TYPE, IS_NULLABLE, COLUMN_KEY, EXTRA \"\n \t\t\"FROM INFORMATION_SCHEMA.COLUMNS \"\n \t\t\"WHERE TABLE_NAME='{0}' and COLUMN_NAME = '{1}'\".format(table,column_name))\n \n self.cursor.execute(GET_COLUMN_INFO_COMMAND)\n \n for row in self.cursor:\n break\n \n info = {'type' : row[0],\n 'not_null' : row[1] != 'YES' , \n 'foreign_key' : row[2] == 'MUL',\n 'auto_incremenet' : row[3] == 'auto_increment'}\n \n if verbose: print(\"Column with label '{0}' found in table '{1}'\".format(column_name, table))\n \n \n return info","def get_field_dtype(self, field=None):\n\n if field in self._fields_dtypes:\n return self._fields_dtypes[field]\n\n # initialize dbtypes for all fields\n field_type = pd.read_sql(\n 'select distinct column_name, type '\n 'from fields',\n self._get_db_engine())\n\n for row in field_type.itertuples():\n self._fields_dtypes[row.column_name] = row.type\n\n return self._fields_dtypes[field] if field in self._fields_dtypes else None","def complete_info_record_type(self, text, line, begidx, endidx):\n begidx = begidx\n endidx = endidx\n mline = line.partition(' ')[2]\n offs = len(mline) - len(text)\n info_record_types = ['description', 'access', 'default', 'bit',\n 'flag', 'max', 'min']\n return [s[offs:] for s in info_record_types if s.startswith(mline)]","def get_ent_type(self, line):\n\n\t\treturn str(self.kb_shm.dataType(line))","def record_type(values):\n field = basic.lookup(values, name='Record Type (one of %s)' % values)\n\n return field.setResultsName('record_type')","def _fieldDefAsString(self, fieldTuple):\n\n fname, ftype, flen = fieldTuple\n if ftype == 'char':\n # pdb.set_trace()\n try:\n slen, flen = flen\n except TypeError as e:\n slen = flen\n flen = 1\n\n if slen > 0:\n fname = '%s[%d]' % (fname, slen)\n else:\n fname = '%s[]' % (fname)\n \n if flen > 1: \n return \" %s %s[%d];\" % (ftype, fname, flen)\n else:\n return \" %s %s;\" % (ftype, fname)","def ddl_table(self, tabela):\r\n sql = \"\"\"SELECT\r\n RF.RDB$FIELD_NAME FIELD_NAME,\r\n CASE F.RDB$FIELD_TYPE\r\n WHEN 7 THEN\r\n CASE F.RDB$FIELD_SUB_TYPE\r\n WHEN 0 THEN 'INT'\r\n WHEN 1 THEN 'NUMERIC(' || F.RDB$FIELD_PRECISION || ', ' || (-F.RDB$FIELD_SCALE) || ')'\r\n WHEN 2 THEN 'DECIMAL'\r\n END\r\n WHEN 8 THEN\r\n CASE F.RDB$FIELD_SUB_TYPE\r\n WHEN 0 THEN 'INTEGER'\r\n WHEN 1 THEN 'NUMERIC(' || F.RDB$FIELD_PRECISION || ', ' || (-F.RDB$FIELD_SCALE) || ')'\r\n WHEN 2 THEN 'DECIMAL'\r\n END\r\n WHEN 9 THEN 'QUAD'\r\n WHEN 10 THEN 'FLOAT'\r\n WHEN 12 THEN 'DATE'\r\n WHEN 13 THEN 'TIME'\r\n WHEN 14 THEN 'CHAR(' || (TRUNC(F.RDB$FIELD_LENGTH / COALESCE(CH.RDB$BYTES_PER_CHARACTER,1))) || ') '\r\n WHEN 16 THEN\r\n CASE F.RDB$FIELD_SUB_TYPE\r\n WHEN 0 THEN 'BIGINT'\r\n WHEN 1 THEN 'NUMERIC(' || F.RDB$FIELD_PRECISION || ', ' || (-F.RDB$FIELD_SCALE) || ')'\r\n WHEN 2 THEN 'DECIMAL'\r\n END\r\n WHEN 27 THEN 'NUMERIC'\r\n WHEN 35 THEN 'TIMESTAMP'\r\n WHEN 37 THEN 'VARCHAR(' || (TRUNC(F.RDB$FIELD_LENGTH / COALESCE(CH.RDB$BYTES_PER_CHARACTER,1))) || ')'\r\n WHEN 40 THEN 'CSTRING' || (TRUNC(F.RDB$FIELD_LENGTH / COALESCE(CH.RDB$BYTES_PER_CHARACTER,1))) || ')'\r\n WHEN 45 THEN 'BLOB_ID'\r\n WHEN 261 THEN 'TEXT'\r\n ELSE 'RDB$FIELD_TYPE: ' || F.RDB$FIELD_TYPE || '?'\r\n END FIELD_TYPE\r\n FROM RDB$RELATION_FIELDS RF\r\n JOIN RDB$FIELDS F ON (F.RDB$FIELD_NAME = RF.RDB$FIELD_SOURCE)\r\n LEFT OUTER JOIN RDB$CHARACTER_SETS CH ON (CH.RDB$CHARACTER_SET_ID = F.RDB$CHARACTER_SET_ID)\r\n LEFT OUTER JOIN RDB$COLLATIONS DCO ON ((DCO.RDB$COLLATION_ID = F.RDB$COLLATION_ID) AND (DCO.RDB$CHARACTER_SET_ID = F.RDB$CHARACTER_SET_ID))\r\n WHERE (RF.RDB$RELATION_NAME = '%s') AND (COALESCE(RF.RDB$SYSTEM_FLAG, 0) = 0)\r\n ORDER BY RF.RDB$FIELD_POSITION;\"\"\" % (tabela)\r\n res = self.cur_origem.execute(sql)\r\n table = \"CREATE TABLE IF NOT EXISTS %s (\" % tabela\r\n tipos = {}\r\n for coluna, tipo, in res.fetchall():\r\n table += \"%s %s,\" % (coluna.strip(), tipo.strip())\r\n tipos[coluna.strip()] = tipo\r\n table = table[:-1]+\");\"\r\n return table, tipos","def get_sql_fields(self):\n return self.mapping_db, 'GeneNames', 'EnsembleID', 'symbol', 'name'","def field_dim(self, str field_name):\n cdef std_string fn = field_name.encode('UTF-8')\n return self.mdb.get().field_dim(fn)","def get_column_type(cls, **kwargs: Any) -> Any:\n return sqlalchemy.Text()","def _GetField(bpo_field_id):\n bpo_field = BPOField.objects.get(id=bpo_field_id)\n # Get BPO Field based on type.\n if bpo_field.type == 'auto_sum':\n return BPOAutoSumField.objects.get(id=bpo_field_id)\n elif bpo_field.type == 'multiple_choice':\n return BPOMultipleChoiceField.objects.get(id=bpo_field_id)\n elif bpo_field.type == 'float_input':\n return BPOFloatField.objects.get(id=bpo_field_id)\n elif bpo_field.type == 'integer_input':\n return BPOIntegerField.objects.get(id=bpo_field_id)\n elif bpo_field.type == 'date_input':\n return BPODateField.objects.get(id=bpo_field_id)\n elif bpo_field.type == 'table':\n return BPOTable.objects.get(id=bpo_field_id)\n else:\n return bpo_field"],"string":"[\n \"def _get_fields(self):\\n if not self._cursor.description:\\n return {}\\n\\n results = {}\\n column = 0\\n\\n for des in self._cursor.description:\\n fieldname = des[0]\\n results[column] = fieldname\\n column = column + 1\\n\\n return results\",\n \"def get_field_type(self, table_name, field_name):\\n \\n dtype = self.field_types[(self.field_types.TABNAME == table_name) & (self.field_types.FIELDNAME == field_name)]['DATATYPE'].values[0] \\n return dtype\",\n \"def getFieldDetails(self, field_name):\\n try:\\n value_list = []\\n con = self.getMetadataDatabaseConnection()\\n results = con.cursor()\\n con.cursor().callproc('qiime_assets.get_field_details', [field_name, results])\\n\\n for row in results:\\n # column_name, data_type, desc_or_value, definition, active\\n value_list.append((row[0], row[1], row[2], row[3], row[4]))\\n \\n if len(value_list) == 0:\\n # If not found in the dictionary, assume this is a user-created column\\n value_list.append((field_name, 'text', '', ''))\\n \\n return value_list[0]\\n except Exception, e:\\n print 'Exception caught: %s.\\\\nThe error is: %s' % (type(e), e)\\n return False\",\n \"def get_geometry_type(self, table_name, description):\\n with self.connection.cursor() as cursor:\\n cursor.execute(\\n \\\"\\\"\\\"\\n SELECT t.coord_dimension, t.srid, t.type FROM (\\n SELECT * FROM geometry_columns\\n UNION ALL\\n SELECT * FROM geography_columns\\n ) AS t WHERE t.f_table_name = %s AND t.f_geometry_column = %s\\n \\\"\\\"\\\",\\n (table_name, description.name),\\n )\\n row = cursor.fetchone()\\n if not row:\\n raise Exception(\\n 'Could not find a geometry or geography column for \\\"%s\\\".\\\"%s\\\"'\\n % (table_name, description.name)\\n )\\n dim, srid, field_type = row\\n # OGRGeomType does not require GDAL and makes it easy to convert\\n # from OGC geom type name to Django field.\\n field_type = OGRGeomType(field_type).django\\n # Getting any GeometryField keyword arguments that are not the default.\\n field_params = {}\\n if self.postgis_oid_lookup.get(description.type_code) == \\\"geography\\\":\\n field_params[\\\"geography\\\"] = True\\n if srid != 4326:\\n field_params[\\\"srid\\\"] = srid\\n if dim != 2:\\n field_params[\\\"dim\\\"] = dim\\n return field_type, field_params\",\n \"def _convert_field_type(row):\\n return row\",\n \"def get_column_def(self):\\r\\n return '{} {}'.format(self.cql, self.db_type)\",\n \"def parse_description(_descriptions, _db_type):\\n _field_names = []\\n _field_types = []\\n\\n \\\"\\\"\\\"name, type_code, display_size, internal_size, precision, scale, null_ok\\\"\\\"\\\"\\n\\n for _column in _descriptions:\\n _field_names.append(_column[0])\\n if _db_type == DB_MYSQL:\\n _field_types.append(mysql_type_to_sql_type(_column[1]))\\n else:\\n _field_types.append(_column[1])\\n\\n return _field_names, _field_types\",\n \"def test_get_field_type_text_field(self):\\n db_introspection = DatabaseIntrospection(self.connection)\\n self.assertEqual(\\n db_introspection.get_field_type(\\n TypeCode.STRING,\\n description=ColumnInfo(\\n name=\\\"name\\\",\\n type_code=TypeCode.STRING,\\n internal_size=\\\"MAX\\\",\\n ),\\n ),\\n \\\"TextField\\\",\\n )\",\n \"def field_type(self):\\n return \\\"\\\"\",\n \"def field_type(name):\\n if name not in field_types:\\n field_types[name] = records.fields_get([name], attributes=['type'])[name]['type']\\n return field_types.get(name)\",\n \"def findMetadataTable(self, field_name, field_type, log, study_id, lock):\\n \\n # log passed in from writeMetadataValue() - it's a list. At end of function, \\n # exception handler will output contents of log to web for viewing if error\\n # occurrs.\\n \\n try:\\n table = ''\\n field_name = field_name.upper()\\n field_name.replace('\\\"', '')\\n\\n # Fill out the field list if it's the first call\\n log.append('Length of fields is: {0}'.format(str(len(self.fields))))\\n if len(self.fields) == 0:\\n log.append('Filling out field list for table lookup. Current field is \\\"{0}\\\"'.format(field_name))\\n lock.acquire()\\n con = self.getMetadataDatabaseConnection()\\n results = con.cursor()\\n con.cursor().callproc('qiime_assets.find_metadata_table', [results])\\n for tab_name, col_name in results:\\n if col_name not in self.fields:\\n self.fields[col_name] = []\\n self.fields[col_name].append(tab_name)\\n lock.release()\\n \\n log.append('field{} successfully filled out')\\n \\n if field_name in self.fields:\\n # If there's only one hit we can assign it\\n tables = self.fields[field_name]\\n log.append('Type of variable is: %s' % str(tables))\\n if len(self.fields[field_name]) == 1:\\n table = self.fields[field_name][0]\\n log.append('Field only in one table: %s' % table)\\n \\n # More than one table was found with this column name. Find the correct one\\n # based on the study id\\n else:\\n log.append('Field in multiple tables(%s): %s' % (len(self.fields[field_name]), str(self.fields[field_name])))\\n log.append('Study is is: %s' % study_id)\\n for table_name in self.fields[field_name]:\\n if str(study_id) in table_name:\\n table = table_name\\n \\n # If table is not found, assume user-defined column\\n else:\\n \\\"\\\"\\\" Code may look bizarre... but here's why:\\n 1. To streamline access and prevent blocking, we first check to see if the field\\n does exist in the field list. If it does, we do not have to lock and can simply\\n look up the table name.\\n \\n 2. If field is not in list, it must be a new column. In this case we must lock the \\n code that handles new column creation. The catch is that if two threads both hit the lock\\n with the same field name, one will get in and the other will block. Once the initial thread \\n exists, it will have handled the new column, gotten the appropriate table name, and returned. \\n The 2nd thread will now enter the critical section, however if we don't again check to see \\n if the field is now in the field list, it will attempt to create the same column again and \\n fail. Thus we check a 2nd time to see if the field exists and if so, simply read it from the \\n field list. \\n \\\"\\\"\\\"\\n lock.acquire() \\n if field_name in self.fields:\\n log.append('Field now exists. Pulling from local list.')\\n table = self.fields[field_name][0]\\n log.append('Table name exists. Using \\\"%s\\\".' % table)\\n else:\\n log.append('Entities do not exist. Creating...')\\n table = self.handleExtraData(study_id, field_name, field_type, log)\\n log.append('Entities created. Table name is \\\"%s\\\"' % table)\\n if field_name not in self.fields:\\n self.fields[field_name] = [table]\\n else:\\n self.fields[field_name].append(table)\\n lock.release()\\n \\n log.append('Returning from findMetadataTable with value: %s' % str(table))\\n return table\\n\\n except Exception, e:\\n lock.release()\\n log.append('Exception caught: %s' % str(e))\\n print 'Exception caught: %s.\\\\nThe error is: %s' % (type(e), e)\\n raise Exception('\\\\n'.join(log))\",\n \"def get_column_def(self):\\r\\n db_type = self.db_type.format(self.value_type.db_type)\\r\\n return '{} {}'.format(self.cql, db_type)\",\n \"def get_unique_name(self, cursor, field_name=None):\\n if cursor.kind in [CursorKind.UNEXPOSED_DECL]:\\n return ''\\n # covers most cases\\n name = cursor.spelling\\n if cursor.kind == CursorKind.CXX_BASE_SPECIFIER:\\n name = cursor.type.spelling\\n # if it's a record decl or field decl and its type is anonymous\\n if name == '':\\n # if cursor.is_anonymous():\\n # a unnamed object at the root TU\\n if (cursor.semantic_parent\\n and cursor.semantic_parent.kind == CursorKind.TRANSLATION_UNIT):\\n name = self.make_python_name(cursor.get_usr())\\n log.debug('get_unique_name: root unnamed type kind %s',cursor.kind)\\n elif cursor.kind in [CursorKind.STRUCT_DECL,CursorKind.UNION_DECL,\\n CursorKind.CLASS_DECL,CursorKind.FIELD_DECL]:\\n name = self._make_unknown_name(cursor, field_name)\\n log.debug('Unnamed cursor type, got name %s',name)\\n else:\\n log.debug('Unnamed cursor, No idea what to do')\\n #import code\\n #code.interact(local=locals())\\n return ''\\n if cursor.kind in [CursorKind.STRUCT_DECL,CursorKind.UNION_DECL,\\n CursorKind.CLASS_DECL, CursorKind.CXX_BASE_SPECIFIER]:\\n names= {CursorKind.STRUCT_DECL: 'struct',\\n CursorKind.UNION_DECL: 'union',\\n CursorKind.CLASS_DECL: 'class',\\n CursorKind.TYPE_REF: '',\\n CursorKind.CXX_BASE_SPECIFIER: 'class'\\n }\\n name = '%s_%s'%(names[cursor.kind],name)\\n log.debug('get_unique_name: name \\\"%s\\\"',name)\\n return name\",\n \"def get_column_def(self):\\r\\n db_type = self.db_type.format(\\r\\n self.key_type.db_type,\\r\\n self.value_type.db_type\\r\\n )\\r\\n return '{} {}'.format(self.cql, db_type)\",\n \"def get_eltype_from_sbmfielddesc(hgf_field):\\n\\tq = \\\"\\\"\\\"SELECT type FROM sbmFIELDDESC where name='%s'\\\"\\\"\\\" %(hgf_field)\\n\\treturn run_sql(q)[0][0]\",\n \"def getdocfield(fieldname):\\t\\t\\n\\tl = [d for d in doctype_dl if d.doctype=='DocField' and d.fieldname==fieldname]\\n\\treturn l and l[0] or None\",\n \"def test_row_description(cursor: pyodbc.Cursor):\\n cursor.execute(\\\"create table t1(a int, b char(3))\\\")\\n cursor.execute(\\\"insert into t1 values(1, 'abc')\\\")\\n row = cursor.execute(\\\"select * from t1\\\").fetchone()\\n assert cursor.description == row.cursor_description\",\n \"def get_field_from_sbmfielddesc(hgf_field):\\n\\tq = \\\"\\\"\\\"SELECT * FROM sbmFIELDDESC where name='%s'\\\"\\\"\\\" %(hgf_field)\\n\\treturn run_sql(q)[0]\",\n \"def get_type(self) -> str:\\n return self.row_dict['type']\",\n \"def _read_metadata(self, conn, tbl_name): \\n # Split table name in libname and actual table name\\n name, schema = tuple(tbl_name.split('.'))\\n # Query the Vertica dictionary to get types and formats\\n query = \\\"\\\"\\\"\\n SELECT column_name as NAME, data_type as TYPE, data_type_length AS LENGTH \\n FROM v_catalog.columns \\n WHERE table_schema = '{}' AND table_name = '{}'\\n \\\"\\\"\\\".format(name, schema)\\n \\n md = conn.fetch(query)\\n if not len(md):\\n raise ValueError('No metadata for table {}'.format(tbl_name))\\n\\n md = (md\\n # Use variable names as row names, then remove the NAME column\\n .set_index('NAME', inplace=False)\\n # Compute the number of bytes for each variable It is given by the LENGTH variable\\n .rename({'LENGTH': 'NUM_BYTES'}, axis=1))\\n\\n # Identify data types\\n type_upper = md['TYPE'].str.upper()\\n md['IS_TEXT'] = type_upper.str.startswith('VARCHAR')\\n md['IS_BOOLEAN'] = type_upper == 'BOOLEAN'\\n md['IS_INTEGER'] = type_upper.isin(['INT', 'INTEGER'])\\n md['IS_FLOAT'] = (type_upper == 'FLOAT') | type_upper.str.startswith('NUMERIC')\\n md['IS_DATE'] = type_upper == 'DATE'\\n md['IS_TIMESTAMP'] = type_upper == 'TIMESTAMP'\\n md['IS_TIME'] = type_upper == 'TIME'\\n # Determine datetime formats for date and time data\\n md['DATETIME_FORMAT'] = np.nan\\n md.loc[md['IS_DATE'], 'DATETIME_FORMAT'] = 'yyyy-MM-dd'\\n md.loc[md['IS_TIME'], 'DATETIME_FORMAT'] = 'HH:mm:ss'\\n # Determine datetime formats for timestamp data\\n # For timestamp data, the right format is:\\n # - yyyy-MM-dd HH:mm:ss.0 with a JDBC connection <-- python default\\n # - yyyy-MM-dd HH:mm:ss with an ODBC connection\\n md.loc[md['IS_TIMESTAMP'], 'DATETIME_FORMAT'] = 'yyyy-MM-dd HH:mm:ss.0'\\n\\n # Original type\\n md.rename({'TYPE': 'TYPE_IN_SOURCE'}, axis=1, inplace=True)\\n # Create the metadata catalog\\n md = MetadataCatalog(md, is_case_sensitive=False)\\n # Check that all formats have been correctly processed\\n format_check = md.check_metadata_completeness()\\n if not all(format_check):\\n unsupported_format = md.get_type_in_source()\\n unsupported_format = unsupported_format[~format_check].unique()\\n raise ValueError('Unsupported Vertica format: {}'.format(unsupported_format))\\n return md\",\n \"def columns_type(self,table):\\n with self.conn.cursor() as cur:\\n #_logger.debug('Columns Query. sql: %r', self.table_columns_query)\\n cur.execute(self.columns_info_query % (self.dbname,table))\\n for row in cur:\\n yield row\",\n \"def _get_tabletype(cls) -> str:\\n raise NotImplementedError\",\n \"def field_type(self) -> Optional[NameObject]:\\n return self.get(\\\"/FT\\\")\",\n \"def get_field_type(field):\\n if (field < len(Field.FIELD_TYPES)):\\n return Field.FIELD_TYPES[field][1]\\n return 'unknown'\",\n \"def db_field_name(self):\\r\\n return self.db_field or self.column_name\",\n \"def db_field_name(self):\\r\\n return self.db_field or self.column_name\",\n \"def get_column_type(type_name: str) -> object:\\n raise NotImplementedError\",\n \"def _get_fields(self, table):\\n fields = list()\\n for column in table.columns:\\n fields.append({'id': column.name, 'type': str(column.type)})\\n return fields\",\n \"def db_fields(self):\",\n \"def dict_factory(self, cursor, row):\\n results = {}\\n for index, col_name in enumerate(cursor.description):\\n results[col_name[0]] = row[index]\\n\\n return results\",\n \"def get_field(cls, name):\\n if name not in cls.get_field_names():\\n # - check field name first, next: column name -\\n name = cls.get_field_name(name)\\n return getattr(cls, name, None)\",\n \"def cursor_data(c):\\r\\n\\r\\n # pull column description\\r\\n d = []\\r\\n for i in range(len(c.description)):\\r\\n d.append(c.description[i][0])\\r\\n\\r\\n # fetch column entries\\r\\n c = c.fetchall()\\r\\n\\r\\n # compile list\\r\\n info = []\\r\\n for i in range(len(c)):\\r\\n # compile dictionary entry\\r\\n entry = {}\\r\\n for j in range(len(d)):\\r\\n entry[d[j]] = c[i][j]\\r\\n info.append(entry)\\t\\r\\n\\r\\n # success\\r\\n return info\",\n \"def getfield(value, arg):\\n #import pdb; pdb.set_trace()\\n if hasattr(value, \\\"fields\\\"):\\n fields = getattr(value, \\\"fields\\\")\\n if str(arg) in fields:\\n return str(fields[str(arg)])\",\n \"def _update_desc(self):\\n if not self.connection:\\n self.close()\\n cname = CREATE_BUFFER_U(1024)\\n ctype_code = C_SHORT()\\n csize = ctypes.c_size_t()\\n cdisp_size = C_SSIZE_T(0)\\n c_decimal_digits = C_SHORT()\\n cnull_ok = C_SHORT()\\n col_descr = []\\n self._col_type_code_list = []\\n for col in range(1, self._num_of_cols() + 1):\\n ret = ODBC_API.SQLColAttribute(self.stmt_h, col, 6, ADDR(CREATE_BUFFER(10)), 10, ADDR(C_SHORT()), ADDR(cdisp_size))\\n if ret != SQL_SUCCESS:\\n check_success(self, ret)\\n ret = ODBC_API.SQLDescribeColW(self.stmt_h, col, cname, len(cname), ADDR(C_SHORT()), ADDR(ctype_code), ADDR(csize), ADDR(c_decimal_digits), ADDR(cnull_ok))\\n if ret != SQL_SUCCESS:\\n check_success(self, ret)\\n # (name, type_code, display_size,\\n col_descr.append((from_buffer_u(cname), SQL_DATA_TYPE_DICT.get(ctype_code.value, (ctype_code.value,))[0], cdisp_size.value, csize.value, csize.value, c_decimal_digits.value, cnull_ok.value == 1 and True or False))\\n self._col_type_code_list.append(ctype_code.value)\\n if len(col_descr) > 0:\\n self.description = col_descr\\n # Create the row type before fetching.\\n self._row_type = self.row_type_callable(self)\\n else:\\n self.description = None\\n self._create_col_buf()\",\n \"def _get_fields(self):\\n tables = [self.sell_table, self.buy_table, self.pending_table]\\n for table in tables:\\n sql = f'SHOW COLUMNS in {table}'\\n self.fields[table] = list(tb.Database().read(sql).Field)\",\n \"def get_field_def(schema, parent_type, field_ast):\\n name = field_ast.name.value\\n if name == SchemaMetaFieldDef.name and schema.get_query_type() == parent_type:\\n return SchemaMetaFieldDef\\n\\n elif name == TypeMetaFieldDef.name and schema.get_query_type() == parent_type:\\n return TypeMetaFieldDef\\n\\n elif name == TypeNameMetaFieldDef.name and \\\\\\n isinstance(parent_type, (\\n GraphQLObjectType,\\n GraphQLInterfaceType,\\n GraphQLUnionType,\\n )):\\n return TypeNameMetaFieldDef\\n\\n elif isinstance(parent_type, (GraphQLObjectType, GraphQLInterfaceType)):\\n return parent_type.get_fields().get(name)\",\n \"def type(self):\\n return self._field.type\",\n \"def _to_known_field(cls, field_name: str, value) -> (Column, dict):\\n field_names = field_name.split(\\\".\\\", maxsplit=1)\\n if len(field_names) == 2:\\n for field in cls.__fields__:\\n if field.name == field_names[0] and field.field_type == dict:\\n return field, {field_names[1]: value}\\n return None, None\",\n \"def dict_factory(cursor, row):\\r\\n\\td = {}\\r\\n\\tfor idx, col in enumerate(cursor.description):\\r\\n\\t\\td[col[0]] = row[idx]\\r\\n\\treturn d\",\n \"def dict_factory(cursor, row):\\n fields = [column[0] for column in cursor.description]\\n return {key: value for key, value in zip(fields, row)}\",\n \"def __parse_field(self, field, tuple_descriptor, alias_on_complex_types, make_visible):\\r\\n alias = None\\r\\n field_type = None\\r\\n return_type = None\\r\\n underlying_fields = None\\r\\n aggregate_factory = None\\r\\n literal_value = None\\r\\n func_factory = None\\r\\n fields_to_verify = []\\r\\n parsed_fds = []\\r\\n field_backup = list(field)\\r\\n self.__clean_list(field)\\r\\n \\r\\n # parse aliases if they exist\\r\\n if (len(field) >= 4) and (field[-2] == QueryTokens.AS):\\r\\n alias = field[-1]\\r\\n field = field[:-2]\\r\\n if (field[0] == QueryTokens.STRING_LITERAL) or \\\\\\r\\n (field[0] == QueryTokens.INTEGER_LITERAL) or \\\\\\r\\n (field[0] == QueryTokens.FLOAT_LITERAL): \\r\\n alias = self.unnamed_operator_name()\\r\\n underlying_fields = []\\r\\n field_type = FieldType.LITERAL\\r\\n literal_value = field[1]\\r\\n if field[0] == QueryTokens.STRING_LITERAL:\\r\\n return_type = ReturnType.STRING\\r\\n elif field[0] == QueryTokens.INTEGER_LITERAL:\\r\\n return_type = ReturnType.INTEGER\\r\\n literal_value = int(literal_value)\\r\\n elif field[0] == QueryTokens.FLOAT_LITERAL:\\r\\n return_type = ReturnType.FLOAT\\r\\n literal_value = float(literal_value)\\r\\n elif field[0] == QueryTokens.COLUMN_NAME: # field or alias\\r\\n if alias == None:\\r\\n alias = field[1]\\r\\n field_descriptor = tuple_descriptor.get_descriptor(field[1])\\r\\n if field_descriptor == None: # underlying field not yet defined. mark to check later\\r\\n field_type = FieldType.UNDEFINED\\r\\n underlying_fields = [field[1]]\\r\\n # check alias and underlying once this process is done to\\r\\n # find yet-undefined fields\\r\\n fields_to_verify.append(field[1])\\r\\n fields_to_verify.append(alias)\\r\\n else: # field found, copy information\\r\\n field_type = field_descriptor.field_type\\r\\n return_type = field_descriptor.return_type\\r\\n underlying_fields = field_descriptor.underlying_fields\\r\\n aggregate_factory = field_descriptor.aggregate_factory\\r\\n func_factory = field_descriptor.func_factory\\r\\n elif field[0] == QueryTokens.FUNCTION_OR_AGGREGATE: # function or aggregate \\r\\n if alias == None:\\r\\n if alias_on_complex_types:\\r\\n raise QueryException(\\\"Must specify alias (AS clause) for '%s'\\\" % (field[1]))\\r\\n else:\\r\\n alias = self.unnamed_operator_name()\\r\\n underlying_field_list = field[2:]\\r\\n underlying_fields = []\\r\\n for underlying in underlying_field_list:\\r\\n (parsed_fd_list, parsed_verify) = self.__parse_field(underlying, tuple_descriptor, False, False)\\r\\n for parsed_fd in parsed_fd_list:\\r\\n parsed_fd.visible = False\\r\\n fields_to_verify.extend(parsed_verify)\\r\\n parsed_fds.extend(parsed_fd_list)\\r\\n underlying_fields.append(parsed_fd_list[0].alias)\\r\\n aggregate_factory = get_aggregate_factory(field[1])\\r\\n if aggregate_factory != None: # found an aggregate function\\r\\n field_type = FieldType.AGGREGATE\\r\\n return_type = ReturnType.FLOAT\\r\\n else:\\r\\n function_information = self.function_registry.get_function(field[1])\\r\\n if function_information != None:\\r\\n field_type = FieldType.FUNCTION\\r\\n func_factory = function_information.func_factory\\r\\n return_type = function_information.return_type\\r\\n else:\\r\\n raise QueryException(\\\"'%s' is neither an aggregate or a registered function\\\" % (field[1]))\\r\\n else:\\r\\n raise QueryException(\\\"Empty field clause found: %s\\\" % (\\\"\\\".join(field_backup)))\\r\\n fd = FieldDescriptor(alias, underlying_fields, field_type, return_type, aggregate_factory, func_factory, literal_value)\\r\\n fd.visible = make_visible\\r\\n parsed_fds.insert(0, fd)\\r\\n return (parsed_fds, fields_to_verify)\",\n \"def get_field_type(field, table):\\n for i in settings.GTFS_SPEC['resources']:\\n print(i['name'])\\n if i['name'] == table:\\n for j in i['schema']['fields']:\\n print(j['name'])\\n if j['name'] == field:\\n return j['gtfs_type']\\n raise ValueError(\\\"Field not found in GTFS spec.\\\")\",\n \"def dict_factory(cursor, row):\\n dic = {}\\n for idx, col in enumerate(cursor.description):\\n if isinstance(row[idx], unicode):\\n dic[col[0]] = u.unicode_to_string(row[idx])\\n else:\\n dic[col[0]] = row[idx]\\n return dic\",\n \"def datetime_type_field_name(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"datetime_type_field_name\\\")\",\n \"def __getitem__(self, field_name):\\n\\n if field_name in self._module._fields.keys():\\n try:\\n return self._fields[field_name]\\n except KeyError:\\n if self['id'] == '':\\n # If this is a new entry, the 'id' field is yet undefined.\\n return ''\\n else:\\n # Retrieve the field from the SugarCRM connection.\\n \\n q_str = \\\"%s.id='%s'\\\" % (self._module._table, self['id'])\\n res = self._module._connection.get_entry_list(\\n self._module._name, q_str,\\n '', 0, [field_name], 1, 0)\\n\\n nvl = res['entry_list'][0]['name_value_list']\\n for attribute in nvl:\\n if attribute == field_name:\\n value = nvl[attribute]['value']\\n if value:\\n self._fields[attribute] = \\\\\\n HTMLParser().unescape(\\n nvl[attribute]['value'])\\n else:\\n self._fields[attribute] = ''\\n\\n return self._fields[attribute]\\n\\n else:\\n raise AttributeError\",\n \"def find_type(line):\\n type_string = line.split(':')[-1].strip(\\\";\\\\n \\\")\\n isOptional = False\\n if \\\"|\\\" in type_string:\\n isOptional = True\\n type_string = type_string.split(' | ')[0].strip()\\n\\n column_type = type_mapping[type_string]\\n\\n register_imports(column_type, isOptional)\\n\\n return (column_type, isOptional)\",\n \"def writeMetadataValue(self, field_type, key_field, field_name, field_value, \\\\\\n study_id, host_key_field, row_num, lock):\\n \\n # This is a mess and it's slow right now. In need of serious speed improvements and cleanup.\\n \\n statement = ''\\n log = []\\n pk_name = ''\\n\\n try:\\n #lock.acquire()\\n \\n # Get our database connection\\n con = self.getMetadataDatabaseConnection()\\n \\n # Set the timeout\\n #con.cursor().execute('alter session set ddl_lock_timeout=100') \\n \\n # Find the table name\\n log.append('Locating table name...')\\n table_name = None\\n table_name = self.findMetadataTable(field_name, field_type, log, study_id, lock)\\n log.append('Successfully found table name. Table name is \\\"%s\\\"' % str(table_name))\\n \\n #if field_name == 'dw1':\\n # raise Exception('asdf')\\n\\n # Double-quote for database safety\\n log.append('Adding quotes to table name...')\\n table_name = '\\\"' + table_name + '\\\"' \\n log.append('Quoted table name is %s' % table_name)\\n log.append('Table name found: %s' % (table_name))\\n \\n # Store the field name in the database. These are the field names which will\\n # be used later to generate a mapping file. We collect the names here because\\n # it's an expensive operation to determine post-commit which fields were\\n # actually submitted to the database.\\n log.append('Attempting to store values in study_actual_columns: %s, %s, %s'\\\\\\n % (study_id, field_name, table_name))\\n self.addStudyActualColumn(study_id, field_name, table_name);\\n \\n # Get extended field info from the database\\n log.append('Loading field details...')\\n field_details = self.getFieldDetails(field_name)\\n log.append(str(field_details))\\n if field_details == None:\\n log.append('Could not obtain detailed field information. Skipping.')\\n raise Exception\\n else:\\n database_data_type = field_details[1]\\n log.append('Read field database data type as \\\"%s\\\"' % database_data_type)\\n \\n # If the field value is 'unknown', switch to 'null' (empty string is the same as null)\\n #pass_values = \\n if str(field_value).upper() == 'UNKNOWN':\\n field_value = ''\\n # Figure out if this needs to be an integer ID instead of a text value\\n elif database_data_type == 'list':\\n log.append('Field is of type list. Looking up integer value...')\\n named_params = {'field_value':field_value.upper()}\\n statement = 'select vocab_value_id from controlled_vocab_values where upper(term) = :field_value'\\n statement = str(statement)\\n log.append(statement)\\n results = con.cursor().execute(statement, named_params).fetchone()\\n if results != None:\\n # If found, set the field_value to its numeric identifier for storage\\n log.append('Value found in controlled_vocab_values. Old field value: \\\"%s\\\", new field value: \\\"%s\\\".'\\\\\\n % (field_value, results[0]))\\n field_value = results[0]\\n else:\\n log.append('Could not determine inteteger value for list term \\\"%s\\\" with value \\\"%s\\\". Skipping.'\\\\\\n % (field_name, field_value))\\n raise Exception\\n \\n # Set the field_name to it's quoted upper-case name to avoid key-work issues with Oracle\\n field_name = '\\\"%s\\\"' % field_name.upper()\\n \\n ########################################\\n ### For STUDY\\n ########################################\\n \\n # Study is special - handle separately since row is guaranteed to exist and there can only be one row\\n if table_name == '\\\"STUDY\\\"' or 'EXTRA_STUDY_' in table_name:\\n log.append('Updating study field...')\\n named_params = {'field_value':field_value, 'study_id':study_id}\\n statement = 'update %s set %s = :field_value where study_id = :study_id' % (table_name, field_name)\\n statement = str(statement)\\n log.append(statement)\\n log.append('field_value = \\\"%s\\\", study_id = \\\"%s\\\"' % (field_value, study_id))\\n results = con.cursor().execute(statement, named_params)\\n con.cursor().execute('commit')\\n log.append('Study updated.')\\n #raise Exception\\n return\\n \\n ########################################\\n ### For other tables\\n ########################################\\n \\n if table_name in ['\\\"AIR\\\"', '\\\"COMMON_FIELDS\\\"', '\\\"MICROBIAL_MAT_BIOFILM\\\"', '\\\"OTHER_ENVIRONMENT\\\"', \\\\\\n '\\\"SAMPLE\\\"', '\\\"SEDIMENT\\\"', '\\\"SOIL\\\"', '\\\"WASTEWATER_SLUDGE\\\"', '\\\"WATER\\\"', '\\\"SEQUENCE_PREP\\\"', \\\\\\n '\\\"HOST_ASSOC_VERTIBRATE\\\"', '\\\"HOST_ASSOCIATED_PLANT\\\"', '\\\"HOST_SAMPLE\\\"', '\\\"HUMAN_ASSOCIATED\\\"',\\n '\\\"COMMON_EXTRA_SAMPLE\\\"', '\\\"COMMON_EXTRA_SAMPLE_2\\\"', '\\\"COMMON_EXTRA_PREP\\\"'] \\\\\\n or 'EXTRA_SAMPLE_' in table_name or 'EXTRA_PREP_' in table_name:\\n named_params = {'key_field':key_field, 'study_id':study_id}\\n statement = 'select sample_id from \\\"SAMPLE\\\" where sample_name = :key_field and study_id = :study_id'\\n statement = str(statement)\\n key_column = 'sample_id'\\n key_table = '\\\"SAMPLE\\\"'\\n elif table_name in ['\\\"HOST\\\"']:\\n named_params = {'key_field':'{0}:{1}'.format(str(study_id), host_key_field)}\\n statement = 'select host_id from \\\"HOST\\\" where host_subject_id = :key_field'\\n statement = str(statement)\\n key_column = 'host_id'\\n key_table = '\\\"HOST\\\"'\\n else:\\n return 'Unknown table found - no action taken. Table name was: \\\"%s\\\". Column name was: \\\"%s\\\"'\\\\\\n % (table_name, field_name)\\n \\n # Find the assocaited key column\\n log.append('Determining if required key row exists...')\\n log.append(statement + '\\\", key_field is ' + key_field + ', study_id is ' + str(study_id))\\n results = con.cursor().execute(statement, named_params).fetchone()\\n if results != None:\\n key_column_value = results[0]\\n log.append('Found key_column_value: %s' % str(key_column_value))\\n else:\\n log.append('Could not determine key. Skipping write for field %s with value \\\"%s\\\".'\\\\\\n % (field_name, field_value))\\n raise Exception\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n\\n ####### to speed up access, create local storage for all items already seen\\n\\n\\n\\n # If it ain't there, create it\\n log.append('Checking if row already exists...')\\n \\n # Must append row_num if sequence table\\n if table_name == '\\\"SEQUENCE_PREP\\\"' or table_name == '\\\"COMMON_EXTRA_PREP\\\"' or 'EXTRA_PREP_' in table_name:\\n named_params = {'key_column_value':key_column_value, 'row_number':row_num}\\n statement = 'select 1 from %s where %s = :key_column_value and row_number = :row_number'\\\\\\n % (table_name, key_column)\\n else:\\n named_params = {'key_column_value':key_column_value}\\n statement = 'select 1 from %s where %s = :key_column_value' % (table_name, key_column)\\n statement = str(statement)\\n log.append(statement)\\n results = con.cursor().execute(statement, named_params).fetchone()\\n \\n if results == None:\\n log.append('No row found, inserting new row')\\n if table_name == '\\\"SEQUENCE_PREP\\\"' or table_name == '\\\"COMMON_EXTRA_PREP\\\"' or 'EXTRA_PREP_' in table_name:\\n log.append('Row number is %s' % (str(row_num)))\\n named_params = {'key_column_value':key_column_value, 'row_number':row_num}\\n statement = 'insert into %s (%s, row_number) values (:key_column_value, :row_number)'\\\\\\n % (table_name, key_column)\\n else:\\n named_params = {'key_column_value':key_column_value}\\n statement = 'insert into %s (%s) values (:key_column_value)' % (table_name, key_column)\\n statement = str(statement)\\n log.append(statement)\\n con.cursor().execute(statement, named_params)\\n\\n\\n\\n\\n\\n\\n \\n # Attempt to write the metadata field\\n log.append('Writing metadata value...')\\n \\n # If it's a date, must not put quotes around the oracle to_date function.\\n if database_data_type == 'date':\\n field_value = self.convertToOracleHappyName(field_value)\\n if table_name == '\\\"SEQUENCE_PREP\\\"' or table_name == '\\\"COMMON_EXTRA_PREP\\\"' or 'EXTRA_PREP_' in table_name:\\n statement = 'update %s set %s = %s where %s = %s and row_number = %s'\\\\\\n % (table_name, field_name, field_value, key_column, key_column_value, row_num)\\n else: \\n statement = 'update %s set %s = %s where %s = %s'\\\\\\n % (table_name, field_name, field_value, key_column, key_column_value) \\n else: \\n if table_name == '\\\"SEQUENCE_PREP\\\"' or table_name == '\\\"COMMON_EXTRA_PREP\\\"' or 'EXTRA_PREP_' in table_name:\\n statement = 'update %s set %s = \\\\'%s\\\\' where %s = %s and row_number = %s'\\\\\\n % (table_name, field_name, field_value, key_column, key_column_value, row_num)\\n else: \\n statement = 'update %s set %s = \\\\'%s\\\\' where %s = %s'\\\\\\n % (table_name, field_name, field_value, key_column, key_column_value)\\n statement = str(statement)\\n log.append(statement)\\n results = con.cursor().execute(statement)\\n \\n # Finally, commit the changes\\n results = con.cursor().execute('commit')\\n\\n #if field_name == '\\\"DW1\\\"':\\n # raise Exception('Found DW1: Dumping log')\\n \\n except Exception, e:\\n call_string = 'writeMetadataValue(\\\"%s\\\", \\\"%s\\\", \\\"%s\\\", \\\"%s\\\", \\\"%s\\\")'\\\\\\n % (field_type, key_field, field_name, field_value, study_id)\\n log_string = '
'.join(log)\\n error_msg = 'Exception caught attempting to store field \\\"%s\\\" with value \\\"%s\\\" into \\\\\\n table \\\"%s\\\".
Method signature: %s
Full error log:
%s
Oracle says: %s' % \\\\\\n (field_name, field_value, table_name, call_string, log_string, str(e))\\n raise Exception(error_msg)\\n finally:\\n # Release the lock\\n #lock.release()\\n log.append('Lock released')\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def get_pymongo_type_string(\\n self, field_type: Union[Type, str], collection_name: str\\n ) -> str:\\n try:\\n type_string = PYMONGO_TYPE_TO_MONGO_TYPE[field_type]\\n except KeyError:\\n self.report.report_warning(\\n collection_name, f\\\"unable to map type {field_type} to metadata schema\\\"\\n )\\n PYMONGO_TYPE_TO_MONGO_TYPE[field_type] = \\\"unknown\\\"\\n type_string = \\\"unknown\\\"\\n\\n return type_string\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def db_type(self, field):\\r\\n if self.connection.settings_dict.get('STORE_RELATIONS_AS_DB_KEYS'):\\r\\n if field.primary_key or field.rel is not None:\\r\\n return 'key'\\r\\n\\r\\n # Primary keys were processed as db.Keys; for related fields\\r\\n # the db_type of primary key of the referenced model was used,\\r\\n # but RelatedAutoField type was not defined and resulted in\\r\\n # \\\"integer\\\" being used for relations to models with AutoFields.\\r\\n # TODO: Check with Positive/SmallIntegerField primary keys.\\r\\n else:\\r\\n if field.primary_key:\\r\\n return 'key'\\r\\n if field.rel is not None:\\r\\n related_field = field.rel.get_related_field()\\r\\n if related_field.get_internal_type() == 'AutoField':\\r\\n return 'integer'\\r\\n else:\\r\\n return related_field.db_type(connection=self.connection)\\r\\n\\r\\n db_type = field.db_type(connection=self.connection)\\r\\n\\r\\n # Override db_type of \\\"string\\\" fields according to indexing.\\r\\n if db_type in ('string', 'text'):\\r\\n indexes = get_model_indexes(field.model)\\r\\n if field.attname in indexes['indexed']:\\r\\n return 'string'\\r\\n elif field.attname in indexes['unindexed']:\\r\\n return 'text'\\r\\n\\r\\n return db_type\",\n \"def dict_factory(cursor, row):\\n rowdict = {}\\n for idx, col in enumerate(cursor.description):\\n rowdict[col[0]] = row[idx]\\n return rowdict\",\n \"def type_fields(self, res, op_item):\\n result = []\\n cast_func = {}\\n header = res[0]\\n for heading in header:\\n cast_func[heading] = DataType.str\\n\\n if \\\"field_type\\\" in op_item:\\n for f, p in findall(FIELD_TYPE_RE, op_item[\\\"field_type\\\"]):\\n cast_func[p] = self.dt.get_func(f)\\n first = True\\n for row in res[1:]:\\n new_row = []\\n for idx in range(len(header)):\\n\\n heading = header[idx]\\n cur_value = row[idx]\\n if type(cur_value) is tuple:\\n cur_value = cur_value[1]\\n if heading == \\\"timespan\\\" and first:\\n first = False\\n new_row.append((cast_func[heading](cur_value), cur_value))\\n\\n result.append(new_row)\\n\\n return [header] + result\",\n \"def get_column_type(cls, **kwargs: Any) -> Any: # pragma no cover\\n return None\",\n \"def extract_generic_credit_type(self, course_row):\\n course_id = row[0]\\n credit_type_res = {re.compile(\\\"Communication\\\"):\\\"CS\\\",\\n re.compile(\\\"Natural Science\\\"):\\\"NS\\\",\\n re.compile(\\\"Humanities\\\"):\\\"H\\\",\\n re.compile(\\\"Performance\\\"):\\\"HP\\\",\\n re.compile(\\\"Social\\\"):\\\"SS\\\",\\n re.compile(\\\"Lab\\\"):\\\"NSL\\\",\\n re.compile(\\\"Quant\\\"):\\\"QS\\\",\\n re.compile(\\\"Elective\\\"):\\\"E\\\",\\n re.compile(\\\"Diversity\\\"):\\\"DC\\\",\\n re.compile(\\\"Prereq\\\"):\\\"PR\\\"}\\n for credit_type_re in credit_type_res:\\n if credit_type_re.search(course_id):\\n type_string = credit_type_res[credit_type_re]\\n credit_type = models.CreditType.objects.get(label_short=type_string)\\n return credit_type\",\n \"def specific(self):\\n field_attr = field_registry.field_map[self.type]\\n return getattr(self, field_attr, None)\",\n \"def _fields(self, doclet):\\n FIELD_TYPES = OrderedDict([('params', _params_formatter),\\n ('properties', _params_formatter),\\n ('exceptions', _exceptions_formatter),\\n ('returns', _returns_formatter)])\\n for field_name, callback in iteritems(FIELD_TYPES):\\n for field in doclet.get(field_name, []):\\n description = field.get('description', '')\\n unwrapped = sub(r'[ \\\\t]*[\\\\r\\\\n]+[ \\\\t]*', ' ', description)\\n yield callback(field, unwrapped)\",\n \"def get_model_details(refobject):\\n typename = type(refobject).__name__\\n\\n if typename in TYPES_TABLE:\\n\\n details = TYPES_TABLE[typename]\\n\\n elif isinstance(refobject, type):\\n clrtype = clr.GetClrType(refobject)\\n\\n if clrtype.IsEnum:\\n details = TYPES_TABLE['enumtype']\\n\\n elif clrtype.IsClass:\\n if clrtype.FullName.startswith('Autodesk.Revit.DB'):\\n details = TYPES_TABLE['revitclass']\\n\\n else:\\n details = TYPES_TABLE['classtype']\\n\\n elif clrtype.IsInterface:\\n details = TYPES_TABLE['interface']\\n\\n elif clrtype.FullName in SYS_TYPES:\\n details = TYPES_TABLE['systype']\\n\\n elif clrtype.FullName in WIN_TYPES:\\n details = TYPES_TABLE['wintype']\\n\\n else:\\n details = TYPES_TABLE['unknown']\\n logger.debug('TODO get_model_details for CLR/type: {} ({})'.format(\\n typename, refobject))\\n\\n # match all list/collection types\\n elif is_iterable(refobject):\\n details = TYPES_TABLE['listtype']\\n\\n # match sub enum types\\n elif clr.GetClrType(type(refobject)).IsEnum:\\n details = TYPES_TABLE['subenumtype']\\n\\n # match sub class types\\n elif clr.GetClrType(type(refobject)).IsClass:\\n\\n if clr.GetClrType(type(refobject)).FullName == 'Autodesk.Revit.DB.Parameter':\\n details = TYPES_TABLE['revitparameter']\\n\\n elif clr.GetClrType(type(refobject)).FullName.startswith('Autodesk.Revit.DB'):\\n details = TYPES_TABLE['revitclass']\\n else:\\n details = TYPES_TABLE['subclasstype']\\n\\n elif clr.GetClrType(type(refobject)).IsInterface:\\n details = TYPES_TABLE['interface']\\n\\n elif clr.GetClrType(type(refobject)).FullName in SYS_TYPES:\\n details = TYPES_TABLE['systype']\\n\\n elif clr.GetClrType(type(refobject)).FullName in WIN_TYPES:\\n details = TYPES_TABLE['wintype']\\n\\n else:\\n details = TYPES_TABLE['unknown']\\n logger.debug('TODO get_model_details for : {} ({})'.format(\\n typename, refobject))\\n\\n return details\",\n \"def init_fields(self):\\n result = self.connection.execute('pragma table_info(files)')\\n rows = result.fetchall()\\n self.fields = [Field(row) for row in rows[4:]]\\n result = self.connection.execute('select _keyword from keywords')\\n rows = result.fetchall()\\n self.keywords = [row[0] for row in rows]\",\n \"def field(self) -> 'outputs.PreventionStoredInfoTypeLargeCustomDictionaryBigQueryFieldField':\\n return pulumi.get(self, \\\"field\\\")\",\n \"def south_field_triple(self):\\n # We'll just introspect ourselves, since we inherit.\\n from south.modelsinspector import introspector\\n field_class = \\\"django.db.models.fields.TextField\\\"\\n args, kwargs = introspector(self)\\n # That's our definition!\\n return (field_class, args, kwargs)\",\n \"async def get_schema_info(self, collection):\\n await self.ensure_collection(collection)\\n try:\\n # Luke handler is not supported in API v2 yet.\\n # /v2/collections//schema/fields doesn't show dynamically\\n # created fields.\\n # So using old API (/solr/...).\\n response = await self.get(\\n '/solr/{}/admin/luke?numTerms=0'.format(collection)\\n )\\n return json.loads(response.body.decode('utf-8'))\\n except SolrError:\\n logger.warning('Failed to fetch fields list for collection {}'\\n .format(collection))\\n raise\",\n \"def sql_type(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"sql_type\\\")\",\n \"def sql_type(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"sql_type\\\")\",\n \"def _init_fields(self):\\n if self._fields is None:\\n M.mset('U', \\\"^\\\") # DBS Calls Require this\\n f = self._fields = {}\\n attrs = self.fieldnames = {}\\n fieldid = \\\"0\\\"\\n while 1:\\n # Subscript 0 is field description, .1 is the title, 3 is help\\n fieldid, info, title, fieldhelp = M.ddwalk(self._fileid, fieldid)\\n #fieldid, info, title, fieldhelp = M.mexec(\\n # \\\"\\\"\\\"set s0=$order(^DD(s2,s0)) Q:s0'=+s0 s s1=$G(^DD(s2,s0,0)),s3=$G(^DD(s2,s0,.1)),s4=$G(^DD(s2,s0,3))\\\"\\\"\\\",\\n # M.INOUT(str(fieldid)), M.INOUT(\\\"\\\"), str(self._fileid), M.INOUT(\\\"\\\"), M.INOUT(\\\"\\\"))\\n if fieldid == \\\"\\\" or fieldid[0] not in \\\"0123456789.\\\":\\n break\\n\\n info = info.split(\\\"^\\\", 4) \\n label = self._clean_label(info[0])\\n try:\\n ftype = info[1]\\n except:\\n ftype = None\\n if ftype:\\n finst = None\\n for klass in FIELD_TYPES:\\n if klass.isa(ftype):\\n finst = f[fieldid] = klass(fieldid, label, info)\\n finst.fileid = self.fileid\\n finst.ownerdd = self\\n attrs[label] = fieldid\\n break\\n if finst is None:\\n print finst, \\\"FIELD [%s], spec [%s] was not identified\\\" % (label, ftype)\\n continue\\n finst.title = title\\n finst.fieldhelp = fieldhelp\\n else:\\n assert finst, \\\"FIELD [%s] %s has no fieldspec\\\" % (label, info)\\n\\n return self._fields\",\n \"def describe(self):\\r\\n return dict((field.name, dict(\\r\\n id=field.name,\\r\\n name=field.label,\\r\\n validators=ValidatorSerializer(\\r\\n field.requires if isSequenceType(field.requires) else [field.requires])(),\\r\\n comment=field.comment,\\r\\n readable=field.readable,\\r\\n writable=field.writable,\\r\\n type=getattr(field, 'wtype',\\r\\n field.type.type if isinstance(field.type, SQLCustomType) else field.type.split('(')[0]),\\r\\n # w2pwidget=field.widget,\\r\\n )) for field in self.descibe_columns)\",\n \"def table_description(classname, nclassname, shape=()):\\n classdict = {}\\n colpos = append_columns(classdict, shape)\\n\\n ndescr = nested_description(nclassname, colpos, shape=shape)\\n classdict['c_nested'] = ndescr\\n colpos += 1\\n\\n extracol = tb.IntCol(shape=shape, pos=colpos)\\n classdict['c_extra'] = extracol\\n colpos += 1\\n\\n idxextracol = tb.IntCol(shape=shape, pos=colpos)\\n classdict['c_idxextra'] = idxextracol\\n colpos += 1\\n\\n return type(classname, (tb.IsDescription,), classdict)\",\n \"def retrievebeamparamproptype(self, cursor, bpptname, bpptunit=None):\\n sql = \\\"\\\"\\\"\\n SELECT\\n beam_param_prop_type_id,\\n beam_param_prop_type_name,\\n beam_param_prop_type_desc,\\n beam_param_prop_type_unit\\n FROM\\n beam_param_prop_type\\n WHERE\\n \\\"\\\"\\\"\\n sql += \\\"beam_param_prop_type_name = '%s'\\\" % (bpptname,)\\n if bpptunit is None:\\n sql += \\\" AND beam_param_prop_type_unit IS NULL\\\"\\n else:\\n sql += \\\" AND beam_param_prop_type_unit = '%s'\\\" % (bpptunit,)\\n cursor.execute(sql)\\n return cursor.fetchone()\",\n \"def _getfield(self, block, name):\\n\\n # First, get the field from the class, if defined\\n block_field = getattr(block.__class__, name, None)\\n if block_field is not None and isinstance(block_field, Field):\\n return block_field\\n\\n # Not in the class, so name\\n # really doesn't name a field\\n raise KeyError(name)\",\n \"def add_field(self, field_name, field_type):\\n field_name = field_name.replace('\\\"','')\\n if field_type == 'keyword':\\n query = \\\"\\\"\\\"insert or ignore into keywords\\n (_keyword) values (\\\"%s\\\")\\\"\\\"\\\" % field_name\\n else:\\n query = 'alter table files add column \\\"%s\\\" %s' % (\\n field_name, field_type)\\n self.connection.execute(query)\\n self.connection.commit()\\n self.init_fields()\",\n \"def column_reflection_fallback(self):\\n col_info_dict_list: List[Dict]\\n if self.sql_engine_dialect.name.lower() == \\\"mssql\\\":\\n type_module = self._get_dialect_type_module()\\n # Get column names and types from the database\\n # StackOverflow to the rescue: https://stackoverflow.com/a/38634368\\n col_info_query: TextClause = sa.text(\\n f\\\"\\\"\\\"\\nSELECT\\n cols.NAME, ty.NAME\\nFROM\\n tempdb.sys.columns AS cols\\nJOIN\\n sys.types AS ty\\nON\\n cols.user_type_id = ty.user_type_id\\nWHERE\\n object_id = OBJECT_ID('tempdb..{self._table}')\\n \\\"\\\"\\\"\\n )\\n col_info_tuples_list = self.engine.execute(col_info_query).fetchall()\\n col_info_dict_list = [\\n {\\\"name\\\": col_name, \\\"type\\\": getattr(type_module, col_type.upper())()}\\n for col_name, col_type in col_info_tuples_list\\n ]\\n else:\\n query: Select = sa.select([sa.text(\\\"*\\\")]).select_from(self._table).limit(1)\\n col_names: list = self.engine.execute(query).keys()\\n col_info_dict_list = [{\\\"name\\\": col_name} for col_name in col_names]\\n return col_info_dict_list\",\n \"def get_field_type(db_code):\\n try:\\n field_type = connection.introspection.get_field_type(\\n db_code, 'django_musicbrainz tests')\\n except KeyError:\\n # if the db_code is not listed in\\n # django.db.backens.postgresql_psycopg2.introspection.\\\\\\n # DatabaseIntrospection.data_types_reverse we guess that\\n # the db type is a TextField\\n field_type = 'TextField'\\n return field_type\",\n \"def get_table_info(line):\\n\\n COMMENT_EXPR = '-- Name: '\\n TYPE_EXPR = '; Type: '\\n SCHEMA_EXPR = '; Schema: '\\n OWNER_EXPR = '; Owner: '\\n TABLESPACE_EXPR = '; Tablespace: '\\n\\n temp = line.strip('\\\\n')\\n type_start = get_all_occurrences(TYPE_EXPR, temp)\\n schema_start = get_all_occurrences(SCHEMA_EXPR, temp)\\n owner_start = get_all_occurrences(OWNER_EXPR, temp)\\n tblspace_start = get_all_occurrences(TABLESPACE_EXPR, temp)\\n if len(type_start) != 1 or len(schema_start) != 1 or len(owner_start) != 1:\\n return (None, None, None, None)\\n name = temp[len(COMMENT_EXPR) : type_start[0]]\\n type = temp[type_start[0] + len(TYPE_EXPR) : schema_start[0]]\\n schema = temp[schema_start[0] + len(SCHEMA_EXPR) : owner_start[0]]\\n if not tblspace_start:\\n tblspace_start.append(None)\\n owner = temp[owner_start[0] + len(OWNER_EXPR) : tblspace_start[0]]\\n return (name, type, schema, owner)\",\n \"def test_get_table_description(self):\\n db_introspection = DatabaseIntrospection(self.connection)\\n cursor = mock.MagicMock()\\n\\n def description(*args, **kwargs):\\n return [[\\\"name\\\", TypeCode.STRING], [\\\"age\\\", TypeCode.INT64]]\\n\\n def get_table_column_schema(*args, **kwargs):\\n column_details = {}\\n column_details[\\\"name\\\"] = ColumnDetails(\\n null_ok=False, spanner_type=\\\"STRING(10)\\\"\\n )\\n column_details[\\\"age\\\"] = ColumnDetails(\\n null_ok=True, spanner_type=\\\"INT64\\\"\\n )\\n return column_details\\n\\n cursor.get_table_column_schema = get_table_column_schema\\n cursor.description = description()\\n table_description = db_introspection.get_table_description(\\n cursor=cursor, table_name=\\\"Table_1\\\"\\n )\\n if USING_DJANGO_3:\\n self.assertEqual(\\n table_description,\\n [\\n FieldInfo(\\n name=\\\"name\\\",\\n type_code=TypeCode.STRING,\\n display_size=None,\\n internal_size=10,\\n precision=None,\\n scale=None,\\n null_ok=False,\\n default=None,\\n collation=None,\\n ),\\n FieldInfo(\\n name=\\\"age\\\",\\n type_code=TypeCode.INT64,\\n display_size=None,\\n internal_size=None,\\n precision=None,\\n scale=None,\\n null_ok=True,\\n default=None,\\n collation=None,\\n ),\\n ],\\n )\\n else:\\n self.assertEqual(\\n table_description,\\n [\\n FieldInfo(\\n name=\\\"name\\\",\\n type_code=TypeCode.STRING,\\n display_size=None,\\n internal_size=10,\\n precision=None,\\n scale=None,\\n null_ok=False,\\n default=None,\\n ),\\n FieldInfo(\\n name=\\\"age\\\",\\n type_code=TypeCode.INT64,\\n display_size=None,\\n internal_size=None,\\n precision=None,\\n scale=None,\\n null_ok=True,\\n default=None,\\n ),\\n ],\\n )\",\n \"def _get_field_details(self, data, fields):\\n fields_metadata = dict()\\n for field in fields:\\n dtype = data[field].dtype\\n field_template = self._FIELD_TEMPLATES.get(dtype.kind)\\n if not field_template:\\n raise ValueError('Unsupported dtype {} in column {}'.format(dtype, field))\\n\\n field_details = copy.deepcopy(field_template)\\n fields_metadata[field] = field_details\\n\\n return fields_metadata\",\n \"def get_description_from_row(row):\\n return [\\n (\\n name, # name\\n get_type(value), # type_code\\n None, # [display_size]\\n None, # [internal_size]\\n None, # [precision]\\n None, # [scale]\\n get_type(value) == Type.STRING, # [null_ok]\\n )\\n for name, value in row.items()\\n ]\",\n \"def get_fields(dgid, metadata=None, computed_columns=None):\\n # NOTE: metadata does not contain computed_columns yet\\n if metadata is None:\\n conn = get_database_connection(dgid)\\n metadata = get_metadata(conn)\\n\\n # Used to evaluate computed columns\\n unify_computed_columns(computed_columns)\\n columns = list(metadata.keys())\\n select_expr_as = [get_field_name(column, metadata) for column in columns]\\n databases = [\\\"datagrid\\\"]\\n\\n if computed_columns:\\n # Only passed in when calling from endpoint\\n update_state(computed_columns, metadata, databases, columns, select_expr_as)\\n # Now metadata has computed columns\\n\\n fields = {}\\n for column in metadata:\\n datatype = metadata[column][\\\"type\\\"]\\n field_name = get_field_name(column, metadata)\\n qbtype = datatype_to_qbtype(datatype)\\n if qbtype is None:\\n continue\\n\\n if datatype in [\\\"FLOAT\\\", \\\"INTEGER\\\", \\\"ROW_ID\\\"]:\\n fields[field_name] = {\\n \\\"label\\\": column,\\n \\\"field\\\": field_name,\\n \\\"type\\\": qbtype,\\n \\\"tooltip\\\": \\\"The '%s' column (type '%s') from the data grid\\\"\\n % (column, qbtype),\\n }\\n # name, datatype, min, max, avg, variance, total, stddev, other\\n if (metadata[column][\\\"minimum\\\"] is not None) and (\\n metadata[column][\\\"minimum\\\"] is not None\\n ):\\n min_value = metadata[column][\\\"minimum\\\"]\\n max_value = metadata[column][\\\"maximum\\\"]\\n fields[field_name][\\\"fieldSettings\\\"] = {\\n \\\"min\\\": min_value,\\n \\\"max\\\": max_value,\\n }\\n fields[field_name][\\\"valueSources\\\"] = [\\\"value\\\", \\\"field\\\"]\\n\\n elif datatype == \\\"DATETIME\\\":\\n field_exp = \\\"datetime(%s, 'unixepoch')\\\" % field_name\\n fields[field_exp] = {\\n \\\"label\\\": column,\\n \\\"field\\\": field_name,\\n \\\"type\\\": qbtype,\\n \\\"tooltip\\\": \\\"The '%s' column (type '%s') from the data grid\\\"\\n % (column, qbtype),\\n }\\n if (metadata[column][\\\"minimum\\\"] is not None) and (\\n metadata[column][\\\"minimum\\\"] is not None\\n ):\\n min_value = metadata[column][\\\"minimum\\\"]\\n max_value = metadata[column][\\\"maximum\\\"]\\n fields[field_exp][\\\"fieldSettings\\\"] = {\\n \\\"min\\\": min_value,\\n \\\"max\\\": max_value,\\n # \\\"dateFormat\\\": \\\"DD-MM-YYYY\\\",\\n # \\\"timeFormat\\\":\\n # \\\"valueFormat\\\":\\n }\\n fields[field_exp][\\\"valueSources\\\"] = [\\n \\\"value\\\",\\n \\\"field\\\",\\n \\\"func\\\",\\n ] # adds Now, and Relative\\n\\n elif datatype == \\\"BOOLEAN\\\":\\n fields[field_name] = {\\n \\\"label\\\": column,\\n \\\"field\\\": field_name,\\n \\\"type\\\": qbtype,\\n \\\"tooltip\\\": \\\"The '%s' column (type '%s') from the data grid\\\"\\n % (column, qbtype),\\n }\\n fields[field_name][\\\"fieldSettings\\\"] = {\\n \\\"labelYes\\\": \\\"True\\\",\\n \\\"labelNo\\\": \\\"False\\\",\\n }\\n fields[field_name][\\\"valueSources\\\"] = [\\\"value\\\", \\\"field\\\"]\\n\\n elif datatype == \\\"TEXT\\\":\\n fields[field_name] = {\\n \\\"label\\\": column,\\n \\\"field\\\": field_name,\\n \\\"type\\\": qbtype,\\n \\\"tooltip\\\": \\\"The '%s' column (type '%s') from the data grid\\\"\\n % (column, qbtype),\\n }\\n fields[field_name][\\\"valueSources\\\"] = [\\\"value\\\", \\\"field\\\"]\\n\\n elif datatype == \\\"JSON\\\":\\n # Asset metadata columns are named\\n # 'COLUMN_NAME.metadata' or 'COLUMN_NAME--metadata'\\n fields[field_name] = {\\n \\\"label\\\": column.replace(\\\".metadata\\\", \\\"\\\").replace(\\\"--metadata\\\", \\\"\\\"),\\n \\\"field\\\": field_name,\\n \\\"tooltip\\\": \\\"The '%s' column (type 'JSON') from the data grid\\\"\\n % (column,),\\n \\\"type\\\": \\\"!struct\\\",\\n \\\"subfields\\\": {},\\n }\\n subfields = ast.literal_eval(metadata[column][\\\"other\\\"])\\n # Only filterable keys are in subfields\\n for key in subfields:\\n # Query Builder filter types: \\\"text\\\", \\\"number\\\", \\\"boolean\\\", or \\\"list-of-text\\\"\\n qbtype = subfields[key][\\\"type\\\"]\\n if qbtype == \\\"list-of-text\\\":\\n field_exp = \\\"json_extract(%s, '$.%s')\\\" % (field_name, key)\\n fields[field_name][\\\"subfields\\\"][field_exp] = {\\n \\\"type\\\": \\\"text\\\",\\n \\\"label\\\": key,\\n \\\"field\\\": field_name,\\n \\\"tableName\\\": \\\"1\\\", # special signal for JSON queries in our QueryBuilder\\n \\\"operators\\\": [\\\"like\\\"],\\n }\\n else:\\n field_exp = \\\"json_extract(%s, '$.%s')\\\" % (field_name, key)\\n fields[field_name][\\\"subfields\\\"][field_exp] = {\\n \\\"type\\\": qbtype,\\n \\\"label\\\": key,\\n \\\"field\\\": field_name,\\n \\\"tableName\\\": \\\"1\\\", # special signal for JSON queries in our QueryBuilder\\n }\\n if \\\"values\\\" in subfields[key]:\\n fields[field_name][\\\"subfields\\\"][field_exp][\\\"type\\\"] = \\\"select\\\"\\n fields[field_name][\\\"subfields\\\"][field_exp][\\\"fieldSettings\\\"] = {\\n \\\"listValues\\\": sorted(subfields[key][\\\"values\\\"])\\n }\\n\\n return fields\",\n \"def getFieldDescr(fieldName, descr):\\n i = getIter(descr)\\n if not i:\\n return\\n\\n try:\\n sw = ''\\n item = i.next()\\n while item:\\n if fieldName == item[0]:\\n yield item\\n break\\n if isinstance(item[1], list):\\n if fieldName.startswith('%s/' %item[0]):\\n sw = item[0]\\n else:\\n item = i.next()\\n continue\\n [trash, newField] = fieldName.split(sw + '/')\\n for c in getFieldDescr(newField, item[1]):\\n sw = '%s/%s' % (sw, c[0])\\n yield (sw, c[1])\\n item = i.next()\\n except StopIteration:\\n pass\",\n \"def createField(schemaName, field):\\n# print(field.domain)\\n# print(field.name, field.domain if isinstance(field.domain, str) else field.domain.type)\\n# print(field.__dict__)\\n return \\\"\\\\\\\"{name}\\\\\\\" {type_}\\\".format(\\n name = field.name,\\n type_ = '\\\"' + schemaName + '\\\".\\\"' + field.domain + '\\\"' if isinstance(field.domain, str) else getType(field.domain)\\n )\",\n \"def _savebeamparamproptype(self, cursor, bpptname, bpptunit=None, bpptdesc=None):\\n sql = \\\"\\\"\\\"\\n INSERT INTO beam_param_prop_type (\\n beam_param_prop_type_name,\\n beam_param_prop_type_desc,\\n beam_param_prop_type_unit\\n ) VALUES (\\n '%s', %s, %s\\n )\\n \\\"\\\"\\\"\\n if bpptunit is None:\\n bpptunit = \\\"NULL\\\"\\n else:\\n bpptunit = \\\"'%s'\\\" % (bpptunit,)\\n\\n if bpptdesc is None:\\n bpptdesc = \\\"NULL\\\"\\n else:\\n bpptdesc = \\\"'%s'\\\" % (bpptdesc,)\\n\\n cursor.execute(sql % (bpptname, bpptdesc, bpptunit))\\n return cursor.lastrowid\",\n \"def _make_unknown_name(self, cursor, field_name):\\n parent = cursor.lexical_parent\\n pname = self.get_unique_name(parent)\\n log.debug('_make_unknown_name: Got parent get_unique_name %s',pname)\\n # we only look at types declarations\\n _cursor_decl = cursor.type.get_declaration()\\n # we had the field index from the parent record, as to differenciate\\n # between unnamed siblings of a same struct\\n _i = 0\\n found = False\\n # Look at the parent fields to find myself\\n for m in parent.get_children():\\n # FIXME: make the good indices for fields\\n log.debug('_make_unknown_name child %d %s %s %s',_i,m.kind, m.type.kind,m.location)\\n if m.kind not in [CursorKind.STRUCT_DECL,CursorKind.UNION_DECL,\\n CursorKind.CLASS_DECL]:#,\\n #CursorKind.FIELD_DECL]:\\n continue\\n if m == _cursor_decl:\\n found = True\\n break\\n _i+=1\\n if not found:\\n raise NotImplementedError(\\\"_make_unknown_name BUG %s\\\" % cursor.location)\\n # truncate parent name to remove the first part (union or struct)\\n _premainer = '_'.join(pname.split('_')[1:])\\n # name the anonymous record with the field name if it has one\\n if field_name:\\n name = '%s_%s' % (_premainer, field_name)\\n else:\\n name = '%s_%d' % (_premainer, _i)\\n return name\",\n \"def get_field(self, field_name):\\n all_fields = self._fields.items(self._fields.root)\\n print(\\\"all_fields\\\", all_fields)\\n for name, field in all_fields:\\n print(name, field_name)\\n if name == field_name:\\n return field\",\n \"def get_fields(self, table_name):\\n return self.get_table_meta(table_name)['fields']\",\n \"def GetFieldDef(fielddef, fields=\\\"format_, addrdef, baseaddr, bits, bitshift, strindex, datadef, arraydef, validate, cmd, group, tasmotacmnd, converter, readconverter, writeconverter\\\"):\\n format_ = addrdef = baseaddr = datadef = arraydef = validate = cmd = group = tasmotacmnd = converter = readconverter = writeconverter = strindex = None\\n bits = bitshift = 0\\n\\n # calling with nothing is wrong\\n if fielddef is None:\\n print(' is None', file=sys.stderr)\\n raise SyntaxError(' error')\\n\\n # get top level items\\n if len(fielddef) == 3:\\n # converter not present\\n format_, addrdef, datadef = fielddef\\n elif len(fielddef) == 4:\\n # converter present\\n format_, addrdef, datadef, converter = fielddef\\n else:\\n print('wrong {} length ({}) in setting'.format(fielddef, len(fielddef)), file=sys.stderr)\\n raise SyntaxError(' error')\\n\\n # ignore calls with 'root' setting\\n if isinstance(format_, dict) and baseaddr is None and datadef is None:\\n return eval(fields)\\n\\n if not isinstance(format_, (str,dict)):\\n print('wrong {} type {} in {}'.format(format_, type(format_), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n\\n # extract addrdef items\\n baseaddr = addrdef\\n if isinstance(baseaddr, (list,tuple)):\\n if len(baseaddr) == 3:\\n # baseaddr bit definition\\n baseaddr, bits, bitshift = baseaddr\\n if not isinstance(bits, int):\\n print(' must be defined as integer in {}'.format(fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n if not isinstance(bitshift, int):\\n print(' must be defined as integer in {}'.format(fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n elif len(baseaddr) == 2:\\n # baseaddr string definition\\n baseaddr, strindex = baseaddr\\n if not isinstance(strindex, int):\\n print(' must be defined as integer in {}'.format(fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n if strindex >= SettingsTextIndex.index('SET_MAX'):\\n print(' out of range [0,{}] in {}'.format(SettingsTextIndex.index('SET_MAX'), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n else:\\n print('wrong {} length ({}) in {}'.format(addrdef, len(addrdef), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n if not isinstance(baseaddr, int):\\n print(' {} must be defined as integer in {}'.format(baseaddr, fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n\\n # extract datadef items\\n arraydef = datadef\\n if isinstance(datadef, (tuple)):\\n if len(datadef) == 2:\\n # datadef has a validator\\n arraydef, validate = datadef\\n elif len(datadef) == 3:\\n # datadef has a validator and cmd set\\n arraydef, validate, cmd = datadef\\n # cmd must be a tuple with 2 objects\\n if isinstance(cmd, tuple) and len(cmd) == 2:\\n group, tasmotacmnd = cmd\\n if group is not None and not isinstance(group, str):\\n print('wrong {} in {}'.format(group, fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n if isinstance(tasmotacmnd, tuple):\\n for tcmnd in tasmotacmnd:\\n if tcmnd is not None and not callable(tcmnd) and not isinstance(tcmnd, str):\\n print('wrong {} in {}'.format(tcmnd, fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n else:\\n if tasmotacmnd is not None and not callable(tasmotacmnd) and not isinstance(tasmotacmnd, str):\\n print('wrong {} in {}'.format(tasmotacmnd, fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n else:\\n print('wrong {} length ({}) in {}'.format(cmd, len(cmd), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n else:\\n print('wrong {} length ({}) in {}'.format(datadef, len(datadef), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n\\n if validate is not None and (not isinstance(validate, str) and not callable(validate)):\\n print('wrong {} type {} in {}'.format(validate, type(validate), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n\\n # convert single int into one-dimensional list\\n if isinstance(arraydef, int):\\n arraydef = [arraydef]\\n\\n if arraydef is not None and not isinstance(arraydef, (list)):\\n print('wrong {} type {} in {}'.format(arraydef, type(arraydef), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n\\n # get read/write converter items\\n readconverter = converter\\n if isinstance(converter, (tuple)):\\n if len(converter) == 2:\\n # converter has read/write converter\\n readconverter, writeconverter = converter\\n if readconverter is not None and not isinstance(readconverter, str) and not callable(readconverter):\\n print('wrong {} type {} in {}'.format(readconverter, type(readconverter), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n if writeconverter is not None and (not isinstance(writeconverter, (bool,str)) and not callable(writeconverter)):\\n print('wrong {} type {} in {}'.format(writeconverter, type(writeconverter), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n else:\\n print('wrong {} length ({}) in {}'.format(converter, len(converter), fielddef), file=sys.stderr)\\n raise SyntaxError(' error')\\n\\n\\n return eval(fields)\",\n \"def getDocObjects(row, field):\\n\\n doc = nlp_larg(str(row[field]).lower())\\n\\n return doc\",\n \"def typeString(self):\\n return Parameter.string_dict[self._field.type]\",\n \"def test_parse_fields(pawprint_default_tracker_db):\\n\\n tracker = pawprint_default_tracker_db\\n\\n # SELECT * FROM table\\n args = ()\\n assert tracker._parse_fields(*args) == \\\"*\\\"\\n\\n # SELECT event FROM table\\n args = (\\\"event\\\",)\\n assert tracker._parse_fields(*args) == \\\"event\\\"\\n\\n # SELECT user_id, timestamp FROM table\\n args = (\\\"user_id\\\", \\\"timestamp\\\")\\n assert tracker._parse_fields(*args) == \\\"user_id, timestamp\\\"\\n\\n # SELECT metadata #>> '{a, b}' FROM table\\n args = (\\\"metadata__a__b\\\",)\\n assert tracker._parse_fields(*args) == \\\"metadata #> '{a, b}' AS json_field\\\"\",\n \"def get_column_information(self, column_name, table, verbose=True): \\n \\n assert(self.connected)\\n try: \\n assert(self.check_table(table, verbose=False)) \\n except AssertionError: \\n raise TableNotFoundError\\n \\n if (not self.check_column(column_name, table, verbose=False)):\\n return\\n \\n GET_COLUMN_INFO_COMMAND = (\\\"SELECT COLUMN_TYPE, IS_NULLABLE, COLUMN_KEY, EXTRA \\\"\\n \\t\\t\\\"FROM INFORMATION_SCHEMA.COLUMNS \\\"\\n \\t\\t\\\"WHERE TABLE_NAME='{0}' and COLUMN_NAME = '{1}'\\\".format(table,column_name))\\n \\n self.cursor.execute(GET_COLUMN_INFO_COMMAND)\\n \\n for row in self.cursor:\\n break\\n \\n info = {'type' : row[0],\\n 'not_null' : row[1] != 'YES' , \\n 'foreign_key' : row[2] == 'MUL',\\n 'auto_incremenet' : row[3] == 'auto_increment'}\\n \\n if verbose: print(\\\"Column with label '{0}' found in table '{1}'\\\".format(column_name, table))\\n \\n \\n return info\",\n \"def get_field_dtype(self, field=None):\\n\\n if field in self._fields_dtypes:\\n return self._fields_dtypes[field]\\n\\n # initialize dbtypes for all fields\\n field_type = pd.read_sql(\\n 'select distinct column_name, type '\\n 'from fields',\\n self._get_db_engine())\\n\\n for row in field_type.itertuples():\\n self._fields_dtypes[row.column_name] = row.type\\n\\n return self._fields_dtypes[field] if field in self._fields_dtypes else None\",\n \"def complete_info_record_type(self, text, line, begidx, endidx):\\n begidx = begidx\\n endidx = endidx\\n mline = line.partition(' ')[2]\\n offs = len(mline) - len(text)\\n info_record_types = ['description', 'access', 'default', 'bit',\\n 'flag', 'max', 'min']\\n return [s[offs:] for s in info_record_types if s.startswith(mline)]\",\n \"def get_ent_type(self, line):\\n\\n\\t\\treturn str(self.kb_shm.dataType(line))\",\n \"def record_type(values):\\n field = basic.lookup(values, name='Record Type (one of %s)' % values)\\n\\n return field.setResultsName('record_type')\",\n \"def _fieldDefAsString(self, fieldTuple):\\n\\n fname, ftype, flen = fieldTuple\\n if ftype == 'char':\\n # pdb.set_trace()\\n try:\\n slen, flen = flen\\n except TypeError as e:\\n slen = flen\\n flen = 1\\n\\n if slen > 0:\\n fname = '%s[%d]' % (fname, slen)\\n else:\\n fname = '%s[]' % (fname)\\n \\n if flen > 1: \\n return \\\" %s %s[%d];\\\" % (ftype, fname, flen)\\n else:\\n return \\\" %s %s;\\\" % (ftype, fname)\",\n \"def ddl_table(self, tabela):\\r\\n sql = \\\"\\\"\\\"SELECT\\r\\n RF.RDB$FIELD_NAME FIELD_NAME,\\r\\n CASE F.RDB$FIELD_TYPE\\r\\n WHEN 7 THEN\\r\\n CASE F.RDB$FIELD_SUB_TYPE\\r\\n WHEN 0 THEN 'INT'\\r\\n WHEN 1 THEN 'NUMERIC(' || F.RDB$FIELD_PRECISION || ', ' || (-F.RDB$FIELD_SCALE) || ')'\\r\\n WHEN 2 THEN 'DECIMAL'\\r\\n END\\r\\n WHEN 8 THEN\\r\\n CASE F.RDB$FIELD_SUB_TYPE\\r\\n WHEN 0 THEN 'INTEGER'\\r\\n WHEN 1 THEN 'NUMERIC(' || F.RDB$FIELD_PRECISION || ', ' || (-F.RDB$FIELD_SCALE) || ')'\\r\\n WHEN 2 THEN 'DECIMAL'\\r\\n END\\r\\n WHEN 9 THEN 'QUAD'\\r\\n WHEN 10 THEN 'FLOAT'\\r\\n WHEN 12 THEN 'DATE'\\r\\n WHEN 13 THEN 'TIME'\\r\\n WHEN 14 THEN 'CHAR(' || (TRUNC(F.RDB$FIELD_LENGTH / COALESCE(CH.RDB$BYTES_PER_CHARACTER,1))) || ') '\\r\\n WHEN 16 THEN\\r\\n CASE F.RDB$FIELD_SUB_TYPE\\r\\n WHEN 0 THEN 'BIGINT'\\r\\n WHEN 1 THEN 'NUMERIC(' || F.RDB$FIELD_PRECISION || ', ' || (-F.RDB$FIELD_SCALE) || ')'\\r\\n WHEN 2 THEN 'DECIMAL'\\r\\n END\\r\\n WHEN 27 THEN 'NUMERIC'\\r\\n WHEN 35 THEN 'TIMESTAMP'\\r\\n WHEN 37 THEN 'VARCHAR(' || (TRUNC(F.RDB$FIELD_LENGTH / COALESCE(CH.RDB$BYTES_PER_CHARACTER,1))) || ')'\\r\\n WHEN 40 THEN 'CSTRING' || (TRUNC(F.RDB$FIELD_LENGTH / COALESCE(CH.RDB$BYTES_PER_CHARACTER,1))) || ')'\\r\\n WHEN 45 THEN 'BLOB_ID'\\r\\n WHEN 261 THEN 'TEXT'\\r\\n ELSE 'RDB$FIELD_TYPE: ' || F.RDB$FIELD_TYPE || '?'\\r\\n END FIELD_TYPE\\r\\n FROM RDB$RELATION_FIELDS RF\\r\\n JOIN RDB$FIELDS F ON (F.RDB$FIELD_NAME = RF.RDB$FIELD_SOURCE)\\r\\n LEFT OUTER JOIN RDB$CHARACTER_SETS CH ON (CH.RDB$CHARACTER_SET_ID = F.RDB$CHARACTER_SET_ID)\\r\\n LEFT OUTER JOIN RDB$COLLATIONS DCO ON ((DCO.RDB$COLLATION_ID = F.RDB$COLLATION_ID) AND (DCO.RDB$CHARACTER_SET_ID = F.RDB$CHARACTER_SET_ID))\\r\\n WHERE (RF.RDB$RELATION_NAME = '%s') AND (COALESCE(RF.RDB$SYSTEM_FLAG, 0) = 0)\\r\\n ORDER BY RF.RDB$FIELD_POSITION;\\\"\\\"\\\" % (tabela)\\r\\n res = self.cur_origem.execute(sql)\\r\\n table = \\\"CREATE TABLE IF NOT EXISTS %s (\\\" % tabela\\r\\n tipos = {}\\r\\n for coluna, tipo, in res.fetchall():\\r\\n table += \\\"%s %s,\\\" % (coluna.strip(), tipo.strip())\\r\\n tipos[coluna.strip()] = tipo\\r\\n table = table[:-1]+\\\");\\\"\\r\\n return table, tipos\",\n \"def get_sql_fields(self):\\n return self.mapping_db, 'GeneNames', 'EnsembleID', 'symbol', 'name'\",\n \"def field_dim(self, str field_name):\\n cdef std_string fn = field_name.encode('UTF-8')\\n return self.mdb.get().field_dim(fn)\",\n \"def get_column_type(cls, **kwargs: Any) -> Any:\\n return sqlalchemy.Text()\",\n \"def _GetField(bpo_field_id):\\n bpo_field = BPOField.objects.get(id=bpo_field_id)\\n # Get BPO Field based on type.\\n if bpo_field.type == 'auto_sum':\\n return BPOAutoSumField.objects.get(id=bpo_field_id)\\n elif bpo_field.type == 'multiple_choice':\\n return BPOMultipleChoiceField.objects.get(id=bpo_field_id)\\n elif bpo_field.type == 'float_input':\\n return BPOFloatField.objects.get(id=bpo_field_id)\\n elif bpo_field.type == 'integer_input':\\n return BPOIntegerField.objects.get(id=bpo_field_id)\\n elif bpo_field.type == 'date_input':\\n return BPODateField.objects.get(id=bpo_field_id)\\n elif bpo_field.type == 'table':\\n return BPOTable.objects.get(id=bpo_field_id)\\n else:\\n return bpo_field\"\n]"},"negative_scores":{"kind":"list like","value":["0.6303345","0.6107471","0.5995526","0.5872125","0.5803399","0.5616249","0.56076336","0.5588405","0.55621403","0.55433136","0.55343395","0.5498443","0.5464399","0.5463323","0.5434962","0.53413516","0.53411543","0.53399295","0.53027624","0.52892405","0.5286212","0.5240713","0.523672","0.5220382","0.5216029","0.5216029","0.52090305","0.52000684","0.5199184","0.5199134","0.519603","0.51899517","0.51496863","0.5146651","0.51453525","0.5143113","0.51334083","0.5128507","0.51285017","0.5127615","0.51149","0.51133597","0.51084137","0.50817835","0.5057224","0.505523","0.50520307","0.504668","0.50398767","0.5029137","0.5029137","0.5029137","0.50258565","0.5016657","0.501603","0.50076437","0.4995999","0.49955755","0.49953455","0.49943903","0.49698576","0.4953548","0.49489984","0.49464265","0.49460816","0.49460816","0.4924896","0.49233735","0.49183613","0.49176002","0.49173906","0.49144787","0.4910695","0.48880753","0.48866415","0.4882979","0.4880796","0.48789588","0.48685762","0.48630545","0.4862595","0.48611355","0.48406118","0.4839562","0.48392063","0.48389784","0.48346445","0.48292667","0.48288226","0.48260307","0.48251355","0.4819546","0.4812242","0.48003334","0.4784031","0.47821686","0.47812393","0.47755903","0.47580972","0.47566792"],"string":"[\n \"0.6303345\",\n \"0.6107471\",\n \"0.5995526\",\n \"0.5872125\",\n \"0.5803399\",\n \"0.5616249\",\n \"0.56076336\",\n \"0.5588405\",\n \"0.55621403\",\n \"0.55433136\",\n \"0.55343395\",\n \"0.5498443\",\n \"0.5464399\",\n \"0.5463323\",\n \"0.5434962\",\n \"0.53413516\",\n \"0.53411543\",\n \"0.53399295\",\n \"0.53027624\",\n \"0.52892405\",\n \"0.5286212\",\n \"0.5240713\",\n \"0.523672\",\n \"0.5220382\",\n \"0.5216029\",\n \"0.5216029\",\n \"0.52090305\",\n \"0.52000684\",\n \"0.5199184\",\n \"0.5199134\",\n \"0.519603\",\n \"0.51899517\",\n \"0.51496863\",\n \"0.5146651\",\n \"0.51453525\",\n \"0.5143113\",\n \"0.51334083\",\n \"0.5128507\",\n \"0.51285017\",\n \"0.5127615\",\n \"0.51149\",\n \"0.51133597\",\n \"0.51084137\",\n \"0.50817835\",\n \"0.5057224\",\n \"0.505523\",\n \"0.50520307\",\n \"0.504668\",\n \"0.50398767\",\n \"0.5029137\",\n \"0.5029137\",\n \"0.5029137\",\n \"0.50258565\",\n \"0.5016657\",\n \"0.501603\",\n \"0.50076437\",\n \"0.4995999\",\n \"0.49955755\",\n \"0.49953455\",\n \"0.49943903\",\n \"0.49698576\",\n \"0.4953548\",\n \"0.49489984\",\n \"0.49464265\",\n \"0.49460816\",\n \"0.49460816\",\n \"0.4924896\",\n \"0.49233735\",\n \"0.49183613\",\n \"0.49176002\",\n \"0.49173906\",\n \"0.49144787\",\n \"0.4910695\",\n \"0.48880753\",\n \"0.48866415\",\n \"0.4882979\",\n \"0.4880796\",\n \"0.48789588\",\n \"0.48685762\",\n \"0.48630545\",\n \"0.4862595\",\n \"0.48611355\",\n \"0.48406118\",\n \"0.4839562\",\n \"0.48392063\",\n \"0.48389784\",\n \"0.48346445\",\n \"0.48292667\",\n \"0.48288226\",\n \"0.48260307\",\n \"0.48251355\",\n \"0.4819546\",\n \"0.4812242\",\n \"0.48003334\",\n \"0.4784031\",\n \"0.47821686\",\n \"0.47812393\",\n \"0.47755903\",\n \"0.47580972\",\n \"0.47566792\"\n]"},"document_score":{"kind":"string","value":"0.7295043"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8561,"cells":{"query":{"kind":"string","value":"Return a sequence comprising the lines of code necessary to construct the inner Meta class for the model corresponding to the given database table name."},"document":{"kind":"string","value":"def get_meta(table_name, constraints, column_to_field_name):\n # unique_together = []\n # for index, params in constraints.items():\n # if params['unique']:\n # columns = params['columns']\n # if len(columns) > 1:\n # we do not want to include the u\"\" or u'' prefix\n # so we build the string rather than interpolate the tuple\n # tup = '(' + ', '.join(\"'%s'\" % column_to_field_name[c] for c in columns) + ')'\n # unique_together.append(tup)\n\n return type('Meta', (),\n dict(managed=False, db_table=table_name, app_label='layers'))\n # if unique_together:\n # tup = '(' + ', '.join(unique_together) + ',)'\n # meta += [\" unique_together = %s\" % tup]\n # return meta"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def test_meta_table_name(engine):\n class Model(engine.model):\n id = Column(UUID, hash_key=True)\n\n assert Model.Meta.table_name == \"Model\"\n\n class Other(engine.model):\n class Meta:\n table_name = \"table_name\"\n write_units = 3\n id = Column(UUID, hash_key=True)\n\n assert Other.Meta.table_name == \"table_name\"","def model_table():\r\n class OccupationTable(tables.Table):\r\n class Meta:\r\n model = Occupation\r\n assert [\"id\", \"name\", \"region\"] == list(OccupationTable.base_columns.keys())\r\n\r\n class OccupationTable2(tables.Table):\r\n extra = tables.Column()\r\n\r\n class Meta:\r\n model = Occupation\r\n assert [\"id\", \"name\", \"region\", \"extra\"] == list(OccupationTable2.base_columns.keys())\r\n\r\n # be aware here, we already have *models* variable, but we're importing\r\n # over the top\r\n from django.db import models\r\n\r\n class ComplexModel(models.Model):\r\n char = models.CharField(max_length=200)\r\n fk = models.ForeignKey(\"self\")\r\n m2m = models.ManyToManyField(\"self\")\r\n\r\n class ComplexTable(tables.Table):\r\n class Meta:\r\n model = ComplexModel\r\n assert [\"id\", \"char\", \"fk\"] == list(ComplexTable.base_columns.keys())","def sequence():\r\n class TestTable(tables.Table):\r\n a = tables.Column()\r\n b = tables.Column()\r\n c = tables.Column()\r\n assert [\"a\", \"b\", \"c\"] == TestTable([]).columns.names()\r\n assert [\"b\", \"a\", \"c\"] == TestTable([], sequence=(\"b\", \"a\", \"c\")).columns.names()\r\n\r\n class TestTable2(TestTable):\r\n class Meta:\r\n sequence = (\"b\", \"a\", \"c\")\r\n assert [\"b\", \"a\", \"c\"] == TestTable2([]).columns.names()\r\n assert [\"a\", \"b\", \"c\"] == TestTable2([], sequence=(\"a\", \"b\", \"c\")).columns.names()\r\n\r\n class TestTable3(TestTable):\r\n class Meta:\r\n sequence = (\"c\", )\r\n assert [\"c\", \"a\", \"b\"] == TestTable3([]).columns.names()\r\n assert [\"c\", \"a\", \"b\"] == TestTable([], sequence=(\"c\", )).columns.names()\r\n\r\n class TestTable4(TestTable):\r\n class Meta:\r\n sequence = (\"...\", )\r\n assert [\"a\", \"b\", \"c\"] == TestTable4([]).columns.names()\r\n assert [\"a\", \"b\", \"c\"] == TestTable([], sequence=(\"...\", )).columns.names()\r\n\r\n class TestTable5(TestTable):\r\n class Meta:\r\n sequence = (\"b\", \"...\")\r\n assert [\"b\", \"a\", \"c\"] == TestTable5([]).columns.names()\r\n assert [\"b\", \"a\", \"c\"] == TestTable([], sequence=(\"b\", \"...\")).columns.names()\r\n\r\n class TestTable6(TestTable):\r\n class Meta:\r\n sequence = (\"...\", \"b\")\r\n assert [\"a\", \"c\", \"b\"] == TestTable6([]).columns.names()\r\n assert [\"a\", \"c\", \"b\"] == TestTable([], sequence=(\"...\", \"b\")).columns.names()\r\n\r\n class TestTable7(TestTable):\r\n class Meta:\r\n sequence = (\"b\", \"...\", \"a\")\r\n assert [\"b\", \"c\", \"a\"] == TestTable7([]).columns.names()\r\n assert [\"b\", \"c\", \"a\"] == TestTable([], sequence=(\"b\", \"...\", \"a\")).columns.names()\r\n\r\n # Let's test inheritence\r\n class TestTable8(TestTable):\r\n d = tables.Column()\r\n e = tables.Column()\r\n f = tables.Column()\r\n\r\n class Meta:\r\n sequence = (\"d\", \"...\")\r\n\r\n class TestTable9(TestTable):\r\n d = tables.Column()\r\n e = tables.Column()\r\n f = tables.Column()\r\n\r\n assert [\"d\", \"a\", \"b\", \"c\", \"e\", \"f\"] == TestTable8([]).columns.names()\r\n assert [\"d\", \"a\", \"b\", \"c\", \"e\", \"f\"] == TestTable9([], sequence=(\"d\", \"...\")).columns.names()","def _analyze_db_model(cls):\n attributes = dir(cls)\n\n table_attributes = {} # type: Dict[str, Union[ColumnProperty, RelationshipProperty]]\n properties = [] # type: List[str]\n mapper_attrs = inspect(cls).attrs\n\n _get_class_attributes(attributes, cls, properties, mapper_attrs, table_attributes)\n\n model_fields = []\n attributes_containing_lists = []\n normal_attributes = []\n unknown_attributes = []\n for name, attr in table_attributes.items():\n if isinstance(attr, RelationshipProperty):\n mapper = attr.mapper # type: Mapper\n if issubclass(mapper.class_, Taxonomy):\n normal_attributes.append((name, mapper.class_))\n model_fields.append(\"'{}': fields.Nested(taxonomy_item_get, description='{}'),\".format(name, mapper.class_.__name__))\n else:\n if name in properties:\n name = name.lstrip('_')\n attributes_containing_lists.append(name)\n classname = mapper.class_.__name__\n if 'To' in classname:\n classname = classname.split('To')[0]\n model_fields.append(\"'{}': fields.List(fields.Nested(taxonomy_item_get, description='{}'), default=[]),\".format(name, classname))\n else:\n model_fields.append(\"'{}': fields.List(fields.Raw(description='{}'), default=[]),\".format(name, classname))\n else:\n model_fields.append(\"'{}': fields.Raw(description='{}'),\".format(name, mapper.class_.__name__))\n normal_attributes.append((name, mapper.class_))\n if isinstance(attr, ColumnProperty):\n col = attr.columns[0] # type: Column\n zusatz = ''\n if col.default is not None:\n default = col.default.arg\n if isinstance(default, str):\n zusatz = \"default='{}'\".format(default)\n else:\n zusatz = 'default={}'.format(default)\n if isinstance(col.type, Integer):\n model_fields.append(\"'{}': fields.Integer({}),\".format(name, zusatz))\n if name != 'id':\n normal_attributes.append((name, int))\n elif isinstance(col.type, Float):\n model_fields.append(\"'{}': fields.Float({}),\".format(name, zusatz))\n normal_attributes.append((name, float))\n elif isinstance(col.type, String):\n model_fields.append(\"'{}': fields.String({}),\".format(name, zusatz))\n normal_attributes.append((name, str))\n elif isinstance(col.type, Boolean):\n model_fields.append(\"'{}': fields.Boolean({}),\".format(name, zusatz))\n normal_attributes.append((name, bool))\n elif isinstance(col.type, Date):\n model_fields.append(\"'{}': fields.Date({}),\".format(name, zusatz))\n normal_attributes.append((name, date))\n else:\n unknown_attributes.append((name, col.type))\n\n return {\n 'model_fields': model_fields,\n 'normal_attributes': tuple(normal_attributes),\n 'attributes_containing_lists': tuple(attributes_containing_lists),\n 'unknown_attributes': tuple(unknown_attributes),\n }","def construct_base_table(self):\n # Get requested biological entities.\n req_biomodels = [exp.biomodel for exp in self.req_exps]\n # Remove duplicates.\n req_biomodels = list(unique_everseen(req_biomodels))\n # Order according to the linearized models.\n relations = Relations(self.app_label, model_superclass=(BiologicalModel, MetaModel))\n relations.start_join()\n linearized_biomodels = relations.linearized\n req_biomodels = sort_by_other(req_biomodels, \n order=linearized_biomodels)\n # Construct the SQL statement.\n sql = self.construct_result_table(req_biomodels)\n return sql","def should_support_both_meta_sequence_and_constructor_exclude():\r\n class SequencedTable(tables.Table):\r\n a = tables.Column()\r\n b = tables.Column()\r\n c = tables.Column()\r\n\r\n class Meta:\r\n sequence = ('a', '...')\r\n\r\n table = SequencedTable([], exclude=('c', ))\r\n table.as_html()","def generate_model(\n self,\n table: Dict,\n singular: bool = True,\n exceptions: Optional[List] = None,\n schema_global: Optional[bool] = True,\n *args,\n **kwargs,\n ) -> str:\n model = \"\"\n model = gt.model_template.format(\n model_name=create_class_name(table.name, singular, exceptions),\n table_name=table.name,\n )\n for column in table.columns:\n model += logic.generate_column(column, table.primary_key, table, gt, self)\n if table.indexes or table.alter or table.checks or not schema_global:\n model = logic.add_table_args(self, model, table, schema_global)\n # create sequence\n return model","def create_table(self, context, connection, *, engine):\n yield Table(self.table_name, MetaData(), autoload=True, autoload_with=engine)","def model_to_sequencesql(self, m):\n from django.db import connection\n\n # tbl has app_label prefix; e.g., testapp_simple\n tbl = m._meta.db_table\n\n # Get name of sequence for this table. Here's\n # a trace from doing it manually.\n #\n # sql> select \"default\" from sys.columns\n # more> where table_id = 4186 and name = 'id';\n # +-------------------------------------+\n # | default |\n # +=====================================+\n # | next value for \"django1\".\"seq_4176\" |\n # +-------------------------------------+\n # 1 tuple\n # sql>\n #\n\n c = connection.cursor()\n fmt = \"\"\"\nSELECT\n \"default\"\nFROM\n sys.columns\nWHERE\n table_id = (SELECT id FROM sys.tables where name = %s) AND\n name = 'id'\n;\n\"\"\"\n c.execute(fmt, [tbl, ])\n row = c.fetchone()\n # default = 'next value for \"django1\".\"seq_4176\"'\n default = row[0]\n p = default.rfind('\".\"seq_')\n if p == -1:\n return ''\n\n # seq = '\"seq_4176\"'\n seq = default[p + 2:]\n\n fmt = 'ALTER SEQUENCE %s RESTART WITH (SELECT MAX(id) + 1 FROM %s);'\n\n return fmt % (seq, tbl)","def sequence():\n class TestTable(tables.Table):\n a = tables.Column()\n b = tables.Column()\n c = tables.Column()\n Assert([\"a\", \"b\", \"c\"]) == TestTable([]).columns.names()\n Assert([\"b\", \"a\", \"c\"]) == TestTable([], sequence=(\"b\", \"a\", \"c\")).columns.names()\n\n class TestTable2(TestTable):\n class Meta:\n sequence = (\"b\", \"a\", \"c\")\n Assert([\"b\", \"a\", \"c\"]) == TestTable2([]).columns.names()\n Assert([\"a\", \"b\", \"c\"]) == TestTable2([], sequence=(\"a\", \"b\", \"c\")).columns.names()\n\n # BAD, all columns must be specified, or must use \"...\"\n with Assert.raises(ValueError):\n class TestTable3(TestTable):\n class Meta:\n sequence = (\"a\", )\n with Assert.raises(ValueError):\n TestTable([], sequence=(\"a\", ))\n\n # GOOD, using a single \"...\" allows you to only specify some columns. The\n # remaining columns are ordered based on their definition order\n class TestTable4(TestTable):\n class Meta:\n sequence = (\"...\", )\n Assert([\"a\", \"b\", \"c\"]) == TestTable4([]).columns.names()\n Assert([\"a\", \"b\", \"c\"]) == TestTable([], sequence=(\"...\", )).columns.names()\n\n class TestTable5(TestTable):\n class Meta:\n sequence = (\"b\", \"...\")\n Assert([\"b\", \"a\", \"c\"]) == TestTable5([]).columns.names()\n Assert([\"b\", \"a\", \"c\"]) == TestTable([], sequence=(\"b\", \"...\")).columns.names()\n\n class TestTable6(TestTable):\n class Meta:\n sequence = (\"...\", \"b\")\n Assert([\"a\", \"c\", \"b\"]) == TestTable6([]).columns.names()\n Assert([\"a\", \"c\", \"b\"]) == TestTable([], sequence=(\"...\", \"b\")).columns.names()\n\n class TestTable7(TestTable):\n class Meta:\n sequence = (\"b\", \"...\", \"a\")\n Assert([\"b\", \"c\", \"a\"]) == TestTable7([]).columns.names()\n Assert([\"b\", \"c\", \"a\"]) == TestTable([], sequence=(\"b\", \"...\", \"a\")).columns.names()\n\n # Let's test inheritence\n class TestTable8(TestTable):\n d = tables.Column()\n e = tables.Column()\n f = tables.Column()\n\n class Meta:\n sequence = (\"d\", \"...\")\n\n class TestTable9(TestTable):\n d = tables.Column()\n e = tables.Column()\n f = tables.Column()\n\n Assert([\"d\", \"a\", \"b\", \"c\", \"e\", \"f\"]) == TestTable8([]).columns.names()\n Assert([\"d\", \"a\", \"b\", \"c\", \"e\", \"f\"]) == TestTable9([], sequence=(\"d\", \"...\")).columns.names()","def find_sql_models():\n for model in find_subclasses(SQLModel):\n # Get model Meta class\n meta = getattr(model, 'Meta', None)\n if meta:\n # If this is marked as abstract ignore it\n if getattr(meta, 'abstract', False):\n continue\n yield model","def db_table(self):","def create_table(cls):\n\n dbmanager = cls.dbm()\n\n # ask model to define its internal fields\n fields = cls.define_fields(dbmanager)\n cls.extend_fields(fields, True)\n # now hash the fieldlist so we can look up fields by name\n cls.hash_fieldlist()\n\n # get the sqlahelper for this schema (usually default one shared by all models), plus some info\n dbtablename = cls.get_dbtablename()\n dbschemaname = cls.get_dbschemaname()\n sqlahelper = dbmanager.get_sqlahelper(dbschemaname)\n metadata = sqlahelper.getmake_metadata()\n\n # build sqlalchemy columns from fields\n sqlalchemycolumns = cls.create_sqlalchemy_columns_from_dbfields()\n\n # tell sqlalchemy to build table object from columns\n modeltable = sqlalchemy.Table(dbtablename, metadata, *sqlalchemycolumns)\n\n # and store the table and other object references in the model class itself\n cls.setclass_dbinfo(modeltable, sqlahelper)","def next_record(self) -> Iterable[DatabaseMetadata]:\n for key, group in groupby(self._get_raw_extract_iter(), get_table_key):\n columns = []\n for row in group:\n last_row = row\n col_type = ''\n if row['col_type'].upper() == 'CHARACTER VARYING':\n col_type = 'VARCHAR'\n elif row['col_type'].upper() == 'CHARACTER' or row['col_type'].upper() == 'NAME':\n col_type = 'CHAR'\n elif row['col_type'].upper() == 'INTEGER':\n col_type = 'INT'\n elif row['col_type'].upper() == 'TIMESTAMP WITHOUT TIME ZONE':\n col_type = 'TIMESTAMP'\n elif row['col_type'].upper() == 'DOUBLE PRECISION':\n col_type = 'DOUBLE'\n elif row['col_type'].upper() == 'OID':\n col_type = 'NUMBER'\n elif row['col_type'].upper() == 'ARRAY':\n col_type = 'ARRAY'\n elif row['col_type'].upper() == 'BOOLEAN':\n col_type = 'BOOLEAN'\n else:\n col_type = None\n if not self.pattern.filter_pattern.included(f'{last_row[1]}.{last_row[2]}'):\n self.status.filtered(f'{last_row[1]}.{last_row[2]}', \"pattern not allowed\", last_row[2])\n continue\n if col_type is not None:\n columns.append(Column(name=row['col_name'], description=row['col_description'],\n columnDataType=col_type, ordinalPosition=int(row['col_sort_order'])))\n table_metadata = Table(id=uuid.uuid4(), name=last_row['name'],\n description=last_row['description'],\n columns=columns)\n\n self.status.scanned(table_metadata.name.__root__)\n\n dm = Database(id=uuid.uuid4(),\n name=row['schema'],\n description=row['description'] if row['description'] is not None else ' ',\n service=EntityReference(id=self.service.id, type=self.SERVICE_TYPE))\n table_and_db = OMetaDatabaseAndTable(table=table_metadata, database=dm)\n yield table_and_db","def map_database(connection):\n eng = create_engine(connection)\n metadata = MetaData()\n metadata.reflect(eng)\n base = automap_base(metadata=metadata)\n base.prepare()\n return base.classes, eng","def __tablename__(cls):\n return get_table_name(cls.__name__)","def model_table(name, *fields, app_label='internal'):\n model = apps.get_model(app_label, name)\n items = model.objects.all().values_list(*fields)\n field_names = [model._meta.get_field(field).verbose_name\n for field in fields]\n return {'items': items, 'fields': field_names}","def TTableModel(metadata=None):\n\n from sqlalchemy import MetaData\n\n @add_metaclass(ComplexModelMeta)\n class TableModel(TTableModelBase()):\n class Attributes(ComplexModelBase.Attributes):\n sqla_metadata = metadata or MetaData()\n\n return TableModel","def parse(self, lines):\n # Keep count of the current line number.\n i = 0\n # list tables and content\n tables = dict()\n attr_param = list()\n\n skipped_lines = list() # DEBUG\n\n # Loop through all lines.\n for i in range(0, len(lines)):\n line_stripped = lineNormalise(lines[i])\n skip = True\n\n for keyword in self.target_keywords:\n\n # Look for keywords at the beginning of the line.\n if line_stripped.startswith(keyword):\n # print(\"{} : {}\".format(i, line_stripped)) # DEBUG\n skip = False\n\n # Found one, do parse\n expression = re.search(r'(\\w+) (\\w+)', line_stripped)\n if keyword is self.target_keywords[0]: # class/table\n # get table name\n table_name = expression.group(2)\n\n # add it in tables if not already in\n # tables (classes) may be at differant place in a PlantUML file\n if table_name not in tables:\n tables[table_name] = list()\n # print(\"Table : «{}» ajoutee\".format(expression.group(2))) # DEBUG\n print(\"{} : +table «{}»\".format(i, table_name)) # DEBUG\n\n elif keyword is self.target_keywords[1]: # primary key\n # import pdb; pdb.set_trace()\n # get related table\n attr_param = (re.sub(r'(pyk\\()|\\)|,|\\n', r' ', line_stripped).strip().split())\n tables[table_name].extend(attr_param)\n print(\"{} :\\t«{}» +{}\".format(i, table_name, attr_param)) # DEBUG\n\n elif keyword is self.target_keywords[2]: # foreign key\n # get related table\n attr_param = (re.sub(r'(fnk\\()|\\)|,|\\n', r' ', line_stripped).strip().split())\n tables[table_name].extend(attr_param)\n print(\"{} :\\t«{}» +{}\".format(i, table_name, attr_param)) # DEBUG\n\n\n elif keyword is self. target_keywords[3]: # primary foreign key\n # get related table\n attr_param = (re.sub(r'(pfk\\()|\\)|,|\\n', r' ', line_stripped).strip().split())\n tables[table_name].extend(attr_param)\n print(\"{} :\\t«{}» +{}\".format(i, table_name, attr_param)) # DEBUG\n\n else: # attribute\n # print(line_stripped) # DEBUG\n print(\"{} : \\t«{}» Attribute? {}\".format(i, line_stripped)) # DEBUG\n\n if skip:\n skipped_lines.append(i)\n\n print(\"\\nNumbers of tables : {}\\n\".format(len(tables)))\n pp = pprint.PrettyPrinter(indent=4, compact=True)\n print(\"Scraped data:\")\n pp.pprint(tables) # DEBUG\n print(\"\\nSkipped lines: {}\\n\".format(skipped_lines)) # DEBUG","def init_model(engine):\n ## Reflected tables must be defined and mapped here\n #global reflected_table\n #reflected_table = sa.Table(\"Reflected\", meta.metadata, autoload=True,\n # autoload_with=engine)\n #orm.mapper(Reflected, reflected_table)\n #\n meta.Session.configure(bind=engine)\n meta.engine = engine","def create_prerequisites(cls, dbmanager):\n subfields = mdbmixins.dbfmixins_authortracker()\n if (cls.flag_mixin_atroot):\n # prepare extra fields that will be added at root; this doesnt actually create any helper models\n cls.extend_fields(subfields)\n else:\n # add a special sub table that will contain some fields, using a helper class object attached to us\n # create (AND REGISTER) the new helper object\n backrefname = cls.get_dbtablename_pure()\n mdbmodel_fieldset.MewloDbFieldset.make_fieldset_dbobjectclass(cls,'tracking','author tracking object',backrefname,dbmanager,subfields)","def meta(cls):\n if getattr(cls, '__from_class__', None) is not None:\n cls = cls.__from_class__\n attribute_info = {}\n for name, value in cls.__table__.columns.items():\n attribute_info[name] = str(value.type).lower()\n\n return {cls.__name__: attribute_info}","def meta_db_tables(self) -> list:\r\n def _passer(**kwargs):\r\n data = self.engine.execute(\"\"\"\r\n SELECT * FROM sqlite_master WHERE type='table';\r\n \"\"\").fetchall()\r\n table_names = [i[1] for i in data]\r\n return table_names\r\n return self._connectionController(_passer)","def generateModelClass(self):\n\t\tself.printt_cls(\"export class {} {}\".format(self.objName, \"{\"))\n\t\tfor col in self.objSchema[\"fields\"]:\n\t\t\tcolName = col[\"name\"]\n\t\t\tcolType = col[\"type\"]\n\t\t\tself.printt_cls(\"\\t{} : {};\".format(colName, self.JS_DATA_TYPES[colType]))\n\t\tself.printt_cls(\"}\")\n\t\tself.printt_cls(\"\")","def __init__(self, table):\n self.thingy_table = table\n self.thingy_type = table.__name__\n\n # Match [...]{tablename}\n regex = ur'(?x) \\[ ([^]]+) \\] \\s* \\{' + table.__singlename__ + ur'(:[^}]+)?\\}'\n\n # old-style classes augh!\n markdown.inlinepatterns.Pattern.__init__(self, regex)","def create_table(cls, *args, **kwargs):\n init = cls._meta.database.create_table_title(cls._meta.table_name)\n i = 1\n fields = zip(cls._meta.sorted_fields_names, cls._meta.sorted_fields)\n for field in fields:\n field_string = field[1].create_field(field[0])\n if i == len(fields):\n if cls._meta.unique:\n init = cls._meta.database.create_unique(init, cls._meta.unique)\n\n init = cls._meta.database.create_table_field_end(init, field_string)\n\n if cls._meta.hypertable:\n init = cls._meta.database.create_hypertable(init,\n cls._meta)\n else:\n init = cls._meta.database.create_table_field(init, field_string)\n i+=1\n\n yield cls._meta.database.runOperation(init)","def create_tables(self):\n for name, attribute in self.__dict__.items():\n if hasattr(attribute, 'create_table_in_sqlite_db'):\n attribute.create_table_in_sqlite_db()","def __init__(self, *args):\n self.engine = db.create_engine('mysql+pymysql://root:''@127.0.0.1:3306/northwind', echo=True)\n self.connection = self.engine.connect()\n self.metadata = db.MetaData()\n self.tables = db.Table(*args, self.metadata, autoload=True, autoload_with=self.engine)","def setup_schema(BaseDao, session):\n def setup_schema_fn():\n for class_ in BaseDao._decl_class_registry.values():\n if hasattr(class_, '__tablename__'):\n if class_.__name__.endswith('Schema'):\n raise ModelConversionError(\n \"For safety, setup_schema can not be used when a\"\n \"Model class ends with 'Schema'\"\n )\n\n class Meta(object):\n model = class_\n sqla_session = session\n dump_only = ('pkId', 'created', 'modified')\n\n schema_class_name = '%sSchema' % class_.__name__\n\n schema_class = type(\n schema_class_name,\n (ModelSchema,),\n {'Meta': Meta}\n )\n\n setattr(class_, '__marshmallow__', schema_class)\n\n return setup_schema_fn","def create_models( self ):","def construct_result_table(self, biomodels):\n select = 'SELECT DISTINCT '\n cached_alias = 'c'\n join_exps = 'FROM %s_%s AS %s' % (self.app_label, \n settings.DISBI['JOINED_TABLENAME'], \n cached_alias)\n left_join_template = '''\n LEFT JOIN (\n %s\n ) AS %s\n ON (%s = %s)\n '''\n subtables_not_null_column = []\n select_bios = []\n relations = Relations(self.app_label, model_superclass=(BiologicalModel, MetaModel))\n for biomodel in biomodels:\n # Requested experiments related to biomodel.\n req_exps_for_bio = [] \n for exp in self.req_exps:\n if exp.biomodel == biomodel:\n req_exps_for_bio.append(exp)\n \n select_bios.extend(self.get_show_columns(biomodel))\n \n\n # Get Meta models for Bio model and the show columns to the \n # SELECT clause.\n metamodels_of_biomodel = relations.get_related_metamodels(biomodel)\n #print(metamodels_of_biomodel)\n for metamodel in metamodels_of_biomodel:\n select_bios.extend(self.get_show_columns(metamodel))\n\n \n for exp in req_exps_for_bio:\n select_bios.extend(self.get_display_names(exp))\n exp_alias = 'exp%s' % exp.pk\n join_exps += left_join_template % (\n self.construct_exptable(exp),\n exp_alias,\n '%s.%s_id' % (cached_alias, biomodel.__name__.lower()),\n '%s.%s' % (exp_alias, exp.biofield.column)\n )\n subtables_not_null_column.append((self.get_notnull_column(exp), \n str(exp.id)))\n exclude_empty = 'WHERE ' + ' OR '.join(['%s_%s IS NOT NULL' % col \n for col in subtables_not_null_column])\n \n sql = '\\n'.join((select + ', '.join(select_bios), join_exps, exclude_empty))\n return re.sub(r'^\\s+', '', sql, flags=re.MULTILINE)","def get_data_models(models_file):\n list_models = []\n model = []\n pos_numeric = [] # Position of numeric fields\n info_keys = [] # Info. about keys\n re_field = re.compile('\\s+\\w+\\s*=\\s*models\\.') # Line with field name\n re_class = re.compile('\\s+class ') # For Admin and Meta\n re_def = re.compile('\\s+def ')\n is_new_model = False\n\n for line in open(models_file):\n # The models start with 'class'\n if not is_new_model and line.startswith('class'):\n model_name = line.replace('class','').split('(')[0].strip()\n model.append(model_name)\n is_new_model = True\n elif is_new_model:\n if re_field.match(line):\n field_name = line.split('=')[0].strip()\n model.append(field_name)\n\n if 'models.DecimalField' in line or 'models.IntegerField' in line:\n pos_numeric.append(len(model)-2) # Discard model name.\n elif 'models.ForeignKey' in line:\n key_name = line.split('(')[-1].strip().strip(')')\n position = len(model)-2 # Discard model name.\n info_keys.append(':')\n info_keys.append(str(position) + ',')\n info_keys.append(key_name)\n # It is supposed that models in localization has at the end:\n # ('class Meta', 'class Admin', or some 'def')\n elif re_class.match(line) or re_def.match(line):\n if pos_numeric:\n pos_num2str = '#'\n for num in pos_numeric:\n pos_num2str += str(num)\n model.append(pos_num2str)\n model.append(':N') # To detect the numeric field.\n pos_numeric = []\n if info_keys:\n all_keys = \"\"\n for key in info_keys:\n all_keys += key\n model.append(all_keys)\n model.append(':K') # To detect fastly some key.\n info_keys = []\n list_models.append(model)\n model = []\n is_new_model = False\n\n return list_models","async def _create_tables_declarative(self, base, engine):\n if hasattr(base, 'metadata'):\n base.metadata.create_all(bind=engine, checkfirst=True)\n return","def __tablename__(self):\n return sub(r\"(? list:\r\n def _passer(**kwargs):\r\n return self.engine.execute(\r\n f\"PRAGMA table_info({kwargs['table_name']});\").fetchall()\r\n return self._connectionController(_passer, table_name=table_name)","def _get_model_from_table_name(table_name: str) -> Optional[Type[RDSModel]]:\n table_model = None\n try:\n if hasattr(Base, '_decl_class_registry'):\n models = Base._decl_class_registry.values() # sqlalchemy < 1.4\n else:\n models = Base.registry._class_registry.values()\n\n for model in models:\n if hasattr(model, '__tablename__') and model.__tablename__ == table_name:\n table_model = model\n except Exception as e:\n LOGGER.exception(f'Failed to get model for the table: {table_name} from rds model base')\n raise e\n\n return table_model","def db_for_read(self, model, **hints):\n model_name = model._meta.label_lower\n pos = model_name.find('.')\n table_name = model_name[pos+1:]\n if table_name in self.route_encuestas:\n return 'encuestas'\n elif table_name in self.route_uxxienc_resul:\n return 'uxxienc_resul'\n return None","def __tablename__(cls) -> str:\n return inflection.underscore(cls.__name__)","def model_definition(self):\n pass","def show_database_structure(self):\n self.analyze()\n items = []\n for model in get_models():\n names = []\n # for f, m in model._meta.get_fields_with_model():\n for f in model._meta.concrete_fields:\n names.append(f.name)\n items.append(\n \"{0} : {1}\".format(fmn(model), ', '.join(names)))\n\n items = sorted(items)\n return rstgen.ul(items)","def create_intermediary_table_model(model):\n name = model.__name__ + 'Relation'\n \n class Meta:\n db_table = '%s_relation' % model._meta.db_table\n unique_together = (('tag', 'content_type', 'object_id'),)\n\n def obj_unicode(self):\n return u'%s [%s]' % (self.content_type.get_object_for_this_type(pk=self.object_id), self.tag)\n \n # Set up a dictionary to simulate declarations within a class \n attrs = {\n '__module__': model.__module__,\n 'Meta': Meta,\n 'tag': models.ForeignKey(model, verbose_name=_('tag'), related_name='items'),\n 'content_type': models.ForeignKey(ContentType, verbose_name=_('content type')),\n 'object_id': models.PositiveIntegerField(_('object id'), db_index=True),\n 'content_object': generic.GenericForeignKey('content_type', 'object_id'),\n '__unicode__': obj_unicode,\n }\n\n return type(name, (models.Model,), attrs)","def map_def_classes(self, table):\n definition = MapperDefinition()\n for rc in self.get_table_classes(table):\n splitted = rc.split()\n abbreviation = \" \".join(splitted[:-1])\n course_number = splitted[-1]\n definition.add(abbreviation, allowed=[course_number])\n return definition","def test_custom_metadata_schema(self):\n # The use-case for this functionality is to allow using\n # Foreign Data Wrappers, each with a full set of Django\n # tables, to copy between databases using SQLAlchemy\n # and the automatically generation of aldjemy.\n metadata = MetaData(schema=\"arbitrary\")\n sa_models = construct_models(metadata)\n self.assertEqual(sa_models[Log].__table__.schema, \"arbitrary\")","def fetchall(self):\n rows = self.cursor.fetchall()\n\n if self.model.single:\n for row in rows:\n yield self.__instance_from_db(self.model, row)\n else:\n for row in rows:\n yield tuple(self.__instance_from_db(m, row) for m in self.model.models)","def __new__(cls, name, bases, ns):\n newbases = []\n table = None\n namer = None\n\n for base in bases:\n if isinstance(base, fromTable):\n if table is not None:\n raise RuntimeError(\n \"Can't define a class from two or more tables at once.\"\n )\n table = base.table\n elif getattr(base, \"table\", None) is not None:\n raise RuntimeError(\n \"Can't define a record class by inheriting one already \"\n \"mapped to a table.\"\n # TODO: more info\n )\n else:\n if namer is None:\n if isinstance(base, _RecordMeta):\n namer = base\n newbases.append(base)\n\n if table is not None:\n attrmap = {}\n colmap = {}\n allColumns = list(table)\n for column in allColumns:\n attrname = namer.namingConvention(column.model.name)\n attrmap[attrname] = column\n colmap[column] = attrname\n ns.update(table=table, __attrmap__=attrmap, __colmap__=colmap)\n ns.update(attrmap)\n\n return super(_RecordMeta, cls).__new__(cls, name, tuple(newbases), ns)","def __init__(self, name, sequence_number):\n super(SQLTableIdentifier, self).__init__()\n self.name = name\n self.sequence_number = sequence_number","def create_tables(self):\n tables = {}\n for cls in find_sql_models():\n table = cls.__table__\n if table is None:\n table = cls.__table__ = create_table(cls, self.metadata)\n if not table.metadata.bind:\n table.metadata.bind = SQLBinding(manager=self, table=table)\n tables[cls] = table\n return tables","def init_models(self):\n from ron import Application\n from ron.models.basemodel import BaseModel\n if self.models == None or not Application().db:\n return\n models_namespace = self.__namespace + \".models\" # TODO: allow customize this\n try:\n models_package = import_module(models_namespace)\n except:\n models_package = None\n if models_package:\n models_modules = self._get_package_modules(models_package)\n for model_name in models_modules:\n imported_model = import_module('.' + model_name, package=models_namespace)\n for i in dir(imported_model):\n attribute = getattr(imported_model, i)\n if inspect.isclass(attribute) and issubclass(attribute, BaseModel):\n self.models.append(attribute)\n Application().db().database.create_tables(self.models)","def _create_tables_classic(self, engine, metadata):\n if engine and metadata:\n with (yield from engine) as conn:\n for x in self._models.values():\n try:\n yield from conn.execute(CreateTable(x))\n except ProgrammingError as error:\n if hasattr(self.app, 'log') and self.app.log:\n if self.app.debug:\n self.app.log.info(\"[PostgressPlugin] [ `{}` already exists]\".format(x))\n else:\n if self.app.debug:\n print(\"[PostgressPlugin] [ `{}` already exists]\".format(x))\n return","def GenMetaTableParam(a_name):\n table_param = Table_Param()\n if a_name == \"meta\":\n table_param.NAME = meta_table_name\n table_param.COLS = \\\n (Column(\"version\", String(50), primary_key=True, index=False),\n Column('site', String),\n Column('pairDbFile', String),\n Column('dumpType', String),\n Column('lock', Integer),\n Column('prNumber', String),\n Column('kbUrl', String),\n Column('desc', String))\n if a_name == \"fixby\":\n table_param.NAME = fixby_table_name\n table_param.COLS = \\\n (Column(\"id\", Integer, primary_key=True), # will auto increase\n Column('module', String),\n Column('desc', String))\n\n return table_param","def build_metadata():\n metadata = sa.MetaData()\n\n sa.Table(\n 'hive_blocks', metadata,\n sa.Column('num', sa.Integer, primary_key=True, autoincrement=False),\n sa.Column('hash', CHAR(40), nullable=False),\n sa.Column('prev', CHAR(40)),\n sa.Column('txs', SMALLINT, server_default='0', nullable=False),\n sa.Column('ops', SMALLINT, server_default='0', nullable=False),\n sa.Column('created_at', sa.DateTime, nullable=False),\n\n sa.UniqueConstraint('hash', name='hive_blocks_ux1'),\n sa.ForeignKeyConstraint(['prev'], ['hive_blocks.hash'], name='hive_blocks_fk1'),\n )\n\n sa.Table(\n 'hive_accounts', metadata,\n sa.Column('id', sa.Integer, primary_key=True),\n sa.Column('name', VARCHAR(16), nullable=False),\n sa.Column('created_at', sa.DateTime, nullable=False),\n #sa.Column('block_num', sa.Integer, nullable=False),\n sa.Column('reputation', sa.Float(precision=6), nullable=False, server_default='25'),\n\n sa.Column('display_name', sa.String(20)),\n sa.Column('about', sa.String(160)),\n sa.Column('location', sa.String(30)),\n sa.Column('website', sa.String(100)),\n sa.Column('profile_image', sa.String(1024), nullable=False, server_default=''),\n sa.Column('cover_image', sa.String(1024), nullable=False, server_default=''),\n\n sa.Column('followers', sa.Integer, nullable=False, server_default='0'),\n sa.Column('following', sa.Integer, nullable=False, server_default='0'),\n\n sa.Column('proxy', VARCHAR(16), nullable=False, server_default=''),\n sa.Column('post_count', sa.Integer, nullable=False, server_default='0'),\n sa.Column('proxy_weight', sa.Float(precision=6), nullable=False, server_default='0'),\n sa.Column('vote_weight', sa.Float(precision=6), nullable=False, server_default='0'),\n sa.Column('kb_used', sa.Integer, nullable=False, server_default='0'), # deprecated\n sa.Column('rank', sa.Integer, nullable=False, server_default='0'),\n\n sa.Column('lastread_at', sa.DateTime, nullable=False, server_default='1970-01-01 00:00:00'),\n sa.Column('active_at', sa.DateTime, nullable=False, server_default='1970-01-01 00:00:00'),\n sa.Column('cached_at', sa.DateTime, nullable=False, server_default='1970-01-01 00:00:00'),\n sa.Column('raw_json', sa.Text),\n\n\n sa.UniqueConstraint('name', name='hive_accounts_ux1'),\n sa.Index('hive_accounts_ix1', 'vote_weight', 'id'), # core: quick ranks\n sa.Index('hive_accounts_ix2', 'name', 'id'), # core: quick id map\n sa.Index('hive_accounts_ix3', 'vote_weight', 'name', postgresql_ops=dict(name='varchar_pattern_ops')), # API: lookup\n sa.Index('hive_accounts_ix4', 'id', 'name'), # API: quick filter/sort\n sa.Index('hive_accounts_ix5', 'cached_at', 'name'), # core/listen sweep\n )\n\n sa.Table(\n 'hive_posts', metadata,\n sa.Column('id', sa.Integer, primary_key=True),\n sa.Column('parent_id', sa.Integer),\n sa.Column('author', VARCHAR(16), nullable=False),\n sa.Column('permlink', VARCHAR(255), nullable=False),\n sa.Column('category', VARCHAR(255), nullable=False, server_default=''),\n sa.Column('community_id', sa.Integer, nullable=True),\n sa.Column('created_at', sa.DateTime, nullable=False),\n sa.Column('depth', SMALLINT, nullable=False),\n sa.Column('is_deleted', BOOLEAN, nullable=False, server_default='0'),\n sa.Column('is_pinned', BOOLEAN, nullable=False, server_default='0'),\n sa.Column('is_muted', BOOLEAN, nullable=False, server_default='0'),\n sa.Column('is_valid', BOOLEAN, nullable=False, server_default='1'),\n sa.Column('promoted', sa.types.DECIMAL(10, 3), nullable=False, server_default='0'),\n\n sa.ForeignKeyConstraint(['author'], ['hive_accounts.name'], name='hive_posts_fk1'),\n sa.ForeignKeyConstraint(['parent_id'], ['hive_posts.id'], name='hive_posts_fk3'),\n sa.UniqueConstraint('author', 'permlink', name='hive_posts_ux1'),\n sa.Index('hive_posts_ix3', 'author', 'depth', 'id', postgresql_where=sql_text(\"is_deleted = '0'\")), # API: author blog/comments\n sa.Index('hive_posts_ix4', 'parent_id', 'id', postgresql_where=sql_text(\"is_deleted = '0'\")), # API: fetching children\n sa.Index('hive_posts_ix5', 'id', postgresql_where=sql_text(\"is_pinned = '1' AND is_deleted = '0'\")), # API: pinned post status\n sa.Index('hive_posts_ix6', 'community_id', 'id', postgresql_where=sql_text(\"community_id IS NOT NULL AND is_pinned = '1' AND is_deleted = '0'\")), # API: community pinned\n )\n\n sa.Table(\n 'hive_post_tags', metadata,\n sa.Column('post_id', sa.Integer, nullable=False),\n sa.Column('tag', sa.String(32), nullable=False),\n sa.UniqueConstraint('tag', 'post_id', name='hive_post_tags_ux1'), # core\n sa.Index('hive_post_tags_ix1', 'post_id'), # core\n )\n\n sa.Table(\n 'hive_follows', metadata,\n sa.Column('follower', sa.Integer, nullable=False),\n sa.Column('following', sa.Integer, nullable=False),\n sa.Column('state', SMALLINT, nullable=False, server_default='1'),\n sa.Column('created_at', sa.DateTime, nullable=False),\n\n sa.UniqueConstraint('following', 'follower', name='hive_follows_ux3'), # core\n sa.Index('hive_follows_ix5a', 'following', 'state', 'created_at', 'follower'),\n sa.Index('hive_follows_ix5b', 'follower', 'state', 'created_at', 'following'),\n )\n\n sa.Table(\n 'hive_reblogs', metadata,\n sa.Column('account', VARCHAR(16), nullable=False),\n sa.Column('post_id', sa.Integer, nullable=False),\n sa.Column('created_at', sa.DateTime, nullable=False),\n\n sa.ForeignKeyConstraint(['account'], ['hive_accounts.name'], name='hive_reblogs_fk1'),\n sa.ForeignKeyConstraint(['post_id'], ['hive_posts.id'], name='hive_reblogs_fk2'),\n sa.UniqueConstraint('account', 'post_id', name='hive_reblogs_ux1'), # core\n sa.Index('hive_reblogs_ix1', 'post_id', 'account', 'created_at'), # API -- not yet used\n )\n\n sa.Table(\n 'hive_payments', metadata,\n sa.Column('id', sa.Integer, primary_key=True),\n sa.Column('block_num', sa.Integer, nullable=False),\n sa.Column('tx_idx', SMALLINT, nullable=False),\n sa.Column('post_id', sa.Integer, nullable=False),\n sa.Column('from_account', sa.Integer, nullable=False),\n sa.Column('to_account', sa.Integer, nullable=False),\n sa.Column('amount', sa.types.DECIMAL(10, 3), nullable=False),\n sa.Column('token', VARCHAR(5), nullable=False),\n\n sa.ForeignKeyConstraint(['from_account'], ['hive_accounts.id'], name='hive_payments_fk1'),\n sa.ForeignKeyConstraint(['to_account'], ['hive_accounts.id'], name='hive_payments_fk2'),\n sa.ForeignKeyConstraint(['post_id'], ['hive_posts.id'], name='hive_payments_fk3'),\n )\n\n sa.Table(\n 'hive_feed_cache', metadata,\n sa.Column('post_id', sa.Integer, nullable=False),\n sa.Column('account_id', sa.Integer, nullable=False),\n sa.Column('created_at', sa.DateTime, nullable=False),\n sa.UniqueConstraint('post_id', 'account_id', name='hive_feed_cache_ux1'), # core\n sa.Index('hive_feed_cache_ix1', 'account_id', 'post_id', 'created_at'), # API (and rebuild?)\n )\n\n sa.Table(\n 'hive_posts_cache', metadata,\n sa.Column('post_id', sa.Integer, primary_key=True, autoincrement=False),\n sa.Column('author', VARCHAR(16), nullable=False),\n sa.Column('permlink', VARCHAR(255), nullable=False),\n sa.Column('category', VARCHAR(255), nullable=False, server_default=''),\n\n # important/index\n sa.Column('community_id', sa.Integer, nullable=True),\n sa.Column('depth', SMALLINT, nullable=False, server_default='0'),\n sa.Column('children', SMALLINT, nullable=False, server_default='0'),\n\n # basic/extended-stats\n sa.Column('author_rep', sa.Float(precision=6), nullable=False, server_default='0'),\n sa.Column('flag_weight', sa.Float(precision=6), nullable=False, server_default='0'),\n sa.Column('total_votes', sa.Integer, nullable=False, server_default='0'),\n sa.Column('up_votes', sa.Integer, nullable=False, server_default='0'),\n\n # basic ui fields\n sa.Column('title', sa.String(255), nullable=False, server_default=''),\n sa.Column('preview', sa.String(1024), nullable=False, server_default=''),\n sa.Column('img_url', sa.String(1024), nullable=False, server_default=''),\n\n # core stats/indexes\n sa.Column('payout', sa.types.DECIMAL(10, 3), nullable=False, server_default='0'),\n sa.Column('promoted', sa.types.DECIMAL(10, 3), nullable=False, server_default='0'),\n sa.Column('created_at', sa.DateTime, nullable=False, server_default='1990-01-01'),\n sa.Column('payout_at', sa.DateTime, nullable=False, server_default='1990-01-01'),\n sa.Column('updated_at', sa.DateTime, nullable=False, server_default='1990-01-01'),\n sa.Column('is_paidout', BOOLEAN, nullable=False, server_default='0'),\n\n # ui flags/filters\n sa.Column('is_nsfw', BOOLEAN, nullable=False, server_default='0'),\n sa.Column('is_declined', BOOLEAN, nullable=False, server_default='0'),\n sa.Column('is_full_power', BOOLEAN, nullable=False, server_default='0'),\n sa.Column('is_hidden', BOOLEAN, nullable=False, server_default='0'),\n sa.Column('is_grayed', BOOLEAN, nullable=False, server_default='0'),\n\n # important indexes\n sa.Column('rshares', sa.BigInteger, nullable=False, server_default='0'),\n sa.Column('sc_trend', sa.Float(precision=6), nullable=False, server_default='0'),\n sa.Column('sc_hot', sa.Float(precision=6), nullable=False, server_default='0'),\n\n # bulk data\n sa.Column('body', TEXT),\n sa.Column('votes', TEXT),\n sa.Column('json', sa.Text),\n sa.Column('raw_json', sa.Text),\n\n # index: misc\n sa.Index('hive_posts_cache_ix3', 'payout_at', 'post_id', postgresql_where=sql_text(\"is_paidout = '0'\")), # core: payout sweep\n sa.Index('hive_posts_cache_ix8', 'category', 'payout', 'depth', postgresql_where=sql_text(\"is_paidout = '0'\")), # API: tag stats\n\n # index: ranked posts\n sa.Index('hive_posts_cache_ix2', 'promoted', postgresql_where=sql_text(\"is_paidout = '0' AND promoted > 0\")), # API: promoted\n\n sa.Index('hive_posts_cache_ix6a', 'sc_trend', 'post_id', postgresql_where=sql_text(\"is_paidout = '0'\")), # API: trending todo: depth=0\n sa.Index('hive_posts_cache_ix7a', 'sc_hot', 'post_id', postgresql_where=sql_text(\"is_paidout = '0'\")), # API: hot todo: depth=0\n sa.Index('hive_posts_cache_ix6b', 'post_id', 'sc_trend', postgresql_where=sql_text(\"is_paidout = '0'\")), # API: trending, filtered todo: depth=0\n sa.Index('hive_posts_cache_ix7b', 'post_id', 'sc_hot', postgresql_where=sql_text(\"is_paidout = '0'\")), # API: hot, filtered todo: depth=0\n\n sa.Index('hive_posts_cache_ix9a', 'depth', 'payout', 'post_id', postgresql_where=sql_text(\"is_paidout = '0'\")), # API: payout todo: rem depth\n sa.Index('hive_posts_cache_ix9b', 'category', 'depth', 'payout', 'post_id', postgresql_where=sql_text(\"is_paidout = '0'\")), # API: payout, filtered todo: rem depth\n\n sa.Index('hive_posts_cache_ix10', 'post_id', 'payout', postgresql_where=sql_text(\"is_grayed = '1' AND payout > 0\")), # API: muted, by filter/date/payout\n\n # index: stats\n sa.Index('hive_posts_cache_ix20', 'community_id', 'author', 'payout', 'post_id', postgresql_where=sql_text(\"is_paidout = '0'\")), # API: pending distribution; author payout\n\n # index: community ranked posts\n sa.Index('hive_posts_cache_ix30', 'community_id', 'sc_trend', 'post_id', postgresql_where=sql_text(\"community_id IS NOT NULL AND is_grayed = '0' AND depth = 0\")), # API: community trend\n sa.Index('hive_posts_cache_ix31', 'community_id', 'sc_hot', 'post_id', postgresql_where=sql_text(\"community_id IS NOT NULL AND is_grayed = '0' AND depth = 0\")), # API: community hot\n sa.Index('hive_posts_cache_ix32', 'community_id', 'created_at', 'post_id', postgresql_where=sql_text(\"community_id IS NOT NULL AND is_grayed = '0' AND depth = 0\")), # API: community created\n sa.Index('hive_posts_cache_ix33', 'community_id', 'payout', 'post_id', postgresql_where=sql_text(\"community_id IS NOT NULL AND is_grayed = '0' AND is_paidout = '0'\")), # API: community payout\n sa.Index('hive_posts_cache_ix34', 'community_id', 'payout', 'post_id', postgresql_where=sql_text(\"community_id IS NOT NULL AND is_grayed = '1' AND is_paidout = '0'\")), # API: community muted\n )\n\n sa.Table(\n 'hive_state', metadata,\n sa.Column('block_num', sa.Integer, primary_key=True, autoincrement=False),\n sa.Column('db_version', sa.Integer, nullable=False),\n sa.Column('steem_per_mvest', sa.types.DECIMAL(8, 3), nullable=False),\n sa.Column('usd_per_steem', sa.types.DECIMAL(8, 3), nullable=False),\n sa.Column('sbd_per_steem', sa.types.DECIMAL(8, 3), nullable=False),\n sa.Column('dgpo', sa.Text, nullable=False),\n )\n\n metadata = build_metadata_community(metadata)\n\n metadata = build_metadata_blacklist(metadata)\n\n metadata = build_trxid_block_num(metadata)\n\n return metadata","def meta(self) -> api.Meta:\n return self._get_model(model=api.Meta)","def test_extraction_with_model_class(self: Any, mock_method: Any) -> None:\n config_dict = {\n 'extractor.sqlalchemy.conn_string': 'TEST_CONNECTION',\n 'extractor.sqlalchemy.extract_sql': 'SELECT 1 FROM TEST_TABLE;',\n 'extractor.sqlalchemy.model_class':\n 'tests.unit.extractor.test_sql_alchemy_extractor.TableMetadataResult'\n }\n self.conf = ConfigFactory.from_dict(config_dict)\n\n extractor = SQLAlchemyExtractor()\n extractor.results = [dict(database='test_database',\n schema='test_schema',\n name='test_table',\n description='test_description',\n column_name='test_column_name',\n column_type='test_column_type',\n column_comment='test_column_comment',\n owner='test_owner')]\n\n extractor.init(Scoped.get_scoped_conf(conf=self.conf,\n scope=extractor.get_scope()))\n\n result = extractor.extract()\n\n self.assertIsInstance(result, TableMetadataResult)\n self.assertEqual(result.name, 'test_table')","def __sanitizeMetaModelName( self, name ):\r\n if( name[-5:] == '_META' ): \r\n return name[:-5]\r\n else: return name","def base_fields(self):\n if not self.model:\n raise NameError('database model has not been set.')\n\n with self.session() as session:\n query = self.get_query(session, [self.model.pkId, self.model.created, self.model.modified])\n data = query.order_by(self.model.pkId).all()\n return data","def declarative_base(model):\n for parent in model.__bases__:\n try:\n parent.metadata\n return declarative_base(parent)\n except AttributeError:\n pass\n return model","def _load_db(self):\n for type_ in self._types:\n try:\n type_.table(self._metadata)\n except InvalidRequestError:\n pass\n # Reflect metadata so auto-mapping works\n self._metadata.reflect(self._engine)\n # Make sure the tables exist\n self._metadata.create_all()","def __table_cls__(cls, *args, **kwargs):\n # check if a table with this name already exists\n # allows reflected tables to be applied to model by name\n key = _get_table_key(args[0], kwargs.get('schema'))\n\n if key in cls.metadata.tables:\n return sa.Table(*args, **kwargs)\n\n # if a primary key or constraint is found, create a table for\n # joined-table inheritance\n for arg in args:\n is_pk_column = isinstance(arg, sa.Column) and arg.primary_key\n is_pk_constraint = isinstance(arg, sa.PrimaryKeyConstraint)\n if is_pk_column or is_pk_constraint:\n return sa.Table(*args, **kwargs)\n\n # if no base classes define a table, return one\n # ensures the correct error shows up when missing a primary key\n for base in cls.__mro__[1:-1]:\n if '__table__' in base.__dict__:\n break\n else:\n return sa.Table(*args, **kwargs)\n\n # single-table inheritance, use the parent tablename\n if '__tablename__' in cls.__dict__:\n del cls.__tablename__","def __init__(self):\n engine = connect_to_db()\n create_lyrics_table(engine) #declarative base stuff\n self.Session = sessionmaker(bind=engine)\n\n # self.create_connection()\n # self.create_table()","def test_field_names(self):\n\n for mb_model in self.mb_model_list:\n mb_fields = mb_model._meta.fields\n db_cols = connection.introspection.get_table_description(\n self.cursor, mb_model._meta.db_table)\n\n for i in range(0, len(mb_model._meta.fields)):\n self.assertEqual(\n mb_fields[i].column,\n db_cols[i].name\n )","def __init__(self,):\n self.logger = conf._init_logger(logger=conf.LOGGER_ORM)\n self.logger = logging.getLogger(conf.LOGGER_ORM)\n\n self.logger.info(\"[+] Initilizing Orm [+]\")\n\n\n self.engine = sqlalchemy.create_engine(\n f\"mysql+mysqldb://{conf.DB_USER}:{conf.DB_PASSWORD}@{conf.DB_ADRESS}/{conf.DB_NAME}\")\n self.metadata = sqlalchemy.MetaData(bind=self.engine)\n self.metadata.reflect(only=[\"examens\", \"sections\", \"patients\", \"medecins\", \"types_intervention\"])\n self.conn = self.engine.connect()\n \"\"\"\n Load the ORM of different table into the class\n \"\"\"\n self.check_table()\n self.hl7_connections = sqlalchemy.Table(\"hl7_connections\", self.metadata)\n self.examens = sqlalchemy.Table(\"examens\", self.metadata)\n self.sections = sqlalchemy.Table(\"sections\", self.metadata)\n self.patients = sqlalchemy.Table(\"patients\", self.metadata)\n self.medecins = sqlalchemy.Table(\"medecins\", self.metadata)\n self.types_interventions = sqlalchemy.Table(\"types_intervention\", self.metadata)\n self.logger.info(\"[+] Orm initialized [+]\")","def items(self):\r\n for column in self.table.columns:\r\n yield (column, self[column.name])","def get_table_metadata(self, a_table_name):\n \n self.connect()\n\n # create MetaData \n meta = sqlalchemy.MetaData()\n\n # bind to an engine\n meta.bind = self._engine\n\n table_metadata = sqlalchemy.Table(a_table_name, meta, autoload = True)\n\n cols = [] \n\n for col in table_metadata.columns:\n desc = {}\n desc['name'] = col.name\n desc['type'] = col.type\n desc['nullable'] = col.nullable\n cols.append(desc)\n\n # a dictionary of dict, one dict for each row\n return cols","def transform(self, sql):\n # Start from scratch.\n self.clear()\n # Parse the SQL into the internal structure.\n self.parse(sql)\n\n # Create an empty list of linus in the output.\n puml_lines = list()\n # Run through all tables.\n for table_name, table in self.puml_tables.items():\n # Add PUML code for the beggining of the table.\n puml_lines.append('table({}) '.format(table_name) + '{')\n\n # Add PUML lines for all primary keys.\n for cname, ctype in table['primary'].items():\n puml_lines.append('\\tprimary_key({}) {}'.format(cname, ctype))\n\n # Add PUML lines for all foreign keys.\n for cname, cval in table['foreign'].items():\n puml_lines.append('\\tforeign_key({},{}) {}'.format(cname, cval[1], cval[0]))\n\n # Add separator if there is regular columns.\n if len(table['default'].keys()) > 0:\n puml_lines.append('\\t---')\n\n # Add regular columns.\n for cname, ctype in table['default'].items():\n puml_lines.append('\\t{} {}'.format(cname, ctype))\n\n # Close the table.\n puml_lines.append('}')\n # Add a single empty line.\n puml_lines.append('')\n\n # Run through all foreign keys and crete the table relations.\n for table_name, table in self.puml_tables.items():\n for fk in table['foreign'].values():\n puml_lines.append('{} \"0..n\" -- \"1..1\" {}'.format(table_name, fk[1].split('.')[0]))\n\n # Add a single empty line.\n puml_lines.append('')\n\n # Join all output lines separated by new lines.\n content = '\\n'.join(puml_lines)\n\n # Return the final PUML string.\n return (self.puml_template.format(content))","def _tables(self):\n assert False, \"subclass responsibility\"","def gen_model():\n\n\tmodel = skipthoughts.load_model()\n\treturn model","def model(self) -> str:\n ...","def table_name(self) -> str:\n return self.model._meta.db_table","def build_model():","def apply_model(engine):\n Base.metadata.create_all(engine)","def __new__(cls, name, bases, attrs):\n if name == 'Model':\n return type.__new__(cls, name, bases, attrs)\n table_name = name\n primary_key = None\n fields = []\n column_to_filed = dict()\n for k, v in attrs.items():\n if isinstance(v, Field):\n column_to_filed[k] = v\n if v.primary_key:\n if primary_key:\n raise NameError('Primary key should only be one.')\n else:\n primary_key = k\n else:\n fields.append(k)\n if primary_key is None:\n raise NameError('Primary key not found.')\n # Delete the class attributes which is belong to `Field` object.\n # Because the class attributes may be overide by the same name of \n # the class instance attributes.\n for key in column_to_filed:\n attrs.pop(key)\n\n attrs['PRIMARY_KEY'] = primary_key\n attrs['COLUMN_TO_FILED'] = column_to_filed\n attrs['TABLE_NAME'] = table_name\n return type.__new__(cls, name, bases, attrs)","def _related_fields(self):\r\n model_class, m2m = self._get_model_class_from_table(self.model._meta.db_table) \r\n related_fields = {\r\n self.model._meta.pk.attname: model_class\r\n }\r\n for attname, model_class in self._get_related_models(self.model):\r\n related_fields[attname] = model_class\r\n return related_fields","def bootstrap():\n Base.metadata.create_all(engine)","def table_name(class_):\n try:\n return class_.__tablename__\n except AttributeError:\n return class_.__table__.name","def _define_tables(self):\n metadata = MetaData(bind=self.engine)\n Base = declarative_base(metadata=metadata)\n\n class Dataset(Base):\n __tablename__ = 'datasets'\n\n id = Column(Integer, primary_key=True, autoincrement=True)\n name = Column(String(100), nullable=False)\n\n # columns necessary for loading/processing data\n class_column = Column(String(100), nullable=False)\n train_path = Column(String(200), nullable=False)\n test_path = Column(String(200))\n description = Column(String(1000))\n\n # metadata columns, for convenience\n n_examples = Column(Integer, nullable=False)\n k_classes = Column(Integer, nullable=False)\n d_features = Column(Integer, nullable=False)\n majority = Column(Numeric(precision=10, scale=9), nullable=False)\n size_kb = Column(Integer, nullable=False)\n\n def __repr__(self):\n base = \"<%s: %s, %d classes, %d features, %d rows>\"\n return base % (self.name, self.description, self.k_classes,\n self.d_features, self.n_examples)\n\n class Datarun(Base):\n __tablename__ = 'dataruns'\n\n # relational columns\n id = Column(Integer, primary_key=True, autoincrement=True)\n dataset_id = Column(Integer, ForeignKey('datasets.id'))\n dataset = relationship('Dataset', back_populates='dataruns')\n\n description = Column(String(200), nullable=False)\n priority = Column(Integer)\n\n # hyperparameter selection and tuning settings\n selector = Column(String(200), nullable=False)\n k_window = Column(Integer)\n tuner = Column(String(200), nullable=False)\n gridding = Column(Integer, nullable=False)\n r_minimum = Column(Integer)\n\n # budget settings\n budget_type = Column(Enum(*BUDGET_TYPES))\n budget = Column(Integer)\n deadline = Column(DateTime)\n\n # which metric to use for judgment, and how to compute it\n metric = Column(Enum(*METRICS))\n score_target = Column(Enum(*[s + '_judgment_metric' for s in\n SCORE_TARGETS]))\n\n # variables that store the status of the datarun\n start_time = Column(DateTime)\n end_time = Column(DateTime)\n status = Column(Enum(*DATARUN_STATUS), default=RunStatus.PENDING)\n\n def __repr__(self):\n base = \"\"\n return base % (self.id, self.dataset_id, self.description,\n self.budget_type, self.budget, self.status)\n\n Dataset.dataruns = relationship('Datarun', order_by='Datarun.id',\n back_populates='dataset')\n\n class Hyperpartition(Base):\n __tablename__ = 'hyperpartitions'\n\n # relational columns\n id = Column(Integer, primary_key=True, autoincrement=True)\n datarun_id = Column(Integer, ForeignKey('dataruns.id'))\n datarun = relationship('Datarun', back_populates='hyperpartitions')\n\n # name of or path to a configured classification method\n method = Column(String(255))\n\n # list of categorical parameters whose values are fixed to define\n # this hyperpartition\n categorical_hyperparameters_64 = Column(Text)\n\n # list of continuous parameters which are not fixed; their values\n # must be selected by a Tuner\n tunable_hyperparameters_64 = Column(Text)\n\n # list of categorical or continuous parameters whose values are\n # always fixed. These do not define the hyperpartition, but their\n # values must be passed on to the method. Here for convenience.\n constant_hyperparameters_64 = Column(Text)\n\n # has the partition had too many errors, or is gridding done?\n status = Column(Enum(*PARTITION_STATUS),\n default=PartitionStatus.INCOMPLETE)\n\n @property\n def categoricals(self):\n \"\"\"\n A list of categorical variables along with the fixed values\n which define this hyperpartition.\n Each element is a ('name', HyperParameter) tuple.\n \"\"\"\n return base_64_to_object(self.categorical_hyperparameters_64)\n\n @categoricals.setter\n def categoricals(self, value):\n self.categorical_hyperparameters_64 = object_to_base_64(value)\n\n @property\n def tunables(self):\n \"\"\"\n A list of parameters which are unspecified and must be selected\n with a Tuner. Each element is a ('name', HyperParameter) tuple.\n \"\"\"\n return base_64_to_object(self.tunable_hyperparameters_64)\n\n @tunables.setter\n def tunables(self, value):\n self.tunable_hyperparameters_64 = object_to_base_64(value)\n\n @property\n def constants(self):\n return base_64_to_object(self.constant_hyperparameters_64)\n\n @constants.setter\n def constants(self, value):\n self.constant_hyperparameters_64 = object_to_base_64(value)\n\n def __repr__(self):\n return \"<%s: %s>\" % (self.method, self.categoricals)\n\n Datarun.hyperpartitions = relationship('Hyperpartition',\n order_by='Hyperpartition.id',\n back_populates='datarun')\n\n class Classifier(Base):\n __tablename__ = 'classifiers'\n\n # relational columns\n id = Column(Integer, primary_key=True, autoincrement=True)\n datarun_id = Column(Integer, ForeignKey('dataruns.id'))\n datarun = relationship('Datarun', back_populates='classifiers')\n hyperpartition_id = Column(Integer, ForeignKey('hyperpartitions.id'))\n hyperpartition = relationship('Hyperpartition',\n back_populates='classifiers')\n\n # name of the host where the model was trained\n host = Column(String(50))\n\n # these columns point to where the output is stored\n model_location = Column(String(300))\n metrics_location = Column(String(300))\n\n # base 64 encoding of the hyperparameter names and values\n hyperparameter_values_64 = Column(Text, nullable=False)\n\n # performance metrics\n cv_judgment_metric = Column(Numeric(precision=20, scale=10))\n cv_judgment_metric_stdev = Column(Numeric(precision=20, scale=10))\n test_judgment_metric = Column(Numeric(precision=20, scale=10))\n\n start_time = Column(DateTime)\n end_time = Column(DateTime)\n status = Column(Enum(*CLASSIFIER_STATUS), nullable=False)\n error_message = Column(Text)\n\n @property\n def hyperparameter_values(self):\n return base_64_to_object(self.hyperparameter_values_64)\n\n @hyperparameter_values.setter\n def hyperparameter_values(self, value):\n self.hyperparameter_values_64 = object_to_base_64(value)\n\n @property\n def mu_sigma_judgment_metric(self):\n # compute the lower confidence bound on the cross-validated\n # judgment metric\n if self.cv_judgment_metric is None:\n return None\n return (self.cv_judgment_metric - 2 *\n self.cv_judgment_metric_stdev)\n\n def __repr__(self):\n params = ', '.join(['%s: %s' % i for i in\n list(self.hyperparameter_values.items())])\n return \"\" % (self.id, params)\n\n Datarun.classifiers = relationship('Classifier',\n order_by='Classifier.id',\n back_populates='datarun')\n Hyperpartition.classifiers = relationship('Classifier',\n order_by='Classifier.id',\n back_populates='hyperpartition')\n\n self.Dataset = Dataset\n self.Datarun = Datarun\n self.Hyperpartition = Hyperpartition\n self.Classifier = Classifier\n\n Base.metadata.create_all(bind=self.engine)","def _generate_rowklass(self):\n header = six.next(self.resolved)\n clean = []\n for h in header:\n underscoreless = h.strip().lower().replace(' ', '_').replace('.', '_')\n specialless = underscoreless.replace('(', '').replace(')', '').replace('?', '').replace('-', '')\n if specialless == '':\n clean.append(specialless)\n continue\n try:\n num = int(specialless[0])\n numbers = {1: 'one', 2: 'two', 3: 'three', 4: 'four', 5: 'five',\n 6: 'six', 7: 'seven', 8: 'eight', 9: 'nine', 10: 'ten'}\n numless = numbers[num] + specialless[1:]\n cleaned = numless\n except ValueError:\n cleaned = specialless\n\n more = 1\n while cleaned in clean:\n more += 1\n cleaned += str(more)\n\n clean.append(cleaned)\n\n for i, v in enumerate(clean):\n if v == '':\n clean[i] = 'field_' + str(i)\n self.rowklass = collections.namedtuple('RowKlass', clean)","def make_tables(self):\n for t in self.tables:\n self.add_table(groupname=t['groupname'],\n tablename=t['tablename'],\n description=t['description'],\n tabletitle=t['tabletitle'])","def table(cls):\n return cls.__name__","def test_reflection(self):\n m = MetaData()\n\n t = Table('test_table_syn', m, autoload=True,\n autoload_with=testing.db, oracle_resolve_synonyms=True)\n eq_(t.c.keys(), ['id', 'data'])\n eq_(list(t.primary_key), [t.c.id])","def model(self):","def model(self):","def model(self):","def model(self):","def model(self):","def test_meta_read_write_units(engine):\n class Model(engine.model):\n id = Column(UUID, hash_key=True)\n\n assert Model.Meta.write_units == 1\n assert Model.Meta.read_units == 1\n\n class Other(engine.model):\n class Meta:\n read_units = 2\n write_units = 3\n id = Column(UUID, hash_key=True)\n\n assert Other.Meta.write_units == 3\n assert Other.Meta.read_units == 2","def get_tables_name_and_type(self) -> Optional[Iterable[Tuple[str, str]]]:\n try:\n schema_name = self.context.database_schema.name.__root__\n if self.source_config.includeTables:\n for table_and_type in self.query_table_names_and_types(schema_name):\n table_name = self.standardize_table_name(\n schema_name, table_and_type.name\n )\n table_fqn = fqn.build(\n self.metadata,\n entity_type=Table,\n service_name=self.context.database_service.name.__root__,\n database_name=self.context.database.name.__root__,\n schema_name=self.context.database_schema.name.__root__,\n table_name=table_name,\n skip_es_search=True,\n )\n if filter_by_table(\n self.source_config.tableFilterPattern,\n table_fqn\n if self.source_config.useFqnForFiltering\n else table_name,\n ):\n self.status.filter(\n table_fqn,\n \"Table Filtered Out\",\n )\n continue\n yield table_name, table_and_type.type_\n\n if self.source_config.includeViews:\n for view_name in self.inspector.get_view_names(schema_name):\n view_name = self.standardize_table_name(schema_name, view_name)\n view_fqn = fqn.build(\n self.metadata,\n entity_type=Table,\n service_name=self.context.database_service.name.__root__,\n database_name=self.context.database.name.__root__,\n schema_name=self.context.database_schema.name.__root__,\n table_name=view_name,\n )\n\n if filter_by_table(\n self.source_config.tableFilterPattern,\n view_fqn\n if self.source_config.useFqnForFiltering\n else view_name,\n ):\n self.status.filter(\n view_fqn,\n \"Table Filtered Out\",\n )\n continue\n yield view_name, TableType.View\n except Exception as err:\n logger.warning(\n f\"Fetching tables names failed for schema {schema_name} due to - {err}\"\n )\n logger.debug(traceback.format_exc())","def create_meta_loan_table(self):\n table_exists = self.check_if_table_exists(\"meta_loan_tables\")\n\n if not table_exists:\n self.read_sql_from_file('create_meta_loan_tables.sql')\n return","def create_table(self):\n pass","def meta(self):\n raise NotImplementedError","def _create_TableDescriptor(self):\n\n self.conn.cursor.execute(\"PRAGMA table_info(\" + self.table_name + \")\")\n descriptions = self.conn.cursor.fetchall()\n column_map = {}\n for description in descriptions:\n column_map[description[1]] = description[2]\n td = TD(self.table_name, column_map) \n\n# self.conn.cursor.execute(\"SELECT sql FROM sqlite_master WHERE name='{tb}'\"\\\n# .format(tb=self.table_name))\n# aa = str(self.conn.cursor.fetchone()[0])\n# sindx = aa.find(\"(\")\n# eindx = aa.find(\")\")\n# aa = aa[sindx+1:eindx]\n# aa = aa.split(\",\")\n# column_map = {kyval.split()[0]:kyval.split()[1] for kyval in aa}\n# td = TD(self.table_name, column_map) \n\n return td","def iteritems(self):\r\n for name in self.table.sequence:\r\n if name not in self.table.exclude:\r\n yield (name, self.columns[name])","def create_translations_model(model, related_name, meta, **fields):\n if not meta:\n meta = {}\n unique = [('language_code', 'master')]\n meta['unique_together'] = list(meta.get('unique_together', [])) + unique\n # Create inner Meta class \n Meta = type('Meta', (object,), meta)\n name = '%sTranslation' % model.__name__\n attrs = {}\n attrs.update(fields)\n attrs['Meta'] = Meta\n attrs['__module__'] = model.__module__\n attrs['language_code'] = models.CharField(max_length=15, db_index=True)\n # null=True is so we can prevent cascade deletion\n attrs['master'] = models.ForeignKey(model, related_name=related_name, editable=False, null=True)\n # Create and return the new model\n return ModelBase(name, (BaseTranslationModel,), attrs)","def create_sqlalchemy_mapperproperties_from_dbfields(cls,modeltable):\n allprops = {}\n #\n for field in cls.fieldlist:\n props = field.create_sqlalchemy_mapperproperties(cls,modeltable)\n if (props!=None):\n allprops.update(props)\n return allprops","def _get_related_models(self, parent_model):\r\n related_models = set()\r\n rev_reversemapping = dict([(v,k) for k,v in self._reversemapping.iteritems()])\r\n if rev_reversemapping:\r\n for attname, related in self._get_reverse_relations(parent_model):\r\n related_models.add((rev_reversemapping[attname], related.model))\r\n\r\n for field in parent_model._meta.fields:\r\n if field.rel and field.rel.to._meta.db_table in self.query.tables and field.rel.to != parent_model:\r\n related_models.add((field.attname, field.rel.to))\r\n \r\n for attname, model_class in related_models:\r\n yield attname, model_class\r\n if attname.endswith(\"_id\"):\r\n attname = attname[:-3]\r\n for join_attname, model_klass in self._get_related_models(model_class):\r\n yield LOOKUP_SEP.join((attname,join_attname)), model_klass","def createTables(self):\n metadata = Base.metadata\n metadata.create_all(self._engine)\n return"],"string":"[\n \"def test_meta_table_name(engine):\\n class Model(engine.model):\\n id = Column(UUID, hash_key=True)\\n\\n assert Model.Meta.table_name == \\\"Model\\\"\\n\\n class Other(engine.model):\\n class Meta:\\n table_name = \\\"table_name\\\"\\n write_units = 3\\n id = Column(UUID, hash_key=True)\\n\\n assert Other.Meta.table_name == \\\"table_name\\\"\",\n \"def model_table():\\r\\n class OccupationTable(tables.Table):\\r\\n class Meta:\\r\\n model = Occupation\\r\\n assert [\\\"id\\\", \\\"name\\\", \\\"region\\\"] == list(OccupationTable.base_columns.keys())\\r\\n\\r\\n class OccupationTable2(tables.Table):\\r\\n extra = tables.Column()\\r\\n\\r\\n class Meta:\\r\\n model = Occupation\\r\\n assert [\\\"id\\\", \\\"name\\\", \\\"region\\\", \\\"extra\\\"] == list(OccupationTable2.base_columns.keys())\\r\\n\\r\\n # be aware here, we already have *models* variable, but we're importing\\r\\n # over the top\\r\\n from django.db import models\\r\\n\\r\\n class ComplexModel(models.Model):\\r\\n char = models.CharField(max_length=200)\\r\\n fk = models.ForeignKey(\\\"self\\\")\\r\\n m2m = models.ManyToManyField(\\\"self\\\")\\r\\n\\r\\n class ComplexTable(tables.Table):\\r\\n class Meta:\\r\\n model = ComplexModel\\r\\n assert [\\\"id\\\", \\\"char\\\", \\\"fk\\\"] == list(ComplexTable.base_columns.keys())\",\n \"def sequence():\\r\\n class TestTable(tables.Table):\\r\\n a = tables.Column()\\r\\n b = tables.Column()\\r\\n c = tables.Column()\\r\\n assert [\\\"a\\\", \\\"b\\\", \\\"c\\\"] == TestTable([]).columns.names()\\r\\n assert [\\\"b\\\", \\\"a\\\", \\\"c\\\"] == TestTable([], sequence=(\\\"b\\\", \\\"a\\\", \\\"c\\\")).columns.names()\\r\\n\\r\\n class TestTable2(TestTable):\\r\\n class Meta:\\r\\n sequence = (\\\"b\\\", \\\"a\\\", \\\"c\\\")\\r\\n assert [\\\"b\\\", \\\"a\\\", \\\"c\\\"] == TestTable2([]).columns.names()\\r\\n assert [\\\"a\\\", \\\"b\\\", \\\"c\\\"] == TestTable2([], sequence=(\\\"a\\\", \\\"b\\\", \\\"c\\\")).columns.names()\\r\\n\\r\\n class TestTable3(TestTable):\\r\\n class Meta:\\r\\n sequence = (\\\"c\\\", )\\r\\n assert [\\\"c\\\", \\\"a\\\", \\\"b\\\"] == TestTable3([]).columns.names()\\r\\n assert [\\\"c\\\", \\\"a\\\", \\\"b\\\"] == TestTable([], sequence=(\\\"c\\\", )).columns.names()\\r\\n\\r\\n class TestTable4(TestTable):\\r\\n class Meta:\\r\\n sequence = (\\\"...\\\", )\\r\\n assert [\\\"a\\\", \\\"b\\\", \\\"c\\\"] == TestTable4([]).columns.names()\\r\\n assert [\\\"a\\\", \\\"b\\\", \\\"c\\\"] == TestTable([], sequence=(\\\"...\\\", )).columns.names()\\r\\n\\r\\n class TestTable5(TestTable):\\r\\n class Meta:\\r\\n sequence = (\\\"b\\\", \\\"...\\\")\\r\\n assert [\\\"b\\\", \\\"a\\\", \\\"c\\\"] == TestTable5([]).columns.names()\\r\\n assert [\\\"b\\\", \\\"a\\\", \\\"c\\\"] == TestTable([], sequence=(\\\"b\\\", \\\"...\\\")).columns.names()\\r\\n\\r\\n class TestTable6(TestTable):\\r\\n class Meta:\\r\\n sequence = (\\\"...\\\", \\\"b\\\")\\r\\n assert [\\\"a\\\", \\\"c\\\", \\\"b\\\"] == TestTable6([]).columns.names()\\r\\n assert [\\\"a\\\", \\\"c\\\", \\\"b\\\"] == TestTable([], sequence=(\\\"...\\\", \\\"b\\\")).columns.names()\\r\\n\\r\\n class TestTable7(TestTable):\\r\\n class Meta:\\r\\n sequence = (\\\"b\\\", \\\"...\\\", \\\"a\\\")\\r\\n assert [\\\"b\\\", \\\"c\\\", \\\"a\\\"] == TestTable7([]).columns.names()\\r\\n assert [\\\"b\\\", \\\"c\\\", \\\"a\\\"] == TestTable([], sequence=(\\\"b\\\", \\\"...\\\", \\\"a\\\")).columns.names()\\r\\n\\r\\n # Let's test inheritence\\r\\n class TestTable8(TestTable):\\r\\n d = tables.Column()\\r\\n e = tables.Column()\\r\\n f = tables.Column()\\r\\n\\r\\n class Meta:\\r\\n sequence = (\\\"d\\\", \\\"...\\\")\\r\\n\\r\\n class TestTable9(TestTable):\\r\\n d = tables.Column()\\r\\n e = tables.Column()\\r\\n f = tables.Column()\\r\\n\\r\\n assert [\\\"d\\\", \\\"a\\\", \\\"b\\\", \\\"c\\\", \\\"e\\\", \\\"f\\\"] == TestTable8([]).columns.names()\\r\\n assert [\\\"d\\\", \\\"a\\\", \\\"b\\\", \\\"c\\\", \\\"e\\\", \\\"f\\\"] == TestTable9([], sequence=(\\\"d\\\", \\\"...\\\")).columns.names()\",\n \"def _analyze_db_model(cls):\\n attributes = dir(cls)\\n\\n table_attributes = {} # type: Dict[str, Union[ColumnProperty, RelationshipProperty]]\\n properties = [] # type: List[str]\\n mapper_attrs = inspect(cls).attrs\\n\\n _get_class_attributes(attributes, cls, properties, mapper_attrs, table_attributes)\\n\\n model_fields = []\\n attributes_containing_lists = []\\n normal_attributes = []\\n unknown_attributes = []\\n for name, attr in table_attributes.items():\\n if isinstance(attr, RelationshipProperty):\\n mapper = attr.mapper # type: Mapper\\n if issubclass(mapper.class_, Taxonomy):\\n normal_attributes.append((name, mapper.class_))\\n model_fields.append(\\\"'{}': fields.Nested(taxonomy_item_get, description='{}'),\\\".format(name, mapper.class_.__name__))\\n else:\\n if name in properties:\\n name = name.lstrip('_')\\n attributes_containing_lists.append(name)\\n classname = mapper.class_.__name__\\n if 'To' in classname:\\n classname = classname.split('To')[0]\\n model_fields.append(\\\"'{}': fields.List(fields.Nested(taxonomy_item_get, description='{}'), default=[]),\\\".format(name, classname))\\n else:\\n model_fields.append(\\\"'{}': fields.List(fields.Raw(description='{}'), default=[]),\\\".format(name, classname))\\n else:\\n model_fields.append(\\\"'{}': fields.Raw(description='{}'),\\\".format(name, mapper.class_.__name__))\\n normal_attributes.append((name, mapper.class_))\\n if isinstance(attr, ColumnProperty):\\n col = attr.columns[0] # type: Column\\n zusatz = ''\\n if col.default is not None:\\n default = col.default.arg\\n if isinstance(default, str):\\n zusatz = \\\"default='{}'\\\".format(default)\\n else:\\n zusatz = 'default={}'.format(default)\\n if isinstance(col.type, Integer):\\n model_fields.append(\\\"'{}': fields.Integer({}),\\\".format(name, zusatz))\\n if name != 'id':\\n normal_attributes.append((name, int))\\n elif isinstance(col.type, Float):\\n model_fields.append(\\\"'{}': fields.Float({}),\\\".format(name, zusatz))\\n normal_attributes.append((name, float))\\n elif isinstance(col.type, String):\\n model_fields.append(\\\"'{}': fields.String({}),\\\".format(name, zusatz))\\n normal_attributes.append((name, str))\\n elif isinstance(col.type, Boolean):\\n model_fields.append(\\\"'{}': fields.Boolean({}),\\\".format(name, zusatz))\\n normal_attributes.append((name, bool))\\n elif isinstance(col.type, Date):\\n model_fields.append(\\\"'{}': fields.Date({}),\\\".format(name, zusatz))\\n normal_attributes.append((name, date))\\n else:\\n unknown_attributes.append((name, col.type))\\n\\n return {\\n 'model_fields': model_fields,\\n 'normal_attributes': tuple(normal_attributes),\\n 'attributes_containing_lists': tuple(attributes_containing_lists),\\n 'unknown_attributes': tuple(unknown_attributes),\\n }\",\n \"def construct_base_table(self):\\n # Get requested biological entities.\\n req_biomodels = [exp.biomodel for exp in self.req_exps]\\n # Remove duplicates.\\n req_biomodels = list(unique_everseen(req_biomodels))\\n # Order according to the linearized models.\\n relations = Relations(self.app_label, model_superclass=(BiologicalModel, MetaModel))\\n relations.start_join()\\n linearized_biomodels = relations.linearized\\n req_biomodels = sort_by_other(req_biomodels, \\n order=linearized_biomodels)\\n # Construct the SQL statement.\\n sql = self.construct_result_table(req_biomodels)\\n return sql\",\n \"def should_support_both_meta_sequence_and_constructor_exclude():\\r\\n class SequencedTable(tables.Table):\\r\\n a = tables.Column()\\r\\n b = tables.Column()\\r\\n c = tables.Column()\\r\\n\\r\\n class Meta:\\r\\n sequence = ('a', '...')\\r\\n\\r\\n table = SequencedTable([], exclude=('c', ))\\r\\n table.as_html()\",\n \"def generate_model(\\n self,\\n table: Dict,\\n singular: bool = True,\\n exceptions: Optional[List] = None,\\n schema_global: Optional[bool] = True,\\n *args,\\n **kwargs,\\n ) -> str:\\n model = \\\"\\\"\\n model = gt.model_template.format(\\n model_name=create_class_name(table.name, singular, exceptions),\\n table_name=table.name,\\n )\\n for column in table.columns:\\n model += logic.generate_column(column, table.primary_key, table, gt, self)\\n if table.indexes or table.alter or table.checks or not schema_global:\\n model = logic.add_table_args(self, model, table, schema_global)\\n # create sequence\\n return model\",\n \"def create_table(self, context, connection, *, engine):\\n yield Table(self.table_name, MetaData(), autoload=True, autoload_with=engine)\",\n \"def model_to_sequencesql(self, m):\\n from django.db import connection\\n\\n # tbl has app_label prefix; e.g., testapp_simple\\n tbl = m._meta.db_table\\n\\n # Get name of sequence for this table. Here's\\n # a trace from doing it manually.\\n #\\n # sql> select \\\"default\\\" from sys.columns\\n # more> where table_id = 4186 and name = 'id';\\n # +-------------------------------------+\\n # | default |\\n # +=====================================+\\n # | next value for \\\"django1\\\".\\\"seq_4176\\\" |\\n # +-------------------------------------+\\n # 1 tuple\\n # sql>\\n #\\n\\n c = connection.cursor()\\n fmt = \\\"\\\"\\\"\\nSELECT\\n \\\"default\\\"\\nFROM\\n sys.columns\\nWHERE\\n table_id = (SELECT id FROM sys.tables where name = %s) AND\\n name = 'id'\\n;\\n\\\"\\\"\\\"\\n c.execute(fmt, [tbl, ])\\n row = c.fetchone()\\n # default = 'next value for \\\"django1\\\".\\\"seq_4176\\\"'\\n default = row[0]\\n p = default.rfind('\\\".\\\"seq_')\\n if p == -1:\\n return ''\\n\\n # seq = '\\\"seq_4176\\\"'\\n seq = default[p + 2:]\\n\\n fmt = 'ALTER SEQUENCE %s RESTART WITH (SELECT MAX(id) + 1 FROM %s);'\\n\\n return fmt % (seq, tbl)\",\n \"def sequence():\\n class TestTable(tables.Table):\\n a = tables.Column()\\n b = tables.Column()\\n c = tables.Column()\\n Assert([\\\"a\\\", \\\"b\\\", \\\"c\\\"]) == TestTable([]).columns.names()\\n Assert([\\\"b\\\", \\\"a\\\", \\\"c\\\"]) == TestTable([], sequence=(\\\"b\\\", \\\"a\\\", \\\"c\\\")).columns.names()\\n\\n class TestTable2(TestTable):\\n class Meta:\\n sequence = (\\\"b\\\", \\\"a\\\", \\\"c\\\")\\n Assert([\\\"b\\\", \\\"a\\\", \\\"c\\\"]) == TestTable2([]).columns.names()\\n Assert([\\\"a\\\", \\\"b\\\", \\\"c\\\"]) == TestTable2([], sequence=(\\\"a\\\", \\\"b\\\", \\\"c\\\")).columns.names()\\n\\n # BAD, all columns must be specified, or must use \\\"...\\\"\\n with Assert.raises(ValueError):\\n class TestTable3(TestTable):\\n class Meta:\\n sequence = (\\\"a\\\", )\\n with Assert.raises(ValueError):\\n TestTable([], sequence=(\\\"a\\\", ))\\n\\n # GOOD, using a single \\\"...\\\" allows you to only specify some columns. The\\n # remaining columns are ordered based on their definition order\\n class TestTable4(TestTable):\\n class Meta:\\n sequence = (\\\"...\\\", )\\n Assert([\\\"a\\\", \\\"b\\\", \\\"c\\\"]) == TestTable4([]).columns.names()\\n Assert([\\\"a\\\", \\\"b\\\", \\\"c\\\"]) == TestTable([], sequence=(\\\"...\\\", )).columns.names()\\n\\n class TestTable5(TestTable):\\n class Meta:\\n sequence = (\\\"b\\\", \\\"...\\\")\\n Assert([\\\"b\\\", \\\"a\\\", \\\"c\\\"]) == TestTable5([]).columns.names()\\n Assert([\\\"b\\\", \\\"a\\\", \\\"c\\\"]) == TestTable([], sequence=(\\\"b\\\", \\\"...\\\")).columns.names()\\n\\n class TestTable6(TestTable):\\n class Meta:\\n sequence = (\\\"...\\\", \\\"b\\\")\\n Assert([\\\"a\\\", \\\"c\\\", \\\"b\\\"]) == TestTable6([]).columns.names()\\n Assert([\\\"a\\\", \\\"c\\\", \\\"b\\\"]) == TestTable([], sequence=(\\\"...\\\", \\\"b\\\")).columns.names()\\n\\n class TestTable7(TestTable):\\n class Meta:\\n sequence = (\\\"b\\\", \\\"...\\\", \\\"a\\\")\\n Assert([\\\"b\\\", \\\"c\\\", \\\"a\\\"]) == TestTable7([]).columns.names()\\n Assert([\\\"b\\\", \\\"c\\\", \\\"a\\\"]) == TestTable([], sequence=(\\\"b\\\", \\\"...\\\", \\\"a\\\")).columns.names()\\n\\n # Let's test inheritence\\n class TestTable8(TestTable):\\n d = tables.Column()\\n e = tables.Column()\\n f = tables.Column()\\n\\n class Meta:\\n sequence = (\\\"d\\\", \\\"...\\\")\\n\\n class TestTable9(TestTable):\\n d = tables.Column()\\n e = tables.Column()\\n f = tables.Column()\\n\\n Assert([\\\"d\\\", \\\"a\\\", \\\"b\\\", \\\"c\\\", \\\"e\\\", \\\"f\\\"]) == TestTable8([]).columns.names()\\n Assert([\\\"d\\\", \\\"a\\\", \\\"b\\\", \\\"c\\\", \\\"e\\\", \\\"f\\\"]) == TestTable9([], sequence=(\\\"d\\\", \\\"...\\\")).columns.names()\",\n \"def find_sql_models():\\n for model in find_subclasses(SQLModel):\\n # Get model Meta class\\n meta = getattr(model, 'Meta', None)\\n if meta:\\n # If this is marked as abstract ignore it\\n if getattr(meta, 'abstract', False):\\n continue\\n yield model\",\n \"def db_table(self):\",\n \"def create_table(cls):\\n\\n dbmanager = cls.dbm()\\n\\n # ask model to define its internal fields\\n fields = cls.define_fields(dbmanager)\\n cls.extend_fields(fields, True)\\n # now hash the fieldlist so we can look up fields by name\\n cls.hash_fieldlist()\\n\\n # get the sqlahelper for this schema (usually default one shared by all models), plus some info\\n dbtablename = cls.get_dbtablename()\\n dbschemaname = cls.get_dbschemaname()\\n sqlahelper = dbmanager.get_sqlahelper(dbschemaname)\\n metadata = sqlahelper.getmake_metadata()\\n\\n # build sqlalchemy columns from fields\\n sqlalchemycolumns = cls.create_sqlalchemy_columns_from_dbfields()\\n\\n # tell sqlalchemy to build table object from columns\\n modeltable = sqlalchemy.Table(dbtablename, metadata, *sqlalchemycolumns)\\n\\n # and store the table and other object references in the model class itself\\n cls.setclass_dbinfo(modeltable, sqlahelper)\",\n \"def next_record(self) -> Iterable[DatabaseMetadata]:\\n for key, group in groupby(self._get_raw_extract_iter(), get_table_key):\\n columns = []\\n for row in group:\\n last_row = row\\n col_type = ''\\n if row['col_type'].upper() == 'CHARACTER VARYING':\\n col_type = 'VARCHAR'\\n elif row['col_type'].upper() == 'CHARACTER' or row['col_type'].upper() == 'NAME':\\n col_type = 'CHAR'\\n elif row['col_type'].upper() == 'INTEGER':\\n col_type = 'INT'\\n elif row['col_type'].upper() == 'TIMESTAMP WITHOUT TIME ZONE':\\n col_type = 'TIMESTAMP'\\n elif row['col_type'].upper() == 'DOUBLE PRECISION':\\n col_type = 'DOUBLE'\\n elif row['col_type'].upper() == 'OID':\\n col_type = 'NUMBER'\\n elif row['col_type'].upper() == 'ARRAY':\\n col_type = 'ARRAY'\\n elif row['col_type'].upper() == 'BOOLEAN':\\n col_type = 'BOOLEAN'\\n else:\\n col_type = None\\n if not self.pattern.filter_pattern.included(f'{last_row[1]}.{last_row[2]}'):\\n self.status.filtered(f'{last_row[1]}.{last_row[2]}', \\\"pattern not allowed\\\", last_row[2])\\n continue\\n if col_type is not None:\\n columns.append(Column(name=row['col_name'], description=row['col_description'],\\n columnDataType=col_type, ordinalPosition=int(row['col_sort_order'])))\\n table_metadata = Table(id=uuid.uuid4(), name=last_row['name'],\\n description=last_row['description'],\\n columns=columns)\\n\\n self.status.scanned(table_metadata.name.__root__)\\n\\n dm = Database(id=uuid.uuid4(),\\n name=row['schema'],\\n description=row['description'] if row['description'] is not None else ' ',\\n service=EntityReference(id=self.service.id, type=self.SERVICE_TYPE))\\n table_and_db = OMetaDatabaseAndTable(table=table_metadata, database=dm)\\n yield table_and_db\",\n \"def map_database(connection):\\n eng = create_engine(connection)\\n metadata = MetaData()\\n metadata.reflect(eng)\\n base = automap_base(metadata=metadata)\\n base.prepare()\\n return base.classes, eng\",\n \"def __tablename__(cls):\\n return get_table_name(cls.__name__)\",\n \"def model_table(name, *fields, app_label='internal'):\\n model = apps.get_model(app_label, name)\\n items = model.objects.all().values_list(*fields)\\n field_names = [model._meta.get_field(field).verbose_name\\n for field in fields]\\n return {'items': items, 'fields': field_names}\",\n \"def TTableModel(metadata=None):\\n\\n from sqlalchemy import MetaData\\n\\n @add_metaclass(ComplexModelMeta)\\n class TableModel(TTableModelBase()):\\n class Attributes(ComplexModelBase.Attributes):\\n sqla_metadata = metadata or MetaData()\\n\\n return TableModel\",\n \"def parse(self, lines):\\n # Keep count of the current line number.\\n i = 0\\n # list tables and content\\n tables = dict()\\n attr_param = list()\\n\\n skipped_lines = list() # DEBUG\\n\\n # Loop through all lines.\\n for i in range(0, len(lines)):\\n line_stripped = lineNormalise(lines[i])\\n skip = True\\n\\n for keyword in self.target_keywords:\\n\\n # Look for keywords at the beginning of the line.\\n if line_stripped.startswith(keyword):\\n # print(\\\"{} : {}\\\".format(i, line_stripped)) # DEBUG\\n skip = False\\n\\n # Found one, do parse\\n expression = re.search(r'(\\\\w+) (\\\\w+)', line_stripped)\\n if keyword is self.target_keywords[0]: # class/table\\n # get table name\\n table_name = expression.group(2)\\n\\n # add it in tables if not already in\\n # tables (classes) may be at differant place in a PlantUML file\\n if table_name not in tables:\\n tables[table_name] = list()\\n # print(\\\"Table : «{}» ajoutee\\\".format(expression.group(2))) # DEBUG\\n print(\\\"{} : +table «{}»\\\".format(i, table_name)) # DEBUG\\n\\n elif keyword is self.target_keywords[1]: # primary key\\n # import pdb; pdb.set_trace()\\n # get related table\\n attr_param = (re.sub(r'(pyk\\\\()|\\\\)|,|\\\\n', r' ', line_stripped).strip().split())\\n tables[table_name].extend(attr_param)\\n print(\\\"{} :\\\\t«{}» +{}\\\".format(i, table_name, attr_param)) # DEBUG\\n\\n elif keyword is self.target_keywords[2]: # foreign key\\n # get related table\\n attr_param = (re.sub(r'(fnk\\\\()|\\\\)|,|\\\\n', r' ', line_stripped).strip().split())\\n tables[table_name].extend(attr_param)\\n print(\\\"{} :\\\\t«{}» +{}\\\".format(i, table_name, attr_param)) # DEBUG\\n\\n\\n elif keyword is self. target_keywords[3]: # primary foreign key\\n # get related table\\n attr_param = (re.sub(r'(pfk\\\\()|\\\\)|,|\\\\n', r' ', line_stripped).strip().split())\\n tables[table_name].extend(attr_param)\\n print(\\\"{} :\\\\t«{}» +{}\\\".format(i, table_name, attr_param)) # DEBUG\\n\\n else: # attribute\\n # print(line_stripped) # DEBUG\\n print(\\\"{} : \\\\t«{}» Attribute? {}\\\".format(i, line_stripped)) # DEBUG\\n\\n if skip:\\n skipped_lines.append(i)\\n\\n print(\\\"\\\\nNumbers of tables : {}\\\\n\\\".format(len(tables)))\\n pp = pprint.PrettyPrinter(indent=4, compact=True)\\n print(\\\"Scraped data:\\\")\\n pp.pprint(tables) # DEBUG\\n print(\\\"\\\\nSkipped lines: {}\\\\n\\\".format(skipped_lines)) # DEBUG\",\n \"def init_model(engine):\\n ## Reflected tables must be defined and mapped here\\n #global reflected_table\\n #reflected_table = sa.Table(\\\"Reflected\\\", meta.metadata, autoload=True,\\n # autoload_with=engine)\\n #orm.mapper(Reflected, reflected_table)\\n #\\n meta.Session.configure(bind=engine)\\n meta.engine = engine\",\n \"def create_prerequisites(cls, dbmanager):\\n subfields = mdbmixins.dbfmixins_authortracker()\\n if (cls.flag_mixin_atroot):\\n # prepare extra fields that will be added at root; this doesnt actually create any helper models\\n cls.extend_fields(subfields)\\n else:\\n # add a special sub table that will contain some fields, using a helper class object attached to us\\n # create (AND REGISTER) the new helper object\\n backrefname = cls.get_dbtablename_pure()\\n mdbmodel_fieldset.MewloDbFieldset.make_fieldset_dbobjectclass(cls,'tracking','author tracking object',backrefname,dbmanager,subfields)\",\n \"def meta(cls):\\n if getattr(cls, '__from_class__', None) is not None:\\n cls = cls.__from_class__\\n attribute_info = {}\\n for name, value in cls.__table__.columns.items():\\n attribute_info[name] = str(value.type).lower()\\n\\n return {cls.__name__: attribute_info}\",\n \"def meta_db_tables(self) -> list:\\r\\n def _passer(**kwargs):\\r\\n data = self.engine.execute(\\\"\\\"\\\"\\r\\n SELECT * FROM sqlite_master WHERE type='table';\\r\\n \\\"\\\"\\\").fetchall()\\r\\n table_names = [i[1] for i in data]\\r\\n return table_names\\r\\n return self._connectionController(_passer)\",\n \"def generateModelClass(self):\\n\\t\\tself.printt_cls(\\\"export class {} {}\\\".format(self.objName, \\\"{\\\"))\\n\\t\\tfor col in self.objSchema[\\\"fields\\\"]:\\n\\t\\t\\tcolName = col[\\\"name\\\"]\\n\\t\\t\\tcolType = col[\\\"type\\\"]\\n\\t\\t\\tself.printt_cls(\\\"\\\\t{} : {};\\\".format(colName, self.JS_DATA_TYPES[colType]))\\n\\t\\tself.printt_cls(\\\"}\\\")\\n\\t\\tself.printt_cls(\\\"\\\")\",\n \"def __init__(self, table):\\n self.thingy_table = table\\n self.thingy_type = table.__name__\\n\\n # Match [...]{tablename}\\n regex = ur'(?x) \\\\[ ([^]]+) \\\\] \\\\s* \\\\{' + table.__singlename__ + ur'(:[^}]+)?\\\\}'\\n\\n # old-style classes augh!\\n markdown.inlinepatterns.Pattern.__init__(self, regex)\",\n \"def create_table(cls, *args, **kwargs):\\n init = cls._meta.database.create_table_title(cls._meta.table_name)\\n i = 1\\n fields = zip(cls._meta.sorted_fields_names, cls._meta.sorted_fields)\\n for field in fields:\\n field_string = field[1].create_field(field[0])\\n if i == len(fields):\\n if cls._meta.unique:\\n init = cls._meta.database.create_unique(init, cls._meta.unique)\\n\\n init = cls._meta.database.create_table_field_end(init, field_string)\\n\\n if cls._meta.hypertable:\\n init = cls._meta.database.create_hypertable(init,\\n cls._meta)\\n else:\\n init = cls._meta.database.create_table_field(init, field_string)\\n i+=1\\n\\n yield cls._meta.database.runOperation(init)\",\n \"def create_tables(self):\\n for name, attribute in self.__dict__.items():\\n if hasattr(attribute, 'create_table_in_sqlite_db'):\\n attribute.create_table_in_sqlite_db()\",\n \"def __init__(self, *args):\\n self.engine = db.create_engine('mysql+pymysql://root:''@127.0.0.1:3306/northwind', echo=True)\\n self.connection = self.engine.connect()\\n self.metadata = db.MetaData()\\n self.tables = db.Table(*args, self.metadata, autoload=True, autoload_with=self.engine)\",\n \"def setup_schema(BaseDao, session):\\n def setup_schema_fn():\\n for class_ in BaseDao._decl_class_registry.values():\\n if hasattr(class_, '__tablename__'):\\n if class_.__name__.endswith('Schema'):\\n raise ModelConversionError(\\n \\\"For safety, setup_schema can not be used when a\\\"\\n \\\"Model class ends with 'Schema'\\\"\\n )\\n\\n class Meta(object):\\n model = class_\\n sqla_session = session\\n dump_only = ('pkId', 'created', 'modified')\\n\\n schema_class_name = '%sSchema' % class_.__name__\\n\\n schema_class = type(\\n schema_class_name,\\n (ModelSchema,),\\n {'Meta': Meta}\\n )\\n\\n setattr(class_, '__marshmallow__', schema_class)\\n\\n return setup_schema_fn\",\n \"def create_models( self ):\",\n \"def construct_result_table(self, biomodels):\\n select = 'SELECT DISTINCT '\\n cached_alias = 'c'\\n join_exps = 'FROM %s_%s AS %s' % (self.app_label, \\n settings.DISBI['JOINED_TABLENAME'], \\n cached_alias)\\n left_join_template = '''\\n LEFT JOIN (\\n %s\\n ) AS %s\\n ON (%s = %s)\\n '''\\n subtables_not_null_column = []\\n select_bios = []\\n relations = Relations(self.app_label, model_superclass=(BiologicalModel, MetaModel))\\n for biomodel in biomodels:\\n # Requested experiments related to biomodel.\\n req_exps_for_bio = [] \\n for exp in self.req_exps:\\n if exp.biomodel == biomodel:\\n req_exps_for_bio.append(exp)\\n \\n select_bios.extend(self.get_show_columns(biomodel))\\n \\n\\n # Get Meta models for Bio model and the show columns to the \\n # SELECT clause.\\n metamodels_of_biomodel = relations.get_related_metamodels(biomodel)\\n #print(metamodels_of_biomodel)\\n for metamodel in metamodels_of_biomodel:\\n select_bios.extend(self.get_show_columns(metamodel))\\n\\n \\n for exp in req_exps_for_bio:\\n select_bios.extend(self.get_display_names(exp))\\n exp_alias = 'exp%s' % exp.pk\\n join_exps += left_join_template % (\\n self.construct_exptable(exp),\\n exp_alias,\\n '%s.%s_id' % (cached_alias, biomodel.__name__.lower()),\\n '%s.%s' % (exp_alias, exp.biofield.column)\\n )\\n subtables_not_null_column.append((self.get_notnull_column(exp), \\n str(exp.id)))\\n exclude_empty = 'WHERE ' + ' OR '.join(['%s_%s IS NOT NULL' % col \\n for col in subtables_not_null_column])\\n \\n sql = '\\\\n'.join((select + ', '.join(select_bios), join_exps, exclude_empty))\\n return re.sub(r'^\\\\s+', '', sql, flags=re.MULTILINE)\",\n \"def get_data_models(models_file):\\n list_models = []\\n model = []\\n pos_numeric = [] # Position of numeric fields\\n info_keys = [] # Info. about keys\\n re_field = re.compile('\\\\s+\\\\w+\\\\s*=\\\\s*models\\\\.') # Line with field name\\n re_class = re.compile('\\\\s+class ') # For Admin and Meta\\n re_def = re.compile('\\\\s+def ')\\n is_new_model = False\\n\\n for line in open(models_file):\\n # The models start with 'class'\\n if not is_new_model and line.startswith('class'):\\n model_name = line.replace('class','').split('(')[0].strip()\\n model.append(model_name)\\n is_new_model = True\\n elif is_new_model:\\n if re_field.match(line):\\n field_name = line.split('=')[0].strip()\\n model.append(field_name)\\n\\n if 'models.DecimalField' in line or 'models.IntegerField' in line:\\n pos_numeric.append(len(model)-2) # Discard model name.\\n elif 'models.ForeignKey' in line:\\n key_name = line.split('(')[-1].strip().strip(')')\\n position = len(model)-2 # Discard model name.\\n info_keys.append(':')\\n info_keys.append(str(position) + ',')\\n info_keys.append(key_name)\\n # It is supposed that models in localization has at the end:\\n # ('class Meta', 'class Admin', or some 'def')\\n elif re_class.match(line) or re_def.match(line):\\n if pos_numeric:\\n pos_num2str = '#'\\n for num in pos_numeric:\\n pos_num2str += str(num)\\n model.append(pos_num2str)\\n model.append(':N') # To detect the numeric field.\\n pos_numeric = []\\n if info_keys:\\n all_keys = \\\"\\\"\\n for key in info_keys:\\n all_keys += key\\n model.append(all_keys)\\n model.append(':K') # To detect fastly some key.\\n info_keys = []\\n list_models.append(model)\\n model = []\\n is_new_model = False\\n\\n return list_models\",\n \"async def _create_tables_declarative(self, base, engine):\\n if hasattr(base, 'metadata'):\\n base.metadata.create_all(bind=engine, checkfirst=True)\\n return\",\n \"def __tablename__(self):\\n return sub(r\\\"(? list:\\r\\n def _passer(**kwargs):\\r\\n return self.engine.execute(\\r\\n f\\\"PRAGMA table_info({kwargs['table_name']});\\\").fetchall()\\r\\n return self._connectionController(_passer, table_name=table_name)\",\n \"def _get_model_from_table_name(table_name: str) -> Optional[Type[RDSModel]]:\\n table_model = None\\n try:\\n if hasattr(Base, '_decl_class_registry'):\\n models = Base._decl_class_registry.values() # sqlalchemy < 1.4\\n else:\\n models = Base.registry._class_registry.values()\\n\\n for model in models:\\n if hasattr(model, '__tablename__') and model.__tablename__ == table_name:\\n table_model = model\\n except Exception as e:\\n LOGGER.exception(f'Failed to get model for the table: {table_name} from rds model base')\\n raise e\\n\\n return table_model\",\n \"def db_for_read(self, model, **hints):\\n model_name = model._meta.label_lower\\n pos = model_name.find('.')\\n table_name = model_name[pos+1:]\\n if table_name in self.route_encuestas:\\n return 'encuestas'\\n elif table_name in self.route_uxxienc_resul:\\n return 'uxxienc_resul'\\n return None\",\n \"def __tablename__(cls) -> str:\\n return inflection.underscore(cls.__name__)\",\n \"def model_definition(self):\\n pass\",\n \"def show_database_structure(self):\\n self.analyze()\\n items = []\\n for model in get_models():\\n names = []\\n # for f, m in model._meta.get_fields_with_model():\\n for f in model._meta.concrete_fields:\\n names.append(f.name)\\n items.append(\\n \\\"{0} : {1}\\\".format(fmn(model), ', '.join(names)))\\n\\n items = sorted(items)\\n return rstgen.ul(items)\",\n \"def create_intermediary_table_model(model):\\n name = model.__name__ + 'Relation'\\n \\n class Meta:\\n db_table = '%s_relation' % model._meta.db_table\\n unique_together = (('tag', 'content_type', 'object_id'),)\\n\\n def obj_unicode(self):\\n return u'%s [%s]' % (self.content_type.get_object_for_this_type(pk=self.object_id), self.tag)\\n \\n # Set up a dictionary to simulate declarations within a class \\n attrs = {\\n '__module__': model.__module__,\\n 'Meta': Meta,\\n 'tag': models.ForeignKey(model, verbose_name=_('tag'), related_name='items'),\\n 'content_type': models.ForeignKey(ContentType, verbose_name=_('content type')),\\n 'object_id': models.PositiveIntegerField(_('object id'), db_index=True),\\n 'content_object': generic.GenericForeignKey('content_type', 'object_id'),\\n '__unicode__': obj_unicode,\\n }\\n\\n return type(name, (models.Model,), attrs)\",\n \"def map_def_classes(self, table):\\n definition = MapperDefinition()\\n for rc in self.get_table_classes(table):\\n splitted = rc.split()\\n abbreviation = \\\" \\\".join(splitted[:-1])\\n course_number = splitted[-1]\\n definition.add(abbreviation, allowed=[course_number])\\n return definition\",\n \"def test_custom_metadata_schema(self):\\n # The use-case for this functionality is to allow using\\n # Foreign Data Wrappers, each with a full set of Django\\n # tables, to copy between databases using SQLAlchemy\\n # and the automatically generation of aldjemy.\\n metadata = MetaData(schema=\\\"arbitrary\\\")\\n sa_models = construct_models(metadata)\\n self.assertEqual(sa_models[Log].__table__.schema, \\\"arbitrary\\\")\",\n \"def fetchall(self):\\n rows = self.cursor.fetchall()\\n\\n if self.model.single:\\n for row in rows:\\n yield self.__instance_from_db(self.model, row)\\n else:\\n for row in rows:\\n yield tuple(self.__instance_from_db(m, row) for m in self.model.models)\",\n \"def __new__(cls, name, bases, ns):\\n newbases = []\\n table = None\\n namer = None\\n\\n for base in bases:\\n if isinstance(base, fromTable):\\n if table is not None:\\n raise RuntimeError(\\n \\\"Can't define a class from two or more tables at once.\\\"\\n )\\n table = base.table\\n elif getattr(base, \\\"table\\\", None) is not None:\\n raise RuntimeError(\\n \\\"Can't define a record class by inheriting one already \\\"\\n \\\"mapped to a table.\\\"\\n # TODO: more info\\n )\\n else:\\n if namer is None:\\n if isinstance(base, _RecordMeta):\\n namer = base\\n newbases.append(base)\\n\\n if table is not None:\\n attrmap = {}\\n colmap = {}\\n allColumns = list(table)\\n for column in allColumns:\\n attrname = namer.namingConvention(column.model.name)\\n attrmap[attrname] = column\\n colmap[column] = attrname\\n ns.update(table=table, __attrmap__=attrmap, __colmap__=colmap)\\n ns.update(attrmap)\\n\\n return super(_RecordMeta, cls).__new__(cls, name, tuple(newbases), ns)\",\n \"def __init__(self, name, sequence_number):\\n super(SQLTableIdentifier, self).__init__()\\n self.name = name\\n self.sequence_number = sequence_number\",\n \"def create_tables(self):\\n tables = {}\\n for cls in find_sql_models():\\n table = cls.__table__\\n if table is None:\\n table = cls.__table__ = create_table(cls, self.metadata)\\n if not table.metadata.bind:\\n table.metadata.bind = SQLBinding(manager=self, table=table)\\n tables[cls] = table\\n return tables\",\n \"def init_models(self):\\n from ron import Application\\n from ron.models.basemodel import BaseModel\\n if self.models == None or not Application().db:\\n return\\n models_namespace = self.__namespace + \\\".models\\\" # TODO: allow customize this\\n try:\\n models_package = import_module(models_namespace)\\n except:\\n models_package = None\\n if models_package:\\n models_modules = self._get_package_modules(models_package)\\n for model_name in models_modules:\\n imported_model = import_module('.' + model_name, package=models_namespace)\\n for i in dir(imported_model):\\n attribute = getattr(imported_model, i)\\n if inspect.isclass(attribute) and issubclass(attribute, BaseModel):\\n self.models.append(attribute)\\n Application().db().database.create_tables(self.models)\",\n \"def _create_tables_classic(self, engine, metadata):\\n if engine and metadata:\\n with (yield from engine) as conn:\\n for x in self._models.values():\\n try:\\n yield from conn.execute(CreateTable(x))\\n except ProgrammingError as error:\\n if hasattr(self.app, 'log') and self.app.log:\\n if self.app.debug:\\n self.app.log.info(\\\"[PostgressPlugin] [ `{}` already exists]\\\".format(x))\\n else:\\n if self.app.debug:\\n print(\\\"[PostgressPlugin] [ `{}` already exists]\\\".format(x))\\n return\",\n \"def GenMetaTableParam(a_name):\\n table_param = Table_Param()\\n if a_name == \\\"meta\\\":\\n table_param.NAME = meta_table_name\\n table_param.COLS = \\\\\\n (Column(\\\"version\\\", String(50), primary_key=True, index=False),\\n Column('site', String),\\n Column('pairDbFile', String),\\n Column('dumpType', String),\\n Column('lock', Integer),\\n Column('prNumber', String),\\n Column('kbUrl', String),\\n Column('desc', String))\\n if a_name == \\\"fixby\\\":\\n table_param.NAME = fixby_table_name\\n table_param.COLS = \\\\\\n (Column(\\\"id\\\", Integer, primary_key=True), # will auto increase\\n Column('module', String),\\n Column('desc', String))\\n\\n return table_param\",\n \"def build_metadata():\\n metadata = sa.MetaData()\\n\\n sa.Table(\\n 'hive_blocks', metadata,\\n sa.Column('num', sa.Integer, primary_key=True, autoincrement=False),\\n sa.Column('hash', CHAR(40), nullable=False),\\n sa.Column('prev', CHAR(40)),\\n sa.Column('txs', SMALLINT, server_default='0', nullable=False),\\n sa.Column('ops', SMALLINT, server_default='0', nullable=False),\\n sa.Column('created_at', sa.DateTime, nullable=False),\\n\\n sa.UniqueConstraint('hash', name='hive_blocks_ux1'),\\n sa.ForeignKeyConstraint(['prev'], ['hive_blocks.hash'], name='hive_blocks_fk1'),\\n )\\n\\n sa.Table(\\n 'hive_accounts', metadata,\\n sa.Column('id', sa.Integer, primary_key=True),\\n sa.Column('name', VARCHAR(16), nullable=False),\\n sa.Column('created_at', sa.DateTime, nullable=False),\\n #sa.Column('block_num', sa.Integer, nullable=False),\\n sa.Column('reputation', sa.Float(precision=6), nullable=False, server_default='25'),\\n\\n sa.Column('display_name', sa.String(20)),\\n sa.Column('about', sa.String(160)),\\n sa.Column('location', sa.String(30)),\\n sa.Column('website', sa.String(100)),\\n sa.Column('profile_image', sa.String(1024), nullable=False, server_default=''),\\n sa.Column('cover_image', sa.String(1024), nullable=False, server_default=''),\\n\\n sa.Column('followers', sa.Integer, nullable=False, server_default='0'),\\n sa.Column('following', sa.Integer, nullable=False, server_default='0'),\\n\\n sa.Column('proxy', VARCHAR(16), nullable=False, server_default=''),\\n sa.Column('post_count', sa.Integer, nullable=False, server_default='0'),\\n sa.Column('proxy_weight', sa.Float(precision=6), nullable=False, server_default='0'),\\n sa.Column('vote_weight', sa.Float(precision=6), nullable=False, server_default='0'),\\n sa.Column('kb_used', sa.Integer, nullable=False, server_default='0'), # deprecated\\n sa.Column('rank', sa.Integer, nullable=False, server_default='0'),\\n\\n sa.Column('lastread_at', sa.DateTime, nullable=False, server_default='1970-01-01 00:00:00'),\\n sa.Column('active_at', sa.DateTime, nullable=False, server_default='1970-01-01 00:00:00'),\\n sa.Column('cached_at', sa.DateTime, nullable=False, server_default='1970-01-01 00:00:00'),\\n sa.Column('raw_json', sa.Text),\\n\\n\\n sa.UniqueConstraint('name', name='hive_accounts_ux1'),\\n sa.Index('hive_accounts_ix1', 'vote_weight', 'id'), # core: quick ranks\\n sa.Index('hive_accounts_ix2', 'name', 'id'), # core: quick id map\\n sa.Index('hive_accounts_ix3', 'vote_weight', 'name', postgresql_ops=dict(name='varchar_pattern_ops')), # API: lookup\\n sa.Index('hive_accounts_ix4', 'id', 'name'), # API: quick filter/sort\\n sa.Index('hive_accounts_ix5', 'cached_at', 'name'), # core/listen sweep\\n )\\n\\n sa.Table(\\n 'hive_posts', metadata,\\n sa.Column('id', sa.Integer, primary_key=True),\\n sa.Column('parent_id', sa.Integer),\\n sa.Column('author', VARCHAR(16), nullable=False),\\n sa.Column('permlink', VARCHAR(255), nullable=False),\\n sa.Column('category', VARCHAR(255), nullable=False, server_default=''),\\n sa.Column('community_id', sa.Integer, nullable=True),\\n sa.Column('created_at', sa.DateTime, nullable=False),\\n sa.Column('depth', SMALLINT, nullable=False),\\n sa.Column('is_deleted', BOOLEAN, nullable=False, server_default='0'),\\n sa.Column('is_pinned', BOOLEAN, nullable=False, server_default='0'),\\n sa.Column('is_muted', BOOLEAN, nullable=False, server_default='0'),\\n sa.Column('is_valid', BOOLEAN, nullable=False, server_default='1'),\\n sa.Column('promoted', sa.types.DECIMAL(10, 3), nullable=False, server_default='0'),\\n\\n sa.ForeignKeyConstraint(['author'], ['hive_accounts.name'], name='hive_posts_fk1'),\\n sa.ForeignKeyConstraint(['parent_id'], ['hive_posts.id'], name='hive_posts_fk3'),\\n sa.UniqueConstraint('author', 'permlink', name='hive_posts_ux1'),\\n sa.Index('hive_posts_ix3', 'author', 'depth', 'id', postgresql_where=sql_text(\\\"is_deleted = '0'\\\")), # API: author blog/comments\\n sa.Index('hive_posts_ix4', 'parent_id', 'id', postgresql_where=sql_text(\\\"is_deleted = '0'\\\")), # API: fetching children\\n sa.Index('hive_posts_ix5', 'id', postgresql_where=sql_text(\\\"is_pinned = '1' AND is_deleted = '0'\\\")), # API: pinned post status\\n sa.Index('hive_posts_ix6', 'community_id', 'id', postgresql_where=sql_text(\\\"community_id IS NOT NULL AND is_pinned = '1' AND is_deleted = '0'\\\")), # API: community pinned\\n )\\n\\n sa.Table(\\n 'hive_post_tags', metadata,\\n sa.Column('post_id', sa.Integer, nullable=False),\\n sa.Column('tag', sa.String(32), nullable=False),\\n sa.UniqueConstraint('tag', 'post_id', name='hive_post_tags_ux1'), # core\\n sa.Index('hive_post_tags_ix1', 'post_id'), # core\\n )\\n\\n sa.Table(\\n 'hive_follows', metadata,\\n sa.Column('follower', sa.Integer, nullable=False),\\n sa.Column('following', sa.Integer, nullable=False),\\n sa.Column('state', SMALLINT, nullable=False, server_default='1'),\\n sa.Column('created_at', sa.DateTime, nullable=False),\\n\\n sa.UniqueConstraint('following', 'follower', name='hive_follows_ux3'), # core\\n sa.Index('hive_follows_ix5a', 'following', 'state', 'created_at', 'follower'),\\n sa.Index('hive_follows_ix5b', 'follower', 'state', 'created_at', 'following'),\\n )\\n\\n sa.Table(\\n 'hive_reblogs', metadata,\\n sa.Column('account', VARCHAR(16), nullable=False),\\n sa.Column('post_id', sa.Integer, nullable=False),\\n sa.Column('created_at', sa.DateTime, nullable=False),\\n\\n sa.ForeignKeyConstraint(['account'], ['hive_accounts.name'], name='hive_reblogs_fk1'),\\n sa.ForeignKeyConstraint(['post_id'], ['hive_posts.id'], name='hive_reblogs_fk2'),\\n sa.UniqueConstraint('account', 'post_id', name='hive_reblogs_ux1'), # core\\n sa.Index('hive_reblogs_ix1', 'post_id', 'account', 'created_at'), # API -- not yet used\\n )\\n\\n sa.Table(\\n 'hive_payments', metadata,\\n sa.Column('id', sa.Integer, primary_key=True),\\n sa.Column('block_num', sa.Integer, nullable=False),\\n sa.Column('tx_idx', SMALLINT, nullable=False),\\n sa.Column('post_id', sa.Integer, nullable=False),\\n sa.Column('from_account', sa.Integer, nullable=False),\\n sa.Column('to_account', sa.Integer, nullable=False),\\n sa.Column('amount', sa.types.DECIMAL(10, 3), nullable=False),\\n sa.Column('token', VARCHAR(5), nullable=False),\\n\\n sa.ForeignKeyConstraint(['from_account'], ['hive_accounts.id'], name='hive_payments_fk1'),\\n sa.ForeignKeyConstraint(['to_account'], ['hive_accounts.id'], name='hive_payments_fk2'),\\n sa.ForeignKeyConstraint(['post_id'], ['hive_posts.id'], name='hive_payments_fk3'),\\n )\\n\\n sa.Table(\\n 'hive_feed_cache', metadata,\\n sa.Column('post_id', sa.Integer, nullable=False),\\n sa.Column('account_id', sa.Integer, nullable=False),\\n sa.Column('created_at', sa.DateTime, nullable=False),\\n sa.UniqueConstraint('post_id', 'account_id', name='hive_feed_cache_ux1'), # core\\n sa.Index('hive_feed_cache_ix1', 'account_id', 'post_id', 'created_at'), # API (and rebuild?)\\n )\\n\\n sa.Table(\\n 'hive_posts_cache', metadata,\\n sa.Column('post_id', sa.Integer, primary_key=True, autoincrement=False),\\n sa.Column('author', VARCHAR(16), nullable=False),\\n sa.Column('permlink', VARCHAR(255), nullable=False),\\n sa.Column('category', VARCHAR(255), nullable=False, server_default=''),\\n\\n # important/index\\n sa.Column('community_id', sa.Integer, nullable=True),\\n sa.Column('depth', SMALLINT, nullable=False, server_default='0'),\\n sa.Column('children', SMALLINT, nullable=False, server_default='0'),\\n\\n # basic/extended-stats\\n sa.Column('author_rep', sa.Float(precision=6), nullable=False, server_default='0'),\\n sa.Column('flag_weight', sa.Float(precision=6), nullable=False, server_default='0'),\\n sa.Column('total_votes', sa.Integer, nullable=False, server_default='0'),\\n sa.Column('up_votes', sa.Integer, nullable=False, server_default='0'),\\n\\n # basic ui fields\\n sa.Column('title', sa.String(255), nullable=False, server_default=''),\\n sa.Column('preview', sa.String(1024), nullable=False, server_default=''),\\n sa.Column('img_url', sa.String(1024), nullable=False, server_default=''),\\n\\n # core stats/indexes\\n sa.Column('payout', sa.types.DECIMAL(10, 3), nullable=False, server_default='0'),\\n sa.Column('promoted', sa.types.DECIMAL(10, 3), nullable=False, server_default='0'),\\n sa.Column('created_at', sa.DateTime, nullable=False, server_default='1990-01-01'),\\n sa.Column('payout_at', sa.DateTime, nullable=False, server_default='1990-01-01'),\\n sa.Column('updated_at', sa.DateTime, nullable=False, server_default='1990-01-01'),\\n sa.Column('is_paidout', BOOLEAN, nullable=False, server_default='0'),\\n\\n # ui flags/filters\\n sa.Column('is_nsfw', BOOLEAN, nullable=False, server_default='0'),\\n sa.Column('is_declined', BOOLEAN, nullable=False, server_default='0'),\\n sa.Column('is_full_power', BOOLEAN, nullable=False, server_default='0'),\\n sa.Column('is_hidden', BOOLEAN, nullable=False, server_default='0'),\\n sa.Column('is_grayed', BOOLEAN, nullable=False, server_default='0'),\\n\\n # important indexes\\n sa.Column('rshares', sa.BigInteger, nullable=False, server_default='0'),\\n sa.Column('sc_trend', sa.Float(precision=6), nullable=False, server_default='0'),\\n sa.Column('sc_hot', sa.Float(precision=6), nullable=False, server_default='0'),\\n\\n # bulk data\\n sa.Column('body', TEXT),\\n sa.Column('votes', TEXT),\\n sa.Column('json', sa.Text),\\n sa.Column('raw_json', sa.Text),\\n\\n # index: misc\\n sa.Index('hive_posts_cache_ix3', 'payout_at', 'post_id', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # core: payout sweep\\n sa.Index('hive_posts_cache_ix8', 'category', 'payout', 'depth', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # API: tag stats\\n\\n # index: ranked posts\\n sa.Index('hive_posts_cache_ix2', 'promoted', postgresql_where=sql_text(\\\"is_paidout = '0' AND promoted > 0\\\")), # API: promoted\\n\\n sa.Index('hive_posts_cache_ix6a', 'sc_trend', 'post_id', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # API: trending todo: depth=0\\n sa.Index('hive_posts_cache_ix7a', 'sc_hot', 'post_id', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # API: hot todo: depth=0\\n sa.Index('hive_posts_cache_ix6b', 'post_id', 'sc_trend', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # API: trending, filtered todo: depth=0\\n sa.Index('hive_posts_cache_ix7b', 'post_id', 'sc_hot', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # API: hot, filtered todo: depth=0\\n\\n sa.Index('hive_posts_cache_ix9a', 'depth', 'payout', 'post_id', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # API: payout todo: rem depth\\n sa.Index('hive_posts_cache_ix9b', 'category', 'depth', 'payout', 'post_id', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # API: payout, filtered todo: rem depth\\n\\n sa.Index('hive_posts_cache_ix10', 'post_id', 'payout', postgresql_where=sql_text(\\\"is_grayed = '1' AND payout > 0\\\")), # API: muted, by filter/date/payout\\n\\n # index: stats\\n sa.Index('hive_posts_cache_ix20', 'community_id', 'author', 'payout', 'post_id', postgresql_where=sql_text(\\\"is_paidout = '0'\\\")), # API: pending distribution; author payout\\n\\n # index: community ranked posts\\n sa.Index('hive_posts_cache_ix30', 'community_id', 'sc_trend', 'post_id', postgresql_where=sql_text(\\\"community_id IS NOT NULL AND is_grayed = '0' AND depth = 0\\\")), # API: community trend\\n sa.Index('hive_posts_cache_ix31', 'community_id', 'sc_hot', 'post_id', postgresql_where=sql_text(\\\"community_id IS NOT NULL AND is_grayed = '0' AND depth = 0\\\")), # API: community hot\\n sa.Index('hive_posts_cache_ix32', 'community_id', 'created_at', 'post_id', postgresql_where=sql_text(\\\"community_id IS NOT NULL AND is_grayed = '0' AND depth = 0\\\")), # API: community created\\n sa.Index('hive_posts_cache_ix33', 'community_id', 'payout', 'post_id', postgresql_where=sql_text(\\\"community_id IS NOT NULL AND is_grayed = '0' AND is_paidout = '0'\\\")), # API: community payout\\n sa.Index('hive_posts_cache_ix34', 'community_id', 'payout', 'post_id', postgresql_where=sql_text(\\\"community_id IS NOT NULL AND is_grayed = '1' AND is_paidout = '0'\\\")), # API: community muted\\n )\\n\\n sa.Table(\\n 'hive_state', metadata,\\n sa.Column('block_num', sa.Integer, primary_key=True, autoincrement=False),\\n sa.Column('db_version', sa.Integer, nullable=False),\\n sa.Column('steem_per_mvest', sa.types.DECIMAL(8, 3), nullable=False),\\n sa.Column('usd_per_steem', sa.types.DECIMAL(8, 3), nullable=False),\\n sa.Column('sbd_per_steem', sa.types.DECIMAL(8, 3), nullable=False),\\n sa.Column('dgpo', sa.Text, nullable=False),\\n )\\n\\n metadata = build_metadata_community(metadata)\\n\\n metadata = build_metadata_blacklist(metadata)\\n\\n metadata = build_trxid_block_num(metadata)\\n\\n return metadata\",\n \"def meta(self) -> api.Meta:\\n return self._get_model(model=api.Meta)\",\n \"def test_extraction_with_model_class(self: Any, mock_method: Any) -> None:\\n config_dict = {\\n 'extractor.sqlalchemy.conn_string': 'TEST_CONNECTION',\\n 'extractor.sqlalchemy.extract_sql': 'SELECT 1 FROM TEST_TABLE;',\\n 'extractor.sqlalchemy.model_class':\\n 'tests.unit.extractor.test_sql_alchemy_extractor.TableMetadataResult'\\n }\\n self.conf = ConfigFactory.from_dict(config_dict)\\n\\n extractor = SQLAlchemyExtractor()\\n extractor.results = [dict(database='test_database',\\n schema='test_schema',\\n name='test_table',\\n description='test_description',\\n column_name='test_column_name',\\n column_type='test_column_type',\\n column_comment='test_column_comment',\\n owner='test_owner')]\\n\\n extractor.init(Scoped.get_scoped_conf(conf=self.conf,\\n scope=extractor.get_scope()))\\n\\n result = extractor.extract()\\n\\n self.assertIsInstance(result, TableMetadataResult)\\n self.assertEqual(result.name, 'test_table')\",\n \"def __sanitizeMetaModelName( self, name ):\\r\\n if( name[-5:] == '_META' ): \\r\\n return name[:-5]\\r\\n else: return name\",\n \"def base_fields(self):\\n if not self.model:\\n raise NameError('database model has not been set.')\\n\\n with self.session() as session:\\n query = self.get_query(session, [self.model.pkId, self.model.created, self.model.modified])\\n data = query.order_by(self.model.pkId).all()\\n return data\",\n \"def declarative_base(model):\\n for parent in model.__bases__:\\n try:\\n parent.metadata\\n return declarative_base(parent)\\n except AttributeError:\\n pass\\n return model\",\n \"def _load_db(self):\\n for type_ in self._types:\\n try:\\n type_.table(self._metadata)\\n except InvalidRequestError:\\n pass\\n # Reflect metadata so auto-mapping works\\n self._metadata.reflect(self._engine)\\n # Make sure the tables exist\\n self._metadata.create_all()\",\n \"def __table_cls__(cls, *args, **kwargs):\\n # check if a table with this name already exists\\n # allows reflected tables to be applied to model by name\\n key = _get_table_key(args[0], kwargs.get('schema'))\\n\\n if key in cls.metadata.tables:\\n return sa.Table(*args, **kwargs)\\n\\n # if a primary key or constraint is found, create a table for\\n # joined-table inheritance\\n for arg in args:\\n is_pk_column = isinstance(arg, sa.Column) and arg.primary_key\\n is_pk_constraint = isinstance(arg, sa.PrimaryKeyConstraint)\\n if is_pk_column or is_pk_constraint:\\n return sa.Table(*args, **kwargs)\\n\\n # if no base classes define a table, return one\\n # ensures the correct error shows up when missing a primary key\\n for base in cls.__mro__[1:-1]:\\n if '__table__' in base.__dict__:\\n break\\n else:\\n return sa.Table(*args, **kwargs)\\n\\n # single-table inheritance, use the parent tablename\\n if '__tablename__' in cls.__dict__:\\n del cls.__tablename__\",\n \"def __init__(self):\\n engine = connect_to_db()\\n create_lyrics_table(engine) #declarative base stuff\\n self.Session = sessionmaker(bind=engine)\\n\\n # self.create_connection()\\n # self.create_table()\",\n \"def test_field_names(self):\\n\\n for mb_model in self.mb_model_list:\\n mb_fields = mb_model._meta.fields\\n db_cols = connection.introspection.get_table_description(\\n self.cursor, mb_model._meta.db_table)\\n\\n for i in range(0, len(mb_model._meta.fields)):\\n self.assertEqual(\\n mb_fields[i].column,\\n db_cols[i].name\\n )\",\n \"def __init__(self,):\\n self.logger = conf._init_logger(logger=conf.LOGGER_ORM)\\n self.logger = logging.getLogger(conf.LOGGER_ORM)\\n\\n self.logger.info(\\\"[+] Initilizing Orm [+]\\\")\\n\\n\\n self.engine = sqlalchemy.create_engine(\\n f\\\"mysql+mysqldb://{conf.DB_USER}:{conf.DB_PASSWORD}@{conf.DB_ADRESS}/{conf.DB_NAME}\\\")\\n self.metadata = sqlalchemy.MetaData(bind=self.engine)\\n self.metadata.reflect(only=[\\\"examens\\\", \\\"sections\\\", \\\"patients\\\", \\\"medecins\\\", \\\"types_intervention\\\"])\\n self.conn = self.engine.connect()\\n \\\"\\\"\\\"\\n Load the ORM of different table into the class\\n \\\"\\\"\\\"\\n self.check_table()\\n self.hl7_connections = sqlalchemy.Table(\\\"hl7_connections\\\", self.metadata)\\n self.examens = sqlalchemy.Table(\\\"examens\\\", self.metadata)\\n self.sections = sqlalchemy.Table(\\\"sections\\\", self.metadata)\\n self.patients = sqlalchemy.Table(\\\"patients\\\", self.metadata)\\n self.medecins = sqlalchemy.Table(\\\"medecins\\\", self.metadata)\\n self.types_interventions = sqlalchemy.Table(\\\"types_intervention\\\", self.metadata)\\n self.logger.info(\\\"[+] Orm initialized [+]\\\")\",\n \"def items(self):\\r\\n for column in self.table.columns:\\r\\n yield (column, self[column.name])\",\n \"def get_table_metadata(self, a_table_name):\\n \\n self.connect()\\n\\n # create MetaData \\n meta = sqlalchemy.MetaData()\\n\\n # bind to an engine\\n meta.bind = self._engine\\n\\n table_metadata = sqlalchemy.Table(a_table_name, meta, autoload = True)\\n\\n cols = [] \\n\\n for col in table_metadata.columns:\\n desc = {}\\n desc['name'] = col.name\\n desc['type'] = col.type\\n desc['nullable'] = col.nullable\\n cols.append(desc)\\n\\n # a dictionary of dict, one dict for each row\\n return cols\",\n \"def transform(self, sql):\\n # Start from scratch.\\n self.clear()\\n # Parse the SQL into the internal structure.\\n self.parse(sql)\\n\\n # Create an empty list of linus in the output.\\n puml_lines = list()\\n # Run through all tables.\\n for table_name, table in self.puml_tables.items():\\n # Add PUML code for the beggining of the table.\\n puml_lines.append('table({}) '.format(table_name) + '{')\\n\\n # Add PUML lines for all primary keys.\\n for cname, ctype in table['primary'].items():\\n puml_lines.append('\\\\tprimary_key({}) {}'.format(cname, ctype))\\n\\n # Add PUML lines for all foreign keys.\\n for cname, cval in table['foreign'].items():\\n puml_lines.append('\\\\tforeign_key({},{}) {}'.format(cname, cval[1], cval[0]))\\n\\n # Add separator if there is regular columns.\\n if len(table['default'].keys()) > 0:\\n puml_lines.append('\\\\t---')\\n\\n # Add regular columns.\\n for cname, ctype in table['default'].items():\\n puml_lines.append('\\\\t{} {}'.format(cname, ctype))\\n\\n # Close the table.\\n puml_lines.append('}')\\n # Add a single empty line.\\n puml_lines.append('')\\n\\n # Run through all foreign keys and crete the table relations.\\n for table_name, table in self.puml_tables.items():\\n for fk in table['foreign'].values():\\n puml_lines.append('{} \\\"0..n\\\" -- \\\"1..1\\\" {}'.format(table_name, fk[1].split('.')[0]))\\n\\n # Add a single empty line.\\n puml_lines.append('')\\n\\n # Join all output lines separated by new lines.\\n content = '\\\\n'.join(puml_lines)\\n\\n # Return the final PUML string.\\n return (self.puml_template.format(content))\",\n \"def _tables(self):\\n assert False, \\\"subclass responsibility\\\"\",\n \"def gen_model():\\n\\n\\tmodel = skipthoughts.load_model()\\n\\treturn model\",\n \"def model(self) -> str:\\n ...\",\n \"def table_name(self) -> str:\\n return self.model._meta.db_table\",\n \"def build_model():\",\n \"def apply_model(engine):\\n Base.metadata.create_all(engine)\",\n \"def __new__(cls, name, bases, attrs):\\n if name == 'Model':\\n return type.__new__(cls, name, bases, attrs)\\n table_name = name\\n primary_key = None\\n fields = []\\n column_to_filed = dict()\\n for k, v in attrs.items():\\n if isinstance(v, Field):\\n column_to_filed[k] = v\\n if v.primary_key:\\n if primary_key:\\n raise NameError('Primary key should only be one.')\\n else:\\n primary_key = k\\n else:\\n fields.append(k)\\n if primary_key is None:\\n raise NameError('Primary key not found.')\\n # Delete the class attributes which is belong to `Field` object.\\n # Because the class attributes may be overide by the same name of \\n # the class instance attributes.\\n for key in column_to_filed:\\n attrs.pop(key)\\n\\n attrs['PRIMARY_KEY'] = primary_key\\n attrs['COLUMN_TO_FILED'] = column_to_filed\\n attrs['TABLE_NAME'] = table_name\\n return type.__new__(cls, name, bases, attrs)\",\n \"def _related_fields(self):\\r\\n model_class, m2m = self._get_model_class_from_table(self.model._meta.db_table) \\r\\n related_fields = {\\r\\n self.model._meta.pk.attname: model_class\\r\\n }\\r\\n for attname, model_class in self._get_related_models(self.model):\\r\\n related_fields[attname] = model_class\\r\\n return related_fields\",\n \"def bootstrap():\\n Base.metadata.create_all(engine)\",\n \"def table_name(class_):\\n try:\\n return class_.__tablename__\\n except AttributeError:\\n return class_.__table__.name\",\n \"def _define_tables(self):\\n metadata = MetaData(bind=self.engine)\\n Base = declarative_base(metadata=metadata)\\n\\n class Dataset(Base):\\n __tablename__ = 'datasets'\\n\\n id = Column(Integer, primary_key=True, autoincrement=True)\\n name = Column(String(100), nullable=False)\\n\\n # columns necessary for loading/processing data\\n class_column = Column(String(100), nullable=False)\\n train_path = Column(String(200), nullable=False)\\n test_path = Column(String(200))\\n description = Column(String(1000))\\n\\n # metadata columns, for convenience\\n n_examples = Column(Integer, nullable=False)\\n k_classes = Column(Integer, nullable=False)\\n d_features = Column(Integer, nullable=False)\\n majority = Column(Numeric(precision=10, scale=9), nullable=False)\\n size_kb = Column(Integer, nullable=False)\\n\\n def __repr__(self):\\n base = \\\"<%s: %s, %d classes, %d features, %d rows>\\\"\\n return base % (self.name, self.description, self.k_classes,\\n self.d_features, self.n_examples)\\n\\n class Datarun(Base):\\n __tablename__ = 'dataruns'\\n\\n # relational columns\\n id = Column(Integer, primary_key=True, autoincrement=True)\\n dataset_id = Column(Integer, ForeignKey('datasets.id'))\\n dataset = relationship('Dataset', back_populates='dataruns')\\n\\n description = Column(String(200), nullable=False)\\n priority = Column(Integer)\\n\\n # hyperparameter selection and tuning settings\\n selector = Column(String(200), nullable=False)\\n k_window = Column(Integer)\\n tuner = Column(String(200), nullable=False)\\n gridding = Column(Integer, nullable=False)\\n r_minimum = Column(Integer)\\n\\n # budget settings\\n budget_type = Column(Enum(*BUDGET_TYPES))\\n budget = Column(Integer)\\n deadline = Column(DateTime)\\n\\n # which metric to use for judgment, and how to compute it\\n metric = Column(Enum(*METRICS))\\n score_target = Column(Enum(*[s + '_judgment_metric' for s in\\n SCORE_TARGETS]))\\n\\n # variables that store the status of the datarun\\n start_time = Column(DateTime)\\n end_time = Column(DateTime)\\n status = Column(Enum(*DATARUN_STATUS), default=RunStatus.PENDING)\\n\\n def __repr__(self):\\n base = \\\"\\\"\\n return base % (self.id, self.dataset_id, self.description,\\n self.budget_type, self.budget, self.status)\\n\\n Dataset.dataruns = relationship('Datarun', order_by='Datarun.id',\\n back_populates='dataset')\\n\\n class Hyperpartition(Base):\\n __tablename__ = 'hyperpartitions'\\n\\n # relational columns\\n id = Column(Integer, primary_key=True, autoincrement=True)\\n datarun_id = Column(Integer, ForeignKey('dataruns.id'))\\n datarun = relationship('Datarun', back_populates='hyperpartitions')\\n\\n # name of or path to a configured classification method\\n method = Column(String(255))\\n\\n # list of categorical parameters whose values are fixed to define\\n # this hyperpartition\\n categorical_hyperparameters_64 = Column(Text)\\n\\n # list of continuous parameters which are not fixed; their values\\n # must be selected by a Tuner\\n tunable_hyperparameters_64 = Column(Text)\\n\\n # list of categorical or continuous parameters whose values are\\n # always fixed. These do not define the hyperpartition, but their\\n # values must be passed on to the method. Here for convenience.\\n constant_hyperparameters_64 = Column(Text)\\n\\n # has the partition had too many errors, or is gridding done?\\n status = Column(Enum(*PARTITION_STATUS),\\n default=PartitionStatus.INCOMPLETE)\\n\\n @property\\n def categoricals(self):\\n \\\"\\\"\\\"\\n A list of categorical variables along with the fixed values\\n which define this hyperpartition.\\n Each element is a ('name', HyperParameter) tuple.\\n \\\"\\\"\\\"\\n return base_64_to_object(self.categorical_hyperparameters_64)\\n\\n @categoricals.setter\\n def categoricals(self, value):\\n self.categorical_hyperparameters_64 = object_to_base_64(value)\\n\\n @property\\n def tunables(self):\\n \\\"\\\"\\\"\\n A list of parameters which are unspecified and must be selected\\n with a Tuner. Each element is a ('name', HyperParameter) tuple.\\n \\\"\\\"\\\"\\n return base_64_to_object(self.tunable_hyperparameters_64)\\n\\n @tunables.setter\\n def tunables(self, value):\\n self.tunable_hyperparameters_64 = object_to_base_64(value)\\n\\n @property\\n def constants(self):\\n return base_64_to_object(self.constant_hyperparameters_64)\\n\\n @constants.setter\\n def constants(self, value):\\n self.constant_hyperparameters_64 = object_to_base_64(value)\\n\\n def __repr__(self):\\n return \\\"<%s: %s>\\\" % (self.method, self.categoricals)\\n\\n Datarun.hyperpartitions = relationship('Hyperpartition',\\n order_by='Hyperpartition.id',\\n back_populates='datarun')\\n\\n class Classifier(Base):\\n __tablename__ = 'classifiers'\\n\\n # relational columns\\n id = Column(Integer, primary_key=True, autoincrement=True)\\n datarun_id = Column(Integer, ForeignKey('dataruns.id'))\\n datarun = relationship('Datarun', back_populates='classifiers')\\n hyperpartition_id = Column(Integer, ForeignKey('hyperpartitions.id'))\\n hyperpartition = relationship('Hyperpartition',\\n back_populates='classifiers')\\n\\n # name of the host where the model was trained\\n host = Column(String(50))\\n\\n # these columns point to where the output is stored\\n model_location = Column(String(300))\\n metrics_location = Column(String(300))\\n\\n # base 64 encoding of the hyperparameter names and values\\n hyperparameter_values_64 = Column(Text, nullable=False)\\n\\n # performance metrics\\n cv_judgment_metric = Column(Numeric(precision=20, scale=10))\\n cv_judgment_metric_stdev = Column(Numeric(precision=20, scale=10))\\n test_judgment_metric = Column(Numeric(precision=20, scale=10))\\n\\n start_time = Column(DateTime)\\n end_time = Column(DateTime)\\n status = Column(Enum(*CLASSIFIER_STATUS), nullable=False)\\n error_message = Column(Text)\\n\\n @property\\n def hyperparameter_values(self):\\n return base_64_to_object(self.hyperparameter_values_64)\\n\\n @hyperparameter_values.setter\\n def hyperparameter_values(self, value):\\n self.hyperparameter_values_64 = object_to_base_64(value)\\n\\n @property\\n def mu_sigma_judgment_metric(self):\\n # compute the lower confidence bound on the cross-validated\\n # judgment metric\\n if self.cv_judgment_metric is None:\\n return None\\n return (self.cv_judgment_metric - 2 *\\n self.cv_judgment_metric_stdev)\\n\\n def __repr__(self):\\n params = ', '.join(['%s: %s' % i for i in\\n list(self.hyperparameter_values.items())])\\n return \\\"\\\" % (self.id, params)\\n\\n Datarun.classifiers = relationship('Classifier',\\n order_by='Classifier.id',\\n back_populates='datarun')\\n Hyperpartition.classifiers = relationship('Classifier',\\n order_by='Classifier.id',\\n back_populates='hyperpartition')\\n\\n self.Dataset = Dataset\\n self.Datarun = Datarun\\n self.Hyperpartition = Hyperpartition\\n self.Classifier = Classifier\\n\\n Base.metadata.create_all(bind=self.engine)\",\n \"def _generate_rowklass(self):\\n header = six.next(self.resolved)\\n clean = []\\n for h in header:\\n underscoreless = h.strip().lower().replace(' ', '_').replace('.', '_')\\n specialless = underscoreless.replace('(', '').replace(')', '').replace('?', '').replace('-', '')\\n if specialless == '':\\n clean.append(specialless)\\n continue\\n try:\\n num = int(specialless[0])\\n numbers = {1: 'one', 2: 'two', 3: 'three', 4: 'four', 5: 'five',\\n 6: 'six', 7: 'seven', 8: 'eight', 9: 'nine', 10: 'ten'}\\n numless = numbers[num] + specialless[1:]\\n cleaned = numless\\n except ValueError:\\n cleaned = specialless\\n\\n more = 1\\n while cleaned in clean:\\n more += 1\\n cleaned += str(more)\\n\\n clean.append(cleaned)\\n\\n for i, v in enumerate(clean):\\n if v == '':\\n clean[i] = 'field_' + str(i)\\n self.rowklass = collections.namedtuple('RowKlass', clean)\",\n \"def make_tables(self):\\n for t in self.tables:\\n self.add_table(groupname=t['groupname'],\\n tablename=t['tablename'],\\n description=t['description'],\\n tabletitle=t['tabletitle'])\",\n \"def table(cls):\\n return cls.__name__\",\n \"def test_reflection(self):\\n m = MetaData()\\n\\n t = Table('test_table_syn', m, autoload=True,\\n autoload_with=testing.db, oracle_resolve_synonyms=True)\\n eq_(t.c.keys(), ['id', 'data'])\\n eq_(list(t.primary_key), [t.c.id])\",\n \"def model(self):\",\n \"def model(self):\",\n \"def model(self):\",\n \"def model(self):\",\n \"def model(self):\",\n \"def test_meta_read_write_units(engine):\\n class Model(engine.model):\\n id = Column(UUID, hash_key=True)\\n\\n assert Model.Meta.write_units == 1\\n assert Model.Meta.read_units == 1\\n\\n class Other(engine.model):\\n class Meta:\\n read_units = 2\\n write_units = 3\\n id = Column(UUID, hash_key=True)\\n\\n assert Other.Meta.write_units == 3\\n assert Other.Meta.read_units == 2\",\n \"def get_tables_name_and_type(self) -> Optional[Iterable[Tuple[str, str]]]:\\n try:\\n schema_name = self.context.database_schema.name.__root__\\n if self.source_config.includeTables:\\n for table_and_type in self.query_table_names_and_types(schema_name):\\n table_name = self.standardize_table_name(\\n schema_name, table_and_type.name\\n )\\n table_fqn = fqn.build(\\n self.metadata,\\n entity_type=Table,\\n service_name=self.context.database_service.name.__root__,\\n database_name=self.context.database.name.__root__,\\n schema_name=self.context.database_schema.name.__root__,\\n table_name=table_name,\\n skip_es_search=True,\\n )\\n if filter_by_table(\\n self.source_config.tableFilterPattern,\\n table_fqn\\n if self.source_config.useFqnForFiltering\\n else table_name,\\n ):\\n self.status.filter(\\n table_fqn,\\n \\\"Table Filtered Out\\\",\\n )\\n continue\\n yield table_name, table_and_type.type_\\n\\n if self.source_config.includeViews:\\n for view_name in self.inspector.get_view_names(schema_name):\\n view_name = self.standardize_table_name(schema_name, view_name)\\n view_fqn = fqn.build(\\n self.metadata,\\n entity_type=Table,\\n service_name=self.context.database_service.name.__root__,\\n database_name=self.context.database.name.__root__,\\n schema_name=self.context.database_schema.name.__root__,\\n table_name=view_name,\\n )\\n\\n if filter_by_table(\\n self.source_config.tableFilterPattern,\\n view_fqn\\n if self.source_config.useFqnForFiltering\\n else view_name,\\n ):\\n self.status.filter(\\n view_fqn,\\n \\\"Table Filtered Out\\\",\\n )\\n continue\\n yield view_name, TableType.View\\n except Exception as err:\\n logger.warning(\\n f\\\"Fetching tables names failed for schema {schema_name} due to - {err}\\\"\\n )\\n logger.debug(traceback.format_exc())\",\n \"def create_meta_loan_table(self):\\n table_exists = self.check_if_table_exists(\\\"meta_loan_tables\\\")\\n\\n if not table_exists:\\n self.read_sql_from_file('create_meta_loan_tables.sql')\\n return\",\n \"def create_table(self):\\n pass\",\n \"def meta(self):\\n raise NotImplementedError\",\n \"def _create_TableDescriptor(self):\\n\\n self.conn.cursor.execute(\\\"PRAGMA table_info(\\\" + self.table_name + \\\")\\\")\\n descriptions = self.conn.cursor.fetchall()\\n column_map = {}\\n for description in descriptions:\\n column_map[description[1]] = description[2]\\n td = TD(self.table_name, column_map) \\n\\n# self.conn.cursor.execute(\\\"SELECT sql FROM sqlite_master WHERE name='{tb}'\\\"\\\\\\n# .format(tb=self.table_name))\\n# aa = str(self.conn.cursor.fetchone()[0])\\n# sindx = aa.find(\\\"(\\\")\\n# eindx = aa.find(\\\")\\\")\\n# aa = aa[sindx+1:eindx]\\n# aa = aa.split(\\\",\\\")\\n# column_map = {kyval.split()[0]:kyval.split()[1] for kyval in aa}\\n# td = TD(self.table_name, column_map) \\n\\n return td\",\n \"def iteritems(self):\\r\\n for name in self.table.sequence:\\r\\n if name not in self.table.exclude:\\r\\n yield (name, self.columns[name])\",\n \"def create_translations_model(model, related_name, meta, **fields):\\n if not meta:\\n meta = {}\\n unique = [('language_code', 'master')]\\n meta['unique_together'] = list(meta.get('unique_together', [])) + unique\\n # Create inner Meta class \\n Meta = type('Meta', (object,), meta)\\n name = '%sTranslation' % model.__name__\\n attrs = {}\\n attrs.update(fields)\\n attrs['Meta'] = Meta\\n attrs['__module__'] = model.__module__\\n attrs['language_code'] = models.CharField(max_length=15, db_index=True)\\n # null=True is so we can prevent cascade deletion\\n attrs['master'] = models.ForeignKey(model, related_name=related_name, editable=False, null=True)\\n # Create and return the new model\\n return ModelBase(name, (BaseTranslationModel,), attrs)\",\n \"def create_sqlalchemy_mapperproperties_from_dbfields(cls,modeltable):\\n allprops = {}\\n #\\n for field in cls.fieldlist:\\n props = field.create_sqlalchemy_mapperproperties(cls,modeltable)\\n if (props!=None):\\n allprops.update(props)\\n return allprops\",\n \"def _get_related_models(self, parent_model):\\r\\n related_models = set()\\r\\n rev_reversemapping = dict([(v,k) for k,v in self._reversemapping.iteritems()])\\r\\n if rev_reversemapping:\\r\\n for attname, related in self._get_reverse_relations(parent_model):\\r\\n related_models.add((rev_reversemapping[attname], related.model))\\r\\n\\r\\n for field in parent_model._meta.fields:\\r\\n if field.rel and field.rel.to._meta.db_table in self.query.tables and field.rel.to != parent_model:\\r\\n related_models.add((field.attname, field.rel.to))\\r\\n \\r\\n for attname, model_class in related_models:\\r\\n yield attname, model_class\\r\\n if attname.endswith(\\\"_id\\\"):\\r\\n attname = attname[:-3]\\r\\n for join_attname, model_klass in self._get_related_models(model_class):\\r\\n yield LOOKUP_SEP.join((attname,join_attname)), model_klass\",\n \"def createTables(self):\\n metadata = Base.metadata\\n metadata.create_all(self._engine)\\n return\"\n]"},"negative_scores":{"kind":"list like","value":["0.64038646","0.6319936","0.61308765","0.58914566","0.58779913","0.5795165","0.5719704","0.5694968","0.5619841","0.56065655","0.5591526","0.55195546","0.5389739","0.5318234","0.5304673","0.5291211","0.52884954","0.5279363","0.52785826","0.52544487","0.52321386","0.5231754","0.51996213","0.5188176","0.5153182","0.5127161","0.51235783","0.5121615","0.51210475","0.51104903","0.5098141","0.5093024","0.50921124","0.50882906","0.50874853","0.5072644","0.50653034","0.5060398","0.50589347","0.50584775","0.50556046","0.504214","0.5039316","0.5033422","0.503156","0.50310296","0.5019509","0.5010189","0.50024277","0.4996406","0.4995856","0.498689","0.49776587","0.49748346","0.49667856","0.49625766","0.49619922","0.49606666","0.4935995","0.49358135","0.49252865","0.49195606","0.49020815","0.48896965","0.48801184","0.48798797","0.4871115","0.4865422","0.486283","0.48554373","0.48424825","0.4835274","0.48310938","0.48258653","0.48199356","0.4811632","0.4810126","0.48001617","0.4788581","0.47878593","0.47852796","0.47764406","0.4767456","0.47581908","0.4755629","0.4755629","0.4755629","0.4755629","0.4755629","0.4753293","0.47497863","0.47462967","0.47417814","0.4739125","0.47350904","0.47333884","0.47295207","0.4728654","0.4722144","0.4716221"],"string":"[\n \"0.64038646\",\n \"0.6319936\",\n \"0.61308765\",\n \"0.58914566\",\n \"0.58779913\",\n \"0.5795165\",\n \"0.5719704\",\n \"0.5694968\",\n \"0.5619841\",\n \"0.56065655\",\n \"0.5591526\",\n \"0.55195546\",\n \"0.5389739\",\n \"0.5318234\",\n \"0.5304673\",\n \"0.5291211\",\n \"0.52884954\",\n \"0.5279363\",\n \"0.52785826\",\n \"0.52544487\",\n \"0.52321386\",\n \"0.5231754\",\n \"0.51996213\",\n \"0.5188176\",\n \"0.5153182\",\n \"0.5127161\",\n \"0.51235783\",\n \"0.5121615\",\n \"0.51210475\",\n \"0.51104903\",\n \"0.5098141\",\n \"0.5093024\",\n \"0.50921124\",\n \"0.50882906\",\n \"0.50874853\",\n \"0.5072644\",\n \"0.50653034\",\n \"0.5060398\",\n \"0.50589347\",\n \"0.50584775\",\n \"0.50556046\",\n \"0.504214\",\n \"0.5039316\",\n \"0.5033422\",\n \"0.503156\",\n \"0.50310296\",\n \"0.5019509\",\n \"0.5010189\",\n \"0.50024277\",\n \"0.4996406\",\n \"0.4995856\",\n \"0.498689\",\n \"0.49776587\",\n \"0.49748346\",\n \"0.49667856\",\n \"0.49625766\",\n \"0.49619922\",\n \"0.49606666\",\n \"0.4935995\",\n \"0.49358135\",\n \"0.49252865\",\n \"0.49195606\",\n \"0.49020815\",\n \"0.48896965\",\n \"0.48801184\",\n \"0.48798797\",\n \"0.4871115\",\n \"0.4865422\",\n \"0.486283\",\n \"0.48554373\",\n \"0.48424825\",\n \"0.4835274\",\n \"0.48310938\",\n \"0.48258653\",\n \"0.48199356\",\n \"0.4811632\",\n \"0.4810126\",\n \"0.48001617\",\n \"0.4788581\",\n \"0.47878593\",\n \"0.47852796\",\n \"0.47764406\",\n \"0.4767456\",\n \"0.47581908\",\n \"0.4755629\",\n \"0.4755629\",\n \"0.4755629\",\n \"0.4755629\",\n \"0.4755629\",\n \"0.4753293\",\n \"0.47497863\",\n \"0.47462967\",\n \"0.47417814\",\n \"0.4739125\",\n \"0.47350904\",\n \"0.47333884\",\n \"0.47295207\",\n \"0.4728654\",\n \"0.4722144\",\n \"0.4716221\"\n]"},"document_score":{"kind":"string","value":"0.58967185"},"document_rank":{"kind":"string","value":"3"}}},{"rowIdx":8562,"cells":{"query":{"kind":"string","value":"returns a tuple (Model, geometry_field, geometry_field_type) for a given table in given schema"},"document":{"kind":"string","value":"def get_layer(schema, table_name):\n fn = '{}.{}'.format(schema, table_name)\n if fn not in LAYER_MODELS:\n LAYER_MODELS[fn] = inspect_table(schema, table_name)\n\n return LAYER_MODELS.get(fn)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_geometry_type(self, table_name, description):\n with self.connection.cursor() as cursor:\n cursor.execute(\n \"\"\"\n SELECT t.coord_dimension, t.srid, t.type FROM (\n SELECT * FROM geometry_columns\n UNION ALL\n SELECT * FROM geography_columns\n ) AS t WHERE t.f_table_name = %s AND t.f_geometry_column = %s\n \"\"\",\n (table_name, description.name),\n )\n row = cursor.fetchone()\n if not row:\n raise Exception(\n 'Could not find a geometry or geography column for \"%s\".\"%s\"'\n % (table_name, description.name)\n )\n dim, srid, field_type = row\n # OGRGeomType does not require GDAL and makes it easy to convert\n # from OGC geom type name to Django field.\n field_type = OGRGeomType(field_type).django\n # Getting any GeometryField keyword arguments that are not the default.\n field_params = {}\n if self.postgis_oid_lookup.get(description.type_code) == \"geography\":\n field_params[\"geography\"] = True\n if srid != 4326:\n field_params[\"srid\"] = srid\n if dim != 2:\n field_params[\"dim\"] = dim\n return field_type, field_params","def get_field_type(connection, table_name, row):\n field_params = OrderedDict()\n field_notes = []\n is_geometry = False\n try:\n field_type = connection.introspection.get_field_type(row[1], row)\n except KeyError:\n field_type = 'TextField'\n field_notes.append('This field type is a guess.')\n\n # This is a hook for data_types_reverse to return a tuple of\n # (field_type, field_params_dict).\n if type(field_type) is tuple:\n field_type, new_params = field_type\n field_params.update(new_params)\n\n # Add max_length for all CharFields.\n if field_type == 'CharField' and row[3]:\n field_params['max_length'] = int(row[3])\n\n if field_type == 'DecimalField':\n if row[4] is None or row[5] is None:\n field_notes.append(\n 'max_digits and decimal_places have been guessed, as this '\n 'database handles decimal fields as float')\n field_params['max_digits'] = row[4] if row[4] is not None else 10\n field_params['decimal_places'] = row[\n 5] if row[5] is not None else 5\n else:\n field_params['max_digits'] = row[4]\n field_params['decimal_places'] = row[5]\n\n if field_type == 'GeometryField':\n geo_col = row[0]\n # Getting a more specific field type and any additional parameters\n # from the `get_geometry_type` routine for the spatial backend.\n field_type, geo_params = connection.introspection.get_geometry_type(\n table_name, geo_col)\n field_params.update(geo_params)\n is_geometry = True\n\n return field_type, field_params, is_geometry\n # return getattr(models.fields, field_type), field_params","def get_table_info(self):\n epsg = None\n meta = MetaData()\n table_obj = Table(self.table, meta,\n autoload=True, autoload_with=self.engine)\n if not self.columns:\n self.columns = table_obj.columns.keys()\n geo_cols = [(col.name, col.type) for col in table_obj.columns\n if hasattr(col.type, 'srid')]\n if geo_cols:\n geo_col = geo_cols[0]\n self.geom_column = geo_col[0]\n geo_obj = geo_col[1]\n if self.geom_column not in self.columns:\n self.columns.append(self.geom_column)\n if hasattr(geo_obj, 'srid'):\n epsg = geo_obj.srid\n if epsg == -1:\n epsg = 4326\n if hasattr(geo_obj, 'geometry_type'):\n self.geometry_type = geo_obj.geometry_type\n\n self.epsg = epsg\n self.table_obj = table_obj\n self.meta = meta","def get_table_info(self):\n epsg = None\n meta = MetaData()\n table_obj = Table(self._table, meta,\n autoload=True, autoload_with=self._engine)\n if not self._columns:\n self._columns = table_obj.columns.keys()\n geo_cols = [(col.name, col.type) for col in table_obj.columns\n if hasattr(col.type, 'srid')]\n if geo_cols:\n geo_col = geo_cols[0]\n self._geom_column = geo_col[0]\n geo_obj = geo_col[1]\n if self._geom_column not in self._columns:\n self._columns.append(self._geom_column)\n if hasattr(geo_obj, 'srid'):\n epsg = geo_obj.srid\n if epsg == -1:\n epsg = 4326\n if hasattr(geo_obj, 'geometry_type'):\n self._geometry_type = geo_obj.geometry_type\n\n self._epsg = epsg\n self._table_obj = table_obj\n self._meta = meta","def getGeometryColumnDef(self, schema, table, column):\r\n defs = self.fetchSqlRecords(\r\n \"select type, srid from geometry_columns where f_table_schema='{}' and f_table_name='{}' and f_geometry_column='{}'\".format(schema, table, column))\r\n if not len(defs) == 1:\r\n return None\r\n\r\n return 'geometry({},{})'.format(defs[0][0], defs[0][1])","def get_geom_type(carto_sql_client, tablename):\n geomtypes = {'ST_Point': 'point',\n 'ST_MultiPoint': 'point',\n 'ST_LineString': 'line',\n 'ST_MultiLineString': 'line',\n 'ST_Polygon': 'polygon',\n 'ST_MultiPolygon': 'polygon'}\n\n # NOTE: assumes one geometry type per table\n result = carto_sql_client.send('''\n SELECT ST_GeometryType(the_geom) As geomtype\n FROM \"{tablename}\"\n WHERE the_geom IS NOT NULL\n LIMIT 1'''.format(tablename=tablename))\n try:\n return geomtypes[result['rows'][0]['geomtype']]\n except (KeyError, IndexError):\n print((\"Cannot create a map from `{tablename}` because this table \"\n \"does not have geometries ({geomreported})\").format(\n tablename=tablename,\n geomreported=None))\n return None\n except Exception as err:\n print(\"ERROR: {}\".format(err))\n return None","def get_schema(schema): # noqa: E501\n return 'do some magic!'","def _get_table_reflection(self, schema: str, table: str) -> Table:\n return self.sql_metadata.tables.get(f\"{schema}.{table}\",\n Table(table, self.sql_metadata, schema=schema, autoload=True))","def schema(self):\n return self.table_info.schema","def get_schema(self) -> dict:","def _get_fields(self, table):\n fields = list()\n for column in table.columns:\n fields.append({'id': column.name, 'type': str(column.type)})\n return fields","def getTableSchema(self,tableName):\n\tif not self.schemaDict.has_key(tableName):\n\t if self.dbType==\"sqlite\":\n\t query = \"SELECT * FROM sqlite_master WHERE name='%s'\"%tableName\n\t tup = self.fetchOne(query)\n\t schema= tup[4]\n\t else: # MySQL \n\t query = \"DESCRIBE %s\"%tableName\n\t tup = self.fetchAll(query)\n\t schema= \"CREATE TABLE %s (\"%tableName\n\t for item in tup:\n\t name = item[0]\n\t\t type = item[1]\n\t\t priKey = item[3]\n\t\t autoInc = item[5] \n\t schema+=name+' '+type+' '+priKey+' '+autoInc\n\t\t if item!=tup[-1]:\n\t\t schema+=','\n\t schema+=\" )\"\n\t return schema\n\telse:\n\t return self.schemaDict[tableName]","def get_gtfs_field_tuple_from_table(table_name, gtfs_spec=None):\n if not gtfs_spec:\n gtfs_spec = settings.GTFS_SPEC\n choice_tuple = choice_tuple = (('',''),)\n for t in gtfs_spec['resources']:\n if t['name'] == table_name:\n for f in t['schema']['fields']:\n choice_tuple = choice_tuple + ((f['name'], f['name']),)\n return choice_tuple\n raise ValueError(\"Table name not found in GTFS spec.\")","def split_table_schema(table_name):\r\n\r\n split = table_name.split('.')\r\n if len(split) > 1:\r\n return (split[0], split[1])\r\n else:\r\n return (None, split[0])","def get_schema(self, repo, table):\n return self.user_con.get_schema(repo=repo, table=table)","def parse_table_schema(conn):\r\n cur = conn.cursor()\r\n\r\n cur.execute(\"PRAGMA table_info({})\".format(\"week5\"))\r\n print(cur.fetchall())","def postgis_metadata(self, data_source_id, schema, table_name):\n metadata = {}\n\n try:\n engine = self.engine_for_data_source(data_source_id)\n if engine is None:\n return {\n 'error': \"FEHLER: DataSource nicht gefunden\"\n }\n\n # connect to data_source\n conn = engine.connect()\n\n # get primary key\n\n # build query SQL\n sql = sql_text(\"\"\"\n SELECT a.attname\n FROM pg_index i\n JOIN pg_attribute a ON a.attrelid = i.indrelid\n AND a.attnum = ANY(i.indkey)\n WHERE i.indrelid = '{schema}.{table}'::regclass\n AND i.indisprimary;\n \"\"\".format(schema=schema, table=table_name))\n\n # execute query\n primary_key = None\n result = conn.execute(sql)\n for row in result:\n primary_key = row['attname']\n\n # get geometry column and srid\n\n # build query SQL\n sql = sql_text(\"\"\"\n SELECT f_geometry_column, srid, type\n FROM geometry_columns\n WHERE f_table_schema = '{schema}' AND f_table_name = '{table}';\n \"\"\".format(schema=schema, table=table_name))\n\n # execute query\n geometry_columns = []\n result = conn.execute(sql)\n for row in result:\n geometry_columns.append({\n 'geometry_column': row['f_geometry_column'],\n 'geometry_type': row['type'],\n 'srid': row['srid']\n })\n\n # close database connection\n conn.close()\n\n metadata = {\n 'schema': schema,\n 'table': table_name,\n 'primary_key': primary_key,\n 'geometry_columns': geometry_columns\n }\n except OperationalError as e:\n self.logger.error(e.orig)\n return {\n 'error': \"OperationalError: %s\" % e.orig\n }\n except ProgrammingError as e:\n self.logger.error(e.orig)\n return {\n 'error': \"ProgrammingError: %s\" % e.orig\n }\n\n return metadata","def get_schema(self):\r\n return self.__schema","def get_schema(self):\n return ', '.join('%s:%s' % (col, self.schema[col]) for col in self.schema)","def _get_model_class_from_table(self, table):\r\n try:\r\n model_class = [m for m in get_models() if connection.introspection.table_name_converter(m._meta.db_table) in map(connection.introspection.table_name_converter,[table])][0] \r\n m2m = False \r\n except IndexError:\r\n try: \r\n # this is a many to many field \r\n model_class = [f.rel.to for m in get_models() for f in m._meta.local_many_to_many if f.m2m_db_table() == table][0] \r\n m2m = True \r\n except IndexError: \r\n # this is an inner join \r\n table = self.query.alias_map[table][0]\r\n return self._get_model_class_from_table(table)\r\n return model_class, m2m","def fields_from_table(table):\r\n\r\n fields = []\r\n\r\n for column in table.columns:\r\n field = brewery.metadata.Field(name=column.name)\r\n field.concrete_storage_type = column.type\r\n\r\n for conv in _sql_to_brewery_types:\r\n if issubclass(column.type.__class__, conv[0]):\r\n field.storage_type = conv[1]\r\n field.analytical_type = conv[2]\r\n break\r\n\r\n if not field.storage_type:\r\n field.storaget_tpye = \"unknown\"\r\n\r\n if not field.analytical_type:\r\n field.analytical_type = \"unknown\"\r\n\r\n fields.append(field)\r\n\r\n return brewery.metadata.FieldList(fields)","def get_table_definition(jwt_payload: dict, schema_name: str, table_name: str):\n DJConnector.set_datajoint_config(jwt_payload)\n\n schema_virtual_module = dj.create_virtual_module(schema_name, schema_name)\n return getattr(schema_virtual_module, table_name).describe()","def get_schema(cls):\n return cls.schema()","def get_schema() -> dict:\n raise NotImplementedError()","def _get_schema(self):\n self._pick()\n return Schema()","def get_geometries ( self, object_class_table, spatial_column, select_column, select_id ) :\n stmt = 'select sdo_util.to_wktgeometry(' + str(spatial_column) + ') from ' + str(object_class_table) + ' where ' + str(select_column) + ' = ' + str(select_id)\n self.oracle_cursor.execute( stmt )\n resultset = self.oracle_cursor.fetchall()\n return resultset","def get_table_info(line):\n\n COMMENT_EXPR = '-- Name: '\n TYPE_EXPR = '; Type: '\n SCHEMA_EXPR = '; Schema: '\n OWNER_EXPR = '; Owner: '\n TABLESPACE_EXPR = '; Tablespace: '\n\n temp = line.strip('\\n')\n type_start = get_all_occurrences(TYPE_EXPR, temp)\n schema_start = get_all_occurrences(SCHEMA_EXPR, temp)\n owner_start = get_all_occurrences(OWNER_EXPR, temp)\n tblspace_start = get_all_occurrences(TABLESPACE_EXPR, temp)\n if len(type_start) != 1 or len(schema_start) != 1 or len(owner_start) != 1:\n return (None, None, None, None)\n name = temp[len(COMMENT_EXPR) : type_start[0]]\n type = temp[type_start[0] + len(TYPE_EXPR) : schema_start[0]]\n schema = temp[schema_start[0] + len(SCHEMA_EXPR) : owner_start[0]]\n if not tblspace_start:\n tblspace_start.append(None)\n owner = temp[owner_start[0] + len(OWNER_EXPR) : tblspace_start[0]]\n return (name, type, schema, owner)","def read_schema_from_db(cur, table):\n num_rows = cur.execute(\"\"\"DESCRIBE {}\"\"\".format(table))\n tbl_schema = []\n for i in range(num_rows):\n row = cur.fetchone()\n tbl_schema.append([row[0], row[1]])\n return tbl_schema","def schema_ref(schema, table):\n return schema + '.' + table","async def _get_schema_info(self, app_id, namespace, gae_index_name):\n collection = get_collection_name(app_id, namespace, gae_index_name)\n solr_schema_info = await self.solr.get_schema_info(collection)\n fields_info = solr_schema_info['fields']\n id_field = SolrSchemaFieldInfo(\n solr_name='id', gae_name='doc_id', type=Field.Type.ATOM,\n language=None, docs_number=fields_info.get('id', {}).get('docs', 0)\n )\n rank_field = SolrSchemaFieldInfo(\n solr_name='rank', gae_name='rank', type=Field.Type.NUMBER,\n language=None, docs_number=fields_info.get('rank', {}).get('docs', 0)\n )\n fields = [id_field, rank_field]\n grouped_fields = {\n 'doc_id': [id_field],\n 'rank': [rank_field]\n }\n facets = []\n grouped_facet_indexes = {}\n\n for solr_field_name, info in fields_info.items():\n try:\n gae_name, type_, language = parse_solr_field_name(solr_field_name)\n except ValueError:\n continue\n schema_field = SolrSchemaFieldInfo(\n solr_field_name, gae_name, type_, language, info.get('docs', 0)\n )\n if SolrSchemaFieldInfo.Type.is_facet_index(type_):\n add_value(grouped_facet_indexes, gae_name, schema_field)\n if SolrSchemaFieldInfo.Type.is_facet(type_):\n facets.append(schema_field)\n else:\n fields.append(schema_field)\n add_value(grouped_fields, gae_name, schema_field)\n\n for fields_group in grouped_fields.values():\n if len(fields_group) > 1:\n # Sadly app uses the same name for fields with different types [*1].\n # Let's sort them from high popularity to low.\n fields_group.sort(key=lambda solr_field: -solr_field.docs_number)\n\n for facets_group in grouped_facet_indexes.values():\n if len(facets_group) > 1:\n # Sadly app uses the same name for facets with different types [*1].\n # Let's sort them from high popularity to low.\n facets_group.sort(key=lambda solr_field: -solr_field.docs_number)\n\n index_info = solr_schema_info['index']\n return SolrIndexSchemaInfo(\n app_id=app_id,\n namespace=namespace,\n gae_index_name=gae_index_name,\n collection=collection,\n docs_number=index_info['numDocs'],\n heap_usage=index_info['indexHeapUsageBytes'],\n size_in_bytes=index_info['segmentsFileSizeInBytes'],\n fields=fields,\n facets=facets,\n grouped_fields=grouped_fields,\n grouped_facet_indexes=grouped_facet_indexes\n )","def get_schema(db, sourcename):\n try:\n schema = db[\"tables\"][sourcename]\n schema[\"type\"] = constants.TABLE\n except KeyError:\n try:\n schema = db[\"views\"][sourcename]\n schema[\"type\"] = constants.VIEW\n except KeyError:\n raise ValueError(\"no such table/view\")\n return schema","def get_field_type(field, table):\n for i in settings.GTFS_SPEC['resources']:\n print(i['name'])\n if i['name'] == table:\n for j in i['schema']['fields']:\n print(j['name'])\n if j['name'] == field:\n return j['gtfs_type']\n raise ValueError(\"Field not found in GTFS spec.\")","def get_schema(self):\n return ', '.join(\n '%s:%s' % (col, self.schema[col]) for col in self.schema)","def get_schema(self) -> dict:\n return schemas.get_object_schema(self.schema)","def Result(row, schema):\r\n return dict(zip(schema.fields(), row))","def model_table():\r\n class OccupationTable(tables.Table):\r\n class Meta:\r\n model = Occupation\r\n assert [\"id\", \"name\", \"region\"] == list(OccupationTable.base_columns.keys())\r\n\r\n class OccupationTable2(tables.Table):\r\n extra = tables.Column()\r\n\r\n class Meta:\r\n model = Occupation\r\n assert [\"id\", \"name\", \"region\", \"extra\"] == list(OccupationTable2.base_columns.keys())\r\n\r\n # be aware here, we already have *models* variable, but we're importing\r\n # over the top\r\n from django.db import models\r\n\r\n class ComplexModel(models.Model):\r\n char = models.CharField(max_length=200)\r\n fk = models.ForeignKey(\"self\")\r\n m2m = models.ManyToManyField(\"self\")\r\n\r\n class ComplexTable(tables.Table):\r\n class Meta:\r\n model = ComplexModel\r\n assert [\"id\", \"char\", \"fk\"] == list(ComplexTable.base_columns.keys())","def as_tuple(self) -> tuple[typing.Any, ...]:\n return tuple(getattr(self, field.name) for field in Schema)","def schema(self):","def fetch_table_schema(self, table_name):\n ddl = self.query(sql.show_create_table(table_name))\n if ddl:\n try:\n return parse_create(ddl[0][\"Create Table\"])\n except ParseError as e:\n raise OSCError(\n \"TABLE_PARSING_ERROR\",\n {\"db\": self._current_db, \"table\": self.table_name, \"msg\": str(e)},\n )","def info_from_geo_field(geo_field):\n\n geo_field_name = geo_field.name\n\n get_geom = lambda obj: getattr(obj, geo_field_name)\n\n if hasattr(geo_field, 'geom_type'):\n geom_type = geo_field.geom_type\n else:\n geom_type = geo_field._geom\n\n if hasattr(geo_field, 'srid'):\n srid = geo_field.srid\n else:\n srid = geo_field._srid\n\n return get_geom, geom_type, srid","def schema_to_features(schema: TableSchema) -> List[LiteFeature]:\n features = []\n for col_name, column_schema in schema.columns.items():\n assert isinstance(column_schema, ColumnSchema)\n\n logical_type = column_schema.logical_type\n assert logical_type\n assert issubclass(type(logical_type), LogicalType)\n\n tags = column_schema.semantic_tags\n assert isinstance(tags, set)\n\n features.append(\n LiteFeature(\n name=col_name,\n logical_type=type(logical_type),\n tags=tags,\n ),\n )\n\n return features","def retrieve_shapely(osm_path,geoType,keyCol,**valConstraint):\n driver=ogr.GetDriverByName('OSM')\n data = driver.Open(osm_path)\n query = query_b(geoType,keyCol,**valConstraint)\n sql_lyr = data.ExecuteSQL(query)\n features =[]\n # cl = columns \n cl = ['osm_id'] \n for a in keyCol: cl.append(a)\n if data is not None:\n print('query is finished, lets start the loop')\n for feature in tqdm(sql_lyr):\n try:\n if feature.GetField(keyCol[0]) is not None:\n geom = loads(feature.geometry().ExportToWkb()) \n if geom is None:\n continue\n # field will become a row in the dataframe.\n field = []\n for i in cl: field.append(feature.GetField(i))\n field.append(geom) \n features.append(field)\n except:\n print(\"WARNING: skipped OSM feature\") \n else:\n print(\"ERROR: Nonetype error when requesting SQL. Check required.\") \n cl.append('geometry') \n if len(features) > 0:\n return geopandas.GeoDataFrame(features,columns=cl,crs={'init': 'epsg:4326'})\n else:\n print(\"WARNING: No features or No Memory. returning empty GeoDataFrame\") \n return geopandas.GeoDataFrame(columns=['osm_id','geometry'],crs={'init': 'epsg:4326'})","def schema(cls, only_self: bool=False):\n try:\n md_tbls = cls.metadata.tables\n insp = reflection.Inspector.from_engine(cls.s.bind.engine)\n tbls = dict()\n for tbl in insp.get_table_names():\n if not only_self or (only_self and tbl == cls.__tablename__):\n cols = dict()\n for col in insp.get_columns(tbl):\n info = dict(col)\n col_info = md_tbls[tbl].c[col['name']]\n info['type'] = {\n 'compiled': col['type'].compile(),\n 'native': col['type'].python_type.__name__\n }\n info['type']['length'] = col['type'].length if hasattr(col['type'], 'length') else None\n if info['autoincrement']:\n info['default'] = 'autoincrement'\n info.update(col_info.info)\n info['placeholder'] = '%s_%s' % (tbl, col['name'])\n cols[col['name']] = info\n tbls[tbl] = cols\n\n return tbls\n except SQLAlchemyError:\n cls.s.rollback()\n raise","def get_schema(self, get_stats=False):\n query = \"schema {}\"\n\n results = self.run_dgraph_query_raw(query)\n\n schema = {}\n\n for row in results[\"schema\"]:\n table_name = row[\"predicate\"]\n\n if table_name not in schema:\n schema[table_name] = {\"name\": table_name, \"columns\": []}\n\n return list(schema.values())","def build_schema(self):\n field_defs = []\n fields = []\n point_rows = []\n line_rows = []\n polygon_rows = []\n for i in self.json_in['features']: # first iterate through it all and get all the fields\n props = i.get('properties')\n\n for k, v in props.items():\n if k not in fields:\n fields.append(k)\n\n for i in self.json_in['features']: # now fill in any props that any features are missing, and sort them all\n geom = i['geometry']\n props = i['properties']\n for f in fields:\n if f not in props.keys():\n props[f] = ''\n props = OrderedDict(sorted(props.items()))\n\n for k, v in props.items():\n schema_row = [k, \"TEXT\", k.replace('_', ' '), 256]\n if schema_row not in field_defs:\n field_defs.append(schema_row)\n row = [str(v) for k, v in sorted(props.items())] # coerce everything to str cause this stuff is a mess\n parsed_geom = GeoJSONUtils.parse_geometry(geom)\n geotype = parsed_geom['type']\n egeom = parsed_geom['esri_geom']\n\n if geotype == \"POINT\":\n row.insert(0, egeom)\n print(row)\n point_rows.append(row)\n elif geotype == \"POLYLINE\":\n row.insert(0, egeom)\n print(row)\n line_rows.append(row)\n else:\n row.insert(0, egeom)\n print(row)\n polygon_rows.append(row)\n\n return {\n \"fields\": fields,\n \"field_defs\": field_defs,\n \"rows\": [point_rows, line_rows, polygon_rows]\n }","def _get_table(self, cursor):\n raise NotImplementedError","def transform_schema(pgschema):\n datatypes = {}\n for field in pgschema:\n if 'cartodb_id' in field:\n continue\n datatypes[field] = map_dtypes(pgschema[field]['type'])\n return datatypes","def info_table(table):\n print \"\\nSCHEMA de la taula \",table, \"es: \"\n con=lite.connect('parking.db')\n cur=con.cursor()\n cur.execute(\"PRAGMA table_info({});\".format(table))\n data = cur.fetchall()\n for d in data:\n print \"\\t\",d[0], d[1], d[2]\n con.close()","def fetch_tuples(jwt_payload: dict, schema_name: str, table_name: str):\n DJConnector.set_datajoint_config(jwt_payload)\n\n schema_virtual_module = dj.create_virtual_module(schema_name, schema_name)\n\n # Get the table object refernece\n table = getattr(schema_virtual_module, table_name)\n\n # Fetch tuples without blobs as dict to be used to create a\n # list of tuples for returning\n non_blobs_rows = table.fetch(*table.heading.non_blobs, as_dict=True,\n limit=DEFAULT_FETCH_LIMIT)\n\n # Buffer list to be return\n rows = []\n\n # Looped through each tuple and deal with TEMPORAL types and replacing\n # blobs with ==BLOB== for json encoding\n for non_blobs_row in non_blobs_rows:\n # Buffer object to store the attributes\n row = []\n # Loop through each attributes, append to the tuple_to_return with specific\n # modification based on data type\n for attribute_name, attribute_info in table.heading.attributes.items():\n if not attribute_info.is_blob:\n if non_blobs_row[attribute_name] is None:\n # If it is none then just append None\n row.append(None)\n elif attribute_info.type == 'date':\n # Date attribute type covert to epoch time\n row.append((non_blobs_row[attribute_name] -\n datetime.date(1970, 1, 1)).days * DAY)\n elif attribute_info.type == 'time':\n # Time attirbute, return total seconds\n row.append(non_blobs_row[attribute_name].total_seconds())\n elif attribute_info.type in ('datetime', 'timestamp'):\n # Datetime or timestamp, use timestamp to covert to epoch time\n row.append(non_blobs_row[attribute_name].timestamp())\n elif attribute_info.type[0:7] == 'decimal':\n # Covert decimal to string\n row.append(str(non_blobs_row[attribute_name]))\n else:\n # Normal attribute, just return value with .item to deal with numpy\n # types\n if isinstance(non_blobs_row[attribute_name], np.generic):\n row.append(np.asscalar(non_blobs_row[attribute_name]))\n else:\n row.append(non_blobs_row[attribute_name])\n else:\n # Attribute is blob type thus fill it in string instead\n row.append('=BLOB=')\n\n # Add the row list to tuples\n rows.append(row)\n return rows","def schema(self) -> 'outputs.TableSchemaResponse':\n return pulumi.get(self, \"schema\")","def get_tables_name_and_type(self) -> Optional[Iterable[Tuple[str, str]]]:\n try:\n schema_name = self.context.database_schema.name.__root__\n if self.source_config.includeTables:\n for table_and_type in self.query_table_names_and_types(schema_name):\n table_name = self.standardize_table_name(\n schema_name, table_and_type.name\n )\n table_fqn = fqn.build(\n self.metadata,\n entity_type=Table,\n service_name=self.context.database_service.name.__root__,\n database_name=self.context.database.name.__root__,\n schema_name=self.context.database_schema.name.__root__,\n table_name=table_name,\n skip_es_search=True,\n )\n if filter_by_table(\n self.source_config.tableFilterPattern,\n table_fqn\n if self.source_config.useFqnForFiltering\n else table_name,\n ):\n self.status.filter(\n table_fqn,\n \"Table Filtered Out\",\n )\n continue\n yield table_name, table_and_type.type_\n\n if self.source_config.includeViews:\n for view_name in self.inspector.get_view_names(schema_name):\n view_name = self.standardize_table_name(schema_name, view_name)\n view_fqn = fqn.build(\n self.metadata,\n entity_type=Table,\n service_name=self.context.database_service.name.__root__,\n database_name=self.context.database.name.__root__,\n schema_name=self.context.database_schema.name.__root__,\n table_name=view_name,\n )\n\n if filter_by_table(\n self.source_config.tableFilterPattern,\n view_fqn\n if self.source_config.useFqnForFiltering\n else view_name,\n ):\n self.status.filter(\n view_fqn,\n \"Table Filtered Out\",\n )\n continue\n yield view_name, TableType.View\n except Exception as err:\n logger.warning(\n f\"Fetching tables names failed for schema {schema_name} due to - {err}\"\n )\n logger.debug(traceback.format_exc())","def _get_tabletype(cls) -> str:\n raise NotImplementedError","def set_schema():\n schema = StructType([\n StructField(\"cicid\",DoubleType(),True),\n StructField(\"arrdate\",DoubleType(),True),\n StructField(\"i94cit\",DoubleType(),True),\n StructField(\"i94res\",DoubleType(),True),\n StructField(\"i94port\",StringType(),True),\n StructField(\"i94mode\",DoubleType(),True),\n StructField(\"i94addr\",StringType(),True),\n StructField(\"depdate\",DoubleType(),True), \n StructField(\"i94bir\",DoubleType(),True),\n StructField(\"i94visa\",DoubleType(),True),\n StructField(\"gender\",StringType(),True),\n StructField(\"airline\",StringType(),True),\n StructField(\"visatype\",StringType(),True)])\n return schema","def get_schemas(self, conn):\n return conn.get_schemas()['table_schema']","def _get_model_from_table_name(table_name: str) -> Optional[Type[RDSModel]]:\n table_model = None\n try:\n if hasattr(Base, '_decl_class_registry'):\n models = Base._decl_class_registry.values() # sqlalchemy < 1.4\n else:\n models = Base.registry._class_registry.values()\n\n for model in models:\n if hasattr(model, '__tablename__') and model.__tablename__ == table_name:\n table_model = model\n except Exception as e:\n LOGGER.exception(f'Failed to get model for the table: {table_name} from rds model base')\n raise e\n\n return table_model","def guess_schema_from_model(model, tensor_type=None, schema=None):\n if schema is not None:\n try:\n guessed = guess_schema_from_model(model)\n except NotImplementedError: # pragma: no cover\n return _replace_tensor_type(schema, tensor_type)\n if len(guessed) != len(schema):\n raise RuntimeError( # pragma: no cover\n \"Given schema and guessed schema are not the same:\\nGOT: {}\\n-----\\nGOT:\\n{}\".format(\n schema, guessed))\n return _replace_tensor_type(schema, tensor_type)\n\n if hasattr(model, 'coef_'):\n # linear model\n init = [('X', FloatTensorType([None, model.coef_.shape[1]]))]\n return _replace_tensor_type(init, tensor_type)\n elif hasattr(model, 'dump_model'):\n dumped = model.dump_model()\n if isinstance(dumped, dict) and 'feature_names' in dumped:\n names = dumped['feature_names']\n init = [(name, FloatTensorType([None, 1])) for name in names]\n return _replace_tensor_type(init, tensor_type)\n\n data = pprint.pformat(model.__dict__)\n dirs = pprint.pformat(dir(model))\n if hasattr(model, 'dump_model'): # pragma: no cover\n dumped = model.dump_model()\n keys = list(sorted(dumped))\n last = pprint.pformat([keys, dumped])\n if len(last) >= 200000:\n last = last[:200000] + \"\\n...\"\n else:\n last = \"\"\n raise NotImplementedError( # pragma: no cover\n \"Unable to guess schema for model {}\\n{}\\n----\\n{}\\n------\\n{}\".format(\n model.__class__, data, dirs, last))","def __init__(self, schema_row):\n self.schema = []\n for field in schema_row['fields']:\n self.schema.append(field['type'])","def table(self, table: Union[str, sa.Table]) -> B[B, E]:","def get_table_schema(dataset_id, table_id):\n logging.info('getting table schema')\n bigquery_client = bigquery.Client()\n dataset_ref = bigquery_client.dataset(dataset_id)\n bg_tableref = bigquery.table.TableReference(dataset_ref, table_id)\n bg_table = bigquery_client.get_table(bg_tableref)\n return bg_table.schema","def schema(self):\n raise NotImplementedError","def build_song_schema():\n schema = StructType(\n [\n StructField('artist_id', StringType(), True),\n StructField('artist_latitude', DecimalType(), True),\n StructField('artist_longitude', DecimalType(), True),\n StructField('artist_location', StringType(), True),\n StructField('artist_name', StringType(), True),\n StructField('duration', DecimalType(), True),\n StructField('num_songs', IntegerType(), True),\n StructField('song_id', StringType(), True),\n StructField('title', StringType(), True),\n StructField('year', IntegerType(), True)\n ]\n )\n return schema","def _get_table(self):\n\t\treturn self._table","def getTableColumnDefs(self, schema, table):\r\n src_columns = self.fetchSqlRecords(\r\n \"select c.column_name, data_type, character_maximum_length, numeric_precision, numeric_scale from information_schema.columns c where c.table_schema = '{}' and c.table_name='{}'\".format(schema, table))\r\n return [dict(zip(('name', 'type', 'max_length', 'precision', 'scale'), c)) for c in src_columns]","def schema() -> None:\n pass","def get_schema_cls() -> t.Any:\n return None","def _get_table_schema(self):\n\n return {\n 'AttributeDefinitions': [\n {\n 'AttributeName': self._key_field.name,\n 'AttributeType': self._key_field.data_type\n }\n ],\n 'TableName': self.table_name,\n 'KeySchema': [\n {\n 'AttributeName': self._key_field.name,\n 'KeyType': 'HASH'\n }\n ],\n 'ProvisionedThroughput': {\n 'ReadCapacityUnits': self.read_capacity_units,\n 'WriteCapacityUnits': self.write_capacity_units\n }\n }","def get_field_type(self, table_name, field_name):\n \n dtype = self.field_types[(self.field_types.TABNAME == table_name) & (self.field_types.FIELDNAME == field_name)]['DATATYPE'].values[0] \n return dtype","def columns_type(self,table):\n with self.conn.cursor() as cur:\n #_logger.debug('Columns Query. sql: %r', self.table_columns_query)\n cur.execute(self.columns_info_query % (self.dbname,table))\n for row in cur:\n yield row","def _create_field_schema(col_schema: dict) -> bigquery.SchemaField:\n name = to_safe_name(col_schema['name'])\n return bigquery.SchemaField(\n name,\n col_schema.get('type'),\n col_schema.get('mode', 'NULLABLE'),\n col_schema.get('description', '')\n )","def get_table_definition(db_name, schema_name, table_name, server_name, data_partition_column_name='', excluded_columns=()):\n server_name = '' if server_name == '127.0.0.1' or server_name == 'localhost' else server_name\n server_name = f'[{server_name}].' if server_name else ''\n\n sql = (\"SELECT T.name AS TABLE_NAME, C.name AS COLUMN_NAME, P.name AS DATA_TYPE, \"\n \"P.max_length AS SIZE, CAST(P.precision AS VARCHAR) + '/' + CAST(P.scale AS VARCHAR) AS PRECISION_SCALE, \"\n \"c.* FROM {0}[{1}].sys.objects AS T JOIN {0}[{1}].sys.columns AS C ON T.object_id = C.object_id \"\n \"JOIN {0}[{1}].sys.types AS P ON C.system_type_id = P.system_type_id \"\n \"JOIN sys.schemas ss ON (T.schema_id = ss.schema_id) \"\n \" WHERE T.type_desc = 'USER_TABLE' and ss.name = ? \"\n \"and T.name = ? and P.name != 'timestamp' and P.name != 'sysname' order by column_id asc\").format(server_name, db_name)\n\n columns = fetch_rows(sql, [schema_name, table_name])\n\n target_table_column_prefix = get_config()['TARGET_TABLE_COLUMN_PREFIX']\n out_columns = {}\n\n for column in columns:\n column['original_data_type'] = column['data_type']\n\n if column['column_name'].upper() in default_columns:\n column['target_table_column_name'] = target_table_column_prefix + column['column_name']\n else:\n column['target_table_column_name'] = column['column_name']\n\n # Update the data type for the data partition column\n if data_partition_column_name != '' and column['column_name'].upper() == data_partition_column_name.upper():\n column['data_type'] = 'datetime'\n\n out_columns[column['column_name'].upper()] = column\n\n if len(excluded_columns) > 0:\n for excluded_column in excluded_columns:\n out_columns.pop(excluded_column)\n\n return out_columns","def get_table_by_person_id(table, person_id, schema=staging_schema, fields=\"default\"):\n if fields == \"default\":\n columns = \" * \"\n elif fields == \"Edit\":\n columns = \" [PersonID], [FirstName], [LastName], [SSN], [DOB], [Phone], [Email], [PersonType], [DataEntryLocationID], [AssignedInfectionStaff], [Note], [PartOfStudyYN], [StudyDetails], [PtHospitalizedYN], [PtCurrentLocationID], [PtHighComplicationRiskYN], [PtContactedYN], [PtDateLastContacted], [PtVABostonPCPYN], [PtPCPName], [PtPCPPhone], [EmplSupervisorName], [EmplSupervisorPhone], [EmplSupervisorNotifiedYN], [EmplIDNotifiedYN], [EmplEmployeeRole], [EmplCampus], [EmplCampusesOther], [EmplShiftSchedule], [EmplWorkLocation], [EmplPatientInteractionYN], [EmplSXSExposureWorkStartDate], [EmplSXSExposureWorkEndDate], [EmplWorkClearedYN1], [EmplReturnToWorkDate1] ,TestDate1, TestLocation1, TestResult1, TestDriveThruNeededYN1, CovidStatus1, AssignedProvider1, NumOfConsecutiveNegTestSinceLastPos1, TestDate2, TestLocation2, TestResult2, TestDriveThruNeededYN2, CovidStatus2, AssignedProvider2, NumOfConsecutiveNegTestSinceLastPos2, TestDate3, TestLocation3, TestResult3, TestDriveThruNeededYN3, CovidStatus3, AssignedProvider3, NumOfConsecutiveNegTestSinceLastPos3, TestDate4, TestLocation4, TestResult4, TestDriveThruNeededYN4, CovidStatus4, AssignedProvider4, NumOfConsecutiveNegTestSinceLastPos4, TestDate5, TestLocation5, TestResult5, TestDriveThruNeededYN5, CovidStatus5, AssignedProvider5, NumOfConsecutiveNegTestSinceLastPos5, TestDate6, TestLocation6, TestResult6, TestDriveThruNeededYN6, CovidStatus6, AssignedProvider6, NumOfConsecutiveNegTestSinceLastPos6, TestDate7, TestLocation7, TestResult7, TestDriveThruNeededYN7, CovidStatus7, AssignedProvider7, NumOfConsecutiveNegTestSinceLastPos7, TestDate8, TestLocation8, TestResult8, TestDriveThruNeededYN8, CovidStatus8, AssignedProvider8, NumOfConsecutiveNegTestSinceLastPos8, TestDate9, TestLocation9, TestResult9, TestDriveThruNeededYN9, CovidStatus9, AssignedProvider9, NumOfConsecutiveNegTestSinceLastPos9, TestDate10, TestLocation10, TestResult10, TestDriveThruNeededYN10, CovidStatus10, AssignedProvider10, NumOfConsecutiveNegTestSinceLastPos10, [QuarantinedYN1], [QuarantineStartDate1], [QuarantineEndDate1], [QuarantineSymptomTrackerYN1], [QuarantinedYN2], [QuarantineStartDate2], [QuarantineEndDate2], [QuarantineSymptomTrackerYN2], [QuarantinedYN3], [QuarantineStartDate3], [QuarantineEndDate3], [QuarantineSymptomTrackerYN3], [QuarantinedYN4], [QuarantineStartDate4], [QuarantineEndDate4], [QuarantineSymptomTrackerYN4], [QuarantinedYN5], [QuarantineStartDate5], [QuarantineEndDate5], [QuarantineSymptomTrackerYN5], [LocationChangeDateTime1], [LocationChangeNewLocationID1], [LocationChangeDateTime2], [LocationChangeNewLocationID2], [LocationChangeDateTime3], [LocationChangeNewLocationID3], [LocationChangeDateTime4], [LocationChangeNewLocationID4], [LocationChangeDateTime5], [LocationChangeNewLocationID5], [ExposureDate1], [ExposureType1], [ExposureLocation1], [ExposureDetails1], [ExposureDate2], [ExposureType2], [ExposureLocation2], [ExposureDetails2], [ExposureDate3], [ExposureType3], [ExposureLocation3], [ExposureDetails3], [ExposureDate4], [ExposureType4], [ExposureLocation4], [ExposureDetails4], [ExposureDate5], [ExposureType5], [ExposureLocation5], [ExposureDetails5], [SymptomType1], [SymptomOnsetDate1], [SymptomOnsetLocationID1], [SymptomResolutionDate1], [SymptomResolutionLocationID1], [SymptomNote1], [SymptomType2], [SymptomOnsetDate2], [SymptomOnsetLocationID2], [SymptomResolutionDate2], [SymptomResolutionLocationID2], [SymptomNote2], [SymptomType3], [SymptomOnsetDate3], [SymptomOnsetLocationID3], [SymptomResolutionDate3], [SymptomResolutionLocationID3], [SymptomNote3], [SymptomType4], [SymptomOnsetDate4], [SymptomOnsetLocationID4], [SymptomResolutionDate4], [SymptomResolutionLocationID4], [SymptomNote4], [SymptomType5], [SymptomOnsetDate5], [SymptomOnsetLocationID5], [SymptomResolutionDate5], [SymptomResolutionLocationID5], [SymptomNote5], [SymptomType6], [SymptomOnsetDate6], [SymptomOnsetLocationID6], [SymptomResolutionDate6], [SymptomResolutionLocationID6], [SymptomNote6], [SymptomType7], [SymptomOnsetDate7], [SymptomOnsetLocationID7], [SymptomResolutionDate7], [SymptomResolutionLocationID7], [SymptomNote7], [SymptomType8], [SymptomOnsetDate8], [SymptomOnsetLocationID8], [SymptomResolutionDate8], [SymptomResolutionLocationID8], [SymptomNote8], [SymptomType9], [SymptomOnsetDate9], [SymptomOnsetLocationID9], [SymptomResolutionDate9], [SymptomResolutionLocationID9], [SymptomNote9], [SymptomType10], [SymptomOnsetDate10], [SymptomOnsetLocationID10], [SymptomResolutionDate10], [SymptomResolutionLocationID10], [SymptomNote10], [Sta3n], [DOD], [EmplWorkClearedYN2], [EmplReturnToWorkDate2], [EmplWorkClearedYN3], [EmplReturnToWorkDate3], [EmplWorkClearedYN4], [EmplReturnToWorkDate4], [EmplWorkClearedYN5], [EmplReturnToWorkDate5], [StreetAddress], [City], [County], [State], [Zip] \"\n elif fields == \"Detail\":\n columns = \" SSN4, LastName, FirstName, DOB, DOD, Phone, Email, PersonType, AdmitStatus, RoomBed, WardLocationName, InstitutionName, PACT_Provider, PACT_Team, PACT_Phone, CDWUpdatedDateTime \"\n\n q = \"select {columns} from {schema}.{table} where PersonID = ?\"\n q = q.format(columns=columns, schema=schema, table=table)\n tb = pd.read_sql(q, engine, params=[person_id])\n return tb","def _get_geometry(self):\r\n if self._geometry_column_name not in self.columns:\r\n raise AttributeError(\"Geometry Column Not Present: %s\" % self._geometry_column_name)\r\n return self[self._geometry_column_name]","async def get_schema_info(self, collection):\n await self.ensure_collection(collection)\n try:\n # Luke handler is not supported in API v2 yet.\n # /v2/collections//schema/fields doesn't show dynamically\n # created fields.\n # So using old API (/solr/...).\n response = await self.get(\n '/solr/{}/admin/luke?numTerms=0'.format(collection)\n )\n return json.loads(response.body.decode('utf-8'))\n except SolrError:\n logger.warning('Failed to fetch fields list for collection {}'\n .format(collection))\n raise","def schema(self):\n return self._schema","def getSchema(cls):\n pass","def _get_schema(self):\n self.to_dask()\n return Schema(dtype=self._df.dtypes,\n shape=(None, len(self._df.columns)),\n npartitions=self._df.npartitions,\n metadata=self.metadata)","def _columns(cls, schema: dsl.Source.Schema) -> typing.Sequence[str]:\n return tuple(f.name for f in schema)","def ArrowSchema(self) -> pa.Schema:","def _get_schema_using_query(self, query: str) -> sch.Schema:\n return sch.Schema.from_tuples(self._metadata(query))","def _get_table_obj(self, mode):\n return self.client[f\"bigquery_{mode}\"].get_table(self.table_full_name[mode])","def tableExists(self, schema, table):\r\n r = self.fetchSqlRecords(\r\n \"SELECT to_regclass('{}.{}')\".format(schema, table))\r\n return r[0][0]","def _get_stored_schema(self, table: str) -> Optional[TableSchema]:\n try:\n with open(self.schemas / (table + '.json'), 'r') as f:\n return json.load(f)\n except FileNotFoundError:\n return None","def table(entity) -> sa.Table:\n return entity.__table__","def geo_field_from_model(model, default_geo_field_name=None):\n try:\n # If the class defines a geomfield property, use it !\n return model.geomfield\n except AttributeError:\n pass\n\n fields = model._meta.fields\n geo_fields = [f for f in fields if isinstance(f, GeometryField)]\n\n # Used for error case\n geo_fields_names = lambda: ', '.join([f.name for f in geo_fields])\n\n if len(geo_fields) > 1:\n if not default_geo_field_name:\n raise ValueError(\"More than one geodjango geometry field found, please specify which to use by name using the 'geo_field' keyword. Available fields are: '%s'\" % geo_fields_names())\n else:\n geo_field_by_name = [fld for fld in geo_fields if fld.name == default_geo_field_name]\n if not geo_field_by_name:\n raise ValueError(\"Geodjango geometry field not found with the name '%s', fields available are: '%s'\" % (default_geo_field_name, geo_fields_names()))\n else:\n geo_field = geo_field_by_name[0]\n elif geo_fields:\n geo_field = geo_fields[0]\n else:\n raise ValueError('No geodjango geometry fields found in this model')\n\n return geo_field","def get_table_attributes(jwt_payload: dict, schema_name: str, table_name: str):\n DJConnector.set_datajoint_config(jwt_payload)\n\n schema_virtual_module = dj.create_virtual_module(schema_name, schema_name)\n table_attributes = dict(primary_attributes=[], secondary_attributes=[])\n for attribute_name, attribute_info in getattr(schema_virtual_module,\n table_name).heading.attributes.items():\n if attribute_info.in_key:\n table_attributes['primary_attributes'].append((\n attribute_name,\n attribute_info.type,\n attribute_info.nullable,\n attribute_info.default,\n attribute_info.autoincrement\n ))\n else:\n table_attributes['secondary_attributes'].append((\n attribute_name,\n attribute_info.type,\n attribute_info.nullable,\n attribute_info.default,\n attribute_info.autoincrement\n ))\n\n return table_attributes","def guess_schema_from_data(X, tensor_type=None, schema=None):\n init = guess_initial_types(X, schema)\n if tensor_type is not None:\n init = _replace_tensor_type(init, tensor_type)\n # Grouping column\n unique = set()\n for _, col in init:\n if len(col.shape) != 2:\n return init # pragma: no cover\n if col.shape[0] is not None:\n return init # pragma: no cover\n if len(unique) > 0 and col.__class__ not in unique:\n return init # pragma: no cover\n unique.add(col.__class__)\n unique = list(unique)\n return [('X', unique[0]([None, sum(_[1].shape[1] for _ in init)]))]","def modelfields(entity) -> Dict[str, Field]:\n return entity.__modelfields__","def get_schema(self) -> ArchiveSchema:\n return self.schema","def get_schema(self):\n response = self.client.get(self._get_collection_url('schema'))\n\n return response.get('schema', {})","def schema(self):\n pass","def resolve_schema_instance(schema: Union[BaseModel, str]) -> BaseModel:\n from smpa.schemas.core import CoreGetSchema, CoreListSchema\n from smpa.schemas.auth import LoginSchema\n\n if schema == 'CoreListSchema':\n return CoreListSchema\n elif schema == 'CoreGetSchema':\n return CoreGetSchema\n elif schema == 'LoginSchema':\n return LoginSchema\n\n if isinstance(schema, type) and issubclass(schema, BaseModel):\n return schema()\n if isinstance(schema, BaseModel):\n return schema\n try:\n return model_registry.get_class(schema)()\n except RegistryError:\n raise ValueError(\n \"{!r} is not a BaseModel subclass or instance and has not\"\n \" been registered in the model registry.\".format(schema)\n )","def get_model_schema(self, app, model):\n model_schema = {\n 'app': {\n 'name': model._meta.app_label,\n 'label': model._meta.app_config.verbose_name,\n },\n 'name': model._meta.model_name,\n 'label': model._meta.verbose_name,\n 'components': []\n }\n\n for field in model._meta.get_fields():\n # 排除不需要在前端构建form的field: id、反向关联field\n # print('field', type(field), field)\n if field.name == 'id':\n continue\n if isinstance(field, ForeignObjectRel):\n # logger.info(\"ForeignObjectRel\", field)\n continue\n\n component = self.get_field_data(model, field)\n # logger.info('component', component)\n model_schema['components'].append(component)\n # print('get_model_schema', model_schema)\n return model_schema\n # return JsonResponse(model_schema)","def create_staging_schema(cursor,table_schema):\n create_schema = \"CREATE SCHEMA IF NOT EXISTS \" + table_schema + \";\"\n cursor.execute(create_schema)","def instance_schema(self):\n raise NotImplementedError","def query_table_names_and_types(\n self, schema_name: str\n ) -> Iterable[TableNameAndType]:\n\n return [\n TableNameAndType(name=table_name)\n for table_name in self.inspector.get_table_names(schema_name) or []\n ]","def _table_from_ft(ft_schema: dict) -> bigquery.Table:\n # A \"TableSchema\" is just a sequence of SchemaFields https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.table.Table.html\n schema = list(map(_create_field_schema, ft_schema['columns']))\n table = bigquery.Table(\n bigquery.TableReference(ds, to_safe_name(ft_schema['name'])),\n schema\n )\n table.description = ft_schema.get('description', '')\n return table","async def schema_state(appname, schema, table):\n base = sprout.cfg.db_str(appname)\n con = await asyncpg.connect(base)\n req = ', '.join([\n 'table_catalog',\n 'table_schema',\n 'table_name',\n 'column_name',\n 'data_type'\n ])\n q = f\"\"\"select {req} from information_schema.columns\nwhere table_schema='{schema}' and table_name='{table}';\"\"\"\n try:\n ret = await con.fetch(q)\n df = pd.DataFrame.from_records(ret, columns=ret[0].keys())\n return df\n except Exception as e:\n sprout.cfg.log.error(f\"fetching current table state failed: {e}\")\n finally:\n await con.close()","def get_schema() -> Dict[str, type]:\n schema: Dict[str, type] = {}\n\n # Add all columns from pipeline configs\n for pipeline in get_pipelines():\n schema.update(pipeline.schema)\n\n # Add new columns from adapter\n for col_old, col_new in OUTPUT_COLUMN_ADAPTER.items():\n if col_old in schema and col_new is not None:\n schema[col_new] = schema[col_old]\n\n return schema","def build_song_schema():\n schema = T.StructType(\n [\n T.StructField('artist_id', T.StringType(), True),\n T.StructField('artist_latitude', T.DecimalType(), True),\n T.StructField('artist_longitude', T.DecimalType(), True),\n T.StructField('artist_location', T.StringType(), True),\n T.StructField('artist_name', T.StringType(), True),\n T.StructField('duration', T.DecimalType(), True),\n T.StructField('num_songs', T.IntegerType(), True),\n T.StructField('song_id', T.StringType(), True),\n T.StructField('title', T.StringType(), True),\n T.StructField('year', T.IntegerType(), True)\n ]\n )\n return schema","def _split_table_name(table_name):\n table_name_items = table_name.split(\".\")\n if len(table_name_items) == 1:\n schema_name = None\n elif len(table_name_items) == 2:\n schema_name, table_name = table_name_items\n else:\n raise ValueError(\"Cannot determine schema/table name from input {}\".format(table_name))\n return schema_name, table_name"],"string":"[\n \"def get_geometry_type(self, table_name, description):\\n with self.connection.cursor() as cursor:\\n cursor.execute(\\n \\\"\\\"\\\"\\n SELECT t.coord_dimension, t.srid, t.type FROM (\\n SELECT * FROM geometry_columns\\n UNION ALL\\n SELECT * FROM geography_columns\\n ) AS t WHERE t.f_table_name = %s AND t.f_geometry_column = %s\\n \\\"\\\"\\\",\\n (table_name, description.name),\\n )\\n row = cursor.fetchone()\\n if not row:\\n raise Exception(\\n 'Could not find a geometry or geography column for \\\"%s\\\".\\\"%s\\\"'\\n % (table_name, description.name)\\n )\\n dim, srid, field_type = row\\n # OGRGeomType does not require GDAL and makes it easy to convert\\n # from OGC geom type name to Django field.\\n field_type = OGRGeomType(field_type).django\\n # Getting any GeometryField keyword arguments that are not the default.\\n field_params = {}\\n if self.postgis_oid_lookup.get(description.type_code) == \\\"geography\\\":\\n field_params[\\\"geography\\\"] = True\\n if srid != 4326:\\n field_params[\\\"srid\\\"] = srid\\n if dim != 2:\\n field_params[\\\"dim\\\"] = dim\\n return field_type, field_params\",\n \"def get_field_type(connection, table_name, row):\\n field_params = OrderedDict()\\n field_notes = []\\n is_geometry = False\\n try:\\n field_type = connection.introspection.get_field_type(row[1], row)\\n except KeyError:\\n field_type = 'TextField'\\n field_notes.append('This field type is a guess.')\\n\\n # This is a hook for data_types_reverse to return a tuple of\\n # (field_type, field_params_dict).\\n if type(field_type) is tuple:\\n field_type, new_params = field_type\\n field_params.update(new_params)\\n\\n # Add max_length for all CharFields.\\n if field_type == 'CharField' and row[3]:\\n field_params['max_length'] = int(row[3])\\n\\n if field_type == 'DecimalField':\\n if row[4] is None or row[5] is None:\\n field_notes.append(\\n 'max_digits and decimal_places have been guessed, as this '\\n 'database handles decimal fields as float')\\n field_params['max_digits'] = row[4] if row[4] is not None else 10\\n field_params['decimal_places'] = row[\\n 5] if row[5] is not None else 5\\n else:\\n field_params['max_digits'] = row[4]\\n field_params['decimal_places'] = row[5]\\n\\n if field_type == 'GeometryField':\\n geo_col = row[0]\\n # Getting a more specific field type and any additional parameters\\n # from the `get_geometry_type` routine for the spatial backend.\\n field_type, geo_params = connection.introspection.get_geometry_type(\\n table_name, geo_col)\\n field_params.update(geo_params)\\n is_geometry = True\\n\\n return field_type, field_params, is_geometry\\n # return getattr(models.fields, field_type), field_params\",\n \"def get_table_info(self):\\n epsg = None\\n meta = MetaData()\\n table_obj = Table(self.table, meta,\\n autoload=True, autoload_with=self.engine)\\n if not self.columns:\\n self.columns = table_obj.columns.keys()\\n geo_cols = [(col.name, col.type) for col in table_obj.columns\\n if hasattr(col.type, 'srid')]\\n if geo_cols:\\n geo_col = geo_cols[0]\\n self.geom_column = geo_col[0]\\n geo_obj = geo_col[1]\\n if self.geom_column not in self.columns:\\n self.columns.append(self.geom_column)\\n if hasattr(geo_obj, 'srid'):\\n epsg = geo_obj.srid\\n if epsg == -1:\\n epsg = 4326\\n if hasattr(geo_obj, 'geometry_type'):\\n self.geometry_type = geo_obj.geometry_type\\n\\n self.epsg = epsg\\n self.table_obj = table_obj\\n self.meta = meta\",\n \"def get_table_info(self):\\n epsg = None\\n meta = MetaData()\\n table_obj = Table(self._table, meta,\\n autoload=True, autoload_with=self._engine)\\n if not self._columns:\\n self._columns = table_obj.columns.keys()\\n geo_cols = [(col.name, col.type) for col in table_obj.columns\\n if hasattr(col.type, 'srid')]\\n if geo_cols:\\n geo_col = geo_cols[0]\\n self._geom_column = geo_col[0]\\n geo_obj = geo_col[1]\\n if self._geom_column not in self._columns:\\n self._columns.append(self._geom_column)\\n if hasattr(geo_obj, 'srid'):\\n epsg = geo_obj.srid\\n if epsg == -1:\\n epsg = 4326\\n if hasattr(geo_obj, 'geometry_type'):\\n self._geometry_type = geo_obj.geometry_type\\n\\n self._epsg = epsg\\n self._table_obj = table_obj\\n self._meta = meta\",\n \"def getGeometryColumnDef(self, schema, table, column):\\r\\n defs = self.fetchSqlRecords(\\r\\n \\\"select type, srid from geometry_columns where f_table_schema='{}' and f_table_name='{}' and f_geometry_column='{}'\\\".format(schema, table, column))\\r\\n if not len(defs) == 1:\\r\\n return None\\r\\n\\r\\n return 'geometry({},{})'.format(defs[0][0], defs[0][1])\",\n \"def get_geom_type(carto_sql_client, tablename):\\n geomtypes = {'ST_Point': 'point',\\n 'ST_MultiPoint': 'point',\\n 'ST_LineString': 'line',\\n 'ST_MultiLineString': 'line',\\n 'ST_Polygon': 'polygon',\\n 'ST_MultiPolygon': 'polygon'}\\n\\n # NOTE: assumes one geometry type per table\\n result = carto_sql_client.send('''\\n SELECT ST_GeometryType(the_geom) As geomtype\\n FROM \\\"{tablename}\\\"\\n WHERE the_geom IS NOT NULL\\n LIMIT 1'''.format(tablename=tablename))\\n try:\\n return geomtypes[result['rows'][0]['geomtype']]\\n except (KeyError, IndexError):\\n print((\\\"Cannot create a map from `{tablename}` because this table \\\"\\n \\\"does not have geometries ({geomreported})\\\").format(\\n tablename=tablename,\\n geomreported=None))\\n return None\\n except Exception as err:\\n print(\\\"ERROR: {}\\\".format(err))\\n return None\",\n \"def get_schema(schema): # noqa: E501\\n return 'do some magic!'\",\n \"def _get_table_reflection(self, schema: str, table: str) -> Table:\\n return self.sql_metadata.tables.get(f\\\"{schema}.{table}\\\",\\n Table(table, self.sql_metadata, schema=schema, autoload=True))\",\n \"def schema(self):\\n return self.table_info.schema\",\n \"def get_schema(self) -> dict:\",\n \"def _get_fields(self, table):\\n fields = list()\\n for column in table.columns:\\n fields.append({'id': column.name, 'type': str(column.type)})\\n return fields\",\n \"def getTableSchema(self,tableName):\\n\\tif not self.schemaDict.has_key(tableName):\\n\\t if self.dbType==\\\"sqlite\\\":\\n\\t query = \\\"SELECT * FROM sqlite_master WHERE name='%s'\\\"%tableName\\n\\t tup = self.fetchOne(query)\\n\\t schema= tup[4]\\n\\t else: # MySQL \\n\\t query = \\\"DESCRIBE %s\\\"%tableName\\n\\t tup = self.fetchAll(query)\\n\\t schema= \\\"CREATE TABLE %s (\\\"%tableName\\n\\t for item in tup:\\n\\t name = item[0]\\n\\t\\t type = item[1]\\n\\t\\t priKey = item[3]\\n\\t\\t autoInc = item[5] \\n\\t schema+=name+' '+type+' '+priKey+' '+autoInc\\n\\t\\t if item!=tup[-1]:\\n\\t\\t schema+=','\\n\\t schema+=\\\" )\\\"\\n\\t return schema\\n\\telse:\\n\\t return self.schemaDict[tableName]\",\n \"def get_gtfs_field_tuple_from_table(table_name, gtfs_spec=None):\\n if not gtfs_spec:\\n gtfs_spec = settings.GTFS_SPEC\\n choice_tuple = choice_tuple = (('',''),)\\n for t in gtfs_spec['resources']:\\n if t['name'] == table_name:\\n for f in t['schema']['fields']:\\n choice_tuple = choice_tuple + ((f['name'], f['name']),)\\n return choice_tuple\\n raise ValueError(\\\"Table name not found in GTFS spec.\\\")\",\n \"def split_table_schema(table_name):\\r\\n\\r\\n split = table_name.split('.')\\r\\n if len(split) > 1:\\r\\n return (split[0], split[1])\\r\\n else:\\r\\n return (None, split[0])\",\n \"def get_schema(self, repo, table):\\n return self.user_con.get_schema(repo=repo, table=table)\",\n \"def parse_table_schema(conn):\\r\\n cur = conn.cursor()\\r\\n\\r\\n cur.execute(\\\"PRAGMA table_info({})\\\".format(\\\"week5\\\"))\\r\\n print(cur.fetchall())\",\n \"def postgis_metadata(self, data_source_id, schema, table_name):\\n metadata = {}\\n\\n try:\\n engine = self.engine_for_data_source(data_source_id)\\n if engine is None:\\n return {\\n 'error': \\\"FEHLER: DataSource nicht gefunden\\\"\\n }\\n\\n # connect to data_source\\n conn = engine.connect()\\n\\n # get primary key\\n\\n # build query SQL\\n sql = sql_text(\\\"\\\"\\\"\\n SELECT a.attname\\n FROM pg_index i\\n JOIN pg_attribute a ON a.attrelid = i.indrelid\\n AND a.attnum = ANY(i.indkey)\\n WHERE i.indrelid = '{schema}.{table}'::regclass\\n AND i.indisprimary;\\n \\\"\\\"\\\".format(schema=schema, table=table_name))\\n\\n # execute query\\n primary_key = None\\n result = conn.execute(sql)\\n for row in result:\\n primary_key = row['attname']\\n\\n # get geometry column and srid\\n\\n # build query SQL\\n sql = sql_text(\\\"\\\"\\\"\\n SELECT f_geometry_column, srid, type\\n FROM geometry_columns\\n WHERE f_table_schema = '{schema}' AND f_table_name = '{table}';\\n \\\"\\\"\\\".format(schema=schema, table=table_name))\\n\\n # execute query\\n geometry_columns = []\\n result = conn.execute(sql)\\n for row in result:\\n geometry_columns.append({\\n 'geometry_column': row['f_geometry_column'],\\n 'geometry_type': row['type'],\\n 'srid': row['srid']\\n })\\n\\n # close database connection\\n conn.close()\\n\\n metadata = {\\n 'schema': schema,\\n 'table': table_name,\\n 'primary_key': primary_key,\\n 'geometry_columns': geometry_columns\\n }\\n except OperationalError as e:\\n self.logger.error(e.orig)\\n return {\\n 'error': \\\"OperationalError: %s\\\" % e.orig\\n }\\n except ProgrammingError as e:\\n self.logger.error(e.orig)\\n return {\\n 'error': \\\"ProgrammingError: %s\\\" % e.orig\\n }\\n\\n return metadata\",\n \"def get_schema(self):\\r\\n return self.__schema\",\n \"def get_schema(self):\\n return ', '.join('%s:%s' % (col, self.schema[col]) for col in self.schema)\",\n \"def _get_model_class_from_table(self, table):\\r\\n try:\\r\\n model_class = [m for m in get_models() if connection.introspection.table_name_converter(m._meta.db_table) in map(connection.introspection.table_name_converter,[table])][0] \\r\\n m2m = False \\r\\n except IndexError:\\r\\n try: \\r\\n # this is a many to many field \\r\\n model_class = [f.rel.to for m in get_models() for f in m._meta.local_many_to_many if f.m2m_db_table() == table][0] \\r\\n m2m = True \\r\\n except IndexError: \\r\\n # this is an inner join \\r\\n table = self.query.alias_map[table][0]\\r\\n return self._get_model_class_from_table(table)\\r\\n return model_class, m2m\",\n \"def fields_from_table(table):\\r\\n\\r\\n fields = []\\r\\n\\r\\n for column in table.columns:\\r\\n field = brewery.metadata.Field(name=column.name)\\r\\n field.concrete_storage_type = column.type\\r\\n\\r\\n for conv in _sql_to_brewery_types:\\r\\n if issubclass(column.type.__class__, conv[0]):\\r\\n field.storage_type = conv[1]\\r\\n field.analytical_type = conv[2]\\r\\n break\\r\\n\\r\\n if not field.storage_type:\\r\\n field.storaget_tpye = \\\"unknown\\\"\\r\\n\\r\\n if not field.analytical_type:\\r\\n field.analytical_type = \\\"unknown\\\"\\r\\n\\r\\n fields.append(field)\\r\\n\\r\\n return brewery.metadata.FieldList(fields)\",\n \"def get_table_definition(jwt_payload: dict, schema_name: str, table_name: str):\\n DJConnector.set_datajoint_config(jwt_payload)\\n\\n schema_virtual_module = dj.create_virtual_module(schema_name, schema_name)\\n return getattr(schema_virtual_module, table_name).describe()\",\n \"def get_schema(cls):\\n return cls.schema()\",\n \"def get_schema() -> dict:\\n raise NotImplementedError()\",\n \"def _get_schema(self):\\n self._pick()\\n return Schema()\",\n \"def get_geometries ( self, object_class_table, spatial_column, select_column, select_id ) :\\n stmt = 'select sdo_util.to_wktgeometry(' + str(spatial_column) + ') from ' + str(object_class_table) + ' where ' + str(select_column) + ' = ' + str(select_id)\\n self.oracle_cursor.execute( stmt )\\n resultset = self.oracle_cursor.fetchall()\\n return resultset\",\n \"def get_table_info(line):\\n\\n COMMENT_EXPR = '-- Name: '\\n TYPE_EXPR = '; Type: '\\n SCHEMA_EXPR = '; Schema: '\\n OWNER_EXPR = '; Owner: '\\n TABLESPACE_EXPR = '; Tablespace: '\\n\\n temp = line.strip('\\\\n')\\n type_start = get_all_occurrences(TYPE_EXPR, temp)\\n schema_start = get_all_occurrences(SCHEMA_EXPR, temp)\\n owner_start = get_all_occurrences(OWNER_EXPR, temp)\\n tblspace_start = get_all_occurrences(TABLESPACE_EXPR, temp)\\n if len(type_start) != 1 or len(schema_start) != 1 or len(owner_start) != 1:\\n return (None, None, None, None)\\n name = temp[len(COMMENT_EXPR) : type_start[0]]\\n type = temp[type_start[0] + len(TYPE_EXPR) : schema_start[0]]\\n schema = temp[schema_start[0] + len(SCHEMA_EXPR) : owner_start[0]]\\n if not tblspace_start:\\n tblspace_start.append(None)\\n owner = temp[owner_start[0] + len(OWNER_EXPR) : tblspace_start[0]]\\n return (name, type, schema, owner)\",\n \"def read_schema_from_db(cur, table):\\n num_rows = cur.execute(\\\"\\\"\\\"DESCRIBE {}\\\"\\\"\\\".format(table))\\n tbl_schema = []\\n for i in range(num_rows):\\n row = cur.fetchone()\\n tbl_schema.append([row[0], row[1]])\\n return tbl_schema\",\n \"def schema_ref(schema, table):\\n return schema + '.' + table\",\n \"async def _get_schema_info(self, app_id, namespace, gae_index_name):\\n collection = get_collection_name(app_id, namespace, gae_index_name)\\n solr_schema_info = await self.solr.get_schema_info(collection)\\n fields_info = solr_schema_info['fields']\\n id_field = SolrSchemaFieldInfo(\\n solr_name='id', gae_name='doc_id', type=Field.Type.ATOM,\\n language=None, docs_number=fields_info.get('id', {}).get('docs', 0)\\n )\\n rank_field = SolrSchemaFieldInfo(\\n solr_name='rank', gae_name='rank', type=Field.Type.NUMBER,\\n language=None, docs_number=fields_info.get('rank', {}).get('docs', 0)\\n )\\n fields = [id_field, rank_field]\\n grouped_fields = {\\n 'doc_id': [id_field],\\n 'rank': [rank_field]\\n }\\n facets = []\\n grouped_facet_indexes = {}\\n\\n for solr_field_name, info in fields_info.items():\\n try:\\n gae_name, type_, language = parse_solr_field_name(solr_field_name)\\n except ValueError:\\n continue\\n schema_field = SolrSchemaFieldInfo(\\n solr_field_name, gae_name, type_, language, info.get('docs', 0)\\n )\\n if SolrSchemaFieldInfo.Type.is_facet_index(type_):\\n add_value(grouped_facet_indexes, gae_name, schema_field)\\n if SolrSchemaFieldInfo.Type.is_facet(type_):\\n facets.append(schema_field)\\n else:\\n fields.append(schema_field)\\n add_value(grouped_fields, gae_name, schema_field)\\n\\n for fields_group in grouped_fields.values():\\n if len(fields_group) > 1:\\n # Sadly app uses the same name for fields with different types [*1].\\n # Let's sort them from high popularity to low.\\n fields_group.sort(key=lambda solr_field: -solr_field.docs_number)\\n\\n for facets_group in grouped_facet_indexes.values():\\n if len(facets_group) > 1:\\n # Sadly app uses the same name for facets with different types [*1].\\n # Let's sort them from high popularity to low.\\n facets_group.sort(key=lambda solr_field: -solr_field.docs_number)\\n\\n index_info = solr_schema_info['index']\\n return SolrIndexSchemaInfo(\\n app_id=app_id,\\n namespace=namespace,\\n gae_index_name=gae_index_name,\\n collection=collection,\\n docs_number=index_info['numDocs'],\\n heap_usage=index_info['indexHeapUsageBytes'],\\n size_in_bytes=index_info['segmentsFileSizeInBytes'],\\n fields=fields,\\n facets=facets,\\n grouped_fields=grouped_fields,\\n grouped_facet_indexes=grouped_facet_indexes\\n )\",\n \"def get_schema(db, sourcename):\\n try:\\n schema = db[\\\"tables\\\"][sourcename]\\n schema[\\\"type\\\"] = constants.TABLE\\n except KeyError:\\n try:\\n schema = db[\\\"views\\\"][sourcename]\\n schema[\\\"type\\\"] = constants.VIEW\\n except KeyError:\\n raise ValueError(\\\"no such table/view\\\")\\n return schema\",\n \"def get_field_type(field, table):\\n for i in settings.GTFS_SPEC['resources']:\\n print(i['name'])\\n if i['name'] == table:\\n for j in i['schema']['fields']:\\n print(j['name'])\\n if j['name'] == field:\\n return j['gtfs_type']\\n raise ValueError(\\\"Field not found in GTFS spec.\\\")\",\n \"def get_schema(self):\\n return ', '.join(\\n '%s:%s' % (col, self.schema[col]) for col in self.schema)\",\n \"def get_schema(self) -> dict:\\n return schemas.get_object_schema(self.schema)\",\n \"def Result(row, schema):\\r\\n return dict(zip(schema.fields(), row))\",\n \"def model_table():\\r\\n class OccupationTable(tables.Table):\\r\\n class Meta:\\r\\n model = Occupation\\r\\n assert [\\\"id\\\", \\\"name\\\", \\\"region\\\"] == list(OccupationTable.base_columns.keys())\\r\\n\\r\\n class OccupationTable2(tables.Table):\\r\\n extra = tables.Column()\\r\\n\\r\\n class Meta:\\r\\n model = Occupation\\r\\n assert [\\\"id\\\", \\\"name\\\", \\\"region\\\", \\\"extra\\\"] == list(OccupationTable2.base_columns.keys())\\r\\n\\r\\n # be aware here, we already have *models* variable, but we're importing\\r\\n # over the top\\r\\n from django.db import models\\r\\n\\r\\n class ComplexModel(models.Model):\\r\\n char = models.CharField(max_length=200)\\r\\n fk = models.ForeignKey(\\\"self\\\")\\r\\n m2m = models.ManyToManyField(\\\"self\\\")\\r\\n\\r\\n class ComplexTable(tables.Table):\\r\\n class Meta:\\r\\n model = ComplexModel\\r\\n assert [\\\"id\\\", \\\"char\\\", \\\"fk\\\"] == list(ComplexTable.base_columns.keys())\",\n \"def as_tuple(self) -> tuple[typing.Any, ...]:\\n return tuple(getattr(self, field.name) for field in Schema)\",\n \"def schema(self):\",\n \"def fetch_table_schema(self, table_name):\\n ddl = self.query(sql.show_create_table(table_name))\\n if ddl:\\n try:\\n return parse_create(ddl[0][\\\"Create Table\\\"])\\n except ParseError as e:\\n raise OSCError(\\n \\\"TABLE_PARSING_ERROR\\\",\\n {\\\"db\\\": self._current_db, \\\"table\\\": self.table_name, \\\"msg\\\": str(e)},\\n )\",\n \"def info_from_geo_field(geo_field):\\n\\n geo_field_name = geo_field.name\\n\\n get_geom = lambda obj: getattr(obj, geo_field_name)\\n\\n if hasattr(geo_field, 'geom_type'):\\n geom_type = geo_field.geom_type\\n else:\\n geom_type = geo_field._geom\\n\\n if hasattr(geo_field, 'srid'):\\n srid = geo_field.srid\\n else:\\n srid = geo_field._srid\\n\\n return get_geom, geom_type, srid\",\n \"def schema_to_features(schema: TableSchema) -> List[LiteFeature]:\\n features = []\\n for col_name, column_schema in schema.columns.items():\\n assert isinstance(column_schema, ColumnSchema)\\n\\n logical_type = column_schema.logical_type\\n assert logical_type\\n assert issubclass(type(logical_type), LogicalType)\\n\\n tags = column_schema.semantic_tags\\n assert isinstance(tags, set)\\n\\n features.append(\\n LiteFeature(\\n name=col_name,\\n logical_type=type(logical_type),\\n tags=tags,\\n ),\\n )\\n\\n return features\",\n \"def retrieve_shapely(osm_path,geoType,keyCol,**valConstraint):\\n driver=ogr.GetDriverByName('OSM')\\n data = driver.Open(osm_path)\\n query = query_b(geoType,keyCol,**valConstraint)\\n sql_lyr = data.ExecuteSQL(query)\\n features =[]\\n # cl = columns \\n cl = ['osm_id'] \\n for a in keyCol: cl.append(a)\\n if data is not None:\\n print('query is finished, lets start the loop')\\n for feature in tqdm(sql_lyr):\\n try:\\n if feature.GetField(keyCol[0]) is not None:\\n geom = loads(feature.geometry().ExportToWkb()) \\n if geom is None:\\n continue\\n # field will become a row in the dataframe.\\n field = []\\n for i in cl: field.append(feature.GetField(i))\\n field.append(geom) \\n features.append(field)\\n except:\\n print(\\\"WARNING: skipped OSM feature\\\") \\n else:\\n print(\\\"ERROR: Nonetype error when requesting SQL. Check required.\\\") \\n cl.append('geometry') \\n if len(features) > 0:\\n return geopandas.GeoDataFrame(features,columns=cl,crs={'init': 'epsg:4326'})\\n else:\\n print(\\\"WARNING: No features or No Memory. returning empty GeoDataFrame\\\") \\n return geopandas.GeoDataFrame(columns=['osm_id','geometry'],crs={'init': 'epsg:4326'})\",\n \"def schema(cls, only_self: bool=False):\\n try:\\n md_tbls = cls.metadata.tables\\n insp = reflection.Inspector.from_engine(cls.s.bind.engine)\\n tbls = dict()\\n for tbl in insp.get_table_names():\\n if not only_self or (only_self and tbl == cls.__tablename__):\\n cols = dict()\\n for col in insp.get_columns(tbl):\\n info = dict(col)\\n col_info = md_tbls[tbl].c[col['name']]\\n info['type'] = {\\n 'compiled': col['type'].compile(),\\n 'native': col['type'].python_type.__name__\\n }\\n info['type']['length'] = col['type'].length if hasattr(col['type'], 'length') else None\\n if info['autoincrement']:\\n info['default'] = 'autoincrement'\\n info.update(col_info.info)\\n info['placeholder'] = '%s_%s' % (tbl, col['name'])\\n cols[col['name']] = info\\n tbls[tbl] = cols\\n\\n return tbls\\n except SQLAlchemyError:\\n cls.s.rollback()\\n raise\",\n \"def get_schema(self, get_stats=False):\\n query = \\\"schema {}\\\"\\n\\n results = self.run_dgraph_query_raw(query)\\n\\n schema = {}\\n\\n for row in results[\\\"schema\\\"]:\\n table_name = row[\\\"predicate\\\"]\\n\\n if table_name not in schema:\\n schema[table_name] = {\\\"name\\\": table_name, \\\"columns\\\": []}\\n\\n return list(schema.values())\",\n \"def build_schema(self):\\n field_defs = []\\n fields = []\\n point_rows = []\\n line_rows = []\\n polygon_rows = []\\n for i in self.json_in['features']: # first iterate through it all and get all the fields\\n props = i.get('properties')\\n\\n for k, v in props.items():\\n if k not in fields:\\n fields.append(k)\\n\\n for i in self.json_in['features']: # now fill in any props that any features are missing, and sort them all\\n geom = i['geometry']\\n props = i['properties']\\n for f in fields:\\n if f not in props.keys():\\n props[f] = ''\\n props = OrderedDict(sorted(props.items()))\\n\\n for k, v in props.items():\\n schema_row = [k, \\\"TEXT\\\", k.replace('_', ' '), 256]\\n if schema_row not in field_defs:\\n field_defs.append(schema_row)\\n row = [str(v) for k, v in sorted(props.items())] # coerce everything to str cause this stuff is a mess\\n parsed_geom = GeoJSONUtils.parse_geometry(geom)\\n geotype = parsed_geom['type']\\n egeom = parsed_geom['esri_geom']\\n\\n if geotype == \\\"POINT\\\":\\n row.insert(0, egeom)\\n print(row)\\n point_rows.append(row)\\n elif geotype == \\\"POLYLINE\\\":\\n row.insert(0, egeom)\\n print(row)\\n line_rows.append(row)\\n else:\\n row.insert(0, egeom)\\n print(row)\\n polygon_rows.append(row)\\n\\n return {\\n \\\"fields\\\": fields,\\n \\\"field_defs\\\": field_defs,\\n \\\"rows\\\": [point_rows, line_rows, polygon_rows]\\n }\",\n \"def _get_table(self, cursor):\\n raise NotImplementedError\",\n \"def transform_schema(pgschema):\\n datatypes = {}\\n for field in pgschema:\\n if 'cartodb_id' in field:\\n continue\\n datatypes[field] = map_dtypes(pgschema[field]['type'])\\n return datatypes\",\n \"def info_table(table):\\n print \\\"\\\\nSCHEMA de la taula \\\",table, \\\"es: \\\"\\n con=lite.connect('parking.db')\\n cur=con.cursor()\\n cur.execute(\\\"PRAGMA table_info({});\\\".format(table))\\n data = cur.fetchall()\\n for d in data:\\n print \\\"\\\\t\\\",d[0], d[1], d[2]\\n con.close()\",\n \"def fetch_tuples(jwt_payload: dict, schema_name: str, table_name: str):\\n DJConnector.set_datajoint_config(jwt_payload)\\n\\n schema_virtual_module = dj.create_virtual_module(schema_name, schema_name)\\n\\n # Get the table object refernece\\n table = getattr(schema_virtual_module, table_name)\\n\\n # Fetch tuples without blobs as dict to be used to create a\\n # list of tuples for returning\\n non_blobs_rows = table.fetch(*table.heading.non_blobs, as_dict=True,\\n limit=DEFAULT_FETCH_LIMIT)\\n\\n # Buffer list to be return\\n rows = []\\n\\n # Looped through each tuple and deal with TEMPORAL types and replacing\\n # blobs with ==BLOB== for json encoding\\n for non_blobs_row in non_blobs_rows:\\n # Buffer object to store the attributes\\n row = []\\n # Loop through each attributes, append to the tuple_to_return with specific\\n # modification based on data type\\n for attribute_name, attribute_info in table.heading.attributes.items():\\n if not attribute_info.is_blob:\\n if non_blobs_row[attribute_name] is None:\\n # If it is none then just append None\\n row.append(None)\\n elif attribute_info.type == 'date':\\n # Date attribute type covert to epoch time\\n row.append((non_blobs_row[attribute_name] -\\n datetime.date(1970, 1, 1)).days * DAY)\\n elif attribute_info.type == 'time':\\n # Time attirbute, return total seconds\\n row.append(non_blobs_row[attribute_name].total_seconds())\\n elif attribute_info.type in ('datetime', 'timestamp'):\\n # Datetime or timestamp, use timestamp to covert to epoch time\\n row.append(non_blobs_row[attribute_name].timestamp())\\n elif attribute_info.type[0:7] == 'decimal':\\n # Covert decimal to string\\n row.append(str(non_blobs_row[attribute_name]))\\n else:\\n # Normal attribute, just return value with .item to deal with numpy\\n # types\\n if isinstance(non_blobs_row[attribute_name], np.generic):\\n row.append(np.asscalar(non_blobs_row[attribute_name]))\\n else:\\n row.append(non_blobs_row[attribute_name])\\n else:\\n # Attribute is blob type thus fill it in string instead\\n row.append('=BLOB=')\\n\\n # Add the row list to tuples\\n rows.append(row)\\n return rows\",\n \"def schema(self) -> 'outputs.TableSchemaResponse':\\n return pulumi.get(self, \\\"schema\\\")\",\n \"def get_tables_name_and_type(self) -> Optional[Iterable[Tuple[str, str]]]:\\n try:\\n schema_name = self.context.database_schema.name.__root__\\n if self.source_config.includeTables:\\n for table_and_type in self.query_table_names_and_types(schema_name):\\n table_name = self.standardize_table_name(\\n schema_name, table_and_type.name\\n )\\n table_fqn = fqn.build(\\n self.metadata,\\n entity_type=Table,\\n service_name=self.context.database_service.name.__root__,\\n database_name=self.context.database.name.__root__,\\n schema_name=self.context.database_schema.name.__root__,\\n table_name=table_name,\\n skip_es_search=True,\\n )\\n if filter_by_table(\\n self.source_config.tableFilterPattern,\\n table_fqn\\n if self.source_config.useFqnForFiltering\\n else table_name,\\n ):\\n self.status.filter(\\n table_fqn,\\n \\\"Table Filtered Out\\\",\\n )\\n continue\\n yield table_name, table_and_type.type_\\n\\n if self.source_config.includeViews:\\n for view_name in self.inspector.get_view_names(schema_name):\\n view_name = self.standardize_table_name(schema_name, view_name)\\n view_fqn = fqn.build(\\n self.metadata,\\n entity_type=Table,\\n service_name=self.context.database_service.name.__root__,\\n database_name=self.context.database.name.__root__,\\n schema_name=self.context.database_schema.name.__root__,\\n table_name=view_name,\\n )\\n\\n if filter_by_table(\\n self.source_config.tableFilterPattern,\\n view_fqn\\n if self.source_config.useFqnForFiltering\\n else view_name,\\n ):\\n self.status.filter(\\n view_fqn,\\n \\\"Table Filtered Out\\\",\\n )\\n continue\\n yield view_name, TableType.View\\n except Exception as err:\\n logger.warning(\\n f\\\"Fetching tables names failed for schema {schema_name} due to - {err}\\\"\\n )\\n logger.debug(traceback.format_exc())\",\n \"def _get_tabletype(cls) -> str:\\n raise NotImplementedError\",\n \"def set_schema():\\n schema = StructType([\\n StructField(\\\"cicid\\\",DoubleType(),True),\\n StructField(\\\"arrdate\\\",DoubleType(),True),\\n StructField(\\\"i94cit\\\",DoubleType(),True),\\n StructField(\\\"i94res\\\",DoubleType(),True),\\n StructField(\\\"i94port\\\",StringType(),True),\\n StructField(\\\"i94mode\\\",DoubleType(),True),\\n StructField(\\\"i94addr\\\",StringType(),True),\\n StructField(\\\"depdate\\\",DoubleType(),True), \\n StructField(\\\"i94bir\\\",DoubleType(),True),\\n StructField(\\\"i94visa\\\",DoubleType(),True),\\n StructField(\\\"gender\\\",StringType(),True),\\n StructField(\\\"airline\\\",StringType(),True),\\n StructField(\\\"visatype\\\",StringType(),True)])\\n return schema\",\n \"def get_schemas(self, conn):\\n return conn.get_schemas()['table_schema']\",\n \"def _get_model_from_table_name(table_name: str) -> Optional[Type[RDSModel]]:\\n table_model = None\\n try:\\n if hasattr(Base, '_decl_class_registry'):\\n models = Base._decl_class_registry.values() # sqlalchemy < 1.4\\n else:\\n models = Base.registry._class_registry.values()\\n\\n for model in models:\\n if hasattr(model, '__tablename__') and model.__tablename__ == table_name:\\n table_model = model\\n except Exception as e:\\n LOGGER.exception(f'Failed to get model for the table: {table_name} from rds model base')\\n raise e\\n\\n return table_model\",\n \"def guess_schema_from_model(model, tensor_type=None, schema=None):\\n if schema is not None:\\n try:\\n guessed = guess_schema_from_model(model)\\n except NotImplementedError: # pragma: no cover\\n return _replace_tensor_type(schema, tensor_type)\\n if len(guessed) != len(schema):\\n raise RuntimeError( # pragma: no cover\\n \\\"Given schema and guessed schema are not the same:\\\\nGOT: {}\\\\n-----\\\\nGOT:\\\\n{}\\\".format(\\n schema, guessed))\\n return _replace_tensor_type(schema, tensor_type)\\n\\n if hasattr(model, 'coef_'):\\n # linear model\\n init = [('X', FloatTensorType([None, model.coef_.shape[1]]))]\\n return _replace_tensor_type(init, tensor_type)\\n elif hasattr(model, 'dump_model'):\\n dumped = model.dump_model()\\n if isinstance(dumped, dict) and 'feature_names' in dumped:\\n names = dumped['feature_names']\\n init = [(name, FloatTensorType([None, 1])) for name in names]\\n return _replace_tensor_type(init, tensor_type)\\n\\n data = pprint.pformat(model.__dict__)\\n dirs = pprint.pformat(dir(model))\\n if hasattr(model, 'dump_model'): # pragma: no cover\\n dumped = model.dump_model()\\n keys = list(sorted(dumped))\\n last = pprint.pformat([keys, dumped])\\n if len(last) >= 200000:\\n last = last[:200000] + \\\"\\\\n...\\\"\\n else:\\n last = \\\"\\\"\\n raise NotImplementedError( # pragma: no cover\\n \\\"Unable to guess schema for model {}\\\\n{}\\\\n----\\\\n{}\\\\n------\\\\n{}\\\".format(\\n model.__class__, data, dirs, last))\",\n \"def __init__(self, schema_row):\\n self.schema = []\\n for field in schema_row['fields']:\\n self.schema.append(field['type'])\",\n \"def table(self, table: Union[str, sa.Table]) -> B[B, E]:\",\n \"def get_table_schema(dataset_id, table_id):\\n logging.info('getting table schema')\\n bigquery_client = bigquery.Client()\\n dataset_ref = bigquery_client.dataset(dataset_id)\\n bg_tableref = bigquery.table.TableReference(dataset_ref, table_id)\\n bg_table = bigquery_client.get_table(bg_tableref)\\n return bg_table.schema\",\n \"def schema(self):\\n raise NotImplementedError\",\n \"def build_song_schema():\\n schema = StructType(\\n [\\n StructField('artist_id', StringType(), True),\\n StructField('artist_latitude', DecimalType(), True),\\n StructField('artist_longitude', DecimalType(), True),\\n StructField('artist_location', StringType(), True),\\n StructField('artist_name', StringType(), True),\\n StructField('duration', DecimalType(), True),\\n StructField('num_songs', IntegerType(), True),\\n StructField('song_id', StringType(), True),\\n StructField('title', StringType(), True),\\n StructField('year', IntegerType(), True)\\n ]\\n )\\n return schema\",\n \"def _get_table(self):\\n\\t\\treturn self._table\",\n \"def getTableColumnDefs(self, schema, table):\\r\\n src_columns = self.fetchSqlRecords(\\r\\n \\\"select c.column_name, data_type, character_maximum_length, numeric_precision, numeric_scale from information_schema.columns c where c.table_schema = '{}' and c.table_name='{}'\\\".format(schema, table))\\r\\n return [dict(zip(('name', 'type', 'max_length', 'precision', 'scale'), c)) for c in src_columns]\",\n \"def schema() -> None:\\n pass\",\n \"def get_schema_cls() -> t.Any:\\n return None\",\n \"def _get_table_schema(self):\\n\\n return {\\n 'AttributeDefinitions': [\\n {\\n 'AttributeName': self._key_field.name,\\n 'AttributeType': self._key_field.data_type\\n }\\n ],\\n 'TableName': self.table_name,\\n 'KeySchema': [\\n {\\n 'AttributeName': self._key_field.name,\\n 'KeyType': 'HASH'\\n }\\n ],\\n 'ProvisionedThroughput': {\\n 'ReadCapacityUnits': self.read_capacity_units,\\n 'WriteCapacityUnits': self.write_capacity_units\\n }\\n }\",\n \"def get_field_type(self, table_name, field_name):\\n \\n dtype = self.field_types[(self.field_types.TABNAME == table_name) & (self.field_types.FIELDNAME == field_name)]['DATATYPE'].values[0] \\n return dtype\",\n \"def columns_type(self,table):\\n with self.conn.cursor() as cur:\\n #_logger.debug('Columns Query. sql: %r', self.table_columns_query)\\n cur.execute(self.columns_info_query % (self.dbname,table))\\n for row in cur:\\n yield row\",\n \"def _create_field_schema(col_schema: dict) -> bigquery.SchemaField:\\n name = to_safe_name(col_schema['name'])\\n return bigquery.SchemaField(\\n name,\\n col_schema.get('type'),\\n col_schema.get('mode', 'NULLABLE'),\\n col_schema.get('description', '')\\n )\",\n \"def get_table_definition(db_name, schema_name, table_name, server_name, data_partition_column_name='', excluded_columns=()):\\n server_name = '' if server_name == '127.0.0.1' or server_name == 'localhost' else server_name\\n server_name = f'[{server_name}].' if server_name else ''\\n\\n sql = (\\\"SELECT T.name AS TABLE_NAME, C.name AS COLUMN_NAME, P.name AS DATA_TYPE, \\\"\\n \\\"P.max_length AS SIZE, CAST(P.precision AS VARCHAR) + '/' + CAST(P.scale AS VARCHAR) AS PRECISION_SCALE, \\\"\\n \\\"c.* FROM {0}[{1}].sys.objects AS T JOIN {0}[{1}].sys.columns AS C ON T.object_id = C.object_id \\\"\\n \\\"JOIN {0}[{1}].sys.types AS P ON C.system_type_id = P.system_type_id \\\"\\n \\\"JOIN sys.schemas ss ON (T.schema_id = ss.schema_id) \\\"\\n \\\" WHERE T.type_desc = 'USER_TABLE' and ss.name = ? \\\"\\n \\\"and T.name = ? and P.name != 'timestamp' and P.name != 'sysname' order by column_id asc\\\").format(server_name, db_name)\\n\\n columns = fetch_rows(sql, [schema_name, table_name])\\n\\n target_table_column_prefix = get_config()['TARGET_TABLE_COLUMN_PREFIX']\\n out_columns = {}\\n\\n for column in columns:\\n column['original_data_type'] = column['data_type']\\n\\n if column['column_name'].upper() in default_columns:\\n column['target_table_column_name'] = target_table_column_prefix + column['column_name']\\n else:\\n column['target_table_column_name'] = column['column_name']\\n\\n # Update the data type for the data partition column\\n if data_partition_column_name != '' and column['column_name'].upper() == data_partition_column_name.upper():\\n column['data_type'] = 'datetime'\\n\\n out_columns[column['column_name'].upper()] = column\\n\\n if len(excluded_columns) > 0:\\n for excluded_column in excluded_columns:\\n out_columns.pop(excluded_column)\\n\\n return out_columns\",\n \"def get_table_by_person_id(table, person_id, schema=staging_schema, fields=\\\"default\\\"):\\n if fields == \\\"default\\\":\\n columns = \\\" * \\\"\\n elif fields == \\\"Edit\\\":\\n columns = \\\" [PersonID], [FirstName], [LastName], [SSN], [DOB], [Phone], [Email], [PersonType], [DataEntryLocationID], [AssignedInfectionStaff], [Note], [PartOfStudyYN], [StudyDetails], [PtHospitalizedYN], [PtCurrentLocationID], [PtHighComplicationRiskYN], [PtContactedYN], [PtDateLastContacted], [PtVABostonPCPYN], [PtPCPName], [PtPCPPhone], [EmplSupervisorName], [EmplSupervisorPhone], [EmplSupervisorNotifiedYN], [EmplIDNotifiedYN], [EmplEmployeeRole], [EmplCampus], [EmplCampusesOther], [EmplShiftSchedule], [EmplWorkLocation], [EmplPatientInteractionYN], [EmplSXSExposureWorkStartDate], [EmplSXSExposureWorkEndDate], [EmplWorkClearedYN1], [EmplReturnToWorkDate1] ,TestDate1, TestLocation1, TestResult1, TestDriveThruNeededYN1, CovidStatus1, AssignedProvider1, NumOfConsecutiveNegTestSinceLastPos1, TestDate2, TestLocation2, TestResult2, TestDriveThruNeededYN2, CovidStatus2, AssignedProvider2, NumOfConsecutiveNegTestSinceLastPos2, TestDate3, TestLocation3, TestResult3, TestDriveThruNeededYN3, CovidStatus3, AssignedProvider3, NumOfConsecutiveNegTestSinceLastPos3, TestDate4, TestLocation4, TestResult4, TestDriveThruNeededYN4, CovidStatus4, AssignedProvider4, NumOfConsecutiveNegTestSinceLastPos4, TestDate5, TestLocation5, TestResult5, TestDriveThruNeededYN5, CovidStatus5, AssignedProvider5, NumOfConsecutiveNegTestSinceLastPos5, TestDate6, TestLocation6, TestResult6, TestDriveThruNeededYN6, CovidStatus6, AssignedProvider6, NumOfConsecutiveNegTestSinceLastPos6, TestDate7, TestLocation7, TestResult7, TestDriveThruNeededYN7, CovidStatus7, AssignedProvider7, NumOfConsecutiveNegTestSinceLastPos7, TestDate8, TestLocation8, TestResult8, TestDriveThruNeededYN8, CovidStatus8, AssignedProvider8, NumOfConsecutiveNegTestSinceLastPos8, TestDate9, TestLocation9, TestResult9, TestDriveThruNeededYN9, CovidStatus9, AssignedProvider9, NumOfConsecutiveNegTestSinceLastPos9, TestDate10, TestLocation10, TestResult10, TestDriveThruNeededYN10, CovidStatus10, AssignedProvider10, NumOfConsecutiveNegTestSinceLastPos10, [QuarantinedYN1], [QuarantineStartDate1], [QuarantineEndDate1], [QuarantineSymptomTrackerYN1], [QuarantinedYN2], [QuarantineStartDate2], [QuarantineEndDate2], [QuarantineSymptomTrackerYN2], [QuarantinedYN3], [QuarantineStartDate3], [QuarantineEndDate3], [QuarantineSymptomTrackerYN3], [QuarantinedYN4], [QuarantineStartDate4], [QuarantineEndDate4], [QuarantineSymptomTrackerYN4], [QuarantinedYN5], [QuarantineStartDate5], [QuarantineEndDate5], [QuarantineSymptomTrackerYN5], [LocationChangeDateTime1], [LocationChangeNewLocationID1], [LocationChangeDateTime2], [LocationChangeNewLocationID2], [LocationChangeDateTime3], [LocationChangeNewLocationID3], [LocationChangeDateTime4], [LocationChangeNewLocationID4], [LocationChangeDateTime5], [LocationChangeNewLocationID5], [ExposureDate1], [ExposureType1], [ExposureLocation1], [ExposureDetails1], [ExposureDate2], [ExposureType2], [ExposureLocation2], [ExposureDetails2], [ExposureDate3], [ExposureType3], [ExposureLocation3], [ExposureDetails3], [ExposureDate4], [ExposureType4], [ExposureLocation4], [ExposureDetails4], [ExposureDate5], [ExposureType5], [ExposureLocation5], [ExposureDetails5], [SymptomType1], [SymptomOnsetDate1], [SymptomOnsetLocationID1], [SymptomResolutionDate1], [SymptomResolutionLocationID1], [SymptomNote1], [SymptomType2], [SymptomOnsetDate2], [SymptomOnsetLocationID2], [SymptomResolutionDate2], [SymptomResolutionLocationID2], [SymptomNote2], [SymptomType3], [SymptomOnsetDate3], [SymptomOnsetLocationID3], [SymptomResolutionDate3], [SymptomResolutionLocationID3], [SymptomNote3], [SymptomType4], [SymptomOnsetDate4], [SymptomOnsetLocationID4], [SymptomResolutionDate4], [SymptomResolutionLocationID4], [SymptomNote4], [SymptomType5], [SymptomOnsetDate5], [SymptomOnsetLocationID5], [SymptomResolutionDate5], [SymptomResolutionLocationID5], [SymptomNote5], [SymptomType6], [SymptomOnsetDate6], [SymptomOnsetLocationID6], [SymptomResolutionDate6], [SymptomResolutionLocationID6], [SymptomNote6], [SymptomType7], [SymptomOnsetDate7], [SymptomOnsetLocationID7], [SymptomResolutionDate7], [SymptomResolutionLocationID7], [SymptomNote7], [SymptomType8], [SymptomOnsetDate8], [SymptomOnsetLocationID8], [SymptomResolutionDate8], [SymptomResolutionLocationID8], [SymptomNote8], [SymptomType9], [SymptomOnsetDate9], [SymptomOnsetLocationID9], [SymptomResolutionDate9], [SymptomResolutionLocationID9], [SymptomNote9], [SymptomType10], [SymptomOnsetDate10], [SymptomOnsetLocationID10], [SymptomResolutionDate10], [SymptomResolutionLocationID10], [SymptomNote10], [Sta3n], [DOD], [EmplWorkClearedYN2], [EmplReturnToWorkDate2], [EmplWorkClearedYN3], [EmplReturnToWorkDate3], [EmplWorkClearedYN4], [EmplReturnToWorkDate4], [EmplWorkClearedYN5], [EmplReturnToWorkDate5], [StreetAddress], [City], [County], [State], [Zip] \\\"\\n elif fields == \\\"Detail\\\":\\n columns = \\\" SSN4, LastName, FirstName, DOB, DOD, Phone, Email, PersonType, AdmitStatus, RoomBed, WardLocationName, InstitutionName, PACT_Provider, PACT_Team, PACT_Phone, CDWUpdatedDateTime \\\"\\n\\n q = \\\"select {columns} from {schema}.{table} where PersonID = ?\\\"\\n q = q.format(columns=columns, schema=schema, table=table)\\n tb = pd.read_sql(q, engine, params=[person_id])\\n return tb\",\n \"def _get_geometry(self):\\r\\n if self._geometry_column_name not in self.columns:\\r\\n raise AttributeError(\\\"Geometry Column Not Present: %s\\\" % self._geometry_column_name)\\r\\n return self[self._geometry_column_name]\",\n \"async def get_schema_info(self, collection):\\n await self.ensure_collection(collection)\\n try:\\n # Luke handler is not supported in API v2 yet.\\n # /v2/collections//schema/fields doesn't show dynamically\\n # created fields.\\n # So using old API (/solr/...).\\n response = await self.get(\\n '/solr/{}/admin/luke?numTerms=0'.format(collection)\\n )\\n return json.loads(response.body.decode('utf-8'))\\n except SolrError:\\n logger.warning('Failed to fetch fields list for collection {}'\\n .format(collection))\\n raise\",\n \"def schema(self):\\n return self._schema\",\n \"def getSchema(cls):\\n pass\",\n \"def _get_schema(self):\\n self.to_dask()\\n return Schema(dtype=self._df.dtypes,\\n shape=(None, len(self._df.columns)),\\n npartitions=self._df.npartitions,\\n metadata=self.metadata)\",\n \"def _columns(cls, schema: dsl.Source.Schema) -> typing.Sequence[str]:\\n return tuple(f.name for f in schema)\",\n \"def ArrowSchema(self) -> pa.Schema:\",\n \"def _get_schema_using_query(self, query: str) -> sch.Schema:\\n return sch.Schema.from_tuples(self._metadata(query))\",\n \"def _get_table_obj(self, mode):\\n return self.client[f\\\"bigquery_{mode}\\\"].get_table(self.table_full_name[mode])\",\n \"def tableExists(self, schema, table):\\r\\n r = self.fetchSqlRecords(\\r\\n \\\"SELECT to_regclass('{}.{}')\\\".format(schema, table))\\r\\n return r[0][0]\",\n \"def _get_stored_schema(self, table: str) -> Optional[TableSchema]:\\n try:\\n with open(self.schemas / (table + '.json'), 'r') as f:\\n return json.load(f)\\n except FileNotFoundError:\\n return None\",\n \"def table(entity) -> sa.Table:\\n return entity.__table__\",\n \"def geo_field_from_model(model, default_geo_field_name=None):\\n try:\\n # If the class defines a geomfield property, use it !\\n return model.geomfield\\n except AttributeError:\\n pass\\n\\n fields = model._meta.fields\\n geo_fields = [f for f in fields if isinstance(f, GeometryField)]\\n\\n # Used for error case\\n geo_fields_names = lambda: ', '.join([f.name for f in geo_fields])\\n\\n if len(geo_fields) > 1:\\n if not default_geo_field_name:\\n raise ValueError(\\\"More than one geodjango geometry field found, please specify which to use by name using the 'geo_field' keyword. Available fields are: '%s'\\\" % geo_fields_names())\\n else:\\n geo_field_by_name = [fld for fld in geo_fields if fld.name == default_geo_field_name]\\n if not geo_field_by_name:\\n raise ValueError(\\\"Geodjango geometry field not found with the name '%s', fields available are: '%s'\\\" % (default_geo_field_name, geo_fields_names()))\\n else:\\n geo_field = geo_field_by_name[0]\\n elif geo_fields:\\n geo_field = geo_fields[0]\\n else:\\n raise ValueError('No geodjango geometry fields found in this model')\\n\\n return geo_field\",\n \"def get_table_attributes(jwt_payload: dict, schema_name: str, table_name: str):\\n DJConnector.set_datajoint_config(jwt_payload)\\n\\n schema_virtual_module = dj.create_virtual_module(schema_name, schema_name)\\n table_attributes = dict(primary_attributes=[], secondary_attributes=[])\\n for attribute_name, attribute_info in getattr(schema_virtual_module,\\n table_name).heading.attributes.items():\\n if attribute_info.in_key:\\n table_attributes['primary_attributes'].append((\\n attribute_name,\\n attribute_info.type,\\n attribute_info.nullable,\\n attribute_info.default,\\n attribute_info.autoincrement\\n ))\\n else:\\n table_attributes['secondary_attributes'].append((\\n attribute_name,\\n attribute_info.type,\\n attribute_info.nullable,\\n attribute_info.default,\\n attribute_info.autoincrement\\n ))\\n\\n return table_attributes\",\n \"def guess_schema_from_data(X, tensor_type=None, schema=None):\\n init = guess_initial_types(X, schema)\\n if tensor_type is not None:\\n init = _replace_tensor_type(init, tensor_type)\\n # Grouping column\\n unique = set()\\n for _, col in init:\\n if len(col.shape) != 2:\\n return init # pragma: no cover\\n if col.shape[0] is not None:\\n return init # pragma: no cover\\n if len(unique) > 0 and col.__class__ not in unique:\\n return init # pragma: no cover\\n unique.add(col.__class__)\\n unique = list(unique)\\n return [('X', unique[0]([None, sum(_[1].shape[1] for _ in init)]))]\",\n \"def modelfields(entity) -> Dict[str, Field]:\\n return entity.__modelfields__\",\n \"def get_schema(self) -> ArchiveSchema:\\n return self.schema\",\n \"def get_schema(self):\\n response = self.client.get(self._get_collection_url('schema'))\\n\\n return response.get('schema', {})\",\n \"def schema(self):\\n pass\",\n \"def resolve_schema_instance(schema: Union[BaseModel, str]) -> BaseModel:\\n from smpa.schemas.core import CoreGetSchema, CoreListSchema\\n from smpa.schemas.auth import LoginSchema\\n\\n if schema == 'CoreListSchema':\\n return CoreListSchema\\n elif schema == 'CoreGetSchema':\\n return CoreGetSchema\\n elif schema == 'LoginSchema':\\n return LoginSchema\\n\\n if isinstance(schema, type) and issubclass(schema, BaseModel):\\n return schema()\\n if isinstance(schema, BaseModel):\\n return schema\\n try:\\n return model_registry.get_class(schema)()\\n except RegistryError:\\n raise ValueError(\\n \\\"{!r} is not a BaseModel subclass or instance and has not\\\"\\n \\\" been registered in the model registry.\\\".format(schema)\\n )\",\n \"def get_model_schema(self, app, model):\\n model_schema = {\\n 'app': {\\n 'name': model._meta.app_label,\\n 'label': model._meta.app_config.verbose_name,\\n },\\n 'name': model._meta.model_name,\\n 'label': model._meta.verbose_name,\\n 'components': []\\n }\\n\\n for field in model._meta.get_fields():\\n # 排除不需要在前端构建form的field: id、反向关联field\\n # print('field', type(field), field)\\n if field.name == 'id':\\n continue\\n if isinstance(field, ForeignObjectRel):\\n # logger.info(\\\"ForeignObjectRel\\\", field)\\n continue\\n\\n component = self.get_field_data(model, field)\\n # logger.info('component', component)\\n model_schema['components'].append(component)\\n # print('get_model_schema', model_schema)\\n return model_schema\\n # return JsonResponse(model_schema)\",\n \"def create_staging_schema(cursor,table_schema):\\n create_schema = \\\"CREATE SCHEMA IF NOT EXISTS \\\" + table_schema + \\\";\\\"\\n cursor.execute(create_schema)\",\n \"def instance_schema(self):\\n raise NotImplementedError\",\n \"def query_table_names_and_types(\\n self, schema_name: str\\n ) -> Iterable[TableNameAndType]:\\n\\n return [\\n TableNameAndType(name=table_name)\\n for table_name in self.inspector.get_table_names(schema_name) or []\\n ]\",\n \"def _table_from_ft(ft_schema: dict) -> bigquery.Table:\\n # A \\\"TableSchema\\\" is just a sequence of SchemaFields https://googleapis.dev/python/bigquery/latest/generated/google.cloud.bigquery.table.Table.html\\n schema = list(map(_create_field_schema, ft_schema['columns']))\\n table = bigquery.Table(\\n bigquery.TableReference(ds, to_safe_name(ft_schema['name'])),\\n schema\\n )\\n table.description = ft_schema.get('description', '')\\n return table\",\n \"async def schema_state(appname, schema, table):\\n base = sprout.cfg.db_str(appname)\\n con = await asyncpg.connect(base)\\n req = ', '.join([\\n 'table_catalog',\\n 'table_schema',\\n 'table_name',\\n 'column_name',\\n 'data_type'\\n ])\\n q = f\\\"\\\"\\\"select {req} from information_schema.columns\\nwhere table_schema='{schema}' and table_name='{table}';\\\"\\\"\\\"\\n try:\\n ret = await con.fetch(q)\\n df = pd.DataFrame.from_records(ret, columns=ret[0].keys())\\n return df\\n except Exception as e:\\n sprout.cfg.log.error(f\\\"fetching current table state failed: {e}\\\")\\n finally:\\n await con.close()\",\n \"def get_schema() -> Dict[str, type]:\\n schema: Dict[str, type] = {}\\n\\n # Add all columns from pipeline configs\\n for pipeline in get_pipelines():\\n schema.update(pipeline.schema)\\n\\n # Add new columns from adapter\\n for col_old, col_new in OUTPUT_COLUMN_ADAPTER.items():\\n if col_old in schema and col_new is not None:\\n schema[col_new] = schema[col_old]\\n\\n return schema\",\n \"def build_song_schema():\\n schema = T.StructType(\\n [\\n T.StructField('artist_id', T.StringType(), True),\\n T.StructField('artist_latitude', T.DecimalType(), True),\\n T.StructField('artist_longitude', T.DecimalType(), True),\\n T.StructField('artist_location', T.StringType(), True),\\n T.StructField('artist_name', T.StringType(), True),\\n T.StructField('duration', T.DecimalType(), True),\\n T.StructField('num_songs', T.IntegerType(), True),\\n T.StructField('song_id', T.StringType(), True),\\n T.StructField('title', T.StringType(), True),\\n T.StructField('year', T.IntegerType(), True)\\n ]\\n )\\n return schema\",\n \"def _split_table_name(table_name):\\n table_name_items = table_name.split(\\\".\\\")\\n if len(table_name_items) == 1:\\n schema_name = None\\n elif len(table_name_items) == 2:\\n schema_name, table_name = table_name_items\\n else:\\n raise ValueError(\\\"Cannot determine schema/table name from input {}\\\".format(table_name))\\n return schema_name, table_name\"\n]"},"negative_scores":{"kind":"list like","value":["0.6816969","0.65374726","0.62112284","0.6156063","0.5837291","0.569644","0.56083405","0.55587506","0.55330145","0.547764","0.5454867","0.5441994","0.54250515","0.54212207","0.5413206","0.5390883","0.5313759","0.5281348","0.52764404","0.52503705","0.5214422","0.5203239","0.51881","0.5138209","0.5130797","0.512235","0.5115746","0.5110222","0.510605","0.5105856","0.5098519","0.50984675","0.5094267","0.5077075","0.50769687","0.50539136","0.50362164","0.501837","0.500501","0.49993223","0.49651104","0.4963914","0.49623787","0.49561557","0.49455547","0.49386814","0.49379078","0.49297807","0.49228823","0.49178168","0.4916689","0.49141946","0.49099532","0.4905032","0.48901516","0.48875237","0.4886075","0.48776555","0.48736033","0.4872982","0.48723057","0.4871822","0.4866216","0.48590702","0.4856022","0.4841703","0.48386475","0.4838168","0.4823492","0.4816273","0.48114282","0.48113325","0.48100972","0.48063752","0.48032632","0.47972527","0.4784114","0.47767892","0.4775406","0.47683606","0.47543156","0.47416347","0.47334343","0.4732999","0.47305095","0.47226188","0.471607","0.47125912","0.4711352","0.47081202","0.46973783","0.4689936","0.4689526","0.46844015","0.467885","0.46688756","0.4661925","0.46602398","0.46568164","0.46560115"],"string":"[\n \"0.6816969\",\n \"0.65374726\",\n \"0.62112284\",\n \"0.6156063\",\n \"0.5837291\",\n \"0.569644\",\n \"0.56083405\",\n \"0.55587506\",\n \"0.55330145\",\n \"0.547764\",\n \"0.5454867\",\n \"0.5441994\",\n \"0.54250515\",\n \"0.54212207\",\n \"0.5413206\",\n \"0.5390883\",\n \"0.5313759\",\n \"0.5281348\",\n \"0.52764404\",\n \"0.52503705\",\n \"0.5214422\",\n \"0.5203239\",\n \"0.51881\",\n \"0.5138209\",\n \"0.5130797\",\n \"0.512235\",\n \"0.5115746\",\n \"0.5110222\",\n \"0.510605\",\n \"0.5105856\",\n \"0.5098519\",\n \"0.50984675\",\n \"0.5094267\",\n \"0.5077075\",\n \"0.50769687\",\n \"0.50539136\",\n \"0.50362164\",\n \"0.501837\",\n \"0.500501\",\n \"0.49993223\",\n \"0.49651104\",\n \"0.4963914\",\n \"0.49623787\",\n \"0.49561557\",\n \"0.49455547\",\n \"0.49386814\",\n \"0.49379078\",\n \"0.49297807\",\n \"0.49228823\",\n \"0.49178168\",\n \"0.4916689\",\n \"0.49141946\",\n \"0.49099532\",\n \"0.4905032\",\n \"0.48901516\",\n \"0.48875237\",\n \"0.4886075\",\n \"0.48776555\",\n \"0.48736033\",\n \"0.4872982\",\n \"0.48723057\",\n \"0.4871822\",\n \"0.4866216\",\n \"0.48590702\",\n \"0.4856022\",\n \"0.4841703\",\n \"0.48386475\",\n \"0.4838168\",\n \"0.4823492\",\n \"0.4816273\",\n \"0.48114282\",\n \"0.48113325\",\n \"0.48100972\",\n \"0.48063752\",\n \"0.48032632\",\n \"0.47972527\",\n \"0.4784114\",\n \"0.47767892\",\n \"0.4775406\",\n \"0.47683606\",\n \"0.47543156\",\n \"0.47416347\",\n \"0.47334343\",\n \"0.4732999\",\n \"0.47305095\",\n \"0.47226188\",\n \"0.471607\",\n \"0.47125912\",\n \"0.4711352\",\n \"0.47081202\",\n \"0.46973783\",\n \"0.4689936\",\n \"0.4689526\",\n \"0.46844015\",\n \"0.467885\",\n \"0.46688756\",\n \"0.4661925\",\n \"0.46602398\",\n \"0.46568164\",\n \"0.46560115\"\n]"},"document_score":{"kind":"string","value":"0.54125166"},"document_rank":{"kind":"string","value":"15"}}},{"rowIdx":8563,"cells":{"query":{"kind":"string","value":"Runs a single userprovided line as a REPL input."},"document":{"kind":"string","value":"def handle_line(line: str, stmt_index: int):\n fn_name = f'repl_{stmt_index}'\n module_text = f\"\"\"\n import std\n fn {fn_name}() -> () {{\n {line}\n }}\n \"\"\"\n\n # For error reporting we use a helper that puts this into a fake filesystem\n # location.\n def make_fakefs_open():\n fs = fake_filesystem.FakeFilesystem()\n fs.CreateFile(FILENAME, module_text)\n return fake_filesystem.FakeFileOpen(fs)\n\n importer = import_helpers.Importer()\n\n while True:\n try:\n fake_module = parser.Parser(\n scanner.Scanner(FILENAME, module_text), fn_name).parse_module()\n except span.PositionalError as e:\n parser_helpers.pprint_positional_error(e, fs_open=make_fakefs_open())\n return\n\n # First attempt at type checking, we expect this may fail the first time\n # around and we'll substitute the real return type we observe.\n try:\n type_info = cpp_typecheck.check_module(fake_module, importer.cache,\n importer.additional_search_paths)\n except XlsTypeError as e:\n # We use nil as a placeholder, and swap it with the type that was expected\n # and retry once we determine what that should be.\n if e.rhs_type == concrete_type_mod.ConcreteType.NIL:\n module_text = module_text.replace(' -> ()', ' -> ' + str(e.lhs_type))\n continue\n # Any other errors are likely real type errors in the code and we should\n # report them.\n parser_helpers.pprint_positional_error(e, fs_open=make_fakefs_open())\n return\n\n # It type checked ok, and we can proceed.\n break\n\n # Interpret the line and print the result.\n # TODO(leary): 2020-06-20 No let bindings for the moment, just useful for\n # evaluating expressions -- could put them into the module scope as consts.\n interpreter = interpreter_mod.Interpreter(\n fake_module,\n type_info,\n importer.typecheck,\n import_cache=importer.cache,\n additional_search_paths=(),\n trace_all=False)\n result = interpreter.run_function(fn_name, args=(), symbolic_bindings=None)\n print(result)\n type_info.clear_type_info_refs_for_gc()\n return result"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _handle_stdin(self, line):\r\n return input(line.replace(STDIN_PROMPT, \"\"))","def read_user_input(self):\n\n self.commandline = raw_input(\"Enter the string you want to parse\\n\")","def do_prompt(self, line):\n self.prompt = line + ': '","def on_user_input(self, line: str) -> str:\n return self.infer_batch(lines=[line])[0]","def do_shell(self, line):\n eval(line)","def parseInputLine(self, line):\r\n if line is not None and line is not '':\r\n func = getattr(self, 'cmd_' + line.split()[0].upper(), None)\r\n if func is not None:\r\n func(line.split()[1:])\r\n else:\r\n self.terminal.write('No such command')\r\n self.showPrompt()","def do_prompt(self, line):\n if line:\n self.prompt = \"(%s) \" %line\n\n else:\n print 'Please specify a prompt text'","def process_input_line(self, line, store_history=True):\r\n #print \"input='%s'\"%self.input\r\n stdout = sys.stdout\r\n splitter = self.IP.input_splitter\r\n try:\r\n sys.stdout = self.cout\r\n splitter.push(line)\r\n more = splitter.push_accepts_more()\r\n if not more:\r\n source_raw = splitter.source_raw_reset()[1]\r\n self.IP.run_cell(source_raw, store_history=store_history)\r\n finally:\r\n sys.stdout = stdout","def do(self, line): \n self.interface.onecmd(line)","def do_input(self, line):\n cmd_args = io.parse_cmd_args(line, io.input_cmd_pattern)\n if cmd_args:\n success = self.manager.input(\n cmd_args.get('target'), \n cmd_args.get('cslist'), \n mode=cmd_args.get('mode')\n )\n if success:\n self.console_print(\"Yippee! input successfull!\", settings.INFO_FORMAT)\n else:\n self.console_print(\"Sorry, something kinda went wrong! You can try again.\", settings.ERROR_FORMAT)\n else:\n self.console_print(settings.COMMMAND_ARGS_ERROR_MSG, settings.ERROR_FORMAT)","def _input(str=''):\n print(str, end='', flush=True)\n return stdin.readline().rstrip('\\n')","def do_run(self, line: str):\n if self._real_module is None:\n print(\"'run' command depends on using a module. See 'use' for help.\")\n return\n\n self._real_module.run()","def raw_next_line() -> str:\n return input()","def input(self, prompt):\r\n return console_input(prompt)","def default(self, line):\n self.history.append(line)\n if line[:1] == '!':\n line = line[1:]\n locals = self.curframe_locals\n ns = self.curframe.f_globals.copy()\n ns.update(locals)\n try:\n code = compile(line + '\\n', '', 'single')\n save_stdout = sys.stdout\n save_stdin = sys.stdin\n save_displayhook = sys.displayhook\n try:\n sys.stdin = self.stdin\n sys.stdout = self.stdout\n sys.displayhook = self.displayhook\n exec(code, ns, locals)\n finally:\n sys.stdout = save_stdout\n sys.stdin = save_stdin\n sys.displayhook = save_displayhook\n except:\n exc_info = sys.exc_info()[:2]\n self.error(traceback.format_exception_only(*exc_info)[-1].strip())","def ilaw(self, line):\n line = line.strip()\n if not line:\n logger.error(r\"the command passed to %ilaw must not be empty\")\n return\n\n argv = shlex.split(line)\n prog = argv.pop(0)\n\n # prog must be a valid law cli prog\n if prog not in law.cli.cli.progs:\n raise ValueError(\"'{}' is not a valid law cli program\".format(prog))\n\n # forward to the actual prog, run special case\n try:\n # call the line_fn when set\n if callable(line_fn):\n logger.info(\"calling line function '{}'\".format(line_fn.__name__))\n line_fn(line)\n\n if prog == \"run\":\n # perform the run call interactively\n return law_run(argv)\n else:\n # forward all other progs to the cli interface\n return law.cli.cli.run([prog] + argv)\n except SystemExit as e:\n # reraise when the exit code is non-zero\n if e.code:\n raise","def get_user_input(self):\n return stdin.readline().strip()","def enter_repl(self):\n text_input = ''\n while True:\n text_input = input('>>')\n if text_input == 'exit':\n break\n #An alias for querying an instrument error string\n elif text_input == 'err?':\n self.write_to_serial(':SYST:ERR?')\n print(self.read_from_serial())\n else:\n self.write_to_serial(text_input)\n print(self.read_from_serial())","def xi(self, line=''):\r\n #line = self.xxFixLine(line)\r\n return Easy.SubInteract( ['/bin/bash', '-i', '-c', line, ] ) #shell=True\r","def read_line():\n # try reading a line, removing any extra whitespace\n try:\n line = sys.stdin.readline().strip()\n # i3status sends EOF, or an empty line\n if not line:\n sys.exit(3)\n return line\n # exit on ctrl-c\n except KeyboardInterrupt:\n sys.exit()","def read_line():\n # try reading a line, removing any extra whitespace\n try:\n line = sys.stdin.readline().strip()\n # i3status sends EOF, or an empty line\n if not line:\n sys.exit(3)\n return line\n # exit on ctrl-c\n except KeyboardInterrupt:\n sys.exit()","def rlinput(prompt, prefill=''):\n if \"readline\" not in sys.modules:\n # For example on Windows\n return input(prompt)\n else:\n readline.set_startup_hook(lambda: readline.insert_text(prefill))\n try:\n return input(prompt)\n finally:\n readline.set_startup_hook()","def xx(self, line=''):\r\n ## line in this context is one ipython line which may have line breaks in it\r\n line = self.xxFixLine(line)\r\n return self.shell.getoutput(line)","def _get_input(question: str) -> str:\n print(question)\n sys.stdout.flush()\n user_input = sys.stdin.readline()\n user_input = user_input.strip()\n return user_input","def lineEdit(args: list) -> QLineEdit:\n lineEdit = QLineEdit()\n lineEdit.setText(args[0])\n return lineEdit","def _interact_with_user(code: str, increase: bool):\n pass","def text_input():\n return input(\">>>\")","def next_line() -> str:\n return input().strip()","def precmd(self, line):\n return line","def eval(self, line):\n self.eval(line)","def do_shell(self, line):\n os.system(line)","def readline(self) -> str | None:","def get_user_text_input(self):\n\t\tuser_input = raw_input('You: ')\n\t\treturn user_input","def _interpreter(self, inp):\n inp = inp.strip()\n elem = inp.split(\" \")\n return self.controller.execute(elem[0], elem[1:])","def _input(msg):\n if sys.version_info.major >= 3:\n ans = input(msg)\n elif sys.version_info.major == 2:\n ans = raw_input(msg)\n else:\n raise Exception(\"Unsupported python version. Please upgrade to python 2 or higher.\")\n\n return ans","def read(self):\n return raw_input('> ')","def onecmd(self, line):\n cmd, arg, line = self.parseline(line)\n if not line:\n return self.emptyline()\n if cmd is None:\n return self.default(line)\n self.lastcmd = line\n if line == 'EOF' : #end the loop\n self.lastcmd = ''\n return True\n if cmd == '':\n return self.default(line)\n else:\n func = None\n for context in reversed(self.__class__.context_stack):\n func = context.resolve_cmd(cmd)\n if not func:\n break\n if not func:\n func = self.__class__.top_context.resolve_cmd(cmd)\n if not func:\n return self.default(line)\n args = self.cmdline_parse(arg)\n return func(args)","def testInterpretingSection(self):\n pl = Pipeline(loadInitFile=False)\n repl = REPL(pl)\n repl.runCommandLine('4')\n self.assertEqual(4, pl.stdin)\n\n repl.runCommandLine('_')\n self.assertEqual(4, pl.stdin)\n\n repl.runCommandLine('[3, 6, 9]')\n self.assertEqual([3, 6, 9], pl.stdin)\n\n repl.runCommandLine(\"print('hello')\")\n self.assertEqual('hello', pl.stdin)\n\n repl.runCommandLine('echo hello too')\n self.assertEqual(['hello too'], pl.stdin)\n\n self.assertEqual(REPL.DEFAULT_PS1, repl.prompt)","def pseudo_raw_input(self, prompt):\n\n if self.use_rawinput:\n try:\n line = sm.input(prompt)\n except EOFError:\n line = 'EOF'\n else:\n self.stdout.write(prompt)\n self.stdout.flush()\n line = self.stdin.readline()\n if not len(line):\n line = 'EOF'\n else:\n if line[-1] == '\\n': # this was always true in Cmd\n line = line[:-1]\n return line","def interpret_line(self, line, source=None, lineno=None):\n\n pline = self.parser.parse_line(line, source=source, lineno=lineno)\n return self.execute(pline)","def cmd_user(args):","def readline(self) -> Optional[str]:","def do_Intermediate (self, line):\r\n GenIntermediate(self.stdin, self.tracking).do_cmdloop()","def requestInput(st):\n return input(st+\": \")","def cli():\n\n while True:\n try:\n i = input()\n except EOFError:\n continue\n \n if i.startswith(\"r \"): # Reload channel\n reload_channel(i[2:])\n else:\n print(\"Invalid command\\n\")","def console():\r\n while True:\r\n interpret_command(input(\"POM> \"))","def run_cmd(server, client):\n msg = [client.get_command()]\n client.input_list += msg\n server.logger.info(\"RECEIVED INPUT {} : {}\".format(client.ip, msg[0]))\n if not client.username or not client.password:\n server.login_screen(client, msg)\n return\n loop_cmds(server, client, msg[0].split(';'))\n server.return_prompt(client)","def test_perform_get_input_raw_input(monkeypatch):\n monkeypatch.setattr(\"builtins.input\", lambda p: \"my name\" if p == \"> \" else \"boo\")\n assert sync_perform(stdio_dispatcher, Effect(Prompt(\"> \"))) == \"my name\"","def get_input(user_input):\n return input(user_input)","def processline(userdata, line):\n\t\n\tdef processcmd(command, args, expected_nargs, delegate):\n\t\t\"\"\"Validate the number of arguments and call a delegate handler.\"\"\"\n\t\t\n\t\tif len(args) != expected_nargs:\n\t\t\traise FormatError(\"Wrong number of arguments for '\" + command + \"', expected \" +\n\t\t\t str(expected_nargs) + \" but got \" + str(len(args)))\n\t\t\t\n\t\tdelegate(userdata, *args)\n\t\n\t# commands should use double quotes if an argument has spaces\n\t# in it and escape internal double quotes as necessary\n\ttokens = shlex.split(line)\n\tif len(tokens) < 1:\n\t\treturn\n\t\n\tcmd = tokens[0]\n\targs = tokens[1:]\n\t\n\t# Specialized handlers; they bridge the user facing interface and the internal implementations;\n\t# see the command dictionary below for more information on each operation\n\t\n\tdef timed_handler(userdata, *args):\n\t\t\"\"\"Accomodate the input for a non-recurrent event.\"\"\"\n\t\tfuzzy = False\n\t\t\n\t\tif args[3] == \"exact\":\n\t\t\tfuzzy = False\n\t\telif args[3] == \"fuzzy\":\n\t\t\tfuzzy = True\n\t\telse:\n\t\t\traise FormatError(\"Expected 'fuzzy' or 'exact' but found '\" + args[3] + \"' instead.\")\n\t\t\n\t\tevent = Event.create_once(args[4], fuzzy, args[2])\n\t\t\n\t\tif args[0] == \"add\":\n\t\t\tdevice.schedule(userdata, args[1], event)\n\t\telif args[0] == \"del\":\n\t\t\tdevice.unschedule(userdata, args[1], event)\n\t\telse:\n\t\t\traise FormatError(\"Expected 'add' or 'del' but found '\" + args[0] + \"' instead.\")\n\t\n\tdef recurrent_handler(userdata, *args):\n\t\t\"\"\"Accomodate the input for a recurrent event.\"\"\"\n\t\tfuzzy = False\n\t\t\n\t\tif args[5] == \"exact\":\n\t\t\tfuzzy = False\n\t\telif args[5] == \"fuzzy\":\n\t\t\tfuzzy = True\n\t\telse:\n\t\t\traise FormatError(\"Expected 'fuzzy' or 'exact' but found '\" + args[5] + \"' instead.\")\n\t\t\n\t\tevent = Event.create_recurrent(args[6], fuzzy, args[2], args[3], args[4])\n\t\t\n\t\tif args[0] == \"add\":\n\t\t\tdevice.schedule(userdata, args[1], event)\n\t\telif args[0] == \"del\":\n\t\t\tdevice.unschedule(userdata, args[1], event)\n\t\telse:\n\t\t\traise FormatError(\"Expected 'add' or 'del' but found '\" + args[0] + \"' instead.\")\n\t\n\tdef devlist_handler(userdata, *args):\n\t\t\"\"\"Transform the raw devlist into a human readable list.\"\"\"\n\t\tfor (dev, connected) in database.devlist(userdata[\"cursor\"]):\n\t\t\tif dev == \"devmaster\":\n\t\t\t\tcontinue\n\t\t\t\n\t\t\tif connected:\n\t\t\t\tprint(shlex.quote(\"+\" + dev), end=\" \")\n\t\t\telse:\n\t\t\t\tprint(shlex.quote(\"-\" + dev), end=\" \")\n\t\t\n\t\tprint()\n\t\n\tdef guestlist_handler(userdata, *args):\n\t\t\"\"\"Transform the raw guestlist into a human readable list.\"\"\"\n\t\tfor guest in userdata[\"guestlist\"]:\n\t\t\tprint(shlex.quote(guest), end=\" \")\n\t\t\n\t\tprint()\n\t\n\tdef info_handler(userdata, *args):\n\t\t\"\"\"Transform the raw info list into a human readable list.\"\"\"\n\t\tinfo = database.devinfo(userdata[\"cursor\"], args[0])\n\t\t\n\t\tif info is None:\n\t\t\tprint(\"can't find user \" + args[0])\n\t\t\treturn\n\t\t\n\t\tstype, connected, status = info\n\t\t\n\t\tprint(shlex.quote((\"+\" if connected else \"-\") + stype), end=\" \")\n\t\tprint(shlex.quote(status))\n\t\n\tdef schedule_handler(userdata, *args):\n\t\t\"\"\"Transform the raw schedule list into a human readable list.\"\"\"\n\t\tfor event in database.devschedule(userdata[\"cursor\"], args[0]):\n\t\t\tprint(str(event))\n\t\t\n\t\tprint(\"\")\n\t\n\t# Command dictionary\n\t\n\tcommands = {\n\t\t# \"command name\": (expected_nargs, delegate)\n\t\t\"add\": (4, device.add),\n\t\t\t# add \n\t\t\t# add a device to the network\n\t\t\"rename\": (2, device.rename),\n\t\t\t# rename \n\t\t\t# change the public display name of a device in the network\n\t\t\"del\": (1, device.delete),\n\t\t\t# del \n\t\t\t# delete a device from the network\n\t\t\"sync\": (1, device.sync),\n\t\t\t# sync \n\t\t\t# send a time synchronization message to the specified device\n\t\t\"ping\": (1, device.ping),\n\t\t\t# ping \n\t\t\t# check a device is still responsive by sending a ping message\n\t\t\"askstatus\": (1, device.askstatus),\n\t\t\t# askstatus \n\t\t\t# ask the device for its current status\n\t\t\"cmd\": (2, device.execute),\n\t\t\t# cmd \n\t\t\t# send immediate command to device;\n\t\t\t# arguments to the operation should be within the operation argument, e.g. 'dimmer 126'\n\t\t\t# the operation must be valid (and have valid arguments) for the device type;\n\t\t\t# otherwise, the command will fail silently\n\t\t\"timed\": (5, timed_handler),\n\t\t\t# timed (add|del) (exact|fuzzy) \n\t\t\t# schedule a command for the future;\n\t\t\t# 'add' indicates to add the operation to the schedule, 'del' indicates to remove it from it;\n\t\t\t# must be formatted as a unix integer timestamp in the future,\n\t\t\t# otherwise the command is a no-op;\n\t\t\t# 'exact' sets the timer for the specific timestamp; 'fuzzy' adds a small amount of time noise;\n\t\t\t# and follow the same rules as the 'cmd' message;\n\t\t\"recurrent\": (7, recurrent_handler),\n\t\t\t# recurrent (add|del) (exact|fuzzy) \n\t\t\t# schedule a recurrent command for the future;\n\t\t\t# 'add' indicates to add the operation to the schedule, 'del' indicates to remove it from it;\n\t\t\t# must be a number between 0 and 9. Passing 0 signals the operation should execute\n\t\t\t# every day; 1-7 signal it should be executed on Mon-Sun respectively; 8 signals Mon-Fri; and\n\t\t\t# 9 signals Sat-Sun;\n\t\t\t# 'exact' sets the timer for the specific timestamp; 'fuzzy' adds a small amount of time noise;\n\t\t\t# and follow the same rules as the 'cmd' message\n\t\t\"clear\": (1, device.clearschedule),\n\t\t\t# clear \n\t\t\t# clear the schedule for a given device\n\t\t\"devlist\": (0, devlist_handler),\n\t\t\t# devlist\n\t\t\t# retrieve verified device list\n\t\t\t# respond with a list of devices, using the format: ('(-|+)' )*\n\t\t\t# where every name is prepended with a positive sign '+' if the device is connected\n\t\t\t# and a negative sign '-' if it is not\n\t\t\"guestlist\": (0, guestlist_handler),\n\t\t\t# guestlist\n\t\t\t# retrieve the guestlist\n\t\t\t# respond with a list of unverified devices, using the format ('' )*\n\t\t\t# note that every guest is connected (otherwise it would just be removed from the list)\n\t\t\"info\": (1, info_handler),\n\t\t\t# info \n\t\t\t# retrieve device profile\n\t\t\t# respond with the list of device properties in the profile using the format\n\t\t\t# \n\t\t\t# where connected is formatted as + if the device is connected as - if it is not, e.g.\n\t\t\t# '-sonoff on' indicates a disconnected sonoff device with a status of 'on'\n\t\t\"schedule\": (1, schedule_handler)\n\t\t\t# schedule \n\t\t\t# retrieve device schedule\n\t\t\t# respond with a list of scheduled commands for the given device using the formats\n\t\t\t# timed (exact|fuzzy) \n\t\t\t# recurrent (exact|fuzzy) []\n\t\t\t# for timed and recurrent operations respectively;\n\t\t\t# the specifics of each formats are the same as for their schedule counterparts\n\t}\n\t\n\ttry:\n\t\t(expected_nargs, delegate) = commands[cmd]\n\texcept KeyError:\n\t\tprint(\"Unrecognized command, skipping\", file=sys.stderr)\n\t\treturn\n\t\n\tprocesscmd(cmd, args, expected_nargs, delegate)","def get_input(prompt):\n return input(prompt)","def get_input(prompt):\n return input(prompt)","def inp(text):\r\n input(text)","def evaluate(self, line):\n locals = self.curframe().f_locals\n globals = self.curframe().f_globals\n try:\n code = compile(line + '\\n', '', 'single')\n exec(code, globals, locals)\n except Exception:\n import sys\n t, v = sys.exc_info()[:2]\n if isinstance(t, type('')):\n exc_type_name = t\n else:\n exc_type_name = t.__name__\n print('*** {}: {}'.format(exc_type_name, v))","def ask_user_input(self, sentence):\n user_input = raw_input(sentence + \" : \")\n return user_input","def do_say(self, line):\n if line != '':\n print(line)","def __edit_line(self, line, code, code_obj): # pylint: disable=R0201\r\n try:\r\n result = eval(code_obj, globals(), locals())\r\n except TypeError as ex:\r\n message = \"failed to execute {}: {}\".format(code, ex)\r\n logger.warning(message)\r\n raise EditorError(message)\r\n if result is None:\r\n raise EditorError(\"cannot process line '{}' with {}\".format(\r\n line, code))\r\n elif isinstance(result, list) or isinstance(result, tuple):\r\n line = ' '.join([str(res_element) for res_element in result])\r\n else:\r\n line = str(result)\r\n return line","def get_input(prompt):\n # type: (str) -> str\n return raw_input(prompt)","def main():\n dt = DropToken()\n play = True\n while play:\n try:\n line = sys.stdin.readline()\n except KeyboardInterrupt:\n break\n if not line:\n break\n play = dt.inputProcess(line)","def ask_user_input(prompt: str) -> str:\n return input(prompt)","def interact(self, prompt='debug> '):\r\n msg = 'Entering Octave Debug Prompt...\\n%s' % prompt\r\n self.stdout.write(msg)\r\n while 1:\r\n inp_func = input if not PY2 else raw_input\r\n try:\r\n inp = inp_func() + '\\n'\r\n except EOFError:\r\n return\r\n if inp in ['exit\\n', 'quit\\n', 'dbcont\\n', 'dbquit\\n']:\r\n inp = 'return\\n'\r\n self.write('disp(char(3));' + inp)\r\n if inp == 'return\\n':\r\n self.write('return\\n')\r\n self.write('clear _\\n')\r\n self.readline()\r\n self.readline()\r\n if not pty is None:\r\n self.readline()\r\n self.write('disp(char(3))\\n')\r\n return\r\n self.expect('\\x03')\r\n self.stdout.write(self.expect(prompt))","def input_helper(prompt):\n if version_info[0] == 2:\n # python2 input is scary - we want raw_input\n return raw_input(prompt)\n else:\n return input(prompt)","def cmd_note(cls): \n print(\"Enter/Paste your release note. To save use Ctrl-Z (windows) or Ctrl-D in a new line and press Enter.\")\n inputNote = sys.stdin.readlines()\n note = ''\n for line in inputNote:\n note += line\n return note","def cmd_note(cls): \n print(\"Enter/Paste your release note. To save use Ctrl-Z (windows) or Ctrl-D in a new line and press Enter.\")\n inputNote = sys.stdin.readlines()\n note = ''\n for line in inputNote:\n note += line\n return note","def Prompt(self):\n self.cli.context_was_set = not self.cli.config.context\n doc = self.cli.run()\n return doc.text if doc else None","def precmd(self, line):\n return line.strip()","def getInput(prompt):\n if platform.python_version().startswith('3'):\n userInput = input('%s ' % prompt).strip()\n if platform.python_version().startswith('2'):\n userInput = raw_input('%s ' % prompt).strip()\n return userInput","def run(self, cmdline):\n self.send(cmdline+\"\\n\")\n rdata = '\\n'.join(self.recv_to_prompt())\n return rdata","def test_single_dialog_prompt_extra_line(monkeypatch, capsys):\n monkeypatch.setattr(\"sys.stdin\", io.StringIO(\"value\" + \"\\n\"))\n _dialog_prompt(\n parameter=DialogParameter(\"Title\", comment=\"Comment\"),\n )\n captured = capsys.readouterr()\n assert captured.out.count(\"\\n\") == 2","def handle_input(self):\n\n\t\tline = sys.stdin.readline().strip()\n\n\t\tif line == '':\n\t\t\t# print('')\n\t\t\tself.print_prompt()\n\t\t\treturn\n\n\t\tcommand_name, *parts = line.split()\n\n\t\tif command_name in self.commands:\n\t\t\t# Call given command and unpack parts into args\n\t\t\tself.commands[command_name]['callback'](*parts)\n\t\telse:\n\t\t\tprint(command_name + ' : command not found')\n\t\t\tself.print_available_commands()\n\n\n\t\tself.print_prompt()","def get_input(*args, **kw):\n if sys.version[0] == \"2\":\n return raw_input(*args, **kw)\n else:\n return input(*args, **kw)","def start_interaction():\r\n\r\n # Loop infinitely\r\n while True:\r\n # Prints 'Say something: ' and then waits for user input\r\n # Note: line gets a string value\r\n line = input('Say something: ')\r\n\r\n # Right now, not very interesting...?\r\n if line == EASTER_EGG:\r\n print(EASTER_EGG_RESPONSE)\r\n else:\r\n print(repeat(line))","def inputProcess(self, line):\n fields = line.split()\n # check if input argument size is not 1 or 2\n if len(fields) < 1 or len(fields) > 2:\n print 'Invalid input size!'\n return True\n # call corresponding functions based on input argument(s)\n if fields[0] == 'GET':\n res = self.get()\n if res != '':\n print res,\n elif fields[0] == 'EXIT':\n return False\n elif fields[0] == 'BOARD':\n print self.displayBoard()\n elif fields[0] == 'PUT':\n if len(fields) != 2:\n print 'PUT command needs one argument!'\n return True\n try:\n column = int(fields[1])\n if column < 1 or column > 4:\n print 'Column number for PUT command needs to be from 1 to 4'\n else:\n print self.put(column)\n except ValueError:\n print 'Invalid input, for column number please enter an integer from 1 to 4'\n else:\n print 'Invalid input, valid commands consists of GET BOARD EXIT PUT only'\n return True","def lineReceived(self, line):\n rbuffer = StringIO()\n po=sys.stdout\n sys.stdout = rbuffer\n err=False\n if not hasattr(self,\"dc\"):\n self.dc={\"self\":self.server}\n print \"dc:\", self.dc\n try: exec(line,self.dc)\n except Exception as e: err=e\n except KeyboardInterrupt : pass\n # remove backeffect on dictionary\n if self.dc.has_key('__builtins__'): \n del self.dc['__builtins__']\n # update data context\n # remember to restore the original stdout!\n sys.stdout = po\n print '>u> '+line\n if err: out = self.pre_e+str(e)+self.post_e\n else: out = rbuffer.getvalue()\n if out!=\"\": print '>s> ' + out","def user_input(self, options, prompt):\n for o in options:\n line = self.selector_line(o)\n o[\"line\"] = line\n self.output(line)\n self.output(prompt, end=\" \")\n while True:\n if self.test_input:\n inp = self.test_input.pop(0)\n self.output(f\"Using '{inp}' test input\")\n else:\n try:\n inp = raw_input()\n except (IOError, KeyboardInterrupt):\n self.game.print_state()\n raise\n if inp:\n matching = []\n for o in options:\n if o[\"selector\"] == inp:\n return o\n if inp.lower() in o[\"line\"].lower() and o[\"selector\"] != \"-\":\n matching.append(o)\n if len(matching) == 1:\n return matching[0]\n self.output(f\"Invalid Option ({inp})\")","def handle_line(self, line):\n LOG.debug(\"Received line of input from client %s: %s\", self.addr, line)","def GetLine(line):\r\n pass","def console():\n repl(click.get_current_context())","def REPL(\n parse_tree_fn: Callable,\n output_style_fn: Callable,\n session: bool,\n mode: str,\n show_tree_fn=None,\n debug=False,\n) -> None:\n print(\n \"Enter a Mathematica expression. Enter either an empty line, Ctrl-C, or Ctrl-D to exit.\"\n )\n in_count = 1\n while True:\n try:\n user_in = input(f\"In[{in_count}]:= \")\n except (KeyboardInterrupt, EOFError):\n break\n else:\n in_count += 1\n if user_in == \"\":\n break\n\n eval_one(\n in_str=user_in,\n parse_tree_fn=parse_tree_fn,\n output_style_fn=output_style_fn,\n mode=mode,\n session=session,\n show_tree_fn=show_tree_fn,\n debug=debug,\n )\n pass\n return","def handle_line(line):\n print line,\n\n line_parts = log_re.match(line).groupdict()\n action = line_parts['action']\n attacker = line_parts['attacker']\n\n (cmd, status, output) = interact(line_parts, method=opts.method)\n\n if status > 0:\n warnings.warn('IP %s (%s)' % (attacker, output), InteractionWarning)\n print '\\t%s FAILURE' % attacker\n else:\n print '\\t%s SUCCESS' % attacker\n \n print","def get_value(Runner, input_str):\n Runner.stdin.write(input_str)\n output = Runner.stdout.readline() \n return output","def user_prompt(prompt, default=None):\n prompt = f\"\\n {prompt} [{default}] runs or type an amount: \"\n response = input(prompt)\n if not response and default:\n return default\n else:\n return response","def lineReceived(self, line):\n self.sendLine('reply '+line)","def main(self):\n cmd = \"self.%s(sys.stdin)\" % sys.argv[1]\n exec(cmd)","def gip(line):\n import os\n import shlex\n import textwrap\n args = shlex.split(line)\n if len(args) == 0:\n path = '~/.ipyscratch'\n else:\n try:\n path = eval(line)\n except:\n path = args[0]\n with open(os.path.expanduser(path)) as f:\n cmd = textwrap.dedent(f.read())\n get_ipython().run_line_magic('pycat', path)\n # update history\n In[-1] = cmd\n get_ipython().run_code(cmd)","def interactive(self, *args, **kwargs):\n if args == (['python'],):\n return\n raise ValueError(self, args, kwargs)","def UserInput(self, username, userinput):\n pass","def run_interactive(cls, shell, command, input):\n feed = '\\\\n'.join(input)\n icommand = \"echo -e '{}' | {}\".format(feed, command)\n _stdout, _stderr = cls.run(shell, icommand)\n return _stdout","def main():\n line_count = int(input().strip())\n lines = sys.stdin.readlines()[:line_count]\n for line in lines:\n print('YES' if contains_hackerrank(line) else 'NO')","def run(self, name, rawtext, text, lineno, inliner, options=None,\n content=None):\n raise NotImplementedError","def safe_input(display_string):\n\n try:\n x = raw_input(display_string)\n except NameError:\n x = input(display_string)\n\n return x","def main():\n user_interaction()","def default(self, line):\n print \"Command not found\\n\"","def user_line(self, frame):\n pass","def default(self, line):\n line = line.split(' ')[0]\n self.PRINT.warning(line + \": command not found\")\n self.PRINT.newline()","def onecmd(self, line):\n statement = self.parsed(line)\n self.lastcmd = statement.parsed.raw\n funcname = self.func_named(statement.parsed.command)\n if not funcname:\n return self._default(statement)\n try:\n func = getattr(self, funcname)\n except AttributeError:\n return self._default(statement)\n stop = func(statement)\n return stop","def getInput(self):\n self.userInput = self.entry.get()","def user_input(self, msg, default=''):\n msg = '%s %s ' % (self.prefix, msg)\n\n if default != '':\n msg += '[%s] ' % default\n\n try:\n vim.command('echohl Debug')\n input_str = vim.eval('input(\"%s> \")' % msg)\n vim.command('echohl none')\n except KeyboardInterrupt:\n input_str = ''\n\n return input_str or default","def rawInput(string):\n if os.name == \"posix\":\n tcflush(sys.stdin, TCIFLUSH)\n return input(string)","def do_action_for_input(self, user_input):\n if user_input == CommandLineProgram.ACTION.HELP:\n self.print_help()\n elif user_input == CommandLineProgram.ACTION.ADD_USER:\n self.input_and_create_user()\n elif user_input == CommandLineProgram.ACTION.LIST_USERS:\n self.print_users()\n elif user_input == CommandLineProgram.ACTION.ADD_TRANSACTION:\n self.select_user_and_add_transaction()\n elif user_input == CommandLineProgram.ACTION.GENERATE_REPORT:\n self.select_user_and_print_report()","def process_input(line: str) -> None:\n\n # Do not lines if empty or commands\n # Built in commands take precedence to other processing\n if line_valid(line) and not check_commands(line):\n\n # Split the line into its constituent words\n words = line.split(' ')\n\n while unknown_words(words) is not None:\n # As long as any words in the last line are unknown, attempt to learn them\n learn_new_word(unknown_words(words))\n\n if len(words) == 1:\n # Attempt to learn the definition of single-word input\n learn_new_defn(words.pop())\n\n wait()"],"string":"[\n \"def _handle_stdin(self, line):\\r\\n return input(line.replace(STDIN_PROMPT, \\\"\\\"))\",\n \"def read_user_input(self):\\n\\n self.commandline = raw_input(\\\"Enter the string you want to parse\\\\n\\\")\",\n \"def do_prompt(self, line):\\n self.prompt = line + ': '\",\n \"def on_user_input(self, line: str) -> str:\\n return self.infer_batch(lines=[line])[0]\",\n \"def do_shell(self, line):\\n eval(line)\",\n \"def parseInputLine(self, line):\\r\\n if line is not None and line is not '':\\r\\n func = getattr(self, 'cmd_' + line.split()[0].upper(), None)\\r\\n if func is not None:\\r\\n func(line.split()[1:])\\r\\n else:\\r\\n self.terminal.write('No such command')\\r\\n self.showPrompt()\",\n \"def do_prompt(self, line):\\n if line:\\n self.prompt = \\\"(%s) \\\" %line\\n\\n else:\\n print 'Please specify a prompt text'\",\n \"def process_input_line(self, line, store_history=True):\\r\\n #print \\\"input='%s'\\\"%self.input\\r\\n stdout = sys.stdout\\r\\n splitter = self.IP.input_splitter\\r\\n try:\\r\\n sys.stdout = self.cout\\r\\n splitter.push(line)\\r\\n more = splitter.push_accepts_more()\\r\\n if not more:\\r\\n source_raw = splitter.source_raw_reset()[1]\\r\\n self.IP.run_cell(source_raw, store_history=store_history)\\r\\n finally:\\r\\n sys.stdout = stdout\",\n \"def do(self, line): \\n self.interface.onecmd(line)\",\n \"def do_input(self, line):\\n cmd_args = io.parse_cmd_args(line, io.input_cmd_pattern)\\n if cmd_args:\\n success = self.manager.input(\\n cmd_args.get('target'), \\n cmd_args.get('cslist'), \\n mode=cmd_args.get('mode')\\n )\\n if success:\\n self.console_print(\\\"Yippee! input successfull!\\\", settings.INFO_FORMAT)\\n else:\\n self.console_print(\\\"Sorry, something kinda went wrong! You can try again.\\\", settings.ERROR_FORMAT)\\n else:\\n self.console_print(settings.COMMMAND_ARGS_ERROR_MSG, settings.ERROR_FORMAT)\",\n \"def _input(str=''):\\n print(str, end='', flush=True)\\n return stdin.readline().rstrip('\\\\n')\",\n \"def do_run(self, line: str):\\n if self._real_module is None:\\n print(\\\"'run' command depends on using a module. See 'use' for help.\\\")\\n return\\n\\n self._real_module.run()\",\n \"def raw_next_line() -> str:\\n return input()\",\n \"def input(self, prompt):\\r\\n return console_input(prompt)\",\n \"def default(self, line):\\n self.history.append(line)\\n if line[:1] == '!':\\n line = line[1:]\\n locals = self.curframe_locals\\n ns = self.curframe.f_globals.copy()\\n ns.update(locals)\\n try:\\n code = compile(line + '\\\\n', '', 'single')\\n save_stdout = sys.stdout\\n save_stdin = sys.stdin\\n save_displayhook = sys.displayhook\\n try:\\n sys.stdin = self.stdin\\n sys.stdout = self.stdout\\n sys.displayhook = self.displayhook\\n exec(code, ns, locals)\\n finally:\\n sys.stdout = save_stdout\\n sys.stdin = save_stdin\\n sys.displayhook = save_displayhook\\n except:\\n exc_info = sys.exc_info()[:2]\\n self.error(traceback.format_exception_only(*exc_info)[-1].strip())\",\n \"def ilaw(self, line):\\n line = line.strip()\\n if not line:\\n logger.error(r\\\"the command passed to %ilaw must not be empty\\\")\\n return\\n\\n argv = shlex.split(line)\\n prog = argv.pop(0)\\n\\n # prog must be a valid law cli prog\\n if prog not in law.cli.cli.progs:\\n raise ValueError(\\\"'{}' is not a valid law cli program\\\".format(prog))\\n\\n # forward to the actual prog, run special case\\n try:\\n # call the line_fn when set\\n if callable(line_fn):\\n logger.info(\\\"calling line function '{}'\\\".format(line_fn.__name__))\\n line_fn(line)\\n\\n if prog == \\\"run\\\":\\n # perform the run call interactively\\n return law_run(argv)\\n else:\\n # forward all other progs to the cli interface\\n return law.cli.cli.run([prog] + argv)\\n except SystemExit as e:\\n # reraise when the exit code is non-zero\\n if e.code:\\n raise\",\n \"def get_user_input(self):\\n return stdin.readline().strip()\",\n \"def enter_repl(self):\\n text_input = ''\\n while True:\\n text_input = input('>>')\\n if text_input == 'exit':\\n break\\n #An alias for querying an instrument error string\\n elif text_input == 'err?':\\n self.write_to_serial(':SYST:ERR?')\\n print(self.read_from_serial())\\n else:\\n self.write_to_serial(text_input)\\n print(self.read_from_serial())\",\n \"def xi(self, line=''):\\r\\n #line = self.xxFixLine(line)\\r\\n return Easy.SubInteract( ['/bin/bash', '-i', '-c', line, ] ) #shell=True\\r\",\n \"def read_line():\\n # try reading a line, removing any extra whitespace\\n try:\\n line = sys.stdin.readline().strip()\\n # i3status sends EOF, or an empty line\\n if not line:\\n sys.exit(3)\\n return line\\n # exit on ctrl-c\\n except KeyboardInterrupt:\\n sys.exit()\",\n \"def read_line():\\n # try reading a line, removing any extra whitespace\\n try:\\n line = sys.stdin.readline().strip()\\n # i3status sends EOF, or an empty line\\n if not line:\\n sys.exit(3)\\n return line\\n # exit on ctrl-c\\n except KeyboardInterrupt:\\n sys.exit()\",\n \"def rlinput(prompt, prefill=''):\\n if \\\"readline\\\" not in sys.modules:\\n # For example on Windows\\n return input(prompt)\\n else:\\n readline.set_startup_hook(lambda: readline.insert_text(prefill))\\n try:\\n return input(prompt)\\n finally:\\n readline.set_startup_hook()\",\n \"def xx(self, line=''):\\r\\n ## line in this context is one ipython line which may have line breaks in it\\r\\n line = self.xxFixLine(line)\\r\\n return self.shell.getoutput(line)\",\n \"def _get_input(question: str) -> str:\\n print(question)\\n sys.stdout.flush()\\n user_input = sys.stdin.readline()\\n user_input = user_input.strip()\\n return user_input\",\n \"def lineEdit(args: list) -> QLineEdit:\\n lineEdit = QLineEdit()\\n lineEdit.setText(args[0])\\n return lineEdit\",\n \"def _interact_with_user(code: str, increase: bool):\\n pass\",\n \"def text_input():\\n return input(\\\">>>\\\")\",\n \"def next_line() -> str:\\n return input().strip()\",\n \"def precmd(self, line):\\n return line\",\n \"def eval(self, line):\\n self.eval(line)\",\n \"def do_shell(self, line):\\n os.system(line)\",\n \"def readline(self) -> str | None:\",\n \"def get_user_text_input(self):\\n\\t\\tuser_input = raw_input('You: ')\\n\\t\\treturn user_input\",\n \"def _interpreter(self, inp):\\n inp = inp.strip()\\n elem = inp.split(\\\" \\\")\\n return self.controller.execute(elem[0], elem[1:])\",\n \"def _input(msg):\\n if sys.version_info.major >= 3:\\n ans = input(msg)\\n elif sys.version_info.major == 2:\\n ans = raw_input(msg)\\n else:\\n raise Exception(\\\"Unsupported python version. Please upgrade to python 2 or higher.\\\")\\n\\n return ans\",\n \"def read(self):\\n return raw_input('> ')\",\n \"def onecmd(self, line):\\n cmd, arg, line = self.parseline(line)\\n if not line:\\n return self.emptyline()\\n if cmd is None:\\n return self.default(line)\\n self.lastcmd = line\\n if line == 'EOF' : #end the loop\\n self.lastcmd = ''\\n return True\\n if cmd == '':\\n return self.default(line)\\n else:\\n func = None\\n for context in reversed(self.__class__.context_stack):\\n func = context.resolve_cmd(cmd)\\n if not func:\\n break\\n if not func:\\n func = self.__class__.top_context.resolve_cmd(cmd)\\n if not func:\\n return self.default(line)\\n args = self.cmdline_parse(arg)\\n return func(args)\",\n \"def testInterpretingSection(self):\\n pl = Pipeline(loadInitFile=False)\\n repl = REPL(pl)\\n repl.runCommandLine('4')\\n self.assertEqual(4, pl.stdin)\\n\\n repl.runCommandLine('_')\\n self.assertEqual(4, pl.stdin)\\n\\n repl.runCommandLine('[3, 6, 9]')\\n self.assertEqual([3, 6, 9], pl.stdin)\\n\\n repl.runCommandLine(\\\"print('hello')\\\")\\n self.assertEqual('hello', pl.stdin)\\n\\n repl.runCommandLine('echo hello too')\\n self.assertEqual(['hello too'], pl.stdin)\\n\\n self.assertEqual(REPL.DEFAULT_PS1, repl.prompt)\",\n \"def pseudo_raw_input(self, prompt):\\n\\n if self.use_rawinput:\\n try:\\n line = sm.input(prompt)\\n except EOFError:\\n line = 'EOF'\\n else:\\n self.stdout.write(prompt)\\n self.stdout.flush()\\n line = self.stdin.readline()\\n if not len(line):\\n line = 'EOF'\\n else:\\n if line[-1] == '\\\\n': # this was always true in Cmd\\n line = line[:-1]\\n return line\",\n \"def interpret_line(self, line, source=None, lineno=None):\\n\\n pline = self.parser.parse_line(line, source=source, lineno=lineno)\\n return self.execute(pline)\",\n \"def cmd_user(args):\",\n \"def readline(self) -> Optional[str]:\",\n \"def do_Intermediate (self, line):\\r\\n GenIntermediate(self.stdin, self.tracking).do_cmdloop()\",\n \"def requestInput(st):\\n return input(st+\\\": \\\")\",\n \"def cli():\\n\\n while True:\\n try:\\n i = input()\\n except EOFError:\\n continue\\n \\n if i.startswith(\\\"r \\\"): # Reload channel\\n reload_channel(i[2:])\\n else:\\n print(\\\"Invalid command\\\\n\\\")\",\n \"def console():\\r\\n while True:\\r\\n interpret_command(input(\\\"POM> \\\"))\",\n \"def run_cmd(server, client):\\n msg = [client.get_command()]\\n client.input_list += msg\\n server.logger.info(\\\"RECEIVED INPUT {} : {}\\\".format(client.ip, msg[0]))\\n if not client.username or not client.password:\\n server.login_screen(client, msg)\\n return\\n loop_cmds(server, client, msg[0].split(';'))\\n server.return_prompt(client)\",\n \"def test_perform_get_input_raw_input(monkeypatch):\\n monkeypatch.setattr(\\\"builtins.input\\\", lambda p: \\\"my name\\\" if p == \\\"> \\\" else \\\"boo\\\")\\n assert sync_perform(stdio_dispatcher, Effect(Prompt(\\\"> \\\"))) == \\\"my name\\\"\",\n \"def get_input(user_input):\\n return input(user_input)\",\n \"def processline(userdata, line):\\n\\t\\n\\tdef processcmd(command, args, expected_nargs, delegate):\\n\\t\\t\\\"\\\"\\\"Validate the number of arguments and call a delegate handler.\\\"\\\"\\\"\\n\\t\\t\\n\\t\\tif len(args) != expected_nargs:\\n\\t\\t\\traise FormatError(\\\"Wrong number of arguments for '\\\" + command + \\\"', expected \\\" +\\n\\t\\t\\t str(expected_nargs) + \\\" but got \\\" + str(len(args)))\\n\\t\\t\\t\\n\\t\\tdelegate(userdata, *args)\\n\\t\\n\\t# commands should use double quotes if an argument has spaces\\n\\t# in it and escape internal double quotes as necessary\\n\\ttokens = shlex.split(line)\\n\\tif len(tokens) < 1:\\n\\t\\treturn\\n\\t\\n\\tcmd = tokens[0]\\n\\targs = tokens[1:]\\n\\t\\n\\t# Specialized handlers; they bridge the user facing interface and the internal implementations;\\n\\t# see the command dictionary below for more information on each operation\\n\\t\\n\\tdef timed_handler(userdata, *args):\\n\\t\\t\\\"\\\"\\\"Accomodate the input for a non-recurrent event.\\\"\\\"\\\"\\n\\t\\tfuzzy = False\\n\\t\\t\\n\\t\\tif args[3] == \\\"exact\\\":\\n\\t\\t\\tfuzzy = False\\n\\t\\telif args[3] == \\\"fuzzy\\\":\\n\\t\\t\\tfuzzy = True\\n\\t\\telse:\\n\\t\\t\\traise FormatError(\\\"Expected 'fuzzy' or 'exact' but found '\\\" + args[3] + \\\"' instead.\\\")\\n\\t\\t\\n\\t\\tevent = Event.create_once(args[4], fuzzy, args[2])\\n\\t\\t\\n\\t\\tif args[0] == \\\"add\\\":\\n\\t\\t\\tdevice.schedule(userdata, args[1], event)\\n\\t\\telif args[0] == \\\"del\\\":\\n\\t\\t\\tdevice.unschedule(userdata, args[1], event)\\n\\t\\telse:\\n\\t\\t\\traise FormatError(\\\"Expected 'add' or 'del' but found '\\\" + args[0] + \\\"' instead.\\\")\\n\\t\\n\\tdef recurrent_handler(userdata, *args):\\n\\t\\t\\\"\\\"\\\"Accomodate the input for a recurrent event.\\\"\\\"\\\"\\n\\t\\tfuzzy = False\\n\\t\\t\\n\\t\\tif args[5] == \\\"exact\\\":\\n\\t\\t\\tfuzzy = False\\n\\t\\telif args[5] == \\\"fuzzy\\\":\\n\\t\\t\\tfuzzy = True\\n\\t\\telse:\\n\\t\\t\\traise FormatError(\\\"Expected 'fuzzy' or 'exact' but found '\\\" + args[5] + \\\"' instead.\\\")\\n\\t\\t\\n\\t\\tevent = Event.create_recurrent(args[6], fuzzy, args[2], args[3], args[4])\\n\\t\\t\\n\\t\\tif args[0] == \\\"add\\\":\\n\\t\\t\\tdevice.schedule(userdata, args[1], event)\\n\\t\\telif args[0] == \\\"del\\\":\\n\\t\\t\\tdevice.unschedule(userdata, args[1], event)\\n\\t\\telse:\\n\\t\\t\\traise FormatError(\\\"Expected 'add' or 'del' but found '\\\" + args[0] + \\\"' instead.\\\")\\n\\t\\n\\tdef devlist_handler(userdata, *args):\\n\\t\\t\\\"\\\"\\\"Transform the raw devlist into a human readable list.\\\"\\\"\\\"\\n\\t\\tfor (dev, connected) in database.devlist(userdata[\\\"cursor\\\"]):\\n\\t\\t\\tif dev == \\\"devmaster\\\":\\n\\t\\t\\t\\tcontinue\\n\\t\\t\\t\\n\\t\\t\\tif connected:\\n\\t\\t\\t\\tprint(shlex.quote(\\\"+\\\" + dev), end=\\\" \\\")\\n\\t\\t\\telse:\\n\\t\\t\\t\\tprint(shlex.quote(\\\"-\\\" + dev), end=\\\" \\\")\\n\\t\\t\\n\\t\\tprint()\\n\\t\\n\\tdef guestlist_handler(userdata, *args):\\n\\t\\t\\\"\\\"\\\"Transform the raw guestlist into a human readable list.\\\"\\\"\\\"\\n\\t\\tfor guest in userdata[\\\"guestlist\\\"]:\\n\\t\\t\\tprint(shlex.quote(guest), end=\\\" \\\")\\n\\t\\t\\n\\t\\tprint()\\n\\t\\n\\tdef info_handler(userdata, *args):\\n\\t\\t\\\"\\\"\\\"Transform the raw info list into a human readable list.\\\"\\\"\\\"\\n\\t\\tinfo = database.devinfo(userdata[\\\"cursor\\\"], args[0])\\n\\t\\t\\n\\t\\tif info is None:\\n\\t\\t\\tprint(\\\"can't find user \\\" + args[0])\\n\\t\\t\\treturn\\n\\t\\t\\n\\t\\tstype, connected, status = info\\n\\t\\t\\n\\t\\tprint(shlex.quote((\\\"+\\\" if connected else \\\"-\\\") + stype), end=\\\" \\\")\\n\\t\\tprint(shlex.quote(status))\\n\\t\\n\\tdef schedule_handler(userdata, *args):\\n\\t\\t\\\"\\\"\\\"Transform the raw schedule list into a human readable list.\\\"\\\"\\\"\\n\\t\\tfor event in database.devschedule(userdata[\\\"cursor\\\"], args[0]):\\n\\t\\t\\tprint(str(event))\\n\\t\\t\\n\\t\\tprint(\\\"\\\")\\n\\t\\n\\t# Command dictionary\\n\\t\\n\\tcommands = {\\n\\t\\t# \\\"command name\\\": (expected_nargs, delegate)\\n\\t\\t\\\"add\\\": (4, device.add),\\n\\t\\t\\t# add \\n\\t\\t\\t# add a device to the network\\n\\t\\t\\\"rename\\\": (2, device.rename),\\n\\t\\t\\t# rename \\n\\t\\t\\t# change the public display name of a device in the network\\n\\t\\t\\\"del\\\": (1, device.delete),\\n\\t\\t\\t# del \\n\\t\\t\\t# delete a device from the network\\n\\t\\t\\\"sync\\\": (1, device.sync),\\n\\t\\t\\t# sync \\n\\t\\t\\t# send a time synchronization message to the specified device\\n\\t\\t\\\"ping\\\": (1, device.ping),\\n\\t\\t\\t# ping \\n\\t\\t\\t# check a device is still responsive by sending a ping message\\n\\t\\t\\\"askstatus\\\": (1, device.askstatus),\\n\\t\\t\\t# askstatus \\n\\t\\t\\t# ask the device for its current status\\n\\t\\t\\\"cmd\\\": (2, device.execute),\\n\\t\\t\\t# cmd \\n\\t\\t\\t# send immediate command to device;\\n\\t\\t\\t# arguments to the operation should be within the operation argument, e.g. 'dimmer 126'\\n\\t\\t\\t# the operation must be valid (and have valid arguments) for the device type;\\n\\t\\t\\t# otherwise, the command will fail silently\\n\\t\\t\\\"timed\\\": (5, timed_handler),\\n\\t\\t\\t# timed (add|del) (exact|fuzzy) \\n\\t\\t\\t# schedule a command for the future;\\n\\t\\t\\t# 'add' indicates to add the operation to the schedule, 'del' indicates to remove it from it;\\n\\t\\t\\t# must be formatted as a unix integer timestamp in the future,\\n\\t\\t\\t# otherwise the command is a no-op;\\n\\t\\t\\t# 'exact' sets the timer for the specific timestamp; 'fuzzy' adds a small amount of time noise;\\n\\t\\t\\t# and follow the same rules as the 'cmd' message;\\n\\t\\t\\\"recurrent\\\": (7, recurrent_handler),\\n\\t\\t\\t# recurrent (add|del) (exact|fuzzy) \\n\\t\\t\\t# schedule a recurrent command for the future;\\n\\t\\t\\t# 'add' indicates to add the operation to the schedule, 'del' indicates to remove it from it;\\n\\t\\t\\t# must be a number between 0 and 9. Passing 0 signals the operation should execute\\n\\t\\t\\t# every day; 1-7 signal it should be executed on Mon-Sun respectively; 8 signals Mon-Fri; and\\n\\t\\t\\t# 9 signals Sat-Sun;\\n\\t\\t\\t# 'exact' sets the timer for the specific timestamp; 'fuzzy' adds a small amount of time noise;\\n\\t\\t\\t# and follow the same rules as the 'cmd' message\\n\\t\\t\\\"clear\\\": (1, device.clearschedule),\\n\\t\\t\\t# clear \\n\\t\\t\\t# clear the schedule for a given device\\n\\t\\t\\\"devlist\\\": (0, devlist_handler),\\n\\t\\t\\t# devlist\\n\\t\\t\\t# retrieve verified device list\\n\\t\\t\\t# respond with a list of devices, using the format: ('(-|+)' )*\\n\\t\\t\\t# where every name is prepended with a positive sign '+' if the device is connected\\n\\t\\t\\t# and a negative sign '-' if it is not\\n\\t\\t\\\"guestlist\\\": (0, guestlist_handler),\\n\\t\\t\\t# guestlist\\n\\t\\t\\t# retrieve the guestlist\\n\\t\\t\\t# respond with a list of unverified devices, using the format ('' )*\\n\\t\\t\\t# note that every guest is connected (otherwise it would just be removed from the list)\\n\\t\\t\\\"info\\\": (1, info_handler),\\n\\t\\t\\t# info \\n\\t\\t\\t# retrieve device profile\\n\\t\\t\\t# respond with the list of device properties in the profile using the format\\n\\t\\t\\t# \\n\\t\\t\\t# where connected is formatted as + if the device is connected as - if it is not, e.g.\\n\\t\\t\\t# '-sonoff on' indicates a disconnected sonoff device with a status of 'on'\\n\\t\\t\\\"schedule\\\": (1, schedule_handler)\\n\\t\\t\\t# schedule \\n\\t\\t\\t# retrieve device schedule\\n\\t\\t\\t# respond with a list of scheduled commands for the given device using the formats\\n\\t\\t\\t# timed (exact|fuzzy) \\n\\t\\t\\t# recurrent (exact|fuzzy) []\\n\\t\\t\\t# for timed and recurrent operations respectively;\\n\\t\\t\\t# the specifics of each formats are the same as for their schedule counterparts\\n\\t}\\n\\t\\n\\ttry:\\n\\t\\t(expected_nargs, delegate) = commands[cmd]\\n\\texcept KeyError:\\n\\t\\tprint(\\\"Unrecognized command, skipping\\\", file=sys.stderr)\\n\\t\\treturn\\n\\t\\n\\tprocesscmd(cmd, args, expected_nargs, delegate)\",\n \"def get_input(prompt):\\n return input(prompt)\",\n \"def get_input(prompt):\\n return input(prompt)\",\n \"def inp(text):\\r\\n input(text)\",\n \"def evaluate(self, line):\\n locals = self.curframe().f_locals\\n globals = self.curframe().f_globals\\n try:\\n code = compile(line + '\\\\n', '', 'single')\\n exec(code, globals, locals)\\n except Exception:\\n import sys\\n t, v = sys.exc_info()[:2]\\n if isinstance(t, type('')):\\n exc_type_name = t\\n else:\\n exc_type_name = t.__name__\\n print('*** {}: {}'.format(exc_type_name, v))\",\n \"def ask_user_input(self, sentence):\\n user_input = raw_input(sentence + \\\" : \\\")\\n return user_input\",\n \"def do_say(self, line):\\n if line != '':\\n print(line)\",\n \"def __edit_line(self, line, code, code_obj): # pylint: disable=R0201\\r\\n try:\\r\\n result = eval(code_obj, globals(), locals())\\r\\n except TypeError as ex:\\r\\n message = \\\"failed to execute {}: {}\\\".format(code, ex)\\r\\n logger.warning(message)\\r\\n raise EditorError(message)\\r\\n if result is None:\\r\\n raise EditorError(\\\"cannot process line '{}' with {}\\\".format(\\r\\n line, code))\\r\\n elif isinstance(result, list) or isinstance(result, tuple):\\r\\n line = ' '.join([str(res_element) for res_element in result])\\r\\n else:\\r\\n line = str(result)\\r\\n return line\",\n \"def get_input(prompt):\\n # type: (str) -> str\\n return raw_input(prompt)\",\n \"def main():\\n dt = DropToken()\\n play = True\\n while play:\\n try:\\n line = sys.stdin.readline()\\n except KeyboardInterrupt:\\n break\\n if not line:\\n break\\n play = dt.inputProcess(line)\",\n \"def ask_user_input(prompt: str) -> str:\\n return input(prompt)\",\n \"def interact(self, prompt='debug> '):\\r\\n msg = 'Entering Octave Debug Prompt...\\\\n%s' % prompt\\r\\n self.stdout.write(msg)\\r\\n while 1:\\r\\n inp_func = input if not PY2 else raw_input\\r\\n try:\\r\\n inp = inp_func() + '\\\\n'\\r\\n except EOFError:\\r\\n return\\r\\n if inp in ['exit\\\\n', 'quit\\\\n', 'dbcont\\\\n', 'dbquit\\\\n']:\\r\\n inp = 'return\\\\n'\\r\\n self.write('disp(char(3));' + inp)\\r\\n if inp == 'return\\\\n':\\r\\n self.write('return\\\\n')\\r\\n self.write('clear _\\\\n')\\r\\n self.readline()\\r\\n self.readline()\\r\\n if not pty is None:\\r\\n self.readline()\\r\\n self.write('disp(char(3))\\\\n')\\r\\n return\\r\\n self.expect('\\\\x03')\\r\\n self.stdout.write(self.expect(prompt))\",\n \"def input_helper(prompt):\\n if version_info[0] == 2:\\n # python2 input is scary - we want raw_input\\n return raw_input(prompt)\\n else:\\n return input(prompt)\",\n \"def cmd_note(cls): \\n print(\\\"Enter/Paste your release note. To save use Ctrl-Z (windows) or Ctrl-D in a new line and press Enter.\\\")\\n inputNote = sys.stdin.readlines()\\n note = ''\\n for line in inputNote:\\n note += line\\n return note\",\n \"def cmd_note(cls): \\n print(\\\"Enter/Paste your release note. To save use Ctrl-Z (windows) or Ctrl-D in a new line and press Enter.\\\")\\n inputNote = sys.stdin.readlines()\\n note = ''\\n for line in inputNote:\\n note += line\\n return note\",\n \"def Prompt(self):\\n self.cli.context_was_set = not self.cli.config.context\\n doc = self.cli.run()\\n return doc.text if doc else None\",\n \"def precmd(self, line):\\n return line.strip()\",\n \"def getInput(prompt):\\n if platform.python_version().startswith('3'):\\n userInput = input('%s ' % prompt).strip()\\n if platform.python_version().startswith('2'):\\n userInput = raw_input('%s ' % prompt).strip()\\n return userInput\",\n \"def run(self, cmdline):\\n self.send(cmdline+\\\"\\\\n\\\")\\n rdata = '\\\\n'.join(self.recv_to_prompt())\\n return rdata\",\n \"def test_single_dialog_prompt_extra_line(monkeypatch, capsys):\\n monkeypatch.setattr(\\\"sys.stdin\\\", io.StringIO(\\\"value\\\" + \\\"\\\\n\\\"))\\n _dialog_prompt(\\n parameter=DialogParameter(\\\"Title\\\", comment=\\\"Comment\\\"),\\n )\\n captured = capsys.readouterr()\\n assert captured.out.count(\\\"\\\\n\\\") == 2\",\n \"def handle_input(self):\\n\\n\\t\\tline = sys.stdin.readline().strip()\\n\\n\\t\\tif line == '':\\n\\t\\t\\t# print('')\\n\\t\\t\\tself.print_prompt()\\n\\t\\t\\treturn\\n\\n\\t\\tcommand_name, *parts = line.split()\\n\\n\\t\\tif command_name in self.commands:\\n\\t\\t\\t# Call given command and unpack parts into args\\n\\t\\t\\tself.commands[command_name]['callback'](*parts)\\n\\t\\telse:\\n\\t\\t\\tprint(command_name + ' : command not found')\\n\\t\\t\\tself.print_available_commands()\\n\\n\\n\\t\\tself.print_prompt()\",\n \"def get_input(*args, **kw):\\n if sys.version[0] == \\\"2\\\":\\n return raw_input(*args, **kw)\\n else:\\n return input(*args, **kw)\",\n \"def start_interaction():\\r\\n\\r\\n # Loop infinitely\\r\\n while True:\\r\\n # Prints 'Say something: ' and then waits for user input\\r\\n # Note: line gets a string value\\r\\n line = input('Say something: ')\\r\\n\\r\\n # Right now, not very interesting...?\\r\\n if line == EASTER_EGG:\\r\\n print(EASTER_EGG_RESPONSE)\\r\\n else:\\r\\n print(repeat(line))\",\n \"def inputProcess(self, line):\\n fields = line.split()\\n # check if input argument size is not 1 or 2\\n if len(fields) < 1 or len(fields) > 2:\\n print 'Invalid input size!'\\n return True\\n # call corresponding functions based on input argument(s)\\n if fields[0] == 'GET':\\n res = self.get()\\n if res != '':\\n print res,\\n elif fields[0] == 'EXIT':\\n return False\\n elif fields[0] == 'BOARD':\\n print self.displayBoard()\\n elif fields[0] == 'PUT':\\n if len(fields) != 2:\\n print 'PUT command needs one argument!'\\n return True\\n try:\\n column = int(fields[1])\\n if column < 1 or column > 4:\\n print 'Column number for PUT command needs to be from 1 to 4'\\n else:\\n print self.put(column)\\n except ValueError:\\n print 'Invalid input, for column number please enter an integer from 1 to 4'\\n else:\\n print 'Invalid input, valid commands consists of GET BOARD EXIT PUT only'\\n return True\",\n \"def lineReceived(self, line):\\n rbuffer = StringIO()\\n po=sys.stdout\\n sys.stdout = rbuffer\\n err=False\\n if not hasattr(self,\\\"dc\\\"):\\n self.dc={\\\"self\\\":self.server}\\n print \\\"dc:\\\", self.dc\\n try: exec(line,self.dc)\\n except Exception as e: err=e\\n except KeyboardInterrupt : pass\\n # remove backeffect on dictionary\\n if self.dc.has_key('__builtins__'): \\n del self.dc['__builtins__']\\n # update data context\\n # remember to restore the original stdout!\\n sys.stdout = po\\n print '>u> '+line\\n if err: out = self.pre_e+str(e)+self.post_e\\n else: out = rbuffer.getvalue()\\n if out!=\\\"\\\": print '>s> ' + out\",\n \"def user_input(self, options, prompt):\\n for o in options:\\n line = self.selector_line(o)\\n o[\\\"line\\\"] = line\\n self.output(line)\\n self.output(prompt, end=\\\" \\\")\\n while True:\\n if self.test_input:\\n inp = self.test_input.pop(0)\\n self.output(f\\\"Using '{inp}' test input\\\")\\n else:\\n try:\\n inp = raw_input()\\n except (IOError, KeyboardInterrupt):\\n self.game.print_state()\\n raise\\n if inp:\\n matching = []\\n for o in options:\\n if o[\\\"selector\\\"] == inp:\\n return o\\n if inp.lower() in o[\\\"line\\\"].lower() and o[\\\"selector\\\"] != \\\"-\\\":\\n matching.append(o)\\n if len(matching) == 1:\\n return matching[0]\\n self.output(f\\\"Invalid Option ({inp})\\\")\",\n \"def handle_line(self, line):\\n LOG.debug(\\\"Received line of input from client %s: %s\\\", self.addr, line)\",\n \"def GetLine(line):\\r\\n pass\",\n \"def console():\\n repl(click.get_current_context())\",\n \"def REPL(\\n parse_tree_fn: Callable,\\n output_style_fn: Callable,\\n session: bool,\\n mode: str,\\n show_tree_fn=None,\\n debug=False,\\n) -> None:\\n print(\\n \\\"Enter a Mathematica expression. Enter either an empty line, Ctrl-C, or Ctrl-D to exit.\\\"\\n )\\n in_count = 1\\n while True:\\n try:\\n user_in = input(f\\\"In[{in_count}]:= \\\")\\n except (KeyboardInterrupt, EOFError):\\n break\\n else:\\n in_count += 1\\n if user_in == \\\"\\\":\\n break\\n\\n eval_one(\\n in_str=user_in,\\n parse_tree_fn=parse_tree_fn,\\n output_style_fn=output_style_fn,\\n mode=mode,\\n session=session,\\n show_tree_fn=show_tree_fn,\\n debug=debug,\\n )\\n pass\\n return\",\n \"def handle_line(line):\\n print line,\\n\\n line_parts = log_re.match(line).groupdict()\\n action = line_parts['action']\\n attacker = line_parts['attacker']\\n\\n (cmd, status, output) = interact(line_parts, method=opts.method)\\n\\n if status > 0:\\n warnings.warn('IP %s (%s)' % (attacker, output), InteractionWarning)\\n print '\\\\t%s FAILURE' % attacker\\n else:\\n print '\\\\t%s SUCCESS' % attacker\\n \\n print\",\n \"def get_value(Runner, input_str):\\n Runner.stdin.write(input_str)\\n output = Runner.stdout.readline() \\n return output\",\n \"def user_prompt(prompt, default=None):\\n prompt = f\\\"\\\\n {prompt} [{default}] runs or type an amount: \\\"\\n response = input(prompt)\\n if not response and default:\\n return default\\n else:\\n return response\",\n \"def lineReceived(self, line):\\n self.sendLine('reply '+line)\",\n \"def main(self):\\n cmd = \\\"self.%s(sys.stdin)\\\" % sys.argv[1]\\n exec(cmd)\",\n \"def gip(line):\\n import os\\n import shlex\\n import textwrap\\n args = shlex.split(line)\\n if len(args) == 0:\\n path = '~/.ipyscratch'\\n else:\\n try:\\n path = eval(line)\\n except:\\n path = args[0]\\n with open(os.path.expanduser(path)) as f:\\n cmd = textwrap.dedent(f.read())\\n get_ipython().run_line_magic('pycat', path)\\n # update history\\n In[-1] = cmd\\n get_ipython().run_code(cmd)\",\n \"def interactive(self, *args, **kwargs):\\n if args == (['python'],):\\n return\\n raise ValueError(self, args, kwargs)\",\n \"def UserInput(self, username, userinput):\\n pass\",\n \"def run_interactive(cls, shell, command, input):\\n feed = '\\\\\\\\n'.join(input)\\n icommand = \\\"echo -e '{}' | {}\\\".format(feed, command)\\n _stdout, _stderr = cls.run(shell, icommand)\\n return _stdout\",\n \"def main():\\n line_count = int(input().strip())\\n lines = sys.stdin.readlines()[:line_count]\\n for line in lines:\\n print('YES' if contains_hackerrank(line) else 'NO')\",\n \"def run(self, name, rawtext, text, lineno, inliner, options=None,\\n content=None):\\n raise NotImplementedError\",\n \"def safe_input(display_string):\\n\\n try:\\n x = raw_input(display_string)\\n except NameError:\\n x = input(display_string)\\n\\n return x\",\n \"def main():\\n user_interaction()\",\n \"def default(self, line):\\n print \\\"Command not found\\\\n\\\"\",\n \"def user_line(self, frame):\\n pass\",\n \"def default(self, line):\\n line = line.split(' ')[0]\\n self.PRINT.warning(line + \\\": command not found\\\")\\n self.PRINT.newline()\",\n \"def onecmd(self, line):\\n statement = self.parsed(line)\\n self.lastcmd = statement.parsed.raw\\n funcname = self.func_named(statement.parsed.command)\\n if not funcname:\\n return self._default(statement)\\n try:\\n func = getattr(self, funcname)\\n except AttributeError:\\n return self._default(statement)\\n stop = func(statement)\\n return stop\",\n \"def getInput(self):\\n self.userInput = self.entry.get()\",\n \"def user_input(self, msg, default=''):\\n msg = '%s %s ' % (self.prefix, msg)\\n\\n if default != '':\\n msg += '[%s] ' % default\\n\\n try:\\n vim.command('echohl Debug')\\n input_str = vim.eval('input(\\\"%s> \\\")' % msg)\\n vim.command('echohl none')\\n except KeyboardInterrupt:\\n input_str = ''\\n\\n return input_str or default\",\n \"def rawInput(string):\\n if os.name == \\\"posix\\\":\\n tcflush(sys.stdin, TCIFLUSH)\\n return input(string)\",\n \"def do_action_for_input(self, user_input):\\n if user_input == CommandLineProgram.ACTION.HELP:\\n self.print_help()\\n elif user_input == CommandLineProgram.ACTION.ADD_USER:\\n self.input_and_create_user()\\n elif user_input == CommandLineProgram.ACTION.LIST_USERS:\\n self.print_users()\\n elif user_input == CommandLineProgram.ACTION.ADD_TRANSACTION:\\n self.select_user_and_add_transaction()\\n elif user_input == CommandLineProgram.ACTION.GENERATE_REPORT:\\n self.select_user_and_print_report()\",\n \"def process_input(line: str) -> None:\\n\\n # Do not lines if empty or commands\\n # Built in commands take precedence to other processing\\n if line_valid(line) and not check_commands(line):\\n\\n # Split the line into its constituent words\\n words = line.split(' ')\\n\\n while unknown_words(words) is not None:\\n # As long as any words in the last line are unknown, attempt to learn them\\n learn_new_word(unknown_words(words))\\n\\n if len(words) == 1:\\n # Attempt to learn the definition of single-word input\\n learn_new_defn(words.pop())\\n\\n wait()\"\n]"},"negative_scores":{"kind":"list like","value":["0.695336","0.66525394","0.65766966","0.6399153","0.63881487","0.63797593","0.63621664","0.6285082","0.62843174","0.6240477","0.6193314","0.6086187","0.60828507","0.6036487","0.5988181","0.59823424","0.5970285","0.59633726","0.59236956","0.5900732","0.5900732","0.58744293","0.58585066","0.5855987","0.5830384","0.5821434","0.573722","0.57318777","0.5709697","0.5680791","0.5657915","0.5655651","0.5649584","0.56370205","0.56324923","0.56302655","0.56287134","0.5620079","0.5617121","0.561243","0.56116605","0.56086504","0.5578386","0.5573463","0.5544984","0.55378884","0.5527542","0.5521601","0.55150205","0.5510962","0.55082816","0.55082816","0.550794","0.54938686","0.54850066","0.5476465","0.54734993","0.54711634","0.5467746","0.54617625","0.5460441","0.54434174","0.543709","0.543709","0.5425275","0.5421998","0.5421081","0.54173934","0.54122514","0.5399537","0.53938824","0.53904015","0.53824246","0.5369121","0.53654414","0.5363004","0.53598166","0.5358896","0.53544044","0.53405094","0.53338534","0.5319089","0.53030705","0.52922326","0.5290135","0.52890736","0.5284703","0.5282021","0.52807033","0.52779156","0.52747416","0.5262039","0.52620256","0.5257792","0.523936","0.52380896","0.5236481","0.5234185","0.5234075","0.52331597","0.5228141"],"string":"[\n \"0.695336\",\n \"0.66525394\",\n \"0.65766966\",\n \"0.6399153\",\n \"0.63881487\",\n \"0.63797593\",\n \"0.63621664\",\n \"0.6285082\",\n \"0.62843174\",\n \"0.6240477\",\n \"0.6193314\",\n \"0.6086187\",\n \"0.60828507\",\n \"0.6036487\",\n \"0.5988181\",\n \"0.59823424\",\n \"0.5970285\",\n \"0.59633726\",\n \"0.59236956\",\n \"0.5900732\",\n \"0.5900732\",\n \"0.58744293\",\n \"0.58585066\",\n \"0.5855987\",\n \"0.5830384\",\n \"0.5821434\",\n \"0.573722\",\n \"0.57318777\",\n \"0.5709697\",\n \"0.5680791\",\n \"0.5657915\",\n \"0.5655651\",\n \"0.5649584\",\n \"0.56370205\",\n \"0.56324923\",\n \"0.56302655\",\n \"0.56287134\",\n \"0.5620079\",\n \"0.5617121\",\n \"0.561243\",\n \"0.56116605\",\n \"0.56086504\",\n \"0.5578386\",\n \"0.5573463\",\n \"0.5544984\",\n \"0.55378884\",\n \"0.5527542\",\n \"0.5521601\",\n \"0.55150205\",\n \"0.5510962\",\n \"0.55082816\",\n \"0.55082816\",\n \"0.550794\",\n \"0.54938686\",\n \"0.54850066\",\n \"0.5476465\",\n \"0.54734993\",\n \"0.54711634\",\n \"0.5467746\",\n \"0.54617625\",\n \"0.5460441\",\n \"0.54434174\",\n \"0.543709\",\n \"0.543709\",\n \"0.5425275\",\n \"0.5421998\",\n \"0.5421081\",\n \"0.54173934\",\n \"0.54122514\",\n \"0.5399537\",\n \"0.53938824\",\n \"0.53904015\",\n \"0.53824246\",\n \"0.5369121\",\n \"0.53654414\",\n \"0.5363004\",\n \"0.53598166\",\n \"0.5358896\",\n \"0.53544044\",\n \"0.53405094\",\n \"0.53338534\",\n \"0.5319089\",\n \"0.53030705\",\n \"0.52922326\",\n \"0.5290135\",\n \"0.52890736\",\n \"0.5284703\",\n \"0.5282021\",\n \"0.52807033\",\n \"0.52779156\",\n \"0.52747416\",\n \"0.5262039\",\n \"0.52620256\",\n \"0.5257792\",\n \"0.523936\",\n \"0.52380896\",\n \"0.5236481\",\n \"0.5234185\",\n \"0.5234075\",\n \"0.52331597\",\n \"0.5228141\"\n]"},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":8564,"cells":{"query":{"kind":"string","value":"Encodes user verification request using user profile ID as pub key."},"document":{"kind":"string","value":"def generate_authentication_code(user):\n\n salt = 'd9!1l@39#c3'\n\n expire_timestamp = time.time() + EXPIRE_TIME_LIMIT\n # Make a string which depends on restaurant id\n # Same encoding mechanism will be used in seerpod hardware\n\n composite_string = \"%s%s%s\" % (user.id, user.password, salt)\n\n str_hex = hashlib.md5(composite_string).hexdigest()\n decoded_str = str(user.owner_email_id) + str(user.id) + \"_\" + str(expire_timestamp) + \"_\" + str_hex\n\n # Encoded string will be a multiple line string, if it is greater\n # than maximum bin size of 76. Browser strips the newline character\n # in the url.\n encoded = base64.encodestring(decoded_str).strip().replace('\\n', '')\n return encoded"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def get_verification_code(self, user_id, verify_type, secret):\n user = self.get(user_id, raise_error=True)\n code_hash = hmac.new(secret)\n code_hash.update(str(user_id))\n code_hash.update(str(user.user_name))\n code_hash.update(str(verify_type))\n return code_hash.hexdigest()","def gen_verification_token(user):\n exp_date = timezone.now() + timedelta(days=3)\n payload = {\n 'user': user.username,\n 'exp': int(exp_date.timestamp()),\n 'type': 'email_confirmation'\n }\n token = jwt.encode(payload, settings.SECRET_KEY, algorithm='HS256')\n return token.decode()","def recipient_public_key(self):","def code_challenge(verifier):\n digest = hashlib.sha256(verifier).digest()\n return base64.urlsafe_b64encode(digest).rstrip(b'=')","def get_verification_code(request):\n\n if request.user.get_profile().is_verified:\n messages.info(request, 'Olet jo vahvistanut osoitteesi')\n else:\n verification_code = request.user.get_profile().gen_verification_code()\n extractx = {\n 'code': verification_code,\n }\n subject = _('Verification code')\n email_helpers.send_user_email(request.user, subject, 'send_verification_code.txt', extractx)\n\n messages.info(request, 'Vahvistuskoodi on lähetetty sähköpostiisi')\n\n return HttpResponseRedirect(reverse('user', args=(request.user.username,)))","def gen_verification_token(user):\n exp_date = timezone.now() + timedelta(days= 3)\n payload = {\n 'user': user.username,\n 'exp': int (exp_date.timestamp()),\n 'type': 'email_confirmation'\n }\n token = jwt.encode(payload, settings.SECRET_KEY, algorithm= 'HS256')\n return token","def gen_verification_token(self, user):\n exp_date = timezone.now() + timedelta(days=3)\n payload = {\n 'user': user.username,\n 'exp': int(exp_date.timestamp()),\n 'type': 'email_confirmation'\n }\n token = jwt.encode(payload, settings.SECRET_KEY, algorithm='HS256')\n return token","def encode_auth_token(user_id, email):\n try:\n payload = {\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=100, seconds=5),\n 'iat': datetime.datetime.utcnow(),\n 'sub': email + ' ' + str(user_id)\n }\n return jwt.encode(\n payload,\n key,\n algorithm='HS256'\n )\n except Exception as e:\n return e","def gen_verification_token(user):\n exp_date = timezone.now() + timedelta(days=3)\n payload = {\n 'user': user.username,\n 'exp': int(exp_date.timestamp()),\n 'type': 'email_confirmation'\n }\n # Generacion del token\n token = jwt.encode(payload, settings.SECRET_KEY, algorithm='HS256')\n return token","def get_recovery_code(self, key, user_id):\n user = self.get(user_id, raise_error=True)\n h = hmac.new(key)\n h.update('%s%s%s%s' % (user_id, user.user_name, user.email, user.password))\n return h.hexdigest()","def get(self, request):\n token = request.GET.get('token')\n payload = jwt.decode(token, settings.SECRET_KEY, algorithms='HS256')\n print(f'payload {payload}')\n user = User.objects.get(id = payload['user_id'])\n \n if not user.email_verified:\n user.email_verified = True\n user.save()\n return response.Response({'email': \"successful email verification\"}, status = status.HTTP_200_OK)\n return response.Response({'error': \"unsuccessful email verification\"}, status = status.HTTP_400_BAD_REQUEST)","def verify_email(self, request, *args, **kwargs):\n verified_key_text = getattr(settings, \"VERIFIED_KEY_TEXT\", None)\n\n if not verified_key_text:\n return Response(status=status.HTTP_204_NO_CONTENT)\n\n redirect_url = request.query_params.get(\"redirect_url\")\n verification_key = request.query_params.get(\"verification_key\")\n response_message = _(\"Missing or invalid verification key\")\n if verification_key:\n registration_profile = None\n try:\n registration_profile = RegistrationProfile.objects.select_related(\n \"user\", \"user__profile\"\n ).get(activation_key=verification_key)\n except RegistrationProfile.DoesNotExist:\n with use_master:\n try:\n registration_profile = (\n RegistrationProfile.objects.select_related(\n \"user\", \"user__profile\"\n ).get(activation_key=verification_key)\n )\n except RegistrationProfile.DoesNotExist:\n pass\n\n if registration_profile:\n registration_profile.activation_key = verified_key_text\n registration_profile.save()\n\n username = registration_profile.user.username\n set_is_email_verified(registration_profile.user.profile, True)\n # Clear profiles cache\n safe_delete(f\"{USER_PROFILE_PREFIX}{username}\")\n\n response_data = {\"username\": username, \"is_email_verified\": True}\n\n if redirect_url:\n query_params_string = urlencode(response_data)\n redirect_url = f\"{redirect_url}?{query_params_string}\"\n\n return HttpResponseRedirect(redirect_url)\n\n return Response(response_data)\n\n return HttpResponseBadRequest(response_message)","def mailru_sig(data):\n param_list = sorted(list(item + '=' + data[item] for item in data))\n return md5(''.join(param_list) +\n settings.MAILRU_OAUTH2_CLIENT_SECRET).hexdigest()","def _gen_activation_hash():\r\n # for now just cheat and generate an api key, that'll work for now\r\n return User.gen_api_key()","def request_verification(data):\n if 'email' in data:\n if user_exists(data['email']):\n return get_user_id(data['email'])\n else:\n return 401\n else:\n return 400","def encode_auth_token(self, user_id):\n try:\n payload = {\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=1, seconds=0),\n 'iat': datetime.datetime.utcnow(),\n 'sub': user_id\n }\n return jwt.encode(\n payload,\n app.config.get('SECRET_KEY'),\n algorithm='HS256'\n )\n except Exception as e:\n return e","def encode_email(email, key):\n return","def verify_user(self, tokendict):\n return self.post('verify', tokendict)","async def _encrypt_external_sub_id(sefl, external_user: ExternalUser) -> str:\n\t\tsalt = external_user.email.lower()\n\t\tsalt = salt.replace(\" \", \"\")\n\t\t# Hash the salt so that the email is not plain text visible in the database\n\t\tsalt = hashlib.sha256(salt.encode()).hexdigest()\n\t\t# bcrypt requires a 22 char salt\n\t\tif len(salt) > 21:\n\t\t\tsalt = salt[:21]\n\n\t\t# As per passlib the last character of the salt should always be one of [.Oeu]\n\t\tsalt = salt + \"O\"\n\n\t\tencrypted_external_sub_id = bcrypt.using(salt=salt).hash(external_user.external_sub_id)\n\t\treturn encrypted_external_sub_id","def key_request(self, user):\n\t\tclient_log.debug(f'Запрос публичного ключа для {user}')\n\t\treq = {\n\t\t\tACTION: PUBLIC_KEY_REQUEST,\n\t\t\tTIME: time.time(),\n\t\t\tACCOUNT_NAME: user\n\t\t}\n\t\twith socket_lock:\n\t\t\tsend_message(self.transport, req)\n\t\t\tans = get_message(self.transport)\n\t\tif RESPONSE in ans and ans[RESPONSE] == 511:\n\t\t\treturn ans[DATA]\n\t\telse:\n\t\t\tclient_log.error(f'Не удалось получить ключ собеседника{user}.')","def get_activation_key(self, user):\n return signing.dumps(obj=user.get_username(), salt=REGISTRATION_SALT)","def public_key(self):","def base64_pub_encode(self, key):\n (y, g, p, q) = (str(key.y), str(key.g), str(key.p), str(key.q))\n return base64.b64encode((y + \",\" + g + \",\" + p + \",\" + q).encode('utf-8')).decode('utf-8')","def encode_u_id(u_id):\n return jwt.encode({\n \"u_id\": u_id,\n \"datetime\": json_time_translator.datetime_to_json(datetime.utcnow())\n }, '1$Arh\"1bWa/7+OS', algorithm='HS256').decode('utf-8')","def get_activation_key(self, user):\n\t\treturn signing.dumps(\n\t\t\tobj=getattr(user, user.USERNAME_FIELD),\n\t\t\tsalt=REGISTRATION_SALT\n\t\t)","def encode_auth_token(self,user_id): \n try: \n exp = datetime.utcnow() + timedelta(days=1)\n \n payload = {\n 'exp': exp, \n 'iat': datetime.utcnow(), \n 'sub': user_id\n }\n \n encoded_auth_token = jwt.encode(\n payload, \n getattr(settings, \"SECRET_KEY\",\"\"),\n algorithm='HS256'\n )\n return encoded_auth_token\n except Exception as e: \n print_exception(e)\n return e","def new_profile(email):\n key = challenge_12.deterministic_random_key()\n profile = bytes(profile_for(email.decode()), 'ascii')\n\n return challenge_11.AES_ECB(key).encrypt(profile)","def test_verified_user(self):\n self.nodes[0].overlay.trustchain.get_github_profile = lambda username: {\n \"username\": username,\n \"bio\": self.nodes[0].overlay.my_peer.mid.encode('hex'),\n \"followers\": 1337\n }\n yield self.nodes[0].overlay.trustchain.import_github_profile(\"test\")\n yield self.deliver_messages()\n\n self.assertTrue(self.nodes[1].overlay.trustchain.persistence.is_verified_user(self.nodes[0].overlay.my_peer.public_key.key_to_bin()))","def encode_auth_token(secret_key, user_id):\n try:\n payload = {\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(minutes=60),\n 'iat': datetime.datetime.utcnow(),\n 'sub': user_id\n }\n return jwt.encode(\n payload,\n secret_key,\n algorithm='HS256'\n )\n except Exception as e:\n return e","def encode_auth_token(user_id):\n rfexp = datetime.datetime.utcnow() + datetime.timedelta(days=1, seconds=5)\n exp = int(time.time()+600)\n try:\n payload = {\n 'exp': exp,\n 'iat': datetime.datetime.utcnow(),\n 'sub': user_id\n }\n RFpayload = {\n 'exp': rfexp,\n 'iat': datetime.datetime.utcnow(),\n 'sub': user_id\n }\n return jwt.encode(\n payload,\n key,\n algorithm='HS256'\n ), jwt.encode(\n RFpayload,\n key,\n algorithm='HS512'\n )\n except Exception as e:\n return e","def encode_auth_token(userdata):\n try:\n payload = {\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=10),\n 'iat': datetime.datetime.utcnow(),\n 'uid': userdata['uid'],\n 'pwd':userdata['pwd'],\n 'role': userdata['role']\n }\n return jwt.encode(\n payload,\n Config.SECRET_KEY,\n algorithm='HS256'\n )\n except Exception as e:\n return e","def _encrypted_user_photo_key_str(self):\r\n face_aes_key_str = settings.VERIFY_STUDENT[\"SOFTWARE_SECURE\"][\"FACE_IMAGE_AES_KEY\"]\r\n face_aes_key = face_aes_key_str.decode(\"hex\")\r\n rsa_key_str = settings.VERIFY_STUDENT[\"SOFTWARE_SECURE\"][\"RSA_PUBLIC_KEY\"]\r\n rsa_encrypted_face_aes_key = rsa_encrypt(face_aes_key, rsa_key_str)\r\n\r\n return rsa_encrypted_face_aes_key.encode(\"base64\")","def email_key(self):\r\n url = '{0}/emailKey/generate'.format(self.get_url())\r\n request = http.Request('POST', url)\r\n return request, parsers.parse_json","def __verify(self):\r\n code = self.request.get('code')\r\n email = None\r\n error = False\r\n # resend if code is not given or in case of some error\r\n if code is not None and code != '':\r\n email = User.verify(code, self.request.remote_addr)\r\n if email is None:\r\n error = True\r\n\r\n if email is None:\r\n template_values = {\r\n 'user_email': self.user_email,\r\n 'error': error\r\n }\r\n template = self.jinja2_env.get_template('verification.html')\r\n self.response.out.write(template.render(template_values))\r\n\r\n # message\r\n template_values = {\r\n 'user_email': self.user_email,\r\n 'message': self.gettext('THANK_YOU')\r\n }\r\n template = self.jinja2_env.get_template('staticmessage.html')\r\n self.response.out.write(template.render(template_values))","def save(self):\n payload = self.context['payload']\n user = User.objects.get(username=payload['user'])\n user.is_verified = True\n user.save()","def __send_verification(self, email):\r\n user = User.getUser(email.lower())\r\n if user is None or user.verified:\r\n self.set_error(constants.STATUS_BAD_REQUEST, message=None, url=\"/\")\r\n return\r\n user.verificationCode = b64encode(CryptoUtil.get_verify_code(), \"*$\")\r\n template_values = {\r\n 'user_email': self.user_email,\r\n 'code': user.verificationCode,\r\n 'url': constants.VERIFICATION_URL\r\n }\r\n template = self.jinja2_env.get_template('verificationemail.jinja')\r\n message = mail.EmailMessage()\r\n message.sender = constants.SENDER_ADDRESS\r\n message.to = user.email\r\n message.subject = 'Please verify your address'\r\n message.body = template.render(template_values)\r\n message.send()\r\n user.put()","def main():\n key, plain = get_key_plain()\n encode(key, plain)","def _get_private_key(self, user_obj):\n return user_obj.private_key.encode('utf-8')","def validate_code(request):\n user_id = api.keystone.get_user_id(request)\n print \"USER CHECK\"\n print user_id\n user = api.keystone.user_get(request, user_id)\n user_auth_code = request.GET.get('auth_code', None)\n secret = request.GET.get('secret', None)\n\n #Generate a code form our side using algorithm and use it to validate\n generated_code = api.keystone.generate_totp(secret)\n\n print secret\n print user_auth_code\n print generated_code\n print 'entering code comparison'\n \n data = {}\n extra = {}\n\n #Code comparison\n if user_auth_code == generated_code:\n data['totp_authenticated'] = True\n extra['two_factor_enabled'] = True\n\textra['secret_key'] = secret\n api.keystone.enable_2fa(request, user, **extra)\n else:\n \tprint 'falseeeeee'\n data['totp_authenticated'] = False\n return JsonResponse(data)","def encoded_validation_cert_pub_key(self) -> str:\n return pulumi.get(self, \"encoded_validation_cert_pub_key\")","def encoded_validation_cert_pub_key(self) -> str:\n return pulumi.get(self, \"encoded_validation_cert_pub_key\")","def send_verification_email(self, request, *args, **kwargs):\n verified_key_text = getattr(settings, \"VERIFIED_KEY_TEXT\", None)\n if not verified_key_text:\n return Response(status=status.HTTP_204_NO_CONTENT)\n\n username = request.data.get(\"username\")\n redirect_url = request.data.get(\"redirect_url\")\n response_message = _(\"Verification email has NOT been sent\")\n\n if username:\n try:\n registration_profile = RegistrationProfile.objects.get(\n user__username=username\n )\n except RegistrationProfile.DoesNotExist:\n pass\n else:\n user = registration_profile.user\n set_is_email_verified(user.profile, False)\n\n verification_key = registration_profile.activation_key\n if verification_key == verified_key_text:\n verification_key = (\n user.registrationprofile.create_new_activation_key()\n )\n\n verification_url = get_verification_url(\n redirect_url, request, verification_key\n )\n\n email_data = get_verification_email_data(\n user.email,\n user.username,\n verification_url,\n request,\n )\n\n send_verification_email.delay(**email_data)\n response_message = _(\"Verification email has been sent\")\n\n return Response(response_message)\n\n return HttpResponseBadRequest(response_message)","def send_verification(self):\n pass","def public_key(ctx):\n if not ctx.data:\n raise RefError(\n \"Ref error: eval_func: public key cannot be derived; try \"\n \"something like '|reveal:path/to/encrypted_private_key|publickey'\"\n )\n\n data_dec = ctx.data\n if ctx.ref_encoding == \"base64\":\n data_dec = base64.b64decode(data_dec).decode()\n\n private_key = serialization.load_pem_private_key(\n data_dec.encode(), password=None, backend=default_backend()\n )\n public_key = private_key.public_key()\n\n ctx.data = str(\n public_key.public_bytes(\n encoding=serialization.Encoding.PEM, format=serialization.PublicFormat.SubjectPublicKeyInfo\n ),\n \"UTF-8\",\n )","def encode_auth_token(userdata):\n try:\n payload = {\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=10),\n 'iat': datetime.datetime.utcnow(),\n 'username': userdata['username'],\n 'password':userdata['password']\n }\n return jwt.encode(\n payload,\n Config.SECRET_KEY,\n algorithm='HS256'\n )\n except Exception as e:\n return e","def _make_hash_value(self, user, timestamp):\n return (\n six.text_type(user.pk) + six.text_type(timestamp) +\n six.text_type(user.profile.signup_confirmation)\n )","def sendPublicKey(g, p, s):\r\n status = \"120 PubKey \" + str(computePublicKey(g, p, s))\r\n return status","def _get_user_id(user_data: dict):\n data = json.dumps(user_data).encode('utf-8')\n hashed_data = hashlib.sha256()\n hashed_data.update(data)\n return hashed_data.hexdigest()","def verifyemail(request,id=None,key=None):\n logging.debug('')\n if settings.EMAIL_VALIDATION == True:\n user = User.objects.get(id=id)\n if user:\n if user.email_key == key:\n user.email_isvalid = True\n clear_email_validation_message(user)\n user.save()\n data = {'action_type': 'validation_complete'}\n return render_to_response(\n 'authenticator/changeemail.html',\n RequestContext(request, data)\n )\n else:\n logging.error('hmm, no user found for email validation message - foul play?')\n raise Http404","def verify_code(email, val):\r\n # TODO: is this the right string?\r\n verification_string = email.lower() + '|' + val\r\n return hashlib.md5(verification_string).hexdigest()","def set_user_verified(self, authenticator_id, uv):\n pass","def create_s256_code_challenge(code_verifier: str) -> str:\n code_verifier_bytes = code_verifier.encode(\"utf-8\")\n data = hashlib.sha256(code_verifier_bytes).digest()\n return base64.urlsafe_b64encode(data).rstrip(b\"=\").decode()","def raw(self) -> bytes:\n return bytes(self._verify_key)","def get_api_key_params(user):\n if user and user.is_authenticated():\n api_key, _ = APIKey.objects.get_or_create(user=user)\n return urlencode({'user': user.pk, 'key': api_key.key})\n return ''","def verify_key(self, providerkey = None):\n h = Https(API_DOMAIN)\n\n data = {'apikey' : self.apikey}\n\n if providerkey is not None:\n data['providerkey'] = providerkey\n\n h.request( \"GET\",\n \"/publicapi/verify\"+ urlencode(data),\n headers=self.headers)\n\n request_status = h.getresponse().status\n\n if request_status != 200:\n raise Exception(\"Invalid API Key %s\" % self.apikey)","def send_verification(self):\n secret_key = app.config['CONTACT_VERIFY_SECRET']\n base_url = app.config['URLS']['BASE_URL']\n redditor = praw.models.Redditor(self.client, name=self.identifier)\n verify_url = contact_verify_url(self.contact.id, base_url, secret_key)\n redditor.message(\"Verify your username!\", verify_url)","def stubbed_receiver() -> PublicKey:\n return PublicKey(\"J3dxNj7nDRRqRRXuEMynDG57DkZK4jYRuv3Garmb1i99\")","def alt_stubbed_receiver() -> PublicKey:\n return PublicKey(\"J3dxNj7nDRRqRRXuEMynDG57DkZK4jYRuv3Garmb1i98\")","def from_key(self, public_id, key):\n otp = self.get_otp(key)\n from_key = modhex_encode(public_id.encode('hex')) + modhex_encode(otp.encode('hex'))\n return from_key","def generate_invitation_token(user_email, expiration=7*3600):\n ser = Serializer(current_app.config['SECRET_KEY'], expiration)\n return ser.dumps(\n {'user_email': user_email}).decode('utf-8')","def profileForEncrypt(self, emailAddress):\n kvstring = profileFor(emailAddress)\n # Turn the string into bytes\n kvbytes = kvstring.encode()\n # Encrypt it.\n data = padPkcs7(kvbytes, 16)\n return self.__aes.ecbEncrypt(data)","def encode_auth_token(user_id: int, user_name:str, user_login:str, perfil_nome:str) -> bytes:\n try:\n payload = {\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=1, seconds=5),\n 'iat': datetime.datetime.utcnow(),\n 'uid': user_id,\n 'name': user_name,\n 'login': user_login,\n 'perfil': perfil_nome,\n }\n return jwt.encode(\n payload,\n key,\n algorithm='HS256'\n )\n except Exception as e:\n return e","def verify(self, signature, body, external_aad, public_key):","def request_idkey(self):\r\n if self.use_http():\r\n self.enqueue_http_request(\"money/idkey\", {}, \"idkey\")\r\n else:\r\n self.send_signed_call(\"private/idkey\", {}, \"idkey\")","def create_pubkey_message(sender_nickname, sender_pubkey):\n tag = (VERSION<<16) | publicKeyOnly\n \n out = struct.pack(\" bytes:\n\n # builds content\n content = InvitationContent(\n **invitation_data.dict(),\n created=datetime.utcnow(),\n )\n\n content_jsonstr: str = _ContentWithShortNames.serialize(content)\n assert \"\\n\" not in content_jsonstr # nosec\n\n # encrypts contents\n return _fernet_encrypt_as_urlsafe_code(\n data=content_jsonstr.encode(),\n secret_key=secret_key,\n )","def get(self, request, token):\n try:\n encoded = token\n key = \"secret\"\n usr_details = jwt.decode(encoded, key=key, algorithms=\"HS256\")\n usr_name = usr_details.get(\"username\")\n check = CustomUser.objects.get(username=usr_name)\n if check:\n check.verified = True\n check.save()\n return Response({\"message\": \"VERIFIED\"}, status=200)\n return Response({\"message\": \"SOME THING WENT WRONG\"}, status=400)\n except Exception as e:\n user_log.exception(\"generic exception occurred\")\n return Response({\"message\": \"SOMETHING WENT WRONG\",\n \"detail\": e.args}, status=400)","def set_confirmation_code(cls, user_obj: User) -> str:\n confirmation_code = cls.generate_new_code()\n if user_obj.phone == '+996553000117' or user_obj.phone == '+996999111222':\n confirmation_code = '123456'\n user_obj.confirmation_code = confirmation_code\n user_obj.confirmation_date = timezone.now()\n user_obj.save(\n update_fields=['confirmation_code', 'confirmation_date'])\n return confirmation_code","def send_verification_email(self):\n url = (\"https://api.imgur.com/3/account/{0}\"\n \"/verifyemail\".format(self.name))\n self._imgur._send_request(url, needs_auth=True, method='POST')","def register(request, key):\n profile = cpm.UserProfile.objects.filter(\n activation_key=key)\n\n if not profile.exists() or profile[0].user.is_active:\n hero_title = 'Hmm... that registration key is invalid.'\n return render_err_msg(request, hero_title)\n\n user = profile[0].user\n\n if request.POST:\n reg_form = RegForm(request.POST)\n if reg_form.is_valid():\n user.is_active = True\n user.first_name = reg_form.cleaned_data['first_name']\n user.last_name = reg_form.cleaned_data['last_name']\n user.set_password(reg_form.cleaned_data['password'])\n\n pic_url = put_profile_pic(\n reg_form.cleaned_data['pic_url'], user.profile)\n if pic_url:\n user.profile.pic_url = pic_url\n\n user.profile.class_year = reg_form.cleaned_data['class_year']\n\n alt_emails = request.POST.getlist('alt_email')\n for alt_email in alt_emails:\n if alt_email:\n user.profile.add_email(alt_email)\n\n user.save()\n user.profile.save()\n\n user = auth.authenticate(username=user.username,\n password=reg_form.cleaned_data['password'])\n if user is not None:\n if user.is_active:\n auth.login(request, user)\n # Redirect to a success page.\n return redirect('/')\n\n else:\n reg_form = RegForm()\n\n template_values = {\n 'page_title': 'register',\n 'form': reg_form,\n 'user': user,\n }\n\n return render_to_response('register.html',\n template_values, request)","def public_key():\n if not Authorizer.__public_key:\n Authorizer.__public_key = download_public_key()\n return Authorizer.__public_key","def send_activation_key_via_email(user, signup_key):\n subject = '[%s]Verify your email.' % (settings.ORGANIZATION_NAME)\n from_email = settings.DEFAULT_FROM_EMAIL\n to = [user.email, ]\n activation_link = '%s%s' % (settings.HOSTNAME_URL,\n reverse('activation_verify',\n args=(signup_key,)))\n\n html_content = \"\"\"\n bytes:\\n\\n # builds content\\n content = InvitationContent(\\n **invitation_data.dict(),\\n created=datetime.utcnow(),\\n )\\n\\n content_jsonstr: str = _ContentWithShortNames.serialize(content)\\n assert \\\"\\\\n\\\" not in content_jsonstr # nosec\\n\\n # encrypts contents\\n return _fernet_encrypt_as_urlsafe_code(\\n data=content_jsonstr.encode(),\\n secret_key=secret_key,\\n )\",\n \"def get(self, request, token):\\n try:\\n encoded = token\\n key = \\\"secret\\\"\\n usr_details = jwt.decode(encoded, key=key, algorithms=\\\"HS256\\\")\\n usr_name = usr_details.get(\\\"username\\\")\\n check = CustomUser.objects.get(username=usr_name)\\n if check:\\n check.verified = True\\n check.save()\\n return Response({\\\"message\\\": \\\"VERIFIED\\\"}, status=200)\\n return Response({\\\"message\\\": \\\"SOME THING WENT WRONG\\\"}, status=400)\\n except Exception as e:\\n user_log.exception(\\\"generic exception occurred\\\")\\n return Response({\\\"message\\\": \\\"SOMETHING WENT WRONG\\\",\\n \\\"detail\\\": e.args}, status=400)\",\n \"def set_confirmation_code(cls, user_obj: User) -> str:\\n confirmation_code = cls.generate_new_code()\\n if user_obj.phone == '+996553000117' or user_obj.phone == '+996999111222':\\n confirmation_code = '123456'\\n user_obj.confirmation_code = confirmation_code\\n user_obj.confirmation_date = timezone.now()\\n user_obj.save(\\n update_fields=['confirmation_code', 'confirmation_date'])\\n return confirmation_code\",\n \"def send_verification_email(self):\\n url = (\\\"https://api.imgur.com/3/account/{0}\\\"\\n \\\"/verifyemail\\\".format(self.name))\\n self._imgur._send_request(url, needs_auth=True, method='POST')\",\n \"def register(request, key):\\n profile = cpm.UserProfile.objects.filter(\\n activation_key=key)\\n\\n if not profile.exists() or profile[0].user.is_active:\\n hero_title = 'Hmm... that registration key is invalid.'\\n return render_err_msg(request, hero_title)\\n\\n user = profile[0].user\\n\\n if request.POST:\\n reg_form = RegForm(request.POST)\\n if reg_form.is_valid():\\n user.is_active = True\\n user.first_name = reg_form.cleaned_data['first_name']\\n user.last_name = reg_form.cleaned_data['last_name']\\n user.set_password(reg_form.cleaned_data['password'])\\n\\n pic_url = put_profile_pic(\\n reg_form.cleaned_data['pic_url'], user.profile)\\n if pic_url:\\n user.profile.pic_url = pic_url\\n\\n user.profile.class_year = reg_form.cleaned_data['class_year']\\n\\n alt_emails = request.POST.getlist('alt_email')\\n for alt_email in alt_emails:\\n if alt_email:\\n user.profile.add_email(alt_email)\\n\\n user.save()\\n user.profile.save()\\n\\n user = auth.authenticate(username=user.username,\\n password=reg_form.cleaned_data['password'])\\n if user is not None:\\n if user.is_active:\\n auth.login(request, user)\\n # Redirect to a success page.\\n return redirect('/')\\n\\n else:\\n reg_form = RegForm()\\n\\n template_values = {\\n 'page_title': 'register',\\n 'form': reg_form,\\n 'user': user,\\n }\\n\\n return render_to_response('register.html',\\n template_values, request)\",\n \"def public_key():\\n if not Authorizer.__public_key:\\n Authorizer.__public_key = download_public_key()\\n return Authorizer.__public_key\",\n \"def send_activation_key_via_email(user, signup_key):\\n subject = '[%s]Verify your email.' % (settings.ORGANIZATION_NAME)\\n from_email = settings.DEFAULT_FROM_EMAIL\\n to = [user.email, ]\\n activation_link = '%s%s' % (settings.HOSTNAME_URL,\\n reverse('activation_verify',\\n args=(signup_key,)))\\n\\n html_content = \\\"\\\"\\\"\\n . '\n 'Wrong credentials or locked account')\n return current_user","def authenticate(cls, handler):\n raise NotImplementedError(\"Missing implementation for authenticate\")","def log_in(codecool):\n\n login = school_view.get_login()\n password = school_view.get_password()\n\n password = utilities.hash_password(password)\n\n users = codecool.managers_list + codecool.administrators_list + codecool.mentors_list + codecool.students_list\n for user in users:\n if user.login == login and user.password == password:\n return user","async def async_step_auth(self, user_input=None):\n if user_input.get(const.CODE):\n self.data = user_input\n return self.async_external_step_done(next_step_id=\"finish\")\n\n profile = user_input.get(const.PROFILE)\n\n auth_client = self.get_auth_client(profile)\n\n url = auth_client.get_authorize_url()\n\n return self.async_external_step(step_id=\"auth\", url=url)","def authenticate():\n try:\n return redirect(authorize_uri + '?client_id=' + client_id + \\\n '&response_type=code&redirect_uri=' + redirect_uri + '&scope=user-library-read user-modify-playback-state')\n except Exception as e:\n return ('authenticate() threw ' +str(e))","def authenticate_userpass():\n return _userpwd_auth(current_app.config.get('VAULT_AUTH_PATH', 'userpass'))","def auth():\n\tcode = request.query.code\n\tauth = 'https://foursquare.com/oauth2/access_token'\n\tparams = dict(\n\t\tclient_id=CLIENT_ID,\n\t\tclient_secret=CLIENT_SECRET,\n\t\tgrant_type='authorization_code',\n\t\tredirect_uri=REDIRECT_URI,\n\t\tcode=code\n\t)\n\tauth_says = fetch('%s?%s'%(auth, urlencode(params)))\n\tauth_response = json.loads(auth_says.content)\n\tif 'access_token' in auth_response:\n\t\toauth_token=auth_response['access_token']\n\t\tresponse.set_cookie('user', oauth_token, secret=CLIENT_SECRET)\n\t\tlogging.info('new oauth_token:%s'%oauth_token)\n\t\tredirect('/')\n\telse:\n\t\tlogging.error(auth_response)\n\t\tabort()","def authenticate_user(data):\n \n try:\n auth_token = data[\"auth_token\"]\n user_token = Token.objects.get(username=data[\"username\"])\n if user_token.token == auth_token:\n return True\n except:\n return False\n return False","def authenticate():\n return \"Please log in... Log in page\"","def func_auth(self, data):\n check = bytes(data).decode().encode('ascii', 'ignore').decode().lower().rstrip()\n if check == 'auth login':\n auth_id = library.q_id_generate(size=12)\n message = '334 ' + auth_id\n self.func_sender(message)\n self.request.recv(self.std_recv_size)\n auth_id_two = library.q_id_generate(size=12)\n message_two = '334 ' + auth_id_two\n self.func_sender(message_two)\n self.request.recv(self.std_recv_size)\n message_three = self.conf_th_ic.get_item(q_key='std-messages').get(check)\n self.func_sender(message_three)\n return True","def authenticate_user( db, request ):\n\n username = request.values.get( 'username' )\n password = request.values.get( 'password' )\n\n if ( not username or not password ):\n return False\n\n user = db.execute(\n text( 'select users_id, name, email from users where name = :name and password_hash = md5( :salt || :password ) and is_active' ),\n name = username, password = password, salt = app.config[ 'SECRET_KEY' ]\n ).fetchone()\n\n if ( user ):\n return user\n else:\n return False","def authenticate_user(self, *, provider: str, user_name: str, password: str) -> UserId:","def authenticate(self, registered_provider=None, template_path=None):\n if self.flow_type == \"web\" and registered_provider is not None:\n response = self.authenticate_from_server(registered_provider)\n if response is None or response.get(\"access_token\") is None:\n return (\n f\"Access Denied: Reason={request.args['error']} \"\n f\"error={request.args['error_description']} \"\n f\"response={response}\"\n )\n session[\"token\"] = response\n return redirect(url_for(\"home\", provider=self.name))\n elif self.flow_type == \"implicit\" and template_path is not None:\n return self.authenticate_implicit(template_path)\n elif self.flow_type == \"client\":\n return redirect(url_for(\"home\", provider=self.name))\n else:\n raise Exception(\n \"Invalid flow type, registered_provider is None, \"\n \"or template_path not specified\"\n )","def check_user_and_login(self) -> Response:\n pass","def verify_auth_code(self, code):\n raise NotImplementedError(\n \"\"\"\n verify_scope must be implemented by a child class\n \"\"\"\n )","def authenticate_user(self):\n raise NotImplementedError(\n \"\"\"\n authenticate_user must be implemented by a child class\n \"\"\"\n )","def _authenticate(self):\n auth = self.settings.get(\"auth\")\n if auth:\n if auth == Auth.PLAIN:\n self._authenticate_plain()\n elif auth == Auth.SHA256_MEMORY:\n self._authenticate_sha256_memory()\n elif auth == Auth.MYSQL41:\n self._authenticate_mysql41()\n elif self.stream.is_secure():\n # Use PLAIN if no auth provided and connection is secure\n self._authenticate_plain()\n else:\n # Use MYSQL41 if connection is not secure\n try:\n self._authenticate_mysql41()\n except InterfaceError:\n pass\n else:\n return\n # Try SHA256_MEMORY if MYSQL41 fails\n try:\n self._authenticate_sha256_memory()\n except InterfaceError as err:\n raise InterfaceError(\n \"Authentication failed using MYSQL41 and \"\n \"SHA256_MEMORY, check username and \"\n f\"password or try a secure connection err:{err}\"\n ) from err","def authn_and_authz():\n authentication()\n authorization()","def authenticate(cls, handler):\n return None","def _oauth_callback(self):\n tokens = self.oauth.get_raw_access_token(data={\n 'code': flask.request.args.get('code', ''),\n 'redirect_uri': self.oauth_redirect_uri,\n 'grant_type': 'authorization_code'\n }).json()\n user = User(tokens=tokens, app=self)\n\n # Add subscriptions\n self.subscriptions.init_user(user)\n\n # Call endpoint for user login\n return self.subscriptions.call_endpoint(\"login\", user) or \"\"","def login():\n if app.testing:\n callback_url = url_for('user.authorize', _external=True)\n else:\n callback_url = 'https://codegolf.uqcs.org.au/user/authorize'\n return git_auth.authorize(callback=callback_url)","def authenticate():\n if request.method == 'POST':\n username = request.form['username']\n password = request.form['password']\n template = request.form['backto']\n car_id = request.form['car-id']\n if check_credentials(username, password):\n return after_auth_redirect(template, car_id, username)\n else:\n return render_template('login.html', error=\"Bad credentials!\")","def login(self):\r\n user_account = db.find_one({\"cpr_number\": request.form.get(\"CPR\")})\r\n if user_account is not None:\r\n if self.verify_password(user_account[\"password\"], request.form.get(\"password\")):\r\n return self.start_session(user_account)\r\n return jsonify({\"error\": \"Invalid login credentials\"}), 401","def _authenticate(self):\n\t\tfrom getpass import getpass\n\t\tpassword = getpass()\n\t\tself.msg('nickserv', 'identify %s' % password)","def auth(self):\n ok = False\n if self.private_token:\n ok = self.token_auth()\n if not ok:\n self.credentials_auth()","def authenticateBackend(self, tried_username=None, tried_password=None):\n\n # we keep these here in case frontend has authenticated and backend hasn't established the secure channel yet;\n # in that case, tried credentials are stored to be used whenever usearauth with backend can be performed\n if tried_username and tried_password:\n self.frontendTriedUsername = tried_username\n self.frontendTriedPassword = tried_password\n\n # do nothing if frontend is not authenticated, or backend has not established a secure channel\n if not self.factory.server.frontendAuthenticated or not self.canAuth:\n return\n\n # we authenticate with the backend using the credentials provided\n # TODO create the account in the backend before (contact the pool of VMs for example)\n # so these credentials from the config may not be needed after all\n username = CowrieConfig().get('proxy', 'backend_user').encode()\n password = CowrieConfig().get('proxy', 'backend_pass').encode()\n\n log.msg('Will auth with backend: {0}/{1}'.format(username, password))\n self.sendPacket(5, bin_string_to_hex(b'ssh-userauth'))\n payload = bin_string_to_hex(username) + \\\n string_to_hex('ssh-connection') + \\\n string_to_hex('password') + \\\n b'\\x00' + \\\n bin_string_to_hex(password)\n\n self.sendPacket(50, payload)\n self.factory.server.backendConnected = True\n\n # send packets from the frontend that were waiting to go to the backend\n for packet in self.factory.server.delayedPackets:\n self.factory.server.sshParse.parse_packet('[SERVER]', packet[0], packet[1])\n self.factory.server.delayedPackets = []\n\n # backend auth is done, attackers will now be connected to the backend\n self.authDone = True","def authenticate():\n # Get JSON data from request\n json = request.get_json()\n\n if 'email' not in json or 'password' not in json:\n raise CustomError(400, message='Must include an email and a password')\n\n # Check email\n user = User.query.filter_by(email=json['email']).first()\n if user is None:\n raise CustomError(401, message='Email or password were not found.')\n\n # Check password\n if not check_password_hash(user.password, json['password']):\n raise CustomError(401, message='Email or password were not found.')\n\n return jsonify({'success': True, 'user': user.to_dict()}), 201","def authenticate():\n return abort(401)","def authenticate(self):\n self.login(closet.app.config['USERNAME'],\n closet.app.config['PASSWORD'])","def authenticate(self, rfid):\n print(\"Auth id: [{}]\".format(rfid))\n\n values = {'id' : rfid}\n data = urllib.parse.urlencode(values)\n data = data.encode('utf-8')\n\n t1 = perf_counter()\n\n req = urllib.request.Request(self.auth_url, data)\n try:\n resp = urllib.request.urlopen(req, timeout=self.request_timeout)\n except URLError as err:\n print(\"URLError: auth_url:[{}]\".format(self.auth_url))\n print(\"URLError: {}\".format(err))\n print(\"Falling back to local cache\")\n cached = self.auth_from_cache(rfid)\n return cached\n except timeout as err:\n cached = self.auth_from_cache(rfid)\n return cached\n\n text = resp.read()\n\n t2 = perf_counter()\n print(\"Auth got [{}] in {} seconds\".format(text, t2-t1))\n\n if text == b'Granted':\n return True","def _auth(self):\n\n def check_response(text):\n \"\"\"Check to see if authentication has failed.\n \"\"\"\n\n if 'incorrect' in response.text:\n msg = ('Username <%(username)s> and password <%(password)s> ' +\n 'do not match.') % {'username': self.username,\n 'password': self.password}\n\n raise exceptions.AuthError(msg)\n\n data = {'action': 'login',\n 'user': self.username,\n 'pwd': self.password}\n\n # step 1: submit login form\n response = self._do('POST', self.URLS['auth_step_one'],\n data=data, allow_redirects=True)\n check_response(response.text)\n\n # step 2: fake second form's submission\n # todo: sprinkle on some error checking,\n # even though this is only a redirect\n response = self._do('POST', self.URLS['auth_step_two'],\n data=data, allow_redirects=True)\n check_response(response.text)\n\n return True","def __authenticate(self, data):\n if 'token' not in data:\n raise TokenError(\"Invalid Token\")\n if data['token'] != app.config['SLACK_TOKEN']:\n raise TokenError(\"Invalid Token\")","def activate_user(username, code, new_pass):\r\n\r\n qry = Activation.query.\\\r\n filter(Activation.code == code).\\\r\n filter(User.username == username)\r\n\r\n res = qry.first()\r\n\r\n if UserMgr.acceptable_password(new_pass) and res is not None:\r\n user = res.user\r\n user.activated = True\r\n user.password = new_pass\r\n res.activate()\r\n\r\n LOG.debug(dict(user))\r\n\r\n return True\r\n else:\r\n return None","def auth_code_handler(self, request, pk=None):\n try:\n # Get xero auth access information form xero connection\n stored_values = OAUTH_PERSISTENT_SERVER_STORAGE\n\n\n if len(stored_values) == 0:\n return Utils.dispatch_failure(request, 'NO_TOKEN_AUTHENTICATION')\n\n secret_keys = Utils.get_access_keys(pk)\n if AccountingConfiguration.PRIVATE == secret_keys.type:\n exists = AccountingOauth2.objects.filter(company=pk).first()\n if not exists:\n auth = AccountingOauth2(accessToken=stored_values['consumer_key'],\n accessSecretKey=stored_values['rsa_key'],\n company_id=pk)\n auth.save()\n else:\n exists.accessToken = stored_values['consumer_key']\n exists.accessSecretKey = stored_values['rsa_key']\n exists.save()\n else:\n auth_verifier_uri = settings.XERO_AUTH_VERIFIER_URI\n oauth_verifier = request.GET.get('oauth_verifier')\n credentials = Utils.get_xero_public_credentials(stored_values)\n\n if credentials.expired():\n return Utils.dispatch_failure(request, 'NO_TOKEN_AUTHENTICATION')\n\n # Verify the auth verifier for establish the connection\n\n credentials.verify(oauth_verifier)\n # Resave our verified credentials\n for key, value in credentials.state.items():\n OAUTH_PERSISTENT_SERVER_STORAGE.update({key: value})\n\n stored_values = OAUTH_PERSISTENT_SERVER_STORAGE\n exists = AccountingOauth2.objects.filter(company=pk).first()\n\n if exists:\n exists.accessToken = stored_values['oauth_token']\n exists.realmId = oauth_verifier\n exists.accessSecretKey = stored_values['oauth_token_secret']\n exists.tokenAcitvatedOn = stored_values['oauth_expires_at']\n exists.tokenExpiryON = stored_values['oauth_authorization_expires_at']\n exists.save()\n else:\n auth = AccountingOauth2(accessToken=stored_values['oauth_token'],\n refreshToken='',\n realmId=oauth_verifier,\n accessSecretKey=stored_values['oauth_token_secret'],\n tokenAcitvatedOn=stored_values['oauth_expires_at'],\n tokenExpiryON=stored_values['oauth_authorization_expires_at'],\n company_id=pk)\n auth.save()\n # auth_redirect_url = os.environ.get ('QBO_AUTH_REDIRECT_URL',\n # 'http://localhost:4200/coa-match/quickbooks')\n\n # auth_redirect_url = os.environ.get ('QBO_AUTH_REDIRECT_URL','http://ec2-52-207-28-114.compute-1.amazonaws.com/ix/coa-match/quickbooks')\n\n # return redirect(auth_redirect_url)\n\n except Exception as e:\n auth_cancel_url = settings.QBO_AUTH_CANCEL_URL\n Utils.send_company_misconfig(pk, e)\n return redirect(auth_cancel_url + '/error')\n #return Utils.dispatch_success(request, 'TOKEN_ALREADY_VALIDATED')\n\n auth_redirect_url = settings.XERO_AUTH_REDIRECT_URL\n return redirect(auth_redirect_url)\n # return Utils.dispatch_success(request, stored_values)","def authenticate(self):\n rv = Form.validate(self)\n if not rv:\n return False\n\n user = self.username.data\n\n cur = get_cursor()\n if email_exists(cur, user):\n user = get_username(cur, user)\n\n if username_exists(cur, user):\n pw_hash = get_pw_hash(cur, user)\n\n if check_password(self.password.data, pw_hash):\n self.username.data = user\n return True\n\n return False","def authenticate(self, *args, **kwargs):\n # Validate backend and arguments. Require that the Social Auth\n # response be passed in as a keyword argument, to make sure we\n # don't match the username/password calling conventions of\n # authenticate.\n if not (self.name and kwargs.get(self.name) and 'response' in kwargs):\n return None\n\n response = kwargs.get('response')\n pipeline = PIPELINE\n kwargs = kwargs.copy()\n kwargs['backend'] = self\n\n if 'pipeline_index' in kwargs:\n pipeline = pipeline[kwargs['pipeline_index']:]\n else:\n kwargs['details'] = self.get_user_details(response)\n kwargs['uid'] = self.get_user_id(kwargs['request'])\n kwargs['is_new'] = False\n \n out = self.pipeline(pipeline, *args, **kwargs)\n if not isinstance(out, dict):\n return out\n\n social_user = out.get('social_user')\n if social_user:\n # define user.social_user attribute to track current social\n # account\n user = social_user.user\n user.social_user = social_user\n user.is_new = out.get('is_new')\n return user","def login_menu(self):\n print(\"\\nPlease enter your email and password\")\n email = self.validate_email()\n password = self.validate_password()\n self.authenticate_user(email, password)","def login():\n auth_state = str(uuid.uuid4())\n SESSION.auth_state = auth_state\n\n # For this sample, the user selects an account to authenticate. Change\n # this value to 'none' for \"silent SSO\" behavior, and if the user is\n # already authenticated they won't need to re-authenticate.\n prompt_behavior = 'select_account'\n\n params = urllib.parse.urlencode({'response_type': 'code',\n 'client_id': config.CLIENT_ID,\n 'redirect_uri': config.REDIRECT_URI,\n 'state': auth_state,\n 'resource': config.RESOURCE,\n 'prompt': prompt_behavior})\n\n return bottle.redirect(config.AUTHORITY_URL + '/oauth2/authorize?' + params)","def _delegate_authentication(username, password):\n payload = json.dumps({\n 'type': 'normal',\n 'username': username,\n 'password': password\n })\n headers = {'Content-Type': 'application/json'}\n login_response = requests.post(API_URL + \"/auth\", data=payload, headers=headers)\n if login_response.status_code != 200:\n return False\n\n try:\n decoded_response = login_response.json()\n except ValueError as error:\n logger.error(f'Cannot decode Taiga auth response: {error}. Response was: {login_response}')\n return False\n return decoded_response","def authenticate(self):\n # self.qobject.remove_authenticate_signal.emit()\n # self.qobject.authenticate_signal.emit( )\n #if self.app.sync_thread.status != const.STATUS_SYNC:\n # self.app.sync_thread.force_sync()\n change_auth_token( )\n self.data_changed()","def authcheck():\n user = get_user()\n return jsonify({'current_identity': user.username})","def authenticator():","def authentication_view(request):\n \n data = request.data\n username = data.get('username', '')\n password = data.get('password', '')\n user = authenticate(request, username=username, password=password) \n\n if user is not None:\n login(request, user)\n return JsonResponse({\"status\": \"success\"})\n else:\n return JsonResponse({\"status\": \"fail\"})","def login_user():\n pass","def get(self):\n\n\t\trequest = user_auth_parser.parse_args(strict=True)\n\n\t\tresult = Authenticator.authenticate(\n\t\t\trequest[\"username\"],\n\t\t\trequest[\"password\"]\n\t\t)\n\n\t\treturn result","def skyserv_authenticator(self):\n \n header = {\n 'Content-Type': accept, \n 'X-Auth-Token': self.casjobtoken,\n 'Accept': accept\n }\n # this format is disgusting but required....\n authdata = {\n 'auth' :{\n 'identity': {\n 'password': {\n 'user': {\n 'name': username,\n 'password': password\n }\n }\n }\n }\n }\n payload = json.dumps(authdata).encode(encoding='utf-8')\n try:\n post = requests.post(self.loginurl, data=payload, headers=header)\n\n if post.status_code == 200:\n response = json.loads(post.text)\n token = response[self.tokenkey]\n return token\n else:\n print('Username and/or password are invalid.')\n post.raise_for_status()\n except Exception as e:\n raise(str(e))","def authenticate(self, func):\n self._authentication_callback = func\n return func","def authenticate():\n\n return Response(\n 'Could not verify your access level for that URL.\\n'\n 'You have to login with proper credentials', 401,\n get_auth_headers())","def authenticate(self, username, password):\n auth = (username, password)\n res = requests.get(\n self.normalize_admin_url(\"authenticate\"),\n headers={\"user-agent\": self.u_agent},\n auth=auth,\n verify=False,\n )\n if res.status_code == 200:\n # authentication ok, keep authentication info for future use\n self.auth = auth\n return Response(0, \"Successfully logged in\")\n elif res.status_code == 401:\n try:\n val = res.json()\n except ValueError:\n val = \"Login credentials not accepted\"\n return Response(401, val)\n else:\n return Response(res.status_code, res.content)","def check_auth(username, password):\n # return username == app.config['USER'] and password == app.config['PASS']\n\n return username == app.config['USER'] and password == app.config['PASS']","def authenticate_credentials(self, payload):\n username = payload.get('username')\n email = payload.get('email')\n if not username and not email:\n msg = _('Invalid payload.')\n raise exceptions.AuthenticationFailed(msg)\n try:\n # Username query is case insensitive\n user_queryset = User.objects.filter(\n Q(username__iexact=username)|\n Q(email__iexact=email)\n ).distinct()\n if user_queryset.exists() and user_queryset.count() == 1:\n user = user_queryset.first()\n return user\n except User.DoesNotExist:\n return None","def authenticate(self, cred): \n auth_helper = AuthHelper.AuthHelper(self.context)\n return auth_helper.auth(cred)","def check_auth_interactive(self, username, submethods):\n return AUTH_FAILED","def authentication(app, user_model):\n login_manager.login_message = \"Please login to access this page.\"\n login_manager.login_view = 'auth.login'\n login_manager.session_protection = 'strong'\n login_manager.login_message_category = 'danger'\n\n @login_manager.user_loader\n def load_user(user_id):\n return user_model.query.get(int(user_id))","def check_auth(*args, **kwargs):\n r = cherrypy.request\n s = cherrypy.session\n\n username = s.get(USERNAME_SESSION_KEY, None)\n course = s.get(CUR_CRS_SESSION_KEY, None)\n # require a course to be selected\n if username and not course and r.path_info != '/auth/course':\n raise cherrypy.HTTPRedirect(\"/auth/course\")\n\n conditions = r.config.get('auth.restrict.require', None)\n if conditions is not None:\n if username:\n r.login = username\n for condition in conditions:\n # A condition is just a callable that returns true or false\n if not condition():\n raise cherrypy.HTTPRedirect(\"/auth/not-authorized\")\n else:\n s[FROMPATH_SESSION_KEY] = r.path_info\n raise cherrypy.HTTPRedirect(\"/auth/login\")","def authenticate(self, username: str, password: str) -> Optional[str]:","def authenticate(self, username: str, password: str) -> Optional[str]:","def authorize():\n resp = git_auth.authorized_response()\n user_info = git_auth.get('user', token=(resp[\"access_token\"],)).data\n u = db_session.query(User).filter(User.email == user_info['email']).first()\n if not u:\n u = User(user_info['login'], user_info['email'])\n db_session.add(u)\n db_session.commit()\n login_user(u, remember=True)\n return redirect(url_for('index'))","def authenticate(self):\n #it's weird i have to do this here, but the code makes this not simple\n auth_json={'email':self.user, 'password':self.password}\n #send a post with no auth. prevents an infinite loop\n auth_response = self.post('/auth', data = json.dumps(auth_json), auth =\n None)\n\n _token = auth_response.json['token']\n\n self._token = _token\n self._wrapped.auth = SpringAuth(_token)","def authenticate(self):\n\n def decorate(func, *args, **kws):\n \"\"\"\n A function returned as a object in load time,\n which returns inner function do_decorate().\n \"\"\"\n def do_authenticate():\n \"\"\"\n A function to perform authentication\n every time decorated function is called.\n \"\"\"\n #try:\n if 1:\n if 'referer' not in self.session:\n path = urlsplit(self.request.url)[2]\n self.session['referer'] = path\n self.session.put()\n #except:\n # pass\n aobj = self.config.auth_obj()\n self.get_controller()\n auth_res = aobj.auth(self.controller, *args, **kws)\n if auth_res:\n return func(*args, **kws)\n aobj.auth_redirect(self.controller, *args, **kws)\n # clear controller for development environment.\n\n return do_authenticate\n\n return decorate","def user_login():\n user = query_db('''select * from user where username = ?''', [request.authorization.username], one=True)\n if user is None:\n error = 'Invalid username'\n elif not check_password_hash(user['pw_hash'],request.authorization.password):\n error = 'Invalid password'\n else:\n flash('You were logged in')\n return jsonify({'user_id':user['user_id']}),200","def login(self, user, password):\n \n def encode_base64(s, eol=None):\n return \"\".join(base64.encodestring(s).split(\"\\n\"))\n \n def encode_cram_md5(challenge, user, password):\n challenge = base64.decodestring(challenge)\n response = user + \" \" + hmac.HMAC(password, challenge).hexdigest()\n return base64_encode(response, eol=\"\")\n\n def encode_plain(user, password):\n return base64_encode(\"%s\\0%s\\0%s\" % (user, user, password), eol=\"\")\n\n\n AUTH_PLAIN = \"PLAIN\"\n AUTH_CRAM_MD5 = \"CRAM-MD5\"\n AUTH_LOGIN = \"LOGIN\"\n\n if self.helo_resp is None and self.ehlo_resp is None:\n if not (200 <= self.ehlo()[0] <= 299):\n (code, resp) = self.helo()\n if not (200 <= code <= 299):\n raise SMTPHeloError(code, resp)\n\n if not self.has_extn(\"auth\"):\n raise SMTPException(\"SMTP AUTH extension not supported by server.\")\n\n # Authentication methods the server supports:\n authlist = self.esmtp_features[\"auth\"]\n if authlist.startswith('='):\n authlist = authlist[1:]\n authlist = authlist.split()\n # List of authentication methods we support: from preferred to\n # less preferred methods. Except for the purpose of testing the weaker\n # ones, we prefer stronger methods like CRAM-MD5:\n \n preferred_auths = [AUTH_CRAM_MD5, AUTH_PLAIN, AUTH_LOGIN]\n if hmac is None:\n preferred_auths.remove(AUTH_CRAM_MD5)\n \n # Determine the authentication method we'll use\n authmethod = None\n for method in preferred_auths:\n if method in authlist:\n authmethod = method\n break\n\n if authmethod == AUTH_CRAM_MD5:\n (code, resp) = self.docmd(\"AUTH\", AUTH_CRAM_MD5)\n if code == 503:\n # 503 == 'Error: already authenticated'\n return (code, resp)\n (code, resp) = self.docmd(encode_cram_md5(resp, user, password))\n elif authmethod == AUTH_PLAIN:\n (code, resp) = self.docmd(\"AUTH\",\n AUTH_PLAIN + \" \" + encode_plain(user, password))\n elif authmethod == AUTH_LOGIN:\n (code, resp) = self.docmd(\"AUTH\",\n \"%s %s\" % (AUTH_LOGIN, encode_base64(user, eol=\"\")))\n if code != 334:\n raise SMTPException(\"Authorization failed.\")\n (code, resp) = self.docmd(encode_base64(password, eol=\"\"))\n elif authmethod == None:\n raise SMTPException(\"No suitable authentication method found.\")\n if code not in [235, 503]:\n # 235 == 'Authentication successful'\n # 503 == 'Error: already authenticated'\n raise SMTPException(\"Authorization failed.\")\n return (code, resp)","def login_entrypoint(request, authentication_form=AuthenticationForm):\n if request.user.is_authenticated:\n return redirect_to_user_settings()\n\n if request.method == 'GET':\n return login_view(request)\n\n # authenticate the user\n form = authentication_form(request, data=request.POST)\n\n # store the user's id in the session so you can perform Instant2FA check\n if form.is_valid():\n user = form.get_user()\n request.session['distinct_id'] = get_user_distinct_id(user)\n return HttpResponseRedirect('/login/two-factor/')\n else:\n logging.debug(\"User did not provide valid authentication credentials.\")\n return login_view(request)","def login_require(request):\n\n if request.method == \"GET\":\n data = request.GET\n else:\n data = request.POST\n user = authenticate(username=data[\"username\"], password=data[\"password\"])\n if user and user.is_active:\n ret = Response(SUCCESS, error_code[SUCCESS])\n else: \n ret = Response(AUTHENTICATION_FAIL, error_code[AUTHENTICATION_FAIL])\n return HttpResponse(ret.serialize(f))\n\n # Generate a token for authentication\n token = token_generator(30)\n try:\n user_token = Token.objects.get(username=data[\"username\"])\n user_token.token = token\n user_token.start_time = datetime.now()\n except: \n user_token = Token(token=token, username=data[\"username\"])\n user_token.save()\n ret.set_ret(\"auth_token\", token) \n user = User.objects.get(username=data[\"username\"])\n ret.set_ret(\"data\", UserSerializer(user.appuser).serialize())\n return HttpResponse(ret.serialize(f))","def activateWebAppUser( self, username, activation_code ):\n try:\n con = self.getMetadataDatabaseConnection()\n user_data = con.cursor()\n\n con.cursor().callproc('verify_user_activation_code', [username, activation_code, user_data])\n row = user_data.fetchone()\n if row:\n con.cursor().callproc('activate_user_account', [username])\n return True\n else:\n return False\n except Exception, e:\n print 'Exception caught: %s.\\nThe error is: %s' % (type(e), e)\n return False","def authenticate_user():\n if request.headers['content-type'] == 'application/json':\n print(request)\n data = request.get_json()\n if data:\n username = data['username']\n password = data['password']\n else:\n return Response(status=400) # no JSON to parse\n\n if username is None or password is None:\n return Response(status=400) # missing arguments\n\n if not verify_password(username, password):\n return Response(status=403) # User not authenticated\n\n return jsonify({'username': username, 'success': True}), 201\n else:\n print(\"invalid request type, no json\")\n return Response(status=400) # invalid request type","def login():\n domain = parser[\"learningmachine\"][\"domain\"]\n secrets_file = \"{}/{}\".format(dir_path, \"client_secret.json\")\n scope = \"https://www.googleapis.com/auth/userinfo.email\"\n redirect_uri = \"http://{}/login\".format(domain)\n login_handler = LoginHandler(secrets_file, scope, redirect_uri)\n\n if \"code\" in request.args:\n login_handler.setup_user_info(request.args[\"code\"])\n session[\"email\"] = login_handler.email\n session[\"display_name\"] = login_handler.display_name\n\n if not fm.user_exists(login_handler.email):\n msg = \"Adding user: {} with ID of {} to the database.\"\\\n .format(login_handler.email, login_handler.display_name)\n fm.add_user(login_handler.email, login_handler.display_name)\n\n msg = \"Sending user: {} to main page\".format(login_handler.email)\n app.logger.info(msg)\n return redirect(\"/static/main.html\")\n\n else:\n msg = \"No login code yet. Letting Google handle the login process at: {}\"\\\n .format(login_handler.auth_url)\n app.logger.info(msg)\n return redirect(login_handler.auth_url)"],"string":"[\n \"def authenticate(self, request, **kwargs):\\n\\n self.request = request\\n if not self.request:\\n return None\\n\\n state = self.request.GET.get('state')\\n code = self.request.GET.get('code')\\n nonce = kwargs.pop('nonce', None)\\n\\n if not code or not state:\\n return None\\n\\n reverse_url = import_from_settings('OIDC_AUTHENTICATION_CALLBACK_URL',\\n 'oidc_authentication_callback')\\n\\n token_payload = {\\n 'client_id': self.OIDC_RP_CLIENT_ID,\\n 'client_secret': self.OIDC_RP_CLIENT_SECRET,\\n 'grant_type': 'authorization_code',\\n 'code': code,\\n 'redirect_uri': absolutify(\\n self.request,\\n reverse(reverse_url)\\n ),\\n }\\n\\n # Get the token\\n token_info = self.get_token(token_payload)\\n id_token = token_info.get('id_token')\\n access_token = token_info.get('access_token')\\n refresh_token = token_info.get('refresh_token')\\n\\n # Validate the token\\n payload = self.verify_token(id_token, nonce=nonce)\\n\\n # Store users tokens\\n usertokens, created = UserTokens.objects.update_or_create(\\n user=payload['sub'],\\n defaults={'access_token': access_token,\\n 'refresh_token': refresh_token}\\n )\\n\\n if payload:\\n self.store_tokens(access_token, id_token)\\n try:\\n return self.get_or_create_user(access_token, id_token, payload)\\n except SuspiciousOperation as exc:\\n LOGGER.warning('failed to get or create user: %s', exc)\\n return None\\n\\n return None\",\n \"def authentication_callback(request):\\n code = request.GET.get('code')\\n user = authenticate(token=code, request=request)\\n if user:\\n auth_login(request, user)\\n set_session_from_user(request, user)\\n region = request.user.endpoint\\n region_name = dict(Login.get_region_choices()).get(region)\\n request.session['region_endpoint'] = region\\n request.session['region_name'] = region_name\\n url = getattr(settings, \\\"LOGIN_REDIRECT_URL\\\", \\\"/\\\")\\n resp = HttpResponseRedirect(url)\\n\\n return resp\",\n \"def authenticate(user, request):\",\n \"def authentication_hook(self):\\n pass\",\n \"def authenticate_user(self, email, password):\\n authentication = self.client.validate(email, password).decode(\\\"utf-8\\\")\\n if authentication == \\\"valid\\\":\\n self.current_email = email\\n self.unlock_time = round(datetime.now().timestamp())\\n if self.is_user and not self.is_return:\\n self.display_successful_unlock_cust()\\n elif self.is_user and self.is_return:\\n self.return_car()\\n else:\\n self.display_successful_unlock_eng()\\n elif authentication == \\\"invalid\\\":\\n print(self.INVALID_USER)\\n time.sleep(3)\\n self.display_main()\",\n \"def validate_code(request):\\n user_id = api.keystone.get_user_id(request)\\n print \\\"USER CHECK\\\"\\n print user_id\\n user = api.keystone.user_get(request, user_id)\\n user_auth_code = request.GET.get('auth_code', None)\\n secret = request.GET.get('secret', None)\\n\\n #Generate a code form our side using algorithm and use it to validate\\n generated_code = api.keystone.generate_totp(secret)\\n\\n print secret\\n print user_auth_code\\n print generated_code\\n print 'entering code comparison'\\n \\n data = {}\\n extra = {}\\n\\n #Code comparison\\n if user_auth_code == generated_code:\\n data['totp_authenticated'] = True\\n extra['two_factor_enabled'] = True\\n\\textra['secret_key'] = secret\\n api.keystone.enable_2fa(request, user, **extra)\\n else:\\n \\tprint 'falseeeeee'\\n data['totp_authenticated'] = False\\n return JsonResponse(data)\",\n \"def authenticate_user():\\n\\n error = request.args.get(\\\"error\\\")\\n if error:\\n logger.warning(\\\"Google sent us an error via OAuth2: %s\\\", error)\\n\\n return redirect(url_for(\\\"login\\\"))\\n\\n # Get OAuth2 authentication code\\n code = request.args.get(\\\"code\\\")\\n\\n # Exchange code for fresh credentials\\n credentials = flow.step2_exchange(code)\\n\\n # Extract email and email verification\\n id_token = credentials.id_token\\n email = id_token[\\\"email\\\"]\\n verified_email = id_token[\\\"email_verified\\\"]\\n\\n if verified_email is True:\\n # Find the user with the given email\\n try:\\n user = FlaskUser(User.objects.get(email = email))\\n except User.DoesNotExist:\\n user = None\\n\\n if not user:\\n flash(\\\"A Galah account does not exist for this email.\\\", \\\"error\\\")\\n\\n logger.info(\\n \\\"User %s has attempted to log in via OAuth2 but an account \\\"\\n \\\"does not exist for them.\\\", email\\n )\\n else:\\n login_user(user)\\n\\n logger.info(\\n \\\"User %s has succesfully logged in via OAuth2.\\\", email\\n )\\n\\n return redirect(url_for(\\\"home\\\"))\\n\\n else:\\n flash(\\\"Sorry, we couldn't verify your email\\\", \\\"error\\\")\\n\\n logger.info(\\\"User %s failed to authenticate with OAuth2 because \\\"\\n \\\"their email has not been verified with google.\\\", email)\\n\\n return redirect(url_for(\\\"login\\\"))\",\n \"def authenticate(self, msg=\\\"\\\"):\\n if self.request.user:\\n return True\\n else:\\n templating = self.server.templating # save current templating settings\\n templating_path = self.server.templating_path\\n self.server.set_templating(\\\"pystache\\\")\\n self.server.set_templating_path(\\\".\\\")\\n params = {'hidden_fields': self.request.params} # pass all parameters\\n self.response.send_template(self.login_template, params)\\n self.server.templating = templating # restore templating settings\\n self.server.templating_path = templating_path\\n raise AlreadyProcessed()\",\n \"def do_authenticate():\\n #try:\\n if 1:\\n if 'referer' not in self.session:\\n path = urlsplit(self.request.url)[2]\\n self.session['referer'] = path\\n self.session.put()\\n #except:\\n # pass\\n aobj = self.config.auth_obj()\\n self.get_controller()\\n auth_res = aobj.auth(self.controller, *args, **kws)\\n if auth_res:\\n return func(*args, **kws)\\n aobj.auth_redirect(self.controller, *args, **kws)\\n # clear controller for development environment.\",\n \"def accesscode(request, code):\\n employee = Employee.objects.get(access_code=code)\\n user = employee.user\\n user.backend = 'django.contrib.auth.backends.ModelBackend'\\n login(request, user)\\n return HttpResponseRedirect('/')\",\n \"def authenticate(credentials):\",\n \"def authenticate_with_github(username=None, password=None, code=None):\\n if username is not None and password is not None:\\n print(' (auth given as {}:{})'.format(username, '*'*len(password)))\\n\\n def _2fa_func():\\n return code\\n\\n if code:\\n return login(username, password, two_factor_callback=_2fa_func)\\n else:\\n return GitHub(username, password)\",\n \"def auth(self, user):\",\n \"def handleAuth(self, opcode, data, client):\\n \\n # Get the data the client sent.\\n clientUser = data.getString()\\n clientPass = data.getString()\\n \\n # Flag to be send back after serverside auth\\n flag = None\\n userpass = False\\n loginTries = 0 # Not thought out now, will return to it later...\\n \\n # Get the data from DB\\n try:\\n # Here we can add the player to the PLAYERS{} by using a player\\n # ID or something\\n details = []\\n details = Database.getAccountData(clientUser, clientPass)\\n \\n except:\\n print \\\"Can't connected to ACCOUNT DATABASE\\\"\\n \\n # Will make some other checks later... this is just good for now..\\n if details == None:\\n flag = 2\\n print \\\"Player: \\\", clientUser, \\\" Doesn't exist! or Incorrect!\\\"\\n loginTries += 1\\n \\n # Check if the password/username match\\n elif clientPass == details[2] and clientUser == details[1]:\\n print details\\n userpass = True\\n self.network.base.PLAYERS[details[0]] = Player(self, details[0], details[1])\\n print \\\"Player: \\\", details[1], \\\" Logged in, ID: \\\", details[0]\\n flag = 1\\n \\n else:\\n userpass = False\\n print \\\"Player: \\\", clientUser, \\\" login incorrect\\\"\\n loginTries += 1\\n flag = 2\\n \\n # Create buffer\\n pkg = PyDatagram()\\n \\n # Add response\\n pkg.addUint16(SMSG_AUTH_RESPONSE)\\n \\n # Add the flag\\n pkg.addUint16(flag)\\n \\n # Send the packet\\n self.network.tcpWriter.send(pkg, client)\",\n \"def auth():\\n pass\",\n \"def auth():\\n pass\",\n \"def do_login(self, backend, user):\",\n \"def authenticate():\\n if request.environ['PATH_INFO'] == \\\"/notification\\\":\\n user = getUser()\\n \\n if user is None:\\n raise HTTPResponse(body=\\\"Forbidden\\\", status=403)\\n \\n try:\\n if authz.login(user):\\n logging.info('Login success: %s', user.username)\\n return\\n except IOError:\\n raise HTTPResponse(body=\\\"Error reading user file\\\", status=400)\\n except Exception as e:\\n raise HTTPResponse(body=\\\"Unexpected error\\\", status=400)\\n \\n raise HTTPResponse(body=\\\"Invalid username or password\\\", status=401)\",\n \"def auth_user():\\n global token\\n app.logger.info(\\\"Microsoft Planner Service running on /auth port as expected\\\")\\n try:\\n request_count = 0\\n if request_count == 0:\\n token = get_tokens_as_app(client_id, user_code_info, tenant_id)\\n request_count = 1 \\n if 'access_token' in token:\\n app.logger.info('Adding access token to cache...')\\n add_token_to_cache(client_id, tenant_id, token)\\n return_object = (f\\\"{token['refresh_token']}\\\")\\n return render_template('token.html', return_object=return_object)\\n else:\\n return_error = (\\\"Token response did not result in a proper response. Athenticate again please.\\\")\\n return render_template('token.html', return_error=return_error)\\n except AttributeError or TypeError:\\n return_error = ('Authentification failed. Please pull and restart your system and authenticate again.')\\n return render_template('token.html', return_error=return_error)\\n except adal.AdalError as err:\\n return_error = (\\\"You're logged in with the wrong user. Please log out and authenticate again.\\\")\\n return render_template('token.html', return_error=return_error)\",\n \"def doAuth(pamh):\\n\\tprint('called third eye')\\n\\t# Abort if third_eye is disabled\\n\\tif config.getboolean(\\\"core\\\", \\\"disabled\\\"):\\n\\t\\tsys.exit(0)\\n\\n\\tif \\\"SSH_CONNECTION\\\" in os.environ or \\\"SSH_CLIENT\\\" in os.environ or \\\"SSHD_OPTS\\\" in os.environ:\\n\\t\\tsys.exit(0)\\n\\tpamh.conversation(pamh.Message(pamh.PAM_TEXT_INFO, \\\"Attempting a face detection\\\"))\\n\\n\\t# Run compare as python3 subprocess to circumvent python version and import issues\\n\\tstatus = subprocess.call([\\\"/usr/bin/python3\\\", os.path.dirname(os.path.abspath(__file__)) + \\\"/new_compare.py\\\", pamh.get_user()])\\n\\n\\t# Status 12 means we aborted\\n\\tif status == 12:\\n\\t\\treturn pamh.PAM_AUTH_ERR\\n\\t# Status 0 is a successful exit\\n\\telif status == 0:\\n\\t\\t# Show the success message if it isn't suppressed\\n\\t\\tpamh.conversation(pamh.Message(pamh.PAM_TEXT_INFO, \\\"Identified face as \\\" + pamh.get_user()))\\n\\t\\treturn pamh.PAM_SUCCESS\\n\\t#unknown err\\n\\treturn pamh.PAM_SYSTEM_ERR\",\n \"def test_auth_code_positive(self, api):\\n self.builder.add_user(api.get_user())\\n resp = api.login_user(api.get_user().username, api.get_user().password)\\n self.builder.del_user(api.get_user())\\n assert resp.status_code == 200\",\n \"def authenticate(self, username, password):\\n user = self.db.get_user(username)\\n print(user)\\n\\n if user is None:\\n self.__deny_state()\\n\\n if not self.argon2.verify(user[1], password):\\n self.__deny_state()\\n\\n self.__accept_state()\",\n \"def auth_code(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"auth_code\\\")\",\n \"def auth_code(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"auth_code\\\")\",\n \"def auth_code(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"auth_code\\\")\",\n \"def auth_code(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"auth_code\\\")\",\n \"def auth_code(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"auth_code\\\")\",\n \"def auth_code(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"auth_code\\\")\",\n \"def auth_code(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"auth_code\\\")\",\n \"def auth_code(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"auth_code\\\")\",\n \"def api_auth():\\n form = request.get_json(force=True)\\n userdata = None\\n if form['register']:\\n userdata = userProvider.register_user(\\n form['username'].encode('utf8'),\\n form['password'].encode('utf8')\\n )\\n else:\\n userdata = userProvider.load_authenticated_user(\\n form['username'].encode('utf8'),\\n form['password'].encode('utf8')\\n )\\n if userdata:\\n user = userProvider.userdata_to_user(userdata)\\n flask_login.login_user(user)\\n return \\\"true\\\"\\n raise Exception(\\\"No user loaded\\\")\",\n \"def _authenticate(self, mix, authenticator):\\n if self._auth_attempt == 0:\\n username, password = self._auth\\n authenticator.setUser(username)\\n authenticator.setPassword(password)\\n self._auth_attempt += 1\",\n \"def check_auth():\",\n \"def authenticate(request):\\n if not current_user.is_authenticated:\\n raise NoAuthProvided()\\n if current_user.is_locked or not current_user.active:\\n raise UnauthorizedError(\\n 'Authentication failed for . '\\n 'Wrong credentials or locked account')\\n return current_user\",\n \"def authenticate(cls, handler):\\n raise NotImplementedError(\\\"Missing implementation for authenticate\\\")\",\n \"def log_in(codecool):\\n\\n login = school_view.get_login()\\n password = school_view.get_password()\\n\\n password = utilities.hash_password(password)\\n\\n users = codecool.managers_list + codecool.administrators_list + codecool.mentors_list + codecool.students_list\\n for user in users:\\n if user.login == login and user.password == password:\\n return user\",\n \"async def async_step_auth(self, user_input=None):\\n if user_input.get(const.CODE):\\n self.data = user_input\\n return self.async_external_step_done(next_step_id=\\\"finish\\\")\\n\\n profile = user_input.get(const.PROFILE)\\n\\n auth_client = self.get_auth_client(profile)\\n\\n url = auth_client.get_authorize_url()\\n\\n return self.async_external_step(step_id=\\\"auth\\\", url=url)\",\n \"def authenticate():\\n try:\\n return redirect(authorize_uri + '?client_id=' + client_id + \\\\\\n '&response_type=code&redirect_uri=' + redirect_uri + '&scope=user-library-read user-modify-playback-state')\\n except Exception as e:\\n return ('authenticate() threw ' +str(e))\",\n \"def authenticate_userpass():\\n return _userpwd_auth(current_app.config.get('VAULT_AUTH_PATH', 'userpass'))\",\n \"def auth():\\n\\tcode = request.query.code\\n\\tauth = 'https://foursquare.com/oauth2/access_token'\\n\\tparams = dict(\\n\\t\\tclient_id=CLIENT_ID,\\n\\t\\tclient_secret=CLIENT_SECRET,\\n\\t\\tgrant_type='authorization_code',\\n\\t\\tredirect_uri=REDIRECT_URI,\\n\\t\\tcode=code\\n\\t)\\n\\tauth_says = fetch('%s?%s'%(auth, urlencode(params)))\\n\\tauth_response = json.loads(auth_says.content)\\n\\tif 'access_token' in auth_response:\\n\\t\\toauth_token=auth_response['access_token']\\n\\t\\tresponse.set_cookie('user', oauth_token, secret=CLIENT_SECRET)\\n\\t\\tlogging.info('new oauth_token:%s'%oauth_token)\\n\\t\\tredirect('/')\\n\\telse:\\n\\t\\tlogging.error(auth_response)\\n\\t\\tabort()\",\n \"def authenticate_user(data):\\n \\n try:\\n auth_token = data[\\\"auth_token\\\"]\\n user_token = Token.objects.get(username=data[\\\"username\\\"])\\n if user_token.token == auth_token:\\n return True\\n except:\\n return False\\n return False\",\n \"def authenticate():\\n return \\\"Please log in... Log in page\\\"\",\n \"def func_auth(self, data):\\n check = bytes(data).decode().encode('ascii', 'ignore').decode().lower().rstrip()\\n if check == 'auth login':\\n auth_id = library.q_id_generate(size=12)\\n message = '334 ' + auth_id\\n self.func_sender(message)\\n self.request.recv(self.std_recv_size)\\n auth_id_two = library.q_id_generate(size=12)\\n message_two = '334 ' + auth_id_two\\n self.func_sender(message_two)\\n self.request.recv(self.std_recv_size)\\n message_three = self.conf_th_ic.get_item(q_key='std-messages').get(check)\\n self.func_sender(message_three)\\n return True\",\n \"def authenticate_user( db, request ):\\n\\n username = request.values.get( 'username' )\\n password = request.values.get( 'password' )\\n\\n if ( not username or not password ):\\n return False\\n\\n user = db.execute(\\n text( 'select users_id, name, email from users where name = :name and password_hash = md5( :salt || :password ) and is_active' ),\\n name = username, password = password, salt = app.config[ 'SECRET_KEY' ]\\n ).fetchone()\\n\\n if ( user ):\\n return user\\n else:\\n return False\",\n \"def authenticate_user(self, *, provider: str, user_name: str, password: str) -> UserId:\",\n \"def authenticate(self, registered_provider=None, template_path=None):\\n if self.flow_type == \\\"web\\\" and registered_provider is not None:\\n response = self.authenticate_from_server(registered_provider)\\n if response is None or response.get(\\\"access_token\\\") is None:\\n return (\\n f\\\"Access Denied: Reason={request.args['error']} \\\"\\n f\\\"error={request.args['error_description']} \\\"\\n f\\\"response={response}\\\"\\n )\\n session[\\\"token\\\"] = response\\n return redirect(url_for(\\\"home\\\", provider=self.name))\\n elif self.flow_type == \\\"implicit\\\" and template_path is not None:\\n return self.authenticate_implicit(template_path)\\n elif self.flow_type == \\\"client\\\":\\n return redirect(url_for(\\\"home\\\", provider=self.name))\\n else:\\n raise Exception(\\n \\\"Invalid flow type, registered_provider is None, \\\"\\n \\\"or template_path not specified\\\"\\n )\",\n \"def check_user_and_login(self) -> Response:\\n pass\",\n \"def verify_auth_code(self, code):\\n raise NotImplementedError(\\n \\\"\\\"\\\"\\n verify_scope must be implemented by a child class\\n \\\"\\\"\\\"\\n )\",\n \"def authenticate_user(self):\\n raise NotImplementedError(\\n \\\"\\\"\\\"\\n authenticate_user must be implemented by a child class\\n \\\"\\\"\\\"\\n )\",\n \"def _authenticate(self):\\n auth = self.settings.get(\\\"auth\\\")\\n if auth:\\n if auth == Auth.PLAIN:\\n self._authenticate_plain()\\n elif auth == Auth.SHA256_MEMORY:\\n self._authenticate_sha256_memory()\\n elif auth == Auth.MYSQL41:\\n self._authenticate_mysql41()\\n elif self.stream.is_secure():\\n # Use PLAIN if no auth provided and connection is secure\\n self._authenticate_plain()\\n else:\\n # Use MYSQL41 if connection is not secure\\n try:\\n self._authenticate_mysql41()\\n except InterfaceError:\\n pass\\n else:\\n return\\n # Try SHA256_MEMORY if MYSQL41 fails\\n try:\\n self._authenticate_sha256_memory()\\n except InterfaceError as err:\\n raise InterfaceError(\\n \\\"Authentication failed using MYSQL41 and \\\"\\n \\\"SHA256_MEMORY, check username and \\\"\\n f\\\"password or try a secure connection err:{err}\\\"\\n ) from err\",\n \"def authn_and_authz():\\n authentication()\\n authorization()\",\n \"def authenticate(cls, handler):\\n return None\",\n \"def _oauth_callback(self):\\n tokens = self.oauth.get_raw_access_token(data={\\n 'code': flask.request.args.get('code', ''),\\n 'redirect_uri': self.oauth_redirect_uri,\\n 'grant_type': 'authorization_code'\\n }).json()\\n user = User(tokens=tokens, app=self)\\n\\n # Add subscriptions\\n self.subscriptions.init_user(user)\\n\\n # Call endpoint for user login\\n return self.subscriptions.call_endpoint(\\\"login\\\", user) or \\\"\\\"\",\n \"def login():\\n if app.testing:\\n callback_url = url_for('user.authorize', _external=True)\\n else:\\n callback_url = 'https://codegolf.uqcs.org.au/user/authorize'\\n return git_auth.authorize(callback=callback_url)\",\n \"def authenticate():\\n if request.method == 'POST':\\n username = request.form['username']\\n password = request.form['password']\\n template = request.form['backto']\\n car_id = request.form['car-id']\\n if check_credentials(username, password):\\n return after_auth_redirect(template, car_id, username)\\n else:\\n return render_template('login.html', error=\\\"Bad credentials!\\\")\",\n \"def login(self):\\r\\n user_account = db.find_one({\\\"cpr_number\\\": request.form.get(\\\"CPR\\\")})\\r\\n if user_account is not None:\\r\\n if self.verify_password(user_account[\\\"password\\\"], request.form.get(\\\"password\\\")):\\r\\n return self.start_session(user_account)\\r\\n return jsonify({\\\"error\\\": \\\"Invalid login credentials\\\"}), 401\",\n \"def _authenticate(self):\\n\\t\\tfrom getpass import getpass\\n\\t\\tpassword = getpass()\\n\\t\\tself.msg('nickserv', 'identify %s' % password)\",\n \"def auth(self):\\n ok = False\\n if self.private_token:\\n ok = self.token_auth()\\n if not ok:\\n self.credentials_auth()\",\n \"def authenticateBackend(self, tried_username=None, tried_password=None):\\n\\n # we keep these here in case frontend has authenticated and backend hasn't established the secure channel yet;\\n # in that case, tried credentials are stored to be used whenever usearauth with backend can be performed\\n if tried_username and tried_password:\\n self.frontendTriedUsername = tried_username\\n self.frontendTriedPassword = tried_password\\n\\n # do nothing if frontend is not authenticated, or backend has not established a secure channel\\n if not self.factory.server.frontendAuthenticated or not self.canAuth:\\n return\\n\\n # we authenticate with the backend using the credentials provided\\n # TODO create the account in the backend before (contact the pool of VMs for example)\\n # so these credentials from the config may not be needed after all\\n username = CowrieConfig().get('proxy', 'backend_user').encode()\\n password = CowrieConfig().get('proxy', 'backend_pass').encode()\\n\\n log.msg('Will auth with backend: {0}/{1}'.format(username, password))\\n self.sendPacket(5, bin_string_to_hex(b'ssh-userauth'))\\n payload = bin_string_to_hex(username) + \\\\\\n string_to_hex('ssh-connection') + \\\\\\n string_to_hex('password') + \\\\\\n b'\\\\x00' + \\\\\\n bin_string_to_hex(password)\\n\\n self.sendPacket(50, payload)\\n self.factory.server.backendConnected = True\\n\\n # send packets from the frontend that were waiting to go to the backend\\n for packet in self.factory.server.delayedPackets:\\n self.factory.server.sshParse.parse_packet('[SERVER]', packet[0], packet[1])\\n self.factory.server.delayedPackets = []\\n\\n # backend auth is done, attackers will now be connected to the backend\\n self.authDone = True\",\n \"def authenticate():\\n # Get JSON data from request\\n json = request.get_json()\\n\\n if 'email' not in json or 'password' not in json:\\n raise CustomError(400, message='Must include an email and a password')\\n\\n # Check email\\n user = User.query.filter_by(email=json['email']).first()\\n if user is None:\\n raise CustomError(401, message='Email or password were not found.')\\n\\n # Check password\\n if not check_password_hash(user.password, json['password']):\\n raise CustomError(401, message='Email or password were not found.')\\n\\n return jsonify({'success': True, 'user': user.to_dict()}), 201\",\n \"def authenticate():\\n return abort(401)\",\n \"def authenticate(self):\\n self.login(closet.app.config['USERNAME'],\\n closet.app.config['PASSWORD'])\",\n \"def authenticate(self, rfid):\\n print(\\\"Auth id: [{}]\\\".format(rfid))\\n\\n values = {'id' : rfid}\\n data = urllib.parse.urlencode(values)\\n data = data.encode('utf-8')\\n\\n t1 = perf_counter()\\n\\n req = urllib.request.Request(self.auth_url, data)\\n try:\\n resp = urllib.request.urlopen(req, timeout=self.request_timeout)\\n except URLError as err:\\n print(\\\"URLError: auth_url:[{}]\\\".format(self.auth_url))\\n print(\\\"URLError: {}\\\".format(err))\\n print(\\\"Falling back to local cache\\\")\\n cached = self.auth_from_cache(rfid)\\n return cached\\n except timeout as err:\\n cached = self.auth_from_cache(rfid)\\n return cached\\n\\n text = resp.read()\\n\\n t2 = perf_counter()\\n print(\\\"Auth got [{}] in {} seconds\\\".format(text, t2-t1))\\n\\n if text == b'Granted':\\n return True\",\n \"def _auth(self):\\n\\n def check_response(text):\\n \\\"\\\"\\\"Check to see if authentication has failed.\\n \\\"\\\"\\\"\\n\\n if 'incorrect' in response.text:\\n msg = ('Username <%(username)s> and password <%(password)s> ' +\\n 'do not match.') % {'username': self.username,\\n 'password': self.password}\\n\\n raise exceptions.AuthError(msg)\\n\\n data = {'action': 'login',\\n 'user': self.username,\\n 'pwd': self.password}\\n\\n # step 1: submit login form\\n response = self._do('POST', self.URLS['auth_step_one'],\\n data=data, allow_redirects=True)\\n check_response(response.text)\\n\\n # step 2: fake second form's submission\\n # todo: sprinkle on some error checking,\\n # even though this is only a redirect\\n response = self._do('POST', self.URLS['auth_step_two'],\\n data=data, allow_redirects=True)\\n check_response(response.text)\\n\\n return True\",\n \"def __authenticate(self, data):\\n if 'token' not in data:\\n raise TokenError(\\\"Invalid Token\\\")\\n if data['token'] != app.config['SLACK_TOKEN']:\\n raise TokenError(\\\"Invalid Token\\\")\",\n \"def activate_user(username, code, new_pass):\\r\\n\\r\\n qry = Activation.query.\\\\\\r\\n filter(Activation.code == code).\\\\\\r\\n filter(User.username == username)\\r\\n\\r\\n res = qry.first()\\r\\n\\r\\n if UserMgr.acceptable_password(new_pass) and res is not None:\\r\\n user = res.user\\r\\n user.activated = True\\r\\n user.password = new_pass\\r\\n res.activate()\\r\\n\\r\\n LOG.debug(dict(user))\\r\\n\\r\\n return True\\r\\n else:\\r\\n return None\",\n \"def auth_code_handler(self, request, pk=None):\\n try:\\n # Get xero auth access information form xero connection\\n stored_values = OAUTH_PERSISTENT_SERVER_STORAGE\\n\\n\\n if len(stored_values) == 0:\\n return Utils.dispatch_failure(request, 'NO_TOKEN_AUTHENTICATION')\\n\\n secret_keys = Utils.get_access_keys(pk)\\n if AccountingConfiguration.PRIVATE == secret_keys.type:\\n exists = AccountingOauth2.objects.filter(company=pk).first()\\n if not exists:\\n auth = AccountingOauth2(accessToken=stored_values['consumer_key'],\\n accessSecretKey=stored_values['rsa_key'],\\n company_id=pk)\\n auth.save()\\n else:\\n exists.accessToken = stored_values['consumer_key']\\n exists.accessSecretKey = stored_values['rsa_key']\\n exists.save()\\n else:\\n auth_verifier_uri = settings.XERO_AUTH_VERIFIER_URI\\n oauth_verifier = request.GET.get('oauth_verifier')\\n credentials = Utils.get_xero_public_credentials(stored_values)\\n\\n if credentials.expired():\\n return Utils.dispatch_failure(request, 'NO_TOKEN_AUTHENTICATION')\\n\\n # Verify the auth verifier for establish the connection\\n\\n credentials.verify(oauth_verifier)\\n # Resave our verified credentials\\n for key, value in credentials.state.items():\\n OAUTH_PERSISTENT_SERVER_STORAGE.update({key: value})\\n\\n stored_values = OAUTH_PERSISTENT_SERVER_STORAGE\\n exists = AccountingOauth2.objects.filter(company=pk).first()\\n\\n if exists:\\n exists.accessToken = stored_values['oauth_token']\\n exists.realmId = oauth_verifier\\n exists.accessSecretKey = stored_values['oauth_token_secret']\\n exists.tokenAcitvatedOn = stored_values['oauth_expires_at']\\n exists.tokenExpiryON = stored_values['oauth_authorization_expires_at']\\n exists.save()\\n else:\\n auth = AccountingOauth2(accessToken=stored_values['oauth_token'],\\n refreshToken='',\\n realmId=oauth_verifier,\\n accessSecretKey=stored_values['oauth_token_secret'],\\n tokenAcitvatedOn=stored_values['oauth_expires_at'],\\n tokenExpiryON=stored_values['oauth_authorization_expires_at'],\\n company_id=pk)\\n auth.save()\\n # auth_redirect_url = os.environ.get ('QBO_AUTH_REDIRECT_URL',\\n # 'http://localhost:4200/coa-match/quickbooks')\\n\\n # auth_redirect_url = os.environ.get ('QBO_AUTH_REDIRECT_URL','http://ec2-52-207-28-114.compute-1.amazonaws.com/ix/coa-match/quickbooks')\\n\\n # return redirect(auth_redirect_url)\\n\\n except Exception as e:\\n auth_cancel_url = settings.QBO_AUTH_CANCEL_URL\\n Utils.send_company_misconfig(pk, e)\\n return redirect(auth_cancel_url + '/error')\\n #return Utils.dispatch_success(request, 'TOKEN_ALREADY_VALIDATED')\\n\\n auth_redirect_url = settings.XERO_AUTH_REDIRECT_URL\\n return redirect(auth_redirect_url)\\n # return Utils.dispatch_success(request, stored_values)\",\n \"def authenticate(self):\\n rv = Form.validate(self)\\n if not rv:\\n return False\\n\\n user = self.username.data\\n\\n cur = get_cursor()\\n if email_exists(cur, user):\\n user = get_username(cur, user)\\n\\n if username_exists(cur, user):\\n pw_hash = get_pw_hash(cur, user)\\n\\n if check_password(self.password.data, pw_hash):\\n self.username.data = user\\n return True\\n\\n return False\",\n \"def authenticate(self, *args, **kwargs):\\n # Validate backend and arguments. Require that the Social Auth\\n # response be passed in as a keyword argument, to make sure we\\n # don't match the username/password calling conventions of\\n # authenticate.\\n if not (self.name and kwargs.get(self.name) and 'response' in kwargs):\\n return None\\n\\n response = kwargs.get('response')\\n pipeline = PIPELINE\\n kwargs = kwargs.copy()\\n kwargs['backend'] = self\\n\\n if 'pipeline_index' in kwargs:\\n pipeline = pipeline[kwargs['pipeline_index']:]\\n else:\\n kwargs['details'] = self.get_user_details(response)\\n kwargs['uid'] = self.get_user_id(kwargs['request'])\\n kwargs['is_new'] = False\\n \\n out = self.pipeline(pipeline, *args, **kwargs)\\n if not isinstance(out, dict):\\n return out\\n\\n social_user = out.get('social_user')\\n if social_user:\\n # define user.social_user attribute to track current social\\n # account\\n user = social_user.user\\n user.social_user = social_user\\n user.is_new = out.get('is_new')\\n return user\",\n \"def login_menu(self):\\n print(\\\"\\\\nPlease enter your email and password\\\")\\n email = self.validate_email()\\n password = self.validate_password()\\n self.authenticate_user(email, password)\",\n \"def login():\\n auth_state = str(uuid.uuid4())\\n SESSION.auth_state = auth_state\\n\\n # For this sample, the user selects an account to authenticate. Change\\n # this value to 'none' for \\\"silent SSO\\\" behavior, and if the user is\\n # already authenticated they won't need to re-authenticate.\\n prompt_behavior = 'select_account'\\n\\n params = urllib.parse.urlencode({'response_type': 'code',\\n 'client_id': config.CLIENT_ID,\\n 'redirect_uri': config.REDIRECT_URI,\\n 'state': auth_state,\\n 'resource': config.RESOURCE,\\n 'prompt': prompt_behavior})\\n\\n return bottle.redirect(config.AUTHORITY_URL + '/oauth2/authorize?' + params)\",\n \"def _delegate_authentication(username, password):\\n payload = json.dumps({\\n 'type': 'normal',\\n 'username': username,\\n 'password': password\\n })\\n headers = {'Content-Type': 'application/json'}\\n login_response = requests.post(API_URL + \\\"/auth\\\", data=payload, headers=headers)\\n if login_response.status_code != 200:\\n return False\\n\\n try:\\n decoded_response = login_response.json()\\n except ValueError as error:\\n logger.error(f'Cannot decode Taiga auth response: {error}. Response was: {login_response}')\\n return False\\n return decoded_response\",\n \"def authenticate(self):\\n # self.qobject.remove_authenticate_signal.emit()\\n # self.qobject.authenticate_signal.emit( )\\n #if self.app.sync_thread.status != const.STATUS_SYNC:\\n # self.app.sync_thread.force_sync()\\n change_auth_token( )\\n self.data_changed()\",\n \"def authcheck():\\n user = get_user()\\n return jsonify({'current_identity': user.username})\",\n \"def authenticator():\",\n \"def authentication_view(request):\\n \\n data = request.data\\n username = data.get('username', '')\\n password = data.get('password', '')\\n user = authenticate(request, username=username, password=password) \\n\\n if user is not None:\\n login(request, user)\\n return JsonResponse({\\\"status\\\": \\\"success\\\"})\\n else:\\n return JsonResponse({\\\"status\\\": \\\"fail\\\"})\",\n \"def login_user():\\n pass\",\n \"def get(self):\\n\\n\\t\\trequest = user_auth_parser.parse_args(strict=True)\\n\\n\\t\\tresult = Authenticator.authenticate(\\n\\t\\t\\trequest[\\\"username\\\"],\\n\\t\\t\\trequest[\\\"password\\\"]\\n\\t\\t)\\n\\n\\t\\treturn result\",\n \"def skyserv_authenticator(self):\\n \\n header = {\\n 'Content-Type': accept, \\n 'X-Auth-Token': self.casjobtoken,\\n 'Accept': accept\\n }\\n # this format is disgusting but required....\\n authdata = {\\n 'auth' :{\\n 'identity': {\\n 'password': {\\n 'user': {\\n 'name': username,\\n 'password': password\\n }\\n }\\n }\\n }\\n }\\n payload = json.dumps(authdata).encode(encoding='utf-8')\\n try:\\n post = requests.post(self.loginurl, data=payload, headers=header)\\n\\n if post.status_code == 200:\\n response = json.loads(post.text)\\n token = response[self.tokenkey]\\n return token\\n else:\\n print('Username and/or password are invalid.')\\n post.raise_for_status()\\n except Exception as e:\\n raise(str(e))\",\n \"def authenticate(self, func):\\n self._authentication_callback = func\\n return func\",\n \"def authenticate():\\n\\n return Response(\\n 'Could not verify your access level for that URL.\\\\n'\\n 'You have to login with proper credentials', 401,\\n get_auth_headers())\",\n \"def authenticate(self, username, password):\\n auth = (username, password)\\n res = requests.get(\\n self.normalize_admin_url(\\\"authenticate\\\"),\\n headers={\\\"user-agent\\\": self.u_agent},\\n auth=auth,\\n verify=False,\\n )\\n if res.status_code == 200:\\n # authentication ok, keep authentication info for future use\\n self.auth = auth\\n return Response(0, \\\"Successfully logged in\\\")\\n elif res.status_code == 401:\\n try:\\n val = res.json()\\n except ValueError:\\n val = \\\"Login credentials not accepted\\\"\\n return Response(401, val)\\n else:\\n return Response(res.status_code, res.content)\",\n \"def check_auth(username, password):\\n # return username == app.config['USER'] and password == app.config['PASS']\\n\\n return username == app.config['USER'] and password == app.config['PASS']\",\n \"def authenticate_credentials(self, payload):\\n username = payload.get('username')\\n email = payload.get('email')\\n if not username and not email:\\n msg = _('Invalid payload.')\\n raise exceptions.AuthenticationFailed(msg)\\n try:\\n # Username query is case insensitive\\n user_queryset = User.objects.filter(\\n Q(username__iexact=username)|\\n Q(email__iexact=email)\\n ).distinct()\\n if user_queryset.exists() and user_queryset.count() == 1:\\n user = user_queryset.first()\\n return user\\n except User.DoesNotExist:\\n return None\",\n \"def authenticate(self, cred): \\n auth_helper = AuthHelper.AuthHelper(self.context)\\n return auth_helper.auth(cred)\",\n \"def check_auth_interactive(self, username, submethods):\\n return AUTH_FAILED\",\n \"def authentication(app, user_model):\\n login_manager.login_message = \\\"Please login to access this page.\\\"\\n login_manager.login_view = 'auth.login'\\n login_manager.session_protection = 'strong'\\n login_manager.login_message_category = 'danger'\\n\\n @login_manager.user_loader\\n def load_user(user_id):\\n return user_model.query.get(int(user_id))\",\n \"def check_auth(*args, **kwargs):\\n r = cherrypy.request\\n s = cherrypy.session\\n\\n username = s.get(USERNAME_SESSION_KEY, None)\\n course = s.get(CUR_CRS_SESSION_KEY, None)\\n # require a course to be selected\\n if username and not course and r.path_info != '/auth/course':\\n raise cherrypy.HTTPRedirect(\\\"/auth/course\\\")\\n\\n conditions = r.config.get('auth.restrict.require', None)\\n if conditions is not None:\\n if username:\\n r.login = username\\n for condition in conditions:\\n # A condition is just a callable that returns true or false\\n if not condition():\\n raise cherrypy.HTTPRedirect(\\\"/auth/not-authorized\\\")\\n else:\\n s[FROMPATH_SESSION_KEY] = r.path_info\\n raise cherrypy.HTTPRedirect(\\\"/auth/login\\\")\",\n \"def authenticate(self, username: str, password: str) -> Optional[str]:\",\n \"def authenticate(self, username: str, password: str) -> Optional[str]:\",\n \"def authorize():\\n resp = git_auth.authorized_response()\\n user_info = git_auth.get('user', token=(resp[\\\"access_token\\\"],)).data\\n u = db_session.query(User).filter(User.email == user_info['email']).first()\\n if not u:\\n u = User(user_info['login'], user_info['email'])\\n db_session.add(u)\\n db_session.commit()\\n login_user(u, remember=True)\\n return redirect(url_for('index'))\",\n \"def authenticate(self):\\n #it's weird i have to do this here, but the code makes this not simple\\n auth_json={'email':self.user, 'password':self.password}\\n #send a post with no auth. prevents an infinite loop\\n auth_response = self.post('/auth', data = json.dumps(auth_json), auth =\\n None)\\n\\n _token = auth_response.json['token']\\n\\n self._token = _token\\n self._wrapped.auth = SpringAuth(_token)\",\n \"def authenticate(self):\\n\\n def decorate(func, *args, **kws):\\n \\\"\\\"\\\"\\n A function returned as a object in load time,\\n which returns inner function do_decorate().\\n \\\"\\\"\\\"\\n def do_authenticate():\\n \\\"\\\"\\\"\\n A function to perform authentication\\n every time decorated function is called.\\n \\\"\\\"\\\"\\n #try:\\n if 1:\\n if 'referer' not in self.session:\\n path = urlsplit(self.request.url)[2]\\n self.session['referer'] = path\\n self.session.put()\\n #except:\\n # pass\\n aobj = self.config.auth_obj()\\n self.get_controller()\\n auth_res = aobj.auth(self.controller, *args, **kws)\\n if auth_res:\\n return func(*args, **kws)\\n aobj.auth_redirect(self.controller, *args, **kws)\\n # clear controller for development environment.\\n\\n return do_authenticate\\n\\n return decorate\",\n \"def user_login():\\n user = query_db('''select * from user where username = ?''', [request.authorization.username], one=True)\\n if user is None:\\n error = 'Invalid username'\\n elif not check_password_hash(user['pw_hash'],request.authorization.password):\\n error = 'Invalid password'\\n else:\\n flash('You were logged in')\\n return jsonify({'user_id':user['user_id']}),200\",\n \"def login(self, user, password):\\n \\n def encode_base64(s, eol=None):\\n return \\\"\\\".join(base64.encodestring(s).split(\\\"\\\\n\\\"))\\n \\n def encode_cram_md5(challenge, user, password):\\n challenge = base64.decodestring(challenge)\\n response = user + \\\" \\\" + hmac.HMAC(password, challenge).hexdigest()\\n return base64_encode(response, eol=\\\"\\\")\\n\\n def encode_plain(user, password):\\n return base64_encode(\\\"%s\\\\0%s\\\\0%s\\\" % (user, user, password), eol=\\\"\\\")\\n\\n\\n AUTH_PLAIN = \\\"PLAIN\\\"\\n AUTH_CRAM_MD5 = \\\"CRAM-MD5\\\"\\n AUTH_LOGIN = \\\"LOGIN\\\"\\n\\n if self.helo_resp is None and self.ehlo_resp is None:\\n if not (200 <= self.ehlo()[0] <= 299):\\n (code, resp) = self.helo()\\n if not (200 <= code <= 299):\\n raise SMTPHeloError(code, resp)\\n\\n if not self.has_extn(\\\"auth\\\"):\\n raise SMTPException(\\\"SMTP AUTH extension not supported by server.\\\")\\n\\n # Authentication methods the server supports:\\n authlist = self.esmtp_features[\\\"auth\\\"]\\n if authlist.startswith('='):\\n authlist = authlist[1:]\\n authlist = authlist.split()\\n # List of authentication methods we support: from preferred to\\n # less preferred methods. Except for the purpose of testing the weaker\\n # ones, we prefer stronger methods like CRAM-MD5:\\n \\n preferred_auths = [AUTH_CRAM_MD5, AUTH_PLAIN, AUTH_LOGIN]\\n if hmac is None:\\n preferred_auths.remove(AUTH_CRAM_MD5)\\n \\n # Determine the authentication method we'll use\\n authmethod = None\\n for method in preferred_auths:\\n if method in authlist:\\n authmethod = method\\n break\\n\\n if authmethod == AUTH_CRAM_MD5:\\n (code, resp) = self.docmd(\\\"AUTH\\\", AUTH_CRAM_MD5)\\n if code == 503:\\n # 503 == 'Error: already authenticated'\\n return (code, resp)\\n (code, resp) = self.docmd(encode_cram_md5(resp, user, password))\\n elif authmethod == AUTH_PLAIN:\\n (code, resp) = self.docmd(\\\"AUTH\\\",\\n AUTH_PLAIN + \\\" \\\" + encode_plain(user, password))\\n elif authmethod == AUTH_LOGIN:\\n (code, resp) = self.docmd(\\\"AUTH\\\",\\n \\\"%s %s\\\" % (AUTH_LOGIN, encode_base64(user, eol=\\\"\\\")))\\n if code != 334:\\n raise SMTPException(\\\"Authorization failed.\\\")\\n (code, resp) = self.docmd(encode_base64(password, eol=\\\"\\\"))\\n elif authmethod == None:\\n raise SMTPException(\\\"No suitable authentication method found.\\\")\\n if code not in [235, 503]:\\n # 235 == 'Authentication successful'\\n # 503 == 'Error: already authenticated'\\n raise SMTPException(\\\"Authorization failed.\\\")\\n return (code, resp)\",\n \"def login_entrypoint(request, authentication_form=AuthenticationForm):\\n if request.user.is_authenticated:\\n return redirect_to_user_settings()\\n\\n if request.method == 'GET':\\n return login_view(request)\\n\\n # authenticate the user\\n form = authentication_form(request, data=request.POST)\\n\\n # store the user's id in the session so you can perform Instant2FA check\\n if form.is_valid():\\n user = form.get_user()\\n request.session['distinct_id'] = get_user_distinct_id(user)\\n return HttpResponseRedirect('/login/two-factor/')\\n else:\\n logging.debug(\\\"User did not provide valid authentication credentials.\\\")\\n return login_view(request)\",\n \"def login_require(request):\\n\\n if request.method == \\\"GET\\\":\\n data = request.GET\\n else:\\n data = request.POST\\n user = authenticate(username=data[\\\"username\\\"], password=data[\\\"password\\\"])\\n if user and user.is_active:\\n ret = Response(SUCCESS, error_code[SUCCESS])\\n else: \\n ret = Response(AUTHENTICATION_FAIL, error_code[AUTHENTICATION_FAIL])\\n return HttpResponse(ret.serialize(f))\\n\\n # Generate a token for authentication\\n token = token_generator(30)\\n try:\\n user_token = Token.objects.get(username=data[\\\"username\\\"])\\n user_token.token = token\\n user_token.start_time = datetime.now()\\n except: \\n user_token = Token(token=token, username=data[\\\"username\\\"])\\n user_token.save()\\n ret.set_ret(\\\"auth_token\\\", token) \\n user = User.objects.get(username=data[\\\"username\\\"])\\n ret.set_ret(\\\"data\\\", UserSerializer(user.appuser).serialize())\\n return HttpResponse(ret.serialize(f))\",\n \"def activateWebAppUser( self, username, activation_code ):\\n try:\\n con = self.getMetadataDatabaseConnection()\\n user_data = con.cursor()\\n\\n con.cursor().callproc('verify_user_activation_code', [username, activation_code, user_data])\\n row = user_data.fetchone()\\n if row:\\n con.cursor().callproc('activate_user_account', [username])\\n return True\\n else:\\n return False\\n except Exception, e:\\n print 'Exception caught: %s.\\\\nThe error is: %s' % (type(e), e)\\n return False\",\n \"def authenticate_user():\\n if request.headers['content-type'] == 'application/json':\\n print(request)\\n data = request.get_json()\\n if data:\\n username = data['username']\\n password = data['password']\\n else:\\n return Response(status=400) # no JSON to parse\\n\\n if username is None or password is None:\\n return Response(status=400) # missing arguments\\n\\n if not verify_password(username, password):\\n return Response(status=403) # User not authenticated\\n\\n return jsonify({'username': username, 'success': True}), 201\\n else:\\n print(\\\"invalid request type, no json\\\")\\n return Response(status=400) # invalid request type\",\n \"def login():\\n domain = parser[\\\"learningmachine\\\"][\\\"domain\\\"]\\n secrets_file = \\\"{}/{}\\\".format(dir_path, \\\"client_secret.json\\\")\\n scope = \\\"https://www.googleapis.com/auth/userinfo.email\\\"\\n redirect_uri = \\\"http://{}/login\\\".format(domain)\\n login_handler = LoginHandler(secrets_file, scope, redirect_uri)\\n\\n if \\\"code\\\" in request.args:\\n login_handler.setup_user_info(request.args[\\\"code\\\"])\\n session[\\\"email\\\"] = login_handler.email\\n session[\\\"display_name\\\"] = login_handler.display_name\\n\\n if not fm.user_exists(login_handler.email):\\n msg = \\\"Adding user: {} with ID of {} to the database.\\\"\\\\\\n .format(login_handler.email, login_handler.display_name)\\n fm.add_user(login_handler.email, login_handler.display_name)\\n\\n msg = \\\"Sending user: {} to main page\\\".format(login_handler.email)\\n app.logger.info(msg)\\n return redirect(\\\"/static/main.html\\\")\\n\\n else:\\n msg = \\\"No login code yet. Letting Google handle the login process at: {}\\\"\\\\\\n .format(login_handler.auth_url)\\n app.logger.info(msg)\\n return redirect(login_handler.auth_url)\"\n]"},"negative_scores":{"kind":"list like","value":["0.66076124","0.6604477","0.6523267","0.64544946","0.6403558","0.6359539","0.6357345","0.6290257","0.6288636","0.6280958","0.6248023","0.6243201","0.6242323","0.6237753","0.6226705","0.6226705","0.62162906","0.61871463","0.6182399","0.61742467","0.6170313","0.61575925","0.6150889","0.6150889","0.6150889","0.6150889","0.6150889","0.6150889","0.6150889","0.6150889","0.6148997","0.6137659","0.61356163","0.60954833","0.60631275","0.6033103","0.60151505","0.6004793","0.6001416","0.5990997","0.59909195","0.59785664","0.59677255","0.5965624","0.59640485","0.59554416","0.59416056","0.5927887","0.59234565","0.59191555","0.59126776","0.5911595","0.5909318","0.5904114","0.5882838","0.58727723","0.5872426","0.5863785","0.58593476","0.58451694","0.581483","0.58099437","0.5801386","0.5798975","0.5796279","0.5794899","0.57869107","0.5785157","0.5785035","0.5783977","0.5783024","0.5780957","0.5774048","0.576689","0.5766561","0.5765667","0.576016","0.5759286","0.57584804","0.5753387","0.57532436","0.57527345","0.5747901","0.5741838","0.5738193","0.57328737","0.57296395","0.57193863","0.57167464","0.57167464","0.5711525","0.5706996","0.5706021","0.5705268","0.5705177","0.57018644","0.5700007","0.5698187","0.56884396","0.5688313"],"string":"[\n \"0.66076124\",\n \"0.6604477\",\n \"0.6523267\",\n \"0.64544946\",\n \"0.6403558\",\n \"0.6359539\",\n \"0.6357345\",\n \"0.6290257\",\n \"0.6288636\",\n \"0.6280958\",\n \"0.6248023\",\n \"0.6243201\",\n \"0.6242323\",\n \"0.6237753\",\n \"0.6226705\",\n \"0.6226705\",\n \"0.62162906\",\n \"0.61871463\",\n \"0.6182399\",\n \"0.61742467\",\n \"0.6170313\",\n \"0.61575925\",\n \"0.6150889\",\n \"0.6150889\",\n \"0.6150889\",\n \"0.6150889\",\n \"0.6150889\",\n \"0.6150889\",\n \"0.6150889\",\n \"0.6150889\",\n \"0.6148997\",\n \"0.6137659\",\n \"0.61356163\",\n \"0.60954833\",\n \"0.60631275\",\n \"0.6033103\",\n \"0.60151505\",\n \"0.6004793\",\n \"0.6001416\",\n \"0.5990997\",\n \"0.59909195\",\n \"0.59785664\",\n \"0.59677255\",\n \"0.5965624\",\n \"0.59640485\",\n \"0.59554416\",\n \"0.59416056\",\n \"0.5927887\",\n \"0.59234565\",\n \"0.59191555\",\n \"0.59126776\",\n \"0.5911595\",\n \"0.5909318\",\n \"0.5904114\",\n \"0.5882838\",\n \"0.58727723\",\n \"0.5872426\",\n \"0.5863785\",\n \"0.58593476\",\n \"0.58451694\",\n \"0.581483\",\n \"0.58099437\",\n \"0.5801386\",\n \"0.5798975\",\n \"0.5796279\",\n \"0.5794899\",\n \"0.57869107\",\n \"0.5785157\",\n \"0.5785035\",\n \"0.5783977\",\n \"0.5783024\",\n \"0.5780957\",\n \"0.5774048\",\n \"0.576689\",\n \"0.5766561\",\n \"0.5765667\",\n \"0.576016\",\n \"0.5759286\",\n \"0.57584804\",\n \"0.5753387\",\n \"0.57532436\",\n \"0.57527345\",\n \"0.5747901\",\n \"0.5741838\",\n \"0.5738193\",\n \"0.57328737\",\n \"0.57296395\",\n \"0.57193863\",\n \"0.57167464\",\n \"0.57167464\",\n \"0.5711525\",\n \"0.5706996\",\n \"0.5706021\",\n \"0.5705268\",\n \"0.5705177\",\n \"0.57018644\",\n \"0.5700007\",\n \"0.5698187\",\n \"0.56884396\",\n \"0.5688313\"\n]"},"document_score":{"kind":"string","value":"0.70372474"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8566,"cells":{"query":{"kind":"string","value":"Creates a new service client"},"document":{"kind":"string","value":"def __init__(self, config, **kwargs):\n validate_config(config, signer=kwargs.get('signer'))\n if 'signer' in kwargs:\n signer = kwargs['signer']\n else:\n signer = Signer(\n tenancy=config[\"tenancy\"],\n user=config[\"user\"],\n fingerprint=config[\"fingerprint\"],\n private_key_file_location=config.get(\"key_file\"),\n pass_phrase=get_config_value_or_default(config, \"pass_phrase\"),\n private_key_content=config.get(\"key_content\")\n )\n\n base_client_init_kwargs = {\n 'regional_client': True,\n 'service_endpoint': kwargs.get('service_endpoint'),\n 'timeout': kwargs.get('timeout'),\n 'base_path': '/20160918',\n 'skip_deserialization': kwargs.get('skip_deserialization', False)\n }\n self.base_client = BaseClient(\"identity\", config, signer, identity_type_mapping, **base_client_init_kwargs)\n self.retry_strategy = kwargs.get('retry_strategy')"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_client(service_name: str, config_name: str = None, **client_args):\n session = get_session(config_name)\n return session.client(service_name, **client_args)","def create_client(self) -> None:\n pass","def create(ctx, name, company, mail, age):\n client = Client(name,company,mail,age)\n client_service = ClientService(ctx.obj['clients_table']) \n client_service.create_client(client)","def make_service(self, endpoint_type, service_name, **client_kwargs):\n binding = self._make_binding(endpoint_type, service_name)\n service_cache_key = (binding, str(client_kwargs))\n\n if service_cache_key in self._service_cache:\n srvc = self._service_cache[service_cache_key]\n else:\n client = self._make_client(\n endpoint_type,\n service_name,\n **client_kwargs\n )\n srvc = client.create_service(binding, client.wsdl.location)\n self._service_cache[service_cache_key] = srvc\n return srvc","def create_client(service, region, access_key_id, secret_access_key):\n client = boto3.client(service,\n region_name=region,\n aws_access_key_id=access_key_id,\n aws_secret_access_key=secret_access_key\n )\n return client","def create_client(service, region, access_key_id, secret_access_key):\n client = boto3.client(service,\n region_name=region,\n aws_access_key_id=access_key_id,\n aws_secret_access_key=secret_access_key\n )\n return client","def add_client(name):\n return create_client(name)","def create_client(name):\n client = Client(name=name)\n print(client.client_secret)\n db.session.add(client)\n db.session.commit()\n return client","def make_client(service_key, constructor=None, options=None, **kwargs):\n cloud = get_config(service_key=service_key, options=options, **kwargs)\n if not constructor:\n constructor = cloud_config._get_client(service_key)\n return cloud.get_legacy_client(service_key, constructor)","def _create_service_client(self, srv_name):\n if self._srv:\n self._srv.close()\n\n if srv_name in rosservice.get_service_list():\n rospy.loginfo(\"Creating proxy for service '%s'\" % srv_name)\n self._srv = rospy.ServiceProxy(srv_name, rosservice.get_service_class_by_name(srv_name))","def create_client(self) -> None:\n self._client = gapic.JobServiceClient(\n client_options=dict(api_endpoint=self._region + _UCAIP_ENDPOINT_SUFFIX))","def create_client(\n body: ClientmodelClientCreateRequest,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n request = CreateClient.create(\n body=body,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","def createService(data):\n return Service(data).create()","def hello_svc_client():\n from clients.hello_svc import HelloServiceClient\n return HelloServiceClient()","def make_rest_client(\n service_key, options=None,\n app_name=None, app_version=None, version=None,\n **kwargs):\n cloud = get_config(\n service_key=service_key, options=options,\n app_name=app_name, app_version=app_version,\n **kwargs)\n return cloud.get_session_client(service_key, version=version)","def create_client(self) -> None:\n self._client = discovery.build('ml', 'v1')","def create_test_service(context, **kw):\n service = get_test_service(context, **kw)\n service.create()\n return service","def create_client(email, password):\n gd_client = gdata.contacts.service.ContactsService()\n gd_client.email = email\n gd_client.password = password\n gd_client.source = 'syncContacts'\n gd_client.ProgrammaticLogin()\n return gd_client","def create_service():\n creds = None\n # The file token.pickle stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n if os.path.exists('token.pickle'):\n with open('token.pickle', 'rb') as token:\n creds = pickle.load(token)\n # If there are no (valid) credentials available, let the user log in.\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file('credentials.json'\n , SCOPES)\n creds = flow.run_local_server(port=9797)\n # Save the credentials for the next run\n with open('token.pickle', 'wb') as token:\n pickle.dump(creds, token)\n\n service = build('drive', 'v3', credentials=creds)\n return service","def make_client(instance):\n network_client = utils.get_client_class(\n API_NAME,\n instance._api_version[API_NAME],\n API_VERSIONS)\n LOG.debug('Instantiating network client: %s', network_client)\n\n endpoint = instance.get_endpoint_for_service_type(\n API_NAME,\n region_name=instance._region_name,\n )\n\n return network_client(\n username=instance._username,\n tenant_name=instance._project_name,\n password=instance._password,\n region_name=instance._region_name,\n auth_url=instance._auth_url,\n endpoint_url=endpoint,\n token=instance.auth.get_token(instance.session),\n insecure=instance._insecure,\n ca_cert=instance._cacert,\n )","def create_service(self, service_name, *args, **kwargs):\n\n creator = self._service_creators.get(service_name, None)\n\n if creator is None:\n return None\n\n return creator(*args, **kwargs)","def make_client(self, context):\n return Client(self.settings['client_routing'], context=context)","def create_client_by_namespace(\n body: ClientmodelClientCreateRequest,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = CreateClientByNamespace.create(\n body=body,\n namespace=namespace,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","def CreateClient():\n client = gdata.docs.client.DocsClient(source=SampleConfig.APP_NAME)\n client.http_client.debug = SampleConfig.DEBUG\n # Authenticate the user with CLientLogin, OAuth, or AuthSub.\n try:\n gdata.sample_util.authorize_client(\n client,\n service=client.auth_service,\n source=client.source,\n scopes=client.auth_scopes\n )\n except gdata.client.BadAuthentication:\n exit('Invalid user credentials given.')\n except gdata.client.Error:\n exit('Login Error')\n return client","def create_service(self, service_id, service_ref):\n raise exception.NotImplemented() # pragma: no cover","def create_service(service, version, creds=None):\n # Instantiate an Http instance\n http = httplib2.Http()\n\n if creds:\n # Authorize the Http instance with the passed credentials\n creds.authorize(http)\n\n return build(service, version, http=http)","def test_create_client(self):\n pass","def create_service(flags, client_id, client_secret):\n flow = OAuth2WebServerFlow(\n client_id=client_id,\n client_secret=client_secret,\n scope='https://www.googleapis.com/auth/drive.readonly',\n redirect_uri='http://localhost')\n storage = Storage('oauth_storage')\n credentials = tools.run_flow(flow, storage, flags)\n http = credentials.authorize(httplib2.Http())\n return build('drive', 'v2', http=http)","def create_client(self, module_name, version, client_class):\n # NOTE(kiennt): Get created client rather create a new one.\n # The key is the combination of module_name and version.\n # because we can create multiple clients of a module with\n # different versions.\n client = self.created_clients.get(module_name + version)\n if client:\n return client\n module_client = self._import_client(module_name)\n try:\n client = getattr(module_client, client_class)(\n version=version,\n session=self._sess)\n self.created_clients[module_name+version] = client\n return client\n except Exception as err:\n raise err","def client(\n service_name: str, version: str = \"v1\", secrets: Secrets = None\n) -> Resource:\n credentials = load_credentials(secrets=secrets)\n return build(service_name, version=version, credentials=credentials)","async def create_client_by_namespace_async(\n body: ClientmodelClientCreateRequest,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = CreateClientByNamespace.create(\n body=body,\n namespace=namespace,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )","def create_service(cls, proto_py_module, service_name):\n\n return cls.create_services(proto_py_module, service_name)","def create_client(self, initiator_iqn):\n client = self._get_target_client(initiator_iqn)\n if not client:\n try:\n self.client.create_client(self.target_iqn,\n initiator_iqn)\n except client_exceptions.ClientException as ex:\n raise exception.VolumeBackendAPIException(\n data=ex.get_description())","def client():\n\n client = Client()\n return client","def serviceClient(self, iTag, srvType, addr):\r\n return ROSServiceClient(self, iTag, srvType, addr)","async def api_create_service(\n data: CreateService, wallet: WalletTypeInfo = Depends(get_key_type)\n):\n try:\n service = await create_service(data=data)\n except Exception as e:\n raise HTTPException(status_code=HTTPStatus.INTERNAL_SERVER_ERROR, detail=str(e))\n\n return service.dict()","def create_generated_client() -> None:\n print(\"Generating client\")\n\n delete_generated_client()\n args = [\n \"{}/../scripts/generate.sh\".format(ROOT),\n \"-i\",\n \"http://localhost:8000/openapi.json\",\n \"-p\",\n CLIENT_NAME,\n \"--include-auth\",\n \"-o\",\n ROOT,\n \"-t\",\n \"/tmp\",\n \"-m\",\n ]\n\n process_result = subprocess.run(args, capture_output=True)\n\n with open(os.path.join(LOG_DIR, \"generation.log\"), \"wb\") as file:\n file.write(process_result.stdout)\n\n with open(os.path.join(LOG_DIR, \"generation.err\"), \"wb\") as file:\n file.write(process_result.stderr)\n\n if process_result.returncode != 0: # pragma: no cover\n if process_result.stderr:\n sys.stderr.write(process_result.stderr.decode(\"utf-8\"))\n pytest.exit(\n \"Failed to generate client api, code {}\"\n \"\\nLogs are in logs/generation.log and logs/generation.err\".format(process_result.returncode),\n returncode=process_result.returncode,\n )\n\n print(\"Client created in {}, logs in logs/generation.log\\n\".format(CLIENT_DIR))","def _create_client(p4, client_name, p4gf_dir):\n view = ['//{depot}/... //{client}/...'.format(depot=p4gf_const.P4GF_DEPOT,\n client=client_name)]\n spec_created = False\n if not p4gf_util.spec_exists(p4, \"client\", client_name):\n # See if the old object clients exist, in which case we will remove them.\n if p4gf_util.spec_exists(p4, \"client\", OLD_OBJECT_CLIENT):\n p4.run('client', '-df', OLD_OBJECT_CLIENT)\n if p4gf_util.spec_exists(p4, \"client\", OLDER_OBJECT_CLIENT):\n p4.run('client', '-df', OLDER_OBJECT_CLIENT)\n spec_created = p4gf_util.ensure_spec(\n p4, \"client\", spec_id=client_name,\n values={'Host': None, 'Root': p4gf_dir,\n 'Description': 'Created by Perforce Git Fusion',\n 'View': view})\n if not spec_created:\n p4gf_util.ensure_spec_values(p4, \"client\", client_name,\n {'Root': p4gf_dir, 'View': view})","def service_create(service, service_type, api, endpoint):\n db = model.Session()\n _assert_absent(db, model.Service, service)\n api = _must_find(db, model.API, api)\n service = model.Service(service, service_type, api, endpoint)\n db.add(service)\n db.commit()","def create_client():\n logger.debug(\"=====create_client fired...\")\n try:\n session = boto3.Session()\n client = session.client('dynamodb', region_name='us-east-1')\n return client\n except ClientError as err:\n logger.error(\n \"[BOTO3_ERROR]Failed to create boto3 client: %s\", str(err))","def create_client(client_id, authority_url, client_secret):\n client = msal.ConfidentialClientApplication(\n client_id=client_id, authority=authority_url, client_credential=client_secret\n )\n return client","def create_service():\n creds = None\n # The file token_sheet.pickle stores the user's access and refresh tokens, and is\n # created automatically when the authorization flow completes for the first\n # time.\n if os.path.exists('token_sheet.pickle'):\n with open('token_sheet.pickle', 'rb') as token:\n creds = pickle.load(token)\n # If there are no (valid) credentials available, let the user log in.\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n 'credentials_sheets.json', SCOPES)\n creds = flow.run_local_server(port=0)\n # Save the credentials for the next run\n with open('token_sheet.pickle', 'wb') as token:\n pickle.dump(creds, token)\n\n service = build('sheets', 'v4', credentials=creds)\n return service","async def create_client_async(\n body: ClientmodelClientCreateRequest,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n request = CreateClient.create(\n body=body,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )","def create_boto3_client(config, service):\n session = boto3.Session(profile_name=config.get('AWS_ACCESS', 'AWS_PROFILE'))\n return session.client(service, region_name=config.get('AWS_ACCESS', 'AWS_REGION'))","def create_client(name: str, url: str, description: str, scopes: str,\n redirect_uri: str) -> None:\n app = create_web_app()\n with app.app_context():\n datastore.create_all()\n\n with datastore.util.transaction() as session:\n db_client = datastore.models.DBClient(\n name=name,\n url=url,\n description=description,\n redirect_uri=redirect_uri\n )\n secret = generate_token(48)\n hashed = hashlib.sha256(secret.encode('utf-8')).hexdigest()\n db_cred = datastore.models.DBClientCredential(client=db_client,\n client_secret=hashed)\n db_scopes = [\n datastore.models.DBClientAuthorization(\n client=db_client, authorized=datetime.now(), scope=scope\n ) for scope in scopes.split()\n ]\n db_grant_type = datastore.models.DBClientGrantType(\n client=db_client,\n grant_type='client_credentials',\n authorized=datetime.now()\n )\n db_grant_type = datastore.models.DBClientGrantType(\n client=db_client,\n grant_type='authorization_code',\n authorized=datetime.now()\n )\n\n session.add(db_client)\n session.add(db_cred)\n session.add(db_grant_type)\n for db_scope in db_scopes:\n session.add(db_scope)\n\n session.commit()\n click.echo(f'Created client {name} with ID {db_client.client_id}'\n f' and secret {secret}')","def boto_client(account_id, service_name, region):\n logger.info('Creating boto3 client for account_id: {}, '\n 'service_name: {}'.format(account_id, service_name))\n return boto3.client(service_name, region_name=region)","def _establish_client():\n logger.debug('SoapService - _establish_client()')\n try:\n client = zeep.Client(wsdl=settings.WSDL)\n except Exception as e:\n message = 'Unable to create soap client from wsdl file, error: {}'.format(e)\n logger.error(message)\n raise IOError(message)\n\n return client","def create_resource(\n service_name: str, config_name: str = None, **resource_args\n):\n session = get_session(config_name)\n return session.resource(service_name, **resource_args)","def create_client():\n result = False\n if g.client_id in drivers:\n result = True\n return jsonify({'Success': result})","def new_instance(cls,\n version: date,\n service_name: str = DEFAULT_SERVICE_NAME,\n ) -> 'DirectLinkApisV1':\n if version is None:\n raise ValueError('version must be provided')\n\n authenticator = get_authenticator_from_environment(service_name)\n service = cls(\n version,\n authenticator\n )\n service.configure_service(service_name)\n return service","def client(service_name, region_name=None):\n return session.client(service_name=service_name, region_name=region_name)","def serviceClient(self, iTag, srvType, cb=None):\r\n if cb and not callable(cb):\r\n raise TypeError('Callback has to be callable.')\r\n\r\n return ServiceClient(self, iTag, srvType, cb)","def _create_soap_object(self, name):\n return self.client.factory.create(name)","def service_create(path, service_name, definition):\n compose_result, loaded_definition, err = __load_compose_definitions(\n path, definition\n )\n if err:\n return err\n services = compose_result[\"compose_content\"][\"services\"]\n if service_name in services:\n msg = \"Service {} already exists\".format(service_name)\n return __standardize_result(False, msg, None, None)\n services[service_name] = loaded_definition\n return __dump_compose_file(\n path,\n compose_result,\n \"Service {} created\".format(service_name),\n already_existed=True,\n )","def createClient(self, name, wid, notes=None):\n\n data = {}\n data['client'] = {}\n data['client']['name'] = name\n data['client']['wid'] = wid\n data['client']['notes'] = notes\n\n response = self.postRequest(Endpoints.CLIENTS, parameters=data)\n return self.decodeJSON(response)","def create(self):\n\t\treturn handle_to_object(call_sdk_function('PrlSrv_Create'))","def create_dummy_client(index, user, client_manager = None, language = None, currency = None):\r\n \r\n if client_manager == None:\r\n client_manager = ClientManager(user)\r\n \r\n if currency is None:\r\n currency = create_dummy_currency(index)\r\n \r\n if language is None:\r\n language = create_dummy_language(index)\r\n \r\n return client_manager.add_client(\r\n name = 'client_%i' %index,\r\n address = 'address_%i' % index,\r\n email = 'corp_email_%i@email.com' % index,\r\n default_currency_id = currency.key().id(),\r\n default_language_id = language.key().id(),\r\n )","def create_client(name):\n address = \"/run/com_handler.sock\"\n sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)\n sock.connect(address)\n return Client(sock, \"\", name)","def create_client(self, version=None, unstable=False, **kwargs):\n version_data = self._calculate_version(version, unstable)\n return self._create_client(version_data, **kwargs)","def create_servicech(self, conf, params):\n\t\tpass","def create_client():\n hostname = \"localhost\"\n username = \"she393\"\n password = os.getenv(\"PASSWORD\")\n\n client = paramiko.SSHClient()\n client.set_missing_host_key_policy(paramiko.AutoAddPolicy())\n client.connect(hostname=hostname, username=username, password=password)\n return client","def test_client_create(self):\n pass","def new(\n cls,\n name: str,\n description: str,\n registration_schema: JSON,\n result_schema: JSON,\n database_session: Session) -> 'Service':\n raise NotImplementedError()","def create_service(self, url_data):\n data = {key: value[0] for key, value in url_data}\n\n publish_key = uuid.uuid4().hex\n service_id = uuid.uuid4().hex\n service_name = data['name']\n\n self.fastly_cache[service_name] = {\n 'service_details': {\n u'comment': '',\n u'locked': False,\n u'updated_at': u'2014-11-13T14:29:10+00:00',\n u'created_at': u'2014-11-13T14:29:10+00:00',\n u'testing': None,\n u'number': 1,\n u'staging': None,\n u'active': None,\n u'service_id': service_id,\n u'deleted_at': None,\n u'inherit_service_id': None,\n u'deployed': None},\n 'service_name': service_name\n }\n self.fastly_cache[service_id] = self.fastly_cache[service_name]\n\n create_service = {\n u'comment': '',\n u'publish_key': publish_key,\n u'name': service_name,\n u'versions': [{u'comment': '', u'locked': u'0',\n u'service': service_id,\n u'updated_at': u'2014-11-12T18:43:21',\n u'created_at': u'2014-11-12T18:43:21',\n u'testing': None, u'number': u'1',\n u'staging': None,\n u'active': None,\n u'service_id': service_id,\n u'deleted_at': None,\n u'inherit_service_id': None,\n u'deployed': None,\n u'backend': 0}],\n u'created_at': u'2014-11-12T18:43:21+00:00',\n u'updated_at': u'2014-11-12T18:43:21+00:00',\n u'customer_id': data['customer_id'],\n u'id': service_id}\n return create_service","def build_service():\n\n\tstore = file.Storage('credentials.json')\n\tcreds = store.get()\n\tif not creds or creds.invalid:\n\t flow = client.flow_from_clientsecrets('client_secret.json', SCOPES)\n\t creds = tools.run_flow(flow, store)\n\tservice = build('gmail', 'v1', http=creds.authorize(Http(disable_ssl_certificate_validation=True)))\n\treturn service","def create():\n form = request.form\n try:\n # create a new BancBox client from the input form\n resp = api.create_client(form)\n except Exception, e:\n logger.error('Error creating new client: %s', e)\n return render_template('created.html', error=e.message)\n\n if resp.status == 1:\n # If the create request was successful, let's render a success\n # message with some data about the new client and a link to the\n # detail page\n new_client = {\n 'firstName': form['firstName'],\n 'lastName': form['lastName'],\n 'clientId': resp.clientId\n }\n return render_template('created.html', new_client=new_client)\n else:\n # If an error was returned by BancBox, let's render it\n if hasattr(resp, 'errors') and hasattr(resp.errors, 'message'):\n message = resp.errors.message\n else:\n message = \"Error creating new client.\"\n return render_template('created.html', error=message)","def create_client(self):\n client = iperf3.Client()\n client.duration = self._host[CONF_DURATION]\n client.server_hostname = self._host[CONF_HOST]\n client.port = self._host[CONF_PORT]\n client.num_streams = self._host[CONF_PARALLEL]\n client.protocol = self._host[CONF_PROTOCOL]\n client.verbose = False\n return client","def make_client(instance):\r\n neutron_client = utils.get_client_class(\r\n API_NAME,\r\n instance._api_version[API_NAME],\r\n API_VERSIONS,\r\n )\r\n instance.initialize()\r\n url = instance._url\r\n url = url.rstrip(\"/\")\r\n if '2.0' == instance._api_version[API_NAME]:\r\n client = neutron_client(username=instance._username,\r\n tenant_name=instance._tenant_name,\r\n password=instance._password,\r\n region_name=instance._region_name,\r\n auth_url=instance._auth_url,\r\n endpoint_url=url,\r\n token=instance._token,\r\n auth_strategy=instance._auth_strategy,\r\n insecure=instance._insecure,\r\n ca_cert=instance._ca_cert)\r\n return client\r\n else:\r\n raise exceptions.UnsupportedVersion(_(\"API version %s is not \"\r\n \"supported\") %\r\n instance._api_version[API_NAME])","def get_client(service_account_json):\n api_scopes = ['https://www.googleapis.com/auth/cloud-platform']\n api_version = 'v1'\n discovery_api = 'https://cloudiot.googleapis.com/$discovery/rest'\n service_name = 'cloudiotcore'\n\n credentials = service_account.Credentials.from_service_account_file(\n service_account_json)\n scoped_credentials = credentials.with_scopes(api_scopes)\n\n discovery_url = '{}?version={}'.format(\n discovery_api, api_version)\n\n return discovery.build(\n service_name,\n api_version,\n discoveryServiceUrl=discovery_url,\n credentials=scoped_credentials)","def create_TestService(test_case, # type: AnyMagpieTestCaseType\n override_service_name=null, # type: Optional[Str]\n override_service_type=null, # type: Optional[Str]\n override_headers=null, # type: Optional[HeadersType]\n override_cookies=null, # type: Optional[CookiesType]\n ): # type: (...) -> JSON\n app_or_url = get_app_or_url(test_case)\n svc_name = override_service_name if override_service_name is not null else test_case.test_service_name\n svc_type = override_service_type if override_service_type is not null else test_case.test_service_type\n data = {\n \"service_name\": svc_name,\n \"service_type\": svc_type,\n \"service_url\": \"http://localhost:9000/{}\".format(svc_name)\n }\n if svc_name:\n test_case.extra_service_names.add(svc_name) # indicate potential removal at a later point\n resp = test_request(app_or_url, \"POST\", \"/services\", json=data,\n headers=override_headers if override_headers is not null else test_case.json_headers,\n cookies=override_cookies if override_cookies is not null else test_case.cookies,\n expect_errors=True)\n if resp.status_code == 409:\n path = \"/services/{svc}\".format(svc=svc_name)\n resp = test_request(app_or_url, \"GET\", path,\n headers=override_headers if override_headers is not null else test_case.json_headers,\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\n body = check_response_basic_info(resp, 200, expected_method=\"GET\")\n if TestVersion(test_case.version) < TestVersion(\"0.9.1\"):\n body.update({\"service\": body[svc_name]})\n body.pop(svc_name)\n return body\n return check_response_basic_info(resp, 201, expected_method=\"POST\")","def create_client(wsdl: str, raw_response: bool = True) -> CachingClient:\n # We want the raw response as there is an error when Zeep parses the XML\n settings: Settings = Settings(raw_response=raw_response)\n\n # Client that caches the WSDL\n client: CachingClient = CachingClient(\n wsdl=wsdl,\n # TODO: Store PW encrypted\n wsse=UsernameToken(\"n00394gz\", \"g427Ix19LMB\"),\n settings=settings,\n )\n logger.debug(f\"Client created\")\n\n return client","def create_service_object(credentials):\n http_auth = httplib2.Http()\n http_auth = credentials.authorize(http_auth)\n service = discovery.build('analytics', 'v3', http=http_auth)\n return service","def create_service(self, project_id, auth_token, service_json):\n try:\n flavor = self.flavor_controller.get(service_json.get('flavor_id'))\n # raise a lookup error if the flavor is not found\n except LookupError as e:\n raise e\n\n # add any default rules so its explicitly defined\n self._append_defaults(service_json, operation='create')\n\n # convert to an object\n service_obj = service.Service.init_from_dict(project_id, service_json)\n service_id = service_obj.service_id\n\n # validate the service\n service_json = service_obj.to_dict()\n schema = service_schema.ServiceSchema.get_schema(\"service\", \"POST\")\n validators.is_valid_service_configuration(service_json, schema)\n\n service_limit = self.storage_controller.get_service_limit(project_id)\n service_count = self.storage_controller.get_service_count(project_id)\n\n services_delete_in_progress = self.storage_controller.\\\n get_services_by_status('delete_in_progress')\n\n services_delete_count = len(services_delete_in_progress)\n\n # Check that the number of deleted services is less\n # than the total number of existing services for the project.\n # Adjust the service count removing delete_in_progress\n # services.\n service_count -= (\n services_delete_count\n if 0 < services_delete_count < service_count else 0\n )\n # service_count should always be a >= 0.\n\n if service_count >= service_limit:\n raise errors.ServicesOverLimit('Maximum Services '\n 'Limit of {0} '\n 'reached!'.format(service_limit))\n\n if any([domain for domain in service_obj.domains\n if domain.certificate == \"shared\"]):\n try:\n store = str(uuid.uuid4()).replace('-', '_')\n service_obj = self._shard_retry(project_id,\n service_obj,\n store=store)\n except errors.SharedShardsExhausted as e:\n raise e\n except ValueError as e:\n raise e\n\n try:\n self.storage_controller.create_service(project_id, service_obj)\n except ValueError as e:\n raise e\n\n providers = [p.provider_id for p in flavor.providers]\n kwargs = {\n 'providers_list_json': json.dumps(providers),\n 'project_id': project_id,\n 'auth_token': auth_token,\n 'service_id': service_id,\n 'time_seconds': self.determine_sleep_times(),\n 'context_dict': context_utils.get_current().to_dict()\n }\n\n self.distributed_task_controller.submit_task(\n create_service.create_service, **kwargs)\n\n return service_obj","def _get_client(self):\n credentials = service_account.Credentials.from_service_account_info(self.service_account_info)\n client = googleapiclient.discovery.build('container', 'v1', credentials=credentials)\n\n return client","def client(db):\n client = ClientFactory()\n db.session.commit()\n return client","def create_client():\n host_api_id = Config.api_id\n host_api_hash = Config.api_hash\n host_user_id = Config.user_id\n host_phone = Config.phone\n\n client = TelegramClient(host_user_id, host_api_id, host_api_hash)\n client.connect()\n if not client.is_user_authorized():\n client.send_code_request(host_phone)\n client.sign_in(host_phone, input('Enter code sent to your telegram: '))\n return client","def gen_nova_client(self):\n\n print \"\\t* Generating nova client\"\n client = nClient.get_client_class('2')\n self.novaclient = client(self.username,\n self.password,\n self.tenant_name,\n self.auth_url,\n service_type='compute')","def client():\n return Client(**common_data.AUTH_ARGS)","def __init__(self, service, acces_key, secret_key):\n \n self.client = boto3.client(\n service,\n aws_access_key_id=acces_key,\n aws_secret_access_key=secret_key,\n )","def create_client(access_key_id, secret_access_key):\r\n client = boto3.client('s3',\r\n aws_access_key_id=access_key_id,\r\n aws_secret_access_key=secret_access_key)\r\n return client","def _init_http_client(service_id=None, opts=None):\n if service_id:\n opts = _get_trs_opts(service_id)\n\n http_client = RequestsClient()\n\n http_client.set_api_key(host=opts['host'],\n api_key=opts['auth'],\n param_in='header')\n return http_client","def service_client_initialization(self) -> global___Snippet.ClientInitialization:","def test_client_create(self, mock_input, mock_pass):\n # Patch username and password.\n mock_input.return_value = \"user\"\n mock_pass.return_value = \"pass\"\n\n # Instantiate Agave object making reference to local mock server.\n local_uri = \"http://localhost:{port}/\".format(port=self.mock_server_port)\n ag = Agave(api_server=local_uri)\n\n # Create client.\n ag.clients_create(\"client-name\", \"some description\")\n\n assert ag.api_key == \"some api key\"\n assert ag.api_secret == \"some secret\"","def create_new_client(main: MainApplication) -> str:\n client = main.create_window(\"client\", \"IPLMS\", main.client_ui.get_layout())\n client[\"_CLIENT_ID_\"].Update(getUUID())\n client[\"_CP_NAME_IP_\"].Update(\"\")\n client[\"_CP_PHONE_IP_\"].Update(\"\")\n client[\"_CP_ADDRESS_IP_\"].Update(\"\")\n client.un_hide()\n event, values = client.read()\n client_logic = Client(main, event, values)\n name = client_logic.run(main)\n client.hide()\n return name","def _CreatePubsubClient():\n client = pubsub_client.PubSubClient()\n client.CreateTopic(DEVICE_NOTE_PUBSUB_TOPIC)\n client.CreateTopic(HOST_NOTE_PUBSUB_TOPIC)\n return client","def get_service(api_name, api_version, scope, client_secrets_path):\n # Parse command-line arguments.\n parser = argparse.ArgumentParser(\n formatter_class=argparse.RawDescriptionHelpFormatter,\n parents=[tools.argparser])\n flags = parser.parse_args([])\n\n # Set up a Flow object to be used if we need to authenticate.\n flow = client.flow_from_clientsecrets(\n client_secrets_path, scope=scope,\n message=tools.message_if_missing(client_secrets_path))\n\n # Prepare credentials, and authorize HTTP object with them.\n # If the credentials don't exist or are invalid run through the native client\n # flow. The Storage object will ensure that if successful the good\n # credentials will get written back to a file.\n storage = file.Storage(api_name + '.dat')\n credentials = storage.get()\n if credentials is None or credentials.invalid:\n credentials = tools.run_flow(flow, storage, flags)\n http = credentials.authorize(http=httplib2.Http())\n\n # Build the service object.\n service = build(api_name, api_version, http=http)\n\n return service","def create_clients(aws_key, aws_secret):\n ec2_client = boto3.resource(\n 'ec2', region_name=AWS_REGION, aws_access_key_id=aws_key,\n aws_secret_access_key=aws_secret\n )\n s3_client = boto3.resource(\n 's3', region_name=AWS_REGION, aws_access_key_id=aws_key,\n aws_secret_access_key=aws_secret\n )\n iam_client = boto3.client(\n 'iam', region_name=AWS_REGION, aws_access_key_id=aws_key,\n aws_secret_access_key=aws_secret\n )\n redshift_client = boto3.client(\n 'redshift', region_name=AWS_REGION, aws_access_key_id=aws_key,\n aws_secret_access_key=aws_secret\n )\n return ec2_client, s3_client, iam_client, redshift_client","def _client(self):\n\n if self._suds_client is None:\n self._suds_client = suds.client.Client(SERVICE_WSDL_URL)\n # Add SOAP Security tokens\n self.set_security_token()\n\n return self._suds_client","def get_client():\n return Client(__address, authkey='strumamor')","def create_clients(client_name): # Crear nuevo Cliente\n global clients\n\n if client_name not in clients:\n clients.append(client_name)\n else:\n print('The client name is alredy in the client\\'s list')","def newClient(self, cid, **kwargs):\n client = Iourt42Client(console=self.console, cid=cid, timeAdd=self.console.time(), **kwargs)\n self[client.cid] = client\n self.resetIndex()\n\n self.console.debug('Urt42 Client Connected: [%s] %s - %s (%s)', self[client.cid].cid, self[client.cid].name,\n self[client.cid].guid, self[client.cid].data)\n\n self.console.queueEvent(self.console.getEvent('EVT_CLIENT_CONNECT', data=client, client=client))\n\n if client.guid:\n client.auth()\n elif not client.authed:\n self.authorizeClients()\n return client","def create(cls, client, fields, **kwargs):\n\t\tres = cls(client, fields, **kwargs)\n\t\treturn res","def newSDDCService(**kwargs):\n # Test for interactive flag - if False, check to ensure additional arguments were give for service entry\n if kwargs['interactive'] is False and (kwargs['l4_protocol'] is None or kwargs['dest_ports'] is None):\n print(\"Error - if not using interactive mode, at least protocol and destination port(s) must be configured. Source port(s) optional, based on your application.\")\n sys.exit(1)\n elif kwargs['interactive'] is True and (kwargs['l4_protocol'] is not None or kwargs['dest_ports'] is not None or kwargs['source_ports'] is not None):\n print(\"Error - if using interactive mode, please only specify the name of the desired service. All other parameters will be obtained interactively.\")\n sys.exit(1)\n else:\n pass\n proxy = kwargs['proxy']\n sessiontoken = kwargs['sessiontoken']\n service_id = kwargs['objectname']\n interactive = kwargs['interactive']\n\n if interactive == True:\n service_entry_list = []\n # Start a loop that will run until the user enters 'quit'.\n # Ask the user for a name.\n destination_port = \"\"\n while destination_port != 'done':\n destination_port_list = []\n source_port_list = []\n service_entry_id = input(\"Please enter the Service Entry ID:\")\n l4_protocol = input(\"Please enter the L4 Protocol:\")\n source_port = \"\"\n destination_port = \"\"\n while source_port != 'done':\n source_port = input(\"Plese enter the Source Ports or type 'done' when your list is finished:\")\n if source_port != \"done\":\n source_port_list.append(source_port)\n while (destination_port != 'next') and (destination_port != \"done\"):\n source_port = \"\"\n destination_port = input(\"Plese enter the Destination Ports, type 'next' when you want to define another service entry or 'done' if you have finished:\")\n if (destination_port != 'next') and (destination_port != \"done\"):\n destination_port_list.append(destination_port)\n service_entry = {\n \"l4_protocol\": l4_protocol,\n \"source_ports\": source_port_list,\n \"destination_ports\" : destination_port_list,\n \"resource_type\" : \"L4PortSetServiceEntry\",\n \"id\" : service_entry_id,\n \"display_name\" : service_entry_id }\n service_entry_list.append(service_entry)\n else:\n source_port_list = kwargs['source_ports']\n destination_port_list = kwargs['dest_ports']\n l4_protocol = kwargs['l4_protocol']\n service_entry_list = [\n {\n \"l4_protocol\": l4_protocol,\n \"source_ports\": source_port_list,\n \"destination_ports\": destination_port_list,\n \"resource_type\": \"L4PortSetServiceEntry\",\n \"display_name\": f'{service_id}_svc_entry'\n }\n ]\n json_data = {\n \"service_entries\":service_entry_list,\n \"id\" : service_id,\n \"display_name\" : service_id,\n }\n response = new_sddc_service_json(proxy,sessiontoken,service_id,json_data)\n if response == 200:\n print(f'Service {service_id} successfully updated.')\n params = {'proxy':proxy, 'sessiontoken':sessiontoken, 'objectname':service_id}\n getSDDCService(**params)\n else:\n print(\"Issues creating the service - please check your syntax and try again.\")\n sys.exit(1)","def post(self, ws_id, project_id):\n service = servicesimpl.create_service(ws_id, project_id, get_json(request))\n return prepare_response(service, 201)","def get_service(\n service_name: str,\n version: str = \"v1\",\n configuration: Configuration = None,\n secrets: Secrets = None,\n) -> Resource:\n return client(service_name, version=version, secrets=secrets)","def client_setup(self):\n self.client = Client()","def create_api_client(base_path, access_token):\n api_client = ApiClient()\n api_client.host = base_path\n api_client.set_default_header(header_name=\"Authorization\",\n header_value=f\"Bearer {access_token}\")\n return api_client","def gen_neutron_client(self):\n\n print \"\\t* Generating neutron client\"\n self.neutronclient = neutronclient.Client(auth_url=self.auth_url,\n username=self.username,\n password=self.password,\n tenant_name=self.tenant_name,\n region_name=self.region_name)","def create_services(cls, proto_py_module, *service_names):\n\n return cls(proto_py_module, *service_names).services","def make_client(db, hdfs_client=None):\n return ImpalaClient(db, hdfs_client=hdfs_client)","def build_service():\n creds = None\n\n # the file token.json stores the user's access and refresh tokens, and is \n # created automatically when the authorization flow completes for the first time\n \n if os.path.exists('../creds/token.json'):\n creds = Credentials.from_authorized_user_file('../creds/token.json', SCOPES)\n\n # if there are no (valid) credentials, ask the user to login\n if not creds or not creds.valid:\n if creds and creds.expired and creds.refresh_token:\n creds.refresh(Request())\n else:\n flow = InstalledAppFlow.from_client_secrets_file(\n '../creds/credentials.json', SCOPES)\n creds = flow.run_local_server(port=0)\n with open('../creds/token.json', 'w') as token:\n token.write(creds.to_json())\n\n service = build('drive', 'v3', credentials=creds)\n return service"],"string":"[\n \"def create_client(service_name: str, config_name: str = None, **client_args):\\n session = get_session(config_name)\\n return session.client(service_name, **client_args)\",\n \"def create_client(self) -> None:\\n pass\",\n \"def create(ctx, name, company, mail, age):\\n client = Client(name,company,mail,age)\\n client_service = ClientService(ctx.obj['clients_table']) \\n client_service.create_client(client)\",\n \"def make_service(self, endpoint_type, service_name, **client_kwargs):\\n binding = self._make_binding(endpoint_type, service_name)\\n service_cache_key = (binding, str(client_kwargs))\\n\\n if service_cache_key in self._service_cache:\\n srvc = self._service_cache[service_cache_key]\\n else:\\n client = self._make_client(\\n endpoint_type,\\n service_name,\\n **client_kwargs\\n )\\n srvc = client.create_service(binding, client.wsdl.location)\\n self._service_cache[service_cache_key] = srvc\\n return srvc\",\n \"def create_client(service, region, access_key_id, secret_access_key):\\n client = boto3.client(service,\\n region_name=region,\\n aws_access_key_id=access_key_id,\\n aws_secret_access_key=secret_access_key\\n )\\n return client\",\n \"def create_client(service, region, access_key_id, secret_access_key):\\n client = boto3.client(service,\\n region_name=region,\\n aws_access_key_id=access_key_id,\\n aws_secret_access_key=secret_access_key\\n )\\n return client\",\n \"def add_client(name):\\n return create_client(name)\",\n \"def create_client(name):\\n client = Client(name=name)\\n print(client.client_secret)\\n db.session.add(client)\\n db.session.commit()\\n return client\",\n \"def make_client(service_key, constructor=None, options=None, **kwargs):\\n cloud = get_config(service_key=service_key, options=options, **kwargs)\\n if not constructor:\\n constructor = cloud_config._get_client(service_key)\\n return cloud.get_legacy_client(service_key, constructor)\",\n \"def _create_service_client(self, srv_name):\\n if self._srv:\\n self._srv.close()\\n\\n if srv_name in rosservice.get_service_list():\\n rospy.loginfo(\\\"Creating proxy for service '%s'\\\" % srv_name)\\n self._srv = rospy.ServiceProxy(srv_name, rosservice.get_service_class_by_name(srv_name))\",\n \"def create_client(self) -> None:\\n self._client = gapic.JobServiceClient(\\n client_options=dict(api_endpoint=self._region + _UCAIP_ENDPOINT_SUFFIX))\",\n \"def create_client(\\n body: ClientmodelClientCreateRequest,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n request = CreateClient.create(\\n body=body,\\n )\\n return run_request(request, additional_headers=x_additional_headers, **kwargs)\",\n \"def createService(data):\\n return Service(data).create()\",\n \"def hello_svc_client():\\n from clients.hello_svc import HelloServiceClient\\n return HelloServiceClient()\",\n \"def make_rest_client(\\n service_key, options=None,\\n app_name=None, app_version=None, version=None,\\n **kwargs):\\n cloud = get_config(\\n service_key=service_key, options=options,\\n app_name=app_name, app_version=app_version,\\n **kwargs)\\n return cloud.get_session_client(service_key, version=version)\",\n \"def create_client(self) -> None:\\n self._client = discovery.build('ml', 'v1')\",\n \"def create_test_service(context, **kw):\\n service = get_test_service(context, **kw)\\n service.create()\\n return service\",\n \"def create_client(email, password):\\n gd_client = gdata.contacts.service.ContactsService()\\n gd_client.email = email\\n gd_client.password = password\\n gd_client.source = 'syncContacts'\\n gd_client.ProgrammaticLogin()\\n return gd_client\",\n \"def create_service():\\n creds = None\\n # The file token.pickle stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n if os.path.exists('token.pickle'):\\n with open('token.pickle', 'rb') as token:\\n creds = pickle.load(token)\\n # If there are no (valid) credentials available, let the user log in.\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file('credentials.json'\\n , SCOPES)\\n creds = flow.run_local_server(port=9797)\\n # Save the credentials for the next run\\n with open('token.pickle', 'wb') as token:\\n pickle.dump(creds, token)\\n\\n service = build('drive', 'v3', credentials=creds)\\n return service\",\n \"def make_client(instance):\\n network_client = utils.get_client_class(\\n API_NAME,\\n instance._api_version[API_NAME],\\n API_VERSIONS)\\n LOG.debug('Instantiating network client: %s', network_client)\\n\\n endpoint = instance.get_endpoint_for_service_type(\\n API_NAME,\\n region_name=instance._region_name,\\n )\\n\\n return network_client(\\n username=instance._username,\\n tenant_name=instance._project_name,\\n password=instance._password,\\n region_name=instance._region_name,\\n auth_url=instance._auth_url,\\n endpoint_url=endpoint,\\n token=instance.auth.get_token(instance.session),\\n insecure=instance._insecure,\\n ca_cert=instance._cacert,\\n )\",\n \"def create_service(self, service_name, *args, **kwargs):\\n\\n creator = self._service_creators.get(service_name, None)\\n\\n if creator is None:\\n return None\\n\\n return creator(*args, **kwargs)\",\n \"def make_client(self, context):\\n return Client(self.settings['client_routing'], context=context)\",\n \"def create_client_by_namespace(\\n body: ClientmodelClientCreateRequest,\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = CreateClientByNamespace.create(\\n body=body,\\n namespace=namespace,\\n )\\n return run_request(request, additional_headers=x_additional_headers, **kwargs)\",\n \"def CreateClient():\\n client = gdata.docs.client.DocsClient(source=SampleConfig.APP_NAME)\\n client.http_client.debug = SampleConfig.DEBUG\\n # Authenticate the user with CLientLogin, OAuth, or AuthSub.\\n try:\\n gdata.sample_util.authorize_client(\\n client,\\n service=client.auth_service,\\n source=client.source,\\n scopes=client.auth_scopes\\n )\\n except gdata.client.BadAuthentication:\\n exit('Invalid user credentials given.')\\n except gdata.client.Error:\\n exit('Login Error')\\n return client\",\n \"def create_service(self, service_id, service_ref):\\n raise exception.NotImplemented() # pragma: no cover\",\n \"def create_service(service, version, creds=None):\\n # Instantiate an Http instance\\n http = httplib2.Http()\\n\\n if creds:\\n # Authorize the Http instance with the passed credentials\\n creds.authorize(http)\\n\\n return build(service, version, http=http)\",\n \"def test_create_client(self):\\n pass\",\n \"def create_service(flags, client_id, client_secret):\\n flow = OAuth2WebServerFlow(\\n client_id=client_id,\\n client_secret=client_secret,\\n scope='https://www.googleapis.com/auth/drive.readonly',\\n redirect_uri='http://localhost')\\n storage = Storage('oauth_storage')\\n credentials = tools.run_flow(flow, storage, flags)\\n http = credentials.authorize(httplib2.Http())\\n return build('drive', 'v2', http=http)\",\n \"def create_client(self, module_name, version, client_class):\\n # NOTE(kiennt): Get created client rather create a new one.\\n # The key is the combination of module_name and version.\\n # because we can create multiple clients of a module with\\n # different versions.\\n client = self.created_clients.get(module_name + version)\\n if client:\\n return client\\n module_client = self._import_client(module_name)\\n try:\\n client = getattr(module_client, client_class)(\\n version=version,\\n session=self._sess)\\n self.created_clients[module_name+version] = client\\n return client\\n except Exception as err:\\n raise err\",\n \"def client(\\n service_name: str, version: str = \\\"v1\\\", secrets: Secrets = None\\n) -> Resource:\\n credentials = load_credentials(secrets=secrets)\\n return build(service_name, version=version, credentials=credentials)\",\n \"async def create_client_by_namespace_async(\\n body: ClientmodelClientCreateRequest,\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = CreateClientByNamespace.create(\\n body=body,\\n namespace=namespace,\\n )\\n return await run_request_async(\\n request, additional_headers=x_additional_headers, **kwargs\\n )\",\n \"def create_service(cls, proto_py_module, service_name):\\n\\n return cls.create_services(proto_py_module, service_name)\",\n \"def create_client(self, initiator_iqn):\\n client = self._get_target_client(initiator_iqn)\\n if not client:\\n try:\\n self.client.create_client(self.target_iqn,\\n initiator_iqn)\\n except client_exceptions.ClientException as ex:\\n raise exception.VolumeBackendAPIException(\\n data=ex.get_description())\",\n \"def client():\\n\\n client = Client()\\n return client\",\n \"def serviceClient(self, iTag, srvType, addr):\\r\\n return ROSServiceClient(self, iTag, srvType, addr)\",\n \"async def api_create_service(\\n data: CreateService, wallet: WalletTypeInfo = Depends(get_key_type)\\n):\\n try:\\n service = await create_service(data=data)\\n except Exception as e:\\n raise HTTPException(status_code=HTTPStatus.INTERNAL_SERVER_ERROR, detail=str(e))\\n\\n return service.dict()\",\n \"def create_generated_client() -> None:\\n print(\\\"Generating client\\\")\\n\\n delete_generated_client()\\n args = [\\n \\\"{}/../scripts/generate.sh\\\".format(ROOT),\\n \\\"-i\\\",\\n \\\"http://localhost:8000/openapi.json\\\",\\n \\\"-p\\\",\\n CLIENT_NAME,\\n \\\"--include-auth\\\",\\n \\\"-o\\\",\\n ROOT,\\n \\\"-t\\\",\\n \\\"/tmp\\\",\\n \\\"-m\\\",\\n ]\\n\\n process_result = subprocess.run(args, capture_output=True)\\n\\n with open(os.path.join(LOG_DIR, \\\"generation.log\\\"), \\\"wb\\\") as file:\\n file.write(process_result.stdout)\\n\\n with open(os.path.join(LOG_DIR, \\\"generation.err\\\"), \\\"wb\\\") as file:\\n file.write(process_result.stderr)\\n\\n if process_result.returncode != 0: # pragma: no cover\\n if process_result.stderr:\\n sys.stderr.write(process_result.stderr.decode(\\\"utf-8\\\"))\\n pytest.exit(\\n \\\"Failed to generate client api, code {}\\\"\\n \\\"\\\\nLogs are in logs/generation.log and logs/generation.err\\\".format(process_result.returncode),\\n returncode=process_result.returncode,\\n )\\n\\n print(\\\"Client created in {}, logs in logs/generation.log\\\\n\\\".format(CLIENT_DIR))\",\n \"def _create_client(p4, client_name, p4gf_dir):\\n view = ['//{depot}/... //{client}/...'.format(depot=p4gf_const.P4GF_DEPOT,\\n client=client_name)]\\n spec_created = False\\n if not p4gf_util.spec_exists(p4, \\\"client\\\", client_name):\\n # See if the old object clients exist, in which case we will remove them.\\n if p4gf_util.spec_exists(p4, \\\"client\\\", OLD_OBJECT_CLIENT):\\n p4.run('client', '-df', OLD_OBJECT_CLIENT)\\n if p4gf_util.spec_exists(p4, \\\"client\\\", OLDER_OBJECT_CLIENT):\\n p4.run('client', '-df', OLDER_OBJECT_CLIENT)\\n spec_created = p4gf_util.ensure_spec(\\n p4, \\\"client\\\", spec_id=client_name,\\n values={'Host': None, 'Root': p4gf_dir,\\n 'Description': 'Created by Perforce Git Fusion',\\n 'View': view})\\n if not spec_created:\\n p4gf_util.ensure_spec_values(p4, \\\"client\\\", client_name,\\n {'Root': p4gf_dir, 'View': view})\",\n \"def service_create(service, service_type, api, endpoint):\\n db = model.Session()\\n _assert_absent(db, model.Service, service)\\n api = _must_find(db, model.API, api)\\n service = model.Service(service, service_type, api, endpoint)\\n db.add(service)\\n db.commit()\",\n \"def create_client():\\n logger.debug(\\\"=====create_client fired...\\\")\\n try:\\n session = boto3.Session()\\n client = session.client('dynamodb', region_name='us-east-1')\\n return client\\n except ClientError as err:\\n logger.error(\\n \\\"[BOTO3_ERROR]Failed to create boto3 client: %s\\\", str(err))\",\n \"def create_client(client_id, authority_url, client_secret):\\n client = msal.ConfidentialClientApplication(\\n client_id=client_id, authority=authority_url, client_credential=client_secret\\n )\\n return client\",\n \"def create_service():\\n creds = None\\n # The file token_sheet.pickle stores the user's access and refresh tokens, and is\\n # created automatically when the authorization flow completes for the first\\n # time.\\n if os.path.exists('token_sheet.pickle'):\\n with open('token_sheet.pickle', 'rb') as token:\\n creds = pickle.load(token)\\n # If there are no (valid) credentials available, let the user log in.\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n 'credentials_sheets.json', SCOPES)\\n creds = flow.run_local_server(port=0)\\n # Save the credentials for the next run\\n with open('token_sheet.pickle', 'wb') as token:\\n pickle.dump(creds, token)\\n\\n service = build('sheets', 'v4', credentials=creds)\\n return service\",\n \"async def create_client_async(\\n body: ClientmodelClientCreateRequest,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n request = CreateClient.create(\\n body=body,\\n )\\n return await run_request_async(\\n request, additional_headers=x_additional_headers, **kwargs\\n )\",\n \"def create_boto3_client(config, service):\\n session = boto3.Session(profile_name=config.get('AWS_ACCESS', 'AWS_PROFILE'))\\n return session.client(service, region_name=config.get('AWS_ACCESS', 'AWS_REGION'))\",\n \"def create_client(name: str, url: str, description: str, scopes: str,\\n redirect_uri: str) -> None:\\n app = create_web_app()\\n with app.app_context():\\n datastore.create_all()\\n\\n with datastore.util.transaction() as session:\\n db_client = datastore.models.DBClient(\\n name=name,\\n url=url,\\n description=description,\\n redirect_uri=redirect_uri\\n )\\n secret = generate_token(48)\\n hashed = hashlib.sha256(secret.encode('utf-8')).hexdigest()\\n db_cred = datastore.models.DBClientCredential(client=db_client,\\n client_secret=hashed)\\n db_scopes = [\\n datastore.models.DBClientAuthorization(\\n client=db_client, authorized=datetime.now(), scope=scope\\n ) for scope in scopes.split()\\n ]\\n db_grant_type = datastore.models.DBClientGrantType(\\n client=db_client,\\n grant_type='client_credentials',\\n authorized=datetime.now()\\n )\\n db_grant_type = datastore.models.DBClientGrantType(\\n client=db_client,\\n grant_type='authorization_code',\\n authorized=datetime.now()\\n )\\n\\n session.add(db_client)\\n session.add(db_cred)\\n session.add(db_grant_type)\\n for db_scope in db_scopes:\\n session.add(db_scope)\\n\\n session.commit()\\n click.echo(f'Created client {name} with ID {db_client.client_id}'\\n f' and secret {secret}')\",\n \"def boto_client(account_id, service_name, region):\\n logger.info('Creating boto3 client for account_id: {}, '\\n 'service_name: {}'.format(account_id, service_name))\\n return boto3.client(service_name, region_name=region)\",\n \"def _establish_client():\\n logger.debug('SoapService - _establish_client()')\\n try:\\n client = zeep.Client(wsdl=settings.WSDL)\\n except Exception as e:\\n message = 'Unable to create soap client from wsdl file, error: {}'.format(e)\\n logger.error(message)\\n raise IOError(message)\\n\\n return client\",\n \"def create_resource(\\n service_name: str, config_name: str = None, **resource_args\\n):\\n session = get_session(config_name)\\n return session.resource(service_name, **resource_args)\",\n \"def create_client():\\n result = False\\n if g.client_id in drivers:\\n result = True\\n return jsonify({'Success': result})\",\n \"def new_instance(cls,\\n version: date,\\n service_name: str = DEFAULT_SERVICE_NAME,\\n ) -> 'DirectLinkApisV1':\\n if version is None:\\n raise ValueError('version must be provided')\\n\\n authenticator = get_authenticator_from_environment(service_name)\\n service = cls(\\n version,\\n authenticator\\n )\\n service.configure_service(service_name)\\n return service\",\n \"def client(service_name, region_name=None):\\n return session.client(service_name=service_name, region_name=region_name)\",\n \"def serviceClient(self, iTag, srvType, cb=None):\\r\\n if cb and not callable(cb):\\r\\n raise TypeError('Callback has to be callable.')\\r\\n\\r\\n return ServiceClient(self, iTag, srvType, cb)\",\n \"def _create_soap_object(self, name):\\n return self.client.factory.create(name)\",\n \"def service_create(path, service_name, definition):\\n compose_result, loaded_definition, err = __load_compose_definitions(\\n path, definition\\n )\\n if err:\\n return err\\n services = compose_result[\\\"compose_content\\\"][\\\"services\\\"]\\n if service_name in services:\\n msg = \\\"Service {} already exists\\\".format(service_name)\\n return __standardize_result(False, msg, None, None)\\n services[service_name] = loaded_definition\\n return __dump_compose_file(\\n path,\\n compose_result,\\n \\\"Service {} created\\\".format(service_name),\\n already_existed=True,\\n )\",\n \"def createClient(self, name, wid, notes=None):\\n\\n data = {}\\n data['client'] = {}\\n data['client']['name'] = name\\n data['client']['wid'] = wid\\n data['client']['notes'] = notes\\n\\n response = self.postRequest(Endpoints.CLIENTS, parameters=data)\\n return self.decodeJSON(response)\",\n \"def create(self):\\n\\t\\treturn handle_to_object(call_sdk_function('PrlSrv_Create'))\",\n \"def create_dummy_client(index, user, client_manager = None, language = None, currency = None):\\r\\n \\r\\n if client_manager == None:\\r\\n client_manager = ClientManager(user)\\r\\n \\r\\n if currency is None:\\r\\n currency = create_dummy_currency(index)\\r\\n \\r\\n if language is None:\\r\\n language = create_dummy_language(index)\\r\\n \\r\\n return client_manager.add_client(\\r\\n name = 'client_%i' %index,\\r\\n address = 'address_%i' % index,\\r\\n email = 'corp_email_%i@email.com' % index,\\r\\n default_currency_id = currency.key().id(),\\r\\n default_language_id = language.key().id(),\\r\\n )\",\n \"def create_client(name):\\n address = \\\"/run/com_handler.sock\\\"\\n sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)\\n sock.connect(address)\\n return Client(sock, \\\"\\\", name)\",\n \"def create_client(self, version=None, unstable=False, **kwargs):\\n version_data = self._calculate_version(version, unstable)\\n return self._create_client(version_data, **kwargs)\",\n \"def create_servicech(self, conf, params):\\n\\t\\tpass\",\n \"def create_client():\\n hostname = \\\"localhost\\\"\\n username = \\\"she393\\\"\\n password = os.getenv(\\\"PASSWORD\\\")\\n\\n client = paramiko.SSHClient()\\n client.set_missing_host_key_policy(paramiko.AutoAddPolicy())\\n client.connect(hostname=hostname, username=username, password=password)\\n return client\",\n \"def test_client_create(self):\\n pass\",\n \"def new(\\n cls,\\n name: str,\\n description: str,\\n registration_schema: JSON,\\n result_schema: JSON,\\n database_session: Session) -> 'Service':\\n raise NotImplementedError()\",\n \"def create_service(self, url_data):\\n data = {key: value[0] for key, value in url_data}\\n\\n publish_key = uuid.uuid4().hex\\n service_id = uuid.uuid4().hex\\n service_name = data['name']\\n\\n self.fastly_cache[service_name] = {\\n 'service_details': {\\n u'comment': '',\\n u'locked': False,\\n u'updated_at': u'2014-11-13T14:29:10+00:00',\\n u'created_at': u'2014-11-13T14:29:10+00:00',\\n u'testing': None,\\n u'number': 1,\\n u'staging': None,\\n u'active': None,\\n u'service_id': service_id,\\n u'deleted_at': None,\\n u'inherit_service_id': None,\\n u'deployed': None},\\n 'service_name': service_name\\n }\\n self.fastly_cache[service_id] = self.fastly_cache[service_name]\\n\\n create_service = {\\n u'comment': '',\\n u'publish_key': publish_key,\\n u'name': service_name,\\n u'versions': [{u'comment': '', u'locked': u'0',\\n u'service': service_id,\\n u'updated_at': u'2014-11-12T18:43:21',\\n u'created_at': u'2014-11-12T18:43:21',\\n u'testing': None, u'number': u'1',\\n u'staging': None,\\n u'active': None,\\n u'service_id': service_id,\\n u'deleted_at': None,\\n u'inherit_service_id': None,\\n u'deployed': None,\\n u'backend': 0}],\\n u'created_at': u'2014-11-12T18:43:21+00:00',\\n u'updated_at': u'2014-11-12T18:43:21+00:00',\\n u'customer_id': data['customer_id'],\\n u'id': service_id}\\n return create_service\",\n \"def build_service():\\n\\n\\tstore = file.Storage('credentials.json')\\n\\tcreds = store.get()\\n\\tif not creds or creds.invalid:\\n\\t flow = client.flow_from_clientsecrets('client_secret.json', SCOPES)\\n\\t creds = tools.run_flow(flow, store)\\n\\tservice = build('gmail', 'v1', http=creds.authorize(Http(disable_ssl_certificate_validation=True)))\\n\\treturn service\",\n \"def create():\\n form = request.form\\n try:\\n # create a new BancBox client from the input form\\n resp = api.create_client(form)\\n except Exception, e:\\n logger.error('Error creating new client: %s', e)\\n return render_template('created.html', error=e.message)\\n\\n if resp.status == 1:\\n # If the create request was successful, let's render a success\\n # message with some data about the new client and a link to the\\n # detail page\\n new_client = {\\n 'firstName': form['firstName'],\\n 'lastName': form['lastName'],\\n 'clientId': resp.clientId\\n }\\n return render_template('created.html', new_client=new_client)\\n else:\\n # If an error was returned by BancBox, let's render it\\n if hasattr(resp, 'errors') and hasattr(resp.errors, 'message'):\\n message = resp.errors.message\\n else:\\n message = \\\"Error creating new client.\\\"\\n return render_template('created.html', error=message)\",\n \"def create_client(self):\\n client = iperf3.Client()\\n client.duration = self._host[CONF_DURATION]\\n client.server_hostname = self._host[CONF_HOST]\\n client.port = self._host[CONF_PORT]\\n client.num_streams = self._host[CONF_PARALLEL]\\n client.protocol = self._host[CONF_PROTOCOL]\\n client.verbose = False\\n return client\",\n \"def make_client(instance):\\r\\n neutron_client = utils.get_client_class(\\r\\n API_NAME,\\r\\n instance._api_version[API_NAME],\\r\\n API_VERSIONS,\\r\\n )\\r\\n instance.initialize()\\r\\n url = instance._url\\r\\n url = url.rstrip(\\\"/\\\")\\r\\n if '2.0' == instance._api_version[API_NAME]:\\r\\n client = neutron_client(username=instance._username,\\r\\n tenant_name=instance._tenant_name,\\r\\n password=instance._password,\\r\\n region_name=instance._region_name,\\r\\n auth_url=instance._auth_url,\\r\\n endpoint_url=url,\\r\\n token=instance._token,\\r\\n auth_strategy=instance._auth_strategy,\\r\\n insecure=instance._insecure,\\r\\n ca_cert=instance._ca_cert)\\r\\n return client\\r\\n else:\\r\\n raise exceptions.UnsupportedVersion(_(\\\"API version %s is not \\\"\\r\\n \\\"supported\\\") %\\r\\n instance._api_version[API_NAME])\",\n \"def get_client(service_account_json):\\n api_scopes = ['https://www.googleapis.com/auth/cloud-platform']\\n api_version = 'v1'\\n discovery_api = 'https://cloudiot.googleapis.com/$discovery/rest'\\n service_name = 'cloudiotcore'\\n\\n credentials = service_account.Credentials.from_service_account_file(\\n service_account_json)\\n scoped_credentials = credentials.with_scopes(api_scopes)\\n\\n discovery_url = '{}?version={}'.format(\\n discovery_api, api_version)\\n\\n return discovery.build(\\n service_name,\\n api_version,\\n discoveryServiceUrl=discovery_url,\\n credentials=scoped_credentials)\",\n \"def create_TestService(test_case, # type: AnyMagpieTestCaseType\\n override_service_name=null, # type: Optional[Str]\\n override_service_type=null, # type: Optional[Str]\\n override_headers=null, # type: Optional[HeadersType]\\n override_cookies=null, # type: Optional[CookiesType]\\n ): # type: (...) -> JSON\\n app_or_url = get_app_or_url(test_case)\\n svc_name = override_service_name if override_service_name is not null else test_case.test_service_name\\n svc_type = override_service_type if override_service_type is not null else test_case.test_service_type\\n data = {\\n \\\"service_name\\\": svc_name,\\n \\\"service_type\\\": svc_type,\\n \\\"service_url\\\": \\\"http://localhost:9000/{}\\\".format(svc_name)\\n }\\n if svc_name:\\n test_case.extra_service_names.add(svc_name) # indicate potential removal at a later point\\n resp = test_request(app_or_url, \\\"POST\\\", \\\"/services\\\", json=data,\\n headers=override_headers if override_headers is not null else test_case.json_headers,\\n cookies=override_cookies if override_cookies is not null else test_case.cookies,\\n expect_errors=True)\\n if resp.status_code == 409:\\n path = \\\"/services/{svc}\\\".format(svc=svc_name)\\n resp = test_request(app_or_url, \\\"GET\\\", path,\\n headers=override_headers if override_headers is not null else test_case.json_headers,\\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\\n body = check_response_basic_info(resp, 200, expected_method=\\\"GET\\\")\\n if TestVersion(test_case.version) < TestVersion(\\\"0.9.1\\\"):\\n body.update({\\\"service\\\": body[svc_name]})\\n body.pop(svc_name)\\n return body\\n return check_response_basic_info(resp, 201, expected_method=\\\"POST\\\")\",\n \"def create_client(wsdl: str, raw_response: bool = True) -> CachingClient:\\n # We want the raw response as there is an error when Zeep parses the XML\\n settings: Settings = Settings(raw_response=raw_response)\\n\\n # Client that caches the WSDL\\n client: CachingClient = CachingClient(\\n wsdl=wsdl,\\n # TODO: Store PW encrypted\\n wsse=UsernameToken(\\\"n00394gz\\\", \\\"g427Ix19LMB\\\"),\\n settings=settings,\\n )\\n logger.debug(f\\\"Client created\\\")\\n\\n return client\",\n \"def create_service_object(credentials):\\n http_auth = httplib2.Http()\\n http_auth = credentials.authorize(http_auth)\\n service = discovery.build('analytics', 'v3', http=http_auth)\\n return service\",\n \"def create_service(self, project_id, auth_token, service_json):\\n try:\\n flavor = self.flavor_controller.get(service_json.get('flavor_id'))\\n # raise a lookup error if the flavor is not found\\n except LookupError as e:\\n raise e\\n\\n # add any default rules so its explicitly defined\\n self._append_defaults(service_json, operation='create')\\n\\n # convert to an object\\n service_obj = service.Service.init_from_dict(project_id, service_json)\\n service_id = service_obj.service_id\\n\\n # validate the service\\n service_json = service_obj.to_dict()\\n schema = service_schema.ServiceSchema.get_schema(\\\"service\\\", \\\"POST\\\")\\n validators.is_valid_service_configuration(service_json, schema)\\n\\n service_limit = self.storage_controller.get_service_limit(project_id)\\n service_count = self.storage_controller.get_service_count(project_id)\\n\\n services_delete_in_progress = self.storage_controller.\\\\\\n get_services_by_status('delete_in_progress')\\n\\n services_delete_count = len(services_delete_in_progress)\\n\\n # Check that the number of deleted services is less\\n # than the total number of existing services for the project.\\n # Adjust the service count removing delete_in_progress\\n # services.\\n service_count -= (\\n services_delete_count\\n if 0 < services_delete_count < service_count else 0\\n )\\n # service_count should always be a >= 0.\\n\\n if service_count >= service_limit:\\n raise errors.ServicesOverLimit('Maximum Services '\\n 'Limit of {0} '\\n 'reached!'.format(service_limit))\\n\\n if any([domain for domain in service_obj.domains\\n if domain.certificate == \\\"shared\\\"]):\\n try:\\n store = str(uuid.uuid4()).replace('-', '_')\\n service_obj = self._shard_retry(project_id,\\n service_obj,\\n store=store)\\n except errors.SharedShardsExhausted as e:\\n raise e\\n except ValueError as e:\\n raise e\\n\\n try:\\n self.storage_controller.create_service(project_id, service_obj)\\n except ValueError as e:\\n raise e\\n\\n providers = [p.provider_id for p in flavor.providers]\\n kwargs = {\\n 'providers_list_json': json.dumps(providers),\\n 'project_id': project_id,\\n 'auth_token': auth_token,\\n 'service_id': service_id,\\n 'time_seconds': self.determine_sleep_times(),\\n 'context_dict': context_utils.get_current().to_dict()\\n }\\n\\n self.distributed_task_controller.submit_task(\\n create_service.create_service, **kwargs)\\n\\n return service_obj\",\n \"def _get_client(self):\\n credentials = service_account.Credentials.from_service_account_info(self.service_account_info)\\n client = googleapiclient.discovery.build('container', 'v1', credentials=credentials)\\n\\n return client\",\n \"def client(db):\\n client = ClientFactory()\\n db.session.commit()\\n return client\",\n \"def create_client():\\n host_api_id = Config.api_id\\n host_api_hash = Config.api_hash\\n host_user_id = Config.user_id\\n host_phone = Config.phone\\n\\n client = TelegramClient(host_user_id, host_api_id, host_api_hash)\\n client.connect()\\n if not client.is_user_authorized():\\n client.send_code_request(host_phone)\\n client.sign_in(host_phone, input('Enter code sent to your telegram: '))\\n return client\",\n \"def gen_nova_client(self):\\n\\n print \\\"\\\\t* Generating nova client\\\"\\n client = nClient.get_client_class('2')\\n self.novaclient = client(self.username,\\n self.password,\\n self.tenant_name,\\n self.auth_url,\\n service_type='compute')\",\n \"def client():\\n return Client(**common_data.AUTH_ARGS)\",\n \"def __init__(self, service, acces_key, secret_key):\\n \\n self.client = boto3.client(\\n service,\\n aws_access_key_id=acces_key,\\n aws_secret_access_key=secret_key,\\n )\",\n \"def create_client(access_key_id, secret_access_key):\\r\\n client = boto3.client('s3',\\r\\n aws_access_key_id=access_key_id,\\r\\n aws_secret_access_key=secret_access_key)\\r\\n return client\",\n \"def _init_http_client(service_id=None, opts=None):\\n if service_id:\\n opts = _get_trs_opts(service_id)\\n\\n http_client = RequestsClient()\\n\\n http_client.set_api_key(host=opts['host'],\\n api_key=opts['auth'],\\n param_in='header')\\n return http_client\",\n \"def service_client_initialization(self) -> global___Snippet.ClientInitialization:\",\n \"def test_client_create(self, mock_input, mock_pass):\\n # Patch username and password.\\n mock_input.return_value = \\\"user\\\"\\n mock_pass.return_value = \\\"pass\\\"\\n\\n # Instantiate Agave object making reference to local mock server.\\n local_uri = \\\"http://localhost:{port}/\\\".format(port=self.mock_server_port)\\n ag = Agave(api_server=local_uri)\\n\\n # Create client.\\n ag.clients_create(\\\"client-name\\\", \\\"some description\\\")\\n\\n assert ag.api_key == \\\"some api key\\\"\\n assert ag.api_secret == \\\"some secret\\\"\",\n \"def create_new_client(main: MainApplication) -> str:\\n client = main.create_window(\\\"client\\\", \\\"IPLMS\\\", main.client_ui.get_layout())\\n client[\\\"_CLIENT_ID_\\\"].Update(getUUID())\\n client[\\\"_CP_NAME_IP_\\\"].Update(\\\"\\\")\\n client[\\\"_CP_PHONE_IP_\\\"].Update(\\\"\\\")\\n client[\\\"_CP_ADDRESS_IP_\\\"].Update(\\\"\\\")\\n client.un_hide()\\n event, values = client.read()\\n client_logic = Client(main, event, values)\\n name = client_logic.run(main)\\n client.hide()\\n return name\",\n \"def _CreatePubsubClient():\\n client = pubsub_client.PubSubClient()\\n client.CreateTopic(DEVICE_NOTE_PUBSUB_TOPIC)\\n client.CreateTopic(HOST_NOTE_PUBSUB_TOPIC)\\n return client\",\n \"def get_service(api_name, api_version, scope, client_secrets_path):\\n # Parse command-line arguments.\\n parser = argparse.ArgumentParser(\\n formatter_class=argparse.RawDescriptionHelpFormatter,\\n parents=[tools.argparser])\\n flags = parser.parse_args([])\\n\\n # Set up a Flow object to be used if we need to authenticate.\\n flow = client.flow_from_clientsecrets(\\n client_secrets_path, scope=scope,\\n message=tools.message_if_missing(client_secrets_path))\\n\\n # Prepare credentials, and authorize HTTP object with them.\\n # If the credentials don't exist or are invalid run through the native client\\n # flow. The Storage object will ensure that if successful the good\\n # credentials will get written back to a file.\\n storage = file.Storage(api_name + '.dat')\\n credentials = storage.get()\\n if credentials is None or credentials.invalid:\\n credentials = tools.run_flow(flow, storage, flags)\\n http = credentials.authorize(http=httplib2.Http())\\n\\n # Build the service object.\\n service = build(api_name, api_version, http=http)\\n\\n return service\",\n \"def create_clients(aws_key, aws_secret):\\n ec2_client = boto3.resource(\\n 'ec2', region_name=AWS_REGION, aws_access_key_id=aws_key,\\n aws_secret_access_key=aws_secret\\n )\\n s3_client = boto3.resource(\\n 's3', region_name=AWS_REGION, aws_access_key_id=aws_key,\\n aws_secret_access_key=aws_secret\\n )\\n iam_client = boto3.client(\\n 'iam', region_name=AWS_REGION, aws_access_key_id=aws_key,\\n aws_secret_access_key=aws_secret\\n )\\n redshift_client = boto3.client(\\n 'redshift', region_name=AWS_REGION, aws_access_key_id=aws_key,\\n aws_secret_access_key=aws_secret\\n )\\n return ec2_client, s3_client, iam_client, redshift_client\",\n \"def _client(self):\\n\\n if self._suds_client is None:\\n self._suds_client = suds.client.Client(SERVICE_WSDL_URL)\\n # Add SOAP Security tokens\\n self.set_security_token()\\n\\n return self._suds_client\",\n \"def get_client():\\n return Client(__address, authkey='strumamor')\",\n \"def create_clients(client_name): # Crear nuevo Cliente\\n global clients\\n\\n if client_name not in clients:\\n clients.append(client_name)\\n else:\\n print('The client name is alredy in the client\\\\'s list')\",\n \"def newClient(self, cid, **kwargs):\\n client = Iourt42Client(console=self.console, cid=cid, timeAdd=self.console.time(), **kwargs)\\n self[client.cid] = client\\n self.resetIndex()\\n\\n self.console.debug('Urt42 Client Connected: [%s] %s - %s (%s)', self[client.cid].cid, self[client.cid].name,\\n self[client.cid].guid, self[client.cid].data)\\n\\n self.console.queueEvent(self.console.getEvent('EVT_CLIENT_CONNECT', data=client, client=client))\\n\\n if client.guid:\\n client.auth()\\n elif not client.authed:\\n self.authorizeClients()\\n return client\",\n \"def create(cls, client, fields, **kwargs):\\n\\t\\tres = cls(client, fields, **kwargs)\\n\\t\\treturn res\",\n \"def newSDDCService(**kwargs):\\n # Test for interactive flag - if False, check to ensure additional arguments were give for service entry\\n if kwargs['interactive'] is False and (kwargs['l4_protocol'] is None or kwargs['dest_ports'] is None):\\n print(\\\"Error - if not using interactive mode, at least protocol and destination port(s) must be configured. Source port(s) optional, based on your application.\\\")\\n sys.exit(1)\\n elif kwargs['interactive'] is True and (kwargs['l4_protocol'] is not None or kwargs['dest_ports'] is not None or kwargs['source_ports'] is not None):\\n print(\\\"Error - if using interactive mode, please only specify the name of the desired service. All other parameters will be obtained interactively.\\\")\\n sys.exit(1)\\n else:\\n pass\\n proxy = kwargs['proxy']\\n sessiontoken = kwargs['sessiontoken']\\n service_id = kwargs['objectname']\\n interactive = kwargs['interactive']\\n\\n if interactive == True:\\n service_entry_list = []\\n # Start a loop that will run until the user enters 'quit'.\\n # Ask the user for a name.\\n destination_port = \\\"\\\"\\n while destination_port != 'done':\\n destination_port_list = []\\n source_port_list = []\\n service_entry_id = input(\\\"Please enter the Service Entry ID:\\\")\\n l4_protocol = input(\\\"Please enter the L4 Protocol:\\\")\\n source_port = \\\"\\\"\\n destination_port = \\\"\\\"\\n while source_port != 'done':\\n source_port = input(\\\"Plese enter the Source Ports or type 'done' when your list is finished:\\\")\\n if source_port != \\\"done\\\":\\n source_port_list.append(source_port)\\n while (destination_port != 'next') and (destination_port != \\\"done\\\"):\\n source_port = \\\"\\\"\\n destination_port = input(\\\"Plese enter the Destination Ports, type 'next' when you want to define another service entry or 'done' if you have finished:\\\")\\n if (destination_port != 'next') and (destination_port != \\\"done\\\"):\\n destination_port_list.append(destination_port)\\n service_entry = {\\n \\\"l4_protocol\\\": l4_protocol,\\n \\\"source_ports\\\": source_port_list,\\n \\\"destination_ports\\\" : destination_port_list,\\n \\\"resource_type\\\" : \\\"L4PortSetServiceEntry\\\",\\n \\\"id\\\" : service_entry_id,\\n \\\"display_name\\\" : service_entry_id }\\n service_entry_list.append(service_entry)\\n else:\\n source_port_list = kwargs['source_ports']\\n destination_port_list = kwargs['dest_ports']\\n l4_protocol = kwargs['l4_protocol']\\n service_entry_list = [\\n {\\n \\\"l4_protocol\\\": l4_protocol,\\n \\\"source_ports\\\": source_port_list,\\n \\\"destination_ports\\\": destination_port_list,\\n \\\"resource_type\\\": \\\"L4PortSetServiceEntry\\\",\\n \\\"display_name\\\": f'{service_id}_svc_entry'\\n }\\n ]\\n json_data = {\\n \\\"service_entries\\\":service_entry_list,\\n \\\"id\\\" : service_id,\\n \\\"display_name\\\" : service_id,\\n }\\n response = new_sddc_service_json(proxy,sessiontoken,service_id,json_data)\\n if response == 200:\\n print(f'Service {service_id} successfully updated.')\\n params = {'proxy':proxy, 'sessiontoken':sessiontoken, 'objectname':service_id}\\n getSDDCService(**params)\\n else:\\n print(\\\"Issues creating the service - please check your syntax and try again.\\\")\\n sys.exit(1)\",\n \"def post(self, ws_id, project_id):\\n service = servicesimpl.create_service(ws_id, project_id, get_json(request))\\n return prepare_response(service, 201)\",\n \"def get_service(\\n service_name: str,\\n version: str = \\\"v1\\\",\\n configuration: Configuration = None,\\n secrets: Secrets = None,\\n) -> Resource:\\n return client(service_name, version=version, secrets=secrets)\",\n \"def client_setup(self):\\n self.client = Client()\",\n \"def create_api_client(base_path, access_token):\\n api_client = ApiClient()\\n api_client.host = base_path\\n api_client.set_default_header(header_name=\\\"Authorization\\\",\\n header_value=f\\\"Bearer {access_token}\\\")\\n return api_client\",\n \"def gen_neutron_client(self):\\n\\n print \\\"\\\\t* Generating neutron client\\\"\\n self.neutronclient = neutronclient.Client(auth_url=self.auth_url,\\n username=self.username,\\n password=self.password,\\n tenant_name=self.tenant_name,\\n region_name=self.region_name)\",\n \"def create_services(cls, proto_py_module, *service_names):\\n\\n return cls(proto_py_module, *service_names).services\",\n \"def make_client(db, hdfs_client=None):\\n return ImpalaClient(db, hdfs_client=hdfs_client)\",\n \"def build_service():\\n creds = None\\n\\n # the file token.json stores the user's access and refresh tokens, and is \\n # created automatically when the authorization flow completes for the first time\\n \\n if os.path.exists('../creds/token.json'):\\n creds = Credentials.from_authorized_user_file('../creds/token.json', SCOPES)\\n\\n # if there are no (valid) credentials, ask the user to login\\n if not creds or not creds.valid:\\n if creds and creds.expired and creds.refresh_token:\\n creds.refresh(Request())\\n else:\\n flow = InstalledAppFlow.from_client_secrets_file(\\n '../creds/credentials.json', SCOPES)\\n creds = flow.run_local_server(port=0)\\n with open('../creds/token.json', 'w') as token:\\n token.write(creds.to_json())\\n\\n service = build('drive', 'v3', credentials=creds)\\n return service\"\n]"},"negative_scores":{"kind":"list like","value":["0.801748","0.78244793","0.72532517","0.7216976","0.71908116","0.71908116","0.70718634","0.7055989","0.69973916","0.6996517","0.6937248","0.68635684","0.68541193","0.68492603","0.6825555","0.67868036","0.66969323","0.6665927","0.6663688","0.6585112","0.6581582","0.6579658","0.6529895","0.65005505","0.6482222","0.6467781","0.64329064","0.6414261","0.63963556","0.6395781","0.63946646","0.6379576","0.63593674","0.63342196","0.63320684","0.633002","0.63062704","0.6286155","0.6273915","0.62580514","0.62486017","0.6247127","0.6240954","0.62365395","0.6220226","0.6219414","0.62024796","0.6177144","0.61426616","0.61358994","0.6100425","0.6082476","0.60682803","0.605948","0.6059402","0.6053242","0.60343313","0.6033299","0.6017835","0.59993064","0.5995884","0.59754145","0.5956289","0.5931459","0.5924004","0.5922091","0.59182644","0.590952","0.58992004","0.5897322","0.58887273","0.5885458","0.5883872","0.58724797","0.5861407","0.58542526","0.58395606","0.58294505","0.5804527","0.5798101","0.5793488","0.57817584","0.5778538","0.5778053","0.5757338","0.57508993","0.57503605","0.5745668","0.57178354","0.57074654","0.5703485","0.57010597","0.5700976","0.56952596","0.5683107","0.5662492","0.56546277","0.5652761","0.5645203","0.5642448","0.5633304"],"string":"[\n \"0.801748\",\n \"0.78244793\",\n \"0.72532517\",\n \"0.7216976\",\n \"0.71908116\",\n \"0.71908116\",\n \"0.70718634\",\n \"0.7055989\",\n \"0.69973916\",\n \"0.6996517\",\n \"0.6937248\",\n \"0.68635684\",\n \"0.68541193\",\n \"0.68492603\",\n \"0.6825555\",\n \"0.67868036\",\n \"0.66969323\",\n \"0.6665927\",\n \"0.6663688\",\n \"0.6585112\",\n \"0.6581582\",\n \"0.6579658\",\n \"0.6529895\",\n \"0.65005505\",\n \"0.6482222\",\n \"0.6467781\",\n \"0.64329064\",\n \"0.6414261\",\n \"0.63963556\",\n \"0.6395781\",\n \"0.63946646\",\n \"0.6379576\",\n \"0.63593674\",\n \"0.63342196\",\n \"0.63320684\",\n \"0.633002\",\n \"0.63062704\",\n \"0.6286155\",\n \"0.6273915\",\n \"0.62580514\",\n \"0.62486017\",\n \"0.6247127\",\n \"0.6240954\",\n \"0.62365395\",\n \"0.6220226\",\n \"0.6219414\",\n \"0.62024796\",\n \"0.6177144\",\n \"0.61426616\",\n \"0.61358994\",\n \"0.6100425\",\n \"0.6082476\",\n \"0.60682803\",\n \"0.605948\",\n \"0.6059402\",\n \"0.6053242\",\n \"0.60343313\",\n \"0.6033299\",\n \"0.6017835\",\n \"0.59993064\",\n \"0.5995884\",\n \"0.59754145\",\n \"0.5956289\",\n \"0.5931459\",\n \"0.5924004\",\n \"0.5922091\",\n \"0.59182644\",\n \"0.590952\",\n \"0.58992004\",\n \"0.5897322\",\n \"0.58887273\",\n \"0.5885458\",\n \"0.5883872\",\n \"0.58724797\",\n \"0.5861407\",\n \"0.58542526\",\n \"0.58395606\",\n \"0.58294505\",\n \"0.5804527\",\n \"0.5798101\",\n \"0.5793488\",\n \"0.57817584\",\n \"0.5778538\",\n \"0.5778053\",\n \"0.5757338\",\n \"0.57508993\",\n \"0.57503605\",\n \"0.5745668\",\n \"0.57178354\",\n \"0.57074654\",\n \"0.5703485\",\n \"0.57010597\",\n \"0.5700976\",\n \"0.56952596\",\n \"0.5683107\",\n \"0.5662492\",\n \"0.56546277\",\n \"0.5652761\",\n \"0.5645203\",\n \"0.5642448\",\n \"0.5633304\"\n]"},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":8567,"cells":{"query":{"kind":"string","value":"Activates the specified MFA TOTP device for the user. Activation requires manual interaction with the Console."},"document":{"kind":"string","value":"def activate_mfa_totp_device(self, user_id, mfa_totp_device_id, mfa_totp_token, **kwargs):\n resource_path = \"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}/actions/activate\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"if_match\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"activate_mfa_totp_device got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id,\n \"mfaTotpDeviceId\": mfa_totp_device_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"if-match\": kwargs.get(\"if_match\", missing),\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=mfa_totp_token,\n response_type=\"MfaTotpDeviceSummary\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=mfa_totp_token,\n response_type=\"MfaTotpDeviceSummary\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["async def activate_application_token(self, apptoken, temptoken) -> bool:\n await self.raw_request(\n self.URL_ACTIVATE.format(apptoken=apptoken, temptoken=temptoken)\n )\n return True","def activate(request, uidb64, token):\n try:\n uid = force_text(urlsafe_base64_decode(uidb64))\n user = User.objects.get(pk=uid)\n except (TypeError, ValueError, OverflowError, User.DoesNotExist):\n user = None\n\n if user is not None and account_activation_token.check_token(user, token):\n user.is_active = True\n user.profile.email_confirmed = True\n user.save()\n login(request, user)\n return redirect('home')\n else:\n return render(request, 'registration/activation_invalid.html')","def activate(request, uidb64, token):\n try:\n uid = force_text(urlsafe_base64_decode(uidb64))\n user = User.objects.get(pk=uid)\n except(TypeError, ValueError, OverflowError, User.DoesNotExist):\n user = None\n if user is not None and account_activation_token.check_token(user, token):\n user.is_active = True\n user.save()\n return render(request, 'accounts/active_done.html')\n else:\n return HttpResponse('Activation link is invalid!')","def enable_mfa_device(self, user_name, serial_number,\r\n auth_code_1, auth_code_2):\r\n params = {'UserName' : user_name,\r\n 'SerialNumber' : serial_number,\r\n 'AuthenticationCode1' : auth_code_1,\r\n 'AuthenticationCode2' : auth_code_2}\r\n return self.get_response('EnableMFADevice', params)","def activate_token(request, token):\n # Getting environment from settings\n debug = settings.DEBUG\n\n # Based on the debug redirect the user to correct url\n if debug:\n REDIRECT_URL = 'http://localhost:3000'\n else:\n REDIRECT_URL = 'https://leadbook-challenge.herokuapp.com'\n\n try:\n profile = Profile.objects.get(activation_key=token)\n profile.is_verified = True\n profile.save()\n except Profile.DoesNotExist:\n profile = None\n\n if profile:\n return HttpResponseRedirect('{}/activation/success'.format(REDIRECT_URL))\n else:\n return HttpResponseRedirect('{}/activation/failed'.format(REDIRECT_URL))","def activate(request, uidb64, token):\r\n\ttry:\r\n\t\tuid = force_text(urlsafe_base64_decode(uidb64))\r\n\t\tuser = User.objects.get(pk=uid)\r\n\texcept (TypeError, ValueError, OverflowError, User.DoesNotExist):\r\n\t\tuser = None\r\n\r\n\tif user is not None and account_activation_token.check_token(user, token):\r\n\t\t# User activated and redirected to the homepage\r\n\t\tuser.is_active = True\r\n\t\tuser.profile.email_confirmed = True\r\n\t\tuser.save()\r\n\t\tlogin(request, user, backend='django.contrib.auth.backends.ModelBackend')\r\n\t\tgames = Game.objects.all()\r\n\t\treturn redirect('/', {'games': games, 'MEDIA_URL': settings.MEDIA_URL})\r\n\telse:\r\n\t\treturn render(request, 'account_activation_invalid.html')","def activate_user(request, uidb64, token):\n activation_session_token = '_activation_reset_token'\n activation_url_token = 'user-activation'\n title = \"Account activation\"\n context = {'title': 'Invalid Activation Link', 'isvalid': False}\n\n try:\n uid = force_text(urlsafe_base64_decode(uidb64))\n user = User.objects.get(pk=uid)\n except (TypeError, ValueError, OverflowError, User.DoesNotExist):\n user = None\n\n if user and user.is_active:\n messages.success(request, 'The account is active.')\n return redirect('login')\n\n if request.method == 'GET':\n if token == activation_url_token:\n session_token = request.session.get(activation_session_token)\n if default_token_generator.check_token(user, session_token):\n # If the token is valid, display the password reset form.\n form = forms.ActivationForm(user=user)\n return render(request, 'user/activate_user.html', {\n 'form': form, 'title': title})\n else:\n if default_token_generator.check_token(user, token):\n # Store the token in the session and redirect to the\n # password reset form at a URL without the token. That\n # avoids the possibility of leaking the token in the\n # HTTP Referer header.\n request.session[activation_session_token] = token\n redirect_url = request.path.replace(token, activation_url_token)\n return HttpResponseRedirect(redirect_url)\n else:\n if token == activation_url_token:\n session_token = request.session.get(activation_session_token)\n form = forms.ActivationForm(user=user, data=request.POST)\n if form.is_valid() and default_token_generator.check_token(user, session_token):\n with transaction.atomic():\n user.set_password(form.cleaned_data['password1'])\n user.is_active = True\n # Check legacy credentials\n check_legacy_credentials(user, user.email)\n user.save()\n email = user.associated_emails.first()\n email.verification_date = timezone.now()\n email.is_verified = True\n email.save()\n request.session.pop(activation_session_token)\n logger.info('User activated - {0}'.format(user.email))\n messages.success(request, 'The account has been activated.')\n login(request, user)\n return redirect('project_home')\n return render(request, 'user/activate_user.html', {'form': form,\n 'title': title})\n\n return render(request, 'user/activate_user_complete.html', context)","def activate():\n try:\n body = request.get_json()\n\n activate_token = body[\"activate_token\"]\n password = body[\"password\"]\n\n if len(password) < 3 or len(password) > 50:\n return bad_request()\n\n if not models.token_exists(activate_token):\n\n return bad_request()\n\n student_hash = models.create_hash(password)\n models.save_hash(student_hash, activate_token)\n\n except KeyError:\n return bad_request()\n except Exception as e:\n print(e)\n return server_error()\n\n return created()","def account_activate(request, uidb64, token):\r\n try:\r\n # decode the user's id and get the user by id.\r\n user_id = smart_str(urlsafe_base64_decode(uidb64))\r\n user = get_object_or_404(User, id=user_id)\r\n if user.is_active:\r\n # Display already activated account message\r\n messages.success(request, f'Your Account already activated. You can login.', extra_tags='activation-valid')\r\n # check if the token is valid.\r\n elif account_activation_token.check_token(user, token):\r\n user.is_active = True\r\n # user.previously_logged_in = True\r\n user.save()\r\n # Display activation success message\r\n messages.success(request, f'Your Account has been activated successfully. Now you can login.', extra_tags='activation-valid') \r\n else:\r\n # Display error message.\r\n messages.error(request, f'The activation link is invalid. Please request a new one.', extra_tags='activation-invalid') \r\n except DjangoUnicodeDecodeError:\r\n # Display error message.\r\n messages.error(request, f'The activation link is invalid. Please request a new one.', extra_tags='activation-invalid') \r\n return redirect('accounts:login')","def req_display_otp(self):\n\n ret = self.ui_auth.create_new_one_time_pwd()\n if ret is not None:\n self.error_msg_queue_list.append(ret)","def activate(request, activation_key, template_name='registration/activate.html'):\n activation_key = activation_key.lower() # Normalize before trying anything with it.\n account = RegistrationProfile.objects.activate_user(activation_key)\n account.is_active = True\n account.save()\n return render(request, template_name,\n { 'account': account,\n 'expiration_days': settings.ACCOUNT_ACTIVATION_DAYS })","def activate_account(self):\n self.driver.execute_script(\"window.scrollTo(0, 1000)\")\n self.click_on_element_by_css(tep.ACTIVATION_LINK)\n self.click_on_element_by_css(tep.ACTIVATION_BUTTON)","def activate_factor(self, state_token, factor_id, passcode, relay_state=None):\n request = {\n 'stateToken': state_token,\n 'passCode': passcode,\n 'relayState': relay_state\n }\n\n response = ApiClient.post_path(self, '/factors/{0}/lifecycle/activate'.format(factor_id), request)\n return Utils.deserialize(response.text, AuthResult)","async def set_mfa_and_connect(self, mfa_input: str):\n await self._set_mfa_code(mfa_input)\n await asyncio.sleep(10)\n await self._set_products()","def check_for_activate(self):\n try:\n # Attempt to activate. If the user has completed pairing on the,\n # backend, this will succeed. Otherwise it throws and HTTPError()\n\n token = self.data.get(\"token\")\n login = self.api.activate(self.state, token) # HTTPError() thrown\n\n # When we get here, the pairing code has been entered on the\n # backend and pairing can now be saved.\n # The following is kinda ugly, but it is really critical that we\n # get this saved successfully or we need to let the user know that\n # they have to perform pairing all over again at the website.\n try:\n IdentityManager.save(login)\n except Exception as e:\n self.log.debug(\"First save attempt failed: \" + repr(e))\n time.sleep(2)\n try:\n IdentityManager.save(login)\n except Exception as e2:\n # Something must be seriously wrong\n self.log.debug(\"Second save attempt failed: \" + repr(e2))\n self.abort_and_restart()\n\n if mycroft.audio.is_speaking():\n # Assume speaking is the pairing code. Stop TTS of that.\n mycroft.audio.stop_speaking()\n\n self.enclosure.activate_mouth_events() # clears the display\n\n # Notify the system it is paired\n self.gui.show_page(\"pairing_done.qml\", override_idle=False)\n self.bus.emit(Message(\"mycroft.paired\", login))\n\n self.pairing_performed = True\n with self.pair_dialog_lock:\n if self.mycroft_ready:\n # Tell user they are now paired\n self.speak_dialog(self.paired_dialog)\n mycroft.audio.wait_while_speaking()\n else:\n self.speak_dialog(\"wait.for.startup\")\n mycroft.audio.wait_while_speaking()\n\n # Un-mute. Would have been muted during onboarding for a new\n # unit, and not dangerous to do if pairing was started\n # independently.\n self.bus.emit(Message(\"mycroft.mic.unmute\", None))\n\n # Send signal to update configuration\n self.bus.emit(Message(\"configuration.updated\"))\n\n # Allow this skill to auto-update again\n self.reload_skill = True\n except HTTPError:\n # speak pairing code every 60th second\n with self.counter_lock:\n if self.count == 0:\n self.speak_code()\n self.count = (self.count + 1) % 6\n\n if time.monotonic() > self.time_code_expires:\n # After 20 hours the token times out. Restart\n # the pairing process.\n with self.counter_lock:\n self.count = -1\n self.data = None\n self.handle_pairing()\n else:\n # trigger another check in 10 seconds\n self.__create_activator()\n except Exception as e:\n self.log.debug(\"Unexpected error: \" + repr(e))\n self.abort_and_restart()","def send_mfa(\n self,\n form: object = None, # noqa: ARG002\n code: str = \"\",\n trusted_device: bool = True,\n ) -> None:\n el_otp = self._driver.find_element(By.CSS_SELECTOR, \"input[name=otc]\", timeout=5)\n el_otp.clear()\n el_otp.send_keys(code)\n\n el_verify = self._driver.find_element(By.CSS_SELECTOR, \"input[type=submit]\", timeout=5)\n if el_verify.accessible_name != \"Verify\":\n msg = f'{self.__class__.__name__}: Cannot find \"Verify\" button'\n raise IdpError(msg)\n\n if trusted_device:\n el_verify.click()\n\n self._stay_signed_in()","def activate_user(self, email):\r\n activation_key = Registration.objects.get(user__email=email).activation_key\r\n # and now we try to activate\r\n check_for_get_code(self, 200, reverse('activate', kwargs={'key': activation_key}))\r\n # Now make sure that the user is now actually activated\r\n self.assertTrue(User.objects.get(email=email).is_active)","def _activate_user(self, email):\r\n activation_key = registration(email).activation_key\r\n\r\n # and now we try to activate\r\n resp = self.client.get(reverse('activate', kwargs={'key': activation_key}))\r\n return resp","def activate(ctx: CLIContext, access_key):\n with Session() as session:\n try:\n data = session.KeyPair.activate(access_key)\n except Exception as e:\n ctx.output.print_mutation_error(\n e,\n item_name='keypair',\n action_name='activation',\n )\n sys.exit(1)\n if not data['ok']:\n ctx.output.print_mutation_error(\n msg=data['msg'],\n item_name='keypair',\n action_name='activation',\n )\n sys.exit(1)\n ctx.output.print_mutation_result(\n data,\n extra_info={\n 'access_key': access_key,\n },\n )","def activate_user(activation_code, new_password):\n um = logic.UserManager()\n try:\n user = um.lookup_user_by_activation_code(activation_code)\n user.activate()\n user.set_password(new_password)\n except ex.UserNotFoundError:\n blogger.debug(\"no user found with activation code %s\" % activation_code)\n transaction.abort()\n return dict(activated=False)\n else:\n transaction.commit()\n return dict(activated=True)","def dev_dial(action):\n\n try:\n client = AMIClient(address=AUTH_CREDS['address'], port=AUTH_CREDS['port'])\n client.login(username=AUTH_CREDS['username'], secret=AUTH_CREDS['secret'])\n\n future = client.send_action(action)\n if VERBOSE:\n print(future.response or \"None\")\n\n client.logoff()\n\n except Exception as e:\n print(\"Error: %s\" % e.strerror)\n sys.exit(1)","def activate(self, *args, **kwargs):\n username = self.validate_key(kwargs.get(\"activation_key\"))\n user = self.get_user(username)\n user.is_active = True\n user.save()\n return user","def add_user(self):\n\n pin, code = self.get_auth_pin() \n print(\"Enter the PIN '{}' into the Add Application window and click Add Application\".format(pin))\n input(\"waiting press enter to continue...\")\n\n access_token, refresh_token = self.get_tokens(code)\n user_id = self.tokens.get_next_user_id()\n self.tokens.insert_user(user_id, access_token, refresh_token)\n tstat_ids = self.get_tstat_ids(access_token)\n for tstat_id in tstat_ids:\n logger.info(\"Adding Thermostat ID: {}\".format(tstat_id))\n self.tokens.insert_tstat(user_id, tstat_id)","def send_otp_to_primary_mobile(otp, mobile):\n print('Sending otp to mobile: ', otp, mobile)","def user_activation(user):\n act_hash = random_password(32)\n user.set_hashword(act_hash)\n user.save()\n base_url = url_for('public.home', _external=True)\n act_url = url_for(\n 'auth.activate',\n userid=user.id,\n userhash=act_hash,\n _external=True)\n if not 'mailman' in current_app.extensions:\n logging.warning('E-mail extension has not been configured')\n return act_hash\n msg = EmailMessage()\n msg.subject = 'Your dribdat account'\n msg.body = \\\n \"Hello %s,\\n\" % user.username \\\n + \"Thanks for signing up at %s\\n\\n\" % base_url \\\n + \"Tap here to activate your account:\\n\\n%s\" % act_url\n msg.to = [user.email]\n logging.info('Sending activation mail to user %d' % user.id)\n logging.debug(act_url)\n msg.send(fail_silently=True)\n return act_hash","def activate(self) -> None:\n self._bot.inject_flows_from(self)\n self.is_activated = True","def login_on_activation(sender, user, request, **kwargs):\n user.backend = 'storybase_user.auth.backends.EmailModelBackend'\n login(request, user)","def _turn_on(self):\n logger.info(\"Check antenna power\")\n power = yield WaitDBus(self.gsm_device.GetAntennaPower)\n logger.info(\"antenna power is %d\", power)\n if power:\n yield None\n logger.info(\"turn on antenna power\")\n try:\n yield WaitDBus(self.gsm_device.SetAntennaPower, True)\n except dbus.exceptions.DBusException, ex:\n if ex.get_dbus_name() != 'org.freesmartphone.GSM.SIM.AuthFailed':\n raise\n yield self._ask_pin()","def turn_on_modem(self):\n if not self.is_power_on():\n self._logger.debug(\"Switching modem on...\")\n self.set_pin()\n # give modem some time to login\n time.sleep(10)\n else:\n self._logger.debug(\"Modem is already powered on...\")","def activate_profile(field, code, request):\n try:\n activation = ActivationProfile.objects.get(**{field:code})\n except ActivationProfile.DoesNotExist:\n messages.error(request, _('Activation code expired or not valid!'))\n return False\n if timezone.now() < activation.valid_through:\n activation.user.is_active = True\n activation.user.set_unusable_password()\n activation.user.save()\n if request.user.is_anonymous():\n if field == 'token':\n user = authenticate(username=activation.user.username, token=activation.token)\n elif field == 'sms_key':\n user = authenticate(username=activation.user.username, code=activation.sms_key)\n else:\n user = None\n activation.delete()\n if user:\n login(request, user)\n messages.success(request, _(\"\"\"Profile activated successfully! You should change your password!\"\"\"))\n return True\n else:\n return False\n else:\n messages.success(request, _(\"\"\"You already have an account!\"\"\"))\n return False","def activate(self):\r\n if self.activation_code == '':\r\n raise ValidationError('The member is already activated')\r\n signer = TimestampSigner()\r\n signer.unsign(self.activation_code, max_age=timedelta(days=2))\r\n self.hidden = False\r\n self.activation_code = ''\r\n self.joined_date = timezone.now()\r\n self.save()","def sendOTP(code):\n # Modify the code here to change from print to any output \n print(\"Your OTP is \" + code + \". Kindly do not share it with anyone\")","def activate_account_api():\n\n # get the data for this query\n data = request.get_json()\n if not data:\n response = jsonify({\n 'success': False,\n 'message': 'Missing request body'\n })\n response.status_code = 422\n return response\n\n # process arguments\n arg_email = data.get('email').strip().lower()\n\n # check if there is a user with this activation_link\n secret_link = data.get('secret_link')\n user = db.session.query(User).filter(\n User.activation_link == secret_link,\n ).one_or_none()\n if not user:\n response = jsonify({\n 'success': False,\n 'message': 'This activation link is no longer active. Contact your system administrator to receive a new one.'\n })\n response.status_code = 200\n return response\n\n # check if this user has already activated their account\n if user.activated:\n response = jsonify({\n 'success': False,\n 'message': 'This account has already been activated. Try forgot password to recover your password.'\n })\n response.status_code = 200\n return response\n\n # check if the correct email address was supplied\n if user.email != arg_email:\n response = jsonify({\n 'success': False,\n 'message': 'This is not the correct email for this activation link. Contact your system administrator to request a link for this email.'\n })\n response.status_code = 200\n return response\n\n # generate and set new password\n new_password = generate_password_hash(data.get('password'))\n user.password = new_password\n user.activated = True\n db.session.add(user)\n db.session.commit()\n\n # log that a user just activated their account\n _log('++ {} just activated their account'.format(user.email), '_signup')\n\n # return authenticated token\n token = generate_auth_token(user_id=user.user_id)\n response = jsonify({\n 'success': True,\n 'token': token\n })\n response.status_code = 200\n return response","def apply_auth():\n\tclient = BaiduOpenApi()\n\tapi = client.device.code\n\tresp = client.device.code.get(response_type=\"device_code\", scope=\"netdisk\")\n\t# open grant page and wait for user confirm\n\twebbrowser.open_new_tab(r\"http://openapi.baidu.com/device?code=%s\"%resp[\"user_code\"])\n\t# yield to main\n\tyield\n\t# main will tell user to confirm and it will take a while\n\t# polling to wait server back\n\tpolling_tokens(resp[\"device_code\"], resp[\"interval\"], resp[\"expires_in\"])","def activate(self):\n if not self.is_active:\n self.is_active = True\n self.activated_at = datetime.datetime.utcnow()\n import messaging # avoid circular import\n messaging.send_activated_emails(self)\n self.save()","def activate_pair(device_pair):\n command = 'pair_activate \"%s\"' % (device_pair.identifier,)\n _run_command(command)","def activate_task(self, task_id):\n if task_id is None:\n print('ERROR: task_id cannot be \"None\".')\n return False\n # Else, the task was specified\n if task_id in self.task_dict:\n self.task_dict[task_id].is_activated = True\n # Update the activation state\n self._update_activation_state()\n return True\n else:\n # Something wrong, agent was not in the dict\n print('ERROR: The task <%s> is not in the task_dict at agent <%d>.' % (str(task_id), self.agent_id))\n return False","def activate(self):\r\n self.update_enrollment(is_active=True)","def confirm(id):\n #: get resources\n user = User.query.get_or_404(id)\n service = SignUpService(user)\n input_token = request.args['token']\n\n #: active current account\n try:\n service.active(input_token)\n except TokenUsedError:\n message = _(u\"The account had been actived.\")\n return render_template(\"confirm-failed.html\", message=message), 403\n except TokenWrongError:\n message = _(u\"The active token is invalid.\")\n return render_template(\"confirm-failed.html\", message=message), 403\n\n #: automatic sign in\n session_login(user)\n #: output a success message\n message = _(u\"The account has been actived successfully.\")\n return render_template(\"confirm-success.html\", message=message)","def test_yes_option_enabled(\n self, wait_tx_settled_mock, confirm_mock, do_transfer_mock\n ):\n password_option = self.get_password_args(self.PASSWORD)\n self.invoke(\n \"transfer\",\n self.LEDGER_ID,\n self.get_address(self.LEDGER_ID, self.PASSWORD),\n \"100000\",\n \"100\",\n \"-y\",\n *password_option,\n )\n confirm_mock.assert_not_called()","def activate_user(self, user):\n if not user.active:\n user.active = True\n return True\n return False","def activate_user(username, code, new_pass):\r\n\r\n qry = Activation.query.\\\r\n filter(Activation.code == code).\\\r\n filter(User.username == username)\r\n\r\n res = qry.first()\r\n\r\n if UserMgr.acceptable_password(new_pass) and res is not None:\r\n user = res.user\r\n user.activated = True\r\n user.password = new_pass\r\n res.activate()\r\n\r\n LOG.debug(dict(user))\r\n\r\n return True\r\n else:\r\n return None","async def async_press(self) -> None:\n try:\n await self.entity_description.press_func(self.device)\n except DevicePasswordProtected as ex:\n self.entry.async_start_reauth(self.hass)\n raise HomeAssistantError(\n f\"Device {self.entry.title} require re-authenticatication to set or change the password\"\n ) from ex\n except DeviceUnavailable as ex:\n raise HomeAssistantError(\n f\"Device {self.entry.title} did not respond\"\n ) from ex","def activate(request, activation_key,\r\n template_name='registration/activate.html',\r\n extra_context=None):\r\n activation_key = activation_key.lower() # Normalize before trying anything with it.\r\n account = RegistrationProfile.objects.activate_user(activation_key)\r\n if extra_context is None:\r\n extra_context = {}\r\n context = RequestContext(request)\r\n for key, value in extra_context.items():\r\n context[key] = callable(value) and value() or value\r\n return render_to_response(template_name,\r\n { 'account': account,\r\n 'expiration_days': settings.ACCOUNT_ACTIVATION_DAYS },\r\n context_instance=context)","def login_auto(token: Token, mac_address: str) -> bool:\n device = Device.get_by_mac(mac_address)\n fail_msg = \"\"\n if device is None:\n fail_msg = \"No device with mac address exist\"\n elif Token.is_token_expired(device.token_expires):\n fail_msg = \"Token is expired\"\n elif token != device.token:\n fail_msg = \"Wrong token\"\n if fail_msg:\n client_logger_security().info(f\"Failed to login automatically: {fail_msg}\")\n return False\n else:\n _set_user_authenticated(device.user_id, device.device_id)\n client_logger_security().info(f\"Successfully logged in automatically: device_id={device.device_id}, \"\n f\"user_id={device.user_id}\")\n return True","def do_mfa_verify(mfa_info):\n headers = {\n \"Content-Type\": \"application/json\",\n \"Origin\": \"https://%s.auth0.com\"%TENANT,\n \"Authorization\": \"Bearer %s\"%mfa_info[\"requestToken\"],\n \"x-global-tracking-id\": mfa_info[\"globalTrackingId\"]\n }\n request = urllib.request.Request(\n \"%s/api/start-flow\"%mfa_info[\"mfaServerUrl\"],\n data=json.dumps({ \"state_transport\": \"polling\" }).encode(),\n method=\"POST\",\n headers=headers)\n try:\n response = urllib.request.urlopen(request)\n result = response.read().decode()\n except urllib.error.HTTPError as e:\n error = e.read().decode()\n raise RuntimeError(\"MFA start flow error: %s\"%error) from None\n mfa_flow_info = json.loads(result)\n mfa_transaction_token = mfa_flow_info[\"transaction_token\"]\n # print(mfa_flow_info)\n # print(mfa_transaction_token)\n\n mfa_code = input(\"Please enter your MFA verification code: \")\n mfa_payload = {\n \"code\": mfa_code,\n \"type\": \"manual_input\"\n }\n mfa_payload_json = json.dumps(mfa_payload).encode()\n headers = {\n \"Content-Type\": \"application/json\",\n \"Origin\": \"https://%s.auth0.com\"%TENANT,\n \"Authorization\": \"Bearer %s\"%mfa_transaction_token,\n \"x-global-tracking-id\": mfa_info[\"globalTrackingId\"]\n }\n request = urllib.request.Request(\n \"%s/api/verify-otp\"%mfa_info[\"mfaServerUrl\"],\n data=mfa_payload_json,\n method=\"POST\",\n headers=headers)\n try:\n response = urllib.request.urlopen(request)\n result = response.read().decode()\n except urllib.error.HTTPError as e:\n error = e.read().decode()\n raise RuntimeError(\"MFA verify error: %s\"%error) from None\n # print(result)\n\n headers = {\n \"Origin\": \"https://%s.auth0.com\"%TENANT,\n \"Authorization\": \"Bearer %s\"%mfa_transaction_token,\n \"x-global-tracking-id\": mfa_info[\"globalTrackingId\"]\n }\n request = urllib.request.Request(\n \"%s/api/transaction-state\"%mfa_info[\"mfaServerUrl\"],\n method=\"POST\",\n headers=headers)\n try:\n response = urllib.request.urlopen(request)\n result = response.read().decode()\n except urllib.error.HTTPError as e:\n error = e.read().decode()\n raise RuntimeError(\"Get MFA result error: %s\"%error) from None\n mfa_result = json.loads(result)\n if mfa_result[\"state\"] != \"accepted\":\n raise RuntimeError(\"MFA verification is not accepted: %s\"%result)\n # print(mfa_result)\n\n return mfa_result","async def async_turn_on_when_active(self, **kwargs: Any) -> None:\n await self._data.controller.programs.start(self.entity_description.uid)\n self._update_activities()","def send_mfa(self):\n\n try:\n response = self.post(\"/authentication/loginToken\",\n {\"user\": self.user, \"password\": self.password, \"TempCode\": True})\n except:\n print(\"Exception - unable to submit token request\")\n return False\n return True if response.status_code in [200, 204] else False","def set_time_based_otp(self, otp_passcode: str):\n self._totp = TOTP(otp_passcode)","def activateWebAppUser( self, username, activation_code ):\n try:\n con = self.getMetadataDatabaseConnection()\n user_data = con.cursor()\n\n con.cursor().callproc('verify_user_activation_code', [username, activation_code, user_data])\n row = user_data.fetchone()\n if row:\n con.cursor().callproc('activate_user_account', [username])\n return True\n else:\n return False\n except Exception, e:\n print 'Exception caught: %s.\\nThe error is: %s' % (type(e), e)\n return False","def test_user_activation(self):\n user = User.objects.get()\n response = self.client.get(reverse('accounts:user-activate',\n kwargs={'uidb64': urlsafe_base64_encode(force_bytes(user.pk)),\n 'token': account_activation_token.make_token(user)}))\n self.assertEqual(response.status_code, status.HTTP_200_OK)","def activate(request, activation_key,template_name='registration/activate.html',extra_context=None):\n\tactivation_key = activation_key.lower() # Normalize before trying anything with it.\n\taccount = RegistrationProfile.objects.activate_user(activation_key)\n\t\n\t\n\t#new profile PROBLEME NON ENREGISTREMENT DU PROFILE\n\t#recuperer l user id de l'account user.id\n\tprofile = UserProfile();\n\tprofile.user = account\n\tprofile.save()\n\t\n\t\n\tif extra_context is None:\n\t\textra_context = {}\n\tcontext = RequestContext(request)\n\tfor key, value in extra_context.items():\n\t\tcontext[key] = callable(value) and value() or value\n\treturn render_to_response(template_name,{ 'account': account,'expiration_days': settings.ACCOUNT_ACTIVATION_DAYS }, context_instance=context)","def active_user(request, uidb36=None, token=None,\r\n template_name='register/activation_confirm.html',\r\n token_generator=default_token_generator,\r\n current_app=None, extra_context=None):\r\n assert uidb36 is not None and token is not None # checked by URLconf\r\n \r\n try:\r\n uid_int = base36_to_int(uidb36)\r\n user = User.objects.get(id=uid_int)\r\n except (ValueError, User.DoesNotExist):\r\n user = None\r\n\r\n if user is not None and token_generator.check_token(user, token):\r\n validlink = True\r\n user.is_active = True\r\n user.save()\r\n \r\n #初始化userprofile\r\n profile_count = UserProfile.objects.filter(user=user).count()\r\n if profile_count == 0:\r\n profile = UserProfile()\r\n profile.user = user\r\n profile.song_ord_filed = 'post_datetime'\r\n profile.save()\r\n else:\r\n validlink = False\r\n context = {\r\n 'validlink': validlink,\r\n }\r\n context.update(extra_context or {})\r\n return render_to_response(template_name, context,\r\n context_instance=RequestContext(request, current_app=current_app))","def enable_call_waiting(self, dtmf_code: str) -> None:","def activate_user(self, user):\n if not user.active:\n user.active = True\n # noinspection PyUnresolvedReferences\n self.save(user)\n return True\n\n return","async def _autopaired(self, new_user_apc_token: str):\n self._user_apc_token = new_user_apc_token\n self._fconfigure()","def test_activate_active_user(self):\n activate_user(self.user, self.request)\n self.assertEqual(self.user.is_active, True)","def test_create_user_auto_activate(self, services):\n data = {\n 'username': 'John',\n 'email': 'John@mailinator.com',\n 'password': 'test123!',\n 'phone': '1234567890',\n 'first_name': 'Chuck',\n 'last_name': 'Norris',\n 'university': {\n \"name\": \"random_university\"\n },\n 'academic_field': {'name': \"random_field\"},\n 'academic_level': {'name': \"random_level\"},\n 'gender': \"M\",\n 'birthdate': \"1999-11-11\",\n }\n\n response = self.client.post(\n reverse('user-list'),\n data,\n format='json',\n )\n\n self.assertEqual(response.status_code, status.HTTP_201_CREATED)\n self.assertEqual(json.loads(response.content)['phone'], '1234567890')\n\n user = User.objects.get(email=\"John@mailinator.com\")\n activation_token = ActionToken.objects.filter(\n user=user,\n type='account_activation',\n )\n\n self.assertTrue(user.is_active)\n self.assertEqual(1, len(activation_token))\n\n # Test that no email was sent:\n self.assertEqual(len(mail.outbox), 0)","def account_activate(request):\r\n params = request.params\r\n\r\n username = params.get('username', None)\r\n activation = params.get('code', None)\r\n password = params.get('password', None)\r\n new_username = params.get('new_username', None)\r\n\r\n if username is None and activation is None and password is None:\r\n # then try to get the same fields out of a json body\r\n json_body = request.json_body\r\n username = json_body.get('username', None)\r\n activation = json_body.get('code', None)\r\n password = json_body.get('password', None)\r\n new_username = json_body.get('new_username', None)\r\n\r\n if not UserMgr.acceptable_password(password):\r\n request.response.status_int = 406\r\n return _api_response(request, {\r\n 'error': \"Come on, pick a real password please\",\r\n })\r\n\r\n username = username.lower()\r\n new_username = new_username.lower() if new_username else None\r\n res = ActivationMgr.activate_user(\r\n username,\r\n activation,\r\n password)\r\n\r\n if res:\r\n # success so respond nicely\r\n AuthLog.reactivate(username, success=True, code=activation)\r\n\r\n # if there's a new username and it's not the same as our current\r\n # username, update it\r\n if new_username and new_username != username:\r\n try:\r\n user = UserMgr.get(username=username)\r\n user.username = new_username\r\n except IntegrityError, exc:\r\n request.response.status_int = 500\r\n return _api_response(request, {\r\n 'error': 'There was an issue setting your new username',\r\n 'exc': str(exc)\r\n })\r\n\r\n return _api_response(request, {\r\n 'message': \"Account activated, please log in.\",\r\n 'username': username,\r\n })\r\n else:\r\n AuthLog.reactivate(username, success=False, code=activation)\r\n request.response.status_int = 500\r\n return _api_response(request, {\r\n 'error': \"There was an issue attempting to activate this account.\",\r\n })","def activate(request, activation_key):\n profile = get_object_or_404(User, activation_key=activation_key)\n if profile.akey_expires < timezone.now():\n return render('user_account/activate.html', {'expired': True})\n\n profile.save(update_fields=['active', 'activation_key'])\n return render(\n 'user_account/activate.html',\n {'success': True, 'name': profile.name + \" \" + profile.surname}\n )","def begin_trial(self):\n self._post(endpoint='{}/cm/trial/begin'.format(self.api_version))","def enable_radio(self):\n self.acquire_response(b'AT*R1')","def do_masterpassword(self, masterpassword):\n if masterpassword:\n if self.taskstarted == True:\n self.masterpassword = masterpassword\n else:\n if self.taskstarted == False:\n print(self.cl.red(\"[!] You need to start a new KeePass Interaction.\"))\n print(self.cl.red(\"[!] Start this with 'new' from the menu.\"))\n print(\"[!] You need to supply the command for typing\")","def auth_active(hass):\n hass.loop.run_until_complete(\n register_auth_provider(hass, {\"type\": \"homeassistant\"})\n )","async def enter_confirmation_сode(self):\n raise VkTwoFactorCodeNeeded()","def activate_user(self, username):\n args = parser_activate.parse_args()\n isActive = request.json.get('isactive')\n\n query = \"\"\"UPDATE users SET isactive=%s WHERE username=%s\"\"\"\n values = isActive, username\n\n conn = self.db\n cursor = conn.cursor()\n cursor.execute(query, values)\n conn.commit()\n return True","def activate(self):\n\t\tself.flash()\n\t\tself.do_action()","def test_activate_user(self):\n activated_user = (RegistrationProfile.objects\n .activate_user(self.activation_key))\n self.assertTrue(activated_user.registrationprofile.activated)\n self.assertFalse(activated_user.is_active)","def enable_aaa_password_restriction(device):\n cmd=\"aaa password restriction\"\n try:\n device.configure(cmd)\n except SubCommandFailure as e:\n raise SubCommandFailure(\n f'Could not configure aaa password restriction:\\n{e}'\n )","def test_pm_profile_activate(profile_manager, test_profile):\n\n profile_manager.activate(test_profile.name)\n assert profile_manager.is_active(test_profile.name)\n profile = profile_manager.get_active_profile()\n assert profile.name == test_profile.name\n assert profile.path == test_profile.path","def activate():\n refresh()\n activate_connection_with_mainloop(get_uuid())","def enable_aaa_authentication_login(device,auth_list,auth_db1,auth_db2=None):\n\n cmd = f'aaa authentication login {auth_list} {auth_db1}'\n if auth_db2:\n cmd += f' {auth_db2}'\n try:\n device.configure(cmd)\n except SubCommandFailure as e:\n raise SubCommandFailure(\n f'Could not configure aaa authentication login:\\n{e}'\n )","def authenticate_bluetooth(self):\n data = self.blu.main()\n if bool(data) == True:\n authentication = self.client.validate_mac(\n data[\"mac_address\"], data[\"email\"]).decode(\"utf-8\")\n if authentication == \"valid\":\n self.current_email = data[\"email\"]\n self.unlock_time = round(datetime.now().timestamp())\n self.display_successful_unlock_eng()\n elif authentication == \"invalid\":\n print(self.INVALID_USER)\n time.sleep(3)\n self.display_main()\n else:\n self.display_eng()","def admin_action(self):\n SCREEN_MANAGER.current = 'passCode'","def activate_user(self, activation_key):\n if SHA1_RE.search(activation_key):\n try:\n profile = RegistrationProfile.objects.get(activation_key=activation_key)\n except self.model.DoesNotExist:\n return False\n if not profile.activation_key_expired():\n user = profile.user\n user.is_active = True\n user.save()\n profile.activation_key = \"ALREADY_ACTIVATED\"\n profile.save()\n return user\n\n return False","def signup_active(request, uidb36=None, token=None,\n post_activation_redirect=None,\n token_generator=default_token_generator,\n domain_override=None, use_https=False):\n assert uidb36 is not None and token is not None\n if post_activation_redirect is None:\n post_activation_redirect = reverse('amscms.core.views.signup_active_done')\n try:\n uid_int = base36_to_int(uidb36)\n user = User.objects.get(id=uid_int)\n except (ValueError, User.DoesNotExists):\n user = None\n \n if user is not None and token_generator.check_token(user, token):\n user.is_active = True\n user.save()\n \"\"\"\n Sends successful email to the user. \n \"\"\"\n if not domain_override:\n current_site = Site.objects.get_current()\n site_name = current_site.name\n domain = current_site.domain\n else:\n site_name = domain = domain_override\n c = {\n 'subject': _(u\"Registration was successful on %(site_name)s\" % {'site_name': site_name, }),\n 'site_name': site_name,\n 'user': user,\n 'domain': domain,\n 'protocol': use_https and 'https' or 'http',\n 'login_url': reverse('django.contrib.auth.views.login'),\n }\n send_email(user.email, c, settings.DEFAULT_FROM_EMAIL,\n \"registration/signup_email_activated.txt\",\n \"registration/signup_email_activated.html\")\n \n else:\n messages.error(request, _(u\"Invalid activation link, you may already activated, try to login. \"))\n return HttpResponseRedirect(\"/\")\n return HttpResponseRedirect(post_activation_redirect)","def activate_user(cls, activation_key):\n #from registration.signals import user_activated\n \n # Make sure the key we're trying conforms to the pattern of a\n # SHA1 hash; if it doesn't, no point trying to look it up in\n # the database.\n db = DB_Session()\n if SHA1_RE.search(activation_key):\n query = db.query(RegistrationProfile)\n profile = query.filter(RegistrationProfile.activation_key == activation_key).one()\n if not profile:\n return False\n if not profile.activation_key_expired():\n user = profile.user\n user.is_active = 1\n profile.activation_key = RegistrationProfile.ACTIVATED\n db.flush()\n db.commit()\n db.close()\n #user_activated.send(sender=self.model, user=user)\n return user\n return False","def mifare_auth_a(self,address,key_a):\n if self._uid == False:\n raise RuntimeError(\"No Mifare card currently activated.\")\n if len(self._uid) == 4:\n uid = self._uid\n elif len(self._uid) == 7: # 10-byte UID cards don't exist yet.\n uid = self._uid[3:7] # Sequence 1, keep it simple.\n self.in_data_exchange(bytearray([MIFARE_COMMAND_AUTH_A,address]) + key_a + uid)","def activate_user(self, activation_key, request=None):\n # Make sure the key we're trying conforms to the pattern of a\n # SHA1 hash; if it doesn't, no point trying to look it up in\n # the database.\n if SHA1_RE.search(activation_key):\n try:\n profile = self.get(activation_key=activation_key)\n except self.model.DoesNotExist:\n profile = None\n statsd.incr('user.activate-error.does-not-exist')\n reason = 'key not found'\n if profile:\n if not profile.activation_key_expired():\n user = profile.user\n user.is_active = True\n user.save()\n\n # We don't need the RegistrationProfile anymore, delete it.\n profile.delete()\n\n # If user registered as contributor, send them the\n # welcome email.\n if user.groups.filter(name=CONTRIBUTOR_GROUP):\n self._send_email(\n confirmation_profile=profile,\n url=None,\n subject=_('Welcome to SUMO!'),\n text_template='users/email/contributor.ltxt',\n html_template='users/email/contributor.html',\n send_to=user.email,\n contributor=user)\n\n return user\n else:\n statsd.incr('user.activate-error.expired')\n reason = 'key expired'\n else:\n statsd.incr('user.activate-error.invalid-key')\n reason = 'invalid key'\n\n log.warning(u'User activation failure ({r}): {k}'.format(\n r=reason, k=activation_key))\n\n return False","def user(self, user_token, user_device=None):\n self.set('user', user_token)\n self.set('device', user_device)","def confirm_start(self, player=str):\n self.clear_screen()\n print(\"\\n\" * 11)\n pass_text = \"Pass the device to \" + player\n print(f\"{pass_text : ^100}\")\n input(f\"{'Press ENTER when ready.' : ^100}\")\n return self.stop_game","def check_mfa(self) -> None:\n try:\n mfa_form = self._driver.find_element(By.CSS_SELECTOR, \"form[name=form]\", timeout=5)\n self._driver.find_element(By.CSS_SELECTOR, \"input[name=otc]\", timeout=5)\n self._halo.stop()\n mfacode = self._csc.prompt_for(\"MFA Code\")\n self._halo.start(SPINNER_MSGS[\"mfa_send\"])\n self.send_mfa(form=mfa_form, code=mfacode)\n self._halo.start(SPINNER_MSGS[\"token_refresh\"])\n self._driver.dump_cookies()\n except selenium.common.exceptions.TimeoutException:\n pass","def test_activate_authenticated(client):\n employee = factories.EmployeeFactory(\n company=factories.CompanyFactory(),\n account_status=False\n )\n with client.session_transaction() as session:\n session[\"user_id\"] = employee.id\n g.user = employee\n response = client.post(\"/auth/activate\")\n assert b\" should be {bool}, {type(value)} given.\")\n\n self._activated = value"],"string":"[\n \"async def activate_application_token(self, apptoken, temptoken) -> bool:\\n await self.raw_request(\\n self.URL_ACTIVATE.format(apptoken=apptoken, temptoken=temptoken)\\n )\\n return True\",\n \"def activate(request, uidb64, token):\\n try:\\n uid = force_text(urlsafe_base64_decode(uidb64))\\n user = User.objects.get(pk=uid)\\n except (TypeError, ValueError, OverflowError, User.DoesNotExist):\\n user = None\\n\\n if user is not None and account_activation_token.check_token(user, token):\\n user.is_active = True\\n user.profile.email_confirmed = True\\n user.save()\\n login(request, user)\\n return redirect('home')\\n else:\\n return render(request, 'registration/activation_invalid.html')\",\n \"def activate(request, uidb64, token):\\n try:\\n uid = force_text(urlsafe_base64_decode(uidb64))\\n user = User.objects.get(pk=uid)\\n except(TypeError, ValueError, OverflowError, User.DoesNotExist):\\n user = None\\n if user is not None and account_activation_token.check_token(user, token):\\n user.is_active = True\\n user.save()\\n return render(request, 'accounts/active_done.html')\\n else:\\n return HttpResponse('Activation link is invalid!')\",\n \"def enable_mfa_device(self, user_name, serial_number,\\r\\n auth_code_1, auth_code_2):\\r\\n params = {'UserName' : user_name,\\r\\n 'SerialNumber' : serial_number,\\r\\n 'AuthenticationCode1' : auth_code_1,\\r\\n 'AuthenticationCode2' : auth_code_2}\\r\\n return self.get_response('EnableMFADevice', params)\",\n \"def activate_token(request, token):\\n # Getting environment from settings\\n debug = settings.DEBUG\\n\\n # Based on the debug redirect the user to correct url\\n if debug:\\n REDIRECT_URL = 'http://localhost:3000'\\n else:\\n REDIRECT_URL = 'https://leadbook-challenge.herokuapp.com'\\n\\n try:\\n profile = Profile.objects.get(activation_key=token)\\n profile.is_verified = True\\n profile.save()\\n except Profile.DoesNotExist:\\n profile = None\\n\\n if profile:\\n return HttpResponseRedirect('{}/activation/success'.format(REDIRECT_URL))\\n else:\\n return HttpResponseRedirect('{}/activation/failed'.format(REDIRECT_URL))\",\n \"def activate(request, uidb64, token):\\r\\n\\ttry:\\r\\n\\t\\tuid = force_text(urlsafe_base64_decode(uidb64))\\r\\n\\t\\tuser = User.objects.get(pk=uid)\\r\\n\\texcept (TypeError, ValueError, OverflowError, User.DoesNotExist):\\r\\n\\t\\tuser = None\\r\\n\\r\\n\\tif user is not None and account_activation_token.check_token(user, token):\\r\\n\\t\\t# User activated and redirected to the homepage\\r\\n\\t\\tuser.is_active = True\\r\\n\\t\\tuser.profile.email_confirmed = True\\r\\n\\t\\tuser.save()\\r\\n\\t\\tlogin(request, user, backend='django.contrib.auth.backends.ModelBackend')\\r\\n\\t\\tgames = Game.objects.all()\\r\\n\\t\\treturn redirect('/', {'games': games, 'MEDIA_URL': settings.MEDIA_URL})\\r\\n\\telse:\\r\\n\\t\\treturn render(request, 'account_activation_invalid.html')\",\n \"def activate_user(request, uidb64, token):\\n activation_session_token = '_activation_reset_token'\\n activation_url_token = 'user-activation'\\n title = \\\"Account activation\\\"\\n context = {'title': 'Invalid Activation Link', 'isvalid': False}\\n\\n try:\\n uid = force_text(urlsafe_base64_decode(uidb64))\\n user = User.objects.get(pk=uid)\\n except (TypeError, ValueError, OverflowError, User.DoesNotExist):\\n user = None\\n\\n if user and user.is_active:\\n messages.success(request, 'The account is active.')\\n return redirect('login')\\n\\n if request.method == 'GET':\\n if token == activation_url_token:\\n session_token = request.session.get(activation_session_token)\\n if default_token_generator.check_token(user, session_token):\\n # If the token is valid, display the password reset form.\\n form = forms.ActivationForm(user=user)\\n return render(request, 'user/activate_user.html', {\\n 'form': form, 'title': title})\\n else:\\n if default_token_generator.check_token(user, token):\\n # Store the token in the session and redirect to the\\n # password reset form at a URL without the token. That\\n # avoids the possibility of leaking the token in the\\n # HTTP Referer header.\\n request.session[activation_session_token] = token\\n redirect_url = request.path.replace(token, activation_url_token)\\n return HttpResponseRedirect(redirect_url)\\n else:\\n if token == activation_url_token:\\n session_token = request.session.get(activation_session_token)\\n form = forms.ActivationForm(user=user, data=request.POST)\\n if form.is_valid() and default_token_generator.check_token(user, session_token):\\n with transaction.atomic():\\n user.set_password(form.cleaned_data['password1'])\\n user.is_active = True\\n # Check legacy credentials\\n check_legacy_credentials(user, user.email)\\n user.save()\\n email = user.associated_emails.first()\\n email.verification_date = timezone.now()\\n email.is_verified = True\\n email.save()\\n request.session.pop(activation_session_token)\\n logger.info('User activated - {0}'.format(user.email))\\n messages.success(request, 'The account has been activated.')\\n login(request, user)\\n return redirect('project_home')\\n return render(request, 'user/activate_user.html', {'form': form,\\n 'title': title})\\n\\n return render(request, 'user/activate_user_complete.html', context)\",\n \"def activate():\\n try:\\n body = request.get_json()\\n\\n activate_token = body[\\\"activate_token\\\"]\\n password = body[\\\"password\\\"]\\n\\n if len(password) < 3 or len(password) > 50:\\n return bad_request()\\n\\n if not models.token_exists(activate_token):\\n\\n return bad_request()\\n\\n student_hash = models.create_hash(password)\\n models.save_hash(student_hash, activate_token)\\n\\n except KeyError:\\n return bad_request()\\n except Exception as e:\\n print(e)\\n return server_error()\\n\\n return created()\",\n \"def account_activate(request, uidb64, token):\\r\\n try:\\r\\n # decode the user's id and get the user by id.\\r\\n user_id = smart_str(urlsafe_base64_decode(uidb64))\\r\\n user = get_object_or_404(User, id=user_id)\\r\\n if user.is_active:\\r\\n # Display already activated account message\\r\\n messages.success(request, f'Your Account already activated. You can login.', extra_tags='activation-valid')\\r\\n # check if the token is valid.\\r\\n elif account_activation_token.check_token(user, token):\\r\\n user.is_active = True\\r\\n # user.previously_logged_in = True\\r\\n user.save()\\r\\n # Display activation success message\\r\\n messages.success(request, f'Your Account has been activated successfully. Now you can login.', extra_tags='activation-valid') \\r\\n else:\\r\\n # Display error message.\\r\\n messages.error(request, f'The activation link is invalid. Please request a new one.', extra_tags='activation-invalid') \\r\\n except DjangoUnicodeDecodeError:\\r\\n # Display error message.\\r\\n messages.error(request, f'The activation link is invalid. Please request a new one.', extra_tags='activation-invalid') \\r\\n return redirect('accounts:login')\",\n \"def req_display_otp(self):\\n\\n ret = self.ui_auth.create_new_one_time_pwd()\\n if ret is not None:\\n self.error_msg_queue_list.append(ret)\",\n \"def activate(request, activation_key, template_name='registration/activate.html'):\\n activation_key = activation_key.lower() # Normalize before trying anything with it.\\n account = RegistrationProfile.objects.activate_user(activation_key)\\n account.is_active = True\\n account.save()\\n return render(request, template_name,\\n { 'account': account,\\n 'expiration_days': settings.ACCOUNT_ACTIVATION_DAYS })\",\n \"def activate_account(self):\\n self.driver.execute_script(\\\"window.scrollTo(0, 1000)\\\")\\n self.click_on_element_by_css(tep.ACTIVATION_LINK)\\n self.click_on_element_by_css(tep.ACTIVATION_BUTTON)\",\n \"def activate_factor(self, state_token, factor_id, passcode, relay_state=None):\\n request = {\\n 'stateToken': state_token,\\n 'passCode': passcode,\\n 'relayState': relay_state\\n }\\n\\n response = ApiClient.post_path(self, '/factors/{0}/lifecycle/activate'.format(factor_id), request)\\n return Utils.deserialize(response.text, AuthResult)\",\n \"async def set_mfa_and_connect(self, mfa_input: str):\\n await self._set_mfa_code(mfa_input)\\n await asyncio.sleep(10)\\n await self._set_products()\",\n \"def check_for_activate(self):\\n try:\\n # Attempt to activate. If the user has completed pairing on the,\\n # backend, this will succeed. Otherwise it throws and HTTPError()\\n\\n token = self.data.get(\\\"token\\\")\\n login = self.api.activate(self.state, token) # HTTPError() thrown\\n\\n # When we get here, the pairing code has been entered on the\\n # backend and pairing can now be saved.\\n # The following is kinda ugly, but it is really critical that we\\n # get this saved successfully or we need to let the user know that\\n # they have to perform pairing all over again at the website.\\n try:\\n IdentityManager.save(login)\\n except Exception as e:\\n self.log.debug(\\\"First save attempt failed: \\\" + repr(e))\\n time.sleep(2)\\n try:\\n IdentityManager.save(login)\\n except Exception as e2:\\n # Something must be seriously wrong\\n self.log.debug(\\\"Second save attempt failed: \\\" + repr(e2))\\n self.abort_and_restart()\\n\\n if mycroft.audio.is_speaking():\\n # Assume speaking is the pairing code. Stop TTS of that.\\n mycroft.audio.stop_speaking()\\n\\n self.enclosure.activate_mouth_events() # clears the display\\n\\n # Notify the system it is paired\\n self.gui.show_page(\\\"pairing_done.qml\\\", override_idle=False)\\n self.bus.emit(Message(\\\"mycroft.paired\\\", login))\\n\\n self.pairing_performed = True\\n with self.pair_dialog_lock:\\n if self.mycroft_ready:\\n # Tell user they are now paired\\n self.speak_dialog(self.paired_dialog)\\n mycroft.audio.wait_while_speaking()\\n else:\\n self.speak_dialog(\\\"wait.for.startup\\\")\\n mycroft.audio.wait_while_speaking()\\n\\n # Un-mute. Would have been muted during onboarding for a new\\n # unit, and not dangerous to do if pairing was started\\n # independently.\\n self.bus.emit(Message(\\\"mycroft.mic.unmute\\\", None))\\n\\n # Send signal to update configuration\\n self.bus.emit(Message(\\\"configuration.updated\\\"))\\n\\n # Allow this skill to auto-update again\\n self.reload_skill = True\\n except HTTPError:\\n # speak pairing code every 60th second\\n with self.counter_lock:\\n if self.count == 0:\\n self.speak_code()\\n self.count = (self.count + 1) % 6\\n\\n if time.monotonic() > self.time_code_expires:\\n # After 20 hours the token times out. Restart\\n # the pairing process.\\n with self.counter_lock:\\n self.count = -1\\n self.data = None\\n self.handle_pairing()\\n else:\\n # trigger another check in 10 seconds\\n self.__create_activator()\\n except Exception as e:\\n self.log.debug(\\\"Unexpected error: \\\" + repr(e))\\n self.abort_and_restart()\",\n \"def send_mfa(\\n self,\\n form: object = None, # noqa: ARG002\\n code: str = \\\"\\\",\\n trusted_device: bool = True,\\n ) -> None:\\n el_otp = self._driver.find_element(By.CSS_SELECTOR, \\\"input[name=otc]\\\", timeout=5)\\n el_otp.clear()\\n el_otp.send_keys(code)\\n\\n el_verify = self._driver.find_element(By.CSS_SELECTOR, \\\"input[type=submit]\\\", timeout=5)\\n if el_verify.accessible_name != \\\"Verify\\\":\\n msg = f'{self.__class__.__name__}: Cannot find \\\"Verify\\\" button'\\n raise IdpError(msg)\\n\\n if trusted_device:\\n el_verify.click()\\n\\n self._stay_signed_in()\",\n \"def activate_user(self, email):\\r\\n activation_key = Registration.objects.get(user__email=email).activation_key\\r\\n # and now we try to activate\\r\\n check_for_get_code(self, 200, reverse('activate', kwargs={'key': activation_key}))\\r\\n # Now make sure that the user is now actually activated\\r\\n self.assertTrue(User.objects.get(email=email).is_active)\",\n \"def _activate_user(self, email):\\r\\n activation_key = registration(email).activation_key\\r\\n\\r\\n # and now we try to activate\\r\\n resp = self.client.get(reverse('activate', kwargs={'key': activation_key}))\\r\\n return resp\",\n \"def activate(ctx: CLIContext, access_key):\\n with Session() as session:\\n try:\\n data = session.KeyPair.activate(access_key)\\n except Exception as e:\\n ctx.output.print_mutation_error(\\n e,\\n item_name='keypair',\\n action_name='activation',\\n )\\n sys.exit(1)\\n if not data['ok']:\\n ctx.output.print_mutation_error(\\n msg=data['msg'],\\n item_name='keypair',\\n action_name='activation',\\n )\\n sys.exit(1)\\n ctx.output.print_mutation_result(\\n data,\\n extra_info={\\n 'access_key': access_key,\\n },\\n )\",\n \"def activate_user(activation_code, new_password):\\n um = logic.UserManager()\\n try:\\n user = um.lookup_user_by_activation_code(activation_code)\\n user.activate()\\n user.set_password(new_password)\\n except ex.UserNotFoundError:\\n blogger.debug(\\\"no user found with activation code %s\\\" % activation_code)\\n transaction.abort()\\n return dict(activated=False)\\n else:\\n transaction.commit()\\n return dict(activated=True)\",\n \"def dev_dial(action):\\n\\n try:\\n client = AMIClient(address=AUTH_CREDS['address'], port=AUTH_CREDS['port'])\\n client.login(username=AUTH_CREDS['username'], secret=AUTH_CREDS['secret'])\\n\\n future = client.send_action(action)\\n if VERBOSE:\\n print(future.response or \\\"None\\\")\\n\\n client.logoff()\\n\\n except Exception as e:\\n print(\\\"Error: %s\\\" % e.strerror)\\n sys.exit(1)\",\n \"def activate(self, *args, **kwargs):\\n username = self.validate_key(kwargs.get(\\\"activation_key\\\"))\\n user = self.get_user(username)\\n user.is_active = True\\n user.save()\\n return user\",\n \"def add_user(self):\\n\\n pin, code = self.get_auth_pin() \\n print(\\\"Enter the PIN '{}' into the Add Application window and click Add Application\\\".format(pin))\\n input(\\\"waiting press enter to continue...\\\")\\n\\n access_token, refresh_token = self.get_tokens(code)\\n user_id = self.tokens.get_next_user_id()\\n self.tokens.insert_user(user_id, access_token, refresh_token)\\n tstat_ids = self.get_tstat_ids(access_token)\\n for tstat_id in tstat_ids:\\n logger.info(\\\"Adding Thermostat ID: {}\\\".format(tstat_id))\\n self.tokens.insert_tstat(user_id, tstat_id)\",\n \"def send_otp_to_primary_mobile(otp, mobile):\\n print('Sending otp to mobile: ', otp, mobile)\",\n \"def user_activation(user):\\n act_hash = random_password(32)\\n user.set_hashword(act_hash)\\n user.save()\\n base_url = url_for('public.home', _external=True)\\n act_url = url_for(\\n 'auth.activate',\\n userid=user.id,\\n userhash=act_hash,\\n _external=True)\\n if not 'mailman' in current_app.extensions:\\n logging.warning('E-mail extension has not been configured')\\n return act_hash\\n msg = EmailMessage()\\n msg.subject = 'Your dribdat account'\\n msg.body = \\\\\\n \\\"Hello %s,\\\\n\\\" % user.username \\\\\\n + \\\"Thanks for signing up at %s\\\\n\\\\n\\\" % base_url \\\\\\n + \\\"Tap here to activate your account:\\\\n\\\\n%s\\\" % act_url\\n msg.to = [user.email]\\n logging.info('Sending activation mail to user %d' % user.id)\\n logging.debug(act_url)\\n msg.send(fail_silently=True)\\n return act_hash\",\n \"def activate(self) -> None:\\n self._bot.inject_flows_from(self)\\n self.is_activated = True\",\n \"def login_on_activation(sender, user, request, **kwargs):\\n user.backend = 'storybase_user.auth.backends.EmailModelBackend'\\n login(request, user)\",\n \"def _turn_on(self):\\n logger.info(\\\"Check antenna power\\\")\\n power = yield WaitDBus(self.gsm_device.GetAntennaPower)\\n logger.info(\\\"antenna power is %d\\\", power)\\n if power:\\n yield None\\n logger.info(\\\"turn on antenna power\\\")\\n try:\\n yield WaitDBus(self.gsm_device.SetAntennaPower, True)\\n except dbus.exceptions.DBusException, ex:\\n if ex.get_dbus_name() != 'org.freesmartphone.GSM.SIM.AuthFailed':\\n raise\\n yield self._ask_pin()\",\n \"def turn_on_modem(self):\\n if not self.is_power_on():\\n self._logger.debug(\\\"Switching modem on...\\\")\\n self.set_pin()\\n # give modem some time to login\\n time.sleep(10)\\n else:\\n self._logger.debug(\\\"Modem is already powered on...\\\")\",\n \"def activate_profile(field, code, request):\\n try:\\n activation = ActivationProfile.objects.get(**{field:code})\\n except ActivationProfile.DoesNotExist:\\n messages.error(request, _('Activation code expired or not valid!'))\\n return False\\n if timezone.now() < activation.valid_through:\\n activation.user.is_active = True\\n activation.user.set_unusable_password()\\n activation.user.save()\\n if request.user.is_anonymous():\\n if field == 'token':\\n user = authenticate(username=activation.user.username, token=activation.token)\\n elif field == 'sms_key':\\n user = authenticate(username=activation.user.username, code=activation.sms_key)\\n else:\\n user = None\\n activation.delete()\\n if user:\\n login(request, user)\\n messages.success(request, _(\\\"\\\"\\\"Profile activated successfully! You should change your password!\\\"\\\"\\\"))\\n return True\\n else:\\n return False\\n else:\\n messages.success(request, _(\\\"\\\"\\\"You already have an account!\\\"\\\"\\\"))\\n return False\",\n \"def activate(self):\\r\\n if self.activation_code == '':\\r\\n raise ValidationError('The member is already activated')\\r\\n signer = TimestampSigner()\\r\\n signer.unsign(self.activation_code, max_age=timedelta(days=2))\\r\\n self.hidden = False\\r\\n self.activation_code = ''\\r\\n self.joined_date = timezone.now()\\r\\n self.save()\",\n \"def sendOTP(code):\\n # Modify the code here to change from print to any output \\n print(\\\"Your OTP is \\\" + code + \\\". Kindly do not share it with anyone\\\")\",\n \"def activate_account_api():\\n\\n # get the data for this query\\n data = request.get_json()\\n if not data:\\n response = jsonify({\\n 'success': False,\\n 'message': 'Missing request body'\\n })\\n response.status_code = 422\\n return response\\n\\n # process arguments\\n arg_email = data.get('email').strip().lower()\\n\\n # check if there is a user with this activation_link\\n secret_link = data.get('secret_link')\\n user = db.session.query(User).filter(\\n User.activation_link == secret_link,\\n ).one_or_none()\\n if not user:\\n response = jsonify({\\n 'success': False,\\n 'message': 'This activation link is no longer active. Contact your system administrator to receive a new one.'\\n })\\n response.status_code = 200\\n return response\\n\\n # check if this user has already activated their account\\n if user.activated:\\n response = jsonify({\\n 'success': False,\\n 'message': 'This account has already been activated. Try forgot password to recover your password.'\\n })\\n response.status_code = 200\\n return response\\n\\n # check if the correct email address was supplied\\n if user.email != arg_email:\\n response = jsonify({\\n 'success': False,\\n 'message': 'This is not the correct email for this activation link. Contact your system administrator to request a link for this email.'\\n })\\n response.status_code = 200\\n return response\\n\\n # generate and set new password\\n new_password = generate_password_hash(data.get('password'))\\n user.password = new_password\\n user.activated = True\\n db.session.add(user)\\n db.session.commit()\\n\\n # log that a user just activated their account\\n _log('++ {} just activated their account'.format(user.email), '_signup')\\n\\n # return authenticated token\\n token = generate_auth_token(user_id=user.user_id)\\n response = jsonify({\\n 'success': True,\\n 'token': token\\n })\\n response.status_code = 200\\n return response\",\n \"def apply_auth():\\n\\tclient = BaiduOpenApi()\\n\\tapi = client.device.code\\n\\tresp = client.device.code.get(response_type=\\\"device_code\\\", scope=\\\"netdisk\\\")\\n\\t# open grant page and wait for user confirm\\n\\twebbrowser.open_new_tab(r\\\"http://openapi.baidu.com/device?code=%s\\\"%resp[\\\"user_code\\\"])\\n\\t# yield to main\\n\\tyield\\n\\t# main will tell user to confirm and it will take a while\\n\\t# polling to wait server back\\n\\tpolling_tokens(resp[\\\"device_code\\\"], resp[\\\"interval\\\"], resp[\\\"expires_in\\\"])\",\n \"def activate(self):\\n if not self.is_active:\\n self.is_active = True\\n self.activated_at = datetime.datetime.utcnow()\\n import messaging # avoid circular import\\n messaging.send_activated_emails(self)\\n self.save()\",\n \"def activate_pair(device_pair):\\n command = 'pair_activate \\\"%s\\\"' % (device_pair.identifier,)\\n _run_command(command)\",\n \"def activate_task(self, task_id):\\n if task_id is None:\\n print('ERROR: task_id cannot be \\\"None\\\".')\\n return False\\n # Else, the task was specified\\n if task_id in self.task_dict:\\n self.task_dict[task_id].is_activated = True\\n # Update the activation state\\n self._update_activation_state()\\n return True\\n else:\\n # Something wrong, agent was not in the dict\\n print('ERROR: The task <%s> is not in the task_dict at agent <%d>.' % (str(task_id), self.agent_id))\\n return False\",\n \"def activate(self):\\r\\n self.update_enrollment(is_active=True)\",\n \"def confirm(id):\\n #: get resources\\n user = User.query.get_or_404(id)\\n service = SignUpService(user)\\n input_token = request.args['token']\\n\\n #: active current account\\n try:\\n service.active(input_token)\\n except TokenUsedError:\\n message = _(u\\\"The account had been actived.\\\")\\n return render_template(\\\"confirm-failed.html\\\", message=message), 403\\n except TokenWrongError:\\n message = _(u\\\"The active token is invalid.\\\")\\n return render_template(\\\"confirm-failed.html\\\", message=message), 403\\n\\n #: automatic sign in\\n session_login(user)\\n #: output a success message\\n message = _(u\\\"The account has been actived successfully.\\\")\\n return render_template(\\\"confirm-success.html\\\", message=message)\",\n \"def test_yes_option_enabled(\\n self, wait_tx_settled_mock, confirm_mock, do_transfer_mock\\n ):\\n password_option = self.get_password_args(self.PASSWORD)\\n self.invoke(\\n \\\"transfer\\\",\\n self.LEDGER_ID,\\n self.get_address(self.LEDGER_ID, self.PASSWORD),\\n \\\"100000\\\",\\n \\\"100\\\",\\n \\\"-y\\\",\\n *password_option,\\n )\\n confirm_mock.assert_not_called()\",\n \"def activate_user(self, user):\\n if not user.active:\\n user.active = True\\n return True\\n return False\",\n \"def activate_user(username, code, new_pass):\\r\\n\\r\\n qry = Activation.query.\\\\\\r\\n filter(Activation.code == code).\\\\\\r\\n filter(User.username == username)\\r\\n\\r\\n res = qry.first()\\r\\n\\r\\n if UserMgr.acceptable_password(new_pass) and res is not None:\\r\\n user = res.user\\r\\n user.activated = True\\r\\n user.password = new_pass\\r\\n res.activate()\\r\\n\\r\\n LOG.debug(dict(user))\\r\\n\\r\\n return True\\r\\n else:\\r\\n return None\",\n \"async def async_press(self) -> None:\\n try:\\n await self.entity_description.press_func(self.device)\\n except DevicePasswordProtected as ex:\\n self.entry.async_start_reauth(self.hass)\\n raise HomeAssistantError(\\n f\\\"Device {self.entry.title} require re-authenticatication to set or change the password\\\"\\n ) from ex\\n except DeviceUnavailable as ex:\\n raise HomeAssistantError(\\n f\\\"Device {self.entry.title} did not respond\\\"\\n ) from ex\",\n \"def activate(request, activation_key,\\r\\n template_name='registration/activate.html',\\r\\n extra_context=None):\\r\\n activation_key = activation_key.lower() # Normalize before trying anything with it.\\r\\n account = RegistrationProfile.objects.activate_user(activation_key)\\r\\n if extra_context is None:\\r\\n extra_context = {}\\r\\n context = RequestContext(request)\\r\\n for key, value in extra_context.items():\\r\\n context[key] = callable(value) and value() or value\\r\\n return render_to_response(template_name,\\r\\n { 'account': account,\\r\\n 'expiration_days': settings.ACCOUNT_ACTIVATION_DAYS },\\r\\n context_instance=context)\",\n \"def login_auto(token: Token, mac_address: str) -> bool:\\n device = Device.get_by_mac(mac_address)\\n fail_msg = \\\"\\\"\\n if device is None:\\n fail_msg = \\\"No device with mac address exist\\\"\\n elif Token.is_token_expired(device.token_expires):\\n fail_msg = \\\"Token is expired\\\"\\n elif token != device.token:\\n fail_msg = \\\"Wrong token\\\"\\n if fail_msg:\\n client_logger_security().info(f\\\"Failed to login automatically: {fail_msg}\\\")\\n return False\\n else:\\n _set_user_authenticated(device.user_id, device.device_id)\\n client_logger_security().info(f\\\"Successfully logged in automatically: device_id={device.device_id}, \\\"\\n f\\\"user_id={device.user_id}\\\")\\n return True\",\n \"def do_mfa_verify(mfa_info):\\n headers = {\\n \\\"Content-Type\\\": \\\"application/json\\\",\\n \\\"Origin\\\": \\\"https://%s.auth0.com\\\"%TENANT,\\n \\\"Authorization\\\": \\\"Bearer %s\\\"%mfa_info[\\\"requestToken\\\"],\\n \\\"x-global-tracking-id\\\": mfa_info[\\\"globalTrackingId\\\"]\\n }\\n request = urllib.request.Request(\\n \\\"%s/api/start-flow\\\"%mfa_info[\\\"mfaServerUrl\\\"],\\n data=json.dumps({ \\\"state_transport\\\": \\\"polling\\\" }).encode(),\\n method=\\\"POST\\\",\\n headers=headers)\\n try:\\n response = urllib.request.urlopen(request)\\n result = response.read().decode()\\n except urllib.error.HTTPError as e:\\n error = e.read().decode()\\n raise RuntimeError(\\\"MFA start flow error: %s\\\"%error) from None\\n mfa_flow_info = json.loads(result)\\n mfa_transaction_token = mfa_flow_info[\\\"transaction_token\\\"]\\n # print(mfa_flow_info)\\n # print(mfa_transaction_token)\\n\\n mfa_code = input(\\\"Please enter your MFA verification code: \\\")\\n mfa_payload = {\\n \\\"code\\\": mfa_code,\\n \\\"type\\\": \\\"manual_input\\\"\\n }\\n mfa_payload_json = json.dumps(mfa_payload).encode()\\n headers = {\\n \\\"Content-Type\\\": \\\"application/json\\\",\\n \\\"Origin\\\": \\\"https://%s.auth0.com\\\"%TENANT,\\n \\\"Authorization\\\": \\\"Bearer %s\\\"%mfa_transaction_token,\\n \\\"x-global-tracking-id\\\": mfa_info[\\\"globalTrackingId\\\"]\\n }\\n request = urllib.request.Request(\\n \\\"%s/api/verify-otp\\\"%mfa_info[\\\"mfaServerUrl\\\"],\\n data=mfa_payload_json,\\n method=\\\"POST\\\",\\n headers=headers)\\n try:\\n response = urllib.request.urlopen(request)\\n result = response.read().decode()\\n except urllib.error.HTTPError as e:\\n error = e.read().decode()\\n raise RuntimeError(\\\"MFA verify error: %s\\\"%error) from None\\n # print(result)\\n\\n headers = {\\n \\\"Origin\\\": \\\"https://%s.auth0.com\\\"%TENANT,\\n \\\"Authorization\\\": \\\"Bearer %s\\\"%mfa_transaction_token,\\n \\\"x-global-tracking-id\\\": mfa_info[\\\"globalTrackingId\\\"]\\n }\\n request = urllib.request.Request(\\n \\\"%s/api/transaction-state\\\"%mfa_info[\\\"mfaServerUrl\\\"],\\n method=\\\"POST\\\",\\n headers=headers)\\n try:\\n response = urllib.request.urlopen(request)\\n result = response.read().decode()\\n except urllib.error.HTTPError as e:\\n error = e.read().decode()\\n raise RuntimeError(\\\"Get MFA result error: %s\\\"%error) from None\\n mfa_result = json.loads(result)\\n if mfa_result[\\\"state\\\"] != \\\"accepted\\\":\\n raise RuntimeError(\\\"MFA verification is not accepted: %s\\\"%result)\\n # print(mfa_result)\\n\\n return mfa_result\",\n \"async def async_turn_on_when_active(self, **kwargs: Any) -> None:\\n await self._data.controller.programs.start(self.entity_description.uid)\\n self._update_activities()\",\n \"def send_mfa(self):\\n\\n try:\\n response = self.post(\\\"/authentication/loginToken\\\",\\n {\\\"user\\\": self.user, \\\"password\\\": self.password, \\\"TempCode\\\": True})\\n except:\\n print(\\\"Exception - unable to submit token request\\\")\\n return False\\n return True if response.status_code in [200, 204] else False\",\n \"def set_time_based_otp(self, otp_passcode: str):\\n self._totp = TOTP(otp_passcode)\",\n \"def activateWebAppUser( self, username, activation_code ):\\n try:\\n con = self.getMetadataDatabaseConnection()\\n user_data = con.cursor()\\n\\n con.cursor().callproc('verify_user_activation_code', [username, activation_code, user_data])\\n row = user_data.fetchone()\\n if row:\\n con.cursor().callproc('activate_user_account', [username])\\n return True\\n else:\\n return False\\n except Exception, e:\\n print 'Exception caught: %s.\\\\nThe error is: %s' % (type(e), e)\\n return False\",\n \"def test_user_activation(self):\\n user = User.objects.get()\\n response = self.client.get(reverse('accounts:user-activate',\\n kwargs={'uidb64': urlsafe_base64_encode(force_bytes(user.pk)),\\n 'token': account_activation_token.make_token(user)}))\\n self.assertEqual(response.status_code, status.HTTP_200_OK)\",\n \"def activate(request, activation_key,template_name='registration/activate.html',extra_context=None):\\n\\tactivation_key = activation_key.lower() # Normalize before trying anything with it.\\n\\taccount = RegistrationProfile.objects.activate_user(activation_key)\\n\\t\\n\\t\\n\\t#new profile PROBLEME NON ENREGISTREMENT DU PROFILE\\n\\t#recuperer l user id de l'account user.id\\n\\tprofile = UserProfile();\\n\\tprofile.user = account\\n\\tprofile.save()\\n\\t\\n\\t\\n\\tif extra_context is None:\\n\\t\\textra_context = {}\\n\\tcontext = RequestContext(request)\\n\\tfor key, value in extra_context.items():\\n\\t\\tcontext[key] = callable(value) and value() or value\\n\\treturn render_to_response(template_name,{ 'account': account,'expiration_days': settings.ACCOUNT_ACTIVATION_DAYS }, context_instance=context)\",\n \"def active_user(request, uidb36=None, token=None,\\r\\n template_name='register/activation_confirm.html',\\r\\n token_generator=default_token_generator,\\r\\n current_app=None, extra_context=None):\\r\\n assert uidb36 is not None and token is not None # checked by URLconf\\r\\n \\r\\n try:\\r\\n uid_int = base36_to_int(uidb36)\\r\\n user = User.objects.get(id=uid_int)\\r\\n except (ValueError, User.DoesNotExist):\\r\\n user = None\\r\\n\\r\\n if user is not None and token_generator.check_token(user, token):\\r\\n validlink = True\\r\\n user.is_active = True\\r\\n user.save()\\r\\n \\r\\n #初始化userprofile\\r\\n profile_count = UserProfile.objects.filter(user=user).count()\\r\\n if profile_count == 0:\\r\\n profile = UserProfile()\\r\\n profile.user = user\\r\\n profile.song_ord_filed = 'post_datetime'\\r\\n profile.save()\\r\\n else:\\r\\n validlink = False\\r\\n context = {\\r\\n 'validlink': validlink,\\r\\n }\\r\\n context.update(extra_context or {})\\r\\n return render_to_response(template_name, context,\\r\\n context_instance=RequestContext(request, current_app=current_app))\",\n \"def enable_call_waiting(self, dtmf_code: str) -> None:\",\n \"def activate_user(self, user):\\n if not user.active:\\n user.active = True\\n # noinspection PyUnresolvedReferences\\n self.save(user)\\n return True\\n\\n return\",\n \"async def _autopaired(self, new_user_apc_token: str):\\n self._user_apc_token = new_user_apc_token\\n self._fconfigure()\",\n \"def test_activate_active_user(self):\\n activate_user(self.user, self.request)\\n self.assertEqual(self.user.is_active, True)\",\n \"def test_create_user_auto_activate(self, services):\\n data = {\\n 'username': 'John',\\n 'email': 'John@mailinator.com',\\n 'password': 'test123!',\\n 'phone': '1234567890',\\n 'first_name': 'Chuck',\\n 'last_name': 'Norris',\\n 'university': {\\n \\\"name\\\": \\\"random_university\\\"\\n },\\n 'academic_field': {'name': \\\"random_field\\\"},\\n 'academic_level': {'name': \\\"random_level\\\"},\\n 'gender': \\\"M\\\",\\n 'birthdate': \\\"1999-11-11\\\",\\n }\\n\\n response = self.client.post(\\n reverse('user-list'),\\n data,\\n format='json',\\n )\\n\\n self.assertEqual(response.status_code, status.HTTP_201_CREATED)\\n self.assertEqual(json.loads(response.content)['phone'], '1234567890')\\n\\n user = User.objects.get(email=\\\"John@mailinator.com\\\")\\n activation_token = ActionToken.objects.filter(\\n user=user,\\n type='account_activation',\\n )\\n\\n self.assertTrue(user.is_active)\\n self.assertEqual(1, len(activation_token))\\n\\n # Test that no email was sent:\\n self.assertEqual(len(mail.outbox), 0)\",\n \"def account_activate(request):\\r\\n params = request.params\\r\\n\\r\\n username = params.get('username', None)\\r\\n activation = params.get('code', None)\\r\\n password = params.get('password', None)\\r\\n new_username = params.get('new_username', None)\\r\\n\\r\\n if username is None and activation is None and password is None:\\r\\n # then try to get the same fields out of a json body\\r\\n json_body = request.json_body\\r\\n username = json_body.get('username', None)\\r\\n activation = json_body.get('code', None)\\r\\n password = json_body.get('password', None)\\r\\n new_username = json_body.get('new_username', None)\\r\\n\\r\\n if not UserMgr.acceptable_password(password):\\r\\n request.response.status_int = 406\\r\\n return _api_response(request, {\\r\\n 'error': \\\"Come on, pick a real password please\\\",\\r\\n })\\r\\n\\r\\n username = username.lower()\\r\\n new_username = new_username.lower() if new_username else None\\r\\n res = ActivationMgr.activate_user(\\r\\n username,\\r\\n activation,\\r\\n password)\\r\\n\\r\\n if res:\\r\\n # success so respond nicely\\r\\n AuthLog.reactivate(username, success=True, code=activation)\\r\\n\\r\\n # if there's a new username and it's not the same as our current\\r\\n # username, update it\\r\\n if new_username and new_username != username:\\r\\n try:\\r\\n user = UserMgr.get(username=username)\\r\\n user.username = new_username\\r\\n except IntegrityError, exc:\\r\\n request.response.status_int = 500\\r\\n return _api_response(request, {\\r\\n 'error': 'There was an issue setting your new username',\\r\\n 'exc': str(exc)\\r\\n })\\r\\n\\r\\n return _api_response(request, {\\r\\n 'message': \\\"Account activated, please log in.\\\",\\r\\n 'username': username,\\r\\n })\\r\\n else:\\r\\n AuthLog.reactivate(username, success=False, code=activation)\\r\\n request.response.status_int = 500\\r\\n return _api_response(request, {\\r\\n 'error': \\\"There was an issue attempting to activate this account.\\\",\\r\\n })\",\n \"def activate(request, activation_key):\\n profile = get_object_or_404(User, activation_key=activation_key)\\n if profile.akey_expires < timezone.now():\\n return render('user_account/activate.html', {'expired': True})\\n\\n profile.save(update_fields=['active', 'activation_key'])\\n return render(\\n 'user_account/activate.html',\\n {'success': True, 'name': profile.name + \\\" \\\" + profile.surname}\\n )\",\n \"def begin_trial(self):\\n self._post(endpoint='{}/cm/trial/begin'.format(self.api_version))\",\n \"def enable_radio(self):\\n self.acquire_response(b'AT*R1')\",\n \"def do_masterpassword(self, masterpassword):\\n if masterpassword:\\n if self.taskstarted == True:\\n self.masterpassword = masterpassword\\n else:\\n if self.taskstarted == False:\\n print(self.cl.red(\\\"[!] You need to start a new KeePass Interaction.\\\"))\\n print(self.cl.red(\\\"[!] Start this with 'new' from the menu.\\\"))\\n print(\\\"[!] You need to supply the command for typing\\\")\",\n \"def auth_active(hass):\\n hass.loop.run_until_complete(\\n register_auth_provider(hass, {\\\"type\\\": \\\"homeassistant\\\"})\\n )\",\n \"async def enter_confirmation_сode(self):\\n raise VkTwoFactorCodeNeeded()\",\n \"def activate_user(self, username):\\n args = parser_activate.parse_args()\\n isActive = request.json.get('isactive')\\n\\n query = \\\"\\\"\\\"UPDATE users SET isactive=%s WHERE username=%s\\\"\\\"\\\"\\n values = isActive, username\\n\\n conn = self.db\\n cursor = conn.cursor()\\n cursor.execute(query, values)\\n conn.commit()\\n return True\",\n \"def activate(self):\\n\\t\\tself.flash()\\n\\t\\tself.do_action()\",\n \"def test_activate_user(self):\\n activated_user = (RegistrationProfile.objects\\n .activate_user(self.activation_key))\\n self.assertTrue(activated_user.registrationprofile.activated)\\n self.assertFalse(activated_user.is_active)\",\n \"def enable_aaa_password_restriction(device):\\n cmd=\\\"aaa password restriction\\\"\\n try:\\n device.configure(cmd)\\n except SubCommandFailure as e:\\n raise SubCommandFailure(\\n f'Could not configure aaa password restriction:\\\\n{e}'\\n )\",\n \"def test_pm_profile_activate(profile_manager, test_profile):\\n\\n profile_manager.activate(test_profile.name)\\n assert profile_manager.is_active(test_profile.name)\\n profile = profile_manager.get_active_profile()\\n assert profile.name == test_profile.name\\n assert profile.path == test_profile.path\",\n \"def activate():\\n refresh()\\n activate_connection_with_mainloop(get_uuid())\",\n \"def enable_aaa_authentication_login(device,auth_list,auth_db1,auth_db2=None):\\n\\n cmd = f'aaa authentication login {auth_list} {auth_db1}'\\n if auth_db2:\\n cmd += f' {auth_db2}'\\n try:\\n device.configure(cmd)\\n except SubCommandFailure as e:\\n raise SubCommandFailure(\\n f'Could not configure aaa authentication login:\\\\n{e}'\\n )\",\n \"def authenticate_bluetooth(self):\\n data = self.blu.main()\\n if bool(data) == True:\\n authentication = self.client.validate_mac(\\n data[\\\"mac_address\\\"], data[\\\"email\\\"]).decode(\\\"utf-8\\\")\\n if authentication == \\\"valid\\\":\\n self.current_email = data[\\\"email\\\"]\\n self.unlock_time = round(datetime.now().timestamp())\\n self.display_successful_unlock_eng()\\n elif authentication == \\\"invalid\\\":\\n print(self.INVALID_USER)\\n time.sleep(3)\\n self.display_main()\\n else:\\n self.display_eng()\",\n \"def admin_action(self):\\n SCREEN_MANAGER.current = 'passCode'\",\n \"def activate_user(self, activation_key):\\n if SHA1_RE.search(activation_key):\\n try:\\n profile = RegistrationProfile.objects.get(activation_key=activation_key)\\n except self.model.DoesNotExist:\\n return False\\n if not profile.activation_key_expired():\\n user = profile.user\\n user.is_active = True\\n user.save()\\n profile.activation_key = \\\"ALREADY_ACTIVATED\\\"\\n profile.save()\\n return user\\n\\n return False\",\n \"def signup_active(request, uidb36=None, token=None,\\n post_activation_redirect=None,\\n token_generator=default_token_generator,\\n domain_override=None, use_https=False):\\n assert uidb36 is not None and token is not None\\n if post_activation_redirect is None:\\n post_activation_redirect = reverse('amscms.core.views.signup_active_done')\\n try:\\n uid_int = base36_to_int(uidb36)\\n user = User.objects.get(id=uid_int)\\n except (ValueError, User.DoesNotExists):\\n user = None\\n \\n if user is not None and token_generator.check_token(user, token):\\n user.is_active = True\\n user.save()\\n \\\"\\\"\\\"\\n Sends successful email to the user. \\n \\\"\\\"\\\"\\n if not domain_override:\\n current_site = Site.objects.get_current()\\n site_name = current_site.name\\n domain = current_site.domain\\n else:\\n site_name = domain = domain_override\\n c = {\\n 'subject': _(u\\\"Registration was successful on %(site_name)s\\\" % {'site_name': site_name, }),\\n 'site_name': site_name,\\n 'user': user,\\n 'domain': domain,\\n 'protocol': use_https and 'https' or 'http',\\n 'login_url': reverse('django.contrib.auth.views.login'),\\n }\\n send_email(user.email, c, settings.DEFAULT_FROM_EMAIL,\\n \\\"registration/signup_email_activated.txt\\\",\\n \\\"registration/signup_email_activated.html\\\")\\n \\n else:\\n messages.error(request, _(u\\\"Invalid activation link, you may already activated, try to login. \\\"))\\n return HttpResponseRedirect(\\\"/\\\")\\n return HttpResponseRedirect(post_activation_redirect)\",\n \"def activate_user(cls, activation_key):\\n #from registration.signals import user_activated\\n \\n # Make sure the key we're trying conforms to the pattern of a\\n # SHA1 hash; if it doesn't, no point trying to look it up in\\n # the database.\\n db = DB_Session()\\n if SHA1_RE.search(activation_key):\\n query = db.query(RegistrationProfile)\\n profile = query.filter(RegistrationProfile.activation_key == activation_key).one()\\n if not profile:\\n return False\\n if not profile.activation_key_expired():\\n user = profile.user\\n user.is_active = 1\\n profile.activation_key = RegistrationProfile.ACTIVATED\\n db.flush()\\n db.commit()\\n db.close()\\n #user_activated.send(sender=self.model, user=user)\\n return user\\n return False\",\n \"def mifare_auth_a(self,address,key_a):\\n if self._uid == False:\\n raise RuntimeError(\\\"No Mifare card currently activated.\\\")\\n if len(self._uid) == 4:\\n uid = self._uid\\n elif len(self._uid) == 7: # 10-byte UID cards don't exist yet.\\n uid = self._uid[3:7] # Sequence 1, keep it simple.\\n self.in_data_exchange(bytearray([MIFARE_COMMAND_AUTH_A,address]) + key_a + uid)\",\n \"def activate_user(self, activation_key, request=None):\\n # Make sure the key we're trying conforms to the pattern of a\\n # SHA1 hash; if it doesn't, no point trying to look it up in\\n # the database.\\n if SHA1_RE.search(activation_key):\\n try:\\n profile = self.get(activation_key=activation_key)\\n except self.model.DoesNotExist:\\n profile = None\\n statsd.incr('user.activate-error.does-not-exist')\\n reason = 'key not found'\\n if profile:\\n if not profile.activation_key_expired():\\n user = profile.user\\n user.is_active = True\\n user.save()\\n\\n # We don't need the RegistrationProfile anymore, delete it.\\n profile.delete()\\n\\n # If user registered as contributor, send them the\\n # welcome email.\\n if user.groups.filter(name=CONTRIBUTOR_GROUP):\\n self._send_email(\\n confirmation_profile=profile,\\n url=None,\\n subject=_('Welcome to SUMO!'),\\n text_template='users/email/contributor.ltxt',\\n html_template='users/email/contributor.html',\\n send_to=user.email,\\n contributor=user)\\n\\n return user\\n else:\\n statsd.incr('user.activate-error.expired')\\n reason = 'key expired'\\n else:\\n statsd.incr('user.activate-error.invalid-key')\\n reason = 'invalid key'\\n\\n log.warning(u'User activation failure ({r}): {k}'.format(\\n r=reason, k=activation_key))\\n\\n return False\",\n \"def user(self, user_token, user_device=None):\\n self.set('user', user_token)\\n self.set('device', user_device)\",\n \"def confirm_start(self, player=str):\\n self.clear_screen()\\n print(\\\"\\\\n\\\" * 11)\\n pass_text = \\\"Pass the device to \\\" + player\\n print(f\\\"{pass_text : ^100}\\\")\\n input(f\\\"{'Press ENTER when ready.' : ^100}\\\")\\n return self.stop_game\",\n \"def check_mfa(self) -> None:\\n try:\\n mfa_form = self._driver.find_element(By.CSS_SELECTOR, \\\"form[name=form]\\\", timeout=5)\\n self._driver.find_element(By.CSS_SELECTOR, \\\"input[name=otc]\\\", timeout=5)\\n self._halo.stop()\\n mfacode = self._csc.prompt_for(\\\"MFA Code\\\")\\n self._halo.start(SPINNER_MSGS[\\\"mfa_send\\\"])\\n self.send_mfa(form=mfa_form, code=mfacode)\\n self._halo.start(SPINNER_MSGS[\\\"token_refresh\\\"])\\n self._driver.dump_cookies()\\n except selenium.common.exceptions.TimeoutException:\\n pass\",\n \"def test_activate_authenticated(client):\\n employee = factories.EmployeeFactory(\\n company=factories.CompanyFactory(),\\n account_status=False\\n )\\n with client.session_transaction() as session:\\n session[\\\"user_id\\\"] = employee.id\\n g.user = employee\\n response = client.post(\\\"/auth/activate\\\")\\n assert b\\\" should be {bool}, {type(value)} given.\\\")\\n\\n self._activated = value\"\n]"},"negative_scores":{"kind":"list like","value":["0.60715777","0.6028133","0.59996897","0.58769685","0.5760404","0.5734255","0.5616806","0.5603392","0.5589512","0.5500395","0.5455279","0.5448774","0.5440349","0.54232854","0.5410598","0.5386604","0.5370613","0.53615427","0.5324096","0.53227437","0.5316876","0.5257387","0.5242015","0.5238215","0.52204853","0.5180888","0.5168266","0.5167923","0.5149471","0.51486313","0.5136919","0.5122194","0.5099806","0.50952345","0.5085686","0.50736505","0.5067133","0.5052447","0.5049608","0.503255","0.50311255","0.50306964","0.5010046","0.5009087","0.5008341","0.5002462","0.49990466","0.49950635","0.49906734","0.49831188","0.49712396","0.49543926","0.49519625","0.49450558","0.49329653","0.49205124","0.49176443","0.49169865","0.48983115","0.48939362","0.4877591","0.48763728","0.48606753","0.48567647","0.48388755","0.48356223","0.48327577","0.48316598","0.48277473","0.4827056","0.4825791","0.48230392","0.48194167","0.48193097","0.48054487","0.48049524","0.4796671","0.47845018","0.47751698","0.47561207","0.47523004","0.475161","0.4746635","0.47390857","0.47390676","0.47375605","0.47259092","0.47257814","0.47257814","0.4707243","0.47054324","0.46902686","0.46831268","0.46723512","0.4666625","0.4656086","0.46479917","0.46470034","0.46439013","0.46407658"],"string":"[\n \"0.60715777\",\n \"0.6028133\",\n \"0.59996897\",\n \"0.58769685\",\n \"0.5760404\",\n \"0.5734255\",\n \"0.5616806\",\n \"0.5603392\",\n \"0.5589512\",\n \"0.5500395\",\n \"0.5455279\",\n \"0.5448774\",\n \"0.5440349\",\n \"0.54232854\",\n \"0.5410598\",\n \"0.5386604\",\n \"0.5370613\",\n \"0.53615427\",\n \"0.5324096\",\n \"0.53227437\",\n \"0.5316876\",\n \"0.5257387\",\n \"0.5242015\",\n \"0.5238215\",\n \"0.52204853\",\n \"0.5180888\",\n \"0.5168266\",\n \"0.5167923\",\n \"0.5149471\",\n \"0.51486313\",\n \"0.5136919\",\n \"0.5122194\",\n \"0.5099806\",\n \"0.50952345\",\n \"0.5085686\",\n \"0.50736505\",\n \"0.5067133\",\n \"0.5052447\",\n \"0.5049608\",\n \"0.503255\",\n \"0.50311255\",\n \"0.50306964\",\n \"0.5010046\",\n \"0.5009087\",\n \"0.5008341\",\n \"0.5002462\",\n \"0.49990466\",\n \"0.49950635\",\n \"0.49906734\",\n \"0.49831188\",\n \"0.49712396\",\n \"0.49543926\",\n \"0.49519625\",\n \"0.49450558\",\n \"0.49329653\",\n \"0.49205124\",\n \"0.49176443\",\n \"0.49169865\",\n \"0.48983115\",\n \"0.48939362\",\n \"0.4877591\",\n \"0.48763728\",\n \"0.48606753\",\n \"0.48567647\",\n \"0.48388755\",\n \"0.48356223\",\n \"0.48327577\",\n \"0.48316598\",\n \"0.48277473\",\n \"0.4827056\",\n \"0.4825791\",\n \"0.48230392\",\n \"0.48194167\",\n \"0.48193097\",\n \"0.48054487\",\n \"0.48049524\",\n \"0.4796671\",\n \"0.47845018\",\n \"0.47751698\",\n \"0.47561207\",\n \"0.47523004\",\n \"0.475161\",\n \"0.4746635\",\n \"0.47390857\",\n \"0.47390676\",\n \"0.47375605\",\n \"0.47259092\",\n \"0.47257814\",\n \"0.47257814\",\n \"0.4707243\",\n \"0.47054324\",\n \"0.46902686\",\n \"0.46831268\",\n \"0.46723512\",\n \"0.4666625\",\n \"0.4656086\",\n \"0.46479917\",\n \"0.46470034\",\n \"0.46439013\",\n \"0.46407658\"\n]"},"document_score":{"kind":"string","value":"0.6753613"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8568,"cells":{"query":{"kind":"string","value":"Adds the specified user to the specified group and returns a `UserGroupMembership` object with its own OCID. After you send your request, the new object's `lifecycleState` will temporarily be CREATING. Before using the object, first make sure its `lifecycleState` has changed to ACTIVE."},"document":{"kind":"string","value":"def add_user_to_group(self, add_user_to_group_details, **kwargs):\n resource_path = \"/userGroupMemberships\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"add_user_to_group got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=add_user_to_group_details,\n response_type=\"UserGroupMembership\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=add_user_to_group_details,\n response_type=\"UserGroupMembership\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def addUserToGroup(self, user, group):\n return self.pm_getUserManager().addUserToGroup(self._unbox(user), self._unbox(group))","def add_user(self, user):\n store = self.get('__store')\n members = Members(store.db)\n membership = members.first(group_id=self._id, user_id=user._id)\n if not membership:\n members.put(Member(group_id=self._id, user_id=user._id))","def add_user_to_group(self, group_name, user_name):\r\n params = {'GroupName' : group_name,\r\n 'UserName' : user_name}\r\n return self.get_response('AddUserToGroup', params)","def AddMemberToGroup(group_id,user_id):\r\n Group.AddMemberToGroup(group_id,user_id)","def add_group_user(self, group_id, user_id):\n resp, body = self.put('groups/%s/users/%s' % (group_id, user_id),\n None)\n self.expected_success(204, resp.status)\n return service_client.ResponseBody(resp, body)","def add_group_user(self, group_id, user_id):\n resp, body = self.put('groups/%s/users/%s' % (group_id, user_id),\n None)\n self.expected_success(204, resp.status)\n return rest_client.ResponseBody(resp, body)","def action_add_to_group(self, kwargs):\n user = kwargs[\"user\"]\n group = kwargs[\"group\"]\n\n if self.engine.add_user_to_group(user, group):\n info(f\"User {user} sucessfully added to {group}\")\n else:\n error(f\"Unable to add {user} to {group}, check privileges or dn\")","def add_member(self, user):\n user_in = user.get_groups()\n for group in user_in:\n if self.usergroup_node == group.usergroup_node:\n print('user is already a member')\n return False\n membership = Relationship(user.get(), 'in', self.usergroup_node)\n graph.create(membership)\n return self.usergroup_node","def add_to_group(user: User, group: Group) -> Result:\n if user.pw_name in group.gr_mem:\n return Result(State.unchanged)\n command([\"/usr/sbin/addgroup\", user.pw_name, group.gr_name])\n group.gr_mem.append(user.pw_name)\n return Result(State.success)","def register(self, user):\n if not self.get():\n user_node = user.get() # transform user object to user node object\n usergroup_node = Node(\"Usergroup\",\n groupname=self.groupname,\n id=uuid4().hex)\n graph.create(usergroup_node)\n ownership = Relationship(user_node, 'owns', usergroup_node)\n membership = Relationship(user_node, 'in', usergroup_node)\n graph.create(ownership)\n graph.create(membership)\n self.usergroup_node = usergroup_node\n self.id = usergroup_node['id']\n return usergroup_node\n return self","def add_user_to_group(backend, details, response, user, is_new=False, *args, **kwargs):\n \n if is_new:\n google_apps_add_group_task.apply_async([GAPPS_GROUP_NAME, user.email])","def add_user_to_group(self, login, group):\n return self.request('put',\n '/groups/{}/users/{}'.format(group, login),\n msg='adding user {} to group {}'.format(login, group)\n )","def post(self, id):\r\n return UserGroupService.addUserGroup(self, id)","def add_group(self, group):\n\n return self._client.group_memberships.create({\n 'account': self,\n 'group': group\n })","def add_user_to_group(user, group):\n Command.run(['usermod', '-a', '-G', user, group])","def add_user_group(self, groupname, ls_user):\n data = {\"groupname\": groupname, \"add_users\": ls_user}\n headers = {\"user-agent\": self.u_agent}\n req_url = self.normalize_admin_url(u\"groups/{}\".format(groupname))\n res = requests.put(\n req_url,\n headers=headers,\n auth=self.auth,\n data=json.dumps(data),\n verify=False,\n )\n if res.status_code in [200, 201, 206]:\n return Response(0, res)\n else:\n return Response(res.status_code, res)","def add_new_member(self, event):\n body = event['body']\n body = json.loads(body)\n\n required_fields = ['group_id', 'new_user_id']\n for f in required_fields:\n if f not in body:\n return get_bad_request('POST body missing field {}'.format(f))\n\n group_id = body['group_id']\n new_user_id = body['new_user_id']\n \n user = self.mealShareUsers.get_user_cognito_data(event)\n current_user = user['user_id']\n \n # Requesting user must already be a member\n if not self.mealShareGroups.is_user_in_group(current_user, str(group_id)):\n return {\n 'statusCode': 401,\n 'statusMessage': 'User {} is not a member of the group ID {} and can not add a person to it'.format(current_user, group_id),\n 'group_id': group_id,\n 'new_user_id': new_user_id\n }\n \n # Check if adding was successful\n success = self.mealShareGroups.add_user_to_group(new_user_id, group_id)\n if success:\n return {\n 'statusCode': 200,\n 'statusMessage': 'Successfully added {} to group {}'.format(new_user_id, group_id),\n 'group_id': group_id,\n 'new_user_id': new_user_id\n }\n else:\n return {\n 'statusCode': 500,\n 'statusMessage': 'FAILED to add user {} to group {} by {}'.format(new_user_id, group_id, current_user),\n 'group_id': group_id,\n 'new_user_id': new_user_id\n }","def add_group(self, resolvable):\n group = self._resolve_group(resolvable)\n return self._client.group_memberships.create({\n 'account': self,\n 'group': group,\n })","def add_user_to_group(self,username,groupname):\n\n if not self.check_prereqs():\n raise StopIteration\n\n db = self.env.get_db_cnx()\n cursor = db.cursor()\n\n query=self.create_query(self.sql_add_user_to_group_query,{'username':username,'groupname':groupname,'username_field':self.sql_username_field,'groupname_field':self.sql_groupname_field})\n self.log.debug(\"sqlflexibleauthstore: add_user_to_group: %s\" % (query,))\n\n cursor.execute(query)\n if cursor.rowcount > 0:\n db.commit()\n return True\n return False","def test_020_add_user_to_group(self):\n testflow.step(\"Adding user %s to group %s\", TEST_USER1, TEST_GROUP1)\n assert MANAGE_CLI.run(\n 'useradd',\n TEST_GROUP1,\n user=TEST_USER1\n )[0], \"Failed to add user to group '%s'\" % TEST_GROUP1\n\n testflow.step(\"Adding nonexisting user to group %s\", TEST_GROUP1)\n assert not MANAGE_CLI.run(\n 'useradd',\n TEST_GROUP1,\n user='nonsense'\n )[0], \"Possible to add nonexisting user to group\"\n\n testflow.step(\"Adding user %s to nonexisting group\", TEST_USER2)\n assert not MANAGE_CLI.run(\n 'useradd',\n 'nonsense',\n user=TEST_USER2\n )[0], \"Possible to add user to nonexisting group\"","def AddUser(effective_user, effective_chat):\n chatId = effective_chat.id\n chatType = effective_chat.type\n chatTitle = effective_chat.title\n userId = effective_user.id\n\n if chatId == userId:\n exists = session.query(User).filter_by(user_id=userId, group_id=None).one_or_none()\n group_exists = False\n else:\n exists = session.query(User).filter_by(user_id=userId, group_id=chatId).one_or_none()\n group_exists = session.query(Group).filter_by(id=chatId).one_or_none()\n\n if(exists is not None):\n return False\n\n userGroupID = None\n if chatId != userId:\n userGroupID = chatId\n\n new_user = User(user_id=userId, \n user_name = effective_user.username, \n first_name=effective_user.first_name, \n last_name=effective_user.last_name, \n is_bot = effective_user.is_bot,\n group_id = userGroupID)\n\n if chatId != userId and group_exists is None:\n new_group = Group(id = chatId,\n group_type = chatType,\n title = chatTitle)\n session.add(new_group)\n\n session.add(new_user)\n session.commit()\n return True","def add_user_to_group(conn, user_dn, old_user_group_dn):\n try:\n conn.extend.microsoft.add_members_to_groups([str(user_dn)], [str(old_user_group_dn)])\n except Exception as e:\n raise Exception(\"Can't add user to this group :: {}\".format(e))","def add_user_to_group(self, token, userGroup, userName, isOwner):\n requestUser = self.get_username_from_token(token)\n if self.check_user_has_owner_clearance(requestUser, userGroup):\n dataBase = self.read_database()\n owners = dataBase['userGroups'][userGroup]['owners']\n members = dataBase['userGroups'][userGroup]['members']\n if isOwner and userName not in owners:\n dataBase['userGroups'][userGroup]['owners'].append(userName)\n elif not isOwner and userName not in members:\n dataBase['userGroups'][userGroup]['members'].append(userName)\n\n self.write_database(dataBase)\n else:\n raise UserPermissionException(\n \"Requesting user is not owner of specified user group\")","def post(self):\n args = parser.parse_args()\n user_group = UserGroup()\n user_group.name = args['name']\n user_group.createdby = auth.username()\n db_session.add(user_group)\n db_session.commit()\n return user_group, 201","def add_owner(self, user):\n user_in = user.get_groups()\n member = False\n for group in user_in:\n if self.usergroup_node == group.usergroup_node:\n member = True\n ownership = Relationship(user.get(), 'owns', self.usergroup_node)\n graph.create(ownership)\n if not member:\n membership = Relationship(user.get(), 'in', self.usergroup_node)\n graph.create(membership)\n return self.usergroup_node","def add_group(self, group_node, group_relationship_properties=None):\n\n user_group_relationship = Relationship(start_node=self.user_node,\n rel=AgoraRelationship.MEMBER_OF,\n end_node=group_node)\n self.graph_db.create_unique(user_group_relationship)\n #TODO set properties on the relationsip\n # group_relationship_properties[\"unique_id\"] = str(uuid.uuid4())","def add_to_group(_request, group_id, email):\n group = models.UserGroup.get_by_id(int(group_id))\n user_key = models.UserProfile.load(email).key()\n if group.users is None:\n group.users = []\n logging.warning('Group \"%s\" had a None users list', group.name)\n group.users.append(user_key)\n group.put()\n\n url = urlresolvers.reverse('views.admin.edit_user', args=[email])\n return http.HttpResponseRedirect(url)","def test_save(self, name='test', user=None):\n group = Group(name=name)\n group.save()\n \n if user:\n group.user_set.add(user)\n \n return group","def add_member_command(client: MsGraphClient, args: dict) -> tuple[str, dict, dict]:\n group_id = str(args.get('group_id'))\n user_id = str(args.get('user_id'))\n required_properties = {\n \"@odata.id\": f'https://graph.microsoft.com/v1.0/users/{user_id}'}\n client.add_member(group_id, required_properties)\n\n human_readable = f'User {user_id} was added to the Group {group_id} successfully.'\n return human_readable, NO_OUTPUTS, NO_OUTPUTS","def _register(self, user=None):\n if user is None:\n user = User.objects.create_user(\n username=self.username,\n password=self.password)\n user.is_active = self.active\n # Automatically add the user to the proper group\n if self._group_name is not None:\n group = get_or_none(Group, name=self._group_name)\n if group is not None:\n user.groups.add(group)\n\n user.save()\n profile = UserProfile(user=user, member=self)\n profile.save()","def create_new_user_group(self, token, userGroup):\n requestUser = self.get_username_from_token(token)\n dataBase = self.read_database()\n userGroups = dataBase['userGroups']\n if userGroup not in userGroups:\n newGroup = dict()\n newGroup['owners'] = [requestUser]\n newGroup['members'] = list()\n newGroup['masterKey'] = self.generate_master_key().decode('cp855')\n dataBase['userGroups'][userGroup] = newGroup\n self.write_database(dataBase)\n else:\n raise GroupAlreadyExistsException(\"Specified user group already exists.\")","def add_user(request):\n if request.method == 'POST':\n form = CreateUserForm(request.POST)\n if form.is_valid():\n new_user = User.objects.create_user(form.cleaned_data['username'], \"user@invalid.com\", form.cleaned_data['password1'])\n role = form.cleaned_data['role']\n group = Group.objects.get(name=role)\n new_user.groups.add(group)\n return redirect(index)\n else:\n form = CreateUserForm() \n return render(request, 'users/add_user.html', {\n 'form': form,\n })","def modify_group_membership(http_method, group_id, user_id):\n\n if http_method not in [\"put\", \"delete\"]:\n raise ValueError(f\"Invalid HTTP request type: {http_method}\")\n endpoint = f\"/identities/groups/{group_id}/userMembers/{user_id}\"\n http_response = call_rest_api(endpoint, http_method, **config.DEFAULT_REST_KWARGS)\n\n # Adding a user:\n if http_method == \"put\":\n if http_response.status_code != 201: # 201 = 'member added to group'\n raise ValueError(http_response.text)\n logger.log(f\"A user with ID: {user_id}, was added to the custom group with ID: {group_id}.\")\n\n # Removing a user:\n elif http_method == \"delete\":\n if http_response.status_code != 204: # 204 = 'member removed'\n raise ValueError(http_response.text)\n logger.log(f\"A user with ID: {user_id}, was removed from the custom group with ID: {group_id}.\")","def add_user(self, user_id, group_id='', user_level=1, user_name='', name='', method_id=1):\n stmt = \"\"\"INSERT INTO users (_user_id, group_id, user_level, _user_name, _name, method_id) \n SELECT ?, ?, ?, ?, ?, ? \n WHERE NOT EXISTS(SELECT 1 FROM users WHERE (?) = _user_id)\"\"\"\n args = (user_id, group_id, user_level, user_name, name, method_id, user_id)\n self.conn.execute(stmt, args)\n self.conn.commit()","def join_group(self, user, group, force=0):\n if not force and not group.can_join(user):\n raise NotEnoughPrivileges\n \n group.add_member(user)\n user.add_to_group(get_usergroup_database().get_usergroup(group.get_user_id()))\n if hasattr(user, 'karma_activity_credit'):\n # groups can join groups, and groups don't have karma_activity_credit\n user.karma_activity_credit()\n \n self._flush_user_data_caches(user)","def handle(self, user):\n\n if not self.group_users:\n return\n for group_name, users in self.group_users.items():\n if user.username in users:\n group = self.get_group_from_db(group_name)\n user.groups.add(group)\n logger.info('Added {} to {}'.format(user.username, group_name))","def add_member(self, parent_group, group_name=None, user_name=None):\n METHOD = 'POST'\n API_PATH = '/groups/add-member'\n\n # Process group_name and user_name and add parent name to resulting dict\n data, target_name = self.__prep_group_or_user(group_name=group_name, user_name=user_name)\n data['parent_name'] = parent_group\n\n # Make REST call\n resp = self._rest_call[METHOD](API_PATH, data=data)\n\n if resp.status_code == 200:\n return target_name\n\n elif resp.status_code == 403:\n raise AuthorizationError(\"User is not authorized or token is incorrect.\")\n\n else:\n if resp.json().get(\"error_code\") in ERROR_CODES:\n raise ERROR_CODES[resp.json().get('error_code')](resp.json().get('message'))\n else:\n raise APIError(\"Response code {0}: {1} {2}\".format(resp.status_code,\n resp.json().get('error_code'),\n resp.json().get('message')))","def add_user_to_group(self, group_name, user_name, delegate_account=None):\n self.log.debug(\"Adding user \" + user_name + \" to group \" + group_name)\n params = {'GroupName': group_name,\n 'UserName': user_name}\n if delegate_account:\n params['DelegateAccount'] = delegate_account\n self.connection.get_response('AddUserToGroup', params)","def add_user(self, session, user_data: Dict) -> User:\n chat_id = user_data[\"chat_id\"]\n username = user_data[\"username\"]\n first_name = user_data[\"first_name\"]\n last_name = user_data[\"last_name\"]\n time_registered = user_data[\"time_registered\"]\n is_admin = False\n reminder_time = datetime.time(hour=21, tzinfo=TIME_ZONE)\n\n user = session.query(User).get(chat_id)\n if user:\n if user.username != username:\n user.username = username\n session.commit()\n if user.is_banned is True:\n user.is_banned = False\n session.commit()\n return user\n\n new_user = User(\n chat_id=chat_id,\n is_banned=False,\n username=username,\n first_name=first_name,\n last_name = last_name,\n time_registered = time_registered,\n is_admin = is_admin,\n reminder_time = reminder_time,\n )\n session.add(new_user)\n session.commit()\n return new_user","def add_user(self, user):\n logging.debug(\"Adding user id = %s \" % str(user.id))\n logging.debug(\"The set has %s users till now\" % str(len(self.users_queue.pending_pages)))\n return self._add_user(user)","def add_member(self, user, is_admin=False):\n # Only add members if they are not already one\n membership_count = InitiativeMembership.objects.filter(user=user, initiative=self).count()\n\n if membership_count > 0:\n raise SuspiciousOperation(\"Is already a member\")\n\n return InitiativeMembership.objects.create(user=user, initiative=self, is_admin=is_admin)","def create_group(user):\n if connexion.request.is_json:\n users_group = [User.from_dict(d) for d in connexion.request.get_json()]\n response = (\"success\", 201)\n if len(users_group) > 4:\n response = (\"Max number of player is 4\", 400)\n else:\n groupId = GroupStorageController.add_new_group(users_group)\n return response","def test_add_user_to_course_group(self):\r\n # Create groups for a new course (and assign instructor role to the creator).\r\n self.assertFalse(has_access(self.creator, CourseInstructorRole(self.course_key)))\r\n add_users(self.global_admin, CourseInstructorRole(self.course_key), self.creator)\r\n add_users(self.global_admin, CourseStaffRole(self.course_key), self.creator)\r\n self.assertTrue(has_access(self.creator, CourseInstructorRole(self.course_key)))\r\n\r\n # Add another user to the staff role.\r\n self.assertFalse(has_access(self.staff, CourseStaffRole(self.course_key)))\r\n add_users(self.creator, CourseStaffRole(self.course_key), self.staff)\r\n self.assertTrue(has_access(self.staff, CourseStaffRole(self.course_key)))","def test_adduser(self):\n self.run_function(\"group.add\", [self._group], gid=self._gid)\n self.run_function(\"user.add\", [self._user])\n self.assertTrue(self.run_function(\"group.adduser\", [self._group, self._user]))\n group_info = self.run_function(\"group.info\", [self._group])\n self.assertIn(self._user, str(group_info[\"members\"]))\n # try add a non existing user\n self.assertFalse(\n self.run_function(\"group.adduser\", [self._group, self._no_user])\n )\n # try add a user to non existing group\n self.assertFalse(\n self.run_function(\"group.adduser\", [self._no_group, self._user])\n )\n # try add a non existing user to a non existing group\n self.assertFalse(\n self.run_function(\"group.adduser\", [self._no_group, self._no_user])\n )","def create(person_group_id, name=None, user_data=None):\n name = person_group_id if name is None else name\n url = 'persongroups/{}'.format(person_group_id)\n json = {\n 'name': name,\n 'userData': user_data,\n }\n\n return util.request('PUT', url, json=json)","def _add_group(self, group):\n\n if group.name not in self.groups:\n # it's brand new, add him!\n self.groups[group.name] = group\n if self.groups[group.name] != group:\n # different object, merge\n self._merge_groups(self.groups[group.name], group)","def add_user_with_status_granted(caller, user):\r\n if _add_user(user, CourseCreator.GRANTED):\r\n update_course_creator_group(caller, user, True)","def addUser(self, user):\r\n self.users.append(user)\r\n return len(self.users)-1","def add_user(self, user, role=OrganizationUserRole.MEMBER):\n users_count = self.users.all().count()\n if users_count == 0:\n role = OrganizationUserRole.OWNER\n org_user = self._org_user_model.objects.create(\n user=user, organization=self, role=role\n )\n if users_count == 0:\n self._org_owner_model.objects.create(\n organization=self, organization_user=org_user\n )\n\n # User added signal\n user_added.send(sender=self, user=user)\n return org_user","def add(self, user):\n int_id = user.get_int_id(self.rooms)\n self.rooms[user.room][\"users\"].append(user)\n\n # Games\n if self.rooms[user.room][\"isGame\"] == \"true\":\n user.send([\"jg\", int_id, user.room])\n # Rooms\n else:\n user.send([\"jr\", int_id, user.room, self.get_strings(user.room)])\n self.packet.send_room([\"ap\", int_id, user.get_string()], user.room)","def add_user(self, user: User):\n raise NotImplementedError","def assign_TestUserGroup(test_case, # type: AnyMagpieTestCaseType\n override_user_name=null, # type: Optional[Str]\n override_group_name=null, # type: Optional[Str]\n override_headers=null, # type: Optional[HeadersType]\n override_cookies=null, # type: Optional[CookiesType]\n ): # type: (...) -> None\n app_or_url = get_app_or_url(test_case)\n usr_name = override_user_name if override_user_name is not null else test_case.test_user_name\n grp_name = override_group_name if override_group_name is not null else test_case.test_group_name\n path = \"/groups/{grp}/users\".format(grp=grp_name)\n resp = test_request(app_or_url, \"GET\", path,\n headers=override_headers if override_headers is not null else test_case.json_headers,\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\n body = check_response_basic_info(resp, 200, expected_method=\"GET\")\n if usr_name not in body[\"user_names\"]:\n path = \"/users/{usr}/groups\".format(usr=usr_name)\n data = {\"group_name\": grp_name}\n resp = test_request(app_or_url, \"POST\", path, json=data,\n headers=override_headers if override_headers is not null else test_case.json_headers,\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\n check_response_basic_info(resp, 201, expected_method=\"POST\")\n TestSetup.check_UserGroupMembership(test_case, override_user_name=usr_name, override_group_name=grp_name,\n override_headers=override_headers, override_cookies=override_cookies)","def add_user_to_groups(username):\n groups = request.get_json().get(\"groups\", [])\n return jsonify(\n admin.add_user_to_groups(current_app.scoped_session(), username, groups=groups)\n )","def add_user(self, REQUEST):\n\n role_id = REQUEST.form['role_id']\n country_code = role_id.rsplit('-', 1)[-1]\n user_id = REQUEST.form['user_id']\n agent = self._get_ldap_agent()\n\n if not self._allowed(agent, REQUEST, country_code):\n return None\n if not nfp_can_change_user(self, user_id, no_org=False):\n # This means somebody is manipulating the DOM in order to\n # add a user that belongs to an organisation from another\n # country (the button doesn't normally appear)\n return None\n\n with agent.new_action():\n role_id_list = agent.add_to_role(role_id, 'user', user_id)\n\n role_msg = get_role_name(agent, role_id)\n msg = \"User %r added to role %s. \\n\" % (user_id, role_msg)\n\n # for Eionet Groups roles only, test if the added user is member of a\n # national organisation\n\n if self.is_eionet_group(role_id):\n if not get_national_org(agent, user_id, role_id):\n msg += (\n \"The user you want to add to an Eionet Group does not\"\n \" have a mandatory reference to an organisation for \"\n \"your country. Please corect!\")\n\n IStatusMessage(REQUEST).add(msg, type='info')\n\n log.info(\"%s ADDED USER %r TO ROLE %r\",\n logged_in_user(REQUEST), user_id, role_id_list)\n\n if '-awp-' in role_id:\n return REQUEST.RESPONSE.redirect(self.absolute_url() +\n '/awps?nfp=%s#role_%s' %\n (country_code, role_id))\n\n return REQUEST.RESPONSE.redirect(self.absolute_url() +\n '/nrcs?nfp=%s#role_%s' %\n (country_code, role_id))","def add_user_to_group(self, group_name, user_login):\n params = {\n 'login': user_login,\n 'name': group_name\n }\n self.sonarqube.make_call('post', API_USER_GROUPS_ADD_USER_ENDPOINT, **params)","def add_user(self,\n\t\t\t\t user_id,\n\t\t\t\t password,\n\t\t\t\t user_group_oid,\n\t\t\t\t enable='',\n\t\t\t\t first_name='',\n\t\t\t\t last_name='',\n\t\t\t\t email='',\n\t\t\t\t description=''):\n\t\tresult = {\n\t\t\t'success': False,\n\t\t\t'response': '',\n\t\t\t'error': '',\n\t\t}\n\n\t\tself.ise.headers.update({'Content-Type': 'application/vnd.com.cisco.ise.identity.internaluser.1.0+xml'})\n\n\t\tdata = open(os.path.join(base_dir, 'xml/user_add.xml'), 'r').read().format(\n\t\t\t\tuser_id, password, enable, first_name, last_name, email, description, user_group_oid)\n\n\t\tresp = self.ise.post('{0}/config/internaluser'.format(self.url_base), data=data, timeout=self.timeout)\n\n\t\tif resp.status_code == 201:\n\t\t\tresult['success'] = True\n\t\t\tresult['response'] = '{0} Added Successfully'.format(user_id)\n\t\t\treturn result\n\t\telse:\n\t\t\tprint ('ERR:',resp.status_code) ; \n\t\t\timport pprint ; pprint.pprint(data) ; print ('RESP:',resp.text)\n\t\t\ttry:\n\t\t\t\tresult['response'] = ERS._to_json(resp.text)['ns3:ersResponse']['messages']['message']['title']\n\t\t\texcept:\n\t\t\t\tresult['response'] = resp.text\n\t\t\tresult['error'] = resp.status_code\n\t\t\treturn result","def add(\n new_user: schemas.UserCreate,\n db_session: Session = Depends(get_db),\n current_user: models.User = Depends(get_current_admin_user)\n):\n db_user = crud.get_by_email(db_session, new_user.email)\n\n if db_user:\n raise HTTPException(\n status_code=status.HTTP_400_BAD_REQUEST,\n detail='The user with this email already exists in the system.'\n )\n\n return crud.create(db_session, new_user)","def create_group(self, event):\n body = event['body']\n body = json.loads(body)\n\n # Required field in POST body\n if 'group_name' not in body:\n return self.get_bad_request('POST body missing group_name')\n\n group_name = body['group_name']\n user = self.mealShareUsers.get_user_cognito_data(event)\n user_id = user['user_id']\n \n # Add the creator to the group, as the initial member\n group_id = self.mealShareGroups.create_group(group_name)\n success = self.mealShareGroups.add_user_to_group(user_id, group_id)\n if success:\n return {\n 'statusCode': 200,\n 'statusMessage': 'Successfully created group {} with ID {}'.format(group_name, group_id),\n 'group_id': group_id,\n 'group_name': group_name,\n 'user_id': user_id\n }\n else:\n return {\n 'statusCode': 500,\n 'statusMessage': 'FAILED to create group {} by user {}'.format(group_name, user_id),\n 'group_id': group_id,\n 'group_name': group_name,\n 'user_id': user_id\n }","def create_group(self, group):\n if self.dryrun:\n self.logger.info(\"Would create group %s\", group)\n return FakeGroupId()\n result = self.conn.usergroup.create(name=group)\n groupid = result['usrgrpids'][0]\n self.logger.info(\"Create group %s with id %s\", group, groupid)\n return groupid","def add_member(self, request, **kwargs):\n valid_user = Member.objects.filter(group=self.get_object(), user=self.request.user).values('role_type').first()\n if valid_user['role_type'] == 'member':\n return Response({'message': 'You have no right to perform this action'}, status=status.HTTP_403_FORBIDDEN)\n if request.data.get('phone') is None:\n return Response({'message': 'Phone number not provided'}, status=status.HTTP_400_BAD_REQUEST)\n if request.data.get('role') is None:\n return Response({'message': 'Role is required'}, status=status.HTTP_400_BAD_REQUEST)\n if request.data.get('display_name') is None:\n return Response({'message': 'Name is required'}, status=status.HTTP_400_BAD_REQUEST)\n req_user = request.data.get('phone')\n user_data = User.objects.get(phone=req_user)\n if user_data is None:\n return Response({'message': 'User with this number is not registered'}, status=status.HTTP_404_NOT_FOUND)\n group = self.get_object()\n if group.members.filter(user=user_data).count() != 0:\n return Response({'message': 'User is already member of this group'}, status=status.HTTP_400_BAD_REQUEST)\n member_role = request.data.get('role')\n new_member_data = Member.objects.create(group=group, user=user_data,role_type=member_role, display_name=request.data.get('display_name'))\n new_member_data.save()\n serializer_data = MemberSerializer(new_member_data)\n return Response(serializer_data.data)","def test_add_new_user_to_public_group(self):\n new_user = User.objects.create_user(self.username)\n self.assertEqual(\n new_user.groups.filter(name=self.public_group_name).count(), 1)","def add_user(self, user_id):\n user_doc = {\n 'type': 'user',\n 'name': user_id\n }\n return self.add_doc_if_not_exists(user_doc, 'name')","def add_to_download_group(self, user):\r\n user.groups.add(self.dl_grp)","def add_new_user(self, user):\n # print(\"Saving new user\")\n self.execute(TABELLE['id_users']['insert']['complete_user'],\n (user['id'], False, False, True, False, False))\n\n self.execute(TABELLE['users']['insert'],\n (user['id'], user['username']))","def insert_user_group_additional(self, id_group:int, id_user:int) -> None:\n try:\n if not self.check_user_group_connection(id_group, id_user):\n self.connect_user_group(id_group, id_user)\n except Exception as e:\n msg = f\"We faced problems with additional insertion values; Mistake: {e}\"\n self.proceed_error(msg)","def add_group_group_member(self, targetgroup, groupname):\n try:\n targetgroup = self.quote(targetgroup)\n groupname = self.quote(groupname)\n self.g.put('groups/%s/groups/%s' % (targetgroup,\n groupname),\n headers={})\n except HTTPError as e:\n return self._manage_errors(e)","def one_group_member_sync_to_ucs(self, ucs_group_object, object):\n\t\t# In AD the object['dn'] is member of the group sync_object\n\n\t\tml = []\n\t\tif not self.__compare_lowercase(object['dn'], ucs_group_object['attributes'].get('uniqueMember', [])):\n\t\t\tml.append((ldap.MOD_ADD, 'uniqueMember', [object['dn']]))\n\n\t\tif object['attributes'].get('uid'):\n\t\t\tuid=object['attributes'].get('uid', [])[0]\n\t\t\tif not self.__compare_lowercase(uid, ucs_group_object['attributes'].get('memberUid', [])):\n\t\t\t\tml.append((ldap.MOD_ADD, 'memberUid', [uid]))\n\n\t\tif ml:\n\t\t\ttry:\n\t\t\t\tself.lo.lo.modify_s(ucs_group_object['dn'],compatible_modlist(ml))\n\t\t\texcept ldap.ALREADY_EXISTS:\n\t\t\t\t# The user is already member in this group or it is his primary group\n\t\t\t\t# This might happen, if we synchronize a rejected file with old informations\n\t\t\t\t# See Bug #25709 Comment #17: https://forge.univention.org/bugzilla/show_bug.cgi?id=25709#c17\n\t\t\t\tud.debug(ud.LDAP, ud.INFO, \"one_group_member_sync_to_ucs: User is already member of the group: %s modlist: %s\" % (ucs_group_object['dn'], ml))\n\t\t\t\tpass\n\n\t\t# The user has been removed from the cache. He must be added in any case\n\t\tif not self.group_members_cache_ucs.get(ucs_group_object['dn'].lower()):\n\t\t\tself.group_members_cache_ucs[ucs_group_object['dn'].lower()] = []\n\t\tud.debug(ud.LDAP, ud.INFO, \"one_group_member_sync_to_ucs: Append user %s to group ucs cache of %s\" % (object['dn'].lower(), ucs_group_object['dn'].lower()))\n\t\tself.group_members_cache_ucs[ucs_group_object['dn'].lower()].append(object['dn'].lower())","def add_user_to_g():\n if CURR_USER_KEY in session:\n g.user = User.query.get(session[CURR_USER_KEY])\n\n else:\n g.user = None","def add_user_to_g():\n\n if CURR_USER_KEY in session:\n g.user = User.query.get(session[CURR_USER_KEY])\n\n else:\n g.user = None","def add_user_to_g():\n\n if CURR_USER_KEY in session:\n g.user = User.query.get(session[CURR_USER_KEY])\n\n else:\n g.user = None","def add_user_to_g():\n\n if CURR_USER_KEY in session:\n g.user = User.query.get(session[CURR_USER_KEY])\n\n else:\n g.user = None","def add_user_to_g():\n \n if CURRENT_USER in session:\n g.user = User.query.get(session[CURRENT_USER])\n\n else:\n g.user = None","def add_member(self, request, pk):\n farm = self.get_object()\n user = request.data.get('user')\n farm.add_member(user)\n return Response({}, status=status.HTTP_202_ACCEPTED)","def subscribe(self, group, user, reason=GroupSubscriptionReason.unknown):\n try:\n with transaction.atomic():\n self.create(\n user=user,\n group=group,\n project=group.project,\n is_active=True,\n reason=reason,\n )\n except IntegrityError:\n pass","def newgroup(self, groupname, groupou=None, grouptype=None,\n description=None, mailaddress=None, notes=None, sd=None,\n gidnumber=None, nisdomain=None):\n\n group_dn = \"CN=%s,%s,%s\" % (groupname, (groupou or \"CN=Users\"), self.domain_dn())\n\n # The new user record. Note the reliance on the SAMLDB module which\n # fills in the default informations\n ldbmessage = {\"dn\": group_dn,\n \"sAMAccountName\": groupname,\n \"objectClass\": \"group\"}\n\n if grouptype is not None:\n ldbmessage[\"groupType\"] = normalise_int32(grouptype)\n\n if description is not None:\n ldbmessage[\"description\"] = description\n\n if mailaddress is not None:\n ldbmessage[\"mail\"] = mailaddress\n\n if notes is not None:\n ldbmessage[\"info\"] = notes\n\n if gidnumber is not None:\n ldbmessage[\"gidNumber\"] = normalise_int32(gidnumber)\n\n if nisdomain is not None:\n ldbmessage[\"msSFU30Name\"] = groupname\n ldbmessage[\"msSFU30NisDomain\"] = nisdomain\n\n if sd is not None:\n ldbmessage[\"nTSecurityDescriptor\"] = ndr_pack(sd)\n\n self.add(ldbmessage)","def add_user(self, user_id):\n\n if not str(user_id).isalnum():\n raise ValueError('Identifier must be the numerical user ID')\n\n # skip adding user if existing & detailed\n existing_user = self.get_user(user_id)\n if existing_user:\n if existing_user.get('detail') == 'full':\n log.info('Not adding user %s, already (full) in graph' % user_id)\n return existing_user\n if existing_user.get('detail') == 'basic':\n log.info('Not adding user %s, already (basic) in graph: updating' % user_id)\n return self.update_user(existing_user)\n\n\n log.info('Adding user %s to graph' % user_id)\n # get and assign user data to node\n props = self.fetch_user_data(user_id)\n user_node = self.gdb.node(**props)\n\n # add user node to indexes\n users = self.gdb.nodes.indexes.get('users')\n users['user_id'][props.get('id_str')] = user_node\n users['screen_name'][props.get('screen_name')] = user_node\n\n # add followers/following\n \n self.add_subscriptions(user_node)\n\n return user_node","def addUserObj(self, userObj : bbUser.bbUser):\n # Ensure no bbUser exists in the db with the same ID as the given bbUser\n if self.userIDExists(userObj.id):\n raise KeyError(\"Attempted to add a user that is already in this bbUserDB: \" + str(userObj))\n # Store the passed bbUser\n self.users[userObj.id] = userObj","def test_user_is_group_member(self):\n self.user.add_to_group(self.thread.group.pk)\n self.assertEqual(\n Thread.public.get_by_user(\n thread_id=self.thread.pk, user=self.user),\n self.thread\n )","def add_member(self, id, user):\n request = self.request_builder('orgs.teams.add_member',\n id=id, user=user)\n return self._put(request)","def add(self, user):\r\n url = '{0}/{1}'.format(self.get_url(), user)\r\n\r\n # include a body, because requests does not send content-length when no\r\n # body is present, and that makes GitHub respond with HTTP 411\r\n return http.Request('PUT', url, '*'), parsers.parse_empty","def signup(request):\n \n user_form = UserCreationForm()\n \n if request.method == 'POST':\n user_form = UserCreationForm(request.POST)\n if user_form.is_valid():\n \"\"\" new user account is created here\"\"\"\n \"\"\" @fixme: this is a buggy peice of code; cannot do commit=False; because a M-M relation cannot be attached to a non-existing object. \"\"\"\n new_user = user_form.save()\n \n \"\"\" @fixme: group is added after the account is created/commited to the DB; this is kinda bad; required two DB calls.\"\"\"\n# new_user.groups.add(Group.objects.get(name='student'))\n return HttpResponseRedirect(reverse(\"home.views.index\"))\n \n return render_to_response(\"auth/signup.html\", {\n 'form' : user_form\n }, context_instance=RequestContext(request))","def _add(self, signup_form_id, group_ids):\n path = '/members/add'\n data = self.extract()\n if group_ids:\n data['group_ids'] = group_ids\n if signup_form_id:\n data['signup_form_id'] = signup_form_id\n\n outcome = self.account.adapter.post(path, data)\n self['member_status_id'] = outcome['status']\n if outcome['added']:\n self['member_id'] = outcome['member_id']","def add_to_group(self, group):\n\n if not self.in_group(group):\n self.secondary_groups.append(group)\n return self","def add_to_groups(self, username, groups):\n pass","def get_user_group_membership(self, user_group_membership_id, **kwargs):\n resource_path = \"/userGroupMemberships/{userGroupMembershipId}\"\n method = \"GET\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"get_user_group_membership got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userGroupMembershipId\": user_group_membership_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"UserGroupMembership\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"UserGroupMembership\")","def create(self, validated_data):\n # print('Validated Data',validated_data['profile'].get('group'))\n group = validated_data['profile'].get('group')\n profile_data = validated_data.pop('profile')\n password = validated_data.pop('password')\n user = User(**validated_data)\n user.set_password(password)\n user.save()\n \"\"\"\n After the creation of the user he is added to a particular group.\n \"\"\"\n user.groups.add(Group.objects.get(name=group))\n UserProfile.objects.create(user=user, **profile_data)\n return user","def add_user(self, user):\n c = self.conn.cursor()\n cursor = c.execute(\"INSERT INTO users VALUES (null, ?, ?, ?)\",\n (user['username'], user['email'], hash_password(user['password']),))\n self.conn.commit()\n return self.get_user(cursor.lastrowid)","def one_group_member_sync_from_ucs(self, ad_group_object, object):\n\t\tml = []\n\t\tif not self.__compare_lowercase(object['dn'], ad_group_object['attributes'].get('member', [])):\n\t\t\tml.append((ldap.MOD_ADD, 'member', [object['dn']]))\n\n\t\tif ml:\n\t\t\ttry:\n\t\t\t\tself.lo_ad.lo.modify_s(ad_group_object['dn'],compatible_modlist(ml))\n\t\t\texcept ldap.ALREADY_EXISTS:\n\t\t\t\t# The user is already member in this group or it is his primary group\n\t\t\t\t# This might happen, if we synchronize a rejected file with old informations\n\t\t\t\t# See Bug #25709 Comment #17: https://forge.univention.org/bugzilla/show_bug.cgi?id=25709#c17\n\t\t\t\tud.debug(ud.LDAP, ud.INFO, \"one_group_member_sync_from_ucs: User is already member of the group: %s modlist: %s\" % (ad_group_object['dn'], ml))\n\t\t\t\tpass\n\n\t\t# The user has been removed from the cache. He must be added in any case\n\t\tud.debug(ud.LDAP, ud.INFO, \"one_group_member_sync_from_ucs: Append user %s to group con cache of %s\" % (object['dn'].lower(), ad_group_object['dn'].lower()))\n\t\tif not self.group_members_cache_con.get(ad_group_object['dn'].lower()):\n\t\t\tself.group_members_cache_con[ad_group_object['dn'].lower()] = []\n\t\tself.group_members_cache_con[ad_group_object['dn'].lower()].append(object['dn'].lower())","def add_group(username: str, gid: int=None, system: bool=False) -> Result[Group]:\n try:\n get_group(username)\n except KeyError:\n pass\n else:\n raise ValueError(\"Username {!r} is already in use\".format(username))\n args = [\"/usr/sbin/addgroup\", username]\n if gid:\n try:\n group = grp.getgrgid(gid)\n except KeyError:\n args[-1:-1] = [\"--gid\", str(gid)]\n else:\n raise ValueError(\"GID {} is already in use by {!r}\".format(gid, group.gr_name))\n if system:\n args[-1:-1] = [\"--system\"]\n command(args)\n return Result(State.success, get_group(username))","def addUser(self, id : int) -> bbUser.bbUser:\n id = self.validateID(id)\n # Ensure no user exists with the specified ID in the database\n if self.userIDExists(id):\n raise KeyError(\"Attempted to add a user that is already in this bbUserDB\")\n # Create and return a new user\n newUser = bbUser.bbUser.fromDict(bbUser.defaultUserDict, id=id)\n self.users[id] = newUser\n return newUser","def add_account(self, account):\n return self._client.group_memberships.create({\n 'account': account,\n 'group': self,\n })","def test_user_in_group_can_access(self):\n\n logged_user = utils.create_user_and_authenticate(self)\n self.group.users.add(logged_user)\n\n utils.test_can_access(self, self.url)","def newUser(self):\n user = IrcUser(hashed=True)\n self.nextId += 1\n id = self.nextId\n self.users[id] = user\n self.flush()\n user.id = id\n return user","def add_member(self, db: Session, *, room: Room, user: User) -> Room:\n members = [x for x in room.members]\n members.append(user)\n return self.update(db=db, db_obj=room, obj_in={\"members\": members})","def create_group(self, user_id, name, owner, description='',\n member_perms=[],\n other_perms=[],\n member_join_perms=[],\n other_join_perms=[],\n anon_read=0,\n no_pay=False):\n \n user_id = user_id.lower()\n \n if self.root.has_key(user_id) or get_usergroup_database().has_key(user_id):\n raise KeyError, \"Key %s already exists.\" % user_id\n\n if not no_pay:\n # charge owner for new group - don't create group if can't pay\n from qon.karma import NoKarmaToGive\n try:\n owner.pay_karma(self._karma_new_group)\n except NoKarmaToGive:\n return None\n\n group = Group(user_id=user_id, name=name, owner=owner)\n group.add_owner(owner)\n group.add_sponsor(owner)\n group.anon_read = anon_read\n group.description = description\n \n usergroup = UserGroup(group.user_id)\n get_usergroup_database().add_usergroup(usergroup)\n group.set_owning_group(usergroup)\n \n # members must have at least read access -- otherwise, what's the point of membership?\n mem_perms = member_perms\n if 'read' not in mem_perms:\n mem_perms.append('read')\n \n group.set_group_perms(mem_perms)\n group.set_other_perms(other_perms)\n group.get_members().set_group_perms(member_join_perms)\n group.get_members().set_other_perms(other_join_perms)\n \n # flush owner's group list cache\n self._flush_user_data_caches(owner)\n\n self.add_group(group)\n return group","def test_resource_user_resource_add_user_groups_for_user_post(self):\n pass","def post(self):\n status = ErrorCode.SUCCESS\n try:\n data = DotDict(json_decode(self.request.body))\n logging.info(\"[UWEB] add group request: %s, cid: %s\",\n data, self.current_user.cid)\n except Exception as e:\n status = ErrorCode.ILLEGAL_DATA_FORMAT\n logging.exception(\"[UWEB] Invalid data format. body:%s, Exception: %s\",\n self.request.body, e.args)\n self.write_ret(status)\n return\n\n try: \n cid = data.cid\n name = data.name\n group = self.get_group_by_cid(cid, name)\n if group:\n status = ErrorCode.GROUP_EXIST\n self.write_ret(status)\n return\n\n group_info = dict(cid=cid,\n name=name,\n type=UWEB.GROUP_TYPE.NEW)\n gid = add_group(group_info, self.db, self.redis)\n # NOTE: wspush to client\n tid = self.current_user.tid\n if status == ErrorCode.SUCCESS:\n WSPushHelper.pushS3(tid, self.db, self.redis)\n\n self.write_ret(status,\n dict_=dict(gid=gid,\n cid=cid,\n name=name))\n\n except Exception as e:\n logging.exception(\"[UWEB] Create group failed. uid: %s, Exception: %s\",\n self.current_user.uid, e.args)\n status = ErrorCode.SERVER_BUSY\n self.write_ret(status)","def add_user(self, userdict):\n return self.post('users', userdict)","def user_add(self, uname):\n # create group if it does not exist\n self.group_add()\n username = self.prefixed(uname)\n args = [\n \"useradd\",\n \"-g\",\n self._gname,\n \"-d\",\n \"/home/{}\".format(username),\n \"-s\",\n \"/sbin/nologin\",\n username\n ]\n logger.debug(args)\n self.call(args)","def add_user_to_division(self, **kwargs):\n try:\n is_head = kwargs.get('isHead')\n except:\n is_head = 0\n request = post(url=self.base_url + 'api/services/etender/division/AddUserToDivision',\n headers=self.headers,\n data=json.dumps({'userid': kwargs.get('user').get('userid'),\n 'divisionid': kwargs.get('division').get('id'),\n 'isHead': is_head}))\n print('Adding result: ', json.loads(request.content))\n return json.loads(request.content)"],"string":"[\n \"def addUserToGroup(self, user, group):\\n return self.pm_getUserManager().addUserToGroup(self._unbox(user), self._unbox(group))\",\n \"def add_user(self, user):\\n store = self.get('__store')\\n members = Members(store.db)\\n membership = members.first(group_id=self._id, user_id=user._id)\\n if not membership:\\n members.put(Member(group_id=self._id, user_id=user._id))\",\n \"def add_user_to_group(self, group_name, user_name):\\r\\n params = {'GroupName' : group_name,\\r\\n 'UserName' : user_name}\\r\\n return self.get_response('AddUserToGroup', params)\",\n \"def AddMemberToGroup(group_id,user_id):\\r\\n Group.AddMemberToGroup(group_id,user_id)\",\n \"def add_group_user(self, group_id, user_id):\\n resp, body = self.put('groups/%s/users/%s' % (group_id, user_id),\\n None)\\n self.expected_success(204, resp.status)\\n return service_client.ResponseBody(resp, body)\",\n \"def add_group_user(self, group_id, user_id):\\n resp, body = self.put('groups/%s/users/%s' % (group_id, user_id),\\n None)\\n self.expected_success(204, resp.status)\\n return rest_client.ResponseBody(resp, body)\",\n \"def action_add_to_group(self, kwargs):\\n user = kwargs[\\\"user\\\"]\\n group = kwargs[\\\"group\\\"]\\n\\n if self.engine.add_user_to_group(user, group):\\n info(f\\\"User {user} sucessfully added to {group}\\\")\\n else:\\n error(f\\\"Unable to add {user} to {group}, check privileges or dn\\\")\",\n \"def add_member(self, user):\\n user_in = user.get_groups()\\n for group in user_in:\\n if self.usergroup_node == group.usergroup_node:\\n print('user is already a member')\\n return False\\n membership = Relationship(user.get(), 'in', self.usergroup_node)\\n graph.create(membership)\\n return self.usergroup_node\",\n \"def add_to_group(user: User, group: Group) -> Result:\\n if user.pw_name in group.gr_mem:\\n return Result(State.unchanged)\\n command([\\\"/usr/sbin/addgroup\\\", user.pw_name, group.gr_name])\\n group.gr_mem.append(user.pw_name)\\n return Result(State.success)\",\n \"def register(self, user):\\n if not self.get():\\n user_node = user.get() # transform user object to user node object\\n usergroup_node = Node(\\\"Usergroup\\\",\\n groupname=self.groupname,\\n id=uuid4().hex)\\n graph.create(usergroup_node)\\n ownership = Relationship(user_node, 'owns', usergroup_node)\\n membership = Relationship(user_node, 'in', usergroup_node)\\n graph.create(ownership)\\n graph.create(membership)\\n self.usergroup_node = usergroup_node\\n self.id = usergroup_node['id']\\n return usergroup_node\\n return self\",\n \"def add_user_to_group(backend, details, response, user, is_new=False, *args, **kwargs):\\n \\n if is_new:\\n google_apps_add_group_task.apply_async([GAPPS_GROUP_NAME, user.email])\",\n \"def add_user_to_group(self, login, group):\\n return self.request('put',\\n '/groups/{}/users/{}'.format(group, login),\\n msg='adding user {} to group {}'.format(login, group)\\n )\",\n \"def post(self, id):\\r\\n return UserGroupService.addUserGroup(self, id)\",\n \"def add_group(self, group):\\n\\n return self._client.group_memberships.create({\\n 'account': self,\\n 'group': group\\n })\",\n \"def add_user_to_group(user, group):\\n Command.run(['usermod', '-a', '-G', user, group])\",\n \"def add_user_group(self, groupname, ls_user):\\n data = {\\\"groupname\\\": groupname, \\\"add_users\\\": ls_user}\\n headers = {\\\"user-agent\\\": self.u_agent}\\n req_url = self.normalize_admin_url(u\\\"groups/{}\\\".format(groupname))\\n res = requests.put(\\n req_url,\\n headers=headers,\\n auth=self.auth,\\n data=json.dumps(data),\\n verify=False,\\n )\\n if res.status_code in [200, 201, 206]:\\n return Response(0, res)\\n else:\\n return Response(res.status_code, res)\",\n \"def add_new_member(self, event):\\n body = event['body']\\n body = json.loads(body)\\n\\n required_fields = ['group_id', 'new_user_id']\\n for f in required_fields:\\n if f not in body:\\n return get_bad_request('POST body missing field {}'.format(f))\\n\\n group_id = body['group_id']\\n new_user_id = body['new_user_id']\\n \\n user = self.mealShareUsers.get_user_cognito_data(event)\\n current_user = user['user_id']\\n \\n # Requesting user must already be a member\\n if not self.mealShareGroups.is_user_in_group(current_user, str(group_id)):\\n return {\\n 'statusCode': 401,\\n 'statusMessage': 'User {} is not a member of the group ID {} and can not add a person to it'.format(current_user, group_id),\\n 'group_id': group_id,\\n 'new_user_id': new_user_id\\n }\\n \\n # Check if adding was successful\\n success = self.mealShareGroups.add_user_to_group(new_user_id, group_id)\\n if success:\\n return {\\n 'statusCode': 200,\\n 'statusMessage': 'Successfully added {} to group {}'.format(new_user_id, group_id),\\n 'group_id': group_id,\\n 'new_user_id': new_user_id\\n }\\n else:\\n return {\\n 'statusCode': 500,\\n 'statusMessage': 'FAILED to add user {} to group {} by {}'.format(new_user_id, group_id, current_user),\\n 'group_id': group_id,\\n 'new_user_id': new_user_id\\n }\",\n \"def add_group(self, resolvable):\\n group = self._resolve_group(resolvable)\\n return self._client.group_memberships.create({\\n 'account': self,\\n 'group': group,\\n })\",\n \"def add_user_to_group(self,username,groupname):\\n\\n if not self.check_prereqs():\\n raise StopIteration\\n\\n db = self.env.get_db_cnx()\\n cursor = db.cursor()\\n\\n query=self.create_query(self.sql_add_user_to_group_query,{'username':username,'groupname':groupname,'username_field':self.sql_username_field,'groupname_field':self.sql_groupname_field})\\n self.log.debug(\\\"sqlflexibleauthstore: add_user_to_group: %s\\\" % (query,))\\n\\n cursor.execute(query)\\n if cursor.rowcount > 0:\\n db.commit()\\n return True\\n return False\",\n \"def test_020_add_user_to_group(self):\\n testflow.step(\\\"Adding user %s to group %s\\\", TEST_USER1, TEST_GROUP1)\\n assert MANAGE_CLI.run(\\n 'useradd',\\n TEST_GROUP1,\\n user=TEST_USER1\\n )[0], \\\"Failed to add user to group '%s'\\\" % TEST_GROUP1\\n\\n testflow.step(\\\"Adding nonexisting user to group %s\\\", TEST_GROUP1)\\n assert not MANAGE_CLI.run(\\n 'useradd',\\n TEST_GROUP1,\\n user='nonsense'\\n )[0], \\\"Possible to add nonexisting user to group\\\"\\n\\n testflow.step(\\\"Adding user %s to nonexisting group\\\", TEST_USER2)\\n assert not MANAGE_CLI.run(\\n 'useradd',\\n 'nonsense',\\n user=TEST_USER2\\n )[0], \\\"Possible to add user to nonexisting group\\\"\",\n \"def AddUser(effective_user, effective_chat):\\n chatId = effective_chat.id\\n chatType = effective_chat.type\\n chatTitle = effective_chat.title\\n userId = effective_user.id\\n\\n if chatId == userId:\\n exists = session.query(User).filter_by(user_id=userId, group_id=None).one_or_none()\\n group_exists = False\\n else:\\n exists = session.query(User).filter_by(user_id=userId, group_id=chatId).one_or_none()\\n group_exists = session.query(Group).filter_by(id=chatId).one_or_none()\\n\\n if(exists is not None):\\n return False\\n\\n userGroupID = None\\n if chatId != userId:\\n userGroupID = chatId\\n\\n new_user = User(user_id=userId, \\n user_name = effective_user.username, \\n first_name=effective_user.first_name, \\n last_name=effective_user.last_name, \\n is_bot = effective_user.is_bot,\\n group_id = userGroupID)\\n\\n if chatId != userId and group_exists is None:\\n new_group = Group(id = chatId,\\n group_type = chatType,\\n title = chatTitle)\\n session.add(new_group)\\n\\n session.add(new_user)\\n session.commit()\\n return True\",\n \"def add_user_to_group(conn, user_dn, old_user_group_dn):\\n try:\\n conn.extend.microsoft.add_members_to_groups([str(user_dn)], [str(old_user_group_dn)])\\n except Exception as e:\\n raise Exception(\\\"Can't add user to this group :: {}\\\".format(e))\",\n \"def add_user_to_group(self, token, userGroup, userName, isOwner):\\n requestUser = self.get_username_from_token(token)\\n if self.check_user_has_owner_clearance(requestUser, userGroup):\\n dataBase = self.read_database()\\n owners = dataBase['userGroups'][userGroup]['owners']\\n members = dataBase['userGroups'][userGroup]['members']\\n if isOwner and userName not in owners:\\n dataBase['userGroups'][userGroup]['owners'].append(userName)\\n elif not isOwner and userName not in members:\\n dataBase['userGroups'][userGroup]['members'].append(userName)\\n\\n self.write_database(dataBase)\\n else:\\n raise UserPermissionException(\\n \\\"Requesting user is not owner of specified user group\\\")\",\n \"def post(self):\\n args = parser.parse_args()\\n user_group = UserGroup()\\n user_group.name = args['name']\\n user_group.createdby = auth.username()\\n db_session.add(user_group)\\n db_session.commit()\\n return user_group, 201\",\n \"def add_owner(self, user):\\n user_in = user.get_groups()\\n member = False\\n for group in user_in:\\n if self.usergroup_node == group.usergroup_node:\\n member = True\\n ownership = Relationship(user.get(), 'owns', self.usergroup_node)\\n graph.create(ownership)\\n if not member:\\n membership = Relationship(user.get(), 'in', self.usergroup_node)\\n graph.create(membership)\\n return self.usergroup_node\",\n \"def add_group(self, group_node, group_relationship_properties=None):\\n\\n user_group_relationship = Relationship(start_node=self.user_node,\\n rel=AgoraRelationship.MEMBER_OF,\\n end_node=group_node)\\n self.graph_db.create_unique(user_group_relationship)\\n #TODO set properties on the relationsip\\n # group_relationship_properties[\\\"unique_id\\\"] = str(uuid.uuid4())\",\n \"def add_to_group(_request, group_id, email):\\n group = models.UserGroup.get_by_id(int(group_id))\\n user_key = models.UserProfile.load(email).key()\\n if group.users is None:\\n group.users = []\\n logging.warning('Group \\\"%s\\\" had a None users list', group.name)\\n group.users.append(user_key)\\n group.put()\\n\\n url = urlresolvers.reverse('views.admin.edit_user', args=[email])\\n return http.HttpResponseRedirect(url)\",\n \"def test_save(self, name='test', user=None):\\n group = Group(name=name)\\n group.save()\\n \\n if user:\\n group.user_set.add(user)\\n \\n return group\",\n \"def add_member_command(client: MsGraphClient, args: dict) -> tuple[str, dict, dict]:\\n group_id = str(args.get('group_id'))\\n user_id = str(args.get('user_id'))\\n required_properties = {\\n \\\"@odata.id\\\": f'https://graph.microsoft.com/v1.0/users/{user_id}'}\\n client.add_member(group_id, required_properties)\\n\\n human_readable = f'User {user_id} was added to the Group {group_id} successfully.'\\n return human_readable, NO_OUTPUTS, NO_OUTPUTS\",\n \"def _register(self, user=None):\\n if user is None:\\n user = User.objects.create_user(\\n username=self.username,\\n password=self.password)\\n user.is_active = self.active\\n # Automatically add the user to the proper group\\n if self._group_name is not None:\\n group = get_or_none(Group, name=self._group_name)\\n if group is not None:\\n user.groups.add(group)\\n\\n user.save()\\n profile = UserProfile(user=user, member=self)\\n profile.save()\",\n \"def create_new_user_group(self, token, userGroup):\\n requestUser = self.get_username_from_token(token)\\n dataBase = self.read_database()\\n userGroups = dataBase['userGroups']\\n if userGroup not in userGroups:\\n newGroup = dict()\\n newGroup['owners'] = [requestUser]\\n newGroup['members'] = list()\\n newGroup['masterKey'] = self.generate_master_key().decode('cp855')\\n dataBase['userGroups'][userGroup] = newGroup\\n self.write_database(dataBase)\\n else:\\n raise GroupAlreadyExistsException(\\\"Specified user group already exists.\\\")\",\n \"def add_user(request):\\n if request.method == 'POST':\\n form = CreateUserForm(request.POST)\\n if form.is_valid():\\n new_user = User.objects.create_user(form.cleaned_data['username'], \\\"user@invalid.com\\\", form.cleaned_data['password1'])\\n role = form.cleaned_data['role']\\n group = Group.objects.get(name=role)\\n new_user.groups.add(group)\\n return redirect(index)\\n else:\\n form = CreateUserForm() \\n return render(request, 'users/add_user.html', {\\n 'form': form,\\n })\",\n \"def modify_group_membership(http_method, group_id, user_id):\\n\\n if http_method not in [\\\"put\\\", \\\"delete\\\"]:\\n raise ValueError(f\\\"Invalid HTTP request type: {http_method}\\\")\\n endpoint = f\\\"/identities/groups/{group_id}/userMembers/{user_id}\\\"\\n http_response = call_rest_api(endpoint, http_method, **config.DEFAULT_REST_KWARGS)\\n\\n # Adding a user:\\n if http_method == \\\"put\\\":\\n if http_response.status_code != 201: # 201 = 'member added to group'\\n raise ValueError(http_response.text)\\n logger.log(f\\\"A user with ID: {user_id}, was added to the custom group with ID: {group_id}.\\\")\\n\\n # Removing a user:\\n elif http_method == \\\"delete\\\":\\n if http_response.status_code != 204: # 204 = 'member removed'\\n raise ValueError(http_response.text)\\n logger.log(f\\\"A user with ID: {user_id}, was removed from the custom group with ID: {group_id}.\\\")\",\n \"def add_user(self, user_id, group_id='', user_level=1, user_name='', name='', method_id=1):\\n stmt = \\\"\\\"\\\"INSERT INTO users (_user_id, group_id, user_level, _user_name, _name, method_id) \\n SELECT ?, ?, ?, ?, ?, ? \\n WHERE NOT EXISTS(SELECT 1 FROM users WHERE (?) = _user_id)\\\"\\\"\\\"\\n args = (user_id, group_id, user_level, user_name, name, method_id, user_id)\\n self.conn.execute(stmt, args)\\n self.conn.commit()\",\n \"def join_group(self, user, group, force=0):\\n if not force and not group.can_join(user):\\n raise NotEnoughPrivileges\\n \\n group.add_member(user)\\n user.add_to_group(get_usergroup_database().get_usergroup(group.get_user_id()))\\n if hasattr(user, 'karma_activity_credit'):\\n # groups can join groups, and groups don't have karma_activity_credit\\n user.karma_activity_credit()\\n \\n self._flush_user_data_caches(user)\",\n \"def handle(self, user):\\n\\n if not self.group_users:\\n return\\n for group_name, users in self.group_users.items():\\n if user.username in users:\\n group = self.get_group_from_db(group_name)\\n user.groups.add(group)\\n logger.info('Added {} to {}'.format(user.username, group_name))\",\n \"def add_member(self, parent_group, group_name=None, user_name=None):\\n METHOD = 'POST'\\n API_PATH = '/groups/add-member'\\n\\n # Process group_name and user_name and add parent name to resulting dict\\n data, target_name = self.__prep_group_or_user(group_name=group_name, user_name=user_name)\\n data['parent_name'] = parent_group\\n\\n # Make REST call\\n resp = self._rest_call[METHOD](API_PATH, data=data)\\n\\n if resp.status_code == 200:\\n return target_name\\n\\n elif resp.status_code == 403:\\n raise AuthorizationError(\\\"User is not authorized or token is incorrect.\\\")\\n\\n else:\\n if resp.json().get(\\\"error_code\\\") in ERROR_CODES:\\n raise ERROR_CODES[resp.json().get('error_code')](resp.json().get('message'))\\n else:\\n raise APIError(\\\"Response code {0}: {1} {2}\\\".format(resp.status_code,\\n resp.json().get('error_code'),\\n resp.json().get('message')))\",\n \"def add_user_to_group(self, group_name, user_name, delegate_account=None):\\n self.log.debug(\\\"Adding user \\\" + user_name + \\\" to group \\\" + group_name)\\n params = {'GroupName': group_name,\\n 'UserName': user_name}\\n if delegate_account:\\n params['DelegateAccount'] = delegate_account\\n self.connection.get_response('AddUserToGroup', params)\",\n \"def add_user(self, session, user_data: Dict) -> User:\\n chat_id = user_data[\\\"chat_id\\\"]\\n username = user_data[\\\"username\\\"]\\n first_name = user_data[\\\"first_name\\\"]\\n last_name = user_data[\\\"last_name\\\"]\\n time_registered = user_data[\\\"time_registered\\\"]\\n is_admin = False\\n reminder_time = datetime.time(hour=21, tzinfo=TIME_ZONE)\\n\\n user = session.query(User).get(chat_id)\\n if user:\\n if user.username != username:\\n user.username = username\\n session.commit()\\n if user.is_banned is True:\\n user.is_banned = False\\n session.commit()\\n return user\\n\\n new_user = User(\\n chat_id=chat_id,\\n is_banned=False,\\n username=username,\\n first_name=first_name,\\n last_name = last_name,\\n time_registered = time_registered,\\n is_admin = is_admin,\\n reminder_time = reminder_time,\\n )\\n session.add(new_user)\\n session.commit()\\n return new_user\",\n \"def add_user(self, user):\\n logging.debug(\\\"Adding user id = %s \\\" % str(user.id))\\n logging.debug(\\\"The set has %s users till now\\\" % str(len(self.users_queue.pending_pages)))\\n return self._add_user(user)\",\n \"def add_member(self, user, is_admin=False):\\n # Only add members if they are not already one\\n membership_count = InitiativeMembership.objects.filter(user=user, initiative=self).count()\\n\\n if membership_count > 0:\\n raise SuspiciousOperation(\\\"Is already a member\\\")\\n\\n return InitiativeMembership.objects.create(user=user, initiative=self, is_admin=is_admin)\",\n \"def create_group(user):\\n if connexion.request.is_json:\\n users_group = [User.from_dict(d) for d in connexion.request.get_json()]\\n response = (\\\"success\\\", 201)\\n if len(users_group) > 4:\\n response = (\\\"Max number of player is 4\\\", 400)\\n else:\\n groupId = GroupStorageController.add_new_group(users_group)\\n return response\",\n \"def test_add_user_to_course_group(self):\\r\\n # Create groups for a new course (and assign instructor role to the creator).\\r\\n self.assertFalse(has_access(self.creator, CourseInstructorRole(self.course_key)))\\r\\n add_users(self.global_admin, CourseInstructorRole(self.course_key), self.creator)\\r\\n add_users(self.global_admin, CourseStaffRole(self.course_key), self.creator)\\r\\n self.assertTrue(has_access(self.creator, CourseInstructorRole(self.course_key)))\\r\\n\\r\\n # Add another user to the staff role.\\r\\n self.assertFalse(has_access(self.staff, CourseStaffRole(self.course_key)))\\r\\n add_users(self.creator, CourseStaffRole(self.course_key), self.staff)\\r\\n self.assertTrue(has_access(self.staff, CourseStaffRole(self.course_key)))\",\n \"def test_adduser(self):\\n self.run_function(\\\"group.add\\\", [self._group], gid=self._gid)\\n self.run_function(\\\"user.add\\\", [self._user])\\n self.assertTrue(self.run_function(\\\"group.adduser\\\", [self._group, self._user]))\\n group_info = self.run_function(\\\"group.info\\\", [self._group])\\n self.assertIn(self._user, str(group_info[\\\"members\\\"]))\\n # try add a non existing user\\n self.assertFalse(\\n self.run_function(\\\"group.adduser\\\", [self._group, self._no_user])\\n )\\n # try add a user to non existing group\\n self.assertFalse(\\n self.run_function(\\\"group.adduser\\\", [self._no_group, self._user])\\n )\\n # try add a non existing user to a non existing group\\n self.assertFalse(\\n self.run_function(\\\"group.adduser\\\", [self._no_group, self._no_user])\\n )\",\n \"def create(person_group_id, name=None, user_data=None):\\n name = person_group_id if name is None else name\\n url = 'persongroups/{}'.format(person_group_id)\\n json = {\\n 'name': name,\\n 'userData': user_data,\\n }\\n\\n return util.request('PUT', url, json=json)\",\n \"def _add_group(self, group):\\n\\n if group.name not in self.groups:\\n # it's brand new, add him!\\n self.groups[group.name] = group\\n if self.groups[group.name] != group:\\n # different object, merge\\n self._merge_groups(self.groups[group.name], group)\",\n \"def add_user_with_status_granted(caller, user):\\r\\n if _add_user(user, CourseCreator.GRANTED):\\r\\n update_course_creator_group(caller, user, True)\",\n \"def addUser(self, user):\\r\\n self.users.append(user)\\r\\n return len(self.users)-1\",\n \"def add_user(self, user, role=OrganizationUserRole.MEMBER):\\n users_count = self.users.all().count()\\n if users_count == 0:\\n role = OrganizationUserRole.OWNER\\n org_user = self._org_user_model.objects.create(\\n user=user, organization=self, role=role\\n )\\n if users_count == 0:\\n self._org_owner_model.objects.create(\\n organization=self, organization_user=org_user\\n )\\n\\n # User added signal\\n user_added.send(sender=self, user=user)\\n return org_user\",\n \"def add(self, user):\\n int_id = user.get_int_id(self.rooms)\\n self.rooms[user.room][\\\"users\\\"].append(user)\\n\\n # Games\\n if self.rooms[user.room][\\\"isGame\\\"] == \\\"true\\\":\\n user.send([\\\"jg\\\", int_id, user.room])\\n # Rooms\\n else:\\n user.send([\\\"jr\\\", int_id, user.room, self.get_strings(user.room)])\\n self.packet.send_room([\\\"ap\\\", int_id, user.get_string()], user.room)\",\n \"def add_user(self, user: User):\\n raise NotImplementedError\",\n \"def assign_TestUserGroup(test_case, # type: AnyMagpieTestCaseType\\n override_user_name=null, # type: Optional[Str]\\n override_group_name=null, # type: Optional[Str]\\n override_headers=null, # type: Optional[HeadersType]\\n override_cookies=null, # type: Optional[CookiesType]\\n ): # type: (...) -> None\\n app_or_url = get_app_or_url(test_case)\\n usr_name = override_user_name if override_user_name is not null else test_case.test_user_name\\n grp_name = override_group_name if override_group_name is not null else test_case.test_group_name\\n path = \\\"/groups/{grp}/users\\\".format(grp=grp_name)\\n resp = test_request(app_or_url, \\\"GET\\\", path,\\n headers=override_headers if override_headers is not null else test_case.json_headers,\\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\\n body = check_response_basic_info(resp, 200, expected_method=\\\"GET\\\")\\n if usr_name not in body[\\\"user_names\\\"]:\\n path = \\\"/users/{usr}/groups\\\".format(usr=usr_name)\\n data = {\\\"group_name\\\": grp_name}\\n resp = test_request(app_or_url, \\\"POST\\\", path, json=data,\\n headers=override_headers if override_headers is not null else test_case.json_headers,\\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\\n check_response_basic_info(resp, 201, expected_method=\\\"POST\\\")\\n TestSetup.check_UserGroupMembership(test_case, override_user_name=usr_name, override_group_name=grp_name,\\n override_headers=override_headers, override_cookies=override_cookies)\",\n \"def add_user_to_groups(username):\\n groups = request.get_json().get(\\\"groups\\\", [])\\n return jsonify(\\n admin.add_user_to_groups(current_app.scoped_session(), username, groups=groups)\\n )\",\n \"def add_user(self, REQUEST):\\n\\n role_id = REQUEST.form['role_id']\\n country_code = role_id.rsplit('-', 1)[-1]\\n user_id = REQUEST.form['user_id']\\n agent = self._get_ldap_agent()\\n\\n if not self._allowed(agent, REQUEST, country_code):\\n return None\\n if not nfp_can_change_user(self, user_id, no_org=False):\\n # This means somebody is manipulating the DOM in order to\\n # add a user that belongs to an organisation from another\\n # country (the button doesn't normally appear)\\n return None\\n\\n with agent.new_action():\\n role_id_list = agent.add_to_role(role_id, 'user', user_id)\\n\\n role_msg = get_role_name(agent, role_id)\\n msg = \\\"User %r added to role %s. \\\\n\\\" % (user_id, role_msg)\\n\\n # for Eionet Groups roles only, test if the added user is member of a\\n # national organisation\\n\\n if self.is_eionet_group(role_id):\\n if not get_national_org(agent, user_id, role_id):\\n msg += (\\n \\\"The user you want to add to an Eionet Group does not\\\"\\n \\\" have a mandatory reference to an organisation for \\\"\\n \\\"your country. Please corect!\\\")\\n\\n IStatusMessage(REQUEST).add(msg, type='info')\\n\\n log.info(\\\"%s ADDED USER %r TO ROLE %r\\\",\\n logged_in_user(REQUEST), user_id, role_id_list)\\n\\n if '-awp-' in role_id:\\n return REQUEST.RESPONSE.redirect(self.absolute_url() +\\n '/awps?nfp=%s#role_%s' %\\n (country_code, role_id))\\n\\n return REQUEST.RESPONSE.redirect(self.absolute_url() +\\n '/nrcs?nfp=%s#role_%s' %\\n (country_code, role_id))\",\n \"def add_user_to_group(self, group_name, user_login):\\n params = {\\n 'login': user_login,\\n 'name': group_name\\n }\\n self.sonarqube.make_call('post', API_USER_GROUPS_ADD_USER_ENDPOINT, **params)\",\n \"def add_user(self,\\n\\t\\t\\t\\t user_id,\\n\\t\\t\\t\\t password,\\n\\t\\t\\t\\t user_group_oid,\\n\\t\\t\\t\\t enable='',\\n\\t\\t\\t\\t first_name='',\\n\\t\\t\\t\\t last_name='',\\n\\t\\t\\t\\t email='',\\n\\t\\t\\t\\t description=''):\\n\\t\\tresult = {\\n\\t\\t\\t'success': False,\\n\\t\\t\\t'response': '',\\n\\t\\t\\t'error': '',\\n\\t\\t}\\n\\n\\t\\tself.ise.headers.update({'Content-Type': 'application/vnd.com.cisco.ise.identity.internaluser.1.0+xml'})\\n\\n\\t\\tdata = open(os.path.join(base_dir, 'xml/user_add.xml'), 'r').read().format(\\n\\t\\t\\t\\tuser_id, password, enable, first_name, last_name, email, description, user_group_oid)\\n\\n\\t\\tresp = self.ise.post('{0}/config/internaluser'.format(self.url_base), data=data, timeout=self.timeout)\\n\\n\\t\\tif resp.status_code == 201:\\n\\t\\t\\tresult['success'] = True\\n\\t\\t\\tresult['response'] = '{0} Added Successfully'.format(user_id)\\n\\t\\t\\treturn result\\n\\t\\telse:\\n\\t\\t\\tprint ('ERR:',resp.status_code) ; \\n\\t\\t\\timport pprint ; pprint.pprint(data) ; print ('RESP:',resp.text)\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tresult['response'] = ERS._to_json(resp.text)['ns3:ersResponse']['messages']['message']['title']\\n\\t\\t\\texcept:\\n\\t\\t\\t\\tresult['response'] = resp.text\\n\\t\\t\\tresult['error'] = resp.status_code\\n\\t\\t\\treturn result\",\n \"def add(\\n new_user: schemas.UserCreate,\\n db_session: Session = Depends(get_db),\\n current_user: models.User = Depends(get_current_admin_user)\\n):\\n db_user = crud.get_by_email(db_session, new_user.email)\\n\\n if db_user:\\n raise HTTPException(\\n status_code=status.HTTP_400_BAD_REQUEST,\\n detail='The user with this email already exists in the system.'\\n )\\n\\n return crud.create(db_session, new_user)\",\n \"def create_group(self, event):\\n body = event['body']\\n body = json.loads(body)\\n\\n # Required field in POST body\\n if 'group_name' not in body:\\n return self.get_bad_request('POST body missing group_name')\\n\\n group_name = body['group_name']\\n user = self.mealShareUsers.get_user_cognito_data(event)\\n user_id = user['user_id']\\n \\n # Add the creator to the group, as the initial member\\n group_id = self.mealShareGroups.create_group(group_name)\\n success = self.mealShareGroups.add_user_to_group(user_id, group_id)\\n if success:\\n return {\\n 'statusCode': 200,\\n 'statusMessage': 'Successfully created group {} with ID {}'.format(group_name, group_id),\\n 'group_id': group_id,\\n 'group_name': group_name,\\n 'user_id': user_id\\n }\\n else:\\n return {\\n 'statusCode': 500,\\n 'statusMessage': 'FAILED to create group {} by user {}'.format(group_name, user_id),\\n 'group_id': group_id,\\n 'group_name': group_name,\\n 'user_id': user_id\\n }\",\n \"def create_group(self, group):\\n if self.dryrun:\\n self.logger.info(\\\"Would create group %s\\\", group)\\n return FakeGroupId()\\n result = self.conn.usergroup.create(name=group)\\n groupid = result['usrgrpids'][0]\\n self.logger.info(\\\"Create group %s with id %s\\\", group, groupid)\\n return groupid\",\n \"def add_member(self, request, **kwargs):\\n valid_user = Member.objects.filter(group=self.get_object(), user=self.request.user).values('role_type').first()\\n if valid_user['role_type'] == 'member':\\n return Response({'message': 'You have no right to perform this action'}, status=status.HTTP_403_FORBIDDEN)\\n if request.data.get('phone') is None:\\n return Response({'message': 'Phone number not provided'}, status=status.HTTP_400_BAD_REQUEST)\\n if request.data.get('role') is None:\\n return Response({'message': 'Role is required'}, status=status.HTTP_400_BAD_REQUEST)\\n if request.data.get('display_name') is None:\\n return Response({'message': 'Name is required'}, status=status.HTTP_400_BAD_REQUEST)\\n req_user = request.data.get('phone')\\n user_data = User.objects.get(phone=req_user)\\n if user_data is None:\\n return Response({'message': 'User with this number is not registered'}, status=status.HTTP_404_NOT_FOUND)\\n group = self.get_object()\\n if group.members.filter(user=user_data).count() != 0:\\n return Response({'message': 'User is already member of this group'}, status=status.HTTP_400_BAD_REQUEST)\\n member_role = request.data.get('role')\\n new_member_data = Member.objects.create(group=group, user=user_data,role_type=member_role, display_name=request.data.get('display_name'))\\n new_member_data.save()\\n serializer_data = MemberSerializer(new_member_data)\\n return Response(serializer_data.data)\",\n \"def test_add_new_user_to_public_group(self):\\n new_user = User.objects.create_user(self.username)\\n self.assertEqual(\\n new_user.groups.filter(name=self.public_group_name).count(), 1)\",\n \"def add_user(self, user_id):\\n user_doc = {\\n 'type': 'user',\\n 'name': user_id\\n }\\n return self.add_doc_if_not_exists(user_doc, 'name')\",\n \"def add_to_download_group(self, user):\\r\\n user.groups.add(self.dl_grp)\",\n \"def add_new_user(self, user):\\n # print(\\\"Saving new user\\\")\\n self.execute(TABELLE['id_users']['insert']['complete_user'],\\n (user['id'], False, False, True, False, False))\\n\\n self.execute(TABELLE['users']['insert'],\\n (user['id'], user['username']))\",\n \"def insert_user_group_additional(self, id_group:int, id_user:int) -> None:\\n try:\\n if not self.check_user_group_connection(id_group, id_user):\\n self.connect_user_group(id_group, id_user)\\n except Exception as e:\\n msg = f\\\"We faced problems with additional insertion values; Mistake: {e}\\\"\\n self.proceed_error(msg)\",\n \"def add_group_group_member(self, targetgroup, groupname):\\n try:\\n targetgroup = self.quote(targetgroup)\\n groupname = self.quote(groupname)\\n self.g.put('groups/%s/groups/%s' % (targetgroup,\\n groupname),\\n headers={})\\n except HTTPError as e:\\n return self._manage_errors(e)\",\n \"def one_group_member_sync_to_ucs(self, ucs_group_object, object):\\n\\t\\t# In AD the object['dn'] is member of the group sync_object\\n\\n\\t\\tml = []\\n\\t\\tif not self.__compare_lowercase(object['dn'], ucs_group_object['attributes'].get('uniqueMember', [])):\\n\\t\\t\\tml.append((ldap.MOD_ADD, 'uniqueMember', [object['dn']]))\\n\\n\\t\\tif object['attributes'].get('uid'):\\n\\t\\t\\tuid=object['attributes'].get('uid', [])[0]\\n\\t\\t\\tif not self.__compare_lowercase(uid, ucs_group_object['attributes'].get('memberUid', [])):\\n\\t\\t\\t\\tml.append((ldap.MOD_ADD, 'memberUid', [uid]))\\n\\n\\t\\tif ml:\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tself.lo.lo.modify_s(ucs_group_object['dn'],compatible_modlist(ml))\\n\\t\\t\\texcept ldap.ALREADY_EXISTS:\\n\\t\\t\\t\\t# The user is already member in this group or it is his primary group\\n\\t\\t\\t\\t# This might happen, if we synchronize a rejected file with old informations\\n\\t\\t\\t\\t# See Bug #25709 Comment #17: https://forge.univention.org/bugzilla/show_bug.cgi?id=25709#c17\\n\\t\\t\\t\\tud.debug(ud.LDAP, ud.INFO, \\\"one_group_member_sync_to_ucs: User is already member of the group: %s modlist: %s\\\" % (ucs_group_object['dn'], ml))\\n\\t\\t\\t\\tpass\\n\\n\\t\\t# The user has been removed from the cache. He must be added in any case\\n\\t\\tif not self.group_members_cache_ucs.get(ucs_group_object['dn'].lower()):\\n\\t\\t\\tself.group_members_cache_ucs[ucs_group_object['dn'].lower()] = []\\n\\t\\tud.debug(ud.LDAP, ud.INFO, \\\"one_group_member_sync_to_ucs: Append user %s to group ucs cache of %s\\\" % (object['dn'].lower(), ucs_group_object['dn'].lower()))\\n\\t\\tself.group_members_cache_ucs[ucs_group_object['dn'].lower()].append(object['dn'].lower())\",\n \"def add_user_to_g():\\n if CURR_USER_KEY in session:\\n g.user = User.query.get(session[CURR_USER_KEY])\\n\\n else:\\n g.user = None\",\n \"def add_user_to_g():\\n\\n if CURR_USER_KEY in session:\\n g.user = User.query.get(session[CURR_USER_KEY])\\n\\n else:\\n g.user = None\",\n \"def add_user_to_g():\\n\\n if CURR_USER_KEY in session:\\n g.user = User.query.get(session[CURR_USER_KEY])\\n\\n else:\\n g.user = None\",\n \"def add_user_to_g():\\n\\n if CURR_USER_KEY in session:\\n g.user = User.query.get(session[CURR_USER_KEY])\\n\\n else:\\n g.user = None\",\n \"def add_user_to_g():\\n \\n if CURRENT_USER in session:\\n g.user = User.query.get(session[CURRENT_USER])\\n\\n else:\\n g.user = None\",\n \"def add_member(self, request, pk):\\n farm = self.get_object()\\n user = request.data.get('user')\\n farm.add_member(user)\\n return Response({}, status=status.HTTP_202_ACCEPTED)\",\n \"def subscribe(self, group, user, reason=GroupSubscriptionReason.unknown):\\n try:\\n with transaction.atomic():\\n self.create(\\n user=user,\\n group=group,\\n project=group.project,\\n is_active=True,\\n reason=reason,\\n )\\n except IntegrityError:\\n pass\",\n \"def newgroup(self, groupname, groupou=None, grouptype=None,\\n description=None, mailaddress=None, notes=None, sd=None,\\n gidnumber=None, nisdomain=None):\\n\\n group_dn = \\\"CN=%s,%s,%s\\\" % (groupname, (groupou or \\\"CN=Users\\\"), self.domain_dn())\\n\\n # The new user record. Note the reliance on the SAMLDB module which\\n # fills in the default informations\\n ldbmessage = {\\\"dn\\\": group_dn,\\n \\\"sAMAccountName\\\": groupname,\\n \\\"objectClass\\\": \\\"group\\\"}\\n\\n if grouptype is not None:\\n ldbmessage[\\\"groupType\\\"] = normalise_int32(grouptype)\\n\\n if description is not None:\\n ldbmessage[\\\"description\\\"] = description\\n\\n if mailaddress is not None:\\n ldbmessage[\\\"mail\\\"] = mailaddress\\n\\n if notes is not None:\\n ldbmessage[\\\"info\\\"] = notes\\n\\n if gidnumber is not None:\\n ldbmessage[\\\"gidNumber\\\"] = normalise_int32(gidnumber)\\n\\n if nisdomain is not None:\\n ldbmessage[\\\"msSFU30Name\\\"] = groupname\\n ldbmessage[\\\"msSFU30NisDomain\\\"] = nisdomain\\n\\n if sd is not None:\\n ldbmessage[\\\"nTSecurityDescriptor\\\"] = ndr_pack(sd)\\n\\n self.add(ldbmessage)\",\n \"def add_user(self, user_id):\\n\\n if not str(user_id).isalnum():\\n raise ValueError('Identifier must be the numerical user ID')\\n\\n # skip adding user if existing & detailed\\n existing_user = self.get_user(user_id)\\n if existing_user:\\n if existing_user.get('detail') == 'full':\\n log.info('Not adding user %s, already (full) in graph' % user_id)\\n return existing_user\\n if existing_user.get('detail') == 'basic':\\n log.info('Not adding user %s, already (basic) in graph: updating' % user_id)\\n return self.update_user(existing_user)\\n\\n\\n log.info('Adding user %s to graph' % user_id)\\n # get and assign user data to node\\n props = self.fetch_user_data(user_id)\\n user_node = self.gdb.node(**props)\\n\\n # add user node to indexes\\n users = self.gdb.nodes.indexes.get('users')\\n users['user_id'][props.get('id_str')] = user_node\\n users['screen_name'][props.get('screen_name')] = user_node\\n\\n # add followers/following\\n \\n self.add_subscriptions(user_node)\\n\\n return user_node\",\n \"def addUserObj(self, userObj : bbUser.bbUser):\\n # Ensure no bbUser exists in the db with the same ID as the given bbUser\\n if self.userIDExists(userObj.id):\\n raise KeyError(\\\"Attempted to add a user that is already in this bbUserDB: \\\" + str(userObj))\\n # Store the passed bbUser\\n self.users[userObj.id] = userObj\",\n \"def test_user_is_group_member(self):\\n self.user.add_to_group(self.thread.group.pk)\\n self.assertEqual(\\n Thread.public.get_by_user(\\n thread_id=self.thread.pk, user=self.user),\\n self.thread\\n )\",\n \"def add_member(self, id, user):\\n request = self.request_builder('orgs.teams.add_member',\\n id=id, user=user)\\n return self._put(request)\",\n \"def add(self, user):\\r\\n url = '{0}/{1}'.format(self.get_url(), user)\\r\\n\\r\\n # include a body, because requests does not send content-length when no\\r\\n # body is present, and that makes GitHub respond with HTTP 411\\r\\n return http.Request('PUT', url, '*'), parsers.parse_empty\",\n \"def signup(request):\\n \\n user_form = UserCreationForm()\\n \\n if request.method == 'POST':\\n user_form = UserCreationForm(request.POST)\\n if user_form.is_valid():\\n \\\"\\\"\\\" new user account is created here\\\"\\\"\\\"\\n \\\"\\\"\\\" @fixme: this is a buggy peice of code; cannot do commit=False; because a M-M relation cannot be attached to a non-existing object. \\\"\\\"\\\"\\n new_user = user_form.save()\\n \\n \\\"\\\"\\\" @fixme: group is added after the account is created/commited to the DB; this is kinda bad; required two DB calls.\\\"\\\"\\\"\\n# new_user.groups.add(Group.objects.get(name='student'))\\n return HttpResponseRedirect(reverse(\\\"home.views.index\\\"))\\n \\n return render_to_response(\\\"auth/signup.html\\\", {\\n 'form' : user_form\\n }, context_instance=RequestContext(request))\",\n \"def _add(self, signup_form_id, group_ids):\\n path = '/members/add'\\n data = self.extract()\\n if group_ids:\\n data['group_ids'] = group_ids\\n if signup_form_id:\\n data['signup_form_id'] = signup_form_id\\n\\n outcome = self.account.adapter.post(path, data)\\n self['member_status_id'] = outcome['status']\\n if outcome['added']:\\n self['member_id'] = outcome['member_id']\",\n \"def add_to_group(self, group):\\n\\n if not self.in_group(group):\\n self.secondary_groups.append(group)\\n return self\",\n \"def add_to_groups(self, username, groups):\\n pass\",\n \"def get_user_group_membership(self, user_group_membership_id, **kwargs):\\n resource_path = \\\"/userGroupMemberships/{userGroupMembershipId}\\\"\\n method = \\\"GET\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"get_user_group_membership got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"userGroupMembershipId\\\": user_group_membership_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"UserGroupMembership\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"UserGroupMembership\\\")\",\n \"def create(self, validated_data):\\n # print('Validated Data',validated_data['profile'].get('group'))\\n group = validated_data['profile'].get('group')\\n profile_data = validated_data.pop('profile')\\n password = validated_data.pop('password')\\n user = User(**validated_data)\\n user.set_password(password)\\n user.save()\\n \\\"\\\"\\\"\\n After the creation of the user he is added to a particular group.\\n \\\"\\\"\\\"\\n user.groups.add(Group.objects.get(name=group))\\n UserProfile.objects.create(user=user, **profile_data)\\n return user\",\n \"def add_user(self, user):\\n c = self.conn.cursor()\\n cursor = c.execute(\\\"INSERT INTO users VALUES (null, ?, ?, ?)\\\",\\n (user['username'], user['email'], hash_password(user['password']),))\\n self.conn.commit()\\n return self.get_user(cursor.lastrowid)\",\n \"def one_group_member_sync_from_ucs(self, ad_group_object, object):\\n\\t\\tml = []\\n\\t\\tif not self.__compare_lowercase(object['dn'], ad_group_object['attributes'].get('member', [])):\\n\\t\\t\\tml.append((ldap.MOD_ADD, 'member', [object['dn']]))\\n\\n\\t\\tif ml:\\n\\t\\t\\ttry:\\n\\t\\t\\t\\tself.lo_ad.lo.modify_s(ad_group_object['dn'],compatible_modlist(ml))\\n\\t\\t\\texcept ldap.ALREADY_EXISTS:\\n\\t\\t\\t\\t# The user is already member in this group or it is his primary group\\n\\t\\t\\t\\t# This might happen, if we synchronize a rejected file with old informations\\n\\t\\t\\t\\t# See Bug #25709 Comment #17: https://forge.univention.org/bugzilla/show_bug.cgi?id=25709#c17\\n\\t\\t\\t\\tud.debug(ud.LDAP, ud.INFO, \\\"one_group_member_sync_from_ucs: User is already member of the group: %s modlist: %s\\\" % (ad_group_object['dn'], ml))\\n\\t\\t\\t\\tpass\\n\\n\\t\\t# The user has been removed from the cache. He must be added in any case\\n\\t\\tud.debug(ud.LDAP, ud.INFO, \\\"one_group_member_sync_from_ucs: Append user %s to group con cache of %s\\\" % (object['dn'].lower(), ad_group_object['dn'].lower()))\\n\\t\\tif not self.group_members_cache_con.get(ad_group_object['dn'].lower()):\\n\\t\\t\\tself.group_members_cache_con[ad_group_object['dn'].lower()] = []\\n\\t\\tself.group_members_cache_con[ad_group_object['dn'].lower()].append(object['dn'].lower())\",\n \"def add_group(username: str, gid: int=None, system: bool=False) -> Result[Group]:\\n try:\\n get_group(username)\\n except KeyError:\\n pass\\n else:\\n raise ValueError(\\\"Username {!r} is already in use\\\".format(username))\\n args = [\\\"/usr/sbin/addgroup\\\", username]\\n if gid:\\n try:\\n group = grp.getgrgid(gid)\\n except KeyError:\\n args[-1:-1] = [\\\"--gid\\\", str(gid)]\\n else:\\n raise ValueError(\\\"GID {} is already in use by {!r}\\\".format(gid, group.gr_name))\\n if system:\\n args[-1:-1] = [\\\"--system\\\"]\\n command(args)\\n return Result(State.success, get_group(username))\",\n \"def addUser(self, id : int) -> bbUser.bbUser:\\n id = self.validateID(id)\\n # Ensure no user exists with the specified ID in the database\\n if self.userIDExists(id):\\n raise KeyError(\\\"Attempted to add a user that is already in this bbUserDB\\\")\\n # Create and return a new user\\n newUser = bbUser.bbUser.fromDict(bbUser.defaultUserDict, id=id)\\n self.users[id] = newUser\\n return newUser\",\n \"def add_account(self, account):\\n return self._client.group_memberships.create({\\n 'account': account,\\n 'group': self,\\n })\",\n \"def test_user_in_group_can_access(self):\\n\\n logged_user = utils.create_user_and_authenticate(self)\\n self.group.users.add(logged_user)\\n\\n utils.test_can_access(self, self.url)\",\n \"def newUser(self):\\n user = IrcUser(hashed=True)\\n self.nextId += 1\\n id = self.nextId\\n self.users[id] = user\\n self.flush()\\n user.id = id\\n return user\",\n \"def add_member(self, db: Session, *, room: Room, user: User) -> Room:\\n members = [x for x in room.members]\\n members.append(user)\\n return self.update(db=db, db_obj=room, obj_in={\\\"members\\\": members})\",\n \"def create_group(self, user_id, name, owner, description='',\\n member_perms=[],\\n other_perms=[],\\n member_join_perms=[],\\n other_join_perms=[],\\n anon_read=0,\\n no_pay=False):\\n \\n user_id = user_id.lower()\\n \\n if self.root.has_key(user_id) or get_usergroup_database().has_key(user_id):\\n raise KeyError, \\\"Key %s already exists.\\\" % user_id\\n\\n if not no_pay:\\n # charge owner for new group - don't create group if can't pay\\n from qon.karma import NoKarmaToGive\\n try:\\n owner.pay_karma(self._karma_new_group)\\n except NoKarmaToGive:\\n return None\\n\\n group = Group(user_id=user_id, name=name, owner=owner)\\n group.add_owner(owner)\\n group.add_sponsor(owner)\\n group.anon_read = anon_read\\n group.description = description\\n \\n usergroup = UserGroup(group.user_id)\\n get_usergroup_database().add_usergroup(usergroup)\\n group.set_owning_group(usergroup)\\n \\n # members must have at least read access -- otherwise, what's the point of membership?\\n mem_perms = member_perms\\n if 'read' not in mem_perms:\\n mem_perms.append('read')\\n \\n group.set_group_perms(mem_perms)\\n group.set_other_perms(other_perms)\\n group.get_members().set_group_perms(member_join_perms)\\n group.get_members().set_other_perms(other_join_perms)\\n \\n # flush owner's group list cache\\n self._flush_user_data_caches(owner)\\n\\n self.add_group(group)\\n return group\",\n \"def test_resource_user_resource_add_user_groups_for_user_post(self):\\n pass\",\n \"def post(self):\\n status = ErrorCode.SUCCESS\\n try:\\n data = DotDict(json_decode(self.request.body))\\n logging.info(\\\"[UWEB] add group request: %s, cid: %s\\\",\\n data, self.current_user.cid)\\n except Exception as e:\\n status = ErrorCode.ILLEGAL_DATA_FORMAT\\n logging.exception(\\\"[UWEB] Invalid data format. body:%s, Exception: %s\\\",\\n self.request.body, e.args)\\n self.write_ret(status)\\n return\\n\\n try: \\n cid = data.cid\\n name = data.name\\n group = self.get_group_by_cid(cid, name)\\n if group:\\n status = ErrorCode.GROUP_EXIST\\n self.write_ret(status)\\n return\\n\\n group_info = dict(cid=cid,\\n name=name,\\n type=UWEB.GROUP_TYPE.NEW)\\n gid = add_group(group_info, self.db, self.redis)\\n # NOTE: wspush to client\\n tid = self.current_user.tid\\n if status == ErrorCode.SUCCESS:\\n WSPushHelper.pushS3(tid, self.db, self.redis)\\n\\n self.write_ret(status,\\n dict_=dict(gid=gid,\\n cid=cid,\\n name=name))\\n\\n except Exception as e:\\n logging.exception(\\\"[UWEB] Create group failed. uid: %s, Exception: %s\\\",\\n self.current_user.uid, e.args)\\n status = ErrorCode.SERVER_BUSY\\n self.write_ret(status)\",\n \"def add_user(self, userdict):\\n return self.post('users', userdict)\",\n \"def user_add(self, uname):\\n # create group if it does not exist\\n self.group_add()\\n username = self.prefixed(uname)\\n args = [\\n \\\"useradd\\\",\\n \\\"-g\\\",\\n self._gname,\\n \\\"-d\\\",\\n \\\"/home/{}\\\".format(username),\\n \\\"-s\\\",\\n \\\"/sbin/nologin\\\",\\n username\\n ]\\n logger.debug(args)\\n self.call(args)\",\n \"def add_user_to_division(self, **kwargs):\\n try:\\n is_head = kwargs.get('isHead')\\n except:\\n is_head = 0\\n request = post(url=self.base_url + 'api/services/etender/division/AddUserToDivision',\\n headers=self.headers,\\n data=json.dumps({'userid': kwargs.get('user').get('userid'),\\n 'divisionid': kwargs.get('division').get('id'),\\n 'isHead': is_head}))\\n print('Adding result: ', json.loads(request.content))\\n return json.loads(request.content)\"\n]"},"negative_scores":{"kind":"list like","value":["0.74806035","0.7402917","0.73061603","0.7215162","0.720623","0.7198249","0.6962066","0.6901342","0.68765295","0.6858431","0.6735927","0.6672501","0.66710955","0.6659128","0.6647979","0.65809935","0.6571874","0.646748","0.6427779","0.6386597","0.62940246","0.6280333","0.62549394","0.61948746","0.61717635","0.6171117","0.61343294","0.61324716","0.6131206","0.61292374","0.611639","0.6091987","0.6084804","0.60679567","0.6056225","0.60253674","0.59916365","0.59801465","0.597571","0.5969927","0.59585756","0.5949648","0.5931489","0.5927645","0.59264314","0.5910277","0.59072506","0.5889663","0.5887331","0.5860543","0.58429223","0.5842214","0.5837445","0.5834859","0.5830742","0.5828205","0.57891965","0.5779917","0.5757","0.57515156","0.5742987","0.57417506","0.5737021","0.5726234","0.5704888","0.56987673","0.56960356","0.56554335","0.5653201","0.5653201","0.5653201","0.56493783","0.56408286","0.5629584","0.5614783","0.5613126","0.56073976","0.55976975","0.5592314","0.5581693","0.55804557","0.5566832","0.55626523","0.55504364","0.5545981","0.5543884","0.55419284","0.5530253","0.55235106","0.5516214","0.5500761","0.54882777","0.5479146","0.5474335","0.5470318","0.54659325","0.546139","0.5454438","0.54541916","0.5444829"],"string":"[\n \"0.74806035\",\n \"0.7402917\",\n \"0.73061603\",\n \"0.7215162\",\n \"0.720623\",\n \"0.7198249\",\n \"0.6962066\",\n \"0.6901342\",\n \"0.68765295\",\n \"0.6858431\",\n \"0.6735927\",\n \"0.6672501\",\n \"0.66710955\",\n \"0.6659128\",\n \"0.6647979\",\n \"0.65809935\",\n \"0.6571874\",\n \"0.646748\",\n \"0.6427779\",\n \"0.6386597\",\n \"0.62940246\",\n \"0.6280333\",\n \"0.62549394\",\n \"0.61948746\",\n \"0.61717635\",\n \"0.6171117\",\n \"0.61343294\",\n \"0.61324716\",\n \"0.6131206\",\n \"0.61292374\",\n \"0.611639\",\n \"0.6091987\",\n \"0.6084804\",\n \"0.60679567\",\n \"0.6056225\",\n \"0.60253674\",\n \"0.59916365\",\n \"0.59801465\",\n \"0.597571\",\n \"0.5969927\",\n \"0.59585756\",\n \"0.5949648\",\n \"0.5931489\",\n \"0.5927645\",\n \"0.59264314\",\n \"0.5910277\",\n \"0.59072506\",\n \"0.5889663\",\n \"0.5887331\",\n \"0.5860543\",\n \"0.58429223\",\n \"0.5842214\",\n \"0.5837445\",\n \"0.5834859\",\n \"0.5830742\",\n \"0.5828205\",\n \"0.57891965\",\n \"0.5779917\",\n \"0.5757\",\n \"0.57515156\",\n \"0.5742987\",\n \"0.57417506\",\n \"0.5737021\",\n \"0.5726234\",\n \"0.5704888\",\n \"0.56987673\",\n \"0.56960356\",\n \"0.56554335\",\n \"0.5653201\",\n \"0.5653201\",\n \"0.5653201\",\n \"0.56493783\",\n \"0.56408286\",\n \"0.5629584\",\n \"0.5614783\",\n \"0.5613126\",\n \"0.56073976\",\n \"0.55976975\",\n \"0.5592314\",\n \"0.5581693\",\n \"0.55804557\",\n \"0.5566832\",\n \"0.55626523\",\n \"0.55504364\",\n \"0.5545981\",\n \"0.5543884\",\n \"0.55419284\",\n \"0.5530253\",\n \"0.55235106\",\n \"0.5516214\",\n \"0.5500761\",\n \"0.54882777\",\n \"0.5479146\",\n \"0.5474335\",\n \"0.5470318\",\n \"0.54659325\",\n \"0.546139\",\n \"0.5454438\",\n \"0.54541916\",\n \"0.5444829\"\n]"},"document_score":{"kind":"string","value":"0.71962476"},"document_rank":{"kind":"string","value":"6"}}},{"rowIdx":8569,"cells":{"query":{"kind":"string","value":"Assembles tag defaults in the specified compartment and any parent compartments to determine the tags to apply. Tag defaults from parent compartments do not override tag defaults referencing the same tag in a compartment lower down the hierarchy. This set of tag defaults includes all tag defaults from the current compartment back to the root compartment."},"document":{"kind":"string","value":"def assemble_effective_tag_set(self, compartment_id, **kwargs):\n resource_path = \"/tagDefaults/actions/assembleEffectiveTagSet\"\n method = \"GET\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"lifecycle_state\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"assemble_effective_tag_set got unknown kwargs: {!r}\".format(extra_kwargs))\n\n if 'lifecycle_state' in kwargs:\n lifecycle_state_allowed_values = [\"ACTIVE\"]\n if kwargs['lifecycle_state'] not in lifecycle_state_allowed_values:\n raise ValueError(\n \"Invalid value for `lifecycle_state`, must be one of {0}\".format(lifecycle_state_allowed_values)\n )\n\n query_params = {\n \"compartmentId\": compartment_id,\n \"lifecycleState\": kwargs.get(\"lifecycle_state\", missing)\n }\n query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None}\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n query_params=query_params,\n header_params=header_params,\n response_type=\"list[TagDefaultSummary]\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n query_params=query_params,\n header_params=header_params,\n response_type=\"list[TagDefaultSummary]\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def initDefaults(self):\n return _libsbml.Compartment_initDefaults(self)","def initDefaults(self):\n return _libsbml.CompartmentGlyph_initDefaults(self)","def set_defaults(self, compmgr=None):\n for section, default_options in self.defaults(compmgr).items():\n for name, value in default_options.items():\n if not ProductSetting.exists(self.env, self.product,\n section, name):\n if any(parent[section].contains(name, defaults=False)\n for parent in self.parents):\n value = None\n self.set(section, name, value)","def propagate_defaults(config_doc):\n for group_name, group_doc in config_doc.items():\n if isinstance(group_doc, dict):\n defaults = group_doc.get('defaults', {})\n\n for item_name, item_doc in group_doc.items():\n if item_name == 'defaults':\n continue\n if isinstance(item_doc, dict):\n\n group_doc[item_name] = \\\n dict_merge_pair(copy.deepcopy(defaults), item_doc)\n\n return config_doc","def init_defaults(self, defaults):\r\n for (sect, opt, default) in defaults:\r\n self._default(sect, opt, default)","def defaults():\n global __preset_staging\n \n t = TreeDict('Default_Parameter_Tree', __defaultpresettree__ = True)\n __preset_staging[id(t)] = t\n return t","def replace_defaults(d):\n\n # remove the defaults section\n defaults = d.pop('.defaults')\n\n # look for default tags and replace them\n for k, v in defaults.items():\n recursive_search_replace(d, '!' + k + '!', v)","def assign_defaults(self):\n\n def module_default_sort_key(module):\n sort_key = (\n 1 if module.marked_as_default else -1,\n module.version,\n module.variant,\n -self.index(module.modulepath),\n )\n return sort_key\n\n self.defaults = {}\n grouped = groupby(\n [module for path in self.path for module in path.modules], lambda x: x.name\n )\n for (_, modules) in grouped:\n for module in modules:\n module.is_default = False\n if len(modules) > 1:\n modules = sorted(modules, key=module_default_sort_key, reverse=True)\n modules[0].is_default = True\n self.defaults[modules[0].name] = modules[0]","def buildTagMap(default, *args):\r\n built = {}\r\n for portion in args:\r\n if hasattr(portion, 'items'):\r\n #It's a map. Merge it.\r\n for k,v in portion.items():\r\n built[k] = v\r\n elif isList(portion):\r\n #It's a list. Map each item to the default.\r\n for k in portion:\r\n built[k] = default\r\n else:\r\n #It's a scalar. Map it to the default.\r\n built[portion] = default\r\n return built","def set_config_all_to_defaults():\n logging.debug(\"Creating default config\")\n for section in all_defaults:\n set_config_section_to_defaults(section)\n global config_changed\n config_changed = True","def setDefaults(self, cs):\n self._xsBlockRepresentation = cs[\"xsBlockRepresentation\"]\n self._disableBlockTypeExclusionInXsGeneration = cs[\n \"disableBlockTypeExclusionInXsGeneration\"\n ]\n for xsId, xsOpt in self.items():\n xsOpt.setDefaults(\n cs[\"xsBlockRepresentation\"],\n cs[\"disableBlockTypeExclusionInXsGeneration\"],\n )","def get_default_vpas(self, composition_space):\n\n default_vpas = {}\n for element in composition_space.get_all_elements():\n default_vpas[element.symbol] = self.all_default_vpas[\n element.symbol]\n return default_vpas","def _merge_with_default_values(self, cr, uid, external_session, ressource, vals, sub_mapping_list, defaults=None, context=None):\n if not defaults: return vals\n for key in defaults:\n if not key in vals:\n vals[key] = defaults[key]\n return vals","def _update_default_configs(\n default_configs: tuple[dict[Any, Any]], passed_configs: tuple[dict[Any, Any]]\n ):\n\n for default_config, passed_config in zip(default_configs, passed_configs):\n if passed_config is not None:\n update_dict_recursively(default_config, passed_config)","def _setup_parents(self, parents=None):\n from trac import config\n self.parents = (parents or [])\n for filename in self.get('inherit', 'file').split(','):\n filename = Section._normalize_path(filename.strip(), self.env)\n self.parents.append(config.Configuration(filename))","def _apply_defaults(self):\n # Applies normal parameter defaults\n for scalar_parameter, value in self._DEFAULT_PARAMETER_SCALARS.items():\n if scalar_parameter not in self.parameters:\n self.parameters[scalar_parameter] = copy.copy(value)\n\n # Applies defaults to all ramp parameters\n for table_parameter, table in self._DEFAULT_PARAMETER_TABLES.items():\n self.parameters[table_parameter] = [list(tup) for tup in table]\n self.parameters['_' + table_parameter] = zip(*self.parameters[table_parameter])","def list_tag_defaults(self, **kwargs):\n resource_path = \"/tagDefaults\"\n method = \"GET\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"page\",\n \"limit\",\n \"id\",\n \"compartment_id\",\n \"tag_definition_id\",\n \"lifecycle_state\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"list_tag_defaults got unknown kwargs: {!r}\".format(extra_kwargs))\n\n if 'lifecycle_state' in kwargs:\n lifecycle_state_allowed_values = [\"ACTIVE\"]\n if kwargs['lifecycle_state'] not in lifecycle_state_allowed_values:\n raise ValueError(\n \"Invalid value for `lifecycle_state`, must be one of {0}\".format(lifecycle_state_allowed_values)\n )\n\n query_params = {\n \"page\": kwargs.get(\"page\", missing),\n \"limit\": kwargs.get(\"limit\", missing),\n \"id\": kwargs.get(\"id\", missing),\n \"compartmentId\": kwargs.get(\"compartment_id\", missing),\n \"tagDefinitionId\": kwargs.get(\"tag_definition_id\", missing),\n \"lifecycleState\": kwargs.get(\"lifecycle_state\", missing)\n }\n query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None}\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n query_params=query_params,\n header_params=header_params,\n response_type=\"list[TagDefaultSummary]\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n query_params=query_params,\n header_params=header_params,\n response_type=\"list[TagDefaultSummary]\")","def ancestor_append_tags(self, tags):\n\n for ancestor in self.lineage():\n ancestor.append_tags(tags)","def _SetCompoundPriorities(self):\n priority = self._GetMaxCommonPriority()\n for c in self.reactants:\n c.compound.SetSpeciesGroupPriority(priority)","def defaultize(self):\n if self.root is None:\n genome.initialize(self)\n self.root.defaultize()","def __init__(self, tagged_sents, default_tag='nc0s000'):\n self._default_tag = default_tag","def to_tag_spec(self, tags):\n\n tag_spec = []\n for child in self.all_children():\n if not child.children:\n child_spec = [{'equals': t} for t in child.path()]\n tag_spec.append({'section': child_spec, 'add_tags': tags})\n return tag_spec","def fill_in_empty_tags(prior, tags):\n print \"filling in empty entries for tags\"\n for key in tags:\n if not key in prior:\n prior[key] = {}\n for key1 in tags:\n for key2 in tags:\n prior[key1].setdefault(key2, 0.0)","def _unset_defaults_and_overrides(self):\n for info, group in self._all_opt_infos():\n info.pop('default', None)\n info.pop('override', None)","def set_attrs_default(input_object, attr_name_list = None):\n if attr_name_list is None:\n attr_name_list = []\n if len(attr_name_list) > 0:\n attr_list = [input_object.attr(attr_name) for attr_name in attr_name_list]\n else:\n attr_list = general.get_channelbox_attributes(input_object)\n\n for attr in attr_list:\n current_val = attr.get()\n if hasattr(attr, 'addAttr'):\n attr.addAttr(e = True, defaultValue = current_val)","def __init__(self, defaults=None, default_sec=\"Uncategorized\"):\n super(XFasterConfig, self).__init__(dict_type=OrderedDict)\n self.default_sec = default_sec\n self.add_section(default_sec)\n if defaults is not None:\n self.update(defaults)","def __defaults__(self): \n self.tag = 'Component'\n self.origin = [[0.0,0.0,0.0]]","def content(tmp_loc, ref_names_dict, order):\n \n fl = '[Content_Types].xml'\n inp_path = '/'.join([tmp_loc, fl])\n out_path = '/'.join([output_path, fl])\n \n cnt_lst = []\n asset_lst = []\n def_att = []\n d = dict()\n \n root1,tree1 = gen_tree(inp_path)\n root2,tree2 = gen_tree(out_path)\n \n # get all the extensions belongs to \"Default\" tag\n for relation in root2:\n if 'Default' in relation.tag:\n def_att.append(relation.attrib['Extension'])\n else:\n break\n \n for relation in root1:\n if 'Override' in relation.tag:\n attrib = relation.attrib['PartName'][1:]\n try:\n cnt = attrib.split('ppt/')[-1]\n ini = '/ppt/'\n except:\n cnt = attrib\n ini = '/'\n if cnt in ref_names_dict.keys():\n relation.attrib['PartName'] = f'{ini}{ref_names_dict[cnt]}'\n cnt_lst.append(relation)\n # asset_lst.append(relation.attrib['PartName'])\n else:\n cnt_lst.append(relation)\n if relation.attrib['PartName'] not in asset_lst:\n asset_lst.append(relation.attrib['PartName'])\n else:\n attrib = relation.attrib['Extension']\n if attrib not in def_att:\n cnt_lst.append(relation)\n # asset_lst.append(relation.attrib['Extension'])\n # deal with the assest_lst\n # print(\"AA: \", asset_lst)\n cnt_lst = natsort.natsorted(cnt_lst)\n for ele in cnt_lst:\n prev = tree2.find(ele.tag)\n prev.addnext(ele)\n \n tree2.write(out_path, pretty_print=True, xml_declaration=True, encoding='UTF-8', standalone=True)\n \n unq_attr = []\n for relation in root2:\n if 'Override' in relation.tag:\n if relation.attrib['PartName'] not in unq_attr:\n unq_attr.append(relation.attrib['PartName'])\n else:\n root2.remove(relation)\n tree2.write(out_path, pretty_print=True, xml_declaration=True, encoding='UTF-8', standalone=True)","def _add_default_tags(self):\n self.tags.add_tag('ban', required=True)","def add_default_options(self):\n\n options = getattr(self.parent, \"pyautodoc_set_default_option\", [])\n for option in options:\n self.set_default_option(option)","def set_defaults(self, agents):\n for a in agents:\n for k, v in a.get_defaults().items():\n self.env[k] = v","def resolve_kwdefaults(sign: inspect.Signature) -> Dict[str, Any]:\n kwdefaults = dict() # type: Dict[str, Any]\n\n # Add to the defaults all the values that are needed by the contracts.\n for param in sign.parameters.values():\n if param.default != inspect.Parameter.empty:\n kwdefaults[param.name] = param.default\n\n return kwdefaults","def initDefaults(self):\n return _libsbml.Layout_initDefaults(self)","def find_defaults(self):\n\n defaults = self.tree.findall('default')\n default_remote = None\n default_revision = None\n\n if len(defaults) > 1 and self.fail_on_invalid:\n raise InvalidManifest(\n 'More than one default entry, must be unique'\n )\n\n try:\n default_remote = defaults[-1].get('remote')\n default_revision = defaults[-1].get('revision', 'master')\n except IndexError:\n pass # Leave defaults to None\n\n self.defaults = {\n 'remote': default_remote, 'revision': default_revision\n }","def set_default_dna_options(treebuilder):\n treebuilder.options = get_default_options()","def defaults(file):\n\n\tUNCAT_TAGID = 47\n\tNOSERIES_TAGID = 375\n\n\treturn [NOSERIES_TAGID, UNCAT_TAGID]","def sections(self, compmgr=None, defaults=True):\n sections = set(to_unicode(s) \\\n for s in ProductSetting.get_sections(self.env, self.product))\n for parent in self.parents:\n sections.update(parent.sections(compmgr, defaults=False))\n if defaults:\n sections.update(self.defaults(compmgr))\n return sorted(sections)","def _populate_default_values(self):\n\n if 'input_data' not in self._definition:\n self._definition['input_data'] = []\n for input_dict in self._definition['input_data']:\n if 'required' not in input_dict:\n input_dict['required'] = True\n\n if 'jobs' not in self._definition:\n self._definition['jobs'] = []\n for job_dict in self._definition['jobs']:\n if 'recipe_inputs' not in job_dict:\n job_dict['recipe_inputs'] = []\n if 'dependencies' not in job_dict:\n job_dict['dependencies'] = []\n for dependency_dict in job_dict['dependencies']:\n if 'connections' not in dependency_dict:\n dependency_dict['connections'] = []","def _write_overrides(\n self, node, parent=None, parent_packmode=None, path_parts=tuple(), root=None\n ):\n if root is None:\n root = node\n if (parent is root) or (\n parent_packmode and node[\"packmode\"] != parent_packmode\n ):\n self.overrides[str(PurePath(*path_parts))] = node[\"packmode\"]\n for key, child in node[\"children\"].items():\n self._write_overrides(\n node=child,\n parent=node,\n parent_packmode=node[\"packmode\"],\n path_parts=path_parts + (key,),\n root=root,\n )","def set_default_protein_options(treebuilder):\n treebuilder.options = get_default_options()","def combine_pax_configs(config, overrides):\n # TODO: we should soon be able to get this from pax, but let's wait a while to prevent incompatibilties\n for section_name, stuff in overrides.items():\n config.setdefault(section_name, {})\n config[section_name].update(stuff)\n return config","def initDefaults(self):\n return _libsbml.SpeciesReference_initDefaults(self)","def merge_new_overrides():\n # Take the dex config as is:\n new_doc = {'config': copy.deepcopy(DEFINES['dex_config'])}\n # Convert old dex certs.web.secret to https-tls volume/volumeMounts\n mount = {'mountPath': get_httpstls_mount(), 'name': 'https-tls'}\n vol = {'secret': {'secretName': get_httpstls_secret(),\n 'defaultMode': DEFAULT_HTTPSTLS_MODE},\n 'name': 'https-tls'}\n # Take 'extra' volumes and mounts that may exist in old dex\n # This is expected to be the WAD certificate\n volumes = []\n volumeMounts = []\n if 'volumes' in DEFINES:\n volumes = copy.deepcopy(DEFINES['volumes'])\n if 'volumeMounts' in DEFINES:\n volumeMounts = copy.deepcopy(DEFINES['volumeMounts'])\n\n # only add volumes/mounts if 'extra' was specified, or\n # if there was non-default mount\n if volumes or 'tls_secret' in DEFINES:\n volumes.append(vol)\n if volumeMounts or 'dex_https_tlsCert' in DEFINES:\n volumeMounts.append(mount)\n if volumes:\n new_doc['volumes'] = volumes\n if volumeMounts:\n new_doc['volumeMounts'] = volumeMounts\n return new_doc","def _set_default_attributes(self):\n # Default input attributes\n self._has_studio_override = False\n self._had_studio_override = False\n\n self._is_overriden = False\n self._was_overriden = False\n\n self._is_modified = False\n self._is_invalid = False\n\n self._is_nullable = False\n self._as_widget = False\n self._is_group = False\n\n # If value should be stored to environments\n self._env_group_key = None\n\n self._any_parent_as_widget = None\n self._any_parent_is_group = None\n\n # Parent input\n self._parent = None\n\n # States of inputs\n self._state = None\n self._child_state = None\n\n # Attributes where values are stored\n self.default_value = NOT_SET\n self.studio_value = NOT_SET\n self.override_value = NOT_SET\n\n # Log object\n self._log = None\n\n # Only for develop mode\n self.defaults_not_set = False","def __init__(self, tagged_sents, default_tag='nc0s000'):\n \n self.default_tag = default_tag\n \n self.word_tags = defaultdict(lambda: defaultdict(int))\n \n for sent in list(tagged_sents):\n for word, tag in sent:\n self.word_tags[word][tag] += 1\n\n self.word_tags = dict(self.word_tags)","def tag(nodes, arg='', split=True, default=0, add_parent_space=True, add_default_spaces=True, zero_node=None, const_node=None):\n\n nodes = mc.ls(nodes)\n orig_const_node = const_node\n orig_zero_node = zero_node\n\n for node in nodes:\n\n # get zero if not specified\n if orig_zero_node:\n zero_node = orig_zero_node\n else:\n zero_node = node+'_ZERO'\n\n # get const node - this is what the parent constraint will be thrown onto\n if orig_const_node:\n const_node = orig_const_node\n else:\n const_node = node+'_CONST'\n\n if add_parent_space and not mc.objExists(zero_node):\n mc.warning('Cannot find a zero for '+node)\n continue\n\n if not mc.objExists(const_node):\n mc.warning('Cannot find a const for '+const_node)\n continue\n\n # build arg\n arg = arg.strip()\n if ' ' in arg:\n arg = re.sub(' +',' ', arg)\n\n arg_kwargs = {\n 'arg': arg,\n 'split': split,\n 'default': default,\n 'const_node': const_node,\n 'zero_node': zero_node,\n 'add_default_spaces': add_default_spaces,\n 'add_parent_space': add_parent_space\n }\n\n # create + set attr\n if not mc.objExists(node+'.tagSpaces'):\n mc.addAttr(node, ln='tagSpaces', dt='string', hidden=False)\n\n mc.setAttr(node+'.tagSpaces', str(arg_kwargs), type='string')\n\n # This convert all this legacy sloppy crap to the new hotness\n space_obj = Space(node)\n space_obj.set_data()\n\n return arg","def _set_default_attrs(self, obj, subs):\n for attr_name, attr_subs in subs.iteritems():\n if not getattr(obj, attr_name, None):\n for newattr_name, newattr_val in attr_subs.iteritems():\n setattr(obj, newattr_name, newattr_val)","def _to_config_recurse(config_cls, environ, prefixes, default=RAISE):\n # We keep track of values we actually got from the getter vs those we set\n # from the `ConfigEntry` default value\n got = {}\n defaulted = {}\n missing_vars = set()\n\n for attr_obj in attr.fields(config_cls):\n try:\n ce = attr_obj.metadata[CNF_KEY]\n except KeyError:\n continue\n name = attr_obj.name\n\n if ce.sub_cls is not None:\n prefix = ce.sub_cls._prefix or name\n got[name] = _to_config_recurse(\n ce.sub_cls, environ, (*prefixes, prefix), default=ce.default\n )\n else:\n getter = ce.callback or _default_getter\n try:\n got[name] = getter(environ, attr_obj.metadata, prefixes, name)\n except MissingEnvValueError as exc:\n if isinstance(ce.default, Raise):\n missing_vars |= set(exc.args)\n else:\n defaulted[name] = (\n attr.NOTHING\n if isinstance(ce.default, attr.Factory)\n else ce.default\n )\n\n if missing_vars:\n # If we were told to raise OR if we got *any* values for our attrs, we\n # will raise a `MissingEnvValueError` with all the missing variables\n if isinstance(default, Raise) or got:\n raise MissingEnvValueError(*missing_vars) from None\n\n # Otherwise we will simply use the default passed into this call.\n # Should be no need to handle `Factory`s here.\n return default\n\n # Merge the defaulted and actually collected values into the config type\n defaulted.update(got)\n return config_cls(**defaulted)","def set_default_configs(self):\n\n raise Exception(\"Child classes must override set_default_configs().\")","def twolevel_default_params(defaults):\n def wrap(function):\n def withargs(*args, **kwargs):\n merged = {}\n merged.update(defaults)\n for k, v in kwargs.items():\n if type(v) == dict and k in merged and type(merged[k]) == dict:\n merged[k].update(v)\n else:\n merged[k] = v\n return function(*args, **merged)\n\n return withargs\n\n return wrap","def initDefaults(self):\n return _libsbml.Parameter_initDefaults(self)","def _get_tags(self):\n if hasattr(self, \"_default_tags\"):\n tags = self._default_tags()\n else:\n tags = deepcopy(_default_tags)\n dynamic_tags = {}\n for cl in reversed(inspect.getmro(self.__class__)):\n if hasattr(cl, \"_more_static_tags\"):\n more_tags = cl._more_static_tags()\n tags.update(more_tags)\n if hasattr(cl, \"_more_tags\"):\n more_tags = cl._more_tags(self)\n dynamic_tags.update(more_tags)\n tags.update(dynamic_tags)\n\n return tags","def initialize_children(self, bibs):\n\t\tpass","def iterate(self, compmgr=None, defaults=True):\n options = set()\n name_str = self.name\n for setting in ProductSetting.select(self.env,\n where={'product': self.product,\n 'section': name_str}):\n option = self.optionxform(setting.option)\n options.add(option)\n yield option\n for parent in self.config.parents:\n for option in parent[self.name].iterate(defaults=False):\n loption = self.optionxform(option)\n if loption not in options:\n options.add(loption)\n yield option\n if defaults:\n for section, option in Option.get_registry(compmgr).keys():\n if section == self.name and \\\n self.optionxform(option) not in options:\n yield option","def _add_merged_attributes(node, all_recipes, all_roles):\n # Get cookbooks from extended recipes\n attributes = {}\n for recipe in node['recipes']:\n # Find this recipe\n found = False\n for r in all_recipes:\n if recipe == r['name']:\n found = True\n for attr in r['attributes']:\n if r['attributes'][attr].get('type') == \"hash\":\n value = {}\n else:\n value = r['attributes'][attr].get('default')\n # Attribute dictionaries are defined as a single\n # compound key. Split and build proper dict\n build_dct(attributes, attr.split(\"/\"), value)\n if not found:\n error = \"Could not find recipe '{0}' while \".format(recipe)\n error += \"building node data bag for '{0}'\".format(node['name'])\n abort(error)\n\n # Get default role attributes\n for role in node['roles']:\n for r in all_roles:\n if role == r['name']:\n update_dct(attributes, r['default_attributes'])\n\n # Get normal node attributes\n non_attribute_fields = [\n 'id', 'name', 'role', 'roles', 'recipes', 'run_list', 'ipaddress']\n node_attributes = {}\n for key in node:\n if key in non_attribute_fields:\n continue\n node_attributes[key] = node[key]\n update_dct(attributes, node_attributes)\n\n # Get override role attributes\n for role in node['roles']:\n for r in all_roles:\n if role == r['name']:\n update_dct(attributes, r['override_attributes'])\n # Merge back to the original node object\n node.update(attributes)","def _autoInitPars(self):\n for p in self._pars:\n setattr(self,p,self.defaultparval)","def defaults() -> dict:\n pass","def setup_defaults(self):\n status = self._lib_vscf_ecc.vscf_ecc_setup_defaults(self.ctx)\n VscfStatus.handle_status(status)","def _merge_and_reorder(\n inherited_fields: Dict[str, Union[Annotation, Input, Output]],\n cls_fields: Dict[str, Union[Annotation, Input, Output]],\n ) -> Dict[str, Union[Annotation, Input, Output]]:\n\n def _split(\n _fields: Dict[str, Union[Annotation, Input, Output]]\n ) -> Tuple[Dict[str, Union[Annotation, Input, Output]], Dict[str, Union[Annotation, Input, Output]]]:\n \"\"\"Split fields to two parts from the first default field.\n\n :param _fields: The fields\n :type _fields: Dict[str, Union[Annotation, Input, Output]]\n :return: A 2-tuple of (fields with no defaults, fields with defaults)\n :rtype: Tuple[Dict[str, Union[Annotation, Input, Output]], Dict[str, Union[Annotation, Input, Output]]]\n \"\"\"\n _no_defaults_fields, _defaults_fields = {}, {}\n seen_default = False\n for key, val in _fields.items():\n if val.get(\"default\", None) or seen_default:\n seen_default = True\n _defaults_fields[key] = val\n else:\n _no_defaults_fields[key] = val\n return _no_defaults_fields, _defaults_fields\n\n inherited_no_default, inherited_default = _split(inherited_fields)\n cls_no_default, cls_default = _split(cls_fields)\n # Cross comparison and delete from inherited_fields if same key appeared in cls_fields\n # pylint: disable=consider-iterating-dictionary\n for key in cls_default.keys():\n if key in inherited_no_default.keys():\n del inherited_no_default[key]\n for key in cls_no_default.keys():\n if key in inherited_default.keys():\n del inherited_default[key]\n return OrderedDict(\n {\n **inherited_no_default,\n **cls_no_default,\n **inherited_default,\n **cls_default,\n }\n )","def _fix_treetags(self, tree):\n for element in tree:\n element.tag = element.tag.split('}')[1]\n if len(element.getchildren()) > 0:\n self._fix_treetags(element)\n return tree","def autoprovisioning_node_pool_defaults(self) -> Optional[pulumi.Input['AutoprovisioningNodePoolDefaultsArgs']]:\n return pulumi.get(self, \"autoprovisioning_node_pool_defaults\")","def recursive_make_defaultdict(conf):\n if isinstance(conf, dict):\n for key in conf.keys():\n conf[key] = recursive_make_defaultdict(conf[key])\n return defaultdict(lambda: None, conf)\n return conf","def default_configs(cls):\n config = super().default_configs()\n config.update(\n {\n \"entry_type\": None,\n \"attribute\": None,\n \"index_annotation\": None,\n }\n )\n return config","def test_defaultdict_config():\n lang_configs = defaultdict(lambda: dict(processors=\"tokenize\"))\n run_multilingual_pipeline(en_has_dependencies=False, fr_has_dependencies=False, lang_configs=lang_configs)\n\n lang_configs = defaultdict(lambda: dict(processors=\"tokenize\"))\n lang_configs[\"en\"] = {\"processors\": \"tokenize,pos,lemma,depparse\"}\n run_multilingual_pipeline(en_has_dependencies=True, fr_has_dependencies=False, lang_configs=lang_configs)","def autodefaults (self):\r\n\r\n self.defaults_from_notes(identifying_key=EMPTYCHAR,\r\n mark=EQUAL,\r\n obj=self.default_dict['commands'],\r\n entrytext=COMMANDMACROSCRIPT)","def _getGroupDefaults(self):\n defaults = self.getDefaultGroupContainer(\n _name = \"defaults\",\n diff_command = self.general.diff_command,\n cia_rpc_server = self.general.cia_rpc_server,\n )\n try:\n self._passConfig(defaults, \"defaults\")\n except ConfigSectionNotFoundError:\n # [defaults] is optional\n pass\n else:\n self._config.remove_section('defaults')\n\n return defaults","def get_defaults():\n\n return {\n 'base_types': _get_base_types(),\n 'template_types': _get_template_types(),\n 'refined_types': _get_refined_types(),\n 'humannames': _get_humannames(),\n 'argument_kinds': _get_argument_kinds(),\n 'variable_namespace': {},\n 'type_aliases': _get_type_aliases(),\n 'cpp_types': _get_cpp_types(),\n 'numpy_types': _get_numpy_types(),\n 'from_pytypes': _get_from_pytypes(),\n 'cython_ctypes': _get_cython_ctypes(),\n 'cython_cytypes': _get_cython_cytypes(),\n 'cython_pytypes': _get_cython_pytypes(),\n 'cython_cimports': _get_cython_cimports(),\n 'cython_cyimports': _get_cython_cyimports(),\n 'cython_pyimports': _get_cython_pyimports(),\n 'cython_functionnames': _get_cython_functionnames(),\n 'cython_classnames': _get_cython_classnames(),\n 'cython_c2py_conv': _get_cython_c2py_conv(),\n 'cython_py2c_conv_vector_ref': CYTHON_PY2C_CONV_VECTOR_REF,\n 'cython_py2c_conv': _get_cython_py2c_conv(),\n }","def _node_defaults(self):\n parent = super(QTree, self)._node_defaults()\n parent[\"state\"] = np.zeros([self.size, self.size])\n parent[\"network\"] = self\n return parent","def update_gui_defaults(GUI_defaults):\n # failure flag\n config_import_error = False\n \n # xml source directory\n src_dir = os.getcwd() + '\\\\src'\n \n # attempt to parse the xml file and get it's root\n try:\n tree = ET.parse(src_dir + '\\\\pySCPI_config.xml')\n root = tree.getroot()\n \n except (IOError, ET.ParseError):\n # parsing failed for some reason\n config_import_error = True\n GUI_defaults.log_error('*** pySCPI_config.xml is'\n 'missing or corrupt ***')\n # end try\n \n # import the default values from the xml file\n if not config_import_error:\n \n # list of tags to look for\n config_tags = ['default_filename', 'default_delay', \n 'default_length', 'default_dp']\n \n # iterate through tags\n for tag in config_tags:\n # find each tag\n config_element = root.findall(tag)\n \n # if there is only one of a tag\n if len(config_element) == 1:\n # convert it to text\n config_text = config_element[0].text\n \n # update the appropriate field\n if tag == 'default_filename':\n GUI_defaults.update_filename(config_text)\n \n elif tag == 'default_delay':\n GUI_defaults.update_delay(config_text)\n \n elif tag == 'default_length':\n GUI_defaults.update_length(config_text)\n \n elif tag == 'default_dp':\n GUI_defaults.update_dp(config_text)\n # end if\n \n else:\n GUI_defaults.log_error('*** There is the wrong number '\n 'of ' + tag + ' declarations in '\n 'pySCPI_config.xml ***') \n # end if\n # end for\n \n # find the default addresses\n address_elements = root.findall('addresses')\n \n # if there are addresses\n if (len(address_elements) == 1) and (len(address_elements[0]) > 0):\n for element in address_elements[0]:\n # add each address to the list\n GUI_defaults.add_address(element.tag, element.get('address'))\n # end for\n \n else:\n GUI_defaults.log_error('*** No addresses were provided in '\n 'pySCPI_config.xml ***') \n # end if\n \n # find the default commands\n command_elements = root.findall('default_commands')\n \n # if there are commands\n if (len(command_elements) == 1) and (len(command_elements[0]) > 0):\n for command in command_elements[0]:\n # add each command to the list\n GUI_defaults.add_command(command.text)\n # end for\n\n else:\n GUI_defaults.log_error('*** No commands were provided in '\n 'pySCPI_config.xml ***') \n # end if \n # end if","def get_defaults(self):\n default_dict = {}\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\n if defaults:\n default_dict = dict(zip(args[-len(defaults):], defaults))\n return default_dict","def update_default_values(self, parent_values):\n raise NotImplementedError(\n \"{} does not have implemented `update_default_values`\".format(self)\n )","def _fill_in_default_kwargs(\n node: torch.fx.Node,\n) -> Tuple[List[fx_type_utils.Argument], Dict[str, fx_type_utils.Argument]]:\n\n # TODO(titaiwang): aten::sym_size has overload, but fx graph is using\n # overloadpacket for some reasons.\n # https://github.com/pytorch/pytorch/issues/97201\n # We manually assigned overload for aten::sym_size.\n if hasattr(node.target, \"_schema\"):\n node_schema = node.target._schema # type: ignore[union-attr]\n else:\n node_schema = torch.ops.aten.sym_size.int._schema # type: ignore[union-attr]\n\n # This function assumes the order of arguments in FX op is the\n # same as the order of arguments in TorchScript op.\n complete_args: List[fx_type_utils.Argument] = []\n complete_kwargs: Dict[str, fx_type_utils.Argument] = {}\n\n if inspect.isbuiltin(node.target):\n complete_args = list(node.args)\n else:\n for i, expected_arg in enumerate(node_schema.arguments):\n if i < len(node.args):\n complete_args.append(node.args[i])\n elif expected_arg.name in node.kwargs:\n complete_kwargs[expected_arg.name] = node.kwargs[expected_arg.name]\n else:\n # Get default from schema.\n complete_kwargs[expected_arg.name] = expected_arg.default_value\n\n return complete_args, complete_kwargs","def _fix_tags(self):\n logging.info('--- Fix Tags ---')\n saved_originals = {\n key: self.git.config.get(key, exit_on_error=False).strip()\n for key in (CI_USER_NAME, CI_USER_EMAIL)}\n try:\n for tag_name in sorted(self.tags):\n # Get commit data from the (latest) commit of a\n # svn/tags/… branch (following the convention for svn,\n # there should only be one),\n # produce a git tag using these data\n # and delete the now-obsolete branch.\n tag_name = tag_name.strip()\n tag_id = PRX_SVNTAGS_PREFIX.sub('', tag_name)\n commit_data = {\n key: self.git.log(\n '-1', f'--pretty=format:{value}', tag_name)\n for (key, value) in COMMIT_DATA_FORMATS.items()}\n self.git.config(CI_USER_NAME, commit_data[CD_AUTHOR_NAME])\n self.git.config(CI_USER_EMAIL, commit_data[CD_AUTHOR_EMAIL])\n original_git_committer_date = ENV.get(ENV_GIT_COMMITTER_DATE)\n ENV[ENV_GIT_COMMITTER_DATE] = commit_data[CD_DATE]\n self.git.tag(\n '-a', '-m', commit_data[CD_COMMENT], tag_id, tag_name)\n if original_git_committer_date is None:\n del ENV[ENV_GIT_COMMITTER_DATE]\n else:\n ENV[ENV_GIT_COMMITTER_DATE] = original_git_committer_date\n #\n self.git.branch('-d', '-r', tag_name)\n #\n finally:\n # We only change the git config values\n # if there are self.tags available.\n # So it stands to reason we should revert them only in that case.\n if self.tags:\n for (key, value) in saved_originals.items():\n if value:\n self.git.config(key, value)\n else:\n self.git.config.unset(key)\n #\n #\n #\n #","def default_nested(self, data, many, **kwargs):\n if not data.get(\"metadata\"):\n data[\"metadata\"] = {}\n if not data.get(\"pids\"):\n data[\"pids\"] = {}\n\n return data","def set_defaults(self, **kw):\n group = kw.pop('group', None)\n for o, v in kw.items():\n self.cfg_fixture.set_default(o, v, group=group)","def voxel_env_override_defaults(env, parser):\n parser.set_defaults(\n encoder_type='conv',\n encoder_subtype='convnet_simple',\n hidden_size=512,\n obs_subtract_mean=0.0,\n obs_scale=255.0,\n actor_worker_gpus=[0],\n )","def defaults():\n return {}","def _initialize_defaults(self):\n for key, value in defaults.items():\n if key not in self.source_params:\n self.source_params[key] = value","def _initialize_defaults(self):\n for key, value in defaults.items():\n if key not in self.source_params:\n self.source_params[key] = value","def build_dictionary_element_tree(element, node_attr_fields=NODE_FIELDS, way_attr_fields=WAY_FIELDS,\n default_tag_type='regular'):\n node_attribs = {}\n way_attribs = {}\n way_nodes = []\n tags = [] # Handle secondary tags the same way for both node and way elements\n \n if element == None:\n print ('Element is Null')\n return None\n \n if element.tag == 'node':\n check = check_id(element.attrib['id'])\n \n if not check:\n print ('Node ID is Null or not a number: ', element.attrib['id'])\n fix_it.node_id_bad[element.attrib['id']] += 1\n return None\n \n for attr in element.attrib:\n if attr in node_attr_fields:\n node_attribs[attr] = element.attrib[attr]\n \n for child in element:\n temp = { }\n \n if 'cityracks.' in child.attrib['k']:\n child.attrib['k'] = child.attrib['k'].replace('cityracks.','')\n \n m = correct_chars_re.search(child.attrib['k']) # No match returns None\n\n if not m: \n print ('Node key -- Problem character! ', 'key = ', child.attrib['k'], ' value = ', child.attrib['v'])\n fix_it.counts['node child key eliminated'] += 1\n infoKey = 'node key: ' + child.attrib['k']\n fix_it.bad_keys[infoKey] += 1\n continue # eliminate the problematic child tag\n \n # Fix value\n fixed = fix_it.fixer(child, 'Node') # Correct or eliminate the child value\n # Function fix_it returns None if there is a data problem\n if fixed == '$skip':\n fix_it.counts['node tag skipped'] += 1\n continue\n \n if not fixed:\n fix_it.counts['node child value eliminated'] += 1\n continue # Eliminate this child tag\n else:\n temp['id'] = element.attrib['id'] # Save the fixed child tag for writing into csv file\n temp['value'] = fixed\n \n if ':' in child.attrib['k']:\n k = child.attrib['k'].split(':',1)\n temp['type'] = k[0]\n temp['key'] = k[1]\n else:\n temp['key'] = child.attrib['k']\n temp['type'] = default_tag_type\n \n fix_it.counts['node tag count'] += 1 # count the child tags not eliminated\n tags.append(temp)\n \n return {'node': node_attribs, 'node_tags': tags}\n \n elif element.tag == 'way':\n check = check_id(element.attrib['id'])\n \n if not check:\n print ('Way ID is Null or not a number: ', element.attrib['id'])\n fix_it.way_id_bad[element.attrib['id']] += 1\n return None\n \n for attr in element.attrib: \n if attr in way_attr_fields:\n way_attribs[attr] = element.attrib[attr]\n \n position = 0\n for child in element:\n temp = { }\n \n if child.tag == 'tag':\n m = correct_chars_re.search(child.attrib['k']) # No match returns None\n \n if not m:\n print ('Way key -- Problem char! ', 'key = ', child.attrib['k'], ' value = ', child.attrib['v'])\n fix_it.counts['way child key eliminated'] += 1\n infoKey = 'way key: ' + child.attrib['k']\n fix_it.bad_keys[infoKey] += 1\n continue # eliminate the problematic child tag\n \n # Fix value\n fixed = fix_it.fixer(child, 'Way') # Correct or eliminate the child value\n # Function fix_it returns None if there is a data problem\n if fixed == '$skip':\n fix_it.counts['way tag skipped'] += 1\n continue\n \n if not fixed:\n fix_it.counts['way child value eliminated'] += 1\n continue # Eliminate this child tag\n else:\n temp['id'] = element.attrib['id'] # Save the fixed child tag for writing into csv file\n temp['value'] = fixed\n\n if ':' in child.attrib['k']:\n k = child.attrib['k'].split(':',1)\n temp['type'] = k[0]\n temp['key'] = k[1]\n else:\n temp['key'] = child.attrib['k']\n temp['type'] = default_tag_type\n \n fix_it.counts['way tag count'] += 1 # count the child tags not eliminated\n tags.append(temp)\n \n elif child.tag == 'nd':\n check = check_id(child.attrib['ref'])\n \n if not check:\n print ('Way Node reference is Null or not a number: ', child.attrib['ref'])\n fix_it.way_node_reference_bad[child.attrib['ref']] += 1\n continue\n \n temp['id'] = element.attrib['id']\n temp['node_id'] = child.attrib['ref']\n temp['position'] = position\n position += 1\n fix_it.counts['way node tag count'] += 1 # count the child tags not eliminated\n way_nodes.append(temp)\n \n #print ('way_attribs:\\n', way_attribs)\n #print ('way_nodes:\\n', way_nodes)\n #print ('way_tags:\\n', tags)\n #print ('---------------\\n')\n return {'way': way_attribs, 'way_nodes': way_nodes, 'way_tags': tags}","def replaceDefaults(d):\n defaults = d.pop('.defaults')\n for k, v in defaults.items():\n recursiveSearchReplace(d, '!' + k + '!', v)","def _get_function_defaults(func: FunctionType) -> dict[str, Any]:\n # extracted bit from inspect.signature... ~20x faster\n pos_count = func.__code__.co_argcount\n arg_names = func.__code__.co_varnames\n\n defaults = func.__defaults__ or ()\n\n non_default_count = pos_count - len(defaults)\n positional_args = arg_names[:pos_count]\n\n output = {\n name: defaults[offset]\n for offset, name in enumerate(positional_args[non_default_count:])\n }\n if func.__kwdefaults__:\n output.update(func.__kwdefaults__)\n return output","def correctDefaultNounTag(idx, tagged_term, tagged_terms, lexicon):\n term, tag, norm = tagged_term\n if tag == 'NND':\n if term.endswith('s'):\n tagged_term[1] = 'NNS'\n tagged_term[2] = term[:-1]\n else:\n tagged_term[1] = 'NN'","def get_default_config():\n\n config = {}\n\n for name, cls in get_tools().items():\n config[name] = cls.get_default_config()\n\n try:\n workers = multiprocessing.cpu_count() - 1\n except NotImplementedError: # pragma: no cover\n workers = 1\n workers = max(1, min(4, workers))\n\n config.update({\n 'exclude': [],\n 'merge-issues': True,\n 'workers': workers,\n 'disabled': [],\n 'noqa': True,\n 'extends': [],\n 'ignore-missing-extends': False,\n })\n\n return config","def xml_tag(inp_tag, out_tag):\n tag_dict = OrderedDict()\n sub_tag = OrderedDict()\n for i in range(len(inp_tag)):\n if inp_tag[i] not in out_tag:\n tag_dict[inp_tag[i]] = [inp_tag[i-1]]\n return tag_dict","def BTagHighLevelAugmenterAlgCfg(ConfigFlags, JetCollection, BTagCollection, Associator, doFlipTagger=False, sequenceName=None, **options):\n\n options = {}\n options['JetCollectionName'] = JetCollection.replace('Track', 'PV0Track') + 'Jets'\n options['BTaggingCollectionName'] = BTagCollection\n options['JetLinkName'] = options['BTaggingCollectionName'] + '.jetLink'\n options['BTagTrackToJetAssociatorName'] = Associator\n options['name'] = (BTagCollection + '_Augment').lower()\n if doFlipTagger: options['FlipTagConfig'] = 'FLIP_SIGN'\n\n # -- create the augmentation algorithm\n if sequenceName:\n acc = ComponentAccumulator(sequenceName)\n acc.addEventAlgo(Analysis__BTagHighLevelAugmenterAlg(**options), sequenceName)\n else:\n acc = ComponentAccumulator()\n acc.addEventAlgo(Analysis__BTagHighLevelAugmenterAlg(**options))\n\n return acc","def override(self, parent):\n return self.__class__(Cfg._mergedicts(self, parent, True))","def setdefault(*dicts):\n param_complete = dict(dicts[0])\n for d in dicts[1:]:\n for k,v in d.items():\n param_complete.setdefault(k, v)\n\n return param_complete","def parse_tag(self, root, fmt, insert_children=True):\n arguments = {}\n extra_args = {}\n children = []\n\n for k, val in root.attrib.iteritems():\n k = k.lower()\n # 'version' is currently the only supported XML attribute.\n if k == 'version' and root.tag == 'odML':\n continue\n\n # We currently do not support XML attributes.\n self.error(\"Attribute not supported, ignoring '%s=%s' \" % (k, val), root)\n\n for node in root:\n node.tag = node.tag.lower()\n self.is_valid_argument(node.tag, fmt, root, node)\n if node.tag in fmt.arguments_keys:\n # this is a heuristic, but works for now\n if node.tag in self.tags and node.tag in fmt.map_keys:\n sub_obj = self.parse_element(node)\n if sub_obj is not None:\n extra_args[fmt.map(node.tag)] = sub_obj\n children.append(sub_obj)\n else:\n tag = fmt.map(node.tag)\n if tag in arguments:\n self.warn(\"Element <%s> is given multiple times in \"\n \"<%s> tag\" % (node.tag, root.tag), node)\n\n # Special handling of values;\n curr_text = node.text.strip() if node.text else None\n if tag == \"values\" and curr_text:\n content = from_csv(node.text)\n arguments[tag] = content\n # Special handling of cardinality\n elif tag.endswith(\"_cardinality\") and curr_text:\n arguments[tag] = parse_cardinality(node.text)\n else:\n arguments[tag] = curr_text\n else:\n self.error(\"Invalid element <%s> in odML document section <%s> \"\n % (node.tag, root.tag), node)\n\n check_args = dict(list(arguments.items()) + list(extra_args.items()))\n self.check_mandatory_arguments(check_args, fmt, root.tag, root)\n\n # Instantiate the current odML object with the parsed attributes.\n obj = fmt.create()\n try:\n obj = fmt.create(**arguments)\n except Exception as exc:\n self.error(str(exc), root)\n\n if insert_children:\n for child in children:\n obj.append(child)\n\n return obj","def _update_attributes(self, parent_node: etree.ElementBase) -> None:\r\n ppj_bool_keys = [\r\n XmlAttributeName.OPTIMIZE,\r\n XmlAttributeName.RELEASE,\r\n XmlAttributeName.FINAL,\r\n XmlAttributeName.ANONYMIZE,\r\n XmlAttributeName.PACKAGE,\r\n XmlAttributeName.ZIP\r\n ]\r\n\r\n other_bool_keys = [\r\n XmlAttributeName.NO_RECURSE,\r\n XmlAttributeName.USE_IN_BUILD\r\n ]\r\n\r\n for node in parent_node.getiterator():\r\n if node.text:\r\n node.text = self.parse(node.text.strip())\r\n\r\n tag = node.tag.replace('{%s}' % self.ppj_root.ns, '')\r\n\r\n if tag == XmlTagName.PAPYRUS_PROJECT:\r\n if XmlAttributeName.GAME not in node.attrib:\r\n node.set(XmlAttributeName.GAME, '')\r\n if XmlAttributeName.FLAGS not in node.attrib:\r\n node.set(XmlAttributeName.FLAGS, self.options.flags_path)\r\n if XmlAttributeName.OUTPUT not in node.attrib:\r\n node.set(XmlAttributeName.OUTPUT, self.options.output_path)\r\n for key in ppj_bool_keys:\r\n if key not in node.attrib:\r\n node.set(key, 'False')\r\n\r\n elif tag == XmlTagName.PACKAGES:\r\n if XmlAttributeName.OUTPUT not in node.attrib:\r\n node.set(XmlAttributeName.OUTPUT, self.options.package_path)\r\n\r\n elif tag == XmlTagName.PACKAGE:\r\n if XmlAttributeName.NAME not in node.attrib:\r\n node.set(XmlAttributeName.NAME, self.project_name)\r\n if XmlAttributeName.ROOT_DIR not in node.attrib:\r\n node.set(XmlAttributeName.ROOT_DIR, self.project_path)\r\n\r\n elif tag in (XmlTagName.FOLDER, XmlTagName.INCLUDE, XmlTagName.MATCH):\r\n if XmlAttributeName.NO_RECURSE not in node.attrib:\r\n node.set(XmlAttributeName.NO_RECURSE, 'False')\r\n if tag in (XmlTagName.INCLUDE, XmlTagName.MATCH):\r\n if XmlAttributeName.PATH not in node.attrib:\r\n node.set(XmlAttributeName.PATH, '')\r\n if tag == XmlTagName.MATCH:\r\n if XmlAttributeName.IN not in node.attrib:\r\n node.set(XmlAttributeName.IN, os.curdir)\r\n if XmlAttributeName.EXCLUDE not in node.attrib:\r\n node.set(XmlAttributeName.EXCLUDE, '')\r\n\r\n elif tag == XmlTagName.ZIP_FILES:\r\n if XmlAttributeName.OUTPUT not in node.attrib:\r\n node.set(XmlAttributeName.OUTPUT, self.options.zip_output_path)\r\n\r\n elif tag == XmlTagName.ZIP_FILE:\r\n if XmlAttributeName.NAME not in node.attrib:\r\n node.set(XmlAttributeName.NAME, self.project_name)\r\n if XmlAttributeName.ROOT_DIR not in node.attrib:\r\n node.set(XmlAttributeName.ROOT_DIR, self.project_path)\r\n if XmlAttributeName.COMPRESSION not in node.attrib:\r\n node.set(XmlAttributeName.COMPRESSION, 'deflate')\r\n else:\r\n node.set(XmlAttributeName.COMPRESSION, node.get(XmlAttributeName.COMPRESSION).casefold())\r\n\r\n elif tag in (XmlTagName.PRE_BUILD_EVENT, XmlTagName.POST_BUILD_EVENT,\r\n XmlTagName.PRE_IMPORT_EVENT, XmlTagName.POST_IMPORT_EVENT):\r\n if XmlAttributeName.DESCRIPTION not in node.attrib:\r\n node.set(XmlAttributeName.DESCRIPTION, '')\r\n if XmlAttributeName.USE_IN_BUILD not in node.attrib:\r\n node.set(XmlAttributeName.USE_IN_BUILD, 'True')\r\n\r\n # parse values\r\n for key, value in node.attrib.items():\r\n value = value.casefold() in ('true', '1') if key in ppj_bool_keys + other_bool_keys else self.parse(value)\r\n node.set(key, str(value))","def setupWidgets(self, parentObject, \n\t\tforceCategory=None, \n\t\tinherit=None, \n\t\tstoreProperties=True, \n\t\tupdateOnly=False):\n\t\tif forceCategory is not None:\n\t\t\tcategory = forceCategory\n\n\t\tif updateOnly:\n\t\t\tstoreProperties = False\n\n\t\tfor widget in parentObject.findChildren(QtWidgets.QWidget):\n\n\t\t\t# Enable expansion of custom rollout group box controls...\n\t\t\tif widget.property('expandable'):\n\t\t\t\tif isinstance(widget, QtWidgets.QGroupBox):\n\t\t\t\t\twidget.setCheckable(True)\n\t\t\t\t\t# widget.setChecked(expand)\n\t\t\t\t\twidget.setFixedHeight(widget.sizeHint().height())\n\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\twidget.toggled.connect(self.toggleExpandGroup)\n\n\t\t\t# Set up handler for push buttons...\n\t\t\tif widget.property('exec'):\n\t\t\t\tif isinstance(widget, QtWidgets.QPushButton):\n\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\twidget.clicked.connect(self.execPushButton)\n\n\t\t\t# Set up handlers for different widget types & apply values\n\t\t\tattr = widget.property('xmlTag')\n\t\t\tif attr:\n\t\t\t\tself.base_widget = widget.objectName()\n\t\t\t\tif forceCategory is None:\n\t\t\t\t\tcategory = self.findCategory(widget)\n\t\t\t\tif category:\n\t\t\t\t\twidget.setProperty('xmlCategory', category)\n\n\t\t\t\t\tif inherit:\n\t\t\t\t\t\tvalue = self.prefs.get_attr(category, attr)\n\t\t\t\t\t\t# if value == \"\":\n\t\t\t\t\t\tif value is None:\n\t\t\t\t\t\t\tvalue = inherit.get_attr(category, attr)\n\n\t\t\t\t\t\t\t# widget.setProperty('xmlTag', None)\n\t\t\t\t\t\t\twidget.setProperty('inheritedValue', True)\n\t\t\t\t\t\t\tif widget.toolTip():\n\t\t\t\t\t\t\t\twidget.setProperty('oldToolTip', widget.toolTip())\n\t\t\t\t\t\t\twidget.setToolTip(\"This value is being inherited. Change the value to override the inherited value.\")\n\n\t\t\t\t\t\t\t# Apply pop-up menu to remove override - can't get to work here\n\t\t\t\t\t\t\t# self.addContextMenu(widget, \"Remove override\", self.remove_overrides)\n\t\t\t\t\t\t\t# widget.setContextMenuPolicy(QtCore.Qt.ActionsContextMenu)\n\n\t\t\t\t\t\t\t# actionRemoveOverride = QtWidgets.QAction(\"Remove override\", None)\n\t\t\t\t\t\t\t# actionRemoveOverride.triggered.connect(self.remove_overrides)\n\t\t\t\t\t\t\t# widget.addAction(actionRemoveOverride)\n\t\t\t\t\telse:\n\t\t\t\t\t\ttry:\n\t\t\t\t\t\t\tvalue = self.prefs.get_attr(category, attr)\n\t\t\t\t\t\texcept AttributeError:\n\t\t\t\t\t\t\tvalue = None\n\n\t\t\t\t\t# Sliders...\n\t\t\t\t\tif isinstance(widget, QtWidgets.QSlider):\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\twidget.setValue(int(value))\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\tself.storeValue(category, attr, widget.value())\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\twidget.valueChanged.connect(self.storeSliderValue)\n\n\t\t\t\t\t# Spin boxes...\n\t\t\t\t\tif isinstance(widget, QtWidgets.QSpinBox):\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\twidget.setValue(int(value))\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\tself.storeValue(category, attr, widget.value())\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\twidget.valueChanged.connect(self.storeSpinBoxValue)\n\n\t\t\t\t\t# Double spin boxes...\n\t\t\t\t\telif isinstance(widget, QtWidgets.QDoubleSpinBox):\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\twidget.setValue(float(value))\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\tself.storeValue(category, attr, widget.value())\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\twidget.valueChanged.connect(self.storeSpinBoxValue)\n\n\t\t\t\t\t# Line edits...\n\t\t\t\t\telif isinstance(widget, QtWidgets.QLineEdit):\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\twidget.setText(value)\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\tself.storeValue(category, attr, widget.text())\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\t# widget.textEdited.connect(self.storeLineEditValue)\n\t\t\t\t\t\t\twidget.textChanged.connect(self.storeLineEditValue)\n\n\t\t\t\t\t# Plain text edits...\n\t\t\t\t\telif isinstance(widget, QtWidgets.QPlainTextEdit):\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\twidget.setPlainText(value)\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\tself.storeValue(category, attr, widget.toPlainText())\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\twidget.textChanged.connect(self.storeTextEditValue)\n\n\t\t\t\t\t# Check boxes...\n\t\t\t\t\telif isinstance(widget, QtWidgets.QCheckBox):\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\tif value == True:\n\t\t\t\t\t\t\t\twidget.setCheckState(QtCore.Qt.Checked)\n\t\t\t\t\t\t\telif value == False:\n\t\t\t\t\t\t\t\twidget.setCheckState(QtCore.Qt.Unchecked)\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\tself.storeValue(category, attr, self.getCheckBoxValue(widget))\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\twidget.toggled.connect(self.storeCheckBoxValue)\n\n\t\t\t\t\t# Radio buttons...\n\t\t\t\t\telif isinstance(widget, QtWidgets.QRadioButton):\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\twidget.setAutoExclusive(False)\n\t\t\t\t\t\t\tif value == widget.text():\n\t\t\t\t\t\t\t\twidget.setChecked(True)\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\twidget.setChecked(False)\n\t\t\t\t\t\t\twidget.setAutoExclusive(True)\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\tif widget.isChecked():\n\t\t\t\t\t\t\t\tself.storeValue(category, attr, widget.text())\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\twidget.toggled.connect(self.storeRadioButtonValue)\n\n\t\t\t\t\t# Combo boxes...\n\t\t\t\t\telif isinstance(widget, QtWidgets.QComboBox):\n\t\t\t\t\t\t# Add items if history is enabled\n\t\t\t\t\t\tif widget.property('storeHistory'):\n\t\t\t\t\t\t\twidget.setInsertPolicy(widget.InsertAtTop)\n\t\t\t\t\t\t\thistory = self.prefs.get_attr(category, \"%s_history\" % attr)\n\t\t\t\t\t\t\tif history:\n\t\t\t\t\t\t\t\twidget.addItems(history)\n\t\t\t\t\t\t# Add/set current item\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\tif widget.findText(value) == -1:\n\t\t\t\t\t\t\t\twidget.insertItem(0, value)\n\t\t\t\t\t\t\twidget.setCurrentIndex(widget.findText(value))\n\t\t\t\t\t\t# Store value in external file\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\tself.storeValue(category, attr, widget.currentText())\n\t\t\t\t\t\t# Connect signals & slots\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\t# widget.currentTextChanged.connect(self.storeComboBoxValue)\n\t\t\t\t\t\t\tif widget.isEditable():\n\t\t\t\t\t\t\t\twidget.editTextChanged.connect(self.storeComboBoxValue)\n\t\t\t\t\t\t\telse:\n\t\t\t\t\t\t\t\twidget.currentIndexChanged.connect(self.storeComboBoxValue)\n\n\t\t\t\t\t# List widgets...\n\t\t\t\t\t# TODO: Add option to remove duplicate entries\n\t\t\t\t\telif isinstance(widget, QtWidgets.QListWidget):\n\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\t# print(value)\n\t\t\t\t\t\t\twidget.clear()\n\t\t\t\t\t\t\twidget.addItems(value)\n\t\t\t\t\t\tif storeProperties:\n\t\t\t\t\t\t\titems = []\n\t\t\t\t\t\t\tfor i in range(widget.count()):\n\t\t\t\t\t\t\t\titems.append(widget.item(i).text())\n\t\t\t\t\t\t\tself.storeValue(category, attr, items)\n\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\twidget.itemChanged.connect(self.storeListWidgetValues)\n\n\t\t\t\t\t# Enable colour chooser buttons...\n\t\t\t\t\telif isinstance(widget, QtWidgets.QToolButton):\n\t\t\t\t\t\tif widget.property('colorChooser'):\n\t\t\t\t\t\t\tif value is not None:\n\t\t\t\t\t\t\t\twidget.setStyleSheet(\"QWidget { background-color: %s }\" % value)\n\t\t\t\t\t\t\t# if storeProperties:\n\t\t\t\t\t\t\t# \tself.storeValue(category, attr, widget.currentText())\n\t\t\t\t\t\t\tif not updateOnly:\n\t\t\t\t\t\t\t\twidget.clicked.connect(self.storeColor)","def set_default_position(self):\n self.set_joint('elbow', 0, radians=False)\n self.set_joint('shoulder', 150, radians=False)\n for joint in self.chain.joints:\n self.set_joint(joint, self.chain.joints[joint]['default_value'], radians=True)","def apply_defaults(self, commands, args):\r\n\r\n args = args[:]\r\n\r\n if RcFile._DISABLE_PANTS_RC_OPTION in args:\r\n return args\r\n\r\n config = Config.create_parser()\r\n read_from = config.read(self.paths)\r\n if not read_from:\r\n log.debug('no rcfile found')\r\n return args\r\n\r\n log.debug('using rcfiles: %s to modify args' % ','.join(read_from))\r\n\r\n def get_rcopts(command, key):\r\n return config.get(command, key).split() if config.has_option(command, key) else []\r\n\r\n commands = list(commands)\r\n if self.process_default:\r\n commands.insert(0, Config.DEFAULT_SECTION)\r\n\r\n for cmd in commands:\r\n opts = get_rcopts(cmd, 'options')\r\n args = (opts + args) if self.default_prepend else (args + opts)\r\n args = get_rcopts(cmd, 'prepend-options') + args + get_rcopts(cmd, 'append-options')\r\n return args","def initDefaults(self):\n return _libsbml.Species_initDefaults(self)","def initDefaults(self):\n return _libsbml.ReferenceGlyph_initDefaults(self)","def visit_cname_place(self, node, children):\n # If a value is supplied it will be a single time list, so extract with [0]\n # If no value is supplied for an optional item, default must also be a single item list [default_value]\n w = children.results.get('wrap')\n wrap_value = 1 if not w else w[0]['wrap']\n cplace = {'cname': children.results['name'][0], # Required component\n 'dir': children.results.get('dir', [1])[0], # many optional components with default values\n 'bend': children.results.get('bend', [1])[0],\n 'notch': children.results.get('notch', [0])[0],\n 'wrap': wrap_value,\n }\n return cplace","def initDefaults(self):\n return _libsbml.SpeciesReferenceGlyph_initDefaults(self)","def default(self, block, name):\r\n if name in self.inheritable_names and block.parent is not None:\r\n parent = block.get_parent()\r\n if parent:\r\n return getattr(parent, name)\r\n super(InheritingFieldData, self).default(block, name)","def parse_defaults(self, stmt):\r\n spec_type = stmt['spec_type']\r\n if spec_type in self._defaults:\r\n raise ValueError('More than one default for {}'.format(stmt['spec_type']))\r\n self._defaults[spec_type] = Default(spec_type, stmt)\r\n return None","def add_parent_attributes(self):\n if len(self.parent_attributes) == 0:\n return\n dest = self.parent.attributes\n source = self.parent_attributes\n changes = {}\n self.merge_attribute_defs(dest, source, changes)\n for aid, value in changes.iteritems():\n# self.parent.h5node.attrs[aid] = value\n # may need modifying for MATLAB\n #- if self.path not in self.file.file_pointer:\n if self.file.get_node(self.path, abort=False) is None:\n # create parent node since it does not exist\n print \"trying to set parent attributes on non-registered parent node:\"\n print \"Non-registered parent node is: '%s'\", self.path\n traceback.print_stack()\n sys.exit(1)\n #- self.file.file_pointer[self.path].attrs[aid] = value\n self.file.set_attribute(self.path, aid, value)"],"string":"[\n \"def initDefaults(self):\\n return _libsbml.Compartment_initDefaults(self)\",\n \"def initDefaults(self):\\n return _libsbml.CompartmentGlyph_initDefaults(self)\",\n \"def set_defaults(self, compmgr=None):\\n for section, default_options in self.defaults(compmgr).items():\\n for name, value in default_options.items():\\n if not ProductSetting.exists(self.env, self.product,\\n section, name):\\n if any(parent[section].contains(name, defaults=False)\\n for parent in self.parents):\\n value = None\\n self.set(section, name, value)\",\n \"def propagate_defaults(config_doc):\\n for group_name, group_doc in config_doc.items():\\n if isinstance(group_doc, dict):\\n defaults = group_doc.get('defaults', {})\\n\\n for item_name, item_doc in group_doc.items():\\n if item_name == 'defaults':\\n continue\\n if isinstance(item_doc, dict):\\n\\n group_doc[item_name] = \\\\\\n dict_merge_pair(copy.deepcopy(defaults), item_doc)\\n\\n return config_doc\",\n \"def init_defaults(self, defaults):\\r\\n for (sect, opt, default) in defaults:\\r\\n self._default(sect, opt, default)\",\n \"def defaults():\\n global __preset_staging\\n \\n t = TreeDict('Default_Parameter_Tree', __defaultpresettree__ = True)\\n __preset_staging[id(t)] = t\\n return t\",\n \"def replace_defaults(d):\\n\\n # remove the defaults section\\n defaults = d.pop('.defaults')\\n\\n # look for default tags and replace them\\n for k, v in defaults.items():\\n recursive_search_replace(d, '!' + k + '!', v)\",\n \"def assign_defaults(self):\\n\\n def module_default_sort_key(module):\\n sort_key = (\\n 1 if module.marked_as_default else -1,\\n module.version,\\n module.variant,\\n -self.index(module.modulepath),\\n )\\n return sort_key\\n\\n self.defaults = {}\\n grouped = groupby(\\n [module for path in self.path for module in path.modules], lambda x: x.name\\n )\\n for (_, modules) in grouped:\\n for module in modules:\\n module.is_default = False\\n if len(modules) > 1:\\n modules = sorted(modules, key=module_default_sort_key, reverse=True)\\n modules[0].is_default = True\\n self.defaults[modules[0].name] = modules[0]\",\n \"def buildTagMap(default, *args):\\r\\n built = {}\\r\\n for portion in args:\\r\\n if hasattr(portion, 'items'):\\r\\n #It's a map. Merge it.\\r\\n for k,v in portion.items():\\r\\n built[k] = v\\r\\n elif isList(portion):\\r\\n #It's a list. Map each item to the default.\\r\\n for k in portion:\\r\\n built[k] = default\\r\\n else:\\r\\n #It's a scalar. Map it to the default.\\r\\n built[portion] = default\\r\\n return built\",\n \"def set_config_all_to_defaults():\\n logging.debug(\\\"Creating default config\\\")\\n for section in all_defaults:\\n set_config_section_to_defaults(section)\\n global config_changed\\n config_changed = True\",\n \"def setDefaults(self, cs):\\n self._xsBlockRepresentation = cs[\\\"xsBlockRepresentation\\\"]\\n self._disableBlockTypeExclusionInXsGeneration = cs[\\n \\\"disableBlockTypeExclusionInXsGeneration\\\"\\n ]\\n for xsId, xsOpt in self.items():\\n xsOpt.setDefaults(\\n cs[\\\"xsBlockRepresentation\\\"],\\n cs[\\\"disableBlockTypeExclusionInXsGeneration\\\"],\\n )\",\n \"def get_default_vpas(self, composition_space):\\n\\n default_vpas = {}\\n for element in composition_space.get_all_elements():\\n default_vpas[element.symbol] = self.all_default_vpas[\\n element.symbol]\\n return default_vpas\",\n \"def _merge_with_default_values(self, cr, uid, external_session, ressource, vals, sub_mapping_list, defaults=None, context=None):\\n if not defaults: return vals\\n for key in defaults:\\n if not key in vals:\\n vals[key] = defaults[key]\\n return vals\",\n \"def _update_default_configs(\\n default_configs: tuple[dict[Any, Any]], passed_configs: tuple[dict[Any, Any]]\\n ):\\n\\n for default_config, passed_config in zip(default_configs, passed_configs):\\n if passed_config is not None:\\n update_dict_recursively(default_config, passed_config)\",\n \"def _setup_parents(self, parents=None):\\n from trac import config\\n self.parents = (parents or [])\\n for filename in self.get('inherit', 'file').split(','):\\n filename = Section._normalize_path(filename.strip(), self.env)\\n self.parents.append(config.Configuration(filename))\",\n \"def _apply_defaults(self):\\n # Applies normal parameter defaults\\n for scalar_parameter, value in self._DEFAULT_PARAMETER_SCALARS.items():\\n if scalar_parameter not in self.parameters:\\n self.parameters[scalar_parameter] = copy.copy(value)\\n\\n # Applies defaults to all ramp parameters\\n for table_parameter, table in self._DEFAULT_PARAMETER_TABLES.items():\\n self.parameters[table_parameter] = [list(tup) for tup in table]\\n self.parameters['_' + table_parameter] = zip(*self.parameters[table_parameter])\",\n \"def list_tag_defaults(self, **kwargs):\\n resource_path = \\\"/tagDefaults\\\"\\n method = \\\"GET\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"page\\\",\\n \\\"limit\\\",\\n \\\"id\\\",\\n \\\"compartment_id\\\",\\n \\\"tag_definition_id\\\",\\n \\\"lifecycle_state\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"list_tag_defaults got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n if 'lifecycle_state' in kwargs:\\n lifecycle_state_allowed_values = [\\\"ACTIVE\\\"]\\n if kwargs['lifecycle_state'] not in lifecycle_state_allowed_values:\\n raise ValueError(\\n \\\"Invalid value for `lifecycle_state`, must be one of {0}\\\".format(lifecycle_state_allowed_values)\\n )\\n\\n query_params = {\\n \\\"page\\\": kwargs.get(\\\"page\\\", missing),\\n \\\"limit\\\": kwargs.get(\\\"limit\\\", missing),\\n \\\"id\\\": kwargs.get(\\\"id\\\", missing),\\n \\\"compartmentId\\\": kwargs.get(\\\"compartment_id\\\", missing),\\n \\\"tagDefinitionId\\\": kwargs.get(\\\"tag_definition_id\\\", missing),\\n \\\"lifecycleState\\\": kwargs.get(\\\"lifecycle_state\\\", missing)\\n }\\n query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None}\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n query_params=query_params,\\n header_params=header_params,\\n response_type=\\\"list[TagDefaultSummary]\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n query_params=query_params,\\n header_params=header_params,\\n response_type=\\\"list[TagDefaultSummary]\\\")\",\n \"def ancestor_append_tags(self, tags):\\n\\n for ancestor in self.lineage():\\n ancestor.append_tags(tags)\",\n \"def _SetCompoundPriorities(self):\\n priority = self._GetMaxCommonPriority()\\n for c in self.reactants:\\n c.compound.SetSpeciesGroupPriority(priority)\",\n \"def defaultize(self):\\n if self.root is None:\\n genome.initialize(self)\\n self.root.defaultize()\",\n \"def __init__(self, tagged_sents, default_tag='nc0s000'):\\n self._default_tag = default_tag\",\n \"def to_tag_spec(self, tags):\\n\\n tag_spec = []\\n for child in self.all_children():\\n if not child.children:\\n child_spec = [{'equals': t} for t in child.path()]\\n tag_spec.append({'section': child_spec, 'add_tags': tags})\\n return tag_spec\",\n \"def fill_in_empty_tags(prior, tags):\\n print \\\"filling in empty entries for tags\\\"\\n for key in tags:\\n if not key in prior:\\n prior[key] = {}\\n for key1 in tags:\\n for key2 in tags:\\n prior[key1].setdefault(key2, 0.0)\",\n \"def _unset_defaults_and_overrides(self):\\n for info, group in self._all_opt_infos():\\n info.pop('default', None)\\n info.pop('override', None)\",\n \"def set_attrs_default(input_object, attr_name_list = None):\\n if attr_name_list is None:\\n attr_name_list = []\\n if len(attr_name_list) > 0:\\n attr_list = [input_object.attr(attr_name) for attr_name in attr_name_list]\\n else:\\n attr_list = general.get_channelbox_attributes(input_object)\\n\\n for attr in attr_list:\\n current_val = attr.get()\\n if hasattr(attr, 'addAttr'):\\n attr.addAttr(e = True, defaultValue = current_val)\",\n \"def __init__(self, defaults=None, default_sec=\\\"Uncategorized\\\"):\\n super(XFasterConfig, self).__init__(dict_type=OrderedDict)\\n self.default_sec = default_sec\\n self.add_section(default_sec)\\n if defaults is not None:\\n self.update(defaults)\",\n \"def __defaults__(self): \\n self.tag = 'Component'\\n self.origin = [[0.0,0.0,0.0]]\",\n \"def content(tmp_loc, ref_names_dict, order):\\n \\n fl = '[Content_Types].xml'\\n inp_path = '/'.join([tmp_loc, fl])\\n out_path = '/'.join([output_path, fl])\\n \\n cnt_lst = []\\n asset_lst = []\\n def_att = []\\n d = dict()\\n \\n root1,tree1 = gen_tree(inp_path)\\n root2,tree2 = gen_tree(out_path)\\n \\n # get all the extensions belongs to \\\"Default\\\" tag\\n for relation in root2:\\n if 'Default' in relation.tag:\\n def_att.append(relation.attrib['Extension'])\\n else:\\n break\\n \\n for relation in root1:\\n if 'Override' in relation.tag:\\n attrib = relation.attrib['PartName'][1:]\\n try:\\n cnt = attrib.split('ppt/')[-1]\\n ini = '/ppt/'\\n except:\\n cnt = attrib\\n ini = '/'\\n if cnt in ref_names_dict.keys():\\n relation.attrib['PartName'] = f'{ini}{ref_names_dict[cnt]}'\\n cnt_lst.append(relation)\\n # asset_lst.append(relation.attrib['PartName'])\\n else:\\n cnt_lst.append(relation)\\n if relation.attrib['PartName'] not in asset_lst:\\n asset_lst.append(relation.attrib['PartName'])\\n else:\\n attrib = relation.attrib['Extension']\\n if attrib not in def_att:\\n cnt_lst.append(relation)\\n # asset_lst.append(relation.attrib['Extension'])\\n # deal with the assest_lst\\n # print(\\\"AA: \\\", asset_lst)\\n cnt_lst = natsort.natsorted(cnt_lst)\\n for ele in cnt_lst:\\n prev = tree2.find(ele.tag)\\n prev.addnext(ele)\\n \\n tree2.write(out_path, pretty_print=True, xml_declaration=True, encoding='UTF-8', standalone=True)\\n \\n unq_attr = []\\n for relation in root2:\\n if 'Override' in relation.tag:\\n if relation.attrib['PartName'] not in unq_attr:\\n unq_attr.append(relation.attrib['PartName'])\\n else:\\n root2.remove(relation)\\n tree2.write(out_path, pretty_print=True, xml_declaration=True, encoding='UTF-8', standalone=True)\",\n \"def _add_default_tags(self):\\n self.tags.add_tag('ban', required=True)\",\n \"def add_default_options(self):\\n\\n options = getattr(self.parent, \\\"pyautodoc_set_default_option\\\", [])\\n for option in options:\\n self.set_default_option(option)\",\n \"def set_defaults(self, agents):\\n for a in agents:\\n for k, v in a.get_defaults().items():\\n self.env[k] = v\",\n \"def resolve_kwdefaults(sign: inspect.Signature) -> Dict[str, Any]:\\n kwdefaults = dict() # type: Dict[str, Any]\\n\\n # Add to the defaults all the values that are needed by the contracts.\\n for param in sign.parameters.values():\\n if param.default != inspect.Parameter.empty:\\n kwdefaults[param.name] = param.default\\n\\n return kwdefaults\",\n \"def initDefaults(self):\\n return _libsbml.Layout_initDefaults(self)\",\n \"def find_defaults(self):\\n\\n defaults = self.tree.findall('default')\\n default_remote = None\\n default_revision = None\\n\\n if len(defaults) > 1 and self.fail_on_invalid:\\n raise InvalidManifest(\\n 'More than one default entry, must be unique'\\n )\\n\\n try:\\n default_remote = defaults[-1].get('remote')\\n default_revision = defaults[-1].get('revision', 'master')\\n except IndexError:\\n pass # Leave defaults to None\\n\\n self.defaults = {\\n 'remote': default_remote, 'revision': default_revision\\n }\",\n \"def set_default_dna_options(treebuilder):\\n treebuilder.options = get_default_options()\",\n \"def defaults(file):\\n\\n\\tUNCAT_TAGID = 47\\n\\tNOSERIES_TAGID = 375\\n\\n\\treturn [NOSERIES_TAGID, UNCAT_TAGID]\",\n \"def sections(self, compmgr=None, defaults=True):\\n sections = set(to_unicode(s) \\\\\\n for s in ProductSetting.get_sections(self.env, self.product))\\n for parent in self.parents:\\n sections.update(parent.sections(compmgr, defaults=False))\\n if defaults:\\n sections.update(self.defaults(compmgr))\\n return sorted(sections)\",\n \"def _populate_default_values(self):\\n\\n if 'input_data' not in self._definition:\\n self._definition['input_data'] = []\\n for input_dict in self._definition['input_data']:\\n if 'required' not in input_dict:\\n input_dict['required'] = True\\n\\n if 'jobs' not in self._definition:\\n self._definition['jobs'] = []\\n for job_dict in self._definition['jobs']:\\n if 'recipe_inputs' not in job_dict:\\n job_dict['recipe_inputs'] = []\\n if 'dependencies' not in job_dict:\\n job_dict['dependencies'] = []\\n for dependency_dict in job_dict['dependencies']:\\n if 'connections' not in dependency_dict:\\n dependency_dict['connections'] = []\",\n \"def _write_overrides(\\n self, node, parent=None, parent_packmode=None, path_parts=tuple(), root=None\\n ):\\n if root is None:\\n root = node\\n if (parent is root) or (\\n parent_packmode and node[\\\"packmode\\\"] != parent_packmode\\n ):\\n self.overrides[str(PurePath(*path_parts))] = node[\\\"packmode\\\"]\\n for key, child in node[\\\"children\\\"].items():\\n self._write_overrides(\\n node=child,\\n parent=node,\\n parent_packmode=node[\\\"packmode\\\"],\\n path_parts=path_parts + (key,),\\n root=root,\\n )\",\n \"def set_default_protein_options(treebuilder):\\n treebuilder.options = get_default_options()\",\n \"def combine_pax_configs(config, overrides):\\n # TODO: we should soon be able to get this from pax, but let's wait a while to prevent incompatibilties\\n for section_name, stuff in overrides.items():\\n config.setdefault(section_name, {})\\n config[section_name].update(stuff)\\n return config\",\n \"def initDefaults(self):\\n return _libsbml.SpeciesReference_initDefaults(self)\",\n \"def merge_new_overrides():\\n # Take the dex config as is:\\n new_doc = {'config': copy.deepcopy(DEFINES['dex_config'])}\\n # Convert old dex certs.web.secret to https-tls volume/volumeMounts\\n mount = {'mountPath': get_httpstls_mount(), 'name': 'https-tls'}\\n vol = {'secret': {'secretName': get_httpstls_secret(),\\n 'defaultMode': DEFAULT_HTTPSTLS_MODE},\\n 'name': 'https-tls'}\\n # Take 'extra' volumes and mounts that may exist in old dex\\n # This is expected to be the WAD certificate\\n volumes = []\\n volumeMounts = []\\n if 'volumes' in DEFINES:\\n volumes = copy.deepcopy(DEFINES['volumes'])\\n if 'volumeMounts' in DEFINES:\\n volumeMounts = copy.deepcopy(DEFINES['volumeMounts'])\\n\\n # only add volumes/mounts if 'extra' was specified, or\\n # if there was non-default mount\\n if volumes or 'tls_secret' in DEFINES:\\n volumes.append(vol)\\n if volumeMounts or 'dex_https_tlsCert' in DEFINES:\\n volumeMounts.append(mount)\\n if volumes:\\n new_doc['volumes'] = volumes\\n if volumeMounts:\\n new_doc['volumeMounts'] = volumeMounts\\n return new_doc\",\n \"def _set_default_attributes(self):\\n # Default input attributes\\n self._has_studio_override = False\\n self._had_studio_override = False\\n\\n self._is_overriden = False\\n self._was_overriden = False\\n\\n self._is_modified = False\\n self._is_invalid = False\\n\\n self._is_nullable = False\\n self._as_widget = False\\n self._is_group = False\\n\\n # If value should be stored to environments\\n self._env_group_key = None\\n\\n self._any_parent_as_widget = None\\n self._any_parent_is_group = None\\n\\n # Parent input\\n self._parent = None\\n\\n # States of inputs\\n self._state = None\\n self._child_state = None\\n\\n # Attributes where values are stored\\n self.default_value = NOT_SET\\n self.studio_value = NOT_SET\\n self.override_value = NOT_SET\\n\\n # Log object\\n self._log = None\\n\\n # Only for develop mode\\n self.defaults_not_set = False\",\n \"def __init__(self, tagged_sents, default_tag='nc0s000'):\\n \\n self.default_tag = default_tag\\n \\n self.word_tags = defaultdict(lambda: defaultdict(int))\\n \\n for sent in list(tagged_sents):\\n for word, tag in sent:\\n self.word_tags[word][tag] += 1\\n\\n self.word_tags = dict(self.word_tags)\",\n \"def tag(nodes, arg='', split=True, default=0, add_parent_space=True, add_default_spaces=True, zero_node=None, const_node=None):\\n\\n nodes = mc.ls(nodes)\\n orig_const_node = const_node\\n orig_zero_node = zero_node\\n\\n for node in nodes:\\n\\n # get zero if not specified\\n if orig_zero_node:\\n zero_node = orig_zero_node\\n else:\\n zero_node = node+'_ZERO'\\n\\n # get const node - this is what the parent constraint will be thrown onto\\n if orig_const_node:\\n const_node = orig_const_node\\n else:\\n const_node = node+'_CONST'\\n\\n if add_parent_space and not mc.objExists(zero_node):\\n mc.warning('Cannot find a zero for '+node)\\n continue\\n\\n if not mc.objExists(const_node):\\n mc.warning('Cannot find a const for '+const_node)\\n continue\\n\\n # build arg\\n arg = arg.strip()\\n if ' ' in arg:\\n arg = re.sub(' +',' ', arg)\\n\\n arg_kwargs = {\\n 'arg': arg,\\n 'split': split,\\n 'default': default,\\n 'const_node': const_node,\\n 'zero_node': zero_node,\\n 'add_default_spaces': add_default_spaces,\\n 'add_parent_space': add_parent_space\\n }\\n\\n # create + set attr\\n if not mc.objExists(node+'.tagSpaces'):\\n mc.addAttr(node, ln='tagSpaces', dt='string', hidden=False)\\n\\n mc.setAttr(node+'.tagSpaces', str(arg_kwargs), type='string')\\n\\n # This convert all this legacy sloppy crap to the new hotness\\n space_obj = Space(node)\\n space_obj.set_data()\\n\\n return arg\",\n \"def _set_default_attrs(self, obj, subs):\\n for attr_name, attr_subs in subs.iteritems():\\n if not getattr(obj, attr_name, None):\\n for newattr_name, newattr_val in attr_subs.iteritems():\\n setattr(obj, newattr_name, newattr_val)\",\n \"def _to_config_recurse(config_cls, environ, prefixes, default=RAISE):\\n # We keep track of values we actually got from the getter vs those we set\\n # from the `ConfigEntry` default value\\n got = {}\\n defaulted = {}\\n missing_vars = set()\\n\\n for attr_obj in attr.fields(config_cls):\\n try:\\n ce = attr_obj.metadata[CNF_KEY]\\n except KeyError:\\n continue\\n name = attr_obj.name\\n\\n if ce.sub_cls is not None:\\n prefix = ce.sub_cls._prefix or name\\n got[name] = _to_config_recurse(\\n ce.sub_cls, environ, (*prefixes, prefix), default=ce.default\\n )\\n else:\\n getter = ce.callback or _default_getter\\n try:\\n got[name] = getter(environ, attr_obj.metadata, prefixes, name)\\n except MissingEnvValueError as exc:\\n if isinstance(ce.default, Raise):\\n missing_vars |= set(exc.args)\\n else:\\n defaulted[name] = (\\n attr.NOTHING\\n if isinstance(ce.default, attr.Factory)\\n else ce.default\\n )\\n\\n if missing_vars:\\n # If we were told to raise OR if we got *any* values for our attrs, we\\n # will raise a `MissingEnvValueError` with all the missing variables\\n if isinstance(default, Raise) or got:\\n raise MissingEnvValueError(*missing_vars) from None\\n\\n # Otherwise we will simply use the default passed into this call.\\n # Should be no need to handle `Factory`s here.\\n return default\\n\\n # Merge the defaulted and actually collected values into the config type\\n defaulted.update(got)\\n return config_cls(**defaulted)\",\n \"def set_default_configs(self):\\n\\n raise Exception(\\\"Child classes must override set_default_configs().\\\")\",\n \"def twolevel_default_params(defaults):\\n def wrap(function):\\n def withargs(*args, **kwargs):\\n merged = {}\\n merged.update(defaults)\\n for k, v in kwargs.items():\\n if type(v) == dict and k in merged and type(merged[k]) == dict:\\n merged[k].update(v)\\n else:\\n merged[k] = v\\n return function(*args, **merged)\\n\\n return withargs\\n\\n return wrap\",\n \"def initDefaults(self):\\n return _libsbml.Parameter_initDefaults(self)\",\n \"def _get_tags(self):\\n if hasattr(self, \\\"_default_tags\\\"):\\n tags = self._default_tags()\\n else:\\n tags = deepcopy(_default_tags)\\n dynamic_tags = {}\\n for cl in reversed(inspect.getmro(self.__class__)):\\n if hasattr(cl, \\\"_more_static_tags\\\"):\\n more_tags = cl._more_static_tags()\\n tags.update(more_tags)\\n if hasattr(cl, \\\"_more_tags\\\"):\\n more_tags = cl._more_tags(self)\\n dynamic_tags.update(more_tags)\\n tags.update(dynamic_tags)\\n\\n return tags\",\n \"def initialize_children(self, bibs):\\n\\t\\tpass\",\n \"def iterate(self, compmgr=None, defaults=True):\\n options = set()\\n name_str = self.name\\n for setting in ProductSetting.select(self.env,\\n where={'product': self.product,\\n 'section': name_str}):\\n option = self.optionxform(setting.option)\\n options.add(option)\\n yield option\\n for parent in self.config.parents:\\n for option in parent[self.name].iterate(defaults=False):\\n loption = self.optionxform(option)\\n if loption not in options:\\n options.add(loption)\\n yield option\\n if defaults:\\n for section, option in Option.get_registry(compmgr).keys():\\n if section == self.name and \\\\\\n self.optionxform(option) not in options:\\n yield option\",\n \"def _add_merged_attributes(node, all_recipes, all_roles):\\n # Get cookbooks from extended recipes\\n attributes = {}\\n for recipe in node['recipes']:\\n # Find this recipe\\n found = False\\n for r in all_recipes:\\n if recipe == r['name']:\\n found = True\\n for attr in r['attributes']:\\n if r['attributes'][attr].get('type') == \\\"hash\\\":\\n value = {}\\n else:\\n value = r['attributes'][attr].get('default')\\n # Attribute dictionaries are defined as a single\\n # compound key. Split and build proper dict\\n build_dct(attributes, attr.split(\\\"/\\\"), value)\\n if not found:\\n error = \\\"Could not find recipe '{0}' while \\\".format(recipe)\\n error += \\\"building node data bag for '{0}'\\\".format(node['name'])\\n abort(error)\\n\\n # Get default role attributes\\n for role in node['roles']:\\n for r in all_roles:\\n if role == r['name']:\\n update_dct(attributes, r['default_attributes'])\\n\\n # Get normal node attributes\\n non_attribute_fields = [\\n 'id', 'name', 'role', 'roles', 'recipes', 'run_list', 'ipaddress']\\n node_attributes = {}\\n for key in node:\\n if key in non_attribute_fields:\\n continue\\n node_attributes[key] = node[key]\\n update_dct(attributes, node_attributes)\\n\\n # Get override role attributes\\n for role in node['roles']:\\n for r in all_roles:\\n if role == r['name']:\\n update_dct(attributes, r['override_attributes'])\\n # Merge back to the original node object\\n node.update(attributes)\",\n \"def _autoInitPars(self):\\n for p in self._pars:\\n setattr(self,p,self.defaultparval)\",\n \"def defaults() -> dict:\\n pass\",\n \"def setup_defaults(self):\\n status = self._lib_vscf_ecc.vscf_ecc_setup_defaults(self.ctx)\\n VscfStatus.handle_status(status)\",\n \"def _merge_and_reorder(\\n inherited_fields: Dict[str, Union[Annotation, Input, Output]],\\n cls_fields: Dict[str, Union[Annotation, Input, Output]],\\n ) -> Dict[str, Union[Annotation, Input, Output]]:\\n\\n def _split(\\n _fields: Dict[str, Union[Annotation, Input, Output]]\\n ) -> Tuple[Dict[str, Union[Annotation, Input, Output]], Dict[str, Union[Annotation, Input, Output]]]:\\n \\\"\\\"\\\"Split fields to two parts from the first default field.\\n\\n :param _fields: The fields\\n :type _fields: Dict[str, Union[Annotation, Input, Output]]\\n :return: A 2-tuple of (fields with no defaults, fields with defaults)\\n :rtype: Tuple[Dict[str, Union[Annotation, Input, Output]], Dict[str, Union[Annotation, Input, Output]]]\\n \\\"\\\"\\\"\\n _no_defaults_fields, _defaults_fields = {}, {}\\n seen_default = False\\n for key, val in _fields.items():\\n if val.get(\\\"default\\\", None) or seen_default:\\n seen_default = True\\n _defaults_fields[key] = val\\n else:\\n _no_defaults_fields[key] = val\\n return _no_defaults_fields, _defaults_fields\\n\\n inherited_no_default, inherited_default = _split(inherited_fields)\\n cls_no_default, cls_default = _split(cls_fields)\\n # Cross comparison and delete from inherited_fields if same key appeared in cls_fields\\n # pylint: disable=consider-iterating-dictionary\\n for key in cls_default.keys():\\n if key in inherited_no_default.keys():\\n del inherited_no_default[key]\\n for key in cls_no_default.keys():\\n if key in inherited_default.keys():\\n del inherited_default[key]\\n return OrderedDict(\\n {\\n **inherited_no_default,\\n **cls_no_default,\\n **inherited_default,\\n **cls_default,\\n }\\n )\",\n \"def _fix_treetags(self, tree):\\n for element in tree:\\n element.tag = element.tag.split('}')[1]\\n if len(element.getchildren()) > 0:\\n self._fix_treetags(element)\\n return tree\",\n \"def autoprovisioning_node_pool_defaults(self) -> Optional[pulumi.Input['AutoprovisioningNodePoolDefaultsArgs']]:\\n return pulumi.get(self, \\\"autoprovisioning_node_pool_defaults\\\")\",\n \"def recursive_make_defaultdict(conf):\\n if isinstance(conf, dict):\\n for key in conf.keys():\\n conf[key] = recursive_make_defaultdict(conf[key])\\n return defaultdict(lambda: None, conf)\\n return conf\",\n \"def default_configs(cls):\\n config = super().default_configs()\\n config.update(\\n {\\n \\\"entry_type\\\": None,\\n \\\"attribute\\\": None,\\n \\\"index_annotation\\\": None,\\n }\\n )\\n return config\",\n \"def test_defaultdict_config():\\n lang_configs = defaultdict(lambda: dict(processors=\\\"tokenize\\\"))\\n run_multilingual_pipeline(en_has_dependencies=False, fr_has_dependencies=False, lang_configs=lang_configs)\\n\\n lang_configs = defaultdict(lambda: dict(processors=\\\"tokenize\\\"))\\n lang_configs[\\\"en\\\"] = {\\\"processors\\\": \\\"tokenize,pos,lemma,depparse\\\"}\\n run_multilingual_pipeline(en_has_dependencies=True, fr_has_dependencies=False, lang_configs=lang_configs)\",\n \"def autodefaults (self):\\r\\n\\r\\n self.defaults_from_notes(identifying_key=EMPTYCHAR,\\r\\n mark=EQUAL,\\r\\n obj=self.default_dict['commands'],\\r\\n entrytext=COMMANDMACROSCRIPT)\",\n \"def _getGroupDefaults(self):\\n defaults = self.getDefaultGroupContainer(\\n _name = \\\"defaults\\\",\\n diff_command = self.general.diff_command,\\n cia_rpc_server = self.general.cia_rpc_server,\\n )\\n try:\\n self._passConfig(defaults, \\\"defaults\\\")\\n except ConfigSectionNotFoundError:\\n # [defaults] is optional\\n pass\\n else:\\n self._config.remove_section('defaults')\\n\\n return defaults\",\n \"def get_defaults():\\n\\n return {\\n 'base_types': _get_base_types(),\\n 'template_types': _get_template_types(),\\n 'refined_types': _get_refined_types(),\\n 'humannames': _get_humannames(),\\n 'argument_kinds': _get_argument_kinds(),\\n 'variable_namespace': {},\\n 'type_aliases': _get_type_aliases(),\\n 'cpp_types': _get_cpp_types(),\\n 'numpy_types': _get_numpy_types(),\\n 'from_pytypes': _get_from_pytypes(),\\n 'cython_ctypes': _get_cython_ctypes(),\\n 'cython_cytypes': _get_cython_cytypes(),\\n 'cython_pytypes': _get_cython_pytypes(),\\n 'cython_cimports': _get_cython_cimports(),\\n 'cython_cyimports': _get_cython_cyimports(),\\n 'cython_pyimports': _get_cython_pyimports(),\\n 'cython_functionnames': _get_cython_functionnames(),\\n 'cython_classnames': _get_cython_classnames(),\\n 'cython_c2py_conv': _get_cython_c2py_conv(),\\n 'cython_py2c_conv_vector_ref': CYTHON_PY2C_CONV_VECTOR_REF,\\n 'cython_py2c_conv': _get_cython_py2c_conv(),\\n }\",\n \"def _node_defaults(self):\\n parent = super(QTree, self)._node_defaults()\\n parent[\\\"state\\\"] = np.zeros([self.size, self.size])\\n parent[\\\"network\\\"] = self\\n return parent\",\n \"def update_gui_defaults(GUI_defaults):\\n # failure flag\\n config_import_error = False\\n \\n # xml source directory\\n src_dir = os.getcwd() + '\\\\\\\\src'\\n \\n # attempt to parse the xml file and get it's root\\n try:\\n tree = ET.parse(src_dir + '\\\\\\\\pySCPI_config.xml')\\n root = tree.getroot()\\n \\n except (IOError, ET.ParseError):\\n # parsing failed for some reason\\n config_import_error = True\\n GUI_defaults.log_error('*** pySCPI_config.xml is'\\n 'missing or corrupt ***')\\n # end try\\n \\n # import the default values from the xml file\\n if not config_import_error:\\n \\n # list of tags to look for\\n config_tags = ['default_filename', 'default_delay', \\n 'default_length', 'default_dp']\\n \\n # iterate through tags\\n for tag in config_tags:\\n # find each tag\\n config_element = root.findall(tag)\\n \\n # if there is only one of a tag\\n if len(config_element) == 1:\\n # convert it to text\\n config_text = config_element[0].text\\n \\n # update the appropriate field\\n if tag == 'default_filename':\\n GUI_defaults.update_filename(config_text)\\n \\n elif tag == 'default_delay':\\n GUI_defaults.update_delay(config_text)\\n \\n elif tag == 'default_length':\\n GUI_defaults.update_length(config_text)\\n \\n elif tag == 'default_dp':\\n GUI_defaults.update_dp(config_text)\\n # end if\\n \\n else:\\n GUI_defaults.log_error('*** There is the wrong number '\\n 'of ' + tag + ' declarations in '\\n 'pySCPI_config.xml ***') \\n # end if\\n # end for\\n \\n # find the default addresses\\n address_elements = root.findall('addresses')\\n \\n # if there are addresses\\n if (len(address_elements) == 1) and (len(address_elements[0]) > 0):\\n for element in address_elements[0]:\\n # add each address to the list\\n GUI_defaults.add_address(element.tag, element.get('address'))\\n # end for\\n \\n else:\\n GUI_defaults.log_error('*** No addresses were provided in '\\n 'pySCPI_config.xml ***') \\n # end if\\n \\n # find the default commands\\n command_elements = root.findall('default_commands')\\n \\n # if there are commands\\n if (len(command_elements) == 1) and (len(command_elements[0]) > 0):\\n for command in command_elements[0]:\\n # add each command to the list\\n GUI_defaults.add_command(command.text)\\n # end for\\n\\n else:\\n GUI_defaults.log_error('*** No commands were provided in '\\n 'pySCPI_config.xml ***') \\n # end if \\n # end if\",\n \"def get_defaults(self):\\n default_dict = {}\\n args, varargs, keyword, defaults = inspect.getargspec(self.exec_obj)\\n if defaults:\\n default_dict = dict(zip(args[-len(defaults):], defaults))\\n return default_dict\",\n \"def update_default_values(self, parent_values):\\n raise NotImplementedError(\\n \\\"{} does not have implemented `update_default_values`\\\".format(self)\\n )\",\n \"def _fill_in_default_kwargs(\\n node: torch.fx.Node,\\n) -> Tuple[List[fx_type_utils.Argument], Dict[str, fx_type_utils.Argument]]:\\n\\n # TODO(titaiwang): aten::sym_size has overload, but fx graph is using\\n # overloadpacket for some reasons.\\n # https://github.com/pytorch/pytorch/issues/97201\\n # We manually assigned overload for aten::sym_size.\\n if hasattr(node.target, \\\"_schema\\\"):\\n node_schema = node.target._schema # type: ignore[union-attr]\\n else:\\n node_schema = torch.ops.aten.sym_size.int._schema # type: ignore[union-attr]\\n\\n # This function assumes the order of arguments in FX op is the\\n # same as the order of arguments in TorchScript op.\\n complete_args: List[fx_type_utils.Argument] = []\\n complete_kwargs: Dict[str, fx_type_utils.Argument] = {}\\n\\n if inspect.isbuiltin(node.target):\\n complete_args = list(node.args)\\n else:\\n for i, expected_arg in enumerate(node_schema.arguments):\\n if i < len(node.args):\\n complete_args.append(node.args[i])\\n elif expected_arg.name in node.kwargs:\\n complete_kwargs[expected_arg.name] = node.kwargs[expected_arg.name]\\n else:\\n # Get default from schema.\\n complete_kwargs[expected_arg.name] = expected_arg.default_value\\n\\n return complete_args, complete_kwargs\",\n \"def _fix_tags(self):\\n logging.info('--- Fix Tags ---')\\n saved_originals = {\\n key: self.git.config.get(key, exit_on_error=False).strip()\\n for key in (CI_USER_NAME, CI_USER_EMAIL)}\\n try:\\n for tag_name in sorted(self.tags):\\n # Get commit data from the (latest) commit of a\\n # svn/tags/… branch (following the convention for svn,\\n # there should only be one),\\n # produce a git tag using these data\\n # and delete the now-obsolete branch.\\n tag_name = tag_name.strip()\\n tag_id = PRX_SVNTAGS_PREFIX.sub('', tag_name)\\n commit_data = {\\n key: self.git.log(\\n '-1', f'--pretty=format:{value}', tag_name)\\n for (key, value) in COMMIT_DATA_FORMATS.items()}\\n self.git.config(CI_USER_NAME, commit_data[CD_AUTHOR_NAME])\\n self.git.config(CI_USER_EMAIL, commit_data[CD_AUTHOR_EMAIL])\\n original_git_committer_date = ENV.get(ENV_GIT_COMMITTER_DATE)\\n ENV[ENV_GIT_COMMITTER_DATE] = commit_data[CD_DATE]\\n self.git.tag(\\n '-a', '-m', commit_data[CD_COMMENT], tag_id, tag_name)\\n if original_git_committer_date is None:\\n del ENV[ENV_GIT_COMMITTER_DATE]\\n else:\\n ENV[ENV_GIT_COMMITTER_DATE] = original_git_committer_date\\n #\\n self.git.branch('-d', '-r', tag_name)\\n #\\n finally:\\n # We only change the git config values\\n # if there are self.tags available.\\n # So it stands to reason we should revert them only in that case.\\n if self.tags:\\n for (key, value) in saved_originals.items():\\n if value:\\n self.git.config(key, value)\\n else:\\n self.git.config.unset(key)\\n #\\n #\\n #\\n #\",\n \"def default_nested(self, data, many, **kwargs):\\n if not data.get(\\\"metadata\\\"):\\n data[\\\"metadata\\\"] = {}\\n if not data.get(\\\"pids\\\"):\\n data[\\\"pids\\\"] = {}\\n\\n return data\",\n \"def set_defaults(self, **kw):\\n group = kw.pop('group', None)\\n for o, v in kw.items():\\n self.cfg_fixture.set_default(o, v, group=group)\",\n \"def voxel_env_override_defaults(env, parser):\\n parser.set_defaults(\\n encoder_type='conv',\\n encoder_subtype='convnet_simple',\\n hidden_size=512,\\n obs_subtract_mean=0.0,\\n obs_scale=255.0,\\n actor_worker_gpus=[0],\\n )\",\n \"def defaults():\\n return {}\",\n \"def _initialize_defaults(self):\\n for key, value in defaults.items():\\n if key not in self.source_params:\\n self.source_params[key] = value\",\n \"def _initialize_defaults(self):\\n for key, value in defaults.items():\\n if key not in self.source_params:\\n self.source_params[key] = value\",\n \"def build_dictionary_element_tree(element, node_attr_fields=NODE_FIELDS, way_attr_fields=WAY_FIELDS,\\n default_tag_type='regular'):\\n node_attribs = {}\\n way_attribs = {}\\n way_nodes = []\\n tags = [] # Handle secondary tags the same way for both node and way elements\\n \\n if element == None:\\n print ('Element is Null')\\n return None\\n \\n if element.tag == 'node':\\n check = check_id(element.attrib['id'])\\n \\n if not check:\\n print ('Node ID is Null or not a number: ', element.attrib['id'])\\n fix_it.node_id_bad[element.attrib['id']] += 1\\n return None\\n \\n for attr in element.attrib:\\n if attr in node_attr_fields:\\n node_attribs[attr] = element.attrib[attr]\\n \\n for child in element:\\n temp = { }\\n \\n if 'cityracks.' in child.attrib['k']:\\n child.attrib['k'] = child.attrib['k'].replace('cityracks.','')\\n \\n m = correct_chars_re.search(child.attrib['k']) # No match returns None\\n\\n if not m: \\n print ('Node key -- Problem character! ', 'key = ', child.attrib['k'], ' value = ', child.attrib['v'])\\n fix_it.counts['node child key eliminated'] += 1\\n infoKey = 'node key: ' + child.attrib['k']\\n fix_it.bad_keys[infoKey] += 1\\n continue # eliminate the problematic child tag\\n \\n # Fix value\\n fixed = fix_it.fixer(child, 'Node') # Correct or eliminate the child value\\n # Function fix_it returns None if there is a data problem\\n if fixed == '$skip':\\n fix_it.counts['node tag skipped'] += 1\\n continue\\n \\n if not fixed:\\n fix_it.counts['node child value eliminated'] += 1\\n continue # Eliminate this child tag\\n else:\\n temp['id'] = element.attrib['id'] # Save the fixed child tag for writing into csv file\\n temp['value'] = fixed\\n \\n if ':' in child.attrib['k']:\\n k = child.attrib['k'].split(':',1)\\n temp['type'] = k[0]\\n temp['key'] = k[1]\\n else:\\n temp['key'] = child.attrib['k']\\n temp['type'] = default_tag_type\\n \\n fix_it.counts['node tag count'] += 1 # count the child tags not eliminated\\n tags.append(temp)\\n \\n return {'node': node_attribs, 'node_tags': tags}\\n \\n elif element.tag == 'way':\\n check = check_id(element.attrib['id'])\\n \\n if not check:\\n print ('Way ID is Null or not a number: ', element.attrib['id'])\\n fix_it.way_id_bad[element.attrib['id']] += 1\\n return None\\n \\n for attr in element.attrib: \\n if attr in way_attr_fields:\\n way_attribs[attr] = element.attrib[attr]\\n \\n position = 0\\n for child in element:\\n temp = { }\\n \\n if child.tag == 'tag':\\n m = correct_chars_re.search(child.attrib['k']) # No match returns None\\n \\n if not m:\\n print ('Way key -- Problem char! ', 'key = ', child.attrib['k'], ' value = ', child.attrib['v'])\\n fix_it.counts['way child key eliminated'] += 1\\n infoKey = 'way key: ' + child.attrib['k']\\n fix_it.bad_keys[infoKey] += 1\\n continue # eliminate the problematic child tag\\n \\n # Fix value\\n fixed = fix_it.fixer(child, 'Way') # Correct or eliminate the child value\\n # Function fix_it returns None if there is a data problem\\n if fixed == '$skip':\\n fix_it.counts['way tag skipped'] += 1\\n continue\\n \\n if not fixed:\\n fix_it.counts['way child value eliminated'] += 1\\n continue # Eliminate this child tag\\n else:\\n temp['id'] = element.attrib['id'] # Save the fixed child tag for writing into csv file\\n temp['value'] = fixed\\n\\n if ':' in child.attrib['k']:\\n k = child.attrib['k'].split(':',1)\\n temp['type'] = k[0]\\n temp['key'] = k[1]\\n else:\\n temp['key'] = child.attrib['k']\\n temp['type'] = default_tag_type\\n \\n fix_it.counts['way tag count'] += 1 # count the child tags not eliminated\\n tags.append(temp)\\n \\n elif child.tag == 'nd':\\n check = check_id(child.attrib['ref'])\\n \\n if not check:\\n print ('Way Node reference is Null or not a number: ', child.attrib['ref'])\\n fix_it.way_node_reference_bad[child.attrib['ref']] += 1\\n continue\\n \\n temp['id'] = element.attrib['id']\\n temp['node_id'] = child.attrib['ref']\\n temp['position'] = position\\n position += 1\\n fix_it.counts['way node tag count'] += 1 # count the child tags not eliminated\\n way_nodes.append(temp)\\n \\n #print ('way_attribs:\\\\n', way_attribs)\\n #print ('way_nodes:\\\\n', way_nodes)\\n #print ('way_tags:\\\\n', tags)\\n #print ('---------------\\\\n')\\n return {'way': way_attribs, 'way_nodes': way_nodes, 'way_tags': tags}\",\n \"def replaceDefaults(d):\\n defaults = d.pop('.defaults')\\n for k, v in defaults.items():\\n recursiveSearchReplace(d, '!' + k + '!', v)\",\n \"def _get_function_defaults(func: FunctionType) -> dict[str, Any]:\\n # extracted bit from inspect.signature... ~20x faster\\n pos_count = func.__code__.co_argcount\\n arg_names = func.__code__.co_varnames\\n\\n defaults = func.__defaults__ or ()\\n\\n non_default_count = pos_count - len(defaults)\\n positional_args = arg_names[:pos_count]\\n\\n output = {\\n name: defaults[offset]\\n for offset, name in enumerate(positional_args[non_default_count:])\\n }\\n if func.__kwdefaults__:\\n output.update(func.__kwdefaults__)\\n return output\",\n \"def correctDefaultNounTag(idx, tagged_term, tagged_terms, lexicon):\\n term, tag, norm = tagged_term\\n if tag == 'NND':\\n if term.endswith('s'):\\n tagged_term[1] = 'NNS'\\n tagged_term[2] = term[:-1]\\n else:\\n tagged_term[1] = 'NN'\",\n \"def get_default_config():\\n\\n config = {}\\n\\n for name, cls in get_tools().items():\\n config[name] = cls.get_default_config()\\n\\n try:\\n workers = multiprocessing.cpu_count() - 1\\n except NotImplementedError: # pragma: no cover\\n workers = 1\\n workers = max(1, min(4, workers))\\n\\n config.update({\\n 'exclude': [],\\n 'merge-issues': True,\\n 'workers': workers,\\n 'disabled': [],\\n 'noqa': True,\\n 'extends': [],\\n 'ignore-missing-extends': False,\\n })\\n\\n return config\",\n \"def xml_tag(inp_tag, out_tag):\\n tag_dict = OrderedDict()\\n sub_tag = OrderedDict()\\n for i in range(len(inp_tag)):\\n if inp_tag[i] not in out_tag:\\n tag_dict[inp_tag[i]] = [inp_tag[i-1]]\\n return tag_dict\",\n \"def BTagHighLevelAugmenterAlgCfg(ConfigFlags, JetCollection, BTagCollection, Associator, doFlipTagger=False, sequenceName=None, **options):\\n\\n options = {}\\n options['JetCollectionName'] = JetCollection.replace('Track', 'PV0Track') + 'Jets'\\n options['BTaggingCollectionName'] = BTagCollection\\n options['JetLinkName'] = options['BTaggingCollectionName'] + '.jetLink'\\n options['BTagTrackToJetAssociatorName'] = Associator\\n options['name'] = (BTagCollection + '_Augment').lower()\\n if doFlipTagger: options['FlipTagConfig'] = 'FLIP_SIGN'\\n\\n # -- create the augmentation algorithm\\n if sequenceName:\\n acc = ComponentAccumulator(sequenceName)\\n acc.addEventAlgo(Analysis__BTagHighLevelAugmenterAlg(**options), sequenceName)\\n else:\\n acc = ComponentAccumulator()\\n acc.addEventAlgo(Analysis__BTagHighLevelAugmenterAlg(**options))\\n\\n return acc\",\n \"def override(self, parent):\\n return self.__class__(Cfg._mergedicts(self, parent, True))\",\n \"def setdefault(*dicts):\\n param_complete = dict(dicts[0])\\n for d in dicts[1:]:\\n for k,v in d.items():\\n param_complete.setdefault(k, v)\\n\\n return param_complete\",\n \"def parse_tag(self, root, fmt, insert_children=True):\\n arguments = {}\\n extra_args = {}\\n children = []\\n\\n for k, val in root.attrib.iteritems():\\n k = k.lower()\\n # 'version' is currently the only supported XML attribute.\\n if k == 'version' and root.tag == 'odML':\\n continue\\n\\n # We currently do not support XML attributes.\\n self.error(\\\"Attribute not supported, ignoring '%s=%s' \\\" % (k, val), root)\\n\\n for node in root:\\n node.tag = node.tag.lower()\\n self.is_valid_argument(node.tag, fmt, root, node)\\n if node.tag in fmt.arguments_keys:\\n # this is a heuristic, but works for now\\n if node.tag in self.tags and node.tag in fmt.map_keys:\\n sub_obj = self.parse_element(node)\\n if sub_obj is not None:\\n extra_args[fmt.map(node.tag)] = sub_obj\\n children.append(sub_obj)\\n else:\\n tag = fmt.map(node.tag)\\n if tag in arguments:\\n self.warn(\\\"Element <%s> is given multiple times in \\\"\\n \\\"<%s> tag\\\" % (node.tag, root.tag), node)\\n\\n # Special handling of values;\\n curr_text = node.text.strip() if node.text else None\\n if tag == \\\"values\\\" and curr_text:\\n content = from_csv(node.text)\\n arguments[tag] = content\\n # Special handling of cardinality\\n elif tag.endswith(\\\"_cardinality\\\") and curr_text:\\n arguments[tag] = parse_cardinality(node.text)\\n else:\\n arguments[tag] = curr_text\\n else:\\n self.error(\\\"Invalid element <%s> in odML document section <%s> \\\"\\n % (node.tag, root.tag), node)\\n\\n check_args = dict(list(arguments.items()) + list(extra_args.items()))\\n self.check_mandatory_arguments(check_args, fmt, root.tag, root)\\n\\n # Instantiate the current odML object with the parsed attributes.\\n obj = fmt.create()\\n try:\\n obj = fmt.create(**arguments)\\n except Exception as exc:\\n self.error(str(exc), root)\\n\\n if insert_children:\\n for child in children:\\n obj.append(child)\\n\\n return obj\",\n \"def _update_attributes(self, parent_node: etree.ElementBase) -> None:\\r\\n ppj_bool_keys = [\\r\\n XmlAttributeName.OPTIMIZE,\\r\\n XmlAttributeName.RELEASE,\\r\\n XmlAttributeName.FINAL,\\r\\n XmlAttributeName.ANONYMIZE,\\r\\n XmlAttributeName.PACKAGE,\\r\\n XmlAttributeName.ZIP\\r\\n ]\\r\\n\\r\\n other_bool_keys = [\\r\\n XmlAttributeName.NO_RECURSE,\\r\\n XmlAttributeName.USE_IN_BUILD\\r\\n ]\\r\\n\\r\\n for node in parent_node.getiterator():\\r\\n if node.text:\\r\\n node.text = self.parse(node.text.strip())\\r\\n\\r\\n tag = node.tag.replace('{%s}' % self.ppj_root.ns, '')\\r\\n\\r\\n if tag == XmlTagName.PAPYRUS_PROJECT:\\r\\n if XmlAttributeName.GAME not in node.attrib:\\r\\n node.set(XmlAttributeName.GAME, '')\\r\\n if XmlAttributeName.FLAGS not in node.attrib:\\r\\n node.set(XmlAttributeName.FLAGS, self.options.flags_path)\\r\\n if XmlAttributeName.OUTPUT not in node.attrib:\\r\\n node.set(XmlAttributeName.OUTPUT, self.options.output_path)\\r\\n for key in ppj_bool_keys:\\r\\n if key not in node.attrib:\\r\\n node.set(key, 'False')\\r\\n\\r\\n elif tag == XmlTagName.PACKAGES:\\r\\n if XmlAttributeName.OUTPUT not in node.attrib:\\r\\n node.set(XmlAttributeName.OUTPUT, self.options.package_path)\\r\\n\\r\\n elif tag == XmlTagName.PACKAGE:\\r\\n if XmlAttributeName.NAME not in node.attrib:\\r\\n node.set(XmlAttributeName.NAME, self.project_name)\\r\\n if XmlAttributeName.ROOT_DIR not in node.attrib:\\r\\n node.set(XmlAttributeName.ROOT_DIR, self.project_path)\\r\\n\\r\\n elif tag in (XmlTagName.FOLDER, XmlTagName.INCLUDE, XmlTagName.MATCH):\\r\\n if XmlAttributeName.NO_RECURSE not in node.attrib:\\r\\n node.set(XmlAttributeName.NO_RECURSE, 'False')\\r\\n if tag in (XmlTagName.INCLUDE, XmlTagName.MATCH):\\r\\n if XmlAttributeName.PATH not in node.attrib:\\r\\n node.set(XmlAttributeName.PATH, '')\\r\\n if tag == XmlTagName.MATCH:\\r\\n if XmlAttributeName.IN not in node.attrib:\\r\\n node.set(XmlAttributeName.IN, os.curdir)\\r\\n if XmlAttributeName.EXCLUDE not in node.attrib:\\r\\n node.set(XmlAttributeName.EXCLUDE, '')\\r\\n\\r\\n elif tag == XmlTagName.ZIP_FILES:\\r\\n if XmlAttributeName.OUTPUT not in node.attrib:\\r\\n node.set(XmlAttributeName.OUTPUT, self.options.zip_output_path)\\r\\n\\r\\n elif tag == XmlTagName.ZIP_FILE:\\r\\n if XmlAttributeName.NAME not in node.attrib:\\r\\n node.set(XmlAttributeName.NAME, self.project_name)\\r\\n if XmlAttributeName.ROOT_DIR not in node.attrib:\\r\\n node.set(XmlAttributeName.ROOT_DIR, self.project_path)\\r\\n if XmlAttributeName.COMPRESSION not in node.attrib:\\r\\n node.set(XmlAttributeName.COMPRESSION, 'deflate')\\r\\n else:\\r\\n node.set(XmlAttributeName.COMPRESSION, node.get(XmlAttributeName.COMPRESSION).casefold())\\r\\n\\r\\n elif tag in (XmlTagName.PRE_BUILD_EVENT, XmlTagName.POST_BUILD_EVENT,\\r\\n XmlTagName.PRE_IMPORT_EVENT, XmlTagName.POST_IMPORT_EVENT):\\r\\n if XmlAttributeName.DESCRIPTION not in node.attrib:\\r\\n node.set(XmlAttributeName.DESCRIPTION, '')\\r\\n if XmlAttributeName.USE_IN_BUILD not in node.attrib:\\r\\n node.set(XmlAttributeName.USE_IN_BUILD, 'True')\\r\\n\\r\\n # parse values\\r\\n for key, value in node.attrib.items():\\r\\n value = value.casefold() in ('true', '1') if key in ppj_bool_keys + other_bool_keys else self.parse(value)\\r\\n node.set(key, str(value))\",\n \"def setupWidgets(self, parentObject, \\n\\t\\tforceCategory=None, \\n\\t\\tinherit=None, \\n\\t\\tstoreProperties=True, \\n\\t\\tupdateOnly=False):\\n\\t\\tif forceCategory is not None:\\n\\t\\t\\tcategory = forceCategory\\n\\n\\t\\tif updateOnly:\\n\\t\\t\\tstoreProperties = False\\n\\n\\t\\tfor widget in parentObject.findChildren(QtWidgets.QWidget):\\n\\n\\t\\t\\t# Enable expansion of custom rollout group box controls...\\n\\t\\t\\tif widget.property('expandable'):\\n\\t\\t\\t\\tif isinstance(widget, QtWidgets.QGroupBox):\\n\\t\\t\\t\\t\\twidget.setCheckable(True)\\n\\t\\t\\t\\t\\t# widget.setChecked(expand)\\n\\t\\t\\t\\t\\twidget.setFixedHeight(widget.sizeHint().height())\\n\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\twidget.toggled.connect(self.toggleExpandGroup)\\n\\n\\t\\t\\t# Set up handler for push buttons...\\n\\t\\t\\tif widget.property('exec'):\\n\\t\\t\\t\\tif isinstance(widget, QtWidgets.QPushButton):\\n\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\twidget.clicked.connect(self.execPushButton)\\n\\n\\t\\t\\t# Set up handlers for different widget types & apply values\\n\\t\\t\\tattr = widget.property('xmlTag')\\n\\t\\t\\tif attr:\\n\\t\\t\\t\\tself.base_widget = widget.objectName()\\n\\t\\t\\t\\tif forceCategory is None:\\n\\t\\t\\t\\t\\tcategory = self.findCategory(widget)\\n\\t\\t\\t\\tif category:\\n\\t\\t\\t\\t\\twidget.setProperty('xmlCategory', category)\\n\\n\\t\\t\\t\\t\\tif inherit:\\n\\t\\t\\t\\t\\t\\tvalue = self.prefs.get_attr(category, attr)\\n\\t\\t\\t\\t\\t\\t# if value == \\\"\\\":\\n\\t\\t\\t\\t\\t\\tif value is None:\\n\\t\\t\\t\\t\\t\\t\\tvalue = inherit.get_attr(category, attr)\\n\\n\\t\\t\\t\\t\\t\\t\\t# widget.setProperty('xmlTag', None)\\n\\t\\t\\t\\t\\t\\t\\twidget.setProperty('inheritedValue', True)\\n\\t\\t\\t\\t\\t\\t\\tif widget.toolTip():\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.setProperty('oldToolTip', widget.toolTip())\\n\\t\\t\\t\\t\\t\\t\\twidget.setToolTip(\\\"This value is being inherited. Change the value to override the inherited value.\\\")\\n\\n\\t\\t\\t\\t\\t\\t\\t# Apply pop-up menu to remove override - can't get to work here\\n\\t\\t\\t\\t\\t\\t\\t# self.addContextMenu(widget, \\\"Remove override\\\", self.remove_overrides)\\n\\t\\t\\t\\t\\t\\t\\t# widget.setContextMenuPolicy(QtCore.Qt.ActionsContextMenu)\\n\\n\\t\\t\\t\\t\\t\\t\\t# actionRemoveOverride = QtWidgets.QAction(\\\"Remove override\\\", None)\\n\\t\\t\\t\\t\\t\\t\\t# actionRemoveOverride.triggered.connect(self.remove_overrides)\\n\\t\\t\\t\\t\\t\\t\\t# widget.addAction(actionRemoveOverride)\\n\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\ttry:\\n\\t\\t\\t\\t\\t\\t\\tvalue = self.prefs.get_attr(category, attr)\\n\\t\\t\\t\\t\\t\\texcept AttributeError:\\n\\t\\t\\t\\t\\t\\t\\tvalue = None\\n\\n\\t\\t\\t\\t\\t# Sliders...\\n\\t\\t\\t\\t\\tif isinstance(widget, QtWidgets.QSlider):\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\twidget.setValue(int(value))\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, widget.value())\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\twidget.valueChanged.connect(self.storeSliderValue)\\n\\n\\t\\t\\t\\t\\t# Spin boxes...\\n\\t\\t\\t\\t\\tif isinstance(widget, QtWidgets.QSpinBox):\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\twidget.setValue(int(value))\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, widget.value())\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\twidget.valueChanged.connect(self.storeSpinBoxValue)\\n\\n\\t\\t\\t\\t\\t# Double spin boxes...\\n\\t\\t\\t\\t\\telif isinstance(widget, QtWidgets.QDoubleSpinBox):\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\twidget.setValue(float(value))\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, widget.value())\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\twidget.valueChanged.connect(self.storeSpinBoxValue)\\n\\n\\t\\t\\t\\t\\t# Line edits...\\n\\t\\t\\t\\t\\telif isinstance(widget, QtWidgets.QLineEdit):\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\twidget.setText(value)\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, widget.text())\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\t# widget.textEdited.connect(self.storeLineEditValue)\\n\\t\\t\\t\\t\\t\\t\\twidget.textChanged.connect(self.storeLineEditValue)\\n\\n\\t\\t\\t\\t\\t# Plain text edits...\\n\\t\\t\\t\\t\\telif isinstance(widget, QtWidgets.QPlainTextEdit):\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\twidget.setPlainText(value)\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, widget.toPlainText())\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\twidget.textChanged.connect(self.storeTextEditValue)\\n\\n\\t\\t\\t\\t\\t# Check boxes...\\n\\t\\t\\t\\t\\telif isinstance(widget, QtWidgets.QCheckBox):\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\tif value == True:\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.setCheckState(QtCore.Qt.Checked)\\n\\t\\t\\t\\t\\t\\t\\telif value == False:\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.setCheckState(QtCore.Qt.Unchecked)\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, self.getCheckBoxValue(widget))\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\twidget.toggled.connect(self.storeCheckBoxValue)\\n\\n\\t\\t\\t\\t\\t# Radio buttons...\\n\\t\\t\\t\\t\\telif isinstance(widget, QtWidgets.QRadioButton):\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\twidget.setAutoExclusive(False)\\n\\t\\t\\t\\t\\t\\t\\tif value == widget.text():\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.setChecked(True)\\n\\t\\t\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.setChecked(False)\\n\\t\\t\\t\\t\\t\\t\\twidget.setAutoExclusive(True)\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\tif widget.isChecked():\\n\\t\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, widget.text())\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\twidget.toggled.connect(self.storeRadioButtonValue)\\n\\n\\t\\t\\t\\t\\t# Combo boxes...\\n\\t\\t\\t\\t\\telif isinstance(widget, QtWidgets.QComboBox):\\n\\t\\t\\t\\t\\t\\t# Add items if history is enabled\\n\\t\\t\\t\\t\\t\\tif widget.property('storeHistory'):\\n\\t\\t\\t\\t\\t\\t\\twidget.setInsertPolicy(widget.InsertAtTop)\\n\\t\\t\\t\\t\\t\\t\\thistory = self.prefs.get_attr(category, \\\"%s_history\\\" % attr)\\n\\t\\t\\t\\t\\t\\t\\tif history:\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.addItems(history)\\n\\t\\t\\t\\t\\t\\t# Add/set current item\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\tif widget.findText(value) == -1:\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.insertItem(0, value)\\n\\t\\t\\t\\t\\t\\t\\twidget.setCurrentIndex(widget.findText(value))\\n\\t\\t\\t\\t\\t\\t# Store value in external file\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, widget.currentText())\\n\\t\\t\\t\\t\\t\\t# Connect signals & slots\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\t# widget.currentTextChanged.connect(self.storeComboBoxValue)\\n\\t\\t\\t\\t\\t\\t\\tif widget.isEditable():\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.editTextChanged.connect(self.storeComboBoxValue)\\n\\t\\t\\t\\t\\t\\t\\telse:\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.currentIndexChanged.connect(self.storeComboBoxValue)\\n\\n\\t\\t\\t\\t\\t# List widgets...\\n\\t\\t\\t\\t\\t# TODO: Add option to remove duplicate entries\\n\\t\\t\\t\\t\\telif isinstance(widget, QtWidgets.QListWidget):\\n\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\t# print(value)\\n\\t\\t\\t\\t\\t\\t\\twidget.clear()\\n\\t\\t\\t\\t\\t\\t\\twidget.addItems(value)\\n\\t\\t\\t\\t\\t\\tif storeProperties:\\n\\t\\t\\t\\t\\t\\t\\titems = []\\n\\t\\t\\t\\t\\t\\t\\tfor i in range(widget.count()):\\n\\t\\t\\t\\t\\t\\t\\t\\titems.append(widget.item(i).text())\\n\\t\\t\\t\\t\\t\\t\\tself.storeValue(category, attr, items)\\n\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\twidget.itemChanged.connect(self.storeListWidgetValues)\\n\\n\\t\\t\\t\\t\\t# Enable colour chooser buttons...\\n\\t\\t\\t\\t\\telif isinstance(widget, QtWidgets.QToolButton):\\n\\t\\t\\t\\t\\t\\tif widget.property('colorChooser'):\\n\\t\\t\\t\\t\\t\\t\\tif value is not None:\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.setStyleSheet(\\\"QWidget { background-color: %s }\\\" % value)\\n\\t\\t\\t\\t\\t\\t\\t# if storeProperties:\\n\\t\\t\\t\\t\\t\\t\\t# \\tself.storeValue(category, attr, widget.currentText())\\n\\t\\t\\t\\t\\t\\t\\tif not updateOnly:\\n\\t\\t\\t\\t\\t\\t\\t\\twidget.clicked.connect(self.storeColor)\",\n \"def set_default_position(self):\\n self.set_joint('elbow', 0, radians=False)\\n self.set_joint('shoulder', 150, radians=False)\\n for joint in self.chain.joints:\\n self.set_joint(joint, self.chain.joints[joint]['default_value'], radians=True)\",\n \"def apply_defaults(self, commands, args):\\r\\n\\r\\n args = args[:]\\r\\n\\r\\n if RcFile._DISABLE_PANTS_RC_OPTION in args:\\r\\n return args\\r\\n\\r\\n config = Config.create_parser()\\r\\n read_from = config.read(self.paths)\\r\\n if not read_from:\\r\\n log.debug('no rcfile found')\\r\\n return args\\r\\n\\r\\n log.debug('using rcfiles: %s to modify args' % ','.join(read_from))\\r\\n\\r\\n def get_rcopts(command, key):\\r\\n return config.get(command, key).split() if config.has_option(command, key) else []\\r\\n\\r\\n commands = list(commands)\\r\\n if self.process_default:\\r\\n commands.insert(0, Config.DEFAULT_SECTION)\\r\\n\\r\\n for cmd in commands:\\r\\n opts = get_rcopts(cmd, 'options')\\r\\n args = (opts + args) if self.default_prepend else (args + opts)\\r\\n args = get_rcopts(cmd, 'prepend-options') + args + get_rcopts(cmd, 'append-options')\\r\\n return args\",\n \"def initDefaults(self):\\n return _libsbml.Species_initDefaults(self)\",\n \"def initDefaults(self):\\n return _libsbml.ReferenceGlyph_initDefaults(self)\",\n \"def visit_cname_place(self, node, children):\\n # If a value is supplied it will be a single time list, so extract with [0]\\n # If no value is supplied for an optional item, default must also be a single item list [default_value]\\n w = children.results.get('wrap')\\n wrap_value = 1 if not w else w[0]['wrap']\\n cplace = {'cname': children.results['name'][0], # Required component\\n 'dir': children.results.get('dir', [1])[0], # many optional components with default values\\n 'bend': children.results.get('bend', [1])[0],\\n 'notch': children.results.get('notch', [0])[0],\\n 'wrap': wrap_value,\\n }\\n return cplace\",\n \"def initDefaults(self):\\n return _libsbml.SpeciesReferenceGlyph_initDefaults(self)\",\n \"def default(self, block, name):\\r\\n if name in self.inheritable_names and block.parent is not None:\\r\\n parent = block.get_parent()\\r\\n if parent:\\r\\n return getattr(parent, name)\\r\\n super(InheritingFieldData, self).default(block, name)\",\n \"def parse_defaults(self, stmt):\\r\\n spec_type = stmt['spec_type']\\r\\n if spec_type in self._defaults:\\r\\n raise ValueError('More than one default for {}'.format(stmt['spec_type']))\\r\\n self._defaults[spec_type] = Default(spec_type, stmt)\\r\\n return None\",\n \"def add_parent_attributes(self):\\n if len(self.parent_attributes) == 0:\\n return\\n dest = self.parent.attributes\\n source = self.parent_attributes\\n changes = {}\\n self.merge_attribute_defs(dest, source, changes)\\n for aid, value in changes.iteritems():\\n# self.parent.h5node.attrs[aid] = value\\n # may need modifying for MATLAB\\n #- if self.path not in self.file.file_pointer:\\n if self.file.get_node(self.path, abort=False) is None:\\n # create parent node since it does not exist\\n print \\\"trying to set parent attributes on non-registered parent node:\\\"\\n print \\\"Non-registered parent node is: '%s'\\\", self.path\\n traceback.print_stack()\\n sys.exit(1)\\n #- self.file.file_pointer[self.path].attrs[aid] = value\\n self.file.set_attribute(self.path, aid, value)\"\n]"},"negative_scores":{"kind":"list like","value":["0.5848242","0.5620025","0.539464","0.5353507","0.53439975","0.5028083","0.49867433","0.49008948","0.48286456","0.46795782","0.46378452","0.4624426","0.46004072","0.45709348","0.45590082","0.4541855","0.44945678","0.44693825","0.4469151","0.44664097","0.4446841","0.44466433","0.4425318","0.44154054","0.43990022","0.43780386","0.43699786","0.43697378","0.43675762","0.433812","0.43333912","0.43150324","0.43061092","0.4289223","0.42846638","0.42783713","0.42708305","0.42573756","0.42514697","0.4234598","0.42239898","0.42047566","0.4202317","0.42011642","0.41899762","0.4187202","0.41785905","0.41660833","0.41545922","0.41498905","0.41498673","0.41474795","0.41452122","0.41441023","0.41310993","0.41154274","0.4113048","0.41113138","0.41095382","0.4108342","0.41076756","0.4101494","0.40987903","0.40852386","0.40847215","0.40785283","0.40772653","0.4073388","0.40686715","0.40663525","0.40595818","0.40564436","0.4050119","0.40484133","0.4030075","0.40280223","0.4025741","0.40252462","0.40252462","0.40114743","0.40079823","0.40078807","0.40066555","0.40065372","0.4003564","0.40024275","0.3998931","0.39969802","0.3996713","0.3995274","0.3992858","0.3991767","0.3991018","0.398954","0.39874497","0.3982112","0.39811853","0.39791167","0.39787734","0.39771158"],"string":"[\n \"0.5848242\",\n \"0.5620025\",\n \"0.539464\",\n \"0.5353507\",\n \"0.53439975\",\n \"0.5028083\",\n \"0.49867433\",\n \"0.49008948\",\n \"0.48286456\",\n \"0.46795782\",\n \"0.46378452\",\n \"0.4624426\",\n \"0.46004072\",\n \"0.45709348\",\n \"0.45590082\",\n \"0.4541855\",\n \"0.44945678\",\n \"0.44693825\",\n \"0.4469151\",\n \"0.44664097\",\n \"0.4446841\",\n \"0.44466433\",\n \"0.4425318\",\n \"0.44154054\",\n \"0.43990022\",\n \"0.43780386\",\n \"0.43699786\",\n \"0.43697378\",\n \"0.43675762\",\n \"0.433812\",\n \"0.43333912\",\n \"0.43150324\",\n \"0.43061092\",\n \"0.4289223\",\n \"0.42846638\",\n \"0.42783713\",\n \"0.42708305\",\n \"0.42573756\",\n \"0.42514697\",\n \"0.4234598\",\n \"0.42239898\",\n \"0.42047566\",\n \"0.4202317\",\n \"0.42011642\",\n \"0.41899762\",\n \"0.4187202\",\n \"0.41785905\",\n \"0.41660833\",\n \"0.41545922\",\n \"0.41498905\",\n \"0.41498673\",\n \"0.41474795\",\n \"0.41452122\",\n \"0.41441023\",\n \"0.41310993\",\n \"0.41154274\",\n \"0.4113048\",\n \"0.41113138\",\n \"0.41095382\",\n \"0.4108342\",\n \"0.41076756\",\n \"0.4101494\",\n \"0.40987903\",\n \"0.40852386\",\n \"0.40847215\",\n \"0.40785283\",\n \"0.40772653\",\n \"0.4073388\",\n \"0.40686715\",\n \"0.40663525\",\n \"0.40595818\",\n \"0.40564436\",\n \"0.4050119\",\n \"0.40484133\",\n \"0.4030075\",\n \"0.40280223\",\n \"0.4025741\",\n \"0.40252462\",\n \"0.40252462\",\n \"0.40114743\",\n \"0.40079823\",\n \"0.40078807\",\n \"0.40066555\",\n \"0.40065372\",\n \"0.4003564\",\n \"0.40024275\",\n \"0.3998931\",\n \"0.39969802\",\n \"0.3996713\",\n \"0.3995274\",\n \"0.3992858\",\n \"0.3991767\",\n \"0.3991018\",\n \"0.398954\",\n \"0.39874497\",\n \"0.3982112\",\n \"0.39811853\",\n \"0.39791167\",\n \"0.39787734\",\n \"0.39771158\"\n]"},"document_score":{"kind":"string","value":"0.43321195"},"document_rank":{"kind":"string","value":"31"}}},{"rowIdx":8570,"cells":{"query":{"kind":"string","value":"Moves the specified tag namespace to the specified compartment within the same tenancy. To move the tag namespace, you must have the manage tagnamespaces permission on both compartments. For more information about IAM policies, see `Details for IAM`__. Moving a tag namespace moves all the tag key definitions contained in the tag namespace."},"document":{"kind":"string","value":"def change_tag_namespace_compartment(self, tag_namespace_id, change_tag_namespace_compartment_detail, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}/actions/changeCompartment\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"change_tag_namespace_compartment got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=change_tag_namespace_compartment_detail)\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=change_tag_namespace_compartment_detail)"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def remove_namespace(self, doc, namespace):\r\n ns = u'{%s}' % namespace\r\n nsl = len(ns)\r\n for elem in doc.getiterator():\r\n if elem.tag.startswith(ns):\r\n elem.tag = elem.tag[nsl:]\r\n else:\r\n pass","def remove_namespace(doc, namespace=u\"{http://www.EcoInvent.org/EcoSpold02}\"):\n ns = u'{}'.format(namespace)\n nsl = len(ns)\n for elem in doc.getiterator():\n if elem.tag.startswith(ns):\n elem.tag = elem.tag[nsl:]","def update():\n for namespace in metadata.get_namespaces():\n logging.info('Switching namespace: \\'%s\\'', namespace)\n namespace_manager.set_namespace(namespace)\n update_per_namespace()\n\n namespace_manager.set_namespace('')\n return ('', 204)","def ReplaceNamespace(self, request, global_params=None):\n config = self.GetMethodConfig('ReplaceNamespace')\n return self._RunMethod(\n config, request, global_params=global_params)","def ReplaceNamespace(self, request, global_params=None):\n config = self.GetMethodConfig('ReplaceNamespace')\n return self._RunMethod(\n config, request, global_params=global_params)","def move_to(i3: i3ipc.Connection, workspace: int):\n i3.command(f\"move container to workspace number {workspace}\")","async def remove_namespace(self, namespace: str) -> Any:\n if namespace == self.get_namespace(): # if it belongs to this app's namespace\n raise ValueError(\"Cannot remove namespace with the same name as operating namespace\")\n\n return await self.AD.state.remove_namespace(namespace)","def clean_up_namespaces(node, namespace=None):\n if namespace is not None:\n Namespaces.delete_namespace(node, namespace)\n return\n\n namespace_copy = deepcopy(Namespaces.__namespaces)\n for namespace_name in namespace_copy:\n Namespaces.delete_namespace(node, namespace_name)","def update_tag_namespace(self, tag_namespace_id, update_tag_namespace_details, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}\"\n method = \"PUT\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"update_tag_namespace got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_namespace_details,\n response_type=\"TagNamespace\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_namespace_details,\n response_type=\"TagNamespace\")","def fix(self):\n for namespace in pm.listNamespaces():\n for elem in namespace.ls():\n elem.rename(elem.split(\":\")[-1])\n namespace.remove()\n\n self.run()","def removeNamespace(self, *args):\n return _libsbml.XMLToken_removeNamespace(self, *args)","def set_target_namespace(self, namespace):\n # do shit\n self.target_namespace = namespace.strip(\":\")","def test_replace_namespaced_deployment_config(self):\n pass","def sync_namespace(alias, reg_code, authToken, space=None, action=None):\n if space == None:\n action = 'get'\n print(\" ACTION: GET\")\n elif action == None:\n if 'aeskey' not in space:\n print(\"Space not encrypted\")\n quit()\n action = 'update'\n print(\" ACTION: UPDATE\")\n elif action == 'delete':\n print(\" ACTION: DELETE\")\n url = endpoint('namespace')\n headers={'authorizationToken': authToken}\n data = json.dumps({'action': action, 'alias': alias, 'reg_code': reg_code, 'namespace': space})\n payload_size = sys.getsizeof(data)\n print(\" Size of payload is: %s\" % (convert_size(payload_size)))\n print(\" Max payload is: %s\" % (convert_size(max_payload_size)))\n if payload_size >= max_payload_size:\n print(\" OVER MAX PAYLOAD: %s\" % (convert_size(max_payload_size)))\n quit()\n r = requests.post(url, headers=headers, data=data) \n print(\" Request made\")\n if r.status_code == 403:\n print(\" Invalid registration code, exiting\")\n quit()\n elif r.status_code == 406:\n print(\" Namespace mismatch\")\n quit()\n else:\n print(\" └──statusCode:\" + str(r.status_code) )\n return r","def delete_namespace(node, namespace):\n cmd_timeout = 5\n cmd = f\"ip netns delete {namespace}\"\n (ret_code, _, delete_errmsg) = \\\n exec_cmd(node, cmd, timeout=cmd_timeout, sudo=True)\n if ret_code != 0:\n cmd = f\"ip netns list {namespace}\"\n (stdout, _) = \\\n exec_cmd_no_error(node, cmd, timeout=cmd_timeout, sudo=True)\n if stdout == namespace:\n raise RuntimeError(f\"Could not delete namespace \"\n f\"({namespace}): {delete_errmsg}\")\n try:\n Namespaces.__namespaces.remove(namespace)\n except ValueError:\n pass","def test_replace_net_namespace(self):\n pass","def test_replace_namespaced_role(self):\n pass","def create_tag_namespace(self, create_tag_namespace_details, **kwargs):\n resource_path = \"/tagNamespaces\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_tag_namespace got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_tag_namespace_details,\n response_type=\"TagNamespace\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_tag_namespace_details,\n response_type=\"TagNamespace\")","def removeNamespace(self, *args):\n return _libsbml.SBMLNamespaces_removeNamespace(self, *args)","def set_namespace(self, namespace: str) -> None:\n self._namespace = namespace","def delete_tag_namespace(self, tag_namespace_id, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}\"\n method = \"DELETE\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"if_match\",\n \"opc_request_id\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"delete_tag_namespace got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"if-match\": kwargs.get(\"if_match\", missing),\n \"opc-request-id\": kwargs.get(\"opc_request_id\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params)\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params)","def move_objects(self, src_s3_prefix_path, destination_s3_prefix_path):\n src_bucket_name, src_prefix = S3Util.get_bucket_and_key(src_s3_prefix_path)\n destination_bucket_name, destination_prefix = S3Util.get_bucket_and_key(destination_s3_prefix_path)\n\n src_bucket = self.s3_resource.Bucket(src_bucket_name)\n destination_bucket = self.s3_resource.Bucket(destination_bucket_name)\n\n for obj in src_bucket.objects.filter(Prefix=src_prefix):\n source_obj = self._object_summary_to_copy_source(obj)\n\n # replace the prefix\n new_key = obj.key.replace(src_prefix, destination_prefix)\n destination_bucket.copy(CopySource=source_obj, Key=new_key)\n obj.delete()","def replace_namespaced_namespace(self, body, name, **kwargs):\n kwargs['_return_http_data_only'] = True\n if kwargs.get('callback'):\n return self.replace_namespaced_namespace_with_http_info(body, name, **kwargs)\n else:\n (data) = self.replace_namespaced_namespace_with_http_info(body, name, **kwargs)\n return data","def test_delete_net_namespace(self):\n pass","def move_tag_seq(words, seq, dest, punc=None):\n if len(seq) > len(words):\n return None\n seq_start = index_tag_seq(words, seq)\n if seq_start > -1:\n move_words = words[seq_start:seq_start+len(seq)]\n words = words[:seq_start] + words[seq_start+len(seq):]\n if dest == 'start':\n words = move_words + words\n if dest == 'end':\n if punc is not None:\n words.append(punc)\n words += move_words\n return words\n return None","def test_delete_namespaced_deployment_config(self):\n pass","def namespace_delete(cursor, namespace_id):\n haystack = (namespace_id,)\n query = \"DELETE FROM namespaces WHERE _id=?\"\n try:\n cursor.execute(query, haystack)\n except Exception as e:\n on_error(e)\n else:\n cursor.connection.commit()\n raise Return((True, None))","def move(owner_id=None, target_album_id=None, photo_id=None):\n params = {\n 'owner_id': owner_id,\n 'target_album_id': target_album_id,\n 'photo_id': photo_id\n }\n result = call('photos.move', **params)\n return parse_response(result)","def swap_cnames(profile, source_environment, destination_environment):\n client = boto3client.get(\"elasticbeanstalk\", profile)\n params = {}\n params[\"SourceEnvironmentName\"] = source_environment\n params[\"DestinationEnvironmentName\"] = destination_environment\n return client.swap_environment_cnames(**params)","def post_namespace_delete(self, resource_id, resource_dict):\n pass","def replace_resource(self, namespace: \"str\" = None):\n names = [\n \"replace_namespaced_csistorage_capacity\",\n \"replace_csistorage_capacity\",\n ]\n\n _kube_api.execute(\n action=\"replace\",\n resource=self,\n names=names,\n namespace=namespace,\n api_client=None,\n api_args={\"body\": self.to_dict(), \"name\": self.metadata.name},\n )","def replace_namespaced_net_namespace(self, body, name, **kwargs):\n\n all_params = ['body', 'name', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method replace_namespaced_net_namespace\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `replace_namespaced_net_namespace`\")\n # verify the required parameter 'name' is set\n if ('name' not in params) or (params['name'] is None):\n raise ValueError(\"Missing the required parameter `name` when calling `replace_namespaced_net_namespace`\")\n\n resource_path = '/oapi/v1/netnamespaces/{name}'.replace('{format}', 'json')\n path_params = {}\n if 'name' in params:\n path_params['name'] = params['name']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'PUT',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1NetNamespace',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def move(name, other, newname=None):","def namespace(*args, absoluteName: bool=True, addNamespace: AnyStr=\"\", collapseAncestors:\n AnyStr=\"\", deleteNamespaceContent: bool=True, exists: Union[AnyStr, bool]=\"\",\n force: bool=True, isRootNamespace: Union[AnyStr, bool]=\"\",\n mergeNamespaceWithOther: AnyStr=\"\", mergeNamespaceWithParent: bool=True,\n mergeNamespaceWithRoot: bool=True, moveNamespace: List[AnyStr, AnyStr]=None,\n parent: AnyStr=\"\", recurse: bool=True, relativeNames: bool=True, removeNamespace:\n AnyStr=\"\", rename: List[AnyStr, AnyStr]=None, setNamespace: AnyStr=\"\",\n validateName: AnyStr=\"\", q=True, query=True, **kwargs)->Union[AnyStr, Any]:\n pass","def test_create_deployment_config_rollback_for_all_namespaces(self):\n pass","def replace_widget(container, tag, widget) -> None:\n try:\n container[tag].destroy()\n except KeyError:\n pass\n container[tag] = widget","def remove(self, camera, namespace='*'):\n with self.lock:\n if namespace == '*':\n for cur_namespace in self.camera_namespaces:\n self.camera_namespaces[cur_namespace].remove(camera)\n else:\n self.camera_namespaces[namespace].remove(camera)","def remove(self, *args):\n return _libsbml.XMLNamespaces_remove(self, *args)","def test_unidirectional_namespace_bucket_replication(\n self,\n awscli_pod_session,\n mcg_obj_session,\n cld_mgr,\n bucket_factory,\n source_bucketclass,\n target_bucketclass,\n test_directory_setup,\n ):\n target_bucket_name = bucket_factory(bucketclass=target_bucketclass)[0].name\n\n replication_policy = (\"basic-replication-rule\", target_bucket_name, None)\n source_bucket = bucket_factory(\n 1, bucketclass=source_bucketclass, replication_policy=replication_policy\n )[0]\n source_bucket_name = source_bucket.name\n source_bucket_uls_name = source_bucket.bucketclass.namespacestores[0].uls_name\n\n namespacestore_aws_s3_creds = {\n \"access_key_id\": cld_mgr.aws_client.access_key,\n \"access_key\": cld_mgr.aws_client.secret_key,\n \"endpoint\": constants.AWS_S3_ENDPOINT,\n \"region\": source_bucketclass[\"namespace_policy_dict\"][\n \"namespacestore_dict\"\n ][\"aws\"][0][1],\n }\n\n written_random_objects = write_random_test_objects_to_bucket(\n awscli_pod_session,\n source_bucket_uls_name,\n test_directory_setup.origin_dir,\n amount=5,\n s3_creds=namespacestore_aws_s3_creds,\n )\n\n listed_obejcts = mcg_obj_session.s3_list_all_objects_in_bucket(\n source_bucket_name\n )\n\n compare_bucket_object_list(\n mcg_obj_session, source_bucket_name, target_bucket_name\n )\n\n assert set(written_random_objects) == {\n obj.key for obj in listed_obejcts\n }, \"Some of the uploaded objects are missing\"","def update_tag(tag):\n remove_tag(tag)\n add_tag(tag)","def list_tag_namespaces(self, compartment_id, **kwargs):\n resource_path = \"/tagNamespaces\"\n method = \"GET\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"page\",\n \"limit\",\n \"include_subcompartments\",\n \"lifecycle_state\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"list_tag_namespaces got unknown kwargs: {!r}\".format(extra_kwargs))\n\n if 'lifecycle_state' in kwargs:\n lifecycle_state_allowed_values = [\"ACTIVE\", \"INACTIVE\", \"DELETING\", \"DELETED\"]\n if kwargs['lifecycle_state'] not in lifecycle_state_allowed_values:\n raise ValueError(\n \"Invalid value for `lifecycle_state`, must be one of {0}\".format(lifecycle_state_allowed_values)\n )\n\n query_params = {\n \"compartmentId\": compartment_id,\n \"page\": kwargs.get(\"page\", missing),\n \"limit\": kwargs.get(\"limit\", missing),\n \"includeSubcompartments\": kwargs.get(\"include_subcompartments\", missing),\n \"lifecycleState\": kwargs.get(\"lifecycle_state\", missing)\n }\n query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None}\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n query_params=query_params,\n header_params=header_params,\n response_type=\"list[TagNamespaceSummary]\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n query_params=query_params,\n header_params=header_params,\n response_type=\"list[TagNamespaceSummary]\")","def get_namespace(self, namespace, lowercase=True, trim_namespace=True):\n\t\treturn self.get_namespace_view(namespace, lowercase, trim_namespace).copy()","async def removetags(self, ctx, tag=None):\r\n\t\tTag = self.settings.ServerConfig(ctx.guild.id, 'Tags')\r\n\t\tif not tag in Tag:\r\n\t\t\treturn await ctx.send('Can\\'t find Tag: '.format(tag))\t\r\n\r\n\t\tdel Tag[tag]\r\n\t\tself.settings.ServerConfig(ctx.guild.id, 'Tags', Tag)\r\n\r\n\t\tawait ctx.send('Removed Tag: '.format(tag))","def test_replace_namespaced_template(self):\n pass","def move_object(self, bucket_name, src_object_name, dst_object_name, no_overwrite=False):\n\n return h3lib.move_object(self._handle, bucket_name, src_object_name, dst_object_name, no_overwrite, self._user_id)","def test_replace_namespaced_role_binding(self):\n pass","def test_create_namespaced_deployment_config_rollback(self):\n pass","def updateNamespace(self):\n import addict\n self.namespace['config'] = addict.Dict(self.namespace['config'])","def namespace(self, namespace: str):\n\n self._namespace = namespace","def delete_tag(tag, directory=None):\n execute_command('git tag -d {0}'.format(tag), shell=True, cwd=directory)","def move_element(self,n_a,n_b):\n self.element_array.insert(n_b,self.element_array.pop(n_a))","def test_patch_namespaced_deployment_config(self):\n pass","def move_node(self, job):\n transfer = Transfer(job.jobInfo)\n target = transfer.target\n direction = transfer.direction\n result = None\n # Check uris\n check_uri(target, self.sm, shouldExist = True)\n checks = check_uri(direction, self.sm, shouldExist = False)\n null = direction.endswith(NULL)\n # Retrieve existing record\n node = self.sm.get_node(target)[0]['node']\n node = self.nf.get_node(node)\n # Check whether endpoint is reserved URI\n if null: self.nm.delete_node(target)\n if direction.endswith(AUTO): \n direction = generate_uri(direction)\n result = {'destination': direction}\n if not(null):\n # Check if endpoint is a container\n if checks['exists'] and checks['container']: direction += target[target.rfind('/'):]\n # Change identifier\n node.set_uri(direction)\n # Update db\n self.sm.update_node(target, direction, node.tostring())\n # Check if target is a container\n if isinstance(node, ContainerNode):\n # Move children\n for child in self.sm.get_children(target):\n node = self.nf.get_node(self.sm.get_node(child)[0]['node'])\n if null:\n self.nm.delete_node(node.uri)\n else:\n new_uri = node.uri.replace(target, direction)\n node.set_uri(new_uri)\n self.sm.update_node(child, new_uri, node.tostring())\n return result","def setElementNamespace(self, *args):\n return _libsbml.ASTBasePlugin_setElementNamespace(self, *args)","def destroyContainer(tag): #@NoSelf","def test_remove_defined_tag(self, test, object_storage):\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\n session_factory = test.oci_session_factory()\n policy = test.load_policy(\n {\n \"name\": \"bucket-remove-tag\",\n \"resource\": \"oci.bucket\",\n \"filters\": [\n {\"type\": \"value\", \"key\": \"name\", \"value\": bucket_name},\n ],\n \"actions\": [\n {\n \"type\": \"remove-tag\",\n \"defined_tags\": [\"cloud-custodian-test.mark-for-resize\"],\n },\n ],\n },\n session_factory=session_factory,\n )\n policy.run()\n resource = self._fetch_bucket_validation_data(\n policy.resource_manager, namespace_name, bucket_name\n )\n test.assertEqual(resource[\"name\"], bucket_name)\n test.assertEqual(self.get_defined_tag_value(resource[\"defined_tags\"]), None)","async def save_namespace(self, **kwargs) -> None:\n namespace = self._get_namespace(**kwargs)\n await self.AD.state.save_namespace(namespace)","def test_update_bucket(self, test, object_storage, with_or_without_compartment):\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\n session_factory = test.oci_session_factory()\n policy = test.load_policy(\n {\n \"name\": \"add-defined-tag-to-bucket\",\n \"resource\": \"oci.bucket\",\n \"query\": [\n {\"namespace_name\": namespace_name},\n ],\n \"filters\": [\n {\"type\": \"value\", \"key\": \"name\", \"value\": bucket_name},\n ],\n \"actions\": [{\"type\": \"update\", \"defined_tags\": self.get_defined_tag(\"add_tag\")}],\n },\n session_factory=session_factory,\n )\n policy.run()\n resource = self._fetch_bucket_validation_data(\n policy.resource_manager, namespace_name, bucket_name\n )\n test.assertEqual(resource[\"name\"], bucket_name)\n test.assertEqual(self.get_defined_tag_value(resource[\"defined_tags\"]), \"true\")","def move_objects(\n source_bucket=None,\n destination_bucket=None,\n prefix=None,\n **kwargs):\n\n storage_objects = kwargs['ti'].xcom_pull(task_ids='list_files')\n\n hook = GoogleCloudStorageHook()\n\n for storage_object in storage_objects:\n destination_object = storage_object\n\n if prefix:\n destination_object = '{}/{}'.format(prefix, storage_object)\n\n hook.copy(source_bucket, storage_object, destination_bucket, destination_object)\n hook.delete(source_bucket, storage_object)","def addNamespace(self, *args):\n return _libsbml.XMLToken_addNamespace(self, *args)","def add_namespace(self, q, ns):\n if ns in self.namespaces: return self.namespaces[ns]\n self.namespaces[ns] = q\n return q","def delete_bucket_tagging(Bucket=None):\n pass","def delete_tag(filename, tag_name):\n storeapps = APP.config[\"storage\"]\n filename = filename.encode(\"utf-8\")\n\n try:\n application = list(nativeapps.io.ls(storeapps, r\".*\" + filename + \"$\"))[0]\n meta_path = os.path.join(os.path.dirname(application), \"metadata.json\")\n metadata = json.loads(nativeapps.io.readfile(meta_path))\n tags = metadata.get(\"tags\", [])\n if tag_name in tags:\n tags.remove(tag_name)\n metadata[\"tags\"] = tags\n nativeapps.io.writefile(meta_path, json.dumps(metadata))\n except IndexError:\n return \"Unknown application: %s\" % (application), 404\n\n return \"removed\", 200","def setNamespaces(self, *args):\n return _libsbml.XMLToken_setNamespaces(self, *args)","def delete_namespace_content(context, namespace_id, session):\n count = 0\n query = (session.query(models.MetadefTag).filter_by(\n namespace_id=namespace_id))\n count = query.delete(synchronize_session='fetch')\n return count","def tag_rename(self, item_id, old_tag, new_tag, **params):\n\n self.queue('tag_rename', item_id=item_id,\n old_tag=old_tag, new_tag=new_tag, **params)","def removePackageNamespace(self, *args):\n return _libsbml.SBMLNamespaces_removePackageNamespace(self, *args)","def move_object(self, src_s3_path, destination_s3_path):\n src_bucket_name, src_key = S3Util.get_bucket_and_key(src_s3_path)\n destination_bucket_name, destination_key = S3Util.get_bucket_and_key(destination_s3_path)\n obj = self.s3_resource.ObjectSummary(src_bucket_name, src_key)\n destination_bucket = self.s3_resource.Bucket(destination_bucket_name)\n destination_bucket.copy(CopySource=self._object_summary_to_copy_source(obj), Key=destination_key)\n obj.delete()","def moveBar(self, from_, to_):\n fromBar = self.widget(from_)\n self.removeWidget(fromBar)\n self.insertWidget(to_, fromBar)","def copyNamespace(self):\n ret = libxml2mod.xmlCopyNamespace(self._o)\n if ret is None:raise treeError('xmlCopyNamespace() failed')\n __tmp = xmlNs(_obj=ret)\n return __tmp","def archive(self, namespace, archive_name, namespace_out=None, format=None):\n raise RuntimeError('Already achieved')","def move(self, target):\n if target.relto(self):\n raise error.EINVAL(target, \"cannot move path into a subdirectory of itself\")\n try:\n self.rename(target)\n except error.EXDEV: # invalid cross-device link\n self.copy(target)\n self.remove()","def namespace(self, namespace):\n\n self._namespace = namespace","def namespace(self, namespace):\n\n self._namespace = namespace","def create_namespace(node, namespace, delete_before_create=True):\n if delete_before_create:\n Namespaces.delete_namespace(node, namespace)\n\n cmd = f\"ip netns add {namespace}\"\n exec_cmd_no_error(node, cmd, sudo=True)\n Namespaces.__namespaces.append(namespace)","def move_container(i3, name, monitor, container_id=None):\n i3.command(f'move container to workspace {name}')\n i3.command(f'workspace {name}, move workspace to output {monitor}')\n if container_id:\n i3.command(f'[con_id=\"{container_id}\"] focus')","def delete_tag(tag):\n tag.destroy()","def tag ():\n\n tagname = get_tag(comp_versions, 'ACE')\n\n if opts.tag:\n if opts.take_action:\n vprint (\"Placing tag %s on ACE_TAO\" % (tagname))\n ex (\"cd $DOC_ROOT/ACE_TAO && git tag -a \" + tagname + \" -m\\\"\" + tagname + \"\\\"\")\n\n vprint (\"Placing tag %s on MPC\" % (tagname))\n ex (\"cd $DOC_ROOT/MPC && git tag -a \" + tagname + \" -m\\\"\" + tagname + \"\\\"\")\n\n # Update release branches\n latest_branch_helper (update_latest_branch, opts.release_type)\n else:\n vprint (\"Placing tag %s on ACE_TAO\" % (tagname))\n vprint (\"Placing tag %s on MPC\" % (tagname))\n print (\"Creating tags:\\n\")\n print (\"Placing tag \" + tagname + \"\\n\")","def test_replace_namespaced_policy(self):\n pass","def reconfigure_namespace(self, namespace, mode, **kwargs):\n\n if namespace not in self.namespaces.keys():\n raise ValueError(\"Namespace '%s' doesn't exist.\" % namespace)\n\n info = self.namespaces[namespace]\n\n sector_size = kwargs.get(\"sector_size\", None)\n map_location = kwargs.get(\"map_location\", None)\n\n if sector_size and mode != \"sector\":\n raise ValueError(\"Sector size cannot be set for selected mode '%s'.\" % mode)\n\n if map_location and mode != \"memory\":\n raise ValueError(\"Map location cannot be set for selected mode '%s'.\" % mode)\n\n mode_t = BlockDev.nvdimm_namespace_get_mode_from_str(mode)\n\n if sector_size:\n extra = {\"-l\": str(sector_size)}\n elif map_location:\n extra = {\"-M\": map_location}\n else:\n extra = None\n\n BlockDev.nvdimm_namespace_reconfigure(namespace, mode_t, info.enabled, extra)\n\n # and update our namespaces info \"cache\"\n self.update_namespaces_info()","def test_replace_namespaced_deployment_config_status(self):\n pass","def test_replace_namespaced_policy_binding(self):\n pass","def move_axis(data, label, new_position):\n # find current position of axis\n try:\n pos = data.dims.index(label)\n except ValueError as e:\n raise ValueError(\n f'Axis name {label} does not exist in input data') from e\n\n # create list of labels with new ordering\n axis_labels = list(data.dims)\n # the new position will be _before_ the given index, so will fail with a negative index\n # convert to a positive index in that case\n if new_position < 0:\n new_position += len(axis_labels)\n axis_labels.insert(new_position, axis_labels.pop(pos))\n # do the move\n return data.transpose(*axis_labels)","def test_replace_namespaced_image_stream_tag(self):\n pass","def MoveToAttributeNs(self, localName, namespaceURI):\n ret = libxml2mod.xmlTextReaderMoveToAttributeNs(self._o, localName, namespaceURI)\n return ret","def remove_namespace(namespace, response, resp_keys=[]):\n if isinstance(namespace, str):\n namespace = str.encode(namespace)\n for key in resp_keys:\n response[key] = remove_namespace(namespace, response[key])\n if isinstance(response, (int, float, bool)):\n pass\n elif isinstance(response, bytes):\n response = response.replace(namespace, b'', 1)\n elif isinstance(response, (tuple, list)):\n response = tuple([remove_namespace(namespace, x) for x in response])\n return response","def updateSBMLNamespace(self, *args):\n return _libsbml.SBMLDocument_updateSBMLNamespace(self, *args)","def remove_tag(args):","def tags_rename(self, item, tags):\n self._createTagAction(item, \"tags_rename\", tags)","def test_patch_net_namespace(self):\n pass","def untag_element(self,tag_name,element):\n pass","def removeNode(self, nTag):\r\n try:\r\n self._nodes.pop(nTag).destroy()\r\n except KeyError:\r\n raise InvalidRequest('Can not remove a non existent node '\r\n \"'{0}' from the container.\".format(nTag))","def remove( self, zone ):\n if zone.space is None:\n raise KeyError( \"zone not in space octree!\" )\n\n # remove zone from space node's contained set\n zone.space.zones.remove( zone )\n\n # set zone's containing space to none\n zone.space = None","def delete_namespace(self, namespace):\n return self.core_client.delete_namespace(namespace)","def replace_namespaced_namespace_finalize(self, body, name, **kwargs):\n kwargs['_return_http_data_only'] = True\n if kwargs.get('callback'):\n return self.replace_namespaced_namespace_finalize_with_http_info(body, name, **kwargs)\n else:\n (data) = self.replace_namespaced_namespace_finalize_with_http_info(body, name, **kwargs)\n return data","def test_create_namespaced_deployment_config_rollback_rollback(self):\n pass","def convert_to_namespace(file, output, keyword):\n resource = parse_bel_resource(file)\n write_namespace(\n namespace_keyword=(keyword or resource['AnnotationDefinition']['Keyword']),\n namespace_name=resource['AnnotationDefinition']['Keyword'],\n namespace_description=resource['AnnotationDefinition']['DescriptionString'],\n author_name='Charles Tapley Hoyt',\n namespace_domain=NAMESPACE_DOMAIN_OTHER,\n values=resource['Values'],\n citation_name=resource['Citation']['NameString'],\n file=output\n )","def destroyNamespace(self, remoteNamespace):\r\n for namespace in self._namespaces:\r\n if namespace.destroyExternal(remoteNamespace):\r\n break","def namespace_name(self, namespace_name):\n\n self._namespace_name = namespace_name","def qos_policy_group_rename(self, policy_group_name, new_name):\n return self.request( \"qos-policy-group-rename\", {\n 'policy_group_name': [ policy_group_name, 'policy-group-name', [ basestring, 'None' ], False ],\n 'new_name': [ new_name, 'new-name', [ basestring, 'None' ], False ],\n }, {\n } )"],"string":"[\n \"def remove_namespace(self, doc, namespace):\\r\\n ns = u'{%s}' % namespace\\r\\n nsl = len(ns)\\r\\n for elem in doc.getiterator():\\r\\n if elem.tag.startswith(ns):\\r\\n elem.tag = elem.tag[nsl:]\\r\\n else:\\r\\n pass\",\n \"def remove_namespace(doc, namespace=u\\\"{http://www.EcoInvent.org/EcoSpold02}\\\"):\\n ns = u'{}'.format(namespace)\\n nsl = len(ns)\\n for elem in doc.getiterator():\\n if elem.tag.startswith(ns):\\n elem.tag = elem.tag[nsl:]\",\n \"def update():\\n for namespace in metadata.get_namespaces():\\n logging.info('Switching namespace: \\\\'%s\\\\'', namespace)\\n namespace_manager.set_namespace(namespace)\\n update_per_namespace()\\n\\n namespace_manager.set_namespace('')\\n return ('', 204)\",\n \"def ReplaceNamespace(self, request, global_params=None):\\n config = self.GetMethodConfig('ReplaceNamespace')\\n return self._RunMethod(\\n config, request, global_params=global_params)\",\n \"def ReplaceNamespace(self, request, global_params=None):\\n config = self.GetMethodConfig('ReplaceNamespace')\\n return self._RunMethod(\\n config, request, global_params=global_params)\",\n \"def move_to(i3: i3ipc.Connection, workspace: int):\\n i3.command(f\\\"move container to workspace number {workspace}\\\")\",\n \"async def remove_namespace(self, namespace: str) -> Any:\\n if namespace == self.get_namespace(): # if it belongs to this app's namespace\\n raise ValueError(\\\"Cannot remove namespace with the same name as operating namespace\\\")\\n\\n return await self.AD.state.remove_namespace(namespace)\",\n \"def clean_up_namespaces(node, namespace=None):\\n if namespace is not None:\\n Namespaces.delete_namespace(node, namespace)\\n return\\n\\n namespace_copy = deepcopy(Namespaces.__namespaces)\\n for namespace_name in namespace_copy:\\n Namespaces.delete_namespace(node, namespace_name)\",\n \"def update_tag_namespace(self, tag_namespace_id, update_tag_namespace_details, **kwargs):\\n resource_path = \\\"/tagNamespaces/{tagNamespaceId}\\\"\\n method = \\\"PUT\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"update_tag_namespace got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tagNamespaceId\\\": tag_namespace_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_tag_namespace_details,\\n response_type=\\\"TagNamespace\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_tag_namespace_details,\\n response_type=\\\"TagNamespace\\\")\",\n \"def fix(self):\\n for namespace in pm.listNamespaces():\\n for elem in namespace.ls():\\n elem.rename(elem.split(\\\":\\\")[-1])\\n namespace.remove()\\n\\n self.run()\",\n \"def removeNamespace(self, *args):\\n return _libsbml.XMLToken_removeNamespace(self, *args)\",\n \"def set_target_namespace(self, namespace):\\n # do shit\\n self.target_namespace = namespace.strip(\\\":\\\")\",\n \"def test_replace_namespaced_deployment_config(self):\\n pass\",\n \"def sync_namespace(alias, reg_code, authToken, space=None, action=None):\\n if space == None:\\n action = 'get'\\n print(\\\" ACTION: GET\\\")\\n elif action == None:\\n if 'aeskey' not in space:\\n print(\\\"Space not encrypted\\\")\\n quit()\\n action = 'update'\\n print(\\\" ACTION: UPDATE\\\")\\n elif action == 'delete':\\n print(\\\" ACTION: DELETE\\\")\\n url = endpoint('namespace')\\n headers={'authorizationToken': authToken}\\n data = json.dumps({'action': action, 'alias': alias, 'reg_code': reg_code, 'namespace': space})\\n payload_size = sys.getsizeof(data)\\n print(\\\" Size of payload is: %s\\\" % (convert_size(payload_size)))\\n print(\\\" Max payload is: %s\\\" % (convert_size(max_payload_size)))\\n if payload_size >= max_payload_size:\\n print(\\\" OVER MAX PAYLOAD: %s\\\" % (convert_size(max_payload_size)))\\n quit()\\n r = requests.post(url, headers=headers, data=data) \\n print(\\\" Request made\\\")\\n if r.status_code == 403:\\n print(\\\" Invalid registration code, exiting\\\")\\n quit()\\n elif r.status_code == 406:\\n print(\\\" Namespace mismatch\\\")\\n quit()\\n else:\\n print(\\\" └──statusCode:\\\" + str(r.status_code) )\\n return r\",\n \"def delete_namespace(node, namespace):\\n cmd_timeout = 5\\n cmd = f\\\"ip netns delete {namespace}\\\"\\n (ret_code, _, delete_errmsg) = \\\\\\n exec_cmd(node, cmd, timeout=cmd_timeout, sudo=True)\\n if ret_code != 0:\\n cmd = f\\\"ip netns list {namespace}\\\"\\n (stdout, _) = \\\\\\n exec_cmd_no_error(node, cmd, timeout=cmd_timeout, sudo=True)\\n if stdout == namespace:\\n raise RuntimeError(f\\\"Could not delete namespace \\\"\\n f\\\"({namespace}): {delete_errmsg}\\\")\\n try:\\n Namespaces.__namespaces.remove(namespace)\\n except ValueError:\\n pass\",\n \"def test_replace_net_namespace(self):\\n pass\",\n \"def test_replace_namespaced_role(self):\\n pass\",\n \"def create_tag_namespace(self, create_tag_namespace_details, **kwargs):\\n resource_path = \\\"/tagNamespaces\\\"\\n method = \\\"POST\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"opc_retry_token\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"create_tag_namespace got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"opc-retry-token\\\": kwargs.get(\\\"opc_retry_token\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\\n self.base_client.add_opc_retry_token_if_needed(header_params)\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n header_params=header_params,\\n body=create_tag_namespace_details,\\n response_type=\\\"TagNamespace\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n header_params=header_params,\\n body=create_tag_namespace_details,\\n response_type=\\\"TagNamespace\\\")\",\n \"def removeNamespace(self, *args):\\n return _libsbml.SBMLNamespaces_removeNamespace(self, *args)\",\n \"def set_namespace(self, namespace: str) -> None:\\n self._namespace = namespace\",\n \"def delete_tag_namespace(self, tag_namespace_id, **kwargs):\\n resource_path = \\\"/tagNamespaces/{tagNamespaceId}\\\"\\n method = \\\"DELETE\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"if_match\\\",\\n \\\"opc_request_id\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"delete_tag_namespace got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tagNamespaceId\\\": tag_namespace_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"if-match\\\": kwargs.get(\\\"if_match\\\", missing),\\n \\\"opc-request-id\\\": kwargs.get(\\\"opc_request_id\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params)\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params)\",\n \"def move_objects(self, src_s3_prefix_path, destination_s3_prefix_path):\\n src_bucket_name, src_prefix = S3Util.get_bucket_and_key(src_s3_prefix_path)\\n destination_bucket_name, destination_prefix = S3Util.get_bucket_and_key(destination_s3_prefix_path)\\n\\n src_bucket = self.s3_resource.Bucket(src_bucket_name)\\n destination_bucket = self.s3_resource.Bucket(destination_bucket_name)\\n\\n for obj in src_bucket.objects.filter(Prefix=src_prefix):\\n source_obj = self._object_summary_to_copy_source(obj)\\n\\n # replace the prefix\\n new_key = obj.key.replace(src_prefix, destination_prefix)\\n destination_bucket.copy(CopySource=source_obj, Key=new_key)\\n obj.delete()\",\n \"def replace_namespaced_namespace(self, body, name, **kwargs):\\n kwargs['_return_http_data_only'] = True\\n if kwargs.get('callback'):\\n return self.replace_namespaced_namespace_with_http_info(body, name, **kwargs)\\n else:\\n (data) = self.replace_namespaced_namespace_with_http_info(body, name, **kwargs)\\n return data\",\n \"def test_delete_net_namespace(self):\\n pass\",\n \"def move_tag_seq(words, seq, dest, punc=None):\\n if len(seq) > len(words):\\n return None\\n seq_start = index_tag_seq(words, seq)\\n if seq_start > -1:\\n move_words = words[seq_start:seq_start+len(seq)]\\n words = words[:seq_start] + words[seq_start+len(seq):]\\n if dest == 'start':\\n words = move_words + words\\n if dest == 'end':\\n if punc is not None:\\n words.append(punc)\\n words += move_words\\n return words\\n return None\",\n \"def test_delete_namespaced_deployment_config(self):\\n pass\",\n \"def namespace_delete(cursor, namespace_id):\\n haystack = (namespace_id,)\\n query = \\\"DELETE FROM namespaces WHERE _id=?\\\"\\n try:\\n cursor.execute(query, haystack)\\n except Exception as e:\\n on_error(e)\\n else:\\n cursor.connection.commit()\\n raise Return((True, None))\",\n \"def move(owner_id=None, target_album_id=None, photo_id=None):\\n params = {\\n 'owner_id': owner_id,\\n 'target_album_id': target_album_id,\\n 'photo_id': photo_id\\n }\\n result = call('photos.move', **params)\\n return parse_response(result)\",\n \"def swap_cnames(profile, source_environment, destination_environment):\\n client = boto3client.get(\\\"elasticbeanstalk\\\", profile)\\n params = {}\\n params[\\\"SourceEnvironmentName\\\"] = source_environment\\n params[\\\"DestinationEnvironmentName\\\"] = destination_environment\\n return client.swap_environment_cnames(**params)\",\n \"def post_namespace_delete(self, resource_id, resource_dict):\\n pass\",\n \"def replace_resource(self, namespace: \\\"str\\\" = None):\\n names = [\\n \\\"replace_namespaced_csistorage_capacity\\\",\\n \\\"replace_csistorage_capacity\\\",\\n ]\\n\\n _kube_api.execute(\\n action=\\\"replace\\\",\\n resource=self,\\n names=names,\\n namespace=namespace,\\n api_client=None,\\n api_args={\\\"body\\\": self.to_dict(), \\\"name\\\": self.metadata.name},\\n )\",\n \"def replace_namespaced_net_namespace(self, body, name, **kwargs):\\n\\n all_params = ['body', 'name', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method replace_namespaced_net_namespace\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `replace_namespaced_net_namespace`\\\")\\n # verify the required parameter 'name' is set\\n if ('name' not in params) or (params['name'] is None):\\n raise ValueError(\\\"Missing the required parameter `name` when calling `replace_namespaced_net_namespace`\\\")\\n\\n resource_path = '/oapi/v1/netnamespaces/{name}'.replace('{format}', 'json')\\n path_params = {}\\n if 'name' in params:\\n path_params['name'] = params['name']\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'PUT',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1NetNamespace',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def move(name, other, newname=None):\",\n \"def namespace(*args, absoluteName: bool=True, addNamespace: AnyStr=\\\"\\\", collapseAncestors:\\n AnyStr=\\\"\\\", deleteNamespaceContent: bool=True, exists: Union[AnyStr, bool]=\\\"\\\",\\n force: bool=True, isRootNamespace: Union[AnyStr, bool]=\\\"\\\",\\n mergeNamespaceWithOther: AnyStr=\\\"\\\", mergeNamespaceWithParent: bool=True,\\n mergeNamespaceWithRoot: bool=True, moveNamespace: List[AnyStr, AnyStr]=None,\\n parent: AnyStr=\\\"\\\", recurse: bool=True, relativeNames: bool=True, removeNamespace:\\n AnyStr=\\\"\\\", rename: List[AnyStr, AnyStr]=None, setNamespace: AnyStr=\\\"\\\",\\n validateName: AnyStr=\\\"\\\", q=True, query=True, **kwargs)->Union[AnyStr, Any]:\\n pass\",\n \"def test_create_deployment_config_rollback_for_all_namespaces(self):\\n pass\",\n \"def replace_widget(container, tag, widget) -> None:\\n try:\\n container[tag].destroy()\\n except KeyError:\\n pass\\n container[tag] = widget\",\n \"def remove(self, camera, namespace='*'):\\n with self.lock:\\n if namespace == '*':\\n for cur_namespace in self.camera_namespaces:\\n self.camera_namespaces[cur_namespace].remove(camera)\\n else:\\n self.camera_namespaces[namespace].remove(camera)\",\n \"def remove(self, *args):\\n return _libsbml.XMLNamespaces_remove(self, *args)\",\n \"def test_unidirectional_namespace_bucket_replication(\\n self,\\n awscli_pod_session,\\n mcg_obj_session,\\n cld_mgr,\\n bucket_factory,\\n source_bucketclass,\\n target_bucketclass,\\n test_directory_setup,\\n ):\\n target_bucket_name = bucket_factory(bucketclass=target_bucketclass)[0].name\\n\\n replication_policy = (\\\"basic-replication-rule\\\", target_bucket_name, None)\\n source_bucket = bucket_factory(\\n 1, bucketclass=source_bucketclass, replication_policy=replication_policy\\n )[0]\\n source_bucket_name = source_bucket.name\\n source_bucket_uls_name = source_bucket.bucketclass.namespacestores[0].uls_name\\n\\n namespacestore_aws_s3_creds = {\\n \\\"access_key_id\\\": cld_mgr.aws_client.access_key,\\n \\\"access_key\\\": cld_mgr.aws_client.secret_key,\\n \\\"endpoint\\\": constants.AWS_S3_ENDPOINT,\\n \\\"region\\\": source_bucketclass[\\\"namespace_policy_dict\\\"][\\n \\\"namespacestore_dict\\\"\\n ][\\\"aws\\\"][0][1],\\n }\\n\\n written_random_objects = write_random_test_objects_to_bucket(\\n awscli_pod_session,\\n source_bucket_uls_name,\\n test_directory_setup.origin_dir,\\n amount=5,\\n s3_creds=namespacestore_aws_s3_creds,\\n )\\n\\n listed_obejcts = mcg_obj_session.s3_list_all_objects_in_bucket(\\n source_bucket_name\\n )\\n\\n compare_bucket_object_list(\\n mcg_obj_session, source_bucket_name, target_bucket_name\\n )\\n\\n assert set(written_random_objects) == {\\n obj.key for obj in listed_obejcts\\n }, \\\"Some of the uploaded objects are missing\\\"\",\n \"def update_tag(tag):\\n remove_tag(tag)\\n add_tag(tag)\",\n \"def list_tag_namespaces(self, compartment_id, **kwargs):\\n resource_path = \\\"/tagNamespaces\\\"\\n method = \\\"GET\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"page\\\",\\n \\\"limit\\\",\\n \\\"include_subcompartments\\\",\\n \\\"lifecycle_state\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"list_tag_namespaces got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n if 'lifecycle_state' in kwargs:\\n lifecycle_state_allowed_values = [\\\"ACTIVE\\\", \\\"INACTIVE\\\", \\\"DELETING\\\", \\\"DELETED\\\"]\\n if kwargs['lifecycle_state'] not in lifecycle_state_allowed_values:\\n raise ValueError(\\n \\\"Invalid value for `lifecycle_state`, must be one of {0}\\\".format(lifecycle_state_allowed_values)\\n )\\n\\n query_params = {\\n \\\"compartmentId\\\": compartment_id,\\n \\\"page\\\": kwargs.get(\\\"page\\\", missing),\\n \\\"limit\\\": kwargs.get(\\\"limit\\\", missing),\\n \\\"includeSubcompartments\\\": kwargs.get(\\\"include_subcompartments\\\", missing),\\n \\\"lifecycleState\\\": kwargs.get(\\\"lifecycle_state\\\", missing)\\n }\\n query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None}\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n query_params=query_params,\\n header_params=header_params,\\n response_type=\\\"list[TagNamespaceSummary]\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n query_params=query_params,\\n header_params=header_params,\\n response_type=\\\"list[TagNamespaceSummary]\\\")\",\n \"def get_namespace(self, namespace, lowercase=True, trim_namespace=True):\\n\\t\\treturn self.get_namespace_view(namespace, lowercase, trim_namespace).copy()\",\n \"async def removetags(self, ctx, tag=None):\\r\\n\\t\\tTag = self.settings.ServerConfig(ctx.guild.id, 'Tags')\\r\\n\\t\\tif not tag in Tag:\\r\\n\\t\\t\\treturn await ctx.send('Can\\\\'t find Tag: '.format(tag))\\t\\r\\n\\r\\n\\t\\tdel Tag[tag]\\r\\n\\t\\tself.settings.ServerConfig(ctx.guild.id, 'Tags', Tag)\\r\\n\\r\\n\\t\\tawait ctx.send('Removed Tag: '.format(tag))\",\n \"def test_replace_namespaced_template(self):\\n pass\",\n \"def move_object(self, bucket_name, src_object_name, dst_object_name, no_overwrite=False):\\n\\n return h3lib.move_object(self._handle, bucket_name, src_object_name, dst_object_name, no_overwrite, self._user_id)\",\n \"def test_replace_namespaced_role_binding(self):\\n pass\",\n \"def test_create_namespaced_deployment_config_rollback(self):\\n pass\",\n \"def updateNamespace(self):\\n import addict\\n self.namespace['config'] = addict.Dict(self.namespace['config'])\",\n \"def namespace(self, namespace: str):\\n\\n self._namespace = namespace\",\n \"def delete_tag(tag, directory=None):\\n execute_command('git tag -d {0}'.format(tag), shell=True, cwd=directory)\",\n \"def move_element(self,n_a,n_b):\\n self.element_array.insert(n_b,self.element_array.pop(n_a))\",\n \"def test_patch_namespaced_deployment_config(self):\\n pass\",\n \"def move_node(self, job):\\n transfer = Transfer(job.jobInfo)\\n target = transfer.target\\n direction = transfer.direction\\n result = None\\n # Check uris\\n check_uri(target, self.sm, shouldExist = True)\\n checks = check_uri(direction, self.sm, shouldExist = False)\\n null = direction.endswith(NULL)\\n # Retrieve existing record\\n node = self.sm.get_node(target)[0]['node']\\n node = self.nf.get_node(node)\\n # Check whether endpoint is reserved URI\\n if null: self.nm.delete_node(target)\\n if direction.endswith(AUTO): \\n direction = generate_uri(direction)\\n result = {'destination': direction}\\n if not(null):\\n # Check if endpoint is a container\\n if checks['exists'] and checks['container']: direction += target[target.rfind('/'):]\\n # Change identifier\\n node.set_uri(direction)\\n # Update db\\n self.sm.update_node(target, direction, node.tostring())\\n # Check if target is a container\\n if isinstance(node, ContainerNode):\\n # Move children\\n for child in self.sm.get_children(target):\\n node = self.nf.get_node(self.sm.get_node(child)[0]['node'])\\n if null:\\n self.nm.delete_node(node.uri)\\n else:\\n new_uri = node.uri.replace(target, direction)\\n node.set_uri(new_uri)\\n self.sm.update_node(child, new_uri, node.tostring())\\n return result\",\n \"def setElementNamespace(self, *args):\\n return _libsbml.ASTBasePlugin_setElementNamespace(self, *args)\",\n \"def destroyContainer(tag): #@NoSelf\",\n \"def test_remove_defined_tag(self, test, object_storage):\\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\\n session_factory = test.oci_session_factory()\\n policy = test.load_policy(\\n {\\n \\\"name\\\": \\\"bucket-remove-tag\\\",\\n \\\"resource\\\": \\\"oci.bucket\\\",\\n \\\"filters\\\": [\\n {\\\"type\\\": \\\"value\\\", \\\"key\\\": \\\"name\\\", \\\"value\\\": bucket_name},\\n ],\\n \\\"actions\\\": [\\n {\\n \\\"type\\\": \\\"remove-tag\\\",\\n \\\"defined_tags\\\": [\\\"cloud-custodian-test.mark-for-resize\\\"],\\n },\\n ],\\n },\\n session_factory=session_factory,\\n )\\n policy.run()\\n resource = self._fetch_bucket_validation_data(\\n policy.resource_manager, namespace_name, bucket_name\\n )\\n test.assertEqual(resource[\\\"name\\\"], bucket_name)\\n test.assertEqual(self.get_defined_tag_value(resource[\\\"defined_tags\\\"]), None)\",\n \"async def save_namespace(self, **kwargs) -> None:\\n namespace = self._get_namespace(**kwargs)\\n await self.AD.state.save_namespace(namespace)\",\n \"def test_update_bucket(self, test, object_storage, with_or_without_compartment):\\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\\n session_factory = test.oci_session_factory()\\n policy = test.load_policy(\\n {\\n \\\"name\\\": \\\"add-defined-tag-to-bucket\\\",\\n \\\"resource\\\": \\\"oci.bucket\\\",\\n \\\"query\\\": [\\n {\\\"namespace_name\\\": namespace_name},\\n ],\\n \\\"filters\\\": [\\n {\\\"type\\\": \\\"value\\\", \\\"key\\\": \\\"name\\\", \\\"value\\\": bucket_name},\\n ],\\n \\\"actions\\\": [{\\\"type\\\": \\\"update\\\", \\\"defined_tags\\\": self.get_defined_tag(\\\"add_tag\\\")}],\\n },\\n session_factory=session_factory,\\n )\\n policy.run()\\n resource = self._fetch_bucket_validation_data(\\n policy.resource_manager, namespace_name, bucket_name\\n )\\n test.assertEqual(resource[\\\"name\\\"], bucket_name)\\n test.assertEqual(self.get_defined_tag_value(resource[\\\"defined_tags\\\"]), \\\"true\\\")\",\n \"def move_objects(\\n source_bucket=None,\\n destination_bucket=None,\\n prefix=None,\\n **kwargs):\\n\\n storage_objects = kwargs['ti'].xcom_pull(task_ids='list_files')\\n\\n hook = GoogleCloudStorageHook()\\n\\n for storage_object in storage_objects:\\n destination_object = storage_object\\n\\n if prefix:\\n destination_object = '{}/{}'.format(prefix, storage_object)\\n\\n hook.copy(source_bucket, storage_object, destination_bucket, destination_object)\\n hook.delete(source_bucket, storage_object)\",\n \"def addNamespace(self, *args):\\n return _libsbml.XMLToken_addNamespace(self, *args)\",\n \"def add_namespace(self, q, ns):\\n if ns in self.namespaces: return self.namespaces[ns]\\n self.namespaces[ns] = q\\n return q\",\n \"def delete_bucket_tagging(Bucket=None):\\n pass\",\n \"def delete_tag(filename, tag_name):\\n storeapps = APP.config[\\\"storage\\\"]\\n filename = filename.encode(\\\"utf-8\\\")\\n\\n try:\\n application = list(nativeapps.io.ls(storeapps, r\\\".*\\\" + filename + \\\"$\\\"))[0]\\n meta_path = os.path.join(os.path.dirname(application), \\\"metadata.json\\\")\\n metadata = json.loads(nativeapps.io.readfile(meta_path))\\n tags = metadata.get(\\\"tags\\\", [])\\n if tag_name in tags:\\n tags.remove(tag_name)\\n metadata[\\\"tags\\\"] = tags\\n nativeapps.io.writefile(meta_path, json.dumps(metadata))\\n except IndexError:\\n return \\\"Unknown application: %s\\\" % (application), 404\\n\\n return \\\"removed\\\", 200\",\n \"def setNamespaces(self, *args):\\n return _libsbml.XMLToken_setNamespaces(self, *args)\",\n \"def delete_namespace_content(context, namespace_id, session):\\n count = 0\\n query = (session.query(models.MetadefTag).filter_by(\\n namespace_id=namespace_id))\\n count = query.delete(synchronize_session='fetch')\\n return count\",\n \"def tag_rename(self, item_id, old_tag, new_tag, **params):\\n\\n self.queue('tag_rename', item_id=item_id,\\n old_tag=old_tag, new_tag=new_tag, **params)\",\n \"def removePackageNamespace(self, *args):\\n return _libsbml.SBMLNamespaces_removePackageNamespace(self, *args)\",\n \"def move_object(self, src_s3_path, destination_s3_path):\\n src_bucket_name, src_key = S3Util.get_bucket_and_key(src_s3_path)\\n destination_bucket_name, destination_key = S3Util.get_bucket_and_key(destination_s3_path)\\n obj = self.s3_resource.ObjectSummary(src_bucket_name, src_key)\\n destination_bucket = self.s3_resource.Bucket(destination_bucket_name)\\n destination_bucket.copy(CopySource=self._object_summary_to_copy_source(obj), Key=destination_key)\\n obj.delete()\",\n \"def moveBar(self, from_, to_):\\n fromBar = self.widget(from_)\\n self.removeWidget(fromBar)\\n self.insertWidget(to_, fromBar)\",\n \"def copyNamespace(self):\\n ret = libxml2mod.xmlCopyNamespace(self._o)\\n if ret is None:raise treeError('xmlCopyNamespace() failed')\\n __tmp = xmlNs(_obj=ret)\\n return __tmp\",\n \"def archive(self, namespace, archive_name, namespace_out=None, format=None):\\n raise RuntimeError('Already achieved')\",\n \"def move(self, target):\\n if target.relto(self):\\n raise error.EINVAL(target, \\\"cannot move path into a subdirectory of itself\\\")\\n try:\\n self.rename(target)\\n except error.EXDEV: # invalid cross-device link\\n self.copy(target)\\n self.remove()\",\n \"def namespace(self, namespace):\\n\\n self._namespace = namespace\",\n \"def namespace(self, namespace):\\n\\n self._namespace = namespace\",\n \"def create_namespace(node, namespace, delete_before_create=True):\\n if delete_before_create:\\n Namespaces.delete_namespace(node, namespace)\\n\\n cmd = f\\\"ip netns add {namespace}\\\"\\n exec_cmd_no_error(node, cmd, sudo=True)\\n Namespaces.__namespaces.append(namespace)\",\n \"def move_container(i3, name, monitor, container_id=None):\\n i3.command(f'move container to workspace {name}')\\n i3.command(f'workspace {name}, move workspace to output {monitor}')\\n if container_id:\\n i3.command(f'[con_id=\\\"{container_id}\\\"] focus')\",\n \"def delete_tag(tag):\\n tag.destroy()\",\n \"def tag ():\\n\\n tagname = get_tag(comp_versions, 'ACE')\\n\\n if opts.tag:\\n if opts.take_action:\\n vprint (\\\"Placing tag %s on ACE_TAO\\\" % (tagname))\\n ex (\\\"cd $DOC_ROOT/ACE_TAO && git tag -a \\\" + tagname + \\\" -m\\\\\\\"\\\" + tagname + \\\"\\\\\\\"\\\")\\n\\n vprint (\\\"Placing tag %s on MPC\\\" % (tagname))\\n ex (\\\"cd $DOC_ROOT/MPC && git tag -a \\\" + tagname + \\\" -m\\\\\\\"\\\" + tagname + \\\"\\\\\\\"\\\")\\n\\n # Update release branches\\n latest_branch_helper (update_latest_branch, opts.release_type)\\n else:\\n vprint (\\\"Placing tag %s on ACE_TAO\\\" % (tagname))\\n vprint (\\\"Placing tag %s on MPC\\\" % (tagname))\\n print (\\\"Creating tags:\\\\n\\\")\\n print (\\\"Placing tag \\\" + tagname + \\\"\\\\n\\\")\",\n \"def test_replace_namespaced_policy(self):\\n pass\",\n \"def reconfigure_namespace(self, namespace, mode, **kwargs):\\n\\n if namespace not in self.namespaces.keys():\\n raise ValueError(\\\"Namespace '%s' doesn't exist.\\\" % namespace)\\n\\n info = self.namespaces[namespace]\\n\\n sector_size = kwargs.get(\\\"sector_size\\\", None)\\n map_location = kwargs.get(\\\"map_location\\\", None)\\n\\n if sector_size and mode != \\\"sector\\\":\\n raise ValueError(\\\"Sector size cannot be set for selected mode '%s'.\\\" % mode)\\n\\n if map_location and mode != \\\"memory\\\":\\n raise ValueError(\\\"Map location cannot be set for selected mode '%s'.\\\" % mode)\\n\\n mode_t = BlockDev.nvdimm_namespace_get_mode_from_str(mode)\\n\\n if sector_size:\\n extra = {\\\"-l\\\": str(sector_size)}\\n elif map_location:\\n extra = {\\\"-M\\\": map_location}\\n else:\\n extra = None\\n\\n BlockDev.nvdimm_namespace_reconfigure(namespace, mode_t, info.enabled, extra)\\n\\n # and update our namespaces info \\\"cache\\\"\\n self.update_namespaces_info()\",\n \"def test_replace_namespaced_deployment_config_status(self):\\n pass\",\n \"def test_replace_namespaced_policy_binding(self):\\n pass\",\n \"def move_axis(data, label, new_position):\\n # find current position of axis\\n try:\\n pos = data.dims.index(label)\\n except ValueError as e:\\n raise ValueError(\\n f'Axis name {label} does not exist in input data') from e\\n\\n # create list of labels with new ordering\\n axis_labels = list(data.dims)\\n # the new position will be _before_ the given index, so will fail with a negative index\\n # convert to a positive index in that case\\n if new_position < 0:\\n new_position += len(axis_labels)\\n axis_labels.insert(new_position, axis_labels.pop(pos))\\n # do the move\\n return data.transpose(*axis_labels)\",\n \"def test_replace_namespaced_image_stream_tag(self):\\n pass\",\n \"def MoveToAttributeNs(self, localName, namespaceURI):\\n ret = libxml2mod.xmlTextReaderMoveToAttributeNs(self._o, localName, namespaceURI)\\n return ret\",\n \"def remove_namespace(namespace, response, resp_keys=[]):\\n if isinstance(namespace, str):\\n namespace = str.encode(namespace)\\n for key in resp_keys:\\n response[key] = remove_namespace(namespace, response[key])\\n if isinstance(response, (int, float, bool)):\\n pass\\n elif isinstance(response, bytes):\\n response = response.replace(namespace, b'', 1)\\n elif isinstance(response, (tuple, list)):\\n response = tuple([remove_namespace(namespace, x) for x in response])\\n return response\",\n \"def updateSBMLNamespace(self, *args):\\n return _libsbml.SBMLDocument_updateSBMLNamespace(self, *args)\",\n \"def remove_tag(args):\",\n \"def tags_rename(self, item, tags):\\n self._createTagAction(item, \\\"tags_rename\\\", tags)\",\n \"def test_patch_net_namespace(self):\\n pass\",\n \"def untag_element(self,tag_name,element):\\n pass\",\n \"def removeNode(self, nTag):\\r\\n try:\\r\\n self._nodes.pop(nTag).destroy()\\r\\n except KeyError:\\r\\n raise InvalidRequest('Can not remove a non existent node '\\r\\n \\\"'{0}' from the container.\\\".format(nTag))\",\n \"def remove( self, zone ):\\n if zone.space is None:\\n raise KeyError( \\\"zone not in space octree!\\\" )\\n\\n # remove zone from space node's contained set\\n zone.space.zones.remove( zone )\\n\\n # set zone's containing space to none\\n zone.space = None\",\n \"def delete_namespace(self, namespace):\\n return self.core_client.delete_namespace(namespace)\",\n \"def replace_namespaced_namespace_finalize(self, body, name, **kwargs):\\n kwargs['_return_http_data_only'] = True\\n if kwargs.get('callback'):\\n return self.replace_namespaced_namespace_finalize_with_http_info(body, name, **kwargs)\\n else:\\n (data) = self.replace_namespaced_namespace_finalize_with_http_info(body, name, **kwargs)\\n return data\",\n \"def test_create_namespaced_deployment_config_rollback_rollback(self):\\n pass\",\n \"def convert_to_namespace(file, output, keyword):\\n resource = parse_bel_resource(file)\\n write_namespace(\\n namespace_keyword=(keyword or resource['AnnotationDefinition']['Keyword']),\\n namespace_name=resource['AnnotationDefinition']['Keyword'],\\n namespace_description=resource['AnnotationDefinition']['DescriptionString'],\\n author_name='Charles Tapley Hoyt',\\n namespace_domain=NAMESPACE_DOMAIN_OTHER,\\n values=resource['Values'],\\n citation_name=resource['Citation']['NameString'],\\n file=output\\n )\",\n \"def destroyNamespace(self, remoteNamespace):\\r\\n for namespace in self._namespaces:\\r\\n if namespace.destroyExternal(remoteNamespace):\\r\\n break\",\n \"def namespace_name(self, namespace_name):\\n\\n self._namespace_name = namespace_name\",\n \"def qos_policy_group_rename(self, policy_group_name, new_name):\\n return self.request( \\\"qos-policy-group-rename\\\", {\\n 'policy_group_name': [ policy_group_name, 'policy-group-name', [ basestring, 'None' ], False ],\\n 'new_name': [ new_name, 'new-name', [ basestring, 'None' ], False ],\\n }, {\\n } )\"\n]"},"negative_scores":{"kind":"list like","value":["0.55153644","0.5485366","0.5347061","0.52107394","0.52107394","0.5199132","0.5165057","0.5079889","0.5022554","0.49942735","0.49675435","0.49604434","0.49384886","0.48304433","0.4796919","0.4729666","0.46716085","0.46684968","0.4638175","0.46381432","0.46096462","0.45636493","0.45625663","0.45530888","0.45495844","0.4545023","0.4537018","0.45306963","0.4528945","0.45188636","0.4513859","0.44731268","0.44713363","0.44707373","0.44516405","0.44463134","0.44463098","0.44382694","0.44290954","0.4417732","0.44082084","0.4397939","0.43856716","0.43625948","0.43596593","0.43594536","0.43451887","0.4345104","0.4342578","0.43381837","0.43359712","0.4335801","0.43342754","0.43292153","0.4328543","0.4317321","0.4316458","0.4295984","0.42938465","0.42923182","0.426023","0.42577487","0.42567372","0.4256192","0.42544794","0.4252844","0.42522085","0.4245407","0.42433196","0.42417425","0.42404345","0.42379874","0.42306948","0.42306948","0.42294544","0.4227811","0.42262134","0.42241132","0.42236793","0.4221493","0.4217459","0.42147943","0.42120618","0.4206442","0.41974786","0.41939682","0.41916794","0.41837955","0.417806","0.41712648","0.41666347","0.41665745","0.41633916","0.41625485","0.41618294","0.41602093","0.41561183","0.4155637","0.41549587","0.41544294"],"string":"[\n \"0.55153644\",\n \"0.5485366\",\n \"0.5347061\",\n \"0.52107394\",\n \"0.52107394\",\n \"0.5199132\",\n \"0.5165057\",\n \"0.5079889\",\n \"0.5022554\",\n \"0.49942735\",\n \"0.49675435\",\n \"0.49604434\",\n \"0.49384886\",\n \"0.48304433\",\n \"0.4796919\",\n \"0.4729666\",\n \"0.46716085\",\n \"0.46684968\",\n \"0.4638175\",\n \"0.46381432\",\n \"0.46096462\",\n \"0.45636493\",\n \"0.45625663\",\n \"0.45530888\",\n \"0.45495844\",\n \"0.4545023\",\n \"0.4537018\",\n \"0.45306963\",\n \"0.4528945\",\n \"0.45188636\",\n \"0.4513859\",\n \"0.44731268\",\n \"0.44713363\",\n \"0.44707373\",\n \"0.44516405\",\n \"0.44463134\",\n \"0.44463098\",\n \"0.44382694\",\n \"0.44290954\",\n \"0.4417732\",\n \"0.44082084\",\n \"0.4397939\",\n \"0.43856716\",\n \"0.43625948\",\n \"0.43596593\",\n \"0.43594536\",\n \"0.43451887\",\n \"0.4345104\",\n \"0.4342578\",\n \"0.43381837\",\n \"0.43359712\",\n \"0.4335801\",\n \"0.43342754\",\n \"0.43292153\",\n \"0.4328543\",\n \"0.4317321\",\n \"0.4316458\",\n \"0.4295984\",\n \"0.42938465\",\n \"0.42923182\",\n \"0.426023\",\n \"0.42577487\",\n \"0.42567372\",\n \"0.4256192\",\n \"0.42544794\",\n \"0.4252844\",\n \"0.42522085\",\n \"0.4245407\",\n \"0.42433196\",\n \"0.42417425\",\n \"0.42404345\",\n \"0.42379874\",\n \"0.42306948\",\n \"0.42306948\",\n \"0.42294544\",\n \"0.4227811\",\n \"0.42262134\",\n \"0.42241132\",\n \"0.42236793\",\n \"0.4221493\",\n \"0.4217459\",\n \"0.42147943\",\n \"0.42120618\",\n \"0.4206442\",\n \"0.41974786\",\n \"0.41939682\",\n \"0.41916794\",\n \"0.41837955\",\n \"0.417806\",\n \"0.41712648\",\n \"0.41666347\",\n \"0.41665745\",\n \"0.41633916\",\n \"0.41625485\",\n \"0.41618294\",\n \"0.41602093\",\n \"0.41561183\",\n \"0.4155637\",\n \"0.41549587\",\n \"0.41544294\"\n]"},"document_score":{"kind":"string","value":"0.61622286"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8571,"cells":{"query":{"kind":"string","value":"Creates a new auth token for the specified user. For information about what auth tokens are for, see `Managing User Credentials`__. You must specify a description for the auth token (although it can be an empty string). It does not have to be unique, and you can change it anytime with"},"document":{"kind":"string","value":"def create_auth_token(self, create_auth_token_details, user_id, **kwargs):\n resource_path = \"/users/{userId}/authTokens\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_auth_token got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_auth_token_details,\n response_type=\"AuthToken\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_auth_token_details,\n response_type=\"AuthToken\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _create_auth_token(self, user=None):\n token, created = Token.objects.get_or_create(user=user)\n return token","def create_token(user, title, expiration=_default_expiration_duration_opt):\n if expiration == _default_expiration_duration_opt:\n duration = _default_expiration_duration()\n expiration = duration + datetime.now() if duration else None\n\n token_code = random_string_generator(TOKEN_NAME_PREFIX_LENGTH + MINIMUM_TOKEN_SUFFIX_LENGTH)()\n token_name = token_code[:TOKEN_NAME_PREFIX_LENGTH]\n token_secret = token_code[TOKEN_NAME_PREFIX_LENGTH:]\n\n assert token_name\n assert token_secret\n\n return AppSpecificAuthToken.create(\n user=user,\n title=title,\n expiration=expiration,\n token_name=token_name,\n token_secret=DecryptedValue(token_secret),\n )","def create_token(user):\n access_token = create_access_token(user)\n payload = jwt.decode(\n access_token,\n app.config['JWT_SECRET_KEY'],\n algorithms=app.config['JWT_DECODE_ALGORITHMS'])\n data = {\n 'token':access_token,\n 'username': user.username,\n }\n data.update(payload)\n data['exp'] = datetime.fromtimestamp(data['exp'])\n app.logger.debug(str(data))\n if app.config.get('KEEP_TOKEN'):\n # deletes old tokens\n tokens = app.data.driver.db[config.DOMAIN['token']['datasource']['source']]\n tokens.delete_many({'username': user.username})\n # insets new token\n result = app.data.insert('token', data)\n return access_token, str(result[0])\n\n return access_token, None","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def post(self):\n _purge_expired_user_tokens()\n\n request_dict = get_json_and_verify_params({\n 'description': {'type': str, 'optional': True},\n 'expiration_date': {'optional': True},\n })\n\n expiration_date = request_dict.get('expiration_date')\n if expiration_date:\n expiration_date = parse_utc_datetime(\n expiration_date, timezone=\"UTC\")\n\n return current_user.create_auth_token(request_dict.get('description'),\n expiration_date)","def create_auth_token(sender, instance=None, created=False, **kwargs): # pylint: disable=unused-argument\n if created:\n Token.objects.create(user=instance) # pylint: disable=no-member","def create_token(user):\n payload = {\n 'sub': user.id,\n 'iat': datetime.utcnow(),\n 'exp': datetime.utcnow() + timedelta(days=1)\n }\n token = jwt.encode(payload, config.SECRET_KEY, algorithm='HS256')\n return token.decode('unicode_escape')","def set_auth_token_header(self):\n\n username = 'test-user'\n passwd = 'testuserpass1234'\n user = User.objects.create(username=username)\n user.set_password(passwd)\n user.save()\n\n assert Account.objects.get(user=user) is not None\n url = reverse('token_obtain_pair')\n res = self.client.post(url,\n data={'username': username, 'password': passwd})\n self.client.credentials(HTTP_AUTHORIZATION=\n f\"Bearer {res.data['access']}\")\n return user","def create_auth_token(\n username: str,\n admin: t.Optional[bool] = False,\n spotify: t.Optional[bool] = False,\n) -> JWT:\n auth_token: JWT = auth_manager.auth_token(\n username, {\"admin\": admin, \"spotify\": spotify}\n )\n return auth_token","def generate_token(user):\n if JWT_AUTH:\n payload = JWT_PAYLOAD_HANDLER(user)\n return JWT_ENCODE_HANDLER(payload)\n else:\n token = Token.objects.create(user=user)\n token.save()\n return token","def create_token(request, user):\n\n key = get_random_string(100)\n data = {}\n ip = get_client_ip_address(request)\n\n return Token.objects.create(user=user, key=key, data=json.dumps(data), ip=ip)","def generate_token(user):\n try:\n # generate the auth token\n auth_token = User.encode_auth_token(user.id)\n response_object = {\n \"status\": \"success\",\n \"message\": \"Successfully registered.\",\n \"Authorization\": auth_token.decode(),\n }\n return response_object, 201\n except Exception as e:\n response_object = {\n \"status\": \"fail\",\n \"message\": \"Some error occurred. Please try again.\",\n }\n return response_object, 401","def test_create_token_for_user(self):\r\n payload = {\r\n 'email': 'test@max.net',\r\n 'password': 'Testpass123',\r\n 'name': 'Maks'\r\n }\r\n create_user(**payload)\r\n\r\n res = self.client.post(TOKEN_URL, payload)\r\n\r\n self.assertIn('token', res.data)\r\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def test_create_token_for_user(self):\n payload = {'email': 'test1@test1.ri',\n 'password': 'testPassWord',\n 'time_zone': 'Europe/Dublin'}\n create_user(**payload)\n res = self.client.post(TOKEN_URL, payload)\n\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def test_create_token_for_user(self):\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'testpass'\n }\n create_user(**payload)\n res = self.client.post(TOKEN_URI, payload)\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def test_create_token_for_user(self):\n payload = {'email': 'test@test.com', 'password': 'testpass'}\n create_user(**payload)\n res = self.client.post(TOKEN_URL, payload)\n\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def test_create_token_for_user(self):\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'abcd1234',\n }\n\n create_user(**payload)\n response = self.client.post(TOKEN_URL, payload)\n\n # We expect a token and should get a HTTP 200\n self.assertIn('token', response.data)\n self.assertEqual(response.status_code, status.HTTP_200_OK)","def test_create_token_for_user(self):\n\n credentials = {'email': 'testuser@gmail.com', 'password': 'Testpass12'}\n get_user_model().objects.create_user(**credentials)\n\n response = self.client.post(URL_TOKEN, credentials)\n\n # Check that the response is HTTP 200, and contains a token.\n self.assertIn('token', response.data)\n self.assertEqual(response.status_code, status.HTTP_200_OK)","def token_auth(self):\n self.client = APIClient()\n self.user = User.objects.create_user(username='testuser', email='test@test.com', password='testpassword')\n self.token = Token.objects.create(user=self.user)\n self.client.credentials(HTTP_AUTHORIZATION='Token ' + self.token.key)","def _create_user(userid, **kw):\n\n new_user = User(userid, **kw)\n USERS[new_user.token] = new_user\n return USERS[new_user.token]","def newToken(self, description):\n self.__require_privilaged_access()\n with DBSession(self.__config_db) as session:\n token = generate_session_token()\n user = self.getLoggedInUser()\n groups = ';'.join(self.__auth_session.groups)\n session_token = Session(token, user, groups, description, False)\n\n session.add(session_token)\n session.commit()\n\n LOG.info(\"New personal access token '%s...' has been generated \"\n \"by '%s'.\", token[:5], self.getLoggedInUser())\n\n return SessionTokenData(token,\n description,\n str(session_token.last_access))","def test_create_token_for_user(setup_client):\n client = setup_client\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'testpass',\n }\n create_user(**payload, **{'role': 'Supplier'})\n res = client.post(TOKEN_URL, payload)\n assert \"token\" in res.data\n assert res.status_code == status.HTTP_200_OK","def create_auth_token():\n data = get_request_data(request)\n address = data.get(\"address\")\n expiration = int(data.get(\"expiration\"))\n\n pk = get_provider_private_key(use_universal_key=True)\n token = jwt.encode({\"exp\": expiration, \"address\": address}, pk, algorithm=\"HS256\")\n token = token.decode(\"utf-8\") if isinstance(token, bytes) else token\n\n valid, message = is_token_valid(token, address)\n if not valid:\n if message == \"Token is deleted.\":\n force_restore_token(token)\n else:\n return jsonify(error=message), 400\n\n return jsonify(token=token)","def create_google_user(self, payload, user_data):\n if not User.objects.filter(email=payload['email']).exists():\n u = User()\n u.generate_token()\n u.email = payload['email']\n u.name = payload['given_name'] or ''\n u.surname = payload['family_name'] or ''\n u.image_url = user_data['image_url'] or ''\n u.google_id = user_data['id']\n u.google_token = user_data['token']\n u.save()\n else:\n u = User.objects.get(email=payload['email'])\n\n return u.token","def generate_token(usr):\n token = jwt.encode({\"user\":usr, \"exp\":datetime.datetime.utcnow()\n + datetime.timedelta(minutes=30)}, KEY)\n user = User.update(token=token).where(User.username == usr)\n user.execute()\n return token","def generate_token_from_user(user, expires_at=None):\n issued_at = datetime.utcnow()\n token = AccessToken()\n token.payload.update(\n {\n \"email\": user.email,\n \"exp\": expires_at or issued_at + timedelta(days=2),\n \"iat\": issued_at,\n \"language\": user.language,\n \"username\": user.username,\n \"full_name\": user.get_full_name(),\n }\n )\n return token","def for_user(cls, user):\n\n token = super().for_user(user)\n\n TokenMeta.objects.get_or_create(\n jti=token['jti'],\n token=str(token),\n )\n\n return token","def insertNewUser(self,user, access_token):\n newUser = UserToken(username=user, user_key = access_token.key, user_secret = access_token.secret)\n newUser.put()","def create_token(self, consumer, token_type, timestamp, user=None):\n token, created = self.first_or_create(consumer=consumer, \n token_type=token_type, \n timestamp=timestamp,\n user=user)\n\n if created:\n token.key, token.secret = self.generate_random_codes()\n token.save()\n\n return token","def create(self, request):\n token = AuthTokenClass().post(request)\n return token","def create(self, user, token):\n\n session['user'] = {\n 'id': str(user.id),\n 'login': user.login,\n 'token': token\n }\n\n return UserSession.create(session['user'])","def create(self, request):\n return ObtainAuthToken().post(request)","def create(self,request):\n return CustomAuthToken().post(request)","def post(self, **kwargs):\n username: str = request.json.get(\"username\", None)\n password: str = request.json.get(\"password\", None)\n user = get_user_instance(username, password)\n return {\"access_token\": create_access_token(identity=user)}, 200","def create_user(self):\n username = \"\".join(choice(\n string.ascii_letters) for x in range (randint(7,10)))\n params = {\n \"first_name\":\"ugali\",\n \"last_name\":\"mayai\",\n \"email\":\"ugalimayai@gmail.com\",\n \"username\":username,\n \"password\":\"password\"\n }\n path = \"/api/v2/auth/signup\"\n user = self.client.post(path,\n data=json.dumps(params),\n content_type=\"application/json\")\n \n user_id = user.json['user_id']\n auth_token = user.json['AuthToken']\n return int(user_id), auth_token","async def create_new_user(*, user: User):\n with Session(engine) as session:\n user.password = simple_hash(user.name, user.password) #Hashing password for security\n session.add(user)\n session.commit()\n return {\"message\": \"User {user_id} created\".format(user_id = user.id)}","def test_create_token(self):\n data = {'email': 'test@test.com', 'password': 'testtest'}\n sigin_in_user(**data)\n payload = {\n 'username': 'test@test.com',\n 'password': 'testtest'\n }\n res = self.client.post(TOKEN_URL, payload)\n \n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def create(self, request, *args, **kwargs):\n serializer = self.get_serializer(data=request.data)\n serializer.is_valid(raise_exception=True)\n user = serializer.save()\n headers = self.get_success_headers(serializer.data)\n return Response(\n dict(serializer.data, token=str(user.auth_token)),\n status=status.HTTP_201_CREATED,\n headers=headers\n )","def generate_new_token(uid):\n random_token = uuid.uuid4()\n token = TokenAuth(user_id=uid, token=random_token)\n token.save()\n return random_token","def get_token(cls, user, full_result=False):\n if user is None:\n return EMPTY_KNOX_TOKEN\n result = AuthToken.objects.create(user=user)\n return result if full_result else result[1]","def generate_token(user: dict):\n\n payload = {\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=1),\n 'iat': datetime.datetime.utcnow(),\n 'user': user\n }\n token = jwt.encode(\n payload,\n os.getenv('SECRET_KEY'),\n algorithm='HS256'\n )\n return token.decode('UTF-8')","def post(self, request, *args, **kwargs):\n self.create(request, *args, **kwargs)\n token, created = Token.objects.get_or_create(user=self.user)\n return Response({'token': token.key}, status=201)","def create_jwt(user, secret):\n logger.debug(\"Create JWT with secret %s\" % secret)\n # username = request.POST['username']\n # password = request.POST['password'\n\n expiry = datetime.datetime.now() + datetime.timedelta(seconds=30)\n expiry_s = time.mktime(expiry.timetuple())\n if user.is_authenticated():\n internalid = user.authprofile.internalid\n payload = {'username': user.username, 'expiry': expiry_s, 'type': \"AuthenticatedUser\", 'internalid': internalid, 'email': user.email}\n token = jws.sign(payload, secret, algorithm='HS256')\n else:\n payload = {'expiry':expiry_s, 'type': \"AnonymousUser\", 'internalid': None, 'email': None}\n token = jws.sign(payload, secret, algorithm='HS256')\n logger.debug(\"Payload: %s\" % payload)\n # logger.info(\"Token: %s\" % token)\n return token","def test_create_token_to_user(self):\n data = {\n 'email': 'test@test.com', \n 'password': \"testtest\"\n }\n res = self.client.post(TOKEN_URL, data)\n\n self.assertNotIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def create(self, request):\n\n return ObtainAuthToken().post(request)","def new_user(client, username, password, apikey=None, docs=None):\n if apikey is None:\n apikey = str(uuid.uuid4())\n passhash = generate_password_hash(password, method='sha1')\n user = User(username, passhash, apikey, docs=docs)\n user.create(client)\n return user","def create_auth_token(sender, instance=None, created=False, **kwargs):\n\n if created:\n # Generate API token for user.\n api_token = Token.objects.create(user=instance)\n\n # Only create agent using username and API token for non-admin users.\n if instance.is_superuser is False:\n Agent.objects.create(scan_agent=instance, api_token=api_token)","def authorize_user(case: APITestCase, user: User):\n\n token = Token.objects.create(user=user)\n case.client.credentials(HTTP_AUTHORIZATION=f'Token {token}')","def create(self, validated_data):\n\t\tinstance = super(UserSerializer, self).create(validated_data)\n\t\tinstance.set_password(validated_data['password'])\n\t\ttoken = Token.objects.create(user=instance)\n\t\tinstance.token = token\n\t\treturn instance","def create_user():\n record = request.get_json()\n if record is None:\n return {\"Error\": \"No data Supplied.\"}, 400\n\n schema = user_schema.load(record)\n\n if UserModel.objects(email=schema['email']):\n return {\"Error\": \"User Data already exists.\"}, 400\n user = UserModel(**schema)\n user.hash_password()\n user.save()\n ser_data = user_schema.dump(user)\n token = Auth.generate_token(ser_data[\"_id\"])\n return {\"message\": \"User Created Successfully\", \"Token\": token, \"id\": str(user.id)}, 200","def make_token(self, user):\n return super()._make_token_with_timestamp(user, int(time.time()))","def create_token_missing_field(self):\n payload = {'email': 'test@test.com', 'password': 'testpass'}\n create_user(**payload)\n payload = {'email': 'test@test.com', 'password': ''}\n res = self.client.post(TOKEN_URL, payload)\n self.assertNotIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def auth_token_generate(identity_param_val, expires_delta=False):\n access_token = ''\n try:\n if expires_delta is not False:\n expires_delta = timedelta(minutes=expires_delta)\n access_token = create_access_token(identity=identity_param_val, expires_delta=expires_delta)\n except Exception as e:\n print(e)\n\n return access_token","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create_fake_JWT_token(userEmail):\n pass","def create_token_no_user(self):\n payload = {'email': 'test@test.com', 'password': 'testpass'}\n res = self.client.post(TOKEN_URL, payload)\n self.assertNotIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","async def create_token(self, *args, **kwargs) -> OAuth2Token:\n token = await super().create_token(*args, **kwargs)\n # NOTE: Save data from token to db here.\n return token","def test_create_token_valid(self):\n create_mock_user(**self.mock_user)\n res = self.client.post(TOKEN_URL, self.mock_user)\n\n self.assertEqual(res.status_code, status.HTTP_200_OK)\n self.assertIn('token', res.data)","def issue_user_token(user, salt):\r\n\r\n\t\tif user is not None:\r\n\t\t\tif (salt == 'login'):\r\n\t\t\t\ttoken, _ = Token.objects.get_or_create(user=user)\r\n\t\t\telse:\r\n\t\t\t\ttoken = signing.dumps({'pk': user.pk}, salt=salt)\r\n\r\n\t\t\treturn token\r\n\r\n\t\treturn None","def generate_token_for_user(user: User, expiration: datetime.timedelta=datetime.timedelta(days=7)):\n\n return generate_token({'id': user.id}, expiration)","def create(self, validated_data):\n request = self._kwargs['context']['request']\n user = User.objects.create(**validated_data)\n user.set_password(validated_data[\"password\"])\n user.save()\n category_list = ['Fuel', 'Bill', 'Entertainment', 'Education', 'Food']\n for category in category_list:\n user.user_categories.create(name=category)\n login(request, user)\n token, created = Token.objects.get_or_create(user=user)\n validated_data[\"token\"] = token.key\n return validated_data","def create_user(UserName=None, MessageAction=None, FirstName=None, LastName=None, AuthenticationType=None):\n pass","def create_token(self):\n ts_datetime = self.logged_at or self.created_at\n ts = int(mktime(ts_datetime.timetuple()))\n key = base64.encodestring(self.email)\n base = \"{}{}\".format(key, ts)\n salt, hsh = self.password.split('$')\n return \"{}$${}\".format(key, get_hexdigest(salt, base))","def token_generate(self, user_id):\n try:\n payload = {\n 'exp': datetime.utcnow() + timedelta(minutes=200),\n 'iat': datetime.utcnow(),\n 'sub': user_id\n }\n encoded_token = jwt.encode(\n payload, current_app.config['SECRET_KEY'], algorithm='HS256'\n )\n return encoded_token\n\n except Exception:\n return str(Exception)","def login(user: User):\n try:\n time = datetime.datetime.utcnow() + datetime.timedelta(seconds=60)\n payload = {\"user_id\": user.name, \"password\": user.password, \"exp\": time}\n token = jwt.encode(payload, JWT_SECRET_KEY, JWT_ALGORITHM).decode('utf-8')\n return {\"token\": token}\n except Exception:\n return {\"message\": \"Error in creating Token\"}","async def r_create_user(*_, role: str = \"USER\") -> User:\n # create api object\n password = token_hex(10)\n # save to db\n user = await User.create(\n key=token_bytes(32),\n username=token_hex(10),\n password_hash=ARGON.hash(password),\n role=role,\n created=time(),\n )\n # set password field on user to pass them their password 1 time\n user.password = password\n # return api object to resolver\n return user","def generate_token(exp=None):\n\n secret_key = getenv('JWT_SECRET_KEY')\n user = {\n 'first_name': fake.name(),\n 'last_name': fake.name(),\n 'email': fake.email(),\n 'is_admin': IsAdmin.yes,\n 'password': fake.password()\n }\n\n payload = {'id': str(User.find_or_create(user, email=user['email']).id)}\n payload.__setitem__('exp', exp) if exp is not None else ''\n token = jwt.encode(payload, secret_key, algorithm='HS256').decode(CHARSET)\n return 'Bearer {0}'.format(token)","def generate_token(user, expire_time=86400):\n session = Session()\n token = session.query(PasswordRecoveryToken)\\\n .filter(PasswordRecoveryToken.user_id == user.user_id)\\\n .first()\n\n if token is not None:\n self.expire(token)\n \n token = PasswordRecoveryToken()\n token.user_id = user.user_id\n session.add(token)\n \n token.expiration = datetime.now() + timedelta(seconds=expire_time)\n \n sha_token = hashlib.sha224(user.login)\n sha_token.update(user.password)\n sha_token.update(str(token.expiration))\n \n token.token = sha_token.hexdigest()\n print token.token\n return token","def create_token():\n def token_helper():\n token = util.prompt_for_user_token(username=\"robbo1992\", scope='user-library-read playlist-modify-private playlist-modify',\n client_id=config[\"spotify\"][\"client_id\"], client_secret=config[\"spotify\"][\"secret_id\"],\n redirect_uri='http://localhost:8080', cache_path=spotify_cache)\n return token\n if token_helper():\n log.debug(\"Succesfully generated a spotify token for authentication\")\n return spotipy.Spotify(auth=token_helper())\n else:\n if motley.internet:\n if token_helper():\n log.debug(\"Succesfully generated a spotify token for authentication\")\n return spotipy.Spotify(auth=token_helper())\n else:\n log.error(\"Authentication error in create_token method.\")","def _create_security_token(user):\n timestamp = int(time.time())\n plaintext = \"%x %s\" % (timestamp, user.email)\n nearest_mult_of_16 = 16 * ((len(plaintext) + 15) // 16)\n # Pad plaintest with whitespace to make the length a multiple of 16,\n # as this is a requirement of AES encryption.\n plaintext = plaintext.rjust(nearest_mult_of_16, ' ')\n if _DISABLE_CRYPTO:\n body = plaintext\n sig = \"sig\"\n else:\n key_storage = KeyStorage.get()\n body = AES.new(key_storage.aes_key, AES.MODE_CBC).encrypt(plaintext)\n hmac_key = key_storage.hmac_key\n if type(hmac_key) == unicode:\n # Crypto requires byte strings\n hmac_key = hmac_key.encode('utf8')\n sig = HMAC.HMAC(key=hmac_key, msg=body).hexdigest()\n return '%s:%s' % (sig, body)","def create_token(self, token_type=DEFAULT_TOKEN, extra_data='{}'):\n if token_type not in dict(TOKEN_TYPES).keys():\n raise ValueError(\"Unable to create token, unknown type\")\n\n value = calc_checksum(self.email, salt=randint(0, maxint))\n\n return LoginToken.objects.create(user=self, value=value, token_type=token_type, extra_data=extra_data)","def create_token(self, consumer, token_type, timestamp, scope,\n user=None, callback=None, callback_confirmed=False):\n token = self.create(consumer=consumer, \n token_type=token_type, \n timestamp=timestamp,\n scope=scope,\n user=user,\n callback=callback,\n callback_confirmed=callback_confirmed,\n key=uuid.uuid4().hex,\n secret=get_random_string(length=SECRET_SIZE))\n\n return token","def post(self):\n parser = reqparse.RequestParser()\n parser.add_argument('username', help='Required field', required=True)\n parser.add_argument('password', help='Required field', required=True)\n args = parser.parse_args()\n\n existing_user = users_db.get_user_by_username(args['username'])\n if not existing_user:\n # Create new user\n hashed_password = BCRYPT.generate_password_hash(args['password']).decode('utf-8')\n user_id = users_db.create_user(\n {\n 'username': args['username'],\n 'password': hashed_password\n }\n )\n\n # Use create_access_token() and create_refresh_token()\n # to create our access and refresh tokens\n response, status = {\n 'message': 'User <{0}> was successfully created: id={1}'.format(\n args['username'], user_id\n ),\n 'access_token': create_access_token(identity=str(user_id)),\n 'refresh_token': create_refresh_token(identity=str(user_id))\n }, 201\n else:\n # check password of existing user and create new jwt token\n if BCRYPT.check_password_hash(existing_user[0]['password'], args['password']):\n response, status = {\n 'message': 'User <{0}> was successfully logged in'.format(\n existing_user[0]['username']\n ),\n 'access_token': create_access_token(identity=str(existing_user[0]['_id'])),\n 'refresh_token': create_refresh_token(identity=str(existing_user[0]['_id']))\n }, 200\n else:\n response, status = {\n 'message': 'Invalid user password'\n }, 400\n\n return Response(dumps(response), status=status, mimetype='application/json')","def test_create_user_endpoint_creates_user(caplog):\n caplog.set_level('INFO')\n\n _request_create_user(SEED_USER_DATA)\n created_user = Advisor.objects.get(email=SEED_USER_DATA['email'])\n\n user_data_keys = SEED_USER_DATA.keys() - set(['token'])\n for key in user_data_keys:\n assert str(getattr(created_user, key)) == SEED_USER_DATA[key]\n\n user_info = [\n 'Creating a user: {',\n f' \"dit_team_id\": \"{SEED_USER_DATA[\"dit_team_id\"]}\",',\n f' \"email\": \"{SEED_USER_DATA[\"email\"]}\",',\n f' \"first_name\": \"{SEED_USER_DATA[\"first_name\"]}\",',\n f' \"last_name\": \"{SEED_USER_DATA[\"last_name\"]}\",',\n f' \"sso_email_user_id\": \"{SEED_USER_DATA[\"sso_email_user_id\"]}\"',\n '}',\n ]\n user_token = f'Created a token `{SEED_USER_DATA[\"token\"]}` for user {created_user.id}.'\n assert caplog.messages == [\n '\\n'.join(user_info),\n user_token,\n ]","def test_create_token_invalid_credentials(setup_client):\n client = setup_client\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'testpass',\n }\n create_user(**payload, **{'role': 'Supplier'})\n payload[\"password\"] = \"Something else\"\n res = client.post(TOKEN_URL, payload)\n assert \"token\" not in res.data\n assert res.status_code == status.HTTP_400_BAD_REQUEST","async def _token(self, user: discord.User = None, user_id: int = None):\n # This is to be used with the registration URL so that it doesn't contain\n # the user's ID in cleartext. This is so that person A cannot trivially\n # generate person B's URL and assign them to person A's team.\n if not user:\n user = self.bot.get_user(user_id)\n hashh = await self.config.user(user).digest()\n if hashh is None:\n salt = await self.config.user(user).secret()\n if salt is None:\n salt = random_salt()\n await self.config.user(user).secret.set(salt)\n hashh = digest(user.id, salt)\n await self.config.user(user).digest.set(hashh)\n await self.config.set_raw('undigest', hashh, value=user.id)\n return hashh","def token_gen_call(username, password, exp=None):\n #pdb.set_trace()\n \n #username_set = params['AUTH']['username_set']\n #password_set = params['AUTH']['password_set']\n username_set = username\n password_set = password\n \"\"\"\n Creates JWT Token\n :return:\n \"\"\"\n if exp is None:\n exp = datetime.utcnow() + timedelta(seconds=3600)\n _token = {\n 'aud': JWT_AUDIENCE,\n 'exp': exp,\n 'iss': JWT_ISSUER,\n 'user': username,\n 'role': 'admin',\n 'time':time.time()\n }\n _token.update(_token)\n \n if password_set == password and username_set == username: # example, don't do this in production\n return {\"token\" : jwt.encode(_token, SECRET_KEY, algorithm=JWT_OPTIONS_ALGORITHM).decode('utf-8') }\n return 'Invalid username and/or password for user: {0}'.format(username)","def create_new_user():\n return get_user_model().objects.create_user(\n email='test@gmail.com',\n password='test@londodnjisdjfois',\n username='tempusername'\n )","def new_user(cls, user):\r\n pass","def create_token_invalid_credentials(self):\n create_user(email='test@test.com', password='testpass')\n payload = {'email': 'test@test.com', 'password': 'wrong'}\n\n res = self.client.post(TOKEN_URL, payload)\n\n self.assertNotIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def test_create_token_invalid_credentials(self):\n\n credentials = {'email': 'testuser@gmail.com', 'password': 'Testpass12'}\n get_user_model().objects.create_user(**credentials)\n\n invalid_credentials = {\n 'email': 'testuser@gmail.com',\n 'password': 'wrong'\n }\n response = self.client.post(URL_TOKEN, invalid_credentials)\n\n # Check that the response is HTTP 400, and does not contain a token.\n self.assertNotIn('token', response.data)\n self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)","def gen_verification_token(user):\n exp_date = timezone.now() + timedelta(days= 3)\n payload = {\n 'user': user.username,\n 'exp': int (exp_date.timestamp()),\n 'type': 'email_confirmation'\n }\n token = jwt.encode(payload, settings.SECRET_KEY, algorithm= 'HS256')\n return token","def gen_verification_token(user):\n exp_date = timezone.now() + timedelta(days=3)\n payload = {\n 'user': user.username,\n 'exp': int(exp_date.timestamp()),\n 'type': 'email_confirmation'\n }\n # Generacion del token\n token = jwt.encode(payload, settings.SECRET_KEY, algorithm='HS256')\n return token","def generateAuthToken(self):\n try:\n payload = {\n 'exp': datetime.utcnow() + timedelta(days=0, minutes=30),\n 'iat': datetime.utcnow(),\n 'sub': self.id\n }\n return jwt.encode(payload, current_app.config['SECRET_KEY'], algorithm='HS256').decode()\n except Exception as error:\n print(error)\n return error","def add_user(self, username='TestUser', password='password',\n with_token=False):\n token = None\n user = User(login=username, password=crypto(username, password))\n if with_token:\n token = str(uuid.uuid4())\n user.last_token = token\n user.save()\n return token","def build_access_token_normal_user():\n return do_build_access_token(tenant_id='intility_tenant_id', admin=False)","def test_create_token_invalid_credentials(self):\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'testpass'\n }\n create_user(**payload)\n wrong_payload = {\n 'email': 'test@gmail.com',\n 'password': 'wrong'\n }\n res = self.client.post(TOKEN_URI, wrong_payload)\n self.assertNotIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def create_user(user_id, password_16char, public_key_32char):\n headers = {'Content-type': 'application/json'}\n payload = {'user_id': user_id\n , 'user_password': password_16char\n , 'public_key': public_key_32char}\n response = requests.post(\"http://localhost:5000/user/createUser\", data=json.dumps(payload), headers=headers)\n return response.text","def default_user(self):\n self.user = self.create_user(create_token=True)\n return","def create_user(email, password, f_name, l_name):\n pass","def new_user(cls, user):\n pass","def create_token(self,uid):\n token_str = self.get_random(5) + str(uid) + str(int(time.time()))\n m = hashlib.md5()\n m.update(token_str)\n return m.hexdigest()","def create_account(self, short_name, author_name=None, author_url=None,\n replace_token=True):\n response = self._telegraph.method('createAccount', values={\n 'short_name': short_name,\n 'author_name': author_name,\n 'author_url': author_url\n })\n\n if replace_token:\n self._telegraph.access_token = response.get('access_token')\n\n return response"],"string":"[\n \"def _create_auth_token(self, user=None):\\n token, created = Token.objects.get_or_create(user=user)\\n return token\",\n \"def create_token(user, title, expiration=_default_expiration_duration_opt):\\n if expiration == _default_expiration_duration_opt:\\n duration = _default_expiration_duration()\\n expiration = duration + datetime.now() if duration else None\\n\\n token_code = random_string_generator(TOKEN_NAME_PREFIX_LENGTH + MINIMUM_TOKEN_SUFFIX_LENGTH)()\\n token_name = token_code[:TOKEN_NAME_PREFIX_LENGTH]\\n token_secret = token_code[TOKEN_NAME_PREFIX_LENGTH:]\\n\\n assert token_name\\n assert token_secret\\n\\n return AppSpecificAuthToken.create(\\n user=user,\\n title=title,\\n expiration=expiration,\\n token_name=token_name,\\n token_secret=DecryptedValue(token_secret),\\n )\",\n \"def create_token(user):\\n access_token = create_access_token(user)\\n payload = jwt.decode(\\n access_token,\\n app.config['JWT_SECRET_KEY'],\\n algorithms=app.config['JWT_DECODE_ALGORITHMS'])\\n data = {\\n 'token':access_token,\\n 'username': user.username,\\n }\\n data.update(payload)\\n data['exp'] = datetime.fromtimestamp(data['exp'])\\n app.logger.debug(str(data))\\n if app.config.get('KEEP_TOKEN'):\\n # deletes old tokens\\n tokens = app.data.driver.db[config.DOMAIN['token']['datasource']['source']]\\n tokens.delete_many({'username': user.username})\\n # insets new token\\n result = app.data.insert('token', data)\\n return access_token, str(result[0])\\n\\n return access_token, None\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def post(self):\\n _purge_expired_user_tokens()\\n\\n request_dict = get_json_and_verify_params({\\n 'description': {'type': str, 'optional': True},\\n 'expiration_date': {'optional': True},\\n })\\n\\n expiration_date = request_dict.get('expiration_date')\\n if expiration_date:\\n expiration_date = parse_utc_datetime(\\n expiration_date, timezone=\\\"UTC\\\")\\n\\n return current_user.create_auth_token(request_dict.get('description'),\\n expiration_date)\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs): # pylint: disable=unused-argument\\n if created:\\n Token.objects.create(user=instance) # pylint: disable=no-member\",\n \"def create_token(user):\\n payload = {\\n 'sub': user.id,\\n 'iat': datetime.utcnow(),\\n 'exp': datetime.utcnow() + timedelta(days=1)\\n }\\n token = jwt.encode(payload, config.SECRET_KEY, algorithm='HS256')\\n return token.decode('unicode_escape')\",\n \"def set_auth_token_header(self):\\n\\n username = 'test-user'\\n passwd = 'testuserpass1234'\\n user = User.objects.create(username=username)\\n user.set_password(passwd)\\n user.save()\\n\\n assert Account.objects.get(user=user) is not None\\n url = reverse('token_obtain_pair')\\n res = self.client.post(url,\\n data={'username': username, 'password': passwd})\\n self.client.credentials(HTTP_AUTHORIZATION=\\n f\\\"Bearer {res.data['access']}\\\")\\n return user\",\n \"def create_auth_token(\\n username: str,\\n admin: t.Optional[bool] = False,\\n spotify: t.Optional[bool] = False,\\n) -> JWT:\\n auth_token: JWT = auth_manager.auth_token(\\n username, {\\\"admin\\\": admin, \\\"spotify\\\": spotify}\\n )\\n return auth_token\",\n \"def generate_token(user):\\n if JWT_AUTH:\\n payload = JWT_PAYLOAD_HANDLER(user)\\n return JWT_ENCODE_HANDLER(payload)\\n else:\\n token = Token.objects.create(user=user)\\n token.save()\\n return token\",\n \"def create_token(request, user):\\n\\n key = get_random_string(100)\\n data = {}\\n ip = get_client_ip_address(request)\\n\\n return Token.objects.create(user=user, key=key, data=json.dumps(data), ip=ip)\",\n \"def generate_token(user):\\n try:\\n # generate the auth token\\n auth_token = User.encode_auth_token(user.id)\\n response_object = {\\n \\\"status\\\": \\\"success\\\",\\n \\\"message\\\": \\\"Successfully registered.\\\",\\n \\\"Authorization\\\": auth_token.decode(),\\n }\\n return response_object, 201\\n except Exception as e:\\n response_object = {\\n \\\"status\\\": \\\"fail\\\",\\n \\\"message\\\": \\\"Some error occurred. Please try again.\\\",\\n }\\n return response_object, 401\",\n \"def test_create_token_for_user(self):\\r\\n payload = {\\r\\n 'email': 'test@max.net',\\r\\n 'password': 'Testpass123',\\r\\n 'name': 'Maks'\\r\\n }\\r\\n create_user(**payload)\\r\\n\\r\\n res = self.client.post(TOKEN_URL, payload)\\r\\n\\r\\n self.assertIn('token', res.data)\\r\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def test_create_token_for_user(self):\\n payload = {'email': 'test1@test1.ri',\\n 'password': 'testPassWord',\\n 'time_zone': 'Europe/Dublin'}\\n create_user(**payload)\\n res = self.client.post(TOKEN_URL, payload)\\n\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def test_create_token_for_user(self):\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'testpass'\\n }\\n create_user(**payload)\\n res = self.client.post(TOKEN_URI, payload)\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def test_create_token_for_user(self):\\n payload = {'email': 'test@test.com', 'password': 'testpass'}\\n create_user(**payload)\\n res = self.client.post(TOKEN_URL, payload)\\n\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def test_create_token_for_user(self):\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'abcd1234',\\n }\\n\\n create_user(**payload)\\n response = self.client.post(TOKEN_URL, payload)\\n\\n # We expect a token and should get a HTTP 200\\n self.assertIn('token', response.data)\\n self.assertEqual(response.status_code, status.HTTP_200_OK)\",\n \"def test_create_token_for_user(self):\\n\\n credentials = {'email': 'testuser@gmail.com', 'password': 'Testpass12'}\\n get_user_model().objects.create_user(**credentials)\\n\\n response = self.client.post(URL_TOKEN, credentials)\\n\\n # Check that the response is HTTP 200, and contains a token.\\n self.assertIn('token', response.data)\\n self.assertEqual(response.status_code, status.HTTP_200_OK)\",\n \"def token_auth(self):\\n self.client = APIClient()\\n self.user = User.objects.create_user(username='testuser', email='test@test.com', password='testpassword')\\n self.token = Token.objects.create(user=self.user)\\n self.client.credentials(HTTP_AUTHORIZATION='Token ' + self.token.key)\",\n \"def _create_user(userid, **kw):\\n\\n new_user = User(userid, **kw)\\n USERS[new_user.token] = new_user\\n return USERS[new_user.token]\",\n \"def newToken(self, description):\\n self.__require_privilaged_access()\\n with DBSession(self.__config_db) as session:\\n token = generate_session_token()\\n user = self.getLoggedInUser()\\n groups = ';'.join(self.__auth_session.groups)\\n session_token = Session(token, user, groups, description, False)\\n\\n session.add(session_token)\\n session.commit()\\n\\n LOG.info(\\\"New personal access token '%s...' has been generated \\\"\\n \\\"by '%s'.\\\", token[:5], self.getLoggedInUser())\\n\\n return SessionTokenData(token,\\n description,\\n str(session_token.last_access))\",\n \"def test_create_token_for_user(setup_client):\\n client = setup_client\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'testpass',\\n }\\n create_user(**payload, **{'role': 'Supplier'})\\n res = client.post(TOKEN_URL, payload)\\n assert \\\"token\\\" in res.data\\n assert res.status_code == status.HTTP_200_OK\",\n \"def create_auth_token():\\n data = get_request_data(request)\\n address = data.get(\\\"address\\\")\\n expiration = int(data.get(\\\"expiration\\\"))\\n\\n pk = get_provider_private_key(use_universal_key=True)\\n token = jwt.encode({\\\"exp\\\": expiration, \\\"address\\\": address}, pk, algorithm=\\\"HS256\\\")\\n token = token.decode(\\\"utf-8\\\") if isinstance(token, bytes) else token\\n\\n valid, message = is_token_valid(token, address)\\n if not valid:\\n if message == \\\"Token is deleted.\\\":\\n force_restore_token(token)\\n else:\\n return jsonify(error=message), 400\\n\\n return jsonify(token=token)\",\n \"def create_google_user(self, payload, user_data):\\n if not User.objects.filter(email=payload['email']).exists():\\n u = User()\\n u.generate_token()\\n u.email = payload['email']\\n u.name = payload['given_name'] or ''\\n u.surname = payload['family_name'] or ''\\n u.image_url = user_data['image_url'] or ''\\n u.google_id = user_data['id']\\n u.google_token = user_data['token']\\n u.save()\\n else:\\n u = User.objects.get(email=payload['email'])\\n\\n return u.token\",\n \"def generate_token(usr):\\n token = jwt.encode({\\\"user\\\":usr, \\\"exp\\\":datetime.datetime.utcnow()\\n + datetime.timedelta(minutes=30)}, KEY)\\n user = User.update(token=token).where(User.username == usr)\\n user.execute()\\n return token\",\n \"def generate_token_from_user(user, expires_at=None):\\n issued_at = datetime.utcnow()\\n token = AccessToken()\\n token.payload.update(\\n {\\n \\\"email\\\": user.email,\\n \\\"exp\\\": expires_at or issued_at + timedelta(days=2),\\n \\\"iat\\\": issued_at,\\n \\\"language\\\": user.language,\\n \\\"username\\\": user.username,\\n \\\"full_name\\\": user.get_full_name(),\\n }\\n )\\n return token\",\n \"def for_user(cls, user):\\n\\n token = super().for_user(user)\\n\\n TokenMeta.objects.get_or_create(\\n jti=token['jti'],\\n token=str(token),\\n )\\n\\n return token\",\n \"def insertNewUser(self,user, access_token):\\n newUser = UserToken(username=user, user_key = access_token.key, user_secret = access_token.secret)\\n newUser.put()\",\n \"def create_token(self, consumer, token_type, timestamp, user=None):\\n token, created = self.first_or_create(consumer=consumer, \\n token_type=token_type, \\n timestamp=timestamp,\\n user=user)\\n\\n if created:\\n token.key, token.secret = self.generate_random_codes()\\n token.save()\\n\\n return token\",\n \"def create(self, request):\\n token = AuthTokenClass().post(request)\\n return token\",\n \"def create(self, user, token):\\n\\n session['user'] = {\\n 'id': str(user.id),\\n 'login': user.login,\\n 'token': token\\n }\\n\\n return UserSession.create(session['user'])\",\n \"def create(self, request):\\n return ObtainAuthToken().post(request)\",\n \"def create(self,request):\\n return CustomAuthToken().post(request)\",\n \"def post(self, **kwargs):\\n username: str = request.json.get(\\\"username\\\", None)\\n password: str = request.json.get(\\\"password\\\", None)\\n user = get_user_instance(username, password)\\n return {\\\"access_token\\\": create_access_token(identity=user)}, 200\",\n \"def create_user(self):\\n username = \\\"\\\".join(choice(\\n string.ascii_letters) for x in range (randint(7,10)))\\n params = {\\n \\\"first_name\\\":\\\"ugali\\\",\\n \\\"last_name\\\":\\\"mayai\\\",\\n \\\"email\\\":\\\"ugalimayai@gmail.com\\\",\\n \\\"username\\\":username,\\n \\\"password\\\":\\\"password\\\"\\n }\\n path = \\\"/api/v2/auth/signup\\\"\\n user = self.client.post(path,\\n data=json.dumps(params),\\n content_type=\\\"application/json\\\")\\n \\n user_id = user.json['user_id']\\n auth_token = user.json['AuthToken']\\n return int(user_id), auth_token\",\n \"async def create_new_user(*, user: User):\\n with Session(engine) as session:\\n user.password = simple_hash(user.name, user.password) #Hashing password for security\\n session.add(user)\\n session.commit()\\n return {\\\"message\\\": \\\"User {user_id} created\\\".format(user_id = user.id)}\",\n \"def test_create_token(self):\\n data = {'email': 'test@test.com', 'password': 'testtest'}\\n sigin_in_user(**data)\\n payload = {\\n 'username': 'test@test.com',\\n 'password': 'testtest'\\n }\\n res = self.client.post(TOKEN_URL, payload)\\n \\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def create(self, request, *args, **kwargs):\\n serializer = self.get_serializer(data=request.data)\\n serializer.is_valid(raise_exception=True)\\n user = serializer.save()\\n headers = self.get_success_headers(serializer.data)\\n return Response(\\n dict(serializer.data, token=str(user.auth_token)),\\n status=status.HTTP_201_CREATED,\\n headers=headers\\n )\",\n \"def generate_new_token(uid):\\n random_token = uuid.uuid4()\\n token = TokenAuth(user_id=uid, token=random_token)\\n token.save()\\n return random_token\",\n \"def get_token(cls, user, full_result=False):\\n if user is None:\\n return EMPTY_KNOX_TOKEN\\n result = AuthToken.objects.create(user=user)\\n return result if full_result else result[1]\",\n \"def generate_token(user: dict):\\n\\n payload = {\\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=1),\\n 'iat': datetime.datetime.utcnow(),\\n 'user': user\\n }\\n token = jwt.encode(\\n payload,\\n os.getenv('SECRET_KEY'),\\n algorithm='HS256'\\n )\\n return token.decode('UTF-8')\",\n \"def post(self, request, *args, **kwargs):\\n self.create(request, *args, **kwargs)\\n token, created = Token.objects.get_or_create(user=self.user)\\n return Response({'token': token.key}, status=201)\",\n \"def create_jwt(user, secret):\\n logger.debug(\\\"Create JWT with secret %s\\\" % secret)\\n # username = request.POST['username']\\n # password = request.POST['password'\\n\\n expiry = datetime.datetime.now() + datetime.timedelta(seconds=30)\\n expiry_s = time.mktime(expiry.timetuple())\\n if user.is_authenticated():\\n internalid = user.authprofile.internalid\\n payload = {'username': user.username, 'expiry': expiry_s, 'type': \\\"AuthenticatedUser\\\", 'internalid': internalid, 'email': user.email}\\n token = jws.sign(payload, secret, algorithm='HS256')\\n else:\\n payload = {'expiry':expiry_s, 'type': \\\"AnonymousUser\\\", 'internalid': None, 'email': None}\\n token = jws.sign(payload, secret, algorithm='HS256')\\n logger.debug(\\\"Payload: %s\\\" % payload)\\n # logger.info(\\\"Token: %s\\\" % token)\\n return token\",\n \"def test_create_token_to_user(self):\\n data = {\\n 'email': 'test@test.com', \\n 'password': \\\"testtest\\\"\\n }\\n res = self.client.post(TOKEN_URL, data)\\n\\n self.assertNotIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def create(self, request):\\n\\n return ObtainAuthToken().post(request)\",\n \"def new_user(client, username, password, apikey=None, docs=None):\\n if apikey is None:\\n apikey = str(uuid.uuid4())\\n passhash = generate_password_hash(password, method='sha1')\\n user = User(username, passhash, apikey, docs=docs)\\n user.create(client)\\n return user\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n\\n if created:\\n # Generate API token for user.\\n api_token = Token.objects.create(user=instance)\\n\\n # Only create agent using username and API token for non-admin users.\\n if instance.is_superuser is False:\\n Agent.objects.create(scan_agent=instance, api_token=api_token)\",\n \"def authorize_user(case: APITestCase, user: User):\\n\\n token = Token.objects.create(user=user)\\n case.client.credentials(HTTP_AUTHORIZATION=f'Token {token}')\",\n \"def create(self, validated_data):\\n\\t\\tinstance = super(UserSerializer, self).create(validated_data)\\n\\t\\tinstance.set_password(validated_data['password'])\\n\\t\\ttoken = Token.objects.create(user=instance)\\n\\t\\tinstance.token = token\\n\\t\\treturn instance\",\n \"def create_user():\\n record = request.get_json()\\n if record is None:\\n return {\\\"Error\\\": \\\"No data Supplied.\\\"}, 400\\n\\n schema = user_schema.load(record)\\n\\n if UserModel.objects(email=schema['email']):\\n return {\\\"Error\\\": \\\"User Data already exists.\\\"}, 400\\n user = UserModel(**schema)\\n user.hash_password()\\n user.save()\\n ser_data = user_schema.dump(user)\\n token = Auth.generate_token(ser_data[\\\"_id\\\"])\\n return {\\\"message\\\": \\\"User Created Successfully\\\", \\\"Token\\\": token, \\\"id\\\": str(user.id)}, 200\",\n \"def make_token(self, user):\\n return super()._make_token_with_timestamp(user, int(time.time()))\",\n \"def create_token_missing_field(self):\\n payload = {'email': 'test@test.com', 'password': 'testpass'}\\n create_user(**payload)\\n payload = {'email': 'test@test.com', 'password': ''}\\n res = self.client.post(TOKEN_URL, payload)\\n self.assertNotIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def auth_token_generate(identity_param_val, expires_delta=False):\\n access_token = ''\\n try:\\n if expires_delta is not False:\\n expires_delta = timedelta(minutes=expires_delta)\\n access_token = create_access_token(identity=identity_param_val, expires_delta=expires_delta)\\n except Exception as e:\\n print(e)\\n\\n return access_token\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create_fake_JWT_token(userEmail):\\n pass\",\n \"def create_token_no_user(self):\\n payload = {'email': 'test@test.com', 'password': 'testpass'}\\n res = self.client.post(TOKEN_URL, payload)\\n self.assertNotIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"async def create_token(self, *args, **kwargs) -> OAuth2Token:\\n token = await super().create_token(*args, **kwargs)\\n # NOTE: Save data from token to db here.\\n return token\",\n \"def test_create_token_valid(self):\\n create_mock_user(**self.mock_user)\\n res = self.client.post(TOKEN_URL, self.mock_user)\\n\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\\n self.assertIn('token', res.data)\",\n \"def issue_user_token(user, salt):\\r\\n\\r\\n\\t\\tif user is not None:\\r\\n\\t\\t\\tif (salt == 'login'):\\r\\n\\t\\t\\t\\ttoken, _ = Token.objects.get_or_create(user=user)\\r\\n\\t\\t\\telse:\\r\\n\\t\\t\\t\\ttoken = signing.dumps({'pk': user.pk}, salt=salt)\\r\\n\\r\\n\\t\\t\\treturn token\\r\\n\\r\\n\\t\\treturn None\",\n \"def generate_token_for_user(user: User, expiration: datetime.timedelta=datetime.timedelta(days=7)):\\n\\n return generate_token({'id': user.id}, expiration)\",\n \"def create(self, validated_data):\\n request = self._kwargs['context']['request']\\n user = User.objects.create(**validated_data)\\n user.set_password(validated_data[\\\"password\\\"])\\n user.save()\\n category_list = ['Fuel', 'Bill', 'Entertainment', 'Education', 'Food']\\n for category in category_list:\\n user.user_categories.create(name=category)\\n login(request, user)\\n token, created = Token.objects.get_or_create(user=user)\\n validated_data[\\\"token\\\"] = token.key\\n return validated_data\",\n \"def create_user(UserName=None, MessageAction=None, FirstName=None, LastName=None, AuthenticationType=None):\\n pass\",\n \"def create_token(self):\\n ts_datetime = self.logged_at or self.created_at\\n ts = int(mktime(ts_datetime.timetuple()))\\n key = base64.encodestring(self.email)\\n base = \\\"{}{}\\\".format(key, ts)\\n salt, hsh = self.password.split('$')\\n return \\\"{}$${}\\\".format(key, get_hexdigest(salt, base))\",\n \"def token_generate(self, user_id):\\n try:\\n payload = {\\n 'exp': datetime.utcnow() + timedelta(minutes=200),\\n 'iat': datetime.utcnow(),\\n 'sub': user_id\\n }\\n encoded_token = jwt.encode(\\n payload, current_app.config['SECRET_KEY'], algorithm='HS256'\\n )\\n return encoded_token\\n\\n except Exception:\\n return str(Exception)\",\n \"def login(user: User):\\n try:\\n time = datetime.datetime.utcnow() + datetime.timedelta(seconds=60)\\n payload = {\\\"user_id\\\": user.name, \\\"password\\\": user.password, \\\"exp\\\": time}\\n token = jwt.encode(payload, JWT_SECRET_KEY, JWT_ALGORITHM).decode('utf-8')\\n return {\\\"token\\\": token}\\n except Exception:\\n return {\\\"message\\\": \\\"Error in creating Token\\\"}\",\n \"async def r_create_user(*_, role: str = \\\"USER\\\") -> User:\\n # create api object\\n password = token_hex(10)\\n # save to db\\n user = await User.create(\\n key=token_bytes(32),\\n username=token_hex(10),\\n password_hash=ARGON.hash(password),\\n role=role,\\n created=time(),\\n )\\n # set password field on user to pass them their password 1 time\\n user.password = password\\n # return api object to resolver\\n return user\",\n \"def generate_token(exp=None):\\n\\n secret_key = getenv('JWT_SECRET_KEY')\\n user = {\\n 'first_name': fake.name(),\\n 'last_name': fake.name(),\\n 'email': fake.email(),\\n 'is_admin': IsAdmin.yes,\\n 'password': fake.password()\\n }\\n\\n payload = {'id': str(User.find_or_create(user, email=user['email']).id)}\\n payload.__setitem__('exp', exp) if exp is not None else ''\\n token = jwt.encode(payload, secret_key, algorithm='HS256').decode(CHARSET)\\n return 'Bearer {0}'.format(token)\",\n \"def generate_token(user, expire_time=86400):\\n session = Session()\\n token = session.query(PasswordRecoveryToken)\\\\\\n .filter(PasswordRecoveryToken.user_id == user.user_id)\\\\\\n .first()\\n\\n if token is not None:\\n self.expire(token)\\n \\n token = PasswordRecoveryToken()\\n token.user_id = user.user_id\\n session.add(token)\\n \\n token.expiration = datetime.now() + timedelta(seconds=expire_time)\\n \\n sha_token = hashlib.sha224(user.login)\\n sha_token.update(user.password)\\n sha_token.update(str(token.expiration))\\n \\n token.token = sha_token.hexdigest()\\n print token.token\\n return token\",\n \"def create_token():\\n def token_helper():\\n token = util.prompt_for_user_token(username=\\\"robbo1992\\\", scope='user-library-read playlist-modify-private playlist-modify',\\n client_id=config[\\\"spotify\\\"][\\\"client_id\\\"], client_secret=config[\\\"spotify\\\"][\\\"secret_id\\\"],\\n redirect_uri='http://localhost:8080', cache_path=spotify_cache)\\n return token\\n if token_helper():\\n log.debug(\\\"Succesfully generated a spotify token for authentication\\\")\\n return spotipy.Spotify(auth=token_helper())\\n else:\\n if motley.internet:\\n if token_helper():\\n log.debug(\\\"Succesfully generated a spotify token for authentication\\\")\\n return spotipy.Spotify(auth=token_helper())\\n else:\\n log.error(\\\"Authentication error in create_token method.\\\")\",\n \"def _create_security_token(user):\\n timestamp = int(time.time())\\n plaintext = \\\"%x %s\\\" % (timestamp, user.email)\\n nearest_mult_of_16 = 16 * ((len(plaintext) + 15) // 16)\\n # Pad plaintest with whitespace to make the length a multiple of 16,\\n # as this is a requirement of AES encryption.\\n plaintext = plaintext.rjust(nearest_mult_of_16, ' ')\\n if _DISABLE_CRYPTO:\\n body = plaintext\\n sig = \\\"sig\\\"\\n else:\\n key_storage = KeyStorage.get()\\n body = AES.new(key_storage.aes_key, AES.MODE_CBC).encrypt(plaintext)\\n hmac_key = key_storage.hmac_key\\n if type(hmac_key) == unicode:\\n # Crypto requires byte strings\\n hmac_key = hmac_key.encode('utf8')\\n sig = HMAC.HMAC(key=hmac_key, msg=body).hexdigest()\\n return '%s:%s' % (sig, body)\",\n \"def create_token(self, token_type=DEFAULT_TOKEN, extra_data='{}'):\\n if token_type not in dict(TOKEN_TYPES).keys():\\n raise ValueError(\\\"Unable to create token, unknown type\\\")\\n\\n value = calc_checksum(self.email, salt=randint(0, maxint))\\n\\n return LoginToken.objects.create(user=self, value=value, token_type=token_type, extra_data=extra_data)\",\n \"def create_token(self, consumer, token_type, timestamp, scope,\\n user=None, callback=None, callback_confirmed=False):\\n token = self.create(consumer=consumer, \\n token_type=token_type, \\n timestamp=timestamp,\\n scope=scope,\\n user=user,\\n callback=callback,\\n callback_confirmed=callback_confirmed,\\n key=uuid.uuid4().hex,\\n secret=get_random_string(length=SECRET_SIZE))\\n\\n return token\",\n \"def post(self):\\n parser = reqparse.RequestParser()\\n parser.add_argument('username', help='Required field', required=True)\\n parser.add_argument('password', help='Required field', required=True)\\n args = parser.parse_args()\\n\\n existing_user = users_db.get_user_by_username(args['username'])\\n if not existing_user:\\n # Create new user\\n hashed_password = BCRYPT.generate_password_hash(args['password']).decode('utf-8')\\n user_id = users_db.create_user(\\n {\\n 'username': args['username'],\\n 'password': hashed_password\\n }\\n )\\n\\n # Use create_access_token() and create_refresh_token()\\n # to create our access and refresh tokens\\n response, status = {\\n 'message': 'User <{0}> was successfully created: id={1}'.format(\\n args['username'], user_id\\n ),\\n 'access_token': create_access_token(identity=str(user_id)),\\n 'refresh_token': create_refresh_token(identity=str(user_id))\\n }, 201\\n else:\\n # check password of existing user and create new jwt token\\n if BCRYPT.check_password_hash(existing_user[0]['password'], args['password']):\\n response, status = {\\n 'message': 'User <{0}> was successfully logged in'.format(\\n existing_user[0]['username']\\n ),\\n 'access_token': create_access_token(identity=str(existing_user[0]['_id'])),\\n 'refresh_token': create_refresh_token(identity=str(existing_user[0]['_id']))\\n }, 200\\n else:\\n response, status = {\\n 'message': 'Invalid user password'\\n }, 400\\n\\n return Response(dumps(response), status=status, mimetype='application/json')\",\n \"def test_create_user_endpoint_creates_user(caplog):\\n caplog.set_level('INFO')\\n\\n _request_create_user(SEED_USER_DATA)\\n created_user = Advisor.objects.get(email=SEED_USER_DATA['email'])\\n\\n user_data_keys = SEED_USER_DATA.keys() - set(['token'])\\n for key in user_data_keys:\\n assert str(getattr(created_user, key)) == SEED_USER_DATA[key]\\n\\n user_info = [\\n 'Creating a user: {',\\n f' \\\"dit_team_id\\\": \\\"{SEED_USER_DATA[\\\"dit_team_id\\\"]}\\\",',\\n f' \\\"email\\\": \\\"{SEED_USER_DATA[\\\"email\\\"]}\\\",',\\n f' \\\"first_name\\\": \\\"{SEED_USER_DATA[\\\"first_name\\\"]}\\\",',\\n f' \\\"last_name\\\": \\\"{SEED_USER_DATA[\\\"last_name\\\"]}\\\",',\\n f' \\\"sso_email_user_id\\\": \\\"{SEED_USER_DATA[\\\"sso_email_user_id\\\"]}\\\"',\\n '}',\\n ]\\n user_token = f'Created a token `{SEED_USER_DATA[\\\"token\\\"]}` for user {created_user.id}.'\\n assert caplog.messages == [\\n '\\\\n'.join(user_info),\\n user_token,\\n ]\",\n \"def test_create_token_invalid_credentials(setup_client):\\n client = setup_client\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'testpass',\\n }\\n create_user(**payload, **{'role': 'Supplier'})\\n payload[\\\"password\\\"] = \\\"Something else\\\"\\n res = client.post(TOKEN_URL, payload)\\n assert \\\"token\\\" not in res.data\\n assert res.status_code == status.HTTP_400_BAD_REQUEST\",\n \"async def _token(self, user: discord.User = None, user_id: int = None):\\n # This is to be used with the registration URL so that it doesn't contain\\n # the user's ID in cleartext. This is so that person A cannot trivially\\n # generate person B's URL and assign them to person A's team.\\n if not user:\\n user = self.bot.get_user(user_id)\\n hashh = await self.config.user(user).digest()\\n if hashh is None:\\n salt = await self.config.user(user).secret()\\n if salt is None:\\n salt = random_salt()\\n await self.config.user(user).secret.set(salt)\\n hashh = digest(user.id, salt)\\n await self.config.user(user).digest.set(hashh)\\n await self.config.set_raw('undigest', hashh, value=user.id)\\n return hashh\",\n \"def token_gen_call(username, password, exp=None):\\n #pdb.set_trace()\\n \\n #username_set = params['AUTH']['username_set']\\n #password_set = params['AUTH']['password_set']\\n username_set = username\\n password_set = password\\n \\\"\\\"\\\"\\n Creates JWT Token\\n :return:\\n \\\"\\\"\\\"\\n if exp is None:\\n exp = datetime.utcnow() + timedelta(seconds=3600)\\n _token = {\\n 'aud': JWT_AUDIENCE,\\n 'exp': exp,\\n 'iss': JWT_ISSUER,\\n 'user': username,\\n 'role': 'admin',\\n 'time':time.time()\\n }\\n _token.update(_token)\\n \\n if password_set == password and username_set == username: # example, don't do this in production\\n return {\\\"token\\\" : jwt.encode(_token, SECRET_KEY, algorithm=JWT_OPTIONS_ALGORITHM).decode('utf-8') }\\n return 'Invalid username and/or password for user: {0}'.format(username)\",\n \"def create_new_user():\\n return get_user_model().objects.create_user(\\n email='test@gmail.com',\\n password='test@londodnjisdjfois',\\n username='tempusername'\\n )\",\n \"def new_user(cls, user):\\r\\n pass\",\n \"def create_token_invalid_credentials(self):\\n create_user(email='test@test.com', password='testpass')\\n payload = {'email': 'test@test.com', 'password': 'wrong'}\\n\\n res = self.client.post(TOKEN_URL, payload)\\n\\n self.assertNotIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def test_create_token_invalid_credentials(self):\\n\\n credentials = {'email': 'testuser@gmail.com', 'password': 'Testpass12'}\\n get_user_model().objects.create_user(**credentials)\\n\\n invalid_credentials = {\\n 'email': 'testuser@gmail.com',\\n 'password': 'wrong'\\n }\\n response = self.client.post(URL_TOKEN, invalid_credentials)\\n\\n # Check that the response is HTTP 400, and does not contain a token.\\n self.assertNotIn('token', response.data)\\n self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def gen_verification_token(user):\\n exp_date = timezone.now() + timedelta(days= 3)\\n payload = {\\n 'user': user.username,\\n 'exp': int (exp_date.timestamp()),\\n 'type': 'email_confirmation'\\n }\\n token = jwt.encode(payload, settings.SECRET_KEY, algorithm= 'HS256')\\n return token\",\n \"def gen_verification_token(user):\\n exp_date = timezone.now() + timedelta(days=3)\\n payload = {\\n 'user': user.username,\\n 'exp': int(exp_date.timestamp()),\\n 'type': 'email_confirmation'\\n }\\n # Generacion del token\\n token = jwt.encode(payload, settings.SECRET_KEY, algorithm='HS256')\\n return token\",\n \"def generateAuthToken(self):\\n try:\\n payload = {\\n 'exp': datetime.utcnow() + timedelta(days=0, minutes=30),\\n 'iat': datetime.utcnow(),\\n 'sub': self.id\\n }\\n return jwt.encode(payload, current_app.config['SECRET_KEY'], algorithm='HS256').decode()\\n except Exception as error:\\n print(error)\\n return error\",\n \"def add_user(self, username='TestUser', password='password',\\n with_token=False):\\n token = None\\n user = User(login=username, password=crypto(username, password))\\n if with_token:\\n token = str(uuid.uuid4())\\n user.last_token = token\\n user.save()\\n return token\",\n \"def build_access_token_normal_user():\\n return do_build_access_token(tenant_id='intility_tenant_id', admin=False)\",\n \"def test_create_token_invalid_credentials(self):\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'testpass'\\n }\\n create_user(**payload)\\n wrong_payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'wrong'\\n }\\n res = self.client.post(TOKEN_URI, wrong_payload)\\n self.assertNotIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def create_user(user_id, password_16char, public_key_32char):\\n headers = {'Content-type': 'application/json'}\\n payload = {'user_id': user_id\\n , 'user_password': password_16char\\n , 'public_key': public_key_32char}\\n response = requests.post(\\\"http://localhost:5000/user/createUser\\\", data=json.dumps(payload), headers=headers)\\n return response.text\",\n \"def default_user(self):\\n self.user = self.create_user(create_token=True)\\n return\",\n \"def create_user(email, password, f_name, l_name):\\n pass\",\n \"def new_user(cls, user):\\n pass\",\n \"def create_token(self,uid):\\n token_str = self.get_random(5) + str(uid) + str(int(time.time()))\\n m = hashlib.md5()\\n m.update(token_str)\\n return m.hexdigest()\",\n \"def create_account(self, short_name, author_name=None, author_url=None,\\n replace_token=True):\\n response = self._telegraph.method('createAccount', values={\\n 'short_name': short_name,\\n 'author_name': author_name,\\n 'author_url': author_url\\n })\\n\\n if replace_token:\\n self._telegraph.access_token = response.get('access_token')\\n\\n return response\"\n]"},"negative_scores":{"kind":"list like","value":["0.7601047","0.7413485","0.7076036","0.70279247","0.70279247","0.70279247","0.6908097","0.68845016","0.683764","0.68366253","0.6822452","0.6817627","0.68121517","0.6806323","0.67799586","0.6771342","0.676491","0.67617136","0.6744228","0.67380023","0.668147","0.66268677","0.6613045","0.660879","0.65834117","0.6496971","0.6480837","0.6447179","0.6446974","0.64392906","0.6407566","0.6359538","0.63285154","0.63216835","0.62730855","0.6271753","0.6267881","0.6261526","0.6251311","0.6240688","0.6238316","0.61928886","0.61924297","0.61919177","0.61906165","0.61901593","0.6167083","0.6160513","0.6159672","0.613919","0.6138683","0.6130583","0.6128868","0.61206627","0.6109322","0.6074863","0.6074863","0.6074863","0.6074863","0.6074863","0.6074863","0.60724163","0.60536456","0.60474616","0.6039723","0.6027003","0.6019266","0.6012439","0.5996157","0.59951603","0.59841335","0.5983542","0.59769326","0.5970406","0.5960097","0.59580415","0.595518","0.59436995","0.591753","0.59125125","0.591038","0.5901625","0.58892876","0.58685285","0.58652484","0.5859687","0.5843304","0.5826938","0.5825239","0.58169013","0.58141387","0.5812102","0.58052546","0.57943016","0.5790545","0.5782189","0.5775316","0.57717836","0.5769745","0.57674825"],"string":"[\n \"0.7601047\",\n \"0.7413485\",\n \"0.7076036\",\n \"0.70279247\",\n \"0.70279247\",\n \"0.70279247\",\n \"0.6908097\",\n \"0.68845016\",\n \"0.683764\",\n \"0.68366253\",\n \"0.6822452\",\n \"0.6817627\",\n \"0.68121517\",\n \"0.6806323\",\n \"0.67799586\",\n \"0.6771342\",\n \"0.676491\",\n \"0.67617136\",\n \"0.6744228\",\n \"0.67380023\",\n \"0.668147\",\n \"0.66268677\",\n \"0.6613045\",\n \"0.660879\",\n \"0.65834117\",\n \"0.6496971\",\n \"0.6480837\",\n \"0.6447179\",\n \"0.6446974\",\n \"0.64392906\",\n \"0.6407566\",\n \"0.6359538\",\n \"0.63285154\",\n \"0.63216835\",\n \"0.62730855\",\n \"0.6271753\",\n \"0.6267881\",\n \"0.6261526\",\n \"0.6251311\",\n \"0.6240688\",\n \"0.6238316\",\n \"0.61928886\",\n \"0.61924297\",\n \"0.61919177\",\n \"0.61906165\",\n \"0.61901593\",\n \"0.6167083\",\n \"0.6160513\",\n \"0.6159672\",\n \"0.613919\",\n \"0.6138683\",\n \"0.6130583\",\n \"0.6128868\",\n \"0.61206627\",\n \"0.6109322\",\n \"0.6074863\",\n \"0.6074863\",\n \"0.6074863\",\n \"0.6074863\",\n \"0.6074863\",\n \"0.6074863\",\n \"0.60724163\",\n \"0.60536456\",\n \"0.60474616\",\n \"0.6039723\",\n \"0.6027003\",\n \"0.6019266\",\n \"0.6012439\",\n \"0.5996157\",\n \"0.59951603\",\n \"0.59841335\",\n \"0.5983542\",\n \"0.59769326\",\n \"0.5970406\",\n \"0.5960097\",\n \"0.59580415\",\n \"0.595518\",\n \"0.59436995\",\n \"0.591753\",\n \"0.59125125\",\n \"0.591038\",\n \"0.5901625\",\n \"0.58892876\",\n \"0.58685285\",\n \"0.58652484\",\n \"0.5859687\",\n \"0.5843304\",\n \"0.5826938\",\n \"0.5825239\",\n \"0.58169013\",\n \"0.58141387\",\n \"0.5812102\",\n \"0.58052546\",\n \"0.57943016\",\n \"0.5790545\",\n \"0.5782189\",\n \"0.5775316\",\n \"0.57717836\",\n \"0.5769745\",\n \"0.57674825\"\n]"},"document_score":{"kind":"string","value":"0.70019704"},"document_rank":{"kind":"string","value":"6"}}},{"rowIdx":8572,"cells":{"query":{"kind":"string","value":"Creates a new compartment in the specified compartment."},"document":{"kind":"string","value":"def create_compartment(self, create_compartment_details, **kwargs):\n resource_path = \"/compartments\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_compartment got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_compartment_details,\n response_type=\"Compartment\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_compartment_details,\n response_type=\"Compartment\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def createCompartment(self):\n return _libsbml.Model_createCompartment(self)","def addCompartment(self, vol=1, comp_id=\"\"):\n\n c1 = self.model.createCompartment()\n self.check(c1, \"create compartment\")\n if len(comp_id) == 0:\n comp_id = \"c\" + str(self.model.getNumCompartments())\n self.check(c1.setId(comp_id), \"set compartment id\")\n self.check(c1.setConstant(True), 'set compartment \"constant\"')\n self.check(c1.setSpatialDimensions(3), \"set compartment dimensions\")\n\n self.check(c1.setSize(vol), 'set compartment \"size\"')\n self.check(c1.setUnits(\"litre\"), \"set compartment size units\")\n return c1","def addCompartment(self, *args):\n return _libsbml.Model_addCompartment(self, *args)","def __init__(self, *args):\n this = _libsbml.new_CompartmentType(*args)\n try: self.this.append(this)\n except: self.this = this","def createCompartmentType(self):\n return _libsbml.Model_createCompartmentType(self)","def __init__(self, *args):\n this = _libsbml.new_Compartment(*args)\n try: self.this.append(this)\n except: self.this = this","def add_compartment(self, Vp=1, Qp=1):\n self.__n_compartments += 1\n self.__compartments.append({'Vp': Vp, 'Qp': Qp})","def create_new_component(self, cname):\n while True:\n try:\n self.model.get_component_by_name(cname)\n cname += u'_'\n except KeyError:\n # Component with this name doesn't exist\n break\n # Create the component\n comp = cellml_component.create_new(self.model, cname)\n self.model._add_component(comp)\n return comp","def setCompartment(self, *args):\n return _libsbml.CompartmentReference_setCompartment(self, *args)","def createCompartmentReference(self):\n return _libsbml.MultiCompartmentPlugin_createCompartmentReference(self)","def setCompartment(self, *args):\n return _libsbml.Reaction_setCompartment(self, *args)","def createObject(self, *args):\n return _libsbml.MultiCompartmentPlugin_createObject(self, *args)","def setCompartment(self, *args):\n return _libsbml.Species_setCompartment(self, *args)","def addCompartmentType(self, *args):\n return _libsbml.Model_addCompartmentType(self, *args)","def createCompartmentGlyph(self):\n return _libsbml.Layout_createCompartmentGlyph(self)","def addCompartmentGlyph(self, *args):\n return _libsbml.Layout_addCompartmentGlyph(self, *args)","def container(name, ostemplate, **kwargs):\n if not openvz.exists(name):\n ctid = openvz.get_available_ctid()\n openvz.create(ctid, ostemplate=ostemplate, **kwargs)\n openvz.set(ctid, name=name)\n return Container(name)","def add_comp(self, name, ctype):\n\n name = self.name + '.' + name\n\n assert name not in self.components, 'A component named \\'{}\\' already exists for node \\'{}\\''.format(\n name, self.name)\n\n try:\n cls = co.str_to_comp(ctype)\n except AttributeError:\n try:\n cls = rc.str_to_comp(ctype)\n except AttributeError:\n cls = None\n\n if cls:\n obj = cls(name=name,\n temperature_driven=self.temperature_driven,\n repr_days=self.repr_days)\n else:\n raise ValueError(\n \"%s is not a valid class name! (component is %s, in node %s)\" % (\n ctype, name, self.name))\n\n self.logger.info('Component {} added to {}'.format(name, self.name))\n\n self.components[name] = obj","def setCompartmentType(self, *args):\n return _libsbml.Compartment_setCompartmentType(self, *args)","def create(cls, name, container_object, enable=True, optional_attributes={}):\n assert type(name) == str\n assert container_object.__class__.__name__ == 'ADContainer'\n return container_object.create_computer(name=name,enable=enable,optional_attributes=optional_attributes)","def setCompartment(self, *args):\n return _libsbml.QualitativeSpecies_setCompartment(self, *args)","def addCompartmentReference(self, *args):\n return _libsbml.MultiCompartmentPlugin_addCompartmentReference(self, *args)","def firmware_pack_create(handle, org_name, name, rack_bundle_version,\n blade_bundle_version, descr=\"\", mode=\"staged\",\n org_parent=\"org-root\"):\n\n org_dn = org_parent + \"/org-\" + org_name\n p_mo = handle.query_dn(org_dn)\n if not p_mo:\n log.info(\"Sub-Org <%s> not found!\" % org_name)\n else:\n from ucsmsdk.mometa.firmware.FirmwareComputeHostPack import\\\n FirmwareComputeHostPack\n\n mo = FirmwareComputeHostPack(parent_mo_or_dn=org_dn,\n name=name,\n descr=descr,\n rack_bundle_version=rack_bundle_version,\n mode=mode,\n blade_bundle_version=blade_bundle_version)\n handle.add_mo(mo)\n handle.commit()","def compartment_id(self, compartment_id):\n self._compartment_id = compartment_id","def compartment_id(self, compartment_id):\n self._compartment_id = compartment_id","def setCompartment(self, *args):\n return _libsbml.MultiSpeciesType_setCompartment(self, *args)","def clone(self):\n return _libsbml.Compartment_clone(self)","def createappendcomp(self, componentname, componentclass, *args, **kwargs):\n component = componentclass(self, self.debugmode, *args, **kwargs)\n self.components.append(componentname, component)\n return component","def clone(self):\n return _libsbml.CompartmentType_clone(self)","def create(\n cls, component_config: Dict[Text, Any], config: DazuConfig\n ) -> \"Component\":\n\n # Check language supporting\n language = config.language\n if not cls.can_handle_language(language):\n # check failed\n raise UnsupportedLanguageError(cls.name, language)\n\n return cls(component_config)","def createElement(tagName):\n print(\"Warning: createElement is deprecated in favor of createComponent\")\n return createComponent(tagName)","def create_port(self, port):\n try:\n backend_id = self.client.create_nic(\n port.vm.backend_id, port.network.backend_id\n )\n except VMwareError as e:\n raise VMwareBackendError(e)\n else:\n port.backend_id = backend_id\n port.save(update_fields=['backend_id'])\n return port","def env_creator(env_config):\n return CartPoleBTEnv(\n goal_state=env_config['goal_state'],\n disturbances=env_config['disturbances'],\n initial_state=env_config['initial_state'],\n initial_state_variance=env_config['initial_state_variance']\n )","def setCompartmentType(self, *args):\n return _libsbml.MultiCompartmentPlugin_setCompartmentType(self, *args)","def create(cls, name, mac_address, comment=None):\n comment = comment if comment else ''\n cls.json = {'name': name,\n 'address': mac_address,\n 'comment': comment}\n return ElementCreator(cls)","def getCompartment(self, *args):\n return _libsbml.Model_getCompartment(self, *args)","def create(args):\n print('Creates an HPC fleet with given name \"{}\"'.format(args.fleet_name))","def setCompartmentId(self, *args):\n return _libsbml.CompartmentGlyph_setCompartmentId(self, *args)","def create_vlan_pool(self, vlan_pool_name, allocation_mode):\n VlanInstP_mo = VlanInstP('uni/infra/', vlan_pool_name, allocation_mode)\n self.commit(VlanInstP_mo)\n return VlanInstP_mo","def make_component(self, name=\"Face\") -> 'Component':\n return BRepComponent(self.brep, component=self.component, name=name)","def ec_contaier_create(self, oclass):\n # Get container params\n self.ec_container = TestContainer(\n self.pool, daos_command=DaosCommand(self.bin))\n self.ec_container.get_params(self)\n self.ec_container.oclass.update(oclass)\n # update object class for container create, if supplied\n # explicitly.\n ec_object = self.get_data_parity_number(oclass)\n self.ec_container.properties.update(\"rf:{}\".format(ec_object['parity']))\n\n # create container\n self.ec_container.create()","def create_environment(cls, full_config):\n\n config = full_config['template']['devops_settings']\n environment = cls.create(config['env_name'])\n\n # create groups and drivers\n groups = config['groups']\n environment.add_groups(groups)\n\n # create address pools\n address_pools = config['address_pools']\n environment.add_address_pools(address_pools)\n\n # process group items\n for group_data in groups:\n group = environment.get_group(name=group_data['name'])\n\n # add l2_network_devices\n group.add_l2_network_devices(\n group_data.get('l2_network_devices', {}))\n\n # add network_pools\n group.add_network_pools(\n group_data.get('network_pools', {}))\n\n # Connect nodes to already created networks\n for group_data in groups:\n group = environment.get_group(name=group_data['name'])\n\n # add group volumes\n group.add_volumes(\n group_data.get('group_volumes', []))\n\n # add nodes\n group.add_nodes(\n group_data.get('nodes', []))\n\n return environment","def create_instance(c_instance):\n return AumPC40(c_instance)","def set_compartment(self, label, init_val=0.):\n assert type(label) is str, 'Compartment label for initial setting not string'\n assert type(init_val) is float or type(init_val) is int, 'Value to start % compartment from not string' % label\n assert init_val >= 0., 'Start with negative compartment not permitted'\n if label not in self.labels:\n self.labels.append(label)\n self.init_compartments[label] = init_val","def _create_org(org_name, org_status):\n new_org = OcOrg().setup_org(name=org_name, status=org_status)\n\n return new_org","def create_container(self, hostname, container_id, endpoint):\n\n endpoint_path = ENDPOINT_PATH % {\"hostname\": hostname,\n \"container_id\": container_id,\n \"endpoint_id\": endpoint.id}\n\n _log.info(\"Creating endpoint at %s\", endpoint_path)\n try:\n self.client.write(endpoint_path + \"addrs\", json.dumps(endpoint.addrs))\n self.client.write(endpoint_path + \"mac\", endpoint.mac)\n self.client.write(endpoint_path + \"state\", endpoint.state)\n except etcd.EtcdException as e:\n _log.exception(\"Hit Exception %s writing to etcd.\", e)\n pass","def create_board(self, board_id, comp):\n new_board = self.create_board_from_template(board_id)\n comp.answer(new_board.id)","def create(\n location: str,\n outputdir: pathlib.Path,\n *,\n extrabindings: Sequence[Binding],\n interactive: bool,\n revision: Optional[str],\n directory: Optional[pathlib.Path],\n in_place: bool,\n) -> None:\n config = ProjectConfig(location, (), revision, directory)\n\n with createproject(\n config, userbindings=extrabindings, interactive=interactive\n ) as project:\n projectdir = outputdir if in_place else outputdir / project.name\n repository = ProjectRepository.create(projectdir, message=\"Initial commit\")\n commit = commitproject(repository, project, commitmessage=createcommitmessage)\n\n repository.import_(commit)","def create_node(self, node_cfg):\n with self.__connect_node(node_cfg) as conn:\n self._provision_node(conn, node_cfg)\n self._bootup_node(conn)","def build(cmpd, density=0.5*u.gram/(u.cm**3), n_compounds=1000, \n ff='ff/TraPPE_UA_3_fully_flexible_propane.xml'):\n density.convert_to_units(u.kilogram/u.m**3)\n\n # Pack a box\n box = mb.fill_box(cmpd, n_compounds=n_compounds, density=density.value)\n\n # Wrap coordinates\n new_xyz = box.xyz - 1 * np.floor_divide(box.xyz, box.periodicity) * box.periodicity\n box.xyz = new_xyz\n\n # Apply non-atomistic, custom element naming convention\n for part in box.particles():\n part.name = \"_\" + part.name\n\n # Utilize foyer to parametrize our box\n ff = foyer.Forcefield(forcefield_files=ff)\n box = box.to_parmed(infer_residues=True)\n parametrized_structure = ff.apply(box, combining_rule='lorentz')\n\n # Dump initial coordinates\n parametrized_structure.save('compound.pdb', overwrite=True)\n parametrized_structure.save('compound.mol2', overwrite=True)\n parametrized_structure.save('compound.gro', overwrite=True)\n\n return parametrized_structure","def CreateComponent(self, name, state):\n component = SimpleTestClientComponent()\n component.__dict__.update(state)\n return component","def create(self):\n config = {}\n for key in ('ident', 'cgroupparent', 'infra', 'labels', 'share'):\n config[key] = self.opts.get(key)\n\n try:\n pod = self.client.pods.create(**config)\n except podman.ErrorOccurred as ex:\n sys.stdout.flush()\n print(\n '{}'.format(ex.reason).capitalize(),\n file=sys.stderr,\n flush=True)\n else:\n print(pod.id)","def createComponent(tagName):\n\n class Component():\n \"\"\"A basic class for a virtual DOM Component\"\"\"\n def __init__(self, *children, **kwargs):\n self.children = _flatten_children(*children, **kwargs)\n self.attributes = kwargs\n self.tagName = tagName\n\n def _repr_mimebundle_(self, include, exclude, **kwargs):\n return {\n 'application/vdom.v1+json': toJSON(self),\n 'text/plain': '<{tagName} />'.format(tagName=tagName)\n }\n \n Component.__doc__ = \"\"\"A virtual DOM component for a {tagName} tag\n \n >>> {tagName}()\n <{tagName} />\n \"\"\".format(tagName=tagName)\n \n return Component","def create_host(self, conf, tenant_id, network_id, params):\n\t\tpass","def __create_cont(self, path, filesystem, cont_stat, component_number):\n try:\n self.logger.debug('Create container interface called')\n status_obj = Status()\n cont_id = \"container\"\n #cont_id = get_container_id()\n tmp_path = '%s/%s/%s/%s/%s' % (self.__fs_base, \\\n filesystem, TMPDIR, cont_id,component_number)\n self.asyn_helper.call(\"create_container\", \\\n tmp_path, path, cont_stat, status_obj)\n return status_obj\n except Exception as err:\n self.logger.error(('create_container for %(con_dir)s failed ',\n 'close failure: %(exc)s : %(stack)s'),\n {'con_dir' : path, \n 'exc': err, 'stack': ''.join(traceback.format_stack())})\n raise err","def create_port(self, component):\n if self.fixed_size is not None and not self.array:\n raise ValueError(\n \"{}.{}: @{}port specified fixed_size but not array=True\".format(\n self, self.name,\n self.kind))\n ptype = self.get_port_type()\n return ptype(component, **self.data)","def __init__(self, *args):\n this = _libsbml.new_MultiCompartmentPlugin(*args)\n try: self.this.append(this)\n except: self.this = this","def __init__(self, *args):\n this = _libsbml.new_ListOfCompartmentTypes(*args)\n try: self.this.append(this)\n except: self.this = this","def newChemCompVar(self, **attrlinks):\n return ChemCompVar(self, **attrlinks)","def mkcomponent(self,\n context=[],\n componentobj=None):\n if componentobj == None:\n raise ValueError, \"mkcomponent: componentobj is None\"\n return jsoncall.do_call(\"mkcomponent\", {'modelname':self.modelname,\\\n 'user':self.user,\\\n 'password':self.password,\\\n 'context':context,\\\n 'componentobj':componentobj.__dict__},\n self.connection)","def test_create_new_placements(self):\n subv = SimpleMachineVertex(None, \"\")\n pl = Placement(subv, 0, 0, 1)\n Placements([pl])","def createComplejoPlatino(c_dict):\n\tnom = c_dict['nombre'].split()\n\tnom.insert(1, 'Platino')\n\tnombre = ' '.join(nom)\n\tc_dict['nombre'] = nombre\n\tc_dict['id_org'] = int(c_dict['id_org']) + 10000\n\tcreateComplejo(c_dict)","def create():","def create():","def createAllocation(name, tag, facility):\n return Allocation(Cuebot.getStub('allocation').Create(\n facility_pb2.AllocCreateRequest(name=name, tag=tag, facility=facility),\n timeout=Cuebot.Timeout).allocation)","def _env_create(name_or_path, init_file=None, dir=False, with_view=None, keep_relative=False):\n if dir:\n env = ev.Environment(name_or_path, init_file, with_view, keep_relative)\n env.write()\n tty.msg(\"Created environment in %s\" % env.path)\n tty.msg(\"You can activate this environment with:\")\n tty.msg(\" spack env activate %s\" % env.path)\n else:\n env = ev.create(name_or_path, init_file, with_view, keep_relative)\n env.write()\n tty.msg(\"Created environment '%s' in %s\" % (name_or_path, env.path))\n tty.msg(\"You can activate this environment with:\")\n tty.msg(\" spack env activate %s\" % (name_or_path))\n return env","def add_cable(self, env, size_range, info={}, cable_idx=0,\n direction='z', max_force=100):\n num_parts = self.num_parts\n radius = self.radius\n length = self.length\n color = self.colors[cable_idx] + [1]\n color_end = U.COLORS['yellow'] + [1]\n\n # Add beaded cable.\n distance = length / num_parts\n position, _ = self.random_pose(env, size_range)\n position = np.float32(position)\n part_shape = p.createCollisionShape(p.GEOM_BOX, halfExtents=[radius]*3)\n part_visual = p.createVisualShape(p.GEOM_SPHERE, radius=radius*1.5)\n\n # Iterate through parts and create constraints as needed.\n for i in range(num_parts):\n if direction == 'x':\n position[0] += distance\n parent_frame = (distance, 0, 0)\n elif direction == 'y':\n position[1] += distance\n parent_frame = (0, distance, 0)\n else:\n position[2] += distance\n parent_frame = (0, 0, distance)\n\n part_id = p.createMultiBody(0.1, part_shape, part_visual,\n basePosition=position)\n if i > 0:\n constraint_id = p.createConstraint(\n parentBodyUniqueId=env.objects[-1],\n parentLinkIndex=-1,\n childBodyUniqueId=part_id,\n childLinkIndex=-1,\n jointType=p.JOINT_POINT2POINT,\n jointAxis=(0, 0, 0),\n parentFramePosition=parent_frame,\n childFramePosition=(0, 0, 0))\n p.changeConstraint(constraint_id, maxForce=max_force)\n\n if (i > 0) and (i < num_parts - 1):\n p.changeVisualShape(part_id, -1, rgbaColor=color)\n elif i == num_parts - 1:\n p.changeVisualShape(part_id, -1, rgbaColor=color_end)\n\n # The usual for tracking IDs. Four things to add.\n self.cable_bead_IDs.append(part_id)\n self._IDs[part_id] = f'cable_part_{str(part_id).zfill(2)}'\n env.objects.append(part_id)\n self.object_points[part_id] = np.float32((0, 0, 0)).reshape(3, 1)\n\n # Get target placing positions for each cable bead, if applicable.\n if self._name == 'cable-shape' or self._name == 'cable-shape-notarget' or \\\n self._name == 'cable-line-notarget':\n # ----------------------------------------------------------- #\n # Here, zone_pose = square_pose, unlike Ravens cable, where the\n # zone_pose is shifted so that its center matches the straight\n # line segment center. For `true_position`, we use `zone_pose`\n # but apply the correct offset to deal with the sides. Note\n # that `length` is the size of a fully smoothed cable, BUT we\n # made a rectangle with each side <= length.\n # ----------------------------------------------------------- #\n lx = info['lengthx']\n ly = info['lengthy']\n r = radius\n\n if info['nb_sides'] == 1:\n # Here it's just a straight line on the 'lx' side.\n x_coord = lx / 2 - (distance * i)\n y_coord = 0\n true_position = (x_coord - r, y_coord, 0)\n\n elif info['nb_sides'] == 2:\n # Start from lx side, go 'left' to the pivot point, then on\n # the ly side, go 'upwards' but offset by `i`. For radius\n # offset, I just got this by tuning. XD\n if i < info['cutoff']:\n x_coord = lx / 2 - (distance * i)\n y_coord = -ly / 2\n true_position = (x_coord - r, y_coord, 0)\n else:\n x_coord = -lx / 2\n y_coord = -ly / 2 + (distance * (i - info['cutoff']))\n true_position = (x_coord, y_coord + r, 0)\n\n elif info['nb_sides'] == 3:\n # Start from positive lx, positive ly, go down to first\n # pivot. Then go left to the second pivot, then up again.\n # For v1, division by two is because we assume BOTH of the\n # 'ly edges' were divided by two.\n v1 = (self.num_parts - info['cutoff']) / 2\n v2 = self.num_parts - v1\n if i < v1:\n x_coord = lx / 2\n y_coord = ly / 2 - (distance * i)\n true_position = (x_coord, y_coord - r, 0)\n elif i < v2:\n x_coord = lx / 2 - (distance * (i - v1))\n y_coord = -ly / 2\n true_position = (x_coord - r, y_coord, 0)\n else:\n x_coord = -lx / 2\n y_coord = -ly / 2 + (distance * (i - v2))\n true_position = (x_coord, y_coord + r, 0)\n\n elif info['nb_sides'] == 4:\n # I think this is similar to the 2-side case: we start in\n # the same direction and go counter-clockwise.\n v1 = info['cutoff'] / 2\n v2 = num_parts / 2\n v3 = (num_parts + info['cutoff']) / 2\n if i < v1:\n x_coord = lx / 2 - (distance * i)\n y_coord = -ly / 2\n true_position = (x_coord, y_coord, 0)\n elif i < v2:\n x_coord = -lx / 2\n y_coord = -ly / 2 + (distance * (i - v1))\n true_position = (x_coord, y_coord, 0)\n elif i < v3:\n x_coord = -lx / 2 + (distance * (i - v2))\n y_coord = ly / 2\n true_position = (x_coord, y_coord, 0)\n else:\n x_coord = lx / 2\n y_coord = ly / 2 - (distance * (i - v3))\n true_position = (x_coord, y_coord, 0)\n\n # Map true_position onto the workspace from zone_pose.\n true_position = self.apply(self.zone_pose, true_position)\n\n # See `cable.py`: just get the places and steps set.\n self.goal['places'][part_id] = (true_position, (0, 0, 0, 1.))\n symmetry = 0\n self.goal['steps'][0][part_id] = (symmetry, [part_id])\n\n # Debugging target zones.\n if self.target_debug_markers:\n sq_pose = ((true_position[0], true_position[1], 0.002), (0,0,0,1))\n sq_template = 'assets/square/square-template-allsides-blue.urdf'\n replace = {'DIM': (0.003,), 'HALF': (0.003 / 2,)}\n urdf = self.fill_template(sq_template, replace)\n env.add_object(urdf, sq_pose, fixed=True)\n os.remove(urdf)\n else:\n print(f'Warning, env {self._name} will not have goals.')","def create(self, config):\n\n assert config[\"name\"] == self.name, \"Given config is not for this template\"\n\n data = self._json_encode(config)\n headers = self._default_headers()\n\n return self._request(\"\",\n ok_status=None,\n data=data,\n headers=headers)","def create(self, nDeviceType):\n\t\treturn handle_to_object(call_sdk_function('PrlVmDev_Create', nDeviceType))","def create_org_vdc(self,\n vdc_name,\n provider_vdc_name,\n description='',\n allocation_model='AllocationVApp',\n cpu_units='MHz',\n cpu_allocated=0,\n cpu_limit=0,\n mem_units='MB',\n mem_allocated=0,\n mem_limit=0,\n nic_quota=0,\n network_quota=0,\n vm_quota=0,\n storage_profiles=[],\n resource_guaranteed_memory=None,\n resource_guaranteed_cpu=None,\n vcpu_in_mhz=None,\n is_thin_provision=None,\n network_pool_name=None,\n uses_fast_provisioning=None,\n over_commit_allowed=None,\n vm_discovery_enabled=None,\n is_enabled=True):\n if self.resource is None:\n self.resource = self.client.get_resource(self.href)\n sys_admin_resource = self.client.get_admin()\n system = System(self.client, admin_resource=sys_admin_resource)\n pvdc = system.get_provider_vdc(provider_vdc_name)\n resource_admin = self.client.get_resource(self.href_admin)\n params = E.CreateVdcParams(\n E.Description(description),\n E.AllocationModel(allocation_model),\n E.ComputeCapacity(\n E.Cpu(\n E.Units(cpu_units), E.Allocated(cpu_allocated),\n E.Limit(cpu_limit)),\n E.Memory(\n E.Units(mem_units), E.Allocated(mem_allocated),\n E.Limit(mem_limit))),\n E.NicQuota(nic_quota),\n E.NetworkQuota(network_quota),\n E.VmQuota(vm_quota),\n E.IsEnabled(is_enabled),\n name=vdc_name)\n for sp in storage_profiles:\n pvdc_sp = system.get_provider_vdc_storage_profile(sp['name'])\n params.append(\n E.VdcStorageProfile(\n E.Enabled(sp['enabled']),\n E.Units(sp['units']),\n E.Limit(sp['limit']),\n E.Default(sp['default']),\n E.ProviderVdcStorageProfile(href=pvdc_sp.get('href'))))\n if resource_guaranteed_memory is not None:\n params.append(\n E.ResourceGuaranteedMemory(resource_guaranteed_memory))\n if resource_guaranteed_cpu is not None:\n params.append(E.ResourceGuaranteedCpu(resource_guaranteed_cpu))\n if vcpu_in_mhz is not None:\n params.append(E.VCpuInMhz(vcpu_in_mhz))\n if is_thin_provision is not None:\n params.append(E.IsThinProvision(is_thin_provision))\n if network_pool_name is not None:\n npr = system.get_network_pool_reference(network_pool_name)\n href = npr.get('href')\n params.append(\n E.NetworkPoolReference(\n href=href,\n id=href.split('/')[-1],\n type=npr.get('type'),\n name=npr.get('name')))\n params.append(pvdc)\n if uses_fast_provisioning is not None:\n params.append(E.UsesFastProvisioning(uses_fast_provisioning))\n if over_commit_allowed is not None:\n params.append(E.OverCommitAllowed(over_commit_allowed))\n if vm_discovery_enabled is not None:\n params.append(E.VmDiscoveryEnabled(vm_discovery_enabled))\n return self.client.post_linked_resource(\n resource_admin, RelationType.ADD, EntityType.VDCS_PARAMS.value,\n params)","def getCompartment(self):\n return _libsbml.CompartmentReference_getCompartment(self)","def create_deployment(deployment_id, blueprint_id, environment):\n environment.add_cleanup(\n environment.cfy.deployments.delete,\n kwargs={\n 'deployment_id': deployment_id,\n },\n )\n environment.cfy.deployments.create(\n blueprint_id=blueprint_id,\n deployment_id=deployment_id,\n skip_plugins_validation=True,\n )","def hfp_create(handle, org_dn, name,\r\n blade_bundle_version=\"\",\r\n rack_bundle_version=\"\",\r\n ignore_comp_check=\"yes\",\r\n update_trigger=\"immediate\",\r\n mode=\"staged\",\r\n stage_size=\"0\",\r\n policy_owner=\"local\",\r\n descr=\"testdescr\"):\r\n\r\n from ucsmsdk.mometa.firmware.FirmwareComputeHostPack import \\\r\n FirmwareComputeHostPack\r\n\r\n org = handle.query_dn(org_dn)\r\n if org is None:\r\n raise ValueError(\"Org '%s' does not exist\" % org_dn)\r\n\r\n mo = FirmwareComputeHostPack(parent_mo_or_dn=\"org-root\",\r\n name=name,\r\n blade_bundle_version=blade_bundle_version,\r\n rack_bundle_version=rack_bundle_version,\r\n ignore_comp_check=ignore_comp_check,\r\n update_trigger=update_trigger,\r\n mode=mode,\r\n stage_size=stage_size,\r\n policy_owner=policy_owner,\r\n descr=descr)\r\n handle.add_mo(mo, modify_present=True)\r\n handle.commit()\r\n\r\n return mo","def generate_compartments(parameterdict):\n\n refcmpts, model = [parameterdict[i] for i in ['refcmpts', 'model']]\n\n peripherals = [] # List for peripheral compartments\n # Iterates through compartments. Adds peripherals to peripheral list,\n # creates main and optionally sub compartment (if in SC model).\n # Doesn't allow multiple main/sub compartments.\n for cmpt in refcmpts:\n if cmpt[2] == 'Peripheral':\n peripherals.append(Compartment(cmpt[0], cmpt[1]))\n\n elif cmpt[2] == 'Main':\n if 'maincmpt' in locals():\n raise ValueError(\"Can't have two main compartments.\")\n else:\n maincmpt = Compartment(cmpt[0], cmpt[1])\n\n elif cmpt[2] == 'Sub' and model == 'sc':\n if 'subcmpt' in locals():\n raise ValueError(\"Can't have two subcompartments.\")\n else:\n subcmpt = Compartment(cmpt[0], cmpt[1])\n if subcmpt not in locals():\n subcmpt = None\n\n return maincmpt, peripherals, subcmpt","def create_cluster(self, provision_details, project_id=\"\"):\n response = self.post(f'{ApiVersion.A1.value}/groups/{project_id}/clusters'\n ,body=provision_details)\n return response","def create_b_obj(ob_name, b_obj_data):\n b_obj = bpy.data.objects.new(ob_name, b_obj_data)\n bpy.context.scene.objects.link(b_obj)\n bpy.context.scene.objects.active = b_obj\n b_obj.select = True\n return b_obj","def create(compte_origine, compte_dest, montant, date=None, notes=\"\"):\n if not isinstance(compte_origine, Compte):\n raise TypeError('pas compte')\n if not isinstance(compte_dest, Compte):\n raise TypeError('pas compte')\n if compte_origine == compte_dest:\n raise TypeError(\"Attention, le compte de départ ne peut être celui d'arrivée\")\n vir = Virement()\n vir.origine = Ope()\n vir.dest = Ope()\n vir.origine.compte = compte_origine\n vir.dest.compte = compte_dest\n vir.montant = montant\n if date:\n vir.date = date\n else:\n vir.date = utils.today()\n vir.notes = notes\n vir._init = True\n moyen = Moyen.objects.filter(type='v')[0]\n vir.dest.moyen = moyen\n vir.origine.moyen = moyen\n vir.save()\n vir.origine.jumelle = vir.dest\n vir.dest.jumelle = vir.origine\n vir.save()\n return vir","def create_component(self, name: str, nx_class: str, description: str) -> Component:\n name = _convert_name_with_spaces(name)\n parent_group = self.nexus.instrument\n if nx_class in COMPONENTS_IN_ENTRY:\n parent_group = self.nexus.entry\n component_group = self.nexus.create_nx_group(name, nx_class, parent_group)\n component = create_component(self.nexus, component_group)\n component.description = description\n return component","def removeCompartment(self, *args):\n return _libsbml.Model_removeCompartment(self, *args)","def add_comp(mol, projects):\n\n # Now attribute all this meta-deta to the compound object\n new_comp = Compound()\n comp = calc_cpd(new_comp, mol, projects)\n return comp","def createPort(self):\n return _libsbml.CompModelPlugin_createPort(self)","def new(name=None):","def create(self):\n flavor = env_vars[\"cassandra_%s_flavor\" % self.type]\n #create the VM\n self.vm = VM(self.name, flavor, self.image, create=True)","def product_group_create(obj, name, department):\n client = get_client(obj)\n\n with Action('Creating product_group: {}'.format(name), nl=True):\n pg = client.product_group_create(name, department)\n\n print(json.dumps(pg, indent=4))","def create_trunk(self, trunk_id, port_id, port_mac):\n trunk = TrunkParentPort(trunk_id, port_id, port_mac)\n try:\n if not trunk.bridge.exists():\n raise exc.TrunkBridgeNotFound(bridge=trunk.bridge.br_name)\n trunk.plug(self.br_int)\n except RuntimeError as e:\n raise TrunkManagerError(error=e)","def create_data_center(\n dc_name, cluster_name, host_name, comp_version=config.COMPATIBILITY_VERSION\n):\n testflow.step(\"Add data-center %s\", dc_name)\n assert ll_dc.addDataCenter(\n True, name=dc_name, local=False, version=comp_version\n ), \"Failed to create dc %s\" % dc_name\n\n testflow.step(\"Add cluster %s\", cluster_name)\n assert ll_clusters.addCluster(\n True, name=cluster_name, cpu=config.CPU_NAME,\n data_center=dc_name, version=comp_version\n ), \"addCluster %s with cpu %s and version %s to datacenter %s failed\" % (\n cluster_name, config.CPU_NAME, comp_version, dc_name\n )\n testflow.step(\"Move host %s to cluster %s\", host_name, cluster_name)\n assert hl_hosts.move_host_to_another_cluster(\n host=host_name, cluster=cluster_name, activate=True\n ), \"Failed to move host %s to cluster %s\" % (host_name, cluster_name)","def create(self, verbose=False):\r\n # delete the window if its handle exists\r\n if cmds.window(self.window, exists=True):\r\n cmds.deleteUI(self.window)\r\n # initialize the window as a pane for docking\r\n self.window = cmds.loadUI(uiFile=self.uiFile, verbose=verbose)\r\n #layoutWin = cmds.paneLayout(configuration='single')\r\n # create a dockControl and parent the control to layoutWin\r\n cmds.dockControl(allowedArea='all', area='right', floating=False, \r\n height=cmds.window(self.window, query=True, height=True), \r\n content=self.window, label='Docked Cone Pointer Window')\r\n cmds.showWindow(self.window)","def create_computer(DirectoryId=None, ComputerName=None, Password=None, OrganizationalUnitDistinguishedName=None, ComputerAttributes=None):\n pass","def create(cls, task_name, cfd_mesh):\n if task_name not in cls._available_tasks:\n raise KeyError(\"Invalid task name: %s\"%task_name)\n tcls = cls._available_tasks[task_name]\n obj = tcls(cfd_mesh)\n return obj","def appendcomp(self, componentname, component):\n self.components.append(componentname, component)\n return component","def clone(self):\n return _libsbml.CompartmentReference_clone(self)","def CreateDataContainer(name):\n dc = simpl.DataContainer.New(name)\n return dc","def add_pod(\n self, pod_name: str, head_host, head_port_in, tail_port_out, head_zmq_identity\n ) -> None:\n if pod_name in self.pods:\n raise ValueError(\n f'Vertex with name {pod_name} already exists. Please check your configuration for unique Pod names.'\n )\n target = self.pods[pod_name]\n\n target.host = head_host\n target.port = head_port_in\n target.port_out = tail_port_out\n target.target_identity = head_zmq_identity","def create(openstack_resource):\n # Update port config before create port\n _update_port_config(openstack_resource.config)\n\n # Create port\n created_resource = openstack_resource.create()\n ipv4_list, ipv6_list = _get_fixed_ips_from_port(created_resource)\n fixed_ips = ipv4_list + ipv6_list\n _export_ips_to_port_instance(ipv4_list, ipv6_list)\n\n # Handle runtime properties\n update_runtime_properties(\n {\n RESOURCE_ID: created_resource.id,\n 'fixed_ips': fixed_ips,\n 'mac_address': created_resource.mac_address,\n 'allowed_address_pairs': created_resource.allowed_address_pairs,\n }\n )","def create(cls , specgrid , zcorn , coord , actnum , mapaxes = None ):\n return cls._grdecl_create( specgrid[0] , specgrid[1] , specgrid[2] , zcorn , coord , actnum , mapaxes )","def create(self):\n\n raise NotImplementedError","def new_object(self):\r\n\t\tpass","def create_comm(comm_title, days, comm_name, comm_plat, comm_desc, comp_rating):\n time = timezone.now() + datetime.timedelta(days=days)\n return Commission.objects.create(commission_title=comm_title,\n commissioner_name=comm_name,\n commissioner_platform=comm_plat,\n commission_description=comm_desc,\n complexity_rating=comp_rating,\n creation_date=time)","def createNode(self, pkg, exe, args, name, nspace):\r\n node = Node(self)\r\n self.callRemote('createNode', pkg, exe, args, name,\r\n nspace).chainDeferred(node)\r\n return node","def create(cls, name, comment=None):\n comment = comment if comment else ''\n cls.json = {'name': name,\n 'comment': comment}\n return ElementCreator(cls)"],"string":"[\n \"def createCompartment(self):\\n return _libsbml.Model_createCompartment(self)\",\n \"def addCompartment(self, vol=1, comp_id=\\\"\\\"):\\n\\n c1 = self.model.createCompartment()\\n self.check(c1, \\\"create compartment\\\")\\n if len(comp_id) == 0:\\n comp_id = \\\"c\\\" + str(self.model.getNumCompartments())\\n self.check(c1.setId(comp_id), \\\"set compartment id\\\")\\n self.check(c1.setConstant(True), 'set compartment \\\"constant\\\"')\\n self.check(c1.setSpatialDimensions(3), \\\"set compartment dimensions\\\")\\n\\n self.check(c1.setSize(vol), 'set compartment \\\"size\\\"')\\n self.check(c1.setUnits(\\\"litre\\\"), \\\"set compartment size units\\\")\\n return c1\",\n \"def addCompartment(self, *args):\\n return _libsbml.Model_addCompartment(self, *args)\",\n \"def __init__(self, *args):\\n this = _libsbml.new_CompartmentType(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def createCompartmentType(self):\\n return _libsbml.Model_createCompartmentType(self)\",\n \"def __init__(self, *args):\\n this = _libsbml.new_Compartment(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def add_compartment(self, Vp=1, Qp=1):\\n self.__n_compartments += 1\\n self.__compartments.append({'Vp': Vp, 'Qp': Qp})\",\n \"def create_new_component(self, cname):\\n while True:\\n try:\\n self.model.get_component_by_name(cname)\\n cname += u'_'\\n except KeyError:\\n # Component with this name doesn't exist\\n break\\n # Create the component\\n comp = cellml_component.create_new(self.model, cname)\\n self.model._add_component(comp)\\n return comp\",\n \"def setCompartment(self, *args):\\n return _libsbml.CompartmentReference_setCompartment(self, *args)\",\n \"def createCompartmentReference(self):\\n return _libsbml.MultiCompartmentPlugin_createCompartmentReference(self)\",\n \"def setCompartment(self, *args):\\n return _libsbml.Reaction_setCompartment(self, *args)\",\n \"def createObject(self, *args):\\n return _libsbml.MultiCompartmentPlugin_createObject(self, *args)\",\n \"def setCompartment(self, *args):\\n return _libsbml.Species_setCompartment(self, *args)\",\n \"def addCompartmentType(self, *args):\\n return _libsbml.Model_addCompartmentType(self, *args)\",\n \"def createCompartmentGlyph(self):\\n return _libsbml.Layout_createCompartmentGlyph(self)\",\n \"def addCompartmentGlyph(self, *args):\\n return _libsbml.Layout_addCompartmentGlyph(self, *args)\",\n \"def container(name, ostemplate, **kwargs):\\n if not openvz.exists(name):\\n ctid = openvz.get_available_ctid()\\n openvz.create(ctid, ostemplate=ostemplate, **kwargs)\\n openvz.set(ctid, name=name)\\n return Container(name)\",\n \"def add_comp(self, name, ctype):\\n\\n name = self.name + '.' + name\\n\\n assert name not in self.components, 'A component named \\\\'{}\\\\' already exists for node \\\\'{}\\\\''.format(\\n name, self.name)\\n\\n try:\\n cls = co.str_to_comp(ctype)\\n except AttributeError:\\n try:\\n cls = rc.str_to_comp(ctype)\\n except AttributeError:\\n cls = None\\n\\n if cls:\\n obj = cls(name=name,\\n temperature_driven=self.temperature_driven,\\n repr_days=self.repr_days)\\n else:\\n raise ValueError(\\n \\\"%s is not a valid class name! (component is %s, in node %s)\\\" % (\\n ctype, name, self.name))\\n\\n self.logger.info('Component {} added to {}'.format(name, self.name))\\n\\n self.components[name] = obj\",\n \"def setCompartmentType(self, *args):\\n return _libsbml.Compartment_setCompartmentType(self, *args)\",\n \"def create(cls, name, container_object, enable=True, optional_attributes={}):\\n assert type(name) == str\\n assert container_object.__class__.__name__ == 'ADContainer'\\n return container_object.create_computer(name=name,enable=enable,optional_attributes=optional_attributes)\",\n \"def setCompartment(self, *args):\\n return _libsbml.QualitativeSpecies_setCompartment(self, *args)\",\n \"def addCompartmentReference(self, *args):\\n return _libsbml.MultiCompartmentPlugin_addCompartmentReference(self, *args)\",\n \"def firmware_pack_create(handle, org_name, name, rack_bundle_version,\\n blade_bundle_version, descr=\\\"\\\", mode=\\\"staged\\\",\\n org_parent=\\\"org-root\\\"):\\n\\n org_dn = org_parent + \\\"/org-\\\" + org_name\\n p_mo = handle.query_dn(org_dn)\\n if not p_mo:\\n log.info(\\\"Sub-Org <%s> not found!\\\" % org_name)\\n else:\\n from ucsmsdk.mometa.firmware.FirmwareComputeHostPack import\\\\\\n FirmwareComputeHostPack\\n\\n mo = FirmwareComputeHostPack(parent_mo_or_dn=org_dn,\\n name=name,\\n descr=descr,\\n rack_bundle_version=rack_bundle_version,\\n mode=mode,\\n blade_bundle_version=blade_bundle_version)\\n handle.add_mo(mo)\\n handle.commit()\",\n \"def compartment_id(self, compartment_id):\\n self._compartment_id = compartment_id\",\n \"def compartment_id(self, compartment_id):\\n self._compartment_id = compartment_id\",\n \"def setCompartment(self, *args):\\n return _libsbml.MultiSpeciesType_setCompartment(self, *args)\",\n \"def clone(self):\\n return _libsbml.Compartment_clone(self)\",\n \"def createappendcomp(self, componentname, componentclass, *args, **kwargs):\\n component = componentclass(self, self.debugmode, *args, **kwargs)\\n self.components.append(componentname, component)\\n return component\",\n \"def clone(self):\\n return _libsbml.CompartmentType_clone(self)\",\n \"def create(\\n cls, component_config: Dict[Text, Any], config: DazuConfig\\n ) -> \\\"Component\\\":\\n\\n # Check language supporting\\n language = config.language\\n if not cls.can_handle_language(language):\\n # check failed\\n raise UnsupportedLanguageError(cls.name, language)\\n\\n return cls(component_config)\",\n \"def createElement(tagName):\\n print(\\\"Warning: createElement is deprecated in favor of createComponent\\\")\\n return createComponent(tagName)\",\n \"def create_port(self, port):\\n try:\\n backend_id = self.client.create_nic(\\n port.vm.backend_id, port.network.backend_id\\n )\\n except VMwareError as e:\\n raise VMwareBackendError(e)\\n else:\\n port.backend_id = backend_id\\n port.save(update_fields=['backend_id'])\\n return port\",\n \"def env_creator(env_config):\\n return CartPoleBTEnv(\\n goal_state=env_config['goal_state'],\\n disturbances=env_config['disturbances'],\\n initial_state=env_config['initial_state'],\\n initial_state_variance=env_config['initial_state_variance']\\n )\",\n \"def setCompartmentType(self, *args):\\n return _libsbml.MultiCompartmentPlugin_setCompartmentType(self, *args)\",\n \"def create(cls, name, mac_address, comment=None):\\n comment = comment if comment else ''\\n cls.json = {'name': name,\\n 'address': mac_address,\\n 'comment': comment}\\n return ElementCreator(cls)\",\n \"def getCompartment(self, *args):\\n return _libsbml.Model_getCompartment(self, *args)\",\n \"def create(args):\\n print('Creates an HPC fleet with given name \\\"{}\\\"'.format(args.fleet_name))\",\n \"def setCompartmentId(self, *args):\\n return _libsbml.CompartmentGlyph_setCompartmentId(self, *args)\",\n \"def create_vlan_pool(self, vlan_pool_name, allocation_mode):\\n VlanInstP_mo = VlanInstP('uni/infra/', vlan_pool_name, allocation_mode)\\n self.commit(VlanInstP_mo)\\n return VlanInstP_mo\",\n \"def make_component(self, name=\\\"Face\\\") -> 'Component':\\n return BRepComponent(self.brep, component=self.component, name=name)\",\n \"def ec_contaier_create(self, oclass):\\n # Get container params\\n self.ec_container = TestContainer(\\n self.pool, daos_command=DaosCommand(self.bin))\\n self.ec_container.get_params(self)\\n self.ec_container.oclass.update(oclass)\\n # update object class for container create, if supplied\\n # explicitly.\\n ec_object = self.get_data_parity_number(oclass)\\n self.ec_container.properties.update(\\\"rf:{}\\\".format(ec_object['parity']))\\n\\n # create container\\n self.ec_container.create()\",\n \"def create_environment(cls, full_config):\\n\\n config = full_config['template']['devops_settings']\\n environment = cls.create(config['env_name'])\\n\\n # create groups and drivers\\n groups = config['groups']\\n environment.add_groups(groups)\\n\\n # create address pools\\n address_pools = config['address_pools']\\n environment.add_address_pools(address_pools)\\n\\n # process group items\\n for group_data in groups:\\n group = environment.get_group(name=group_data['name'])\\n\\n # add l2_network_devices\\n group.add_l2_network_devices(\\n group_data.get('l2_network_devices', {}))\\n\\n # add network_pools\\n group.add_network_pools(\\n group_data.get('network_pools', {}))\\n\\n # Connect nodes to already created networks\\n for group_data in groups:\\n group = environment.get_group(name=group_data['name'])\\n\\n # add group volumes\\n group.add_volumes(\\n group_data.get('group_volumes', []))\\n\\n # add nodes\\n group.add_nodes(\\n group_data.get('nodes', []))\\n\\n return environment\",\n \"def create_instance(c_instance):\\n return AumPC40(c_instance)\",\n \"def set_compartment(self, label, init_val=0.):\\n assert type(label) is str, 'Compartment label for initial setting not string'\\n assert type(init_val) is float or type(init_val) is int, 'Value to start % compartment from not string' % label\\n assert init_val >= 0., 'Start with negative compartment not permitted'\\n if label not in self.labels:\\n self.labels.append(label)\\n self.init_compartments[label] = init_val\",\n \"def _create_org(org_name, org_status):\\n new_org = OcOrg().setup_org(name=org_name, status=org_status)\\n\\n return new_org\",\n \"def create_container(self, hostname, container_id, endpoint):\\n\\n endpoint_path = ENDPOINT_PATH % {\\\"hostname\\\": hostname,\\n \\\"container_id\\\": container_id,\\n \\\"endpoint_id\\\": endpoint.id}\\n\\n _log.info(\\\"Creating endpoint at %s\\\", endpoint_path)\\n try:\\n self.client.write(endpoint_path + \\\"addrs\\\", json.dumps(endpoint.addrs))\\n self.client.write(endpoint_path + \\\"mac\\\", endpoint.mac)\\n self.client.write(endpoint_path + \\\"state\\\", endpoint.state)\\n except etcd.EtcdException as e:\\n _log.exception(\\\"Hit Exception %s writing to etcd.\\\", e)\\n pass\",\n \"def create_board(self, board_id, comp):\\n new_board = self.create_board_from_template(board_id)\\n comp.answer(new_board.id)\",\n \"def create(\\n location: str,\\n outputdir: pathlib.Path,\\n *,\\n extrabindings: Sequence[Binding],\\n interactive: bool,\\n revision: Optional[str],\\n directory: Optional[pathlib.Path],\\n in_place: bool,\\n) -> None:\\n config = ProjectConfig(location, (), revision, directory)\\n\\n with createproject(\\n config, userbindings=extrabindings, interactive=interactive\\n ) as project:\\n projectdir = outputdir if in_place else outputdir / project.name\\n repository = ProjectRepository.create(projectdir, message=\\\"Initial commit\\\")\\n commit = commitproject(repository, project, commitmessage=createcommitmessage)\\n\\n repository.import_(commit)\",\n \"def create_node(self, node_cfg):\\n with self.__connect_node(node_cfg) as conn:\\n self._provision_node(conn, node_cfg)\\n self._bootup_node(conn)\",\n \"def build(cmpd, density=0.5*u.gram/(u.cm**3), n_compounds=1000, \\n ff='ff/TraPPE_UA_3_fully_flexible_propane.xml'):\\n density.convert_to_units(u.kilogram/u.m**3)\\n\\n # Pack a box\\n box = mb.fill_box(cmpd, n_compounds=n_compounds, density=density.value)\\n\\n # Wrap coordinates\\n new_xyz = box.xyz - 1 * np.floor_divide(box.xyz, box.periodicity) * box.periodicity\\n box.xyz = new_xyz\\n\\n # Apply non-atomistic, custom element naming convention\\n for part in box.particles():\\n part.name = \\\"_\\\" + part.name\\n\\n # Utilize foyer to parametrize our box\\n ff = foyer.Forcefield(forcefield_files=ff)\\n box = box.to_parmed(infer_residues=True)\\n parametrized_structure = ff.apply(box, combining_rule='lorentz')\\n\\n # Dump initial coordinates\\n parametrized_structure.save('compound.pdb', overwrite=True)\\n parametrized_structure.save('compound.mol2', overwrite=True)\\n parametrized_structure.save('compound.gro', overwrite=True)\\n\\n return parametrized_structure\",\n \"def CreateComponent(self, name, state):\\n component = SimpleTestClientComponent()\\n component.__dict__.update(state)\\n return component\",\n \"def create(self):\\n config = {}\\n for key in ('ident', 'cgroupparent', 'infra', 'labels', 'share'):\\n config[key] = self.opts.get(key)\\n\\n try:\\n pod = self.client.pods.create(**config)\\n except podman.ErrorOccurred as ex:\\n sys.stdout.flush()\\n print(\\n '{}'.format(ex.reason).capitalize(),\\n file=sys.stderr,\\n flush=True)\\n else:\\n print(pod.id)\",\n \"def createComponent(tagName):\\n\\n class Component():\\n \\\"\\\"\\\"A basic class for a virtual DOM Component\\\"\\\"\\\"\\n def __init__(self, *children, **kwargs):\\n self.children = _flatten_children(*children, **kwargs)\\n self.attributes = kwargs\\n self.tagName = tagName\\n\\n def _repr_mimebundle_(self, include, exclude, **kwargs):\\n return {\\n 'application/vdom.v1+json': toJSON(self),\\n 'text/plain': '<{tagName} />'.format(tagName=tagName)\\n }\\n \\n Component.__doc__ = \\\"\\\"\\\"A virtual DOM component for a {tagName} tag\\n \\n >>> {tagName}()\\n <{tagName} />\\n \\\"\\\"\\\".format(tagName=tagName)\\n \\n return Component\",\n \"def create_host(self, conf, tenant_id, network_id, params):\\n\\t\\tpass\",\n \"def __create_cont(self, path, filesystem, cont_stat, component_number):\\n try:\\n self.logger.debug('Create container interface called')\\n status_obj = Status()\\n cont_id = \\\"container\\\"\\n #cont_id = get_container_id()\\n tmp_path = '%s/%s/%s/%s/%s' % (self.__fs_base, \\\\\\n filesystem, TMPDIR, cont_id,component_number)\\n self.asyn_helper.call(\\\"create_container\\\", \\\\\\n tmp_path, path, cont_stat, status_obj)\\n return status_obj\\n except Exception as err:\\n self.logger.error(('create_container for %(con_dir)s failed ',\\n 'close failure: %(exc)s : %(stack)s'),\\n {'con_dir' : path, \\n 'exc': err, 'stack': ''.join(traceback.format_stack())})\\n raise err\",\n \"def create_port(self, component):\\n if self.fixed_size is not None and not self.array:\\n raise ValueError(\\n \\\"{}.{}: @{}port specified fixed_size but not array=True\\\".format(\\n self, self.name,\\n self.kind))\\n ptype = self.get_port_type()\\n return ptype(component, **self.data)\",\n \"def __init__(self, *args):\\n this = _libsbml.new_MultiCompartmentPlugin(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def __init__(self, *args):\\n this = _libsbml.new_ListOfCompartmentTypes(*args)\\n try: self.this.append(this)\\n except: self.this = this\",\n \"def newChemCompVar(self, **attrlinks):\\n return ChemCompVar(self, **attrlinks)\",\n \"def mkcomponent(self,\\n context=[],\\n componentobj=None):\\n if componentobj == None:\\n raise ValueError, \\\"mkcomponent: componentobj is None\\\"\\n return jsoncall.do_call(\\\"mkcomponent\\\", {'modelname':self.modelname,\\\\\\n 'user':self.user,\\\\\\n 'password':self.password,\\\\\\n 'context':context,\\\\\\n 'componentobj':componentobj.__dict__},\\n self.connection)\",\n \"def test_create_new_placements(self):\\n subv = SimpleMachineVertex(None, \\\"\\\")\\n pl = Placement(subv, 0, 0, 1)\\n Placements([pl])\",\n \"def createComplejoPlatino(c_dict):\\n\\tnom = c_dict['nombre'].split()\\n\\tnom.insert(1, 'Platino')\\n\\tnombre = ' '.join(nom)\\n\\tc_dict['nombre'] = nombre\\n\\tc_dict['id_org'] = int(c_dict['id_org']) + 10000\\n\\tcreateComplejo(c_dict)\",\n \"def create():\",\n \"def create():\",\n \"def createAllocation(name, tag, facility):\\n return Allocation(Cuebot.getStub('allocation').Create(\\n facility_pb2.AllocCreateRequest(name=name, tag=tag, facility=facility),\\n timeout=Cuebot.Timeout).allocation)\",\n \"def _env_create(name_or_path, init_file=None, dir=False, with_view=None, keep_relative=False):\\n if dir:\\n env = ev.Environment(name_or_path, init_file, with_view, keep_relative)\\n env.write()\\n tty.msg(\\\"Created environment in %s\\\" % env.path)\\n tty.msg(\\\"You can activate this environment with:\\\")\\n tty.msg(\\\" spack env activate %s\\\" % env.path)\\n else:\\n env = ev.create(name_or_path, init_file, with_view, keep_relative)\\n env.write()\\n tty.msg(\\\"Created environment '%s' in %s\\\" % (name_or_path, env.path))\\n tty.msg(\\\"You can activate this environment with:\\\")\\n tty.msg(\\\" spack env activate %s\\\" % (name_or_path))\\n return env\",\n \"def add_cable(self, env, size_range, info={}, cable_idx=0,\\n direction='z', max_force=100):\\n num_parts = self.num_parts\\n radius = self.radius\\n length = self.length\\n color = self.colors[cable_idx] + [1]\\n color_end = U.COLORS['yellow'] + [1]\\n\\n # Add beaded cable.\\n distance = length / num_parts\\n position, _ = self.random_pose(env, size_range)\\n position = np.float32(position)\\n part_shape = p.createCollisionShape(p.GEOM_BOX, halfExtents=[radius]*3)\\n part_visual = p.createVisualShape(p.GEOM_SPHERE, radius=radius*1.5)\\n\\n # Iterate through parts and create constraints as needed.\\n for i in range(num_parts):\\n if direction == 'x':\\n position[0] += distance\\n parent_frame = (distance, 0, 0)\\n elif direction == 'y':\\n position[1] += distance\\n parent_frame = (0, distance, 0)\\n else:\\n position[2] += distance\\n parent_frame = (0, 0, distance)\\n\\n part_id = p.createMultiBody(0.1, part_shape, part_visual,\\n basePosition=position)\\n if i > 0:\\n constraint_id = p.createConstraint(\\n parentBodyUniqueId=env.objects[-1],\\n parentLinkIndex=-1,\\n childBodyUniqueId=part_id,\\n childLinkIndex=-1,\\n jointType=p.JOINT_POINT2POINT,\\n jointAxis=(0, 0, 0),\\n parentFramePosition=parent_frame,\\n childFramePosition=(0, 0, 0))\\n p.changeConstraint(constraint_id, maxForce=max_force)\\n\\n if (i > 0) and (i < num_parts - 1):\\n p.changeVisualShape(part_id, -1, rgbaColor=color)\\n elif i == num_parts - 1:\\n p.changeVisualShape(part_id, -1, rgbaColor=color_end)\\n\\n # The usual for tracking IDs. Four things to add.\\n self.cable_bead_IDs.append(part_id)\\n self._IDs[part_id] = f'cable_part_{str(part_id).zfill(2)}'\\n env.objects.append(part_id)\\n self.object_points[part_id] = np.float32((0, 0, 0)).reshape(3, 1)\\n\\n # Get target placing positions for each cable bead, if applicable.\\n if self._name == 'cable-shape' or self._name == 'cable-shape-notarget' or \\\\\\n self._name == 'cable-line-notarget':\\n # ----------------------------------------------------------- #\\n # Here, zone_pose = square_pose, unlike Ravens cable, where the\\n # zone_pose is shifted so that its center matches the straight\\n # line segment center. For `true_position`, we use `zone_pose`\\n # but apply the correct offset to deal with the sides. Note\\n # that `length` is the size of a fully smoothed cable, BUT we\\n # made a rectangle with each side <= length.\\n # ----------------------------------------------------------- #\\n lx = info['lengthx']\\n ly = info['lengthy']\\n r = radius\\n\\n if info['nb_sides'] == 1:\\n # Here it's just a straight line on the 'lx' side.\\n x_coord = lx / 2 - (distance * i)\\n y_coord = 0\\n true_position = (x_coord - r, y_coord, 0)\\n\\n elif info['nb_sides'] == 2:\\n # Start from lx side, go 'left' to the pivot point, then on\\n # the ly side, go 'upwards' but offset by `i`. For radius\\n # offset, I just got this by tuning. XD\\n if i < info['cutoff']:\\n x_coord = lx / 2 - (distance * i)\\n y_coord = -ly / 2\\n true_position = (x_coord - r, y_coord, 0)\\n else:\\n x_coord = -lx / 2\\n y_coord = -ly / 2 + (distance * (i - info['cutoff']))\\n true_position = (x_coord, y_coord + r, 0)\\n\\n elif info['nb_sides'] == 3:\\n # Start from positive lx, positive ly, go down to first\\n # pivot. Then go left to the second pivot, then up again.\\n # For v1, division by two is because we assume BOTH of the\\n # 'ly edges' were divided by two.\\n v1 = (self.num_parts - info['cutoff']) / 2\\n v2 = self.num_parts - v1\\n if i < v1:\\n x_coord = lx / 2\\n y_coord = ly / 2 - (distance * i)\\n true_position = (x_coord, y_coord - r, 0)\\n elif i < v2:\\n x_coord = lx / 2 - (distance * (i - v1))\\n y_coord = -ly / 2\\n true_position = (x_coord - r, y_coord, 0)\\n else:\\n x_coord = -lx / 2\\n y_coord = -ly / 2 + (distance * (i - v2))\\n true_position = (x_coord, y_coord + r, 0)\\n\\n elif info['nb_sides'] == 4:\\n # I think this is similar to the 2-side case: we start in\\n # the same direction and go counter-clockwise.\\n v1 = info['cutoff'] / 2\\n v2 = num_parts / 2\\n v3 = (num_parts + info['cutoff']) / 2\\n if i < v1:\\n x_coord = lx / 2 - (distance * i)\\n y_coord = -ly / 2\\n true_position = (x_coord, y_coord, 0)\\n elif i < v2:\\n x_coord = -lx / 2\\n y_coord = -ly / 2 + (distance * (i - v1))\\n true_position = (x_coord, y_coord, 0)\\n elif i < v3:\\n x_coord = -lx / 2 + (distance * (i - v2))\\n y_coord = ly / 2\\n true_position = (x_coord, y_coord, 0)\\n else:\\n x_coord = lx / 2\\n y_coord = ly / 2 - (distance * (i - v3))\\n true_position = (x_coord, y_coord, 0)\\n\\n # Map true_position onto the workspace from zone_pose.\\n true_position = self.apply(self.zone_pose, true_position)\\n\\n # See `cable.py`: just get the places and steps set.\\n self.goal['places'][part_id] = (true_position, (0, 0, 0, 1.))\\n symmetry = 0\\n self.goal['steps'][0][part_id] = (symmetry, [part_id])\\n\\n # Debugging target zones.\\n if self.target_debug_markers:\\n sq_pose = ((true_position[0], true_position[1], 0.002), (0,0,0,1))\\n sq_template = 'assets/square/square-template-allsides-blue.urdf'\\n replace = {'DIM': (0.003,), 'HALF': (0.003 / 2,)}\\n urdf = self.fill_template(sq_template, replace)\\n env.add_object(urdf, sq_pose, fixed=True)\\n os.remove(urdf)\\n else:\\n print(f'Warning, env {self._name} will not have goals.')\",\n \"def create(self, config):\\n\\n assert config[\\\"name\\\"] == self.name, \\\"Given config is not for this template\\\"\\n\\n data = self._json_encode(config)\\n headers = self._default_headers()\\n\\n return self._request(\\\"\\\",\\n ok_status=None,\\n data=data,\\n headers=headers)\",\n \"def create(self, nDeviceType):\\n\\t\\treturn handle_to_object(call_sdk_function('PrlVmDev_Create', nDeviceType))\",\n \"def create_org_vdc(self,\\n vdc_name,\\n provider_vdc_name,\\n description='',\\n allocation_model='AllocationVApp',\\n cpu_units='MHz',\\n cpu_allocated=0,\\n cpu_limit=0,\\n mem_units='MB',\\n mem_allocated=0,\\n mem_limit=0,\\n nic_quota=0,\\n network_quota=0,\\n vm_quota=0,\\n storage_profiles=[],\\n resource_guaranteed_memory=None,\\n resource_guaranteed_cpu=None,\\n vcpu_in_mhz=None,\\n is_thin_provision=None,\\n network_pool_name=None,\\n uses_fast_provisioning=None,\\n over_commit_allowed=None,\\n vm_discovery_enabled=None,\\n is_enabled=True):\\n if self.resource is None:\\n self.resource = self.client.get_resource(self.href)\\n sys_admin_resource = self.client.get_admin()\\n system = System(self.client, admin_resource=sys_admin_resource)\\n pvdc = system.get_provider_vdc(provider_vdc_name)\\n resource_admin = self.client.get_resource(self.href_admin)\\n params = E.CreateVdcParams(\\n E.Description(description),\\n E.AllocationModel(allocation_model),\\n E.ComputeCapacity(\\n E.Cpu(\\n E.Units(cpu_units), E.Allocated(cpu_allocated),\\n E.Limit(cpu_limit)),\\n E.Memory(\\n E.Units(mem_units), E.Allocated(mem_allocated),\\n E.Limit(mem_limit))),\\n E.NicQuota(nic_quota),\\n E.NetworkQuota(network_quota),\\n E.VmQuota(vm_quota),\\n E.IsEnabled(is_enabled),\\n name=vdc_name)\\n for sp in storage_profiles:\\n pvdc_sp = system.get_provider_vdc_storage_profile(sp['name'])\\n params.append(\\n E.VdcStorageProfile(\\n E.Enabled(sp['enabled']),\\n E.Units(sp['units']),\\n E.Limit(sp['limit']),\\n E.Default(sp['default']),\\n E.ProviderVdcStorageProfile(href=pvdc_sp.get('href'))))\\n if resource_guaranteed_memory is not None:\\n params.append(\\n E.ResourceGuaranteedMemory(resource_guaranteed_memory))\\n if resource_guaranteed_cpu is not None:\\n params.append(E.ResourceGuaranteedCpu(resource_guaranteed_cpu))\\n if vcpu_in_mhz is not None:\\n params.append(E.VCpuInMhz(vcpu_in_mhz))\\n if is_thin_provision is not None:\\n params.append(E.IsThinProvision(is_thin_provision))\\n if network_pool_name is not None:\\n npr = system.get_network_pool_reference(network_pool_name)\\n href = npr.get('href')\\n params.append(\\n E.NetworkPoolReference(\\n href=href,\\n id=href.split('/')[-1],\\n type=npr.get('type'),\\n name=npr.get('name')))\\n params.append(pvdc)\\n if uses_fast_provisioning is not None:\\n params.append(E.UsesFastProvisioning(uses_fast_provisioning))\\n if over_commit_allowed is not None:\\n params.append(E.OverCommitAllowed(over_commit_allowed))\\n if vm_discovery_enabled is not None:\\n params.append(E.VmDiscoveryEnabled(vm_discovery_enabled))\\n return self.client.post_linked_resource(\\n resource_admin, RelationType.ADD, EntityType.VDCS_PARAMS.value,\\n params)\",\n \"def getCompartment(self):\\n return _libsbml.CompartmentReference_getCompartment(self)\",\n \"def create_deployment(deployment_id, blueprint_id, environment):\\n environment.add_cleanup(\\n environment.cfy.deployments.delete,\\n kwargs={\\n 'deployment_id': deployment_id,\\n },\\n )\\n environment.cfy.deployments.create(\\n blueprint_id=blueprint_id,\\n deployment_id=deployment_id,\\n skip_plugins_validation=True,\\n )\",\n \"def hfp_create(handle, org_dn, name,\\r\\n blade_bundle_version=\\\"\\\",\\r\\n rack_bundle_version=\\\"\\\",\\r\\n ignore_comp_check=\\\"yes\\\",\\r\\n update_trigger=\\\"immediate\\\",\\r\\n mode=\\\"staged\\\",\\r\\n stage_size=\\\"0\\\",\\r\\n policy_owner=\\\"local\\\",\\r\\n descr=\\\"testdescr\\\"):\\r\\n\\r\\n from ucsmsdk.mometa.firmware.FirmwareComputeHostPack import \\\\\\r\\n FirmwareComputeHostPack\\r\\n\\r\\n org = handle.query_dn(org_dn)\\r\\n if org is None:\\r\\n raise ValueError(\\\"Org '%s' does not exist\\\" % org_dn)\\r\\n\\r\\n mo = FirmwareComputeHostPack(parent_mo_or_dn=\\\"org-root\\\",\\r\\n name=name,\\r\\n blade_bundle_version=blade_bundle_version,\\r\\n rack_bundle_version=rack_bundle_version,\\r\\n ignore_comp_check=ignore_comp_check,\\r\\n update_trigger=update_trigger,\\r\\n mode=mode,\\r\\n stage_size=stage_size,\\r\\n policy_owner=policy_owner,\\r\\n descr=descr)\\r\\n handle.add_mo(mo, modify_present=True)\\r\\n handle.commit()\\r\\n\\r\\n return mo\",\n \"def generate_compartments(parameterdict):\\n\\n refcmpts, model = [parameterdict[i] for i in ['refcmpts', 'model']]\\n\\n peripherals = [] # List for peripheral compartments\\n # Iterates through compartments. Adds peripherals to peripheral list,\\n # creates main and optionally sub compartment (if in SC model).\\n # Doesn't allow multiple main/sub compartments.\\n for cmpt in refcmpts:\\n if cmpt[2] == 'Peripheral':\\n peripherals.append(Compartment(cmpt[0], cmpt[1]))\\n\\n elif cmpt[2] == 'Main':\\n if 'maincmpt' in locals():\\n raise ValueError(\\\"Can't have two main compartments.\\\")\\n else:\\n maincmpt = Compartment(cmpt[0], cmpt[1])\\n\\n elif cmpt[2] == 'Sub' and model == 'sc':\\n if 'subcmpt' in locals():\\n raise ValueError(\\\"Can't have two subcompartments.\\\")\\n else:\\n subcmpt = Compartment(cmpt[0], cmpt[1])\\n if subcmpt not in locals():\\n subcmpt = None\\n\\n return maincmpt, peripherals, subcmpt\",\n \"def create_cluster(self, provision_details, project_id=\\\"\\\"):\\n response = self.post(f'{ApiVersion.A1.value}/groups/{project_id}/clusters'\\n ,body=provision_details)\\n return response\",\n \"def create_b_obj(ob_name, b_obj_data):\\n b_obj = bpy.data.objects.new(ob_name, b_obj_data)\\n bpy.context.scene.objects.link(b_obj)\\n bpy.context.scene.objects.active = b_obj\\n b_obj.select = True\\n return b_obj\",\n \"def create(compte_origine, compte_dest, montant, date=None, notes=\\\"\\\"):\\n if not isinstance(compte_origine, Compte):\\n raise TypeError('pas compte')\\n if not isinstance(compte_dest, Compte):\\n raise TypeError('pas compte')\\n if compte_origine == compte_dest:\\n raise TypeError(\\\"Attention, le compte de départ ne peut être celui d'arrivée\\\")\\n vir = Virement()\\n vir.origine = Ope()\\n vir.dest = Ope()\\n vir.origine.compte = compte_origine\\n vir.dest.compte = compte_dest\\n vir.montant = montant\\n if date:\\n vir.date = date\\n else:\\n vir.date = utils.today()\\n vir.notes = notes\\n vir._init = True\\n moyen = Moyen.objects.filter(type='v')[0]\\n vir.dest.moyen = moyen\\n vir.origine.moyen = moyen\\n vir.save()\\n vir.origine.jumelle = vir.dest\\n vir.dest.jumelle = vir.origine\\n vir.save()\\n return vir\",\n \"def create_component(self, name: str, nx_class: str, description: str) -> Component:\\n name = _convert_name_with_spaces(name)\\n parent_group = self.nexus.instrument\\n if nx_class in COMPONENTS_IN_ENTRY:\\n parent_group = self.nexus.entry\\n component_group = self.nexus.create_nx_group(name, nx_class, parent_group)\\n component = create_component(self.nexus, component_group)\\n component.description = description\\n return component\",\n \"def removeCompartment(self, *args):\\n return _libsbml.Model_removeCompartment(self, *args)\",\n \"def add_comp(mol, projects):\\n\\n # Now attribute all this meta-deta to the compound object\\n new_comp = Compound()\\n comp = calc_cpd(new_comp, mol, projects)\\n return comp\",\n \"def createPort(self):\\n return _libsbml.CompModelPlugin_createPort(self)\",\n \"def new(name=None):\",\n \"def create(self):\\n flavor = env_vars[\\\"cassandra_%s_flavor\\\" % self.type]\\n #create the VM\\n self.vm = VM(self.name, flavor, self.image, create=True)\",\n \"def product_group_create(obj, name, department):\\n client = get_client(obj)\\n\\n with Action('Creating product_group: {}'.format(name), nl=True):\\n pg = client.product_group_create(name, department)\\n\\n print(json.dumps(pg, indent=4))\",\n \"def create_trunk(self, trunk_id, port_id, port_mac):\\n trunk = TrunkParentPort(trunk_id, port_id, port_mac)\\n try:\\n if not trunk.bridge.exists():\\n raise exc.TrunkBridgeNotFound(bridge=trunk.bridge.br_name)\\n trunk.plug(self.br_int)\\n except RuntimeError as e:\\n raise TrunkManagerError(error=e)\",\n \"def create_data_center(\\n dc_name, cluster_name, host_name, comp_version=config.COMPATIBILITY_VERSION\\n):\\n testflow.step(\\\"Add data-center %s\\\", dc_name)\\n assert ll_dc.addDataCenter(\\n True, name=dc_name, local=False, version=comp_version\\n ), \\\"Failed to create dc %s\\\" % dc_name\\n\\n testflow.step(\\\"Add cluster %s\\\", cluster_name)\\n assert ll_clusters.addCluster(\\n True, name=cluster_name, cpu=config.CPU_NAME,\\n data_center=dc_name, version=comp_version\\n ), \\\"addCluster %s with cpu %s and version %s to datacenter %s failed\\\" % (\\n cluster_name, config.CPU_NAME, comp_version, dc_name\\n )\\n testflow.step(\\\"Move host %s to cluster %s\\\", host_name, cluster_name)\\n assert hl_hosts.move_host_to_another_cluster(\\n host=host_name, cluster=cluster_name, activate=True\\n ), \\\"Failed to move host %s to cluster %s\\\" % (host_name, cluster_name)\",\n \"def create(self, verbose=False):\\r\\n # delete the window if its handle exists\\r\\n if cmds.window(self.window, exists=True):\\r\\n cmds.deleteUI(self.window)\\r\\n # initialize the window as a pane for docking\\r\\n self.window = cmds.loadUI(uiFile=self.uiFile, verbose=verbose)\\r\\n #layoutWin = cmds.paneLayout(configuration='single')\\r\\n # create a dockControl and parent the control to layoutWin\\r\\n cmds.dockControl(allowedArea='all', area='right', floating=False, \\r\\n height=cmds.window(self.window, query=True, height=True), \\r\\n content=self.window, label='Docked Cone Pointer Window')\\r\\n cmds.showWindow(self.window)\",\n \"def create_computer(DirectoryId=None, ComputerName=None, Password=None, OrganizationalUnitDistinguishedName=None, ComputerAttributes=None):\\n pass\",\n \"def create(cls, task_name, cfd_mesh):\\n if task_name not in cls._available_tasks:\\n raise KeyError(\\\"Invalid task name: %s\\\"%task_name)\\n tcls = cls._available_tasks[task_name]\\n obj = tcls(cfd_mesh)\\n return obj\",\n \"def appendcomp(self, componentname, component):\\n self.components.append(componentname, component)\\n return component\",\n \"def clone(self):\\n return _libsbml.CompartmentReference_clone(self)\",\n \"def CreateDataContainer(name):\\n dc = simpl.DataContainer.New(name)\\n return dc\",\n \"def add_pod(\\n self, pod_name: str, head_host, head_port_in, tail_port_out, head_zmq_identity\\n ) -> None:\\n if pod_name in self.pods:\\n raise ValueError(\\n f'Vertex with name {pod_name} already exists. Please check your configuration for unique Pod names.'\\n )\\n target = self.pods[pod_name]\\n\\n target.host = head_host\\n target.port = head_port_in\\n target.port_out = tail_port_out\\n target.target_identity = head_zmq_identity\",\n \"def create(openstack_resource):\\n # Update port config before create port\\n _update_port_config(openstack_resource.config)\\n\\n # Create port\\n created_resource = openstack_resource.create()\\n ipv4_list, ipv6_list = _get_fixed_ips_from_port(created_resource)\\n fixed_ips = ipv4_list + ipv6_list\\n _export_ips_to_port_instance(ipv4_list, ipv6_list)\\n\\n # Handle runtime properties\\n update_runtime_properties(\\n {\\n RESOURCE_ID: created_resource.id,\\n 'fixed_ips': fixed_ips,\\n 'mac_address': created_resource.mac_address,\\n 'allowed_address_pairs': created_resource.allowed_address_pairs,\\n }\\n )\",\n \"def create(cls , specgrid , zcorn , coord , actnum , mapaxes = None ):\\n return cls._grdecl_create( specgrid[0] , specgrid[1] , specgrid[2] , zcorn , coord , actnum , mapaxes )\",\n \"def create(self):\\n\\n raise NotImplementedError\",\n \"def new_object(self):\\r\\n\\t\\tpass\",\n \"def create_comm(comm_title, days, comm_name, comm_plat, comm_desc, comp_rating):\\n time = timezone.now() + datetime.timedelta(days=days)\\n return Commission.objects.create(commission_title=comm_title,\\n commissioner_name=comm_name,\\n commissioner_platform=comm_plat,\\n commission_description=comm_desc,\\n complexity_rating=comp_rating,\\n creation_date=time)\",\n \"def createNode(self, pkg, exe, args, name, nspace):\\r\\n node = Node(self)\\r\\n self.callRemote('createNode', pkg, exe, args, name,\\r\\n nspace).chainDeferred(node)\\r\\n return node\",\n \"def create(cls, name, comment=None):\\n comment = comment if comment else ''\\n cls.json = {'name': name,\\n 'comment': comment}\\n return ElementCreator(cls)\"\n]"},"negative_scores":{"kind":"list like","value":["0.736534","0.7325312","0.66521376","0.6403803","0.6099133","0.60763836","0.6029606","0.59636647","0.5960595","0.59251946","0.57609355","0.57137877","0.5665697","0.563881","0.55801606","0.5452205","0.54070544","0.53563625","0.5342132","0.5272799","0.5225759","0.52138823","0.5193385","0.51932365","0.51932365","0.5170296","0.51327497","0.510586","0.50864923","0.5050677","0.50235975","0.50020546","0.499863","0.49834025","0.49655697","0.49607366","0.49476153","0.49365166","0.49184203","0.4892837","0.4888291","0.4879354","0.4869009","0.48590887","0.48461714","0.48433676","0.4836576","0.48358646","0.48340952","0.48277715","0.48205927","0.48086292","0.47939035","0.479008","0.47895938","0.47818884","0.47799912","0.4760526","0.47581747","0.4751541","0.47425914","0.4740594","0.473945","0.473945","0.4732469","0.4716388","0.4715481","0.4704558","0.46965876","0.46884087","0.46871576","0.46869037","0.4674155","0.46726263","0.46698022","0.4662941","0.46608776","0.4656949","0.46272","0.46207342","0.46182996","0.46170294","0.46131828","0.46098003","0.46025735","0.45954907","0.45914477","0.45849815","0.458323","0.4577306","0.45726094","0.45675448","0.45674413","0.45489955","0.45449355","0.4538911","0.4532393","0.4531944","0.45304164","0.45280948"],"string":"[\n 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Secret keys are used for authentication with the Object Storage Service's Amazon S3 compatible API. For information, see `Managing User Credentials`__. You must specify a description for the secret key (although it can be an empty string). It does not have to be unique, and you can change it anytime with"},"document":{"kind":"string","value":"def create_customer_secret_key(self, create_customer_secret_key_details, user_id, **kwargs):\n resource_path = \"/users/{userId}/customerSecretKeys\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_customer_secret_key got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_customer_secret_key_details,\n response_type=\"CustomerSecretKey\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_customer_secret_key_details,\n response_type=\"CustomerSecretKey\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_access_key(self, user_name=None):\r\n params = {'UserName' : user_name}\r\n return self.get_response('CreateAccessKey', params)","def create_key(iam_username):\n\n try:\n response = iam.create_access_key(UserName=iam_username)\n access_key = response[\"AccessKey\"][\"AccessKeyId\"]\n secret_key = response[\"AccessKey\"][\"SecretAccessKey\"]\n json_data = json.dumps({\"AccessKey\": access_key, \"SecretKey\": secret_key})\n secretmanager.put_secret_value(SecretId=iam_username, SecretString=json_data)\n\n \n emailmsg = (\n \"Hello,\\n\\n\"\n \"A new access key has been created for key rotation. \\n\\n\"\n f\"Access Key Id: {access_key}\\n\"\n f\"Secrets Manager Secret Id: {iam_username}\"\n )\n\n emailmsg = (\n f\"{emailmsg}\\n\\n\"\n f\"Please obtain the new access key information from \"\n \"secrets manager using the secret Id provided above in \"\n f\"{AWS_REGION_NAME} and update your application within 14 days \"\n \"to avoid interruption.\\n\"\n )\n\n sns.publish(\n TopicArn=SNS_TOPIC_ARN,\n Message=emailmsg,\n Subject=f\"AWS Access Key Rotation: New key is available for \"\n f\"{iam_username}\",\n )\n print(f\"New access key has been created for {iam_username}\")\n return {\"status\": 200}\n except ClientError as e:\n print(e)\n return {\"status\": 500}","def create(self):\n id_access_secretkey = uuid.uuid4()\n id_webuser = Base.logged_id_webuser or None\n keys = Token().generate_secretkey(config.PACKAGE_NAME)\n\n with Database() as db:\n db.insert(Table(id_access_secretkey, id_webuser, config.PACKAGE_NAME,\n keys['randomkey'], keys['secretkey']))\n db.commit()\n\n return {\n 'secretkey': keys['secretkey'],\n 'message': 'access secretkey successfully created'\n }","def add(ctx: CLIContext, user_id, resource_policy, admin, inactive, rate_limit):\n with Session() as session:\n try:\n data = session.KeyPair.create(\n user_id,\n is_active=not inactive,\n is_admin=admin,\n resource_policy=resource_policy,\n rate_limit=rate_limit)\n except Exception as e:\n ctx.output.print_mutation_error(\n e,\n item_name='keypair',\n action_name='add',\n )\n sys.exit(1)\n if not data['ok']:\n ctx.output.print_mutation_error(\n msg=data['msg'],\n item_name='keypair',\n action_name='add',\n )\n sys.exit(1)\n ctx.output.print_mutation_result(\n data,\n item_name='keypair',\n extra_info={\n 'access_key': data['keypair']['access_key'],\n 'secret_key': data['keypair']['secret_key'],\n },\n )","def create_secret(secret_name, secret_value, environment):\n environment.add_cleanup(\n environment.cfy.secrets.delete,\n kwargs={\n 'secret_name': secret_name,\n },\n )\n environment.cfy.secrets.create(\n secret_name=secret_name,\n secret_value=secret_value,\n )","def GetSecretKey(cls, user_id):\n uid = hashlib.sha256(str(user_id)).hexdigest()\n entity = ndb.Key(cls, uid).get()\n if not entity:\n entity = cls(id=uid, secret_key=GenerateRandomHexKey())\n entity.put()\n return entity.secret_key","def create_keypair(self, username):\n msg = \"create_keypair not implemented\"\n raise NotImplementedError(msg)","def create_consumer(self, name, description=None, user=None):\n consumer, created = self.get_or_create(name=name)\n\n if user:\n consumer.user = user\n\n if description:\n consumer.description = description\n\n if created:\n consumer.key, consumer.secret = self.generate_random_codes()\n consumer.save()\n\n return consumer","def create_with_user_id(cls: Type[T], user_id: int, secret: str) -> T:\n if not isinstance(user_id, int):\n raise TypeError('user_id must be of type `int`')\n\n if not isinstance(secret, str):\n raise TypeError('secret must be of type `str`')\n\n return cls._create(user_id, None, secret)","def create_access_key(self, user_name=None, delegate_account=None):\n self.log.debug(\"Creating access key for \" + user_name )\n params = {'UserName': user_name}\n if delegate_account:\n params['DelegateAccount'] = delegate_account\n response = self.connection.get_response('CreateAccessKey', params)\n access_tuple = {}\n access_tuple['access_key_id'] = response['create_access_key_response']\\\n ['create_access_key_result']['access_key']['access_key_id']\n access_tuple['secret_access_key'] = response['create_access_key_response']\\\n ['create_access_key_result']['access_key']['secret_access_key']\n return access_tuple","def create_jwt(user, secret):\n logger.debug(\"Create JWT with secret %s\" % secret)\n # username = request.POST['username']\n # password = request.POST['password'\n\n expiry = datetime.datetime.now() + datetime.timedelta(seconds=30)\n expiry_s = time.mktime(expiry.timetuple())\n if user.is_authenticated():\n internalid = user.authprofile.internalid\n payload = {'username': user.username, 'expiry': expiry_s, 'type': \"AuthenticatedUser\", 'internalid': internalid, 'email': user.email}\n token = jws.sign(payload, secret, algorithm='HS256')\n else:\n payload = {'expiry':expiry_s, 'type': \"AnonymousUser\", 'internalid': None, 'email': None}\n token = jws.sign(payload, secret, algorithm='HS256')\n logger.debug(\"Payload: %s\" % payload)\n # logger.info(\"Token: %s\" % token)\n return token","def api_key( self, trans, user_id, **kwd ):\n user = self.get_user( trans, user_id )\n key = self.create_api_key( trans, user )\n return key","def add_ssh_key(self, user_id, title, ssh_key):\n _gu = self.get_user(user_id)\n if _gu is None:\n return None\n\n # build URL and make request\n return self._post(\n '/users/{0}/keys'.format(_gu['id']),\n data={'title': title, 'key': ssh_key},\n )","def create_user(user_id, password_16char, public_key_32char):\n headers = {'Content-type': 'application/json'}\n payload = {'user_id': user_id\n , 'user_password': password_16char\n , 'public_key': public_key_32char}\n response = requests.post(\"http://localhost:5000/user/createUser\", data=json.dumps(payload), headers=headers)\n return response.text","def create_secret(logger,namespace,body,v1=None):\n if v1 is None:\n v1 = client.CoreV1Api()\n logger.debug('new client - fn create secret')\n try:\n name = body['metadata']['name']\n except KeyError:\n logger.debug(\"No name in body ?\")\n raise kopf.TemporaryError(\"can not get the name.\")\n try:\n data = body.get('data')\n except KeyError:\n data = ''\n logger.error(\"Empty secret?? could not get the data.\")\n \n secret_type = 'Opaque'\n if 'type' in body:\n secret_type = body['type']\n\n metadata = {'name': name, 'namespace': namespace}\n api_version = 'v1'\n kind = 'Secret'\n body = client.V1Secret(api_version, data , kind, metadata, type = secret_type)\n # kopf.adopt(body)\n logger.info(f\"cloning secret in namespace {namespace}\")\n try:\n api_response = v1.create_namespaced_secret(namespace, body)\n except client.rest.ApiException as e:\n if e.reason == 'Conflict':\n logger.warning(f\"secret `{name}` already exist in namesace '{namespace}'\")\n return 0\n logger.error(f'Can not create a secret, it is base64 encoded? data: {data}')\n logger.error(f'Kube exception {e}')\n return 1\n return 0","def _create_user(userid, **kw):\n\n new_user = User(userid, **kw)\n USERS[new_user.token] = new_user\n return USERS[new_user.token]","def secret_key(self, val):\n self.__secret_key = val","def create_keypair(econfig_file=None, region=None, keyname=\"bcbio\"):\n import boto\n import boto.ec2\n if econfig_file:\n keypair_dir = os.path.dirname(econfig_file).replace(\"elasticluster\", \"aws_keypairs\")\n else:\n keypair_dir = os.path.join(os.getcwd(), \"aws_keypairs\")\n if not os.path.exists(keypair_dir):\n os.makedirs(keypair_dir)\n private_key = os.path.join(os.path.join(keypair_dir, keyname))\n new_key = not os.path.exists(private_key)\n if new_key:\n cmd = [\"ssh-keygen\", \"-t\", \"rsa\", \"-N\", \"\", \"-f\", private_key, \"-C\", \"bcbio_aws_keypair\"]\n subprocess.check_call(cmd)\n public_key = private_key + \".pub\"\n if region:\n ec2 = boto.ec2.connect_to_region(region)\n else:\n ec2 = boto.connect_ec2()\n key = ec2.get_key_pair(keyname)\n if key and new_key:\n print(\"Non matching key %s found in AWS, removing.\" % keyname)\n ec2.delete_key_pair(keyname)\n key = None\n if not key:\n print(\"Key %s not found in AWS, importing created key\" % keyname)\n with open(public_key) as in_handle:\n body = in_handle.read()\n try:\n ec2.import_key_pair(keyname, body)\n except TypeError as e:\n body = body.encode('utf-8')\n ec2.import_key_pair(keyname, body)\n return {\"user_key_name\": keyname, \"user_key_private\": private_key,\n \"user_key_public\": public_key}","def create_secret(self, name, namespace):\n secret_manifest = {\n \"apiVersion\": \"v1\",\n \"kind\": \"Secret\",\n \"metadata\": {\n \"name\": name,\n \"annotations\": {\n \"kubernetes.io/service-account.name\": name\n }\n }\n }\n self.v1_client.create_namespaced_secret(namespace=namespace,\n body=secret_manifest)","def install_secret_key(app, filename='secret_key'):\n filename = os.path.join(app.instance_path, filename)\n\n try:\n app.config['SECRET_KEY'] = open(filename, 'rb').read()\n except IOError:\n print('Error: No secret key. Create it with:')\n full_path = os.path.dirname(filename)\n if not os.path.isdir(full_path):\n print('mkdir -p {filename}'.format(filename=full_path))\n print('head -c 24 /dev/urandom > {filename}'.format(filename=filename))\n sys.exit(1)","def add(key, value, **kwargs):\n cluster_call(\"secret_add\", key=key, value=value, **kwargs, prefix=f\"Adding secret {key}...\", postfix=\"added.\")","def ssh_keygen(username):\n d = user_exists(username)\n assert d, fabric.colors.red(\"User does not exist: %s\" % username)\n\n home = d['home']\n if not fabric.contrib.files.exists(os.path.join(home, \".ssh/id_rsa.pub\")):\n fabric.api.run(\"mkdir -p %s\" % os.path.join(home, \".ssh/\"))\n fabric.api.run(\n \"ssh-keygen -q -t rsa -f '%s' -N ''\" %\n os.path.join(\n home, '.ssh/id_rsa'))\n run('chown indabom:indabom {}'.format(\"/home/indabom/.ssh\"))\n run('chown indabom:indabom {}'.format(\"/home/indabom/.ssh/id_rsa\"))\n run('chown indabom:indabom {}'.format(\"/home/indabom/.ssh/id_rsa.pub\"))","def create_jwt(user_obj):\n return jwt.encode(\n user_serializer.GetUserInfoSerializer(user_obj).data,\n settings.SECRET_KEY, algorithm='HS256').decode('utf-8')","def create_key ():","def create_keypair(key_name):\n if os.path.isfile(SSH_FOLDER + key_name + \".pem\"):\n return # Key already created\n ec2 = boto.ec2.connect_to_region(AWS_REGION)\n key = ec2.create_key_pair(key_name)\n key.save(SSH_FOLDER)","def create_user_key_file(username: str):\n\n user: User = UserModel().get_user(username=username)\n user_key: Key = user.public_key\n\n public_key: bytes = user_key.public_key\n\n if not os.path.exists(\"./ssh_ca\"):\n os.mkdir(\"./ssh_ca\")\n\n with open(f\"./ssh_ca/{username}.pub\") as public_key_file:\n public_key_file.write(public_key.decode())","def generate_user_api_key(user):\n now = datetime.datetime.utcnow()\n payload = {\n 'iss': 'minesweeper-api',\n 'aud': 'client',\n 'iat': now,\n 'nbf': now,\n 'exp': now + _get_api_token_exp_from_config(),\n 'user_id': str(user.id),\n 'is_admin': user.is_admin,\n }\n bytestring = jwt.encode(payload, _get_api_key_from_config())\n token = bytestring.decode('utf-8')\n return token","def generate_access_key(self):\n\t\tfrom app import app\n\t\ts = JSONWebSignatureSerializer(app.config['SECRET_KEY'])\n\t\taccess_key = s.dumps({'username': self.username}) \n\t\tself.access_key = access_key","def create_ssh_key_file(username: str, ssh_key: bytes, ip_address: str):\n\n if not os.path.exists(\"./ansible/keys\"):\n os.mkdir(\"./ansible/keys\")\n\n with open(f\"./ansible/keys/admin_{ip_address}.pem\", \"w\") as ssh_key_file:\n ssh_key_file.write(ssh_key.decode())\n\n os.system(f\"chmod 400 ./ansible/keys/admin_{ip_address}.pem\")","def create_apikey(self, username, api_key):\r\n return 'ApiKey %s:%s' % (username, api_key)","def create_token(user):\n payload = {\n 'sub': user.id,\n 'iat': datetime.utcnow(),\n 'exp': datetime.utcnow() + timedelta(days=1)\n }\n token = jwt.encode(payload, config.SECRET_KEY, algorithm='HS256')\n return token.decode('unicode_escape')","def manage_createNewSecret(self, REQUEST):\n manager = getUtility(IKeyManager)\n manager.rotate()\n response = REQUEST.response\n response.redirect(\n '%s/manage_secret?manage_tabs_message=%s' %\n (self.absolute_url(), 'New+secret+created.')\n )","def gen_api_key(username):\n salt = str(os.urandom(64)).encode('utf-8')\n return hash_password(username, salt)","def upload_api_key(self, user_id, create_api_key_details, **kwargs):\n resource_path = \"/users/{userId}/apiKeys\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"upload_api_key got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_api_key_details,\n response_type=\"ApiKey\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_api_key_details,\n response_type=\"ApiKey\")","def generate_token(user: dict):\n\n payload = {\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=1),\n 'iat': datetime.datetime.utcnow(),\n 'user': user\n }\n token = jwt.encode(\n payload,\n os.getenv('SECRET_KEY'),\n algorithm='HS256'\n )\n return token.decode('UTF-8')","def create(self, validated_data):\n resource = Resource.objects.create(**validated_data.get(\"resource\"))\n return Secret.objects.create(resource=resource)","def create_ssh_keypair(keyname, comment):\n sshdir = os.path.join(util.get_homedir(), '.ssh')\n util.create_directory(sshdir, 0o700)\n keyfile = os.path.join(sshdir, keyname)\n if util.try_stat(keyfile):\n raise RuntimeError('~/.ssh/{} already exists'.format(keyname))\n subprocess.check_call(['ssh-keygen', '-f', keyfile, '-N', \"\", '-q', '-C', comment])\n os.chmod(keyfile, 0o600)\n os.chmod(keyfile + '.pub', 0o644)\n return keyfile","def set_s3_credentials(secret_key_id, secret_access_key, session_token = None):\n if secret_key_id is None:\n raise H2OValueError(\"Secret key ID must be specified\")\n\n if secret_access_key is None:\n raise H2OValueError(\"Secret access key must be specified\")\n \n if not secret_key_id:\n raise H2OValueError(\"Secret key ID must not be empty\")\n \n if not secret_access_key:\n raise H2OValueError(\"Secret access key must not be empty\")\n\n params = {\"secret_key_id\": secret_key_id,\n \"secret_access_key\": secret_access_key,\n \"session_token\": session_token\n }\n h2o.api(\"POST /3/PersistS3\", data=params)\n print(\"Credentials successfully set.\")","async def create_new_user(*, user: User):\n with Session(engine) as session:\n user.password = simple_hash(user.name, user.password) #Hashing password for security\n session.add(user)\n session.commit()\n return {\"message\": \"User {user_id} created\".format(user_id = user.id)}","def generate_user(self):\n user = self.iam_client.create_user(\n UserName=self.generate_username(),\n Tags=self.get_tags()\n )\n\n username = user['User']['UserName']\n accesskey = self.iam_client.create_access_key(UserName=username)\n\n print('UserName = {}\\nAccessKeyId = {}\\nSecretAccessKey = {}'\n .format(\n username,\n accesskey['AccessKey']['AccessKeyId'],\n accesskey['AccessKey']['SecretAccessKey']\n ))\n\n return username, user['User']['Arn']","def create_user_profile(IamUserArn=None, SshUsername=None, SshPublicKey=None, AllowSelfManagement=None):\n pass","def add(ctx, secret, name, issuer, period, oath_type, digits, touch, algorithm,\n counter, force):\n\n digits = int(digits)\n\n if not secret:\n while True:\n secret = click.prompt('Enter a secret key (base32)', err=True)\n try:\n secret = parse_b32_key(secret)\n break\n except Exception as e:\n click.echo(e)\n\n ensure_validated(ctx)\n\n _add_cred(ctx, CredentialData(secret, issuer, name, oath_type, algorithm,\n digits, period, counter, touch), force)","def create_api_key(sender, **kwargs):\r\n if kwargs.get('created') is True:\r\n ApiKey.objects.create(user=kwargs.get('instance'))","def insertNewUser(self,user, access_token):\n newUser = UserToken(username=user, user_key = access_token.key, user_secret = access_token.secret)\n newUser.put()","def generate_key():\n key = Fernet.generate_key()\n with open(\"Secret.key\",\"wb\")as key_file:\n key_file.write(key)","def create_bucket(request: Dict) -> Dict:\n global config\n\n body = {\n \"user_name\": request.get(\"user_name\"),\n \"prefix\": request.get(\"bucket_name\")[0:5],\n \"bucket_name\": request.get(\"bucket_name\"),\n \"region\": request.get(\"region\")\n }\n\n response = requests.post(url=config.api_url('bucket'),\n data=json.dumps(body),\n headers={'content-type': 'application/json'})\n\n if response.status_code == HTTPStatus.OK:\n return response.json()","def set_SecretKey(self, value):\n super(RetrieveUserDashboardInputSet, self)._set_input('SecretKey', value)","def create_token(self, consumer, token_type, timestamp, user=None):\n token, created = self.first_or_create(consumer=consumer, \n token_type=token_type, \n timestamp=timestamp,\n user=user)\n\n if created:\n token.key, token.secret = self.generate_random_codes()\n token.save()\n\n return token","def addPubKey(User, pubkey):\n with cd('~%s' % (User)):\n sudo('mkdir -p .ssh && chmod 700 .ssh', user=User)\n # add key if it doesn't already exist #\n _hazKey = 'no'\n _hazFile = sudo(\"[ -f .ssh/authorized_keys ] && echo 'yes' || echo 'no'\", user=User)\n if _hazFile == 'yes':\n # authorized_keys exist - check if the key already exists\n _hazKey = sudo(\"grep '%s' .ssh/authorized_keys >/dev/null 2>&1 && echo 'yes'\" % (pubkey), user=User)\n if _hazKey == 'no':\n sudo(\"echo '%s' >> .ssh/authorized_keys\" % (pubkey), user=User)\n else:\n print \"[Info] User '%s' key already exists on host '%s'\" % (User, env.host_string)","def create_profile(self, user):\r\n salt = sha.new(str(random.random())).hexdigest()[:5]\r\n activation_key = sha.new(salt+user.username).hexdigest()\r\n return self.create(user=user,\r\n activation_key=activation_key)","def _generateSecretKey():\n return f\"secret.{str(datetime.now())}\"","def add_user_key(self, obj, validity = 0, max_queries_per_ip_per_hour = 0, max_hits_per_query = 0, indexes = None):\n if obj is dict:\n params = obj\n else:\n params = {\"acl\": obj}\n if validity != 0:\n params[\"validity\"] = validity\n if max_queries_per_ip_per_hour != 0:\n params[\"maxQueriesPerIPPerHour\"] = max_queries_per_ip_per_hour\n if max_hits_per_query != 0:\n params[\"maxHitsPerQuery\"] = max_hits_per_query\n if not indexes is None:\n params['indexes'] = indexes\n return AlgoliaUtils_request(self.headers, self.write_hosts, \"POST\", \"/1/keys\", self.timeout, params)","def _secret(value):\n\n match = SECRET_ARN_RE.match(value)\n if match:\n named_groups = match.groupdict()\n return AwsSecret(arn=value,region=named_groups[\"Region\"])\n\n raise argparse.ArgumentTypeError('Given argument \"%s\" is not a valid secret' % value)","def create_namespaced_secret(self, body, namespace, **kwargs):\n kwargs['_return_http_data_only'] = True\n if kwargs.get('callback'):\n return self.create_namespaced_secret_with_http_info(body, namespace, **kwargs)\n else:\n (data) = self.create_namespaced_secret_with_http_info(body, namespace, **kwargs)\n return data","def create_profile(self, user):\n salt = sha.new(str(random.random())).hexdigest()[:5]\n activation_key = sha.new(salt+user.username).hexdigest()\n return self.create(user=user,\n activation_key=activation_key)","def _bcbio_iam_user(conn, args):\n import boto\n name = \"bcbio\"\n access_key_name = \"full_admin_access\"\n if args.nocreate:\n need_creds = False\n else:\n try:\n conn.get_user(name)\n if args.recreate:\n keys = conn.get_all_access_keys(name)\n for access_key in tz.get_in([\"list_access_keys_response\", \"list_access_keys_result\",\n \"access_key_metadata\"], keys, []):\n conn.delete_access_key(access_key[\"access_key_id\"], name)\n need_creds = True\n else:\n need_creds = False\n except boto.exception.BotoServerError:\n conn.create_user(name)\n conn.put_user_policy(name, access_key_name, IAM_POLICY)\n need_creds = True\n if need_creds:\n creds = conn.create_access_key(name)\n else:\n creds = {}\n if creds:\n creds = tz.get_in([\"create_access_key_response\", \"create_access_key_result\", \"access_key\"], creds)\n print(\"User credentials for %s:\" % name)\n for awsid in [\"access_key_id\", \"secret_access_key\"]:\n print(\" %s: %s\" % (awsid, creds.get(awsid)))\n return {\"ec2_access_key\": creds.get(\"access_key_id\"),\n \"ec2_secret_key\": creds.get(\"secret_access_key\")}\n else:\n print(\"User %s already exists, no new credentials\" % name)\n print(\"Edit the configuration file to add existing user's access and secret keys\")\n return {}","def create_profile(self, user, *args, **kwargs):\n salt = hashlib.sha1(str(random.random())).hexdigest()[:5]\n activation_key = hashlib.sha1(salt + user.username).hexdigest()\n return self.create(user=user, activation_key=activation_key, **kwargs)","def create_privatekey():\n \n # Generate the private key\n key_jwk = wallet.create_JWK()\n response_jwk = key_jwk.export(private_key=True, as_dict=True)\n\n return response_jwk","def user_key(user_name=DEFAULT_USER_NAME):\n return ndb.Key('User', user_name)","def test_creating_a_bucket(self):\n with self.client:\n self.create_bucket(self.get_user_token())","def UpdateSecretKey():\n _LOG.info('Updating webapp2_secret_key.')\n webapp2_secret_key = Webapp2SecretKey(id='current_secret_key')\n webapp2_secret_key.secret_key = os.urandom(16).encode('hex')\n webapp2_secret_key.put()\n return True","def create_token(user, title, expiration=_default_expiration_duration_opt):\n if expiration == _default_expiration_duration_opt:\n duration = _default_expiration_duration()\n expiration = duration + datetime.now() if duration else None\n\n token_code = random_string_generator(TOKEN_NAME_PREFIX_LENGTH + MINIMUM_TOKEN_SUFFIX_LENGTH)()\n token_name = token_code[:TOKEN_NAME_PREFIX_LENGTH]\n token_secret = token_code[TOKEN_NAME_PREFIX_LENGTH:]\n\n assert token_name\n assert token_secret\n\n return AppSpecificAuthToken.create(\n user=user,\n title=title,\n expiration=expiration,\n token_name=token_name,\n token_secret=DecryptedValue(token_secret),\n )","def generate_pair(cls, user: User) -> Dict[str, str]:\n if not isinstance(user, User):\n raise PermissionDenied()\n\n refresh_token = RefreshToken.objects.create(user=user)\n access_payload = refresh_token.get_payload_by_token()\n access_payload['type'] = 'access'\n access_token = jwt_encode(access_payload)\n\n return {\n 'access_token': access_token,\n 'refresh_token': refresh_token.token,\n }","def generate_key():\n key = Fernet.generate_key()\n with open(\"secret.key\", \"wb\") as key_file:\n key_file.write(key)","def test_aws_service_api_keypair_generate_post(self):\n pass","def _create_user(self, new_user):\n new_user = User(user_name=new_user['user_name'], pin=new_user['pin'], user_type='customer')\n self.session.output(new_user.get_user_info(), '\\n[ New user created ]')","def create_bucket() -> None:\n try:\n client.make_bucket(DATASETS_BUCKET)\n except BucketAlreadyOwnedByYou:\n logger.debug(f\"Not creating bucket {DATASETS_BUCKET}: Bucket already exists\")\n pass\n else:\n logger.debug(f\"Successfully created bucket {DATASETS_BUCKET}\")","def add(\n ctx,\n secret,\n name,\n issuer,\n period,\n oath_type,\n digits,\n touch,\n algorithm,\n counter,\n force,\n password,\n remember,\n):\n\n digits = int(digits)\n\n if not secret:\n while True:\n secret = click_prompt(\"Enter a secret key (base32)\")\n try:\n secret = parse_b32_key(secret)\n break\n except Exception as e:\n click.echo(e)\n\n _init_session(ctx, password, remember)\n\n _add_cred(\n ctx,\n CredentialData(\n name, oath_type, algorithm, secret, digits, period, counter, issuer\n ),\n touch,\n force,\n )","def add_user():\n load_jws_from_request(request)\n if not hasattr(request, 'jws_header') or request.jws_header is None:\n return \"Invalid Payload\", 401\n username = request.jws_payload['data'].get('username')\n address = request.jws_header['kid']\n user = SLM_User(username=username)\n ses.add(user)\n try:\n ses.commit()\n except Exception as ie:\n current_app.logger.exception(ie)\n ses.rollback()\n ses.flush()\n return 'username taken', 400\n userkey = UserKey(key=address, keytype='public', user_id=user.id,\n last_nonce=request.jws_payload['iat']*1000)\n ses.add(userkey)\n try:\n ses.commit()\n except Exception as ie:\n current_app.logger.exception(ie)\n ses.rollback()\n ses.flush()\n #ses.delete(user)\n #ses.commit()\n return 'username taken', 400\n jresult = jsonify2(userkey, 'UserKey')\n current_app.logger.info(\"registered user %s with key %s\" % (user.id, userkey.key))\n return current_app.bitjws.create_response(jresult)","def new_super_secret(self):\n super_secret_obj = gen_new_super_secret()\n\n temp_cursor = user_db.cursor()\n\n temp_cursor.execute(\n \"\"\"\n UPDATE users\n SET super_secret=?,\n secret_salt=?\n WHERE user_id=?\n \"\"\",\n (\n super_secret_obj[\"super_secret\"],\n super_secret_obj[\"salt\"],\n self.user_id,\n ),\n )\n user_db.commit()\n\n return {\n \"key\": super_secret_obj[\"key\"],\n \"salt\": super_secret_obj[\"salt\"]\n }","def prepareInstance(username, sshId):\n print os.environ['EC2_KEYPAIR_PATH']\n with settings(user='ubuntu',\n key_filename=os.environ['EC2_KEYPAIR_PATH']):\n password = getpass('Enter a new password for user %s:' % username)\n password2 = getpass('Enter the password a again:')\n if password != password2:\n raise RuntimeError(\"Passwords don't match\")\n sudo('adduser --disabled-password --gecos \",,,\" %s' % username)\n cryptedPassword = _hashPassword(password)\n sudo('usermod --password %s %s' % (cryptedPassword, username))\n sudo('gpasswd --add %s admin' % username)\n authorizeSshKey(username, sshId)\n sudo('apt-get update')\n sudo('DEBIAN_FRONTEND=noninteractive apt-get dist-upgrade -y')\n if exists('/var/run/reboot-required'):\n reboot()","def create_keypair(address_type, addresses_path, address_prefix, name):\n vkey_file = get_vkey_file(addresses_path, address_prefix, name)\n skey_file = get_skey_file(addresses_path, address_prefix, name)\n\n if(path.exists(vkey_file)) :\n print(address_prefix, \"key pair already exists for\", name)\n return\n \n makedirs(path.dirname(vkey_file), mode=0o777, exist_ok=True)\n\n run_params = ['cardano-cli', address_type, 'key-gen', '--verification-key-file', vkey_file, '--signing-key-file', skey_file]\n subprocess_run(run_params, capture_output=False, text=True)\n return","def setup_keys():\n if os.path.isfile(\"key.txt\"):\n message = \"Key already generated\"\n else:\n secret = secrets.token_urlsafe(64)\n message = \"Secret generated and saved in key.txt\"\n with open(\"key.txt\", \"w\") as fd:\n fd.write(secret)\n return json.dumps({'message': message})","def create(self, name, public_key=None):\n data = {\n \"keypair\": {\n \"name\": name\n }\n }\n if public_key is not None:\n data['keypair']['public_key'] = public_key\n \n path = '/os-keypairs'\n res = self.client.call(path, 'POST', data=json.dumps(data), \n token=self.manager.identity.token)\n self.logger.debug('Create/import openstack keypair: %s' % truncate(res))\n return res[0]['keypair']","def s3_create_bucket(self):\n self.conn.create_bucket(DEFAULT_BUCKET_NAME)","def create_key(key_name, save_path, region=None, key=None, keyid=None, profile=None):\n conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile)\n\n try:\n key = conn.create_key_pair(key_name)\n log.debug(\"the key to return is : %s\", key)\n key.save(save_path)\n return key.material\n except boto.exception.BotoServerError as e:\n log.debug(e)\n return False","def create_user(self):\n # TODO-ROB: This is used ONLY when the user registers in flask\n # TODO-ROB: Create the cookiecutter.json file\n # extra_context overrides user and default configs\n cookiecutter(self.user_cookie, no_input=True, extra_context={\"user_name\": self.user}, output_dir=self.users)","def create_new_credential(account,userName,password):\n new_credential = Credentials(account,userName,password)\n return new_credential","def create_tags(resource_id, key, value):\n response = EC2.create_tags(\n Resources=[\n resource_id,\n ],\n Tags=[\n {\n 'Key': key,\n 'Value': value\n },\n ]\n )\n return response","async def add_secret(app: Sanic, secret: str, passphrase: str, ttl: Optional[int]) -> str:\n\n key = get_fernet_key(app, passphrase)\n\n sign = hmac.digest(key=key, msg=passphrase.encode(), digest='sha512').hex()\n secret_key = secrets.token_hex(16)\n\n cipher = fernet.Fernet(key)\n encrypted = cipher.encrypt(secret.encode()).decode()\n\n expires = None\n if ttl:\n expires = datetime.utcnow() + timedelta(seconds=ttl)\n\n await app.db.secrets.insert_one({\n 'secret': encrypted,\n 'secret_key': secret_key,\n 'signature': sign,\n 'expires': expires, # for mongo index\n 'ttl': ttl, # for fernet check\n })\n\n return secret_key","def add_user():\n if not request.json:\n abort(400)\n\n db_conn = sqlite3.connect(db_path)\n db = db_conn.cursor()\n\n username = request.json['username']\n public_key = request.json['public_key']\n\n try:\n db.execute(\"INSERT INTO users (username) VALUES (?)\", [username])\n db.execute(\"INSERT INTO public_keys (username, public_key, status) VALUES (?,?,?)\", [username, public_key, PK_STATUS_OK])\n db_conn.commit()\n db_conn.close()\n except sqlite3.IntegrityError:\n db_conn.close()\n abort(400)\n return jsonify({'success':True})","def new_user(client, username, password, apikey=None, docs=None):\n if apikey is None:\n apikey = str(uuid.uuid4())\n passhash = generate_password_hash(password, method='sha1')\n user = User(username, passhash, apikey, docs=docs)\n user.create(client)\n return user","def create_profile(self, user):\n salt = sha.new(str(random.random())).hexdigest()[:5]\n activation_key = sha.new(salt+user.username).hexdigest()\n# prepend \"key_\" to the key_name, because key_names can't start with numbers\n registrationprofile = RegistrationProfile(user=user, activation_key=activation_key)\n db = DB_Session()\n db.add(registrationprofile)\n db.flush()\n db.refresh(registrationprofile)\n db.commit()\n db.close()\n return registrationprofile","def generate_key(self):\n self.key = Fernet.generate_key()\n with open(\"secret.key\", \"wb\") as key_file:\n key_file.write(self.key)","def process_create_dropbox_client_account ( iam_conn, base_name, action_params ) :\n account_name = create_dropbox_client_name( base_name, action_params[ 'name' ] )\n if does_user_exist( iam_conn, account_name ) :\n print 'AWS account ' + account_name + ' already exists. Skipping.'\n return None\n\n print \"Creating AWS account \" + account_name\n iam_conn.create_user( account_name )\n\n if action_params.get( 'generate-access-key', 'NO' ) == 'YES' :\n print \"Generating access key\"\n response = iam_conn.create_access_key( account_name )\n access_key = response[ 'create_access_key_response' ][ 'create_access_key_result' ][ 'access_key' ][ 'access_key_id' ]\n access_key_secret = response[ 'create_access_key_response' ][ 'create_access_key_result' ][ 'access_key' ][ 'secret_access_key' ]\n\n ## FIX: Need to store these with the credentials service at some point.\n key_filename = account_name + '.accesskey.txt'\n print 'Saving access key to file ' + key_filename\n key_file = open( key_filename, 'w' )\n key_file.write( 'Access Key: ' + access_key + '\\n' )\n key_file.write( 'Access Key Secret: ' + access_key_secret )\n key_file.close( )\n print '** WARNING: The access key MUST be registered manually with the credential service before it can be used.'","def create( cls, user_id = None, private_keyfile_path = None ) :\n user_id = user_id or config.USER_ID()\n private_keyfile_path = private_keyfile_path or PRIVATE_RSA_KEYFILE_PATH()\n with open( private_keyfile_path, \"r\" ) as stream :\n private_key = rsa.PrivateKey.load_pkcs1( stream.read() )\n return cls( user_id, private_key )","def token_generate(self, user_id):\n try:\n payload = {\n 'exp': datetime.utcnow() + timedelta(minutes=200),\n 'iat': datetime.utcnow(),\n 'sub': user_id\n }\n encoded_token = jwt.encode(\n payload, current_app.config['SECRET_KEY'], algorithm='HS256'\n )\n return encoded_token\n\n except Exception:\n return str(Exception)","def put_slice_secret( observer_pkey_pem, slice_name, slice_secret, slice_fk=None, opencloud_slice=None ):\n \n ss = None \n \n if opencloud_slice is None:\n # look up the slice \n try:\n if slice_fk is None:\n opencloud_slice = models.Slice.objects.get( name=slice_name )\n else:\n opencloud_slice = models.Slice.objects.get( id=slice_fk.id )\n except Exception, e:\n logger.exception(e)\n logger.error(\"Failed to load slice (%s, %s)\" % (slice_fk, slice_name) )\n return False \n \n ss = models.SliceSecret( slice_id=opencloud_slice, secret=slice_secret )\n \n ss.save()\n \n return True","def create_secrets(file):\n with open(file, 'w') as secfile:\n secfile.write((\n '# _credentials: Maintain your credentials below. Do not remove unused fields.\\n'\n 'USER = \\'\\'\\nPASSWORD = \\'\\'\\n# _courses: Define which courses should be crawled\\nCOURSES = []\\n\\n'\n '# local: Required if you want to download files and store them in a local folder'\n ' (for example in the Dropbox client folder)\\n'\n 'PATH = \\'\\' # Path to the destination folder\\n\\n'\n '# dropbox (-d): Required if you want to download files and upload them to Dropbox\\n'\n 'DROPBOX_TOKEN = \\'\\' # Personal Dropbox API token\\n'\n 'PATH_IN_DB = \\'\\' # Destination path of downloaded files within Dropbox\\n'))\n print('File app_secrets.py was created. Please maintain your credentials.')\n sys.exit(1)","def create_token(request, user):\n\n key = get_random_string(100)\n data = {}\n ip = get_client_ip_address(request)\n\n return Token.objects.create(user=user, key=key, data=json.dumps(data), ip=ip)","def createSaltKey(operation,newPassword,newPasswordTag):\n \n newPasswordEncrypted=encrypt(GlobalSaltKeyValue,newPassword)\n \n if os.path.isfile(GlobalKeyVaultFile):\n if checkTag(GlobalKeyVaultFileSection,newPasswordTag):\n if operation == 'update':\n addUpdateTag(newPasswordTag, newPasswordEncrypted)\n print \"Success-Password updated\"\n else:\n print \"Error:0001-Section and password tag already exists.\"\n sys.exit(2)\n\n else:\n if operation == 'add': \n addUpdateTag(newPasswordTag, newPasswordEncrypted)\n print \"Success-Password added\"\n else:\n print \"Error:0002-No matching tag found.\"\n sys.exit(2)\n else:\n print \"Error:0003-Missing file \", GlobalKeyVaultFile\n sys.exit(2)","def secret_cognito_hash(\n username: str,\n cognito_client_id: str,\n cognito_secret: str\n) -> str:\n message = bytes(username + cognito_client_id, encoding='utf-8')\n key = bytes(cognito_secret, encoding='utf-8')\n\n secret_hash = base64.b64encode(\n hmac.new(\n key=key,\n msg=message,\n digestmod=hashlib.sha256\n ).digest()\n ).decode()\n\n return secret_hash","def create_new_user():\n username = input('Vad är ditt användarID?: ')\n filename = 'user_db.json'\n \n with open(f'txt_files/{filename}', 'w') as f:\n json.dump(username, f)\n return username","def _generateSSHKey(self, private_filepath, public_filepath):\n self.log.debug(\"Writing SSH keys to: \" + private_filepath + \" and \" + public_filepath)\n\n (ssh_dir, filename) = os.path.split(os.path.expanduser(private_filepath))\n if not os.path.exists(ssh_dir):\n self.log.debug(\"SSH Directory doesn't exist, creating \" + ssh_dir)\n os.makedirs(ssh_dir)\n\n key = paramiko.RSAKey.generate(1024)\n key.write_private_key_file(os.path.expanduser(private_filepath))\n \n with open(os.path.expanduser(public_filepath),\"w\") as public:\n public.write(\"%s %s\" % (key.get_name(), key.get_base64()))\n\n public.close()","def create_sample_tag(user, name=\"spicy\"):\n return Tag.objects.create(custom_user=user, name=name)","def create_user_credentials(storage_type, storage_id, space_name, client_ip,\n user_details):\n user_id = user_details[\"id\"]\n if user_id == \"0\":\n return PosixCredentials(0, 0)\n\n uid = gid = gen_storage_id(user_id)\n return PosixCredentials(uid, gid)","async def write_secret(self, name: str, value: str, content_type: str, tags: dict):\n pass","def create_temp_user(client, role_arn):\n try:\n response = client.assume_role(\n RoleArn=role_arn,\n RoleSessionName=\"Lambda-Start-Stop-functionality\"\n )\n ec2_user = boto3.client(\n 'ec2',\n aws_access_key_id=response['Credentials']['AccessKeyId'],\n aws_secret_access_key=response['Credentials']['SecretAccessKey'],\n aws_session_token=response['Credentials']['SessionToken']\n )\n return ec2_user\n except Exception as error:\n logger.info(\"Creating a temporary ec2 privileged user failed with the following error : {}\".format(error))","def create_sample_recipe(user, **params):\n\n defaults = {\n 'title': 'Polish Soup',\n 'time_minutes': 45,\n 'price': 15.89\n }\n defaults.update(params)\n return Recipe.objects.create(user=user, **defaults)","async def create_wallet(self, user_id: str) -> None:\n self._wallet_id = self.generate_wallet_id()\n\n transaction = Transaction(\n wallet_id=self.wallet_id,\n type=TransactionType.CREATE,\n data={\"amount\": self.DEFAULT_BALANCE},\n nonce=None,\n )\n\n # todo: create separate user storage\n user_pk = f\"{user_id}{self.USER_KEY_POSTFIX}\"\n\n try:\n await self.storage.transaction_write_items(\n items=[\n # create transaction record\n self.storage.item_factory.put_idempotency_item(\n pk=transaction.unique_id, data=transaction.as_dict()\n ),\n # create wallet\n self.storage.item_factory.put_idempotency_item(\n pk=self.unique_id,\n data={self.BALANCE_KEY: self.DEFAULT_BALANCE},\n ),\n # create link between wallet and user\n self.storage.item_factory.put_idempotency_item(\n pk=user_pk, data={self.USER_WALLET_KEY: self.wallet_id}\n ),\n ]\n )\n except storage.exceptions.TransactionMultipleError as e:\n if e.errors[0]:\n raise crud.exceptions.WalletTransactionAlreadyRegisteredError(\n str(e.errors[0])\n )\n\n raise crud.exceptions.WalletAlreadyExistsError(\n f\"Wallet already exists for the user {user_pk}\"\n )"],"string":"[\n \"def create_access_key(self, user_name=None):\\r\\n params = {'UserName' : user_name}\\r\\n return self.get_response('CreateAccessKey', params)\",\n \"def create_key(iam_username):\\n\\n try:\\n response = iam.create_access_key(UserName=iam_username)\\n access_key = response[\\\"AccessKey\\\"][\\\"AccessKeyId\\\"]\\n secret_key = response[\\\"AccessKey\\\"][\\\"SecretAccessKey\\\"]\\n json_data = json.dumps({\\\"AccessKey\\\": access_key, \\\"SecretKey\\\": secret_key})\\n secretmanager.put_secret_value(SecretId=iam_username, SecretString=json_data)\\n\\n \\n emailmsg = (\\n \\\"Hello,\\\\n\\\\n\\\"\\n \\\"A new access key has been created for key rotation. \\\\n\\\\n\\\"\\n f\\\"Access Key Id: {access_key}\\\\n\\\"\\n f\\\"Secrets Manager Secret Id: {iam_username}\\\"\\n )\\n\\n emailmsg = (\\n f\\\"{emailmsg}\\\\n\\\\n\\\"\\n f\\\"Please obtain the new access key information from \\\"\\n \\\"secrets manager using the secret Id provided above in \\\"\\n f\\\"{AWS_REGION_NAME} and update your application within 14 days \\\"\\n \\\"to avoid interruption.\\\\n\\\"\\n )\\n\\n sns.publish(\\n TopicArn=SNS_TOPIC_ARN,\\n Message=emailmsg,\\n Subject=f\\\"AWS Access Key Rotation: New key is available for \\\"\\n f\\\"{iam_username}\\\",\\n )\\n print(f\\\"New access key has been created for {iam_username}\\\")\\n return {\\\"status\\\": 200}\\n except ClientError as e:\\n print(e)\\n return {\\\"status\\\": 500}\",\n \"def create(self):\\n id_access_secretkey = uuid.uuid4()\\n id_webuser = Base.logged_id_webuser or None\\n keys = Token().generate_secretkey(config.PACKAGE_NAME)\\n\\n with Database() as db:\\n db.insert(Table(id_access_secretkey, id_webuser, config.PACKAGE_NAME,\\n keys['randomkey'], keys['secretkey']))\\n db.commit()\\n\\n return {\\n 'secretkey': keys['secretkey'],\\n 'message': 'access secretkey successfully created'\\n }\",\n \"def add(ctx: CLIContext, user_id, resource_policy, admin, inactive, rate_limit):\\n with Session() as session:\\n try:\\n data = session.KeyPair.create(\\n user_id,\\n is_active=not inactive,\\n is_admin=admin,\\n resource_policy=resource_policy,\\n rate_limit=rate_limit)\\n except Exception as e:\\n ctx.output.print_mutation_error(\\n e,\\n item_name='keypair',\\n action_name='add',\\n )\\n sys.exit(1)\\n if not data['ok']:\\n ctx.output.print_mutation_error(\\n msg=data['msg'],\\n item_name='keypair',\\n action_name='add',\\n )\\n sys.exit(1)\\n ctx.output.print_mutation_result(\\n data,\\n item_name='keypair',\\n extra_info={\\n 'access_key': data['keypair']['access_key'],\\n 'secret_key': data['keypair']['secret_key'],\\n },\\n )\",\n \"def create_secret(secret_name, secret_value, environment):\\n environment.add_cleanup(\\n environment.cfy.secrets.delete,\\n kwargs={\\n 'secret_name': secret_name,\\n },\\n )\\n environment.cfy.secrets.create(\\n secret_name=secret_name,\\n secret_value=secret_value,\\n )\",\n \"def GetSecretKey(cls, user_id):\\n uid = hashlib.sha256(str(user_id)).hexdigest()\\n entity = ndb.Key(cls, uid).get()\\n if not entity:\\n entity = cls(id=uid, secret_key=GenerateRandomHexKey())\\n entity.put()\\n return entity.secret_key\",\n \"def create_keypair(self, username):\\n msg = \\\"create_keypair not implemented\\\"\\n raise NotImplementedError(msg)\",\n \"def create_consumer(self, name, description=None, user=None):\\n consumer, created = self.get_or_create(name=name)\\n\\n if user:\\n consumer.user = user\\n\\n if description:\\n consumer.description = description\\n\\n if created:\\n consumer.key, consumer.secret = self.generate_random_codes()\\n consumer.save()\\n\\n return consumer\",\n \"def create_with_user_id(cls: Type[T], user_id: int, secret: str) -> T:\\n if not isinstance(user_id, int):\\n raise TypeError('user_id must be of type `int`')\\n\\n if not isinstance(secret, str):\\n raise TypeError('secret must be of type `str`')\\n\\n return cls._create(user_id, None, secret)\",\n \"def create_access_key(self, user_name=None, delegate_account=None):\\n self.log.debug(\\\"Creating access key for \\\" + user_name )\\n params = {'UserName': user_name}\\n if delegate_account:\\n params['DelegateAccount'] = delegate_account\\n response = self.connection.get_response('CreateAccessKey', params)\\n access_tuple = {}\\n access_tuple['access_key_id'] = response['create_access_key_response']\\\\\\n ['create_access_key_result']['access_key']['access_key_id']\\n access_tuple['secret_access_key'] = response['create_access_key_response']\\\\\\n ['create_access_key_result']['access_key']['secret_access_key']\\n return access_tuple\",\n \"def create_jwt(user, secret):\\n logger.debug(\\\"Create JWT with secret %s\\\" % secret)\\n # username = request.POST['username']\\n # password = request.POST['password'\\n\\n expiry = datetime.datetime.now() + datetime.timedelta(seconds=30)\\n expiry_s = time.mktime(expiry.timetuple())\\n if user.is_authenticated():\\n internalid = user.authprofile.internalid\\n payload = {'username': user.username, 'expiry': expiry_s, 'type': \\\"AuthenticatedUser\\\", 'internalid': internalid, 'email': user.email}\\n token = jws.sign(payload, secret, algorithm='HS256')\\n else:\\n payload = {'expiry':expiry_s, 'type': \\\"AnonymousUser\\\", 'internalid': None, 'email': None}\\n token = jws.sign(payload, secret, algorithm='HS256')\\n logger.debug(\\\"Payload: %s\\\" % payload)\\n # logger.info(\\\"Token: %s\\\" % token)\\n return token\",\n \"def api_key( self, trans, user_id, **kwd ):\\n user = self.get_user( trans, user_id )\\n key = self.create_api_key( trans, user )\\n return key\",\n \"def add_ssh_key(self, user_id, title, ssh_key):\\n _gu = self.get_user(user_id)\\n if _gu is None:\\n return None\\n\\n # build URL and make request\\n return self._post(\\n '/users/{0}/keys'.format(_gu['id']),\\n data={'title': title, 'key': ssh_key},\\n )\",\n \"def create_user(user_id, password_16char, public_key_32char):\\n headers = {'Content-type': 'application/json'}\\n payload = {'user_id': user_id\\n , 'user_password': password_16char\\n , 'public_key': public_key_32char}\\n response = requests.post(\\\"http://localhost:5000/user/createUser\\\", data=json.dumps(payload), headers=headers)\\n return response.text\",\n \"def create_secret(logger,namespace,body,v1=None):\\n if v1 is None:\\n v1 = client.CoreV1Api()\\n logger.debug('new client - fn create secret')\\n try:\\n name = body['metadata']['name']\\n except KeyError:\\n logger.debug(\\\"No name in body ?\\\")\\n raise kopf.TemporaryError(\\\"can not get the name.\\\")\\n try:\\n data = body.get('data')\\n except KeyError:\\n data = ''\\n logger.error(\\\"Empty secret?? could not get the data.\\\")\\n \\n secret_type = 'Opaque'\\n if 'type' in body:\\n secret_type = body['type']\\n\\n metadata = {'name': name, 'namespace': namespace}\\n api_version = 'v1'\\n kind = 'Secret'\\n body = client.V1Secret(api_version, data , kind, metadata, type = secret_type)\\n # kopf.adopt(body)\\n logger.info(f\\\"cloning secret in namespace {namespace}\\\")\\n try:\\n api_response = v1.create_namespaced_secret(namespace, body)\\n except client.rest.ApiException as e:\\n if e.reason == 'Conflict':\\n logger.warning(f\\\"secret `{name}` already exist in namesace '{namespace}'\\\")\\n return 0\\n logger.error(f'Can not create a secret, it is base64 encoded? data: {data}')\\n logger.error(f'Kube exception {e}')\\n return 1\\n return 0\",\n \"def _create_user(userid, **kw):\\n\\n new_user = User(userid, **kw)\\n USERS[new_user.token] = new_user\\n return USERS[new_user.token]\",\n \"def secret_key(self, val):\\n self.__secret_key = val\",\n \"def create_keypair(econfig_file=None, region=None, keyname=\\\"bcbio\\\"):\\n import boto\\n import boto.ec2\\n if econfig_file:\\n keypair_dir = os.path.dirname(econfig_file).replace(\\\"elasticluster\\\", \\\"aws_keypairs\\\")\\n else:\\n keypair_dir = os.path.join(os.getcwd(), \\\"aws_keypairs\\\")\\n if not os.path.exists(keypair_dir):\\n os.makedirs(keypair_dir)\\n private_key = os.path.join(os.path.join(keypair_dir, keyname))\\n new_key = not os.path.exists(private_key)\\n if new_key:\\n cmd = [\\\"ssh-keygen\\\", \\\"-t\\\", \\\"rsa\\\", \\\"-N\\\", \\\"\\\", \\\"-f\\\", private_key, \\\"-C\\\", \\\"bcbio_aws_keypair\\\"]\\n subprocess.check_call(cmd)\\n public_key = private_key + \\\".pub\\\"\\n if region:\\n ec2 = boto.ec2.connect_to_region(region)\\n else:\\n ec2 = boto.connect_ec2()\\n key = ec2.get_key_pair(keyname)\\n if key and new_key:\\n print(\\\"Non matching key %s found in AWS, removing.\\\" % keyname)\\n ec2.delete_key_pair(keyname)\\n key = None\\n if not key:\\n print(\\\"Key %s not found in AWS, importing created key\\\" % keyname)\\n with open(public_key) as in_handle:\\n body = in_handle.read()\\n try:\\n ec2.import_key_pair(keyname, body)\\n except TypeError as e:\\n body = body.encode('utf-8')\\n ec2.import_key_pair(keyname, body)\\n return {\\\"user_key_name\\\": keyname, \\\"user_key_private\\\": private_key,\\n \\\"user_key_public\\\": public_key}\",\n \"def create_secret(self, name, namespace):\\n secret_manifest = {\\n \\\"apiVersion\\\": \\\"v1\\\",\\n \\\"kind\\\": \\\"Secret\\\",\\n \\\"metadata\\\": {\\n \\\"name\\\": name,\\n \\\"annotations\\\": {\\n \\\"kubernetes.io/service-account.name\\\": name\\n }\\n }\\n }\\n self.v1_client.create_namespaced_secret(namespace=namespace,\\n body=secret_manifest)\",\n \"def install_secret_key(app, filename='secret_key'):\\n filename = os.path.join(app.instance_path, filename)\\n\\n try:\\n app.config['SECRET_KEY'] = open(filename, 'rb').read()\\n except IOError:\\n print('Error: No secret key. Create it with:')\\n full_path = os.path.dirname(filename)\\n if not os.path.isdir(full_path):\\n print('mkdir -p {filename}'.format(filename=full_path))\\n print('head -c 24 /dev/urandom > {filename}'.format(filename=filename))\\n sys.exit(1)\",\n \"def add(key, value, **kwargs):\\n cluster_call(\\\"secret_add\\\", key=key, value=value, **kwargs, prefix=f\\\"Adding secret {key}...\\\", postfix=\\\"added.\\\")\",\n \"def ssh_keygen(username):\\n d = user_exists(username)\\n assert d, fabric.colors.red(\\\"User does not exist: %s\\\" % username)\\n\\n home = d['home']\\n if not fabric.contrib.files.exists(os.path.join(home, \\\".ssh/id_rsa.pub\\\")):\\n fabric.api.run(\\\"mkdir -p %s\\\" % os.path.join(home, \\\".ssh/\\\"))\\n fabric.api.run(\\n \\\"ssh-keygen -q -t rsa -f '%s' -N ''\\\" %\\n os.path.join(\\n home, '.ssh/id_rsa'))\\n run('chown indabom:indabom {}'.format(\\\"/home/indabom/.ssh\\\"))\\n run('chown indabom:indabom {}'.format(\\\"/home/indabom/.ssh/id_rsa\\\"))\\n run('chown indabom:indabom {}'.format(\\\"/home/indabom/.ssh/id_rsa.pub\\\"))\",\n \"def create_jwt(user_obj):\\n return jwt.encode(\\n user_serializer.GetUserInfoSerializer(user_obj).data,\\n settings.SECRET_KEY, algorithm='HS256').decode('utf-8')\",\n \"def create_key ():\",\n \"def create_keypair(key_name):\\n if os.path.isfile(SSH_FOLDER + key_name + \\\".pem\\\"):\\n return # Key already created\\n ec2 = boto.ec2.connect_to_region(AWS_REGION)\\n key = ec2.create_key_pair(key_name)\\n key.save(SSH_FOLDER)\",\n \"def create_user_key_file(username: str):\\n\\n user: User = UserModel().get_user(username=username)\\n user_key: Key = user.public_key\\n\\n public_key: bytes = user_key.public_key\\n\\n if not os.path.exists(\\\"./ssh_ca\\\"):\\n os.mkdir(\\\"./ssh_ca\\\")\\n\\n with open(f\\\"./ssh_ca/{username}.pub\\\") as public_key_file:\\n public_key_file.write(public_key.decode())\",\n \"def generate_user_api_key(user):\\n now = datetime.datetime.utcnow()\\n payload = {\\n 'iss': 'minesweeper-api',\\n 'aud': 'client',\\n 'iat': now,\\n 'nbf': now,\\n 'exp': now + _get_api_token_exp_from_config(),\\n 'user_id': str(user.id),\\n 'is_admin': user.is_admin,\\n }\\n bytestring = jwt.encode(payload, _get_api_key_from_config())\\n token = bytestring.decode('utf-8')\\n return token\",\n \"def generate_access_key(self):\\n\\t\\tfrom app import app\\n\\t\\ts = JSONWebSignatureSerializer(app.config['SECRET_KEY'])\\n\\t\\taccess_key = s.dumps({'username': self.username}) \\n\\t\\tself.access_key = access_key\",\n \"def create_ssh_key_file(username: str, ssh_key: bytes, ip_address: str):\\n\\n if not os.path.exists(\\\"./ansible/keys\\\"):\\n os.mkdir(\\\"./ansible/keys\\\")\\n\\n with open(f\\\"./ansible/keys/admin_{ip_address}.pem\\\", \\\"w\\\") as ssh_key_file:\\n ssh_key_file.write(ssh_key.decode())\\n\\n os.system(f\\\"chmod 400 ./ansible/keys/admin_{ip_address}.pem\\\")\",\n \"def create_apikey(self, username, api_key):\\r\\n return 'ApiKey %s:%s' % (username, api_key)\",\n \"def create_token(user):\\n payload = {\\n 'sub': user.id,\\n 'iat': datetime.utcnow(),\\n 'exp': datetime.utcnow() + timedelta(days=1)\\n }\\n token = jwt.encode(payload, config.SECRET_KEY, algorithm='HS256')\\n return token.decode('unicode_escape')\",\n \"def manage_createNewSecret(self, REQUEST):\\n manager = getUtility(IKeyManager)\\n manager.rotate()\\n response = REQUEST.response\\n response.redirect(\\n '%s/manage_secret?manage_tabs_message=%s' %\\n (self.absolute_url(), 'New+secret+created.')\\n )\",\n \"def gen_api_key(username):\\n salt = str(os.urandom(64)).encode('utf-8')\\n return hash_password(username, salt)\",\n \"def upload_api_key(self, user_id, create_api_key_details, **kwargs):\\n resource_path = \\\"/users/{userId}/apiKeys\\\"\\n method = \\\"POST\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"opc_retry_token\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"upload_api_key got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"userId\\\": user_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"opc-retry-token\\\": kwargs.get(\\\"opc_retry_token\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\\n self.base_client.add_opc_retry_token_if_needed(header_params)\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=create_api_key_details,\\n response_type=\\\"ApiKey\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=create_api_key_details,\\n response_type=\\\"ApiKey\\\")\",\n \"def generate_token(user: dict):\\n\\n payload = {\\n 'exp': datetime.datetime.utcnow() + datetime.timedelta(days=1),\\n 'iat': datetime.datetime.utcnow(),\\n 'user': user\\n }\\n token = jwt.encode(\\n payload,\\n os.getenv('SECRET_KEY'),\\n algorithm='HS256'\\n )\\n return token.decode('UTF-8')\",\n \"def create(self, validated_data):\\n resource = Resource.objects.create(**validated_data.get(\\\"resource\\\"))\\n return Secret.objects.create(resource=resource)\",\n \"def create_ssh_keypair(keyname, comment):\\n sshdir = os.path.join(util.get_homedir(), '.ssh')\\n util.create_directory(sshdir, 0o700)\\n keyfile = os.path.join(sshdir, keyname)\\n if util.try_stat(keyfile):\\n raise RuntimeError('~/.ssh/{} already exists'.format(keyname))\\n subprocess.check_call(['ssh-keygen', '-f', keyfile, '-N', \\\"\\\", '-q', '-C', comment])\\n os.chmod(keyfile, 0o600)\\n os.chmod(keyfile + '.pub', 0o644)\\n return keyfile\",\n \"def set_s3_credentials(secret_key_id, secret_access_key, session_token = None):\\n if secret_key_id is None:\\n raise H2OValueError(\\\"Secret key ID must be specified\\\")\\n\\n if secret_access_key is None:\\n raise H2OValueError(\\\"Secret access key must be specified\\\")\\n \\n if not secret_key_id:\\n raise H2OValueError(\\\"Secret key ID must not be empty\\\")\\n \\n if not secret_access_key:\\n raise H2OValueError(\\\"Secret access key must not be empty\\\")\\n\\n params = {\\\"secret_key_id\\\": secret_key_id,\\n \\\"secret_access_key\\\": secret_access_key,\\n \\\"session_token\\\": session_token\\n }\\n h2o.api(\\\"POST /3/PersistS3\\\", data=params)\\n print(\\\"Credentials successfully set.\\\")\",\n \"async def create_new_user(*, user: User):\\n with Session(engine) as session:\\n user.password = simple_hash(user.name, user.password) #Hashing password for security\\n session.add(user)\\n session.commit()\\n return {\\\"message\\\": \\\"User {user_id} created\\\".format(user_id = user.id)}\",\n \"def generate_user(self):\\n user = self.iam_client.create_user(\\n UserName=self.generate_username(),\\n Tags=self.get_tags()\\n )\\n\\n username = user['User']['UserName']\\n accesskey = self.iam_client.create_access_key(UserName=username)\\n\\n print('UserName = {}\\\\nAccessKeyId = {}\\\\nSecretAccessKey = {}'\\n .format(\\n username,\\n accesskey['AccessKey']['AccessKeyId'],\\n accesskey['AccessKey']['SecretAccessKey']\\n ))\\n\\n return username, user['User']['Arn']\",\n \"def create_user_profile(IamUserArn=None, SshUsername=None, SshPublicKey=None, AllowSelfManagement=None):\\n pass\",\n \"def add(ctx, secret, name, issuer, period, oath_type, digits, touch, algorithm,\\n counter, force):\\n\\n digits = int(digits)\\n\\n if not secret:\\n while True:\\n secret = click.prompt('Enter a secret key (base32)', err=True)\\n try:\\n secret = parse_b32_key(secret)\\n break\\n except Exception as e:\\n click.echo(e)\\n\\n ensure_validated(ctx)\\n\\n _add_cred(ctx, CredentialData(secret, issuer, name, oath_type, algorithm,\\n digits, period, counter, touch), force)\",\n \"def create_api_key(sender, **kwargs):\\r\\n if kwargs.get('created') is True:\\r\\n ApiKey.objects.create(user=kwargs.get('instance'))\",\n \"def insertNewUser(self,user, access_token):\\n newUser = UserToken(username=user, user_key = access_token.key, user_secret = access_token.secret)\\n newUser.put()\",\n \"def generate_key():\\n key = Fernet.generate_key()\\n with open(\\\"Secret.key\\\",\\\"wb\\\")as key_file:\\n key_file.write(key)\",\n \"def create_bucket(request: Dict) -> Dict:\\n global config\\n\\n body = {\\n \\\"user_name\\\": request.get(\\\"user_name\\\"),\\n \\\"prefix\\\": request.get(\\\"bucket_name\\\")[0:5],\\n \\\"bucket_name\\\": request.get(\\\"bucket_name\\\"),\\n \\\"region\\\": request.get(\\\"region\\\")\\n }\\n\\n response = requests.post(url=config.api_url('bucket'),\\n data=json.dumps(body),\\n headers={'content-type': 'application/json'})\\n\\n if response.status_code == HTTPStatus.OK:\\n return response.json()\",\n \"def set_SecretKey(self, value):\\n super(RetrieveUserDashboardInputSet, self)._set_input('SecretKey', value)\",\n \"def create_token(self, consumer, token_type, timestamp, user=None):\\n token, created = self.first_or_create(consumer=consumer, \\n token_type=token_type, \\n timestamp=timestamp,\\n user=user)\\n\\n if created:\\n token.key, token.secret = self.generate_random_codes()\\n token.save()\\n\\n return token\",\n \"def addPubKey(User, pubkey):\\n with cd('~%s' % (User)):\\n sudo('mkdir -p .ssh && chmod 700 .ssh', user=User)\\n # add key if it doesn't already exist #\\n _hazKey = 'no'\\n _hazFile = sudo(\\\"[ -f .ssh/authorized_keys ] && echo 'yes' || echo 'no'\\\", user=User)\\n if _hazFile == 'yes':\\n # authorized_keys exist - check if the key already exists\\n _hazKey = sudo(\\\"grep '%s' .ssh/authorized_keys >/dev/null 2>&1 && echo 'yes'\\\" % (pubkey), user=User)\\n if _hazKey == 'no':\\n sudo(\\\"echo '%s' >> .ssh/authorized_keys\\\" % (pubkey), user=User)\\n else:\\n print \\\"[Info] User '%s' key already exists on host '%s'\\\" % (User, env.host_string)\",\n \"def create_profile(self, user):\\r\\n salt = sha.new(str(random.random())).hexdigest()[:5]\\r\\n activation_key = sha.new(salt+user.username).hexdigest()\\r\\n return self.create(user=user,\\r\\n activation_key=activation_key)\",\n \"def _generateSecretKey():\\n return f\\\"secret.{str(datetime.now())}\\\"\",\n \"def add_user_key(self, obj, validity = 0, max_queries_per_ip_per_hour = 0, max_hits_per_query = 0, indexes = None):\\n if obj is dict:\\n params = obj\\n else:\\n params = {\\\"acl\\\": obj}\\n if validity != 0:\\n params[\\\"validity\\\"] = validity\\n if max_queries_per_ip_per_hour != 0:\\n params[\\\"maxQueriesPerIPPerHour\\\"] = max_queries_per_ip_per_hour\\n if max_hits_per_query != 0:\\n params[\\\"maxHitsPerQuery\\\"] = max_hits_per_query\\n if not indexes is None:\\n params['indexes'] = indexes\\n return AlgoliaUtils_request(self.headers, self.write_hosts, \\\"POST\\\", \\\"/1/keys\\\", self.timeout, params)\",\n \"def _secret(value):\\n\\n match = SECRET_ARN_RE.match(value)\\n if match:\\n named_groups = match.groupdict()\\n return AwsSecret(arn=value,region=named_groups[\\\"Region\\\"])\\n\\n raise argparse.ArgumentTypeError('Given argument \\\"%s\\\" is not a valid secret' % value)\",\n \"def create_namespaced_secret(self, body, namespace, **kwargs):\\n kwargs['_return_http_data_only'] = True\\n if kwargs.get('callback'):\\n return self.create_namespaced_secret_with_http_info(body, namespace, **kwargs)\\n else:\\n (data) = self.create_namespaced_secret_with_http_info(body, namespace, **kwargs)\\n return data\",\n \"def create_profile(self, user):\\n salt = sha.new(str(random.random())).hexdigest()[:5]\\n activation_key = sha.new(salt+user.username).hexdigest()\\n return self.create(user=user,\\n activation_key=activation_key)\",\n \"def _bcbio_iam_user(conn, args):\\n import boto\\n name = \\\"bcbio\\\"\\n access_key_name = \\\"full_admin_access\\\"\\n if args.nocreate:\\n need_creds = False\\n else:\\n try:\\n conn.get_user(name)\\n if args.recreate:\\n keys = conn.get_all_access_keys(name)\\n for access_key in tz.get_in([\\\"list_access_keys_response\\\", \\\"list_access_keys_result\\\",\\n \\\"access_key_metadata\\\"], keys, []):\\n conn.delete_access_key(access_key[\\\"access_key_id\\\"], name)\\n need_creds = True\\n else:\\n need_creds = False\\n except boto.exception.BotoServerError:\\n conn.create_user(name)\\n conn.put_user_policy(name, access_key_name, IAM_POLICY)\\n need_creds = True\\n if need_creds:\\n creds = conn.create_access_key(name)\\n else:\\n creds = {}\\n if creds:\\n creds = tz.get_in([\\\"create_access_key_response\\\", \\\"create_access_key_result\\\", \\\"access_key\\\"], creds)\\n print(\\\"User credentials for %s:\\\" % name)\\n for awsid in [\\\"access_key_id\\\", \\\"secret_access_key\\\"]:\\n print(\\\" %s: %s\\\" % (awsid, creds.get(awsid)))\\n return {\\\"ec2_access_key\\\": creds.get(\\\"access_key_id\\\"),\\n \\\"ec2_secret_key\\\": creds.get(\\\"secret_access_key\\\")}\\n else:\\n print(\\\"User %s already exists, no new credentials\\\" % name)\\n print(\\\"Edit the configuration file to add existing user's access and secret keys\\\")\\n return {}\",\n \"def create_profile(self, user, *args, **kwargs):\\n salt = hashlib.sha1(str(random.random())).hexdigest()[:5]\\n activation_key = hashlib.sha1(salt + user.username).hexdigest()\\n return self.create(user=user, activation_key=activation_key, **kwargs)\",\n \"def create_privatekey():\\n \\n # Generate the private key\\n key_jwk = wallet.create_JWK()\\n response_jwk = key_jwk.export(private_key=True, as_dict=True)\\n\\n return response_jwk\",\n \"def user_key(user_name=DEFAULT_USER_NAME):\\n return ndb.Key('User', user_name)\",\n \"def test_creating_a_bucket(self):\\n with self.client:\\n self.create_bucket(self.get_user_token())\",\n \"def UpdateSecretKey():\\n _LOG.info('Updating webapp2_secret_key.')\\n webapp2_secret_key = Webapp2SecretKey(id='current_secret_key')\\n webapp2_secret_key.secret_key = os.urandom(16).encode('hex')\\n webapp2_secret_key.put()\\n return True\",\n \"def create_token(user, title, expiration=_default_expiration_duration_opt):\\n if expiration == _default_expiration_duration_opt:\\n duration = _default_expiration_duration()\\n expiration = duration + datetime.now() if duration else None\\n\\n token_code = random_string_generator(TOKEN_NAME_PREFIX_LENGTH + MINIMUM_TOKEN_SUFFIX_LENGTH)()\\n token_name = token_code[:TOKEN_NAME_PREFIX_LENGTH]\\n token_secret = token_code[TOKEN_NAME_PREFIX_LENGTH:]\\n\\n assert token_name\\n assert token_secret\\n\\n return AppSpecificAuthToken.create(\\n user=user,\\n title=title,\\n expiration=expiration,\\n token_name=token_name,\\n token_secret=DecryptedValue(token_secret),\\n )\",\n \"def generate_pair(cls, user: User) -> Dict[str, str]:\\n if not isinstance(user, User):\\n raise PermissionDenied()\\n\\n refresh_token = RefreshToken.objects.create(user=user)\\n access_payload = refresh_token.get_payload_by_token()\\n access_payload['type'] = 'access'\\n access_token = jwt_encode(access_payload)\\n\\n return {\\n 'access_token': access_token,\\n 'refresh_token': refresh_token.token,\\n }\",\n \"def generate_key():\\n key = Fernet.generate_key()\\n with open(\\\"secret.key\\\", \\\"wb\\\") as key_file:\\n key_file.write(key)\",\n \"def test_aws_service_api_keypair_generate_post(self):\\n pass\",\n \"def _create_user(self, new_user):\\n new_user = User(user_name=new_user['user_name'], pin=new_user['pin'], user_type='customer')\\n self.session.output(new_user.get_user_info(), '\\\\n[ New user created ]')\",\n \"def create_bucket() -> None:\\n try:\\n client.make_bucket(DATASETS_BUCKET)\\n except BucketAlreadyOwnedByYou:\\n logger.debug(f\\\"Not creating bucket {DATASETS_BUCKET}: Bucket already exists\\\")\\n pass\\n else:\\n logger.debug(f\\\"Successfully created bucket {DATASETS_BUCKET}\\\")\",\n \"def add(\\n ctx,\\n secret,\\n name,\\n issuer,\\n period,\\n oath_type,\\n digits,\\n touch,\\n algorithm,\\n counter,\\n force,\\n password,\\n remember,\\n):\\n\\n digits = int(digits)\\n\\n if not secret:\\n while True:\\n secret = click_prompt(\\\"Enter a secret key (base32)\\\")\\n try:\\n secret = parse_b32_key(secret)\\n break\\n except Exception as e:\\n click.echo(e)\\n\\n _init_session(ctx, password, remember)\\n\\n _add_cred(\\n ctx,\\n CredentialData(\\n name, oath_type, algorithm, secret, digits, period, counter, issuer\\n ),\\n touch,\\n force,\\n )\",\n \"def add_user():\\n load_jws_from_request(request)\\n if not hasattr(request, 'jws_header') or request.jws_header is None:\\n return \\\"Invalid Payload\\\", 401\\n username = request.jws_payload['data'].get('username')\\n address = request.jws_header['kid']\\n user = SLM_User(username=username)\\n ses.add(user)\\n try:\\n ses.commit()\\n except Exception as ie:\\n current_app.logger.exception(ie)\\n ses.rollback()\\n ses.flush()\\n return 'username taken', 400\\n userkey = UserKey(key=address, keytype='public', user_id=user.id,\\n last_nonce=request.jws_payload['iat']*1000)\\n ses.add(userkey)\\n try:\\n ses.commit()\\n except Exception as ie:\\n current_app.logger.exception(ie)\\n ses.rollback()\\n ses.flush()\\n #ses.delete(user)\\n #ses.commit()\\n return 'username taken', 400\\n jresult = jsonify2(userkey, 'UserKey')\\n current_app.logger.info(\\\"registered user %s with key %s\\\" % (user.id, userkey.key))\\n return current_app.bitjws.create_response(jresult)\",\n \"def new_super_secret(self):\\n super_secret_obj = gen_new_super_secret()\\n\\n temp_cursor = user_db.cursor()\\n\\n temp_cursor.execute(\\n \\\"\\\"\\\"\\n UPDATE users\\n SET super_secret=?,\\n secret_salt=?\\n WHERE user_id=?\\n \\\"\\\"\\\",\\n (\\n super_secret_obj[\\\"super_secret\\\"],\\n super_secret_obj[\\\"salt\\\"],\\n self.user_id,\\n ),\\n )\\n user_db.commit()\\n\\n return {\\n \\\"key\\\": super_secret_obj[\\\"key\\\"],\\n \\\"salt\\\": super_secret_obj[\\\"salt\\\"]\\n }\",\n \"def prepareInstance(username, sshId):\\n print os.environ['EC2_KEYPAIR_PATH']\\n with settings(user='ubuntu',\\n key_filename=os.environ['EC2_KEYPAIR_PATH']):\\n password = getpass('Enter a new password for user %s:' % username)\\n password2 = getpass('Enter the password a again:')\\n if password != password2:\\n raise RuntimeError(\\\"Passwords don't match\\\")\\n sudo('adduser --disabled-password --gecos \\\",,,\\\" %s' % username)\\n cryptedPassword = _hashPassword(password)\\n sudo('usermod --password %s %s' % (cryptedPassword, username))\\n sudo('gpasswd --add %s admin' % username)\\n authorizeSshKey(username, sshId)\\n sudo('apt-get update')\\n sudo('DEBIAN_FRONTEND=noninteractive apt-get dist-upgrade -y')\\n if exists('/var/run/reboot-required'):\\n reboot()\",\n \"def create_keypair(address_type, addresses_path, address_prefix, name):\\n vkey_file = get_vkey_file(addresses_path, address_prefix, name)\\n skey_file = get_skey_file(addresses_path, address_prefix, name)\\n\\n if(path.exists(vkey_file)) :\\n print(address_prefix, \\\"key pair already exists for\\\", name)\\n return\\n \\n makedirs(path.dirname(vkey_file), mode=0o777, exist_ok=True)\\n\\n run_params = ['cardano-cli', address_type, 'key-gen', '--verification-key-file', vkey_file, '--signing-key-file', skey_file]\\n subprocess_run(run_params, capture_output=False, text=True)\\n return\",\n \"def setup_keys():\\n if os.path.isfile(\\\"key.txt\\\"):\\n message = \\\"Key already generated\\\"\\n else:\\n secret = secrets.token_urlsafe(64)\\n message = \\\"Secret generated and saved in key.txt\\\"\\n with open(\\\"key.txt\\\", \\\"w\\\") as fd:\\n fd.write(secret)\\n return json.dumps({'message': message})\",\n \"def create(self, name, public_key=None):\\n data = {\\n \\\"keypair\\\": {\\n \\\"name\\\": name\\n }\\n }\\n if public_key is not None:\\n data['keypair']['public_key'] = public_key\\n \\n path = '/os-keypairs'\\n res = self.client.call(path, 'POST', data=json.dumps(data), \\n token=self.manager.identity.token)\\n self.logger.debug('Create/import openstack keypair: %s' % truncate(res))\\n return res[0]['keypair']\",\n \"def s3_create_bucket(self):\\n self.conn.create_bucket(DEFAULT_BUCKET_NAME)\",\n \"def create_key(key_name, save_path, region=None, key=None, keyid=None, profile=None):\\n conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile)\\n\\n try:\\n key = conn.create_key_pair(key_name)\\n log.debug(\\\"the key to return is : %s\\\", key)\\n key.save(save_path)\\n return key.material\\n except boto.exception.BotoServerError as e:\\n log.debug(e)\\n return False\",\n \"def create_user(self):\\n # TODO-ROB: This is used ONLY when the user registers in flask\\n # TODO-ROB: Create the cookiecutter.json file\\n # extra_context overrides user and default configs\\n cookiecutter(self.user_cookie, no_input=True, extra_context={\\\"user_name\\\": self.user}, output_dir=self.users)\",\n \"def create_new_credential(account,userName,password):\\n new_credential = Credentials(account,userName,password)\\n return new_credential\",\n \"def create_tags(resource_id, key, value):\\n response = EC2.create_tags(\\n Resources=[\\n resource_id,\\n ],\\n Tags=[\\n {\\n 'Key': key,\\n 'Value': value\\n },\\n ]\\n )\\n return response\",\n \"async def add_secret(app: Sanic, secret: str, passphrase: str, ttl: Optional[int]) -> str:\\n\\n key = get_fernet_key(app, passphrase)\\n\\n sign = hmac.digest(key=key, msg=passphrase.encode(), digest='sha512').hex()\\n secret_key = secrets.token_hex(16)\\n\\n cipher = fernet.Fernet(key)\\n encrypted = cipher.encrypt(secret.encode()).decode()\\n\\n expires = None\\n if ttl:\\n expires = datetime.utcnow() + timedelta(seconds=ttl)\\n\\n await app.db.secrets.insert_one({\\n 'secret': encrypted,\\n 'secret_key': secret_key,\\n 'signature': sign,\\n 'expires': expires, # for mongo index\\n 'ttl': ttl, # for fernet check\\n })\\n\\n return secret_key\",\n \"def add_user():\\n if not request.json:\\n abort(400)\\n\\n db_conn = sqlite3.connect(db_path)\\n db = db_conn.cursor()\\n\\n username = request.json['username']\\n public_key = request.json['public_key']\\n\\n try:\\n db.execute(\\\"INSERT INTO users (username) VALUES (?)\\\", [username])\\n db.execute(\\\"INSERT INTO public_keys (username, public_key, status) VALUES (?,?,?)\\\", [username, public_key, PK_STATUS_OK])\\n db_conn.commit()\\n db_conn.close()\\n except sqlite3.IntegrityError:\\n db_conn.close()\\n abort(400)\\n return jsonify({'success':True})\",\n \"def new_user(client, username, password, apikey=None, docs=None):\\n if apikey is None:\\n apikey = str(uuid.uuid4())\\n passhash = generate_password_hash(password, method='sha1')\\n user = User(username, passhash, apikey, docs=docs)\\n user.create(client)\\n return user\",\n \"def create_profile(self, user):\\n salt = sha.new(str(random.random())).hexdigest()[:5]\\n activation_key = sha.new(salt+user.username).hexdigest()\\n# prepend \\\"key_\\\" to the key_name, because key_names can't start with numbers\\n registrationprofile = RegistrationProfile(user=user, activation_key=activation_key)\\n db = DB_Session()\\n db.add(registrationprofile)\\n db.flush()\\n db.refresh(registrationprofile)\\n db.commit()\\n db.close()\\n return registrationprofile\",\n \"def generate_key(self):\\n self.key = Fernet.generate_key()\\n with open(\\\"secret.key\\\", \\\"wb\\\") as key_file:\\n key_file.write(self.key)\",\n \"def process_create_dropbox_client_account ( iam_conn, base_name, action_params ) :\\n account_name = create_dropbox_client_name( base_name, action_params[ 'name' ] )\\n if does_user_exist( iam_conn, account_name ) :\\n print 'AWS account ' + account_name + ' already exists. Skipping.'\\n return None\\n\\n print \\\"Creating AWS account \\\" + account_name\\n iam_conn.create_user( account_name )\\n\\n if action_params.get( 'generate-access-key', 'NO' ) == 'YES' :\\n print \\\"Generating access key\\\"\\n response = iam_conn.create_access_key( account_name )\\n access_key = response[ 'create_access_key_response' ][ 'create_access_key_result' ][ 'access_key' ][ 'access_key_id' ]\\n access_key_secret = response[ 'create_access_key_response' ][ 'create_access_key_result' ][ 'access_key' ][ 'secret_access_key' ]\\n\\n ## FIX: Need to store these with the credentials service at some point.\\n key_filename = account_name + '.accesskey.txt'\\n print 'Saving access key to file ' + key_filename\\n key_file = open( key_filename, 'w' )\\n key_file.write( 'Access Key: ' + access_key + '\\\\n' )\\n key_file.write( 'Access Key Secret: ' + access_key_secret )\\n key_file.close( )\\n print '** WARNING: The access key MUST be registered manually with the credential service before it can be used.'\",\n \"def create( cls, user_id = None, private_keyfile_path = None ) :\\n user_id = user_id or config.USER_ID()\\n private_keyfile_path = private_keyfile_path or PRIVATE_RSA_KEYFILE_PATH()\\n with open( private_keyfile_path, \\\"r\\\" ) as stream :\\n private_key = rsa.PrivateKey.load_pkcs1( stream.read() )\\n return cls( user_id, private_key )\",\n \"def token_generate(self, user_id):\\n try:\\n payload = {\\n 'exp': datetime.utcnow() + timedelta(minutes=200),\\n 'iat': datetime.utcnow(),\\n 'sub': user_id\\n }\\n encoded_token = jwt.encode(\\n payload, current_app.config['SECRET_KEY'], algorithm='HS256'\\n )\\n return encoded_token\\n\\n except Exception:\\n return str(Exception)\",\n \"def put_slice_secret( observer_pkey_pem, slice_name, slice_secret, slice_fk=None, opencloud_slice=None ):\\n \\n ss = None \\n \\n if opencloud_slice is None:\\n # look up the slice \\n try:\\n if slice_fk is None:\\n opencloud_slice = models.Slice.objects.get( name=slice_name )\\n else:\\n opencloud_slice = models.Slice.objects.get( id=slice_fk.id )\\n except Exception, e:\\n logger.exception(e)\\n logger.error(\\\"Failed to load slice (%s, %s)\\\" % (slice_fk, slice_name) )\\n return False \\n \\n ss = models.SliceSecret( slice_id=opencloud_slice, secret=slice_secret )\\n \\n ss.save()\\n \\n return True\",\n \"def create_secrets(file):\\n with open(file, 'w') as secfile:\\n secfile.write((\\n '# _credentials: Maintain your credentials below. Do not remove unused fields.\\\\n'\\n 'USER = \\\\'\\\\'\\\\nPASSWORD = \\\\'\\\\'\\\\n# _courses: Define which courses should be crawled\\\\nCOURSES = []\\\\n\\\\n'\\n '# local: Required if you want to download files and store them in a local folder'\\n ' (for example in the Dropbox client folder)\\\\n'\\n 'PATH = \\\\'\\\\' # Path to the destination folder\\\\n\\\\n'\\n '# dropbox (-d): Required if you want to download files and upload them to Dropbox\\\\n'\\n 'DROPBOX_TOKEN = \\\\'\\\\' # Personal Dropbox API token\\\\n'\\n 'PATH_IN_DB = \\\\'\\\\' # Destination path of downloaded files within Dropbox\\\\n'))\\n print('File app_secrets.py was created. Please maintain your credentials.')\\n sys.exit(1)\",\n \"def create_token(request, user):\\n\\n key = get_random_string(100)\\n data = {}\\n ip = get_client_ip_address(request)\\n\\n return Token.objects.create(user=user, key=key, data=json.dumps(data), ip=ip)\",\n \"def createSaltKey(operation,newPassword,newPasswordTag):\\n \\n newPasswordEncrypted=encrypt(GlobalSaltKeyValue,newPassword)\\n \\n if os.path.isfile(GlobalKeyVaultFile):\\n if checkTag(GlobalKeyVaultFileSection,newPasswordTag):\\n if operation == 'update':\\n addUpdateTag(newPasswordTag, newPasswordEncrypted)\\n print \\\"Success-Password updated\\\"\\n else:\\n print \\\"Error:0001-Section and password tag already exists.\\\"\\n sys.exit(2)\\n\\n else:\\n if operation == 'add': \\n addUpdateTag(newPasswordTag, newPasswordEncrypted)\\n print \\\"Success-Password added\\\"\\n else:\\n print \\\"Error:0002-No matching tag found.\\\"\\n sys.exit(2)\\n else:\\n print \\\"Error:0003-Missing file \\\", GlobalKeyVaultFile\\n sys.exit(2)\",\n \"def secret_cognito_hash(\\n username: str,\\n cognito_client_id: str,\\n cognito_secret: str\\n) -> str:\\n message = bytes(username + cognito_client_id, encoding='utf-8')\\n key = bytes(cognito_secret, encoding='utf-8')\\n\\n secret_hash = base64.b64encode(\\n hmac.new(\\n key=key,\\n msg=message,\\n digestmod=hashlib.sha256\\n ).digest()\\n ).decode()\\n\\n return secret_hash\",\n \"def create_new_user():\\n username = input('Vad är ditt användarID?: ')\\n filename = 'user_db.json'\\n \\n with open(f'txt_files/{filename}', 'w') as f:\\n json.dump(username, f)\\n return username\",\n \"def _generateSSHKey(self, private_filepath, public_filepath):\\n self.log.debug(\\\"Writing SSH keys to: \\\" + private_filepath + \\\" and \\\" + public_filepath)\\n\\n (ssh_dir, filename) = os.path.split(os.path.expanduser(private_filepath))\\n if not os.path.exists(ssh_dir):\\n self.log.debug(\\\"SSH Directory doesn't exist, creating \\\" + ssh_dir)\\n os.makedirs(ssh_dir)\\n\\n key = paramiko.RSAKey.generate(1024)\\n key.write_private_key_file(os.path.expanduser(private_filepath))\\n \\n with open(os.path.expanduser(public_filepath),\\\"w\\\") as public:\\n public.write(\\\"%s %s\\\" % (key.get_name(), key.get_base64()))\\n\\n public.close()\",\n \"def create_sample_tag(user, name=\\\"spicy\\\"):\\n return Tag.objects.create(custom_user=user, name=name)\",\n \"def create_user_credentials(storage_type, storage_id, space_name, client_ip,\\n user_details):\\n user_id = user_details[\\\"id\\\"]\\n if user_id == \\\"0\\\":\\n return PosixCredentials(0, 0)\\n\\n uid = gid = gen_storage_id(user_id)\\n return PosixCredentials(uid, gid)\",\n \"async def write_secret(self, name: str, value: str, content_type: str, tags: dict):\\n pass\",\n \"def create_temp_user(client, role_arn):\\n try:\\n response = client.assume_role(\\n RoleArn=role_arn,\\n RoleSessionName=\\\"Lambda-Start-Stop-functionality\\\"\\n )\\n ec2_user = boto3.client(\\n 'ec2',\\n aws_access_key_id=response['Credentials']['AccessKeyId'],\\n aws_secret_access_key=response['Credentials']['SecretAccessKey'],\\n aws_session_token=response['Credentials']['SessionToken']\\n )\\n return ec2_user\\n except Exception as error:\\n logger.info(\\\"Creating a temporary ec2 privileged user failed with the following error : {}\\\".format(error))\",\n \"def create_sample_recipe(user, **params):\\n\\n defaults = {\\n 'title': 'Polish Soup',\\n 'time_minutes': 45,\\n 'price': 15.89\\n }\\n defaults.update(params)\\n return Recipe.objects.create(user=user, **defaults)\",\n \"async def create_wallet(self, user_id: str) -> None:\\n self._wallet_id = self.generate_wallet_id()\\n\\n transaction = Transaction(\\n wallet_id=self.wallet_id,\\n type=TransactionType.CREATE,\\n data={\\\"amount\\\": self.DEFAULT_BALANCE},\\n nonce=None,\\n )\\n\\n # todo: create separate user storage\\n user_pk = f\\\"{user_id}{self.USER_KEY_POSTFIX}\\\"\\n\\n try:\\n await self.storage.transaction_write_items(\\n items=[\\n # create transaction record\\n self.storage.item_factory.put_idempotency_item(\\n pk=transaction.unique_id, data=transaction.as_dict()\\n ),\\n # create wallet\\n self.storage.item_factory.put_idempotency_item(\\n pk=self.unique_id,\\n data={self.BALANCE_KEY: self.DEFAULT_BALANCE},\\n ),\\n # create link between wallet and user\\n self.storage.item_factory.put_idempotency_item(\\n pk=user_pk, data={self.USER_WALLET_KEY: self.wallet_id}\\n ),\\n ]\\n )\\n except storage.exceptions.TransactionMultipleError as e:\\n if e.errors[0]:\\n raise crud.exceptions.WalletTransactionAlreadyRegisteredError(\\n str(e.errors[0])\\n )\\n\\n raise crud.exceptions.WalletAlreadyExistsError(\\n f\\\"Wallet already exists for the user {user_pk}\\\"\\n )\"\n]"},"negative_scores":{"kind":"list like","value":["0.6538113","0.6313658","0.6207733","0.61237496","0.60848606","0.6013739","0.6008015","0.58083314","0.5791427","0.56150365","0.5601213","0.55981004","0.5564056","0.55623674","0.5552964","0.5467448","0.54615223","0.545093","0.5446797","0.5376637","0.5359139","0.5348455","0.5324149","0.53158396","0.531524","0.531401","0.5294298","0.5270801","0.5247391","0.5245174","0.52391446","0.52151966","0.5178087","0.5155728","0.51480955","0.5146912","0.51419073","0.51297593","0.5124745","0.5085309","0.50827247","0.50765675","0.5072045","0.5070251","0.5054839","0.5052295","0.50494564","0.50442725","0.50433695","0.50367606","0.50289196","0.50233203","0.5017201","0.5014731","0.50039005","0.50012356","0.4997671","0.49934122","0.49903914","0.4976262","0.4971201","0.49581695","0.49501428","0.49378198","0.49354157","0.49342546","0.49251273","0.4916669","0.49146828","0.4909562","0.49087533","0.49032003","0.48913097","0.4890683","0.48904285","0.4873788","0.48715183","0.48630196","0.48625377","0.48491824","0.48441297","0.48270258","0.48240247","0.48173767","0.48119023","0.48051327","0.48039898","0.48018038","0.4801658","0.47962716","0.4795972","0.47934136","0.4792127","0.47832453","0.47824788","0.4780954","0.4780568","0.47803503","0.47779685","0.47737724"],"string":"[\n \"0.6538113\",\n \"0.6313658\",\n \"0.6207733\",\n \"0.61237496\",\n \"0.60848606\",\n \"0.6013739\",\n \"0.6008015\",\n \"0.58083314\",\n \"0.5791427\",\n \"0.56150365\",\n \"0.5601213\",\n \"0.55981004\",\n \"0.5564056\",\n \"0.55623674\",\n \"0.5552964\",\n \"0.5467448\",\n \"0.54615223\",\n \"0.545093\",\n \"0.5446797\",\n \"0.5376637\",\n \"0.5359139\",\n \"0.5348455\",\n \"0.5324149\",\n \"0.53158396\",\n \"0.531524\",\n \"0.531401\",\n \"0.5294298\",\n \"0.5270801\",\n \"0.5247391\",\n \"0.5245174\",\n \"0.52391446\",\n \"0.52151966\",\n \"0.5178087\",\n \"0.5155728\",\n \"0.51480955\",\n \"0.5146912\",\n \"0.51419073\",\n \"0.51297593\",\n \"0.5124745\",\n \"0.5085309\",\n \"0.50827247\",\n \"0.50765675\",\n \"0.5072045\",\n \"0.5070251\",\n \"0.5054839\",\n \"0.5052295\",\n \"0.50494564\",\n \"0.50442725\",\n \"0.50433695\",\n \"0.50367606\",\n \"0.50289196\",\n \"0.50233203\",\n \"0.5017201\",\n \"0.5014731\",\n \"0.50039005\",\n \"0.50012356\",\n \"0.4997671\",\n \"0.49934122\",\n \"0.49903914\",\n \"0.4976262\",\n \"0.4971201\",\n \"0.49581695\",\n \"0.49501428\",\n \"0.49378198\",\n \"0.49354157\",\n \"0.49342546\",\n \"0.49251273\",\n \"0.4916669\",\n \"0.49146828\",\n \"0.4909562\",\n \"0.49087533\",\n \"0.49032003\",\n \"0.48913097\",\n \"0.4890683\",\n \"0.48904285\",\n \"0.4873788\",\n \"0.48715183\",\n \"0.48630196\",\n \"0.48625377\",\n \"0.48491824\",\n \"0.48441297\",\n \"0.48270258\",\n \"0.48240247\",\n \"0.48173767\",\n \"0.48119023\",\n \"0.48051327\",\n \"0.48039898\",\n \"0.48018038\",\n \"0.4801658\",\n \"0.47962716\",\n \"0.4795972\",\n \"0.47934136\",\n \"0.4792127\",\n \"0.47832453\",\n \"0.47824788\",\n \"0.4780954\",\n \"0.4780568\",\n \"0.47803503\",\n \"0.47779685\",\n \"0.47737724\"\n]"},"document_score":{"kind":"string","value":"0.62441874"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":8574,"cells":{"query":{"kind":"string","value":"Creates a new dynamic group in your tenancy. You must specify your tenancy's OCID as the compartment ID in the request object (remember that the tenancy is simply the root compartment). Notice that IAM resources (users, groups, compartments, and some policies) reside within the tenancy itself, unlike cloud resources such as compute instances, which typically reside within compartments inside the tenancy. For information about OCIDs, see `Resource Identifiers`__. You must also specify a name for the dynamic group, which must be unique across all dynamic groups in your tenancy, and cannot be changed. Note that this name has to be also unique across all groups in your tenancy. You can use this name or the OCID when writing policies that apply to the dynamic group. For more information about policies, see `How Policies Work`__. You must also specify a description for the dynamic group (although it can be an empty string). It does not"},"document":{"kind":"string","value":"def create_dynamic_group(self, create_dynamic_group_details, **kwargs):\n resource_path = \"/dynamicGroups\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_dynamic_group got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_dynamic_group_details,\n response_type=\"DynamicGroup\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_dynamic_group_details,\n response_type=\"DynamicGroup\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_group():\n groupname = request.get_json().get(\"name\")\n description = request.get_json().get(\"description\")\n grp = admin.create_group(current_app.scoped_session(), groupname, description)\n if grp:\n response = admin.get_group_info(current_app.scoped_session(), groupname)\n else:\n response = {\"result\": \"group creation failed\"}\n response = jsonify(response)\n return response","def create_group(group_id, group_name):\n\n kwargs = config.DEFAULT_REST_KWARGS\n kwargs[\"data\"] = {\"id\": group_id, \"name\": group_name}\n http_response = call_rest_api(\"/identities/groups/\", \"post\", **kwargs)\n if http_response.status_code != 201: # 201 = 'new group created'\n raise ValueError(http_response.text)\n logger.log(f\"New custom group, {group_name}, with ID: {group_id}, was created successfully.\")","def product_group_create(obj, name, department):\n client = get_client(obj)\n\n with Action('Creating product_group: {}'.format(name), nl=True):\n pg = client.product_group_create(name, department)\n\n print(json.dumps(pg, indent=4))","def create_group(self, groupname):\n data = {\"groupname\": groupname}\n headers = {\"user-agent\": self.u_agent}\n req_url = self.normalize_admin_url(\"groups\")\n res = requests.post(\n req_url,\n headers=headers,\n auth=self.auth,\n data=json.dumps(data),\n verify=False,\n )\n if res.status_code == 201:\n return Response(0, u\"Group {} has been created\".format(groupname))\n else:\n return Response(res.status_code, res)","def create_group(self, **kwargs):\n post_body = json.dumps({'group': kwargs})\n resp, body = self.post('groups', post_body)\n self.expected_success(201, resp.status)\n body = json.loads(body)\n return rest_client.ResponseBody(resp, body)","def create_namespaced_group(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_group\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_group`\")\n\n resource_path = '/oapi/v1/groups'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Group',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def create_group(self, group_name, group_type):\n grp_data = {\"name\": group_name, \"type\": group_type}\n return requests.post(self.groups_url, data=json.dumps(grp_data),\n headers=self.headers)","def create_TestGroup(test_case, # type: AnyMagpieTestCaseType\n override_group_name=null, # type: Optional[Str]\n override_discoverable=null, # type: Optional[bool]\n override_data=null, # type: Optional[JSON]\n override_headers=null, # type: Optional[HeadersType]\n override_cookies=null, # type: Optional[CookiesType]\n ): # type: (...) -> JSON\n app_or_url = get_app_or_url(test_case)\n data = override_data\n if override_data is null:\n data = {\"group_name\": override_group_name if override_group_name is not null else test_case.test_group_name}\n # only add 'discoverable' if explicitly provided here to preserve original behaviour of 'no value provided'\n if override_discoverable is not null:\n data[\"discoverable\"] = override_discoverable\n grp_name = (data or {}).get(\"group_name\")\n if grp_name:\n test_case.extra_group_names.add(grp_name) # indicate potential removal at a later point\n resp = test_request(app_or_url, \"POST\", \"/groups\", json=data,\n headers=override_headers if override_headers is not null else test_case.json_headers,\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\n return check_response_basic_info(resp, 201, expected_method=\"POST\")","def __create_new_group(self, group_name) -> None:\n group = Group(name=group_name)\n group.save()\n\n self.__add_permission_to_group(group)","def create_group(self, name):\n\t\tdata = {\"name\":name}\n\t\tresponse = self.client.post(self._endpoint + \"/group\", content=data)\n\t\treturn Group(\n\t\t\tresponse.json['group_id'],\n\t\t\tself.user_id,\n\t\t\tself.site_id,\n\t\t\tdata=response.json\n\t\t)","def create_placement_group(self, name, strategy='cluster'):\r\n params = {'GroupName':name, 'Strategy':strategy}\r\n group = self.get_status('CreatePlacementGroup', params, verb='POST')\r\n return group","def create_group(self, event):\n body = event['body']\n body = json.loads(body)\n\n # Required field in POST body\n if 'group_name' not in body:\n return self.get_bad_request('POST body missing group_name')\n\n group_name = body['group_name']\n user = self.mealShareUsers.get_user_cognito_data(event)\n user_id = user['user_id']\n \n # Add the creator to the group, as the initial member\n group_id = self.mealShareGroups.create_group(group_name)\n success = self.mealShareGroups.add_user_to_group(user_id, group_id)\n if success:\n return {\n 'statusCode': 200,\n 'statusMessage': 'Successfully created group {} with ID {}'.format(group_name, group_id),\n 'group_id': group_id,\n 'group_name': group_name,\n 'user_id': user_id\n }\n else:\n return {\n 'statusCode': 500,\n 'statusMessage': 'FAILED to create group {} by user {}'.format(group_name, user_id),\n 'group_id': group_id,\n 'group_name': group_name,\n 'user_id': user_id\n }","def create(self, group_name):\n METHOD = 'POST'\n API_PATH = '/groups/create'\n\n data = {'group_name': group_name}\n\n # Make REST call\n resp = self._rest_call[METHOD](API_PATH, data=data)\n if resp.status_code == 200:\n return resp.json()\n\n elif resp.status_code == 403:\n raise AuthorizationError(\"User is not authorized or token is incorrect.\")\n\n else:\n if resp.json().get(\"error_code\") in ERROR_CODES:\n raise ERROR_CODES[resp.json().get('error_code')](resp.json().get('message'))\n else:\n raise APIError(\"Response code {0}: {1} {2}\".format(resp.status_code,\n resp.json().get('error_code'),\n resp.json().get('message')))","def allocate_group(remote, objectid):\n cmd1 = mmapi.StoredCommands()\n key1 = cmd1.AppendSceneCommand_AllocateNewGroupID(objectid)\n remote.runCommand(cmd1)\n result_val = mmapi.any_result()\n cmd1.GetSceneCommandResult_AllocateNewGroupID(key1, result_val)\n return result_val.i","def add_group():\n name = request.form['name']\n data, code, message = FIELD_SERVICE.add_group(name)\n return __result(data, code, message)","def create_group(self, identifier: str, group_name: str) -> Group:\n\n # APM-137701 - Namespace for custom device calculation should not be set\n group_id = get_group_id(\"\", identifier)\n if group_id in self._groups:\n raise ValueError(\"Group \" + group_name + \" already exist, id: \" + str(group_id))\n else:\n group = Group(group_id, group_name, self._technologies, self._results_builder)\n\n self._groups[group_id] = group\n return group","def test_create_group(self):\n groupid = 'villains'\n\n # create the group\n resp = self.app.post('/groups', data=json.dumps({'name':groupid}))\n assert resp.status_code == 200\n\n # Fetch the group to check that it persists\n resp = self.app.get('/groups/{}'.format(groupid))\n assert resp.status_code == 200","def createGroup(self, name):\n new_group = ET.SubElement(self._root,'group')\n group_name = ET.SubElement(new_group, 'name')\n group_name.text = name\n # update the document's groups\n self._groups = self._root.findall('group') \n print 'Creating group, \\'%s\\'' % name\n return CAGroup(new_group)","def create_group(self, create_group_details, **kwargs):\n resource_path = \"/groups\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_group got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_group_details,\n response_type=\"Group\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_group_details,\n response_type=\"Group\")","def post_groups(\n data: PostGroupIn, tkn: Token = Depends(from_authotization_header_nondyn),\n):\n assert_has_clearance(tkn.owner, \"sni.create_group\")\n grp = Group(\n description=data.description,\n members=[tkn.owner],\n group_name=data.group_name,\n owner=tkn.owner,\n ).save()\n logging.debug(\n \"Created group %s (%s) owned by %s\",\n data.group_name,\n str(grp.pk),\n tkn.owner.character_name,\n )\n return GetGroupOut.from_record(grp)","def create_adgroup(self, account_id, name, campaign_id,\n creative_id, bid_type=None, bid_info=None, max_bid=None,\n tracking_specs=None, view_tags=None, objective=None,\n adgroup_status=None, targeting=None, conversion_specs=None, batch=False):\n path = 'act_%s/adgroups' % account_id\n args = {\n 'name': name,\n 'campaign_id': campaign_id,\n 'creative': json.dumps({'creative_id': creative_id}),\n }\n if bid_type:\n args['bid_type'] = bid_type\n if max_bid:\n # can only use max_bid with CPM bidding\n args['max_bid'] = max_bid\n elif bid_info:\n args['bid_info'] = json.dumps(bid_info)\n\n if tracking_specs:\n args['tracking_specs'] = json.dumps(tracking_specs)\n if view_tags:\n args['view_tags'] = json.dumps(view_tags)\n if objective:\n args['objective'] = objective\n if adgroup_status:\n args['adgroup_status'] = adgroup_status\n if targeting:\n args['targeting'] = json.dumps(targeting)\n if conversion_specs:\n args['conversion_specs'] = json.dumps(conversion_specs)\n return self.make_request(path, 'POST', args, batch=batch)","def autoCreateGroup(cleaned_data, cookie_user, isAutoApproved=False, querystring_content=False):\n existingSites = Site.objects.filter(\n domain=cleaned_data['domain'],\n )\n if len(existingSites) > 0:\n\n try:\n site = existingSites[0]\n group = site.group\n except Exception, e:\n raise Exception(\"Site \"+cleaned_data['domain']+\" has no group.\")\n else:\n # make a group and site\n try:\n group = Group.objects.create(\n name=cleaned_data['name'],\n short_name=cleaned_data['short_name'],\n approved=False,\n temp_interact=0,\n requires_approval=False,\n )\n except Exception, e:\n print \"* * * ** * * * * * * * EXCEPTION \"\n print e\n logger.warn(e)\n groups = Group.objects.filter(\n short_name=cleaned_data['short_name']\n )\n if len(groups) == 1:\n group = groups[0]\n elif len(groups) > 1:\n raise Exception(\"More than one group with shortname found: \" + cleaned_data['short_name'])\n else:\n raise Exception(\"No groups found with shortname: \" + cleaned_data['short_name'])\n\n site = Site.objects.create(\n name=cleaned_data['domain'],\n domain=cleaned_data['domain'],\n group=group,\n # this is whether or not a querystring is counted in the url - we should rename this\n querystring_content=querystring_content,\n )\n\n blessed_tags = addDefaultsForNewGroup(group, cookie_user)\n autoApproveUserAsAdmin(group, cookie_user, isAutoApproved=isAutoApproved)\n\n return group, site, blessed_tags","def create():\n name = request.json['name']\n level = request.json['level']\n manager = request.json['manager']\n if models.user.Group.get(name):\n raise Conflict('Group already exists.', creation=False)\n else:\n authorize(manager, level=level)\n group = models.user.Group(name=name, level=level, manager=manager)\n models.db.session.add(group)\n models.db.session.commit()\n return response(200, creation=True)","def create_ad_group(client, customer_id, campaign_resource_name):\n ad_group_service = client.get_service(\"AdGroupService\")\n\n # Creates the ad group.\n # Note that the ad group type must not be set.\n # Since the advertising_channel_sub_type is APP_CAMPAIGN,\n # 1- you cannot override bid settings at the ad group level.\n # 2- you cannot add ad group criteria.\n ad_group_operation = client.get_type(\"AdGroupOperation\")\n ad_group = ad_group_operation.create\n ad_group.name = f\"Earth to Mars cruises {uuid4()}\"\n ad_group.status = client.enums.AdGroupStatusEnum.ENABLED\n ad_group.campaign = campaign_resource_name\n\n ad_group_response = ad_group_service.mutate_ad_groups(\n customer_id=customer_id, operations=[ad_group_operation]\n )\n\n ad_group_resource_name = ad_group_response.results[0].resource_name\n print(f'Ad Group created with resource name: \"{ad_group_resource_name}\".')\n return ad_group_resource_name","def create(person_group_id, name=None, user_data=None):\n name = person_group_id if name is None else name\n url = 'persongroups/{}'.format(person_group_id)\n json = {\n 'name': name,\n 'userData': user_data,\n }\n\n return util.request('PUT', url, json=json)","def create_new_group(self, group_id, poll_id, name):\n obj = self.table()\n obj.group_id = str(group_id)\n obj.poll_id = poll_id\n obj.name = name\n self.db.session.add(obj)\n self.db.session.commit()","def createGroup(self, *group):\n if not self.rank:\n logging.info('Creating atom group {}'.format(group))\n\n if not len(group):\n for idSS in self.pargs['idSS']:\n self.lmp.command('group group{} type {}'.format(idSS, idSS))\n else:\n self.lmp.command('group ' + ('{} ' * len(group)).format(*group))","def capacitygroup_create(cmd_ctx, cpc, **options):\n cmd_ctx.execute_cmd(\n lambda: cmd_capacitygroup_create(cmd_ctx, cpc, options))","def group_add_name(org_id, data):\n if data.has_key('groupname'):\n groupname = data['groupname']\n add_group(org_id, groupname, False)","def request_group_create():\n return Response(render_template('admin/group/create-update.html',\n csrf_token=(\n get_raw_jwt() or {}).get(\"csrf\"),\n target=\"/admin/group/create\"),\n mimetype='text/html')","def _make_group(self, _rk, _group_hint):\n\n if isinstance(_group_hint, dict):\n # _group_hint is a single key/value pair\n g = _group_hint[list(_group_hint)[0]]\n\n r_type = g.get(\"type\", \"none\")\n if r_type != \"OS::Nova::ServerGroup\":\n return \"support only ServerGroup resource\"\n\n properties = g.get(\"properties\", {})\n if len(properties) == 0:\n return \"no properties\"\n\n group_name = properties.get(\"name\", None)\n if group_name is None:\n return \"no group name\"\n group_name = group_name.strip()\n\n policies = properties.get(\"policies\", [])\n if len(policies) == 0:\n return \"no policy of the group\"\n\n if len(policies) > 1:\n return \"multiple policies\"\n\n # TODO: exclude soft-affinity and soft-anti-affinity?\n\n if group_name in self.groups.keys():\n group = self.groups[group_name]\n else:\n group = Group(group_name)\n\n policy = policies[0].strip()\n if policy == \"anti-affinity\":\n group_type = \"diversity\"\n else:\n group_type = policy\n\n group.group_type = group_type\n group.factory = \"server-group\"\n group.level = \"host\"\n\n self.groups[group_name] = group\n else:\n # group hint is uuid string.\n rg = self.resource.get_group_by_uuid(_group_hint)\n if rg is None:\n return \"unknown group found while making group\"\n\n # TODO: exclude soft-affinity and soft-anti-affinity?\n\n if rg.name in self.groups.keys():\n group = self.groups[rg.name]\n else:\n group = Group(rg.name)\n\n group.group_type = rg.group_type\n group.factory = rg.factory\n group.level = \"host\"\n\n self.groups[rg.name] = group\n\n if group is not None:\n group.server_list.append(self.app_name + \":\" + _rk)\n\n return \"ok\"","def create_group_scene(self, name, group):\n data = {\n \"name\": name,\n \"group\": group,\n \"recycle\": True,\n \"type\": \"GroupScene\"\n }\n return self.bridge.bridge.post('/scenes', data)","def create(self, name, desc, tenant_id):\n data = {\"security_group\": {\"name\": name, \n \"description\": desc, \n \"tenant_id\":tenant_id}}\n\n path = '%s/security-groups' % self.ver\n res = self.client.call(path, 'POST', data=json.dumps(data), \n token=self.manager.identity.token)\n self.logger.debug('Create openstack security group: %s' % truncate(res))\n return res[0]['security_group']","def post_security_group_create(self, resource_dict):\n pass","async def async_create_group(\n hass: HomeAssistant,\n name: str,\n entity_ids: Collection[str] | None = None,\n user_defined: bool = True,\n icon: str | None = None,\n object_id: str | None = None,\n mode: bool | None = None,\n order: int | None = None,\n ) -> Group:\n group = Group.async_create_group_entity(\n hass, name, entity_ids, user_defined, icon, object_id, mode, order\n )\n\n # If called before the platform async_setup is called (test cases)\n await _async_get_component(hass).async_add_entities([group])\n return group","def new_group(request):\n return edit_group(request, None)","def createNewGroup():\n if request.method == 'POST':\n groupname = request.form['groupname1']\n internal = request.form['internal1']\n external = request.form['external1']\n userNo = request.form['usersNo1']\n if 'node1' in request.form:\n node = int(request.form['node1'])\n else:\n node = -1\n\n if int(userNo) == 0:\n if hl.createGroup(groupname, internal, external, node):\n return True\n elif int(userNo) > 0:\n if hl.createGroup(groupname, internal, external, node, genUsers=True, numUsers=int(userNo)):\n return True\n\n return False","def _assert_create_group(self, personality, response=400):\n group_response = self.autoscale_behaviors.create_scaling_group_given(\n lc_personality=personality)\n self.assertEquals(group_response.status_code, response, msg='Create group '\n 'with invalid lc_personality returned {0} as against '\n '{1}'.format(group_response.status_code, response))\n if response is 200:\n group = group_response.entity\n self.resources.add(group, self.empty_scaling_group)\n return group","def create_groups(**kwargs):\n for gname in SEC_GROUP_NAMES.itervalues():\n Group.objects.get_or_create(name=gname)","def _create_child_group(self, name) -> \"GroupBase\":\n pass","async def create_group(ctx, name: str, role: str, group_type: str=None, comp: str=None, rating: int=None, time: str=None):\n\n owner = ctx.message.author.name\n \n if comp:\n comp = [int(i) for i in comp.split()] # convert string input to array\n\n new_group = Group(owner, name, role, group_type, rating, time, comp)\n bg_bot.manager.add_group(owner, new_group)\n \n await ctx.send(f'Created new {group_type} group for leader {owner}!')","def post(self):\n status = ErrorCode.SUCCESS\n try:\n data = DotDict(json_decode(self.request.body))\n logging.info(\"[UWEB] add group request: %s, cid: %s\",\n data, self.current_user.cid)\n except Exception as e:\n status = ErrorCode.ILLEGAL_DATA_FORMAT\n logging.exception(\"[UWEB] Invalid data format. body:%s, Exception: %s\",\n self.request.body, e.args)\n self.write_ret(status)\n return\n\n try: \n cid = data.cid\n name = data.name\n group = self.get_group_by_cid(cid, name)\n if group:\n status = ErrorCode.GROUP_EXIST\n self.write_ret(status)\n return\n\n group_info = dict(cid=cid,\n name=name,\n type=UWEB.GROUP_TYPE.NEW)\n gid = add_group(group_info, self.db, self.redis)\n # NOTE: wspush to client\n tid = self.current_user.tid\n if status == ErrorCode.SUCCESS:\n WSPushHelper.pushS3(tid, self.db, self.redis)\n\n self.write_ret(status,\n dict_=dict(gid=gid,\n cid=cid,\n name=name))\n\n except Exception as e:\n logging.exception(\"[UWEB] Create group failed. uid: %s, Exception: %s\",\n self.current_user.uid, e.args)\n status = ErrorCode.SERVER_BUSY\n self.write_ret(status)","def create(self, context=None):\n values = self.obj_get_changes()\n db_nodegroup = self.dbapi.create_nodegroup(values)\n self._from_db_object(self, db_nodegroup)","def CreateGroup(self, name, alloc_policy=None, dry_run=False, reason=None):\n query = []\n _AppendDryRunIf(query, dry_run)\n _AppendReason(query, reason)\n\n body = {\n \"name\": name,\n \"alloc_policy\": alloc_policy,\n }\n\n return self._SendRequest(HTTP_POST, \"/%s/groups\" % GANETI_RAPI_VERSION,\n query, body)","def create_group(name, nodes, description=None):\n group, created = Group.get_or_create(name=name)\n if created:\n print('Group created with PK={} and name {}'.format(group.pk, group.name))\n else:\n print('Group with name {} and pk {} already exists. Do you want to add nodes?[y/n]'.format(group.name, group.pk))\n answer = raw_input()\n if answer.strip().lower() == 'y':\n pass\n else:\n return\n nodes2 = []\n nodes2_pks = []\n for node in nodes:\n try:\n node = int(node)\n except ValueError:\n pass\n nodes2_pks.append(node)\n try:\n nodes2.append(load_node(node))\n except:# NotExistentError:\n pass\n\n group.add_nodes(nodes2)\n print('added nodes: {} to group {} {}'.format(nodes2_pks, group.name, group.pk))\n\n if description:\n group.description = description\n\n return group","async def create(\n self,\n resource_group_name: str,\n project_name: str,\n group_name: str,\n group: Optional[\"models.Group\"] = None,\n **kwargs\n ) -> \"models.Group\":\n cls = kwargs.pop('cls', None) # type: ClsType[\"models.Group\"]\n error_map = {\n 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError\n }\n error_map.update(kwargs.pop('error_map', {}))\n api_version = \"2018-06-01\"\n content_type = kwargs.pop(\"content_type\", \"application/json\")\n accept = \"application/json\"\n\n # Construct URL\n url = self.create.metadata['url'] # type: ignore\n path_format_arguments = {\n 'subscriptionId': self._serialize.url(\"self._config.subscription_id\", self._config.subscription_id, 'str'),\n 'resourceGroupName': self._serialize.url(\"resource_group_name\", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\\w\\._\\(\\)]+$'),\n 'projectName': self._serialize.url(\"project_name\", project_name, 'str'),\n 'groupName': self._serialize.url(\"group_name\", group_name, 'str'),\n }\n url = self._client.format_url(url, **path_format_arguments)\n\n # Construct parameters\n query_parameters = {} # type: Dict[str, Any]\n query_parameters['api-version'] = self._serialize.query(\"api_version\", api_version, 'str')\n\n # Construct headers\n header_parameters = {} # type: Dict[str, Any]\n header_parameters['Content-Type'] = self._serialize.header(\"content_type\", content_type, 'str')\n header_parameters['Accept'] = self._serialize.header(\"accept\", accept, 'str')\n\n body_content_kwargs = {} # type: Dict[str, Any]\n if group is not None:\n body_content = self._serialize.body(group, 'Group')\n else:\n body_content = None\n body_content_kwargs['content'] = body_content\n request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs)\n pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)\n response = pipeline_response.http_response\n\n if response.status_code not in [200, 201]:\n map_error(status_code=response.status_code, response=response, error_map=error_map)\n raise HttpResponseError(response=response, error_format=ARMErrorFormat)\n\n response_headers = {}\n if response.status_code == 200:\n response_headers['x-ms-request-id']=self._deserialize('str', response.headers.get('x-ms-request-id'))\n deserialized = self._deserialize('Group', pipeline_response)\n\n if response.status_code == 201:\n response_headers['x-ms-request-id']=self._deserialize('str', response.headers.get('x-ms-request-id'))\n deserialized = self._deserialize('Group', pipeline_response)\n\n if cls:\n return cls(pipeline_response, deserialized, response_headers)\n\n return deserialized","def post(self):\n args = parser.parse_args()\n user_group = UserGroup()\n user_group.name = args['name']\n user_group.createdby = auth.username()\n db_session.add(user_group)\n db_session.commit()\n return user_group, 201","def createGroup(self):\n return _libsbml.GroupsModelPlugin_createGroup(self)","def test_createGroup(self):\n\t\tself.client.force_authenticate(user=User.objects.get(id=1))\n\t\turl = \"/groups/\"\n\t\tdata = {\n\t\t\t'name' : 'testGroup3',\n\t\t\t'description' : 'This is another test group that just created.',\n\t\t\t'isPublic' : True\n\t\t}\n\t\tresponse = self.client.post(url, data, format='json')\n\t\tself.assertEqual(response.status_code, status.HTTP_201_CREATED)\n\t\tself.assertEqual(response.data[\"id\"], 3)\n\t\tself.assertEqual(response.data[\"name\"], 'testGroup3')","def create_group(self, tenant_id, group_id):\n maas_client = self._get_maas_client()\n d = maas_client.add_notification_and_plan()\n\n def create_group_in_db((notification, notification_plan)):\n return cass.create_group(\n self._db, tenant_id, group_id, notification, notification_plan)\n d.addCallback(create_group_in_db)\n\n return d","def create_group(self, properties: dict[str, Any | None]) -> dict:\n group = self.ms_client.http_request(method='POST', url_suffix='groups', json_data=properties)\n return group","def create_group(\n self,\n name,\n group,\n validate_only=None,\n retry=google.api_core.gapic_v1.method.DEFAULT,\n timeout=google.api_core.gapic_v1.method.DEFAULT,\n metadata=None,\n ):\n if metadata is None:\n metadata = []\n metadata = list(metadata)\n # Wrap the transport method to add retry and timeout logic.\n if \"create_group\" not in self._inner_api_calls:\n self._inner_api_calls[\n \"create_group\"\n ] = google.api_core.gapic_v1.method.wrap_method(\n self.transport.create_group,\n default_retry=self._method_configs[\"CreateGroup\"].retry,\n default_timeout=self._method_configs[\"CreateGroup\"].timeout,\n client_info=self._client_info,\n )\n\n request = group_service_pb2.CreateGroupRequest(\n name=name, group=group, validate_only=validate_only,\n )\n if metadata is None:\n metadata = []\n metadata = list(metadata)\n try:\n routing_header = [(\"name\", name)]\n except AttributeError:\n pass\n else:\n routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(\n routing_header\n )\n metadata.append(routing_metadata)\n\n return self._inner_api_calls[\"create_group\"](\n request, retry=retry, timeout=timeout, metadata=metadata\n )","def create_group(self, group_name, user_ids=[], role_ids=[]):\n payload = {}\n payload['name'] = group_name\n payload['user_ids'] = user_ids\n payload['role_ids'] = role_ids\n return Client._post(self, payload)","def create_group_with_http_info(self, bucket_id, group, **kwargs):\n\n all_params = ['bucket_id', 'group', 'if_match', 'if_none_match']\n all_params.append('callback')\n all_params.append('_return_http_data_only')\n all_params.append('_preload_content')\n all_params.append('_request_timeout')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_group\" % key\n )\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'bucket_id' is set\n if ('bucket_id' not in params) or (params['bucket_id'] is None):\n raise ValueError(\"Missing the required parameter `bucket_id` when calling `create_group`\")\n # verify the required parameter 'group' is set\n if ('group' not in params) or (params['group'] is None):\n raise ValueError(\"Missing the required parameter `group` when calling `create_group`\")\n\n if 'if_match' in params and not re.search('\\\\\\\"[0-9]+\\\\\\\"', params['if_match']):\n raise ValueError(\"Invalid value for parameter `if_match` when calling `create_group`, must conform to the pattern `/\\\\\\\"[0-9]+\\\\\\\"/`\")\n if 'if_none_match' in params and not re.search('\\\\\\\"[0-9]+\\\\\\\"', params['if_none_match']):\n raise ValueError(\"Invalid value for parameter `if_none_match` when calling `create_group`, must conform to the pattern `/\\\\\\\"[0-9]+\\\\\\\"/`\")\n\n collection_formats = {}\n\n resource_path = '/buckets/{bucket_id}/groups'.replace('{format}', 'json')\n path_params = {}\n if 'bucket_id' in params:\n path_params['bucket_id'] = params['bucket_id']\n\n query_params = {}\n\n header_params = {}\n if 'if_match' in params:\n header_params['If-Match'] = params['if_match']\n if 'if_none_match' in params:\n header_params['If-None-Match'] = params['if_none_match']\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'group' in params:\n body_params = params['group']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['application/json'])\n\n # Authentication setting\n auth_settings = ['basicAuth']\n\n return self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='Group',\n auth_settings=auth_settings,\n callback=params.get('callback'),\n _return_http_data_only=params.get('_return_http_data_only'),\n _preload_content=params.get('_preload_content', True),\n _request_timeout=params.get('_request_timeout'),\n collection_formats=collection_formats)","def create(isamAppliance, id, check_mode=False, force=False):\n if force is True or _check(isamAppliance, id=id) is False:\n if check_mode is True:\n return isamAppliance.create_return_object(changed=True)\n else:\n return isamAppliance.invoke_post(\"Creating group\", \"/sysaccount/groups/v1\",\n {\n 'id': id\n })\n\n return isamAppliance.create_return_object()","def gen_group(group_name=None, group_vars={}):\n group = Group(name=group_name)\n for key, value in group_vars.iteritems():\n group.set_variable(key, value)\n return group","def create_group(self, group):\n if self.dryrun:\n self.logger.info(\"Would create group %s\", group)\n return FakeGroupId()\n result = self.conn.usergroup.create(name=group)\n groupid = result['usrgrpids'][0]\n self.logger.info(\"Create group %s with id %s\", group, groupid)\n return groupid","def create( self, trans, payload, **kwd ):\n group_dict = dict( message='', status='ok' )\n name = payload.get( 'name', '' )\n if name:\n description = payload.get( 'description', '' )\n if not description:\n description = ''\n else:\n # TODO add description field to the model\n group_dict = self.group_manager.create( trans, name=name ).to_dict( view='element', value_mapper=self.__get_value_mapper( trans ) )\n else:\n raise RequestParameterMissingException( 'Missing required parameter \"name\".' )\n return group_dict","def create_group(self):\n # TODO: Assuming first server is good - need to make fallback logic\n return self.session.get_any(\"{base}{request_url}\".format(base=self.servers[0],\n request_url=F\"/GroupV2/Create/\"))","def create_security_group(self, body=None):\r\n return self.post(self.security_groups_path, body=body)","def handle(self, *args, **options):\n new_group, created = Group.objects.get_or_create(name=options.get('group_name')) \n self.stdout.write(f\"Group {options.get('group_name')} created\")","def create_secgroup(self, args):\n message = MessageClass()\n region = args[\"Region\"]\n sgid = args[\"Group-Name\"]\n desc = args[\"Description\"]\n\n # Boto3 client creation by providing the access_id and access_secret\n ec2 = boto3.client(service_name='ec2', region_name=region, api_version=None, use_ssl=True,\n verify=None, endpoint_url=None, aws_access_key_id=self.aws_access_key,\n aws_secret_access_key=self.aws_secret_token, aws_session_token=None,\n config=None)\n response = ec2.describe_vpcs()\n vpc_id = response.get('Vpcs', [{}])[0].get('VpcId', '')\n\n response = ec2.create_security_group(GroupName=sgid,\n Description=desc,\n VpcId=vpc_id)\n attachment = MessageAttachmentsClass()\n d = response[\"GroupId\"]\n attachment.title = d\n message.message_text = \"Security group created:\"\n message.attach(attachment)\n\n return message.to_json()","def replace_namespaced_group(self, body, name, **kwargs):\n\n all_params = ['body', 'name', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method replace_namespaced_group\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `replace_namespaced_group`\")\n # verify the required parameter 'name' is set\n if ('name' not in params) or (params['name'] is None):\n raise ValueError(\"Missing the required parameter `name` when calling `replace_namespaced_group`\")\n\n resource_path = '/oapi/v1/groups/{name}'.replace('{format}', 'json')\n path_params = {}\n if 'name' in params:\n path_params['name'] = params['name']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'PUT',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Group',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def create_new_scaling_group(self, request, data):\n group_cfg = data['groupConfiguration']\n\n group_cfg.setdefault('maxEntities', MAX_ENTITIES)\n group_cfg.setdefault('metadata', {})\n\n if group_cfg['minEntities'] > group_cfg['maxEntities']:\n raise InvalidMinEntities(\n \"minEntities must be less than or equal to maxEntities\")\n\n if data['launchConfiguration']['type'] == 'launch_server':\n validate_launch_config_servicenet(data['launchConfiguration'])\n\n deferred = get_supervisor().validate_launch_config(\n self.log, self.tenant_id, data['launchConfiguration'])\n\n deferred.addCallback(\n lambda _: self.store.create_scaling_group(\n self.log, self.tenant_id,\n group_cfg,\n normalize_launch_config(data['launchConfiguration']),\n data.get('scalingPolicies', None)))\n\n def _do_obey_config_change(result):\n group_id = result['id']\n config = result['groupConfiguration']\n launch = result['launchConfiguration']\n group = self.store.get_scaling_group(\n self.log, self.tenant_id, group_id)\n log = self.log.bind(scaling_group_id=group_id)\n d = controller.modify_and_trigger(\n self.dispatcher,\n group,\n bound_log_kwargs(log),\n partial(\n controller.obey_config_change, log,\n transaction_id(request), config, launch_config=launch),\n modify_state_reason='create_new_scaling_group')\n return d.addCallback(lambda _: result)\n\n deferred.addCallback(_do_obey_config_change)\n\n def _add_to_bobby(result, client):\n d = client.create_group(self.tenant_id, result['id'])\n return d.addCallback(lambda _: result)\n\n bobby = get_bobby()\n if bobby is not None:\n deferred.addCallback(_add_to_bobby, bobby)\n\n def _format_output(result):\n uuid = result['id']\n result[\"state\"] = format_state_dict(result[\"state\"])\n request.setHeader(\n \"Location\",\n get_autoscale_links(self.tenant_id, uuid, format=None))\n result[\"links\"] = get_autoscale_links(self.tenant_id, uuid)\n linkify_policy_list(\n result['scalingPolicies'], self.tenant_id, uuid)\n result['scalingPolicies_links'] = get_policies_links(\n result['scalingPolicies'],\n self.tenant_id, uuid, rel='policies')\n return {\"group\": result}\n\n deferred.addCallback(_format_output)\n deferred.addCallback(json.dumps)\n return deferred","def make_grp(self, name='grp'):\n self.base[name] = self.get_group_array()","def create_rule_group(self: object,\n body: dict,\n cs_username: str = None # pylint: disable=W0613 # cs_username is deprecated\n ) -> dict:\n # [POST] https://assets.falcon.crowdstrike.com/support/api/swagger.html#/custom-ioa/create-rule-groupMixin0\n return process_service_request(\n calling_object=self,\n endpoints=Endpoints,\n operation_id=\"create_rule_groupMixin0\",\n body=body\n )","def create_group(user):\n if connexion.request.is_json:\n users_group = [User.from_dict(d) for d in connexion.request.get_json()]\n response = (\"success\", 201)\n if len(users_group) > 4:\n response = (\"Max number of player is 4\", 400)\n else:\n groupId = GroupStorageController.add_new_group(users_group)\n return response","def create_group():\n incoming = request.get_json()\n chatroom = Chatroom(\n name = incoming['name'],\n tag = incoming['tag'],\n )\n db.session.add(chatroom)\n db.session.commit()\n participant = Participant(\n user_id = session['user_id'],\n room_id = chatroom.room_id,\n )\n db.session.add(participant)\n db.session.commit()\n return jsonify(results = chatroom.room_id)","def creategroup(body):\n group = body.get(\"groupname\", None)\n pps = body.get(\"pilotpoints\", None)\n print('lol',group, pps)\n print(type(pps))\n\n # Does the person exist already?\n if group not in group_dict and group is not None:\n group_dict[group] = {\n \"groupname\": group,\n \"pilotpoints\": pps,\n }\n return group_dict[group], 201\n\n # Otherwise, they exist, that's an error\n else:\n abort(\n 406,\n \"Person with last name {group} already exists\".format(group=group),\n )","def groups_create(self, mar, request):\n if not permissions.CanCreateGroup(mar.perms):\n raise permissions.PermissionException(\n 'The user is not allowed to create groups.')\n\n user_dict = self._services.user.LookupExistingUserIDs(\n mar.cnxn, [request.groupName])\n if request.groupName.lower() in user_dict:\n raise exceptions.GroupExistsException(\n 'group %s already exists' % request.groupName)\n\n if request.ext_group_type:\n ext_group_type = str(request.ext_group_type).lower()\n else:\n ext_group_type = None\n group_id = self._services.usergroup.CreateGroup(\n mar.cnxn, self._services, request.groupName,\n str(request.who_can_view_members).lower(),\n ext_group_type)\n\n return api_pb2_v1.GroupsCreateResponse(\n groupID=group_id)","def newgroup(self, groupname, groupou=None, grouptype=None,\n description=None, mailaddress=None, notes=None, sd=None,\n gidnumber=None, nisdomain=None):\n\n group_dn = \"CN=%s,%s,%s\" % (groupname, (groupou or \"CN=Users\"), self.domain_dn())\n\n # The new user record. Note the reliance on the SAMLDB module which\n # fills in the default informations\n ldbmessage = {\"dn\": group_dn,\n \"sAMAccountName\": groupname,\n \"objectClass\": \"group\"}\n\n if grouptype is not None:\n ldbmessage[\"groupType\"] = normalise_int32(grouptype)\n\n if description is not None:\n ldbmessage[\"description\"] = description\n\n if mailaddress is not None:\n ldbmessage[\"mail\"] = mailaddress\n\n if notes is not None:\n ldbmessage[\"info\"] = notes\n\n if gidnumber is not None:\n ldbmessage[\"gidNumber\"] = normalise_int32(gidnumber)\n\n if nisdomain is not None:\n ldbmessage[\"msSFU30Name\"] = groupname\n ldbmessage[\"msSFU30NisDomain\"] = nisdomain\n\n if sd is not None:\n ldbmessage[\"nTSecurityDescriptor\"] = ndr_pack(sd)\n\n self.add(ldbmessage)","def create(self, body: CloudSecurityGroup) -> Dict:\n\t\treturn self._post(route=AWSSecurityGroupConsts.CLOUD_SECURITY_GROUP.value, body=body)","def create_new_group(self, a, b):\n self.groups[self.group_id] = set([a,b])\n self.node_id[a] = self.node_id[b] = self.group_id\n self.group_id += 1","def post(self):\n args = platform_group_arguments.parse_args()\n\n platform_group = PlatformGroup(**args)\n self.session.add(platform_group)\n self.session.commit()\n\n return platform_group","def test_create_group(self):\n pass","def test_create_group(self):\n pass","def create_group(self, groupname, filters=[], filter_options=[], **kwargs):\n pytan.utils.check_for_help(kwargs=kwargs)\n clean_kwargs = pytan.utils.clean_kwargs(kwargs=kwargs)\n\n filter_defs = pytan.utils.dehumanize_question_filters(question_filters=filters)\n option_defs = pytan.utils.dehumanize_question_options(question_options=filter_options)\n\n h = (\n \"Issue a GetObject to get the full object of specified sensors for inclusion in a \"\n \"group\"\n )\n filter_defs = self._get_sensor_defs(defs=filter_defs, pytan_help=h, **clean_kwargs)\n\n add_group_obj = pytan.utils.build_group_obj(\n q_filter_defs=filter_defs, q_option_defs=option_defs,\n )\n add_group_obj.name = groupname\n\n h = \"Issue an AddObject to add a Group object\"\n group_obj = self._add(obj=add_group_obj, pytan_help=h, **clean_kwargs)\n\n m = \"New group {!r} created with ID {!r}, filter text: {!r}\".format\n self.mylog.info(m(group_obj.name, group_obj.id, group_obj.text))\n return group_obj","def make_custom_group(self, qid, name='', path='', attrs={}):\n gslash = \"/\"\n parent = self\n sdef, name, path = self.file.get_custom_node_info(qid, gslash, name, path, parent) \n grp = Group(self.file, sdef, name, path, attrs, parent)\n return grp","async def command_create(self, context):\n # await self._create_new_role(context, name, target=GROUP_CATEGORY_NAME)\n print('main create')","def create_sec_group(ec2, sec_group_name):\n sec = ec2.create_security_group(sec_group_name, 'Jvivian Boto SecGroup')\n port = 22\n sec.authorize('tcp', port, port, '0.0.0.0/0')","def placement_group(template, name):\n p = PlacementGroup(name, template=template)\n p.Strategy = 'cluster'\n return p","def security_group_create(auth=None, **kwargs):\n cloud = get_operator_cloud(auth)\n kwargs = _clean_kwargs(keep_name=True, **kwargs)\n return cloud.create_security_group(**kwargs)","def __create_group(self):\n\n group = time.strftime(_GROUP_NAME_FORMAT, time.localtime())\n LOG.info(\"Creating backup group '%s'.\", group)\n\n group_path = self.group_path(group)\n\n try:\n os.mkdir(group_path)\n except EnvironmentError as e:\n if e.errno != errno.EEXIST:\n raise Error(\"Unable to create a new backup group '{}': {}.\",\n group_path, psys.e(e))\n\n self.__on_group_created(group)\n\n return group","def create_app_policy_group(self, name, **kwargs):\n post_body = {'application_policy_group': {'name': name}}\n if kwargs.get('description'):\n post_body['description'] = kwargs.get('description')\n post_body = json.dumps(post_body)\n resp, body = self.post(self.get_uri(self.resource), post_body)\n body = json.loads(body)\n self.expected_success(http_client.CREATED, resp.status)\n return rest_client.ResponseBody(resp, body)","def add_group_to_json(args):\n\n sanitised_group = args.group.replace('/', '-')\n new_group = {\n \"name\": sanitised_group,\n \"propogate_permissions\": False,\n \"allowed_attributes\": [\n\t\t\t{\n \t\"attribute_requirements\": {}, \n \"permissions\": \"l\"\n }\n\t\t],\n \"buckets\": []\n }\n\n try:\n with open(args.file, \"r\") as f:\n config = json.load(f)\n except FileNotFoundError:\n print(\"Error: could not find given auth JSON file\")\n return 1\n\n config[\"groups\"].append(new_group)\n\n with open(args.file, \"w\") as f:\n json.dump(config, f, indent=4)\n\n return 0","def create_sg(vpc_id, description, group_name):\n client = boto3.client('ec2')\n security_group = str(group_name + \"_sg\")\n\n # get the security groups\n idle_sg = get_sg()\n\n print(idle_sg)\n print(security_group)\n\n # if security group doesnt exist, create it\n if security_group not in idle_sg:\n print(\"Creating SG\")\n return client.create_security_group(\n Description=description,\n GroupName=security_group,\n VpcId=vpc_id\n )\n return get_sg_id(security_group)","def create_subgroup_global(request_ctx, id, title, description=None, vendor_guid=None, **request_kwargs):\n\n path = '/v1/global/outcome_groups/{id}/subgroups'\n payload = {\n 'title' : title,\n 'description' : description,\n 'vendor_guid' : vendor_guid,\n }\n url = request_ctx.base_api_url + path.format(id=id)\n response = client.post(request_ctx, url, payload=payload, **request_kwargs)\n\n return response","def create_group_command(client: MsGraphClient, args: dict) -> tuple[str, dict, dict]:\n required_properties = {\n 'displayName': str(args.get('display_name')),\n 'mailNickname': str(args.get('mail_nickname')),\n 'mailEnabled': args.get('mail_enabled') == 'true',\n 'securityEnabled': args.get('security_enabled')\n }\n\n # create the group\n group = client.create_group(required_properties)\n\n # display the new group and it's properties\n group_readable, group_outputs = parse_outputs(group)\n human_readable = tableToMarkdown(name=f\"{required_properties['displayName']} was created successfully:\",\n t=group_readable,\n headers=['ID', 'Display Name', 'Description', 'Created Date Time', 'Mail',\n 'Security Enabled', 'Mail Enabled'],\n removeNull=True)\n entry_context = {f'{INTEGRATION_CONTEXT_NAME}(val.ID === obj.ID)': group_outputs}\n return human_readable, entry_context, group","async def create_contact_group(dbcon: DBConnection, name: str, active: bool) -> str:\n q = \"\"\"insert into contact_groups (name, active) values (%s, %s)\"\"\"\n q_args = (name, active)\n contact_group_id = await dbcon.operation(q, q_args)\n return contact_group_id","def test_create_group_409(self):\n request = {\n 'name': self.test_group1_groupid\n }\n # First create a group indirectly by making a user with a group\n resp = self.app.post('/users', data=json.dumps(self.test_user1_data))\n assert resp.status_code == 200\n\n # Now create a group that is already there\n resp = self.app.post('/groups', data=json.dumps(request))\n assert resp.status_code == 409","def createGroup(self):\n return _libsbml.ListOfGroups_createGroup(self)","def make_custom_group(self, qid, name='', path='', attrs={}):\n gslash = \"/\"\n sdef, name, path = self.get_custom_node_info(qid, gslash, name, path) \n parent = None # no parent since this node created from File object (top level)\n grp = Group(self, sdef, name, path, attrs, parent)\n return grp","def make_group(self, qid, name='', path='', attrs={}, link='', abort=True):\n gqid = qid + \"/\"\n sdef = self.get_sdef(gqid, self.default_ns, \"referenced in make_group\")\n id = sdef['id']\n ns = sdef['ns']\n path = self.deduce_path(id, ns, path)\n if not abort:\n id_noslash = id.rstrip('/') # could be different from gqid if namespace present\n grp = self.get_existing_group(path, id_noslash, name)\n if grp:\n # found already existing group\n return grp \n link_info = self.extract_link_info(name, link, Group)\n # create the group\n parent = None # no parent since this node created from File object (top level)\n grp = Group(self, sdef, name, path, attrs, parent, link_info)\n return grp","def post(self, request, *args, **kwargs):\n\n task_log, fund_source = get_task_log_and_fund_source(kwargs['workspace_id'])\n\n async_create_expense_groups(kwargs['workspace_id'], fund_source, task_log)\n\n return Response(status=status.HTTP_200_OK)","def add_group(self,groupname):\n\n if not self.check_prereqs():\n raise StopIteration\n\n db = self.env.get_db_cnx()\n cursor = db.cursor()\n\n query=self.create_query(self.sql_add_group_query,{'groupname':groupname,'groupname_field':self.sql_groupname_field})\n self.log.debug(\"sqlflexibleauthstore: add_group: %s\" % (query,))\n\n cursor.execute(query)\n if cursor.rowcount > 0:\n db.commit()\n return True\n return False","def create_test_portgroup(**kw):\n portgroup = get_test_portgroup(**kw)\n # Let DB generate ID if it isn't specified explicitly\n if 'id' not in kw:\n del portgroup['id']\n dbapi = db_api.get_instance()\n return dbapi.create_portgroup(portgroup)","def async_create_group_entity(\n hass: HomeAssistant,\n name: str,\n entity_ids: Collection[str] | None = None,\n user_defined: bool = True,\n icon: str | None = None,\n object_id: str | None = None,\n mode: bool | None = None,\n order: int | None = None,\n ) -> Group:\n if order is None:\n hass.data.setdefault(GROUP_ORDER, 0)\n order = hass.data[GROUP_ORDER]\n # Keep track of the group order without iterating\n # every state in the state machine every time\n # we setup a new group\n hass.data[GROUP_ORDER] += 1\n\n group = Group(\n hass,\n name,\n order=order,\n icon=icon,\n user_defined=user_defined,\n entity_ids=entity_ids,\n mode=mode,\n )\n\n group.entity_id = async_generate_entity_id(\n ENTITY_ID_FORMAT, object_id or name, hass=hass\n )\n\n return group","def create_group(self, name) -> \"GroupBase\":\n ancestor, group_names, last_name = self._descend(name)\n parent = ancestor._require_descendant_groups(*group_names)\n if last_name in parent:\n raise FileExistsError(f\"Group or dataset found at '{name}'\")\n return parent._create_child_group(last_name)","def create_dataset(request: CreateDatasetRequest) -> CreateDatasetResponse:\n assert isinstance(request, CreateDatasetRequest)\n\n create_privacy_group_if_not_exists(\n privacy_group_id=str(request.privacy_group_id),\n privacy_group_name=request.privacy_group_name,\n description=request.description,\n in_use=True,\n fetcher_active=request.fetcher_active,\n matcher_active=request.matcher_active,\n write_back=request.write_back,\n )\n\n return CreateDatasetResponse(\n response=f\"Created dataset {request.privacy_group_id}\"\n )","def test_create_resource_group(self):\n pass"],"string":"[\n \"def create_group():\\n groupname = request.get_json().get(\\\"name\\\")\\n description = request.get_json().get(\\\"description\\\")\\n grp = admin.create_group(current_app.scoped_session(), groupname, description)\\n if grp:\\n response = admin.get_group_info(current_app.scoped_session(), groupname)\\n else:\\n response = {\\\"result\\\": \\\"group creation failed\\\"}\\n response = jsonify(response)\\n return response\",\n \"def create_group(group_id, group_name):\\n\\n kwargs = config.DEFAULT_REST_KWARGS\\n kwargs[\\\"data\\\"] = {\\\"id\\\": group_id, \\\"name\\\": group_name}\\n http_response = call_rest_api(\\\"/identities/groups/\\\", \\\"post\\\", **kwargs)\\n if http_response.status_code != 201: # 201 = 'new group created'\\n raise ValueError(http_response.text)\\n logger.log(f\\\"New custom group, {group_name}, with ID: {group_id}, was created successfully.\\\")\",\n \"def product_group_create(obj, name, department):\\n client = get_client(obj)\\n\\n with Action('Creating product_group: {}'.format(name), nl=True):\\n pg = client.product_group_create(name, department)\\n\\n print(json.dumps(pg, indent=4))\",\n \"def create_group(self, groupname):\\n data = {\\\"groupname\\\": groupname}\\n headers = {\\\"user-agent\\\": self.u_agent}\\n req_url = self.normalize_admin_url(\\\"groups\\\")\\n res = requests.post(\\n req_url,\\n headers=headers,\\n auth=self.auth,\\n data=json.dumps(data),\\n verify=False,\\n )\\n if res.status_code == 201:\\n return Response(0, u\\\"Group {} has been created\\\".format(groupname))\\n else:\\n return Response(res.status_code, res)\",\n \"def create_group(self, **kwargs):\\n post_body = json.dumps({'group': kwargs})\\n resp, body = self.post('groups', post_body)\\n self.expected_success(201, resp.status)\\n body = json.loads(body)\\n return rest_client.ResponseBody(resp, body)\",\n \"def create_namespaced_group(self, body, **kwargs):\\n\\n all_params = ['body', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_namespaced_group\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `create_namespaced_group`\\\")\\n\\n resource_path = '/oapi/v1/groups'.replace('{format}', 'json')\\n path_params = {}\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1Group',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def create_group(self, group_name, group_type):\\n grp_data = {\\\"name\\\": group_name, \\\"type\\\": group_type}\\n return requests.post(self.groups_url, data=json.dumps(grp_data),\\n headers=self.headers)\",\n \"def create_TestGroup(test_case, # type: AnyMagpieTestCaseType\\n override_group_name=null, # type: Optional[Str]\\n override_discoverable=null, # type: Optional[bool]\\n override_data=null, # type: Optional[JSON]\\n override_headers=null, # type: Optional[HeadersType]\\n override_cookies=null, # type: Optional[CookiesType]\\n ): # type: (...) -> JSON\\n app_or_url = get_app_or_url(test_case)\\n data = override_data\\n if override_data is null:\\n data = {\\\"group_name\\\": override_group_name if override_group_name is not null else test_case.test_group_name}\\n # only add 'discoverable' if explicitly provided here to preserve original behaviour of 'no value provided'\\n if override_discoverable is not null:\\n data[\\\"discoverable\\\"] = override_discoverable\\n grp_name = (data or {}).get(\\\"group_name\\\")\\n if grp_name:\\n test_case.extra_group_names.add(grp_name) # indicate potential removal at a later point\\n resp = test_request(app_or_url, \\\"POST\\\", \\\"/groups\\\", json=data,\\n headers=override_headers if override_headers is not null else test_case.json_headers,\\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\\n return check_response_basic_info(resp, 201, expected_method=\\\"POST\\\")\",\n \"def __create_new_group(self, group_name) -> None:\\n group = Group(name=group_name)\\n group.save()\\n\\n self.__add_permission_to_group(group)\",\n \"def create_group(self, name):\\n\\t\\tdata = {\\\"name\\\":name}\\n\\t\\tresponse = self.client.post(self._endpoint + \\\"/group\\\", content=data)\\n\\t\\treturn Group(\\n\\t\\t\\tresponse.json['group_id'],\\n\\t\\t\\tself.user_id,\\n\\t\\t\\tself.site_id,\\n\\t\\t\\tdata=response.json\\n\\t\\t)\",\n \"def create_placement_group(self, name, strategy='cluster'):\\r\\n params = {'GroupName':name, 'Strategy':strategy}\\r\\n group = self.get_status('CreatePlacementGroup', params, verb='POST')\\r\\n return group\",\n \"def create_group(self, event):\\n body = event['body']\\n body = json.loads(body)\\n\\n # Required field in POST body\\n if 'group_name' not in body:\\n return self.get_bad_request('POST body missing group_name')\\n\\n group_name = body['group_name']\\n user = self.mealShareUsers.get_user_cognito_data(event)\\n user_id = user['user_id']\\n \\n # Add the creator to the group, as the initial member\\n group_id = self.mealShareGroups.create_group(group_name)\\n success = self.mealShareGroups.add_user_to_group(user_id, group_id)\\n if success:\\n return {\\n 'statusCode': 200,\\n 'statusMessage': 'Successfully created group {} with ID {}'.format(group_name, group_id),\\n 'group_id': group_id,\\n 'group_name': group_name,\\n 'user_id': user_id\\n }\\n else:\\n return {\\n 'statusCode': 500,\\n 'statusMessage': 'FAILED to create group {} by user {}'.format(group_name, user_id),\\n 'group_id': group_id,\\n 'group_name': group_name,\\n 'user_id': user_id\\n }\",\n \"def create(self, group_name):\\n METHOD = 'POST'\\n API_PATH = '/groups/create'\\n\\n data = {'group_name': group_name}\\n\\n # Make REST call\\n resp = self._rest_call[METHOD](API_PATH, data=data)\\n if resp.status_code == 200:\\n return resp.json()\\n\\n elif resp.status_code == 403:\\n raise AuthorizationError(\\\"User is not authorized or token is incorrect.\\\")\\n\\n else:\\n if resp.json().get(\\\"error_code\\\") in ERROR_CODES:\\n raise ERROR_CODES[resp.json().get('error_code')](resp.json().get('message'))\\n else:\\n raise APIError(\\\"Response code {0}: {1} {2}\\\".format(resp.status_code,\\n resp.json().get('error_code'),\\n resp.json().get('message')))\",\n \"def allocate_group(remote, objectid):\\n cmd1 = mmapi.StoredCommands()\\n key1 = cmd1.AppendSceneCommand_AllocateNewGroupID(objectid)\\n remote.runCommand(cmd1)\\n result_val = mmapi.any_result()\\n cmd1.GetSceneCommandResult_AllocateNewGroupID(key1, result_val)\\n return result_val.i\",\n \"def add_group():\\n name = request.form['name']\\n data, code, message = FIELD_SERVICE.add_group(name)\\n return __result(data, code, message)\",\n \"def create_group(self, identifier: str, group_name: str) -> Group:\\n\\n # APM-137701 - Namespace for custom device calculation should not be set\\n group_id = get_group_id(\\\"\\\", identifier)\\n if group_id in self._groups:\\n raise ValueError(\\\"Group \\\" + group_name + \\\" already exist, id: \\\" + str(group_id))\\n else:\\n group = Group(group_id, group_name, self._technologies, self._results_builder)\\n\\n self._groups[group_id] = group\\n return group\",\n \"def test_create_group(self):\\n groupid = 'villains'\\n\\n # create the group\\n resp = self.app.post('/groups', data=json.dumps({'name':groupid}))\\n assert resp.status_code == 200\\n\\n # Fetch the group to check that it persists\\n resp = self.app.get('/groups/{}'.format(groupid))\\n assert resp.status_code == 200\",\n \"def createGroup(self, name):\\n new_group = ET.SubElement(self._root,'group')\\n group_name = ET.SubElement(new_group, 'name')\\n group_name.text = name\\n # update the document's groups\\n self._groups = self._root.findall('group') \\n print 'Creating group, \\\\'%s\\\\'' % name\\n return CAGroup(new_group)\",\n \"def create_group(self, create_group_details, **kwargs):\\n resource_path = \\\"/groups\\\"\\n method = \\\"POST\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"opc_retry_token\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"create_group got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"opc-retry-token\\\": kwargs.get(\\\"opc_retry_token\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\\n self.base_client.add_opc_retry_token_if_needed(header_params)\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n header_params=header_params,\\n body=create_group_details,\\n response_type=\\\"Group\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n header_params=header_params,\\n body=create_group_details,\\n response_type=\\\"Group\\\")\",\n \"def post_groups(\\n data: PostGroupIn, tkn: Token = Depends(from_authotization_header_nondyn),\\n):\\n assert_has_clearance(tkn.owner, \\\"sni.create_group\\\")\\n grp = Group(\\n description=data.description,\\n members=[tkn.owner],\\n group_name=data.group_name,\\n owner=tkn.owner,\\n ).save()\\n logging.debug(\\n \\\"Created group %s (%s) owned by %s\\\",\\n data.group_name,\\n str(grp.pk),\\n tkn.owner.character_name,\\n )\\n return GetGroupOut.from_record(grp)\",\n \"def create_adgroup(self, account_id, name, campaign_id,\\n creative_id, bid_type=None, bid_info=None, max_bid=None,\\n tracking_specs=None, view_tags=None, objective=None,\\n adgroup_status=None, targeting=None, conversion_specs=None, batch=False):\\n path = 'act_%s/adgroups' % account_id\\n args = {\\n 'name': name,\\n 'campaign_id': campaign_id,\\n 'creative': json.dumps({'creative_id': creative_id}),\\n }\\n if bid_type:\\n args['bid_type'] = bid_type\\n if max_bid:\\n # can only use max_bid with CPM bidding\\n args['max_bid'] = max_bid\\n elif bid_info:\\n args['bid_info'] = json.dumps(bid_info)\\n\\n if tracking_specs:\\n args['tracking_specs'] = json.dumps(tracking_specs)\\n if view_tags:\\n args['view_tags'] = json.dumps(view_tags)\\n if objective:\\n args['objective'] = objective\\n if adgroup_status:\\n args['adgroup_status'] = adgroup_status\\n if targeting:\\n args['targeting'] = json.dumps(targeting)\\n if conversion_specs:\\n args['conversion_specs'] = json.dumps(conversion_specs)\\n return self.make_request(path, 'POST', args, batch=batch)\",\n \"def autoCreateGroup(cleaned_data, cookie_user, isAutoApproved=False, querystring_content=False):\\n existingSites = Site.objects.filter(\\n domain=cleaned_data['domain'],\\n )\\n if len(existingSites) > 0:\\n\\n try:\\n site = existingSites[0]\\n group = site.group\\n except Exception, e:\\n raise Exception(\\\"Site \\\"+cleaned_data['domain']+\\\" has no group.\\\")\\n else:\\n # make a group and site\\n try:\\n group = Group.objects.create(\\n name=cleaned_data['name'],\\n short_name=cleaned_data['short_name'],\\n approved=False,\\n temp_interact=0,\\n requires_approval=False,\\n )\\n except Exception, e:\\n print \\\"* * * ** * * * * * * * EXCEPTION \\\"\\n print e\\n logger.warn(e)\\n groups = Group.objects.filter(\\n short_name=cleaned_data['short_name']\\n )\\n if len(groups) == 1:\\n group = groups[0]\\n elif len(groups) > 1:\\n raise Exception(\\\"More than one group with shortname found: \\\" + cleaned_data['short_name'])\\n else:\\n raise Exception(\\\"No groups found with shortname: \\\" + cleaned_data['short_name'])\\n\\n site = Site.objects.create(\\n name=cleaned_data['domain'],\\n domain=cleaned_data['domain'],\\n group=group,\\n # this is whether or not a querystring is counted in the url - we should rename this\\n querystring_content=querystring_content,\\n )\\n\\n blessed_tags = addDefaultsForNewGroup(group, cookie_user)\\n autoApproveUserAsAdmin(group, cookie_user, isAutoApproved=isAutoApproved)\\n\\n return group, site, blessed_tags\",\n \"def create():\\n name = request.json['name']\\n level = request.json['level']\\n manager = request.json['manager']\\n if models.user.Group.get(name):\\n raise Conflict('Group already exists.', creation=False)\\n else:\\n authorize(manager, level=level)\\n group = models.user.Group(name=name, level=level, manager=manager)\\n models.db.session.add(group)\\n models.db.session.commit()\\n return response(200, creation=True)\",\n \"def create_ad_group(client, customer_id, campaign_resource_name):\\n ad_group_service = client.get_service(\\\"AdGroupService\\\")\\n\\n # Creates the ad group.\\n # Note that the ad group type must not be set.\\n # Since the advertising_channel_sub_type is APP_CAMPAIGN,\\n # 1- you cannot override bid settings at the ad group level.\\n # 2- you cannot add ad group criteria.\\n ad_group_operation = client.get_type(\\\"AdGroupOperation\\\")\\n ad_group = ad_group_operation.create\\n ad_group.name = f\\\"Earth to Mars cruises {uuid4()}\\\"\\n ad_group.status = client.enums.AdGroupStatusEnum.ENABLED\\n ad_group.campaign = campaign_resource_name\\n\\n ad_group_response = ad_group_service.mutate_ad_groups(\\n customer_id=customer_id, operations=[ad_group_operation]\\n )\\n\\n ad_group_resource_name = ad_group_response.results[0].resource_name\\n print(f'Ad Group created with resource name: \\\"{ad_group_resource_name}\\\".')\\n return ad_group_resource_name\",\n \"def create(person_group_id, name=None, user_data=None):\\n name = person_group_id if name is None else name\\n url = 'persongroups/{}'.format(person_group_id)\\n json = {\\n 'name': name,\\n 'userData': user_data,\\n }\\n\\n return util.request('PUT', url, json=json)\",\n \"def create_new_group(self, group_id, poll_id, name):\\n obj = self.table()\\n obj.group_id = str(group_id)\\n obj.poll_id = poll_id\\n obj.name = name\\n self.db.session.add(obj)\\n self.db.session.commit()\",\n \"def createGroup(self, *group):\\n if not self.rank:\\n logging.info('Creating atom group {}'.format(group))\\n\\n if not len(group):\\n for idSS in self.pargs['idSS']:\\n self.lmp.command('group group{} type {}'.format(idSS, idSS))\\n else:\\n self.lmp.command('group ' + ('{} ' * len(group)).format(*group))\",\n \"def capacitygroup_create(cmd_ctx, cpc, **options):\\n cmd_ctx.execute_cmd(\\n lambda: cmd_capacitygroup_create(cmd_ctx, cpc, options))\",\n \"def group_add_name(org_id, data):\\n if data.has_key('groupname'):\\n groupname = data['groupname']\\n add_group(org_id, groupname, False)\",\n \"def request_group_create():\\n return Response(render_template('admin/group/create-update.html',\\n csrf_token=(\\n get_raw_jwt() or {}).get(\\\"csrf\\\"),\\n target=\\\"/admin/group/create\\\"),\\n mimetype='text/html')\",\n \"def _make_group(self, _rk, _group_hint):\\n\\n if isinstance(_group_hint, dict):\\n # _group_hint is a single key/value pair\\n g = _group_hint[list(_group_hint)[0]]\\n\\n r_type = g.get(\\\"type\\\", \\\"none\\\")\\n if r_type != \\\"OS::Nova::ServerGroup\\\":\\n return \\\"support only ServerGroup resource\\\"\\n\\n properties = g.get(\\\"properties\\\", {})\\n if len(properties) == 0:\\n return \\\"no properties\\\"\\n\\n group_name = properties.get(\\\"name\\\", None)\\n if group_name is None:\\n return \\\"no group name\\\"\\n group_name = group_name.strip()\\n\\n policies = properties.get(\\\"policies\\\", [])\\n if len(policies) == 0:\\n return \\\"no policy of the group\\\"\\n\\n if len(policies) > 1:\\n return \\\"multiple policies\\\"\\n\\n # TODO: exclude soft-affinity and soft-anti-affinity?\\n\\n if group_name in self.groups.keys():\\n group = self.groups[group_name]\\n else:\\n group = Group(group_name)\\n\\n policy = policies[0].strip()\\n if policy == \\\"anti-affinity\\\":\\n group_type = \\\"diversity\\\"\\n else:\\n group_type = policy\\n\\n group.group_type = group_type\\n group.factory = \\\"server-group\\\"\\n group.level = \\\"host\\\"\\n\\n self.groups[group_name] = group\\n else:\\n # group hint is uuid string.\\n rg = self.resource.get_group_by_uuid(_group_hint)\\n if rg is None:\\n return \\\"unknown group found while making group\\\"\\n\\n # TODO: exclude soft-affinity and soft-anti-affinity?\\n\\n if rg.name in self.groups.keys():\\n group = self.groups[rg.name]\\n else:\\n group = Group(rg.name)\\n\\n group.group_type = rg.group_type\\n group.factory = rg.factory\\n group.level = \\\"host\\\"\\n\\n self.groups[rg.name] = group\\n\\n if group is not None:\\n group.server_list.append(self.app_name + \\\":\\\" + _rk)\\n\\n return \\\"ok\\\"\",\n \"def create_group_scene(self, name, group):\\n data = {\\n \\\"name\\\": name,\\n \\\"group\\\": group,\\n \\\"recycle\\\": True,\\n \\\"type\\\": \\\"GroupScene\\\"\\n }\\n return self.bridge.bridge.post('/scenes', data)\",\n \"def create(self, name, desc, tenant_id):\\n data = {\\\"security_group\\\": {\\\"name\\\": name, \\n \\\"description\\\": desc, \\n \\\"tenant_id\\\":tenant_id}}\\n\\n path = '%s/security-groups' % self.ver\\n res = self.client.call(path, 'POST', data=json.dumps(data), \\n token=self.manager.identity.token)\\n self.logger.debug('Create openstack security group: %s' % truncate(res))\\n return res[0]['security_group']\",\n \"def post_security_group_create(self, resource_dict):\\n pass\",\n \"async def async_create_group(\\n hass: HomeAssistant,\\n name: str,\\n entity_ids: Collection[str] | None = None,\\n user_defined: bool = True,\\n icon: str | None = None,\\n object_id: str | None = None,\\n mode: bool | None = None,\\n order: int | None = None,\\n ) -> Group:\\n group = Group.async_create_group_entity(\\n hass, name, entity_ids, user_defined, icon, object_id, mode, order\\n )\\n\\n # If called before the platform async_setup is called (test cases)\\n await _async_get_component(hass).async_add_entities([group])\\n return group\",\n \"def new_group(request):\\n return edit_group(request, None)\",\n \"def createNewGroup():\\n if request.method == 'POST':\\n groupname = request.form['groupname1']\\n internal = request.form['internal1']\\n external = request.form['external1']\\n userNo = request.form['usersNo1']\\n if 'node1' in request.form:\\n node = int(request.form['node1'])\\n else:\\n node = -1\\n\\n if int(userNo) == 0:\\n if hl.createGroup(groupname, internal, external, node):\\n return True\\n elif int(userNo) > 0:\\n if hl.createGroup(groupname, internal, external, node, genUsers=True, numUsers=int(userNo)):\\n return True\\n\\n return False\",\n \"def _assert_create_group(self, personality, response=400):\\n group_response = self.autoscale_behaviors.create_scaling_group_given(\\n lc_personality=personality)\\n self.assertEquals(group_response.status_code, response, msg='Create group '\\n 'with invalid lc_personality returned {0} as against '\\n '{1}'.format(group_response.status_code, response))\\n if response is 200:\\n group = group_response.entity\\n self.resources.add(group, self.empty_scaling_group)\\n return group\",\n \"def create_groups(**kwargs):\\n for gname in SEC_GROUP_NAMES.itervalues():\\n Group.objects.get_or_create(name=gname)\",\n \"def _create_child_group(self, name) -> \\\"GroupBase\\\":\\n pass\",\n \"async def create_group(ctx, name: str, role: str, group_type: str=None, comp: str=None, rating: int=None, time: str=None):\\n\\n owner = ctx.message.author.name\\n \\n if comp:\\n comp = [int(i) for i in comp.split()] # convert string input to array\\n\\n new_group = Group(owner, name, role, group_type, rating, time, comp)\\n bg_bot.manager.add_group(owner, new_group)\\n \\n await ctx.send(f'Created new {group_type} group for leader {owner}!')\",\n \"def post(self):\\n status = ErrorCode.SUCCESS\\n try:\\n data = DotDict(json_decode(self.request.body))\\n logging.info(\\\"[UWEB] add group request: %s, cid: %s\\\",\\n data, self.current_user.cid)\\n except Exception as e:\\n status = ErrorCode.ILLEGAL_DATA_FORMAT\\n logging.exception(\\\"[UWEB] Invalid data format. body:%s, Exception: %s\\\",\\n self.request.body, e.args)\\n self.write_ret(status)\\n return\\n\\n try: \\n cid = data.cid\\n name = data.name\\n group = self.get_group_by_cid(cid, name)\\n if group:\\n status = ErrorCode.GROUP_EXIST\\n self.write_ret(status)\\n return\\n\\n group_info = dict(cid=cid,\\n name=name,\\n type=UWEB.GROUP_TYPE.NEW)\\n gid = add_group(group_info, self.db, self.redis)\\n # NOTE: wspush to client\\n tid = self.current_user.tid\\n if status == ErrorCode.SUCCESS:\\n WSPushHelper.pushS3(tid, self.db, self.redis)\\n\\n self.write_ret(status,\\n dict_=dict(gid=gid,\\n cid=cid,\\n name=name))\\n\\n except Exception as e:\\n logging.exception(\\\"[UWEB] Create group failed. uid: %s, Exception: %s\\\",\\n self.current_user.uid, e.args)\\n status = ErrorCode.SERVER_BUSY\\n self.write_ret(status)\",\n \"def create(self, context=None):\\n values = self.obj_get_changes()\\n db_nodegroup = self.dbapi.create_nodegroup(values)\\n self._from_db_object(self, db_nodegroup)\",\n \"def CreateGroup(self, name, alloc_policy=None, dry_run=False, reason=None):\\n query = []\\n _AppendDryRunIf(query, dry_run)\\n _AppendReason(query, reason)\\n\\n body = {\\n \\\"name\\\": name,\\n \\\"alloc_policy\\\": alloc_policy,\\n }\\n\\n return self._SendRequest(HTTP_POST, \\\"/%s/groups\\\" % GANETI_RAPI_VERSION,\\n query, body)\",\n \"def create_group(name, nodes, description=None):\\n group, created = Group.get_or_create(name=name)\\n if created:\\n print('Group created with PK={} and name {}'.format(group.pk, group.name))\\n else:\\n print('Group with name {} and pk {} already exists. Do you want to add nodes?[y/n]'.format(group.name, group.pk))\\n answer = raw_input()\\n if answer.strip().lower() == 'y':\\n pass\\n else:\\n return\\n nodes2 = []\\n nodes2_pks = []\\n for node in nodes:\\n try:\\n node = int(node)\\n except ValueError:\\n pass\\n nodes2_pks.append(node)\\n try:\\n nodes2.append(load_node(node))\\n except:# NotExistentError:\\n pass\\n\\n group.add_nodes(nodes2)\\n print('added nodes: {} to group {} {}'.format(nodes2_pks, group.name, group.pk))\\n\\n if description:\\n group.description = description\\n\\n return group\",\n \"async def create(\\n self,\\n resource_group_name: str,\\n project_name: str,\\n group_name: str,\\n group: Optional[\\\"models.Group\\\"] = None,\\n **kwargs\\n ) -> \\\"models.Group\\\":\\n cls = kwargs.pop('cls', None) # type: ClsType[\\\"models.Group\\\"]\\n error_map = {\\n 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError\\n }\\n error_map.update(kwargs.pop('error_map', {}))\\n api_version = \\\"2018-06-01\\\"\\n content_type = kwargs.pop(\\\"content_type\\\", \\\"application/json\\\")\\n accept = \\\"application/json\\\"\\n\\n # Construct URL\\n url = self.create.metadata['url'] # type: ignore\\n path_format_arguments = {\\n 'subscriptionId': self._serialize.url(\\\"self._config.subscription_id\\\", self._config.subscription_id, 'str'),\\n 'resourceGroupName': self._serialize.url(\\\"resource_group_name\\\", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\\\\w\\\\._\\\\(\\\\)]+$'),\\n 'projectName': self._serialize.url(\\\"project_name\\\", project_name, 'str'),\\n 'groupName': self._serialize.url(\\\"group_name\\\", group_name, 'str'),\\n }\\n url = self._client.format_url(url, **path_format_arguments)\\n\\n # Construct parameters\\n query_parameters = {} # type: Dict[str, Any]\\n query_parameters['api-version'] = self._serialize.query(\\\"api_version\\\", api_version, 'str')\\n\\n # Construct headers\\n header_parameters = {} # type: Dict[str, Any]\\n header_parameters['Content-Type'] = self._serialize.header(\\\"content_type\\\", content_type, 'str')\\n header_parameters['Accept'] = self._serialize.header(\\\"accept\\\", accept, 'str')\\n\\n body_content_kwargs = {} # type: Dict[str, Any]\\n if group is not None:\\n body_content = self._serialize.body(group, 'Group')\\n else:\\n body_content = None\\n body_content_kwargs['content'] = body_content\\n request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs)\\n pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)\\n response = pipeline_response.http_response\\n\\n if response.status_code not in [200, 201]:\\n map_error(status_code=response.status_code, response=response, error_map=error_map)\\n raise HttpResponseError(response=response, error_format=ARMErrorFormat)\\n\\n response_headers = {}\\n if response.status_code == 200:\\n response_headers['x-ms-request-id']=self._deserialize('str', response.headers.get('x-ms-request-id'))\\n deserialized = self._deserialize('Group', pipeline_response)\\n\\n if response.status_code == 201:\\n response_headers['x-ms-request-id']=self._deserialize('str', response.headers.get('x-ms-request-id'))\\n deserialized = self._deserialize('Group', pipeline_response)\\n\\n if cls:\\n return cls(pipeline_response, deserialized, response_headers)\\n\\n return deserialized\",\n \"def post(self):\\n args = parser.parse_args()\\n user_group = UserGroup()\\n user_group.name = args['name']\\n user_group.createdby = auth.username()\\n db_session.add(user_group)\\n db_session.commit()\\n return user_group, 201\",\n \"def createGroup(self):\\n return _libsbml.GroupsModelPlugin_createGroup(self)\",\n \"def test_createGroup(self):\\n\\t\\tself.client.force_authenticate(user=User.objects.get(id=1))\\n\\t\\turl = \\\"/groups/\\\"\\n\\t\\tdata = {\\n\\t\\t\\t'name' : 'testGroup3',\\n\\t\\t\\t'description' : 'This is another test group that just created.',\\n\\t\\t\\t'isPublic' : True\\n\\t\\t}\\n\\t\\tresponse = self.client.post(url, data, format='json')\\n\\t\\tself.assertEqual(response.status_code, status.HTTP_201_CREATED)\\n\\t\\tself.assertEqual(response.data[\\\"id\\\"], 3)\\n\\t\\tself.assertEqual(response.data[\\\"name\\\"], 'testGroup3')\",\n \"def create_group(self, tenant_id, group_id):\\n maas_client = self._get_maas_client()\\n d = maas_client.add_notification_and_plan()\\n\\n def create_group_in_db((notification, notification_plan)):\\n return cass.create_group(\\n self._db, tenant_id, group_id, notification, notification_plan)\\n d.addCallback(create_group_in_db)\\n\\n return d\",\n \"def create_group(self, properties: dict[str, Any | None]) -> dict:\\n group = self.ms_client.http_request(method='POST', url_suffix='groups', json_data=properties)\\n return group\",\n \"def create_group(\\n self,\\n name,\\n group,\\n validate_only=None,\\n retry=google.api_core.gapic_v1.method.DEFAULT,\\n timeout=google.api_core.gapic_v1.method.DEFAULT,\\n metadata=None,\\n ):\\n if metadata is None:\\n metadata = []\\n metadata = list(metadata)\\n # Wrap the transport method to add retry and timeout logic.\\n if \\\"create_group\\\" not in self._inner_api_calls:\\n self._inner_api_calls[\\n \\\"create_group\\\"\\n ] = google.api_core.gapic_v1.method.wrap_method(\\n self.transport.create_group,\\n default_retry=self._method_configs[\\\"CreateGroup\\\"].retry,\\n default_timeout=self._method_configs[\\\"CreateGroup\\\"].timeout,\\n client_info=self._client_info,\\n )\\n\\n request = group_service_pb2.CreateGroupRequest(\\n name=name, group=group, validate_only=validate_only,\\n )\\n if metadata is None:\\n metadata = []\\n metadata = list(metadata)\\n try:\\n routing_header = [(\\\"name\\\", name)]\\n except AttributeError:\\n pass\\n else:\\n routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(\\n routing_header\\n )\\n metadata.append(routing_metadata)\\n\\n return self._inner_api_calls[\\\"create_group\\\"](\\n request, retry=retry, timeout=timeout, metadata=metadata\\n )\",\n \"def create_group(self, group_name, user_ids=[], role_ids=[]):\\n payload = {}\\n payload['name'] = group_name\\n payload['user_ids'] = user_ids\\n payload['role_ids'] = role_ids\\n return Client._post(self, payload)\",\n \"def create_group_with_http_info(self, bucket_id, group, **kwargs):\\n\\n all_params = ['bucket_id', 'group', 'if_match', 'if_none_match']\\n all_params.append('callback')\\n all_params.append('_return_http_data_only')\\n all_params.append('_preload_content')\\n all_params.append('_request_timeout')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_group\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'bucket_id' is set\\n if ('bucket_id' not in params) or (params['bucket_id'] is None):\\n raise ValueError(\\\"Missing the required parameter `bucket_id` when calling `create_group`\\\")\\n # verify the required parameter 'group' is set\\n if ('group' not in params) or (params['group'] is None):\\n raise ValueError(\\\"Missing the required parameter `group` when calling `create_group`\\\")\\n\\n if 'if_match' in params and not re.search('\\\\\\\\\\\\\\\"[0-9]+\\\\\\\\\\\\\\\"', params['if_match']):\\n raise ValueError(\\\"Invalid value for parameter `if_match` when calling `create_group`, must conform to the pattern `/\\\\\\\\\\\\\\\"[0-9]+\\\\\\\\\\\\\\\"/`\\\")\\n if 'if_none_match' in params and not re.search('\\\\\\\\\\\\\\\"[0-9]+\\\\\\\\\\\\\\\"', params['if_none_match']):\\n raise ValueError(\\\"Invalid value for parameter `if_none_match` when calling `create_group`, must conform to the pattern `/\\\\\\\\\\\\\\\"[0-9]+\\\\\\\\\\\\\\\"/`\\\")\\n\\n collection_formats = {}\\n\\n resource_path = '/buckets/{bucket_id}/groups'.replace('{format}', 'json')\\n path_params = {}\\n if 'bucket_id' in params:\\n path_params['bucket_id'] = params['bucket_id']\\n\\n query_params = {}\\n\\n header_params = {}\\n if 'if_match' in params:\\n header_params['If-Match'] = params['if_match']\\n if 'if_none_match' in params:\\n header_params['If-None-Match'] = params['if_none_match']\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'group' in params:\\n body_params = params['group']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['application/json'])\\n\\n # Authentication setting\\n auth_settings = ['basicAuth']\\n\\n return self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='Group',\\n auth_settings=auth_settings,\\n callback=params.get('callback'),\\n _return_http_data_only=params.get('_return_http_data_only'),\\n _preload_content=params.get('_preload_content', True),\\n _request_timeout=params.get('_request_timeout'),\\n collection_formats=collection_formats)\",\n \"def create(isamAppliance, id, check_mode=False, force=False):\\n if force is True or _check(isamAppliance, id=id) is False:\\n if check_mode is True:\\n return isamAppliance.create_return_object(changed=True)\\n else:\\n return isamAppliance.invoke_post(\\\"Creating group\\\", \\\"/sysaccount/groups/v1\\\",\\n {\\n 'id': id\\n })\\n\\n return isamAppliance.create_return_object()\",\n \"def gen_group(group_name=None, group_vars={}):\\n group = Group(name=group_name)\\n for key, value in group_vars.iteritems():\\n group.set_variable(key, value)\\n return group\",\n \"def create_group(self, group):\\n if self.dryrun:\\n self.logger.info(\\\"Would create group %s\\\", group)\\n return FakeGroupId()\\n result = self.conn.usergroup.create(name=group)\\n groupid = result['usrgrpids'][0]\\n self.logger.info(\\\"Create group %s with id %s\\\", group, groupid)\\n return groupid\",\n \"def create( self, trans, payload, **kwd ):\\n group_dict = dict( message='', status='ok' )\\n name = payload.get( 'name', '' )\\n if name:\\n description = payload.get( 'description', '' )\\n if not description:\\n description = ''\\n else:\\n # TODO add description field to the model\\n group_dict = self.group_manager.create( trans, name=name ).to_dict( view='element', value_mapper=self.__get_value_mapper( trans ) )\\n else:\\n raise RequestParameterMissingException( 'Missing required parameter \\\"name\\\".' )\\n return group_dict\",\n \"def create_group(self):\\n # TODO: Assuming first server is good - need to make fallback logic\\n return self.session.get_any(\\\"{base}{request_url}\\\".format(base=self.servers[0],\\n request_url=F\\\"/GroupV2/Create/\\\"))\",\n \"def create_security_group(self, body=None):\\r\\n return self.post(self.security_groups_path, body=body)\",\n \"def handle(self, *args, **options):\\n new_group, created = Group.objects.get_or_create(name=options.get('group_name')) \\n self.stdout.write(f\\\"Group {options.get('group_name')} created\\\")\",\n \"def create_secgroup(self, args):\\n message = MessageClass()\\n region = args[\\\"Region\\\"]\\n sgid = args[\\\"Group-Name\\\"]\\n desc = args[\\\"Description\\\"]\\n\\n # Boto3 client creation by providing the access_id and access_secret\\n ec2 = boto3.client(service_name='ec2', region_name=region, api_version=None, use_ssl=True,\\n verify=None, endpoint_url=None, aws_access_key_id=self.aws_access_key,\\n aws_secret_access_key=self.aws_secret_token, aws_session_token=None,\\n config=None)\\n response = ec2.describe_vpcs()\\n vpc_id = response.get('Vpcs', [{}])[0].get('VpcId', '')\\n\\n response = ec2.create_security_group(GroupName=sgid,\\n Description=desc,\\n VpcId=vpc_id)\\n attachment = MessageAttachmentsClass()\\n d = response[\\\"GroupId\\\"]\\n attachment.title = d\\n message.message_text = \\\"Security group created:\\\"\\n message.attach(attachment)\\n\\n return message.to_json()\",\n \"def replace_namespaced_group(self, body, name, **kwargs):\\n\\n all_params = ['body', 'name', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method replace_namespaced_group\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `replace_namespaced_group`\\\")\\n # verify the required parameter 'name' is set\\n if ('name' not in params) or (params['name'] is None):\\n raise ValueError(\\\"Missing the required parameter `name` when calling `replace_namespaced_group`\\\")\\n\\n resource_path = '/oapi/v1/groups/{name}'.replace('{format}', 'json')\\n path_params = {}\\n if 'name' in params:\\n path_params['name'] = params['name']\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'PUT',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1Group',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def create_new_scaling_group(self, request, data):\\n group_cfg = data['groupConfiguration']\\n\\n group_cfg.setdefault('maxEntities', MAX_ENTITIES)\\n group_cfg.setdefault('metadata', {})\\n\\n if group_cfg['minEntities'] > group_cfg['maxEntities']:\\n raise InvalidMinEntities(\\n \\\"minEntities must be less than or equal to maxEntities\\\")\\n\\n if data['launchConfiguration']['type'] == 'launch_server':\\n validate_launch_config_servicenet(data['launchConfiguration'])\\n\\n deferred = get_supervisor().validate_launch_config(\\n self.log, self.tenant_id, data['launchConfiguration'])\\n\\n deferred.addCallback(\\n lambda _: self.store.create_scaling_group(\\n self.log, self.tenant_id,\\n group_cfg,\\n normalize_launch_config(data['launchConfiguration']),\\n data.get('scalingPolicies', None)))\\n\\n def _do_obey_config_change(result):\\n group_id = result['id']\\n config = result['groupConfiguration']\\n launch = result['launchConfiguration']\\n group = self.store.get_scaling_group(\\n self.log, self.tenant_id, group_id)\\n log = self.log.bind(scaling_group_id=group_id)\\n d = controller.modify_and_trigger(\\n self.dispatcher,\\n group,\\n bound_log_kwargs(log),\\n partial(\\n controller.obey_config_change, log,\\n transaction_id(request), config, launch_config=launch),\\n modify_state_reason='create_new_scaling_group')\\n return d.addCallback(lambda _: result)\\n\\n deferred.addCallback(_do_obey_config_change)\\n\\n def _add_to_bobby(result, client):\\n d = client.create_group(self.tenant_id, result['id'])\\n return d.addCallback(lambda _: result)\\n\\n bobby = get_bobby()\\n if bobby is not None:\\n deferred.addCallback(_add_to_bobby, bobby)\\n\\n def _format_output(result):\\n uuid = result['id']\\n result[\\\"state\\\"] = format_state_dict(result[\\\"state\\\"])\\n request.setHeader(\\n \\\"Location\\\",\\n get_autoscale_links(self.tenant_id, uuid, format=None))\\n result[\\\"links\\\"] = get_autoscale_links(self.tenant_id, uuid)\\n linkify_policy_list(\\n result['scalingPolicies'], self.tenant_id, uuid)\\n result['scalingPolicies_links'] = get_policies_links(\\n result['scalingPolicies'],\\n self.tenant_id, uuid, rel='policies')\\n return {\\\"group\\\": result}\\n\\n deferred.addCallback(_format_output)\\n deferred.addCallback(json.dumps)\\n return deferred\",\n \"def make_grp(self, name='grp'):\\n self.base[name] = self.get_group_array()\",\n \"def create_rule_group(self: object,\\n body: dict,\\n cs_username: str = None # pylint: disable=W0613 # cs_username is deprecated\\n ) -> dict:\\n # [POST] https://assets.falcon.crowdstrike.com/support/api/swagger.html#/custom-ioa/create-rule-groupMixin0\\n return process_service_request(\\n calling_object=self,\\n endpoints=Endpoints,\\n operation_id=\\\"create_rule_groupMixin0\\\",\\n body=body\\n )\",\n \"def create_group(user):\\n if connexion.request.is_json:\\n users_group = [User.from_dict(d) for d in connexion.request.get_json()]\\n response = (\\\"success\\\", 201)\\n if len(users_group) > 4:\\n response = (\\\"Max number of player is 4\\\", 400)\\n else:\\n groupId = GroupStorageController.add_new_group(users_group)\\n return response\",\n \"def create_group():\\n incoming = request.get_json()\\n chatroom = Chatroom(\\n name = incoming['name'],\\n tag = incoming['tag'],\\n )\\n db.session.add(chatroom)\\n db.session.commit()\\n participant = Participant(\\n user_id = session['user_id'],\\n room_id = chatroom.room_id,\\n )\\n db.session.add(participant)\\n db.session.commit()\\n return jsonify(results = chatroom.room_id)\",\n \"def creategroup(body):\\n group = body.get(\\\"groupname\\\", None)\\n pps = body.get(\\\"pilotpoints\\\", None)\\n print('lol',group, pps)\\n print(type(pps))\\n\\n # Does the person exist already?\\n if group not in group_dict and group is not None:\\n group_dict[group] = {\\n \\\"groupname\\\": group,\\n \\\"pilotpoints\\\": pps,\\n }\\n return group_dict[group], 201\\n\\n # Otherwise, they exist, that's an error\\n else:\\n abort(\\n 406,\\n \\\"Person with last name {group} already exists\\\".format(group=group),\\n )\",\n \"def groups_create(self, mar, request):\\n if not permissions.CanCreateGroup(mar.perms):\\n raise permissions.PermissionException(\\n 'The user is not allowed to create groups.')\\n\\n user_dict = self._services.user.LookupExistingUserIDs(\\n mar.cnxn, [request.groupName])\\n if request.groupName.lower() in user_dict:\\n raise exceptions.GroupExistsException(\\n 'group %s already exists' % request.groupName)\\n\\n if request.ext_group_type:\\n ext_group_type = str(request.ext_group_type).lower()\\n else:\\n ext_group_type = None\\n group_id = self._services.usergroup.CreateGroup(\\n mar.cnxn, self._services, request.groupName,\\n str(request.who_can_view_members).lower(),\\n ext_group_type)\\n\\n return api_pb2_v1.GroupsCreateResponse(\\n groupID=group_id)\",\n \"def newgroup(self, groupname, groupou=None, grouptype=None,\\n description=None, mailaddress=None, notes=None, sd=None,\\n gidnumber=None, nisdomain=None):\\n\\n group_dn = \\\"CN=%s,%s,%s\\\" % (groupname, (groupou or \\\"CN=Users\\\"), self.domain_dn())\\n\\n # The new user record. Note the reliance on the SAMLDB module which\\n # fills in the default informations\\n ldbmessage = {\\\"dn\\\": group_dn,\\n \\\"sAMAccountName\\\": groupname,\\n \\\"objectClass\\\": \\\"group\\\"}\\n\\n if grouptype is not None:\\n ldbmessage[\\\"groupType\\\"] = normalise_int32(grouptype)\\n\\n if description is not None:\\n ldbmessage[\\\"description\\\"] = description\\n\\n if mailaddress is not None:\\n ldbmessage[\\\"mail\\\"] = mailaddress\\n\\n if notes is not None:\\n ldbmessage[\\\"info\\\"] = notes\\n\\n if gidnumber is not None:\\n ldbmessage[\\\"gidNumber\\\"] = normalise_int32(gidnumber)\\n\\n if nisdomain is not None:\\n ldbmessage[\\\"msSFU30Name\\\"] = groupname\\n ldbmessage[\\\"msSFU30NisDomain\\\"] = nisdomain\\n\\n if sd is not None:\\n ldbmessage[\\\"nTSecurityDescriptor\\\"] = ndr_pack(sd)\\n\\n self.add(ldbmessage)\",\n \"def create(self, body: CloudSecurityGroup) -> Dict:\\n\\t\\treturn self._post(route=AWSSecurityGroupConsts.CLOUD_SECURITY_GROUP.value, body=body)\",\n \"def create_new_group(self, a, b):\\n self.groups[self.group_id] = set([a,b])\\n self.node_id[a] = self.node_id[b] = self.group_id\\n self.group_id += 1\",\n \"def post(self):\\n args = platform_group_arguments.parse_args()\\n\\n platform_group = PlatformGroup(**args)\\n self.session.add(platform_group)\\n self.session.commit()\\n\\n return platform_group\",\n \"def test_create_group(self):\\n pass\",\n \"def test_create_group(self):\\n pass\",\n \"def create_group(self, groupname, filters=[], filter_options=[], **kwargs):\\n pytan.utils.check_for_help(kwargs=kwargs)\\n clean_kwargs = pytan.utils.clean_kwargs(kwargs=kwargs)\\n\\n filter_defs = pytan.utils.dehumanize_question_filters(question_filters=filters)\\n option_defs = pytan.utils.dehumanize_question_options(question_options=filter_options)\\n\\n h = (\\n \\\"Issue a GetObject to get the full object of specified sensors for inclusion in a \\\"\\n \\\"group\\\"\\n )\\n filter_defs = self._get_sensor_defs(defs=filter_defs, pytan_help=h, **clean_kwargs)\\n\\n add_group_obj = pytan.utils.build_group_obj(\\n q_filter_defs=filter_defs, q_option_defs=option_defs,\\n )\\n add_group_obj.name = groupname\\n\\n h = \\\"Issue an AddObject to add a Group object\\\"\\n group_obj = self._add(obj=add_group_obj, pytan_help=h, **clean_kwargs)\\n\\n m = \\\"New group {!r} created with ID {!r}, filter text: {!r}\\\".format\\n self.mylog.info(m(group_obj.name, group_obj.id, group_obj.text))\\n return group_obj\",\n \"def make_custom_group(self, qid, name='', path='', attrs={}):\\n gslash = \\\"/\\\"\\n parent = self\\n sdef, name, path = self.file.get_custom_node_info(qid, gslash, name, path, parent) \\n grp = Group(self.file, sdef, name, path, attrs, parent)\\n return grp\",\n \"async def command_create(self, context):\\n # await self._create_new_role(context, name, target=GROUP_CATEGORY_NAME)\\n print('main create')\",\n \"def create_sec_group(ec2, sec_group_name):\\n sec = ec2.create_security_group(sec_group_name, 'Jvivian Boto SecGroup')\\n port = 22\\n sec.authorize('tcp', port, port, '0.0.0.0/0')\",\n \"def placement_group(template, name):\\n p = PlacementGroup(name, template=template)\\n p.Strategy = 'cluster'\\n return p\",\n \"def security_group_create(auth=None, **kwargs):\\n cloud = get_operator_cloud(auth)\\n kwargs = _clean_kwargs(keep_name=True, **kwargs)\\n return cloud.create_security_group(**kwargs)\",\n \"def __create_group(self):\\n\\n group = time.strftime(_GROUP_NAME_FORMAT, time.localtime())\\n LOG.info(\\\"Creating backup group '%s'.\\\", group)\\n\\n group_path = self.group_path(group)\\n\\n try:\\n os.mkdir(group_path)\\n except EnvironmentError as e:\\n if e.errno != errno.EEXIST:\\n raise Error(\\\"Unable to create a new backup group '{}': {}.\\\",\\n group_path, psys.e(e))\\n\\n self.__on_group_created(group)\\n\\n return group\",\n \"def create_app_policy_group(self, name, **kwargs):\\n post_body = {'application_policy_group': {'name': name}}\\n if kwargs.get('description'):\\n post_body['description'] = kwargs.get('description')\\n post_body = json.dumps(post_body)\\n resp, body = self.post(self.get_uri(self.resource), post_body)\\n body = json.loads(body)\\n self.expected_success(http_client.CREATED, resp.status)\\n return rest_client.ResponseBody(resp, body)\",\n \"def add_group_to_json(args):\\n\\n sanitised_group = args.group.replace('/', '-')\\n new_group = {\\n \\\"name\\\": sanitised_group,\\n \\\"propogate_permissions\\\": False,\\n \\\"allowed_attributes\\\": [\\n\\t\\t\\t{\\n \\t\\\"attribute_requirements\\\": {}, \\n \\\"permissions\\\": \\\"l\\\"\\n }\\n\\t\\t],\\n \\\"buckets\\\": []\\n }\\n\\n try:\\n with open(args.file, \\\"r\\\") as f:\\n config = json.load(f)\\n except FileNotFoundError:\\n print(\\\"Error: could not find given auth JSON file\\\")\\n return 1\\n\\n config[\\\"groups\\\"].append(new_group)\\n\\n with open(args.file, \\\"w\\\") as f:\\n json.dump(config, f, indent=4)\\n\\n return 0\",\n \"def create_sg(vpc_id, description, group_name):\\n client = boto3.client('ec2')\\n security_group = str(group_name + \\\"_sg\\\")\\n\\n # get the security groups\\n idle_sg = get_sg()\\n\\n print(idle_sg)\\n print(security_group)\\n\\n # if security group doesnt exist, create it\\n if security_group not in idle_sg:\\n print(\\\"Creating SG\\\")\\n return client.create_security_group(\\n Description=description,\\n GroupName=security_group,\\n VpcId=vpc_id\\n )\\n return get_sg_id(security_group)\",\n \"def create_subgroup_global(request_ctx, id, title, description=None, vendor_guid=None, **request_kwargs):\\n\\n path = '/v1/global/outcome_groups/{id}/subgroups'\\n payload = {\\n 'title' : title,\\n 'description' : description,\\n 'vendor_guid' : vendor_guid,\\n }\\n url = request_ctx.base_api_url + path.format(id=id)\\n response = client.post(request_ctx, url, payload=payload, **request_kwargs)\\n\\n return response\",\n \"def create_group_command(client: MsGraphClient, args: dict) -> tuple[str, dict, dict]:\\n required_properties = {\\n 'displayName': str(args.get('display_name')),\\n 'mailNickname': str(args.get('mail_nickname')),\\n 'mailEnabled': args.get('mail_enabled') == 'true',\\n 'securityEnabled': args.get('security_enabled')\\n }\\n\\n # create the group\\n group = client.create_group(required_properties)\\n\\n # display the new group and it's properties\\n group_readable, group_outputs = parse_outputs(group)\\n human_readable = tableToMarkdown(name=f\\\"{required_properties['displayName']} was created successfully:\\\",\\n t=group_readable,\\n headers=['ID', 'Display Name', 'Description', 'Created Date Time', 'Mail',\\n 'Security Enabled', 'Mail Enabled'],\\n removeNull=True)\\n entry_context = {f'{INTEGRATION_CONTEXT_NAME}(val.ID === obj.ID)': group_outputs}\\n return human_readable, entry_context, group\",\n \"async def create_contact_group(dbcon: DBConnection, name: str, active: bool) -> str:\\n q = \\\"\\\"\\\"insert into contact_groups (name, active) values (%s, %s)\\\"\\\"\\\"\\n q_args = (name, active)\\n contact_group_id = await dbcon.operation(q, q_args)\\n return contact_group_id\",\n \"def test_create_group_409(self):\\n request = {\\n 'name': self.test_group1_groupid\\n }\\n # First create a group indirectly by making a user with a group\\n resp = self.app.post('/users', data=json.dumps(self.test_user1_data))\\n assert resp.status_code == 200\\n\\n # Now create a group that is already there\\n resp = self.app.post('/groups', data=json.dumps(request))\\n assert resp.status_code == 409\",\n \"def createGroup(self):\\n return _libsbml.ListOfGroups_createGroup(self)\",\n \"def make_custom_group(self, qid, name='', path='', attrs={}):\\n gslash = \\\"/\\\"\\n sdef, name, path = self.get_custom_node_info(qid, gslash, name, path) \\n parent = None # no parent since this node created from File object (top level)\\n grp = Group(self, sdef, name, path, attrs, parent)\\n return grp\",\n \"def make_group(self, qid, name='', path='', attrs={}, link='', abort=True):\\n gqid = qid + \\\"/\\\"\\n sdef = self.get_sdef(gqid, self.default_ns, \\\"referenced in make_group\\\")\\n id = sdef['id']\\n ns = sdef['ns']\\n path = self.deduce_path(id, ns, path)\\n if not abort:\\n id_noslash = id.rstrip('/') # could be different from gqid if namespace present\\n grp = self.get_existing_group(path, id_noslash, name)\\n if grp:\\n # found already existing group\\n return grp \\n link_info = self.extract_link_info(name, link, Group)\\n # create the group\\n parent = None # no parent since this node created from File object (top level)\\n grp = Group(self, sdef, name, path, attrs, parent, link_info)\\n return grp\",\n \"def post(self, request, *args, **kwargs):\\n\\n task_log, fund_source = get_task_log_and_fund_source(kwargs['workspace_id'])\\n\\n async_create_expense_groups(kwargs['workspace_id'], fund_source, task_log)\\n\\n return Response(status=status.HTTP_200_OK)\",\n \"def add_group(self,groupname):\\n\\n if not self.check_prereqs():\\n raise StopIteration\\n\\n db = self.env.get_db_cnx()\\n cursor = db.cursor()\\n\\n query=self.create_query(self.sql_add_group_query,{'groupname':groupname,'groupname_field':self.sql_groupname_field})\\n self.log.debug(\\\"sqlflexibleauthstore: add_group: %s\\\" % (query,))\\n\\n cursor.execute(query)\\n if cursor.rowcount > 0:\\n db.commit()\\n return True\\n return False\",\n \"def create_test_portgroup(**kw):\\n portgroup = get_test_portgroup(**kw)\\n # Let DB generate ID if it isn't specified explicitly\\n if 'id' not in kw:\\n del portgroup['id']\\n dbapi = db_api.get_instance()\\n return dbapi.create_portgroup(portgroup)\",\n \"def async_create_group_entity(\\n hass: HomeAssistant,\\n name: str,\\n entity_ids: Collection[str] | None = None,\\n user_defined: bool = True,\\n icon: str | None = None,\\n object_id: str | None = None,\\n mode: bool | None = None,\\n order: int | None = None,\\n ) -> Group:\\n if order is None:\\n hass.data.setdefault(GROUP_ORDER, 0)\\n order = hass.data[GROUP_ORDER]\\n # Keep track of the group order without iterating\\n # every state in the state machine every time\\n # we setup a new group\\n hass.data[GROUP_ORDER] += 1\\n\\n group = Group(\\n hass,\\n name,\\n order=order,\\n icon=icon,\\n user_defined=user_defined,\\n entity_ids=entity_ids,\\n mode=mode,\\n )\\n\\n group.entity_id = async_generate_entity_id(\\n ENTITY_ID_FORMAT, object_id or name, hass=hass\\n )\\n\\n return group\",\n \"def create_group(self, name) -> \\\"GroupBase\\\":\\n ancestor, group_names, last_name = self._descend(name)\\n parent = ancestor._require_descendant_groups(*group_names)\\n if last_name in parent:\\n raise FileExistsError(f\\\"Group or dataset found at '{name}'\\\")\\n return parent._create_child_group(last_name)\",\n \"def create_dataset(request: CreateDatasetRequest) -> CreateDatasetResponse:\\n assert isinstance(request, CreateDatasetRequest)\\n\\n create_privacy_group_if_not_exists(\\n privacy_group_id=str(request.privacy_group_id),\\n privacy_group_name=request.privacy_group_name,\\n description=request.description,\\n in_use=True,\\n fetcher_active=request.fetcher_active,\\n matcher_active=request.matcher_active,\\n write_back=request.write_back,\\n )\\n\\n return CreateDatasetResponse(\\n response=f\\\"Created dataset {request.privacy_group_id}\\\"\\n )\",\n \"def test_create_resource_group(self):\\n pass\"\n]"},"negative_scores":{"kind":"list like","value":["0.7186179","0.71604204","0.7018895","0.679185","0.6695333","0.661491","0.6580392","0.6452021","0.64109707","0.64004433","0.6369519","0.63523793","0.6294868","0.628068","0.6277388","0.62702346","0.6215326","0.6186225","0.61719334","0.6139862","0.61309004","0.6128545","0.6117724","0.6116714","0.61166877","0.6114094","0.61130893","0.61098534","0.6097828","0.60967726","0.60910565","0.60856557","0.60209066","0.5993855","0.5961947","0.5955662","0.59547627","0.5951312","0.5948155","0.5934469","0.5928412","0.59261185","0.59146506","0.5907985","0.590323","0.5900247","0.5897385","0.5890283","0.5878735","0.5877304","0.58734035","0.58618337","0.5841242","0.5829357","0.5818993","0.58050513","0.57855034","0.5769989","0.57687587","0.57674813","0.57602143","0.5749873","0.57495475","0.5748384","0.5738509","0.57288253","0.57278144","0.572261","0.5706104","0.5689989","0.5689505","0.56874144","0.56719726","0.565817","0.56463003","0.56463003","0.5642606","0.5642302","0.56399184","0.5628184","0.56101185","0.5581777","0.5573728","0.55523866","0.5550261","0.55469614","0.5533662","0.5522931","0.5514987","0.55103326","0.55030173","0.55012363","0.5501194","0.5493946","0.5490748","0.5488968","0.54805857","0.5479473","0.54778916","0.5474399"],"string":"[\n \"0.7186179\",\n \"0.71604204\",\n \"0.7018895\",\n \"0.679185\",\n \"0.6695333\",\n \"0.661491\",\n \"0.6580392\",\n \"0.6452021\",\n \"0.64109707\",\n \"0.64004433\",\n \"0.6369519\",\n \"0.63523793\",\n \"0.6294868\",\n \"0.628068\",\n \"0.6277388\",\n \"0.62702346\",\n \"0.6215326\",\n \"0.6186225\",\n \"0.61719334\",\n \"0.6139862\",\n \"0.61309004\",\n \"0.6128545\",\n \"0.6117724\",\n \"0.6116714\",\n \"0.61166877\",\n \"0.6114094\",\n \"0.61130893\",\n \"0.61098534\",\n \"0.6097828\",\n \"0.60967726\",\n \"0.60910565\",\n \"0.60856557\",\n \"0.60209066\",\n \"0.5993855\",\n \"0.5961947\",\n \"0.5955662\",\n \"0.59547627\",\n \"0.5951312\",\n \"0.5948155\",\n \"0.5934469\",\n \"0.5928412\",\n \"0.59261185\",\n \"0.59146506\",\n \"0.5907985\",\n \"0.590323\",\n \"0.5900247\",\n \"0.5897385\",\n \"0.5890283\",\n \"0.5878735\",\n \"0.5877304\",\n \"0.58734035\",\n \"0.58618337\",\n \"0.5841242\",\n \"0.5829357\",\n \"0.5818993\",\n \"0.58050513\",\n \"0.57855034\",\n \"0.5769989\",\n \"0.57687587\",\n \"0.57674813\",\n \"0.57602143\",\n \"0.5749873\",\n \"0.57495475\",\n \"0.5748384\",\n \"0.5738509\",\n \"0.57288253\",\n \"0.57278144\",\n \"0.572261\",\n \"0.5706104\",\n \"0.5689989\",\n \"0.5689505\",\n \"0.56874144\",\n \"0.56719726\",\n \"0.565817\",\n \"0.56463003\",\n \"0.56463003\",\n \"0.5642606\",\n \"0.5642302\",\n \"0.56399184\",\n \"0.5628184\",\n \"0.56101185\",\n \"0.5581777\",\n \"0.5573728\",\n \"0.55523866\",\n \"0.5550261\",\n \"0.55469614\",\n \"0.5533662\",\n \"0.5522931\",\n \"0.5514987\",\n \"0.55103326\",\n \"0.55030173\",\n \"0.55012363\",\n \"0.5501194\",\n \"0.5493946\",\n \"0.5490748\",\n \"0.5488968\",\n \"0.54805857\",\n \"0.5479473\",\n \"0.54778916\",\n \"0.5474399\"\n]"},"document_score":{"kind":"string","value":"0.71613544"},"document_rank":{"kind":"string","value":"1"}}},{"rowIdx":8575,"cells":{"query":{"kind":"string","value":"Creates a new group in your tenancy. You must specify your tenancy's OCID as the compartment ID in the request object (remember that the tenancy is simply the root compartment). Notice that IAM resources (users, groups, compartments, and some policies) reside within the tenancy itself, unlike cloud resources such as compute instances, which typically reside within compartments inside the tenancy. For information about OCIDs, see `Resource Identifiers`__. You must also specify a name for the group, which must be unique across all groups in your tenancy and cannot be changed. You can use this name or the OCID when writing policies that apply to the group. For more information about policies, see `How Policies Work`__. You must also specify a description for the group (although it can be an empty string). It does not"},"document":{"kind":"string","value":"def create_group(self, create_group_details, **kwargs):\n resource_path = \"/groups\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_group got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_group_details,\n response_type=\"Group\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_group_details,\n response_type=\"Group\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_group(group_id, group_name):\n\n kwargs = config.DEFAULT_REST_KWARGS\n kwargs[\"data\"] = {\"id\": group_id, \"name\": group_name}\n http_response = call_rest_api(\"/identities/groups/\", \"post\", **kwargs)\n if http_response.status_code != 201: # 201 = 'new group created'\n raise ValueError(http_response.text)\n logger.log(f\"New custom group, {group_name}, with ID: {group_id}, was created successfully.\")","def create_group():\n groupname = request.get_json().get(\"name\")\n description = request.get_json().get(\"description\")\n grp = admin.create_group(current_app.scoped_session(), groupname, description)\n if grp:\n response = admin.get_group_info(current_app.scoped_session(), groupname)\n else:\n response = {\"result\": \"group creation failed\"}\n response = jsonify(response)\n return response","def create_group(self, **kwargs):\n post_body = json.dumps({'group': kwargs})\n resp, body = self.post('groups', post_body)\n self.expected_success(201, resp.status)\n body = json.loads(body)\n return rest_client.ResponseBody(resp, body)","def create_group(self, groupname):\n data = {\"groupname\": groupname}\n headers = {\"user-agent\": self.u_agent}\n req_url = self.normalize_admin_url(\"groups\")\n res = requests.post(\n req_url,\n headers=headers,\n auth=self.auth,\n data=json.dumps(data),\n verify=False,\n )\n if res.status_code == 201:\n return Response(0, u\"Group {} has been created\".format(groupname))\n else:\n return Response(res.status_code, res)","def create_group(self, group_name, group_type):\n grp_data = {\"name\": group_name, \"type\": group_type}\n return requests.post(self.groups_url, data=json.dumps(grp_data),\n headers=self.headers)","def product_group_create(obj, name, department):\n client = get_client(obj)\n\n with Action('Creating product_group: {}'.format(name), nl=True):\n pg = client.product_group_create(name, department)\n\n print(json.dumps(pg, indent=4))","def create_group(self, event):\n body = event['body']\n body = json.loads(body)\n\n # Required field in POST body\n if 'group_name' not in body:\n return self.get_bad_request('POST body missing group_name')\n\n group_name = body['group_name']\n user = self.mealShareUsers.get_user_cognito_data(event)\n user_id = user['user_id']\n \n # Add the creator to the group, as the initial member\n group_id = self.mealShareGroups.create_group(group_name)\n success = self.mealShareGroups.add_user_to_group(user_id, group_id)\n if success:\n return {\n 'statusCode': 200,\n 'statusMessage': 'Successfully created group {} with ID {}'.format(group_name, group_id),\n 'group_id': group_id,\n 'group_name': group_name,\n 'user_id': user_id\n }\n else:\n return {\n 'statusCode': 500,\n 'statusMessage': 'FAILED to create group {} by user {}'.format(group_name, user_id),\n 'group_id': group_id,\n 'group_name': group_name,\n 'user_id': user_id\n }","def create_group(self, name):\n\t\tdata = {\"name\":name}\n\t\tresponse = self.client.post(self._endpoint + \"/group\", content=data)\n\t\treturn Group(\n\t\t\tresponse.json['group_id'],\n\t\t\tself.user_id,\n\t\t\tself.site_id,\n\t\t\tdata=response.json\n\t\t)","def test_create_group(self):\n groupid = 'villains'\n\n # create the group\n resp = self.app.post('/groups', data=json.dumps({'name':groupid}))\n assert resp.status_code == 200\n\n # Fetch the group to check that it persists\n resp = self.app.get('/groups/{}'.format(groupid))\n assert resp.status_code == 200","def __create_new_group(self, group_name) -> None:\n group = Group(name=group_name)\n group.save()\n\n self.__add_permission_to_group(group)","def CreateGroup(self, name, alloc_policy=None, dry_run=False, reason=None):\n query = []\n _AppendDryRunIf(query, dry_run)\n _AppendReason(query, reason)\n\n body = {\n \"name\": name,\n \"alloc_policy\": alloc_policy,\n }\n\n return self._SendRequest(HTTP_POST, \"/%s/groups\" % GANETI_RAPI_VERSION,\n query, body)","async def create(\n self,\n resource_group_name: str,\n project_name: str,\n group_name: str,\n group: Optional[\"models.Group\"] = None,\n **kwargs\n ) -> \"models.Group\":\n cls = kwargs.pop('cls', None) # type: ClsType[\"models.Group\"]\n error_map = {\n 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError\n }\n error_map.update(kwargs.pop('error_map', {}))\n api_version = \"2018-06-01\"\n content_type = kwargs.pop(\"content_type\", \"application/json\")\n accept = \"application/json\"\n\n # Construct URL\n url = self.create.metadata['url'] # type: ignore\n path_format_arguments = {\n 'subscriptionId': self._serialize.url(\"self._config.subscription_id\", self._config.subscription_id, 'str'),\n 'resourceGroupName': self._serialize.url(\"resource_group_name\", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\\w\\._\\(\\)]+$'),\n 'projectName': self._serialize.url(\"project_name\", project_name, 'str'),\n 'groupName': self._serialize.url(\"group_name\", group_name, 'str'),\n }\n url = self._client.format_url(url, **path_format_arguments)\n\n # Construct parameters\n query_parameters = {} # type: Dict[str, Any]\n query_parameters['api-version'] = self._serialize.query(\"api_version\", api_version, 'str')\n\n # Construct headers\n header_parameters = {} # type: Dict[str, Any]\n header_parameters['Content-Type'] = self._serialize.header(\"content_type\", content_type, 'str')\n header_parameters['Accept'] = self._serialize.header(\"accept\", accept, 'str')\n\n body_content_kwargs = {} # type: Dict[str, Any]\n if group is not None:\n body_content = self._serialize.body(group, 'Group')\n else:\n body_content = None\n body_content_kwargs['content'] = body_content\n request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs)\n pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)\n response = pipeline_response.http_response\n\n if response.status_code not in [200, 201]:\n map_error(status_code=response.status_code, response=response, error_map=error_map)\n raise HttpResponseError(response=response, error_format=ARMErrorFormat)\n\n response_headers = {}\n if response.status_code == 200:\n response_headers['x-ms-request-id']=self._deserialize('str', response.headers.get('x-ms-request-id'))\n deserialized = self._deserialize('Group', pipeline_response)\n\n if response.status_code == 201:\n response_headers['x-ms-request-id']=self._deserialize('str', response.headers.get('x-ms-request-id'))\n deserialized = self._deserialize('Group', pipeline_response)\n\n if cls:\n return cls(pipeline_response, deserialized, response_headers)\n\n return deserialized","def create_security_group(self, body=None):\r\n return self.post(self.security_groups_path, body=body)","def create():\n name = request.json['name']\n level = request.json['level']\n manager = request.json['manager']\n if models.user.Group.get(name):\n raise Conflict('Group already exists.', creation=False)\n else:\n authorize(manager, level=level)\n group = models.user.Group(name=name, level=level, manager=manager)\n models.db.session.add(group)\n models.db.session.commit()\n return response(200, creation=True)","def create_group(\n self,\n name,\n group,\n validate_only=None,\n retry=google.api_core.gapic_v1.method.DEFAULT,\n timeout=google.api_core.gapic_v1.method.DEFAULT,\n metadata=None,\n ):\n if metadata is None:\n metadata = []\n metadata = list(metadata)\n # Wrap the transport method to add retry and timeout logic.\n if \"create_group\" not in self._inner_api_calls:\n self._inner_api_calls[\n \"create_group\"\n ] = google.api_core.gapic_v1.method.wrap_method(\n self.transport.create_group,\n default_retry=self._method_configs[\"CreateGroup\"].retry,\n default_timeout=self._method_configs[\"CreateGroup\"].timeout,\n client_info=self._client_info,\n )\n\n request = group_service_pb2.CreateGroupRequest(\n name=name, group=group, validate_only=validate_only,\n )\n if metadata is None:\n metadata = []\n metadata = list(metadata)\n try:\n routing_header = [(\"name\", name)]\n except AttributeError:\n pass\n else:\n routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(\n routing_header\n )\n metadata.append(routing_metadata)\n\n return self._inner_api_calls[\"create_group\"](\n request, retry=retry, timeout=timeout, metadata=metadata\n )","def create(self, group_name):\n METHOD = 'POST'\n API_PATH = '/groups/create'\n\n data = {'group_name': group_name}\n\n # Make REST call\n resp = self._rest_call[METHOD](API_PATH, data=data)\n if resp.status_code == 200:\n return resp.json()\n\n elif resp.status_code == 403:\n raise AuthorizationError(\"User is not authorized or token is incorrect.\")\n\n else:\n if resp.json().get(\"error_code\") in ERROR_CODES:\n raise ERROR_CODES[resp.json().get('error_code')](resp.json().get('message'))\n else:\n raise APIError(\"Response code {0}: {1} {2}\".format(resp.status_code,\n resp.json().get('error_code'),\n resp.json().get('message')))","def create_namespaced_group(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_group\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_group`\")\n\n resource_path = '/oapi/v1/groups'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Group',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def test_createGroup(self):\n\t\tself.client.force_authenticate(user=User.objects.get(id=1))\n\t\turl = \"/groups/\"\n\t\tdata = {\n\t\t\t'name' : 'testGroup3',\n\t\t\t'description' : 'This is another test group that just created.',\n\t\t\t'isPublic' : True\n\t\t}\n\t\tresponse = self.client.post(url, data, format='json')\n\t\tself.assertEqual(response.status_code, status.HTTP_201_CREATED)\n\t\tself.assertEqual(response.data[\"id\"], 3)\n\t\tself.assertEqual(response.data[\"name\"], 'testGroup3')","async def create_group(ctx, name: str, role: str, group_type: str=None, comp: str=None, rating: int=None, time: str=None):\n\n owner = ctx.message.author.name\n \n if comp:\n comp = [int(i) for i in comp.split()] # convert string input to array\n\n new_group = Group(owner, name, role, group_type, rating, time, comp)\n bg_bot.manager.add_group(owner, new_group)\n \n await ctx.send(f'Created new {group_type} group for leader {owner}!')","def create(self, name, desc, tenant_id):\n data = {\"security_group\": {\"name\": name, \n \"description\": desc, \n \"tenant_id\":tenant_id}}\n\n path = '%s/security-groups' % self.ver\n res = self.client.call(path, 'POST', data=json.dumps(data), \n token=self.manager.identity.token)\n self.logger.debug('Create openstack security group: %s' % truncate(res))\n return res[0]['security_group']","def createGroup(self, name):\n new_group = ET.SubElement(self._root,'group')\n group_name = ET.SubElement(new_group, 'name')\n group_name.text = name\n # update the document's groups\n self._groups = self._root.findall('group') \n print 'Creating group, \\'%s\\'' % name\n return CAGroup(new_group)","def create_group(self, identifier: str, group_name: str) -> Group:\n\n # APM-137701 - Namespace for custom device calculation should not be set\n group_id = get_group_id(\"\", identifier)\n if group_id in self._groups:\n raise ValueError(\"Group \" + group_name + \" already exist, id: \" + str(group_id))\n else:\n group = Group(group_id, group_name, self._technologies, self._results_builder)\n\n self._groups[group_id] = group\n return group","def add_group():\n name = request.form['name']\n data, code, message = FIELD_SERVICE.add_group(name)\n return __result(data, code, message)","def create_placement_group(self, name, strategy='cluster'):\r\n params = {'GroupName':name, 'Strategy':strategy}\r\n group = self.get_status('CreatePlacementGroup', params, verb='POST')\r\n return group","def security_group_create(auth=None, **kwargs):\n cloud = get_operator_cloud(auth)\n kwargs = _clean_kwargs(keep_name=True, **kwargs)\n return cloud.create_security_group(**kwargs)","def create_new_group(self, group_id, poll_id, name):\n obj = self.table()\n obj.group_id = str(group_id)\n obj.poll_id = poll_id\n obj.name = name\n self.db.session.add(obj)\n self.db.session.commit()","def create_group(self, group):\n if self.dryrun:\n self.logger.info(\"Would create group %s\", group)\n return FakeGroupId()\n result = self.conn.usergroup.create(name=group)\n groupid = result['usrgrpids'][0]\n self.logger.info(\"Create group %s with id %s\", group, groupid)\n return groupid","def createGroup(self, *group):\n if not self.rank:\n logging.info('Creating atom group {}'.format(group))\n\n if not len(group):\n for idSS in self.pargs['idSS']:\n self.lmp.command('group group{} type {}'.format(idSS, idSS))\n else:\n self.lmp.command('group ' + ('{} ' * len(group)).format(*group))","def create_group(self, group_name, user_ids=[], role_ids=[]):\n payload = {}\n payload['name'] = group_name\n payload['user_ids'] = user_ids\n payload['role_ids'] = role_ids\n return Client._post(self, payload)","def groups_create(self, mar, request):\n if not permissions.CanCreateGroup(mar.perms):\n raise permissions.PermissionException(\n 'The user is not allowed to create groups.')\n\n user_dict = self._services.user.LookupExistingUserIDs(\n mar.cnxn, [request.groupName])\n if request.groupName.lower() in user_dict:\n raise exceptions.GroupExistsException(\n 'group %s already exists' % request.groupName)\n\n if request.ext_group_type:\n ext_group_type = str(request.ext_group_type).lower()\n else:\n ext_group_type = None\n group_id = self._services.usergroup.CreateGroup(\n mar.cnxn, self._services, request.groupName,\n str(request.who_can_view_members).lower(),\n ext_group_type)\n\n return api_pb2_v1.GroupsCreateResponse(\n groupID=group_id)","def create(self, body: CloudSecurityGroup) -> Dict:\n\t\treturn self._post(route=AWSSecurityGroupConsts.CLOUD_SECURITY_GROUP.value, body=body)","def request_group_create():\n return Response(render_template('admin/group/create-update.html',\n csrf_token=(\n get_raw_jwt() or {}).get(\"csrf\"),\n target=\"/admin/group/create\"),\n mimetype='text/html')","def capacitygroup_create(cmd_ctx, cpc, **options):\n cmd_ctx.execute_cmd(\n lambda: cmd_capacitygroup_create(cmd_ctx, cpc, options))","def post(self):\n args = parser.parse_args()\n user_group = UserGroup()\n user_group.name = args['name']\n user_group.createdby = auth.username()\n db_session.add(user_group)\n db_session.commit()\n return user_group, 201","def newgroup(self, groupname, groupou=None, grouptype=None,\n description=None, mailaddress=None, notes=None, sd=None,\n gidnumber=None, nisdomain=None):\n\n group_dn = \"CN=%s,%s,%s\" % (groupname, (groupou or \"CN=Users\"), self.domain_dn())\n\n # The new user record. Note the reliance on the SAMLDB module which\n # fills in the default informations\n ldbmessage = {\"dn\": group_dn,\n \"sAMAccountName\": groupname,\n \"objectClass\": \"group\"}\n\n if grouptype is not None:\n ldbmessage[\"groupType\"] = normalise_int32(grouptype)\n\n if description is not None:\n ldbmessage[\"description\"] = description\n\n if mailaddress is not None:\n ldbmessage[\"mail\"] = mailaddress\n\n if notes is not None:\n ldbmessage[\"info\"] = notes\n\n if gidnumber is not None:\n ldbmessage[\"gidNumber\"] = normalise_int32(gidnumber)\n\n if nisdomain is not None:\n ldbmessage[\"msSFU30Name\"] = groupname\n ldbmessage[\"msSFU30NisDomain\"] = nisdomain\n\n if sd is not None:\n ldbmessage[\"nTSecurityDescriptor\"] = ndr_pack(sd)\n\n self.add(ldbmessage)","def post_groups(\n data: PostGroupIn, tkn: Token = Depends(from_authotization_header_nondyn),\n):\n assert_has_clearance(tkn.owner, \"sni.create_group\")\n grp = Group(\n description=data.description,\n members=[tkn.owner],\n group_name=data.group_name,\n owner=tkn.owner,\n ).save()\n logging.debug(\n \"Created group %s (%s) owned by %s\",\n data.group_name,\n str(grp.pk),\n tkn.owner.character_name,\n )\n return GetGroupOut.from_record(grp)","def createGroup(self):\n return _libsbml.GroupsModelPlugin_createGroup(self)","def create_secgroup(self, args):\n message = MessageClass()\n region = args[\"Region\"]\n sgid = args[\"Group-Name\"]\n desc = args[\"Description\"]\n\n # Boto3 client creation by providing the access_id and access_secret\n ec2 = boto3.client(service_name='ec2', region_name=region, api_version=None, use_ssl=True,\n verify=None, endpoint_url=None, aws_access_key_id=self.aws_access_key,\n aws_secret_access_key=self.aws_secret_token, aws_session_token=None,\n config=None)\n response = ec2.describe_vpcs()\n vpc_id = response.get('Vpcs', [{}])[0].get('VpcId', '')\n\n response = ec2.create_security_group(GroupName=sgid,\n Description=desc,\n VpcId=vpc_id)\n attachment = MessageAttachmentsClass()\n d = response[\"GroupId\"]\n attachment.title = d\n message.message_text = \"Security group created:\"\n message.attach(attachment)\n\n return message.to_json()","def create_adgroup(self, account_id, name, campaign_id,\n creative_id, bid_type=None, bid_info=None, max_bid=None,\n tracking_specs=None, view_tags=None, objective=None,\n adgroup_status=None, targeting=None, conversion_specs=None, batch=False):\n path = 'act_%s/adgroups' % account_id\n args = {\n 'name': name,\n 'campaign_id': campaign_id,\n 'creative': json.dumps({'creative_id': creative_id}),\n }\n if bid_type:\n args['bid_type'] = bid_type\n if max_bid:\n # can only use max_bid with CPM bidding\n args['max_bid'] = max_bid\n elif bid_info:\n args['bid_info'] = json.dumps(bid_info)\n\n if tracking_specs:\n args['tracking_specs'] = json.dumps(tracking_specs)\n if view_tags:\n args['view_tags'] = json.dumps(view_tags)\n if objective:\n args['objective'] = objective\n if adgroup_status:\n args['adgroup_status'] = adgroup_status\n if targeting:\n args['targeting'] = json.dumps(targeting)\n if conversion_specs:\n args['conversion_specs'] = json.dumps(conversion_specs)\n return self.make_request(path, 'POST', args, batch=batch)","def create_group_with_http_info(self, bucket_id, group, **kwargs):\n\n all_params = ['bucket_id', 'group', 'if_match', 'if_none_match']\n all_params.append('callback')\n all_params.append('_return_http_data_only')\n all_params.append('_preload_content')\n all_params.append('_request_timeout')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_group\" % key\n )\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'bucket_id' is set\n if ('bucket_id' not in params) or (params['bucket_id'] is None):\n raise ValueError(\"Missing the required parameter `bucket_id` when calling `create_group`\")\n # verify the required parameter 'group' is set\n if ('group' not in params) or (params['group'] is None):\n raise ValueError(\"Missing the required parameter `group` when calling `create_group`\")\n\n if 'if_match' in params and not re.search('\\\\\\\"[0-9]+\\\\\\\"', params['if_match']):\n raise ValueError(\"Invalid value for parameter `if_match` when calling `create_group`, must conform to the pattern `/\\\\\\\"[0-9]+\\\\\\\"/`\")\n if 'if_none_match' in params and not re.search('\\\\\\\"[0-9]+\\\\\\\"', params['if_none_match']):\n raise ValueError(\"Invalid value for parameter `if_none_match` when calling `create_group`, must conform to the pattern `/\\\\\\\"[0-9]+\\\\\\\"/`\")\n\n collection_formats = {}\n\n resource_path = '/buckets/{bucket_id}/groups'.replace('{format}', 'json')\n path_params = {}\n if 'bucket_id' in params:\n path_params['bucket_id'] = params['bucket_id']\n\n query_params = {}\n\n header_params = {}\n if 'if_match' in params:\n header_params['If-Match'] = params['if_match']\n if 'if_none_match' in params:\n header_params['If-None-Match'] = params['if_none_match']\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'group' in params:\n body_params = params['group']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['application/json'])\n\n # Authentication setting\n auth_settings = ['basicAuth']\n\n return self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='Group',\n auth_settings=auth_settings,\n callback=params.get('callback'),\n _return_http_data_only=params.get('_return_http_data_only'),\n _preload_content=params.get('_preload_content', True),\n _request_timeout=params.get('_request_timeout'),\n collection_formats=collection_formats)","def test_create_group(self):\n pass","def test_create_group(self):\n pass","def new_group(request):\n return edit_group(request, None)","def create(person_group_id, name=None, user_data=None):\n name = person_group_id if name is None else name\n url = 'persongroups/{}'.format(person_group_id)\n json = {\n 'name': name,\n 'userData': user_data,\n }\n\n return util.request('PUT', url, json=json)","def create_ad_group(client, customer_id, campaign_resource_name):\n ad_group_service = client.get_service(\"AdGroupService\")\n\n # Creates the ad group.\n # Note that the ad group type must not be set.\n # Since the advertising_channel_sub_type is APP_CAMPAIGN,\n # 1- you cannot override bid settings at the ad group level.\n # 2- you cannot add ad group criteria.\n ad_group_operation = client.get_type(\"AdGroupOperation\")\n ad_group = ad_group_operation.create\n ad_group.name = f\"Earth to Mars cruises {uuid4()}\"\n ad_group.status = client.enums.AdGroupStatusEnum.ENABLED\n ad_group.campaign = campaign_resource_name\n\n ad_group_response = ad_group_service.mutate_ad_groups(\n customer_id=customer_id, operations=[ad_group_operation]\n )\n\n ad_group_resource_name = ad_group_response.results[0].resource_name\n print(f'Ad Group created with resource name: \"{ad_group_resource_name}\".')\n return ad_group_resource_name","def _assert_create_group(self, personality, response=400):\n group_response = self.autoscale_behaviors.create_scaling_group_given(\n lc_personality=personality)\n self.assertEquals(group_response.status_code, response, msg='Create group '\n 'with invalid lc_personality returned {0} as against '\n '{1}'.format(group_response.status_code, response))\n if response is 200:\n group = group_response.entity\n self.resources.add(group, self.empty_scaling_group)\n return group","def create_group_command(client: MsGraphClient, args: dict) -> tuple[str, dict, dict]:\n required_properties = {\n 'displayName': str(args.get('display_name')),\n 'mailNickname': str(args.get('mail_nickname')),\n 'mailEnabled': args.get('mail_enabled') == 'true',\n 'securityEnabled': args.get('security_enabled')\n }\n\n # create the group\n group = client.create_group(required_properties)\n\n # display the new group and it's properties\n group_readable, group_outputs = parse_outputs(group)\n human_readable = tableToMarkdown(name=f\"{required_properties['displayName']} was created successfully:\",\n t=group_readable,\n headers=['ID', 'Display Name', 'Description', 'Created Date Time', 'Mail',\n 'Security Enabled', 'Mail Enabled'],\n removeNull=True)\n entry_context = {f'{INTEGRATION_CONTEXT_NAME}(val.ID === obj.ID)': group_outputs}\n return human_readable, entry_context, group","def create_TestGroup(test_case, # type: AnyMagpieTestCaseType\n override_group_name=null, # type: Optional[Str]\n override_discoverable=null, # type: Optional[bool]\n override_data=null, # type: Optional[JSON]\n override_headers=null, # type: Optional[HeadersType]\n override_cookies=null, # type: Optional[CookiesType]\n ): # type: (...) -> JSON\n app_or_url = get_app_or_url(test_case)\n data = override_data\n if override_data is null:\n data = {\"group_name\": override_group_name if override_group_name is not null else test_case.test_group_name}\n # only add 'discoverable' if explicitly provided here to preserve original behaviour of 'no value provided'\n if override_discoverable is not null:\n data[\"discoverable\"] = override_discoverable\n grp_name = (data or {}).get(\"group_name\")\n if grp_name:\n test_case.extra_group_names.add(grp_name) # indicate potential removal at a later point\n resp = test_request(app_or_url, \"POST\", \"/groups\", json=data,\n headers=override_headers if override_headers is not null else test_case.json_headers,\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\n return check_response_basic_info(resp, 201, expected_method=\"POST\")","def create_group():\n incoming = request.get_json()\n chatroom = Chatroom(\n name = incoming['name'],\n tag = incoming['tag'],\n )\n db.session.add(chatroom)\n db.session.commit()\n participant = Participant(\n user_id = session['user_id'],\n room_id = chatroom.room_id,\n )\n db.session.add(participant)\n db.session.commit()\n return jsonify(results = chatroom.room_id)","def create_group(self, properties: dict[str, Any | None]) -> dict:\n group = self.ms_client.http_request(method='POST', url_suffix='groups', json_data=properties)\n return group","def allocate_group(remote, objectid):\n cmd1 = mmapi.StoredCommands()\n key1 = cmd1.AppendSceneCommand_AllocateNewGroupID(objectid)\n remote.runCommand(cmd1)\n result_val = mmapi.any_result()\n cmd1.GetSceneCommandResult_AllocateNewGroupID(key1, result_val)\n return result_val.i","def create(\n self, draft: CustomerGroupDraft, *, expand: OptionalListStr = None\n ) -> CustomerGroup:\n params = self._serialize_params({\"expand\": expand}, traits.ExpandableSchema)\n return self._client._post(\n endpoint=\"customer-groups\",\n params=params,\n data_object=draft,\n response_class=CustomerGroup,\n )","def create_security_group(self, name, description, vpc_id=None):\r\n params = {\r\n 'GroupName': name,\r\n 'GroupDescription': description\r\n }\r\n\r\n if vpc_id is not None:\r\n params['VpcId'] = vpc_id\r\n\r\n group = self.get_object('CreateSecurityGroup', params,\r\n SecurityGroup, verb='POST')\r\n group.name = name\r\n group.description = description\r\n return group","def create_security_group(group_name):\n ec2 = boto.ec2.connect_to_region(AWS_REGION)\n for g in ec2.get_all_security_groups():\n if g.name == group_name:\n return # We already have this group setup\n group = ec2.create_security_group(group_name,\n \"%s SSH access group\" % group_name)\n group.authorize(\"tcp\", 22, 22, \"0.0.0.0/0\") # SSH is on port 22, all IPs\n group.authorize(\"tcp\", 80, 80, \"0.0.0.0/0\")\n group.authorize(\"tcp\", 61000, 65000, \"0.0.0.0/0\")\n print \"Created new security group\"","def create_group(name, nodes, description=None):\n group, created = Group.get_or_create(name=name)\n if created:\n print('Group created with PK={} and name {}'.format(group.pk, group.name))\n else:\n print('Group with name {} and pk {} already exists. Do you want to add nodes?[y/n]'.format(group.name, group.pk))\n answer = raw_input()\n if answer.strip().lower() == 'y':\n pass\n else:\n return\n nodes2 = []\n nodes2_pks = []\n for node in nodes:\n try:\n node = int(node)\n except ValueError:\n pass\n nodes2_pks.append(node)\n try:\n nodes2.append(load_node(node))\n except:# NotExistentError:\n pass\n\n group.add_nodes(nodes2)\n print('added nodes: {} to group {} {}'.format(nodes2_pks, group.name, group.pk))\n\n if description:\n group.description = description\n\n return group","def create(self, context=None):\n values = self.obj_get_changes()\n db_nodegroup = self.dbapi.create_nodegroup(values)\n self._from_db_object(self, db_nodegroup)","async def async_create_group(\n hass: HomeAssistant,\n name: str,\n entity_ids: Collection[str] | None = None,\n user_defined: bool = True,\n icon: str | None = None,\n object_id: str | None = None,\n mode: bool | None = None,\n order: int | None = None,\n ) -> Group:\n group = Group.async_create_group_entity(\n hass, name, entity_ids, user_defined, icon, object_id, mode, order\n )\n\n # If called before the platform async_setup is called (test cases)\n await _async_get_component(hass).async_add_entities([group])\n return group","def create_groups(**kwargs):\n for gname in SEC_GROUP_NAMES.itervalues():\n Group.objects.get_or_create(name=gname)","def create(self, name, desc):\n body = {'security_group': {'name': name,\n 'description': desc,\n 'tenant_id': self.request.user.project_id}}\n secgroup = self.client.create_security_group(body)\n return SecurityGroup(secgroup.get('security_group'))","def create_rule_group(self: object,\n body: dict,\n cs_username: str = None # pylint: disable=W0613 # cs_username is deprecated\n ) -> dict:\n # [POST] https://assets.falcon.crowdstrike.com/support/api/swagger.html#/custom-ioa/create-rule-groupMixin0\n return process_service_request(\n calling_object=self,\n endpoints=Endpoints,\n operation_id=\"create_rule_groupMixin0\",\n body=body\n )","def test_create_resource_group(self):\n pass","def create_sec_group(self, conn, name, project):\n sec_group = conn.create_security_group(\n name=name, description=\"Security Group\",\n project_id=project.id)\n conn.create_security_group_rule(sec_group)\n return sec_group","def post(self):\n status = ErrorCode.SUCCESS\n try:\n data = DotDict(json_decode(self.request.body))\n logging.info(\"[UWEB] add group request: %s, cid: %s\",\n data, self.current_user.cid)\n except Exception as e:\n status = ErrorCode.ILLEGAL_DATA_FORMAT\n logging.exception(\"[UWEB] Invalid data format. body:%s, Exception: %s\",\n self.request.body, e.args)\n self.write_ret(status)\n return\n\n try: \n cid = data.cid\n name = data.name\n group = self.get_group_by_cid(cid, name)\n if group:\n status = ErrorCode.GROUP_EXIST\n self.write_ret(status)\n return\n\n group_info = dict(cid=cid,\n name=name,\n type=UWEB.GROUP_TYPE.NEW)\n gid = add_group(group_info, self.db, self.redis)\n # NOTE: wspush to client\n tid = self.current_user.tid\n if status == ErrorCode.SUCCESS:\n WSPushHelper.pushS3(tid, self.db, self.redis)\n\n self.write_ret(status,\n dict_=dict(gid=gid,\n cid=cid,\n name=name))\n\n except Exception as e:\n logging.exception(\"[UWEB] Create group failed. uid: %s, Exception: %s\",\n self.current_user.uid, e.args)\n status = ErrorCode.SERVER_BUSY\n self.write_ret(status)","def test_create_team_user_group(client):\n group = client.create_team_user_group(TEAM_ID, {\n \"name\": \"Python group\",\n \"is_reviewer\": True,\n \"is_admin\": True,\n \"admin_rights\": [\"upload\"]\n })\n assert group.team_id == TEAM_ID\n assert group.group_id == NEW_GROUP_ID\n assert group.name == \"Python group\"\n assert group.permissions['is_admin']\n assert group.permissions['is_reviewer']\n assert group.permissions['admin_rights'] == [\"upload\"]","def create_group(self, tenant_id, group_id):\n maas_client = self._get_maas_client()\n d = maas_client.add_notification_and_plan()\n\n def create_group_in_db((notification, notification_plan)):\n return cass.create_group(\n self._db, tenant_id, group_id, notification, notification_plan)\n d.addCallback(create_group_in_db)\n\n return d","def createNewGroup():\n if request.method == 'POST':\n groupname = request.form['groupname1']\n internal = request.form['internal1']\n external = request.form['external1']\n userNo = request.form['usersNo1']\n if 'node1' in request.form:\n node = int(request.form['node1'])\n else:\n node = -1\n\n if int(userNo) == 0:\n if hl.createGroup(groupname, internal, external, node):\n return True\n elif int(userNo) > 0:\n if hl.createGroup(groupname, internal, external, node, genUsers=True, numUsers=int(userNo)):\n return True\n\n return False","def create_group(self, bucket_id, group, **kwargs):\n kwargs['_return_http_data_only'] = True\n if kwargs.get('callback'):\n return self.create_group_with_http_info(bucket_id, group, **kwargs)\n else:\n (data) = self.create_group_with_http_info(bucket_id, group, **kwargs)\n return data","def create( self, trans, payload, **kwd ):\n group_dict = dict( message='', status='ok' )\n name = payload.get( 'name', '' )\n if name:\n description = payload.get( 'description', '' )\n if not description:\n description = ''\n else:\n # TODO add description field to the model\n group_dict = self.group_manager.create( trans, name=name ).to_dict( view='element', value_mapper=self.__get_value_mapper( trans ) )\n else:\n raise RequestParameterMissingException( 'Missing required parameter \"name\".' )\n return group_dict","def create_group(username: str, gid: int=None, system: bool=False) -> Result[Group]:\n try:\n group = get_group(username)\n except KeyError:\n return add_group(username, gid, system)\n else:\n if group.gr_gid != gid:\n raise ValueError(\"Group {!r} has GID {}, expected {}\"\n .format(username, group.gr_gid, gid))\n return Result(State.unchanged, group)","def create_sec_group(ec2, sec_group_name):\n sec = ec2.create_security_group(sec_group_name, 'Jvivian Boto SecGroup')\n port = 22\n sec.authorize('tcp', port, port, '0.0.0.0/0')","def __create_group(self):\n\n group = time.strftime(_GROUP_NAME_FORMAT, time.localtime())\n LOG.info(\"Creating backup group '%s'.\", group)\n\n group_path = self.group_path(group)\n\n try:\n os.mkdir(group_path)\n except EnvironmentError as e:\n if e.errno != errno.EEXIST:\n raise Error(\"Unable to create a new backup group '{}': {}.\",\n group_path, psys.e(e))\n\n self.__on_group_created(group)\n\n return group","def create_group(user):\n if connexion.request.is_json:\n users_group = [User.from_dict(d) for d in connexion.request.get_json()]\n response = (\"success\", 201)\n if len(users_group) > 4:\n response = (\"Max number of player is 4\", 400)\n else:\n groupId = GroupStorageController.add_new_group(users_group)\n return response","def create_group(self, groupname, filters=[], filter_options=[], **kwargs):\n pytan.utils.check_for_help(kwargs=kwargs)\n clean_kwargs = pytan.utils.clean_kwargs(kwargs=kwargs)\n\n filter_defs = pytan.utils.dehumanize_question_filters(question_filters=filters)\n option_defs = pytan.utils.dehumanize_question_options(question_options=filter_options)\n\n h = (\n \"Issue a GetObject to get the full object of specified sensors for inclusion in a \"\n \"group\"\n )\n filter_defs = self._get_sensor_defs(defs=filter_defs, pytan_help=h, **clean_kwargs)\n\n add_group_obj = pytan.utils.build_group_obj(\n q_filter_defs=filter_defs, q_option_defs=option_defs,\n )\n add_group_obj.name = groupname\n\n h = \"Issue an AddObject to add a Group object\"\n group_obj = self._add(obj=add_group_obj, pytan_help=h, **clean_kwargs)\n\n m = \"New group {!r} created with ID {!r}, filter text: {!r}\".format\n self.mylog.info(m(group_obj.name, group_obj.id, group_obj.text))\n return group_obj","def _make_group(self, _rk, _group_hint):\n\n if isinstance(_group_hint, dict):\n # _group_hint is a single key/value pair\n g = _group_hint[list(_group_hint)[0]]\n\n r_type = g.get(\"type\", \"none\")\n if r_type != \"OS::Nova::ServerGroup\":\n return \"support only ServerGroup resource\"\n\n properties = g.get(\"properties\", {})\n if len(properties) == 0:\n return \"no properties\"\n\n group_name = properties.get(\"name\", None)\n if group_name is None:\n return \"no group name\"\n group_name = group_name.strip()\n\n policies = properties.get(\"policies\", [])\n if len(policies) == 0:\n return \"no policy of the group\"\n\n if len(policies) > 1:\n return \"multiple policies\"\n\n # TODO: exclude soft-affinity and soft-anti-affinity?\n\n if group_name in self.groups.keys():\n group = self.groups[group_name]\n else:\n group = Group(group_name)\n\n policy = policies[0].strip()\n if policy == \"anti-affinity\":\n group_type = \"diversity\"\n else:\n group_type = policy\n\n group.group_type = group_type\n group.factory = \"server-group\"\n group.level = \"host\"\n\n self.groups[group_name] = group\n else:\n # group hint is uuid string.\n rg = self.resource.get_group_by_uuid(_group_hint)\n if rg is None:\n return \"unknown group found while making group\"\n\n # TODO: exclude soft-affinity and soft-anti-affinity?\n\n if rg.name in self.groups.keys():\n group = self.groups[rg.name]\n else:\n group = Group(rg.name)\n\n group.group_type = rg.group_type\n group.factory = rg.factory\n group.level = \"host\"\n\n self.groups[rg.name] = group\n\n if group is not None:\n group.server_list.append(self.app_name + \":\" + _rk)\n\n return \"ok\"","def create(isamAppliance, id, check_mode=False, force=False):\n if force is True or _check(isamAppliance, id=id) is False:\n if check_mode is True:\n return isamAppliance.create_return_object(changed=True)\n else:\n return isamAppliance.invoke_post(\"Creating group\", \"/sysaccount/groups/v1\",\n {\n 'id': id\n })\n\n return isamAppliance.create_return_object()","def group(self, request, group_id):\n return OtterGroup(self.store, self.tenant_id,\n group_id, self.dispatcher).app.resource()","def group_add_name(org_id, data):\n if data.has_key('groupname'):\n groupname = data['groupname']\n add_group(org_id, groupname, False)","def test_create_group_409(self):\n request = {\n 'name': self.test_group1_groupid\n }\n # First create a group indirectly by making a user with a group\n resp = self.app.post('/users', data=json.dumps(self.test_user1_data))\n assert resp.status_code == 200\n\n # Now create a group that is already there\n resp = self.app.post('/groups', data=json.dumps(request))\n assert resp.status_code == 409","def create_group(self):\n # TODO: Assuming first server is good - need to make fallback logic\n return self.session.get_any(\"{base}{request_url}\".format(base=self.servers[0],\n request_url=F\"/GroupV2/Create/\"))","async def create_contact_group(dbcon: DBConnection, name: str, active: bool) -> str:\n q = \"\"\"insert into contact_groups (name, active) values (%s, %s)\"\"\"\n q_args = (name, active)\n contact_group_id = await dbcon.operation(q, q_args)\n return contact_group_id","def createGroup(self, group, members):\n connection = self.sock\n\n connection.send(\"create_group\".encode())\n\n status_code = connection.recv(2)\n\n if status_code != SUCCESS:\n print(\"Error\")\n return -1\n message = []\n message.append(\"gname:\")\n message.append(group)\n message.append(\";\")\n message.append(\"members:\")\n for i in members:\n message.append(i)\n message.append(\",\")\n if members:\n message.pop()\n message = ''.join(message)\n message = message.encode()\n connection.send(message)\n result = connection.recv(2)\n if result != SUCCESS:\n return -1\n\n packed_gid = connection.recv(4)\n gid = struct.unpack(\" \"GroupBase\":\n ancestor, group_names, last_name = self._descend(name)\n parent = ancestor._require_descendant_groups(*group_names)\n if last_name in parent:\n raise FileExistsError(f\"Group or dataset found at '{name}'\")\n return parent._create_child_group(last_name)","def createMainGroup(self):\n\t\tmc.group( n = self.grp.name, em = True )","def post_security_group_create(self, resource_dict):\n pass","def create(self, validated_data):\n admin_id = validated_data.pop('admin_id', None)\n users = validated_data.pop('users', None)\n group = Group.objects.create(\n admin=admin_id, **validated_data\n )\n if users is not None:\n group.users.set(users)\n group.save()\n return group","def add_group(self, resolvable):\n group = self._resolve_group(resolvable)\n return self._client.group_memberships.create({\n 'account': self,\n 'group': group,\n })","async def add_country_group_async(\n body: Optional[AddCountryGroupRequest] = None,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = AddCountryGroup.create(\n body=body,\n namespace=namespace,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )"],"string":"[\n \"def create_group(group_id, group_name):\\n\\n kwargs = config.DEFAULT_REST_KWARGS\\n kwargs[\\\"data\\\"] = {\\\"id\\\": group_id, \\\"name\\\": group_name}\\n http_response = call_rest_api(\\\"/identities/groups/\\\", \\\"post\\\", **kwargs)\\n if http_response.status_code != 201: # 201 = 'new group created'\\n raise ValueError(http_response.text)\\n logger.log(f\\\"New custom group, {group_name}, with ID: {group_id}, was created successfully.\\\")\",\n \"def create_group():\\n groupname = request.get_json().get(\\\"name\\\")\\n description = request.get_json().get(\\\"description\\\")\\n grp = admin.create_group(current_app.scoped_session(), groupname, description)\\n if grp:\\n response = admin.get_group_info(current_app.scoped_session(), groupname)\\n else:\\n response = {\\\"result\\\": \\\"group creation failed\\\"}\\n response = jsonify(response)\\n return response\",\n \"def create_group(self, **kwargs):\\n post_body = json.dumps({'group': kwargs})\\n resp, body = self.post('groups', post_body)\\n self.expected_success(201, resp.status)\\n body = json.loads(body)\\n return rest_client.ResponseBody(resp, body)\",\n \"def create_group(self, groupname):\\n data = {\\\"groupname\\\": groupname}\\n headers = {\\\"user-agent\\\": self.u_agent}\\n req_url = self.normalize_admin_url(\\\"groups\\\")\\n res = requests.post(\\n req_url,\\n headers=headers,\\n auth=self.auth,\\n data=json.dumps(data),\\n verify=False,\\n )\\n if res.status_code == 201:\\n return Response(0, u\\\"Group {} has been created\\\".format(groupname))\\n else:\\n return Response(res.status_code, res)\",\n \"def create_group(self, group_name, group_type):\\n grp_data = {\\\"name\\\": group_name, \\\"type\\\": group_type}\\n return requests.post(self.groups_url, data=json.dumps(grp_data),\\n headers=self.headers)\",\n \"def product_group_create(obj, name, department):\\n client = get_client(obj)\\n\\n with Action('Creating product_group: {}'.format(name), nl=True):\\n pg = client.product_group_create(name, department)\\n\\n print(json.dumps(pg, indent=4))\",\n \"def create_group(self, event):\\n body = event['body']\\n body = json.loads(body)\\n\\n # Required field in POST body\\n if 'group_name' not in body:\\n return self.get_bad_request('POST body missing group_name')\\n\\n group_name = body['group_name']\\n user = self.mealShareUsers.get_user_cognito_data(event)\\n user_id = user['user_id']\\n \\n # Add the creator to the group, as the initial member\\n group_id = self.mealShareGroups.create_group(group_name)\\n success = self.mealShareGroups.add_user_to_group(user_id, group_id)\\n if success:\\n return {\\n 'statusCode': 200,\\n 'statusMessage': 'Successfully created group {} with ID {}'.format(group_name, group_id),\\n 'group_id': group_id,\\n 'group_name': group_name,\\n 'user_id': user_id\\n }\\n else:\\n return {\\n 'statusCode': 500,\\n 'statusMessage': 'FAILED to create group {} by user {}'.format(group_name, user_id),\\n 'group_id': group_id,\\n 'group_name': group_name,\\n 'user_id': user_id\\n }\",\n \"def create_group(self, name):\\n\\t\\tdata = {\\\"name\\\":name}\\n\\t\\tresponse = self.client.post(self._endpoint + \\\"/group\\\", content=data)\\n\\t\\treturn Group(\\n\\t\\t\\tresponse.json['group_id'],\\n\\t\\t\\tself.user_id,\\n\\t\\t\\tself.site_id,\\n\\t\\t\\tdata=response.json\\n\\t\\t)\",\n \"def test_create_group(self):\\n groupid = 'villains'\\n\\n # create the group\\n resp = self.app.post('/groups', data=json.dumps({'name':groupid}))\\n assert resp.status_code == 200\\n\\n # Fetch the group to check that it persists\\n resp = self.app.get('/groups/{}'.format(groupid))\\n assert resp.status_code == 200\",\n \"def __create_new_group(self, group_name) -> None:\\n group = Group(name=group_name)\\n group.save()\\n\\n self.__add_permission_to_group(group)\",\n \"def CreateGroup(self, name, alloc_policy=None, dry_run=False, reason=None):\\n query = []\\n _AppendDryRunIf(query, dry_run)\\n _AppendReason(query, reason)\\n\\n body = {\\n \\\"name\\\": name,\\n \\\"alloc_policy\\\": alloc_policy,\\n }\\n\\n return self._SendRequest(HTTP_POST, \\\"/%s/groups\\\" % GANETI_RAPI_VERSION,\\n query, body)\",\n \"async def create(\\n self,\\n resource_group_name: str,\\n project_name: str,\\n group_name: str,\\n group: Optional[\\\"models.Group\\\"] = None,\\n **kwargs\\n ) -> \\\"models.Group\\\":\\n cls = kwargs.pop('cls', None) # type: ClsType[\\\"models.Group\\\"]\\n error_map = {\\n 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError\\n }\\n error_map.update(kwargs.pop('error_map', {}))\\n api_version = \\\"2018-06-01\\\"\\n content_type = kwargs.pop(\\\"content_type\\\", \\\"application/json\\\")\\n accept = \\\"application/json\\\"\\n\\n # Construct URL\\n url = self.create.metadata['url'] # type: ignore\\n path_format_arguments = {\\n 'subscriptionId': self._serialize.url(\\\"self._config.subscription_id\\\", self._config.subscription_id, 'str'),\\n 'resourceGroupName': self._serialize.url(\\\"resource_group_name\\\", resource_group_name, 'str', max_length=90, min_length=1, pattern=r'^[-\\\\w\\\\._\\\\(\\\\)]+$'),\\n 'projectName': self._serialize.url(\\\"project_name\\\", project_name, 'str'),\\n 'groupName': self._serialize.url(\\\"group_name\\\", group_name, 'str'),\\n }\\n url = self._client.format_url(url, **path_format_arguments)\\n\\n # Construct parameters\\n query_parameters = {} # type: Dict[str, Any]\\n query_parameters['api-version'] = self._serialize.query(\\\"api_version\\\", api_version, 'str')\\n\\n # Construct headers\\n header_parameters = {} # type: Dict[str, Any]\\n header_parameters['Content-Type'] = self._serialize.header(\\\"content_type\\\", content_type, 'str')\\n header_parameters['Accept'] = self._serialize.header(\\\"accept\\\", accept, 'str')\\n\\n body_content_kwargs = {} # type: Dict[str, Any]\\n if group is not None:\\n body_content = self._serialize.body(group, 'Group')\\n else:\\n body_content = None\\n body_content_kwargs['content'] = body_content\\n request = self._client.put(url, query_parameters, header_parameters, **body_content_kwargs)\\n pipeline_response = await self._client._pipeline.run(request, stream=False, **kwargs)\\n response = pipeline_response.http_response\\n\\n if response.status_code not in [200, 201]:\\n map_error(status_code=response.status_code, response=response, error_map=error_map)\\n raise HttpResponseError(response=response, error_format=ARMErrorFormat)\\n\\n response_headers = {}\\n if response.status_code == 200:\\n response_headers['x-ms-request-id']=self._deserialize('str', response.headers.get('x-ms-request-id'))\\n deserialized = self._deserialize('Group', pipeline_response)\\n\\n if response.status_code == 201:\\n response_headers['x-ms-request-id']=self._deserialize('str', response.headers.get('x-ms-request-id'))\\n deserialized = self._deserialize('Group', pipeline_response)\\n\\n if cls:\\n return cls(pipeline_response, deserialized, response_headers)\\n\\n return deserialized\",\n \"def create_security_group(self, body=None):\\r\\n return self.post(self.security_groups_path, body=body)\",\n \"def create():\\n name = request.json['name']\\n level = request.json['level']\\n manager = request.json['manager']\\n if models.user.Group.get(name):\\n raise Conflict('Group already exists.', creation=False)\\n else:\\n authorize(manager, level=level)\\n group = models.user.Group(name=name, level=level, manager=manager)\\n models.db.session.add(group)\\n models.db.session.commit()\\n return response(200, creation=True)\",\n \"def create_group(\\n self,\\n name,\\n group,\\n validate_only=None,\\n retry=google.api_core.gapic_v1.method.DEFAULT,\\n timeout=google.api_core.gapic_v1.method.DEFAULT,\\n metadata=None,\\n ):\\n if metadata is None:\\n metadata = []\\n metadata = list(metadata)\\n # Wrap the transport method to add retry and timeout logic.\\n if \\\"create_group\\\" not in self._inner_api_calls:\\n self._inner_api_calls[\\n \\\"create_group\\\"\\n ] = google.api_core.gapic_v1.method.wrap_method(\\n self.transport.create_group,\\n default_retry=self._method_configs[\\\"CreateGroup\\\"].retry,\\n default_timeout=self._method_configs[\\\"CreateGroup\\\"].timeout,\\n client_info=self._client_info,\\n )\\n\\n request = group_service_pb2.CreateGroupRequest(\\n name=name, group=group, validate_only=validate_only,\\n )\\n if metadata is None:\\n metadata = []\\n metadata = list(metadata)\\n try:\\n routing_header = [(\\\"name\\\", name)]\\n except AttributeError:\\n pass\\n else:\\n routing_metadata = google.api_core.gapic_v1.routing_header.to_grpc_metadata(\\n routing_header\\n )\\n metadata.append(routing_metadata)\\n\\n return self._inner_api_calls[\\\"create_group\\\"](\\n request, retry=retry, timeout=timeout, metadata=metadata\\n )\",\n \"def create(self, group_name):\\n METHOD = 'POST'\\n API_PATH = '/groups/create'\\n\\n data = {'group_name': group_name}\\n\\n # Make REST call\\n resp = self._rest_call[METHOD](API_PATH, data=data)\\n if resp.status_code == 200:\\n return resp.json()\\n\\n elif resp.status_code == 403:\\n raise AuthorizationError(\\\"User is not authorized or token is incorrect.\\\")\\n\\n else:\\n if resp.json().get(\\\"error_code\\\") in ERROR_CODES:\\n raise ERROR_CODES[resp.json().get('error_code')](resp.json().get('message'))\\n else:\\n raise APIError(\\\"Response code {0}: {1} {2}\\\".format(resp.status_code,\\n resp.json().get('error_code'),\\n resp.json().get('message')))\",\n \"def create_namespaced_group(self, body, **kwargs):\\n\\n all_params = ['body', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_namespaced_group\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `create_namespaced_group`\\\")\\n\\n resource_path = '/oapi/v1/groups'.replace('{format}', 'json')\\n path_params = {}\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1Group',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def test_createGroup(self):\\n\\t\\tself.client.force_authenticate(user=User.objects.get(id=1))\\n\\t\\turl = \\\"/groups/\\\"\\n\\t\\tdata = {\\n\\t\\t\\t'name' : 'testGroup3',\\n\\t\\t\\t'description' : 'This is another test group that just created.',\\n\\t\\t\\t'isPublic' : True\\n\\t\\t}\\n\\t\\tresponse = self.client.post(url, data, format='json')\\n\\t\\tself.assertEqual(response.status_code, status.HTTP_201_CREATED)\\n\\t\\tself.assertEqual(response.data[\\\"id\\\"], 3)\\n\\t\\tself.assertEqual(response.data[\\\"name\\\"], 'testGroup3')\",\n \"async def create_group(ctx, name: str, role: str, group_type: str=None, comp: str=None, rating: int=None, time: str=None):\\n\\n owner = ctx.message.author.name\\n \\n if comp:\\n comp = [int(i) for i in comp.split()] # convert string input to array\\n\\n new_group = Group(owner, name, role, group_type, rating, time, comp)\\n bg_bot.manager.add_group(owner, new_group)\\n \\n await ctx.send(f'Created new {group_type} group for leader {owner}!')\",\n \"def create(self, name, desc, tenant_id):\\n data = {\\\"security_group\\\": {\\\"name\\\": name, \\n \\\"description\\\": desc, \\n \\\"tenant_id\\\":tenant_id}}\\n\\n path = '%s/security-groups' % self.ver\\n res = self.client.call(path, 'POST', data=json.dumps(data), \\n token=self.manager.identity.token)\\n self.logger.debug('Create openstack security group: %s' % truncate(res))\\n return res[0]['security_group']\",\n \"def createGroup(self, name):\\n new_group = ET.SubElement(self._root,'group')\\n group_name = ET.SubElement(new_group, 'name')\\n group_name.text = name\\n # update the document's groups\\n self._groups = self._root.findall('group') \\n print 'Creating group, \\\\'%s\\\\'' % name\\n return CAGroup(new_group)\",\n \"def create_group(self, identifier: str, group_name: str) -> Group:\\n\\n # APM-137701 - Namespace for custom device calculation should not be set\\n group_id = get_group_id(\\\"\\\", identifier)\\n if group_id in self._groups:\\n raise ValueError(\\\"Group \\\" + group_name + \\\" already exist, id: \\\" + str(group_id))\\n else:\\n group = Group(group_id, group_name, self._technologies, self._results_builder)\\n\\n self._groups[group_id] = group\\n return group\",\n \"def add_group():\\n name = request.form['name']\\n data, code, message = FIELD_SERVICE.add_group(name)\\n return __result(data, code, message)\",\n \"def create_placement_group(self, name, strategy='cluster'):\\r\\n params = {'GroupName':name, 'Strategy':strategy}\\r\\n group = self.get_status('CreatePlacementGroup', params, verb='POST')\\r\\n return group\",\n \"def security_group_create(auth=None, **kwargs):\\n cloud = get_operator_cloud(auth)\\n kwargs = _clean_kwargs(keep_name=True, **kwargs)\\n return cloud.create_security_group(**kwargs)\",\n \"def create_new_group(self, group_id, poll_id, name):\\n obj = self.table()\\n obj.group_id = str(group_id)\\n obj.poll_id = poll_id\\n obj.name = name\\n self.db.session.add(obj)\\n self.db.session.commit()\",\n \"def create_group(self, group):\\n if self.dryrun:\\n self.logger.info(\\\"Would create group %s\\\", group)\\n return FakeGroupId()\\n result = self.conn.usergroup.create(name=group)\\n groupid = result['usrgrpids'][0]\\n self.logger.info(\\\"Create group %s with id %s\\\", group, groupid)\\n return groupid\",\n \"def createGroup(self, *group):\\n if not self.rank:\\n logging.info('Creating atom group {}'.format(group))\\n\\n if not len(group):\\n for idSS in self.pargs['idSS']:\\n self.lmp.command('group group{} type {}'.format(idSS, idSS))\\n else:\\n self.lmp.command('group ' + ('{} ' * len(group)).format(*group))\",\n \"def create_group(self, group_name, user_ids=[], role_ids=[]):\\n payload = {}\\n payload['name'] = group_name\\n payload['user_ids'] = user_ids\\n payload['role_ids'] = role_ids\\n return Client._post(self, payload)\",\n \"def groups_create(self, mar, request):\\n if not permissions.CanCreateGroup(mar.perms):\\n raise permissions.PermissionException(\\n 'The user is not allowed to create groups.')\\n\\n user_dict = self._services.user.LookupExistingUserIDs(\\n mar.cnxn, [request.groupName])\\n if request.groupName.lower() in user_dict:\\n raise exceptions.GroupExistsException(\\n 'group %s already exists' % request.groupName)\\n\\n if request.ext_group_type:\\n ext_group_type = str(request.ext_group_type).lower()\\n else:\\n ext_group_type = None\\n group_id = self._services.usergroup.CreateGroup(\\n mar.cnxn, self._services, request.groupName,\\n str(request.who_can_view_members).lower(),\\n ext_group_type)\\n\\n return api_pb2_v1.GroupsCreateResponse(\\n groupID=group_id)\",\n \"def create(self, body: CloudSecurityGroup) -> Dict:\\n\\t\\treturn self._post(route=AWSSecurityGroupConsts.CLOUD_SECURITY_GROUP.value, body=body)\",\n \"def request_group_create():\\n return Response(render_template('admin/group/create-update.html',\\n csrf_token=(\\n get_raw_jwt() or {}).get(\\\"csrf\\\"),\\n target=\\\"/admin/group/create\\\"),\\n mimetype='text/html')\",\n \"def capacitygroup_create(cmd_ctx, cpc, **options):\\n cmd_ctx.execute_cmd(\\n lambda: cmd_capacitygroup_create(cmd_ctx, cpc, options))\",\n \"def post(self):\\n args = parser.parse_args()\\n user_group = UserGroup()\\n user_group.name = args['name']\\n user_group.createdby = auth.username()\\n db_session.add(user_group)\\n db_session.commit()\\n return user_group, 201\",\n \"def newgroup(self, groupname, groupou=None, grouptype=None,\\n description=None, mailaddress=None, notes=None, sd=None,\\n gidnumber=None, nisdomain=None):\\n\\n group_dn = \\\"CN=%s,%s,%s\\\" % (groupname, (groupou or \\\"CN=Users\\\"), self.domain_dn())\\n\\n # The new user record. Note the reliance on the SAMLDB module which\\n # fills in the default informations\\n ldbmessage = {\\\"dn\\\": group_dn,\\n \\\"sAMAccountName\\\": groupname,\\n \\\"objectClass\\\": \\\"group\\\"}\\n\\n if grouptype is not None:\\n ldbmessage[\\\"groupType\\\"] = normalise_int32(grouptype)\\n\\n if description is not None:\\n ldbmessage[\\\"description\\\"] = description\\n\\n if mailaddress is not None:\\n ldbmessage[\\\"mail\\\"] = mailaddress\\n\\n if notes is not None:\\n ldbmessage[\\\"info\\\"] = notes\\n\\n if gidnumber is not None:\\n ldbmessage[\\\"gidNumber\\\"] = normalise_int32(gidnumber)\\n\\n if nisdomain is not None:\\n ldbmessage[\\\"msSFU30Name\\\"] = groupname\\n ldbmessage[\\\"msSFU30NisDomain\\\"] = nisdomain\\n\\n if sd is not None:\\n ldbmessage[\\\"nTSecurityDescriptor\\\"] = ndr_pack(sd)\\n\\n self.add(ldbmessage)\",\n \"def post_groups(\\n data: PostGroupIn, tkn: Token = Depends(from_authotization_header_nondyn),\\n):\\n assert_has_clearance(tkn.owner, \\\"sni.create_group\\\")\\n grp = Group(\\n description=data.description,\\n members=[tkn.owner],\\n group_name=data.group_name,\\n owner=tkn.owner,\\n ).save()\\n logging.debug(\\n \\\"Created group %s (%s) owned by %s\\\",\\n data.group_name,\\n str(grp.pk),\\n tkn.owner.character_name,\\n )\\n return GetGroupOut.from_record(grp)\",\n \"def createGroup(self):\\n return _libsbml.GroupsModelPlugin_createGroup(self)\",\n \"def create_secgroup(self, args):\\n message = MessageClass()\\n region = args[\\\"Region\\\"]\\n sgid = args[\\\"Group-Name\\\"]\\n desc = args[\\\"Description\\\"]\\n\\n # Boto3 client creation by providing the access_id and access_secret\\n ec2 = boto3.client(service_name='ec2', region_name=region, api_version=None, use_ssl=True,\\n verify=None, endpoint_url=None, aws_access_key_id=self.aws_access_key,\\n aws_secret_access_key=self.aws_secret_token, aws_session_token=None,\\n config=None)\\n response = ec2.describe_vpcs()\\n vpc_id = response.get('Vpcs', [{}])[0].get('VpcId', '')\\n\\n response = ec2.create_security_group(GroupName=sgid,\\n Description=desc,\\n VpcId=vpc_id)\\n attachment = MessageAttachmentsClass()\\n d = response[\\\"GroupId\\\"]\\n attachment.title = d\\n message.message_text = \\\"Security group created:\\\"\\n message.attach(attachment)\\n\\n return message.to_json()\",\n \"def create_adgroup(self, account_id, name, campaign_id,\\n creative_id, bid_type=None, bid_info=None, max_bid=None,\\n tracking_specs=None, view_tags=None, objective=None,\\n adgroup_status=None, targeting=None, conversion_specs=None, batch=False):\\n path = 'act_%s/adgroups' % account_id\\n args = {\\n 'name': name,\\n 'campaign_id': campaign_id,\\n 'creative': json.dumps({'creative_id': creative_id}),\\n }\\n if bid_type:\\n args['bid_type'] = bid_type\\n if max_bid:\\n # can only use max_bid with CPM bidding\\n args['max_bid'] = max_bid\\n elif bid_info:\\n args['bid_info'] = json.dumps(bid_info)\\n\\n if tracking_specs:\\n args['tracking_specs'] = json.dumps(tracking_specs)\\n if view_tags:\\n args['view_tags'] = json.dumps(view_tags)\\n if objective:\\n args['objective'] = objective\\n if adgroup_status:\\n args['adgroup_status'] = adgroup_status\\n if targeting:\\n args['targeting'] = json.dumps(targeting)\\n if conversion_specs:\\n args['conversion_specs'] = json.dumps(conversion_specs)\\n return self.make_request(path, 'POST', args, batch=batch)\",\n \"def create_group_with_http_info(self, bucket_id, group, **kwargs):\\n\\n all_params = ['bucket_id', 'group', 'if_match', 'if_none_match']\\n all_params.append('callback')\\n all_params.append('_return_http_data_only')\\n all_params.append('_preload_content')\\n all_params.append('_request_timeout')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_group\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'bucket_id' is set\\n if ('bucket_id' not in params) or (params['bucket_id'] is None):\\n raise ValueError(\\\"Missing the required parameter `bucket_id` when calling `create_group`\\\")\\n # verify the required parameter 'group' is set\\n if ('group' not in params) or (params['group'] is None):\\n raise ValueError(\\\"Missing the required parameter `group` when calling `create_group`\\\")\\n\\n if 'if_match' in params and not re.search('\\\\\\\\\\\\\\\"[0-9]+\\\\\\\\\\\\\\\"', params['if_match']):\\n raise ValueError(\\\"Invalid value for parameter `if_match` when calling `create_group`, must conform to the pattern `/\\\\\\\\\\\\\\\"[0-9]+\\\\\\\\\\\\\\\"/`\\\")\\n if 'if_none_match' in params and not re.search('\\\\\\\\\\\\\\\"[0-9]+\\\\\\\\\\\\\\\"', params['if_none_match']):\\n raise ValueError(\\\"Invalid value for parameter `if_none_match` when calling `create_group`, must conform to the pattern `/\\\\\\\\\\\\\\\"[0-9]+\\\\\\\\\\\\\\\"/`\\\")\\n\\n collection_formats = {}\\n\\n resource_path = '/buckets/{bucket_id}/groups'.replace('{format}', 'json')\\n path_params = {}\\n if 'bucket_id' in params:\\n path_params['bucket_id'] = params['bucket_id']\\n\\n query_params = {}\\n\\n header_params = {}\\n if 'if_match' in params:\\n header_params['If-Match'] = params['if_match']\\n if 'if_none_match' in params:\\n header_params['If-None-Match'] = params['if_none_match']\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'group' in params:\\n body_params = params['group']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['application/json'])\\n\\n # Authentication setting\\n auth_settings = ['basicAuth']\\n\\n return self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='Group',\\n auth_settings=auth_settings,\\n callback=params.get('callback'),\\n _return_http_data_only=params.get('_return_http_data_only'),\\n _preload_content=params.get('_preload_content', True),\\n _request_timeout=params.get('_request_timeout'),\\n collection_formats=collection_formats)\",\n \"def test_create_group(self):\\n pass\",\n \"def test_create_group(self):\\n pass\",\n \"def new_group(request):\\n return edit_group(request, None)\",\n \"def create(person_group_id, name=None, user_data=None):\\n name = person_group_id if name is None else name\\n url = 'persongroups/{}'.format(person_group_id)\\n json = {\\n 'name': name,\\n 'userData': user_data,\\n }\\n\\n return util.request('PUT', url, json=json)\",\n \"def create_ad_group(client, customer_id, campaign_resource_name):\\n ad_group_service = client.get_service(\\\"AdGroupService\\\")\\n\\n # Creates the ad group.\\n # Note that the ad group type must not be set.\\n # Since the advertising_channel_sub_type is APP_CAMPAIGN,\\n # 1- you cannot override bid settings at the ad group level.\\n # 2- you cannot add ad group criteria.\\n ad_group_operation = client.get_type(\\\"AdGroupOperation\\\")\\n ad_group = ad_group_operation.create\\n ad_group.name = f\\\"Earth to Mars cruises {uuid4()}\\\"\\n ad_group.status = client.enums.AdGroupStatusEnum.ENABLED\\n ad_group.campaign = campaign_resource_name\\n\\n ad_group_response = ad_group_service.mutate_ad_groups(\\n customer_id=customer_id, operations=[ad_group_operation]\\n )\\n\\n ad_group_resource_name = ad_group_response.results[0].resource_name\\n print(f'Ad Group created with resource name: \\\"{ad_group_resource_name}\\\".')\\n return ad_group_resource_name\",\n \"def _assert_create_group(self, personality, response=400):\\n group_response = self.autoscale_behaviors.create_scaling_group_given(\\n lc_personality=personality)\\n self.assertEquals(group_response.status_code, response, msg='Create group '\\n 'with invalid lc_personality returned {0} as against '\\n '{1}'.format(group_response.status_code, response))\\n if response is 200:\\n group = group_response.entity\\n self.resources.add(group, self.empty_scaling_group)\\n return group\",\n \"def create_group_command(client: MsGraphClient, args: dict) -> tuple[str, dict, dict]:\\n required_properties = {\\n 'displayName': str(args.get('display_name')),\\n 'mailNickname': str(args.get('mail_nickname')),\\n 'mailEnabled': args.get('mail_enabled') == 'true',\\n 'securityEnabled': args.get('security_enabled')\\n }\\n\\n # create the group\\n group = client.create_group(required_properties)\\n\\n # display the new group and it's properties\\n group_readable, group_outputs = parse_outputs(group)\\n human_readable = tableToMarkdown(name=f\\\"{required_properties['displayName']} was created successfully:\\\",\\n t=group_readable,\\n headers=['ID', 'Display Name', 'Description', 'Created Date Time', 'Mail',\\n 'Security Enabled', 'Mail Enabled'],\\n removeNull=True)\\n entry_context = {f'{INTEGRATION_CONTEXT_NAME}(val.ID === obj.ID)': group_outputs}\\n return human_readable, entry_context, group\",\n \"def create_TestGroup(test_case, # type: AnyMagpieTestCaseType\\n override_group_name=null, # type: Optional[Str]\\n override_discoverable=null, # type: Optional[bool]\\n override_data=null, # type: Optional[JSON]\\n override_headers=null, # type: Optional[HeadersType]\\n override_cookies=null, # type: Optional[CookiesType]\\n ): # type: (...) -> JSON\\n app_or_url = get_app_or_url(test_case)\\n data = override_data\\n if override_data is null:\\n data = {\\\"group_name\\\": override_group_name if override_group_name is not null else test_case.test_group_name}\\n # only add 'discoverable' if explicitly provided here to preserve original behaviour of 'no value provided'\\n if override_discoverable is not null:\\n data[\\\"discoverable\\\"] = override_discoverable\\n grp_name = (data or {}).get(\\\"group_name\\\")\\n if grp_name:\\n test_case.extra_group_names.add(grp_name) # indicate potential removal at a later point\\n resp = test_request(app_or_url, \\\"POST\\\", \\\"/groups\\\", json=data,\\n headers=override_headers if override_headers is not null else test_case.json_headers,\\n cookies=override_cookies if override_cookies is not null else test_case.cookies)\\n return check_response_basic_info(resp, 201, expected_method=\\\"POST\\\")\",\n \"def create_group():\\n incoming = request.get_json()\\n chatroom = Chatroom(\\n name = incoming['name'],\\n tag = incoming['tag'],\\n )\\n db.session.add(chatroom)\\n db.session.commit()\\n participant = Participant(\\n user_id = session['user_id'],\\n room_id = chatroom.room_id,\\n )\\n db.session.add(participant)\\n db.session.commit()\\n return jsonify(results = chatroom.room_id)\",\n \"def create_group(self, properties: dict[str, Any | None]) -> dict:\\n group = self.ms_client.http_request(method='POST', url_suffix='groups', json_data=properties)\\n return group\",\n \"def allocate_group(remote, objectid):\\n cmd1 = mmapi.StoredCommands()\\n key1 = cmd1.AppendSceneCommand_AllocateNewGroupID(objectid)\\n remote.runCommand(cmd1)\\n result_val = mmapi.any_result()\\n cmd1.GetSceneCommandResult_AllocateNewGroupID(key1, result_val)\\n return result_val.i\",\n \"def create(\\n self, draft: CustomerGroupDraft, *, expand: OptionalListStr = None\\n ) -> CustomerGroup:\\n params = self._serialize_params({\\\"expand\\\": expand}, traits.ExpandableSchema)\\n return self._client._post(\\n endpoint=\\\"customer-groups\\\",\\n params=params,\\n data_object=draft,\\n response_class=CustomerGroup,\\n )\",\n \"def create_security_group(self, name, description, vpc_id=None):\\r\\n params = {\\r\\n 'GroupName': name,\\r\\n 'GroupDescription': description\\r\\n }\\r\\n\\r\\n if vpc_id is not None:\\r\\n params['VpcId'] = vpc_id\\r\\n\\r\\n group = self.get_object('CreateSecurityGroup', params,\\r\\n SecurityGroup, verb='POST')\\r\\n group.name = name\\r\\n group.description = description\\r\\n return group\",\n \"def create_security_group(group_name):\\n ec2 = boto.ec2.connect_to_region(AWS_REGION)\\n for g in ec2.get_all_security_groups():\\n if g.name == group_name:\\n return # We already have this group setup\\n group = ec2.create_security_group(group_name,\\n \\\"%s SSH access group\\\" % group_name)\\n group.authorize(\\\"tcp\\\", 22, 22, \\\"0.0.0.0/0\\\") # SSH is on port 22, all IPs\\n group.authorize(\\\"tcp\\\", 80, 80, \\\"0.0.0.0/0\\\")\\n group.authorize(\\\"tcp\\\", 61000, 65000, \\\"0.0.0.0/0\\\")\\n print \\\"Created new security group\\\"\",\n \"def create_group(name, nodes, description=None):\\n group, created = Group.get_or_create(name=name)\\n if created:\\n print('Group created with PK={} and name {}'.format(group.pk, group.name))\\n else:\\n print('Group with name {} and pk {} already exists. Do you want to add nodes?[y/n]'.format(group.name, group.pk))\\n answer = raw_input()\\n if answer.strip().lower() == 'y':\\n pass\\n else:\\n return\\n nodes2 = []\\n nodes2_pks = []\\n for node in nodes:\\n try:\\n node = int(node)\\n except ValueError:\\n pass\\n nodes2_pks.append(node)\\n try:\\n nodes2.append(load_node(node))\\n except:# NotExistentError:\\n pass\\n\\n group.add_nodes(nodes2)\\n print('added nodes: {} to group {} {}'.format(nodes2_pks, group.name, group.pk))\\n\\n if description:\\n group.description = description\\n\\n return group\",\n \"def create(self, context=None):\\n values = self.obj_get_changes()\\n db_nodegroup = self.dbapi.create_nodegroup(values)\\n self._from_db_object(self, db_nodegroup)\",\n \"async def async_create_group(\\n hass: HomeAssistant,\\n name: str,\\n entity_ids: Collection[str] | None = None,\\n user_defined: bool = True,\\n icon: str | None = None,\\n object_id: str | None = None,\\n mode: bool | None = None,\\n order: int | None = None,\\n ) -> Group:\\n group = Group.async_create_group_entity(\\n hass, name, entity_ids, user_defined, icon, object_id, mode, order\\n )\\n\\n # If called before the platform async_setup is called (test cases)\\n await _async_get_component(hass).async_add_entities([group])\\n return group\",\n \"def create_groups(**kwargs):\\n for gname in SEC_GROUP_NAMES.itervalues():\\n Group.objects.get_or_create(name=gname)\",\n \"def create(self, name, desc):\\n body = {'security_group': {'name': name,\\n 'description': desc,\\n 'tenant_id': self.request.user.project_id}}\\n secgroup = self.client.create_security_group(body)\\n return SecurityGroup(secgroup.get('security_group'))\",\n \"def create_rule_group(self: object,\\n body: dict,\\n cs_username: str = None # pylint: disable=W0613 # cs_username is deprecated\\n ) -> dict:\\n # [POST] https://assets.falcon.crowdstrike.com/support/api/swagger.html#/custom-ioa/create-rule-groupMixin0\\n return process_service_request(\\n calling_object=self,\\n endpoints=Endpoints,\\n operation_id=\\\"create_rule_groupMixin0\\\",\\n body=body\\n )\",\n \"def test_create_resource_group(self):\\n pass\",\n \"def create_sec_group(self, conn, name, project):\\n sec_group = conn.create_security_group(\\n name=name, description=\\\"Security Group\\\",\\n project_id=project.id)\\n conn.create_security_group_rule(sec_group)\\n return sec_group\",\n \"def post(self):\\n status = ErrorCode.SUCCESS\\n try:\\n data = DotDict(json_decode(self.request.body))\\n logging.info(\\\"[UWEB] add group request: %s, cid: %s\\\",\\n data, self.current_user.cid)\\n except Exception as e:\\n status = ErrorCode.ILLEGAL_DATA_FORMAT\\n logging.exception(\\\"[UWEB] Invalid data format. body:%s, Exception: %s\\\",\\n self.request.body, e.args)\\n self.write_ret(status)\\n return\\n\\n try: \\n cid = data.cid\\n name = data.name\\n group = self.get_group_by_cid(cid, name)\\n if group:\\n status = ErrorCode.GROUP_EXIST\\n self.write_ret(status)\\n return\\n\\n group_info = dict(cid=cid,\\n name=name,\\n type=UWEB.GROUP_TYPE.NEW)\\n gid = add_group(group_info, self.db, self.redis)\\n # NOTE: wspush to client\\n tid = self.current_user.tid\\n if status == ErrorCode.SUCCESS:\\n WSPushHelper.pushS3(tid, self.db, self.redis)\\n\\n self.write_ret(status,\\n dict_=dict(gid=gid,\\n cid=cid,\\n name=name))\\n\\n except Exception as e:\\n logging.exception(\\\"[UWEB] Create group failed. uid: %s, Exception: %s\\\",\\n self.current_user.uid, e.args)\\n status = ErrorCode.SERVER_BUSY\\n self.write_ret(status)\",\n \"def test_create_team_user_group(client):\\n group = client.create_team_user_group(TEAM_ID, {\\n \\\"name\\\": \\\"Python group\\\",\\n \\\"is_reviewer\\\": True,\\n \\\"is_admin\\\": True,\\n \\\"admin_rights\\\": [\\\"upload\\\"]\\n })\\n assert group.team_id == TEAM_ID\\n assert group.group_id == NEW_GROUP_ID\\n assert group.name == \\\"Python group\\\"\\n assert group.permissions['is_admin']\\n assert group.permissions['is_reviewer']\\n assert group.permissions['admin_rights'] == [\\\"upload\\\"]\",\n \"def create_group(self, tenant_id, group_id):\\n maas_client = self._get_maas_client()\\n d = maas_client.add_notification_and_plan()\\n\\n def create_group_in_db((notification, notification_plan)):\\n return cass.create_group(\\n self._db, tenant_id, group_id, notification, notification_plan)\\n d.addCallback(create_group_in_db)\\n\\n return d\",\n \"def createNewGroup():\\n if request.method == 'POST':\\n groupname = request.form['groupname1']\\n internal = request.form['internal1']\\n external = request.form['external1']\\n userNo = request.form['usersNo1']\\n if 'node1' in request.form:\\n node = int(request.form['node1'])\\n else:\\n node = -1\\n\\n if int(userNo) == 0:\\n if hl.createGroup(groupname, internal, external, node):\\n return True\\n elif int(userNo) > 0:\\n if hl.createGroup(groupname, internal, external, node, genUsers=True, numUsers=int(userNo)):\\n return True\\n\\n return False\",\n \"def create_group(self, bucket_id, group, **kwargs):\\n kwargs['_return_http_data_only'] = True\\n if kwargs.get('callback'):\\n return self.create_group_with_http_info(bucket_id, group, **kwargs)\\n else:\\n (data) = self.create_group_with_http_info(bucket_id, group, **kwargs)\\n return data\",\n \"def create( self, trans, payload, **kwd ):\\n group_dict = dict( message='', status='ok' )\\n name = payload.get( 'name', '' )\\n if name:\\n description = payload.get( 'description', '' )\\n if not description:\\n description = ''\\n else:\\n # TODO add description field to the model\\n group_dict = self.group_manager.create( trans, name=name ).to_dict( view='element', value_mapper=self.__get_value_mapper( trans ) )\\n else:\\n raise RequestParameterMissingException( 'Missing required parameter \\\"name\\\".' )\\n return group_dict\",\n \"def create_group(username: str, gid: int=None, system: bool=False) -> Result[Group]:\\n try:\\n group = get_group(username)\\n except KeyError:\\n return add_group(username, gid, system)\\n else:\\n if group.gr_gid != gid:\\n raise ValueError(\\\"Group {!r} has GID {}, expected {}\\\"\\n .format(username, group.gr_gid, gid))\\n return Result(State.unchanged, group)\",\n \"def create_sec_group(ec2, sec_group_name):\\n sec = ec2.create_security_group(sec_group_name, 'Jvivian Boto SecGroup')\\n port = 22\\n sec.authorize('tcp', port, port, '0.0.0.0/0')\",\n \"def __create_group(self):\\n\\n group = time.strftime(_GROUP_NAME_FORMAT, time.localtime())\\n LOG.info(\\\"Creating backup group '%s'.\\\", group)\\n\\n group_path = self.group_path(group)\\n\\n try:\\n os.mkdir(group_path)\\n except EnvironmentError as e:\\n if e.errno != errno.EEXIST:\\n raise Error(\\\"Unable to create a new backup group '{}': {}.\\\",\\n group_path, psys.e(e))\\n\\n self.__on_group_created(group)\\n\\n return group\",\n \"def create_group(user):\\n if connexion.request.is_json:\\n users_group = [User.from_dict(d) for d in connexion.request.get_json()]\\n response = (\\\"success\\\", 201)\\n if len(users_group) > 4:\\n response = (\\\"Max number of player is 4\\\", 400)\\n else:\\n groupId = GroupStorageController.add_new_group(users_group)\\n return response\",\n \"def create_group(self, groupname, filters=[], filter_options=[], **kwargs):\\n pytan.utils.check_for_help(kwargs=kwargs)\\n clean_kwargs = pytan.utils.clean_kwargs(kwargs=kwargs)\\n\\n filter_defs = pytan.utils.dehumanize_question_filters(question_filters=filters)\\n option_defs = pytan.utils.dehumanize_question_options(question_options=filter_options)\\n\\n h = (\\n \\\"Issue a GetObject to get the full object of specified sensors for inclusion in a \\\"\\n \\\"group\\\"\\n )\\n filter_defs = self._get_sensor_defs(defs=filter_defs, pytan_help=h, **clean_kwargs)\\n\\n add_group_obj = pytan.utils.build_group_obj(\\n q_filter_defs=filter_defs, q_option_defs=option_defs,\\n )\\n add_group_obj.name = groupname\\n\\n h = \\\"Issue an AddObject to add a Group object\\\"\\n group_obj = self._add(obj=add_group_obj, pytan_help=h, **clean_kwargs)\\n\\n m = \\\"New group {!r} created with ID {!r}, filter text: {!r}\\\".format\\n self.mylog.info(m(group_obj.name, group_obj.id, group_obj.text))\\n return group_obj\",\n \"def _make_group(self, _rk, _group_hint):\\n\\n if isinstance(_group_hint, dict):\\n # _group_hint is a single key/value pair\\n g = _group_hint[list(_group_hint)[0]]\\n\\n r_type = g.get(\\\"type\\\", \\\"none\\\")\\n if r_type != \\\"OS::Nova::ServerGroup\\\":\\n return \\\"support only ServerGroup resource\\\"\\n\\n properties = g.get(\\\"properties\\\", {})\\n if len(properties) == 0:\\n return \\\"no properties\\\"\\n\\n group_name = properties.get(\\\"name\\\", None)\\n if group_name is None:\\n return \\\"no group name\\\"\\n group_name = group_name.strip()\\n\\n policies = properties.get(\\\"policies\\\", [])\\n if len(policies) == 0:\\n return \\\"no policy of the group\\\"\\n\\n if len(policies) > 1:\\n return \\\"multiple policies\\\"\\n\\n # TODO: exclude soft-affinity and soft-anti-affinity?\\n\\n if group_name in self.groups.keys():\\n group = self.groups[group_name]\\n else:\\n group = Group(group_name)\\n\\n policy = policies[0].strip()\\n if policy == \\\"anti-affinity\\\":\\n group_type = \\\"diversity\\\"\\n else:\\n group_type = policy\\n\\n group.group_type = group_type\\n group.factory = \\\"server-group\\\"\\n group.level = \\\"host\\\"\\n\\n self.groups[group_name] = group\\n else:\\n # group hint is uuid string.\\n rg = self.resource.get_group_by_uuid(_group_hint)\\n if rg is None:\\n return \\\"unknown group found while making group\\\"\\n\\n # TODO: exclude soft-affinity and soft-anti-affinity?\\n\\n if rg.name in self.groups.keys():\\n group = self.groups[rg.name]\\n else:\\n group = Group(rg.name)\\n\\n group.group_type = rg.group_type\\n group.factory = rg.factory\\n group.level = \\\"host\\\"\\n\\n self.groups[rg.name] = group\\n\\n if group is not None:\\n group.server_list.append(self.app_name + \\\":\\\" + _rk)\\n\\n return \\\"ok\\\"\",\n \"def create(isamAppliance, id, check_mode=False, force=False):\\n if force is True or _check(isamAppliance, id=id) is False:\\n if check_mode is True:\\n return isamAppliance.create_return_object(changed=True)\\n else:\\n return isamAppliance.invoke_post(\\\"Creating group\\\", \\\"/sysaccount/groups/v1\\\",\\n {\\n 'id': id\\n })\\n\\n return isamAppliance.create_return_object()\",\n \"def group(self, request, group_id):\\n return OtterGroup(self.store, self.tenant_id,\\n group_id, self.dispatcher).app.resource()\",\n \"def group_add_name(org_id, data):\\n if data.has_key('groupname'):\\n groupname = data['groupname']\\n add_group(org_id, groupname, False)\",\n \"def test_create_group_409(self):\\n request = {\\n 'name': self.test_group1_groupid\\n }\\n # First create a group indirectly by making a user with a group\\n resp = self.app.post('/users', data=json.dumps(self.test_user1_data))\\n assert resp.status_code == 200\\n\\n # Now create a group that is already there\\n resp = self.app.post('/groups', data=json.dumps(request))\\n assert resp.status_code == 409\",\n \"def create_group(self):\\n # TODO: Assuming first server is good - need to make fallback logic\\n return self.session.get_any(\\\"{base}{request_url}\\\".format(base=self.servers[0],\\n request_url=F\\\"/GroupV2/Create/\\\"))\",\n \"async def create_contact_group(dbcon: DBConnection, name: str, active: bool) -> str:\\n q = \\\"\\\"\\\"insert into contact_groups (name, active) values (%s, %s)\\\"\\\"\\\"\\n q_args = (name, active)\\n contact_group_id = await dbcon.operation(q, q_args)\\n return contact_group_id\",\n \"def createGroup(self, group, members):\\n connection = self.sock\\n\\n connection.send(\\\"create_group\\\".encode())\\n\\n status_code = connection.recv(2)\\n\\n if status_code != SUCCESS:\\n print(\\\"Error\\\")\\n return -1\\n message = []\\n message.append(\\\"gname:\\\")\\n message.append(group)\\n message.append(\\\";\\\")\\n message.append(\\\"members:\\\")\\n for i in members:\\n message.append(i)\\n message.append(\\\",\\\")\\n if members:\\n message.pop()\\n message = ''.join(message)\\n message = message.encode()\\n connection.send(message)\\n result = connection.recv(2)\\n if result != SUCCESS:\\n return -1\\n\\n packed_gid = connection.recv(4)\\n gid = struct.unpack(\\\" \\\"GroupBase\\\":\\n ancestor, group_names, last_name = self._descend(name)\\n parent = ancestor._require_descendant_groups(*group_names)\\n if last_name in parent:\\n raise FileExistsError(f\\\"Group or dataset found at '{name}'\\\")\\n return parent._create_child_group(last_name)\",\n \"def createMainGroup(self):\\n\\t\\tmc.group( n = self.grp.name, em = True )\",\n \"def post_security_group_create(self, resource_dict):\\n pass\",\n \"def create(self, validated_data):\\n admin_id = validated_data.pop('admin_id', None)\\n users = validated_data.pop('users', None)\\n group = Group.objects.create(\\n admin=admin_id, **validated_data\\n )\\n if users is not None:\\n group.users.set(users)\\n group.save()\\n return group\",\n \"def add_group(self, resolvable):\\n group = self._resolve_group(resolvable)\\n return self._client.group_memberships.create({\\n 'account': self,\\n 'group': group,\\n })\",\n \"async def add_country_group_async(\\n body: Optional[AddCountryGroupRequest] = None,\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = AddCountryGroup.create(\\n body=body,\\n namespace=namespace,\\n )\\n return await run_request_async(\\n request, additional_headers=x_additional_headers, **kwargs\\n )\"\n]"},"negative_scores":{"kind":"list like","value":["0.7795205","0.76985514","0.75594074","0.7485939","0.7361224","0.7275385","0.7226914","0.7171012","0.7022135","0.7012331","0.70026654","0.6958713","0.6953057","0.6946662","0.6930038","0.68761617","0.68680024","0.6829689","0.6791976","0.67673075","0.67458194","0.6739689","0.67273766","0.6694578","0.6683829","0.66818786","0.6666198","0.66433865","0.66410846","0.663097","0.6591401","0.65880996","0.658466","0.657879","0.65678144","0.6565356","0.65637505","0.6554267","0.6546635","0.6514908","0.6507296","0.6507296","0.6469481","0.6465262","0.64547205","0.6448505","0.64376134","0.64343834","0.64154005","0.6414627","0.6396364","0.6376567","0.6365447","0.63453394","0.6341325","0.6341231","0.633921","0.6331937","0.6328687","0.62847745","0.6277781","0.6267766","0.6262555","0.625486","0.6246472","0.62288123","0.6228652","0.6227351","0.6223595","0.62165976","0.62141347","0.6211684","0.62101644","0.6208205","0.61926514","0.6189376","0.6182613","0.6181146","0.61696476","0.6164491","0.61601025","0.6146641","0.61334515","0.61317176","0.6128281","0.6102575","0.6084897","0.6079304","0.60532016","0.60482174","0.6046931","0.60465133","0.6035445","0.60300994","0.6008034","0.6000354","0.59863174","0.5980952","0.5971276","0.5953805"],"string":"[\n \"0.7795205\",\n \"0.76985514\",\n \"0.75594074\",\n \"0.7485939\",\n \"0.7361224\",\n \"0.7275385\",\n \"0.7226914\",\n \"0.7171012\",\n \"0.7022135\",\n \"0.7012331\",\n \"0.70026654\",\n \"0.6958713\",\n \"0.6953057\",\n \"0.6946662\",\n \"0.6930038\",\n \"0.68761617\",\n \"0.68680024\",\n \"0.6829689\",\n \"0.6791976\",\n \"0.67673075\",\n \"0.67458194\",\n \"0.6739689\",\n \"0.67273766\",\n \"0.6694578\",\n \"0.6683829\",\n \"0.66818786\",\n \"0.6666198\",\n \"0.66433865\",\n \"0.66410846\",\n \"0.663097\",\n \"0.6591401\",\n \"0.65880996\",\n \"0.658466\",\n \"0.657879\",\n \"0.65678144\",\n \"0.6565356\",\n \"0.65637505\",\n \"0.6554267\",\n \"0.6546635\",\n \"0.6514908\",\n \"0.6507296\",\n \"0.6507296\",\n \"0.6469481\",\n \"0.6465262\",\n \"0.64547205\",\n \"0.6448505\",\n \"0.64376134\",\n \"0.64343834\",\n \"0.64154005\",\n \"0.6414627\",\n \"0.6396364\",\n \"0.6376567\",\n \"0.6365447\",\n \"0.63453394\",\n \"0.6341325\",\n \"0.6341231\",\n \"0.633921\",\n \"0.6331937\",\n \"0.6328687\",\n \"0.62847745\",\n \"0.6277781\",\n \"0.6267766\",\n \"0.6262555\",\n \"0.625486\",\n \"0.6246472\",\n \"0.62288123\",\n \"0.6228652\",\n \"0.6227351\",\n \"0.6223595\",\n \"0.62165976\",\n \"0.62141347\",\n \"0.6211684\",\n \"0.62101644\",\n \"0.6208205\",\n \"0.61926514\",\n \"0.6189376\",\n \"0.6182613\",\n \"0.6181146\",\n \"0.61696476\",\n \"0.6164491\",\n \"0.61601025\",\n \"0.6146641\",\n \"0.61334515\",\n \"0.61317176\",\n \"0.6128281\",\n \"0.6102575\",\n \"0.6084897\",\n \"0.6079304\",\n \"0.60532016\",\n \"0.60482174\",\n \"0.6046931\",\n \"0.60465133\",\n \"0.6035445\",\n \"0.60300994\",\n \"0.6008034\",\n \"0.6000354\",\n \"0.59863174\",\n \"0.5980952\",\n \"0.5971276\",\n \"0.5953805\"\n]"},"document_score":{"kind":"string","value":"0.6698751"},"document_rank":{"kind":"string","value":"23"}}},{"rowIdx":8576,"cells":{"query":{"kind":"string","value":"Creates a new identity provider in your tenancy. For more information, see `Identity Providers and Federation`__. You must specify your tenancy's OCID as the compartment ID in the request object. Remember that the tenancy is simply the root compartment. For information about OCIDs, see `Resource Identifiers`__. You must also specify a name for the `IdentityProvider`, which must be unique across all `IdentityProvider` objects in your tenancy and cannot be changed. You must also specify a description for the `IdentityProvider` (although it can be an empty string). It does not have to be unique, and you can change it anytime with"},"document":{"kind":"string","value":"def create_identity_provider(self, create_identity_provider_details, **kwargs):\n resource_path = \"/identityProviders\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_identity_provider got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_identity_provider_details,\n response_type=\"IdentityProvider\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_identity_provider_details,\n response_type=\"IdentityProvider\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_identity_provider(module, sdk, cloud, name):\n\n if module.check_mode:\n return True, None\n\n description = module.params.get('description')\n enabled = module.params.get('enabled')\n domain_id = module.params.get('domain_id')\n remote_ids = module.params.get('remote_ids')\n\n if enabled is None:\n enabled = True\n if remote_ids is None:\n remote_ids = []\n\n attributes = {\n 'domain_id': domain_id,\n 'enabled': enabled,\n 'remote_ids': remote_ids,\n }\n if description is not None:\n attributes['description'] = description\n\n try:\n idp = cloud.identity.create_identity_provider(id=name, **attributes)\n except sdk.exceptions.OpenStackCloudException as ex:\n module.fail_json(msg='Failed to create identity provider: {0}'.format(str(ex)))\n return (True, idp)","def create_provider(\n provider_id:UUID = Form(...),\n name:str = Form(...),\n qualification:str = Form(...),\n speciality:str = Form(...),\n phone:str = Form(...),\n department:Optional[str] = Form(\"N/A\"),\n organization:str = Form(...),\n location:Optional[str] = Form(\"N/A\"),\n address:str = Form(...),\n active:bool = Form(...)\n ):\n\n post_data = {\n \"name\": name,\n \"qualification\": qualification,\n \"speciality\": speciality,\n \"phone\": phone,\n \"department\": department,\n \"organization\": organization,\n \"location\": location,\n \"address\": address,\n \"active\": active\n }\n provider_data = open_for_reading()\n if str(provider_id) in provider_data.keys():\n response = {\"message\": \"ID already exists\"}\n else:\n provider_data[str(provider_id)] = post_data\n open_for_writing(data=provider_data)\n response = {\"message\": \"provider created\"}\n\n return response","def create_cloud_provider(providername):\n backend_name = request.get_json().get(\"backend\")\n service_name = request.get_json().get(\"service\")\n response = jsonify(\n admin.create_provider(\n current_app.scoped_session(),\n providername,\n backend=backend_name,\n service=service_name,\n )\n )\n return response","def create(self, identity, record=None, data=None, **kwargs):\n data['id'] = data['id'].lower()\n self._validate(data['id'])\n record['id'] = data['id']\n try:\n provider = record.__class__.pid.field._provider.create(record=record)\n except PIDAlreadyExists:\n raise ValidationError(\n 'A community with this identifier already exists.',\n field_name='id',\n )\n setattr(record, 'pid', provider.pid)","def m_create_identity(DID, domain_name, website, commercial_name, parent_node_account, password, overwrite):\n\n error, didDoc = create_identity(\n DID, domain_name, website, commercial_name, parent_node_account, password, overwrite)\n if error is not None:\n print(error)\n\n print(f\"Created\")","def add_new_provider(self, provider_name, provider_type, endpoints, zone_id, provider_region):\n try:\n result = self.client.post(self.providers_url, name=provider_name,\n type=ManageIQProvider.PROVIDER_TYPES[provider_type],\n zone={'id': zone_id},\n connection_configurations=endpoints,\n provider_region=provider_region)\n provider_id = result['results'][0]['id']\n self.changed = True\n except Exception as e:\n self.module.fail_json(msg=\"Failed to add provider. Error: {!r}\".format(e))\n return provider_id","def create(self, identity, data=None, record=None, **kwargs):\n self._populate_access_and_validate(identity, data, record, **kwargs)\n self._init_owners(identity, record, **kwargs)","def create(self, identity, data=None, record=None, **kwargs):\n if system_process in identity.provides:\n return\n\n member = {\n \"type\": \"user\",\n \"id\": str(identity.id),\n }\n self.service.members.add(\n # the user is not yet owner of the community (is being added)\n # therefore we cannot use `identity`\n system_identity,\n record.id,\n {\"members\": [member], \"role\": current_roles.owner_role.name},\n uow=self.uow,\n )\n\n # Invalidate the membership cache\n on_user_membership_change(identity=identity)","def __init__(__self__, *,\n identity_pool_id: pulumi.Input[str],\n identity_provider_name: pulumi.Input[str],\n principal_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n use_defaults: Optional[pulumi.Input[bool]] = None):\n pulumi.set(__self__, \"identity_pool_id\", identity_pool_id)\n pulumi.set(__self__, \"identity_provider_name\", identity_provider_name)\n if principal_tags is not None:\n pulumi.set(__self__, \"principal_tags\", principal_tags)\n if use_defaults is not None:\n pulumi.set(__self__, \"use_defaults\", use_defaults)","def test_create_identity(self):\n pass","def __init__(__self__, *,\n principal_id: Optional[pulumi.Input[str]] = None,\n tenant_id: Optional[pulumi.Input[str]] = None,\n type: Optional[pulumi.Input[Union[str, 'ManagedIdentityType']]] = None,\n user_assigned_identities: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\n if principal_id is not None:\n pulumi.set(__self__, \"principal_id\", principal_id)\n if tenant_id is not None:\n pulumi.set(__self__, \"tenant_id\", tenant_id)\n if type is not None:\n pulumi.set(__self__, \"type\", type)\n if user_assigned_identities is not None:\n pulumi.set(__self__, \"user_assigned_identities\", user_assigned_identities)","def _create_resource_provider(context, uuid, name,\n parent_provider_uuid=None):\n return {\n 'uuid': uuid,\n 'name': name,\n 'generation': 0,\n 'parent_provider_uuid': parent_provider_uuid\n }","def __init__(__self__, *,\n identity_pool_id: Optional[pulumi.Input[str]] = None,\n identity_provider_name: Optional[pulumi.Input[str]] = None,\n principal_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n use_defaults: Optional[pulumi.Input[bool]] = None):\n if identity_pool_id is not None:\n pulumi.set(__self__, \"identity_pool_id\", identity_pool_id)\n if identity_provider_name is not None:\n pulumi.set(__self__, \"identity_provider_name\", identity_provider_name)\n if principal_tags is not None:\n pulumi.set(__self__, \"principal_tags\", principal_tags)\n if use_defaults is not None:\n pulumi.set(__self__, \"use_defaults\", use_defaults)","def _create_resource_provider(self, uuid, name):\n url = \"/resource_providers\"\n payload = {\n 'uuid': uuid,\n 'name': name,\n }\n resp = self.post(url, payload)\n if resp.status_code == 201:\n msg = _LI(\"Created resource provider record via placement API \"\n \"for resource provider with UUID {0} and name {1}.\")\n msg = msg.format(uuid, name)\n LOG.info(msg)\n return objects.ResourceProvider(\n uuid=uuid,\n name=name,\n generation=1,\n )\n elif resp.status_code == 409:\n # Another thread concurrently created a resource provider with the\n # same UUID. Log a warning and then just return the resource\n # provider object from _get_resource_provider()\n msg = _LI(\"Another thread already created a resource provider \"\n \"with the UUID {0}. Grabbing that record from \"\n \"the placement API.\")\n msg = msg.format(uuid)\n LOG.info(msg)\n return self._get_resource_provider(uuid)\n else:\n msg = _LE(\"Failed to create resource provider record in \"\n \"placement API for UUID %(uuid)s. \"\n \"Got %(status_code)d: %(err_text)s.\")\n args = {\n 'uuid': uuid,\n 'status_code': resp.status_code,\n 'err_text': resp.text,\n }\n LOG.error(msg, args)","async def create_issuer(self, issuer_name: str, provider: str, **kwargs) -> CertificateIssuer:\n\n enabled = kwargs.pop(\"enabled\", None)\n account_id = kwargs.pop(\"account_id\", None)\n password = kwargs.pop(\"password\", None)\n organization_id = kwargs.pop(\"organization_id\", None)\n admin_contacts = kwargs.pop(\"admin_contacts\", None)\n\n if account_id or password:\n issuer_credentials = self._models.IssuerCredentials(account_id=account_id, password=password)\n else:\n issuer_credentials = None\n if admin_contacts:\n admin_details: Optional[List[Any]] = [\n self._models.AdministratorDetails(\n first_name=contact.first_name,\n last_name=contact.last_name,\n email_address=contact.email,\n phone=contact.phone,\n )\n for contact in admin_contacts\n ]\n else:\n admin_details = None\n if organization_id or admin_details:\n organization_details = self._models.OrganizationDetails(id=organization_id, admin_details=admin_details)\n else:\n organization_details = None\n if enabled is not None:\n issuer_attributes = self._models.IssuerAttributes(enabled=enabled)\n else:\n issuer_attributes = None\n\n parameters = self._models.CertificateIssuerSetParameters(\n provider=provider,\n credentials=issuer_credentials,\n organization_details=organization_details,\n attributes=issuer_attributes,\n )\n\n issuer_bundle = await self._client.set_certificate_issuer(\n vault_base_url=self.vault_url, issuer_name=issuer_name, parameter=parameters, **kwargs\n )\n return CertificateIssuer._from_issuer_bundle(issuer_bundle=issuer_bundle)","def create_namespaced_identity(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_identity\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_identity`\")\n\n resource_path = '/oapi/v1/identities'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Identity',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def __init__(__self__,\n resource_name: str,\n args: OpenIdConnectProviderArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def create(self, identity, data=None, record=None, **kwargs):\n if record.access.visibility != \"public\":\n return\n\n community_set = self._create_set_from_community(record)\n # NOTE: will be indexed via a listener in oaiserver module\n db.session.add(community_set)","def create(self, identity, data=None, record=None, **kwargs):\n self._populate_access_and_validate(identity, data, record, **kwargs)","def _create_entity_in_domain(entity_type, domain_id):\n if entity_type == 'users':\n new_entity = unit.new_user_ref(domain_id=domain_id)\n new_entity = self.identity_api.create_user(new_entity)\n elif entity_type == 'groups':\n new_entity = unit.new_group_ref(domain_id=domain_id)\n new_entity = self.identity_api.create_group(new_entity)\n elif entity_type == 'roles':\n new_entity = self._create_role(domain_id=domain_id)\n else:\n # Must be a bad test plan\n raise exception.NotImplemented()\n return new_entity","def create_with_instance_principal(iam_auth_uri=None):\n if iam_auth_uri is None:\n return SignatureProvider(\n oci.auth.signers.InstancePrincipalsSecurityTokenSigner())\n else:\n return SignatureProvider(\n oci.auth.signers.InstancePrincipalsSecurityTokenSigner(\n federation_endpoint=iam_auth_uri))","def __init__(__self__,\n resource_name: str,\n args: IdentityPoolProviderPrincipalTagArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def __init__(self, region, user_pool_id, app_client_id):\n self.region = region\n self.user_pool_id = user_pool_id\n self.client_id = app_client_id\n self.client = boto3.client('cognito-idp', region_name=self.region)","def register_provider(args):\n if len(args) == 0:\n click.echo(\"Usage: mephisto register --arg1:value --arg2:value\")\n return\n\n from mephisto.core.local_database import LocalMephistoDB\n from mephisto.core.registry import get_crowd_provider_from_type\n from mephisto.core.argparse_parser import parse_arg_dict, get_extra_argument_dicts\n\n provider_type, requester_args = args[0], args[1:]\n args_dict = dict(arg.split(\":\") for arg in requester_args)\n transformed = dict(\n (key, {\"option_string\": key, \"value\": value})\n for (key, value) in args_dict.items()\n )\n\n crowd_provider = get_crowd_provider_from_type(provider_type)\n RequesterClass = crowd_provider.RequesterClass\n\n if len(requester_args) == 0:\n from tabulate import tabulate\n\n params = get_extra_argument_dicts(RequesterClass)\n for param in params:\n click.echo(param[\"desc\"])\n click.echo(tabulate(param[\"args\"].values(), headers=\"keys\"))\n return\n\n try:\n parsed_options = parse_arg_dict(RequesterClass, transformed)\n except Exception as e:\n click.echo(str(e))\n\n if \"name\" not in parsed_options:\n click.echo(\"No name was specified for the requester.\")\n\n db = LocalMephistoDB()\n requesters = db.find_requesters(requester_name=parsed_options[\"name\"])\n if len(requesters) == 0:\n requester = RequesterClass.new(db, parsed_options[\"name\"])\n else:\n requester = requesters[0]\n try:\n requester.register(parsed_options)\n click.echo(\"Registered successfully.\")\n except Exception as e:\n click.echo(str(e))","def add_tomcat7_idp():\n pass","def sso_test_create_user(request, idp_slug):\n if settings.SERVER_ENVIRONMENT not in ['staging']:\n raise Http404()\n\n username = request.GET.get('username')\n if username:\n prepare_session_with_sso_username(request, username)\n\n invitation_uuid = request.GET.get('invitation')\n invitation = Invitation.objects.get(uuid=invitation_uuid)\n if invitation:\n prepare_session_for_sso_invitation(request, invitation)\n\n return HttpResponseRedirect(reverse(\"sso_saml_login\", args=(idp_slug,)))","def test_create_resource_provider(self):\n uuid = uuids.compute_node\n name = 'computehost'\n resp_mock = mock.Mock(status_code=200)\n self.ks_adap_mock.post.return_value = resp_mock\n\n self.assertEqual(\n resp_mock.json.return_value,\n self.client._create_resource_provider(self.context, uuid, name))\n\n expected_payload = {\n 'uuid': uuid,\n 'name': name,\n }\n\n expected_url = '/resource_providers'\n self.ks_adap_mock.post.assert_called_once_with(\n expected_url, json=expected_payload, microversion='1.20',\n global_request_id=self.context.global_id)","def __init__(__self__, *,\n identity_namespace: Optional[pulumi.Input[str]] = None,\n identity_provider: Optional[pulumi.Input[str]] = None,\n workload_pool: Optional[pulumi.Input[str]] = None):\n if identity_namespace is not None:\n pulumi.set(__self__, \"identity_namespace\", identity_namespace)\n if identity_provider is not None:\n pulumi.set(__self__, \"identity_provider\", identity_provider)\n if workload_pool is not None:\n pulumi.set(__self__, \"workload_pool\", workload_pool)","def create(self, request, *args, **kwargs):\n \n serializer = self.serializer_class(data=request.data)\n serializer.is_valid(raise_exception=True)\n provider = serializer.data.get('provider')\n\n access_token = serializer.data.get('access_token')\n user = None if request.user.is_anonymous else request.user\n\n # strategy sets up the required custom configuration for working with Django\n strategy = load_strategy(request)\n try:\n # Loads backends defined on SOCIAL_AUTH_AUTHENTICATION_BACKENDS,\n # checks the appropriate one by using the provider given\n\n backend = load_backend(strategy=strategy, name=provider, redirect_uri=None)\n access_token = self.update_access_token(backend, request, access_token)\n\n except MissingBackend:\n return Response({\n \"errors\": {\n \"provider\": [\"Invalid provider\"]\n }\n }, status=status.HTTP_400_BAD_REQUEST)\n\n try:\n # creates a user in our user model \n # If the user exists, we just authenticate the user.\n user = backend.do_auth(access_token, user=user)\n\n except BaseException as error:\n return Response({\"error\": str(error)}, status=status.HTTP_400_BAD_REQUEST)\n\n # Since the user is using social authentication, there is no need for email verification.\n # We therefore set the user to active here.\n # And also subscribe them for notifications\n\n user.is_active = True\n user.save()\n\n subscribe_user(user, self.subscription_class)\n\n serializer = UserSerializer(user)\n \n return Response(serializer.data, status=status.HTTP_200_OK)","def createTenant(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def create_epic():\n client = RequestManager()\n client.set_method(\"POST\")\n client.set_endpoint(\"/projects/{0}/epics\".format(STORED_ID['project_id']))\n name = \"\".join(choices(string.ascii_letters, k=6))\n body = {\"name\": name}\n client.set_body(json.dumps(body))\n response = client.execute_request()\n STORED_ID['epic_id'] = response.json()['id']","def application_create(request, name, redirect_uris, scopes=['all_info'],\n client_type='confidential', description=None,\n grant_type='authorization_code', **kwargs):\n manager = api.keystone.keystoneclient(request, admin=True).oauth2.consumers\n return manager.create(name=name,\n redirect_uris=redirect_uris,\n description=description,\n scopes=scopes,\n client_type=client_type,\n grant_type=grant_type,\n **kwargs)","def __init__(__self__, *,\n auth_type: pulumi.Input[str],\n client_id: pulumi.Input[str],\n subscription_id: pulumi.Input[str]):\n pulumi.set(__self__, \"auth_type\", 'userAssignedIdentity')\n pulumi.set(__self__, \"client_id\", client_id)\n pulumi.set(__self__, \"subscription_id\", subscription_id)","def create(self, request):\n\n return ObtainAuthToken().post(request)","def register_api_provider(api_provider, contact_info):\n\n req = requests.post(domain_name + \"register_api_provider?\",\n data=json.dumps({'api_provider': api_provider,\n 'contact_info': contact_info}),\n headers={'Content-type': 'application/json',\n 'Accept': 'application/json'})\n response = req.json()\n return response","def create(self, request):\n return ObtainAuthToken().post(request)","def __init__(__self__, *,\n auth_type: pulumi.Input[str]):\n pulumi.set(__self__, \"auth_type\", 'systemAssignedIdentity')","def create_customer(email=None, name=None, user_type='customer'):\n if user_type == 'charity':\n stripe.api_key = Config.STRIPE_SECRET_KEY_FOR_PLAN\n else:\n stripe.api_key = Config.STRIPE_SECRET_KEY\n if email and name:\n customer = stripe.Customer.create(email=email, name=name)\n else:\n customer = stripe.Customer.create()\n return customer.id","def __init__(__self__, *,\n cognitive_service_region: Optional[pulumi.Input[str]] = None,\n cognitive_service_resource_id: Optional[pulumi.Input[str]] = None,\n cognitive_service_subscription_key: Optional[pulumi.Input[str]] = None,\n default_locale: Optional[pulumi.Input[str]] = None,\n id: Optional[pulumi.Input[str]] = None,\n provider_name: Optional[pulumi.Input[str]] = None):\n if cognitive_service_region is not None:\n pulumi.set(__self__, \"cognitive_service_region\", cognitive_service_region)\n if cognitive_service_resource_id is not None:\n pulumi.set(__self__, \"cognitive_service_resource_id\", cognitive_service_resource_id)\n if cognitive_service_subscription_key is not None:\n pulumi.set(__self__, \"cognitive_service_subscription_key\", cognitive_service_subscription_key)\n if default_locale is not None:\n pulumi.set(__self__, \"default_locale\", default_locale)\n if id is not None:\n pulumi.set(__self__, \"id\", id)\n if provider_name is not None:\n pulumi.set(__self__, \"provider_name\", provider_name)","def identity_provider(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"identity_provider\")","def get_identity_provider(self, identity_provider_id, **kwargs):\n resource_path = \"/identityProviders/{identityProviderId}\"\n method = \"GET\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"get_identity_provider got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"identityProviderId\": identity_provider_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"IdentityProvider\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"IdentityProvider\")","def test_create_resource_provider_with_parent(self):\n parent_uuid = uuids.parent\n uuid = uuids.compute_node\n name = 'computehost'\n resp_mock = mock.Mock(status_code=200)\n self.ks_adap_mock.post.return_value = resp_mock\n\n self.assertEqual(\n resp_mock.json.return_value,\n self.client._create_resource_provider(\n self.context,\n uuid,\n name,\n parent_provider_uuid=parent_uuid,\n )\n )\n\n expected_payload = {\n 'uuid': uuid,\n 'name': name,\n 'parent_provider_uuid': parent_uuid,\n }\n expected_url = '/resource_providers'\n self.ks_adap_mock.post.assert_called_once_with(\n expected_url, json=expected_payload, microversion='1.20',\n global_request_id=self.context.global_id)","def create_identity(self, realm=None, type=\"users\", user_data=None):\n if not user_data:\n raise ValueError(\"Please provide correct user information.\")\n\n user_data = self._to_string(data=user_data)\n type = self._type_validator(type=type)\n uri = self._uri_realm_creator(realm=realm, uri=type + '/?_action=create')\n data = self._post(uri=uri, data=user_data, headers=self.headers)\n return data.json()","def create_tenant(self, tenant_info):\n LOG_OBJ.debug(\"Creating Tenant:%s\" % tenant_info['project_name'])\n _tenant_name = tenant_info['project_name']\n _user_name = tenant_info.get('user_name', _tenant_name + \"_user\")\n _password = tenant_info.get('password', _tenant_name + \"_pass\")\n\n _url = \"http://\" + self.host_ip + \":35357/v2.0/tenants\"\n _headers = {'Content-type': 'application/json',\n 'x-auth-token': self.cloud_admin_info['token_project']}\n _tenant_data = {\"tenant\": {\"enabled\": True, \"name\": _tenant_name,\n \"description\": \"Testing API 3\"}}\n\n _body = json.dumps(_tenant_data)\n\n response = self.request(\"POST\", _url, _headers, _body)\n if response is None:\n LOG_OBJ.error(\"No response from Server while creating tenant: %s\"\n % _tenant_name)\n return response\n if response.status not in [200, 201, 202, 203, 204]:\n LOG_OBJ.error(\"Create tenant Failed with status %s \" %\n response.status)\n return response.status\n\n output = json.loads(response.data)\n LOG_OBJ.info(\"Created tenant: %s successfully.\" % _tenant_name)\n\n _tenant_id = output['tenant']['id']\n # If user id is passed then, directly add that user to the tenant.\n # otherwise Create a new user.\n _user_id = tenant_info.get('user_id', None)\n if not _user_id:\n _user_data = {\"user\": {\"email\": None,\n \"password\": _password,\n \"enabled\": True,\n \"name\": _user_name,\n \"tenantId\": _tenant_id}}\n _user_id = self.create_user(_user_data)\n if not isinstance(_user_id, unicode):\n return\n tenant_info['userID'] = _user_id\n\n # Add the user roles.\n for role_name in tenant_info['roles']:\n role_id = self.get_role_id(role_name)\n if not isinstance(role_id, unicode):\n return\n # Add user role.\n if not self.add_user_role(_tenant_id, _user_id, role_id):\n return\n # Get the token.\n token_id = self.get_token(_tenant_name, _user_name, _password)\n if not isinstance(token_id, unicode):\n return\n # Set the new context. note: This is v2 token, so only project scope.\n self.set_tenant_info(_tenant_name, token_id, token_id, _tenant_id)\n\n # Adding Security Group Rules\n # Add the ICMP rule.\n # if not isinstance(self.add_security_group_rules(\"icmp\"), bool):\n # return\n # Add the rule for ssh\n # if not isinstance(self.add_security_group_rules(\n # \"tcp\", from_port='22', to_port='22'), bool):\n # return\n # Add the rule for all udp\n # if not isinstance(self.add_security_group_rules(\n # \"udp\", from_port='1', to_port='65535'), bool):\n # return\n\n # Modify the tenant quota.\n # if not isinstance(self.set_quota(_tenant_id), bool):\n # return\n # Update the quota\n # fields = {\"network\": 50, \"subnet\": 50, \"port\": 100, \"floatingip\": 50}\n # quotas = self.quota_update(_tenant_id, fields)\n # if not isinstance(quotas, dict):\n # return\n # LOG_OBJ.info(\"Quota for tenant[%s] is:%s\" % (_tenant_id,\n # str(quotas)))\n return _tenant_id","def testCreateOrg(self):\n self.timeline.orgSignup()\n self.data.createProfile()\n self.record.createOrgApp('new_org', self.data.user)\n\n url = '/gci/profile/organization/' + self.gci.key().name()\n create_url = url + '?org_id=new_org'\n response = self.get(create_url)\n self.assertResponseOK(response)\n self.assertOrgProfilePageTemplatesUsed(response)\n \n postdata = {\n 'founder': self.data.user, 'home': self.createDocument().key(),\n 'scope': self.gci, 'irc_channel': 'irc://example.com',\n 'pub_mailing_list': 'http://example.com',\n }\n response, properties = self.modelPost(create_url, GCIOrganization, postdata)\n self.assertResponseRedirect(response, url + '/new_org?validated')\n profile = db.get(self.data.profile.key())\n self.assertEqual(1, len(profile.org_admin_for))","def create_tenant(tenant):\n exists = identity.Tenant.query.filter_by(name=tenant.name).first()\n if exists:\n abort(409, \"Tenant Already Exists\")\n db.session.add(tenant)\n db.session.commit()\n return tenant.id","def __init__(self, *args, **kwargs):\n super(EnterpriseCustomerIdentityProviderAdminForm, self).__init__(*args, **kwargs)\n idp_choices = utils.get_idp_choices()\n if idp_choices is not None:\n self.fields['provider_id'] = forms.TypedChoiceField(choices=idp_choices)","def create_org(self, provider='qbo', status=CONNECTED, set_provider_config=True):\n\n if set_provider_config:\n provider_config = self.provider_configs[provider]\n else:\n provider_config = None\n\n org = Org(provider=provider, id='test', status=status, provider_config=provider_config).put()\n\n OrgCredentials(id='test', parent=org, token={'expires_at': 0}).put()","async def register_investigator(request):\n required_fields = ['name']\n general.validate_fields(required_fields, request.json)\n\n name = request.json.get('name')\n\n clinic_signer = request.app.config.SIGNER_INVESTIGATOR # .get_public_key().as_hex()\n\n client_txn = consent_transaction.create_investigator_client(\n txn_signer=clinic_signer,\n batch_signer=clinic_signer\n )\n clinic_txn = ehr_transaction.create_investigator(\n txn_signer=clinic_signer,\n batch_signer=clinic_signer,\n name=name\n )\n batch, batch_id = ehr_transaction.make_batch_and_id([client_txn, clinic_txn], clinic_signer)\n\n await security_messaging.add_investigator(\n request.app.config.VAL_CONN,\n request.app.config.TIMEOUT,\n [batch])\n\n try:\n await security_messaging.check_batch_status(\n request.app.config.VAL_CONN, [batch_id])\n except (ApiBadRequest, ApiInternalError) as err:\n # await auth_query.remove_auth_entry(\n # request.app.config.DB_CONN, request.json.get('email'))\n raise err\n\n return response.json(body={'status': general.DONE},\n headers=general.get_response_headers())","def create_manager(self, username, tenancy):\n raise NotImplementedError","def makeIdentity(self) -> None:\n ...","def create_tenant(tenant_name, description, enabled, auth_admin_url, admin_token):\n keystone = get_client(auth_admin_url, admin_token)\n tenant = keystone.tenants.create(tenant_name=tenant_name, description=description, enabled=enabled)\n print tenant\n return tenant.to_dict()","async def async_oauth_create_entry(self, data):\n\n await self.async_set_unique_id(unique_id=f\"{DOMAIN}Cloud\")\n return self.async_create_entry(title=f\"{DOMAIN}Cloud\", data=data)","def __init__(__self__,\n resource_name: str,\n opts: Optional[pulumi.ResourceOptions] = None,\n identity_pool_id: Optional[pulumi.Input[str]] = None,\n identity_provider_name: Optional[pulumi.Input[str]] = None,\n principal_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n use_defaults: Optional[pulumi.Input[bool]] = None,\n __props__=None):\n ...","def __init__(__self__, *,\n identity_type: Optional[pulumi.Input[Union[str, 'CmkIdentityType']]] = None,\n user_assigned_identity_resource_id: Optional[pulumi.Input[str]] = None):\n if identity_type is not None:\n pulumi.set(__self__, \"identity_type\", identity_type)\n if user_assigned_identity_resource_id is not None:\n pulumi.set(__self__, \"user_assigned_identity_resource_id\", user_assigned_identity_resource_id)","def create_partner(name):\n\n return Partner.objects.create(name=name)","def post(self):\n data = request.json\n return save_new_provider(data=data)","def identity_provider_name(self) -> pulumi.Input[str]:\n return pulumi.get(self, \"identity_provider_name\")","def __init__(__self__, *,\n principal_id: str,\n tenant_id: str,\n type: Optional[str] = None,\n user_assigned_identities: Optional[Mapping[str, 'outputs.UserAssignedIdentityResponse']] = None):\n pulumi.set(__self__, \"principal_id\", principal_id)\n pulumi.set(__self__, \"tenant_id\", tenant_id)\n if type is not None:\n pulumi.set(__self__, \"type\", type)\n if user_assigned_identities is not None:\n pulumi.set(__self__, \"user_assigned_identities\", user_assigned_identities)","def __init__(__self__, *,\n principal_id: str,\n tenant_id: str,\n type: Optional[str] = None,\n user_assigned_identities: Optional[Mapping[str, 'outputs.UserAssignedIdentityResponse']] = None):\n pulumi.set(__self__, \"principal_id\", principal_id)\n pulumi.set(__self__, \"tenant_id\", tenant_id)\n if type is not None:\n pulumi.set(__self__, \"type\", type)\n if user_assigned_identities is not None:\n pulumi.set(__self__, \"user_assigned_identities\", user_assigned_identities)","def test_create_provider(self):\n url = reverse('provider-list')\n data = {'name': 'foo'}\n response = self.client.post(url, data, format='json')\n self.assertEqual(response.status_code, status.HTTP_201_CREATED)\n self.assertEqual(Provider.objects.count(), 1)","def CreateOIDCClient(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def create(self, validated_data, request: HttpRequest = None):\n # Writing of .get(\"xy\", None) or None makes sure that empty strings will be mapped to None\n user = user_helper.get_user(request=request)\n get_capabilities_uri = validated_data.get(\"uri\", None) or None\n registering_with_group = validated_data.get(\"group\", None) or None\n registering_for_org = validated_data.get(\"for-org\", None) or None\n has_ext_auth = validated_data.get(\"ext-auth\", False) or False\n ext_auth_username = validated_data.get(\"ext-username\", None) or None\n ext_auth_password = validated_data.get(\"ext-password\", None) or None\n ext_auth_type = validated_data.get(\"ext-auth-type\", None) or None\n\n # Split uri in components as it is done with RegisterNewServiceWizardPage1\n url_dict = service_helper.split_service_uri(get_capabilities_uri)\n ogc_request = url_dict[\"request\"]\n ogc_service = url_dict[\"service\"].value\n ogc_version = url_dict[\"version\"]\n uri = url_dict[\"base_uri\"]\n\n init_data = {\n \"ogc_request\": ogc_request,\n \"ogc_service\": ogc_service,\n \"ogc_version\": ogc_version,\n \"uri\": uri,\n \"registering_with_group\": registering_with_group,\n \"registering_for_other_organization\": registering_for_org,\n \"service_needs_authentication\": has_ext_auth,\n \"username\": ext_auth_username,\n \"password\": ext_auth_password,\n \"authentication_type\": ext_auth_type,\n }\n\n # Use RegisterNewResourceWizardPage2 workflow as for frontend registration\n form = RegisterNewResourceWizardPage2(\n data=init_data,\n request=request\n )\n if form.is_valid():\n pending_task = service_helper.create_new_service(form, user)\n return pending_task\n return form","def create(self,request):\n return CustomAuthToken().post(request)","def __init__(__self__, *,\n authorizations: Sequence['outputs.AuthorizationResponse'],\n managed_by_tenant_id: str,\n managed_by_tenant_name: str,\n managee_tenant_id: str,\n managee_tenant_name: str,\n provisioning_state: str,\n description: Optional[str] = None,\n eligible_authorizations: Optional[Sequence['outputs.EligibleAuthorizationResponse']] = None,\n registration_definition_name: Optional[str] = None):\n pulumi.set(__self__, \"authorizations\", authorizations)\n pulumi.set(__self__, \"managed_by_tenant_id\", managed_by_tenant_id)\n pulumi.set(__self__, \"managed_by_tenant_name\", managed_by_tenant_name)\n pulumi.set(__self__, \"managee_tenant_id\", managee_tenant_id)\n pulumi.set(__self__, \"managee_tenant_name\", managee_tenant_name)\n pulumi.set(__self__, \"provisioning_state\", provisioning_state)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if eligible_authorizations is not None:\n pulumi.set(__self__, \"eligible_authorizations\", eligible_authorizations)\n if registration_definition_name is not None:\n pulumi.set(__self__, \"registration_definition_name\", registration_definition_name)","def _create_citizen(self, citizen_id, relatives):\n return models.Citizen(\n citizen_id=citizen_id,\n town='a', street='b', building='c', apartment=1, name='e', birth_date='01.01.1970',\n gender='male', relatives=relatives\n )","def setup_test_tenant(self):\n self.test_tenant = rand_name('test_tenant_')\n self.test_description = rand_name('desc_')\n resp, self.tenant = self.client.create_tenant(\n name=self.test_tenant,\n description=self.test_description)\n self.tenants.append(self.tenant)","def __init__(__self__,\n resource_name: str,\n args: ApplicationFederatedIdentityCredentialArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def __init__(__self__, *,\n authorizations: Optional[Sequence['outputs.AuthorizationResponse']] = None,\n description: Optional[str] = None,\n eligible_authorizations: Optional[Sequence['outputs.EligibleAuthorizationResponse']] = None,\n managed_by_tenant_id: Optional[str] = None,\n managed_by_tenant_name: Optional[str] = None,\n managee_tenant_id: Optional[str] = None,\n managee_tenant_name: Optional[str] = None,\n provisioning_state: Optional[str] = None,\n registration_definition_name: Optional[str] = None):\n if authorizations is not None:\n pulumi.set(__self__, \"authorizations\", authorizations)\n if description is not None:\n pulumi.set(__self__, \"description\", description)\n if eligible_authorizations is not None:\n pulumi.set(__self__, \"eligible_authorizations\", eligible_authorizations)\n if managed_by_tenant_id is not None:\n pulumi.set(__self__, \"managed_by_tenant_id\", managed_by_tenant_id)\n if managed_by_tenant_name is not None:\n pulumi.set(__self__, \"managed_by_tenant_name\", managed_by_tenant_name)\n if managee_tenant_id is not None:\n pulumi.set(__self__, \"managee_tenant_id\", managee_tenant_id)\n if managee_tenant_name is not None:\n pulumi.set(__self__, \"managee_tenant_name\", managee_tenant_name)\n if provisioning_state is not None:\n pulumi.set(__self__, \"provisioning_state\", provisioning_state)\n if registration_definition_name is not None:\n pulumi.set(__self__, \"registration_definition_name\", registration_definition_name)","def create_identity(msg: CreateIdentity_request):\n \n # Check if we have received some data in the POST\n if len(msg.DID) == 0:\n log.error(\"No data received\")\n raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=\"No data received\")\n\n # Create the identity using the library\n try:\n error, didDoc = tf.create_identity_subnode(\n msg.DID, msg.domain_name, msg.website, msg.commercial_name, msg.new_privatekey, msg.parent_privatekey)\n except Exception as e:\n detail=str(e)\n log.error(detail)\n raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=detail)\n\n if error is not None:\n log.error(error)\n raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=error)\n\n return {\"didDoc\": didDoc.to_dict()}","def catalog_alias_create(self, args):\n try:\n if args.id:\n alias = self.server.connect_ermrest_alias(args.id)\n try:\n if alias.retrieve():\n print(\"Catalog alias already exists\")\n return\n except requests.HTTPError as e:\n if e.response.status_code == 404:\n pass\n else:\n raise\n owner = args.owner if args.owner else None\n alias = self.server.create_ermrest_alias(args.id, owner, args.alias_target)\n if not args.quiet:\n print(\"Created new catalog alias %s with the following configuration:\\n\" % alias.alias_id)\n pp(alias.retrieve())\n except HTTPError as e:\n if e.response.status_code == requests.codes.not_found:\n raise ResourceException('Catalog alias not found', e)\n elif e.response.status_code == requests.codes.conflict:\n raise ResourceException(\"Catalog alias already exists\", e)\n else:\n raise","def __init__(__self__, *,\n authentication_type: Optional[pulumi.Input[str]] = None,\n connection_string: Optional[pulumi.Input[str]] = None,\n endpoint_uri: Optional[pulumi.Input[str]] = None,\n entity_path: Optional[pulumi.Input[str]] = None,\n identity_id: Optional[pulumi.Input[str]] = None,\n iothub_id: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None,\n resource_group_name: Optional[pulumi.Input[str]] = None):\n if authentication_type is not None:\n pulumi.set(__self__, \"authentication_type\", authentication_type)\n if connection_string is not None:\n pulumi.set(__self__, \"connection_string\", connection_string)\n if endpoint_uri is not None:\n pulumi.set(__self__, \"endpoint_uri\", endpoint_uri)\n if entity_path is not None:\n pulumi.set(__self__, \"entity_path\", entity_path)\n if identity_id is not None:\n pulumi.set(__self__, \"identity_id\", identity_id)\n if iothub_id is not None:\n pulumi.set(__self__, \"iothub_id\", iothub_id)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if resource_group_name is not None:\n pulumi.set(__self__, \"resource_group_name\", resource_group_name)","def __init__(__self__, *,\n acs_endpoint: Optional[pulumi.Input[str]] = None,\n acs_resource_id: Optional[pulumi.Input[str]] = None,\n acs_secret: Optional[pulumi.Input[str]] = None,\n cognitive_service_region: Optional[pulumi.Input[str]] = None,\n cognitive_service_resource_id: Optional[pulumi.Input[str]] = None,\n cognitive_service_subscription_key: Optional[pulumi.Input[str]] = None,\n default_locale: Optional[pulumi.Input[str]] = None,\n id: Optional[pulumi.Input[str]] = None,\n offer_type: Optional[pulumi.Input[str]] = None,\n phone_number: Optional[pulumi.Input[str]] = None):\n if acs_endpoint is not None:\n pulumi.set(__self__, \"acs_endpoint\", acs_endpoint)\n if acs_resource_id is not None:\n pulumi.set(__self__, \"acs_resource_id\", acs_resource_id)\n if acs_secret is not None:\n pulumi.set(__self__, \"acs_secret\", acs_secret)\n if cognitive_service_region is not None:\n pulumi.set(__self__, \"cognitive_service_region\", cognitive_service_region)\n if cognitive_service_resource_id is not None:\n pulumi.set(__self__, \"cognitive_service_resource_id\", cognitive_service_resource_id)\n if cognitive_service_subscription_key is not None:\n pulumi.set(__self__, \"cognitive_service_subscription_key\", cognitive_service_subscription_key)\n if default_locale is not None:\n pulumi.set(__self__, \"default_locale\", default_locale)\n if id is not None:\n pulumi.set(__self__, \"id\", id)\n if offer_type is not None:\n pulumi.set(__self__, \"offer_type\", offer_type)\n if phone_number is not None:\n pulumi.set(__self__, \"phone_number\", phone_number)","def createCustomer(self, **params):\n return self.__req('create_customer', params)","def CreateIDPConnector(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def create_tenant(name, domain):\n manager = get_manager()\n tenant = manager.resolve_tenant_id(name, domain=domain)\n if not tenant:\n manager.create_tenant(tenant_name=name,\n domain=domain,\n description='Created by Juju')\n log(\"Created new tenant '%s' in domain '%s'\" % (name, domain),\n level=DEBUG)\n return\n\n log(\"Tenant '%s' already exists.\" % name, level=DEBUG)","def m_create_test_identities():\n\n # Get the ROOT account (it was created in the deployment of the Smart Contracts)\n ROOT_address, ROOT_key = wallet.account_from_name(\"ROOT\", \"ThePassword\")\n\n # Create the Alastria account for node \"ala\"\n print(f\"\\n==> Creating the Alastria account\")\n Alastria_account = wallet.new_account(\n \"Alastria\", \"ThePassword\")\n alakey = Alastria_account.key\n print(f\"Alastria key: {alakey}\")\n\n print(f\"Done\")\n\n # Set the subnode \"ala\"\n print(f\"\\n==> Creating the ala subnode in the Trust Framework\")\n success, _, _ = ens.setSubnodeOwner(\n node_name=\"root\",\n label=\"ala\",\n new_owner_address=Alastria_account.address,\n current_owner_key=ROOT_key\n )\n print(f\"ala subnode created\")\n\n # Assign the name for reverse resolution\n resolver.setName(\"ala\", \"ala\", Alastria_account.key)\n\n # And assign approval to the PublicResolver contract so it can call ENS methods on behalf of Alastria\n print(f\"Resolver address for ROOT: {resolver.address()}\")\n ens.setApprovalForAll(resolver.address(), True, Alastria_account.key)\n\n ################################\n # Heathrow airport\n print(f\"\\n==> Creating the Heathrow identity\")\n\n DID = \"did:elsi:VATGB-927365404\"\n domain_name = \"heathrow.ala\"\n website = \"www.heathrow.com\"\n commercial_name = \"Heathrow Airport Limited\"\n\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \"Alastria\", \"ThePassword\", False)\n if didDoc is not None:\n pprint(didDoc)\n\n ################################\n # AENA\n print(f\"\\n==> Creating the AENA identity\")\n\n DID = \"did:elsi:VATES-A86212420\"\n domain_name = \"aena.ala\"\n website = \"www.aena.es\"\n commercial_name = \"Aena\"\n\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \"Alastria\", \"ThePassword\", False)\n if didDoc is not None:\n pprint(didDoc)\n\n ################################\n # Lanzarote airport\n # The airport belongs to AENA and does not have independent entity (shares the same VAT, for example)\n # In production, the node should be created by AENA, as a subnode controlled by them.\n # In this PoC, the node is created automatically to facilitate the tests\n print(f\"\\n==> Creating the César Manrique airport identity\")\n\n DID = \"did:elsi:VATES-A86212420-1\"\n domain_name = \"ace.ala\"\n website = \"www.aena.es/es/aeropuerto-lanzarote\"\n commercial_name = \"Aeropuerto de Lanzarote-Cesar Manrique\"\n\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \"Alastria\", \"ThePassword\", False)\n if didDoc is not None:\n pprint(didDoc)\n\n ################################\n # Metrovacesa\n print(f\"\\n==> Creating the Metrovacesa identity\")\n\n DID = \"did:elsi:VATES-A87471264\"\n domain_name = \"metrovacesa.ala\"\n website = \"metrovacesa.com\"\n commercial_name = \"Metrovacesa\"\n\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \"Alastria\", \"ThePassword\", False)\n if didDoc is not None:\n pprint(didDoc)\n\n ################################\n # IN2\n print(f\"\\n==> Creating the IN2 identity\")\n\n DID = \"did:elsi:VATES-B60645900\"\n domain_name = \"in2.ala\"\n website = \"www.in2.es\"\n commercial_name = \"IN2 Innovating 2gether\"\n\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \"Alastria\", \"ThePassword\", False)\n if didDoc is not None:\n pprint(didDoc)\n\n ################################\n # Perfect Health\n print(f\"\\n==> Creating the Perfect Health identity\")\n\n DID = \"did:elsi:VATES-X12345678X\"\n domain_name = \"perfecthealth.ala\"\n website = \"www.perfecthealth.org\"\n commercial_name = \"Perfect Health plc\"\n\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \"Alastria\", \"ThePassword\", False)\n if didDoc is not None:\n pprint(didDoc)\n\n ################################\n # BME\n print(f\"\\n==> Creating the BME identity\")\n\n DID = \"did:elsi:VATES-A83246314\"\n domain_name = \"bme.ala\"\n website = \"www.bolsasymercados.es\"\n commercial_name = \"Bolsas y Mercados Españoles\"\n\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \"Alastria\", \"ThePassword\", False)\n if didDoc is not None:\n pprint(didDoc)","def create_endpoint(coriolis, name, platform_type, connection_info,\n barbican=None, description=''):\n # check provider type is installed server-side:\n providers_dict = coriolis.providers.list().to_dict()\n if platform_type not in providers_dict:\n raise ValueError(\n 'platform_type must be one of %s' % providers_dict.keys())\n\n # if Barbican is available, store the connection info in it:\n if barbican:\n secret_ref = store_barbican_secret_for_coriolis(\n barbican, connection_info, name='Coriolis Endpoint %s' % name)\n connection_info = {'secret_ref': secret_ref}\n\n # create the endpoint:\n endpoint = coriolis.endpoints.create(\n name, platform_type, connection_info, description)\n\n return endpoint","def create(self, identity, data=None, record=None, **kwargs):\n record.metadata = data.get('metadata', {})","def create_identity(name, tags=None, typ=None):\n if tags:\n tags = frozenset(tags.items())\n return (typ, name, tags)","def __init__(__self__, *,\n iothub_id: pulumi.Input[str],\n resource_group_name: pulumi.Input[str],\n authentication_type: Optional[pulumi.Input[str]] = None,\n connection_string: Optional[pulumi.Input[str]] = None,\n endpoint_uri: Optional[pulumi.Input[str]] = None,\n entity_path: Optional[pulumi.Input[str]] = None,\n identity_id: Optional[pulumi.Input[str]] = None,\n name: Optional[pulumi.Input[str]] = None):\n pulumi.set(__self__, \"iothub_id\", iothub_id)\n pulumi.set(__self__, \"resource_group_name\", resource_group_name)\n if authentication_type is not None:\n pulumi.set(__self__, \"authentication_type\", authentication_type)\n if connection_string is not None:\n pulumi.set(__self__, \"connection_string\", connection_string)\n if endpoint_uri is not None:\n pulumi.set(__self__, \"endpoint_uri\", endpoint_uri)\n if entity_path is not None:\n pulumi.set(__self__, \"entity_path\", entity_path)\n if identity_id is not None:\n pulumi.set(__self__, \"identity_id\", identity_id)\n if name is not None:\n pulumi.set(__self__, \"name\", name)","def create_providerinfo(self, setup=None):\n pcr_class = self.server.message_factory.get_response_type(\n \"configuration_endpoint\"\n )\n _provider_info = copy.deepcopy(self.capabilities.to_dict())\n\n if self.jwks_uri and self.keyjar:\n _provider_info[\"jwks_uri\"] = self.jwks_uri\n\n for endp in self.endp:\n if not self.baseurl.endswith(\"/\"):\n baseurl = self.baseurl + \"/\"\n else:\n baseurl = self.baseurl\n _provider_info[\"{}_endpoint\".format(endp.etype)] = urljoin(\n baseurl, endp.url\n )\n\n if setup and isinstance(setup, dict):\n for key in pcr_class.c_param.keys():\n if key in setup:\n _provider_info[key] = setup[key]\n\n _provider_info[\"issuer\"] = self.name\n _provider_info[\"version\"] = \"3.0\"\n\n return pcr_class(**_provider_info)","def __init__(__self__, *,\n identity_client_id: Optional[str] = None,\n resource_id: Optional[str] = None):\n if identity_client_id is not None:\n pulumi.set(__self__, \"identity_client_id\", identity_client_id)\n if resource_id is not None:\n pulumi.set(__self__, \"resource_id\", resource_id)","def create_course(self, org, offering, user_id=None, fields=None, store_name='default', **kwargs):\r\n store = self.modulestores[store_name]\r\n\r\n if not hasattr(store, 'create_course'):\r\n raise NotImplementedError(u\"Cannot create a course on store %s\" % store_name)\r\n\r\n return store.create_course(org, offering, user_id, fields, **kwargs)","def create_policy(policystore_url, create_policy_request, verbose):\n\n if verbose:\n logging.info('Creating policy')\n pprint.pprint(create_policy_request)\n\n create_url = policystore_url + POLICYSTORE_PREFIX + 'CreateEntitlementPolicy'\n\n r = requests.post(\n create_url, headers=headers(), json=create_policy_request)\n if r.status_code != 200:\n logging.error(f'ERROR: Unexpected response: {r.status_code}')\n pprint.pprint(r.json())\n\n sys.exit('Failed to create policy')\n\n resp = r.json()\n\n logging.info(\n f'SUCCESS: Created policy - ID: {resp[\"policy_id\"]}, Token: {resp[\"token\"]}'\n )\n\n return resp","def create_authorizer(self, ApiId: str, AuthorizerType: str, AuthorizerUri: str, IdentitySource: List, Name: str, AuthorizerCredentialsArn: str = None, AuthorizerResultTtlInSeconds: int = None, IdentityValidationExpression: str = None, ProviderArns: List = None) -> Dict:\n pass","def provider_setup(cls, args, config):\n if len(args) < 1:\n print \"USAGE: molns provider setup name\"\n print \"\\tCreates a new provider with the given name.\"\n return\n # check if provider exists\n try:\n provider_obj = config.get_object(args[0], kind='Provider')\n except DatastoreException:\n # ask provider type\n print \"Select a provider type:\"\n for n, p in enumerate(VALID_PROVIDER_TYPES):\n print \"\\t[{0}] {1}\".format(n, p)\n while True:\n try:\n provider_ndx = int(raw_input_default(\"Enter the number of type:\", default='0'))\n provider_type = VALID_PROVIDER_TYPES[provider_ndx]\n break\n except (ValueError, IndexError):\n pass\n logging.debug(\"Provider type '{0}'\".format(provider_type))\n # Create provider\n try:\n provider_obj = config.create_object(name=args[0], ptype=provider_type, kind='Provider')\n except DatastoreException as e:\n logging.exception(e)\n print e\n return\n print \"Enter configuration for provider {0}:\".format(args[0])\n setup_object(provider_obj)\n config.save_object(provider_obj, kind='Provider')\n\n cls.provider_initialize(args[0], config)","def create(self, request, *args, **kwargs):\n response = super(ProviderViewSet, self).create(request, *args, **kwargs)\n response.data['message'] = \"Provedor ha sido creado\"\n return response","def add_new_identity(self, identity):\n query = \"\"\"INSERT INTO yubikeys (\n active,\n created,\n modified,\n yk_publicname,\n yk_counter,\n yk_use,\n yk_low,\n yk_high,\n nonce\n ) VALUES (\n %(active)s,\n %(created)s,\n %(modified)s,\n %(yk_publicname)s,\n %(yk_counter)s,\n %(yk_use)s,\n %(yk_low)s,\n %(yk_high)s,\n %(nonce)s\n )\"\"\"\n self._execute(query, identity)","def register_vim(cls,\n cloud_owner: str,\n cloud_region_id: str,\n default_tenant: str = None) -> None:\n cls.send_message(\n \"POST\",\n \"Register VIM instance to ONAP\",\n f\"{cls.base_url}/{cloud_owner}/{cloud_region_id}/registry\",\n data={\"defaultTenant\": default_tenant} if default_tenant else None\n )","def test_creating_new_dietitian(self):\n\n form_data = {\"fname\": \"Jill\", \"lname\": \"Jones\", \n \"email\": \"jill23@gmail.com\", \"password\": \"password\", \n \"street-address\": \"33 Blue St\", \"city\": \"San Francisco\", \n \"state\": \"CA\", \"zipcode\": \"43223\"}\n\n dietitian_id = create_new_dietitian_account(form_data)\n\n self.assertEqual(2, dietitian_id)","def create_organization(user, name):\n organization = Organization.objects.create(name=name)\n new_user = OrganizationUser.objects.create(organization=organization,\n user=user, is_admin=True)\n OrganizationOwner.objects.create(organization=organization,\n organization_user=new_user)\n return organization","def create(request: PlantRequestCreate) -> Plant:\n logger.debug(f'Executing Plant create with request:{request}')\n return Plant(request.name, request.bed_id)","def create(self, identity, record=None, data=None, **kwargs):\n self.set_slug(record, data[\"slug\"])","def create_entity(self, data):\n url = '{}/ngsi-ld/v1/entities'.format(self.url)\n return self.post(url, data=data, headers=self.headers_ld)","def catalog_create(self, args):\n try:\n if args.id and self.server.connect_ermrest(args.id).exists():\n print(\"Catalog already exists\")\n return\n owner = args.owner if args.owner else None\n catalog = self.server.create_ermrest_catalog(args.id, owner)\n if args.auto_configure:\n model = catalog.getCatalogModel()\n model.configure_baseline_catalog(**args.configure_args)\n if not args.quiet:\n print(\"Created new catalog %s with the following default configuration:\\n\" % catalog.catalog_id)\n pp(catalog.get('/').json())\n except HTTPError as e:\n if e.response.status_code == requests.codes.not_found:\n raise ResourceException('Catalog not found', e)\n elif e.response.status_code == requests.codes.conflict:\n raise ResourceException(\"Catalog already exists\", e)\n else:\n raise e","def create_provider(storage_auth):\n if not storage_auth:\n provider = Local(storage_auth)\n elif storage_auth.type == 'MINIO':\n provider = Minio(storage_auth)\n elif storage_auth.type == 'ONEDATA':\n provider = Onedata(storage_auth)\n elif storage_auth.type == 'S3':\n provider = S3(storage_auth)\n elif storage_auth.type == 'WEBDAV':\n provider = WebDav(storage_auth)\n else:\n raise InvalidStorageProviderError(storage_type=storage_auth.type)\n return provider","def identity_provider_name(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"identity_provider_name\")","def __init__(__self__, *,\n identity: pulumi.Input['UserAssignedIdentityArgs'],\n name: pulumi.Input[str],\n namespace: pulumi.Input[str],\n binding_selector: Optional[pulumi.Input[str]] = None):\n pulumi.set(__self__, \"identity\", identity)\n pulumi.set(__self__, \"name\", name)\n pulumi.set(__self__, \"namespace\", namespace)\n if binding_selector is not None:\n pulumi.set(__self__, \"binding_selector\", binding_selector)","def set_up_identity(self, mc: ManagedCluster) -> ManagedCluster:\n self._ensure_mc(mc)\n\n identity = None\n enable_managed_identity = self.context.get_enable_managed_identity()\n assign_identity = self.context.get_assign_identity()\n if enable_managed_identity and not assign_identity:\n identity = self.models.ManagedClusterIdentity(\n type=\"SystemAssigned\"\n )\n elif enable_managed_identity and assign_identity:\n user_assigned_identity = {\n assign_identity: self.models.ManagedServiceIdentityUserAssignedIdentitiesValue()\n }\n identity = self.models.ManagedClusterIdentity(\n type=\"UserAssigned\",\n user_assigned_identities=user_assigned_identity\n )\n mc.identity = identity\n return mc"],"string":"[\n \"def create_identity_provider(module, sdk, cloud, name):\\n\\n if module.check_mode:\\n return True, None\\n\\n description = module.params.get('description')\\n enabled = module.params.get('enabled')\\n domain_id = module.params.get('domain_id')\\n remote_ids = module.params.get('remote_ids')\\n\\n if enabled is None:\\n enabled = True\\n if remote_ids is None:\\n remote_ids = []\\n\\n attributes = {\\n 'domain_id': domain_id,\\n 'enabled': enabled,\\n 'remote_ids': remote_ids,\\n }\\n if description is not None:\\n attributes['description'] = description\\n\\n try:\\n idp = cloud.identity.create_identity_provider(id=name, **attributes)\\n except sdk.exceptions.OpenStackCloudException as ex:\\n module.fail_json(msg='Failed to create identity provider: {0}'.format(str(ex)))\\n return (True, idp)\",\n \"def create_provider(\\n provider_id:UUID = Form(...),\\n name:str = Form(...),\\n qualification:str = Form(...),\\n speciality:str = Form(...),\\n phone:str = Form(...),\\n department:Optional[str] = Form(\\\"N/A\\\"),\\n organization:str = Form(...),\\n location:Optional[str] = Form(\\\"N/A\\\"),\\n address:str = Form(...),\\n active:bool = Form(...)\\n ):\\n\\n post_data = {\\n \\\"name\\\": name,\\n \\\"qualification\\\": qualification,\\n \\\"speciality\\\": speciality,\\n \\\"phone\\\": phone,\\n \\\"department\\\": department,\\n \\\"organization\\\": organization,\\n \\\"location\\\": location,\\n \\\"address\\\": address,\\n \\\"active\\\": active\\n }\\n provider_data = open_for_reading()\\n if str(provider_id) in provider_data.keys():\\n response = {\\\"message\\\": \\\"ID already exists\\\"}\\n else:\\n provider_data[str(provider_id)] = post_data\\n open_for_writing(data=provider_data)\\n response = {\\\"message\\\": \\\"provider created\\\"}\\n\\n return response\",\n \"def create_cloud_provider(providername):\\n backend_name = request.get_json().get(\\\"backend\\\")\\n service_name = request.get_json().get(\\\"service\\\")\\n response = jsonify(\\n admin.create_provider(\\n current_app.scoped_session(),\\n providername,\\n backend=backend_name,\\n service=service_name,\\n )\\n )\\n return response\",\n \"def create(self, identity, record=None, data=None, **kwargs):\\n data['id'] = data['id'].lower()\\n self._validate(data['id'])\\n record['id'] = data['id']\\n try:\\n provider = record.__class__.pid.field._provider.create(record=record)\\n except PIDAlreadyExists:\\n raise ValidationError(\\n 'A community with this identifier already exists.',\\n field_name='id',\\n )\\n setattr(record, 'pid', provider.pid)\",\n \"def m_create_identity(DID, domain_name, website, commercial_name, parent_node_account, password, overwrite):\\n\\n error, didDoc = create_identity(\\n DID, domain_name, website, commercial_name, parent_node_account, password, overwrite)\\n if error is not None:\\n print(error)\\n\\n print(f\\\"Created\\\")\",\n \"def add_new_provider(self, provider_name, provider_type, endpoints, zone_id, provider_region):\\n try:\\n result = self.client.post(self.providers_url, name=provider_name,\\n type=ManageIQProvider.PROVIDER_TYPES[provider_type],\\n zone={'id': zone_id},\\n connection_configurations=endpoints,\\n provider_region=provider_region)\\n provider_id = result['results'][0]['id']\\n self.changed = True\\n except Exception as e:\\n self.module.fail_json(msg=\\\"Failed to add provider. Error: {!r}\\\".format(e))\\n return provider_id\",\n \"def create(self, identity, data=None, record=None, **kwargs):\\n self._populate_access_and_validate(identity, data, record, **kwargs)\\n self._init_owners(identity, record, **kwargs)\",\n \"def create(self, identity, data=None, record=None, **kwargs):\\n if system_process in identity.provides:\\n return\\n\\n member = {\\n \\\"type\\\": \\\"user\\\",\\n \\\"id\\\": str(identity.id),\\n }\\n self.service.members.add(\\n # the user is not yet owner of the community (is being added)\\n # therefore we cannot use `identity`\\n system_identity,\\n record.id,\\n {\\\"members\\\": [member], \\\"role\\\": current_roles.owner_role.name},\\n uow=self.uow,\\n )\\n\\n # Invalidate the membership cache\\n on_user_membership_change(identity=identity)\",\n \"def __init__(__self__, *,\\n identity_pool_id: pulumi.Input[str],\\n identity_provider_name: pulumi.Input[str],\\n principal_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n use_defaults: Optional[pulumi.Input[bool]] = None):\\n pulumi.set(__self__, \\\"identity_pool_id\\\", identity_pool_id)\\n pulumi.set(__self__, \\\"identity_provider_name\\\", identity_provider_name)\\n if principal_tags is not None:\\n pulumi.set(__self__, \\\"principal_tags\\\", principal_tags)\\n if use_defaults is not None:\\n pulumi.set(__self__, \\\"use_defaults\\\", use_defaults)\",\n \"def test_create_identity(self):\\n pass\",\n \"def __init__(__self__, *,\\n principal_id: Optional[pulumi.Input[str]] = None,\\n tenant_id: Optional[pulumi.Input[str]] = None,\\n type: Optional[pulumi.Input[Union[str, 'ManagedIdentityType']]] = None,\\n user_assigned_identities: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None):\\n if principal_id is not None:\\n pulumi.set(__self__, \\\"principal_id\\\", principal_id)\\n if tenant_id is not None:\\n pulumi.set(__self__, \\\"tenant_id\\\", tenant_id)\\n if type is not None:\\n pulumi.set(__self__, \\\"type\\\", type)\\n if user_assigned_identities is not None:\\n pulumi.set(__self__, \\\"user_assigned_identities\\\", user_assigned_identities)\",\n \"def _create_resource_provider(context, uuid, name,\\n parent_provider_uuid=None):\\n return {\\n 'uuid': uuid,\\n 'name': name,\\n 'generation': 0,\\n 'parent_provider_uuid': parent_provider_uuid\\n }\",\n \"def __init__(__self__, *,\\n identity_pool_id: Optional[pulumi.Input[str]] = None,\\n identity_provider_name: Optional[pulumi.Input[str]] = None,\\n principal_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n use_defaults: Optional[pulumi.Input[bool]] = None):\\n if identity_pool_id is not None:\\n pulumi.set(__self__, \\\"identity_pool_id\\\", identity_pool_id)\\n if identity_provider_name is not None:\\n pulumi.set(__self__, \\\"identity_provider_name\\\", identity_provider_name)\\n if principal_tags is not None:\\n pulumi.set(__self__, \\\"principal_tags\\\", principal_tags)\\n if use_defaults is not None:\\n pulumi.set(__self__, \\\"use_defaults\\\", use_defaults)\",\n \"def _create_resource_provider(self, uuid, name):\\n url = \\\"/resource_providers\\\"\\n payload = {\\n 'uuid': uuid,\\n 'name': name,\\n }\\n resp = self.post(url, payload)\\n if resp.status_code == 201:\\n msg = _LI(\\\"Created resource provider record via placement API \\\"\\n \\\"for resource provider with UUID {0} and name {1}.\\\")\\n msg = msg.format(uuid, name)\\n LOG.info(msg)\\n return objects.ResourceProvider(\\n uuid=uuid,\\n name=name,\\n generation=1,\\n )\\n elif resp.status_code == 409:\\n # Another thread concurrently created a resource provider with the\\n # same UUID. Log a warning and then just return the resource\\n # provider object from _get_resource_provider()\\n msg = _LI(\\\"Another thread already created a resource provider \\\"\\n \\\"with the UUID {0}. Grabbing that record from \\\"\\n \\\"the placement API.\\\")\\n msg = msg.format(uuid)\\n LOG.info(msg)\\n return self._get_resource_provider(uuid)\\n else:\\n msg = _LE(\\\"Failed to create resource provider record in \\\"\\n \\\"placement API for UUID %(uuid)s. \\\"\\n \\\"Got %(status_code)d: %(err_text)s.\\\")\\n args = {\\n 'uuid': uuid,\\n 'status_code': resp.status_code,\\n 'err_text': resp.text,\\n }\\n LOG.error(msg, args)\",\n \"async def create_issuer(self, issuer_name: str, provider: str, **kwargs) -> CertificateIssuer:\\n\\n enabled = kwargs.pop(\\\"enabled\\\", None)\\n account_id = kwargs.pop(\\\"account_id\\\", None)\\n password = kwargs.pop(\\\"password\\\", None)\\n organization_id = kwargs.pop(\\\"organization_id\\\", None)\\n admin_contacts = kwargs.pop(\\\"admin_contacts\\\", None)\\n\\n if account_id or password:\\n issuer_credentials = self._models.IssuerCredentials(account_id=account_id, password=password)\\n else:\\n issuer_credentials = None\\n if admin_contacts:\\n admin_details: Optional[List[Any]] = [\\n self._models.AdministratorDetails(\\n first_name=contact.first_name,\\n last_name=contact.last_name,\\n email_address=contact.email,\\n phone=contact.phone,\\n )\\n for contact in admin_contacts\\n ]\\n else:\\n admin_details = None\\n if organization_id or admin_details:\\n organization_details = self._models.OrganizationDetails(id=organization_id, admin_details=admin_details)\\n else:\\n organization_details = None\\n if enabled is not None:\\n issuer_attributes = self._models.IssuerAttributes(enabled=enabled)\\n else:\\n issuer_attributes = None\\n\\n parameters = self._models.CertificateIssuerSetParameters(\\n provider=provider,\\n credentials=issuer_credentials,\\n organization_details=organization_details,\\n attributes=issuer_attributes,\\n )\\n\\n issuer_bundle = await self._client.set_certificate_issuer(\\n vault_base_url=self.vault_url, issuer_name=issuer_name, parameter=parameters, **kwargs\\n )\\n return CertificateIssuer._from_issuer_bundle(issuer_bundle=issuer_bundle)\",\n \"def create_namespaced_identity(self, body, **kwargs):\\n\\n all_params = ['body', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_namespaced_identity\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `create_namespaced_identity`\\\")\\n\\n resource_path = '/oapi/v1/identities'.replace('{format}', 'json')\\n path_params = {}\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1Identity',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: OpenIdConnectProviderArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def create(self, identity, data=None, record=None, **kwargs):\\n if record.access.visibility != \\\"public\\\":\\n return\\n\\n community_set = self._create_set_from_community(record)\\n # NOTE: will be indexed via a listener in oaiserver module\\n db.session.add(community_set)\",\n \"def create(self, identity, data=None, record=None, **kwargs):\\n self._populate_access_and_validate(identity, data, record, **kwargs)\",\n \"def _create_entity_in_domain(entity_type, domain_id):\\n if entity_type == 'users':\\n new_entity = unit.new_user_ref(domain_id=domain_id)\\n new_entity = self.identity_api.create_user(new_entity)\\n elif entity_type == 'groups':\\n new_entity = unit.new_group_ref(domain_id=domain_id)\\n new_entity = self.identity_api.create_group(new_entity)\\n elif entity_type == 'roles':\\n new_entity = self._create_role(domain_id=domain_id)\\n else:\\n # Must be a bad test plan\\n raise exception.NotImplemented()\\n return new_entity\",\n \"def create_with_instance_principal(iam_auth_uri=None):\\n if iam_auth_uri is None:\\n return SignatureProvider(\\n oci.auth.signers.InstancePrincipalsSecurityTokenSigner())\\n else:\\n return SignatureProvider(\\n oci.auth.signers.InstancePrincipalsSecurityTokenSigner(\\n federation_endpoint=iam_auth_uri))\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: IdentityPoolProviderPrincipalTagArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def __init__(self, region, user_pool_id, app_client_id):\\n self.region = region\\n self.user_pool_id = user_pool_id\\n self.client_id = app_client_id\\n self.client = boto3.client('cognito-idp', region_name=self.region)\",\n \"def register_provider(args):\\n if len(args) == 0:\\n click.echo(\\\"Usage: mephisto register --arg1:value --arg2:value\\\")\\n return\\n\\n from mephisto.core.local_database import LocalMephistoDB\\n from mephisto.core.registry import get_crowd_provider_from_type\\n from mephisto.core.argparse_parser import parse_arg_dict, get_extra_argument_dicts\\n\\n provider_type, requester_args = args[0], args[1:]\\n args_dict = dict(arg.split(\\\":\\\") for arg in requester_args)\\n transformed = dict(\\n (key, {\\\"option_string\\\": key, \\\"value\\\": value})\\n for (key, value) in args_dict.items()\\n )\\n\\n crowd_provider = get_crowd_provider_from_type(provider_type)\\n RequesterClass = crowd_provider.RequesterClass\\n\\n if len(requester_args) == 0:\\n from tabulate import tabulate\\n\\n params = get_extra_argument_dicts(RequesterClass)\\n for param in params:\\n click.echo(param[\\\"desc\\\"])\\n click.echo(tabulate(param[\\\"args\\\"].values(), headers=\\\"keys\\\"))\\n return\\n\\n try:\\n parsed_options = parse_arg_dict(RequesterClass, transformed)\\n except Exception as e:\\n click.echo(str(e))\\n\\n if \\\"name\\\" not in parsed_options:\\n click.echo(\\\"No name was specified for the requester.\\\")\\n\\n db = LocalMephistoDB()\\n requesters = db.find_requesters(requester_name=parsed_options[\\\"name\\\"])\\n if len(requesters) == 0:\\n requester = RequesterClass.new(db, parsed_options[\\\"name\\\"])\\n else:\\n requester = requesters[0]\\n try:\\n requester.register(parsed_options)\\n click.echo(\\\"Registered successfully.\\\")\\n except Exception as e:\\n click.echo(str(e))\",\n \"def add_tomcat7_idp():\\n pass\",\n \"def sso_test_create_user(request, idp_slug):\\n if settings.SERVER_ENVIRONMENT not in ['staging']:\\n raise Http404()\\n\\n username = request.GET.get('username')\\n if username:\\n prepare_session_with_sso_username(request, username)\\n\\n invitation_uuid = request.GET.get('invitation')\\n invitation = Invitation.objects.get(uuid=invitation_uuid)\\n if invitation:\\n prepare_session_for_sso_invitation(request, invitation)\\n\\n return HttpResponseRedirect(reverse(\\\"sso_saml_login\\\", args=(idp_slug,)))\",\n \"def test_create_resource_provider(self):\\n uuid = uuids.compute_node\\n name = 'computehost'\\n resp_mock = mock.Mock(status_code=200)\\n self.ks_adap_mock.post.return_value = resp_mock\\n\\n self.assertEqual(\\n resp_mock.json.return_value,\\n self.client._create_resource_provider(self.context, uuid, name))\\n\\n expected_payload = {\\n 'uuid': uuid,\\n 'name': name,\\n }\\n\\n expected_url = '/resource_providers'\\n self.ks_adap_mock.post.assert_called_once_with(\\n expected_url, json=expected_payload, microversion='1.20',\\n global_request_id=self.context.global_id)\",\n \"def __init__(__self__, *,\\n identity_namespace: Optional[pulumi.Input[str]] = None,\\n identity_provider: Optional[pulumi.Input[str]] = None,\\n workload_pool: Optional[pulumi.Input[str]] = None):\\n if identity_namespace is not None:\\n pulumi.set(__self__, \\\"identity_namespace\\\", identity_namespace)\\n if identity_provider is not None:\\n pulumi.set(__self__, \\\"identity_provider\\\", identity_provider)\\n if workload_pool is not None:\\n pulumi.set(__self__, \\\"workload_pool\\\", workload_pool)\",\n \"def create(self, request, *args, **kwargs):\\n \\n serializer = self.serializer_class(data=request.data)\\n serializer.is_valid(raise_exception=True)\\n provider = serializer.data.get('provider')\\n\\n access_token = serializer.data.get('access_token')\\n user = None if request.user.is_anonymous else request.user\\n\\n # strategy sets up the required custom configuration for working with Django\\n strategy = load_strategy(request)\\n try:\\n # Loads backends defined on SOCIAL_AUTH_AUTHENTICATION_BACKENDS,\\n # checks the appropriate one by using the provider given\\n\\n backend = load_backend(strategy=strategy, name=provider, redirect_uri=None)\\n access_token = self.update_access_token(backend, request, access_token)\\n\\n except MissingBackend:\\n return Response({\\n \\\"errors\\\": {\\n \\\"provider\\\": [\\\"Invalid provider\\\"]\\n }\\n }, status=status.HTTP_400_BAD_REQUEST)\\n\\n try:\\n # creates a user in our user model \\n # If the user exists, we just authenticate the user.\\n user = backend.do_auth(access_token, user=user)\\n\\n except BaseException as error:\\n return Response({\\\"error\\\": str(error)}, status=status.HTTP_400_BAD_REQUEST)\\n\\n # Since the user is using social authentication, there is no need for email verification.\\n # We therefore set the user to active here.\\n # And also subscribe them for notifications\\n\\n user.is_active = True\\n user.save()\\n\\n subscribe_user(user, self.subscription_class)\\n\\n serializer = UserSerializer(user)\\n \\n return Response(serializer.data, status=status.HTTP_200_OK)\",\n \"def createTenant(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def create_epic():\\n client = RequestManager()\\n client.set_method(\\\"POST\\\")\\n client.set_endpoint(\\\"/projects/{0}/epics\\\".format(STORED_ID['project_id']))\\n name = \\\"\\\".join(choices(string.ascii_letters, k=6))\\n body = {\\\"name\\\": name}\\n client.set_body(json.dumps(body))\\n response = client.execute_request()\\n STORED_ID['epic_id'] = response.json()['id']\",\n \"def application_create(request, name, redirect_uris, scopes=['all_info'],\\n client_type='confidential', description=None,\\n grant_type='authorization_code', **kwargs):\\n manager = api.keystone.keystoneclient(request, admin=True).oauth2.consumers\\n return manager.create(name=name,\\n redirect_uris=redirect_uris,\\n description=description,\\n scopes=scopes,\\n client_type=client_type,\\n grant_type=grant_type,\\n **kwargs)\",\n \"def __init__(__self__, *,\\n auth_type: pulumi.Input[str],\\n client_id: pulumi.Input[str],\\n subscription_id: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"auth_type\\\", 'userAssignedIdentity')\\n pulumi.set(__self__, \\\"client_id\\\", client_id)\\n pulumi.set(__self__, \\\"subscription_id\\\", subscription_id)\",\n \"def create(self, request):\\n\\n return ObtainAuthToken().post(request)\",\n \"def register_api_provider(api_provider, contact_info):\\n\\n req = requests.post(domain_name + \\\"register_api_provider?\\\",\\n data=json.dumps({'api_provider': api_provider,\\n 'contact_info': contact_info}),\\n headers={'Content-type': 'application/json',\\n 'Accept': 'application/json'})\\n response = req.json()\\n return response\",\n \"def create(self, request):\\n return ObtainAuthToken().post(request)\",\n \"def __init__(__self__, *,\\n auth_type: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"auth_type\\\", 'systemAssignedIdentity')\",\n \"def create_customer(email=None, name=None, user_type='customer'):\\n if user_type == 'charity':\\n stripe.api_key = Config.STRIPE_SECRET_KEY_FOR_PLAN\\n else:\\n stripe.api_key = Config.STRIPE_SECRET_KEY\\n if email and name:\\n customer = stripe.Customer.create(email=email, name=name)\\n else:\\n customer = stripe.Customer.create()\\n return customer.id\",\n \"def __init__(__self__, *,\\n cognitive_service_region: Optional[pulumi.Input[str]] = None,\\n cognitive_service_resource_id: Optional[pulumi.Input[str]] = None,\\n cognitive_service_subscription_key: Optional[pulumi.Input[str]] = None,\\n default_locale: Optional[pulumi.Input[str]] = None,\\n id: Optional[pulumi.Input[str]] = None,\\n provider_name: Optional[pulumi.Input[str]] = None):\\n if cognitive_service_region is not None:\\n pulumi.set(__self__, \\\"cognitive_service_region\\\", cognitive_service_region)\\n if cognitive_service_resource_id is not None:\\n pulumi.set(__self__, \\\"cognitive_service_resource_id\\\", cognitive_service_resource_id)\\n if cognitive_service_subscription_key is not None:\\n pulumi.set(__self__, \\\"cognitive_service_subscription_key\\\", cognitive_service_subscription_key)\\n if default_locale is not None:\\n pulumi.set(__self__, \\\"default_locale\\\", default_locale)\\n if id is not None:\\n pulumi.set(__self__, \\\"id\\\", id)\\n if provider_name is not None:\\n pulumi.set(__self__, \\\"provider_name\\\", provider_name)\",\n \"def identity_provider(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"identity_provider\\\")\",\n \"def get_identity_provider(self, identity_provider_id, **kwargs):\\n resource_path = \\\"/identityProviders/{identityProviderId}\\\"\\n method = \\\"GET\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"get_identity_provider got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"identityProviderId\\\": identity_provider_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"IdentityProvider\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"IdentityProvider\\\")\",\n \"def test_create_resource_provider_with_parent(self):\\n parent_uuid = uuids.parent\\n uuid = uuids.compute_node\\n name = 'computehost'\\n resp_mock = mock.Mock(status_code=200)\\n self.ks_adap_mock.post.return_value = resp_mock\\n\\n self.assertEqual(\\n resp_mock.json.return_value,\\n self.client._create_resource_provider(\\n self.context,\\n uuid,\\n name,\\n parent_provider_uuid=parent_uuid,\\n )\\n )\\n\\n expected_payload = {\\n 'uuid': uuid,\\n 'name': name,\\n 'parent_provider_uuid': parent_uuid,\\n }\\n expected_url = '/resource_providers'\\n self.ks_adap_mock.post.assert_called_once_with(\\n expected_url, json=expected_payload, microversion='1.20',\\n global_request_id=self.context.global_id)\",\n \"def create_identity(self, realm=None, type=\\\"users\\\", user_data=None):\\n if not user_data:\\n raise ValueError(\\\"Please provide correct user information.\\\")\\n\\n user_data = self._to_string(data=user_data)\\n type = self._type_validator(type=type)\\n uri = self._uri_realm_creator(realm=realm, uri=type + '/?_action=create')\\n data = self._post(uri=uri, data=user_data, headers=self.headers)\\n return data.json()\",\n \"def create_tenant(self, tenant_info):\\n LOG_OBJ.debug(\\\"Creating Tenant:%s\\\" % tenant_info['project_name'])\\n _tenant_name = tenant_info['project_name']\\n _user_name = tenant_info.get('user_name', _tenant_name + \\\"_user\\\")\\n _password = tenant_info.get('password', _tenant_name + \\\"_pass\\\")\\n\\n _url = \\\"http://\\\" + self.host_ip + \\\":35357/v2.0/tenants\\\"\\n _headers = {'Content-type': 'application/json',\\n 'x-auth-token': self.cloud_admin_info['token_project']}\\n _tenant_data = {\\\"tenant\\\": {\\\"enabled\\\": True, \\\"name\\\": _tenant_name,\\n \\\"description\\\": \\\"Testing API 3\\\"}}\\n\\n _body = json.dumps(_tenant_data)\\n\\n response = self.request(\\\"POST\\\", _url, _headers, _body)\\n if response is None:\\n LOG_OBJ.error(\\\"No response from Server while creating tenant: %s\\\"\\n % _tenant_name)\\n return response\\n if response.status not in [200, 201, 202, 203, 204]:\\n LOG_OBJ.error(\\\"Create tenant Failed with status %s \\\" %\\n response.status)\\n return response.status\\n\\n output = json.loads(response.data)\\n LOG_OBJ.info(\\\"Created tenant: %s successfully.\\\" % _tenant_name)\\n\\n _tenant_id = output['tenant']['id']\\n # If user id is passed then, directly add that user to the tenant.\\n # otherwise Create a new user.\\n _user_id = tenant_info.get('user_id', None)\\n if not _user_id:\\n _user_data = {\\\"user\\\": {\\\"email\\\": None,\\n \\\"password\\\": _password,\\n \\\"enabled\\\": True,\\n \\\"name\\\": _user_name,\\n \\\"tenantId\\\": _tenant_id}}\\n _user_id = self.create_user(_user_data)\\n if not isinstance(_user_id, unicode):\\n return\\n tenant_info['userID'] = _user_id\\n\\n # Add the user roles.\\n for role_name in tenant_info['roles']:\\n role_id = self.get_role_id(role_name)\\n if not isinstance(role_id, unicode):\\n return\\n # Add user role.\\n if not self.add_user_role(_tenant_id, _user_id, role_id):\\n return\\n # Get the token.\\n token_id = self.get_token(_tenant_name, _user_name, _password)\\n if not isinstance(token_id, unicode):\\n return\\n # Set the new context. note: This is v2 token, so only project scope.\\n self.set_tenant_info(_tenant_name, token_id, token_id, _tenant_id)\\n\\n # Adding Security Group Rules\\n # Add the ICMP rule.\\n # if not isinstance(self.add_security_group_rules(\\\"icmp\\\"), bool):\\n # return\\n # Add the rule for ssh\\n # if not isinstance(self.add_security_group_rules(\\n # \\\"tcp\\\", from_port='22', to_port='22'), bool):\\n # return\\n # Add the rule for all udp\\n # if not isinstance(self.add_security_group_rules(\\n # \\\"udp\\\", from_port='1', to_port='65535'), bool):\\n # return\\n\\n # Modify the tenant quota.\\n # if not isinstance(self.set_quota(_tenant_id), bool):\\n # return\\n # Update the quota\\n # fields = {\\\"network\\\": 50, \\\"subnet\\\": 50, \\\"port\\\": 100, \\\"floatingip\\\": 50}\\n # quotas = self.quota_update(_tenant_id, fields)\\n # if not isinstance(quotas, dict):\\n # return\\n # LOG_OBJ.info(\\\"Quota for tenant[%s] is:%s\\\" % (_tenant_id,\\n # str(quotas)))\\n return _tenant_id\",\n \"def testCreateOrg(self):\\n self.timeline.orgSignup()\\n self.data.createProfile()\\n self.record.createOrgApp('new_org', self.data.user)\\n\\n url = '/gci/profile/organization/' + self.gci.key().name()\\n create_url = url + '?org_id=new_org'\\n response = self.get(create_url)\\n self.assertResponseOK(response)\\n self.assertOrgProfilePageTemplatesUsed(response)\\n \\n postdata = {\\n 'founder': self.data.user, 'home': self.createDocument().key(),\\n 'scope': self.gci, 'irc_channel': 'irc://example.com',\\n 'pub_mailing_list': 'http://example.com',\\n }\\n response, properties = self.modelPost(create_url, GCIOrganization, postdata)\\n self.assertResponseRedirect(response, url + '/new_org?validated')\\n profile = db.get(self.data.profile.key())\\n self.assertEqual(1, len(profile.org_admin_for))\",\n \"def create_tenant(tenant):\\n exists = identity.Tenant.query.filter_by(name=tenant.name).first()\\n if exists:\\n abort(409, \\\"Tenant Already Exists\\\")\\n db.session.add(tenant)\\n db.session.commit()\\n return tenant.id\",\n \"def __init__(self, *args, **kwargs):\\n super(EnterpriseCustomerIdentityProviderAdminForm, self).__init__(*args, **kwargs)\\n idp_choices = utils.get_idp_choices()\\n if idp_choices is not None:\\n self.fields['provider_id'] = forms.TypedChoiceField(choices=idp_choices)\",\n \"def create_org(self, provider='qbo', status=CONNECTED, set_provider_config=True):\\n\\n if set_provider_config:\\n provider_config = self.provider_configs[provider]\\n else:\\n provider_config = None\\n\\n org = Org(provider=provider, id='test', status=status, provider_config=provider_config).put()\\n\\n OrgCredentials(id='test', parent=org, token={'expires_at': 0}).put()\",\n \"async def register_investigator(request):\\n required_fields = ['name']\\n general.validate_fields(required_fields, request.json)\\n\\n name = request.json.get('name')\\n\\n clinic_signer = request.app.config.SIGNER_INVESTIGATOR # .get_public_key().as_hex()\\n\\n client_txn = consent_transaction.create_investigator_client(\\n txn_signer=clinic_signer,\\n batch_signer=clinic_signer\\n )\\n clinic_txn = ehr_transaction.create_investigator(\\n txn_signer=clinic_signer,\\n batch_signer=clinic_signer,\\n name=name\\n )\\n batch, batch_id = ehr_transaction.make_batch_and_id([client_txn, clinic_txn], clinic_signer)\\n\\n await security_messaging.add_investigator(\\n request.app.config.VAL_CONN,\\n request.app.config.TIMEOUT,\\n [batch])\\n\\n try:\\n await security_messaging.check_batch_status(\\n request.app.config.VAL_CONN, [batch_id])\\n except (ApiBadRequest, ApiInternalError) as err:\\n # await auth_query.remove_auth_entry(\\n # request.app.config.DB_CONN, request.json.get('email'))\\n raise err\\n\\n return response.json(body={'status': general.DONE},\\n headers=general.get_response_headers())\",\n \"def create_manager(self, username, tenancy):\\n raise NotImplementedError\",\n \"def makeIdentity(self) -> None:\\n ...\",\n \"def create_tenant(tenant_name, description, enabled, auth_admin_url, admin_token):\\n keystone = get_client(auth_admin_url, admin_token)\\n tenant = keystone.tenants.create(tenant_name=tenant_name, description=description, enabled=enabled)\\n print tenant\\n return tenant.to_dict()\",\n \"async def async_oauth_create_entry(self, data):\\n\\n await self.async_set_unique_id(unique_id=f\\\"{DOMAIN}Cloud\\\")\\n return self.async_create_entry(title=f\\\"{DOMAIN}Cloud\\\", data=data)\",\n \"def __init__(__self__,\\n resource_name: str,\\n opts: Optional[pulumi.ResourceOptions] = None,\\n identity_pool_id: Optional[pulumi.Input[str]] = None,\\n identity_provider_name: Optional[pulumi.Input[str]] = None,\\n principal_tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n use_defaults: Optional[pulumi.Input[bool]] = None,\\n __props__=None):\\n ...\",\n \"def __init__(__self__, *,\\n identity_type: Optional[pulumi.Input[Union[str, 'CmkIdentityType']]] = None,\\n user_assigned_identity_resource_id: Optional[pulumi.Input[str]] = None):\\n if identity_type is not None:\\n pulumi.set(__self__, \\\"identity_type\\\", identity_type)\\n if user_assigned_identity_resource_id is not None:\\n pulumi.set(__self__, \\\"user_assigned_identity_resource_id\\\", user_assigned_identity_resource_id)\",\n \"def create_partner(name):\\n\\n return Partner.objects.create(name=name)\",\n \"def post(self):\\n data = request.json\\n return save_new_provider(data=data)\",\n \"def identity_provider_name(self) -> pulumi.Input[str]:\\n return pulumi.get(self, \\\"identity_provider_name\\\")\",\n \"def __init__(__self__, *,\\n principal_id: str,\\n tenant_id: str,\\n type: Optional[str] = None,\\n user_assigned_identities: Optional[Mapping[str, 'outputs.UserAssignedIdentityResponse']] = None):\\n pulumi.set(__self__, \\\"principal_id\\\", principal_id)\\n pulumi.set(__self__, \\\"tenant_id\\\", tenant_id)\\n if type is not None:\\n pulumi.set(__self__, \\\"type\\\", type)\\n if user_assigned_identities is not None:\\n pulumi.set(__self__, \\\"user_assigned_identities\\\", user_assigned_identities)\",\n \"def __init__(__self__, *,\\n principal_id: str,\\n tenant_id: str,\\n type: Optional[str] = None,\\n user_assigned_identities: Optional[Mapping[str, 'outputs.UserAssignedIdentityResponse']] = None):\\n pulumi.set(__self__, \\\"principal_id\\\", principal_id)\\n pulumi.set(__self__, \\\"tenant_id\\\", tenant_id)\\n if type is not None:\\n pulumi.set(__self__, \\\"type\\\", type)\\n if user_assigned_identities is not None:\\n pulumi.set(__self__, \\\"user_assigned_identities\\\", user_assigned_identities)\",\n \"def test_create_provider(self):\\n url = reverse('provider-list')\\n data = {'name': 'foo'}\\n response = self.client.post(url, data, format='json')\\n self.assertEqual(response.status_code, status.HTTP_201_CREATED)\\n self.assertEqual(Provider.objects.count(), 1)\",\n \"def CreateOIDCClient(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def create(self, validated_data, request: HttpRequest = None):\\n # Writing of .get(\\\"xy\\\", None) or None makes sure that empty strings will be mapped to None\\n user = user_helper.get_user(request=request)\\n get_capabilities_uri = validated_data.get(\\\"uri\\\", None) or None\\n registering_with_group = validated_data.get(\\\"group\\\", None) or None\\n registering_for_org = validated_data.get(\\\"for-org\\\", None) or None\\n has_ext_auth = validated_data.get(\\\"ext-auth\\\", False) or False\\n ext_auth_username = validated_data.get(\\\"ext-username\\\", None) or None\\n ext_auth_password = validated_data.get(\\\"ext-password\\\", None) or None\\n ext_auth_type = validated_data.get(\\\"ext-auth-type\\\", None) or None\\n\\n # Split uri in components as it is done with RegisterNewServiceWizardPage1\\n url_dict = service_helper.split_service_uri(get_capabilities_uri)\\n ogc_request = url_dict[\\\"request\\\"]\\n ogc_service = url_dict[\\\"service\\\"].value\\n ogc_version = url_dict[\\\"version\\\"]\\n uri = url_dict[\\\"base_uri\\\"]\\n\\n init_data = {\\n \\\"ogc_request\\\": ogc_request,\\n \\\"ogc_service\\\": ogc_service,\\n \\\"ogc_version\\\": ogc_version,\\n \\\"uri\\\": uri,\\n \\\"registering_with_group\\\": registering_with_group,\\n \\\"registering_for_other_organization\\\": registering_for_org,\\n \\\"service_needs_authentication\\\": has_ext_auth,\\n \\\"username\\\": ext_auth_username,\\n \\\"password\\\": ext_auth_password,\\n \\\"authentication_type\\\": ext_auth_type,\\n }\\n\\n # Use RegisterNewResourceWizardPage2 workflow as for frontend registration\\n form = RegisterNewResourceWizardPage2(\\n data=init_data,\\n request=request\\n )\\n if form.is_valid():\\n pending_task = service_helper.create_new_service(form, user)\\n return pending_task\\n return form\",\n \"def create(self,request):\\n return CustomAuthToken().post(request)\",\n \"def __init__(__self__, *,\\n authorizations: Sequence['outputs.AuthorizationResponse'],\\n managed_by_tenant_id: str,\\n managed_by_tenant_name: str,\\n managee_tenant_id: str,\\n managee_tenant_name: str,\\n provisioning_state: str,\\n description: Optional[str] = None,\\n eligible_authorizations: Optional[Sequence['outputs.EligibleAuthorizationResponse']] = None,\\n registration_definition_name: Optional[str] = None):\\n pulumi.set(__self__, \\\"authorizations\\\", authorizations)\\n pulumi.set(__self__, \\\"managed_by_tenant_id\\\", managed_by_tenant_id)\\n pulumi.set(__self__, \\\"managed_by_tenant_name\\\", managed_by_tenant_name)\\n pulumi.set(__self__, \\\"managee_tenant_id\\\", managee_tenant_id)\\n pulumi.set(__self__, \\\"managee_tenant_name\\\", managee_tenant_name)\\n pulumi.set(__self__, \\\"provisioning_state\\\", provisioning_state)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if eligible_authorizations is not None:\\n pulumi.set(__self__, \\\"eligible_authorizations\\\", eligible_authorizations)\\n if registration_definition_name is not None:\\n pulumi.set(__self__, \\\"registration_definition_name\\\", registration_definition_name)\",\n \"def _create_citizen(self, citizen_id, relatives):\\n return models.Citizen(\\n citizen_id=citizen_id,\\n town='a', street='b', building='c', apartment=1, name='e', birth_date='01.01.1970',\\n gender='male', relatives=relatives\\n )\",\n \"def setup_test_tenant(self):\\n self.test_tenant = rand_name('test_tenant_')\\n self.test_description = rand_name('desc_')\\n resp, self.tenant = self.client.create_tenant(\\n name=self.test_tenant,\\n description=self.test_description)\\n self.tenants.append(self.tenant)\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: ApplicationFederatedIdentityCredentialArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def __init__(__self__, *,\\n authorizations: Optional[Sequence['outputs.AuthorizationResponse']] = None,\\n description: Optional[str] = None,\\n eligible_authorizations: Optional[Sequence['outputs.EligibleAuthorizationResponse']] = None,\\n managed_by_tenant_id: Optional[str] = None,\\n managed_by_tenant_name: Optional[str] = None,\\n managee_tenant_id: Optional[str] = None,\\n managee_tenant_name: Optional[str] = None,\\n provisioning_state: Optional[str] = None,\\n registration_definition_name: Optional[str] = None):\\n if authorizations is not None:\\n pulumi.set(__self__, \\\"authorizations\\\", authorizations)\\n if description is not None:\\n pulumi.set(__self__, \\\"description\\\", description)\\n if eligible_authorizations is not None:\\n pulumi.set(__self__, \\\"eligible_authorizations\\\", eligible_authorizations)\\n if managed_by_tenant_id is not None:\\n pulumi.set(__self__, \\\"managed_by_tenant_id\\\", managed_by_tenant_id)\\n if managed_by_tenant_name is not None:\\n pulumi.set(__self__, \\\"managed_by_tenant_name\\\", managed_by_tenant_name)\\n if managee_tenant_id is not None:\\n pulumi.set(__self__, \\\"managee_tenant_id\\\", managee_tenant_id)\\n if managee_tenant_name is not None:\\n pulumi.set(__self__, \\\"managee_tenant_name\\\", managee_tenant_name)\\n if provisioning_state is not None:\\n pulumi.set(__self__, \\\"provisioning_state\\\", provisioning_state)\\n if registration_definition_name is not None:\\n pulumi.set(__self__, \\\"registration_definition_name\\\", registration_definition_name)\",\n \"def create_identity(msg: CreateIdentity_request):\\n \\n # Check if we have received some data in the POST\\n if len(msg.DID) == 0:\\n log.error(\\\"No data received\\\")\\n raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=\\\"No data received\\\")\\n\\n # Create the identity using the library\\n try:\\n error, didDoc = tf.create_identity_subnode(\\n msg.DID, msg.domain_name, msg.website, msg.commercial_name, msg.new_privatekey, msg.parent_privatekey)\\n except Exception as e:\\n detail=str(e)\\n log.error(detail)\\n raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=detail)\\n\\n if error is not None:\\n log.error(error)\\n raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=error)\\n\\n return {\\\"didDoc\\\": didDoc.to_dict()}\",\n \"def catalog_alias_create(self, args):\\n try:\\n if args.id:\\n alias = self.server.connect_ermrest_alias(args.id)\\n try:\\n if alias.retrieve():\\n print(\\\"Catalog alias already exists\\\")\\n return\\n except requests.HTTPError as e:\\n if e.response.status_code == 404:\\n pass\\n else:\\n raise\\n owner = args.owner if args.owner else None\\n alias = self.server.create_ermrest_alias(args.id, owner, args.alias_target)\\n if not args.quiet:\\n print(\\\"Created new catalog alias %s with the following configuration:\\\\n\\\" % alias.alias_id)\\n pp(alias.retrieve())\\n except HTTPError as e:\\n if e.response.status_code == requests.codes.not_found:\\n raise ResourceException('Catalog alias not found', e)\\n elif e.response.status_code == requests.codes.conflict:\\n raise ResourceException(\\\"Catalog alias already exists\\\", e)\\n else:\\n raise\",\n \"def __init__(__self__, *,\\n authentication_type: Optional[pulumi.Input[str]] = None,\\n connection_string: Optional[pulumi.Input[str]] = None,\\n endpoint_uri: Optional[pulumi.Input[str]] = None,\\n entity_path: Optional[pulumi.Input[str]] = None,\\n identity_id: Optional[pulumi.Input[str]] = None,\\n iothub_id: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None,\\n resource_group_name: Optional[pulumi.Input[str]] = None):\\n if authentication_type is not None:\\n pulumi.set(__self__, \\\"authentication_type\\\", authentication_type)\\n if connection_string is not None:\\n pulumi.set(__self__, \\\"connection_string\\\", connection_string)\\n if endpoint_uri is not None:\\n pulumi.set(__self__, \\\"endpoint_uri\\\", endpoint_uri)\\n if entity_path is not None:\\n pulumi.set(__self__, \\\"entity_path\\\", entity_path)\\n if identity_id is not None:\\n pulumi.set(__self__, \\\"identity_id\\\", identity_id)\\n if iothub_id is not None:\\n pulumi.set(__self__, \\\"iothub_id\\\", iothub_id)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if resource_group_name is not None:\\n pulumi.set(__self__, \\\"resource_group_name\\\", resource_group_name)\",\n \"def __init__(__self__, *,\\n acs_endpoint: Optional[pulumi.Input[str]] = None,\\n acs_resource_id: Optional[pulumi.Input[str]] = None,\\n acs_secret: Optional[pulumi.Input[str]] = None,\\n cognitive_service_region: Optional[pulumi.Input[str]] = None,\\n cognitive_service_resource_id: Optional[pulumi.Input[str]] = None,\\n cognitive_service_subscription_key: Optional[pulumi.Input[str]] = None,\\n default_locale: Optional[pulumi.Input[str]] = None,\\n id: Optional[pulumi.Input[str]] = None,\\n offer_type: Optional[pulumi.Input[str]] = None,\\n phone_number: Optional[pulumi.Input[str]] = None):\\n if acs_endpoint is not None:\\n pulumi.set(__self__, \\\"acs_endpoint\\\", acs_endpoint)\\n if acs_resource_id is not None:\\n pulumi.set(__self__, \\\"acs_resource_id\\\", acs_resource_id)\\n if acs_secret is not None:\\n pulumi.set(__self__, \\\"acs_secret\\\", acs_secret)\\n if cognitive_service_region is not None:\\n pulumi.set(__self__, \\\"cognitive_service_region\\\", cognitive_service_region)\\n if cognitive_service_resource_id is not None:\\n pulumi.set(__self__, \\\"cognitive_service_resource_id\\\", cognitive_service_resource_id)\\n if cognitive_service_subscription_key is not None:\\n pulumi.set(__self__, \\\"cognitive_service_subscription_key\\\", cognitive_service_subscription_key)\\n if default_locale is not None:\\n pulumi.set(__self__, \\\"default_locale\\\", default_locale)\\n if id is not None:\\n pulumi.set(__self__, \\\"id\\\", id)\\n if offer_type is not None:\\n pulumi.set(__self__, \\\"offer_type\\\", offer_type)\\n if phone_number is not None:\\n pulumi.set(__self__, \\\"phone_number\\\", phone_number)\",\n \"def createCustomer(self, **params):\\n return self.__req('create_customer', params)\",\n \"def CreateIDPConnector(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def create_tenant(name, domain):\\n manager = get_manager()\\n tenant = manager.resolve_tenant_id(name, domain=domain)\\n if not tenant:\\n manager.create_tenant(tenant_name=name,\\n domain=domain,\\n description='Created by Juju')\\n log(\\\"Created new tenant '%s' in domain '%s'\\\" % (name, domain),\\n level=DEBUG)\\n return\\n\\n log(\\\"Tenant '%s' already exists.\\\" % name, level=DEBUG)\",\n \"def m_create_test_identities():\\n\\n # Get the ROOT account (it was created in the deployment of the Smart Contracts)\\n ROOT_address, ROOT_key = wallet.account_from_name(\\\"ROOT\\\", \\\"ThePassword\\\")\\n\\n # Create the Alastria account for node \\\"ala\\\"\\n print(f\\\"\\\\n==> Creating the Alastria account\\\")\\n Alastria_account = wallet.new_account(\\n \\\"Alastria\\\", \\\"ThePassword\\\")\\n alakey = Alastria_account.key\\n print(f\\\"Alastria key: {alakey}\\\")\\n\\n print(f\\\"Done\\\")\\n\\n # Set the subnode \\\"ala\\\"\\n print(f\\\"\\\\n==> Creating the ala subnode in the Trust Framework\\\")\\n success, _, _ = ens.setSubnodeOwner(\\n node_name=\\\"root\\\",\\n label=\\\"ala\\\",\\n new_owner_address=Alastria_account.address,\\n current_owner_key=ROOT_key\\n )\\n print(f\\\"ala subnode created\\\")\\n\\n # Assign the name for reverse resolution\\n resolver.setName(\\\"ala\\\", \\\"ala\\\", Alastria_account.key)\\n\\n # And assign approval to the PublicResolver contract so it can call ENS methods on behalf of Alastria\\n print(f\\\"Resolver address for ROOT: {resolver.address()}\\\")\\n ens.setApprovalForAll(resolver.address(), True, Alastria_account.key)\\n\\n ################################\\n # Heathrow airport\\n print(f\\\"\\\\n==> Creating the Heathrow identity\\\")\\n\\n DID = \\\"did:elsi:VATGB-927365404\\\"\\n domain_name = \\\"heathrow.ala\\\"\\n website = \\\"www.heathrow.com\\\"\\n commercial_name = \\\"Heathrow Airport Limited\\\"\\n\\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \\\"Alastria\\\", \\\"ThePassword\\\", False)\\n if didDoc is not None:\\n pprint(didDoc)\\n\\n ################################\\n # AENA\\n print(f\\\"\\\\n==> Creating the AENA identity\\\")\\n\\n DID = \\\"did:elsi:VATES-A86212420\\\"\\n domain_name = \\\"aena.ala\\\"\\n website = \\\"www.aena.es\\\"\\n commercial_name = \\\"Aena\\\"\\n\\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \\\"Alastria\\\", \\\"ThePassword\\\", False)\\n if didDoc is not None:\\n pprint(didDoc)\\n\\n ################################\\n # Lanzarote airport\\n # The airport belongs to AENA and does not have independent entity (shares the same VAT, for example)\\n # In production, the node should be created by AENA, as a subnode controlled by them.\\n # In this PoC, the node is created automatically to facilitate the tests\\n print(f\\\"\\\\n==> Creating the César Manrique airport identity\\\")\\n\\n DID = \\\"did:elsi:VATES-A86212420-1\\\"\\n domain_name = \\\"ace.ala\\\"\\n website = \\\"www.aena.es/es/aeropuerto-lanzarote\\\"\\n commercial_name = \\\"Aeropuerto de Lanzarote-Cesar Manrique\\\"\\n\\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \\\"Alastria\\\", \\\"ThePassword\\\", False)\\n if didDoc is not None:\\n pprint(didDoc)\\n\\n ################################\\n # Metrovacesa\\n print(f\\\"\\\\n==> Creating the Metrovacesa identity\\\")\\n\\n DID = \\\"did:elsi:VATES-A87471264\\\"\\n domain_name = \\\"metrovacesa.ala\\\"\\n website = \\\"metrovacesa.com\\\"\\n commercial_name = \\\"Metrovacesa\\\"\\n\\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \\\"Alastria\\\", \\\"ThePassword\\\", False)\\n if didDoc is not None:\\n pprint(didDoc)\\n\\n ################################\\n # IN2\\n print(f\\\"\\\\n==> Creating the IN2 identity\\\")\\n\\n DID = \\\"did:elsi:VATES-B60645900\\\"\\n domain_name = \\\"in2.ala\\\"\\n website = \\\"www.in2.es\\\"\\n commercial_name = \\\"IN2 Innovating 2gether\\\"\\n\\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \\\"Alastria\\\", \\\"ThePassword\\\", False)\\n if didDoc is not None:\\n pprint(didDoc)\\n\\n ################################\\n # Perfect Health\\n print(f\\\"\\\\n==> Creating the Perfect Health identity\\\")\\n\\n DID = \\\"did:elsi:VATES-X12345678X\\\"\\n domain_name = \\\"perfecthealth.ala\\\"\\n website = \\\"www.perfecthealth.org\\\"\\n commercial_name = \\\"Perfect Health plc\\\"\\n\\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \\\"Alastria\\\", \\\"ThePassword\\\", False)\\n if didDoc is not None:\\n pprint(didDoc)\\n\\n ################################\\n # BME\\n print(f\\\"\\\\n==> Creating the BME identity\\\")\\n\\n DID = \\\"did:elsi:VATES-A83246314\\\"\\n domain_name = \\\"bme.ala\\\"\\n website = \\\"www.bolsasymercados.es\\\"\\n commercial_name = \\\"Bolsas y Mercados Españoles\\\"\\n\\n error, didDoc = create_identity(DID, domain_name, website, commercial_name, \\\"Alastria\\\", \\\"ThePassword\\\", False)\\n if didDoc is not None:\\n pprint(didDoc)\",\n \"def create_endpoint(coriolis, name, platform_type, connection_info,\\n barbican=None, description=''):\\n # check provider type is installed server-side:\\n providers_dict = coriolis.providers.list().to_dict()\\n if platform_type not in providers_dict:\\n raise ValueError(\\n 'platform_type must be one of %s' % providers_dict.keys())\\n\\n # if Barbican is available, store the connection info in it:\\n if barbican:\\n secret_ref = store_barbican_secret_for_coriolis(\\n barbican, connection_info, name='Coriolis Endpoint %s' % name)\\n connection_info = {'secret_ref': secret_ref}\\n\\n # create the endpoint:\\n endpoint = coriolis.endpoints.create(\\n name, platform_type, connection_info, description)\\n\\n return endpoint\",\n \"def create(self, identity, data=None, record=None, **kwargs):\\n record.metadata = data.get('metadata', {})\",\n \"def create_identity(name, tags=None, typ=None):\\n if tags:\\n tags = frozenset(tags.items())\\n return (typ, name, tags)\",\n \"def __init__(__self__, *,\\n iothub_id: pulumi.Input[str],\\n resource_group_name: pulumi.Input[str],\\n authentication_type: Optional[pulumi.Input[str]] = None,\\n connection_string: Optional[pulumi.Input[str]] = None,\\n endpoint_uri: Optional[pulumi.Input[str]] = None,\\n entity_path: Optional[pulumi.Input[str]] = None,\\n identity_id: Optional[pulumi.Input[str]] = None,\\n name: Optional[pulumi.Input[str]] = None):\\n pulumi.set(__self__, \\\"iothub_id\\\", iothub_id)\\n pulumi.set(__self__, \\\"resource_group_name\\\", resource_group_name)\\n if authentication_type is not None:\\n pulumi.set(__self__, \\\"authentication_type\\\", authentication_type)\\n if connection_string is not None:\\n pulumi.set(__self__, \\\"connection_string\\\", connection_string)\\n if endpoint_uri is not None:\\n pulumi.set(__self__, \\\"endpoint_uri\\\", endpoint_uri)\\n if entity_path is not None:\\n pulumi.set(__self__, \\\"entity_path\\\", entity_path)\\n if identity_id is not None:\\n pulumi.set(__self__, \\\"identity_id\\\", identity_id)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\",\n \"def create_providerinfo(self, setup=None):\\n pcr_class = self.server.message_factory.get_response_type(\\n \\\"configuration_endpoint\\\"\\n )\\n _provider_info = copy.deepcopy(self.capabilities.to_dict())\\n\\n if self.jwks_uri and self.keyjar:\\n _provider_info[\\\"jwks_uri\\\"] = self.jwks_uri\\n\\n for endp in self.endp:\\n if not self.baseurl.endswith(\\\"/\\\"):\\n baseurl = self.baseurl + \\\"/\\\"\\n else:\\n baseurl = self.baseurl\\n _provider_info[\\\"{}_endpoint\\\".format(endp.etype)] = urljoin(\\n baseurl, endp.url\\n )\\n\\n if setup and isinstance(setup, dict):\\n for key in pcr_class.c_param.keys():\\n if key in setup:\\n _provider_info[key] = setup[key]\\n\\n _provider_info[\\\"issuer\\\"] = self.name\\n _provider_info[\\\"version\\\"] = \\\"3.0\\\"\\n\\n return pcr_class(**_provider_info)\",\n \"def __init__(__self__, *,\\n identity_client_id: Optional[str] = None,\\n resource_id: Optional[str] = None):\\n if identity_client_id is not None:\\n pulumi.set(__self__, \\\"identity_client_id\\\", identity_client_id)\\n if resource_id is not None:\\n pulumi.set(__self__, \\\"resource_id\\\", resource_id)\",\n \"def create_course(self, org, offering, user_id=None, fields=None, store_name='default', **kwargs):\\r\\n store = self.modulestores[store_name]\\r\\n\\r\\n if not hasattr(store, 'create_course'):\\r\\n raise NotImplementedError(u\\\"Cannot create a course on store %s\\\" % store_name)\\r\\n\\r\\n return store.create_course(org, offering, user_id, fields, **kwargs)\",\n \"def create_policy(policystore_url, create_policy_request, verbose):\\n\\n if verbose:\\n logging.info('Creating policy')\\n pprint.pprint(create_policy_request)\\n\\n create_url = policystore_url + POLICYSTORE_PREFIX + 'CreateEntitlementPolicy'\\n\\n r = requests.post(\\n create_url, headers=headers(), json=create_policy_request)\\n if r.status_code != 200:\\n logging.error(f'ERROR: Unexpected response: {r.status_code}')\\n pprint.pprint(r.json())\\n\\n sys.exit('Failed to create policy')\\n\\n resp = r.json()\\n\\n logging.info(\\n f'SUCCESS: Created policy - ID: {resp[\\\"policy_id\\\"]}, Token: {resp[\\\"token\\\"]}'\\n )\\n\\n return resp\",\n \"def create_authorizer(self, ApiId: str, AuthorizerType: str, AuthorizerUri: str, IdentitySource: List, Name: str, AuthorizerCredentialsArn: str = None, AuthorizerResultTtlInSeconds: int = None, IdentityValidationExpression: str = None, ProviderArns: List = None) -> Dict:\\n pass\",\n \"def provider_setup(cls, args, config):\\n if len(args) < 1:\\n print \\\"USAGE: molns provider setup name\\\"\\n print \\\"\\\\tCreates a new provider with the given name.\\\"\\n return\\n # check if provider exists\\n try:\\n provider_obj = config.get_object(args[0], kind='Provider')\\n except DatastoreException:\\n # ask provider type\\n print \\\"Select a provider type:\\\"\\n for n, p in enumerate(VALID_PROVIDER_TYPES):\\n print \\\"\\\\t[{0}] {1}\\\".format(n, p)\\n while True:\\n try:\\n provider_ndx = int(raw_input_default(\\\"Enter the number of type:\\\", default='0'))\\n provider_type = VALID_PROVIDER_TYPES[provider_ndx]\\n break\\n except (ValueError, IndexError):\\n pass\\n logging.debug(\\\"Provider type '{0}'\\\".format(provider_type))\\n # Create provider\\n try:\\n provider_obj = config.create_object(name=args[0], ptype=provider_type, kind='Provider')\\n except DatastoreException as e:\\n logging.exception(e)\\n print e\\n return\\n print \\\"Enter configuration for provider {0}:\\\".format(args[0])\\n setup_object(provider_obj)\\n config.save_object(provider_obj, kind='Provider')\\n\\n cls.provider_initialize(args[0], config)\",\n \"def create(self, request, *args, **kwargs):\\n response = super(ProviderViewSet, self).create(request, *args, **kwargs)\\n response.data['message'] = \\\"Provedor ha sido creado\\\"\\n return response\",\n \"def add_new_identity(self, identity):\\n query = \\\"\\\"\\\"INSERT INTO yubikeys (\\n active,\\n created,\\n modified,\\n yk_publicname,\\n yk_counter,\\n yk_use,\\n yk_low,\\n yk_high,\\n nonce\\n ) VALUES (\\n %(active)s,\\n %(created)s,\\n %(modified)s,\\n %(yk_publicname)s,\\n %(yk_counter)s,\\n %(yk_use)s,\\n %(yk_low)s,\\n %(yk_high)s,\\n %(nonce)s\\n )\\\"\\\"\\\"\\n self._execute(query, identity)\",\n \"def register_vim(cls,\\n cloud_owner: str,\\n cloud_region_id: str,\\n default_tenant: str = None) -> None:\\n cls.send_message(\\n \\\"POST\\\",\\n \\\"Register VIM instance to ONAP\\\",\\n f\\\"{cls.base_url}/{cloud_owner}/{cloud_region_id}/registry\\\",\\n data={\\\"defaultTenant\\\": default_tenant} if default_tenant else None\\n )\",\n \"def test_creating_new_dietitian(self):\\n\\n form_data = {\\\"fname\\\": \\\"Jill\\\", \\\"lname\\\": \\\"Jones\\\", \\n \\\"email\\\": \\\"jill23@gmail.com\\\", \\\"password\\\": \\\"password\\\", \\n \\\"street-address\\\": \\\"33 Blue St\\\", \\\"city\\\": \\\"San Francisco\\\", \\n \\\"state\\\": \\\"CA\\\", \\\"zipcode\\\": \\\"43223\\\"}\\n\\n dietitian_id = create_new_dietitian_account(form_data)\\n\\n self.assertEqual(2, dietitian_id)\",\n \"def create_organization(user, name):\\n organization = Organization.objects.create(name=name)\\n new_user = OrganizationUser.objects.create(organization=organization,\\n user=user, is_admin=True)\\n OrganizationOwner.objects.create(organization=organization,\\n organization_user=new_user)\\n return organization\",\n \"def create(request: PlantRequestCreate) -> Plant:\\n logger.debug(f'Executing Plant create with request:{request}')\\n return Plant(request.name, request.bed_id)\",\n \"def create(self, identity, record=None, data=None, **kwargs):\\n self.set_slug(record, data[\\\"slug\\\"])\",\n \"def create_entity(self, data):\\n url = '{}/ngsi-ld/v1/entities'.format(self.url)\\n return self.post(url, data=data, headers=self.headers_ld)\",\n \"def catalog_create(self, args):\\n try:\\n if args.id and self.server.connect_ermrest(args.id).exists():\\n print(\\\"Catalog already exists\\\")\\n return\\n owner = args.owner if args.owner else None\\n catalog = self.server.create_ermrest_catalog(args.id, owner)\\n if args.auto_configure:\\n model = catalog.getCatalogModel()\\n model.configure_baseline_catalog(**args.configure_args)\\n if not args.quiet:\\n print(\\\"Created new catalog %s with the following default configuration:\\\\n\\\" % catalog.catalog_id)\\n pp(catalog.get('/').json())\\n except HTTPError as e:\\n if e.response.status_code == requests.codes.not_found:\\n raise ResourceException('Catalog not found', e)\\n elif e.response.status_code == requests.codes.conflict:\\n raise ResourceException(\\\"Catalog already exists\\\", e)\\n else:\\n raise e\",\n \"def create_provider(storage_auth):\\n if not storage_auth:\\n provider = Local(storage_auth)\\n elif storage_auth.type == 'MINIO':\\n provider = Minio(storage_auth)\\n elif storage_auth.type == 'ONEDATA':\\n provider = Onedata(storage_auth)\\n elif storage_auth.type == 'S3':\\n provider = S3(storage_auth)\\n elif storage_auth.type == 'WEBDAV':\\n provider = WebDav(storage_auth)\\n else:\\n raise InvalidStorageProviderError(storage_type=storage_auth.type)\\n return provider\",\n \"def identity_provider_name(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"identity_provider_name\\\")\",\n \"def __init__(__self__, *,\\n identity: pulumi.Input['UserAssignedIdentityArgs'],\\n name: pulumi.Input[str],\\n namespace: pulumi.Input[str],\\n binding_selector: Optional[pulumi.Input[str]] = None):\\n pulumi.set(__self__, \\\"identity\\\", identity)\\n pulumi.set(__self__, \\\"name\\\", name)\\n pulumi.set(__self__, \\\"namespace\\\", namespace)\\n if binding_selector is not None:\\n pulumi.set(__self__, \\\"binding_selector\\\", binding_selector)\",\n \"def set_up_identity(self, mc: ManagedCluster) -> ManagedCluster:\\n self._ensure_mc(mc)\\n\\n identity = None\\n enable_managed_identity = self.context.get_enable_managed_identity()\\n assign_identity = self.context.get_assign_identity()\\n if enable_managed_identity and not assign_identity:\\n identity = self.models.ManagedClusterIdentity(\\n type=\\\"SystemAssigned\\\"\\n )\\n elif enable_managed_identity and assign_identity:\\n user_assigned_identity = {\\n assign_identity: self.models.ManagedServiceIdentityUserAssignedIdentitiesValue()\\n }\\n identity = self.models.ManagedClusterIdentity(\\n type=\\\"UserAssigned\\\",\\n user_assigned_identities=user_assigned_identity\\n )\\n mc.identity = identity\\n return mc\"\n]"},"negative_scores":{"kind":"list like","value":["0.6144289","0.5990092","0.5924737","0.5494253","0.5485202","0.53507775","0.53166866","0.51905113","0.5181825","0.51246256","0.5108798","0.51040316","0.5087071","0.50794953","0.50547856","0.50211","0.50116605","0.5002519","0.4999784","0.49900097","0.49755615","0.49569455","0.49335718","0.49200395","0.48801878","0.48650733","0.48602","0.4849936","0.48346928","0.48288682","0.4822313","0.4812243","0.4808785","0.47864598","0.478513","0.47799176","0.47696725","0.4766216","0.47441348","0.474185","0.47396144","0.47211447","0.4691938","0.4669608","0.46668106","0.46544063","0.46327364","0.46303168","0.46154886","0.46135175","0.4600081","0.45957485","0.45938447","0.45807824","0.45780686","0.45743057","0.45720914","0.45684895","0.45622417","0.45622417","0.4562011","0.45581207","0.455003","0.45374","0.45317268","0.45253313","0.45212337","0.45187786","0.45102787","0.45082206","0.44999415","0.4498287","0.44897586","0.44825053","0.44784242","0.44638413","0.4463559","0.4457431","0.4455178","0.44503322","0.44465393","0.44435173","0.4442427","0.4429296","0.44247583","0.44201916","0.441777","0.44053167","0.44037873","0.4395962","0.4393481","0.439326","0.43897533","0.43885937","0.43873098","0.43854132","0.4380034","0.4375211","0.4374899","0.43659025"],"string":"[\n \"0.6144289\",\n \"0.5990092\",\n \"0.5924737\",\n \"0.5494253\",\n \"0.5485202\",\n \"0.53507775\",\n \"0.53166866\",\n \"0.51905113\",\n \"0.5181825\",\n \"0.51246256\",\n \"0.5108798\",\n \"0.51040316\",\n \"0.5087071\",\n \"0.50794953\",\n \"0.50547856\",\n \"0.50211\",\n \"0.50116605\",\n \"0.5002519\",\n \"0.4999784\",\n \"0.49900097\",\n \"0.49755615\",\n \"0.49569455\",\n \"0.49335718\",\n \"0.49200395\",\n \"0.48801878\",\n \"0.48650733\",\n \"0.48602\",\n \"0.4849936\",\n \"0.48346928\",\n \"0.48288682\",\n \"0.4822313\",\n \"0.4812243\",\n \"0.4808785\",\n \"0.47864598\",\n \"0.478513\",\n \"0.47799176\",\n \"0.47696725\",\n \"0.4766216\",\n \"0.47441348\",\n \"0.474185\",\n \"0.47396144\",\n \"0.47211447\",\n \"0.4691938\",\n \"0.4669608\",\n \"0.46668106\",\n \"0.46544063\",\n \"0.46327364\",\n \"0.46303168\",\n \"0.46154886\",\n \"0.46135175\",\n \"0.4600081\",\n \"0.45957485\",\n \"0.45938447\",\n \"0.45807824\",\n \"0.45780686\",\n \"0.45743057\",\n \"0.45720914\",\n \"0.45684895\",\n \"0.45622417\",\n \"0.45622417\",\n \"0.4562011\",\n \"0.45581207\",\n \"0.455003\",\n \"0.45374\",\n \"0.45317268\",\n \"0.45253313\",\n \"0.45212337\",\n \"0.45187786\",\n \"0.45102787\",\n \"0.45082206\",\n \"0.44999415\",\n \"0.4498287\",\n \"0.44897586\",\n \"0.44825053\",\n \"0.44784242\",\n \"0.44638413\",\n \"0.4463559\",\n \"0.4457431\",\n \"0.4455178\",\n \"0.44503322\",\n \"0.44465393\",\n \"0.44435173\",\n \"0.4442427\",\n \"0.4429296\",\n \"0.44247583\",\n \"0.44201916\",\n \"0.441777\",\n \"0.44053167\",\n \"0.44037873\",\n \"0.4395962\",\n \"0.4393481\",\n \"0.439326\",\n \"0.43897533\",\n \"0.43885937\",\n \"0.43873098\",\n \"0.43854132\",\n \"0.4380034\",\n \"0.4375211\",\n \"0.4374899\",\n \"0.43659025\"\n]"},"document_score":{"kind":"string","value":"0.61856276"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8577,"cells":{"query":{"kind":"string","value":"Creates a single mapping between an IdP group and an IAM Service"},"document":{"kind":"string","value":"def create_idp_group_mapping(self, create_idp_group_mapping_details, identity_provider_id, **kwargs):\n resource_path = \"/identityProviders/{identityProviderId}/groupMappings\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_idp_group_mapping got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"identityProviderId\": identity_provider_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_idp_group_mapping_details,\n response_type=\"IdpGroupMapping\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_idp_group_mapping_details,\n response_type=\"IdpGroupMapping\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_api_mapping(self, ApiId: str, DomainName: str, Stage: str, ApiMappingKey: str = None) -> Dict:\n pass","def get_service_mapping():\r\n # Get all Service types:\r\n all_service_type = requests.get(base_url + 'services/v2/service_types', headers=headers3).json()\r\n # Make Dict of service names and ids\r\n service_name_to_id = {service_type['attributes']['name']:service_type['id'] for service_type in all_service_type['data']} \r\n return service_name_to_id","def test_ipam_services_create(self):\n pass","def normalize_idp(idp):\n if idp is None:\n return None\n\n _idp = idp.to_dict()\n _idp['enabled'] = idp['is_enabled']\n _idp['name'] = idp['id']\n return _idp","def test_aws_service_api_keypair_generate_post(self):\n pass","def create_mapping(self):\n\n indice = client.IndicesClient(self.es)\n\n indice.put_mapping(index=self.es_main_index,\n doc_type=self.es_main_type,\n body=self.mapping)","def create_participant_group_mapping(\n self,\n qualification_name: str,\n requester_id: str,\n prolific_project_id: str,\n prolific_participant_group_name: str,\n prolific_participant_group_id: str,\n ) -> None:\n try:\n with self.table_access_condition, self._get_connection() as conn:\n c = conn.cursor()\n c.execute(\n \"\"\"\n INSERT INTO participant_groups(\n qualification_name,\n requester_id,\n prolific_project_id,\n prolific_participant_group_name,\n prolific_participant_group_id\n ) VALUES (?, ?, ?, ?, ?);\n \"\"\",\n (\n qualification_name,\n requester_id,\n prolific_project_id,\n prolific_participant_group_name,\n prolific_participant_group_id,\n ),\n )\n return None\n\n except sqlite3.IntegrityError as e:\n if is_unique_failure(e):\n # Ignore attempt to add another mapping for an existing key\n db_qualification = self.get_qualification_mapping(qualification_name)\n\n logger.debug(\n f\"Multiple Prolific mapping creations \"\n f'for qualification \"{qualification_name}\". '\n f\"Found existing one: {db_qualification}. \"\n )\n assert (\n db_qualification is not None\n ), \"Cannot be none given is_unique_failure on insert\"\n\n db_requester_id = db_qualification[\"requester_id\"]\n db_prolific_qualification_name = db_qualification[\"prolific_participant_group_name\"]\n\n if db_requester_id != requester_id:\n logger.warning(\n f\"Prolific Qualification mapping create for {qualification_name} \"\n f\"under requester {requester_id}, already exists under {db_requester_id}.\"\n )\n\n if db_prolific_qualification_name != prolific_participant_group_name:\n logger.warning(\n f\"Prolific Qualification mapping create for {qualification_name} \"\n f\"with Prolific name {prolific_participant_group_name}, \"\n f\"already exists under {db_prolific_qualification_name}.\"\n )\n\n return None\n else:\n raise e","def _build_ec2_mapping_from_sg(resource_to_analyse, result_dict, session):\n for instance, security_group in _generate_ec2_instance_and_sg(resource_to_analyse):\n sg_dict = _check_if_in_list(result_dict, security_group[\"GroupId\"], \"sg_id\")\n if sg_dict is not None:\n sg_dict[\"resources_attached\"].append({\n \"resource_id\": instance.id,\n \"resource_type\": \"ec2\",\n \"resource_name\": \"\" if _check_if_in_list(instance.tags, \"Name\", \"Key\") is None else _check_if_in_list(instance.tags, \"Name\", \"Key\").get(\"Value\", \"\")\n })\n else:\n result_dict.append({\n \"sg_id\": security_group[\"GroupId\"],\n \"sg_name\": security_group[\"GroupName\"],\n \"resources_attached\": [{\n \"resource_id\": instance.id,\n \"resource_type\": \"ec2\",\n \"resource_name\": \"\" if _check_if_in_list(instance.tags, \"Name\", \"Key\") is None else _check_if_in_list(instance.tags, \"Name\", \"Key\").get(\"Value\", \"\")\n }]\n })\n return result_dict","async def groups_service_handler(service: ServiceCall) -> None:\n object_id = service.data[ATTR_OBJECT_ID]\n entity_id = f\"{DOMAIN}.{object_id}\"\n group = component.get_entity(entity_id)\n\n # new group\n if service.service == SERVICE_SET and group is None:\n entity_ids = (\n service.data.get(ATTR_ENTITIES)\n or service.data.get(ATTR_ADD_ENTITIES)\n or None\n )\n\n extra_arg = {\n attr: service.data[attr]\n for attr in (ATTR_ICON,)\n if service.data.get(attr) is not None\n }\n\n await Group.async_create_group(\n hass,\n service.data.get(ATTR_NAME, object_id),\n object_id=object_id,\n entity_ids=entity_ids,\n user_defined=False,\n mode=service.data.get(ATTR_ALL),\n **extra_arg,\n )\n return\n\n if group is None:\n _LOGGER.warning(\"%s:Group '%s' doesn't exist!\", service.service, object_id)\n return\n\n # update group\n if service.service == SERVICE_SET:\n need_update = False\n\n if ATTR_ADD_ENTITIES in service.data:\n delta = service.data[ATTR_ADD_ENTITIES]\n entity_ids = set(group.tracking) | set(delta)\n await group.async_update_tracked_entity_ids(entity_ids)\n\n if ATTR_REMOVE_ENTITIES in service.data:\n delta = service.data[ATTR_REMOVE_ENTITIES]\n entity_ids = set(group.tracking) - set(delta)\n await group.async_update_tracked_entity_ids(entity_ids)\n\n if ATTR_ENTITIES in service.data:\n entity_ids = service.data[ATTR_ENTITIES]\n await group.async_update_tracked_entity_ids(entity_ids)\n\n if ATTR_NAME in service.data:\n group.name = service.data[ATTR_NAME]\n need_update = True\n\n if ATTR_ICON in service.data:\n group.icon = service.data[ATTR_ICON]\n need_update = True\n\n if ATTR_ALL in service.data:\n group.mode = all if service.data[ATTR_ALL] else any\n need_update = True\n\n if need_update:\n group.async_write_ha_state()\n\n return\n\n # remove group\n if service.service == SERVICE_REMOVE:\n await component.async_remove_entity(entity_id)","def update_pin_group():\n create_instance(new=False)","def create_sg(vpc_id, description, group_name):\n client = boto3.client('ec2')\n security_group = str(group_name + \"_sg\")\n\n # get the security groups\n idle_sg = get_sg()\n\n print(idle_sg)\n print(security_group)\n\n # if security group doesnt exist, create it\n if security_group not in idle_sg:\n print(\"Creating SG\")\n return client.create_security_group(\n Description=description,\n GroupName=security_group,\n VpcId=vpc_id\n )\n return get_sg_id(security_group)","def create_mapping_group(access_path, block_volumes, client_group, host=None):\n retval = -1\n if not isinstance(access_path, int):\n access_path = AccessPath.get_access_path_id(access_path, host)\n if not isinstance(client_group, int):\n client_group = ClientGroup.get_client_group_id(client_group, host)\n if access_path == -1 or client_group == -1:\n print \"[Error] The access path or client group name/id is invalid.\"\n else:\n try:\n retval, block_volumes = _handle_block_volumes(block_volumes, host)\n if retval != 0:\n return retval\n except Exception as e:\n print \"[Error] The block volumes are not valid.\"\n else:\n cmd = utils.XMS_CLI_HEADER + \"mapping-group create --access-path {ap} --block-volumes {bvs} --client-group {cg}\".format(ap=access_path, bvs=block_volumes, cg=client_group)\n print cmd\n ret = utils.execute_cmd_in_host(cmd, host)\n if ret[2] != 0:\n retval = -1\n print \"[Error] Failed to create mapping group. Error message: [{err}]\".format(err=ret[1])\n else:\n retval = 0\n return retval","def testServiceMapping_NoRegistry(self):\n mapping = self.DoMappingTest({'/my-service': MyService}, None)","def add_tomcat7_idp():\n pass","def create_mapping(project, img):\n with BMI(_username, _password, project) as bmi:\n ret = bmi.mount_image(img)\n if ret[constants.STATUS_CODE_KEY] == 200:\n click.echo('Success')\n else:\n click.echo(ret[constants.MESSAGE_KEY])","def _addProteinIdsToGroupMapping(self, proteinIds, groupId):\n for proteinId in AUX.toList(proteinIds):\n self._proteinToGroupIds[proteinId].add(groupId)","def _build_ec2_mapping_from_resources(resource_to_analyse, result_dict, session):\n for instance, security_group in _generate_ec2_instance_and_sg(resource_to_analyse):\n resource_dict = _check_if_in_list(result_dict, instance.id, \"resource_id\")\n if resource_dict is not None:\n resource_dict[\"sg_attached\"].append({\n \"sg_id\": security_group[\"GroupId\"],\n \"sg_name\": security_group[\"GroupName\"]\n })\n else:\n result_dict.append({\n \"resource_id\": instance.id,\n \"resource_type\": \"ec2\",\n \"resource_name\": \"\" if _check_if_in_list(instance.tags, \"Name\", \"Key\") is None else _check_if_in_list(instance.tags, \"Name\", \"Key\").get(\"Value\", \"\"),\n \"sg_attached\": [{\n \"sg_id\": security_group[\"GroupId\"],\n \"sg_name\": security_group[\"GroupName\"]\n }]\n })\n return result_dict","def test_create_user_identity_mapping(self):\n pass","def post_service_instance_create(self, resource_dict):\n pass","def handle_region(self, region, args):\n result = [CHECKMARK, str(region), \"created security group '{}'\".format(GROUP_NAME)]\n\n try:\n # Create the security group\n response = region.conn.create_security_group(\n Description='Security group for Alia replicas and clients.',\n GroupName=GROUP_NAME,\n )\n\n # Get the newly created group id\n group_id = response[\"GroupId\"]\n\n # Allow all network traffic from within the security group\n response = region.conn.authorize_security_group_ingress(\n GroupId = group_id,\n IpPermissions = [\n {\n \"IpProtocol\": \"tcp\", \"FromPort\": 0, \"ToPort\": 65535,\n \"UserIdGroupPairs\": [\n {\n \"GroupId\": group_id,\n \"Description\": \"allow all traffic from the same group\",\n }\n ]\n }\n ]\n )\n\n # Open Alia-specific ports for access\n reponse = region.conn.authorize_security_group_ingress(\n GroupId = group_id,\n IpPermissions = [\n {\n \"IpProtocol\": \"tcp\", \"FromPort\": 22, \"ToPort\": 22,\n \"IpRanges\": [\n {\n \"CidrIp\": \"0.0.0.0/0\",\n \"Description\": \"allow remote SSH access\"\n }\n ]\n },\n {\n \"IpProtocol\": \"tcp\", \"FromPort\": 3264, \"ToPort\": 3285,\n \"IpRanges\": [\n {\n \"CidrIp\": \"0.0.0.0/0\",\n \"Description\": \"external Alia service access\",\n }\n ],\n \"Ipv6Ranges\": [\n {\n \"CidrIpv6\": \"::/0\",\n \"Description\": \"external Alia service IPv6 access\"\n }\n ]\n },\n {\n \"IpProtocol\": \"tcp\", \"FromPort\": 5356, \"ToPort\": 5356,\n \"IpRanges\": [\n {\n \"CidrIp\": \"0.0.0.0/0\",\n \"Description\": \"research services access\"\n }\n ]\n },\n {\n \"IpProtocol\": \"tcp\", \"FromPort\": 4157, \"ToPort\": 4157,\n \"IpRanges\": [\n {\n \"CidrIp\": \"0.0.0.0/0\",\n \"Description\": \"master services access\",\n }\n ]\n },\n ]\n )\n\n\n except Exception as e:\n result[0] = CROSSMARK\n result[2] = str(e)\n\n\n return result","def createFieldMapping(sgidPoints):\n # Create field mappings\n sgidFMs = arcpy.FieldMappings()\n\n # Perform some field renaming\n mapPairs = [\n ('State', 'State'),\n ('City', 'Inc_Muni'),\n ('CountyID', 'County'),\n ('ZipCode', 'Zip_Code'),\n ('PrefixDir', 'StN_PreDir'),\n ('StreetName', 'StreetName'),\n ('StreetType', 'StN_PosTyp'),\n ('SuffixDir', 'StN_PosDir'),\n ('AddNum', 'Add_Number'),\n ('LandmarkName', 'landmkName'),\n ('Building', 'Building'),\n ('UnitType', 'Unit'),\n ('AddSource', 'AddAuth'),\n ('AddSystem', 'UniqWithin'),\n ('LoadDate', 'LastUpdate')]\n\n for p in mapPairs:\n print p\n sgidFMs.addFieldMap(getRenameFieldMap(sgidPoints, p[0], p[1]))\n\n return sgidFMs","def remap_ids(self, id_map: Dict[int, int]) -> None:","def pre_service_instance_create(self, resource_dict):\n pass","def servicebindingmaps(self, servicebindingmap_id, data, tenant_id=None, api_version=\"v2.1\"):\n\n if tenant_id is None and self._parent_class.tenant_id:\n # Pull tenant_id from parent namespace cache.\n tenant_id = self._parent_class.tenant_id\n elif not tenant_id:\n # No value for tenant_id.\n raise TypeError(\"tenant_id is required but not set or cached.\")\n cur_ctlr = self._parent_class.controller\n\n url = str(cur_ctlr) + \"/{}/api/tenants/{}/servicebindingmaps/{}\".format(api_version,\n tenant_id,\n servicebindingmap_id)\n\n api_logger.debug(\"URL = %s\", url)\n return self._parent_class.rest_call(url, \"put\", data=data)","def post_security_group_create(self, resource_dict):\n pass","def remap_ids(self, id_map: Dict[int, int]) -> None:\n super().remap_ids(id_map)\n self.puppet = id_map.get(self.puppet, 0)","def _build_rds_mapping_from_sg(resource_to_analyse, result_dict, session):\n for db_instance, security_group, sg_name in _generate_rds_instances_and_sg(resource_to_analyse, session):\n resource_dict = _check_if_in_list(result_dict, security_group[\"VpcSecurityGroupId\"], \"sg_id\")\n if resource_dict is not None:\n resource_dict[\"resources_attached\"].append({\n \"resource_id\": db_instance[\"DBInstanceIdentifier\"],\n \"resource_type\": \"rds\"\n })\n else:\n result_dict.append({\n \"sg_id\": security_group[\"VpcSecurityGroupId\"],\n \"sg_name\": sg_name,\n \"resources_attached\": [{\n \"resource_id\": db_instance[\"DBInstanceIdentifier\"],\n \"resource_type\": \"rds\"\n }]\n })\n return result_dict","def __init__(__self__, *,\n arn: Optional[pulumi.Input[str]] = None,\n auto_scaling_configuration_arn: Optional[pulumi.Input[str]] = None,\n encryption_configuration: Optional[pulumi.Input['ServiceEncryptionConfigurationArgs']] = None,\n health_check_configuration: Optional[pulumi.Input['ServiceHealthCheckConfigurationArgs']] = None,\n instance_configuration: Optional[pulumi.Input['ServiceInstanceConfigurationArgs']] = None,\n network_configuration: Optional[pulumi.Input['ServiceNetworkConfigurationArgs']] = None,\n observability_configuration: Optional[pulumi.Input['ServiceObservabilityConfigurationArgs']] = None,\n service_id: Optional[pulumi.Input[str]] = None,\n service_name: Optional[pulumi.Input[str]] = None,\n service_url: Optional[pulumi.Input[str]] = None,\n source_configuration: Optional[pulumi.Input['ServiceSourceConfigurationArgs']] = None,\n status: Optional[pulumi.Input[str]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\n tags_all: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\n if arn is not None:\n pulumi.set(__self__, \"arn\", arn)\n if auto_scaling_configuration_arn is not None:\n pulumi.set(__self__, \"auto_scaling_configuration_arn\", auto_scaling_configuration_arn)\n if encryption_configuration is not None:\n pulumi.set(__self__, \"encryption_configuration\", encryption_configuration)\n if health_check_configuration is not None:\n pulumi.set(__self__, \"health_check_configuration\", health_check_configuration)\n if instance_configuration is not None:\n pulumi.set(__self__, \"instance_configuration\", instance_configuration)\n if network_configuration is not None:\n pulumi.set(__self__, \"network_configuration\", network_configuration)\n if observability_configuration is not None:\n pulumi.set(__self__, \"observability_configuration\", observability_configuration)\n if service_id is not None:\n pulumi.set(__self__, \"service_id\", service_id)\n if service_name is not None:\n pulumi.set(__self__, \"service_name\", service_name)\n if service_url is not None:\n pulumi.set(__self__, \"service_url\", service_url)\n if source_configuration is not None:\n pulumi.set(__self__, \"source_configuration\", source_configuration)\n if status is not None:\n pulumi.set(__self__, \"status\", status)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)\n if tags_all is not None:\n pulumi.set(__self__, \"tags_all\", tags_all)","def pre_security_group_create(self, resource_dict):\n pass","def _build_elbv2_mapping_from_sg(resource_to_analyse, result_dict, session):\n for elb_instance, security_group_id, security_group_name in _generate_elb_instances_and_sg(resource_to_analyse, session):\n resource_dict = _check_if_in_list(result_dict, security_group_id, \"sg_id\")\n if resource_dict is not None:\n resource_dict[\"resources_attached\"].append({\n \"resource_id\": elb_instance[\"LoadBalancerName\"],\n \"resource_type\": \"elb\"\n })\n else:\n result_dict.append({\n \"sg_id\": security_group_id,\n \"sg_name\": security_group_name,\n \"resources_attached\": [{\n \"resource_id\": elb_instance[\"LoadBalancerName\"],\n \"resource_type\": \"elb\"\n }]\n })\n return result_dict","def map_service_info(port, nmap_store):\n service = port.find(\"service\")\n nmap_store[\"service_name\"] = service.get(\"name\")\n nmap_store[\"service_method\"] = service.get(\"method\")\n nmap_store[\"service_conf\"] = service.get(\"conf\")","def testDomainMappingCreateAlreadyExistsPrompts(self):\n\n self.operations.CreateDomainMapping.side_effect = [\n exceptions.DomainMappingAlreadyExistsError(), self.domain_mapping\n ]\n\n with mock.patch(\n 'googlecloudsdk.api_lib.run.global_methods.GetServerlessClientInstance',\n return_value=self.mock_serverless_client):\n verified_domains = [\n self.mock_serverless_client.MESSAGES_MODULE.AuthorizedDomain(\n id='www.example.com')\n ]\n with mock.patch(\n 'googlecloudsdk.api_lib.run.global_methods.ListVerifiedDomains',\n return_value=verified_domains):\n self.WriteInput('y\\n')\n self.Run('run domain-mappings create '\n '--service myapp --domain www.example.com')\n self.AssertOutputContains(\n \"\"\"NAME RECORD TYPE CONTENTS\n myapp A 216.239.32.21\"\"\",\n normalize_space=True)","def generate_public_ID(self, mapping):\n raise exception.NotImplemented() # pragma: no cover","def createMappingSetMapping(self,mappingSetId:str=None,mapping:dict=None,verbose:bool=False)->dict:\n if mappingSetId is None:\n raise ValueError(\"Require a mapping ID\")\n if mapping is None or type(mapping)!=dict:\n raise Exception(\"Require a dictionary as mapping\")\n path = f\"/mappingSets/{mappingSetId}/mappings\"\n res = self.connector.postData(self.endpoint+path,data=mapping,verbose=verbose)\n return res","def __init__(__self__, *,\n region: str,\n service_id: str,\n tag: str):\n pulumi.set(__self__, \"region\", region)\n pulumi.set(__self__, \"service_id\", service_id)\n pulumi.set(__self__, \"tag\", tag)","def __init__(__self__, *,\n application_name: pulumi.Input[str],\n cluster_name: pulumi.Input[str],\n resource_group_name: pulumi.Input[str],\n service_kind: pulumi.Input[Union[str, 'ServiceKind']],\n correlation_scheme: Optional[pulumi.Input[Sequence[pulumi.Input['ServiceCorrelationDescriptionArgs']]]] = None,\n default_move_cost: Optional[pulumi.Input[Union[str, 'MoveCost']]] = None,\n location: Optional[pulumi.Input[str]] = None,\n partition_description: Optional[pulumi.Input[Union['NamedPartitionSchemeDescriptionArgs', 'SingletonPartitionSchemeDescriptionArgs', 'UniformInt64RangePartitionSchemeDescriptionArgs']]] = None,\n placement_constraints: Optional[pulumi.Input[str]] = None,\n service_dns_name: Optional[pulumi.Input[str]] = None,\n service_load_metrics: Optional[pulumi.Input[Sequence[pulumi.Input['ServiceLoadMetricDescriptionArgs']]]] = None,\n service_name: Optional[pulumi.Input[str]] = None,\n service_package_activation_mode: Optional[pulumi.Input[Union[str, 'ArmServicePackageActivationMode']]] = None,\n service_placement_policies: Optional[pulumi.Input[Sequence[pulumi.Input['ServicePlacementPolicyDescriptionArgs']]]] = None,\n service_type_name: Optional[pulumi.Input[str]] = None,\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\n pulumi.set(__self__, \"application_name\", application_name)\n pulumi.set(__self__, \"cluster_name\", cluster_name)\n pulumi.set(__self__, \"resource_group_name\", resource_group_name)\n pulumi.set(__self__, \"service_kind\", service_kind)\n if correlation_scheme is not None:\n pulumi.set(__self__, \"correlation_scheme\", correlation_scheme)\n if default_move_cost is not None:\n pulumi.set(__self__, \"default_move_cost\", default_move_cost)\n if location is not None:\n pulumi.set(__self__, \"location\", location)\n if partition_description is not None:\n pulumi.set(__self__, \"partition_description\", partition_description)\n if placement_constraints is not None:\n pulumi.set(__self__, \"placement_constraints\", placement_constraints)\n if service_dns_name is not None:\n pulumi.set(__self__, \"service_dns_name\", service_dns_name)\n if service_load_metrics is not None:\n pulumi.set(__self__, \"service_load_metrics\", service_load_metrics)\n if service_name is not None:\n pulumi.set(__self__, \"service_name\", service_name)\n if service_package_activation_mode is not None:\n pulumi.set(__self__, \"service_package_activation_mode\", service_package_activation_mode)\n if service_placement_policies is not None:\n pulumi.set(__self__, \"service_placement_policies\", service_placement_policies)\n if service_type_name is not None:\n pulumi.set(__self__, \"service_type_name\", service_type_name)\n if tags is not None:\n pulumi.set(__self__, \"tags\", tags)","def create_mapset(self, mapset, dbase=None, location=None):\n module = 'g.c.mapset'\n gs.run_command(module, mapset=mapset, dbase=dbase, location=location)","def creategroup(body):\n group = body.get(\"groupname\", None)\n pps = body.get(\"pilotpoints\", None)\n print('lol',group, pps)\n print(type(pps))\n\n # Does the person exist already?\n if group not in group_dict and group is not None:\n group_dict[group] = {\n \"groupname\": group,\n \"pilotpoints\": pps,\n }\n return group_dict[group], 201\n\n # Otherwise, they exist, that's an error\n else:\n abort(\n 406,\n \"Person with last name {group} already exists\".format(group=group),\n )","def _make_group(self, _rk, _group_hint):\n\n if isinstance(_group_hint, dict):\n # _group_hint is a single key/value pair\n g = _group_hint[list(_group_hint)[0]]\n\n r_type = g.get(\"type\", \"none\")\n if r_type != \"OS::Nova::ServerGroup\":\n return \"support only ServerGroup resource\"\n\n properties = g.get(\"properties\", {})\n if len(properties) == 0:\n return \"no properties\"\n\n group_name = properties.get(\"name\", None)\n if group_name is None:\n return \"no group name\"\n group_name = group_name.strip()\n\n policies = properties.get(\"policies\", [])\n if len(policies) == 0:\n return \"no policy of the group\"\n\n if len(policies) > 1:\n return \"multiple policies\"\n\n # TODO: exclude soft-affinity and soft-anti-affinity?\n\n if group_name in self.groups.keys():\n group = self.groups[group_name]\n else:\n group = Group(group_name)\n\n policy = policies[0].strip()\n if policy == \"anti-affinity\":\n group_type = \"diversity\"\n else:\n group_type = policy\n\n group.group_type = group_type\n group.factory = \"server-group\"\n group.level = \"host\"\n\n self.groups[group_name] = group\n else:\n # group hint is uuid string.\n rg = self.resource.get_group_by_uuid(_group_hint)\n if rg is None:\n return \"unknown group found while making group\"\n\n # TODO: exclude soft-affinity and soft-anti-affinity?\n\n if rg.name in self.groups.keys():\n group = self.groups[rg.name]\n else:\n group = Group(rg.name)\n\n group.group_type = rg.group_type\n group.factory = rg.factory\n group.level = \"host\"\n\n self.groups[rg.name] = group\n\n if group is not None:\n group.server_list.append(self.app_name + \":\" + _rk)\n\n return \"ok\"","def create(person_group_id, name=None, user_data=None):\n name = person_group_id if name is None else name\n url = 'persongroups/{}'.format(person_group_id)\n json = {\n 'name': name,\n 'userData': user_data,\n }\n\n return util.request('PUT', url, json=json)","def pre_network_ipam_create(self, resource_dict):\n pass","def create_mapset(self, mapset, dbase=None, location=None):\n module = 'g.mapset'\n gs.run_command(module, flags='c', mapset=mapset, dbase=dbase, location=location)","def create(self, mapItem: MapItem) -> int:\n pass","def create_sec_group(ec2, sec_group_name):\n sec = ec2.create_security_group(sec_group_name, 'Jvivian Boto SecGroup')\n port = 22\n sec.authorize('tcp', port, port, '0.0.0.0/0')","def _build_rds_mapping_from_resources(resource_to_analyse, result_dict, session):\n for db_instance, security_group, sg_name in _generate_rds_instances_and_sg(resource_to_analyse, session):\n resource_dict = _check_if_in_list(result_dict, db_instance[\"DBInstanceIdentifier\"], \"resource_id\")\n if resource_dict is not None:\n resource_dict[\"sg_attached\"].append({\n \"sg_id\": security_group[\"VpcSecurityGroupId\"],\n \"sg_name\": sg_name\n })\n else:\n result_dict.append({\n \"resource_id\": db_instance[\"DBInstanceIdentifier\"],\n \"resource_type\": \"rds\",\n \"sg_attached\": [{\n \"sg_id\": security_group[\"VpcSecurityGroupId\"],\n \"sg_name\": sg_name\n }]\n })\n return result_dict","def makeMapping(globalMap):\n \n from memops.xml.Implementation import bool2str, str2bool\n\n # Set up top level dictionaries\n loadMaps = globalMap.get('loadMaps')\n mapsByGuid = globalMap.get('mapsByGuid')\n\n abstractTypes = globalMap.get('ACCO').get('abstractTypes')\n exolinks = globalMap.get('ACCO').get('exolinks')\n\n # Class AccessControlStore\n currentMap = {}\n abstractTypes['AccessControlStore'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-09-04-17:18:10_00001'] = currentMap\n loadMaps['ACCO.AccessControlStore'] = currentMap\n currentMap['tag'] = 'ACCO.AccessControlStore'\n currentMap['type'] = 'class'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:18:10_00001'\n currentMap['eType'] = 'cplx'\n currentMap['fromParent'] = 'accessControlStores'\n currentMap['isTop'] = True\n currentMap['objkey'] = 'name'\n currentMap['class'] = memops.api.AccessControl.AccessControlStore\n contentMap = {}\n currentMap['content'] = contentMap\n\n # Attribute AccessControlStore.applicationData\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\n\n # Attribute AccessControlStore.createdBy\n contentMap['createdBy'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:00:59_00002__www.ccpn.ac.uk_Fogh_2007-10-03-14:53:27_00001__www.ccpn.ac.uk_Fogh_2006-09-14-16:28:57_00002')\n\n # Attribute AccessControlStore.guid\n contentMap['guid'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:26_00002')\n\n # Attribute AccessControlStore.isModifiable\n contentMap['isModifiable'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-17-14:16:26_00010__www.ccpn.ac.uk_Fogh_2007-10-03-14:53:27_00001__www.ccpn.ac.uk_Fogh_2006-09-14-16:28:57_00002')\n\n # Attribute AccessControlStore.lastUnlockedBy\n contentMap['lastUnlockedBy'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:00:59_00003__www.ccpn.ac.uk_Fogh_2007-10-03-14:53:27_00001__www.ccpn.ac.uk_Fogh_2006-09-14-16:28:57_00002')\n\n # Attribute AccessControlStore.name\n currentMap = {}\n contentMap['name'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00006'] = currentMap\n loadMaps['ACCO.AccessControlStore.name'] = currentMap\n currentMap['tag'] = 'ACCO.AccessControlStore.name'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00006'\n currentMap['name'] = 'name'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['eType'] = 'cplx'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033')\n\n # Role AccessControlStore.access\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\n\n # Role AccessControlStore.accessObjects\n currentMap = {}\n contentMap['accessObjects'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00013'] = currentMap\n loadMaps['ACCO.AccessControlStore.accessObjects'] = currentMap\n currentMap['tag'] = 'ACCO.AccessControlStore.accessObjects'\n currentMap['type'] = 'child'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00013'\n currentMap['name'] = 'accessObjects'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['eType'] = 'cplx'\n currentMap['implSkip'] = True\n currentMap['content'] = globalMap.get('ACCO').get('abstractTypes')\n\n # Role AccessControlStore.userGroups\n currentMap = {}\n contentMap['userGroups'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00003'] = currentMap\n loadMaps['ACCO.AccessControlStore.userGroups'] = currentMap\n currentMap['tag'] = 'ACCO.AccessControlStore.userGroups'\n currentMap['type'] = 'child'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00003'\n currentMap['name'] = 'userGroups'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['eType'] = 'cplx'\n currentMap['implSkip'] = True\n currentMap['content'] = globalMap.get('ACCO').get('abstractTypes')\n\n # Role AccessControlStore.users\n currentMap = {}\n contentMap['users'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00001'] = currentMap\n loadMaps['ACCO.AccessControlStore.users'] = currentMap\n currentMap['tag'] = 'ACCO.AccessControlStore.users'\n currentMap['type'] = 'child'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00001'\n currentMap['name'] = 'users'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['eType'] = 'cplx'\n currentMap['implSkip'] = True\n currentMap['content'] = globalMap.get('ACCO').get('abstractTypes')\n # End of AccessControlStore\n\n currentMap = abstractTypes.get('AccessControlStore')\n aList = ['createdBy', 'guid', 'isModifiable', 'lastUnlockedBy']\n currentMap['headerAttrs'] = aList\n aList = ['name']\n currentMap['simpleAttrs'] = aList\n aList = ['users', 'userGroups', 'accessObjects', 'access', 'applicationData']\n currentMap['cplxAttrs'] = aList\n aList = ['accessObjects', 'userGroups', 'users']\n currentMap['children'] = aList\n\n # Class AccessObject\n currentMap = {}\n abstractTypes['AccessObject'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00014'] = currentMap\n loadMaps['ACCO.AccessObject'] = currentMap\n currentMap['tag'] = 'ACCO.AccessObject'\n currentMap['type'] = 'class'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00014'\n currentMap['eType'] = 'cplx'\n currentMap['fromParent'] = 'accessObjects'\n currentMap['objkey'] = 'name'\n currentMap['class'] = memops.api.AccessControl.AccessObject\n contentMap = {}\n currentMap['content'] = contentMap\n\n # Attribute AccessObject.applicationData\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\n\n # Attribute AccessObject.description\n currentMap = {}\n contentMap['description'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00005'] = currentMap\n loadMaps['ACCO.AccessObject.description'] = currentMap\n currentMap['tag'] = 'ACCO.AccessObject.description'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00005'\n currentMap['name'] = 'description'\n currentMap['hicard'] = 1\n currentMap['locard'] = 0\n currentMap['eType'] = 'cplx'\n currentMap['proc'] = 'direct'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00035')\n\n # Attribute AccessObject.name\n currentMap = {}\n contentMap['name'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00004'] = currentMap\n loadMaps['ACCO.AccessObject.name'] = currentMap\n currentMap['tag'] = 'ACCO.AccessObject.name'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00004'\n currentMap['name'] = 'name'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['eType'] = 'cplx'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033')\n\n # Role AccessObject.access\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\n\n # Role AccessObject.permissions\n currentMap = {}\n contentMap['permissions'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00001'] = currentMap\n loadMaps['ACCO.AccessObject.permissions'] = currentMap\n currentMap['tag'] = 'ACCO.AccessObject.permissions'\n currentMap['type'] = 'child'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00001'\n currentMap['name'] = 'permissions'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['eType'] = 'cplx'\n currentMap['content'] = globalMap.get('ACCO').get('abstractTypes')\n # End of AccessObject\n\n currentMap = abstractTypes.get('AccessObject')\n aList = ['description', 'name']\n currentMap['simpleAttrs'] = aList\n aList = ['permissions', 'access', 'applicationData']\n currentMap['cplxAttrs'] = aList\n aList = ['permissions']\n currentMap['children'] = aList\n\n # Class Permission\n currentMap = {}\n abstractTypes['Permission'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00018'] = currentMap\n loadMaps['ACCO.Permission'] = currentMap\n currentMap['tag'] = 'ACCO.Permission'\n currentMap['type'] = 'class'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00018'\n currentMap['eType'] = 'cplx'\n currentMap['fromParent'] = 'permissions'\n currentMap['class'] = memops.api.AccessControl.Permission\n contentMap = {}\n currentMap['content'] = contentMap\n\n # Attribute Permission.applicationData\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\n\n # Attribute Permission.opType\n currentMap = {}\n contentMap['opType'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00021'] = currentMap\n loadMaps['ACCO.Permission.opType'] = currentMap\n currentMap['tag'] = 'ACCO.Permission.opType'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00021'\n currentMap['name'] = 'opType'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['default'] = 'any'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037')\n\n # Attribute Permission.permission\n currentMap = {}\n contentMap['permission'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00023'] = currentMap\n loadMaps['ACCO.Permission.permission'] = currentMap\n currentMap['tag'] = 'ACCO.Permission.permission'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00023'\n currentMap['name'] = 'permission'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['default'] = True\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00028')\n\n # Attribute Permission.permissionClass\n currentMap = {}\n contentMap['permissionClass'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00020'] = currentMap\n loadMaps['ACCO.Permission.permissionClass'] = currentMap\n currentMap['tag'] = 'ACCO.Permission.permissionClass'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00020'\n currentMap['name'] = 'permissionClass'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['default'] = 'any'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037')\n\n # Attribute Permission.roleName\n currentMap = {}\n contentMap['roleName'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00022'] = currentMap\n loadMaps['ACCO.Permission.roleName'] = currentMap\n currentMap['tag'] = 'ACCO.Permission.roleName'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00022'\n currentMap['name'] = 'roleName'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['default'] = 'any'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037')\n\n # Role Permission.access\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\n\n # Role Permission.userGroup\n currentMap = {}\n contentMap['userGroup'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00016'] = currentMap\n loadMaps['ACCO.Permission.userGroup'] = currentMap\n currentMap['tag'] = 'ACCO.Permission.userGroup'\n currentMap['type'] = 'link'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00016'\n currentMap['name'] = 'userGroup'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['copyOverride'] = True\n # End of Permission\n\n currentMap = abstractTypes.get('Permission')\n aList = ['opType', 'permission', 'permissionClass', 'roleName']\n currentMap['headerAttrs'] = aList\n aList = ['userGroup']\n currentMap['optLinks'] = aList\n aList = ['access', 'applicationData']\n currentMap['cplxAttrs'] = aList\n\n # Class User\n currentMap = {}\n abstractTypes['User'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00017'] = currentMap\n loadMaps['ACCO.User'] = currentMap\n currentMap['tag'] = 'ACCO.User'\n currentMap['type'] = 'class'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00017'\n currentMap['eType'] = 'cplx'\n currentMap['fromParent'] = 'users'\n currentMap['objkey'] = 'name'\n currentMap['class'] = memops.api.AccessControl.User\n contentMap = {}\n currentMap['content'] = contentMap\n\n # Attribute User.applicationData\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\n\n # Attribute User.isSuperuser\n currentMap = {}\n contentMap['isSuperuser'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2010-05-06-13:30:17_00060'] = currentMap\n loadMaps['ACCO.User.isSuperuser'] = currentMap\n currentMap['tag'] = 'ACCO.User.isSuperuser'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2010-05-06-13:30:17_00060'\n currentMap['name'] = 'isSuperuser'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['default'] = False\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00028')\n\n # Attribute User.name\n currentMap = {}\n contentMap['name'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00019'] = currentMap\n loadMaps['ACCO.User.name'] = currentMap\n currentMap['tag'] = 'ACCO.User.name'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00019'\n currentMap['name'] = 'name'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['eType'] = 'cplx'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033')\n\n # Attribute User.passwordHashed\n currentMap = {}\n contentMap['passwordHashed'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2009-08-19-17:31:11_00005'] = currentMap\n loadMaps['ACCO.User.passwordHashed'] = currentMap\n currentMap['tag'] = 'ACCO.User.passwordHashed'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2009-08-19-17:31:11_00005'\n currentMap['name'] = 'passwordHashed'\n currentMap['hicard'] = 1\n currentMap['locard'] = 0\n currentMap['eType'] = 'cplx'\n currentMap['proc'] = 'direct'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00035')\n\n # Role User.access\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\n\n # Role User.ledGroups\n currentMap = {}\n contentMap['ledGroups'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00014'] = currentMap\n loadMaps['ACCO.User.ledGroups'] = currentMap\n currentMap['tag'] = 'ACCO.User.ledGroups'\n currentMap['type'] = 'link'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00014'\n currentMap['name'] = 'ledGroups'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['copyOverride'] = True\n\n # Role User.userGroups\n currentMap = {}\n contentMap['userGroups'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00012'] = currentMap\n loadMaps['ACCO.User.userGroups'] = currentMap\n currentMap['tag'] = 'ACCO.User.userGroups'\n currentMap['type'] = 'link'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00012'\n currentMap['name'] = 'userGroups'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['copyOverride'] = True\n # End of User\n\n currentMap = abstractTypes.get('User')\n aList = ['isSuperuser']\n currentMap['headerAttrs'] = aList\n aList = ['name', 'passwordHashed', 'ledGroups', 'userGroups']\n currentMap['simpleAttrs'] = aList\n aList = ['access', 'applicationData']\n currentMap['cplxAttrs'] = aList\n\n # Class UserGroup\n currentMap = {}\n abstractTypes['UserGroup'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00016'] = currentMap\n loadMaps['ACCO.UserGroup'] = currentMap\n currentMap['tag'] = 'ACCO.UserGroup'\n currentMap['type'] = 'class'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00016'\n currentMap['eType'] = 'cplx'\n currentMap['fromParent'] = 'userGroups'\n currentMap['objkey'] = 'name'\n currentMap['class'] = memops.api.AccessControl.UserGroup\n contentMap = {}\n currentMap['content'] = contentMap\n\n # Attribute UserGroup.applicationData\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\n\n # Attribute UserGroup.name\n currentMap = {}\n contentMap['name'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00018'] = currentMap\n loadMaps['ACCO.UserGroup.name'] = currentMap\n currentMap['tag'] = 'ACCO.UserGroup.name'\n currentMap['type'] = 'attr'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00018'\n currentMap['name'] = 'name'\n currentMap['hicard'] = 1\n currentMap['locard'] = 1\n currentMap['eType'] = 'cplx'\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033')\n\n # Role UserGroup.access\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\n\n # Role UserGroup.leaders\n currentMap = {}\n contentMap['leaders'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00015'] = currentMap\n loadMaps['ACCO.UserGroup.leaders'] = currentMap\n currentMap['tag'] = 'ACCO.UserGroup.leaders'\n currentMap['type'] = 'link'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00015'\n currentMap['name'] = 'leaders'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['copyOverride'] = True\n\n # Role UserGroup.members\n currentMap = {}\n contentMap['members'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00013'] = currentMap\n loadMaps['ACCO.UserGroup.members'] = currentMap\n currentMap['tag'] = 'ACCO.UserGroup.members'\n currentMap['type'] = 'link'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00013'\n currentMap['name'] = 'members'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['copyOverride'] = False\n\n # Role UserGroup.permissions\n currentMap = {}\n contentMap['permissions'] = currentMap\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00017'] = currentMap\n loadMaps['ACCO.UserGroup.permissions'] = currentMap\n currentMap['tag'] = 'ACCO.UserGroup.permissions'\n currentMap['type'] = 'link'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00017'\n currentMap['name'] = 'permissions'\n currentMap['hicard'] = -1\n currentMap['locard'] = 0\n currentMap['copyOverride'] = False\n # End of UserGroup\n\n currentMap = abstractTypes.get('UserGroup')\n aList = ['name', 'leaders', 'members', 'permissions']\n currentMap['simpleAttrs'] = aList\n aList = ['access', 'applicationData']\n currentMap['cplxAttrs'] = aList\n\n # Out-of-package link to AccessControlStore\n currentMap = {}\n exolinks['AccessControlStore'] = currentMap\n loadMaps['ACCO.exo-AccessControlStore'] = currentMap\n currentMap['tag'] = 'ACCO.exo-AccessControlStore'\n currentMap['type'] = 'exo'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:18:10_00001'\n currentMap['name'] = 'AccessControlStore'\n currentMap['eType'] = 'cplx'\n currentMap['class'] = memops.api.AccessControl.AccessControlStore\n aList = list()\n currentMap['keyMaps'] = aList\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\n\n # Out-of-package link to AccessObject\n currentMap = {}\n exolinks['AccessObject'] = currentMap\n loadMaps['ACCO.exo-AccessObject'] = currentMap\n currentMap['tag'] = 'ACCO.exo-AccessObject'\n currentMap['type'] = 'exo'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00014'\n currentMap['name'] = 'AccessObject'\n currentMap['eType'] = 'cplx'\n currentMap['class'] = memops.api.AccessControl.AccessObject\n aList = list()\n currentMap['keyMaps'] = aList\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033'))\n\n # Out-of-package link to Permission\n currentMap = {}\n exolinks['Permission'] = currentMap\n loadMaps['ACCO.exo-Permission'] = currentMap\n currentMap['tag'] = 'ACCO.exo-Permission'\n currentMap['type'] = 'exo'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00018'\n currentMap['name'] = 'Permission'\n currentMap['eType'] = 'cplx'\n currentMap['class'] = memops.api.AccessControl.Permission\n aList = list()\n currentMap['keyMaps'] = aList\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033'))\n aList.append(globalMap.get('ACCO').get('exolinks'))\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037'))\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037'))\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037'))\n\n # Out-of-package link to User\n currentMap = {}\n exolinks['User'] = currentMap\n loadMaps['ACCO.exo-User'] = currentMap\n currentMap['tag'] = 'ACCO.exo-User'\n currentMap['type'] = 'exo'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00017'\n currentMap['name'] = 'User'\n currentMap['eType'] = 'cplx'\n currentMap['class'] = memops.api.AccessControl.User\n aList = list()\n currentMap['keyMaps'] = aList\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033'))\n\n # Out-of-package link to UserGroup\n currentMap = {}\n exolinks['UserGroup'] = currentMap\n loadMaps['ACCO.exo-UserGroup'] = currentMap\n currentMap['tag'] = 'ACCO.exo-UserGroup'\n currentMap['type'] = 'exo'\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00016'\n currentMap['name'] = 'UserGroup'\n currentMap['eType'] = 'cplx'\n currentMap['class'] = memops.api.AccessControl.UserGroup\n aList = list()\n currentMap['keyMaps'] = aList\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033'))","def generate_object(self, **kwargs):\n from ranger_performance_tool import perf_globals\n service_type_mapping = perf_globals.CONFIG_READER.get_config_value(\"secondary\", \"service_type_mapping\")\n if \"id\" not in kwargs:\n kwargs[\"id\"] = self.random_generator.generate_int()\n if \"name\" not in kwargs:\n kwargs[\"name\"] = self.random_generator.generate_string()\n if \"service\" not in kwargs:\n enabled_service = random.choice(perf_globals.CONFIG_READER.get_config_value(\"secondary\", \"enabled_services\"))\n service_type = service_type_mapping[enabled_service]\n kwargs[\"service\"] = enabled_service\n kwargs[\"serviceType\"] = service_type\n policy_object = RangerPolicy()\n for key, value in kwargs.items():\n if key not in dir(policy_object):\n raise Exception(\"Invalid key: \" + key)\n policy_object[key] = value\n service_type = policy_object.serviceType\n service_store = perf_globals.OBJECT_STORE.service_store[service_type]\n policy_object.resources = service_store.generate_resources()\n return policy_object","def role_create(ctx, name, service):\n # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/iam.html#IAM.Client.create_role\n service_code = SERVICE.get(service, None)\n if service_code:\n res = IAM.client().create_role(\n RoleName=name,\n AssumeRolePolicyDocument=service_policy(service_code),\n )\n click.echo(J(res))","def execute(self, pool, vthunder):\n\n args = {'service_group': self.meta(pool, 'service_group', {})}\n try:\n conf_templates = self.readConf('SERVICE_GROUP','templates').strip('\"')\n service_group_temp = {}\n service_group_temp['template-server'] = conf_templates\n except:\n service_group_temp = None\n\n try:\n c = self.client_factory(vthunder)\n lb_method=openstack_mappings.service_group_lb_method(c,pool.lb_algorithm)\n out = c.slb.service_group.create(pool.id, pool.protocol, lb_method,\n service_group_temp, axapi_args=args)\n LOG.info(\"Pool created successfully.\")\n except Exception as e:\n print(str(e))\n LOG.info(\"Error occurred\")","def create_project_apikey(self\n ,project_id\n ,description='pyatlas generated project apikey'\n ,roles='PROJECT_OWNER'):\n print('pyatlas - create_apikey') \n roles = roles.split(',')\n pprint.pprint(roles)\n data = { 'desc' : description, 'roles' : roles }\n pprint.pprint(data)\n \n target = f'{ApiVersion.CM1.value}/groups/{project_id}/apiKeys'\n print( f'target={target}' )\n print( f'data={data}' )\n response = self.post(target, body=data)\n return response","def _db_key_to_servicekey(key):\n return ServiceKey(\n name=key.name,\n kid=key.kid,\n service=key.service,\n jwk=key.jwk,\n metadata=key.metadata,\n created_date=key.created_date,\n expiration_date=key.expiration_date,\n rotation_duration=key.rotation_duration,\n approval=key.approval,\n )","def mk_rg1(self):\n name = f\"{self.env_name}/sg/project-default\"\n self.sg_project_default = ec2.SecurityGroup(\n \"SecurityGroupProjectDefault\",\n rp_GroupDescription=\"Resources that has this security can talk to each other\",\n p_GroupName=name,\n p_VpcId=self.vpc_id,\n p_SecurityGroupIngress=[\n ec2.PropSecurityGroupIngress(\n rp_IpProtocol=\"-1\",\n p_FromPort=-1,\n p_ToPort=-1,\n p_CidrIp=f\"{authorized_ip}/32\",\n )\n for authorized_ip in self.sg_authorized_ips\n ],\n p_Tags=cf.Tag.make_many(\n Name=name\n ),\n )","def placement_group(template, name):\n p = PlacementGroup(name, template=template)\n p.Strategy = 'cluster'\n return p","def create_datasource_mapping(connection: Connection, body, error_msg: Optional[str] = None):\n url = f\"{connection.base_url}/api/datasources/mappings\"\n response = connection.session.post(url=url, json=body)\n if not response.ok:\n if error_msg is None:\n error_msg = \"Error creating Datasource mapping\"\n response_handler(response, error_msg)\n return response","def create_placement_group(self, name, strategy='cluster'):\r\n params = {'GroupName':name, 'Strategy':strategy}\r\n group = self.get_status('CreatePlacementGroup', params, verb='POST')\r\n return group","def _build_elbv2_mapping_from_resources(resource_to_analyse, result_dict, session):\n for elb_instance, security_group_id, security_group_name in _generate_elb_instances_and_sg(resource_to_analyse, session):\n resource_dict = _check_if_in_list(result_dict, elb_instance[\"LoadBalancerName\"], \"resource_id\")\n if resource_dict is not None:\n resource_dict[\"sg_attached\"].append({\n \"sg_id\": security_group_id,\n \"sg_name\": security_group_name\n })\n else:\n result_dict.append({\n \"resource_id\": elb_instance[\"LoadBalancerName\"],\n \"resource_type\": \"elb\",\n \"sg_attached\": [{\n \"sg_id\": security_group_id,\n \"sg_name\": security_group_name\n }]\n })\n return result_dict","def setUp(self):\n user = User.objects.create(email=\"test1@test.com\", first_name=\"Test1\", last_name=\"User\")\n group = AnaGroup.objects.create(name=\"test group\")\n IAM.objects.create(user=user,\n aws_user=\"AWS user\",\n aws_access_key=\"AWS access key\",\n aws_secret_access_key=\"AWS secret key\",\n group=group)","def service_account(configure_security):\n try:\n name = config.SERVICE_NAME\n secret = \"{}-secret\".format(name)\n sdk_security.create_service_account(\n service_account_name=name, service_account_secret=secret)\n # TODO(mh): Fine grained permissions needs to be addressed in DCOS-16475\n sdk_cmd.run_cli(\n \"security org groups add_user superusers {name}\".format(name=name))\n yield {\"name\": name, \"secret\": secret}\n finally:\n return","def test_create_resource_group(self):\n pass","def mapping(self, release_id, grouping):\n\n helper = Known(self.config, self.session)\n classes = [g['name']['full'] for g in grouping]\n return helper.mapping(release_id, classes)","def test_create_namespaced_image_stream_mapping(self):\n pass","def create_group(group_id, group_name):\n\n kwargs = config.DEFAULT_REST_KWARGS\n kwargs[\"data\"] = {\"id\": group_id, \"name\": group_name}\n http_response = call_rest_api(\"/identities/groups/\", \"post\", **kwargs)\n if http_response.status_code != 201: # 201 = 'new group created'\n raise ValueError(http_response.text)\n logger.log(f\"New custom group, {group_name}, with ID: {group_id}, was created successfully.\")","def make_mapping(self) -> None:\n start_mark = StreamMark('generated node', 0, 0, 0)\n end_mark = StreamMark('generated node', 0, 0, 0)\n self.yaml_node = yaml.MappingNode('tag:yaml.org,2002:map', list(),\n start_mark, end_mark)","def group_single(self, dss_group, unix_user, hadoop_user=None):\n self.raw['type'] = 'SINGLE_MAPPING'\n self.raw['dssGroup'] = dss_group\n self.raw['targetUnix'] = unix_user\n self.raw['targetHadoop'] = hadoop_user\n return self","def post_network_ipam_create(self, resource_dict):\n pass","def __init__(__self__, *,\n domain_id: Optional[pulumi.Input[str]] = None,\n group_id: Optional[pulumi.Input[str]] = None,\n project_id: Optional[pulumi.Input[str]] = None,\n region: Optional[pulumi.Input[str]] = None,\n role_id: Optional[pulumi.Input[str]] = None,\n user_id: Optional[pulumi.Input[str]] = None):\n if domain_id is not None:\n pulumi.set(__self__, \"domain_id\", domain_id)\n if group_id is not None:\n pulumi.set(__self__, \"group_id\", group_id)\n if project_id is not None:\n pulumi.set(__self__, \"project_id\", project_id)\n if region is not None:\n pulumi.set(__self__, \"region\", region)\n if role_id is not None:\n pulumi.set(__self__, \"role_id\", role_id)\n if user_id is not None:\n pulumi.set(__self__, \"user_id\", user_id)","def testServiceMapping_ByList(self):\n self.DoMappingTest(\n [('/my-service1', MyService.new_factory('service1')),\n ('/my-service2', MyService.new_factory('service2')),\n ])","def create_asu_map(mapin, mapout):\n\n # Masking object\n masker = CommandManager('mapmask')\n # Set input files\n masker.add_command_line_arguments(['mapin',mapin,'mapout',mapout])\n # Set stdin\n masker.add_standard_input(['XYZLIM ASU','END'])\n # Run!\n masker.run()\n # Report errors\n if masker.process.returncode!=0:\n raise RuntimeError('mapmask failed to create asu map from {!s}'.format(mapin))\n\n # Return Command Managers for flexible handling of out & err\n return masker","def create_iam_role(iam):\n print(\"Creating a new IAM Role\") \n try:\n resp = iam.create_role(Path='/',\n RoleName=DWH_IAM_ROLE_NAME,\n Description = \"Allows Redshift clusters to call AWS services on your behalf.\",\n AssumeRolePolicyDocument=json.dumps({'Statement': [{'Action': 'sts:AssumeRole',\n 'Effect': 'Allow',\n 'Principal': {'Service': 'redshift.amazonaws.com'}}],\n 'Version': '2012-10-17'}\n )\n )\n print(\"IAM Role created:\")\n print(resp)\n except iam.exceptions.EntityAlreadyExistsException:\n print(\"IAM Role already created\")\n except Exception as e:\n print(\"Error creating IAM Role:\", e)","def assignGroupIDs(self):\n components = self.getComponents(graph_dictionary=self.graph_dict)\n self._gIDs = np.zeros(self.no_plants, dtype='object')\n for i in components.keys():\n self._gIDs[components[i]] = 'gID_' + str(i)","def create_srv_entry(srv_name, ip, port):\n res = {}\n res['service'] = \"_{}._tcp.marathon.mesos\".format(srv_name)\n res['host'] = \"{}-74b1w-s1.marathon.mesos.\".format(srv_name)\n res['ip'] = ip\n res['port'] = port\n\n return res","def generate_control_mappings(self, control):\n acr_creator = all_models.AccessControlRole.query.filter_by(\n name=\"Creators\", object_type=\"Assessment\"\n ).first()\n with factories.single_commit():\n person = factories.PersonFactory()\n asmnt_ids = []\n for _ in range(2):\n asmnt = factories.AssessmentFactory()\n asmnt_ids.append(asmnt.id)\n factories.AccessControlListFactory(\n object=asmnt, person=person, ac_role=acr_creator\n )\n\n for asmnt_id in asmnt_ids:\n asmnt = all_models.Assessment.query.get(asmnt_id)\n self.gen.generate_relationship(source=asmnt, destination=control)","def create_namespaced_user_identity_mapping(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_user_identity_mapping\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_user_identity_mapping`\")\n\n resource_path = '/oapi/v1/useridentitymappings'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1UserIdentityMapping',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def testServiceMapping_ByFactory(self):\n self.DoMappingTest({'/my-service': MyService.new_factory('new-value')})","def testMapping(self):\n factory = service_handlers.ServiceHandlerFactory(Service)\n path, mapped_factory = factory.mapping('/my_service')\n\n self.assertEquals(r'(/my_service)' + service_handlers._METHOD_PATTERN, path)\n self.assertEquals(id(factory), id(mapped_factory))\n match = re.match(path, '/my_service.my_method')\n self.assertEquals('/my_service', match.group(1))\n self.assertEquals('my_method', match.group(2))\n\n path, mapped_factory = factory.mapping('/my_service/nested')\n self.assertEquals('(/my_service/nested)' +\n service_handlers._METHOD_PATTERN, path)\n match = re.match(path, '/my_service/nested.my_method')\n self.assertEquals('/my_service/nested', match.group(1))\n self.assertEquals('my_method', match.group(2))","def amazonEc2_create(amazonEc2):\n\treturn amazonEc2","def _mrp_service(self, _, address, port, properties):\n identifier = properties.get(\"UniqueIdentifier\")\n name = properties.get(\"Name\")\n service = conf.MrpService(identifier, port, properties=properties)\n self._handle_service(address, name, service)","def create_inbound(self, keys):","def post_service_appliance_set_create(self, resource_dict):\n pass","def create_new_group(self, a, b):\n self.groups[self.group_id] = set([a,b])\n self.node_id[a] = self.node_id[b] = self.group_id\n self.group_id += 1","def create_entry_group(self, location_id, entry_group_id):\n entry_group = self.__datacatalog.create_entry_group(\n parent=f'projects/{self.__project_id}/locations/{location_id}',\n entry_group_id=entry_group_id,\n entry_group=datacatalog.EntryGroup())\n logging.info('Entry Group created: %s', entry_group.name)\n return entry_group","def _makeimap(self):\n self.map_[\"source\"] = \"nasa\"\n self.map_[\"instrument\"] = \"goes\"\n self.map_[\"physobs\"] = \"irradiance\"\n self.map_[\"provider\"] = \"sdac\"","def _transform(self, resource_from_api):\n for (project_id, backend_services) in resource_from_api.iteritems():\n for backend_service in backend_services:\n yield {'project_id': project_id,\n 'id': backend_service.get('id'),\n 'creation_timestamp': parser.format_timestamp(\n backend_service.get('creationTimestamp'),\n self.MYSQL_DATETIME_FORMAT),\n 'name': backend_service.get('name'),\n 'description': backend_service.get('description'),\n 'affinity_cookie_ttl_sec': self._to_int(\n backend_service.get('affinityCookieTtlSec')),\n 'backends': parser.json_stringify(\n backend_service.get('backends', [])),\n 'cdn_policy': parser.json_stringify(\n backend_service.get('cdnPolicy', {})),\n 'connection_draining': parser.json_stringify(\n backend_service.get('connectionDraining', {})),\n 'enable_cdn': self._to_bool(\n backend_service.get('enableCDN')),\n 'health_checks': parser.json_stringify(\n backend_service.get('healthChecks', [])),\n 'iap': parser.json_stringify(\n backend_service.get('iap', {})),\n 'load_balancing_scheme': backend_service.get(\n 'loadBalancingScheme'),\n 'port': self._to_int(backend_service.get('port')),\n 'port_name': backend_service.get('portName'),\n 'protocol': backend_service.get('protocol'),\n 'region': backend_service.get('region'),\n 'session_affinity': backend_service.get(\n 'sessionAffinity'),\n 'timeout_sec': backend_service.get('timeoutSec'),\n 'raw_backend_service':\n parser.json_stringify(backend_service)}","def test_create_group(self):\n pass","def test_create_group(self):\n pass","def create(self, name, public_key=None):\n data = {\n \"keypair\": {\n \"name\": name\n }\n }\n if public_key is not None:\n data['keypair']['public_key'] = public_key\n \n path = '/os-keypairs'\n res = self.client.call(path, 'POST', data=json.dumps(data), \n token=self.manager.identity.token)\n self.logger.debug('Create/import openstack keypair: %s' % truncate(res))\n return res[0]['keypair']","def createService(data):\n return Service(data).create()","def form_point_to_tract_mapping(voter, mapping, geoid_to_id_mapping: GeoIDToIDMapping):\n # voter.name refers to the point ID\n mapping[voter.name] = geoid_to_id_mapping[voter[\"GEOID\"]]","def create_from_changeset(changeset, stub=None, update_sender=None, update_recipient=None):\n group = Identity.create_from_changeset(changeset,\n stub=stub, update_sender=update_sender, update_recipient=update_recipient, kind=Group)\n\n group.description = changeset[\"description\"]\n group.set_state(changeset[\"state\"])\n request_list = list()\n\n # Update admin\n admin = Persona.query.get(changeset[\"admin_id\"])\n if admin is None or admin._stub:\n request_list.append({\n \"type\": \"Persona\",\n \"id\": changeset[\"admin_id\"],\n \"author_id\": update_recipient.id if update_recipient else None,\n \"recipient_id\": update_sender.id if update_sender else None,\n })\n\n if admin is None:\n admin = Persona(\n id=changeset[\"admin_id\"],\n )\n admin._stub = True\n\n group.admin = admin\n\n mc = group.update_members(changeset[\"members\"])\n for m in mc:\n request_list.append({\n \"type\": \"Persona\",\n \"id\": m,\n \"author_id\": update_recipient.id if update_recipient else None,\n \"recipient_id\": update_sender.id if update_sender else None,\n })\n\n for req in request_list:\n request_objects.send(Group.create_from_changeset, message=req)\n\n return group","def write_map(sample_group, sample_dir):\n\n\n map_fname = new_file(\"map.txt\", basedir=sample_dir)\n\n def _write(targets):\n with open(map_fname, 'w') as map_file:\n # print the headers first\n print >> map_file, \"#\"+\"\\t\".join(sample_group[0]._fields)\n\n for _, samples_bycode in itertools.groupby(\n sample_group, operator.attrgetter(\"BarcodeSequence\")):\n # get the first (hopefully only) sample from the samples\n # grouped by ID then barcode. Ignore any other samples\n # under the same ID for the same barcode\n sample = samples_bycode.next()\n bcode = sample.BarcodeSequence\n # uniq-ify to make qiime happy\n sample = list(sample)\n sample[0] += \"_\" + bcode\n print >> map_file, \"\\t\".join(sample)\n\n return {\n \"name\": \"write_map:\"+map_fname,\n \"actions\": [_write],\n \"targets\": [map_fname],\n \"title\": lambda t: t.name+\" Estimated mem=200 time=5 threads=1\"\n }","def test_groups_group_id_state_put(self):\n pass","def get_idp_group_mapping(self, identity_provider_id, mapping_id, **kwargs):\n resource_path = \"/identityProviders/{identityProviderId}/groupMappings/{mappingId}\"\n method = \"GET\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"get_idp_group_mapping got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"identityProviderId\": identity_provider_id,\n \"mappingId\": mapping_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"IdpGroupMapping\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"IdpGroupMapping\")","def test_valid_service_account_registration_multiple_service_accounts(\n app,\n db_session,\n client,\n encoded_jwt_service_accounts_access,\n cloud_manager,\n valid_google_project_patcher,\n valid_service_account_patcher,\n):\n proj_patcher = valid_google_project_patcher\n project = Project(id=1, auth_id=\"some_auth_id\")\n\n bucket = Bucket(id=1)\n\n db_session.add(project)\n db_session.add(bucket)\n db_session.commit()\n\n project_to_bucket = ProjectToBucket(project_id=1, bucket_id=1)\n\n db_session.add(project_to_bucket)\n db_session.commit()\n\n gbag = GoogleBucketAccessGroup(id=1, bucket_id=1, email=\"gbag@gmail.com\")\n\n db_session.add(gbag)\n db_session.commit()\n\n google_project_id = \"project-id\"\n encoded_creds_jwt = encoded_jwt_service_accounts_access[\"jwt\"]\n project_access = [\"some_auth_id\"]\n proj_patcher[\"get_service_account_ids_from_google_members\"].return_value = [\n \"test-{}@test.com\".format(google_project_id),\n \"{}@compute-system.iam.gserviceaccount.com\".format(google_project_id),\n ]\n valid_service_account = {\n \"service_account_email\": \"sa@gmail.com\",\n \"google_project_id\": google_project_id,\n \"project_access\": project_access,\n }\n\n (\n cloud_manager.return_value.__enter__.return_value.get_service_account.return_value\n ) = {\"uniqueId\": \"sa_unique_id\", \"email\": \"sa@gmail.com\"}\n\n (\n cloud_manager.return_value.__enter__.return_value.add_member_to_group.return_value\n ) = {\"email\": \"sa@gmail.com\"}\n\n assert len(db_session.query(UserServiceAccount).all()) == 0\n assert len(db_session.query(ServiceAccountAccessPrivilege).all()) == 0\n assert len(db_session.query(ServiceAccountToGoogleBucketAccessGroup).all()) == 0\n\n response = client.post(\n \"/google/service_accounts\",\n headers={\"Authorization\": \"Bearer \" + encoded_creds_jwt},\n data=json.dumps(valid_service_account),\n content_type=\"application/json\",\n )\n\n assert response.status_code == 200\n\n assert len(db_session.query(UserServiceAccount).all()) == 1\n assert len(db_session.query(ServiceAccountAccessPrivilege).all()) == 1\n assert len(db_session.query(ServiceAccountToGoogleBucketAccessGroup).all()) == 1","def test_creation_mapped_control(self):\n control = factories.ControlFactory()\n # Map original of control to several assessments to get propagated roles\n self.generate_control_mappings(control)\n\n # Existing control should be updated to create new revision with ACL\n self.api.put(control, {\"title\": \"Test Control\"})\n\n program = factories.ProgramFactory()\n factories.RelationshipFactory(source=program, destination=control)\n response = self.api.post(all_models.Audit, [{\n \"audit\": {\n \"title\": \"New Audit\",\n \"program\": {\"id\": program.id},\n \"status\": \"Planned\",\n \"context\": None\n }\n }])\n self.assert200(response)","def service_for_map(self, map_name):\n return getattr(self.map_services[map_name], self.service_name)","def create_tap_service(attrs=None):\n attrs = attrs or {}\n tap_service_attrs = {\n 'id': uuidutils.generate_uuid(),\n 'tenant_id': uuidutils.generate_uuid(),\n 'name': 'test_tap_service' + uuidutils.generate_uuid(),\n 'status': 'ACTIVE',\n }\n tap_service_attrs.update(attrs)\n return copy.deepcopy(tap_service_attrs)","def pre_service_template_create(self, resource_dict):\n pass","def pairing_group_create(curve='MNT224'):\n return PairingGroup(curve)","def create_group(self):\n # TODO: Assuming first server is good - need to make fallback logic\n return self.session.get_any(\"{base}{request_url}\".format(base=self.servers[0],\n request_url=F\"/GroupV2/Create/\"))","def createGroup(self, *group):\n if not self.rank:\n logging.info('Creating atom group {}'.format(group))\n\n if not len(group):\n for idSS in self.pargs['idSS']:\n self.lmp.command('group group{} type {}'.format(idSS, idSS))\n else:\n self.lmp.command('group ' + ('{} ' * len(group)).format(*group))"],"string":"[\n \"def create_api_mapping(self, ApiId: str, DomainName: str, Stage: str, ApiMappingKey: str = None) -> Dict:\\n pass\",\n \"def get_service_mapping():\\r\\n # Get all Service types:\\r\\n all_service_type = requests.get(base_url + 'services/v2/service_types', headers=headers3).json()\\r\\n # Make Dict of service names and ids\\r\\n service_name_to_id = {service_type['attributes']['name']:service_type['id'] for service_type in all_service_type['data']} \\r\\n return service_name_to_id\",\n \"def test_ipam_services_create(self):\\n pass\",\n \"def normalize_idp(idp):\\n if idp is None:\\n return None\\n\\n _idp = idp.to_dict()\\n _idp['enabled'] = idp['is_enabled']\\n _idp['name'] = idp['id']\\n return _idp\",\n \"def test_aws_service_api_keypair_generate_post(self):\\n pass\",\n \"def create_mapping(self):\\n\\n indice = client.IndicesClient(self.es)\\n\\n indice.put_mapping(index=self.es_main_index,\\n doc_type=self.es_main_type,\\n body=self.mapping)\",\n \"def create_participant_group_mapping(\\n self,\\n qualification_name: str,\\n requester_id: str,\\n prolific_project_id: str,\\n prolific_participant_group_name: str,\\n prolific_participant_group_id: str,\\n ) -> None:\\n try:\\n with self.table_access_condition, self._get_connection() as conn:\\n c = conn.cursor()\\n c.execute(\\n \\\"\\\"\\\"\\n INSERT INTO participant_groups(\\n qualification_name,\\n requester_id,\\n prolific_project_id,\\n prolific_participant_group_name,\\n prolific_participant_group_id\\n ) VALUES (?, ?, ?, ?, ?);\\n \\\"\\\"\\\",\\n (\\n qualification_name,\\n requester_id,\\n prolific_project_id,\\n prolific_participant_group_name,\\n prolific_participant_group_id,\\n ),\\n )\\n return None\\n\\n except sqlite3.IntegrityError as e:\\n if is_unique_failure(e):\\n # Ignore attempt to add another mapping for an existing key\\n db_qualification = self.get_qualification_mapping(qualification_name)\\n\\n logger.debug(\\n f\\\"Multiple Prolific mapping creations \\\"\\n f'for qualification \\\"{qualification_name}\\\". '\\n f\\\"Found existing one: {db_qualification}. \\\"\\n )\\n assert (\\n db_qualification is not None\\n ), \\\"Cannot be none given is_unique_failure on insert\\\"\\n\\n db_requester_id = db_qualification[\\\"requester_id\\\"]\\n db_prolific_qualification_name = db_qualification[\\\"prolific_participant_group_name\\\"]\\n\\n if db_requester_id != requester_id:\\n logger.warning(\\n f\\\"Prolific Qualification mapping create for {qualification_name} \\\"\\n f\\\"under requester {requester_id}, already exists under {db_requester_id}.\\\"\\n )\\n\\n if db_prolific_qualification_name != prolific_participant_group_name:\\n logger.warning(\\n f\\\"Prolific Qualification mapping create for {qualification_name} \\\"\\n f\\\"with Prolific name {prolific_participant_group_name}, \\\"\\n f\\\"already exists under {db_prolific_qualification_name}.\\\"\\n )\\n\\n return None\\n else:\\n raise e\",\n \"def _build_ec2_mapping_from_sg(resource_to_analyse, result_dict, session):\\n for instance, security_group in _generate_ec2_instance_and_sg(resource_to_analyse):\\n sg_dict = _check_if_in_list(result_dict, security_group[\\\"GroupId\\\"], \\\"sg_id\\\")\\n if sg_dict is not None:\\n sg_dict[\\\"resources_attached\\\"].append({\\n \\\"resource_id\\\": instance.id,\\n \\\"resource_type\\\": \\\"ec2\\\",\\n \\\"resource_name\\\": \\\"\\\" if _check_if_in_list(instance.tags, \\\"Name\\\", \\\"Key\\\") is None else _check_if_in_list(instance.tags, \\\"Name\\\", \\\"Key\\\").get(\\\"Value\\\", \\\"\\\")\\n })\\n else:\\n result_dict.append({\\n \\\"sg_id\\\": security_group[\\\"GroupId\\\"],\\n \\\"sg_name\\\": security_group[\\\"GroupName\\\"],\\n \\\"resources_attached\\\": [{\\n \\\"resource_id\\\": instance.id,\\n \\\"resource_type\\\": \\\"ec2\\\",\\n \\\"resource_name\\\": \\\"\\\" if _check_if_in_list(instance.tags, \\\"Name\\\", \\\"Key\\\") is None else _check_if_in_list(instance.tags, \\\"Name\\\", \\\"Key\\\").get(\\\"Value\\\", \\\"\\\")\\n }]\\n })\\n return result_dict\",\n \"async def groups_service_handler(service: ServiceCall) -> None:\\n object_id = service.data[ATTR_OBJECT_ID]\\n entity_id = f\\\"{DOMAIN}.{object_id}\\\"\\n group = component.get_entity(entity_id)\\n\\n # new group\\n if service.service == SERVICE_SET and group is None:\\n entity_ids = (\\n service.data.get(ATTR_ENTITIES)\\n or service.data.get(ATTR_ADD_ENTITIES)\\n or None\\n )\\n\\n extra_arg = {\\n attr: service.data[attr]\\n for attr in (ATTR_ICON,)\\n if service.data.get(attr) is not None\\n }\\n\\n await Group.async_create_group(\\n hass,\\n service.data.get(ATTR_NAME, object_id),\\n object_id=object_id,\\n entity_ids=entity_ids,\\n user_defined=False,\\n mode=service.data.get(ATTR_ALL),\\n **extra_arg,\\n )\\n return\\n\\n if group is None:\\n _LOGGER.warning(\\\"%s:Group '%s' doesn't exist!\\\", service.service, object_id)\\n return\\n\\n # update group\\n if service.service == SERVICE_SET:\\n need_update = False\\n\\n if ATTR_ADD_ENTITIES in service.data:\\n delta = service.data[ATTR_ADD_ENTITIES]\\n entity_ids = set(group.tracking) | set(delta)\\n await group.async_update_tracked_entity_ids(entity_ids)\\n\\n if ATTR_REMOVE_ENTITIES in service.data:\\n delta = service.data[ATTR_REMOVE_ENTITIES]\\n entity_ids = set(group.tracking) - set(delta)\\n await group.async_update_tracked_entity_ids(entity_ids)\\n\\n if ATTR_ENTITIES in service.data:\\n entity_ids = service.data[ATTR_ENTITIES]\\n await group.async_update_tracked_entity_ids(entity_ids)\\n\\n if ATTR_NAME in service.data:\\n group.name = service.data[ATTR_NAME]\\n need_update = True\\n\\n if ATTR_ICON in service.data:\\n group.icon = service.data[ATTR_ICON]\\n need_update = True\\n\\n if ATTR_ALL in service.data:\\n group.mode = all if service.data[ATTR_ALL] else any\\n need_update = True\\n\\n if need_update:\\n group.async_write_ha_state()\\n\\n return\\n\\n # remove group\\n if service.service == SERVICE_REMOVE:\\n await component.async_remove_entity(entity_id)\",\n \"def update_pin_group():\\n create_instance(new=False)\",\n \"def create_sg(vpc_id, description, group_name):\\n client = boto3.client('ec2')\\n security_group = str(group_name + \\\"_sg\\\")\\n\\n # get the security groups\\n idle_sg = get_sg()\\n\\n print(idle_sg)\\n print(security_group)\\n\\n # if security group doesnt exist, create it\\n if security_group not in idle_sg:\\n print(\\\"Creating SG\\\")\\n return client.create_security_group(\\n Description=description,\\n GroupName=security_group,\\n VpcId=vpc_id\\n )\\n return get_sg_id(security_group)\",\n \"def create_mapping_group(access_path, block_volumes, client_group, host=None):\\n retval = -1\\n if not isinstance(access_path, int):\\n access_path = AccessPath.get_access_path_id(access_path, host)\\n if not isinstance(client_group, int):\\n client_group = ClientGroup.get_client_group_id(client_group, host)\\n if access_path == -1 or client_group == -1:\\n print \\\"[Error] The access path or client group name/id is invalid.\\\"\\n else:\\n try:\\n retval, block_volumes = _handle_block_volumes(block_volumes, host)\\n if retval != 0:\\n return retval\\n except Exception as e:\\n print \\\"[Error] The block volumes are not valid.\\\"\\n else:\\n cmd = utils.XMS_CLI_HEADER + \\\"mapping-group create --access-path {ap} --block-volumes {bvs} --client-group {cg}\\\".format(ap=access_path, bvs=block_volumes, cg=client_group)\\n print cmd\\n ret = utils.execute_cmd_in_host(cmd, host)\\n if ret[2] != 0:\\n retval = -1\\n print \\\"[Error] Failed to create mapping group. Error message: [{err}]\\\".format(err=ret[1])\\n else:\\n retval = 0\\n return retval\",\n \"def testServiceMapping_NoRegistry(self):\\n mapping = self.DoMappingTest({'/my-service': MyService}, None)\",\n \"def add_tomcat7_idp():\\n pass\",\n \"def create_mapping(project, img):\\n with BMI(_username, _password, project) as bmi:\\n ret = bmi.mount_image(img)\\n if ret[constants.STATUS_CODE_KEY] == 200:\\n click.echo('Success')\\n else:\\n click.echo(ret[constants.MESSAGE_KEY])\",\n \"def _addProteinIdsToGroupMapping(self, proteinIds, groupId):\\n for proteinId in AUX.toList(proteinIds):\\n self._proteinToGroupIds[proteinId].add(groupId)\",\n \"def _build_ec2_mapping_from_resources(resource_to_analyse, result_dict, session):\\n for instance, security_group in _generate_ec2_instance_and_sg(resource_to_analyse):\\n resource_dict = _check_if_in_list(result_dict, instance.id, \\\"resource_id\\\")\\n if resource_dict is not None:\\n resource_dict[\\\"sg_attached\\\"].append({\\n \\\"sg_id\\\": security_group[\\\"GroupId\\\"],\\n \\\"sg_name\\\": security_group[\\\"GroupName\\\"]\\n })\\n else:\\n result_dict.append({\\n \\\"resource_id\\\": instance.id,\\n \\\"resource_type\\\": \\\"ec2\\\",\\n \\\"resource_name\\\": \\\"\\\" if _check_if_in_list(instance.tags, \\\"Name\\\", \\\"Key\\\") is None else _check_if_in_list(instance.tags, \\\"Name\\\", \\\"Key\\\").get(\\\"Value\\\", \\\"\\\"),\\n \\\"sg_attached\\\": [{\\n \\\"sg_id\\\": security_group[\\\"GroupId\\\"],\\n \\\"sg_name\\\": security_group[\\\"GroupName\\\"]\\n }]\\n })\\n return result_dict\",\n \"def test_create_user_identity_mapping(self):\\n pass\",\n \"def post_service_instance_create(self, resource_dict):\\n pass\",\n \"def handle_region(self, region, args):\\n result = [CHECKMARK, str(region), \\\"created security group '{}'\\\".format(GROUP_NAME)]\\n\\n try:\\n # Create the security group\\n response = region.conn.create_security_group(\\n Description='Security group for Alia replicas and clients.',\\n GroupName=GROUP_NAME,\\n )\\n\\n # Get the newly created group id\\n group_id = response[\\\"GroupId\\\"]\\n\\n # Allow all network traffic from within the security group\\n response = region.conn.authorize_security_group_ingress(\\n GroupId = group_id,\\n IpPermissions = [\\n {\\n \\\"IpProtocol\\\": \\\"tcp\\\", \\\"FromPort\\\": 0, \\\"ToPort\\\": 65535,\\n \\\"UserIdGroupPairs\\\": [\\n {\\n \\\"GroupId\\\": group_id,\\n \\\"Description\\\": \\\"allow all traffic from the same group\\\",\\n }\\n ]\\n }\\n ]\\n )\\n\\n # Open Alia-specific ports for access\\n reponse = region.conn.authorize_security_group_ingress(\\n GroupId = group_id,\\n IpPermissions = [\\n {\\n \\\"IpProtocol\\\": \\\"tcp\\\", \\\"FromPort\\\": 22, \\\"ToPort\\\": 22,\\n \\\"IpRanges\\\": [\\n {\\n \\\"CidrIp\\\": \\\"0.0.0.0/0\\\",\\n \\\"Description\\\": \\\"allow remote SSH access\\\"\\n }\\n ]\\n },\\n {\\n \\\"IpProtocol\\\": \\\"tcp\\\", \\\"FromPort\\\": 3264, \\\"ToPort\\\": 3285,\\n \\\"IpRanges\\\": [\\n {\\n \\\"CidrIp\\\": \\\"0.0.0.0/0\\\",\\n \\\"Description\\\": \\\"external Alia service access\\\",\\n }\\n ],\\n \\\"Ipv6Ranges\\\": [\\n {\\n \\\"CidrIpv6\\\": \\\"::/0\\\",\\n \\\"Description\\\": \\\"external Alia service IPv6 access\\\"\\n }\\n ]\\n },\\n {\\n \\\"IpProtocol\\\": \\\"tcp\\\", \\\"FromPort\\\": 5356, \\\"ToPort\\\": 5356,\\n \\\"IpRanges\\\": [\\n {\\n \\\"CidrIp\\\": \\\"0.0.0.0/0\\\",\\n \\\"Description\\\": \\\"research services access\\\"\\n }\\n ]\\n },\\n {\\n \\\"IpProtocol\\\": \\\"tcp\\\", \\\"FromPort\\\": 4157, \\\"ToPort\\\": 4157,\\n \\\"IpRanges\\\": [\\n {\\n \\\"CidrIp\\\": \\\"0.0.0.0/0\\\",\\n \\\"Description\\\": \\\"master services access\\\",\\n }\\n ]\\n },\\n ]\\n )\\n\\n\\n except Exception as e:\\n result[0] = CROSSMARK\\n result[2] = str(e)\\n\\n\\n return result\",\n \"def createFieldMapping(sgidPoints):\\n # Create field mappings\\n sgidFMs = arcpy.FieldMappings()\\n\\n # Perform some field renaming\\n mapPairs = [\\n ('State', 'State'),\\n ('City', 'Inc_Muni'),\\n ('CountyID', 'County'),\\n ('ZipCode', 'Zip_Code'),\\n ('PrefixDir', 'StN_PreDir'),\\n ('StreetName', 'StreetName'),\\n ('StreetType', 'StN_PosTyp'),\\n ('SuffixDir', 'StN_PosDir'),\\n ('AddNum', 'Add_Number'),\\n ('LandmarkName', 'landmkName'),\\n ('Building', 'Building'),\\n ('UnitType', 'Unit'),\\n ('AddSource', 'AddAuth'),\\n ('AddSystem', 'UniqWithin'),\\n ('LoadDate', 'LastUpdate')]\\n\\n for p in mapPairs:\\n print p\\n sgidFMs.addFieldMap(getRenameFieldMap(sgidPoints, p[0], p[1]))\\n\\n return sgidFMs\",\n \"def remap_ids(self, id_map: Dict[int, int]) -> None:\",\n \"def pre_service_instance_create(self, resource_dict):\\n pass\",\n \"def servicebindingmaps(self, servicebindingmap_id, data, tenant_id=None, api_version=\\\"v2.1\\\"):\\n\\n if tenant_id is None and self._parent_class.tenant_id:\\n # Pull tenant_id from parent namespace cache.\\n tenant_id = self._parent_class.tenant_id\\n elif not tenant_id:\\n # No value for tenant_id.\\n raise TypeError(\\\"tenant_id is required but not set or cached.\\\")\\n cur_ctlr = self._parent_class.controller\\n\\n url = str(cur_ctlr) + \\\"/{}/api/tenants/{}/servicebindingmaps/{}\\\".format(api_version,\\n tenant_id,\\n servicebindingmap_id)\\n\\n api_logger.debug(\\\"URL = %s\\\", url)\\n return self._parent_class.rest_call(url, \\\"put\\\", data=data)\",\n \"def post_security_group_create(self, resource_dict):\\n pass\",\n \"def remap_ids(self, id_map: Dict[int, int]) -> None:\\n super().remap_ids(id_map)\\n self.puppet = id_map.get(self.puppet, 0)\",\n \"def _build_rds_mapping_from_sg(resource_to_analyse, result_dict, session):\\n for db_instance, security_group, sg_name in _generate_rds_instances_and_sg(resource_to_analyse, session):\\n resource_dict = _check_if_in_list(result_dict, security_group[\\\"VpcSecurityGroupId\\\"], \\\"sg_id\\\")\\n if resource_dict is not None:\\n resource_dict[\\\"resources_attached\\\"].append({\\n \\\"resource_id\\\": db_instance[\\\"DBInstanceIdentifier\\\"],\\n \\\"resource_type\\\": \\\"rds\\\"\\n })\\n else:\\n result_dict.append({\\n \\\"sg_id\\\": security_group[\\\"VpcSecurityGroupId\\\"],\\n \\\"sg_name\\\": sg_name,\\n \\\"resources_attached\\\": [{\\n \\\"resource_id\\\": db_instance[\\\"DBInstanceIdentifier\\\"],\\n \\\"resource_type\\\": \\\"rds\\\"\\n }]\\n })\\n return result_dict\",\n \"def __init__(__self__, *,\\n arn: Optional[pulumi.Input[str]] = None,\\n auto_scaling_configuration_arn: Optional[pulumi.Input[str]] = None,\\n encryption_configuration: Optional[pulumi.Input['ServiceEncryptionConfigurationArgs']] = None,\\n health_check_configuration: Optional[pulumi.Input['ServiceHealthCheckConfigurationArgs']] = None,\\n instance_configuration: Optional[pulumi.Input['ServiceInstanceConfigurationArgs']] = None,\\n network_configuration: Optional[pulumi.Input['ServiceNetworkConfigurationArgs']] = None,\\n observability_configuration: Optional[pulumi.Input['ServiceObservabilityConfigurationArgs']] = None,\\n service_id: Optional[pulumi.Input[str]] = None,\\n service_name: Optional[pulumi.Input[str]] = None,\\n service_url: Optional[pulumi.Input[str]] = None,\\n source_configuration: Optional[pulumi.Input['ServiceSourceConfigurationArgs']] = None,\\n status: Optional[pulumi.Input[str]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,\\n tags_all: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\\n if arn is not None:\\n pulumi.set(__self__, \\\"arn\\\", arn)\\n if auto_scaling_configuration_arn is not None:\\n pulumi.set(__self__, \\\"auto_scaling_configuration_arn\\\", auto_scaling_configuration_arn)\\n if encryption_configuration is not None:\\n pulumi.set(__self__, \\\"encryption_configuration\\\", encryption_configuration)\\n if health_check_configuration is not None:\\n pulumi.set(__self__, \\\"health_check_configuration\\\", health_check_configuration)\\n if instance_configuration is not None:\\n pulumi.set(__self__, \\\"instance_configuration\\\", instance_configuration)\\n if network_configuration is not None:\\n pulumi.set(__self__, \\\"network_configuration\\\", network_configuration)\\n if observability_configuration is not None:\\n pulumi.set(__self__, \\\"observability_configuration\\\", observability_configuration)\\n if service_id is not None:\\n pulumi.set(__self__, \\\"service_id\\\", service_id)\\n if service_name is not None:\\n pulumi.set(__self__, \\\"service_name\\\", service_name)\\n if service_url is not None:\\n pulumi.set(__self__, \\\"service_url\\\", service_url)\\n if source_configuration is not None:\\n pulumi.set(__self__, \\\"source_configuration\\\", source_configuration)\\n if status is not None:\\n pulumi.set(__self__, \\\"status\\\", status)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\\n if tags_all is not None:\\n pulumi.set(__self__, \\\"tags_all\\\", tags_all)\",\n \"def pre_security_group_create(self, resource_dict):\\n pass\",\n \"def _build_elbv2_mapping_from_sg(resource_to_analyse, result_dict, session):\\n for elb_instance, security_group_id, security_group_name in _generate_elb_instances_and_sg(resource_to_analyse, session):\\n resource_dict = _check_if_in_list(result_dict, security_group_id, \\\"sg_id\\\")\\n if resource_dict is not None:\\n resource_dict[\\\"resources_attached\\\"].append({\\n \\\"resource_id\\\": elb_instance[\\\"LoadBalancerName\\\"],\\n \\\"resource_type\\\": \\\"elb\\\"\\n })\\n else:\\n result_dict.append({\\n \\\"sg_id\\\": security_group_id,\\n \\\"sg_name\\\": security_group_name,\\n \\\"resources_attached\\\": [{\\n \\\"resource_id\\\": elb_instance[\\\"LoadBalancerName\\\"],\\n \\\"resource_type\\\": \\\"elb\\\"\\n }]\\n })\\n return result_dict\",\n \"def map_service_info(port, nmap_store):\\n service = port.find(\\\"service\\\")\\n nmap_store[\\\"service_name\\\"] = service.get(\\\"name\\\")\\n nmap_store[\\\"service_method\\\"] = service.get(\\\"method\\\")\\n nmap_store[\\\"service_conf\\\"] = service.get(\\\"conf\\\")\",\n \"def testDomainMappingCreateAlreadyExistsPrompts(self):\\n\\n self.operations.CreateDomainMapping.side_effect = [\\n exceptions.DomainMappingAlreadyExistsError(), self.domain_mapping\\n ]\\n\\n with mock.patch(\\n 'googlecloudsdk.api_lib.run.global_methods.GetServerlessClientInstance',\\n return_value=self.mock_serverless_client):\\n verified_domains = [\\n self.mock_serverless_client.MESSAGES_MODULE.AuthorizedDomain(\\n id='www.example.com')\\n ]\\n with mock.patch(\\n 'googlecloudsdk.api_lib.run.global_methods.ListVerifiedDomains',\\n return_value=verified_domains):\\n self.WriteInput('y\\\\n')\\n self.Run('run domain-mappings create '\\n '--service myapp --domain www.example.com')\\n self.AssertOutputContains(\\n \\\"\\\"\\\"NAME RECORD TYPE CONTENTS\\n myapp A 216.239.32.21\\\"\\\"\\\",\\n normalize_space=True)\",\n \"def generate_public_ID(self, mapping):\\n raise exception.NotImplemented() # pragma: no cover\",\n \"def createMappingSetMapping(self,mappingSetId:str=None,mapping:dict=None,verbose:bool=False)->dict:\\n if mappingSetId is None:\\n raise ValueError(\\\"Require a mapping ID\\\")\\n if mapping is None or type(mapping)!=dict:\\n raise Exception(\\\"Require a dictionary as mapping\\\")\\n path = f\\\"/mappingSets/{mappingSetId}/mappings\\\"\\n res = self.connector.postData(self.endpoint+path,data=mapping,verbose=verbose)\\n return res\",\n \"def __init__(__self__, *,\\n region: str,\\n service_id: str,\\n tag: str):\\n pulumi.set(__self__, \\\"region\\\", region)\\n pulumi.set(__self__, \\\"service_id\\\", service_id)\\n pulumi.set(__self__, \\\"tag\\\", tag)\",\n \"def __init__(__self__, *,\\n application_name: pulumi.Input[str],\\n cluster_name: pulumi.Input[str],\\n resource_group_name: pulumi.Input[str],\\n service_kind: pulumi.Input[Union[str, 'ServiceKind']],\\n correlation_scheme: Optional[pulumi.Input[Sequence[pulumi.Input['ServiceCorrelationDescriptionArgs']]]] = None,\\n default_move_cost: Optional[pulumi.Input[Union[str, 'MoveCost']]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n partition_description: Optional[pulumi.Input[Union['NamedPartitionSchemeDescriptionArgs', 'SingletonPartitionSchemeDescriptionArgs', 'UniformInt64RangePartitionSchemeDescriptionArgs']]] = None,\\n placement_constraints: Optional[pulumi.Input[str]] = None,\\n service_dns_name: Optional[pulumi.Input[str]] = None,\\n service_load_metrics: Optional[pulumi.Input[Sequence[pulumi.Input['ServiceLoadMetricDescriptionArgs']]]] = None,\\n service_name: Optional[pulumi.Input[str]] = None,\\n service_package_activation_mode: Optional[pulumi.Input[Union[str, 'ArmServicePackageActivationMode']]] = None,\\n service_placement_policies: Optional[pulumi.Input[Sequence[pulumi.Input['ServicePlacementPolicyDescriptionArgs']]]] = None,\\n service_type_name: Optional[pulumi.Input[str]] = None,\\n tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None):\\n pulumi.set(__self__, \\\"application_name\\\", application_name)\\n pulumi.set(__self__, \\\"cluster_name\\\", cluster_name)\\n pulumi.set(__self__, \\\"resource_group_name\\\", resource_group_name)\\n pulumi.set(__self__, \\\"service_kind\\\", service_kind)\\n if correlation_scheme is not None:\\n pulumi.set(__self__, \\\"correlation_scheme\\\", correlation_scheme)\\n if default_move_cost is not None:\\n pulumi.set(__self__, \\\"default_move_cost\\\", default_move_cost)\\n if location is not None:\\n pulumi.set(__self__, \\\"location\\\", location)\\n if partition_description is not None:\\n pulumi.set(__self__, \\\"partition_description\\\", partition_description)\\n if placement_constraints is not None:\\n pulumi.set(__self__, \\\"placement_constraints\\\", placement_constraints)\\n if service_dns_name is not None:\\n pulumi.set(__self__, \\\"service_dns_name\\\", service_dns_name)\\n if service_load_metrics is not None:\\n pulumi.set(__self__, \\\"service_load_metrics\\\", service_load_metrics)\\n if service_name is not None:\\n pulumi.set(__self__, \\\"service_name\\\", service_name)\\n if service_package_activation_mode is not None:\\n pulumi.set(__self__, \\\"service_package_activation_mode\\\", service_package_activation_mode)\\n if service_placement_policies is not None:\\n pulumi.set(__self__, \\\"service_placement_policies\\\", service_placement_policies)\\n if service_type_name is not None:\\n pulumi.set(__self__, \\\"service_type_name\\\", service_type_name)\\n if tags is not None:\\n pulumi.set(__self__, \\\"tags\\\", tags)\",\n \"def create_mapset(self, mapset, dbase=None, location=None):\\n module = 'g.c.mapset'\\n gs.run_command(module, mapset=mapset, dbase=dbase, location=location)\",\n \"def creategroup(body):\\n group = body.get(\\\"groupname\\\", None)\\n pps = body.get(\\\"pilotpoints\\\", None)\\n print('lol',group, pps)\\n print(type(pps))\\n\\n # Does the person exist already?\\n if group not in group_dict and group is not None:\\n group_dict[group] = {\\n \\\"groupname\\\": group,\\n \\\"pilotpoints\\\": pps,\\n }\\n return group_dict[group], 201\\n\\n # Otherwise, they exist, that's an error\\n else:\\n abort(\\n 406,\\n \\\"Person with last name {group} already exists\\\".format(group=group),\\n )\",\n \"def _make_group(self, _rk, _group_hint):\\n\\n if isinstance(_group_hint, dict):\\n # _group_hint is a single key/value pair\\n g = _group_hint[list(_group_hint)[0]]\\n\\n r_type = g.get(\\\"type\\\", \\\"none\\\")\\n if r_type != \\\"OS::Nova::ServerGroup\\\":\\n return \\\"support only ServerGroup resource\\\"\\n\\n properties = g.get(\\\"properties\\\", {})\\n if len(properties) == 0:\\n return \\\"no properties\\\"\\n\\n group_name = properties.get(\\\"name\\\", None)\\n if group_name is None:\\n return \\\"no group name\\\"\\n group_name = group_name.strip()\\n\\n policies = properties.get(\\\"policies\\\", [])\\n if len(policies) == 0:\\n return \\\"no policy of the group\\\"\\n\\n if len(policies) > 1:\\n return \\\"multiple policies\\\"\\n\\n # TODO: exclude soft-affinity and soft-anti-affinity?\\n\\n if group_name in self.groups.keys():\\n group = self.groups[group_name]\\n else:\\n group = Group(group_name)\\n\\n policy = policies[0].strip()\\n if policy == \\\"anti-affinity\\\":\\n group_type = \\\"diversity\\\"\\n else:\\n group_type = policy\\n\\n group.group_type = group_type\\n group.factory = \\\"server-group\\\"\\n group.level = \\\"host\\\"\\n\\n self.groups[group_name] = group\\n else:\\n # group hint is uuid string.\\n rg = self.resource.get_group_by_uuid(_group_hint)\\n if rg is None:\\n return \\\"unknown group found while making group\\\"\\n\\n # TODO: exclude soft-affinity and soft-anti-affinity?\\n\\n if rg.name in self.groups.keys():\\n group = self.groups[rg.name]\\n else:\\n group = Group(rg.name)\\n\\n group.group_type = rg.group_type\\n group.factory = rg.factory\\n group.level = \\\"host\\\"\\n\\n self.groups[rg.name] = group\\n\\n if group is not None:\\n group.server_list.append(self.app_name + \\\":\\\" + _rk)\\n\\n return \\\"ok\\\"\",\n \"def create(person_group_id, name=None, user_data=None):\\n name = person_group_id if name is None else name\\n url = 'persongroups/{}'.format(person_group_id)\\n json = {\\n 'name': name,\\n 'userData': user_data,\\n }\\n\\n return util.request('PUT', url, json=json)\",\n \"def pre_network_ipam_create(self, resource_dict):\\n pass\",\n \"def create_mapset(self, mapset, dbase=None, location=None):\\n module = 'g.mapset'\\n gs.run_command(module, flags='c', mapset=mapset, dbase=dbase, location=location)\",\n \"def create(self, mapItem: MapItem) -> int:\\n pass\",\n \"def create_sec_group(ec2, sec_group_name):\\n sec = ec2.create_security_group(sec_group_name, 'Jvivian Boto SecGroup')\\n port = 22\\n sec.authorize('tcp', port, port, '0.0.0.0/0')\",\n \"def _build_rds_mapping_from_resources(resource_to_analyse, result_dict, session):\\n for db_instance, security_group, sg_name in _generate_rds_instances_and_sg(resource_to_analyse, session):\\n resource_dict = _check_if_in_list(result_dict, db_instance[\\\"DBInstanceIdentifier\\\"], \\\"resource_id\\\")\\n if resource_dict is not None:\\n resource_dict[\\\"sg_attached\\\"].append({\\n \\\"sg_id\\\": security_group[\\\"VpcSecurityGroupId\\\"],\\n \\\"sg_name\\\": sg_name\\n })\\n else:\\n result_dict.append({\\n \\\"resource_id\\\": db_instance[\\\"DBInstanceIdentifier\\\"],\\n \\\"resource_type\\\": \\\"rds\\\",\\n \\\"sg_attached\\\": [{\\n \\\"sg_id\\\": security_group[\\\"VpcSecurityGroupId\\\"],\\n \\\"sg_name\\\": sg_name\\n }]\\n })\\n return result_dict\",\n \"def makeMapping(globalMap):\\n \\n from memops.xml.Implementation import bool2str, str2bool\\n\\n # Set up top level dictionaries\\n loadMaps = globalMap.get('loadMaps')\\n mapsByGuid = globalMap.get('mapsByGuid')\\n\\n abstractTypes = globalMap.get('ACCO').get('abstractTypes')\\n exolinks = globalMap.get('ACCO').get('exolinks')\\n\\n # Class AccessControlStore\\n currentMap = {}\\n abstractTypes['AccessControlStore'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-09-04-17:18:10_00001'] = currentMap\\n loadMaps['ACCO.AccessControlStore'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessControlStore'\\n currentMap['type'] = 'class'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:18:10_00001'\\n currentMap['eType'] = 'cplx'\\n currentMap['fromParent'] = 'accessControlStores'\\n currentMap['isTop'] = True\\n currentMap['objkey'] = 'name'\\n currentMap['class'] = memops.api.AccessControl.AccessControlStore\\n contentMap = {}\\n currentMap['content'] = contentMap\\n\\n # Attribute AccessControlStore.applicationData\\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\\n\\n # Attribute AccessControlStore.createdBy\\n contentMap['createdBy'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:00:59_00002__www.ccpn.ac.uk_Fogh_2007-10-03-14:53:27_00001__www.ccpn.ac.uk_Fogh_2006-09-14-16:28:57_00002')\\n\\n # Attribute AccessControlStore.guid\\n contentMap['guid'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:26_00002')\\n\\n # Attribute AccessControlStore.isModifiable\\n contentMap['isModifiable'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-17-14:16:26_00010__www.ccpn.ac.uk_Fogh_2007-10-03-14:53:27_00001__www.ccpn.ac.uk_Fogh_2006-09-14-16:28:57_00002')\\n\\n # Attribute AccessControlStore.lastUnlockedBy\\n contentMap['lastUnlockedBy'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:00:59_00003__www.ccpn.ac.uk_Fogh_2007-10-03-14:53:27_00001__www.ccpn.ac.uk_Fogh_2006-09-14-16:28:57_00002')\\n\\n # Attribute AccessControlStore.name\\n currentMap = {}\\n contentMap['name'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00006'] = currentMap\\n loadMaps['ACCO.AccessControlStore.name'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessControlStore.name'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00006'\\n currentMap['name'] = 'name'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['eType'] = 'cplx'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033')\\n\\n # Role AccessControlStore.access\\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\\n\\n # Role AccessControlStore.accessObjects\\n currentMap = {}\\n contentMap['accessObjects'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00013'] = currentMap\\n loadMaps['ACCO.AccessControlStore.accessObjects'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessControlStore.accessObjects'\\n currentMap['type'] = 'child'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00013'\\n currentMap['name'] = 'accessObjects'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['eType'] = 'cplx'\\n currentMap['implSkip'] = True\\n currentMap['content'] = globalMap.get('ACCO').get('abstractTypes')\\n\\n # Role AccessControlStore.userGroups\\n currentMap = {}\\n contentMap['userGroups'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00003'] = currentMap\\n loadMaps['ACCO.AccessControlStore.userGroups'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessControlStore.userGroups'\\n currentMap['type'] = 'child'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00003'\\n currentMap['name'] = 'userGroups'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['eType'] = 'cplx'\\n currentMap['implSkip'] = True\\n currentMap['content'] = globalMap.get('ACCO').get('abstractTypes')\\n\\n # Role AccessControlStore.users\\n currentMap = {}\\n contentMap['users'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00001'] = currentMap\\n loadMaps['ACCO.AccessControlStore.users'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessControlStore.users'\\n currentMap['type'] = 'child'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:21:38_00001'\\n currentMap['name'] = 'users'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['eType'] = 'cplx'\\n currentMap['implSkip'] = True\\n currentMap['content'] = globalMap.get('ACCO').get('abstractTypes')\\n # End of AccessControlStore\\n\\n currentMap = abstractTypes.get('AccessControlStore')\\n aList = ['createdBy', 'guid', 'isModifiable', 'lastUnlockedBy']\\n currentMap['headerAttrs'] = aList\\n aList = ['name']\\n currentMap['simpleAttrs'] = aList\\n aList = ['users', 'userGroups', 'accessObjects', 'access', 'applicationData']\\n currentMap['cplxAttrs'] = aList\\n aList = ['accessObjects', 'userGroups', 'users']\\n currentMap['children'] = aList\\n\\n # Class AccessObject\\n currentMap = {}\\n abstractTypes['AccessObject'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00014'] = currentMap\\n loadMaps['ACCO.AccessObject'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessObject'\\n currentMap['type'] = 'class'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00014'\\n currentMap['eType'] = 'cplx'\\n currentMap['fromParent'] = 'accessObjects'\\n currentMap['objkey'] = 'name'\\n currentMap['class'] = memops.api.AccessControl.AccessObject\\n contentMap = {}\\n currentMap['content'] = contentMap\\n\\n # Attribute AccessObject.applicationData\\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\\n\\n # Attribute AccessObject.description\\n currentMap = {}\\n contentMap['description'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00005'] = currentMap\\n loadMaps['ACCO.AccessObject.description'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessObject.description'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00005'\\n currentMap['name'] = 'description'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 0\\n currentMap['eType'] = 'cplx'\\n currentMap['proc'] = 'direct'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00035')\\n\\n # Attribute AccessObject.name\\n currentMap = {}\\n contentMap['name'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00004'] = currentMap\\n loadMaps['ACCO.AccessObject.name'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessObject.name'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00004'\\n currentMap['name'] = 'name'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['eType'] = 'cplx'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033')\\n\\n # Role AccessObject.access\\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\\n\\n # Role AccessObject.permissions\\n currentMap = {}\\n contentMap['permissions'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00001'] = currentMap\\n loadMaps['ACCO.AccessObject.permissions'] = currentMap\\n currentMap['tag'] = 'ACCO.AccessObject.permissions'\\n currentMap['type'] = 'child'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:27_00001'\\n currentMap['name'] = 'permissions'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['eType'] = 'cplx'\\n currentMap['content'] = globalMap.get('ACCO').get('abstractTypes')\\n # End of AccessObject\\n\\n currentMap = abstractTypes.get('AccessObject')\\n aList = ['description', 'name']\\n currentMap['simpleAttrs'] = aList\\n aList = ['permissions', 'access', 'applicationData']\\n currentMap['cplxAttrs'] = aList\\n aList = ['permissions']\\n currentMap['children'] = aList\\n\\n # Class Permission\\n currentMap = {}\\n abstractTypes['Permission'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00018'] = currentMap\\n loadMaps['ACCO.Permission'] = currentMap\\n currentMap['tag'] = 'ACCO.Permission'\\n currentMap['type'] = 'class'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00018'\\n currentMap['eType'] = 'cplx'\\n currentMap['fromParent'] = 'permissions'\\n currentMap['class'] = memops.api.AccessControl.Permission\\n contentMap = {}\\n currentMap['content'] = contentMap\\n\\n # Attribute Permission.applicationData\\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\\n\\n # Attribute Permission.opType\\n currentMap = {}\\n contentMap['opType'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00021'] = currentMap\\n loadMaps['ACCO.Permission.opType'] = currentMap\\n currentMap['tag'] = 'ACCO.Permission.opType'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00021'\\n currentMap['name'] = 'opType'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['default'] = 'any'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037')\\n\\n # Attribute Permission.permission\\n currentMap = {}\\n contentMap['permission'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00023'] = currentMap\\n loadMaps['ACCO.Permission.permission'] = currentMap\\n currentMap['tag'] = 'ACCO.Permission.permission'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00023'\\n currentMap['name'] = 'permission'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['default'] = True\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00028')\\n\\n # Attribute Permission.permissionClass\\n currentMap = {}\\n contentMap['permissionClass'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00020'] = currentMap\\n loadMaps['ACCO.Permission.permissionClass'] = currentMap\\n currentMap['tag'] = 'ACCO.Permission.permissionClass'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00020'\\n currentMap['name'] = 'permissionClass'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['default'] = 'any'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037')\\n\\n # Attribute Permission.roleName\\n currentMap = {}\\n contentMap['roleName'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00022'] = currentMap\\n loadMaps['ACCO.Permission.roleName'] = currentMap\\n currentMap['tag'] = 'ACCO.Permission.roleName'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00022'\\n currentMap['name'] = 'roleName'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['default'] = 'any'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037')\\n\\n # Role Permission.access\\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\\n\\n # Role Permission.userGroup\\n currentMap = {}\\n contentMap['userGroup'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00016'] = currentMap\\n loadMaps['ACCO.Permission.userGroup'] = currentMap\\n currentMap['tag'] = 'ACCO.Permission.userGroup'\\n currentMap['type'] = 'link'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00016'\\n currentMap['name'] = 'userGroup'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['copyOverride'] = True\\n # End of Permission\\n\\n currentMap = abstractTypes.get('Permission')\\n aList = ['opType', 'permission', 'permissionClass', 'roleName']\\n currentMap['headerAttrs'] = aList\\n aList = ['userGroup']\\n currentMap['optLinks'] = aList\\n aList = ['access', 'applicationData']\\n currentMap['cplxAttrs'] = aList\\n\\n # Class User\\n currentMap = {}\\n abstractTypes['User'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00017'] = currentMap\\n loadMaps['ACCO.User'] = currentMap\\n currentMap['tag'] = 'ACCO.User'\\n currentMap['type'] = 'class'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00017'\\n currentMap['eType'] = 'cplx'\\n currentMap['fromParent'] = 'users'\\n currentMap['objkey'] = 'name'\\n currentMap['class'] = memops.api.AccessControl.User\\n contentMap = {}\\n currentMap['content'] = contentMap\\n\\n # Attribute User.applicationData\\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\\n\\n # Attribute User.isSuperuser\\n currentMap = {}\\n contentMap['isSuperuser'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2010-05-06-13:30:17_00060'] = currentMap\\n loadMaps['ACCO.User.isSuperuser'] = currentMap\\n currentMap['tag'] = 'ACCO.User.isSuperuser'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2010-05-06-13:30:17_00060'\\n currentMap['name'] = 'isSuperuser'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['default'] = False\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00028')\\n\\n # Attribute User.name\\n currentMap = {}\\n contentMap['name'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00019'] = currentMap\\n loadMaps['ACCO.User.name'] = currentMap\\n currentMap['tag'] = 'ACCO.User.name'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00019'\\n currentMap['name'] = 'name'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['eType'] = 'cplx'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033')\\n\\n # Attribute User.passwordHashed\\n currentMap = {}\\n contentMap['passwordHashed'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2009-08-19-17:31:11_00005'] = currentMap\\n loadMaps['ACCO.User.passwordHashed'] = currentMap\\n currentMap['tag'] = 'ACCO.User.passwordHashed'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2009-08-19-17:31:11_00005'\\n currentMap['name'] = 'passwordHashed'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 0\\n currentMap['eType'] = 'cplx'\\n currentMap['proc'] = 'direct'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00035')\\n\\n # Role User.access\\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\\n\\n # Role User.ledGroups\\n currentMap = {}\\n contentMap['ledGroups'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00014'] = currentMap\\n loadMaps['ACCO.User.ledGroups'] = currentMap\\n currentMap['tag'] = 'ACCO.User.ledGroups'\\n currentMap['type'] = 'link'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00014'\\n currentMap['name'] = 'ledGroups'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['copyOverride'] = True\\n\\n # Role User.userGroups\\n currentMap = {}\\n contentMap['userGroups'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00012'] = currentMap\\n loadMaps['ACCO.User.userGroups'] = currentMap\\n currentMap['tag'] = 'ACCO.User.userGroups'\\n currentMap['type'] = 'link'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00012'\\n currentMap['name'] = 'userGroups'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['copyOverride'] = True\\n # End of User\\n\\n currentMap = abstractTypes.get('User')\\n aList = ['isSuperuser']\\n currentMap['headerAttrs'] = aList\\n aList = ['name', 'passwordHashed', 'ledGroups', 'userGroups']\\n currentMap['simpleAttrs'] = aList\\n aList = ['access', 'applicationData']\\n currentMap['cplxAttrs'] = aList\\n\\n # Class UserGroup\\n currentMap = {}\\n abstractTypes['UserGroup'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00016'] = currentMap\\n loadMaps['ACCO.UserGroup'] = currentMap\\n currentMap['tag'] = 'ACCO.UserGroup'\\n currentMap['type'] = 'class'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00016'\\n currentMap['eType'] = 'cplx'\\n currentMap['fromParent'] = 'userGroups'\\n currentMap['objkey'] = 'name'\\n currentMap['class'] = memops.api.AccessControl.UserGroup\\n contentMap = {}\\n currentMap['content'] = contentMap\\n\\n # Attribute UserGroup.applicationData\\n contentMap['applicationData'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-09-14-18:48:27_00007')\\n\\n # Attribute UserGroup.name\\n currentMap = {}\\n contentMap['name'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00018'] = currentMap\\n loadMaps['ACCO.UserGroup.name'] = currentMap\\n currentMap['tag'] = 'ACCO.UserGroup.name'\\n currentMap['type'] = 'attr'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00018'\\n currentMap['name'] = 'name'\\n currentMap['hicard'] = 1\\n currentMap['locard'] = 1\\n currentMap['eType'] = 'cplx'\\n currentMap['data'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033')\\n\\n # Role UserGroup.access\\n contentMap['access'] = mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-12-31-09:03:01_00014')\\n\\n # Role UserGroup.leaders\\n currentMap = {}\\n contentMap['leaders'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00015'] = currentMap\\n loadMaps['ACCO.UserGroup.leaders'] = currentMap\\n currentMap['tag'] = 'ACCO.UserGroup.leaders'\\n currentMap['type'] = 'link'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00015'\\n currentMap['name'] = 'leaders'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['copyOverride'] = True\\n\\n # Role UserGroup.members\\n currentMap = {}\\n contentMap['members'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00013'] = currentMap\\n loadMaps['ACCO.UserGroup.members'] = currentMap\\n currentMap['tag'] = 'ACCO.UserGroup.members'\\n currentMap['type'] = 'link'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00013'\\n currentMap['name'] = 'members'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['copyOverride'] = False\\n\\n # Role UserGroup.permissions\\n currentMap = {}\\n contentMap['permissions'] = currentMap\\n mapsByGuid['www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00017'] = currentMap\\n loadMaps['ACCO.UserGroup.permissions'] = currentMap\\n currentMap['tag'] = 'ACCO.UserGroup.permissions'\\n currentMap['type'] = 'link'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-17-14:16:23_00017'\\n currentMap['name'] = 'permissions'\\n currentMap['hicard'] = -1\\n currentMap['locard'] = 0\\n currentMap['copyOverride'] = False\\n # End of UserGroup\\n\\n currentMap = abstractTypes.get('UserGroup')\\n aList = ['name', 'leaders', 'members', 'permissions']\\n currentMap['simpleAttrs'] = aList\\n aList = ['access', 'applicationData']\\n currentMap['cplxAttrs'] = aList\\n\\n # Out-of-package link to AccessControlStore\\n currentMap = {}\\n exolinks['AccessControlStore'] = currentMap\\n loadMaps['ACCO.exo-AccessControlStore'] = currentMap\\n currentMap['tag'] = 'ACCO.exo-AccessControlStore'\\n currentMap['type'] = 'exo'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-09-04-17:18:10_00001'\\n currentMap['name'] = 'AccessControlStore'\\n currentMap['eType'] = 'cplx'\\n currentMap['class'] = memops.api.AccessControl.AccessControlStore\\n aList = list()\\n currentMap['keyMaps'] = aList\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\\n\\n # Out-of-package link to AccessObject\\n currentMap = {}\\n exolinks['AccessObject'] = currentMap\\n loadMaps['ACCO.exo-AccessObject'] = currentMap\\n currentMap['tag'] = 'ACCO.exo-AccessObject'\\n currentMap['type'] = 'exo'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00014'\\n currentMap['name'] = 'AccessObject'\\n currentMap['eType'] = 'cplx'\\n currentMap['class'] = memops.api.AccessControl.AccessObject\\n aList = list()\\n currentMap['keyMaps'] = aList\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033'))\\n\\n # Out-of-package link to Permission\\n currentMap = {}\\n exolinks['Permission'] = currentMap\\n loadMaps['ACCO.exo-Permission'] = currentMap\\n currentMap['tag'] = 'ACCO.exo-Permission'\\n currentMap['type'] = 'exo'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00018'\\n currentMap['name'] = 'Permission'\\n currentMap['eType'] = 'cplx'\\n currentMap['class'] = memops.api.AccessControl.Permission\\n aList = list()\\n currentMap['keyMaps'] = aList\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033'))\\n aList.append(globalMap.get('ACCO').get('exolinks'))\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037'))\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037'))\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00037'))\\n\\n # Out-of-package link to User\\n currentMap = {}\\n exolinks['User'] = currentMap\\n loadMaps['ACCO.exo-User'] = currentMap\\n currentMap['tag'] = 'ACCO.exo-User'\\n currentMap['type'] = 'exo'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00017'\\n currentMap['name'] = 'User'\\n currentMap['eType'] = 'cplx'\\n currentMap['class'] = memops.api.AccessControl.User\\n aList = list()\\n currentMap['keyMaps'] = aList\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033'))\\n\\n # Out-of-package link to UserGroup\\n currentMap = {}\\n exolinks['UserGroup'] = currentMap\\n loadMaps['ACCO.exo-UserGroup'] = currentMap\\n currentMap['tag'] = 'ACCO.exo-UserGroup'\\n currentMap['type'] = 'exo'\\n currentMap['guid'] = 'www.ccpn.ac.uk_Fogh_2006-08-16-14:22:54_00016'\\n currentMap['name'] = 'UserGroup'\\n currentMap['eType'] = 'cplx'\\n currentMap['class'] = memops.api.AccessControl.UserGroup\\n aList = list()\\n currentMap['keyMaps'] = aList\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2008-06-30-16:30:50_00001'))\\n aList.append(mapsByGuid.get('www.ccpn.ac.uk_Fogh_2006-08-16-14:22:53_00033'))\",\n \"def generate_object(self, **kwargs):\\n from ranger_performance_tool import perf_globals\\n service_type_mapping = perf_globals.CONFIG_READER.get_config_value(\\\"secondary\\\", \\\"service_type_mapping\\\")\\n if \\\"id\\\" not in kwargs:\\n kwargs[\\\"id\\\"] = self.random_generator.generate_int()\\n if \\\"name\\\" not in kwargs:\\n kwargs[\\\"name\\\"] = self.random_generator.generate_string()\\n if \\\"service\\\" not in kwargs:\\n enabled_service = random.choice(perf_globals.CONFIG_READER.get_config_value(\\\"secondary\\\", \\\"enabled_services\\\"))\\n service_type = service_type_mapping[enabled_service]\\n kwargs[\\\"service\\\"] = enabled_service\\n kwargs[\\\"serviceType\\\"] = service_type\\n policy_object = RangerPolicy()\\n for key, value in kwargs.items():\\n if key not in dir(policy_object):\\n raise Exception(\\\"Invalid key: \\\" + key)\\n policy_object[key] = value\\n service_type = policy_object.serviceType\\n service_store = perf_globals.OBJECT_STORE.service_store[service_type]\\n policy_object.resources = service_store.generate_resources()\\n return policy_object\",\n \"def role_create(ctx, name, service):\\n # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/iam.html#IAM.Client.create_role\\n service_code = SERVICE.get(service, None)\\n if service_code:\\n res = IAM.client().create_role(\\n RoleName=name,\\n AssumeRolePolicyDocument=service_policy(service_code),\\n )\\n click.echo(J(res))\",\n \"def execute(self, pool, vthunder):\\n\\n args = {'service_group': self.meta(pool, 'service_group', {})}\\n try:\\n conf_templates = self.readConf('SERVICE_GROUP','templates').strip('\\\"')\\n service_group_temp = {}\\n service_group_temp['template-server'] = conf_templates\\n except:\\n service_group_temp = None\\n\\n try:\\n c = self.client_factory(vthunder)\\n lb_method=openstack_mappings.service_group_lb_method(c,pool.lb_algorithm)\\n out = c.slb.service_group.create(pool.id, pool.protocol, lb_method,\\n service_group_temp, axapi_args=args)\\n LOG.info(\\\"Pool created successfully.\\\")\\n except Exception as e:\\n print(str(e))\\n LOG.info(\\\"Error occurred\\\")\",\n \"def create_project_apikey(self\\n ,project_id\\n ,description='pyatlas generated project apikey'\\n ,roles='PROJECT_OWNER'):\\n print('pyatlas - create_apikey') \\n roles = roles.split(',')\\n pprint.pprint(roles)\\n data = { 'desc' : description, 'roles' : roles }\\n pprint.pprint(data)\\n \\n target = f'{ApiVersion.CM1.value}/groups/{project_id}/apiKeys'\\n print( f'target={target}' )\\n print( f'data={data}' )\\n response = self.post(target, body=data)\\n return response\",\n \"def _db_key_to_servicekey(key):\\n return ServiceKey(\\n name=key.name,\\n kid=key.kid,\\n service=key.service,\\n jwk=key.jwk,\\n metadata=key.metadata,\\n created_date=key.created_date,\\n expiration_date=key.expiration_date,\\n rotation_duration=key.rotation_duration,\\n approval=key.approval,\\n )\",\n \"def mk_rg1(self):\\n name = f\\\"{self.env_name}/sg/project-default\\\"\\n self.sg_project_default = ec2.SecurityGroup(\\n \\\"SecurityGroupProjectDefault\\\",\\n rp_GroupDescription=\\\"Resources that has this security can talk to each other\\\",\\n p_GroupName=name,\\n p_VpcId=self.vpc_id,\\n p_SecurityGroupIngress=[\\n ec2.PropSecurityGroupIngress(\\n rp_IpProtocol=\\\"-1\\\",\\n p_FromPort=-1,\\n p_ToPort=-1,\\n p_CidrIp=f\\\"{authorized_ip}/32\\\",\\n )\\n for authorized_ip in self.sg_authorized_ips\\n ],\\n p_Tags=cf.Tag.make_many(\\n Name=name\\n ),\\n )\",\n \"def placement_group(template, name):\\n p = PlacementGroup(name, template=template)\\n p.Strategy = 'cluster'\\n return p\",\n \"def create_datasource_mapping(connection: Connection, body, error_msg: Optional[str] = None):\\n url = f\\\"{connection.base_url}/api/datasources/mappings\\\"\\n response = connection.session.post(url=url, json=body)\\n if not response.ok:\\n if error_msg is None:\\n error_msg = \\\"Error creating Datasource mapping\\\"\\n response_handler(response, error_msg)\\n return response\",\n \"def create_placement_group(self, name, strategy='cluster'):\\r\\n params = {'GroupName':name, 'Strategy':strategy}\\r\\n group = self.get_status('CreatePlacementGroup', params, verb='POST')\\r\\n return group\",\n \"def _build_elbv2_mapping_from_resources(resource_to_analyse, result_dict, session):\\n for elb_instance, security_group_id, security_group_name in _generate_elb_instances_and_sg(resource_to_analyse, session):\\n resource_dict = _check_if_in_list(result_dict, elb_instance[\\\"LoadBalancerName\\\"], \\\"resource_id\\\")\\n if resource_dict is not None:\\n resource_dict[\\\"sg_attached\\\"].append({\\n \\\"sg_id\\\": security_group_id,\\n \\\"sg_name\\\": security_group_name\\n })\\n else:\\n result_dict.append({\\n \\\"resource_id\\\": elb_instance[\\\"LoadBalancerName\\\"],\\n \\\"resource_type\\\": \\\"elb\\\",\\n \\\"sg_attached\\\": [{\\n \\\"sg_id\\\": security_group_id,\\n \\\"sg_name\\\": security_group_name\\n }]\\n })\\n return result_dict\",\n \"def setUp(self):\\n user = User.objects.create(email=\\\"test1@test.com\\\", first_name=\\\"Test1\\\", last_name=\\\"User\\\")\\n group = AnaGroup.objects.create(name=\\\"test group\\\")\\n IAM.objects.create(user=user,\\n aws_user=\\\"AWS user\\\",\\n aws_access_key=\\\"AWS access key\\\",\\n aws_secret_access_key=\\\"AWS secret key\\\",\\n group=group)\",\n \"def service_account(configure_security):\\n try:\\n name = config.SERVICE_NAME\\n secret = \\\"{}-secret\\\".format(name)\\n sdk_security.create_service_account(\\n service_account_name=name, service_account_secret=secret)\\n # TODO(mh): Fine grained permissions needs to be addressed in DCOS-16475\\n sdk_cmd.run_cli(\\n \\\"security org groups add_user superusers {name}\\\".format(name=name))\\n yield {\\\"name\\\": name, \\\"secret\\\": secret}\\n finally:\\n return\",\n \"def test_create_resource_group(self):\\n pass\",\n \"def mapping(self, release_id, grouping):\\n\\n helper = Known(self.config, self.session)\\n classes = [g['name']['full'] for g in grouping]\\n return helper.mapping(release_id, classes)\",\n \"def test_create_namespaced_image_stream_mapping(self):\\n pass\",\n \"def create_group(group_id, group_name):\\n\\n kwargs = config.DEFAULT_REST_KWARGS\\n kwargs[\\\"data\\\"] = {\\\"id\\\": group_id, \\\"name\\\": group_name}\\n http_response = call_rest_api(\\\"/identities/groups/\\\", \\\"post\\\", **kwargs)\\n if http_response.status_code != 201: # 201 = 'new group created'\\n raise ValueError(http_response.text)\\n logger.log(f\\\"New custom group, {group_name}, with ID: {group_id}, was created successfully.\\\")\",\n \"def make_mapping(self) -> None:\\n start_mark = StreamMark('generated node', 0, 0, 0)\\n end_mark = StreamMark('generated node', 0, 0, 0)\\n self.yaml_node = yaml.MappingNode('tag:yaml.org,2002:map', list(),\\n start_mark, end_mark)\",\n \"def group_single(self, dss_group, unix_user, hadoop_user=None):\\n self.raw['type'] = 'SINGLE_MAPPING'\\n self.raw['dssGroup'] = dss_group\\n self.raw['targetUnix'] = unix_user\\n self.raw['targetHadoop'] = hadoop_user\\n return self\",\n \"def post_network_ipam_create(self, resource_dict):\\n pass\",\n \"def __init__(__self__, *,\\n domain_id: Optional[pulumi.Input[str]] = None,\\n group_id: Optional[pulumi.Input[str]] = None,\\n project_id: Optional[pulumi.Input[str]] = None,\\n region: Optional[pulumi.Input[str]] = None,\\n role_id: Optional[pulumi.Input[str]] = None,\\n user_id: Optional[pulumi.Input[str]] = None):\\n if domain_id is not None:\\n pulumi.set(__self__, \\\"domain_id\\\", domain_id)\\n if group_id is not None:\\n pulumi.set(__self__, \\\"group_id\\\", group_id)\\n if project_id is not None:\\n pulumi.set(__self__, \\\"project_id\\\", project_id)\\n if region is not None:\\n pulumi.set(__self__, \\\"region\\\", region)\\n if role_id is not None:\\n pulumi.set(__self__, \\\"role_id\\\", role_id)\\n if user_id is not None:\\n pulumi.set(__self__, \\\"user_id\\\", user_id)\",\n \"def testServiceMapping_ByList(self):\\n self.DoMappingTest(\\n [('/my-service1', MyService.new_factory('service1')),\\n ('/my-service2', MyService.new_factory('service2')),\\n ])\",\n \"def create_asu_map(mapin, mapout):\\n\\n # Masking object\\n masker = CommandManager('mapmask')\\n # Set input files\\n masker.add_command_line_arguments(['mapin',mapin,'mapout',mapout])\\n # Set stdin\\n masker.add_standard_input(['XYZLIM ASU','END'])\\n # Run!\\n masker.run()\\n # Report errors\\n if masker.process.returncode!=0:\\n raise RuntimeError('mapmask failed to create asu map from {!s}'.format(mapin))\\n\\n # Return Command Managers for flexible handling of out & err\\n return masker\",\n \"def create_iam_role(iam):\\n print(\\\"Creating a new IAM Role\\\") \\n try:\\n resp = iam.create_role(Path='/',\\n RoleName=DWH_IAM_ROLE_NAME,\\n Description = \\\"Allows Redshift clusters to call AWS services on your behalf.\\\",\\n AssumeRolePolicyDocument=json.dumps({'Statement': [{'Action': 'sts:AssumeRole',\\n 'Effect': 'Allow',\\n 'Principal': {'Service': 'redshift.amazonaws.com'}}],\\n 'Version': '2012-10-17'}\\n )\\n )\\n print(\\\"IAM Role created:\\\")\\n print(resp)\\n except iam.exceptions.EntityAlreadyExistsException:\\n print(\\\"IAM Role already created\\\")\\n except Exception as e:\\n print(\\\"Error creating IAM Role:\\\", e)\",\n \"def assignGroupIDs(self):\\n components = self.getComponents(graph_dictionary=self.graph_dict)\\n self._gIDs = np.zeros(self.no_plants, dtype='object')\\n for i in components.keys():\\n self._gIDs[components[i]] = 'gID_' + str(i)\",\n \"def create_srv_entry(srv_name, ip, port):\\n res = {}\\n res['service'] = \\\"_{}._tcp.marathon.mesos\\\".format(srv_name)\\n res['host'] = \\\"{}-74b1w-s1.marathon.mesos.\\\".format(srv_name)\\n res['ip'] = ip\\n res['port'] = port\\n\\n return res\",\n \"def generate_control_mappings(self, control):\\n acr_creator = all_models.AccessControlRole.query.filter_by(\\n name=\\\"Creators\\\", object_type=\\\"Assessment\\\"\\n ).first()\\n with factories.single_commit():\\n person = factories.PersonFactory()\\n asmnt_ids = []\\n for _ in range(2):\\n asmnt = factories.AssessmentFactory()\\n asmnt_ids.append(asmnt.id)\\n factories.AccessControlListFactory(\\n object=asmnt, person=person, ac_role=acr_creator\\n )\\n\\n for asmnt_id in asmnt_ids:\\n asmnt = all_models.Assessment.query.get(asmnt_id)\\n self.gen.generate_relationship(source=asmnt, destination=control)\",\n \"def create_namespaced_user_identity_mapping(self, body, **kwargs):\\n\\n all_params = ['body', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_namespaced_user_identity_mapping\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `create_namespaced_user_identity_mapping`\\\")\\n\\n resource_path = '/oapi/v1/useridentitymappings'.replace('{format}', 'json')\\n path_params = {}\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1UserIdentityMapping',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def testServiceMapping_ByFactory(self):\\n self.DoMappingTest({'/my-service': MyService.new_factory('new-value')})\",\n \"def testMapping(self):\\n factory = service_handlers.ServiceHandlerFactory(Service)\\n path, mapped_factory = factory.mapping('/my_service')\\n\\n self.assertEquals(r'(/my_service)' + service_handlers._METHOD_PATTERN, path)\\n self.assertEquals(id(factory), id(mapped_factory))\\n match = re.match(path, '/my_service.my_method')\\n self.assertEquals('/my_service', match.group(1))\\n self.assertEquals('my_method', match.group(2))\\n\\n path, mapped_factory = factory.mapping('/my_service/nested')\\n self.assertEquals('(/my_service/nested)' +\\n service_handlers._METHOD_PATTERN, path)\\n match = re.match(path, '/my_service/nested.my_method')\\n self.assertEquals('/my_service/nested', match.group(1))\\n self.assertEquals('my_method', match.group(2))\",\n \"def amazonEc2_create(amazonEc2):\\n\\treturn amazonEc2\",\n \"def _mrp_service(self, _, address, port, properties):\\n identifier = properties.get(\\\"UniqueIdentifier\\\")\\n name = properties.get(\\\"Name\\\")\\n service = conf.MrpService(identifier, port, properties=properties)\\n self._handle_service(address, name, service)\",\n \"def create_inbound(self, keys):\",\n \"def post_service_appliance_set_create(self, resource_dict):\\n pass\",\n \"def create_new_group(self, a, b):\\n self.groups[self.group_id] = set([a,b])\\n self.node_id[a] = self.node_id[b] = self.group_id\\n self.group_id += 1\",\n \"def create_entry_group(self, location_id, entry_group_id):\\n entry_group = self.__datacatalog.create_entry_group(\\n parent=f'projects/{self.__project_id}/locations/{location_id}',\\n entry_group_id=entry_group_id,\\n entry_group=datacatalog.EntryGroup())\\n logging.info('Entry Group created: %s', entry_group.name)\\n return entry_group\",\n \"def _makeimap(self):\\n self.map_[\\\"source\\\"] = \\\"nasa\\\"\\n self.map_[\\\"instrument\\\"] = \\\"goes\\\"\\n self.map_[\\\"physobs\\\"] = \\\"irradiance\\\"\\n self.map_[\\\"provider\\\"] = \\\"sdac\\\"\",\n \"def _transform(self, resource_from_api):\\n for (project_id, backend_services) in resource_from_api.iteritems():\\n for backend_service in backend_services:\\n yield {'project_id': project_id,\\n 'id': backend_service.get('id'),\\n 'creation_timestamp': parser.format_timestamp(\\n backend_service.get('creationTimestamp'),\\n self.MYSQL_DATETIME_FORMAT),\\n 'name': backend_service.get('name'),\\n 'description': backend_service.get('description'),\\n 'affinity_cookie_ttl_sec': self._to_int(\\n backend_service.get('affinityCookieTtlSec')),\\n 'backends': parser.json_stringify(\\n backend_service.get('backends', [])),\\n 'cdn_policy': parser.json_stringify(\\n backend_service.get('cdnPolicy', {})),\\n 'connection_draining': parser.json_stringify(\\n backend_service.get('connectionDraining', {})),\\n 'enable_cdn': self._to_bool(\\n backend_service.get('enableCDN')),\\n 'health_checks': parser.json_stringify(\\n backend_service.get('healthChecks', [])),\\n 'iap': parser.json_stringify(\\n backend_service.get('iap', {})),\\n 'load_balancing_scheme': backend_service.get(\\n 'loadBalancingScheme'),\\n 'port': self._to_int(backend_service.get('port')),\\n 'port_name': backend_service.get('portName'),\\n 'protocol': backend_service.get('protocol'),\\n 'region': backend_service.get('region'),\\n 'session_affinity': backend_service.get(\\n 'sessionAffinity'),\\n 'timeout_sec': backend_service.get('timeoutSec'),\\n 'raw_backend_service':\\n parser.json_stringify(backend_service)}\",\n \"def test_create_group(self):\\n pass\",\n \"def test_create_group(self):\\n pass\",\n \"def create(self, name, public_key=None):\\n data = {\\n \\\"keypair\\\": {\\n \\\"name\\\": name\\n }\\n }\\n if public_key is not None:\\n data['keypair']['public_key'] = public_key\\n \\n path = '/os-keypairs'\\n res = self.client.call(path, 'POST', data=json.dumps(data), \\n token=self.manager.identity.token)\\n self.logger.debug('Create/import openstack keypair: %s' % truncate(res))\\n return res[0]['keypair']\",\n \"def createService(data):\\n return Service(data).create()\",\n \"def form_point_to_tract_mapping(voter, mapping, geoid_to_id_mapping: GeoIDToIDMapping):\\n # voter.name refers to the point ID\\n mapping[voter.name] = geoid_to_id_mapping[voter[\\\"GEOID\\\"]]\",\n \"def create_from_changeset(changeset, stub=None, update_sender=None, update_recipient=None):\\n group = Identity.create_from_changeset(changeset,\\n stub=stub, update_sender=update_sender, update_recipient=update_recipient, kind=Group)\\n\\n group.description = changeset[\\\"description\\\"]\\n group.set_state(changeset[\\\"state\\\"])\\n request_list = list()\\n\\n # Update admin\\n admin = Persona.query.get(changeset[\\\"admin_id\\\"])\\n if admin is None or admin._stub:\\n request_list.append({\\n \\\"type\\\": \\\"Persona\\\",\\n \\\"id\\\": changeset[\\\"admin_id\\\"],\\n \\\"author_id\\\": update_recipient.id if update_recipient else None,\\n \\\"recipient_id\\\": update_sender.id if update_sender else None,\\n })\\n\\n if admin is None:\\n admin = Persona(\\n id=changeset[\\\"admin_id\\\"],\\n )\\n admin._stub = True\\n\\n group.admin = admin\\n\\n mc = group.update_members(changeset[\\\"members\\\"])\\n for m in mc:\\n request_list.append({\\n \\\"type\\\": \\\"Persona\\\",\\n \\\"id\\\": m,\\n \\\"author_id\\\": update_recipient.id if update_recipient else None,\\n \\\"recipient_id\\\": update_sender.id if update_sender else None,\\n })\\n\\n for req in request_list:\\n request_objects.send(Group.create_from_changeset, message=req)\\n\\n return group\",\n \"def write_map(sample_group, sample_dir):\\n\\n\\n map_fname = new_file(\\\"map.txt\\\", basedir=sample_dir)\\n\\n def _write(targets):\\n with open(map_fname, 'w') as map_file:\\n # print the headers first\\n print >> map_file, \\\"#\\\"+\\\"\\\\t\\\".join(sample_group[0]._fields)\\n\\n for _, samples_bycode in itertools.groupby(\\n sample_group, operator.attrgetter(\\\"BarcodeSequence\\\")):\\n # get the first (hopefully only) sample from the samples\\n # grouped by ID then barcode. Ignore any other samples\\n # under the same ID for the same barcode\\n sample = samples_bycode.next()\\n bcode = sample.BarcodeSequence\\n # uniq-ify to make qiime happy\\n sample = list(sample)\\n sample[0] += \\\"_\\\" + bcode\\n print >> map_file, \\\"\\\\t\\\".join(sample)\\n\\n return {\\n \\\"name\\\": \\\"write_map:\\\"+map_fname,\\n \\\"actions\\\": [_write],\\n \\\"targets\\\": [map_fname],\\n \\\"title\\\": lambda t: t.name+\\\" Estimated mem=200 time=5 threads=1\\\"\\n }\",\n \"def test_groups_group_id_state_put(self):\\n pass\",\n \"def get_idp_group_mapping(self, identity_provider_id, mapping_id, **kwargs):\\n resource_path = \\\"/identityProviders/{identityProviderId}/groupMappings/{mappingId}\\\"\\n method = \\\"GET\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"get_idp_group_mapping got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"identityProviderId\\\": identity_provider_id,\\n \\\"mappingId\\\": mapping_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"IdpGroupMapping\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"IdpGroupMapping\\\")\",\n \"def test_valid_service_account_registration_multiple_service_accounts(\\n app,\\n db_session,\\n client,\\n encoded_jwt_service_accounts_access,\\n cloud_manager,\\n valid_google_project_patcher,\\n valid_service_account_patcher,\\n):\\n proj_patcher = valid_google_project_patcher\\n project = Project(id=1, auth_id=\\\"some_auth_id\\\")\\n\\n bucket = Bucket(id=1)\\n\\n db_session.add(project)\\n db_session.add(bucket)\\n db_session.commit()\\n\\n project_to_bucket = ProjectToBucket(project_id=1, bucket_id=1)\\n\\n db_session.add(project_to_bucket)\\n db_session.commit()\\n\\n gbag = GoogleBucketAccessGroup(id=1, bucket_id=1, email=\\\"gbag@gmail.com\\\")\\n\\n db_session.add(gbag)\\n db_session.commit()\\n\\n google_project_id = \\\"project-id\\\"\\n encoded_creds_jwt = encoded_jwt_service_accounts_access[\\\"jwt\\\"]\\n project_access = [\\\"some_auth_id\\\"]\\n proj_patcher[\\\"get_service_account_ids_from_google_members\\\"].return_value = [\\n \\\"test-{}@test.com\\\".format(google_project_id),\\n \\\"{}@compute-system.iam.gserviceaccount.com\\\".format(google_project_id),\\n ]\\n valid_service_account = {\\n \\\"service_account_email\\\": \\\"sa@gmail.com\\\",\\n \\\"google_project_id\\\": google_project_id,\\n \\\"project_access\\\": project_access,\\n }\\n\\n (\\n cloud_manager.return_value.__enter__.return_value.get_service_account.return_value\\n ) = {\\\"uniqueId\\\": \\\"sa_unique_id\\\", \\\"email\\\": \\\"sa@gmail.com\\\"}\\n\\n (\\n cloud_manager.return_value.__enter__.return_value.add_member_to_group.return_value\\n ) = {\\\"email\\\": \\\"sa@gmail.com\\\"}\\n\\n assert len(db_session.query(UserServiceAccount).all()) == 0\\n assert len(db_session.query(ServiceAccountAccessPrivilege).all()) == 0\\n assert len(db_session.query(ServiceAccountToGoogleBucketAccessGroup).all()) == 0\\n\\n response = client.post(\\n \\\"/google/service_accounts\\\",\\n headers={\\\"Authorization\\\": \\\"Bearer \\\" + encoded_creds_jwt},\\n data=json.dumps(valid_service_account),\\n content_type=\\\"application/json\\\",\\n )\\n\\n assert response.status_code == 200\\n\\n assert len(db_session.query(UserServiceAccount).all()) == 1\\n assert len(db_session.query(ServiceAccountAccessPrivilege).all()) == 1\\n assert len(db_session.query(ServiceAccountToGoogleBucketAccessGroup).all()) == 1\",\n \"def test_creation_mapped_control(self):\\n control = factories.ControlFactory()\\n # Map original of control to several assessments to get propagated roles\\n self.generate_control_mappings(control)\\n\\n # Existing control should be updated to create new revision with ACL\\n self.api.put(control, {\\\"title\\\": \\\"Test Control\\\"})\\n\\n program = factories.ProgramFactory()\\n factories.RelationshipFactory(source=program, destination=control)\\n response = self.api.post(all_models.Audit, [{\\n \\\"audit\\\": {\\n \\\"title\\\": \\\"New Audit\\\",\\n \\\"program\\\": {\\\"id\\\": program.id},\\n \\\"status\\\": \\\"Planned\\\",\\n \\\"context\\\": None\\n }\\n }])\\n self.assert200(response)\",\n \"def service_for_map(self, map_name):\\n return getattr(self.map_services[map_name], self.service_name)\",\n \"def create_tap_service(attrs=None):\\n attrs = attrs or {}\\n tap_service_attrs = {\\n 'id': uuidutils.generate_uuid(),\\n 'tenant_id': uuidutils.generate_uuid(),\\n 'name': 'test_tap_service' + uuidutils.generate_uuid(),\\n 'status': 'ACTIVE',\\n }\\n tap_service_attrs.update(attrs)\\n return copy.deepcopy(tap_service_attrs)\",\n \"def pre_service_template_create(self, resource_dict):\\n pass\",\n \"def pairing_group_create(curve='MNT224'):\\n return PairingGroup(curve)\",\n \"def create_group(self):\\n # TODO: Assuming first server is good - need to make fallback logic\\n return self.session.get_any(\\\"{base}{request_url}\\\".format(base=self.servers[0],\\n request_url=F\\\"/GroupV2/Create/\\\"))\",\n \"def createGroup(self, *group):\\n if not self.rank:\\n logging.info('Creating atom group {}'.format(group))\\n\\n if not len(group):\\n for idSS in self.pargs['idSS']:\\n self.lmp.command('group group{} type {}'.format(idSS, idSS))\\n else:\\n self.lmp.command('group ' + ('{} ' * len(group)).format(*group))\"\n]"},"negative_scores":{"kind":"list like","value":["0.5638617","0.535589","0.52390397","0.5175165","0.5099908","0.50906384","0.5057816","0.5040309","0.50400156","0.5031047","0.5025609","0.49890697","0.49736708","0.49677986","0.49640617","0.49320868","0.49188626","0.4918003","0.4915699","0.48859853","0.48664403","0.48657614","0.48556882","0.48550412","0.48329398","0.482938","0.48289818","0.48210335","0.4819092","0.4818401","0.4805326","0.47917113","0.47863165","0.47797883","0.47793153","0.4774191","0.47699392","0.47538427","0.4747265","0.47448146","0.47445607","0.47281212","0.4727731","0.4707899","0.47053295","0.46970582","0.4692016","0.46903306","0.46802178","0.4678766","0.46715838","0.46642473","0.4659402","0.46573117","0.4653107","0.4641925","0.4641725","0.4639226","0.46284246","0.46226","0.46220678","0.46193025","0.4618647","0.46103933","0.46021172","0.4589371","0.45870268","0.45811903","0.45695955","0.45692232","0.45653656","0.45454472","0.45433107","0.45367375","0.45331404","0.45317465","0.45283136","0.45281196","0.45264888","0.45229253","0.45193213","0.45170024","0.4516713","0.4516558","0.4516558","0.4515323","0.45145604","0.450457","0.45032442","0.45021445","0.45010355","0.44975236","0.4495599","0.44953844","0.44917595","0.44906196","0.44883204","0.44861823","0.448293","0.44793564"],"string":"[\n \"0.5638617\",\n \"0.535589\",\n \"0.52390397\",\n \"0.5175165\",\n \"0.5099908\",\n \"0.50906384\",\n \"0.5057816\",\n \"0.5040309\",\n \"0.50400156\",\n \"0.5031047\",\n \"0.5025609\",\n \"0.49890697\",\n \"0.49736708\",\n \"0.49677986\",\n \"0.49640617\",\n \"0.49320868\",\n \"0.49188626\",\n \"0.4918003\",\n \"0.4915699\",\n \"0.48859853\",\n \"0.48664403\",\n \"0.48657614\",\n \"0.48556882\",\n \"0.48550412\",\n \"0.48329398\",\n \"0.482938\",\n \"0.48289818\",\n \"0.48210335\",\n \"0.4819092\",\n \"0.4818401\",\n \"0.4805326\",\n \"0.47917113\",\n \"0.47863165\",\n \"0.47797883\",\n \"0.47793153\",\n \"0.4774191\",\n \"0.47699392\",\n \"0.47538427\",\n \"0.4747265\",\n \"0.47448146\",\n \"0.47445607\",\n \"0.47281212\",\n \"0.4727731\",\n \"0.4707899\",\n \"0.47053295\",\n \"0.46970582\",\n \"0.4692016\",\n \"0.46903306\",\n \"0.46802178\",\n \"0.4678766\",\n \"0.46715838\",\n \"0.46642473\",\n \"0.4659402\",\n \"0.46573117\",\n \"0.4653107\",\n \"0.4641925\",\n \"0.4641725\",\n \"0.4639226\",\n \"0.46284246\",\n \"0.46226\",\n \"0.46220678\",\n \"0.46193025\",\n \"0.4618647\",\n \"0.46103933\",\n \"0.46021172\",\n \"0.4589371\",\n \"0.45870268\",\n \"0.45811903\",\n \"0.45695955\",\n \"0.45692232\",\n \"0.45653656\",\n \"0.45454472\",\n \"0.45433107\",\n \"0.45367375\",\n \"0.45331404\",\n \"0.45317465\",\n \"0.45283136\",\n \"0.45281196\",\n \"0.45264888\",\n \"0.45229253\",\n \"0.45193213\",\n \"0.45170024\",\n \"0.4516713\",\n \"0.4516558\",\n \"0.4516558\",\n \"0.4515323\",\n \"0.45145604\",\n \"0.450457\",\n \"0.45032442\",\n \"0.45021445\",\n \"0.45010355\",\n \"0.44975236\",\n \"0.4495599\",\n \"0.44953844\",\n \"0.44917595\",\n \"0.44906196\",\n \"0.44883204\",\n \"0.44861823\",\n \"0.448293\",\n \"0.44793564\"\n]"},"document_score":{"kind":"string","value":"0.5351723"},"document_rank":{"kind":"string","value":"2"}}},{"rowIdx":8578,"cells":{"query":{"kind":"string","value":"Creates a new MFA TOTP device for the user. A user can have one MFA TOTP device."},"document":{"kind":"string","value":"def create_mfa_totp_device(self, user_id, **kwargs):\n resource_path = \"/users/{userId}/mfaTotpDevices\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_mfa_totp_device got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"MfaTotpDevice\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"MfaTotpDevice\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def activate_mfa_totp_device(self, user_id, mfa_totp_device_id, mfa_totp_token, **kwargs):\n resource_path = \"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}/actions/activate\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"if_match\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"activate_mfa_totp_device got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id,\n \"mfaTotpDeviceId\": mfa_totp_device_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"if-match\": kwargs.get(\"if_match\", missing),\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=mfa_totp_token,\n response_type=\"MfaTotpDeviceSummary\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=mfa_totp_token,\n response_type=\"MfaTotpDeviceSummary\")","def post(self, request):\n request_data = request.data\n if 'mobile' not in request_data or not request_data['mobile']:\n return StandardHttpResponse.bad_rsp([], 'Invalid Data.')\n email = None\n mobile = None\n if '@' in request_data['mobile']:\n email = request_data['mobile']\n else:\n mobile = request_data['mobile']\n if mobile:\n user_profile_obj = UserModelQueries.get_user_profile_by_mobile(mobile)\n if not user_profile_obj:\n return StandardHttpResponse.bad_rsp([], 'Mobile is yet not registered or not verified.')\n else:\n user_profile_obj = UserModelQueries.get_user_profile_by_email(email)\n if not user_profile_obj:\n return StandardHttpResponse.bad_rsp([], 'Looks like You haven\\'t registered yet. Please Registered.')\n\n result, response = MobileOtpService.create_otp(user_profile_obj.mobile,\n 'ForgetPassword')\n if not result:\n return StandardHttpResponse.bad_rsp([], response)\n # TODO: Code to send the otp to mobile\n SentOTP.send_otp_to_email(email, response['otp'], 'Forget Password')\n response_data = {'otp_ref': response['otp_ref']}\n return StandardHttpResponse.rsp_200(response_data, 'An OTP Sent to {} to reset the password'\n .format(user_profile_obj.mobile.__str__()))","def generate_totp_seed(self, user_id, mfa_totp_device_id, **kwargs):\n resource_path = \"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}/actions/generateSeed\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"if_match\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"generate_totp_seed got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id,\n \"mfaTotpDeviceId\": mfa_totp_device_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"if-match\": kwargs.get(\"if_match\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"MfaTotpDevice\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"MfaTotpDevice\")","def post(self, request):\n\n email = request.data.get('email')\n phone_number = request.data.get('phone_number')\n otp = request.data.get('otp')\n\n # check that otp is correct or not (otp should match with email or phone number\n otp_obj = Otp.objects.filter(Q(email_phone=email) | Q(email_phone=phone_number) & Q(code=otp)).first()\n if not otp_obj:\n response_json = {\n 'status': False,\n 'message': 'otp is incorrect',\n 'data': {}\n }\n\n return Response(response_json, status=400)\n\n # create new user\n request_json = {\n \"username\": request.data.get('username'),\n \"password\": make_password(request.data.get('password')),\n \"email\": email,\n \"phone_number\": phone_number\n }\n\n user_serialized = UserProfileSerializer(data=request_json)\n if not user_serialized.is_valid():\n return validate_error(user_serialized)\n user_serialized.save()\n\n user_obj = UserProfile.objects.filter(id=user_serialized.data.get('id')).first()\n if not user_obj:\n return existence_error('user')\n\n # create following and follower object\n following_obj = UserFollowing.objects.create(user=user_obj)\n follower_obj = UserFollower.objects.create(user=user_obj)\n\n token, created = Token.objects.get_or_create(user=user_obj)\n\n otp_obj.delete()\n\n response_json = {\n 'status': True,\n 'message': 'User successfully registered',\n 'data': 'Token {}'.format(token.key)\n }\n\n return Response(response_json, status=201)","def create(self, validated_data):\n return MFAMethod.objects.get_or_create(\n user=self.user,\n name=self.context['name'],\n defaults={\n 'secret': create_secret(),\n 'is_active': False,\n }\n )","def do_user_create():\n target = User(\n request.form['gender'],\n request.form['first_name'],\n request.form['name'],\n request.form['mail'],\n request.form['meter_id'],\n request.form['group_id'],\n secrets.token_hex(33))\n target.set_role(request.form['role'])\n target.nick = request.form['nick']\n db.session.add(target)\n db.session.commit()\n return user_list(\"Created user \" + target.name)","def post(self, request):\n\n email = request.data.get('email')\n phone_number = request.data.get('phone_number')\n otp = request.data.get('otp')\n\n # check that otp is correct or not (otp should match with email or phone number\n otp_obj = Otp.objects.filter(Q(email_phone=email) | Q(email_phone=phone_number) & Q(code=otp)).first()\n if not otp_obj:\n response_json = {\n 'status': False,\n 'message': 'otp is incorrect',\n 'data': {}\n }\n\n return Response(response_json, status=400)\n\n # login user\n user_obj = UserProfile.objects.filter(\n Q(phone_number=request.data.get('phone_number')) | Q(email=request.data.get('email'))).first()\n\n token, created = Token.objects.get_or_create(user=user_obj)\n\n otp_obj.delete()\n\n response_json = {\n 'status': True,\n 'message': 'User successfully Logged in',\n 'data': 'Token {}'.format(token.key)\n }\n\n return Response(response_json, status=200)","def create_token(request, user):\n\n key = get_random_string(100)\n data = {}\n ip = get_client_ip_address(request)\n\n return Token.objects.create(user=user, key=key, data=json.dumps(data), ip=ip)","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def create_user(self, phone_number, type, password, is_staff):\n return self.__create_user(phone_number, type, password, is_staff, False, False)","def create(self, user, token):\n\n session['user'] = {\n 'id': str(user.id),\n 'login': user.login,\n 'token': token\n }\n\n return UserSession.create(session['user'])","def create_gateway_device(self, body=None):\r\n return self.post(self.gateway_devices_path, body=body)","def create_teacher(username, password, email, preferred_language,skype_id,name, phone_number, country,availability):\n person.create_person(username,password,email,preferred_language,skype_id,name,phone_number,country)\n teacher_account_id = person.get_last()\n query = 'INSERT INTO teacher VALUES( %s,%s );'\n args = (teacher_account_id, availability)\n database.connection.save_data(query, args)","def _create_user(self, email, mobile_number, password, **extra_fields):\n\n print('model number')\n print(mobile_number)\n \n user = self.model(email=email,mobile_number = mobile_number, **extra_fields)\n user.set_password(password)\n \n user.save(using=self._db)\n return user","def create_user(session, phone_number, name, pass_hash, funds=0.0):\n # Perform the db job\n user = User(phone_number=phone_number, name=name, pass_hash=pass_hash, funds=funds)\n session.add(user)\n session.commit()\n return USER_GET_URI.format(user_id=phone_number)","def create(self,request):\n return CustomAuthToken().post(request)","def create_new_user(cls, user_email, user_password, user_phone):\n\n new_user = User(email=user_email, password=user_password, mobile_phone=user_phone)\n\n db.session.add(new_user)\n db.session.commit()\n\n print \"Successfully added new user with the email: %s\" % user_email","def add_user(self):\n\n pin, code = self.get_auth_pin() \n print(\"Enter the PIN '{}' into the Add Application window and click Add Application\".format(pin))\n input(\"waiting press enter to continue...\")\n\n access_token, refresh_token = self.get_tokens(code)\n user_id = self.tokens.get_next_user_id()\n self.tokens.insert_user(user_id, access_token, refresh_token)\n tstat_ids = self.get_tstat_ids(access_token)\n for tstat_id in tstat_ids:\n logger.info(\"Adding Thermostat ID: {}\".format(tstat_id))\n self.tokens.insert_tstat(user_id, tstat_id)","def create_user(self):\n User.objects.create_user('test', 'testing@test.com', 'testing')","def create_device(self, device_dict):\n devices = {'devices': [device_dict]}\n url = '{}/iot/devices'.format(self.url)\n return self.post(url, data=json.dumps(devices), headers=self.headers)","def create_user_device(self, email, device_str):\n if self.database is None:\n raise Exception(\"No database.\")\n if email is None or len(email) == 0:\n raise Exception(\"Email address not provided.\")\n if device_str is None or len(device_str) == 0:\n raise Exception(\"Device string not provided.\")\n user_id, _, _ = self.database.retrieve_user(email)\n return self.database.create_user_device(user_id, device_str)","def user(self, user_token, user_device=None):\n self.set('user', user_token)\n self.set('device', user_device)","def register_user_device(username: str, password: str, mac_address: str, email: Optional[str] = None) -> \\\n Union[str, Token]:\n ret = register_user(username, password, email)\n if isinstance(ret, str):\n return ret\n else:\n user_id = ret\n token, device_id = _add_update_device(user_id, mac_address)\n client_logger_security().info(f\"Successfully added new device: user_id={user_id}, device_id={device_id}\")\n _set_user_authenticated(user_id, device_id)\n return token","def create(self, validated_data):\n request = self._kwargs['context']['request']\n user = User.objects.create(**validated_data)\n user.set_password(validated_data[\"password\"])\n user.save()\n category_list = ['Fuel', 'Bill', 'Entertainment', 'Education', 'Food']\n for category in category_list:\n user.user_categories.create(name=category)\n login(request, user)\n token, created = Token.objects.get_or_create(user=user)\n validated_data[\"token\"] = token.key\n return validated_data","def create_user(self, email_or_phone, password=None, **extra_fields):\n return self._create_user(email_or_phone, password, False, False, **extra_fields)","def RegisterDevice(self, device_id, machine_id, type, username):\n dmtoken_chars = []\n while len(dmtoken_chars) < 32:\n dmtoken_chars.append(random.choice('0123456789abcdef'))\n dmtoken = ''.join(dmtoken_chars)\n allowed_policy_types = {\n dm.DeviceRegisterRequest.BROWSER: [\n 'google/chrome/user',\n 'google/chrome/extension'\n ],\n dm.DeviceRegisterRequest.USER: [\n 'google/chromeos/user',\n 'google/chrome/extension'\n ],\n dm.DeviceRegisterRequest.DEVICE: [\n 'google/chromeos/device',\n 'google/chromeos/publicaccount',\n 'google/chrome/extension',\n 'google/chromeos/signinextension'\n ],\n dm.DeviceRegisterRequest.ANDROID_BROWSER: [\n 'google/android/user'\n ],\n dm.DeviceRegisterRequest.TT: ['google/chromeos/user',\n 'google/chrome/user'],\n }\n if machine_id in KIOSK_MACHINE_IDS:\n enrollment_mode = dm.DeviceRegisterResponse.RETAIL\n else:\n enrollment_mode = dm.DeviceRegisterResponse.ENTERPRISE\n self._registered_tokens[dmtoken] = {\n 'device_id': device_id,\n 'device_token': dmtoken,\n 'allowed_policy_types': allowed_policy_types[type],\n 'machine_name': 'chromeos-' + machine_id,\n 'machine_id': machine_id,\n 'enrollment_mode': enrollment_mode,\n 'username': username,\n }\n self.WriteClientState()\n return self._registered_tokens[dmtoken]","def create_user():\n record = request.get_json()\n if record is None:\n return {\"Error\": \"No data Supplied.\"}, 400\n\n schema = user_schema.load(record)\n\n if UserModel.objects(email=schema['email']):\n return {\"Error\": \"User Data already exists.\"}, 400\n user = UserModel(**schema)\n user.hash_password()\n user.save()\n ser_data = user_schema.dump(user)\n token = Auth.generate_token(ser_data[\"_id\"])\n return {\"message\": \"User Created Successfully\", \"Token\": token, \"id\": str(user.id)}, 200","def create_user(self, email, mobile_number, password, **extra_fields):\n extra_fields.setdefault('is_staff', False)\n extra_fields.setdefault('is_superuser', False)\n return self._create_user(email, mobile_number, password , **extra_fields)","def create(self, data):\n data.pop('password_confirmation')\n try:\n availability = data.pop(\"availability\")\n babysitter = data.pop(\"user_bbs\")\n user = User.objects.create_user(**data, is_verified=False)\n if babysitter:\n bbs = Babysitter.objects.create(user_bbs=user, **babysitter)\n for shift in availability:\n Availability.objects.create(bbs=bbs, **shift)\n except KeyError:\n logging.info('This is a instance client')\n user = User.objects.create_user(**data, is_verified=False)\n logging.info(f'User created, whit pk {user.pk}')\n client = Client.objects.create(user_client=user)\n logging.info(f'User pk is already to pass {user.pk}')\n send_confirmation_email.delay(username=user.username, email=user.email )\n return user","def get_mfa_totp_device(self, user_id, mfa_totp_device_id, **kwargs):\n resource_path = \"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}\"\n method = \"GET\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"get_mfa_totp_device got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id,\n \"mfaTotpDeviceId\": mfa_totp_device_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"MfaTotpDeviceSummary\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"MfaTotpDeviceSummary\")","def create_auth_token(sender, instance=None, created=False, **kwargs): # pylint: disable=unused-argument\n if created:\n Token.objects.create(user=instance) # pylint: disable=no-member","def test_api_create_atmuser(self):\n users_num = ATMUser.objects.count()\n\n atmuser = ATMUser.objects.get(card='0000000000000000') # get admin\n view = ATMUserViewSet.as_view({'post': 'create'})\n\n data = {'card': '7777777777777777', 'password': '7777', 'cash': 700}\n request = factory.post(reverse('atmuser-list'), data, format='json')\n\n force_authenticate(request, user=atmuser)\n response = view(request)\n\n self.assertEqual(response.status_code, status.HTTP_201_CREATED)\n self.assertEqual(ATMUser.objects.count(), users_num + 1)","def new_user(testapp):\n SessionFactory = testapp.app.registry[\"dbsession_factory\"]\n with transaction.manager:\n dbsession = get_tm_session(SessionFactory, transaction.manager)\n new_user = User(username=\"test\", password=pwd_context.hash(\"test\"))\n dbsession.add(new_user)","def _create_auth_token(self, user=None):\n token, created = Token.objects.get_or_create(user=user)\n return token","def create_form_user(self, **kwargs):\n user = User.objects.create_user(\n **kwargs\n )\n return user","def create(self, data):\n # Make User\n code = (random.randint(1000, 9999))\n user = User.objects.get(pk=self.context['user'].pk)\n new = str(code).strip()\n hs = hashlib.sha1(new.encode()).hexdigest()\n user.password = hs\n user.save()\n send_verification_email.delay(email=data['email'], code=code)\n return user","def create_user(self, password=None, phone=None, **extra_fields):\n extra_fields.setdefault('is_staff', False)\n extra_fields.setdefault('is_superuser', False)\n\n return self._create_user(password=password, phone=phone, **extra_fields)","def _add_update_device(user_id: int, mac_address: str) -> Tuple[Token, int]:\n possible_device = Device.get_by_mac(mac_address)\n if possible_device is not None:\n if Token.is_token_expired(possible_device.token_expires):\n new_token = Token()\n possible_device.token = new_token\n possible_device.token_expires = Token.get_next_expired()\n return new_token, possible_device.device_id\n else:\n return possible_device.token, possible_device.device_id\n device_id = Device.create(user_id, mac_address, Token(), Token.get_next_expired())\n device_token = Device.from_id(device_id).token\n assert os.path.exists(path_utils.get_users_root_folder(user_id))\n server_json.create_changes_file_for_new_device(user_id, device_id, empty=True)\n return device_token, device_id","def create(cls, imei, device_id):\n try:\n imei_device = cls(imei, device_id)\n imei_device.save()\n except Exception:\n raise Exception","def create_user(fname, phone_num):\n\n user = User(fname=fname, phone_num=phone_num)\n\n db.session.add(user)\n db.session.commit()\n\n return user","def new_user(cls, user):\r\n pass","def create_custom_user(sender, instance, signal, created, **kwargs):\n from gpsfun.main.User.models import GPSFunUser\n if created:\n GPSFunUser.objects.create(user=instance)\n instance.gpsfunuser.save()","def create_new_user():\n return get_user_model().objects.create_user(\n email='test@gmail.com',\n password='test@londodnjisdjfois',\n username='tempusername'\n )","def create_device(self, app_name='FooBar', device_type='Raspberry Pi 2'):\n\n app = self.resin.models.application.create(app_name, device_type)\n return app, self.resin.models.device.register(app['id'], self.resin.models.device.generate_uuid())","def create_user_by_id(cls, m_id):","def create_register_user(self, data, user_type):\n data.pop('password_confirm')\n data['user_type'] = user_type\n user = User.objects.create_user(**data)\n return user","def create_user(self):\n unique_id = str(uuid.uuid4())\n new_user_properties = {\n \"name\": self.name,\n \"mission_statement\": self.mission_statement,\n \"unique_id\": unique_id,\n \"email\": self.email.lower(),\n \"is_mentor\": True,\n \"is_tutor\": True,\n \"is_visible\": True,\n \"is_available_for_in_person\": True,\n \"is_admin\": True}\n new_user_node = Node.cast(AgoraLabel.USER, new_user_properties)\n try:\n self.graph_db.create(new_user_node)\n except:\n pass\n return new_user_node","def register():\n user_gender = request.form['user_gender']\n user_age = request.form['user_age']\n sensors = {\n 'accelerometer': request.form.get('accelerometer', False),\n 'ambient_temperature': request.form.get('ambient_temperature', False),\n 'gravity': request.form.get('gravity', False),\n 'gyroscope': request.form.get('gyroscope', False),\n 'light': request.form.get('light', False),\n 'linear_accelerometer': request.form.get('linear_accelerometer', False),\n 'magnetic_field': request.form.get('magnetic_field', False),\n 'orientation': request.form.get('orientation', False),\n 'pressure': request.form.get('pressure', False),\n 'proximity': request.form.get('proximity', False),\n 'relative_humidity': request.form.get('relative_humidity', False),\n 'rotation_vector': request.form.get('rotation_vector', False),\n 'temperature': request.form.get('temperature', False)\n }\n\n device, token = create_subject(user_gender, user_age, sensors)\n\n response = jsonify(status=\"Register Success\", message=\"Your device has been registered.\",\n device=device, token=token)\n\n response.status_code = 201\n\n return response","def test_create_token_for_user(self):\r\n payload = {\r\n 'email': 'test@max.net',\r\n 'password': 'Testpass123',\r\n 'name': 'Maks'\r\n }\r\n create_user(**payload)\r\n\r\n res = self.client.post(TOKEN_URL, payload)\r\n\r\n self.assertIn('token', res.data)\r\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def create_user(self):\n u = USER.objects.create(username='test_user1',\n email='test_email@example.com', )\n u.set_password('test_password')\n u.save()\n self.user = u\n return u","def post(self):\r\n return create_user(request)","def post(self, request, *args, **kwargs):\n self.create(request, *args, **kwargs)\n token, created = Token.objects.get_or_create(user=self.user)\n return Response({'token': token.key}, status=201)","def create_user(fname, lname, email, password, phone_number):\n user = User(fname = fname, lname = lname , email = email ,password = password, phone_number = phone_number)\n #setting password hash\n user.set_password(password)\n db.session.add(user)\n db.session.commit()\n\n return user","def create_user_wallet(sender, instance, created, **kwargs):\n if created:\n Wallet.objects.create(user=instance)","async def create_new_user(*, user: User):\n with Session(engine) as session:\n user.password = simple_hash(user.name, user.password) #Hashing password for security\n session.add(user)\n session.commit()\n return {\"message\": \"User {user_id} created\".format(user_id = user.id)}","def new_user(cls, user):\n pass","def create_user(self, phone, password=None, **extra_fields):\n print(extra_fields)\n if not phone:\n raise ValueError('Users must have an phone number')\n if not password:\n raise ValueError('Users must have a password')\n try:\n extra_fields['role']\n except Exception:\n raise ValueError('Users must have a role')\n try:\n extra_fields['name']\n except Exception:\n raise ValueError('Users must have a name') \n user = self.model(phone=phone, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n\n return user","def test_create_new_user(self, mapp, new_user_id):\n\n result = mapp.out_devpi(\n 'user', '-c',\n new_user_id, 'password=1234',\n 'email=%s@example.com' % new_user_id)\n assert result.ret == 0\n result.stdout.fnmatch_lines('user created: %s' % new_user_id)\n result = mapp.out_devpi('user', '-l')\n assert result.ret == 0\n result.stdout.fnmatch_lines(new_user_id)\n result = mapp.out_devpi('user', new_user_id)\n assert result.ret == 0\n result.stdout.fnmatch_lines('*email=%s@example.com' % new_user_id)","def create_user(self):\n username = \"\".join(choice(\n string.ascii_letters) for x in range (randint(7,10)))\n params = {\n \"first_name\":\"ugali\",\n \"last_name\":\"mayai\",\n \"email\":\"ugalimayai@gmail.com\",\n \"username\":username,\n \"password\":\"password\"\n }\n path = \"/api/v2/auth/signup\"\n user = self.client.post(path,\n data=json.dumps(params),\n content_type=\"application/json\")\n \n user_id = user.json['user_id']\n auth_token = user.json['AuthToken']\n return int(user_id), auth_token","def create_user(UserName=None, MessageAction=None, FirstName=None, LastName=None, AuthenticationType=None):\n pass","def flask_create_device():\n try:\n # retrieve the authorization token\n token = retrieve_auth_token(request)\n\n params = {\n 'count': request.args.get('count', '1'),\n 'verbose': request.args.get('verbose', 'false'),\n 'content_type': request.headers.get('Content-Type'),\n 'data': request.data\n }\n\n result = DeviceHandler.create_device(params, token)\n devices = result.get('devices')\n deviceId = devices[0].get('id')\n LOGGER.info(f' Creating a new device with id {deviceId}.')\n return make_response(jsonify(result), 200)\n except HTTPRequestError as e:\n LOGGER.error(f' {e.message} - {e.error_code}.')\n if isinstance(e.message, dict):\n return make_response(jsonify(e.message), e.error_code)\n\n return format_response(e.error_code, e.message)","def create_user(self) -> 'outputs.ActingUserResponse':\n return pulumi.get(self, \"create_user\")","def create_user(self):\n if not self.is_valid():\n return None\n # generate a username \n ids = User.objects.values_list('id', flat=True).order_by('-id')[:1]\n if len(ids) > 0:\n # ids[0] will be the maximum value (due to order_by: '-id')\n idnum = ids[0] + 1\n else:\n idnum = 1\n # create User object \n username = \"user%s\" % idnum\n # NOTE: store email in lower case\n email = self.clean_email().lower()\n password = self.clean_password2()\n user = User(username=username, email=email, password='tmp')\n user.save()\n # set the real password\n user.set_password(password)\n # make user inactive (until user has confirmed account)\n user.is_active = False\n # update\n user.save()\n return user","def _create_user(self, new_user):\n new_user = User(user_name=new_user['user_name'], pin=new_user['pin'], user_type='customer')\n self.session.output(new_user.get_user_info(), '\\n[ New user created ]')","def create_user_device_for_user_id(self, user_id, device_str):\n if self.database is None:\n raise Exception(\"No database.\")\n if user_id is None:\n raise Exception(\"User ID not provided.\")\n if device_str is None or len(device_str) == 0:\n raise Exception(\"Device string not provided.\")\n return self.database.create_user_device(user_id, device_str)","def delete_mfa_totp_device(self, user_id, mfa_totp_device_id, **kwargs):\n resource_path = \"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}\"\n method = \"DELETE\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"if_match\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"delete_mfa_totp_device got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id,\n \"mfaTotpDeviceId\": mfa_totp_device_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"if-match\": kwargs.get(\"if_match\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params)\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params)","def create_ticket(self, user):\n return Ticket.objects.create_ticket('test', user)","def create_user_object():\n user = User.objects.get_or_create(username='testuser',\n first_name='Test',\n last_name='User',\n email='test@test.com')[0]\n user.set_password('testabc123')\n user.save()\n return user","def create(self, request):\n\n return ObtainAuthToken().post(request)","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, request):\n return ObtainAuthToken().post(request)","def test_create_token_for_user(self):\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'testpass'\n }\n create_user(**payload)\n res = self.client.post(TOKEN_URI, payload)\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def test_create_token_for_user(self):\n payload = {'email': 'test1@test1.ri',\n 'password': 'testPassWord',\n 'time_zone': 'Europe/Dublin'}\n create_user(**payload)\n res = self.client.post(TOKEN_URL, payload)\n\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def test_create_token_for_user(self):\n payload = {'email': 'test@test.com', 'password': 'testpass'}\n create_user(**payload)\n res = self.client.post(TOKEN_URL, payload)\n\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def __initialize_totp(self) -> pyotp.totp.TOTP:\n return pyotp.totp.TOTP(self.user.totp_secret)","def create_user_object():\n user = User.objects.get_or_create(username='testuser',\n first_name='Test',\n last_name='User',\n email='test@test.com')[0]\n user.set_password('testabc123')\n user.save()\n\n return user","def req_display_otp(self):\n\n ret = self.ui_auth.create_new_one_time_pwd()\n if ret is not None:\n self.error_msg_queue_list.append(ret)","def create_user(self):\n return User.objects.create_user(**self.user_data)","def _create_user(self, phone_number, password, **extra_fields):\n if not phone_number:\n raise ValueError('The given phone_number must be set')\n phone_number = phone_number\n user = self.model(phone_number=phone_number, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n return user","def create_and_login(self):\n with self.context():\n user = self.factory(meido.factories.UserFactory)\n self.client.post('/management/login', data={\n 'username': 'admin', 'password': 'pretender'\n })","def create_device():\n sonyapilib.device.TIMEOUT = 0.1\n device = SonyDevice(\"test\", \"test\")\n device.api_version = 3\n device.cookies = jsonpickle.decode(read_file(\"data/cookies.json\"))\n return device","def create_user(context, params):\n form_user = dict()\n # form_user['edited_by'] = context.user\n if params.get('username'):\n form_user['username'] = params.get('username')\n else:\n form_user['username'] = create_username(params) # 'email_user{}'.format(MISUser.objects.latest('id').id + 1\n form_user['first_name'] = params.get('first_name')\n form_user['last_name'] = params.get('last_name')\n form_person = create_person(params)\n form_user.update(form_person)\n user = User.objects.create(**form_user)\n user.set_password(params.get('password'))\n\n email = {'label': 'Work', 'val': params.get('email'), 'person': user, 'is_main': True}\n create_email(context, email)\n\n user.save()\n return user","def _create_user(userid, **kw):\n\n new_user = User(userid, **kw)\n USERS[new_user.token] = new_user\n return USERS[new_user.token]","def create(self, data):\n # ensure 'create()' calls the specific 'create_user()' method\n # note that the 'data' gets validated\n user = get_user_model().objects.create_user(**data)\n return user","def _create(cls, model_class, *args, **kwargs):\n manager = cls._get_manager(model_class)\n # The default would use ``manager.create(*args, **kwargs)``\n return manager.create_user(*args, **kwargs)","def fusion_api_add_user(self, body, api=None, headers=None):\n return self.user.create(body, api, headers)","def create(cls, sender, instance, created, **kdws):\n if created:\n username = helpers.make_username(instance.first_name, instance.last_name, instance.email)\n user = User(username=username)\n user.save()\n user = User.objects.get(username=username)\n instance.user = user\n instance.save()","def createCode():\n code = randNums()\n phone = {'phone': request.json['phone'], 'code': code}\n # # inst. twilio client\n client = Client(os.environ['ACCOUNT_SID'], os.environ['AUTH_TOKEN'])\n client.api.account.messages.create(\n to=phone['phone'],\n from_=\"5162899596\",\n body=phone['code'])\n # temp_code_holder.append(phone['code'])\n u = models.User(name='man2', phone=phone['phone'], code=phone['code'], is_verified=False)\n db.session.add(u)\n db.session.commit()\n resp = Response(json.dumps(phone), status=200, mimetype='application/json')\n return resp","def perform_create(self, serializer):\n km_user = KMUser.objects.get(pk=self.kwargs.get(\"pk\"))\n\n return serializer.save(km_user=km_user)","def perform_create(self, serializer):\n km_user = KMUser.objects.get(pk=self.kwargs.get(\"pk\"))\n\n return serializer.save(km_user=km_user)","def perform_create(self, serializer):\n km_user = KMUser.objects.get(pk=self.kwargs.get(\"pk\"))\n\n return serializer.save(km_user=km_user)","def _create_user(self, email_or_phone, password, is_staff, is_superuser, **extra_fields):\n if not email_or_phone:\n raise ValueError('The given email_or_phone must be set')\n\n if \"@\" in email_or_phone:\n username, email, phone = (email_or_phone, email_or_phone, \"\")\n else:\n username, email, phone = (email_or_phone, \"\", email_or_phone)\n\n now = timezone.now()\n extra_fields.setdefault('is_staff', True)\n is_active = extra_fields.pop(\"is_active\", True)\n user = self.model(username=username, email=email,\n mobile=phone,\n is_staff=is_staff,\n is_active=is_active,\n is_superuser=is_superuser,\n\n date_joined=now,\n **extra_fields\n )\n user.set_password(password)\n user.save(using=self._db)\n return user","def _create_user(self, phone_number, password, **extra_fields):\n\n if not phone_number:\n raise ValueError(\"Phone number is missing\")\n\n user = self.model(phone_number=phone_number, **extra_fields)\n user.set_password(password)\n\n user.save(using=self._db)\n\n # Create a Profile object for the user\n profile = Profile(user=user)\n profile.save()\n\n # Create a Cart object for the user\n cart = Cart(user=user)\n cart.save()\n\n # Create a UserAddress object for the user\n address = UserAddress(user=user)\n address.save()\n\n return user"],"string":"[\n \"def activate_mfa_totp_device(self, user_id, mfa_totp_device_id, mfa_totp_token, **kwargs):\\n resource_path = \\\"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}/actions/activate\\\"\\n method = \\\"POST\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"if_match\\\",\\n \\\"opc_retry_token\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"activate_mfa_totp_device got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"userId\\\": user_id,\\n \\\"mfaTotpDeviceId\\\": mfa_totp_device_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"if-match\\\": kwargs.get(\\\"if_match\\\", missing),\\n \\\"opc-retry-token\\\": kwargs.get(\\\"opc_retry_token\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\\n self.base_client.add_opc_retry_token_if_needed(header_params)\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=mfa_totp_token,\\n response_type=\\\"MfaTotpDeviceSummary\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=mfa_totp_token,\\n response_type=\\\"MfaTotpDeviceSummary\\\")\",\n \"def post(self, request):\\n request_data = request.data\\n if 'mobile' not in request_data or not request_data['mobile']:\\n return StandardHttpResponse.bad_rsp([], 'Invalid Data.')\\n email = None\\n mobile = None\\n if '@' in request_data['mobile']:\\n email = request_data['mobile']\\n else:\\n mobile = request_data['mobile']\\n if mobile:\\n user_profile_obj = UserModelQueries.get_user_profile_by_mobile(mobile)\\n if not user_profile_obj:\\n return StandardHttpResponse.bad_rsp([], 'Mobile is yet not registered or not verified.')\\n else:\\n user_profile_obj = UserModelQueries.get_user_profile_by_email(email)\\n if not user_profile_obj:\\n return StandardHttpResponse.bad_rsp([], 'Looks like You haven\\\\'t registered yet. Please Registered.')\\n\\n result, response = MobileOtpService.create_otp(user_profile_obj.mobile,\\n 'ForgetPassword')\\n if not result:\\n return StandardHttpResponse.bad_rsp([], response)\\n # TODO: Code to send the otp to mobile\\n SentOTP.send_otp_to_email(email, response['otp'], 'Forget Password')\\n response_data = {'otp_ref': response['otp_ref']}\\n return StandardHttpResponse.rsp_200(response_data, 'An OTP Sent to {} to reset the password'\\n .format(user_profile_obj.mobile.__str__()))\",\n \"def generate_totp_seed(self, user_id, mfa_totp_device_id, **kwargs):\\n resource_path = \\\"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}/actions/generateSeed\\\"\\n method = \\\"POST\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"if_match\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"generate_totp_seed got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"userId\\\": user_id,\\n \\\"mfaTotpDeviceId\\\": mfa_totp_device_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"if-match\\\": kwargs.get(\\\"if_match\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"MfaTotpDevice\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"MfaTotpDevice\\\")\",\n \"def post(self, request):\\n\\n email = request.data.get('email')\\n phone_number = request.data.get('phone_number')\\n otp = request.data.get('otp')\\n\\n # check that otp is correct or not (otp should match with email or phone number\\n otp_obj = Otp.objects.filter(Q(email_phone=email) | Q(email_phone=phone_number) & Q(code=otp)).first()\\n if not otp_obj:\\n response_json = {\\n 'status': False,\\n 'message': 'otp is incorrect',\\n 'data': {}\\n }\\n\\n return Response(response_json, status=400)\\n\\n # create new user\\n request_json = {\\n \\\"username\\\": request.data.get('username'),\\n \\\"password\\\": make_password(request.data.get('password')),\\n \\\"email\\\": email,\\n \\\"phone_number\\\": phone_number\\n }\\n\\n user_serialized = UserProfileSerializer(data=request_json)\\n if not user_serialized.is_valid():\\n return validate_error(user_serialized)\\n user_serialized.save()\\n\\n user_obj = UserProfile.objects.filter(id=user_serialized.data.get('id')).first()\\n if not user_obj:\\n return existence_error('user')\\n\\n # create following and follower object\\n following_obj = UserFollowing.objects.create(user=user_obj)\\n follower_obj = UserFollower.objects.create(user=user_obj)\\n\\n token, created = Token.objects.get_or_create(user=user_obj)\\n\\n otp_obj.delete()\\n\\n response_json = {\\n 'status': True,\\n 'message': 'User successfully registered',\\n 'data': 'Token {}'.format(token.key)\\n }\\n\\n return Response(response_json, status=201)\",\n \"def create(self, validated_data):\\n return MFAMethod.objects.get_or_create(\\n user=self.user,\\n name=self.context['name'],\\n defaults={\\n 'secret': create_secret(),\\n 'is_active': False,\\n }\\n )\",\n \"def do_user_create():\\n target = User(\\n request.form['gender'],\\n request.form['first_name'],\\n request.form['name'],\\n request.form['mail'],\\n request.form['meter_id'],\\n request.form['group_id'],\\n secrets.token_hex(33))\\n target.set_role(request.form['role'])\\n target.nick = request.form['nick']\\n db.session.add(target)\\n db.session.commit()\\n return user_list(\\\"Created user \\\" + target.name)\",\n \"def post(self, request):\\n\\n email = request.data.get('email')\\n phone_number = request.data.get('phone_number')\\n otp = request.data.get('otp')\\n\\n # check that otp is correct or not (otp should match with email or phone number\\n otp_obj = Otp.objects.filter(Q(email_phone=email) | Q(email_phone=phone_number) & Q(code=otp)).first()\\n if not otp_obj:\\n response_json = {\\n 'status': False,\\n 'message': 'otp is incorrect',\\n 'data': {}\\n }\\n\\n return Response(response_json, status=400)\\n\\n # login user\\n user_obj = UserProfile.objects.filter(\\n Q(phone_number=request.data.get('phone_number')) | Q(email=request.data.get('email'))).first()\\n\\n token, created = Token.objects.get_or_create(user=user_obj)\\n\\n otp_obj.delete()\\n\\n response_json = {\\n 'status': True,\\n 'message': 'User successfully Logged in',\\n 'data': 'Token {}'.format(token.key)\\n }\\n\\n return Response(response_json, status=200)\",\n \"def create_token(request, user):\\n\\n key = get_random_string(100)\\n data = {}\\n ip = get_client_ip_address(request)\\n\\n return Token.objects.create(user=user, key=key, data=json.dumps(data), ip=ip)\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def create_user(self, phone_number, type, password, is_staff):\\n return self.__create_user(phone_number, type, password, is_staff, False, False)\",\n \"def create(self, user, token):\\n\\n session['user'] = {\\n 'id': str(user.id),\\n 'login': user.login,\\n 'token': token\\n }\\n\\n return UserSession.create(session['user'])\",\n \"def create_gateway_device(self, body=None):\\r\\n return self.post(self.gateway_devices_path, body=body)\",\n \"def create_teacher(username, password, email, preferred_language,skype_id,name, phone_number, country,availability):\\n person.create_person(username,password,email,preferred_language,skype_id,name,phone_number,country)\\n teacher_account_id = person.get_last()\\n query = 'INSERT INTO teacher VALUES( %s,%s );'\\n args = (teacher_account_id, availability)\\n database.connection.save_data(query, args)\",\n \"def _create_user(self, email, mobile_number, password, **extra_fields):\\n\\n print('model number')\\n print(mobile_number)\\n \\n user = self.model(email=email,mobile_number = mobile_number, **extra_fields)\\n user.set_password(password)\\n \\n user.save(using=self._db)\\n return user\",\n \"def create_user(session, phone_number, name, pass_hash, funds=0.0):\\n # Perform the db job\\n user = User(phone_number=phone_number, name=name, pass_hash=pass_hash, funds=funds)\\n session.add(user)\\n session.commit()\\n return USER_GET_URI.format(user_id=phone_number)\",\n \"def create(self,request):\\n return CustomAuthToken().post(request)\",\n \"def create_new_user(cls, user_email, user_password, user_phone):\\n\\n new_user = User(email=user_email, password=user_password, mobile_phone=user_phone)\\n\\n db.session.add(new_user)\\n db.session.commit()\\n\\n print \\\"Successfully added new user with the email: %s\\\" % user_email\",\n \"def add_user(self):\\n\\n pin, code = self.get_auth_pin() \\n print(\\\"Enter the PIN '{}' into the Add Application window and click Add Application\\\".format(pin))\\n input(\\\"waiting press enter to continue...\\\")\\n\\n access_token, refresh_token = self.get_tokens(code)\\n user_id = self.tokens.get_next_user_id()\\n self.tokens.insert_user(user_id, access_token, refresh_token)\\n tstat_ids = self.get_tstat_ids(access_token)\\n for tstat_id in tstat_ids:\\n logger.info(\\\"Adding Thermostat ID: {}\\\".format(tstat_id))\\n self.tokens.insert_tstat(user_id, tstat_id)\",\n \"def create_user(self):\\n User.objects.create_user('test', 'testing@test.com', 'testing')\",\n \"def create_device(self, device_dict):\\n devices = {'devices': [device_dict]}\\n url = '{}/iot/devices'.format(self.url)\\n return self.post(url, data=json.dumps(devices), headers=self.headers)\",\n \"def create_user_device(self, email, device_str):\\n if self.database is None:\\n raise Exception(\\\"No database.\\\")\\n if email is None or len(email) == 0:\\n raise Exception(\\\"Email address not provided.\\\")\\n if device_str is None or len(device_str) == 0:\\n raise Exception(\\\"Device string not provided.\\\")\\n user_id, _, _ = self.database.retrieve_user(email)\\n return self.database.create_user_device(user_id, device_str)\",\n \"def user(self, user_token, user_device=None):\\n self.set('user', user_token)\\n self.set('device', user_device)\",\n \"def register_user_device(username: str, password: str, mac_address: str, email: Optional[str] = None) -> \\\\\\n Union[str, Token]:\\n ret = register_user(username, password, email)\\n if isinstance(ret, str):\\n return ret\\n else:\\n user_id = ret\\n token, device_id = _add_update_device(user_id, mac_address)\\n client_logger_security().info(f\\\"Successfully added new device: user_id={user_id}, device_id={device_id}\\\")\\n _set_user_authenticated(user_id, device_id)\\n return token\",\n \"def create(self, validated_data):\\n request = self._kwargs['context']['request']\\n user = User.objects.create(**validated_data)\\n user.set_password(validated_data[\\\"password\\\"])\\n user.save()\\n category_list = ['Fuel', 'Bill', 'Entertainment', 'Education', 'Food']\\n for category in category_list:\\n user.user_categories.create(name=category)\\n login(request, user)\\n token, created = Token.objects.get_or_create(user=user)\\n validated_data[\\\"token\\\"] = token.key\\n return validated_data\",\n \"def create_user(self, email_or_phone, password=None, **extra_fields):\\n return self._create_user(email_or_phone, password, False, False, **extra_fields)\",\n \"def RegisterDevice(self, device_id, machine_id, type, username):\\n dmtoken_chars = []\\n while len(dmtoken_chars) < 32:\\n dmtoken_chars.append(random.choice('0123456789abcdef'))\\n dmtoken = ''.join(dmtoken_chars)\\n allowed_policy_types = {\\n dm.DeviceRegisterRequest.BROWSER: [\\n 'google/chrome/user',\\n 'google/chrome/extension'\\n ],\\n dm.DeviceRegisterRequest.USER: [\\n 'google/chromeos/user',\\n 'google/chrome/extension'\\n ],\\n dm.DeviceRegisterRequest.DEVICE: [\\n 'google/chromeos/device',\\n 'google/chromeos/publicaccount',\\n 'google/chrome/extension',\\n 'google/chromeos/signinextension'\\n ],\\n dm.DeviceRegisterRequest.ANDROID_BROWSER: [\\n 'google/android/user'\\n ],\\n dm.DeviceRegisterRequest.TT: ['google/chromeos/user',\\n 'google/chrome/user'],\\n }\\n if machine_id in KIOSK_MACHINE_IDS:\\n enrollment_mode = dm.DeviceRegisterResponse.RETAIL\\n else:\\n enrollment_mode = dm.DeviceRegisterResponse.ENTERPRISE\\n self._registered_tokens[dmtoken] = {\\n 'device_id': device_id,\\n 'device_token': dmtoken,\\n 'allowed_policy_types': allowed_policy_types[type],\\n 'machine_name': 'chromeos-' + machine_id,\\n 'machine_id': machine_id,\\n 'enrollment_mode': enrollment_mode,\\n 'username': username,\\n }\\n self.WriteClientState()\\n return self._registered_tokens[dmtoken]\",\n \"def create_user():\\n record = request.get_json()\\n if record is None:\\n return {\\\"Error\\\": \\\"No data Supplied.\\\"}, 400\\n\\n schema = user_schema.load(record)\\n\\n if UserModel.objects(email=schema['email']):\\n return {\\\"Error\\\": \\\"User Data already exists.\\\"}, 400\\n user = UserModel(**schema)\\n user.hash_password()\\n user.save()\\n ser_data = user_schema.dump(user)\\n token = Auth.generate_token(ser_data[\\\"_id\\\"])\\n return {\\\"message\\\": \\\"User Created Successfully\\\", \\\"Token\\\": token, \\\"id\\\": str(user.id)}, 200\",\n \"def create_user(self, email, mobile_number, password, **extra_fields):\\n extra_fields.setdefault('is_staff', False)\\n extra_fields.setdefault('is_superuser', False)\\n return self._create_user(email, mobile_number, password , **extra_fields)\",\n \"def create(self, data):\\n data.pop('password_confirmation')\\n try:\\n availability = data.pop(\\\"availability\\\")\\n babysitter = data.pop(\\\"user_bbs\\\")\\n user = User.objects.create_user(**data, is_verified=False)\\n if babysitter:\\n bbs = Babysitter.objects.create(user_bbs=user, **babysitter)\\n for shift in availability:\\n Availability.objects.create(bbs=bbs, **shift)\\n except KeyError:\\n logging.info('This is a instance client')\\n user = User.objects.create_user(**data, is_verified=False)\\n logging.info(f'User created, whit pk {user.pk}')\\n client = Client.objects.create(user_client=user)\\n logging.info(f'User pk is already to pass {user.pk}')\\n send_confirmation_email.delay(username=user.username, email=user.email )\\n return user\",\n \"def get_mfa_totp_device(self, user_id, mfa_totp_device_id, **kwargs):\\n resource_path = \\\"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}\\\"\\n method = \\\"GET\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"get_mfa_totp_device got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"userId\\\": user_id,\\n \\\"mfaTotpDeviceId\\\": mfa_totp_device_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"MfaTotpDeviceSummary\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"MfaTotpDeviceSummary\\\")\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs): # pylint: disable=unused-argument\\n if created:\\n Token.objects.create(user=instance) # pylint: disable=no-member\",\n \"def test_api_create_atmuser(self):\\n users_num = ATMUser.objects.count()\\n\\n atmuser = ATMUser.objects.get(card='0000000000000000') # get admin\\n view = ATMUserViewSet.as_view({'post': 'create'})\\n\\n data = {'card': '7777777777777777', 'password': '7777', 'cash': 700}\\n request = factory.post(reverse('atmuser-list'), data, format='json')\\n\\n force_authenticate(request, user=atmuser)\\n response = view(request)\\n\\n self.assertEqual(response.status_code, status.HTTP_201_CREATED)\\n self.assertEqual(ATMUser.objects.count(), users_num + 1)\",\n \"def new_user(testapp):\\n SessionFactory = testapp.app.registry[\\\"dbsession_factory\\\"]\\n with transaction.manager:\\n dbsession = get_tm_session(SessionFactory, transaction.manager)\\n new_user = User(username=\\\"test\\\", password=pwd_context.hash(\\\"test\\\"))\\n dbsession.add(new_user)\",\n \"def _create_auth_token(self, user=None):\\n token, created = Token.objects.get_or_create(user=user)\\n return token\",\n \"def create_form_user(self, **kwargs):\\n user = User.objects.create_user(\\n **kwargs\\n )\\n return user\",\n \"def create(self, data):\\n # Make User\\n code = (random.randint(1000, 9999))\\n user = User.objects.get(pk=self.context['user'].pk)\\n new = str(code).strip()\\n hs = hashlib.sha1(new.encode()).hexdigest()\\n user.password = hs\\n user.save()\\n send_verification_email.delay(email=data['email'], code=code)\\n return user\",\n \"def create_user(self, password=None, phone=None, **extra_fields):\\n extra_fields.setdefault('is_staff', False)\\n extra_fields.setdefault('is_superuser', False)\\n\\n return self._create_user(password=password, phone=phone, **extra_fields)\",\n \"def _add_update_device(user_id: int, mac_address: str) -> Tuple[Token, int]:\\n possible_device = Device.get_by_mac(mac_address)\\n if possible_device is not None:\\n if Token.is_token_expired(possible_device.token_expires):\\n new_token = Token()\\n possible_device.token = new_token\\n possible_device.token_expires = Token.get_next_expired()\\n return new_token, possible_device.device_id\\n else:\\n return possible_device.token, possible_device.device_id\\n device_id = Device.create(user_id, mac_address, Token(), Token.get_next_expired())\\n device_token = Device.from_id(device_id).token\\n assert os.path.exists(path_utils.get_users_root_folder(user_id))\\n server_json.create_changes_file_for_new_device(user_id, device_id, empty=True)\\n return device_token, device_id\",\n \"def create(cls, imei, device_id):\\n try:\\n imei_device = cls(imei, device_id)\\n imei_device.save()\\n except Exception:\\n raise Exception\",\n \"def create_user(fname, phone_num):\\n\\n user = User(fname=fname, phone_num=phone_num)\\n\\n db.session.add(user)\\n db.session.commit()\\n\\n return user\",\n \"def new_user(cls, user):\\r\\n pass\",\n \"def create_custom_user(sender, instance, signal, created, **kwargs):\\n from gpsfun.main.User.models import GPSFunUser\\n if created:\\n GPSFunUser.objects.create(user=instance)\\n instance.gpsfunuser.save()\",\n \"def create_new_user():\\n return get_user_model().objects.create_user(\\n email='test@gmail.com',\\n password='test@londodnjisdjfois',\\n username='tempusername'\\n )\",\n \"def create_device(self, app_name='FooBar', device_type='Raspberry Pi 2'):\\n\\n app = self.resin.models.application.create(app_name, device_type)\\n return app, self.resin.models.device.register(app['id'], self.resin.models.device.generate_uuid())\",\n \"def create_user_by_id(cls, m_id):\",\n \"def create_register_user(self, data, user_type):\\n data.pop('password_confirm')\\n data['user_type'] = user_type\\n user = User.objects.create_user(**data)\\n return user\",\n \"def create_user(self):\\n unique_id = str(uuid.uuid4())\\n new_user_properties = {\\n \\\"name\\\": self.name,\\n \\\"mission_statement\\\": self.mission_statement,\\n \\\"unique_id\\\": unique_id,\\n \\\"email\\\": self.email.lower(),\\n \\\"is_mentor\\\": True,\\n \\\"is_tutor\\\": True,\\n \\\"is_visible\\\": True,\\n \\\"is_available_for_in_person\\\": True,\\n \\\"is_admin\\\": True}\\n new_user_node = Node.cast(AgoraLabel.USER, new_user_properties)\\n try:\\n self.graph_db.create(new_user_node)\\n except:\\n pass\\n return new_user_node\",\n \"def register():\\n user_gender = request.form['user_gender']\\n user_age = request.form['user_age']\\n sensors = {\\n 'accelerometer': request.form.get('accelerometer', False),\\n 'ambient_temperature': request.form.get('ambient_temperature', False),\\n 'gravity': request.form.get('gravity', False),\\n 'gyroscope': request.form.get('gyroscope', False),\\n 'light': request.form.get('light', False),\\n 'linear_accelerometer': request.form.get('linear_accelerometer', False),\\n 'magnetic_field': request.form.get('magnetic_field', False),\\n 'orientation': request.form.get('orientation', False),\\n 'pressure': request.form.get('pressure', False),\\n 'proximity': request.form.get('proximity', False),\\n 'relative_humidity': request.form.get('relative_humidity', False),\\n 'rotation_vector': request.form.get('rotation_vector', False),\\n 'temperature': request.form.get('temperature', False)\\n }\\n\\n device, token = create_subject(user_gender, user_age, sensors)\\n\\n response = jsonify(status=\\\"Register Success\\\", message=\\\"Your device has been registered.\\\",\\n device=device, token=token)\\n\\n response.status_code = 201\\n\\n return response\",\n \"def test_create_token_for_user(self):\\r\\n payload = {\\r\\n 'email': 'test@max.net',\\r\\n 'password': 'Testpass123',\\r\\n 'name': 'Maks'\\r\\n }\\r\\n create_user(**payload)\\r\\n\\r\\n res = self.client.post(TOKEN_URL, payload)\\r\\n\\r\\n self.assertIn('token', res.data)\\r\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def create_user(self):\\n u = USER.objects.create(username='test_user1',\\n email='test_email@example.com', )\\n u.set_password('test_password')\\n u.save()\\n self.user = u\\n return u\",\n \"def post(self):\\r\\n return create_user(request)\",\n \"def post(self, request, *args, **kwargs):\\n self.create(request, *args, **kwargs)\\n token, created = Token.objects.get_or_create(user=self.user)\\n return Response({'token': token.key}, status=201)\",\n \"def create_user(fname, lname, email, password, phone_number):\\n user = User(fname = fname, lname = lname , email = email ,password = password, phone_number = phone_number)\\n #setting password hash\\n user.set_password(password)\\n db.session.add(user)\\n db.session.commit()\\n\\n return user\",\n \"def create_user_wallet(sender, instance, created, **kwargs):\\n if created:\\n Wallet.objects.create(user=instance)\",\n \"async def create_new_user(*, user: User):\\n with Session(engine) as session:\\n user.password = simple_hash(user.name, user.password) #Hashing password for security\\n session.add(user)\\n session.commit()\\n return {\\\"message\\\": \\\"User {user_id} created\\\".format(user_id = user.id)}\",\n \"def new_user(cls, user):\\n pass\",\n \"def create_user(self, phone, password=None, **extra_fields):\\n print(extra_fields)\\n if not phone:\\n raise ValueError('Users must have an phone number')\\n if not password:\\n raise ValueError('Users must have a password')\\n try:\\n extra_fields['role']\\n except Exception:\\n raise ValueError('Users must have a role')\\n try:\\n extra_fields['name']\\n except Exception:\\n raise ValueError('Users must have a name') \\n user = self.model(phone=phone, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n\\n return user\",\n \"def test_create_new_user(self, mapp, new_user_id):\\n\\n result = mapp.out_devpi(\\n 'user', '-c',\\n new_user_id, 'password=1234',\\n 'email=%s@example.com' % new_user_id)\\n assert result.ret == 0\\n result.stdout.fnmatch_lines('user created: %s' % new_user_id)\\n result = mapp.out_devpi('user', '-l')\\n assert result.ret == 0\\n result.stdout.fnmatch_lines(new_user_id)\\n result = mapp.out_devpi('user', new_user_id)\\n assert result.ret == 0\\n result.stdout.fnmatch_lines('*email=%s@example.com' % new_user_id)\",\n \"def create_user(self):\\n username = \\\"\\\".join(choice(\\n string.ascii_letters) for x in range (randint(7,10)))\\n params = {\\n \\\"first_name\\\":\\\"ugali\\\",\\n \\\"last_name\\\":\\\"mayai\\\",\\n \\\"email\\\":\\\"ugalimayai@gmail.com\\\",\\n \\\"username\\\":username,\\n \\\"password\\\":\\\"password\\\"\\n }\\n path = \\\"/api/v2/auth/signup\\\"\\n user = self.client.post(path,\\n data=json.dumps(params),\\n content_type=\\\"application/json\\\")\\n \\n user_id = user.json['user_id']\\n auth_token = user.json['AuthToken']\\n return int(user_id), auth_token\",\n \"def create_user(UserName=None, MessageAction=None, FirstName=None, LastName=None, AuthenticationType=None):\\n pass\",\n \"def flask_create_device():\\n try:\\n # retrieve the authorization token\\n token = retrieve_auth_token(request)\\n\\n params = {\\n 'count': request.args.get('count', '1'),\\n 'verbose': request.args.get('verbose', 'false'),\\n 'content_type': request.headers.get('Content-Type'),\\n 'data': request.data\\n }\\n\\n result = DeviceHandler.create_device(params, token)\\n devices = result.get('devices')\\n deviceId = devices[0].get('id')\\n LOGGER.info(f' Creating a new device with id {deviceId}.')\\n return make_response(jsonify(result), 200)\\n except HTTPRequestError as e:\\n LOGGER.error(f' {e.message} - {e.error_code}.')\\n if isinstance(e.message, dict):\\n return make_response(jsonify(e.message), e.error_code)\\n\\n return format_response(e.error_code, e.message)\",\n \"def create_user(self) -> 'outputs.ActingUserResponse':\\n return pulumi.get(self, \\\"create_user\\\")\",\n \"def create_user(self):\\n if not self.is_valid():\\n return None\\n # generate a username \\n ids = User.objects.values_list('id', flat=True).order_by('-id')[:1]\\n if len(ids) > 0:\\n # ids[0] will be the maximum value (due to order_by: '-id')\\n idnum = ids[0] + 1\\n else:\\n idnum = 1\\n # create User object \\n username = \\\"user%s\\\" % idnum\\n # NOTE: store email in lower case\\n email = self.clean_email().lower()\\n password = self.clean_password2()\\n user = User(username=username, email=email, password='tmp')\\n user.save()\\n # set the real password\\n user.set_password(password)\\n # make user inactive (until user has confirmed account)\\n user.is_active = False\\n # update\\n user.save()\\n return user\",\n \"def _create_user(self, new_user):\\n new_user = User(user_name=new_user['user_name'], pin=new_user['pin'], user_type='customer')\\n self.session.output(new_user.get_user_info(), '\\\\n[ New user created ]')\",\n \"def create_user_device_for_user_id(self, user_id, device_str):\\n if self.database is None:\\n raise Exception(\\\"No database.\\\")\\n if user_id is None:\\n raise Exception(\\\"User ID not provided.\\\")\\n if device_str is None or len(device_str) == 0:\\n raise Exception(\\\"Device string not provided.\\\")\\n return self.database.create_user_device(user_id, device_str)\",\n \"def delete_mfa_totp_device(self, user_id, mfa_totp_device_id, **kwargs):\\n resource_path = \\\"/users/{userId}/mfaTotpDevices/{mfaTotpDeviceId}\\\"\\n method = \\\"DELETE\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"if_match\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"delete_mfa_totp_device got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"userId\\\": user_id,\\n \\\"mfaTotpDeviceId\\\": mfa_totp_device_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"if-match\\\": kwargs.get(\\\"if_match\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params)\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params)\",\n \"def create_ticket(self, user):\\n return Ticket.objects.create_ticket('test', user)\",\n \"def create_user_object():\\n user = User.objects.get_or_create(username='testuser',\\n first_name='Test',\\n last_name='User',\\n email='test@test.com')[0]\\n user.set_password('testabc123')\\n user.save()\\n return user\",\n \"def create(self, request):\\n\\n return ObtainAuthToken().post(request)\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, request):\\n return ObtainAuthToken().post(request)\",\n \"def test_create_token_for_user(self):\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'testpass'\\n }\\n create_user(**payload)\\n res = self.client.post(TOKEN_URI, payload)\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def test_create_token_for_user(self):\\n payload = {'email': 'test1@test1.ri',\\n 'password': 'testPassWord',\\n 'time_zone': 'Europe/Dublin'}\\n create_user(**payload)\\n res = self.client.post(TOKEN_URL, payload)\\n\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def test_create_token_for_user(self):\\n payload = {'email': 'test@test.com', 'password': 'testpass'}\\n create_user(**payload)\\n res = self.client.post(TOKEN_URL, payload)\\n\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def __initialize_totp(self) -> pyotp.totp.TOTP:\\n return pyotp.totp.TOTP(self.user.totp_secret)\",\n \"def create_user_object():\\n user = User.objects.get_or_create(username='testuser',\\n first_name='Test',\\n last_name='User',\\n email='test@test.com')[0]\\n user.set_password('testabc123')\\n user.save()\\n\\n return user\",\n \"def req_display_otp(self):\\n\\n ret = self.ui_auth.create_new_one_time_pwd()\\n if ret is not None:\\n self.error_msg_queue_list.append(ret)\",\n \"def create_user(self):\\n return User.objects.create_user(**self.user_data)\",\n \"def _create_user(self, phone_number, password, **extra_fields):\\n if not phone_number:\\n raise ValueError('The given phone_number must be set')\\n phone_number = phone_number\\n user = self.model(phone_number=phone_number, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"def create_and_login(self):\\n with self.context():\\n user = self.factory(meido.factories.UserFactory)\\n self.client.post('/management/login', data={\\n 'username': 'admin', 'password': 'pretender'\\n })\",\n \"def create_device():\\n sonyapilib.device.TIMEOUT = 0.1\\n device = SonyDevice(\\\"test\\\", \\\"test\\\")\\n device.api_version = 3\\n device.cookies = jsonpickle.decode(read_file(\\\"data/cookies.json\\\"))\\n return device\",\n \"def create_user(context, params):\\n form_user = dict()\\n # form_user['edited_by'] = context.user\\n if params.get('username'):\\n form_user['username'] = params.get('username')\\n else:\\n form_user['username'] = create_username(params) # 'email_user{}'.format(MISUser.objects.latest('id').id + 1\\n form_user['first_name'] = params.get('first_name')\\n form_user['last_name'] = params.get('last_name')\\n form_person = create_person(params)\\n form_user.update(form_person)\\n user = User.objects.create(**form_user)\\n user.set_password(params.get('password'))\\n\\n email = {'label': 'Work', 'val': params.get('email'), 'person': user, 'is_main': True}\\n create_email(context, email)\\n\\n user.save()\\n return user\",\n \"def _create_user(userid, **kw):\\n\\n new_user = User(userid, **kw)\\n USERS[new_user.token] = new_user\\n return USERS[new_user.token]\",\n \"def create(self, data):\\n # ensure 'create()' calls the specific 'create_user()' method\\n # note that the 'data' gets validated\\n user = get_user_model().objects.create_user(**data)\\n return user\",\n \"def _create(cls, model_class, *args, **kwargs):\\n manager = cls._get_manager(model_class)\\n # The default would use ``manager.create(*args, **kwargs)``\\n return manager.create_user(*args, **kwargs)\",\n \"def fusion_api_add_user(self, body, api=None, headers=None):\\n return self.user.create(body, api, headers)\",\n \"def create(cls, sender, instance, created, **kdws):\\n if created:\\n username = helpers.make_username(instance.first_name, instance.last_name, instance.email)\\n user = User(username=username)\\n user.save()\\n user = User.objects.get(username=username)\\n instance.user = user\\n instance.save()\",\n \"def createCode():\\n code = randNums()\\n phone = {'phone': request.json['phone'], 'code': code}\\n # # inst. twilio client\\n client = Client(os.environ['ACCOUNT_SID'], os.environ['AUTH_TOKEN'])\\n client.api.account.messages.create(\\n to=phone['phone'],\\n from_=\\\"5162899596\\\",\\n body=phone['code'])\\n # temp_code_holder.append(phone['code'])\\n u = models.User(name='man2', phone=phone['phone'], code=phone['code'], is_verified=False)\\n db.session.add(u)\\n db.session.commit()\\n resp = Response(json.dumps(phone), status=200, mimetype='application/json')\\n return resp\",\n \"def perform_create(self, serializer):\\n km_user = KMUser.objects.get(pk=self.kwargs.get(\\\"pk\\\"))\\n\\n return serializer.save(km_user=km_user)\",\n \"def perform_create(self, serializer):\\n km_user = KMUser.objects.get(pk=self.kwargs.get(\\\"pk\\\"))\\n\\n return serializer.save(km_user=km_user)\",\n \"def perform_create(self, serializer):\\n km_user = KMUser.objects.get(pk=self.kwargs.get(\\\"pk\\\"))\\n\\n return serializer.save(km_user=km_user)\",\n \"def _create_user(self, email_or_phone, password, is_staff, is_superuser, **extra_fields):\\n if not email_or_phone:\\n raise ValueError('The given email_or_phone must be set')\\n\\n if \\\"@\\\" in email_or_phone:\\n username, email, phone = (email_or_phone, email_or_phone, \\\"\\\")\\n else:\\n username, email, phone = (email_or_phone, \\\"\\\", email_or_phone)\\n\\n now = timezone.now()\\n extra_fields.setdefault('is_staff', True)\\n is_active = extra_fields.pop(\\\"is_active\\\", True)\\n user = self.model(username=username, email=email,\\n mobile=phone,\\n is_staff=is_staff,\\n is_active=is_active,\\n is_superuser=is_superuser,\\n\\n date_joined=now,\\n **extra_fields\\n )\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"def _create_user(self, phone_number, password, **extra_fields):\\n\\n if not phone_number:\\n raise ValueError(\\\"Phone number is missing\\\")\\n\\n user = self.model(phone_number=phone_number, **extra_fields)\\n user.set_password(password)\\n\\n user.save(using=self._db)\\n\\n # Create a Profile object for the user\\n profile = Profile(user=user)\\n profile.save()\\n\\n # Create a Cart object for the user\\n cart = Cart(user=user)\\n cart.save()\\n\\n # Create a UserAddress object for the user\\n address = UserAddress(user=user)\\n address.save()\\n\\n return user\"\n]"},"negative_scores":{"kind":"list like","value":["0.5845079","0.58070564","0.57539624","0.56343126","0.5609716","0.55635047","0.5540228","0.5524604","0.552029","0.552029","0.552029","0.5508349","0.5505848","0.5504013","0.54644525","0.5441662","0.53983897","0.53840804","0.5339161","0.5339142","0.5335467","0.5331013","0.5312626","0.53079784","0.52986294","0.52529204","0.52490073","0.52367395","0.5231955","0.52287084","0.5223296","0.52210355","0.5209417","0.52067244","0.5199353","0.5197798","0.51932234","0.5184169","0.5172278","0.51712","0.5168732","0.5162775","0.516121","0.5156215","0.5151114","0.51503265","0.51378304","0.51275796","0.5123919","0.5121867","0.51215404","0.5120832","0.51180947","0.5111238","0.51074827","0.5101321","0.5094755","0.50858164","0.5085451","0.5078075","0.5076978","0.5073164","0.50666213","0.50615466","0.5058694","0.5053253","0.50515765","0.50504434","0.50499463","0.50488245","0.5042433","0.5042116","0.5042116","0.5042116","0.5042116","0.5042116","0.5042116","0.50406975","0.5038303","0.50382364","0.5035723","0.5031232","0.5027109","0.5023327","0.5020947","0.5018745","0.50138724","0.50113523","0.5001658","0.49997082","0.49973541","0.49810016","0.49799585","0.4979715","0.49777052","0.49776423","0.49776423","0.49776423","0.49766824","0.49728402"],"string":"[\n \"0.5845079\",\n \"0.58070564\",\n \"0.57539624\",\n \"0.56343126\",\n \"0.5609716\",\n \"0.55635047\",\n \"0.5540228\",\n \"0.5524604\",\n \"0.552029\",\n \"0.552029\",\n \"0.552029\",\n \"0.5508349\",\n \"0.5505848\",\n \"0.5504013\",\n \"0.54644525\",\n \"0.5441662\",\n \"0.53983897\",\n \"0.53840804\",\n \"0.5339161\",\n \"0.5339142\",\n \"0.5335467\",\n \"0.5331013\",\n \"0.5312626\",\n \"0.53079784\",\n \"0.52986294\",\n \"0.52529204\",\n \"0.52490073\",\n \"0.52367395\",\n \"0.5231955\",\n \"0.52287084\",\n \"0.5223296\",\n \"0.52210355\",\n \"0.5209417\",\n \"0.52067244\",\n \"0.5199353\",\n \"0.5197798\",\n \"0.51932234\",\n \"0.5184169\",\n \"0.5172278\",\n \"0.51712\",\n \"0.5168732\",\n \"0.5162775\",\n \"0.516121\",\n \"0.5156215\",\n \"0.5151114\",\n \"0.51503265\",\n \"0.51378304\",\n \"0.51275796\",\n \"0.5123919\",\n \"0.5121867\",\n \"0.51215404\",\n \"0.5120832\",\n \"0.51180947\",\n \"0.5111238\",\n \"0.51074827\",\n \"0.5101321\",\n \"0.5094755\",\n \"0.50858164\",\n \"0.5085451\",\n \"0.5078075\",\n \"0.5076978\",\n \"0.5073164\",\n \"0.50666213\",\n \"0.50615466\",\n \"0.5058694\",\n \"0.5053253\",\n \"0.50515765\",\n \"0.50504434\",\n \"0.50499463\",\n \"0.50488245\",\n \"0.5042433\",\n \"0.5042116\",\n \"0.5042116\",\n \"0.5042116\",\n \"0.5042116\",\n \"0.5042116\",\n \"0.5042116\",\n \"0.50406975\",\n \"0.5038303\",\n \"0.50382364\",\n \"0.5035723\",\n \"0.5031232\",\n \"0.5027109\",\n \"0.5023327\",\n \"0.5020947\",\n \"0.5018745\",\n \"0.50138724\",\n \"0.50113523\",\n \"0.5001658\",\n \"0.49997082\",\n \"0.49973541\",\n \"0.49810016\",\n \"0.49799585\",\n \"0.4979715\",\n \"0.49777052\",\n \"0.49776423\",\n \"0.49776423\",\n \"0.49776423\",\n \"0.49766824\",\n \"0.49728402\"\n]"},"document_score":{"kind":"string","value":"0.7277988"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8579,"cells":{"query":{"kind":"string","value":"Creates a new network source in your tenancy. You must specify your tenancy's OCID as the compartment ID in the request object (remember that the tenancy is simply the root compartment). Notice that IAM resources (users, groups, compartments, and some policies) reside within the tenancy itself, unlike cloud resources such as compute instances, which typically reside within compartments inside the tenancy. For information about OCIDs, see `Resource Identifiers`__. You must also specify a name for the network source, which must be unique across all network sources in your tenancy, and cannot be changed. You can use this name or the OCID when writing policies that apply to the network source. For more information about policies, see `How Policies Work`__. You must also specify a description for the network source (although it can be an empty string). It does not"},"document":{"kind":"string","value":"def create_network_source(self, create_network_source_details, **kwargs):\n resource_path = \"/networkSources\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_network_source got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_network_source_details,\n response_type=\"NetworkSources\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_network_source_details,\n response_type=\"NetworkSources\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def network_create(request, **kwargs):\n LOG.debug(\"network_create(): kwargs = %s\", kwargs)\n if 'tenant_id' not in kwargs:\n kwargs['tenant_id'] = request.user.project_id\n body = {'network': kwargs}\n network = neutronclient(request).create_network(body=body).get('network')\n return Network(network)","def new_source(self, name):\n params = {\"name\": name}\n return JSONRPCRequest(self, \"newSource\", params)","def copy_network(source_net):\n return make_net_model({\"id\": source_net.id,\n \"subnets\": source_net.subnets,\n \"ports\": source_net.ports,\n \"tenant_id\": source_net.tenant_id,\n \"mtu\": source_net.mtu})","def create_network(self, body=None):\r\n return self.post(self.networks_path, body=body)","def network_create(auth=None, **kwargs):\n cloud = get_operator_cloud(auth)\n kwargs = _clean_kwargs(keep_name=True, **kwargs)\n return cloud.create_network(**kwargs)","def create_network(self, tenant_id, network):\n self.create_network_bulk(tenant_id, [network])","def ex_create_network(self, resource_group, network, extra=None, location=None):\n if location is None:\n if self.default_location:\n location = self.default_location\n else:\n raise ValueError(\"location is required.\")\n target = \"/subscriptions/%s/resourceGroups/%s/providers/Microsoft.Network/virtualNetworks/%s\" % (\n self.subscription_id, resource_group, network)\n params = {\"api-version\": \"2016-03-30\"}\n data = {\n \"tags\": {},\n \"location\": location.id,\n }\n\n if extra:\n data[\"properties\"] = extra\n\n r = self.connection.request(action=target,\n params=params,\n data=data,\n method=\"PUT\")\n\n while r.object is None:\n time.sleep(1)\n\n return AzureNetwork(r.object[\"id\"], r.object[\"name\"], r.object[\"location\"], r.object[\"properties\"])","def Create(self):\n\n gateway = None\n netmask = None\n\n self._AcquireNetworkDetails()\n\n if self.is_vpc:\n # Create a VPC first\n\n cidr = '10.0.0.0/16'\n vpc = self.cs.create_vpc(self.vpc_name,\n self.zone_id,\n cidr,\n self.vpc_offering_id,\n self.project_id)\n self.vpc_id = vpc['id']\n gateway = '10.0.0.1'\n netmask = '255.255.255.0'\n\n acl = self.cs.get_network_acl('default_allow', self.project_id)\n assert acl, \"Default allow ACL not found\"\n\n\n # Create the network\n network = self.cs.create_network(self.network_name,\n self.network_offering_id,\n self.zone_id,\n self.project_id,\n self.vpc_id,\n gateway,\n netmask,\n acl['id'])\n\n\n\n assert network, \"No network could be created\"\n\n self.network_id = network['id']\n self.id = self.network_id","def create_network(self, context, network):\n LOG.debug(_(\"NeutronRestProxyV2: create_network() called\"))\n\n self._warn_on_state_status(network['network'])\n\n with context.session.begin(subtransactions=True):\n # Validate args\n tenant_id = self._get_tenant_id_for_create(context,\n network[\"network\"])\n\n # create network in DB\n new_net = super(NeutronRestProxyV2, self).create_network(context,\n network)\n self._process_l3_create(context, new_net, network['network'])\n mapped_network = self._get_mapped_network_with_subnets(new_net,\n context)\n\n # create network on the network controller\n self.servers.rest_create_network(tenant_id, mapped_network)\n\n # return created network\n return new_net","def fusion_api_create_network_set(self, body, api=None, headers=None):\n return self.network_set.create(body, api, headers)","def create_default_network(context):\n return [{\n 'type': 'templates/network.py',\n 'name': 'fc-network',\n 'properties': {\n 'resourceName': 'network',\n 'name': 'network',\n 'projectId': '$(ref.fc-project.projectId)',\n 'autoCreateSubnetworks': True,\n # We pass the dependsOn list into the network template as a\n # parameter. Deployment Manager doesn't support dependsOn for\n # template-call nodes, so we can't have this resource itself depend on\n # the project-wide resources.\n 'dependsOn': '$(ref.fc-project.resourceNames)',\n },\n }]","def create_network(self, context, network):\n\n LOG.debug(_(\"QuantumRestProxyV2: create_network() called\"))\n\n # Validate args\n tenant_id = self._get_tenant_id_for_create(context, network[\"network\"])\n net_name = network[\"network\"][\"name\"]\n if network[\"network\"][\"admin_state_up\"] is False:\n LOG.warning(_(\"Network with admin_state_up=False are not yet \"\n \"supported by this plugin. Ignoring setting for \"\n \"network %s\"), net_name)\n\n # create in DB\n new_net = super(QuantumRestProxyV2, self).create_network(context,\n network)\n\n # create on networl ctrl\n try:\n resource = NET_RESOURCE_PATH % tenant_id\n data = {\n \"network\": {\n \"id\": new_net[\"id\"],\n \"name\": new_net[\"name\"],\n }\n }\n ret = self.servers.post(resource, data)\n if not self.servers.action_success(ret):\n raise RemoteRestError(ret[2])\n except RemoteRestError as e:\n LOG.error(_(\"QuantumRestProxyV2:Unable to create remote \"\n \"network: %s\"), e.message)\n super(QuantumRestProxyV2, self).delete_network(context,\n new_net['id'])\n raise\n\n # return created network\n return new_net","def create_network_profile(self, body=None):\r\n return self.post(self.network_profiles_path, body=body)","def subnetpool_create(request, name, prefixes, **kwargs):\n LOG.debug(\"subnetpool_create(): name=%(name)s, prefixes=%(prefixes)s, \"\n \"kwargs=%(kwargs)s\", {'name': name, 'prefixes': prefixes,\n 'kwargs': kwargs})\n body = {'subnetpool':\n {'name': name,\n 'prefixes': prefixes,\n }\n }\n if 'tenant_id' not in kwargs:\n kwargs['tenant_id'] = request.user.project_id\n body['subnetpool'].update(kwargs)\n subnetpool = \\\n neutronclient(request).create_subnetpool(body=body).get('subnetpool')\n return SubnetPool(subnetpool)","def create_from_src(self, cgsnapshot_id, source_cgid, name=None,\n description=None, user_id=None,\n project_id=None):\n body = {'consistencygroup-from-src': {'name': name,\n 'description': description,\n 'cgsnapshot_id': cgsnapshot_id,\n 'source_cgid': source_cgid,\n 'user_id': user_id,\n 'project_id': project_id,\n 'status': \"creating\",\n }}\n\n self.run_hooks('modify_body_for_update', body,\n 'consistencygroup-from-src')\n resp, body = self.api.client.post(\n \"/consistencygroups/create_from_src\", body=body)\n return common_base.DictWithMeta(body['consistencygroup'], resp)","def CreateGcpWorkloadSource(\n client,\n messages,\n workload_source_id: str,\n resources: Optional[List[str]],\n attached_service_accounts: Optional[List[str]],\n parent: str,\n for_managed_identity: bool = False,\n):\n conditions = []\n if resources is not None:\n conditions += [\n messages.WorkloadSourceCondition(attribute='resource', value=resource)\n for resource in resources\n ]\n if attached_service_accounts is not None:\n conditions += [\n messages.WorkloadSourceCondition(\n attribute='attached_service_account', value=account\n )\n for account in attached_service_accounts\n ]\n new_workload_source = messages.WorkloadSource(\n conditionSet=messages.WorkloadSourceConditionSet(conditions=conditions)\n )\n if for_managed_identity:\n return client.projects_locations_workloadIdentityPools_namespaces_managedIdentities_workloadSources.Create(\n messages.IamProjectsLocationsWorkloadIdentityPoolsNamespacesManagedIdentitiesWorkloadSourcesCreateRequest(\n parent=parent,\n workloadSource=new_workload_source,\n workloadSourceId=workload_source_id,\n )\n )\n else:\n return client.projects_locations_workloadIdentityPools_namespaces_workloadSources.Create(\n messages.IamProjectsLocationsWorkloadIdentityPoolsNamespacesWorkloadSourcesCreateRequest(\n parent=parent,\n workloadSource=new_workload_source,\n workloadSourceId=workload_source_id,\n )\n )","def subnet_create(request, network_id, **kwargs):\n LOG.debug(\"subnet_create(): netid=%(network_id)s, kwargs=%(kwargs)s\",\n {'network_id': network_id, 'kwargs': kwargs})\n body = {'subnet': {'network_id': network_id}}\n if 'tenant_id' not in kwargs:\n kwargs['tenant_id'] = request.user.project_id\n body['subnet'].update(kwargs)\n subnet = neutronclient(request).create_subnet(body=body).get('subnet')\n return Subnet(subnet)","def init_network(session: \"Session\", new_network_name: str) -> None:\n url_tail = f\"/{CoordConstsV2.RSC_NETWORKS}\"\n _post(session, url_tail, None, params={CoordConstsV2.QP_NAME: new_network_name})","def create(self):\n logging.debug(\"%s create called\" % self)\n # networks = self.infra.get(\"networks\")\n notify(\"Creating network %s\" % self.name)\n self.cloudnet = cn.create(self.name, cidr=self.cidr)\n return True","def create_source(self, **kwargs):\n kwargs['_return_http_data_only'] = True\n if kwargs.get('callback'):\n return self.create_source_with_http_info(**kwargs)\n else:\n (data) = self.create_source_with_http_info(**kwargs)\n return data","def create_network_gateway(self, body=None):\r\n return self.post(self.network_gateways_path, body=body)","def add_provider_network(network_id, network_type, segmentation_id):\n session = db.get_session()\n if session.query(network_models_v2.ProviderNetwork).filter_by(\n network_id=network_id).first():\n raise c_exc.ProviderNetworkExists(network_id)\n pnet = network_models_v2.ProviderNetwork(network_id=network_id,\n network_type=network_type,\n segmentation_id=segmentation_id)\n session.add(pnet)\n session.flush()","def test_03_network_create(self):\n # Validate the following\n # 1. Create a project.\n # 2. Add virtual/direct network resource to the project. User shared\n # network resource for the project\n # 3. Verify any number of Project level Virtual/Direct networks can be\n # created and used for vm deployment within the project.\n # 4. Verify shared networks (zone and domain wide) from outside the\n # project can also be used in a project.\n\n # Create project as a domain admin\n project = Project.create(\n self.apiclient,\n self.services[\"project\"],\n account=self.account.name,\n domainid=self.account.domainid\n )\n # Cleanup created project at end of test\n self.cleanup.append(project)\n self.debug(\"Created project with domain admin with ID: %s\" %\n project.id)\n\n network_offerings = list_network_offerings(\n self.apiclient,\n projectid=project.id,\n supportedServices='SourceNat',\n type='isolated',\n state='Enabled'\n )\n self.assertEqual(\n isinstance(network_offerings, list),\n True,\n \"Check for the valid network offerings\"\n )\n network_offering = network_offerings[0]\n\n self.debug(\"creating a network with network offering ID: %s\" %\n network_offering.id)\n self.services[\"network\"][\"zoneid\"] = self.zone.id\n network = Network.create(\n self.apiclient,\n self.services[\"network\"],\n networkofferingid=network_offering.id,\n projectid=project.id\n )\n self.debug(\"Created network with ID: %s\" % network.id)\n networks = Network.list(\n self.apiclient,\n projectid=project.id,\n listall=True\n )\n self.assertEqual(\n isinstance(networks, list),\n True,\n \"Check for the valid network list response\"\n )\n\n self.debug(\"Deploying VM with network: %s\" % network.id)\n\n virtual_machine = VirtualMachine.create(\n self.apiclient,\n self.services[\"server\"],\n templateid=self.template.id,\n networkids=[str(network.id)],\n serviceofferingid=self.service_offering.id,\n projectid=project.id\n )\n self.debug(\"Deployed VM with ID: %s\" % virtual_machine.id)\n # Verify VM state\n self.assertEqual(\n virtual_machine.state,\n 'Running',\n \"Check VM state is Running or not\"\n )\n\n network_offerings = list_network_offerings(\n self.apiclient,\n state='Enabled',\n guestiptype='Shared',\n name='DefaultSharedNetworkOffering',\n displaytext='Offering for Shared networks'\n )\n self.assertEqual(\n isinstance(network_offerings, list),\n True,\n \"Check for the valid network offerings\"\n )\n network_offering = network_offerings[0]\n\n self.debug(\"creating a shared network in domain: %s\" %\n self.domain.id)\n\n # Getting physical network and free vlan in it\n physical_network, vlan = get_free_vlan(self.apiclient, self.zone.id)\n\n self.services[\"domain_network\"][\"vlan\"] = vlan\n self.services[\"domain_network\"][\"physicalnetworkid\"] = physical_network.id\n\n # Generating random subnet number for shared network creation\n shared_network_subnet_number = random.randrange(1,254)\n\n self.services[\"domain_network\"][\"gateway\"] = \"172.16.\"+str(shared_network_subnet_number)+\".1\"\n self.services[\"domain_network\"][\"startip\"] = \"172.16.\"+str(shared_network_subnet_number)+\".2\"\n self.services[\"domain_network\"][\"endip\"] = \"172.16.\"+str(shared_network_subnet_number)+\".20\"\n\n domain_network = Network.create(\n self.apiclient,\n self.services[\"domain_network\"],\n domainid=self.domain.id,\n networkofferingid=network_offering.id,\n zoneid=self.zone.id\n )\n self.cleanup.append(domain_network)\n self.debug(\"Created network with ID: %s\" % domain_network.id)\n\n virtual_machine = VirtualMachine.create(\n self.apiclient,\n self.services[\"server\"],\n templateid=self.template.id,\n networkids=[str(domain_network.id)],\n serviceofferingid=self.service_offering.id,\n projectid=project.id\n )\n self.debug(\"Deployed VM with ID: %s\" % virtual_machine.id)\n # Verify VM state\n self.assertEqual(\n virtual_machine.state,\n 'Running',\n \"Check VM state is Running or not\"\n )\n\n # Delete VM before network gets deleted in cleanup\n virtual_machine.delete(self.apiclient, expunge=True)\n return","def _create_network_resources(self, tenant_id):\n logger.info(\"Creating network resources...\")\n net_name = \"ostf-autoscaling-test-service-net\"\n net_body = {\n \"network\": {\n \"name\": net_name,\n \"tenant_id\": tenant_id\n }\n }\n ext_net = None\n net = None\n for network in self.neutron_cli.list_networks()[\"networks\"]:\n if not net and network[\"name\"] == net_name:\n net = network\n if not ext_net and network[\"router:external\"]:\n ext_net = network\n if not net:\n net = self.neutron_cli.create_network(net_body)[\"network\"]\n subnet = self.helpers.os_conn.create_subnet(\n \"sub\" + net_name, net[\"id\"], \"10.1.7.0/24\", tenant_id=tenant_id\n )\n router_name = 'ostf-autoscaling-test-service-router'\n router = self.helpers.os_conn.create_router(\n router_name, self.helpers.os_conn.get_tenant(\"admin\"))\n self.neutron_cli.add_interface_router(\n router[\"id\"], {\"subnet_id\": subnet[\"id\"]})\n return net[\"id\"]","def create_network(client, overwrite_net=False, network_name=DOCK_NETWORK_NAME, subnetwork=DOCK_NETWORK_SUBNET,\n gw=DOCK_NETWORK_GW):\n\n if overwrite_net:\n try:\n client.networks.get(network_name).remove()\n logging.info(\" Overwriting existing network\")\n except docker.errors.APIError:\n logging.info(\" Warning: Couldn't find network to overwrite (does it exist?)\")\n\n ipam_pool = docker.types.IPAMPool(subnet=subnetwork, gateway=gw)\n ipam_config = docker.types.IPAMConfig(pool_configs=[ipam_pool])\n client.networks.create(network_name, driver=\"bridge\", ipam=ipam_config)","def run(self, network_create_args=None):\n network = self.neutron.create_network(**(network_create_args or {}))\n self.neutron.get_network(network[\"id\"])","def new_network():\n new_names = Names()\n new_devices = Devices(new_names)\n return Network(new_names, new_devices)","def create_network(address=None, **options):\n return NetworkDefinition(address, **options)","def create_network(self, *, name: t.Optional[str] = None) -> Network:\n network = Network(self, name=name)\n self._networks.add(network)\n return network","def test_networking_project_network_create(self):\n pass","def get_network_source(self, network_source_id, **kwargs):\n resource_path = \"/networkSources/{networkSourceId}\"\n method = \"GET\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"get_network_source got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"networkSourceId\": network_source_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"NetworkSources\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"NetworkSources\")","def create_network(options, vsm_obj):\n edge_id = get_edge(vsm_obj)\n if not edge_id:\n if not add_edge(options):\n print(\"Failed to create edge\")\n return False\n edge_id = get_edge(vsm_obj)\n\n vdn_scope = get_transport_zone(options)\n virtual_wire = VirtualWire(vdn_scope)\n name = get_network_name(options)\n response = virtual_wire.read_by_name(name)\n if response != \"FAILURE\":\n print(\"Found network %s already exists\" % options.name)\n return True\n\n virtual_wire_create = VirtualWireCreateSpecSchema()\n virtual_wire_create.name = name\n virtual_wire_create.tenantId = name\n virtual_wire_create.description = 'NSX network %s' % name\n\n # check if user needs to enable guest vlan tagging,\n # this is require if one needs to run vlan tests in nested\n # environment.\n if hasattr(options, 'guest_vlan'):\n if options.guest_vlan is True:\n print(\"network %s has guest vlan tagging enabled\"\\\n % options.name)\n virtual_wire_create.guestVlanAllowed = True\n\n print(\"Creating network %s\" % options.name)\n result = virtual_wire.create(virtual_wire_create)\n if (result[0].response.status != 201):\n print \"response: %s\" % result[0].response.status\n print \"response: %s\" % result[0].response.reason\n return False\n print(\"Changing security settings on the network\")\n set_network_security_policy(options)\n return add_edge_interface(options, edge_id)","def create_net(self, net_name, shared=\"false\"):\n _url = \"http://\" + self.host_ip + \":9696/v2.0/networks.json\"\n _headers = {'Content-type': 'application/json',\n 'x-auth-token': self.project_info[\"token_project\"]}\n _net_info = {\"network\":\n {\"name\": net_name,\n \"shared\": shared,\n \"admin_state_up\": True}}\n _body = json.dumps(_net_info)\n\n response = self.request(\"POST\", _url, _headers, _body)\n if response is None:\n LOG_OBJ.error(\"No response from Server while creating network.\")\n return response\n\n if response.status not in [200, 201, 202, 203, 204]:\n LOG_OBJ.error(\"Creation of network Failed with status %s \" %\n response.status)\n return response.status\n\n output = json.loads(response.data)\n LOG_OBJ.info(\"Network is created successfully. Details : %s \" %\n output['network'])\n\n return output['network']['id']","def run(self, network_create_args=None, subnet_create_args=None,\n subnet_cidr_start=None, subnets_per_network=1,\n router_create_args=None):\n subnet_create_args = dict(subnet_create_args or {})\n subnet_create_args[\"start_cidr\"] = subnet_cidr_start\n\n self.neutron.create_network_topology(\n network_create_args=(network_create_args or {}),\n router_create_args=(router_create_args or {}),\n router_per_subnet=True,\n subnet_create_args=subnet_create_args,\n subnets_count=subnets_per_network\n )\n self.neutron.list_routers()","def _precreate_network(self):\n # check cidr format\n net_cidr = CONF.azure.vnet_cidr\n subnet_cidr = CONF.azure.vsubnet_cidr\n if not (self._is_valid_cidr(net_cidr) and\n self._is_valid_cidr(subnet_cidr)):\n msg = 'Invalid network: %(net_cidr)s/subnet: %(subnet_cidr)s' \\\n ' CIDR' % dict(net_cidr=net_cidr, subnet_cidr=subnet_cidr)\n LOG.error(msg)\n raise exception.NetworkCreateFailure(reason=msg)\n # Creaet Network\n try:\n nets = self.network.virtual_networks.list(\n CONF.azure.resource_group)\n net_exist = False\n for i in nets:\n if i.name == CONF.azure.vnet_name:\n net_exist = True\n break\n if not net_exist:\n network_info = dict(location=CONF.azure.location,\n address_space=dict(\n address_prefixes=[net_cidr]))\n async_vnet_creation = \\\n self.network.virtual_networks.create_or_update(\n CONF.azure.resource_group,\n CONF.azure.vnet_name,\n network_info)\n async_vnet_creation.wait(CONF.azure.async_timeout)\n LOG.info(_LI(\"Create Network\"))\n except Exception as e:\n msg = six.text_type(e)\n ex = exception.NetworkCreateFailure(reason=msg)\n LOG.exception(msg)\n raise ex\n\n # Create Subnet\n try:\n # subnet can't recreate, check existing before create.\n subnets = self.network.subnets.list(\n CONF.azure.resource_group,\n CONF.azure.vnet_name)\n subnet_exist = False\n subnet_details = None\n for i in subnets:\n if i.name == CONF.azure.vsubnet_name:\n subnet_exist = True\n subnet_details = i\n break\n if not subnet_exist:\n subnet_info = {'address_prefix': subnet_cidr}\n async_subnet_creation = self.network.subnets.create_or_update(\n CONF.azure.resource_group,\n CONF.azure.vnet_name,\n CONF.azure.vsubnet_name,\n subnet_info\n )\n subnet_details = async_subnet_creation.result()\n except Exception as e:\n # delete network if subnet create fail.\n try:\n async_vm_action = self.network.virtual_networks.delete(\n CONF.azure.resource_group, CONF.azure.vnet_name)\n async_vm_action.wait(CONF.azure.async_timeout)\n LOG.info(_LI(\"Deleted Network %s after Subnet create \"\n \"failed.\"), CONF.azure.vnet_name)\n except Exception:\n LOG.error(_LE('Delete Network %s failed after Subnet create '\n 'failed.'), CONF.azure.vnet_name)\n msg = six.text_type(e)\n ex = exception.SubnetCreateFailure(reason=msg)\n LOG.exception(msg)\n raise ex\n CONF.set_override('vsubnet_id', subnet_details.id, 'azure')\n LOG.info(_LI(\"Create/Update Subnet: %s\"), CONF.azure.vsubnet_id)","def run(self, network_create_args=None):\n self.neutron.create_network(**(network_create_args or {}))\n self.neutron.list_networks()","def _add_source_net_filter(self, rule_list, source_net):\n for rule in rule_list:\n if (\"source\" in rule.keys()):\n if (\"nets\" in rule[\"source\"].keys()):\n rule[\"source\"][\"nets\"].append(source_net)\n else:\n rule[\"source\"].update({\"nets\": [source_net]})\n else:\n rule.update({\"source\": {\"nets\": [source_net]}})","def create_source_with_http_info(self, **kwargs):\n\n all_params = ['body']\n all_params.append('callback')\n all_params.append('_return_http_data_only')\n all_params.append('_preload_content')\n all_params.append('_request_timeout')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_source\" % key\n )\n params[key] = val\n del params['kwargs']\n\n\n collection_formats = {}\n\n path_params = {}\n\n query_params = []\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['application/json'])\n\n # Authentication setting\n auth_settings = ['Using HTTP Header', 'Using URL Query Parameter']\n\n return self.api_client.call_api('/sources', 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='str',\n auth_settings=auth_settings,\n callback=params.get('callback'),\n _return_http_data_only=params.get('_return_http_data_only'),\n _preload_content=params.get('_preload_content', True),\n _request_timeout=params.get('_request_timeout'),\n collection_formats=collection_formats)","def network_initial(request, SPIC_group, SPIC_id):\n SPIC_obj = get_object_or_404(SPIC, group=SPIC_group, local_id=SPIC_id)\n network_obj, created = Network.objects.get_or_create(user_id=request.user.pk, SPIC=SPIC_obj, local_id=0, deleted=False)\n\n if created is True:\n # Check if prototype exists\n prototype = get_object_or_404(Network, user_id=0, SPIC=SPIC_obj)\n network_obj.nodes_json = prototype.nodes_json\n network_obj.links_json = prototype.links_json\n network_obj.save()\n\n return network(request, SPIC_group, SPIC_id, 0)","def create_network(region_name, vpc_cidr, tag_prefix,\n tls_priv_key=None, tls_fullchain_cert=None,\n ssh_key_name=None, ssh_key_content=None, sally_ip=None,\n s3_logs_bucket=None, s3_identities_bucket=None,\n storage_enckey=None,\n dry_run=False):\n sg_tag_prefix = tag_prefix\n\n LOGGER.info(\"Provisions network ...\")\n ec2_client = boto3.client('ec2', region_name=region_name)\n\n # Create a VPC\n vpc_id, vpc_cidr_read = _get_vpc_id(tag_prefix, ec2_client=ec2_client,\n region_name=region_name)\n if vpc_id:\n if vpc_cidr != vpc_cidr_read:\n raise RuntimeError(\n \"%s cidr block for VPC is %s while it was expected to be %s\" %\n (tag_prefix, vpc_cidr_read, vpc_cidr))\n else:\n if not vpc_cidr:\n raise RuntimeError(\n \"%s could not find VPC and no cidr block is specified\"\\\n \" to create one.\" % tag_prefix)\n resp = ec2_client.create_vpc(\n DryRun=dry_run,\n CidrBlock=vpc_cidr,\n AmazonProvidedIpv6CidrBlock=False,\n InstanceTenancy='default')\n vpc_id = resp['Vpc']['VpcId']\n ec2_client.create_tags(\n DryRun=dry_run,\n Resources=[vpc_id],\n Tags=[\n {'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\", 'Value': \"%s-vpc\" % tag_prefix}])\n LOGGER.info(\"%s created VPC %s\", tag_prefix, vpc_id)\n\n # Create subnets for app, dbs and web services\n # ELB will require that there is at least one subnet per availability zones.\n # RDS will require that there is at least two subnets for databases.\n resp = ec2_client.describe_availability_zones()\n zones = {(zone['ZoneId'], zone['ZoneName'])\n for zone in resp['AvailabilityZones']}\n web_subnet_cidrs, dbs_subnet_cidrs, app_subnet_cidrs = _split_cidrs(\n vpc_cidr, zones=zones, region_name=region_name)\n\n LOGGER.info(\"%s provisioning web subnets...\", tag_prefix)\n web_zones = set([])\n web_subnet_by_cidrs = _get_subnet_by_cidrs(\n web_subnet_cidrs, tag_prefix, vpc_id=vpc_id, ec2_client=ec2_client)\n for cidr_block, subnet in web_subnet_by_cidrs.items():\n if subnet:\n web_zones |= {\n (subnet['AvailabilityZoneId'], subnet['AvailabilityZone'])}\n for cidr_block, subnet in web_subnet_by_cidrs.items():\n if not subnet:\n available_zones = zones - web_zones\n zone_id, zone_name = available_zones.pop()\n try:\n resp = ec2_client.create_subnet(\n AvailabilityZoneId=zone_id,\n CidrBlock=cidr_block,\n VpcId=vpc_id,\n TagSpecifications=[{\n 'ResourceType': 'subnet',\n 'Tags': [\n {'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\",\n 'Value': \"%s %s web\" % (tag_prefix, zone_name)}]}],\n DryRun=dry_run)\n subnet = resp['Subnet']\n web_subnet_by_cidrs[cidr_block] = subnet\n web_zones |= set([(zone_id, zone_name)])\n subnet_id = subnet['SubnetId']\n LOGGER.info(\"%s created subnet %s in zone %s for cidr %s\",\n tag_prefix, subnet_id, zone_name, cidr_block)\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidSubnet.Conflict':\n raise\n # We have a conflict, let's just skip over it.\n LOGGER.warning(\n \"%s (skip) created subnet in zone %s because '%s'\",\n tag_prefix, zone_name, err)\n if subnet and not subnet['MapPublicIpOnLaunch']:\n subnet_id = subnet['SubnetId']\n if not dry_run:\n resp = ec2_client.modify_subnet_attribute(\n SubnetId=subnet_id,\n MapPublicIpOnLaunch={'Value': True})\n LOGGER.info(\"%s modify web subnet %s so instance can receive\"\\\n \" a public IP by default\", tag_prefix, subnet_id)\n\n LOGGER.info(\"%s provisioning dbs subnets...\", tag_prefix)\n dbs_zones = set([])\n dbs_subnet_by_cidrs = _get_subnet_by_cidrs(\n dbs_subnet_cidrs, tag_prefix, vpc_id=vpc_id, ec2_client=ec2_client)\n for cidr_block, subnet in dbs_subnet_by_cidrs.items():\n if subnet:\n dbs_zones |= {\n (subnet['AvailabilityZoneId'], subnet['AvailabilityZone'])}\n for cidr_block, subnet in dbs_subnet_by_cidrs.items():\n if not subnet:\n available_zones = zones - dbs_zones\n zone_id, zone_name = available_zones.pop()\n resp = ec2_client.create_subnet(\n AvailabilityZoneId=zone_id,\n CidrBlock=cidr_block,\n VpcId=vpc_id,\n TagSpecifications=[{\n 'ResourceType': 'subnet',\n 'Tags': [\n {'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\",\n 'Value': \"%s %s dbs\" % (tag_prefix, zone_name)}]}],\n DryRun=dry_run)\n subnet = resp['Subnet']\n dbs_subnet_by_cidrs[cidr_block] = subnet\n dbs_zones |= set([(zone_id, zone_name)])\n subnet_id = subnet['SubnetId']\n LOGGER.info(\"%s created subnet %s in zone %s for cidr %s\",\n tag_prefix, subnet_id, zone_name, cidr_block)\n if subnet['MapPublicIpOnLaunch']:\n subnet_id = subnet['SubnetId']\n if not dry_run:\n resp = ec2_client.modify_subnet_attribute(\n SubnetId=subnet_id,\n MapPublicIpOnLaunch={'Value': False})\n LOGGER.info(\"%s modify dbs subnet %s so instance do not receive\"\\\n \" a public IP by default\", tag_prefix, subnet_id)\n\n LOGGER.info(\"%s provisioning apps subnets...\", tag_prefix)\n app_zones = set([])\n app_subnet_by_cidrs = _get_subnet_by_cidrs(\n app_subnet_cidrs, tag_prefix, vpc_id=vpc_id, ec2_client=ec2_client)\n for cidr_block, subnet in app_subnet_by_cidrs.items():\n if subnet:\n app_zones |= {\n (subnet['AvailabilityZoneId'], subnet['AvailabilityZone'])}\n for cidr_block, subnet in app_subnet_by_cidrs.items():\n if not subnet:\n available_zones = zones - app_zones\n zone_id, zone_name = available_zones.pop()\n resp = ec2_client.create_subnet(\n AvailabilityZoneId=zone_id,\n CidrBlock=cidr_block,\n VpcId=vpc_id,\n # COMMIT MSG:\n # this requires boto3>=1.14, using `createTag` might fail\n # because the subnet is not fully created yet.\n TagSpecifications=[{\n 'ResourceType': 'subnet',\n 'Tags': [\n {'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\",\n 'Value': \"%s %s app\" % (tag_prefix, zone_name)}]}],\n DryRun=dry_run)\n subnet = resp['Subnet']\n app_subnet_by_cidrs[cidr_block] = subnet\n app_zones |= set([(zone_id, zone_name)])\n subnet_id = subnet['SubnetId']\n LOGGER.info(\"%s created subnet %s in %s for cidr %s\",\n tag_prefix, subnet_id, zone_name, cidr_block)\n if subnet['MapPublicIpOnLaunch']:\n subnet_id = subnet['SubnetId']\n if not dry_run:\n resp = ec2_client.modify_subnet_attribute(\n SubnetId=subnet_id,\n MapPublicIpOnLaunch={'Value': False})\n LOGGER.info(\"%s modify app subnet %s so instance do not receive\"\\\n \" a public IP by default\", tag_prefix, subnet_id)\n\n # Ensure that the VPC has an Internet Gateway.\n resp = ec2_client.describe_internet_gateways(\n Filters=[{'Name': 'attachment.vpc-id', 'Values': [vpc_id]}])\n if resp['InternetGateways']:\n igw_id = resp['InternetGateways'][0]['InternetGatewayId']\n LOGGER.info(\"%s found Internet Gateway %s\", tag_prefix, igw_id)\n else:\n resp = ec2_client.describe_internet_gateways(\n Filters=[{'Name': 'tag:Prefix', 'Values': [tag_prefix]}])\n if resp['InternetGateways']:\n igw_id = resp['InternetGateways'][0]['InternetGatewayId']\n LOGGER.info(\"%s found Internet Gateway %s\", tag_prefix, igw_id)\n else:\n resp = ec2_client.create_internet_gateway(DryRun=dry_run)\n igw_id = resp['InternetGateway']['InternetGatewayId']\n ec2_client.create_tags(\n DryRun=dry_run,\n Resources=[igw_id],\n Tags=[{'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\",\n 'Value': \"%s internet gateway\" % tag_prefix}])\n LOGGER.info(\"%s created Internet Gateway %s\", tag_prefix, igw_id)\n resp = ec2_client.attach_internet_gateway(\n DryRun=dry_run,\n InternetGatewayId=igw_id,\n VpcId=vpc_id)\n\n # Create the NAT gateway by which private subnets connect to Internet\n # XXX Why do we have a Network interface eni-****?\n nat_elastic_ip = None\n web_elastic_ip = None\n resp = ec2_client.describe_addresses(\n Filters=[{'Name': 'tag:Prefix', 'Values': [tag_prefix]}])\n if resp['Addresses']:\n for resp_address in resp['Addresses']:\n for resp_tag in resp_address['Tags']:\n if resp_tag['Key'] == 'Name':\n if 'NAT gateway' in resp_tag['Value']:\n nat_elastic_ip = resp_address['AllocationId']\n break\n if 'Sally' in resp_tag['Value']:\n web_elastic_ip = resp_address['AllocationId']\n break\n\n if nat_elastic_ip:\n LOGGER.info(\"%s found NAT gateway public IP %s\",\n tag_prefix, nat_elastic_ip)\n else:\n resp = ec2_client.allocate_address(\n DryRun=dry_run,\n Domain='vpc')\n nat_elastic_ip = resp['AllocationId']\n ec2_client.create_tags(\n DryRun=dry_run,\n Resources=[nat_elastic_ip],\n Tags=[{'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\",\n 'Value': \"%s NAT gateway public IP\" % tag_prefix}])\n LOGGER.info(\"%s created NAT gateway public IP %s\",\n tag_prefix, nat_elastic_ip)\n if web_elastic_ip:\n LOGGER.info(\"%s found Sally public IP %s\",\n tag_prefix, web_elastic_ip)\n else:\n resp = ec2_client.allocate_address(\n DryRun=dry_run,\n Domain='vpc')\n web_elastic_ip = resp['AllocationId']\n ec2_client.create_tags(\n DryRun=dry_run,\n Resources=[web_elastic_ip],\n Tags=[{'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\",\n 'Value': \"%s Sally public IP\" % tag_prefix}])\n LOGGER.info(\"%s created Sally public IP %s\",\n tag_prefix, web_elastic_ip)\n\n # We have 2 EIP addresses. They need to be connected to machines\n # running in an Internet facing subnet.\n client_token = tag_prefix\n # XXX shouldn't it be the first web subnet instead?\n resp = ec2_client.describe_nat_gateways(Filters=[\n {'Name': \"vpc-id\", 'Values': [vpc_id]},\n {'Name': \"state\", 'Values': ['pending', 'available']}])\n if resp['NatGateways']:\n if len(resp['NatGateways']) > 1:\n LOGGER.warning(\"%s found more than one NAT gateway.\"\\\n \" Using first one in the list.\", tag_prefix)\n nat_gateway = resp['NatGateways'][0]\n nat_gateway_id = nat_gateway['NatGatewayId']\n nat_gateway_subnet_id = nat_gateway['SubnetId']\n LOGGER.info(\"%s found NAT gateway %s\", tag_prefix, nat_gateway_id)\n else:\n nat_gateway_subnet_id = next(web_subnet_by_cidrs.values())['SubnetId']\n resp = ec2_client.create_nat_gateway(\n AllocationId=nat_elastic_ip,\n ClientToken=client_token,\n SubnetId=nat_gateway_subnet_id)\n nat_gateway_id = resp['NatGateway']['NatGatewayId']\n ec2_client.create_tags(\n DryRun=dry_run,\n Resources=[nat_gateway_id],\n Tags=[{'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\",\n 'Value': \"%s NAT gateway\" % tag_prefix}])\n LOGGER.info(\"%s created NAT gateway %s\",\n tag_prefix, nat_gateway_id)\n\n # Set up public and NAT-protected route tables\n resp = ec2_client.describe_route_tables(\n Filters=[{'Name': \"vpc-id\", 'Values': [vpc_id]}])\n public_route_table_id = None\n private_route_table_id = None\n for route_table in resp['RouteTables']:\n for route in route_table['Routes']:\n if 'GatewayId' in route and route['GatewayId'] == igw_id:\n public_route_table_id = route_table['RouteTableId']\n LOGGER.info(\"%s found public route table %s\",\n tag_prefix, public_route_table_id)\n break\n if ('NatGatewayId' in route and\n route['NatGatewayId'] == nat_gateway_id):\n private_route_table_id = route_table['RouteTableId']\n LOGGER.info(\"%s found private route table %s\",\n tag_prefix, private_route_table_id)\n\n if not public_route_table_id:\n resp = ec2_client.create_route_table(\n DryRun=dry_run,\n VpcId=vpc_id)\n public_route_table_id = resp['RouteTable']['RouteTableId']\n ec2_client.create_tags(\n DryRun=dry_run,\n Resources=[public_route_table_id],\n Tags=[\n {'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\", 'Value': \"%s public\" % tag_prefix}])\n LOGGER.info(\"%s created public subnet route table %s\",\n tag_prefix, public_route_table_id)\n resp = ec2_client.create_route(\n DryRun=dry_run,\n DestinationCidrBlock='0.0.0.0/0',\n GatewayId=igw_id,\n RouteTableId=public_route_table_id)\n\n if not private_route_table_id:\n resp = ec2_client.create_route_table(\n DryRun=dry_run,\n VpcId=vpc_id)\n private_route_table_id = resp['RouteTable']['RouteTableId']\n ec2_client.create_tags(\n DryRun=dry_run,\n Resources=[private_route_table_id],\n Tags=[\n {'Key': \"Prefix\", 'Value': tag_prefix},\n {'Key': \"Name\", 'Value': \"%s internal\" % tag_prefix}])\n private_route_table_id = resp['RouteTable']['RouteTableId']\n LOGGER.info(\"%s created private route table %s\",\n tag_prefix, private_route_table_id)\n for _ in range(0, NB_RETRIES):\n # The NAT Gateway takes some time to be fully operational.\n try:\n resp = ec2_client.create_route(\n DryRun=dry_run,\n DestinationCidrBlock='0.0.0.0/0',\n NatGatewayId=nat_gateway_id,\n RouteTableId=private_route_table_id)\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidNatGatewayID.NotFound':\n raise\n time.sleep(RETRY_WAIT_DELAY)\n\n resp = ec2_client.describe_route_tables(\n DryRun=dry_run,\n RouteTableIds=[public_route_table_id])\n assocs = resp['RouteTables'][0]['Associations']\n if len(assocs) > 1:\n LOGGER.warning(\"%s found more than one route table association for\"\\\n \" public route table. Using first one in the list.\", tag_prefix)\n if not assocs[0]['Main']:\n LOGGER.warning(\"%s public route table is not the main one for the VPC.\",\n tag_prefix)\n\n for cidr_block, subnet in web_subnet_by_cidrs.items():\n if not subnet:\n # Maybe there was a conflict and we skipped this cidr_block.\n continue\n subnet_id = subnet['SubnetId']\n resp = ec2_client.describe_route_tables(\n DryRun=dry_run,\n Filters=[{\n 'Name': 'association.subnet-id',\n 'Values': [subnet_id]\n }])\n # The Main route table does not show as an explicit association.\n found_association = not bool(resp['RouteTables'])\n if found_association:\n LOGGER.info(\n \"%s found public route table %s associated to web subnet %s\",\n tag_prefix, public_route_table_id, subnet_id)\n else:\n resp = ec2_client.associate_route_table(\n DryRun=dry_run,\n RouteTableId=public_route_table_id,\n SubnetId=subnet_id)\n LOGGER.info(\n \"%s associate public route table %s to web subnet %s\",\n tag_prefix, public_route_table_id, subnet_id)\n\n for cidr_block, subnet in dbs_subnet_by_cidrs.items():\n subnet_id = subnet['SubnetId']\n resp = ec2_client.describe_route_tables(\n DryRun=dry_run,\n Filters=[{\n 'Name': 'association.subnet-id',\n 'Values': [subnet_id]\n }])\n # The Main route table does not show as an explicit association.\n found_association = False\n if resp['RouteTables']:\n found_association = (\n resp['RouteTables'][0]['Associations'][0]['RouteTableId'] ==\n private_route_table_id\n )\n if found_association:\n LOGGER.info(\n \"%s found private route table %s associated to dbs subnet %s\",\n tag_prefix, private_route_table_id, subnet_id)\n else:\n resp = ec2_client.associate_route_table(\n DryRun=dry_run,\n RouteTableId=private_route_table_id,\n SubnetId=subnet_id)\n LOGGER.info(\n \"%s associate private route table %s to dbs subnet %s\",\n tag_prefix, private_route_table_id, subnet_id)\n\n for cidr_block, subnet in app_subnet_by_cidrs.items():\n subnet_id = subnet['SubnetId']\n resp = ec2_client.describe_route_tables(\n DryRun=dry_run,\n Filters=[{\n 'Name': 'association.subnet-id',\n 'Values': [subnet_id]\n }])\n # The Main route table does not show as an explicit association.\n found_association = False\n if resp['RouteTables']:\n found_association = (\n resp['RouteTables'][0]['Associations'][0]['RouteTableId'] ==\n private_route_table_id\n )\n if found_association:\n LOGGER.info(\n \"%s found private route table %s associated to app subnet %s\",\n tag_prefix, private_route_table_id, subnet_id)\n else:\n resp = ec2_client.associate_route_table(\n DryRun=dry_run,\n RouteTableId=private_route_table_id,\n SubnetId=subnet_id)\n LOGGER.info(\n \"%s associate private route table %s to app subnet %s\",\n tag_prefix, private_route_table_id, subnet_id)\n\n # Create the ELB, proxies and databases security groups\n # The app security group (as the instance role) will be specific\n # to the application.\n #pylint:disable=unbalanced-tuple-unpacking\n moat_name, vault_name, gate_name, kitchen_door_name = \\\n _get_security_group_names([\n 'moat', 'vault', 'castle-gate', 'kitchen-door'],\n tag_prefix=sg_tag_prefix)\n moat_sg_id, vault_sg_id, gate_sg_id, kitchen_door_sg_id = \\\n _get_security_group_ids(\n [moat_name, vault_name, gate_name, kitchen_door_name],\n tag_prefix, vpc_id=vpc_id, ec2_client=ec2_client)\n\n update_moat_rules = (not moat_sg_id)\n update_gate_rules = (not gate_sg_id)\n update_vault_rules = (not vault_sg_id)\n update_kitchen_door_rules = (not kitchen_door_sg_id)\n\n if not moat_sg_id:\n resp = ec2_client.create_security_group(\n Description='%s ELB' % tag_prefix,\n GroupName=moat_name,\n VpcId=vpc_id,\n DryRun=dry_run)\n moat_sg_id = resp['GroupId']\n LOGGER.info(\"%s created %s security group %s\",\n tag_prefix, moat_name, moat_sg_id)\n if not gate_sg_id:\n resp = ec2_client.create_security_group(\n Description='%s session managers' % tag_prefix,\n GroupName=gate_name,\n VpcId=vpc_id,\n DryRun=dry_run)\n gate_sg_id = resp['GroupId']\n LOGGER.info(\"%s created %s security group %s\",\n tag_prefix, gate_name, gate_sg_id)\n if not vault_sg_id:\n resp = ec2_client.create_security_group(\n Description='%s databases' % tag_prefix,\n GroupName=vault_name,\n VpcId=vpc_id,\n DryRun=dry_run)\n vault_sg_id = resp['GroupId']\n LOGGER.info(\"%s created %s security group %s\",\n tag_prefix, vault_name, vault_sg_id)\n # kitchen_door_sg_id: Kitchen door security group is created later on\n # if we have ssh keys.\n\n resp = ec2_client.describe_security_groups(\n DryRun=dry_run,\n GroupIds=[moat_sg_id, vault_sg_id, gate_sg_id])\n for security_group in resp['SecurityGroups']:\n if security_group['GroupId'] == moat_sg_id:\n # moat rules\n LOGGER.info(\"%s check ingress rules for %s\", tag_prefix, moat_name)\n check_security_group_ingress(security_group, expected_rules=[\n {'port': 80, 'source': '0.0.0.0/0'},\n {'port': 80, 'source': '::/0'},\n {'port': 443, 'source': '0.0.0.0/0'},\n {'port': 443, 'source': '::/0'},\n ],\n tag_prefix=tag_prefix)\n elif security_group['GroupId'] == gate_sg_id:\n # castle-gate rules\n LOGGER.info(\"%s check ingress rules for %s\", tag_prefix, gate_name)\n check_security_group_ingress(security_group, expected_rules=[\n {'port': 80, 'source': moat_sg_id},\n {'port': 443, 'source': moat_sg_id}\n ],\n tag_prefix=tag_prefix)\n elif security_group['GroupId'] == vault_sg_id:\n # vault rules\n LOGGER.info(\"%s check ingress rules for %s\", tag_prefix, vault_name)\n check_security_group_ingress(security_group, expected_rules=[\n {'port': 5432, 'source': gate_sg_id}\n ],\n tag_prefix=tag_prefix)\n\n # moat allow rules\n if update_moat_rules:\n try:\n resp = ec2_client.authorize_security_group_ingress(\n DryRun=dry_run,\n GroupId=moat_sg_id,\n IpPermissions=[{\n 'FromPort': 80,\n 'IpProtocol': 'tcp',\n 'IpRanges': [{\n 'CidrIp': '0.0.0.0/0'\n }],\n 'ToPort': 80\n }, {\n 'FromPort': 80,\n 'IpProtocol': 'tcp',\n 'Ipv6Ranges': [{\n 'CidrIpv6': '::/0',\n }],\n 'ToPort': 80\n }, {\n 'FromPort': 443,\n 'IpProtocol': 'tcp',\n 'IpRanges': [{\n 'CidrIp': '0.0.0.0/0'\n }],\n 'ToPort': 443\n }, {\n 'FromPort': 443,\n 'IpProtocol': 'tcp',\n 'Ipv6Ranges': [{\n 'CidrIpv6': '::/0',\n }],\n 'ToPort': 443\n }])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n\n if update_gate_rules:\n # castle-gate allow rules\n try:\n resp = ec2_client.authorize_security_group_ingress(\n DryRun=dry_run,\n GroupId=gate_sg_id,\n IpPermissions=[{\n 'IpProtocol': 'tcp',\n 'FromPort': 80,\n 'ToPort': 80,\n 'UserIdGroupPairs': [{'GroupId': moat_sg_id}]\n }])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n try:\n resp = ec2_client.authorize_security_group_ingress(\n DryRun=dry_run,\n GroupId=gate_sg_id,\n IpPermissions=[{\n 'IpProtocol': 'tcp',\n 'FromPort': 443,\n 'ToPort': 443,\n 'UserIdGroupPairs': [{'GroupId': moat_sg_id}]\n }])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n try:\n resp = ec2_client.authorize_security_group_egress(\n DryRun=dry_run,\n GroupId=gate_sg_id,\n IpPermissions=[{\n 'IpProtocol': '-1',\n 'IpRanges': [{\n 'CidrIp': '0.0.0.0/0',\n }]}])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n # vault allow rules\n if update_vault_rules:\n try:\n resp = ec2_client.authorize_security_group_ingress(\n DryRun=dry_run,\n GroupId=vault_sg_id,\n IpPermissions=[{\n 'IpProtocol': 'tcp',\n 'FromPort': 5432,\n 'ToPort': 5432,\n 'UserIdGroupPairs': [{'GroupId': gate_sg_id}]\n }])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n try:\n resp = ec2_client.authorize_security_group_egress(\n DryRun=dry_run,\n GroupId=vault_sg_id,\n IpPermissions=[{\n 'IpProtocol': '-1',\n 'IpRanges': [{\n 'CidrIp': '0.0.0.0/0',\n }]}])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n\n # Create uploads and logs S3 buckets\n # XXX create the identities bucket?\n # XXX need to force private.\n if not s3_identities_bucket:\n s3_identities_bucket = '%s-identities' % tag_prefix\n s3_uploads_bucket = tag_prefix\n s3_client = boto3.client('s3')\n if s3_logs_bucket:\n try:\n resp = s3_client.create_bucket(\n ACL='private',\n Bucket=s3_logs_bucket,\n CreateBucketConfiguration={\n 'LocationConstraint': region_name\n })\n LOGGER.info(\"%s created S3 bucket for logs %s\",\n tag_prefix, s3_logs_bucket)\n except botocore.exceptions.ClientError as err:\n LOGGER.info(\"%s found S3 bucket for logs %s\",\n tag_prefix, s3_logs_bucket)\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'BucketAlreadyOwnedByYou':\n raise\n # Apply bucket encryption by default\n found_encryption = False\n try:\n resp = s3_client.get_bucket_encryption(\n Bucket=s3_logs_bucket)\n if resp['ServerSideEncryptionConfiguration']['Rules'][0][\n 'ApplyServerSideEncryptionByDefault'][\n 'SSEAlgorithm'] == 'AES256':\n found_encryption = True\n LOGGER.info(\"%s found encryption AES256 enabled on %s bucket\",\n tag_prefix, s3_logs_bucket)\n except botocore.exceptions.ClientError as err:\n LOGGER.info(\"%s found S3 bucket for logs %s\",\n tag_prefix, s3_logs_bucket)\n if not err.response.get('Error', {}).get('Code', 'Unknown') == \\\n 'ServerSideEncryptionConfigurationNotFoundError':\n raise\n if not found_encryption:\n s3_client.put_bucket_encryption(\n Bucket=s3_logs_bucket,\n ServerSideEncryptionConfiguration={\n 'Rules': [{\n 'ApplyServerSideEncryptionByDefault': {\n 'SSEAlgorithm': 'AES256',\n }\n }]\n })\n LOGGER.info(\"%s enable encryption on %s bucket\",\n tag_prefix, s3_logs_bucket)\n\n # Set versioning and lifecycle policies\n resp = s3_client.get_bucket_versioning(\n Bucket=s3_logs_bucket)\n if 'Status' in resp and resp['Status'] == 'Enabled':\n LOGGER.info(\"%s found versioning enabled on %s bucket\",\n tag_prefix, s3_logs_bucket)\n else:\n s3_client.put_bucket_versioning(\n Bucket=s3_logs_bucket,\n VersioningConfiguration={\n 'MFADelete': 'Disabled',\n 'Status': 'Enabled'\n })\n LOGGER.info(\"%s enable versioning on %s bucket\",\n tag_prefix, s3_logs_bucket)\n found_policy = False\n #pylint:disable=too-many-nested-blocks\n try:\n resp = s3_client.get_bucket_lifecycle_configuration(\n Bucket=s3_logs_bucket)\n for rule in resp['Rules']:\n if rule['Status'] == 'Enabled':\n found_rule = True\n for transition in rule['Transitions']:\n if transition['StorageClass'] == 'GLACIER':\n if transition.get('Days', 0) < 90:\n found_rule = False\n LOGGER.warning(\"%s lifecycle for 'GLACIER'\"\\\n \" is less than 90 days.\", tag_prefix)\n break\n if rule['Expiration'].get('Days', 0) < 365:\n found_rule = False\n LOGGER.warning(\n \"%s lifecycle expiration is less than 365 days.\",\n tag_prefix)\n for transition in rule['NoncurrentVersionTransitions']:\n if transition['StorageClass'] == 'GLACIER':\n if transition.get('NoncurrentDays', 0) < 90:\n found_rule = False\n LOGGER.warning(\n \"%s version lifecycle for 'GLACIER'\"\\\n \" is less than 90 days.\", tag_prefix)\n break\n if rule['NoncurrentVersionExpiration'].get(\n 'NoncurrentDays', 0) < 365:\n found_rule = False\n LOGGER.warning(\"%s lifecycle version expiration is\"\\\n \" less than 365 days.\", tag_prefix)\n if found_rule:\n found_policy = True\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'NoSuchLifecycleConfiguration':\n raise\n if found_policy:\n LOGGER.info(\"%s found lifecycle policy on %s bucket\",\n tag_prefix, s3_logs_bucket)\n else:\n s3_client.put_bucket_lifecycle_configuration(\n Bucket=s3_logs_bucket,\n LifecycleConfiguration={\n \"Rules\": [{\n \"Status\": \"Enabled\",\n \"ID\": \"expire-logs\",\n \"Filter\": {\n \"Prefix\": \"\", # This is required.\n },\n \"Transitions\": [{\n \"Days\": 90,\n \"StorageClass\": \"GLACIER\"\n }],\n \"Expiration\" : {\n \"Days\": 365\n },\n \"NoncurrentVersionTransitions\": [{\n \"NoncurrentDays\": 90,\n \"StorageClass\": \"GLACIER\"\n }],\n 'NoncurrentVersionExpiration': {\n 'NoncurrentDays': 365\n },\n }]})\n LOGGER.info(\"%s update lifecycle policy on %s bucket\",\n tag_prefix, s3_logs_bucket)\n\n # https://docs.aws.amazon.com/elasticloadbalancing/latest/classic/enable-access-logs.html#attach-bucket-policy\n elb_account_ids_per_region = {\n 'us-east-1': '127311923021',\n 'us-east-2': '033677994240',\n 'us-west-1': '027434742980',\n 'us-west-2': '797873946194',\n 'af-south-1': '098369216593',\n 'ca-central-1': '985666609251',\n 'eu-central-1': '054676820928',\n 'eu-west-1': '156460612806',\n 'eu-west-2': '652711504416',\n 'eu-south-1': '635631232127',\n 'eu-west-3': '009996457667',\n 'eu-north-1': '897822967062',\n 'ap-east-1': '754344448648',\n 'ap-northeast-1': '582318560864',\n 'ap-northeast-2': '600734575887',\n 'ap-northeast-3': '383597477331',\n 'ap-southeast-1': '114774131450',\n 'ap-southeast-2': '783225319266',\n 'ap-south-1': '718504428378',\n 'me-south-1': '076674570225',\n 'sa-east-1': '507241528517'\n }\n elb_account_id = elb_account_ids_per_region[region_name]\n s3_client.put_bucket_policy(\n Bucket=s3_logs_bucket,\n Policy=json.dumps({\n \"Version\": \"2008-10-17\",\n \"Id\": \"WriteLogs\",\n \"Statement\": [{\n # billing reports\n \"Effect\": \"Allow\",\n \"Principal\": {\n \"Service\": \"billingreports.amazonaws.com\"\n },\n \"Action\": [\n \"s3:GetBucketAcl\",\n \"s3:GetBucketPolicy\"\n ],\n \"Resource\": \"arn:aws:s3:::%s\" % s3_logs_bucket\n }, {\n \"Effect\": \"Allow\",\n \"Principal\": {\n \"Service\": \"billingreports.amazonaws.com\"\n },\n \"Action\": \"s3:PutObject\",\n \"Resource\": \"arn:aws:s3:::%s/*\" % s3_logs_bucket\n }, {\n # ELB access logs\n \"Effect\": \"Allow\",\n \"Principal\": {\n \"AWS\": \"arn:aws:iam::%s:root\" % elb_account_id\n },\n \"Action\": \"s3:PutObject\",\n \"Resource\":\n \"arn:aws:s3:::%s/var/log/elb/*\" % s3_logs_bucket\n }, {\n \"Effect\": \"Allow\",\n \"Principal\": {\n \"Service\": \"delivery.logs.amazonaws.com\"\n },\n \"Action\": \"s3:PutObject\",\n \"Resource\":\n (\"arn:aws:s3:::%s/var/log/elb/*\" % s3_logs_bucket),\n \"Condition\": {\n \"StringEquals\": {\n \"s3:x-amz-acl\": \"bucket-owner-full-control\"\n }\n }\n }, {\n \"Effect\": \"Allow\",\n \"Principal\": {\n \"Service\": \"delivery.logs.amazonaws.com\"\n },\n \"Action\": \"s3:GetBucketAcl\",\n \"Resource\": \"arn:aws:s3:::%s\" % s3_logs_bucket\n }]\n }))\n\n if s3_uploads_bucket:\n try:\n resp = s3_client.create_bucket(\n ACL='private',\n Bucket=s3_uploads_bucket,\n CreateBucketConfiguration={\n 'LocationConstraint': region_name\n })\n LOGGER.info(\"%s created S3 bucket for uploads %s\",\n tag_prefix, s3_uploads_bucket)\n except botocore.exceptions.ClientError as err:\n LOGGER.info(\"%s found S3 bucket for uploads %s\",\n tag_prefix, s3_uploads_bucket)\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'BucketAlreadyOwnedByYou':\n raise\n\n # Create instance profiles ...\n iam_client = boto3.client('iam')\n # ... for webfront instances\n create_instance_profile(\n create_gate_role(gate_name,\n s3_logs_bucket=s3_logs_bucket, s3_uploads_bucket=s3_uploads_bucket,\n iam_client=iam_client, tag_prefix=tag_prefix),\n iam_client=iam_client, region_name=region_name,\n tag_prefix=tag_prefix, dry_run=dry_run)\n # ... for databases instances\n create_instance_profile(\n create_vault_role(vault_name,\n s3_logs_bucket=s3_logs_bucket, s3_uploads_bucket=s3_uploads_bucket,\n iam_client=iam_client, tag_prefix=tag_prefix),\n iam_client=iam_client, region_name=region_name,\n tag_prefix=tag_prefix, dry_run=dry_run)\n\n if ssh_key_name:\n if not ssh_key_content:\n ssh_key_path = os.path.join(os.getenv('HOME'),\n '.ssh', '%s.pub' % ssh_key_name)\n if os.path.exists(ssh_key_path):\n with open(ssh_key_path, 'rb') as ssh_key_obj:\n ssh_key_content = ssh_key_obj.read()\n else:\n LOGGER.warning(\"%s no content for SSH key %s\",\n tag_prefix, ssh_key_name)\n # import SSH keys\n try:\n resp = ec2_client.import_key_pair(\n DryRun=dry_run,\n KeyName=ssh_key_name,\n PublicKeyMaterial=ssh_key_content)\n LOGGER.info(\"%s imported SSH key %s\", tag_prefix, ssh_key_name)\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidKeyPair.Duplicate':\n raise\n LOGGER.info(\"%s found SSH key %s\", tag_prefix, ssh_key_name)\n\n # ... for sally instances\n create_instance_profile(\n create_logs_role(kitchen_door_name,\n s3_logs_bucket=s3_logs_bucket,\n iam_client=iam_client, tag_prefix=tag_prefix),\n iam_client=iam_client, region_name=region_name,\n tag_prefix=tag_prefix, dry_run=dry_run)\n\n # allows SSH connection to instances for debugging\n update_kitchen_door_rules = (not kitchen_door_sg_id)\n if not kitchen_door_sg_id:\n resp = ec2_client.create_security_group(\n Description='%s SSH access' % tag_prefix,\n GroupName=kitchen_door_name,\n VpcId=vpc_id,\n DryRun=dry_run)\n kitchen_door_sg_id = resp['GroupId']\n LOGGER.info(\"%s created %s security group %s\",\n tag_prefix, kitchen_door_name, kitchen_door_sg_id)\n\n if update_kitchen_door_rules:\n try:\n if sally_ip:\n cidr_block = '%s/32' % sally_ip\n else:\n LOGGER.warning(\"no IP range was specified to restrict\"\\\n \" access to SSH port\")\n cidr_block = '0.0.0.0/0'\n resp = ec2_client.authorize_security_group_ingress(\n DryRun=dry_run,\n GroupId=kitchen_door_sg_id,\n CidrIp=cidr_block,\n IpProtocol='tcp',\n FromPort=22,\n ToPort=22)\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n try:\n resp = ec2_client.authorize_security_group_egress(\n DryRun=dry_run,\n GroupId=kitchen_door_sg_id,\n IpPermissions=[{\n 'IpProtocol': '-1',\n 'IpRanges': [{\n 'CidrIp': '0.0.0.0/0',\n }]}])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n try:\n resp = ec2_client.authorize_security_group_ingress(\n DryRun=dry_run,\n GroupId=gate_sg_id,\n IpPermissions=[{\n 'IpProtocol': 'tcp',\n 'FromPort': 22,\n 'ToPort': 22,\n 'UserIdGroupPairs': [{'GroupId': kitchen_door_sg_id}]\n }])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n try:\n resp = ec2_client.authorize_security_group_ingress(\n DryRun=dry_run,\n GroupId=vault_sg_id,\n IpPermissions=[{\n 'IpProtocol': 'tcp',\n 'FromPort': 22,\n 'ToPort': 22,\n 'UserIdGroupPairs': [{'GroupId': kitchen_door_sg_id}]\n }])\n except botocore.exceptions.ClientError as err:\n if not err.response.get('Error', {}).get(\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\n raise\n\n # Creates encryption keys (KMS) in region\n if not storage_enckey:\n storage_enckey = _get_or_create_storage_enckey(\n region_name, tag_prefix, dry_run=dry_run)\n\n # Create an Application ELB and WAF\n load_balancer_arn = create_elb(\n tag_prefix, web_subnet_by_cidrs, moat_sg_id,\n s3_logs_bucket=s3_logs_bucket,\n tls_priv_key=tls_priv_key, tls_fullchain_cert=tls_fullchain_cert,\n region_name=region_name)\n create_waf(\n tag_prefix,\n elb_arn=load_balancer_arn,\n s3_logs_bucket=s3_logs_bucket,\n region_name=region_name,\n dry_run=dry_run)","def test_create_network_and_subnet(self):\n suffix = datetime.utcnow().strftime('%Y%m%d%H%M%S')\n network_name = TEST_NETWORK_PREFIX + \"_\" + suffix\n network_cidr = TEST_CIDR_PATTERN % 254\n self.__create_network_and_subnet_test_helper__(network_name, network_cidr)","def create_network(layers):\r\n return NeuronNetwork(layers)","def post(self):\n context = request.environ.get('context')\n json = util.copy_project_id_into_json(context, g.json)\n network_obj = dbapi.networks_create(context, json)\n return jsonutils.to_primitive(network_obj), 200, None","def create_network(num_subs):\n\n # Need one host for each subscriber, one for a publisher, and one for a broker\n n_hosts = num_subs + 2\n\n topo = SingleSwitchTopo(n=n_hosts)\n\n return Mininet(topo=topo, controller=OVSController)","def create_platform_network(enode, category, config):\n # Check if this category has a defined netns\n netns = config.get('netns', None)\n if netns is None:\n return\n\n # Create the given network namespace\n enode._docker_exec('ip netns add {}'.format(netns))\n\n # lo should always be up\n enode._docker_exec('ip netns exec {} ip link set dev lo up'.format(netns))","def run(self, network_create_args=None, subnet_create_args=None,\n subnet_cidr_start=None, subnets_per_network=1,\n router_create_args=None):\n subnet_create_args = dict(subnet_create_args or {})\n subnet_create_args[\"start_cidr\"] = subnet_cidr_start\n\n net_topo = self.neutron.create_network_topology(\n network_create_args=(network_create_args or {}),\n router_create_args=(router_create_args or {}),\n router_per_subnet=True,\n subnet_create_args=subnet_create_args,\n subnets_count=subnets_per_network\n )\n\n for router in net_topo[\"routers\"]:\n self.neutron.get_router(router[\"id\"])","def add_network(self, # pylint: disable=too-many-arguments\n network: \"Network\",\n line_of_business: \"LineOfBusiness\",\n platform: \"Platform\",\n cloud_region: \"CloudRegion\" = None,\n tenant: \"Tenant\" = None,\n network_instance_name: str = None,\n subnets: Iterator[\"Subnet\"] = None) -> \"NetworkInstantiation\":\n if not self.active:\n msg = f'Service orchestration status must be \"Active\"'\n raise StatusError(msg)\n\n return NetworkInstantiation.instantiate_ala_carte(\n self,\n network,\n line_of_business,\n platform,\n cloud_region=cloud_region,\n tenant=tenant,\n network_instance_name=network_instance_name,\n subnets=subnets\n )","def create(profile):\n client = boto3client.get(\"ec2\", profile)\n return client.create_internet_gateway()","def test_create_network():\n _network = Network()","def update_network_source(self, network_source_id, update_network_source_details, **kwargs):\n resource_path = \"/networkSources/{networkSourceId}\"\n method = \"PUT\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"if_match\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"update_network_source got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"networkSourceId\": network_source_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"if-match\": kwargs.get(\"if_match\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_network_source_details,\n response_type=\"NetworkSources\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_network_source_details,\n response_type=\"NetworkSources\")","def test_create_router_external_network(self):\n\n # skip test if suite couldn't start from an empty, clean list of allocated IPs (to avoid cascading failures)\n if self.suite_world['allocated_ips']:\n self.skipTest(\"There were pre-existing, not deallocated IPs\")\n\n # First, get external network id\n external_network_id = self.__get_external_network_test_helper__()\n\n # Then, create router\n suffix = datetime.utcnow().strftime('%Y%m%d%H%M%S')\n router_name = TEST_ROUTER_PREFIX + \"_ext_\" + suffix\n self.__create_router_test_helper__(router_name, external_network_id)","def create(self):\n\t\treturn handle_to_object(call_sdk_function('PrlVirtNet_Create'))","def nic_add(args):\n name = args.name\n network = args.network\n config = Kconfig(client=args.client, debug=args.debug, region=args.region, zone=args.zone, namespace=args.namespace)\n k = config.k\n if network is None:\n common.pprint(\"Missing network. Leaving...\", color='red')\n os._exit(1)\n common.pprint(\"Adding Nic to %s...\" % name)\n k.add_nic(name=name, network=network)","def create_VirtualNetwork(network_name, network_subnet, network_mask, vnc, domain, project_name):\n\n project = vnc.project_read(fq_name = [domain, project_name])\n\n vn_obj = vnc_api.VirtualNetwork(name=network_name, parent_obj=project)\n vn_obj.add_network_ipam(vnc_api.NetworkIpam(),\n vnc_api.VnSubnetsType([vnc_api.IpamSubnetType(subnet = vnc_api.SubnetType(network_subnet,network_mask))]))\n\n vnc.virtual_network_create(vn_obj)\n\n print 'Network \"{}\" created successfully\\n'.format(network_name)","def ogrCreateLayer(sourceLayer, pgConn, destinationLayer):\r\n print \" Creating {0}\".format(destinationLayer)\r\n newLayer = pgConn.CreateLayer(destinationLayer)\r\n\r\n lyrDefn = sourceLayer.GetLayerDefn()\r\n for i in range( lyrDefn.GetFieldCount() ):\r\n ##print \"Creating field: {0}\".format(lyrDefn.GetFieldDefn( i ).GetName())\r\n\r\n fieldName = lyrDefn.GetFieldDefn( i ).GetName()\r\n fieldType = lyrDefn.GetFieldDefn( i ).GetType()\r\n newField = ogr.FieldDefn(fieldName, fieldType)\r\n newLayer.CreateField(newField)","def new(name, source):","def mutate(self, info, input):\n # Convert input to dictionary\n data = api_utils.input_to_dictionary(input)\n data_source_type = Operation('ModelDataSourceType').create(**data)\n return CreateDataSourceType(data_source_type=data_source_type)","def test_add_network(self):\n pass","def fusion_api_create_ethernet_network(self, body, api=None, headers=None):\n return self.ethernet_network.create(body, api, headers)","def _create_network(self, name):\n network = self.network(self.num_actions, self.quantile_embedding_dim,\n name=name)\n return network","def fusion_api_create_fc_network(self, body, api=None, headers=None):\n return self.fc_network.create(body, api, headers)","def test_create_router_no_external_network_and_add_network_port(self):\n # Create Router\n suffix = datetime.utcnow().strftime('%Y%m%d%H%M%S')\n router_name = TEST_ROUTER_PREFIX + \"_ports_\" + suffix\n router_id = self.__create_router_test_helper__(router_name)\n\n # Create Network with only one subnet\n network_name = TEST_NETWORK_PREFIX + \"_\" + suffix\n network_cidr = TEST_CIDR_PATTERN % 253\n network_id, subnet_id = self.__create_network_and_subnet_test_helper__(network_name, network_cidr)\n\n port_id = self.neutron_operations.add_interface_router(router_id, subnet_id)\n self.test_world['ports'].append(port_id)","def add_source(ctx, username, id, features, no_validation, token=None, indent=None):\n mapbox_api = _get_api()\n mapbox_token = _get_token(token)\n url = (\n f\"{mapbox_api}/tilesets/v1/sources/{username}/{id}?access_token={mapbox_token}\"\n )\n\n with tempfile.TemporaryFile() as file:\n for feature in features:\n if not no_validation:\n utils.validate_geojson(feature)\n file.write((json.dumps(feature) + \"\\n\").encode(\"utf-8\"))\n\n file.seek(0)\n m = MultipartEncoder(fields={\"file\": (\"file\", file)})\n resp = requests.post(\n url,\n data=m,\n headers={\n \"Content-Disposition\": \"multipart/form-data\",\n \"Content-type\": m.content_type,\n },\n )\n\n if resp.status_code == 200:\n click.echo(json.dumps(resp.json(), indent=indent))\n else:\n raise errors.TilesetsError(resp.text)","def create_network_precommit(self, mech_context):\n\n LOG.debug(\"create_network_precommit: called\")\n network = mech_context.current\n context = mech_context._plugin_context\n tenant_id = network['tenant_id']\n network_id = network['id']\n\n segments = mech_context.network_segments\n # currently supports only one segment per network\n segment = segments[0]\n\n network_type = segment['network_type']\n vlan_id = segment['segmentation_id']\n segment_id = segment['id']\n\n if network_type != 'vlan':\n raise Exception(\n _(\"SeaMicro Mechanism: failed to create network, \"\n \"only network type vlan is supported\"))\n\n try:\n seamicro_db.create_network(context, network_id, vlan_id,\n segment_id, network_type, tenant_id)\n except Exception:\n LOG.exception(\n _LE(\"SeaMicro Mechanism: failed to create network in db\"))\n raise Exception(\n _(\"SeaMicro Mechanism: create_network_precommit failed\"))\n\n LOG.info(_LI(\"create network (precommit): %(network_id)s \"\n \"of network type = %(network_type)s \"\n \"with vlan = %(vlan_id)s \"\n \"for tenant %(tenant_id)s\"),\n {'network_id': network_id,\n 'network_type': network_type,\n 'vlan_id': vlan_id,\n 'tenant_id': tenant_id})","def create(self, objectType, initialParameters):\n command_line = 'rsg create -ot=\"%s\" -pl=\"%s\" -ht=\"%s\"' % (\n objectType, initialParameters, self.host_name)\n return self._execTool(command_line)","def create_connection(location=None, bandwidth=None, connectionName=None):\n pass","def create_high_security_network(context):\n subnetworks = []\n private_ip_google_access = context.properties.get('privateIpGoogleAccess', False)\n for region in FIRECLOUD_NETWORK_REGIONS:\n subnetworks.append({\n # We append the region to the subnetwork's DM resource name, since\n # each resource name needs to be globally unique within the deployment.\n 'resourceName': FIRECLOUD_VPC_SUBNETWORK_NAME + '_' + region,\n # We want all subnetworks to have the same object name, since this most\n # closely mirrors how auto-mode subnets work and is what PAPI expects.\n 'name': FIRECLOUD_VPC_SUBNETWORK_NAME,\n 'region': region,\n 'ipCidrRange': FIRECLOUD_NETWORK_REGIONS[region],\n 'enableFlowLogs': context.properties.get('enableFlowLogs', False),\n 'privateIpGoogleAccess': private_ip_google_access\n })\n\n return [{\n 'type': 'templates/network.py',\n 'name': 'fc-network',\n 'properties': {\n 'resourceName': 'network',\n 'name': FIRECLOUD_VPC_NETWORK_NAME,\n 'projectId': '$(ref.fc-project.projectId)',\n 'autoCreateSubnetworks': False,\n 'subnetworks': subnetworks,\n # We pass the dependsOn list into the network template as a\n # parameter. Deployment Manager doesn't support dependsOn for\n # template-call nodes, so we can't have this resource itself depend on\n # the project-wide resources.\n 'dependsOn': '$(ref.fc-project.resourceNames)',\n 'createCustomStaticRoute': private_ip_google_access\n },\n }]","def test_add_flow_request_with_sources(self):\n res = self._add_flow_request(flow_request=self.flow_request)\n self.assertEqual(res.status_code, 201)\n flow_request = res.json()\n destination = Destination.objects.get(name='Destination 1')\n self.assertEqual(flow_request['flow_id'], self.flow_request['flow_id'])\n self.assertEqual(flow_request['status'], 'PE')\n self.assertDictEqual(flow_request['profile'], self.flow_request['profile'])\n self.assertEqual(FlowRequest.objects.all().count(), 4)\n self.assertEqual(ConfirmationCode.objects.all().count(), 1)\n self.assertEqual(FlowRequest.objects.get(flow_id=flow_request['flow_id']).destination, destination)\n self.assertEqual(FlowRequest.objects.get(flow_id=flow_request['flow_id']).sources.count(), 1)\n source = FlowRequest.objects.get(flow_id=flow_request['flow_id']).sources.first()\n self.assertDictEqual(\n {'source_id': source.source_id, 'name': source.name},\n {'source_id': SOURCE_1_ID, 'name': SOURCE_1_NAME}\n )","def test_networking_project_network_tag_create(self):\n pass","def start_network(self):\n try:\n self.topo.build_topo()\n except:\n error('Cannot build the topology.')\n try:\n self.net = IPNet(topo=self.topo, use_v4=False, use_v6=True)\n self.net.start()\n except:\n self.stop_network()\n error('Cannot start the network.')","def list_network_sources(self, compartment_id, **kwargs):\n resource_path = \"/networkSources\"\n method = \"GET\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"page\",\n \"limit\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"list_network_sources got unknown kwargs: {!r}\".format(extra_kwargs))\n\n query_params = {\n \"compartmentId\": compartment_id,\n \"page\": kwargs.get(\"page\", missing),\n \"limit\": kwargs.get(\"limit\", missing)\n }\n query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None}\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n query_params=query_params,\n header_params=header_params,\n response_type=\"list[NetworkSourcesSummary]\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n query_params=query_params,\n header_params=header_params,\n response_type=\"list[NetworkSourcesSummary]\")","def __init__(__self__, *,\n id: str,\n source: str):\n pulumi.set(__self__, \"id\", id)\n pulumi.set(__self__, \"source\", 'Azure')","def run(self, network_create_args=None, subnet_create_args=None,\n subnet_cidr_start=None, subnets_per_network=1):\n network = self.neutron.create_network(**(network_create_args or {}))\n for _ in range(subnets_per_network):\n self.neutron.create_subnet(network[\"id\"],\n start_cidr=subnet_cidr_start,\n **(subnet_create_args or {}))\n self.neutron.list_subnets()","def add_Circuit(self, name, circuit_type, neuropil = None, data_source = None):\n assert isinstance(name, str), 'name must be of str type'\n self._database_writeable_check()\n connect_DataSource = self._default_DataSource if data_source is None \\\n else self._get_obj_from_str(data_source)\n if connect_DataSource is None:\n raise TypeError('Default DataSource is missing.')\n self._uniqueness_check('Circuit', unique_in = connect_DataSource,\n name = name)\n\n circuit_info = {'name': name}\n \n batch = self.graph.batch()\n node_name = _to_var_name('Circuit_{}'.format(name))\n plural = getattr(models, circuit_type).element_plural\n batch[node_name] = getattr(batch, plural).create(**circuit_info)\n\n # Link subsystem if specified\n if neuropil is not None:\n if isinstance(neuropil, str):\n neuropil_obj = self.get('Neuropil', neuropil, connect_DataSource)\n elif isinstance(neuropil, models.Neuropil):\n if self._is_in_datasource(connect_DataSource, neuropil):\n neuropil_obj = neuropil\n else:\n raise ValueError(\n 'Neuropil {} with rid {} to be linked with subregion is \\\n not in the same datasource {} version {}'.format(\n neuropil.name, neuropil._id,\n connect_DataSource.name, connect_DataSource.version))\n self.link_with_batch(batch, neuropil_obj, batch[:node_name], 'Owns')\n\n # Link data_source\n self.link_with_batch(batch, connect_DataSource, batch[:node_name],\n 'Owns')\n\n circuit = batch['${}'.format(node_name)]\n batch.commit(20)\n\n self.set('Circuit', name, circuit, data_source = connect_DataSource)\n return circuit","def run(self, network_create_args=None):\n network = self.neutron.create_network(**(network_create_args or {}))\n self.neutron.delete_network(network[\"id\"])","def network_create_event(self, network_info):\n net = network_info['network']\n net_id = net['id']\n net_name = net.get('name')\n network_db_elem = self.get_network(net_id)\n # Check if the source of network creation is FW and if yes, skip\n # this event.\n # Check if there's a way to read the DB from service class\n # TODO(padkrish)\n if self.fw_api.is_network_source_fw(network_db_elem, net_name):\n LOG.info(_LI(\"Service network %s, returning\"), net_name)\n return\n self.network[net_id] = {}\n self.network[net_id].update(net)\n\n net_name = net.get('name')\n tenant_id = net.get('tenant_id')\n\n # Extract segmentation_id from the network name\n net_ext_name = self.cfg.dcnm.dcnm_net_ext\n nobj = re.search(net_ext_name, net_name)\n try:\n seg_id = int((net_name[nobj.start(0) + len(net_ext_name) - 1:]\n if nobj else None))\n except (IndexError, TypeError, ValueError):\n seg_id = None\n\n # Check if network is already created.\n query_net = self.get_network_by_segid(seg_id) if seg_id else None\n if query_net:\n # The network is already created no need to process the event.\n if query_net.source.lower() == 'dcnm':\n # DCNM created the network. Only update network id in database.\n prev_id = query_net.network_id\n params = dict(columns=dict(network_id=net_id))\n self.update_network(prev_id, **params)\n\n # Update the network cache.\n prev_info = self.network.pop(prev_id)\n prev_info['id'] = net_id\n self.network[net_id] = prev_info\n\n # Update the network name. After extracting the segmentation_id\n # no need to keep it in the name. Removing it and update\n # the network.\n updated_net_name = (\n net_name[:nobj.start(0) + len(net_ext_name) - 1])\n try:\n body = {'network': {'name': updated_net_name, }}\n dcnm_net = self.neutronclient.update_network(\n net_id, body=body).get('network')\n LOG.debug('Updated network %(network)s', dcnm_net)\n except Exception as exc:\n LOG.exception(_LE('Failed to update network '\n '%(network)s. Reason %(err)s.'),\n {'network': updated_net_name,\n 'err': str(exc)})\n return\n\n LOG.info(_LI('network_create_event: network %(name)s was created '\n 'by %(source)s. Ignoring processing the event.'),\n {'name': net_name, 'source': 'dcnm'})\n return\n\n # Check if project (i.e. tenant) exist.\n tenant_name = self.get_project_name(tenant_id)\n if not tenant_name:\n LOG.error(_LE('Failed to create network %(name)s. Project '\n '%(tenant_id)s does not exist.'),\n {'name': net_name, 'tenant_id': tenant_id})\n return\n\n pseg_id = self.network[net_id].get('provider:segmentation_id')\n seg_id = self._get_segmentation_id(net_id, pseg_id, 'openstack')\n self.network[net_id]['segmentation_id'] = seg_id\n try:\n cfgp, fwd_mod = self.dcnm_client.get_config_profile_for_network(\n net.get('name'))\n self.network[net_id]['config_profile'] = cfgp\n self.network[net_id]['fwd_mod'] = fwd_mod\n self.add_network_db(net_id, self.network[net_id],\n 'openstack',\n constants.RESULT_SUCCESS)\n LOG.debug('network_create_event: network=%s', self.network)\n except dexc.DfaClientRequestFailed:\n # Fail to get config profile from DCNM.\n # Save the network info with failure result and send the request\n # to DCNM later.\n self.add_network_db(net_id, self.network[net_id], 'openstack',\n constants.CREATE_FAIL)\n LOG.error(_LE('Failed to create network=%s.'), self.network)","def initialize_network(self, cidr, is_external):\n raise NotImplementedError()","def create_network(\n self, is_internal: bool = True\n ) -> None:\n if self.network:\n self.log.warn(f\"Network {self.network_name} was already created!\")\n return\n\n existing_networks = self.docker.networks.list(\n names=[self.network_name]\n )\n if existing_networks:\n if len(existing_networks) > 1:\n self.log.error(\n f\"Found multiple ({len(existing_networks)}) existing \"\n f\"networks {self.network_name}. Please delete all or all \"\n \"but one before starting the server!\")\n exit(1)\n self.log.info(f\"Network {self.network_name} already exists! Using \"\n \"existing network\")\n self.network = existing_networks[0]\n self.network.reload() # required to initialize containers in netw\n else:\n self.network = self.docker.networks.create(\n self.network_name,\n driver=\"bridge\",\n internal=is_internal,\n scope=\"local\",\n )","def run(self, network_update_args, network_create_args=None):\n network = self.neutron.create_network(**(network_create_args or {}))\n self.neutron.update_network(network[\"id\"], **network_update_args)","def create_network_profile(projectArn=None, name=None, description=None, type=None, uplinkBandwidthBits=None, downlinkBandwidthBits=None, uplinkDelayMs=None, downlinkDelayMs=None, uplinkJitterMs=None, downlinkJitterMs=None, uplinkLossPercent=None, downlinkLossPercent=None):\n pass","def createLotsNetworks(proxy_url, sessiontoken,network_number):\n myHeader = {\"Content-Type\": \"application/json\",\"Accept\": \"application/json\", 'csp-auth-token': sessiontoken}\n for x in range(0,network_number):\n display_name = \"network-name\"+str(x)\n myURL = (proxy_url + \"/policy/api/v1/infra/tier-1s/cgw/segments/\" + display_name)\n # '/tier-1s/cgw' might only be applicable for multi tier-1s architecture. To be confirmed.\n # print(myURL)\n json_data = {\n \"subnets\":[{\"gateway_address\":\"10.200.\"+str(x)+\".1/24\"}],\n \"type\":\"ROUTED\",\n \"display_name\":display_name,\n \"advanced_config\":{\"connectivity\":\"ON\"},\n \"id\":\"network-test\"+str(x)\n }\n response = requests.put(myURL, headers=myHeader, json=json_data)\n json_response_status_code = response.status_code","def CreateRequests(self, args):\n\n target_vpn_gateway_ref = self.TARGET_VPN_GATEWAY_ARG.ResolveAsResource(\n args,\n self.resources,\n scope_lister=compute_flags.GetDefaultScopeLister(self.compute_client,\n self.project))\n network_ref = self.NETWORK_ARG.ResolveAsResource(args, self.resources)\n\n request = self.messages.ComputeTargetVpnGatewaysInsertRequest(\n project=self.project,\n region=target_vpn_gateway_ref.region,\n targetVpnGateway=self.messages.TargetVpnGateway(\n description=args.description,\n name=target_vpn_gateway_ref.Name(),\n network=network_ref.SelfLink()\n ))\n return [request]","def _source_subnet(value):\n match = SOURCE_SUBNET_RE.match(value)\n if match:\n named_groups = match.groupdict()\n subnet_id = named_groups['SubnetID']\n role = named_groups['Role']\n registration_status = named_groups['RegistrationStatus']\n return SourceSubnet(\n role = role,\n registration_status = registration_status,\n subnet_id = subnet_id\n )\n\n raise argparse.ArgumentTypeError('Given argument \"%s\" is not a valid source subnet' % value)","def empty_network(network_id=NETWORK_ID):\n return make_net_model({\"id\": network_id,\n \"subnets\": [],\n \"ports\": [],\n \"tenant_id\": \"calico\",\n \"mtu\": neutron_constants.DEFAULT_NETWORK_MTU})","def testCreateWmsSource(self):\n\n path = '/minerva_source_wms'\n name = 'testWMS'\n username = ''\n password = ''\n baseURL = 'http://demo.boundlessgeo.com/geoserver/ows'\n params = {\n 'name': name,\n 'username': username,\n 'password': password,\n 'baseURL': baseURL\n }\n response = self.request(path=path, method='POST', params=params, user=self._user)\n self.assertStatusOk(response)\n wmsSource = response.json\n minerva_metadata = wmsSource['meta']['minerva']\n self.assertEquals(wmsSource['name'], name, 'incorrect wms source name')\n self.assertEquals(minerva_metadata['source_type'], 'wms', 'incorrect wms source type')\n self.assertEquals(minerva_metadata['wms_params']['base_url'], baseURL, 'incorrect wms source baseURL')","def create_community_resource(dataset_id, cr_file):\n logging.debug(\"Creating a community resource on dataset %s\", dataset_id)\n headers = {\"X-API-KEY\": DATAGOUV_API_KEY}\n files = {\"file\": open(cr_file, \"rb\")}\n url = f\"{DATAGOUV_API}/datasets/{dataset_id}/upload/community/\"\n\n ret = requests.post(url, headers=headers, files=files)\n ret.raise_for_status()\n json = ret.json()\n\n logging.debug(\n \"Created a new community resource %s on dataset %s\", json[\"id\"], dataset_id\n )\n\n return json","def create_stac_item(\n source: Union[str, DatasetReader, DatasetWriter, WarpedVRT, MemoryFile],\n input_datetime: Optional[datetime.datetime] = None,\n extensions: Optional[List[str]] = None,\n collection: Optional[str] = None,\n collection_url: Optional[str] = None,\n properties: Optional[Dict] = None,\n id: Optional[str] = None,\n assets: Optional[Dict[str, pystac.Asset]] = None,\n asset_name: str = \"asset\",\n asset_roles: Optional[List[str]] = None,\n asset_media_type: Optional[Union[str, pystac.MediaType]] = None,\n asset_href: Optional[str] = None,\n with_proj: bool = False,\n with_raster: bool = False,\n raster_max_size: int = 1024,\n) -> pystac.Item:\n properties = properties or {}\n extensions = extensions or []\n\n with ExitStack() as ctx:\n if isinstance(source, (DatasetReader, DatasetWriter, WarpedVRT)):\n dataset = source\n else:\n dataset = ctx.enter_context(rasterio.open(source))\n\n if dataset.gcps[0]:\n src_dst = ctx.enter_context(\n WarpedVRT(\n dataset,\n src_crs=dataset.gcps[1],\n src_transform=transform.from_gcps(dataset.gcps[0]),\n )\n )\n else:\n src_dst = dataset\n\n meta = get_metadata(src_dst)\n\n media_type = (\n get_media_type(dataset) if asset_media_type == \"auto\" else asset_media_type\n )\n\n # add projection properties\n if with_proj:\n properties.update(\n {\n f\"proj:{name}\": value\n for name, value in get_projection_info(src_dst).items()\n }\n )\n extensions.append(\n f\"https://stac-extensions.github.io/projection/{PROJECTION_EXT_VERSION}/schema.json\",\n )\n\n # add raster properties\n raster_info = {}\n if with_raster:\n raster_info = {\"raster:bands\": get_raster_info(dataset)}\n extensions.append(\n f\"https://stac-extensions.github.io/raster/{RASTER_EXT_VERSION}/schema.json\",\n )\n\n # item\n item = pystac.Item(\n id=id or os.path.basename(dataset.name),\n geometry=meta[\"footprint\"],\n bbox=meta[\"bbox\"],\n collection=collection,\n stac_extensions=extensions,\n datetime=input_datetime,\n properties=properties,\n )\n\n # if we add a collection we MUST add a link\n if collection:\n item.add_link(\n pystac.Link(\n pystac.RelType.COLLECTION,\n collection_url or collection,\n media_type=pystac.MediaType.JSON,\n )\n )\n\n # item.assets\n if assets:\n for key, asset in assets.items():\n item.add_asset(\n key=key, asset=asset,\n )\n\n else:\n item.add_asset(\n key=asset_name,\n asset=pystac.Asset(\n href=asset_href or dataset.name,\n media_type=media_type,\n extra_fields=raster_info,\n ),\n )\n\n return item","def __init__(__self__, *,\n managed_network_name: pulumi.Input[str],\n resource_group_name: pulumi.Input[str],\n kind: Optional[pulumi.Input[Union[str, 'Kind']]] = None,\n location: Optional[pulumi.Input[str]] = None,\n managed_network_group_name: Optional[pulumi.Input[str]] = None,\n management_groups: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceIdArgs']]]] = None,\n subnets: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceIdArgs']]]] = None,\n subscriptions: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceIdArgs']]]] = None,\n virtual_networks: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceIdArgs']]]] = None):\n pulumi.set(__self__, \"managed_network_name\", managed_network_name)\n pulumi.set(__self__, \"resource_group_name\", resource_group_name)\n if kind is not None:\n pulumi.set(__self__, \"kind\", kind)\n if location is not None:\n pulumi.set(__self__, \"location\", location)\n if managed_network_group_name is not None:\n pulumi.set(__self__, \"managed_network_group_name\", managed_network_group_name)\n if management_groups is not None:\n pulumi.set(__self__, \"management_groups\", management_groups)\n if subnets is not None:\n pulumi.set(__self__, \"subnets\", subnets)\n if subscriptions is not None:\n pulumi.set(__self__, \"subscriptions\", subscriptions)\n if virtual_networks is not None:\n pulumi.set(__self__, \"virtual_networks\", virtual_networks)","def CreateRequests(self, args):\n\n image = self.messages.Image(\n name=args.name,\n description=args.description,\n sourceType=self.messages.Image.SourceTypeValueValuesEnum.RAW,\n family=args.family)\n\n csek_keys = csek_utils.CsekKeyStore.FromArgs(\n args, self._ALLOW_RSA_ENCRYPTED_CSEK_KEYS)\n if csek_keys:\n image_ref = self.resources.Parse(args.name, collection='compute.images')\n image.imageEncryptionKey = csek_utils.MaybeToMessage(\n csek_keys.LookupKey(image_ref,\n raise_if_missing=args.require_csek_key_create),\n self.compute_client.apitools_client)\n\n # Validate parameters.\n if args.source_disk_zone and not args.source_disk:\n raise exceptions.ToolException(\n 'You cannot specify [--source-disk-zone] unless you are specifying '\n '[--source-disk].')\n\n if args.source_disk and args.source_uri:\n raise exceptions.ConflictingArgumentsException(\n '--source-uri', '--source-disk')\n\n if not (args.source_disk or args.source_uri):\n raise exceptions.MinimumArgumentException(\n ['--source-uri', '--source-disk'],\n 'Please specify either the source disk or the Google Cloud Storage '\n 'URI of the disk image.'\n )\n\n # TODO(user): use resources.REGISTRY.Parse() for GCS URIs (b/30086260).\n if args.source_uri:\n source_uri = utils.NormalizeGoogleStorageUri(args.source_uri)\n image.rawDisk = self.messages.Image.RawDiskValue(source=source_uri)\n else:\n source_disk_ref = flags.SOURCE_DISK_ARG.ResolveAsResource(\n args, self.resources,\n scope_lister=compute_flags.GetDefaultScopeLister(\n self.compute_client, self.project))\n image.sourceDisk = source_disk_ref.SelfLink()\n image.sourceDiskEncryptionKey = csek_utils.MaybeLookupKeyMessage(\n csek_keys, source_disk_ref, self.compute_client.apitools_client)\n\n if args.licenses:\n image.licenses = args.licenses\n\n guest_os_features = getattr(args, 'guest_os_features', [])\n if guest_os_features:\n guest_os_feature_messages = []\n for feature in guest_os_features:\n gf_type = self.messages.GuestOsFeature.TypeValueValuesEnum(feature)\n guest_os_feature = self.messages.GuestOsFeature()\n guest_os_feature.type = gf_type\n guest_os_feature_messages.append(guest_os_feature)\n image.guestOsFeatures = guest_os_feature_messages\n\n request = self.messages.ComputeImagesInsertRequest(\n image=image,\n project=self.project)\n\n return [request]","def request_workspace_add(self, request):\n user_id = request['user_id']\n alias = request['alias'] \n source_uuid = request['source'] \n# print('###', user_id)\n# print('###', alias)\n# print('###', source_uuid)\n \n response = self.copy_workspace(user_id, source_uuid=source_uuid, target_alias=alias)\n \n return response","def new_network(router_simulator):\n router = input('Enter router name: ')\n network = input('Enter network: ')\n try:\n distance = int(input('Enter distance: '))\n except ValueError:\n print('Distance not valid.')\n return\n\n try:\n router_simulator.add_network(router, network, distance)\n except KeyError:\n print('Router was not found.')","def __init__(__self__, *,\n kind: str,\n name: Optional[str] = None,\n source_id: Optional[str] = None):\n pulumi.set(__self__, \"kind\", kind)\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if source_id is not None:\n pulumi.set(__self__, \"source_id\", source_id)","def AddNetwork(parser):\n parser.add_argument(\n '--network',\n help=(\n 'Network in the current project that the instance will be part '\n 'of. To specify using a network with a shared VPC, use the full '\n \"URL of the network. For an example host project, 'testproject', \"\n \"and shared network, 'testsharednetwork', this would use the \"\n 'form: '\n '`--network`=`projects/testproject/global/networks/'\n 'testsharednetwork`'\n ),\n )","def __init__(__self__, *,\n machine_name: str,\n source: str,\n source_computer_id: str,\n vmuuid: str,\n workspace_id: str):\n pulumi.set(__self__, \"machine_name\", machine_name)\n pulumi.set(__self__, \"source\", 'OnPremise')\n pulumi.set(__self__, \"source_computer_id\", source_computer_id)\n pulumi.set(__self__, \"vmuuid\", vmuuid)\n pulumi.set(__self__, \"workspace_id\", workspace_id)","def copy_to_region(self, region, name=None):\r\n if region.name == self.region:\r\n raise BotoClientError('Unable to copy to the same Region')\r\n conn_params = self.connection.get_params()\r\n rconn = region.connect(**conn_params)\r\n sg = rconn.create_security_group(name or self.name, self.description)\r\n source_groups = []\r\n for rule in self.rules:\r\n grant = rule.grants[0]\r\n for grant in rule.grants:\r\n if grant.name:\r\n if grant.name not in source_groups:\r\n source_groups.append(grant.name)\r\n sg.authorize(None, None, None, None, grant)\r\n else:\r\n sg.authorize(rule.ip_protocol, rule.from_port, rule.to_port,\r\n grant.cidr_ip)\r\n return sg","def create(ctx, iface, resource_config, **_):\n resource_id = \\\n utils.get_resource_id(\n ctx.node,\n ctx.instance,\n resource_config.get(VPN_CONNECTION_ID),\n use_instance_id=True\n )\n utils.update_resource_id(ctx.instance, resource_id)\n # Actually create the resource\n create_response = iface.create(resource_config)\n ctx.instance.runtime_properties['create_response'] = \\\n utils.JsonCleanuper(create_response).to_dict()\n ctx.instance.runtime_properties['VPN_CONNECTION_ID'] = \\\n resource_config.get(VPN_CONNECTION_ID)\n ctx.instance.runtime_properties['DESTINATION_CIDR_BLOCK'] = \\\n resource_config.get(DESTINATION_CIDR_BLOCK)","def GenerateAssetForCreateRequest(args):\n module = dataplex_api.GetMessageModule()\n resource_spec_field = module.GoogleCloudDataplexV1AssetResourceSpec\n resource_spec = module.GoogleCloudDataplexV1AssetResourceSpec(\n name=args.resource_name,\n type=resource_spec_field.TypeValueValuesEnum(args.resource_type),\n )\n request = module.GoogleCloudDataplexV1Asset(\n description=args.description,\n displayName=args.display_name,\n labels=dataplex_api.CreateLabels(module.GoogleCloudDataplexV1Asset, args),\n resourceSpec=resource_spec,\n )\n discovery = GenerateDiscoverySpec(args)\n if discovery != module.GoogleCloudDataplexV1AssetDiscoverySpec():\n setattr(request, 'discoverySpec', discovery)\n return request","def _create_graph(netlist):\n G = nx.Graph()\n for t in netlist:\n G.add_edges_from([(t.name, t.drain), (t.name, t.gate), (t.name, t.source)])\n return G","def create_network(model_file=DEFAULT_MODEL_FILE, pretrained=DEFAULT_PRETRAINED, *args, **kwargs):\n net = imagenet_classifier(*args,**kwargs)\n net.set_phase_test()\n net.set_mode_cpu()\n return net","def make_network_set(name, networkUris=[]):\n\n return {\n 'name': name,\n 'type': 'network-set',\n 'nativeNetworkUri': None,\n 'networkUris': networkUris[:],\n 'connectionTemplateUri': None}"],"string":"[\n \"def network_create(request, **kwargs):\\n LOG.debug(\\\"network_create(): kwargs = %s\\\", kwargs)\\n if 'tenant_id' not in kwargs:\\n kwargs['tenant_id'] = request.user.project_id\\n body = {'network': kwargs}\\n network = neutronclient(request).create_network(body=body).get('network')\\n return Network(network)\",\n \"def new_source(self, name):\\n params = {\\\"name\\\": name}\\n return JSONRPCRequest(self, \\\"newSource\\\", params)\",\n \"def copy_network(source_net):\\n return make_net_model({\\\"id\\\": source_net.id,\\n \\\"subnets\\\": source_net.subnets,\\n \\\"ports\\\": source_net.ports,\\n \\\"tenant_id\\\": source_net.tenant_id,\\n \\\"mtu\\\": source_net.mtu})\",\n \"def create_network(self, body=None):\\r\\n return self.post(self.networks_path, body=body)\",\n \"def network_create(auth=None, **kwargs):\\n cloud = get_operator_cloud(auth)\\n kwargs = _clean_kwargs(keep_name=True, **kwargs)\\n return cloud.create_network(**kwargs)\",\n \"def create_network(self, tenant_id, network):\\n self.create_network_bulk(tenant_id, [network])\",\n \"def ex_create_network(self, resource_group, network, extra=None, location=None):\\n if location is None:\\n if self.default_location:\\n location = self.default_location\\n else:\\n raise ValueError(\\\"location is required.\\\")\\n target = \\\"/subscriptions/%s/resourceGroups/%s/providers/Microsoft.Network/virtualNetworks/%s\\\" % (\\n self.subscription_id, resource_group, network)\\n params = {\\\"api-version\\\": \\\"2016-03-30\\\"}\\n data = {\\n \\\"tags\\\": {},\\n \\\"location\\\": location.id,\\n }\\n\\n if extra:\\n data[\\\"properties\\\"] = extra\\n\\n r = self.connection.request(action=target,\\n params=params,\\n data=data,\\n method=\\\"PUT\\\")\\n\\n while r.object is None:\\n time.sleep(1)\\n\\n return AzureNetwork(r.object[\\\"id\\\"], r.object[\\\"name\\\"], r.object[\\\"location\\\"], r.object[\\\"properties\\\"])\",\n \"def Create(self):\\n\\n gateway = None\\n netmask = None\\n\\n self._AcquireNetworkDetails()\\n\\n if self.is_vpc:\\n # Create a VPC first\\n\\n cidr = '10.0.0.0/16'\\n vpc = self.cs.create_vpc(self.vpc_name,\\n self.zone_id,\\n cidr,\\n self.vpc_offering_id,\\n self.project_id)\\n self.vpc_id = vpc['id']\\n gateway = '10.0.0.1'\\n netmask = '255.255.255.0'\\n\\n acl = self.cs.get_network_acl('default_allow', self.project_id)\\n assert acl, \\\"Default allow ACL not found\\\"\\n\\n\\n # Create the network\\n network = self.cs.create_network(self.network_name,\\n self.network_offering_id,\\n self.zone_id,\\n self.project_id,\\n self.vpc_id,\\n gateway,\\n netmask,\\n acl['id'])\\n\\n\\n\\n assert network, \\\"No network could be created\\\"\\n\\n self.network_id = network['id']\\n self.id = self.network_id\",\n \"def create_network(self, context, network):\\n LOG.debug(_(\\\"NeutronRestProxyV2: create_network() called\\\"))\\n\\n self._warn_on_state_status(network['network'])\\n\\n with context.session.begin(subtransactions=True):\\n # Validate args\\n tenant_id = self._get_tenant_id_for_create(context,\\n network[\\\"network\\\"])\\n\\n # create network in DB\\n new_net = super(NeutronRestProxyV2, self).create_network(context,\\n network)\\n self._process_l3_create(context, new_net, network['network'])\\n mapped_network = self._get_mapped_network_with_subnets(new_net,\\n context)\\n\\n # create network on the network controller\\n self.servers.rest_create_network(tenant_id, mapped_network)\\n\\n # return created network\\n return new_net\",\n \"def fusion_api_create_network_set(self, body, api=None, headers=None):\\n return self.network_set.create(body, api, headers)\",\n \"def create_default_network(context):\\n return [{\\n 'type': 'templates/network.py',\\n 'name': 'fc-network',\\n 'properties': {\\n 'resourceName': 'network',\\n 'name': 'network',\\n 'projectId': '$(ref.fc-project.projectId)',\\n 'autoCreateSubnetworks': True,\\n # We pass the dependsOn list into the network template as a\\n # parameter. Deployment Manager doesn't support dependsOn for\\n # template-call nodes, so we can't have this resource itself depend on\\n # the project-wide resources.\\n 'dependsOn': '$(ref.fc-project.resourceNames)',\\n },\\n }]\",\n \"def create_network(self, context, network):\\n\\n LOG.debug(_(\\\"QuantumRestProxyV2: create_network() called\\\"))\\n\\n # Validate args\\n tenant_id = self._get_tenant_id_for_create(context, network[\\\"network\\\"])\\n net_name = network[\\\"network\\\"][\\\"name\\\"]\\n if network[\\\"network\\\"][\\\"admin_state_up\\\"] is False:\\n LOG.warning(_(\\\"Network with admin_state_up=False are not yet \\\"\\n \\\"supported by this plugin. Ignoring setting for \\\"\\n \\\"network %s\\\"), net_name)\\n\\n # create in DB\\n new_net = super(QuantumRestProxyV2, self).create_network(context,\\n network)\\n\\n # create on networl ctrl\\n try:\\n resource = NET_RESOURCE_PATH % tenant_id\\n data = {\\n \\\"network\\\": {\\n \\\"id\\\": new_net[\\\"id\\\"],\\n \\\"name\\\": new_net[\\\"name\\\"],\\n }\\n }\\n ret = self.servers.post(resource, data)\\n if not self.servers.action_success(ret):\\n raise RemoteRestError(ret[2])\\n except RemoteRestError as e:\\n LOG.error(_(\\\"QuantumRestProxyV2:Unable to create remote \\\"\\n \\\"network: %s\\\"), e.message)\\n super(QuantumRestProxyV2, self).delete_network(context,\\n new_net['id'])\\n raise\\n\\n # return created network\\n return new_net\",\n \"def create_network_profile(self, body=None):\\r\\n return self.post(self.network_profiles_path, body=body)\",\n \"def subnetpool_create(request, name, prefixes, **kwargs):\\n LOG.debug(\\\"subnetpool_create(): name=%(name)s, prefixes=%(prefixes)s, \\\"\\n \\\"kwargs=%(kwargs)s\\\", {'name': name, 'prefixes': prefixes,\\n 'kwargs': kwargs})\\n body = {'subnetpool':\\n {'name': name,\\n 'prefixes': prefixes,\\n }\\n }\\n if 'tenant_id' not in kwargs:\\n kwargs['tenant_id'] = request.user.project_id\\n body['subnetpool'].update(kwargs)\\n subnetpool = \\\\\\n neutronclient(request).create_subnetpool(body=body).get('subnetpool')\\n return SubnetPool(subnetpool)\",\n \"def create_from_src(self, cgsnapshot_id, source_cgid, name=None,\\n description=None, user_id=None,\\n project_id=None):\\n body = {'consistencygroup-from-src': {'name': name,\\n 'description': description,\\n 'cgsnapshot_id': cgsnapshot_id,\\n 'source_cgid': source_cgid,\\n 'user_id': user_id,\\n 'project_id': project_id,\\n 'status': \\\"creating\\\",\\n }}\\n\\n self.run_hooks('modify_body_for_update', body,\\n 'consistencygroup-from-src')\\n resp, body = self.api.client.post(\\n \\\"/consistencygroups/create_from_src\\\", body=body)\\n return common_base.DictWithMeta(body['consistencygroup'], resp)\",\n \"def CreateGcpWorkloadSource(\\n client,\\n messages,\\n workload_source_id: str,\\n resources: Optional[List[str]],\\n attached_service_accounts: Optional[List[str]],\\n parent: str,\\n for_managed_identity: bool = False,\\n):\\n conditions = []\\n if resources is not None:\\n conditions += [\\n messages.WorkloadSourceCondition(attribute='resource', value=resource)\\n for resource in resources\\n ]\\n if attached_service_accounts is not None:\\n conditions += [\\n messages.WorkloadSourceCondition(\\n attribute='attached_service_account', value=account\\n )\\n for account in attached_service_accounts\\n ]\\n new_workload_source = messages.WorkloadSource(\\n conditionSet=messages.WorkloadSourceConditionSet(conditions=conditions)\\n )\\n if for_managed_identity:\\n return client.projects_locations_workloadIdentityPools_namespaces_managedIdentities_workloadSources.Create(\\n messages.IamProjectsLocationsWorkloadIdentityPoolsNamespacesManagedIdentitiesWorkloadSourcesCreateRequest(\\n parent=parent,\\n workloadSource=new_workload_source,\\n workloadSourceId=workload_source_id,\\n )\\n )\\n else:\\n return client.projects_locations_workloadIdentityPools_namespaces_workloadSources.Create(\\n messages.IamProjectsLocationsWorkloadIdentityPoolsNamespacesWorkloadSourcesCreateRequest(\\n parent=parent,\\n workloadSource=new_workload_source,\\n workloadSourceId=workload_source_id,\\n )\\n )\",\n \"def subnet_create(request, network_id, **kwargs):\\n LOG.debug(\\\"subnet_create(): netid=%(network_id)s, kwargs=%(kwargs)s\\\",\\n {'network_id': network_id, 'kwargs': kwargs})\\n body = {'subnet': {'network_id': network_id}}\\n if 'tenant_id' not in kwargs:\\n kwargs['tenant_id'] = request.user.project_id\\n body['subnet'].update(kwargs)\\n subnet = neutronclient(request).create_subnet(body=body).get('subnet')\\n return Subnet(subnet)\",\n \"def init_network(session: \\\"Session\\\", new_network_name: str) -> None:\\n url_tail = f\\\"/{CoordConstsV2.RSC_NETWORKS}\\\"\\n _post(session, url_tail, None, params={CoordConstsV2.QP_NAME: new_network_name})\",\n \"def create(self):\\n logging.debug(\\\"%s create called\\\" % self)\\n # networks = self.infra.get(\\\"networks\\\")\\n notify(\\\"Creating network %s\\\" % self.name)\\n self.cloudnet = cn.create(self.name, cidr=self.cidr)\\n return True\",\n \"def create_source(self, **kwargs):\\n kwargs['_return_http_data_only'] = True\\n if kwargs.get('callback'):\\n return self.create_source_with_http_info(**kwargs)\\n else:\\n (data) = self.create_source_with_http_info(**kwargs)\\n return data\",\n \"def create_network_gateway(self, body=None):\\r\\n return self.post(self.network_gateways_path, body=body)\",\n \"def add_provider_network(network_id, network_type, segmentation_id):\\n session = db.get_session()\\n if session.query(network_models_v2.ProviderNetwork).filter_by(\\n network_id=network_id).first():\\n raise c_exc.ProviderNetworkExists(network_id)\\n pnet = network_models_v2.ProviderNetwork(network_id=network_id,\\n network_type=network_type,\\n segmentation_id=segmentation_id)\\n session.add(pnet)\\n session.flush()\",\n \"def test_03_network_create(self):\\n # Validate the following\\n # 1. Create a project.\\n # 2. Add virtual/direct network resource to the project. User shared\\n # network resource for the project\\n # 3. Verify any number of Project level Virtual/Direct networks can be\\n # created and used for vm deployment within the project.\\n # 4. Verify shared networks (zone and domain wide) from outside the\\n # project can also be used in a project.\\n\\n # Create project as a domain admin\\n project = Project.create(\\n self.apiclient,\\n self.services[\\\"project\\\"],\\n account=self.account.name,\\n domainid=self.account.domainid\\n )\\n # Cleanup created project at end of test\\n self.cleanup.append(project)\\n self.debug(\\\"Created project with domain admin with ID: %s\\\" %\\n project.id)\\n\\n network_offerings = list_network_offerings(\\n self.apiclient,\\n projectid=project.id,\\n supportedServices='SourceNat',\\n type='isolated',\\n state='Enabled'\\n )\\n self.assertEqual(\\n isinstance(network_offerings, list),\\n True,\\n \\\"Check for the valid network offerings\\\"\\n )\\n network_offering = network_offerings[0]\\n\\n self.debug(\\\"creating a network with network offering ID: %s\\\" %\\n network_offering.id)\\n self.services[\\\"network\\\"][\\\"zoneid\\\"] = self.zone.id\\n network = Network.create(\\n self.apiclient,\\n self.services[\\\"network\\\"],\\n networkofferingid=network_offering.id,\\n projectid=project.id\\n )\\n self.debug(\\\"Created network with ID: %s\\\" % network.id)\\n networks = Network.list(\\n self.apiclient,\\n projectid=project.id,\\n listall=True\\n )\\n self.assertEqual(\\n isinstance(networks, list),\\n True,\\n \\\"Check for the valid network list response\\\"\\n )\\n\\n self.debug(\\\"Deploying VM with network: %s\\\" % network.id)\\n\\n virtual_machine = VirtualMachine.create(\\n self.apiclient,\\n self.services[\\\"server\\\"],\\n templateid=self.template.id,\\n networkids=[str(network.id)],\\n serviceofferingid=self.service_offering.id,\\n projectid=project.id\\n )\\n self.debug(\\\"Deployed VM with ID: %s\\\" % virtual_machine.id)\\n # Verify VM state\\n self.assertEqual(\\n virtual_machine.state,\\n 'Running',\\n \\\"Check VM state is Running or not\\\"\\n )\\n\\n network_offerings = list_network_offerings(\\n self.apiclient,\\n state='Enabled',\\n guestiptype='Shared',\\n name='DefaultSharedNetworkOffering',\\n displaytext='Offering for Shared networks'\\n )\\n self.assertEqual(\\n isinstance(network_offerings, list),\\n True,\\n \\\"Check for the valid network offerings\\\"\\n )\\n network_offering = network_offerings[0]\\n\\n self.debug(\\\"creating a shared network in domain: %s\\\" %\\n self.domain.id)\\n\\n # Getting physical network and free vlan in it\\n physical_network, vlan = get_free_vlan(self.apiclient, self.zone.id)\\n\\n self.services[\\\"domain_network\\\"][\\\"vlan\\\"] = vlan\\n self.services[\\\"domain_network\\\"][\\\"physicalnetworkid\\\"] = physical_network.id\\n\\n # Generating random subnet number for shared network creation\\n shared_network_subnet_number = random.randrange(1,254)\\n\\n self.services[\\\"domain_network\\\"][\\\"gateway\\\"] = \\\"172.16.\\\"+str(shared_network_subnet_number)+\\\".1\\\"\\n self.services[\\\"domain_network\\\"][\\\"startip\\\"] = \\\"172.16.\\\"+str(shared_network_subnet_number)+\\\".2\\\"\\n self.services[\\\"domain_network\\\"][\\\"endip\\\"] = \\\"172.16.\\\"+str(shared_network_subnet_number)+\\\".20\\\"\\n\\n domain_network = Network.create(\\n self.apiclient,\\n self.services[\\\"domain_network\\\"],\\n domainid=self.domain.id,\\n networkofferingid=network_offering.id,\\n zoneid=self.zone.id\\n )\\n self.cleanup.append(domain_network)\\n self.debug(\\\"Created network with ID: %s\\\" % domain_network.id)\\n\\n virtual_machine = VirtualMachine.create(\\n self.apiclient,\\n self.services[\\\"server\\\"],\\n templateid=self.template.id,\\n networkids=[str(domain_network.id)],\\n serviceofferingid=self.service_offering.id,\\n projectid=project.id\\n )\\n self.debug(\\\"Deployed VM with ID: %s\\\" % virtual_machine.id)\\n # Verify VM state\\n self.assertEqual(\\n virtual_machine.state,\\n 'Running',\\n \\\"Check VM state is Running or not\\\"\\n )\\n\\n # Delete VM before network gets deleted in cleanup\\n virtual_machine.delete(self.apiclient, expunge=True)\\n return\",\n \"def _create_network_resources(self, tenant_id):\\n logger.info(\\\"Creating network resources...\\\")\\n net_name = \\\"ostf-autoscaling-test-service-net\\\"\\n net_body = {\\n \\\"network\\\": {\\n \\\"name\\\": net_name,\\n \\\"tenant_id\\\": tenant_id\\n }\\n }\\n ext_net = None\\n net = None\\n for network in self.neutron_cli.list_networks()[\\\"networks\\\"]:\\n if not net and network[\\\"name\\\"] == net_name:\\n net = network\\n if not ext_net and network[\\\"router:external\\\"]:\\n ext_net = network\\n if not net:\\n net = self.neutron_cli.create_network(net_body)[\\\"network\\\"]\\n subnet = self.helpers.os_conn.create_subnet(\\n \\\"sub\\\" + net_name, net[\\\"id\\\"], \\\"10.1.7.0/24\\\", tenant_id=tenant_id\\n )\\n router_name = 'ostf-autoscaling-test-service-router'\\n router = self.helpers.os_conn.create_router(\\n router_name, self.helpers.os_conn.get_tenant(\\\"admin\\\"))\\n self.neutron_cli.add_interface_router(\\n router[\\\"id\\\"], {\\\"subnet_id\\\": subnet[\\\"id\\\"]})\\n return net[\\\"id\\\"]\",\n \"def create_network(client, overwrite_net=False, network_name=DOCK_NETWORK_NAME, subnetwork=DOCK_NETWORK_SUBNET,\\n gw=DOCK_NETWORK_GW):\\n\\n if overwrite_net:\\n try:\\n client.networks.get(network_name).remove()\\n logging.info(\\\" Overwriting existing network\\\")\\n except docker.errors.APIError:\\n logging.info(\\\" Warning: Couldn't find network to overwrite (does it exist?)\\\")\\n\\n ipam_pool = docker.types.IPAMPool(subnet=subnetwork, gateway=gw)\\n ipam_config = docker.types.IPAMConfig(pool_configs=[ipam_pool])\\n client.networks.create(network_name, driver=\\\"bridge\\\", ipam=ipam_config)\",\n \"def run(self, network_create_args=None):\\n network = self.neutron.create_network(**(network_create_args or {}))\\n self.neutron.get_network(network[\\\"id\\\"])\",\n \"def new_network():\\n new_names = Names()\\n new_devices = Devices(new_names)\\n return Network(new_names, new_devices)\",\n \"def create_network(address=None, **options):\\n return NetworkDefinition(address, **options)\",\n \"def create_network(self, *, name: t.Optional[str] = None) -> Network:\\n network = Network(self, name=name)\\n self._networks.add(network)\\n return network\",\n \"def test_networking_project_network_create(self):\\n pass\",\n \"def get_network_source(self, network_source_id, **kwargs):\\n resource_path = \\\"/networkSources/{networkSourceId}\\\"\\n method = \\\"GET\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"get_network_source got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"networkSourceId\\\": network_source_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"NetworkSources\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"NetworkSources\\\")\",\n \"def create_network(options, vsm_obj):\\n edge_id = get_edge(vsm_obj)\\n if not edge_id:\\n if not add_edge(options):\\n print(\\\"Failed to create edge\\\")\\n return False\\n edge_id = get_edge(vsm_obj)\\n\\n vdn_scope = get_transport_zone(options)\\n virtual_wire = VirtualWire(vdn_scope)\\n name = get_network_name(options)\\n response = virtual_wire.read_by_name(name)\\n if response != \\\"FAILURE\\\":\\n print(\\\"Found network %s already exists\\\" % options.name)\\n return True\\n\\n virtual_wire_create = VirtualWireCreateSpecSchema()\\n virtual_wire_create.name = name\\n virtual_wire_create.tenantId = name\\n virtual_wire_create.description = 'NSX network %s' % name\\n\\n # check if user needs to enable guest vlan tagging,\\n # this is require if one needs to run vlan tests in nested\\n # environment.\\n if hasattr(options, 'guest_vlan'):\\n if options.guest_vlan is True:\\n print(\\\"network %s has guest vlan tagging enabled\\\"\\\\\\n % options.name)\\n virtual_wire_create.guestVlanAllowed = True\\n\\n print(\\\"Creating network %s\\\" % options.name)\\n result = virtual_wire.create(virtual_wire_create)\\n if (result[0].response.status != 201):\\n print \\\"response: %s\\\" % result[0].response.status\\n print \\\"response: %s\\\" % result[0].response.reason\\n return False\\n print(\\\"Changing security settings on the network\\\")\\n set_network_security_policy(options)\\n return add_edge_interface(options, edge_id)\",\n \"def create_net(self, net_name, shared=\\\"false\\\"):\\n _url = \\\"http://\\\" + self.host_ip + \\\":9696/v2.0/networks.json\\\"\\n _headers = {'Content-type': 'application/json',\\n 'x-auth-token': self.project_info[\\\"token_project\\\"]}\\n _net_info = {\\\"network\\\":\\n {\\\"name\\\": net_name,\\n \\\"shared\\\": shared,\\n \\\"admin_state_up\\\": True}}\\n _body = json.dumps(_net_info)\\n\\n response = self.request(\\\"POST\\\", _url, _headers, _body)\\n if response is None:\\n LOG_OBJ.error(\\\"No response from Server while creating network.\\\")\\n return response\\n\\n if response.status not in [200, 201, 202, 203, 204]:\\n LOG_OBJ.error(\\\"Creation of network Failed with status %s \\\" %\\n response.status)\\n return response.status\\n\\n output = json.loads(response.data)\\n LOG_OBJ.info(\\\"Network is created successfully. Details : %s \\\" %\\n output['network'])\\n\\n return output['network']['id']\",\n \"def run(self, network_create_args=None, subnet_create_args=None,\\n subnet_cidr_start=None, subnets_per_network=1,\\n router_create_args=None):\\n subnet_create_args = dict(subnet_create_args or {})\\n subnet_create_args[\\\"start_cidr\\\"] = subnet_cidr_start\\n\\n self.neutron.create_network_topology(\\n network_create_args=(network_create_args or {}),\\n router_create_args=(router_create_args or {}),\\n router_per_subnet=True,\\n subnet_create_args=subnet_create_args,\\n subnets_count=subnets_per_network\\n )\\n self.neutron.list_routers()\",\n \"def _precreate_network(self):\\n # check cidr format\\n net_cidr = CONF.azure.vnet_cidr\\n subnet_cidr = CONF.azure.vsubnet_cidr\\n if not (self._is_valid_cidr(net_cidr) and\\n self._is_valid_cidr(subnet_cidr)):\\n msg = 'Invalid network: %(net_cidr)s/subnet: %(subnet_cidr)s' \\\\\\n ' CIDR' % dict(net_cidr=net_cidr, subnet_cidr=subnet_cidr)\\n LOG.error(msg)\\n raise exception.NetworkCreateFailure(reason=msg)\\n # Creaet Network\\n try:\\n nets = self.network.virtual_networks.list(\\n CONF.azure.resource_group)\\n net_exist = False\\n for i in nets:\\n if i.name == CONF.azure.vnet_name:\\n net_exist = True\\n break\\n if not net_exist:\\n network_info = dict(location=CONF.azure.location,\\n address_space=dict(\\n address_prefixes=[net_cidr]))\\n async_vnet_creation = \\\\\\n self.network.virtual_networks.create_or_update(\\n CONF.azure.resource_group,\\n CONF.azure.vnet_name,\\n network_info)\\n async_vnet_creation.wait(CONF.azure.async_timeout)\\n LOG.info(_LI(\\\"Create Network\\\"))\\n except Exception as e:\\n msg = six.text_type(e)\\n ex = exception.NetworkCreateFailure(reason=msg)\\n LOG.exception(msg)\\n raise ex\\n\\n # Create Subnet\\n try:\\n # subnet can't recreate, check existing before create.\\n subnets = self.network.subnets.list(\\n CONF.azure.resource_group,\\n CONF.azure.vnet_name)\\n subnet_exist = False\\n subnet_details = None\\n for i in subnets:\\n if i.name == CONF.azure.vsubnet_name:\\n subnet_exist = True\\n subnet_details = i\\n break\\n if not subnet_exist:\\n subnet_info = {'address_prefix': subnet_cidr}\\n async_subnet_creation = self.network.subnets.create_or_update(\\n CONF.azure.resource_group,\\n CONF.azure.vnet_name,\\n CONF.azure.vsubnet_name,\\n subnet_info\\n )\\n subnet_details = async_subnet_creation.result()\\n except Exception as e:\\n # delete network if subnet create fail.\\n try:\\n async_vm_action = self.network.virtual_networks.delete(\\n CONF.azure.resource_group, CONF.azure.vnet_name)\\n async_vm_action.wait(CONF.azure.async_timeout)\\n LOG.info(_LI(\\\"Deleted Network %s after Subnet create \\\"\\n \\\"failed.\\\"), CONF.azure.vnet_name)\\n except Exception:\\n LOG.error(_LE('Delete Network %s failed after Subnet create '\\n 'failed.'), CONF.azure.vnet_name)\\n msg = six.text_type(e)\\n ex = exception.SubnetCreateFailure(reason=msg)\\n LOG.exception(msg)\\n raise ex\\n CONF.set_override('vsubnet_id', subnet_details.id, 'azure')\\n LOG.info(_LI(\\\"Create/Update Subnet: %s\\\"), CONF.azure.vsubnet_id)\",\n \"def run(self, network_create_args=None):\\n self.neutron.create_network(**(network_create_args or {}))\\n self.neutron.list_networks()\",\n \"def _add_source_net_filter(self, rule_list, source_net):\\n for rule in rule_list:\\n if (\\\"source\\\" in rule.keys()):\\n if (\\\"nets\\\" in rule[\\\"source\\\"].keys()):\\n rule[\\\"source\\\"][\\\"nets\\\"].append(source_net)\\n else:\\n rule[\\\"source\\\"].update({\\\"nets\\\": [source_net]})\\n else:\\n rule.update({\\\"source\\\": {\\\"nets\\\": [source_net]}})\",\n \"def create_source_with_http_info(self, **kwargs):\\n\\n all_params = ['body']\\n all_params.append('callback')\\n all_params.append('_return_http_data_only')\\n all_params.append('_preload_content')\\n all_params.append('_request_timeout')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_source\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n\\n collection_formats = {}\\n\\n path_params = {}\\n\\n query_params = []\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['application/json'])\\n\\n # Authentication setting\\n auth_settings = ['Using HTTP Header', 'Using URL Query Parameter']\\n\\n return self.api_client.call_api('/sources', 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='str',\\n auth_settings=auth_settings,\\n callback=params.get('callback'),\\n _return_http_data_only=params.get('_return_http_data_only'),\\n _preload_content=params.get('_preload_content', True),\\n _request_timeout=params.get('_request_timeout'),\\n collection_formats=collection_formats)\",\n \"def network_initial(request, SPIC_group, SPIC_id):\\n SPIC_obj = get_object_or_404(SPIC, group=SPIC_group, local_id=SPIC_id)\\n network_obj, created = Network.objects.get_or_create(user_id=request.user.pk, SPIC=SPIC_obj, local_id=0, deleted=False)\\n\\n if created is True:\\n # Check if prototype exists\\n prototype = get_object_or_404(Network, user_id=0, SPIC=SPIC_obj)\\n network_obj.nodes_json = prototype.nodes_json\\n network_obj.links_json = prototype.links_json\\n network_obj.save()\\n\\n return network(request, SPIC_group, SPIC_id, 0)\",\n \"def create_network(region_name, vpc_cidr, tag_prefix,\\n tls_priv_key=None, tls_fullchain_cert=None,\\n ssh_key_name=None, ssh_key_content=None, sally_ip=None,\\n s3_logs_bucket=None, s3_identities_bucket=None,\\n storage_enckey=None,\\n dry_run=False):\\n sg_tag_prefix = tag_prefix\\n\\n LOGGER.info(\\\"Provisions network ...\\\")\\n ec2_client = boto3.client('ec2', region_name=region_name)\\n\\n # Create a VPC\\n vpc_id, vpc_cidr_read = _get_vpc_id(tag_prefix, ec2_client=ec2_client,\\n region_name=region_name)\\n if vpc_id:\\n if vpc_cidr != vpc_cidr_read:\\n raise RuntimeError(\\n \\\"%s cidr block for VPC is %s while it was expected to be %s\\\" %\\n (tag_prefix, vpc_cidr_read, vpc_cidr))\\n else:\\n if not vpc_cidr:\\n raise RuntimeError(\\n \\\"%s could not find VPC and no cidr block is specified\\\"\\\\\\n \\\" to create one.\\\" % tag_prefix)\\n resp = ec2_client.create_vpc(\\n DryRun=dry_run,\\n CidrBlock=vpc_cidr,\\n AmazonProvidedIpv6CidrBlock=False,\\n InstanceTenancy='default')\\n vpc_id = resp['Vpc']['VpcId']\\n ec2_client.create_tags(\\n DryRun=dry_run,\\n Resources=[vpc_id],\\n Tags=[\\n {'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\", 'Value': \\\"%s-vpc\\\" % tag_prefix}])\\n LOGGER.info(\\\"%s created VPC %s\\\", tag_prefix, vpc_id)\\n\\n # Create subnets for app, dbs and web services\\n # ELB will require that there is at least one subnet per availability zones.\\n # RDS will require that there is at least two subnets for databases.\\n resp = ec2_client.describe_availability_zones()\\n zones = {(zone['ZoneId'], zone['ZoneName'])\\n for zone in resp['AvailabilityZones']}\\n web_subnet_cidrs, dbs_subnet_cidrs, app_subnet_cidrs = _split_cidrs(\\n vpc_cidr, zones=zones, region_name=region_name)\\n\\n LOGGER.info(\\\"%s provisioning web subnets...\\\", tag_prefix)\\n web_zones = set([])\\n web_subnet_by_cidrs = _get_subnet_by_cidrs(\\n web_subnet_cidrs, tag_prefix, vpc_id=vpc_id, ec2_client=ec2_client)\\n for cidr_block, subnet in web_subnet_by_cidrs.items():\\n if subnet:\\n web_zones |= {\\n (subnet['AvailabilityZoneId'], subnet['AvailabilityZone'])}\\n for cidr_block, subnet in web_subnet_by_cidrs.items():\\n if not subnet:\\n available_zones = zones - web_zones\\n zone_id, zone_name = available_zones.pop()\\n try:\\n resp = ec2_client.create_subnet(\\n AvailabilityZoneId=zone_id,\\n CidrBlock=cidr_block,\\n VpcId=vpc_id,\\n TagSpecifications=[{\\n 'ResourceType': 'subnet',\\n 'Tags': [\\n {'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\",\\n 'Value': \\\"%s %s web\\\" % (tag_prefix, zone_name)}]}],\\n DryRun=dry_run)\\n subnet = resp['Subnet']\\n web_subnet_by_cidrs[cidr_block] = subnet\\n web_zones |= set([(zone_id, zone_name)])\\n subnet_id = subnet['SubnetId']\\n LOGGER.info(\\\"%s created subnet %s in zone %s for cidr %s\\\",\\n tag_prefix, subnet_id, zone_name, cidr_block)\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidSubnet.Conflict':\\n raise\\n # We have a conflict, let's just skip over it.\\n LOGGER.warning(\\n \\\"%s (skip) created subnet in zone %s because '%s'\\\",\\n tag_prefix, zone_name, err)\\n if subnet and not subnet['MapPublicIpOnLaunch']:\\n subnet_id = subnet['SubnetId']\\n if not dry_run:\\n resp = ec2_client.modify_subnet_attribute(\\n SubnetId=subnet_id,\\n MapPublicIpOnLaunch={'Value': True})\\n LOGGER.info(\\\"%s modify web subnet %s so instance can receive\\\"\\\\\\n \\\" a public IP by default\\\", tag_prefix, subnet_id)\\n\\n LOGGER.info(\\\"%s provisioning dbs subnets...\\\", tag_prefix)\\n dbs_zones = set([])\\n dbs_subnet_by_cidrs = _get_subnet_by_cidrs(\\n dbs_subnet_cidrs, tag_prefix, vpc_id=vpc_id, ec2_client=ec2_client)\\n for cidr_block, subnet in dbs_subnet_by_cidrs.items():\\n if subnet:\\n dbs_zones |= {\\n (subnet['AvailabilityZoneId'], subnet['AvailabilityZone'])}\\n for cidr_block, subnet in dbs_subnet_by_cidrs.items():\\n if not subnet:\\n available_zones = zones - dbs_zones\\n zone_id, zone_name = available_zones.pop()\\n resp = ec2_client.create_subnet(\\n AvailabilityZoneId=zone_id,\\n CidrBlock=cidr_block,\\n VpcId=vpc_id,\\n TagSpecifications=[{\\n 'ResourceType': 'subnet',\\n 'Tags': [\\n {'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\",\\n 'Value': \\\"%s %s dbs\\\" % (tag_prefix, zone_name)}]}],\\n DryRun=dry_run)\\n subnet = resp['Subnet']\\n dbs_subnet_by_cidrs[cidr_block] = subnet\\n dbs_zones |= set([(zone_id, zone_name)])\\n subnet_id = subnet['SubnetId']\\n LOGGER.info(\\\"%s created subnet %s in zone %s for cidr %s\\\",\\n tag_prefix, subnet_id, zone_name, cidr_block)\\n if subnet['MapPublicIpOnLaunch']:\\n subnet_id = subnet['SubnetId']\\n if not dry_run:\\n resp = ec2_client.modify_subnet_attribute(\\n SubnetId=subnet_id,\\n MapPublicIpOnLaunch={'Value': False})\\n LOGGER.info(\\\"%s modify dbs subnet %s so instance do not receive\\\"\\\\\\n \\\" a public IP by default\\\", tag_prefix, subnet_id)\\n\\n LOGGER.info(\\\"%s provisioning apps subnets...\\\", tag_prefix)\\n app_zones = set([])\\n app_subnet_by_cidrs = _get_subnet_by_cidrs(\\n app_subnet_cidrs, tag_prefix, vpc_id=vpc_id, ec2_client=ec2_client)\\n for cidr_block, subnet in app_subnet_by_cidrs.items():\\n if subnet:\\n app_zones |= {\\n (subnet['AvailabilityZoneId'], subnet['AvailabilityZone'])}\\n for cidr_block, subnet in app_subnet_by_cidrs.items():\\n if not subnet:\\n available_zones = zones - app_zones\\n zone_id, zone_name = available_zones.pop()\\n resp = ec2_client.create_subnet(\\n AvailabilityZoneId=zone_id,\\n CidrBlock=cidr_block,\\n VpcId=vpc_id,\\n # COMMIT MSG:\\n # this requires boto3>=1.14, using `createTag` might fail\\n # because the subnet is not fully created yet.\\n TagSpecifications=[{\\n 'ResourceType': 'subnet',\\n 'Tags': [\\n {'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\",\\n 'Value': \\\"%s %s app\\\" % (tag_prefix, zone_name)}]}],\\n DryRun=dry_run)\\n subnet = resp['Subnet']\\n app_subnet_by_cidrs[cidr_block] = subnet\\n app_zones |= set([(zone_id, zone_name)])\\n subnet_id = subnet['SubnetId']\\n LOGGER.info(\\\"%s created subnet %s in %s for cidr %s\\\",\\n tag_prefix, subnet_id, zone_name, cidr_block)\\n if subnet['MapPublicIpOnLaunch']:\\n subnet_id = subnet['SubnetId']\\n if not dry_run:\\n resp = ec2_client.modify_subnet_attribute(\\n SubnetId=subnet_id,\\n MapPublicIpOnLaunch={'Value': False})\\n LOGGER.info(\\\"%s modify app subnet %s so instance do not receive\\\"\\\\\\n \\\" a public IP by default\\\", tag_prefix, subnet_id)\\n\\n # Ensure that the VPC has an Internet Gateway.\\n resp = ec2_client.describe_internet_gateways(\\n Filters=[{'Name': 'attachment.vpc-id', 'Values': [vpc_id]}])\\n if resp['InternetGateways']:\\n igw_id = resp['InternetGateways'][0]['InternetGatewayId']\\n LOGGER.info(\\\"%s found Internet Gateway %s\\\", tag_prefix, igw_id)\\n else:\\n resp = ec2_client.describe_internet_gateways(\\n Filters=[{'Name': 'tag:Prefix', 'Values': [tag_prefix]}])\\n if resp['InternetGateways']:\\n igw_id = resp['InternetGateways'][0]['InternetGatewayId']\\n LOGGER.info(\\\"%s found Internet Gateway %s\\\", tag_prefix, igw_id)\\n else:\\n resp = ec2_client.create_internet_gateway(DryRun=dry_run)\\n igw_id = resp['InternetGateway']['InternetGatewayId']\\n ec2_client.create_tags(\\n DryRun=dry_run,\\n Resources=[igw_id],\\n Tags=[{'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\",\\n 'Value': \\\"%s internet gateway\\\" % tag_prefix}])\\n LOGGER.info(\\\"%s created Internet Gateway %s\\\", tag_prefix, igw_id)\\n resp = ec2_client.attach_internet_gateway(\\n DryRun=dry_run,\\n InternetGatewayId=igw_id,\\n VpcId=vpc_id)\\n\\n # Create the NAT gateway by which private subnets connect to Internet\\n # XXX Why do we have a Network interface eni-****?\\n nat_elastic_ip = None\\n web_elastic_ip = None\\n resp = ec2_client.describe_addresses(\\n Filters=[{'Name': 'tag:Prefix', 'Values': [tag_prefix]}])\\n if resp['Addresses']:\\n for resp_address in resp['Addresses']:\\n for resp_tag in resp_address['Tags']:\\n if resp_tag['Key'] == 'Name':\\n if 'NAT gateway' in resp_tag['Value']:\\n nat_elastic_ip = resp_address['AllocationId']\\n break\\n if 'Sally' in resp_tag['Value']:\\n web_elastic_ip = resp_address['AllocationId']\\n break\\n\\n if nat_elastic_ip:\\n LOGGER.info(\\\"%s found NAT gateway public IP %s\\\",\\n tag_prefix, nat_elastic_ip)\\n else:\\n resp = ec2_client.allocate_address(\\n DryRun=dry_run,\\n Domain='vpc')\\n nat_elastic_ip = resp['AllocationId']\\n ec2_client.create_tags(\\n DryRun=dry_run,\\n Resources=[nat_elastic_ip],\\n Tags=[{'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\",\\n 'Value': \\\"%s NAT gateway public IP\\\" % tag_prefix}])\\n LOGGER.info(\\\"%s created NAT gateway public IP %s\\\",\\n tag_prefix, nat_elastic_ip)\\n if web_elastic_ip:\\n LOGGER.info(\\\"%s found Sally public IP %s\\\",\\n tag_prefix, web_elastic_ip)\\n else:\\n resp = ec2_client.allocate_address(\\n DryRun=dry_run,\\n Domain='vpc')\\n web_elastic_ip = resp['AllocationId']\\n ec2_client.create_tags(\\n DryRun=dry_run,\\n Resources=[web_elastic_ip],\\n Tags=[{'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\",\\n 'Value': \\\"%s Sally public IP\\\" % tag_prefix}])\\n LOGGER.info(\\\"%s created Sally public IP %s\\\",\\n tag_prefix, web_elastic_ip)\\n\\n # We have 2 EIP addresses. They need to be connected to machines\\n # running in an Internet facing subnet.\\n client_token = tag_prefix\\n # XXX shouldn't it be the first web subnet instead?\\n resp = ec2_client.describe_nat_gateways(Filters=[\\n {'Name': \\\"vpc-id\\\", 'Values': [vpc_id]},\\n {'Name': \\\"state\\\", 'Values': ['pending', 'available']}])\\n if resp['NatGateways']:\\n if len(resp['NatGateways']) > 1:\\n LOGGER.warning(\\\"%s found more than one NAT gateway.\\\"\\\\\\n \\\" Using first one in the list.\\\", tag_prefix)\\n nat_gateway = resp['NatGateways'][0]\\n nat_gateway_id = nat_gateway['NatGatewayId']\\n nat_gateway_subnet_id = nat_gateway['SubnetId']\\n LOGGER.info(\\\"%s found NAT gateway %s\\\", tag_prefix, nat_gateway_id)\\n else:\\n nat_gateway_subnet_id = next(web_subnet_by_cidrs.values())['SubnetId']\\n resp = ec2_client.create_nat_gateway(\\n AllocationId=nat_elastic_ip,\\n ClientToken=client_token,\\n SubnetId=nat_gateway_subnet_id)\\n nat_gateway_id = resp['NatGateway']['NatGatewayId']\\n ec2_client.create_tags(\\n DryRun=dry_run,\\n Resources=[nat_gateway_id],\\n Tags=[{'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\",\\n 'Value': \\\"%s NAT gateway\\\" % tag_prefix}])\\n LOGGER.info(\\\"%s created NAT gateway %s\\\",\\n tag_prefix, nat_gateway_id)\\n\\n # Set up public and NAT-protected route tables\\n resp = ec2_client.describe_route_tables(\\n Filters=[{'Name': \\\"vpc-id\\\", 'Values': [vpc_id]}])\\n public_route_table_id = None\\n private_route_table_id = None\\n for route_table in resp['RouteTables']:\\n for route in route_table['Routes']:\\n if 'GatewayId' in route and route['GatewayId'] == igw_id:\\n public_route_table_id = route_table['RouteTableId']\\n LOGGER.info(\\\"%s found public route table %s\\\",\\n tag_prefix, public_route_table_id)\\n break\\n if ('NatGatewayId' in route and\\n route['NatGatewayId'] == nat_gateway_id):\\n private_route_table_id = route_table['RouteTableId']\\n LOGGER.info(\\\"%s found private route table %s\\\",\\n tag_prefix, private_route_table_id)\\n\\n if not public_route_table_id:\\n resp = ec2_client.create_route_table(\\n DryRun=dry_run,\\n VpcId=vpc_id)\\n public_route_table_id = resp['RouteTable']['RouteTableId']\\n ec2_client.create_tags(\\n DryRun=dry_run,\\n Resources=[public_route_table_id],\\n Tags=[\\n {'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\", 'Value': \\\"%s public\\\" % tag_prefix}])\\n LOGGER.info(\\\"%s created public subnet route table %s\\\",\\n tag_prefix, public_route_table_id)\\n resp = ec2_client.create_route(\\n DryRun=dry_run,\\n DestinationCidrBlock='0.0.0.0/0',\\n GatewayId=igw_id,\\n RouteTableId=public_route_table_id)\\n\\n if not private_route_table_id:\\n resp = ec2_client.create_route_table(\\n DryRun=dry_run,\\n VpcId=vpc_id)\\n private_route_table_id = resp['RouteTable']['RouteTableId']\\n ec2_client.create_tags(\\n DryRun=dry_run,\\n Resources=[private_route_table_id],\\n Tags=[\\n {'Key': \\\"Prefix\\\", 'Value': tag_prefix},\\n {'Key': \\\"Name\\\", 'Value': \\\"%s internal\\\" % tag_prefix}])\\n private_route_table_id = resp['RouteTable']['RouteTableId']\\n LOGGER.info(\\\"%s created private route table %s\\\",\\n tag_prefix, private_route_table_id)\\n for _ in range(0, NB_RETRIES):\\n # The NAT Gateway takes some time to be fully operational.\\n try:\\n resp = ec2_client.create_route(\\n DryRun=dry_run,\\n DestinationCidrBlock='0.0.0.0/0',\\n NatGatewayId=nat_gateway_id,\\n RouteTableId=private_route_table_id)\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidNatGatewayID.NotFound':\\n raise\\n time.sleep(RETRY_WAIT_DELAY)\\n\\n resp = ec2_client.describe_route_tables(\\n DryRun=dry_run,\\n RouteTableIds=[public_route_table_id])\\n assocs = resp['RouteTables'][0]['Associations']\\n if len(assocs) > 1:\\n LOGGER.warning(\\\"%s found more than one route table association for\\\"\\\\\\n \\\" public route table. Using first one in the list.\\\", tag_prefix)\\n if not assocs[0]['Main']:\\n LOGGER.warning(\\\"%s public route table is not the main one for the VPC.\\\",\\n tag_prefix)\\n\\n for cidr_block, subnet in web_subnet_by_cidrs.items():\\n if not subnet:\\n # Maybe there was a conflict and we skipped this cidr_block.\\n continue\\n subnet_id = subnet['SubnetId']\\n resp = ec2_client.describe_route_tables(\\n DryRun=dry_run,\\n Filters=[{\\n 'Name': 'association.subnet-id',\\n 'Values': [subnet_id]\\n }])\\n # The Main route table does not show as an explicit association.\\n found_association = not bool(resp['RouteTables'])\\n if found_association:\\n LOGGER.info(\\n \\\"%s found public route table %s associated to web subnet %s\\\",\\n tag_prefix, public_route_table_id, subnet_id)\\n else:\\n resp = ec2_client.associate_route_table(\\n DryRun=dry_run,\\n RouteTableId=public_route_table_id,\\n SubnetId=subnet_id)\\n LOGGER.info(\\n \\\"%s associate public route table %s to web subnet %s\\\",\\n tag_prefix, public_route_table_id, subnet_id)\\n\\n for cidr_block, subnet in dbs_subnet_by_cidrs.items():\\n subnet_id = subnet['SubnetId']\\n resp = ec2_client.describe_route_tables(\\n DryRun=dry_run,\\n Filters=[{\\n 'Name': 'association.subnet-id',\\n 'Values': [subnet_id]\\n }])\\n # The Main route table does not show as an explicit association.\\n found_association = False\\n if resp['RouteTables']:\\n found_association = (\\n resp['RouteTables'][0]['Associations'][0]['RouteTableId'] ==\\n private_route_table_id\\n )\\n if found_association:\\n LOGGER.info(\\n \\\"%s found private route table %s associated to dbs subnet %s\\\",\\n tag_prefix, private_route_table_id, subnet_id)\\n else:\\n resp = ec2_client.associate_route_table(\\n DryRun=dry_run,\\n RouteTableId=private_route_table_id,\\n SubnetId=subnet_id)\\n LOGGER.info(\\n \\\"%s associate private route table %s to dbs subnet %s\\\",\\n tag_prefix, private_route_table_id, subnet_id)\\n\\n for cidr_block, subnet in app_subnet_by_cidrs.items():\\n subnet_id = subnet['SubnetId']\\n resp = ec2_client.describe_route_tables(\\n DryRun=dry_run,\\n Filters=[{\\n 'Name': 'association.subnet-id',\\n 'Values': [subnet_id]\\n }])\\n # The Main route table does not show as an explicit association.\\n found_association = False\\n if resp['RouteTables']:\\n found_association = (\\n resp['RouteTables'][0]['Associations'][0]['RouteTableId'] ==\\n private_route_table_id\\n )\\n if found_association:\\n LOGGER.info(\\n \\\"%s found private route table %s associated to app subnet %s\\\",\\n tag_prefix, private_route_table_id, subnet_id)\\n else:\\n resp = ec2_client.associate_route_table(\\n DryRun=dry_run,\\n RouteTableId=private_route_table_id,\\n SubnetId=subnet_id)\\n LOGGER.info(\\n \\\"%s associate private route table %s to app subnet %s\\\",\\n tag_prefix, private_route_table_id, subnet_id)\\n\\n # Create the ELB, proxies and databases security groups\\n # The app security group (as the instance role) will be specific\\n # to the application.\\n #pylint:disable=unbalanced-tuple-unpacking\\n moat_name, vault_name, gate_name, kitchen_door_name = \\\\\\n _get_security_group_names([\\n 'moat', 'vault', 'castle-gate', 'kitchen-door'],\\n tag_prefix=sg_tag_prefix)\\n moat_sg_id, vault_sg_id, gate_sg_id, kitchen_door_sg_id = \\\\\\n _get_security_group_ids(\\n [moat_name, vault_name, gate_name, kitchen_door_name],\\n tag_prefix, vpc_id=vpc_id, ec2_client=ec2_client)\\n\\n update_moat_rules = (not moat_sg_id)\\n update_gate_rules = (not gate_sg_id)\\n update_vault_rules = (not vault_sg_id)\\n update_kitchen_door_rules = (not kitchen_door_sg_id)\\n\\n if not moat_sg_id:\\n resp = ec2_client.create_security_group(\\n Description='%s ELB' % tag_prefix,\\n GroupName=moat_name,\\n VpcId=vpc_id,\\n DryRun=dry_run)\\n moat_sg_id = resp['GroupId']\\n LOGGER.info(\\\"%s created %s security group %s\\\",\\n tag_prefix, moat_name, moat_sg_id)\\n if not gate_sg_id:\\n resp = ec2_client.create_security_group(\\n Description='%s session managers' % tag_prefix,\\n GroupName=gate_name,\\n VpcId=vpc_id,\\n DryRun=dry_run)\\n gate_sg_id = resp['GroupId']\\n LOGGER.info(\\\"%s created %s security group %s\\\",\\n tag_prefix, gate_name, gate_sg_id)\\n if not vault_sg_id:\\n resp = ec2_client.create_security_group(\\n Description='%s databases' % tag_prefix,\\n GroupName=vault_name,\\n VpcId=vpc_id,\\n DryRun=dry_run)\\n vault_sg_id = resp['GroupId']\\n LOGGER.info(\\\"%s created %s security group %s\\\",\\n tag_prefix, vault_name, vault_sg_id)\\n # kitchen_door_sg_id: Kitchen door security group is created later on\\n # if we have ssh keys.\\n\\n resp = ec2_client.describe_security_groups(\\n DryRun=dry_run,\\n GroupIds=[moat_sg_id, vault_sg_id, gate_sg_id])\\n for security_group in resp['SecurityGroups']:\\n if security_group['GroupId'] == moat_sg_id:\\n # moat rules\\n LOGGER.info(\\\"%s check ingress rules for %s\\\", tag_prefix, moat_name)\\n check_security_group_ingress(security_group, expected_rules=[\\n {'port': 80, 'source': '0.0.0.0/0'},\\n {'port': 80, 'source': '::/0'},\\n {'port': 443, 'source': '0.0.0.0/0'},\\n {'port': 443, 'source': '::/0'},\\n ],\\n tag_prefix=tag_prefix)\\n elif security_group['GroupId'] == gate_sg_id:\\n # castle-gate rules\\n LOGGER.info(\\\"%s check ingress rules for %s\\\", tag_prefix, gate_name)\\n check_security_group_ingress(security_group, expected_rules=[\\n {'port': 80, 'source': moat_sg_id},\\n {'port': 443, 'source': moat_sg_id}\\n ],\\n tag_prefix=tag_prefix)\\n elif security_group['GroupId'] == vault_sg_id:\\n # vault rules\\n LOGGER.info(\\\"%s check ingress rules for %s\\\", tag_prefix, vault_name)\\n check_security_group_ingress(security_group, expected_rules=[\\n {'port': 5432, 'source': gate_sg_id}\\n ],\\n tag_prefix=tag_prefix)\\n\\n # moat allow rules\\n if update_moat_rules:\\n try:\\n resp = ec2_client.authorize_security_group_ingress(\\n DryRun=dry_run,\\n GroupId=moat_sg_id,\\n IpPermissions=[{\\n 'FromPort': 80,\\n 'IpProtocol': 'tcp',\\n 'IpRanges': [{\\n 'CidrIp': '0.0.0.0/0'\\n }],\\n 'ToPort': 80\\n }, {\\n 'FromPort': 80,\\n 'IpProtocol': 'tcp',\\n 'Ipv6Ranges': [{\\n 'CidrIpv6': '::/0',\\n }],\\n 'ToPort': 80\\n }, {\\n 'FromPort': 443,\\n 'IpProtocol': 'tcp',\\n 'IpRanges': [{\\n 'CidrIp': '0.0.0.0/0'\\n }],\\n 'ToPort': 443\\n }, {\\n 'FromPort': 443,\\n 'IpProtocol': 'tcp',\\n 'Ipv6Ranges': [{\\n 'CidrIpv6': '::/0',\\n }],\\n 'ToPort': 443\\n }])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n\\n if update_gate_rules:\\n # castle-gate allow rules\\n try:\\n resp = ec2_client.authorize_security_group_ingress(\\n DryRun=dry_run,\\n GroupId=gate_sg_id,\\n IpPermissions=[{\\n 'IpProtocol': 'tcp',\\n 'FromPort': 80,\\n 'ToPort': 80,\\n 'UserIdGroupPairs': [{'GroupId': moat_sg_id}]\\n }])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n try:\\n resp = ec2_client.authorize_security_group_ingress(\\n DryRun=dry_run,\\n GroupId=gate_sg_id,\\n IpPermissions=[{\\n 'IpProtocol': 'tcp',\\n 'FromPort': 443,\\n 'ToPort': 443,\\n 'UserIdGroupPairs': [{'GroupId': moat_sg_id}]\\n }])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n try:\\n resp = ec2_client.authorize_security_group_egress(\\n DryRun=dry_run,\\n GroupId=gate_sg_id,\\n IpPermissions=[{\\n 'IpProtocol': '-1',\\n 'IpRanges': [{\\n 'CidrIp': '0.0.0.0/0',\\n }]}])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n # vault allow rules\\n if update_vault_rules:\\n try:\\n resp = ec2_client.authorize_security_group_ingress(\\n DryRun=dry_run,\\n GroupId=vault_sg_id,\\n IpPermissions=[{\\n 'IpProtocol': 'tcp',\\n 'FromPort': 5432,\\n 'ToPort': 5432,\\n 'UserIdGroupPairs': [{'GroupId': gate_sg_id}]\\n }])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n try:\\n resp = ec2_client.authorize_security_group_egress(\\n DryRun=dry_run,\\n GroupId=vault_sg_id,\\n IpPermissions=[{\\n 'IpProtocol': '-1',\\n 'IpRanges': [{\\n 'CidrIp': '0.0.0.0/0',\\n }]}])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n\\n # Create uploads and logs S3 buckets\\n # XXX create the identities bucket?\\n # XXX need to force private.\\n if not s3_identities_bucket:\\n s3_identities_bucket = '%s-identities' % tag_prefix\\n s3_uploads_bucket = tag_prefix\\n s3_client = boto3.client('s3')\\n if s3_logs_bucket:\\n try:\\n resp = s3_client.create_bucket(\\n ACL='private',\\n Bucket=s3_logs_bucket,\\n CreateBucketConfiguration={\\n 'LocationConstraint': region_name\\n })\\n LOGGER.info(\\\"%s created S3 bucket for logs %s\\\",\\n tag_prefix, s3_logs_bucket)\\n except botocore.exceptions.ClientError as err:\\n LOGGER.info(\\\"%s found S3 bucket for logs %s\\\",\\n tag_prefix, s3_logs_bucket)\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'BucketAlreadyOwnedByYou':\\n raise\\n # Apply bucket encryption by default\\n found_encryption = False\\n try:\\n resp = s3_client.get_bucket_encryption(\\n Bucket=s3_logs_bucket)\\n if resp['ServerSideEncryptionConfiguration']['Rules'][0][\\n 'ApplyServerSideEncryptionByDefault'][\\n 'SSEAlgorithm'] == 'AES256':\\n found_encryption = True\\n LOGGER.info(\\\"%s found encryption AES256 enabled on %s bucket\\\",\\n tag_prefix, s3_logs_bucket)\\n except botocore.exceptions.ClientError as err:\\n LOGGER.info(\\\"%s found S3 bucket for logs %s\\\",\\n tag_prefix, s3_logs_bucket)\\n if not err.response.get('Error', {}).get('Code', 'Unknown') == \\\\\\n 'ServerSideEncryptionConfigurationNotFoundError':\\n raise\\n if not found_encryption:\\n s3_client.put_bucket_encryption(\\n Bucket=s3_logs_bucket,\\n ServerSideEncryptionConfiguration={\\n 'Rules': [{\\n 'ApplyServerSideEncryptionByDefault': {\\n 'SSEAlgorithm': 'AES256',\\n }\\n }]\\n })\\n LOGGER.info(\\\"%s enable encryption on %s bucket\\\",\\n tag_prefix, s3_logs_bucket)\\n\\n # Set versioning and lifecycle policies\\n resp = s3_client.get_bucket_versioning(\\n Bucket=s3_logs_bucket)\\n if 'Status' in resp and resp['Status'] == 'Enabled':\\n LOGGER.info(\\\"%s found versioning enabled on %s bucket\\\",\\n tag_prefix, s3_logs_bucket)\\n else:\\n s3_client.put_bucket_versioning(\\n Bucket=s3_logs_bucket,\\n VersioningConfiguration={\\n 'MFADelete': 'Disabled',\\n 'Status': 'Enabled'\\n })\\n LOGGER.info(\\\"%s enable versioning on %s bucket\\\",\\n tag_prefix, s3_logs_bucket)\\n found_policy = False\\n #pylint:disable=too-many-nested-blocks\\n try:\\n resp = s3_client.get_bucket_lifecycle_configuration(\\n Bucket=s3_logs_bucket)\\n for rule in resp['Rules']:\\n if rule['Status'] == 'Enabled':\\n found_rule = True\\n for transition in rule['Transitions']:\\n if transition['StorageClass'] == 'GLACIER':\\n if transition.get('Days', 0) < 90:\\n found_rule = False\\n LOGGER.warning(\\\"%s lifecycle for 'GLACIER'\\\"\\\\\\n \\\" is less than 90 days.\\\", tag_prefix)\\n break\\n if rule['Expiration'].get('Days', 0) < 365:\\n found_rule = False\\n LOGGER.warning(\\n \\\"%s lifecycle expiration is less than 365 days.\\\",\\n tag_prefix)\\n for transition in rule['NoncurrentVersionTransitions']:\\n if transition['StorageClass'] == 'GLACIER':\\n if transition.get('NoncurrentDays', 0) < 90:\\n found_rule = False\\n LOGGER.warning(\\n \\\"%s version lifecycle for 'GLACIER'\\\"\\\\\\n \\\" is less than 90 days.\\\", tag_prefix)\\n break\\n if rule['NoncurrentVersionExpiration'].get(\\n 'NoncurrentDays', 0) < 365:\\n found_rule = False\\n LOGGER.warning(\\\"%s lifecycle version expiration is\\\"\\\\\\n \\\" less than 365 days.\\\", tag_prefix)\\n if found_rule:\\n found_policy = True\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'NoSuchLifecycleConfiguration':\\n raise\\n if found_policy:\\n LOGGER.info(\\\"%s found lifecycle policy on %s bucket\\\",\\n tag_prefix, s3_logs_bucket)\\n else:\\n s3_client.put_bucket_lifecycle_configuration(\\n Bucket=s3_logs_bucket,\\n LifecycleConfiguration={\\n \\\"Rules\\\": [{\\n \\\"Status\\\": \\\"Enabled\\\",\\n \\\"ID\\\": \\\"expire-logs\\\",\\n \\\"Filter\\\": {\\n \\\"Prefix\\\": \\\"\\\", # This is required.\\n },\\n \\\"Transitions\\\": [{\\n \\\"Days\\\": 90,\\n \\\"StorageClass\\\": \\\"GLACIER\\\"\\n }],\\n \\\"Expiration\\\" : {\\n \\\"Days\\\": 365\\n },\\n \\\"NoncurrentVersionTransitions\\\": [{\\n \\\"NoncurrentDays\\\": 90,\\n \\\"StorageClass\\\": \\\"GLACIER\\\"\\n }],\\n 'NoncurrentVersionExpiration': {\\n 'NoncurrentDays': 365\\n },\\n }]})\\n LOGGER.info(\\\"%s update lifecycle policy on %s bucket\\\",\\n tag_prefix, s3_logs_bucket)\\n\\n # https://docs.aws.amazon.com/elasticloadbalancing/latest/classic/enable-access-logs.html#attach-bucket-policy\\n elb_account_ids_per_region = {\\n 'us-east-1': '127311923021',\\n 'us-east-2': '033677994240',\\n 'us-west-1': '027434742980',\\n 'us-west-2': '797873946194',\\n 'af-south-1': '098369216593',\\n 'ca-central-1': '985666609251',\\n 'eu-central-1': '054676820928',\\n 'eu-west-1': '156460612806',\\n 'eu-west-2': '652711504416',\\n 'eu-south-1': '635631232127',\\n 'eu-west-3': '009996457667',\\n 'eu-north-1': '897822967062',\\n 'ap-east-1': '754344448648',\\n 'ap-northeast-1': '582318560864',\\n 'ap-northeast-2': '600734575887',\\n 'ap-northeast-3': '383597477331',\\n 'ap-southeast-1': '114774131450',\\n 'ap-southeast-2': '783225319266',\\n 'ap-south-1': '718504428378',\\n 'me-south-1': '076674570225',\\n 'sa-east-1': '507241528517'\\n }\\n elb_account_id = elb_account_ids_per_region[region_name]\\n s3_client.put_bucket_policy(\\n Bucket=s3_logs_bucket,\\n Policy=json.dumps({\\n \\\"Version\\\": \\\"2008-10-17\\\",\\n \\\"Id\\\": \\\"WriteLogs\\\",\\n \\\"Statement\\\": [{\\n # billing reports\\n \\\"Effect\\\": \\\"Allow\\\",\\n \\\"Principal\\\": {\\n \\\"Service\\\": \\\"billingreports.amazonaws.com\\\"\\n },\\n \\\"Action\\\": [\\n \\\"s3:GetBucketAcl\\\",\\n \\\"s3:GetBucketPolicy\\\"\\n ],\\n \\\"Resource\\\": \\\"arn:aws:s3:::%s\\\" % s3_logs_bucket\\n }, {\\n \\\"Effect\\\": \\\"Allow\\\",\\n \\\"Principal\\\": {\\n \\\"Service\\\": \\\"billingreports.amazonaws.com\\\"\\n },\\n \\\"Action\\\": \\\"s3:PutObject\\\",\\n \\\"Resource\\\": \\\"arn:aws:s3:::%s/*\\\" % s3_logs_bucket\\n }, {\\n # ELB access logs\\n \\\"Effect\\\": \\\"Allow\\\",\\n \\\"Principal\\\": {\\n \\\"AWS\\\": \\\"arn:aws:iam::%s:root\\\" % elb_account_id\\n },\\n \\\"Action\\\": \\\"s3:PutObject\\\",\\n \\\"Resource\\\":\\n \\\"arn:aws:s3:::%s/var/log/elb/*\\\" % s3_logs_bucket\\n }, {\\n \\\"Effect\\\": \\\"Allow\\\",\\n \\\"Principal\\\": {\\n \\\"Service\\\": \\\"delivery.logs.amazonaws.com\\\"\\n },\\n \\\"Action\\\": \\\"s3:PutObject\\\",\\n \\\"Resource\\\":\\n (\\\"arn:aws:s3:::%s/var/log/elb/*\\\" % s3_logs_bucket),\\n \\\"Condition\\\": {\\n \\\"StringEquals\\\": {\\n \\\"s3:x-amz-acl\\\": \\\"bucket-owner-full-control\\\"\\n }\\n }\\n }, {\\n \\\"Effect\\\": \\\"Allow\\\",\\n \\\"Principal\\\": {\\n \\\"Service\\\": \\\"delivery.logs.amazonaws.com\\\"\\n },\\n \\\"Action\\\": \\\"s3:GetBucketAcl\\\",\\n \\\"Resource\\\": \\\"arn:aws:s3:::%s\\\" % s3_logs_bucket\\n }]\\n }))\\n\\n if s3_uploads_bucket:\\n try:\\n resp = s3_client.create_bucket(\\n ACL='private',\\n Bucket=s3_uploads_bucket,\\n CreateBucketConfiguration={\\n 'LocationConstraint': region_name\\n })\\n LOGGER.info(\\\"%s created S3 bucket for uploads %s\\\",\\n tag_prefix, s3_uploads_bucket)\\n except botocore.exceptions.ClientError as err:\\n LOGGER.info(\\\"%s found S3 bucket for uploads %s\\\",\\n tag_prefix, s3_uploads_bucket)\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'BucketAlreadyOwnedByYou':\\n raise\\n\\n # Create instance profiles ...\\n iam_client = boto3.client('iam')\\n # ... for webfront instances\\n create_instance_profile(\\n create_gate_role(gate_name,\\n s3_logs_bucket=s3_logs_bucket, s3_uploads_bucket=s3_uploads_bucket,\\n iam_client=iam_client, tag_prefix=tag_prefix),\\n iam_client=iam_client, region_name=region_name,\\n tag_prefix=tag_prefix, dry_run=dry_run)\\n # ... for databases instances\\n create_instance_profile(\\n create_vault_role(vault_name,\\n s3_logs_bucket=s3_logs_bucket, s3_uploads_bucket=s3_uploads_bucket,\\n iam_client=iam_client, tag_prefix=tag_prefix),\\n iam_client=iam_client, region_name=region_name,\\n tag_prefix=tag_prefix, dry_run=dry_run)\\n\\n if ssh_key_name:\\n if not ssh_key_content:\\n ssh_key_path = os.path.join(os.getenv('HOME'),\\n '.ssh', '%s.pub' % ssh_key_name)\\n if os.path.exists(ssh_key_path):\\n with open(ssh_key_path, 'rb') as ssh_key_obj:\\n ssh_key_content = ssh_key_obj.read()\\n else:\\n LOGGER.warning(\\\"%s no content for SSH key %s\\\",\\n tag_prefix, ssh_key_name)\\n # import SSH keys\\n try:\\n resp = ec2_client.import_key_pair(\\n DryRun=dry_run,\\n KeyName=ssh_key_name,\\n PublicKeyMaterial=ssh_key_content)\\n LOGGER.info(\\\"%s imported SSH key %s\\\", tag_prefix, ssh_key_name)\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidKeyPair.Duplicate':\\n raise\\n LOGGER.info(\\\"%s found SSH key %s\\\", tag_prefix, ssh_key_name)\\n\\n # ... for sally instances\\n create_instance_profile(\\n create_logs_role(kitchen_door_name,\\n s3_logs_bucket=s3_logs_bucket,\\n iam_client=iam_client, tag_prefix=tag_prefix),\\n iam_client=iam_client, region_name=region_name,\\n tag_prefix=tag_prefix, dry_run=dry_run)\\n\\n # allows SSH connection to instances for debugging\\n update_kitchen_door_rules = (not kitchen_door_sg_id)\\n if not kitchen_door_sg_id:\\n resp = ec2_client.create_security_group(\\n Description='%s SSH access' % tag_prefix,\\n GroupName=kitchen_door_name,\\n VpcId=vpc_id,\\n DryRun=dry_run)\\n kitchen_door_sg_id = resp['GroupId']\\n LOGGER.info(\\\"%s created %s security group %s\\\",\\n tag_prefix, kitchen_door_name, kitchen_door_sg_id)\\n\\n if update_kitchen_door_rules:\\n try:\\n if sally_ip:\\n cidr_block = '%s/32' % sally_ip\\n else:\\n LOGGER.warning(\\\"no IP range was specified to restrict\\\"\\\\\\n \\\" access to SSH port\\\")\\n cidr_block = '0.0.0.0/0'\\n resp = ec2_client.authorize_security_group_ingress(\\n DryRun=dry_run,\\n GroupId=kitchen_door_sg_id,\\n CidrIp=cidr_block,\\n IpProtocol='tcp',\\n FromPort=22,\\n ToPort=22)\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n try:\\n resp = ec2_client.authorize_security_group_egress(\\n DryRun=dry_run,\\n GroupId=kitchen_door_sg_id,\\n IpPermissions=[{\\n 'IpProtocol': '-1',\\n 'IpRanges': [{\\n 'CidrIp': '0.0.0.0/0',\\n }]}])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n try:\\n resp = ec2_client.authorize_security_group_ingress(\\n DryRun=dry_run,\\n GroupId=gate_sg_id,\\n IpPermissions=[{\\n 'IpProtocol': 'tcp',\\n 'FromPort': 22,\\n 'ToPort': 22,\\n 'UserIdGroupPairs': [{'GroupId': kitchen_door_sg_id}]\\n }])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n try:\\n resp = ec2_client.authorize_security_group_ingress(\\n DryRun=dry_run,\\n GroupId=vault_sg_id,\\n IpPermissions=[{\\n 'IpProtocol': 'tcp',\\n 'FromPort': 22,\\n 'ToPort': 22,\\n 'UserIdGroupPairs': [{'GroupId': kitchen_door_sg_id}]\\n }])\\n except botocore.exceptions.ClientError as err:\\n if not err.response.get('Error', {}).get(\\n 'Code', 'Unknown') == 'InvalidPermission.Duplicate':\\n raise\\n\\n # Creates encryption keys (KMS) in region\\n if not storage_enckey:\\n storage_enckey = _get_or_create_storage_enckey(\\n region_name, tag_prefix, dry_run=dry_run)\\n\\n # Create an Application ELB and WAF\\n load_balancer_arn = create_elb(\\n tag_prefix, web_subnet_by_cidrs, moat_sg_id,\\n s3_logs_bucket=s3_logs_bucket,\\n tls_priv_key=tls_priv_key, tls_fullchain_cert=tls_fullchain_cert,\\n region_name=region_name)\\n create_waf(\\n tag_prefix,\\n elb_arn=load_balancer_arn,\\n s3_logs_bucket=s3_logs_bucket,\\n region_name=region_name,\\n dry_run=dry_run)\",\n \"def test_create_network_and_subnet(self):\\n suffix = datetime.utcnow().strftime('%Y%m%d%H%M%S')\\n network_name = TEST_NETWORK_PREFIX + \\\"_\\\" + suffix\\n network_cidr = TEST_CIDR_PATTERN % 254\\n self.__create_network_and_subnet_test_helper__(network_name, network_cidr)\",\n \"def create_network(layers):\\r\\n return NeuronNetwork(layers)\",\n \"def post(self):\\n context = request.environ.get('context')\\n json = util.copy_project_id_into_json(context, g.json)\\n network_obj = dbapi.networks_create(context, json)\\n return jsonutils.to_primitive(network_obj), 200, None\",\n \"def create_network(num_subs):\\n\\n # Need one host for each subscriber, one for a publisher, and one for a broker\\n n_hosts = num_subs + 2\\n\\n topo = SingleSwitchTopo(n=n_hosts)\\n\\n return Mininet(topo=topo, controller=OVSController)\",\n \"def create_platform_network(enode, category, config):\\n # Check if this category has a defined netns\\n netns = config.get('netns', None)\\n if netns is None:\\n return\\n\\n # Create the given network namespace\\n enode._docker_exec('ip netns add {}'.format(netns))\\n\\n # lo should always be up\\n enode._docker_exec('ip netns exec {} ip link set dev lo up'.format(netns))\",\n \"def run(self, network_create_args=None, subnet_create_args=None,\\n subnet_cidr_start=None, subnets_per_network=1,\\n router_create_args=None):\\n subnet_create_args = dict(subnet_create_args or {})\\n subnet_create_args[\\\"start_cidr\\\"] = subnet_cidr_start\\n\\n net_topo = self.neutron.create_network_topology(\\n network_create_args=(network_create_args or {}),\\n router_create_args=(router_create_args or {}),\\n router_per_subnet=True,\\n subnet_create_args=subnet_create_args,\\n subnets_count=subnets_per_network\\n )\\n\\n for router in net_topo[\\\"routers\\\"]:\\n self.neutron.get_router(router[\\\"id\\\"])\",\n \"def add_network(self, # pylint: disable=too-many-arguments\\n network: \\\"Network\\\",\\n line_of_business: \\\"LineOfBusiness\\\",\\n platform: \\\"Platform\\\",\\n cloud_region: \\\"CloudRegion\\\" = None,\\n tenant: \\\"Tenant\\\" = None,\\n network_instance_name: str = None,\\n subnets: Iterator[\\\"Subnet\\\"] = None) -> \\\"NetworkInstantiation\\\":\\n if not self.active:\\n msg = f'Service orchestration status must be \\\"Active\\\"'\\n raise StatusError(msg)\\n\\n return NetworkInstantiation.instantiate_ala_carte(\\n self,\\n network,\\n line_of_business,\\n platform,\\n cloud_region=cloud_region,\\n tenant=tenant,\\n network_instance_name=network_instance_name,\\n subnets=subnets\\n )\",\n \"def create(profile):\\n client = boto3client.get(\\\"ec2\\\", profile)\\n return client.create_internet_gateway()\",\n \"def test_create_network():\\n _network = Network()\",\n \"def update_network_source(self, network_source_id, update_network_source_details, **kwargs):\\n resource_path = \\\"/networkSources/{networkSourceId}\\\"\\n method = \\\"PUT\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"if_match\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"update_network_source got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"networkSourceId\\\": network_source_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"if-match\\\": kwargs.get(\\\"if_match\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_network_source_details,\\n response_type=\\\"NetworkSources\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_network_source_details,\\n response_type=\\\"NetworkSources\\\")\",\n \"def test_create_router_external_network(self):\\n\\n # skip test if suite couldn't start from an empty, clean list of allocated IPs (to avoid cascading failures)\\n if self.suite_world['allocated_ips']:\\n self.skipTest(\\\"There were pre-existing, not deallocated IPs\\\")\\n\\n # First, get external network id\\n external_network_id = self.__get_external_network_test_helper__()\\n\\n # Then, create router\\n suffix = datetime.utcnow().strftime('%Y%m%d%H%M%S')\\n router_name = TEST_ROUTER_PREFIX + \\\"_ext_\\\" + suffix\\n self.__create_router_test_helper__(router_name, external_network_id)\",\n \"def create(self):\\n\\t\\treturn handle_to_object(call_sdk_function('PrlVirtNet_Create'))\",\n \"def nic_add(args):\\n name = args.name\\n network = args.network\\n config = Kconfig(client=args.client, debug=args.debug, region=args.region, zone=args.zone, namespace=args.namespace)\\n k = config.k\\n if network is None:\\n common.pprint(\\\"Missing network. Leaving...\\\", color='red')\\n os._exit(1)\\n common.pprint(\\\"Adding Nic to %s...\\\" % name)\\n k.add_nic(name=name, network=network)\",\n \"def create_VirtualNetwork(network_name, network_subnet, network_mask, vnc, domain, project_name):\\n\\n project = vnc.project_read(fq_name = [domain, project_name])\\n\\n vn_obj = vnc_api.VirtualNetwork(name=network_name, parent_obj=project)\\n vn_obj.add_network_ipam(vnc_api.NetworkIpam(),\\n vnc_api.VnSubnetsType([vnc_api.IpamSubnetType(subnet = vnc_api.SubnetType(network_subnet,network_mask))]))\\n\\n vnc.virtual_network_create(vn_obj)\\n\\n print 'Network \\\"{}\\\" created successfully\\\\n'.format(network_name)\",\n \"def ogrCreateLayer(sourceLayer, pgConn, destinationLayer):\\r\\n print \\\" Creating {0}\\\".format(destinationLayer)\\r\\n newLayer = pgConn.CreateLayer(destinationLayer)\\r\\n\\r\\n lyrDefn = sourceLayer.GetLayerDefn()\\r\\n for i in range( lyrDefn.GetFieldCount() ):\\r\\n ##print \\\"Creating field: {0}\\\".format(lyrDefn.GetFieldDefn( i ).GetName())\\r\\n\\r\\n fieldName = lyrDefn.GetFieldDefn( i ).GetName()\\r\\n fieldType = lyrDefn.GetFieldDefn( i ).GetType()\\r\\n newField = ogr.FieldDefn(fieldName, fieldType)\\r\\n newLayer.CreateField(newField)\",\n \"def new(name, source):\",\n \"def mutate(self, info, input):\\n # Convert input to dictionary\\n data = api_utils.input_to_dictionary(input)\\n data_source_type = Operation('ModelDataSourceType').create(**data)\\n return CreateDataSourceType(data_source_type=data_source_type)\",\n \"def test_add_network(self):\\n pass\",\n \"def fusion_api_create_ethernet_network(self, body, api=None, headers=None):\\n return self.ethernet_network.create(body, api, headers)\",\n \"def _create_network(self, name):\\n network = self.network(self.num_actions, self.quantile_embedding_dim,\\n name=name)\\n return network\",\n \"def fusion_api_create_fc_network(self, body, api=None, headers=None):\\n return self.fc_network.create(body, api, headers)\",\n \"def test_create_router_no_external_network_and_add_network_port(self):\\n # Create Router\\n suffix = datetime.utcnow().strftime('%Y%m%d%H%M%S')\\n router_name = TEST_ROUTER_PREFIX + \\\"_ports_\\\" + suffix\\n router_id = self.__create_router_test_helper__(router_name)\\n\\n # Create Network with only one subnet\\n network_name = TEST_NETWORK_PREFIX + \\\"_\\\" + suffix\\n network_cidr = TEST_CIDR_PATTERN % 253\\n network_id, subnet_id = self.__create_network_and_subnet_test_helper__(network_name, network_cidr)\\n\\n port_id = self.neutron_operations.add_interface_router(router_id, subnet_id)\\n self.test_world['ports'].append(port_id)\",\n \"def add_source(ctx, username, id, features, no_validation, token=None, indent=None):\\n mapbox_api = _get_api()\\n mapbox_token = _get_token(token)\\n url = (\\n f\\\"{mapbox_api}/tilesets/v1/sources/{username}/{id}?access_token={mapbox_token}\\\"\\n )\\n\\n with tempfile.TemporaryFile() as file:\\n for feature in features:\\n if not no_validation:\\n utils.validate_geojson(feature)\\n file.write((json.dumps(feature) + \\\"\\\\n\\\").encode(\\\"utf-8\\\"))\\n\\n file.seek(0)\\n m = MultipartEncoder(fields={\\\"file\\\": (\\\"file\\\", file)})\\n resp = requests.post(\\n url,\\n data=m,\\n headers={\\n \\\"Content-Disposition\\\": \\\"multipart/form-data\\\",\\n \\\"Content-type\\\": m.content_type,\\n },\\n )\\n\\n if resp.status_code == 200:\\n click.echo(json.dumps(resp.json(), indent=indent))\\n else:\\n raise errors.TilesetsError(resp.text)\",\n \"def create_network_precommit(self, mech_context):\\n\\n LOG.debug(\\\"create_network_precommit: called\\\")\\n network = mech_context.current\\n context = mech_context._plugin_context\\n tenant_id = network['tenant_id']\\n network_id = network['id']\\n\\n segments = mech_context.network_segments\\n # currently supports only one segment per network\\n segment = segments[0]\\n\\n network_type = segment['network_type']\\n vlan_id = segment['segmentation_id']\\n segment_id = segment['id']\\n\\n if network_type != 'vlan':\\n raise Exception(\\n _(\\\"SeaMicro Mechanism: failed to create network, \\\"\\n \\\"only network type vlan is supported\\\"))\\n\\n try:\\n seamicro_db.create_network(context, network_id, vlan_id,\\n segment_id, network_type, tenant_id)\\n except Exception:\\n LOG.exception(\\n _LE(\\\"SeaMicro Mechanism: failed to create network in db\\\"))\\n raise Exception(\\n _(\\\"SeaMicro Mechanism: create_network_precommit failed\\\"))\\n\\n LOG.info(_LI(\\\"create network (precommit): %(network_id)s \\\"\\n \\\"of network type = %(network_type)s \\\"\\n \\\"with vlan = %(vlan_id)s \\\"\\n \\\"for tenant %(tenant_id)s\\\"),\\n {'network_id': network_id,\\n 'network_type': network_type,\\n 'vlan_id': vlan_id,\\n 'tenant_id': tenant_id})\",\n \"def create(self, objectType, initialParameters):\\n command_line = 'rsg create -ot=\\\"%s\\\" -pl=\\\"%s\\\" -ht=\\\"%s\\\"' % (\\n objectType, initialParameters, self.host_name)\\n return self._execTool(command_line)\",\n \"def create_connection(location=None, bandwidth=None, connectionName=None):\\n pass\",\n \"def create_high_security_network(context):\\n subnetworks = []\\n private_ip_google_access = context.properties.get('privateIpGoogleAccess', False)\\n for region in FIRECLOUD_NETWORK_REGIONS:\\n subnetworks.append({\\n # We append the region to the subnetwork's DM resource name, since\\n # each resource name needs to be globally unique within the deployment.\\n 'resourceName': FIRECLOUD_VPC_SUBNETWORK_NAME + '_' + region,\\n # We want all subnetworks to have the same object name, since this most\\n # closely mirrors how auto-mode subnets work and is what PAPI expects.\\n 'name': FIRECLOUD_VPC_SUBNETWORK_NAME,\\n 'region': region,\\n 'ipCidrRange': FIRECLOUD_NETWORK_REGIONS[region],\\n 'enableFlowLogs': context.properties.get('enableFlowLogs', False),\\n 'privateIpGoogleAccess': private_ip_google_access\\n })\\n\\n return [{\\n 'type': 'templates/network.py',\\n 'name': 'fc-network',\\n 'properties': {\\n 'resourceName': 'network',\\n 'name': FIRECLOUD_VPC_NETWORK_NAME,\\n 'projectId': '$(ref.fc-project.projectId)',\\n 'autoCreateSubnetworks': False,\\n 'subnetworks': subnetworks,\\n # We pass the dependsOn list into the network template as a\\n # parameter. Deployment Manager doesn't support dependsOn for\\n # template-call nodes, so we can't have this resource itself depend on\\n # the project-wide resources.\\n 'dependsOn': '$(ref.fc-project.resourceNames)',\\n 'createCustomStaticRoute': private_ip_google_access\\n },\\n }]\",\n \"def test_add_flow_request_with_sources(self):\\n res = self._add_flow_request(flow_request=self.flow_request)\\n self.assertEqual(res.status_code, 201)\\n flow_request = res.json()\\n destination = Destination.objects.get(name='Destination 1')\\n self.assertEqual(flow_request['flow_id'], self.flow_request['flow_id'])\\n self.assertEqual(flow_request['status'], 'PE')\\n self.assertDictEqual(flow_request['profile'], self.flow_request['profile'])\\n self.assertEqual(FlowRequest.objects.all().count(), 4)\\n self.assertEqual(ConfirmationCode.objects.all().count(), 1)\\n self.assertEqual(FlowRequest.objects.get(flow_id=flow_request['flow_id']).destination, destination)\\n self.assertEqual(FlowRequest.objects.get(flow_id=flow_request['flow_id']).sources.count(), 1)\\n source = FlowRequest.objects.get(flow_id=flow_request['flow_id']).sources.first()\\n self.assertDictEqual(\\n {'source_id': source.source_id, 'name': source.name},\\n {'source_id': SOURCE_1_ID, 'name': SOURCE_1_NAME}\\n )\",\n \"def test_networking_project_network_tag_create(self):\\n pass\",\n \"def start_network(self):\\n try:\\n self.topo.build_topo()\\n except:\\n error('Cannot build the topology.')\\n try:\\n self.net = IPNet(topo=self.topo, use_v4=False, use_v6=True)\\n self.net.start()\\n except:\\n self.stop_network()\\n error('Cannot start the network.')\",\n \"def list_network_sources(self, compartment_id, **kwargs):\\n resource_path = \\\"/networkSources\\\"\\n method = \\\"GET\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"page\\\",\\n \\\"limit\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"list_network_sources got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n query_params = {\\n \\\"compartmentId\\\": compartment_id,\\n \\\"page\\\": kwargs.get(\\\"page\\\", missing),\\n \\\"limit\\\": kwargs.get(\\\"limit\\\", missing)\\n }\\n query_params = {k: v for (k, v) in six.iteritems(query_params) if v is not missing and v is not None}\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n query_params=query_params,\\n header_params=header_params,\\n response_type=\\\"list[NetworkSourcesSummary]\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n query_params=query_params,\\n header_params=header_params,\\n response_type=\\\"list[NetworkSourcesSummary]\\\")\",\n \"def __init__(__self__, *,\\n id: str,\\n source: str):\\n pulumi.set(__self__, \\\"id\\\", id)\\n pulumi.set(__self__, \\\"source\\\", 'Azure')\",\n \"def run(self, network_create_args=None, subnet_create_args=None,\\n subnet_cidr_start=None, subnets_per_network=1):\\n network = self.neutron.create_network(**(network_create_args or {}))\\n for _ in range(subnets_per_network):\\n self.neutron.create_subnet(network[\\\"id\\\"],\\n start_cidr=subnet_cidr_start,\\n **(subnet_create_args or {}))\\n self.neutron.list_subnets()\",\n \"def add_Circuit(self, name, circuit_type, neuropil = None, data_source = None):\\n assert isinstance(name, str), 'name must be of str type'\\n self._database_writeable_check()\\n connect_DataSource = self._default_DataSource if data_source is None \\\\\\n else self._get_obj_from_str(data_source)\\n if connect_DataSource is None:\\n raise TypeError('Default DataSource is missing.')\\n self._uniqueness_check('Circuit', unique_in = connect_DataSource,\\n name = name)\\n\\n circuit_info = {'name': name}\\n \\n batch = self.graph.batch()\\n node_name = _to_var_name('Circuit_{}'.format(name))\\n plural = getattr(models, circuit_type).element_plural\\n batch[node_name] = getattr(batch, plural).create(**circuit_info)\\n\\n # Link subsystem if specified\\n if neuropil is not None:\\n if isinstance(neuropil, str):\\n neuropil_obj = self.get('Neuropil', neuropil, connect_DataSource)\\n elif isinstance(neuropil, models.Neuropil):\\n if self._is_in_datasource(connect_DataSource, neuropil):\\n neuropil_obj = neuropil\\n else:\\n raise ValueError(\\n 'Neuropil {} with rid {} to be linked with subregion is \\\\\\n not in the same datasource {} version {}'.format(\\n neuropil.name, neuropil._id,\\n connect_DataSource.name, connect_DataSource.version))\\n self.link_with_batch(batch, neuropil_obj, batch[:node_name], 'Owns')\\n\\n # Link data_source\\n self.link_with_batch(batch, connect_DataSource, batch[:node_name],\\n 'Owns')\\n\\n circuit = batch['${}'.format(node_name)]\\n batch.commit(20)\\n\\n self.set('Circuit', name, circuit, data_source = connect_DataSource)\\n return circuit\",\n \"def run(self, network_create_args=None):\\n network = self.neutron.create_network(**(network_create_args or {}))\\n self.neutron.delete_network(network[\\\"id\\\"])\",\n \"def network_create_event(self, network_info):\\n net = network_info['network']\\n net_id = net['id']\\n net_name = net.get('name')\\n network_db_elem = self.get_network(net_id)\\n # Check if the source of network creation is FW and if yes, skip\\n # this event.\\n # Check if there's a way to read the DB from service class\\n # TODO(padkrish)\\n if self.fw_api.is_network_source_fw(network_db_elem, net_name):\\n LOG.info(_LI(\\\"Service network %s, returning\\\"), net_name)\\n return\\n self.network[net_id] = {}\\n self.network[net_id].update(net)\\n\\n net_name = net.get('name')\\n tenant_id = net.get('tenant_id')\\n\\n # Extract segmentation_id from the network name\\n net_ext_name = self.cfg.dcnm.dcnm_net_ext\\n nobj = re.search(net_ext_name, net_name)\\n try:\\n seg_id = int((net_name[nobj.start(0) + len(net_ext_name) - 1:]\\n if nobj else None))\\n except (IndexError, TypeError, ValueError):\\n seg_id = None\\n\\n # Check if network is already created.\\n query_net = self.get_network_by_segid(seg_id) if seg_id else None\\n if query_net:\\n # The network is already created no need to process the event.\\n if query_net.source.lower() == 'dcnm':\\n # DCNM created the network. Only update network id in database.\\n prev_id = query_net.network_id\\n params = dict(columns=dict(network_id=net_id))\\n self.update_network(prev_id, **params)\\n\\n # Update the network cache.\\n prev_info = self.network.pop(prev_id)\\n prev_info['id'] = net_id\\n self.network[net_id] = prev_info\\n\\n # Update the network name. After extracting the segmentation_id\\n # no need to keep it in the name. Removing it and update\\n # the network.\\n updated_net_name = (\\n net_name[:nobj.start(0) + len(net_ext_name) - 1])\\n try:\\n body = {'network': {'name': updated_net_name, }}\\n dcnm_net = self.neutronclient.update_network(\\n net_id, body=body).get('network')\\n LOG.debug('Updated network %(network)s', dcnm_net)\\n except Exception as exc:\\n LOG.exception(_LE('Failed to update network '\\n '%(network)s. Reason %(err)s.'),\\n {'network': updated_net_name,\\n 'err': str(exc)})\\n return\\n\\n LOG.info(_LI('network_create_event: network %(name)s was created '\\n 'by %(source)s. Ignoring processing the event.'),\\n {'name': net_name, 'source': 'dcnm'})\\n return\\n\\n # Check if project (i.e. tenant) exist.\\n tenant_name = self.get_project_name(tenant_id)\\n if not tenant_name:\\n LOG.error(_LE('Failed to create network %(name)s. Project '\\n '%(tenant_id)s does not exist.'),\\n {'name': net_name, 'tenant_id': tenant_id})\\n return\\n\\n pseg_id = self.network[net_id].get('provider:segmentation_id')\\n seg_id = self._get_segmentation_id(net_id, pseg_id, 'openstack')\\n self.network[net_id]['segmentation_id'] = seg_id\\n try:\\n cfgp, fwd_mod = self.dcnm_client.get_config_profile_for_network(\\n net.get('name'))\\n self.network[net_id]['config_profile'] = cfgp\\n self.network[net_id]['fwd_mod'] = fwd_mod\\n self.add_network_db(net_id, self.network[net_id],\\n 'openstack',\\n constants.RESULT_SUCCESS)\\n LOG.debug('network_create_event: network=%s', self.network)\\n except dexc.DfaClientRequestFailed:\\n # Fail to get config profile from DCNM.\\n # Save the network info with failure result and send the request\\n # to DCNM later.\\n self.add_network_db(net_id, self.network[net_id], 'openstack',\\n constants.CREATE_FAIL)\\n LOG.error(_LE('Failed to create network=%s.'), self.network)\",\n \"def initialize_network(self, cidr, is_external):\\n raise NotImplementedError()\",\n \"def create_network(\\n self, is_internal: bool = True\\n ) -> None:\\n if self.network:\\n self.log.warn(f\\\"Network {self.network_name} was already created!\\\")\\n return\\n\\n existing_networks = self.docker.networks.list(\\n names=[self.network_name]\\n )\\n if existing_networks:\\n if len(existing_networks) > 1:\\n self.log.error(\\n f\\\"Found multiple ({len(existing_networks)}) existing \\\"\\n f\\\"networks {self.network_name}. Please delete all or all \\\"\\n \\\"but one before starting the server!\\\")\\n exit(1)\\n self.log.info(f\\\"Network {self.network_name} already exists! Using \\\"\\n \\\"existing network\\\")\\n self.network = existing_networks[0]\\n self.network.reload() # required to initialize containers in netw\\n else:\\n self.network = self.docker.networks.create(\\n self.network_name,\\n driver=\\\"bridge\\\",\\n internal=is_internal,\\n scope=\\\"local\\\",\\n )\",\n \"def run(self, network_update_args, network_create_args=None):\\n network = self.neutron.create_network(**(network_create_args or {}))\\n self.neutron.update_network(network[\\\"id\\\"], **network_update_args)\",\n \"def create_network_profile(projectArn=None, name=None, description=None, type=None, uplinkBandwidthBits=None, downlinkBandwidthBits=None, uplinkDelayMs=None, downlinkDelayMs=None, uplinkJitterMs=None, downlinkJitterMs=None, uplinkLossPercent=None, downlinkLossPercent=None):\\n pass\",\n \"def createLotsNetworks(proxy_url, sessiontoken,network_number):\\n myHeader = {\\\"Content-Type\\\": \\\"application/json\\\",\\\"Accept\\\": \\\"application/json\\\", 'csp-auth-token': sessiontoken}\\n for x in range(0,network_number):\\n display_name = \\\"network-name\\\"+str(x)\\n myURL = (proxy_url + \\\"/policy/api/v1/infra/tier-1s/cgw/segments/\\\" + display_name)\\n # '/tier-1s/cgw' might only be applicable for multi tier-1s architecture. To be confirmed.\\n # print(myURL)\\n json_data = {\\n \\\"subnets\\\":[{\\\"gateway_address\\\":\\\"10.200.\\\"+str(x)+\\\".1/24\\\"}],\\n \\\"type\\\":\\\"ROUTED\\\",\\n \\\"display_name\\\":display_name,\\n \\\"advanced_config\\\":{\\\"connectivity\\\":\\\"ON\\\"},\\n \\\"id\\\":\\\"network-test\\\"+str(x)\\n }\\n response = requests.put(myURL, headers=myHeader, json=json_data)\\n json_response_status_code = response.status_code\",\n \"def CreateRequests(self, args):\\n\\n target_vpn_gateway_ref = self.TARGET_VPN_GATEWAY_ARG.ResolveAsResource(\\n args,\\n self.resources,\\n scope_lister=compute_flags.GetDefaultScopeLister(self.compute_client,\\n self.project))\\n network_ref = self.NETWORK_ARG.ResolveAsResource(args, self.resources)\\n\\n request = self.messages.ComputeTargetVpnGatewaysInsertRequest(\\n project=self.project,\\n region=target_vpn_gateway_ref.region,\\n targetVpnGateway=self.messages.TargetVpnGateway(\\n description=args.description,\\n name=target_vpn_gateway_ref.Name(),\\n network=network_ref.SelfLink()\\n ))\\n return [request]\",\n \"def _source_subnet(value):\\n match = SOURCE_SUBNET_RE.match(value)\\n if match:\\n named_groups = match.groupdict()\\n subnet_id = named_groups['SubnetID']\\n role = named_groups['Role']\\n registration_status = named_groups['RegistrationStatus']\\n return SourceSubnet(\\n role = role,\\n registration_status = registration_status,\\n subnet_id = subnet_id\\n )\\n\\n raise argparse.ArgumentTypeError('Given argument \\\"%s\\\" is not a valid source subnet' % value)\",\n \"def empty_network(network_id=NETWORK_ID):\\n return make_net_model({\\\"id\\\": network_id,\\n \\\"subnets\\\": [],\\n \\\"ports\\\": [],\\n \\\"tenant_id\\\": \\\"calico\\\",\\n \\\"mtu\\\": neutron_constants.DEFAULT_NETWORK_MTU})\",\n \"def testCreateWmsSource(self):\\n\\n path = '/minerva_source_wms'\\n name = 'testWMS'\\n username = ''\\n password = ''\\n baseURL = 'http://demo.boundlessgeo.com/geoserver/ows'\\n params = {\\n 'name': name,\\n 'username': username,\\n 'password': password,\\n 'baseURL': baseURL\\n }\\n response = self.request(path=path, method='POST', params=params, user=self._user)\\n self.assertStatusOk(response)\\n wmsSource = response.json\\n minerva_metadata = wmsSource['meta']['minerva']\\n self.assertEquals(wmsSource['name'], name, 'incorrect wms source name')\\n self.assertEquals(minerva_metadata['source_type'], 'wms', 'incorrect wms source type')\\n self.assertEquals(minerva_metadata['wms_params']['base_url'], baseURL, 'incorrect wms source baseURL')\",\n \"def create_community_resource(dataset_id, cr_file):\\n logging.debug(\\\"Creating a community resource on dataset %s\\\", dataset_id)\\n headers = {\\\"X-API-KEY\\\": DATAGOUV_API_KEY}\\n files = {\\\"file\\\": open(cr_file, \\\"rb\\\")}\\n url = f\\\"{DATAGOUV_API}/datasets/{dataset_id}/upload/community/\\\"\\n\\n ret = requests.post(url, headers=headers, files=files)\\n ret.raise_for_status()\\n json = ret.json()\\n\\n logging.debug(\\n \\\"Created a new community resource %s on dataset %s\\\", json[\\\"id\\\"], dataset_id\\n )\\n\\n return json\",\n \"def create_stac_item(\\n source: Union[str, DatasetReader, DatasetWriter, WarpedVRT, MemoryFile],\\n input_datetime: Optional[datetime.datetime] = None,\\n extensions: Optional[List[str]] = None,\\n collection: Optional[str] = None,\\n collection_url: Optional[str] = None,\\n properties: Optional[Dict] = None,\\n id: Optional[str] = None,\\n assets: Optional[Dict[str, pystac.Asset]] = None,\\n asset_name: str = \\\"asset\\\",\\n asset_roles: Optional[List[str]] = None,\\n asset_media_type: Optional[Union[str, pystac.MediaType]] = None,\\n asset_href: Optional[str] = None,\\n with_proj: bool = False,\\n with_raster: bool = False,\\n raster_max_size: int = 1024,\\n) -> pystac.Item:\\n properties = properties or {}\\n extensions = extensions or []\\n\\n with ExitStack() as ctx:\\n if isinstance(source, (DatasetReader, DatasetWriter, WarpedVRT)):\\n dataset = source\\n else:\\n dataset = ctx.enter_context(rasterio.open(source))\\n\\n if dataset.gcps[0]:\\n src_dst = ctx.enter_context(\\n WarpedVRT(\\n dataset,\\n src_crs=dataset.gcps[1],\\n src_transform=transform.from_gcps(dataset.gcps[0]),\\n )\\n )\\n else:\\n src_dst = dataset\\n\\n meta = get_metadata(src_dst)\\n\\n media_type = (\\n get_media_type(dataset) if asset_media_type == \\\"auto\\\" else asset_media_type\\n )\\n\\n # add projection properties\\n if with_proj:\\n properties.update(\\n {\\n f\\\"proj:{name}\\\": value\\n for name, value in get_projection_info(src_dst).items()\\n }\\n )\\n extensions.append(\\n f\\\"https://stac-extensions.github.io/projection/{PROJECTION_EXT_VERSION}/schema.json\\\",\\n )\\n\\n # add raster properties\\n raster_info = {}\\n if with_raster:\\n raster_info = {\\\"raster:bands\\\": get_raster_info(dataset)}\\n extensions.append(\\n f\\\"https://stac-extensions.github.io/raster/{RASTER_EXT_VERSION}/schema.json\\\",\\n )\\n\\n # item\\n item = pystac.Item(\\n id=id or os.path.basename(dataset.name),\\n geometry=meta[\\\"footprint\\\"],\\n bbox=meta[\\\"bbox\\\"],\\n collection=collection,\\n stac_extensions=extensions,\\n datetime=input_datetime,\\n properties=properties,\\n )\\n\\n # if we add a collection we MUST add a link\\n if collection:\\n item.add_link(\\n pystac.Link(\\n pystac.RelType.COLLECTION,\\n collection_url or collection,\\n media_type=pystac.MediaType.JSON,\\n )\\n )\\n\\n # item.assets\\n if assets:\\n for key, asset in assets.items():\\n item.add_asset(\\n key=key, asset=asset,\\n )\\n\\n else:\\n item.add_asset(\\n key=asset_name,\\n asset=pystac.Asset(\\n href=asset_href or dataset.name,\\n media_type=media_type,\\n extra_fields=raster_info,\\n ),\\n )\\n\\n return item\",\n \"def __init__(__self__, *,\\n managed_network_name: pulumi.Input[str],\\n resource_group_name: pulumi.Input[str],\\n kind: Optional[pulumi.Input[Union[str, 'Kind']]] = None,\\n location: Optional[pulumi.Input[str]] = None,\\n managed_network_group_name: Optional[pulumi.Input[str]] = None,\\n management_groups: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceIdArgs']]]] = None,\\n subnets: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceIdArgs']]]] = None,\\n subscriptions: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceIdArgs']]]] = None,\\n virtual_networks: Optional[pulumi.Input[Sequence[pulumi.Input['ResourceIdArgs']]]] = None):\\n pulumi.set(__self__, \\\"managed_network_name\\\", managed_network_name)\\n pulumi.set(__self__, \\\"resource_group_name\\\", resource_group_name)\\n if kind is not None:\\n pulumi.set(__self__, \\\"kind\\\", kind)\\n if location is not None:\\n pulumi.set(__self__, \\\"location\\\", location)\\n if managed_network_group_name is not None:\\n pulumi.set(__self__, \\\"managed_network_group_name\\\", managed_network_group_name)\\n if management_groups is not None:\\n pulumi.set(__self__, \\\"management_groups\\\", management_groups)\\n if subnets is not None:\\n pulumi.set(__self__, \\\"subnets\\\", subnets)\\n if subscriptions is not None:\\n pulumi.set(__self__, \\\"subscriptions\\\", subscriptions)\\n if virtual_networks is not None:\\n pulumi.set(__self__, \\\"virtual_networks\\\", virtual_networks)\",\n \"def CreateRequests(self, args):\\n\\n image = self.messages.Image(\\n name=args.name,\\n description=args.description,\\n sourceType=self.messages.Image.SourceTypeValueValuesEnum.RAW,\\n family=args.family)\\n\\n csek_keys = csek_utils.CsekKeyStore.FromArgs(\\n args, self._ALLOW_RSA_ENCRYPTED_CSEK_KEYS)\\n if csek_keys:\\n image_ref = self.resources.Parse(args.name, collection='compute.images')\\n image.imageEncryptionKey = csek_utils.MaybeToMessage(\\n csek_keys.LookupKey(image_ref,\\n raise_if_missing=args.require_csek_key_create),\\n self.compute_client.apitools_client)\\n\\n # Validate parameters.\\n if args.source_disk_zone and not args.source_disk:\\n raise exceptions.ToolException(\\n 'You cannot specify [--source-disk-zone] unless you are specifying '\\n '[--source-disk].')\\n\\n if args.source_disk and args.source_uri:\\n raise exceptions.ConflictingArgumentsException(\\n '--source-uri', '--source-disk')\\n\\n if not (args.source_disk or args.source_uri):\\n raise exceptions.MinimumArgumentException(\\n ['--source-uri', '--source-disk'],\\n 'Please specify either the source disk or the Google Cloud Storage '\\n 'URI of the disk image.'\\n )\\n\\n # TODO(user): use resources.REGISTRY.Parse() for GCS URIs (b/30086260).\\n if args.source_uri:\\n source_uri = utils.NormalizeGoogleStorageUri(args.source_uri)\\n image.rawDisk = self.messages.Image.RawDiskValue(source=source_uri)\\n else:\\n source_disk_ref = flags.SOURCE_DISK_ARG.ResolveAsResource(\\n args, self.resources,\\n scope_lister=compute_flags.GetDefaultScopeLister(\\n self.compute_client, self.project))\\n image.sourceDisk = source_disk_ref.SelfLink()\\n image.sourceDiskEncryptionKey = csek_utils.MaybeLookupKeyMessage(\\n csek_keys, source_disk_ref, self.compute_client.apitools_client)\\n\\n if args.licenses:\\n image.licenses = args.licenses\\n\\n guest_os_features = getattr(args, 'guest_os_features', [])\\n if guest_os_features:\\n guest_os_feature_messages = []\\n for feature in guest_os_features:\\n gf_type = self.messages.GuestOsFeature.TypeValueValuesEnum(feature)\\n guest_os_feature = self.messages.GuestOsFeature()\\n guest_os_feature.type = gf_type\\n guest_os_feature_messages.append(guest_os_feature)\\n image.guestOsFeatures = guest_os_feature_messages\\n\\n request = self.messages.ComputeImagesInsertRequest(\\n image=image,\\n project=self.project)\\n\\n return [request]\",\n \"def request_workspace_add(self, request):\\n user_id = request['user_id']\\n alias = request['alias'] \\n source_uuid = request['source'] \\n# print('###', user_id)\\n# print('###', alias)\\n# print('###', source_uuid)\\n \\n response = self.copy_workspace(user_id, source_uuid=source_uuid, target_alias=alias)\\n \\n return response\",\n \"def new_network(router_simulator):\\n router = input('Enter router name: ')\\n network = input('Enter network: ')\\n try:\\n distance = int(input('Enter distance: '))\\n except ValueError:\\n print('Distance not valid.')\\n return\\n\\n try:\\n router_simulator.add_network(router, network, distance)\\n except KeyError:\\n print('Router was not found.')\",\n \"def __init__(__self__, *,\\n kind: str,\\n name: Optional[str] = None,\\n source_id: Optional[str] = None):\\n pulumi.set(__self__, \\\"kind\\\", kind)\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if source_id is not None:\\n pulumi.set(__self__, \\\"source_id\\\", source_id)\",\n \"def AddNetwork(parser):\\n parser.add_argument(\\n '--network',\\n help=(\\n 'Network in the current project that the instance will be part '\\n 'of. To specify using a network with a shared VPC, use the full '\\n \\\"URL of the network. For an example host project, 'testproject', \\\"\\n \\\"and shared network, 'testsharednetwork', this would use the \\\"\\n 'form: '\\n '`--network`=`projects/testproject/global/networks/'\\n 'testsharednetwork`'\\n ),\\n )\",\n \"def __init__(__self__, *,\\n machine_name: str,\\n source: str,\\n source_computer_id: str,\\n vmuuid: str,\\n workspace_id: str):\\n pulumi.set(__self__, \\\"machine_name\\\", machine_name)\\n pulumi.set(__self__, \\\"source\\\", 'OnPremise')\\n pulumi.set(__self__, \\\"source_computer_id\\\", source_computer_id)\\n pulumi.set(__self__, \\\"vmuuid\\\", vmuuid)\\n pulumi.set(__self__, \\\"workspace_id\\\", workspace_id)\",\n \"def copy_to_region(self, region, name=None):\\r\\n if region.name == self.region:\\r\\n raise BotoClientError('Unable to copy to the same Region')\\r\\n conn_params = self.connection.get_params()\\r\\n rconn = region.connect(**conn_params)\\r\\n sg = rconn.create_security_group(name or self.name, self.description)\\r\\n source_groups = []\\r\\n for rule in self.rules:\\r\\n grant = rule.grants[0]\\r\\n for grant in rule.grants:\\r\\n if grant.name:\\r\\n if grant.name not in source_groups:\\r\\n source_groups.append(grant.name)\\r\\n sg.authorize(None, None, None, None, grant)\\r\\n else:\\r\\n sg.authorize(rule.ip_protocol, rule.from_port, rule.to_port,\\r\\n grant.cidr_ip)\\r\\n return sg\",\n \"def create(ctx, iface, resource_config, **_):\\n resource_id = \\\\\\n utils.get_resource_id(\\n ctx.node,\\n ctx.instance,\\n resource_config.get(VPN_CONNECTION_ID),\\n use_instance_id=True\\n )\\n utils.update_resource_id(ctx.instance, resource_id)\\n # Actually create the resource\\n create_response = iface.create(resource_config)\\n ctx.instance.runtime_properties['create_response'] = \\\\\\n utils.JsonCleanuper(create_response).to_dict()\\n ctx.instance.runtime_properties['VPN_CONNECTION_ID'] = \\\\\\n resource_config.get(VPN_CONNECTION_ID)\\n ctx.instance.runtime_properties['DESTINATION_CIDR_BLOCK'] = \\\\\\n resource_config.get(DESTINATION_CIDR_BLOCK)\",\n \"def GenerateAssetForCreateRequest(args):\\n module = dataplex_api.GetMessageModule()\\n resource_spec_field = module.GoogleCloudDataplexV1AssetResourceSpec\\n resource_spec = module.GoogleCloudDataplexV1AssetResourceSpec(\\n name=args.resource_name,\\n type=resource_spec_field.TypeValueValuesEnum(args.resource_type),\\n )\\n request = module.GoogleCloudDataplexV1Asset(\\n description=args.description,\\n displayName=args.display_name,\\n labels=dataplex_api.CreateLabels(module.GoogleCloudDataplexV1Asset, args),\\n resourceSpec=resource_spec,\\n )\\n discovery = GenerateDiscoverySpec(args)\\n if discovery != module.GoogleCloudDataplexV1AssetDiscoverySpec():\\n setattr(request, 'discoverySpec', discovery)\\n return request\",\n \"def _create_graph(netlist):\\n G = nx.Graph()\\n for t in netlist:\\n G.add_edges_from([(t.name, t.drain), (t.name, t.gate), (t.name, t.source)])\\n return G\",\n \"def create_network(model_file=DEFAULT_MODEL_FILE, pretrained=DEFAULT_PRETRAINED, *args, **kwargs):\\n net = imagenet_classifier(*args,**kwargs)\\n net.set_phase_test()\\n net.set_mode_cpu()\\n return net\",\n \"def make_network_set(name, networkUris=[]):\\n\\n return {\\n 'name': name,\\n 'type': 'network-set',\\n 'nativeNetworkUri': None,\\n 'networkUris': networkUris[:],\\n 'connectionTemplateUri': None}\"\n]"},"negative_scores":{"kind":"list like","value":["0.65968263","0.64328766","0.63080657","0.60401773","0.585405","0.5773544","0.5750441","0.5715569","0.569809","0.55888134","0.5588614","0.5553594","0.54480547","0.5373371","0.5347243","0.53328407","0.5326178","0.53198993","0.5311947","0.52965164","0.52929527","0.5270218","0.5234661","0.5220858","0.52133614","0.52063507","0.5205628","0.5166636","0.51565284","0.51444143","0.51334774","0.5131441","0.51275235","0.51014805","0.50814223","0.50769323","0.5074249","0.5062834","0.5058499","0.5056606","0.50371295","0.5033076","0.502778","0.50139195","0.50113475","0.5001417","0.49939573","0.49828845","0.49820232","0.4970704","0.49672854","0.4965855","0.4939921","0.49304464","0.49101698","0.49085504","0.49052817","0.48938397","0.4884536","0.48842368","0.4879119","0.48719698","0.48550883","0.48500666","0.4846681","0.4831963","0.48290277","0.48251617","0.48162788","0.47990924","0.47881907","0.47873548","0.47703046","0.47696108","0.47659346","0.47645563","0.47627604","0.47617888","0.4750368","0.47498903","0.4742167","0.47378832","0.47321358","0.47317696","0.47269976","0.47260365","0.47219142","0.47218364","0.471429","0.47125453","0.47111624","0.4704347","0.46965212","0.46930036","0.4690475","0.4689405","0.4686237","0.4679039","0.46789414","0.46759167"],"string":"[\n \"0.65968263\",\n \"0.64328766\",\n \"0.63080657\",\n \"0.60401773\",\n \"0.585405\",\n \"0.5773544\",\n \"0.5750441\",\n \"0.5715569\",\n \"0.569809\",\n \"0.55888134\",\n \"0.5588614\",\n \"0.5553594\",\n \"0.54480547\",\n \"0.5373371\",\n \"0.5347243\",\n \"0.53328407\",\n \"0.5326178\",\n \"0.53198993\",\n \"0.5311947\",\n \"0.52965164\",\n \"0.52929527\",\n \"0.5270218\",\n \"0.5234661\",\n \"0.5220858\",\n \"0.52133614\",\n \"0.52063507\",\n \"0.5205628\",\n \"0.5166636\",\n \"0.51565284\",\n \"0.51444143\",\n \"0.51334774\",\n \"0.5131441\",\n \"0.51275235\",\n \"0.51014805\",\n \"0.50814223\",\n \"0.50769323\",\n \"0.5074249\",\n \"0.5062834\",\n \"0.5058499\",\n \"0.5056606\",\n \"0.50371295\",\n \"0.5033076\",\n \"0.502778\",\n \"0.50139195\",\n \"0.50113475\",\n \"0.5001417\",\n \"0.49939573\",\n \"0.49828845\",\n \"0.49820232\",\n \"0.4970704\",\n \"0.49672854\",\n \"0.4965855\",\n \"0.4939921\",\n \"0.49304464\",\n \"0.49101698\",\n \"0.49085504\",\n \"0.49052817\",\n \"0.48938397\",\n \"0.4884536\",\n \"0.48842368\",\n \"0.4879119\",\n \"0.48719698\",\n \"0.48550883\",\n \"0.48500666\",\n \"0.4846681\",\n \"0.4831963\",\n \"0.48290277\",\n \"0.48251617\",\n \"0.48162788\",\n \"0.47990924\",\n \"0.47881907\",\n \"0.47873548\",\n \"0.47703046\",\n \"0.47696108\",\n \"0.47659346\",\n \"0.47645563\",\n \"0.47627604\",\n \"0.47617888\",\n \"0.4750368\",\n \"0.47498903\",\n \"0.4742167\",\n \"0.47378832\",\n \"0.47321358\",\n \"0.47317696\",\n \"0.47269976\",\n \"0.47260365\",\n \"0.47219142\",\n \"0.47218364\",\n \"0.471429\",\n \"0.47125453\",\n \"0.47111624\",\n \"0.4704347\",\n \"0.46965212\",\n \"0.46930036\",\n \"0.4690475\",\n \"0.4689405\",\n \"0.4686237\",\n \"0.4679039\",\n \"0.46789414\",\n \"0.46759167\"\n]"},"document_score":{"kind":"string","value":"0.6830833"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8580,"cells":{"query":{"kind":"string","value":"Creates Oauth token for the user"},"document":{"kind":"string","value":"def create_o_auth_client_credential(self, user_id, create_o_auth2_client_credential_details, **kwargs):\n resource_path = \"/users/{userId}/oauth2ClientCredentials\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_o_auth_client_credential got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_o_auth2_client_credential_details,\n response_type=\"OAuth2ClientCredential\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_o_auth2_client_credential_details,\n response_type=\"OAuth2ClientCredential\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def _create_auth_token(self, user=None):\n token, created = Token.objects.get_or_create(user=user)\n return token","def token_auth(self):\n self.client = APIClient()\n self.user = User.objects.create_user(username='testuser', email='test@test.com', password='testpassword')\n self.token = Token.objects.create(user=self.user)\n self.client.credentials(HTTP_AUTHORIZATION='Token ' + self.token.key)","def create_token(request, user):\n\n key = get_random_string(100)\n data = {}\n ip = get_client_ip_address(request)\n\n return Token.objects.create(user=user, key=key, data=json.dumps(data), ip=ip)","def create_auth_token():\n data = get_request_data(request)\n address = data.get(\"address\")\n expiration = int(data.get(\"expiration\"))\n\n pk = get_provider_private_key(use_universal_key=True)\n token = jwt.encode({\"exp\": expiration, \"address\": address}, pk, algorithm=\"HS256\")\n token = token.decode(\"utf-8\") if isinstance(token, bytes) else token\n\n valid, message = is_token_valid(token, address)\n if not valid:\n if message == \"Token is deleted.\":\n force_restore_token(token)\n else:\n return jsonify(error=message), 400\n\n return jsonify(token=token)","def create_token(user):\n access_token = create_access_token(user)\n payload = jwt.decode(\n access_token,\n app.config['JWT_SECRET_KEY'],\n algorithms=app.config['JWT_DECODE_ALGORITHMS'])\n data = {\n 'token':access_token,\n 'username': user.username,\n }\n data.update(payload)\n data['exp'] = datetime.fromtimestamp(data['exp'])\n app.logger.debug(str(data))\n if app.config.get('KEEP_TOKEN'):\n # deletes old tokens\n tokens = app.data.driver.db[config.DOMAIN['token']['datasource']['source']]\n tokens.delete_many({'username': user.username})\n # insets new token\n result = app.data.insert('token', data)\n return access_token, str(result[0])\n\n return access_token, None","def test_create_o_auth_access_token(self):\n pass","def generate_token(user):\n if JWT_AUTH:\n payload = JWT_PAYLOAD_HANDLER(user)\n return JWT_ENCODE_HANDLER(payload)\n else:\n token = Token.objects.create(user=user)\n token.save()\n return token","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def create_auth_token(sender, instance=None, created=False, **kwargs):\n if created:\n Token.objects.create(user=instance)","def post(self, **kwargs):\n username: str = request.json.get(\"username\", None)\n password: str = request.json.get(\"password\", None)\n user = get_user_instance(username, password)\n return {\"access_token\": create_access_token(identity=user)}, 200","def create_token():\n def token_helper():\n token = util.prompt_for_user_token(username=\"robbo1992\", scope='user-library-read playlist-modify-private playlist-modify',\n client_id=config[\"spotify\"][\"client_id\"], client_secret=config[\"spotify\"][\"secret_id\"],\n redirect_uri='http://localhost:8080', cache_path=spotify_cache)\n return token\n if token_helper():\n log.debug(\"Succesfully generated a spotify token for authentication\")\n return spotipy.Spotify(auth=token_helper())\n else:\n if motley.internet:\n if token_helper():\n log.debug(\"Succesfully generated a spotify token for authentication\")\n return spotipy.Spotify(auth=token_helper())\n else:\n log.error(\"Authentication error in create_token method.\")","def create(self, request):\n token = AuthTokenClass().post(request)\n return token","def post(self):\n _purge_expired_user_tokens()\n\n request_dict = get_json_and_verify_params({\n 'description': {'type': str, 'optional': True},\n 'expiration_date': {'optional': True},\n })\n\n expiration_date = request_dict.get('expiration_date')\n if expiration_date:\n expiration_date = parse_utc_datetime(\n expiration_date, timezone=\"UTC\")\n\n return current_user.create_auth_token(request_dict.get('description'),\n expiration_date)","def generate_token(user):\n try:\n # generate the auth token\n auth_token = User.encode_auth_token(user.id)\n response_object = {\n \"status\": \"success\",\n \"message\": \"Successfully registered.\",\n \"Authorization\": auth_token.decode(),\n }\n return response_object, 201\n except Exception as e:\n response_object = {\n \"status\": \"fail\",\n \"message\": \"Some error occurred. Please try again.\",\n }\n return response_object, 401","async def create_token(self, *args, **kwargs) -> OAuth2Token:\n token = await super().create_token(*args, **kwargs)\n # NOTE: Save data from token to db here.\n return token","def create_auth_token(sender, instance=None, created=False, **kwargs): # pylint: disable=unused-argument\n if created:\n Token.objects.create(user=instance) # pylint: disable=no-member","def create(self,request):\n return CustomAuthToken().post(request)","def generate_token(usr):\n token = jwt.encode({\"user\":usr, \"exp\":datetime.datetime.utcnow()\n + datetime.timedelta(minutes=30)}, KEY)\n user = User.update(token=token).where(User.username == usr)\n user.execute()\n return token","def test_create_token_for_user(self):\n\n credentials = {'email': 'testuser@gmail.com', 'password': 'Testpass12'}\n get_user_model().objects.create_user(**credentials)\n\n response = self.client.post(URL_TOKEN, credentials)\n\n # Check that the response is HTTP 200, and contains a token.\n self.assertIn('token', response.data)\n self.assertEqual(response.status_code, status.HTTP_200_OK)","def create(self, request):\n return ObtainAuthToken().post(request)","def generate_token(self):\n self.__get_auth_token_and_secret()\n return self.get_token()","def create(self, request, *args, **kwargs):\n serializer = self.get_serializer(data=request.data)\n serializer.is_valid(raise_exception=True)\n user = serializer.save()\n headers = self.get_success_headers(serializer.data)\n return Response(\n dict(serializer.data, token=str(user.auth_token)),\n status=status.HTTP_201_CREATED,\n headers=headers\n )","def create_bearer_token(self):\n headers = {\"Content-Type\": \"application/x-www-form-urlencoded\"}\n\n data = {\n \"grant_type\": \"refresh_token\",\n \"refresh_token\": self.refresh_token,\n \"client_id\": self.client_id,\n \"client_secret\": self.client_secret,\n }\n\n r = requests.post(self.token_endpoint, headers=headers, data=data)\n\n if r.status_code == 200:\n logging.info(\"Successfully obtained bearer token\")\n self.bearer_token = r.json()[\"access_token\"]\n else:\n logging.warning(\"HTTP Error {}\".format(r.status_code))","def post(self, request, *args, **kwargs):\n self.create(request, *args, **kwargs)\n token, created = Token.objects.get_or_create(user=self.user)\n return Response({'token': token.key}, status=201)","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create(self, data):\n token, created = Token.objects.get_or_create(user=self.context['user'])\n return self.context['user'], token.key","def create_auth_token(\n username: str,\n admin: t.Optional[bool] = False,\n spotify: t.Optional[bool] = False,\n) -> JWT:\n auth_token: JWT = auth_manager.auth_token(\n username, {\"admin\": admin, \"spotify\": spotify}\n )\n return auth_token","def test_create_o_auth_authorize_token(self):\n pass","def test_create_token_for_user(self):\n payload = {'email': 'test1@test1.ri',\n 'password': 'testPassWord',\n 'time_zone': 'Europe/Dublin'}\n create_user(**payload)\n res = self.client.post(TOKEN_URL, payload)\n\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def create(self, request):\n\n return ObtainAuthToken().post(request)","def test_create_token_for_user(self):\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'abcd1234',\n }\n\n create_user(**payload)\n response = self.client.post(TOKEN_URL, payload)\n\n # We expect a token and should get a HTTP 200\n self.assertIn('token', response.data)\n self.assertEqual(response.status_code, status.HTTP_200_OK)","def get_token(self):\n client_auth = requests.auth.HTTPBasicAuth(self.client, self.secret)\n post_data = {'grant_type': 'password', 'username': self.user, 'password': self.password}\n headers = {'User-Agent': self.user_agent}\n response = requests.Session()\n response2 = response.post(self.token_url, auth=client_auth, data=post_data, headers=headers)\n self.token = response2.json()['access_token']\n self.t_type = response2.json()['token_type']","def get_token(self):\n client_auth = requests.auth.HTTPBasicAuth(self.client, self.secret)\n post_data = {'grant_type': 'password', 'username': self.user, 'password': self.password}\n headers = {'User-Agent': self.user_agent}\n response = requests.Session()\n response2 = response.post(self.token_url, auth=client_auth, data=post_data, headers=headers)\n self.token = response2.json()['access_token']\n self.t_type = response2.json()['token_type']","def test_create_token_for_user(self):\r\n payload = {\r\n 'email': 'test@max.net',\r\n 'password': 'Testpass123',\r\n 'name': 'Maks'\r\n }\r\n create_user(**payload)\r\n\r\n res = self.client.post(TOKEN_URL, payload)\r\n\r\n self.assertIn('token', res.data)\r\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def create_access_token(oauth):\n #create parameters for API authorization\n\tredirect_uri = 'oob'\n\tparams = {'client_secret': oauth.client_secret,\n\t\t\t 'redirect_uri': redirect_uri,\n\t\t\t 'response_type': 'code'}\n\t#store the access code\n\turl = oauth.get_authorize_url(**params)\n\n\t#open a web browser to get access token and then store it via manual input\n\twebbrowser.open(url)\n\tcode = input('Enter code: ')\n\t#create credentials item\n\tstart_time = time.time()\n\t#create dictionary to hold credentials and store beginning time\n\tcredentials = {'token_time': start_time}\n\n\t#NEED TO ADD IN 'REFRESH TOKEN' FUNCTION HERE SOMEWHERE\n\t#\n\t\n\t#create parameters\n\tdata = {'code': code,\n\t\t\t'redirect_uri': redirect_uri,\n\t\t\t'grant_type': 'authorization_code'}\n\t#build the headers\n\theaders = oauth_headers(oauth)\n\t#create the raw access token\n\traw_access = oauth.get_raw_access_token(data=data, headers=headers)\n\t#parse the raw access token and add to credentials variable\n\tcredentials.update(access_parse(raw_access))\n\n\t#parse access token from credentials\n\taccess_token = credentials['access_token']\n\t#return access token\n\treturn access_token","def build_access_token_normal_user():\n return do_build_access_token(tenant_id='intility_tenant_id', admin=False)","def grant_token(request):\n\n grant_token_svc = request.find_service(name=\"grant_token\")\n h_user = request.lti_user.h_user\n\n return {\"grant_token\": grant_token_svc.generate_token(h_user)}","def get_token(self):\n\t\tself.client.post('/api/v1/auth/signup', data=json.dumps(self.signup_user), content_type='application/json')\n\t\tresponse = self.client.post('/api/v1/auth/login', data=json.dumps(self.login_user), content_type='application/json')\n\t\tresp = json.loads(response.data.decode())\n\t\treturn 'Bearer ' + resp['access_token']","def create_token(self):\n ts_datetime = self.logged_at or self.created_at\n ts = int(mktime(ts_datetime.timetuple()))\n key = base64.encodestring(self.email)\n base = \"{}{}\".format(key, ts)\n salt, hsh = self.password.split('$')\n return \"{}$${}\".format(key, get_hexdigest(salt, base))","def test_create_token_for_user(self):\n payload = {'email': 'test@test.com', 'password': 'testpass'}\n create_user(**payload)\n res = self.client.post(TOKEN_URL, payload)\n\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def UserToken(self) -> object:","def test_create_token_for_user(self):\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'testpass'\n }\n create_user(**payload)\n res = self.client.post(TOKEN_URI, payload)\n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def create_token(user):\n payload = {\n 'sub': user.id,\n 'iat': datetime.utcnow(),\n 'exp': datetime.utcnow() + timedelta(days=1)\n }\n token = jwt.encode(payload, config.SECRET_KEY, algorithm='HS256')\n return token.decode('unicode_escape')","def set_auth_token_header(self):\n\n username = 'test-user'\n passwd = 'testuserpass1234'\n user = User.objects.create(username=username)\n user.set_password(passwd)\n user.save()\n\n assert Account.objects.get(user=user) is not None\n url = reverse('token_obtain_pair')\n res = self.client.post(url,\n data={'username': username, 'password': passwd})\n self.client.credentials(HTTP_AUTHORIZATION=\n f\"Bearer {res.data['access']}\")\n return user","def create_token_response(self):\n client = self.request.client\n scope = self.request.credential.get_scope()\n token = self.generate_token(\n user=self.request.user,\n scope=scope,\n include_refresh_token=client.check_grant_type('refresh_token'),\n )\n log.debug('Issue token %r to %r', token, client)\n self.save_token(token)\n self.execute_hook('process_token', token=token)\n return 200, token, self.TOKEN_RESPONSE_HEADER","def create_token(self, consumer, token_type, timestamp, scope,\n user=None, callback=None, callback_confirmed=False):\n token = self.create(consumer=consumer, \n token_type=token_type, \n timestamp=timestamp,\n scope=scope,\n user=user,\n callback=callback,\n callback_confirmed=callback_confirmed,\n key=uuid.uuid4().hex,\n secret=get_random_string(length=SECRET_SIZE))\n\n return token","def create_auth_token(sender, instance=None, created=False, **kwargs):\n\n if created:\n # Generate API token for user.\n api_token = Token.objects.create(user=instance)\n\n # Only create agent using username and API token for non-admin users.\n if instance.is_superuser is False:\n Agent.objects.create(scan_agent=instance, api_token=api_token)","def get_user_token(username, expires_at=None):\n issued_at = datetime.utcnow()\n token = AccessToken()\n token.payload.update(\n {\n \"email\": f\"{username}@funmooc.fr\",\n \"exp\": expires_at or issued_at + timedelta(days=2),\n \"iat\": issued_at,\n \"language\": settings.LANGUAGE_CODE,\n \"username\": username,\n }\n )\n return token","def token_gen_call(username, password, exp=None):\n #pdb.set_trace()\n \n #username_set = params['AUTH']['username_set']\n #password_set = params['AUTH']['password_set']\n username_set = username\n password_set = password\n \"\"\"\n Creates JWT Token\n :return:\n \"\"\"\n if exp is None:\n exp = datetime.utcnow() + timedelta(seconds=3600)\n _token = {\n 'aud': JWT_AUDIENCE,\n 'exp': exp,\n 'iss': JWT_ISSUER,\n 'user': username,\n 'role': 'admin',\n 'time':time.time()\n }\n _token.update(_token)\n \n if password_set == password and username_set == username: # example, don't do this in production\n return {\"token\" : jwt.encode(_token, SECRET_KEY, algorithm=JWT_OPTIONS_ALGORITHM).decode('utf-8') }\n return 'Invalid username and/or password for user: {0}'.format(username)","def get_token():\n if g.current_user.is_anonymous or g.token_used:\n return unauthorized('Invalid credentials')\n return jsonify({'token': g.current_user.generate_auth_token(\n expiration=3600), 'expiration': 3600})","def get_token():\n if g.current_user.is_anonymous or g.token_used:\n return unauthorized('Invalid credentials')\n return jsonify({'token': g.current_user.generate_auth_token(\n expiration=3600), 'expiration': 3600})","def generate_token(email):\n access_token = create_access_token(email)\n return access_token","def create_oauth(self, user):\r\n from oauth_provider.models import Consumer, Token, Resource\r\n\r\n # Necessary setup for ``oauth_provider``.\r\n resource, _ = Resource.objects.get_or_create(url='test', defaults={\r\n 'name': 'Test Resource'\r\n })\r\n consumer, _ = Consumer.objects.get_or_create(key='123', defaults={\r\n 'name': 'Test',\r\n 'description': 'Testing...'\r\n })\r\n token, _ = Token.objects.get_or_create(key='foo', token_type=Token.ACCESS, defaults={\r\n 'consumer': consumer,\r\n 'resource': resource,\r\n 'secret': '',\r\n 'user': user,\r\n })\r\n\r\n # Then generate the header.\r\n oauth_data = {\r\n 'oauth_consumer_key': '123',\r\n 'oauth_nonce': 'abc',\r\n 'oauth_signature': '&',\r\n 'oauth_signature_method': 'PLAINTEXT',\r\n 'oauth_timestamp': str(int(time.time())),\r\n 'oauth_token': 'foo',\r\n }\r\n return 'OAuth %s' % ','.join([key + '=' + value for key, value in oauth_data.items()])","def post(self):\n current_user_id = get_jwt_identity()\n new_token = create_access_token(identity=current_user_id)\n response, status = {\n 'message': 'Access token was successfully refreshed',\n 'access_token': new_token\n }, 200\n return Response(dumps(response), status=status, mimetype='application/json')","def test_create_token_to_user(self):\n data = {\n 'email': 'test@test.com', \n 'password': \"testtest\"\n }\n res = self.client.post(TOKEN_URL, data)\n\n self.assertNotIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def get_token():\n if not request.is_json:\n return jsonify({\"msg\": \"Missing JSON in request\"}), 400\n username = request.json.get('username', None)\n password = request.json.get('password', None)\n\n if not username:\n abort(400, \"Invalid username or password\")\n if not password:\n abort(400, \"Invalid username or password\")\n users = app.data.driver.db[config.DOMAIN['user']['datasource']['source']]\n user = users.find_one({'email':username})\n # validate the user in the user's service\n if not user:\n abort(401, \"Invalid username or password\")\n if not check_password_hash(user.get('password'), password):\n abort(401, \"Invalid username or password\")\n role = user.get('role', 'user')\n user_id = str(user.get('_id'))\n user = User(user_id, username, role)\n access_token, refresh_token = create_token(user)\n return jsonify(\n token=access_token,\n type='bearer',\n roles=role,\n user=username,\n refreshToken=refresh_token), 200","def get_token(cls, user, full_result=False):\n if user is None:\n return EMPTY_KNOX_TOKEN\n result = AuthToken.objects.create(user=user)\n return result if full_result else result[1]","def test_create_token(self):\n data = {'email': 'test@test.com', 'password': 'testtest'}\n sigin_in_user(**data)\n payload = {\n 'username': 'test@test.com',\n 'password': 'testtest'\n }\n res = self.client.post(TOKEN_URL, payload)\n \n self.assertIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_200_OK)","def create_access_token(identity: Union[str,int], type_token: str, fresh: Optional[bool] = False) -> bytes:\n return AuthJWT.create_token(\n identity=identity,\n type_token=type_token,\n fresh=fresh,\n exp_time=timedelta(minutes=AuthJWT._ACCESS_TOKEN_EXPIRES)\n )","def generate_token_from_user(user, expires_at=None):\n issued_at = datetime.utcnow()\n token = AccessToken()\n token.payload.update(\n {\n \"email\": user.email,\n \"exp\": expires_at or issued_at + timedelta(days=2),\n \"iat\": issued_at,\n \"language\": user.language,\n \"username\": user.username,\n \"full_name\": user.get_full_name(),\n }\n )\n return token","def auth_token_generate(identity_param_val, expires_delta=False):\n access_token = ''\n try:\n if expires_delta is not False:\n expires_delta = timedelta(minutes=expires_delta)\n access_token = create_access_token(identity=identity_param_val, expires_delta=expires_delta)\n except Exception as e:\n print(e)\n\n return access_token","async def oauth2_token(\n request: Request, oauth2_request=Depends(_oauth2_request)\n):","def create_access_token(self):\n\t\t# Wraper for also caching invalid results\n #def getMetadataRofs(path):\n #\ttry:\n # \treturn self.client.metadata(path)\n # except Exception, e:\n # log.write('Exception at getMetadataRofs for path '+ path + '\\n')\n # pprint(e, log)\n # return False\n\n\t\ttry:\n\t\t\trequest_token = self.session.obtain_request_token()\n\t\t\turl = self.session.build_authorize_url(request_token)\n\t\t\tprint url\n\t\t\traw_input()\n\t\t\taccess_token = self.session.obtain_access_token(request_token)\n\t\t\tself.client = client.DropboxClient(self.session)\n\t\t\t\n\t\t\t# Build cache for metadata querying\n\n\t\t\t# Wraper for also caching invalid results\n\t\t\tdef getMetadataRofs(path):\n\t\t\t\ttry:\n\t\t\t\t\treturn self.client.metadata(path)\n\t\t\t\texcept Exception, e:\n\t\t\t\t\tlogger.error('Exception at getMetadataRofs for path '+ path + '\\n')\n\t\t logger.debug(sys.exc_info()[0])\n\t\t\t\t\treturn False\n\n\t\t\tself.cache_metadata = Cache(getMetadataRofs)\n\t\t\tself.cache_files = {}\n\n\t\texcept Exception, e:\n\t\t\tlogger.error('Exception %s at create_access_token' % (sys.exc_info()[0]))\n\t\t\tlogger.debug(pformat(sys.exc_info()))","def _generate_jwt_token(self):\n import jwt\n from datetime import datetime, timedelta\n from django.conf import settings\n\n dt = datetime.now() + timedelta(days=60)\n\n token = jwt.encode({\n 'id': self.pk,\n 'username': self.username,\n 'exp': int(dt.strftime('%s')),\n }, settings.SECRET_KEY, algorithm='HS256')\n # print(token)\n return token","def post(self):\n data = request.get_json()\n is_verified = actions.verify(data['username'], data['password'])\n if not is_verified:\n abort(404, message='A user with matching credentials does not exist.')\n else:\n token = actions.create_token(data['username'], data['password'])\n token = token.decode('utf-8')\n return{'token': token}, 200\n pass","def get_auth_token():\n token = g.user.generate_auth_token(24*3600)\n return jsonify({'user_id': g.user.id, 'token': token.decode('ascii')})","def _request_token(self):\n response = requests.post(\n \"%s/generateToken\" % self.root_uri.rstrip(\"/\"), {\n \"username\": self.username,\n \"password\": self.password,\n \"expiration\": '60',\n \"referer\": 'https://wsdot.maps.arcgis.com',\n \"f\": 'json'\n })\n\n token_info = response.json()\n if \"error\" in token_info:\n raise TokenError(token_info[\"error\"])\n self._token = token_info[\"token\"]\n self._expires = datetime.fromtimestamp(token_info[\"expires\"] / 1000)","def test_create_token_for_user(setup_client):\n client = setup_client\n payload = {\n 'email': 'test@gmail.com',\n 'password': 'testpass',\n }\n create_user(**payload, **{'role': 'Supplier'})\n res = client.post(TOKEN_URL, payload)\n assert \"token\" in res.data\n assert res.status_code == status.HTTP_200_OK","def create_token(self, consumer, token_type, timestamp, user=None):\n token, created = self.first_or_create(consumer=consumer, \n token_type=token_type, \n timestamp=timestamp,\n user=user)\n\n if created:\n token.key, token.secret = self.generate_random_codes()\n token.save()\n\n return token","def create_auth_token(self, create_auth_token_details, user_id, **kwargs):\n resource_path = \"/users/{userId}/authTokens\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_auth_token got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_auth_token_details,\n response_type=\"AuthToken\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_auth_token_details,\n response_type=\"AuthToken\")","def get_access_token(self, path='/oauth/token', data={}):\n if data.keys():\n data.update(self.data)\n else:\n data = self.data.copy()\n data.update({\n 'grant_type': 'password',\n 'email': self.env.get('TESLA_EMAIL'),\n 'password': self.env.get('TESLA_PASSWORD')\n })\n try:\n req = requests.post(url='%s%s' % (self.url, path), data=data)\n # print(req.status_code)\n # print(req.content)\n self.token.update(req.json())\n except:\n raise 'invalid credentials'\n return self.token","def _get_token(self, client):\n\n url = self._url('token')\n data = {'grant_type': 'password',\n 'username': self.user,\n 'password': self.password,\n 'scope': 'PRODUCTION'}\n client_data = self.clients[client]\n consumer_key = client_data['response']['consumerKey']\n consumer_secret = client_data['response']['consumerSecret']\n auth = requests.auth.HTTPBasicAuth(consumer_key, consumer_secret)\n return self.POST(url, data=data, auth=auth)","def get_new_token(self):\n self.register_user(self.user_data2)\n result = self.login_user(self.login_data2)\n header_access_token = json.loads(result.data.decode())['header_access_token']\n return header_access_token","def get_oauth_token():\n\n # make a request to goodreads authorization url, and pass in request tokens\n gr_session = goodreads.get_auth_session(session['request_token'],\n session['request_token_secret'])\n\n ACCESS_TOKEN = gr_session.access_token\n ACCESS_TOKEN_SECRET = gr_session.access_token_secret\n\n # add OAuth tokens to Account object.\n acct = Account.query.get(session[\"acct\"])\n acct.access_token = ACCESS_TOKEN\n acct.access_token_secret = ACCESS_TOKEN_SECRET\n # get goodreads ID and url for a user and assign to user record.\n gr_id, gr_url, name, image_url = get_acct_id(acct, GR_KEY, GR_SECRET)\n acct.user.gr_id = gr_id\n acct.user.gr_url = gr_url\n acct.user.gr_name = name\n acct.user.image_url = image_url\n # commit changes to db.\n db.session.commit()\n\n return redirect(\"/\")","def _create_jwt(request, user, expires_in):\n oauth_application = _get_login_oauth_client()\n access_token = create_dot_access_token(\n # Note: Scopes for JWT cookies do not require additional permissions\n request, user, oauth_application, expires_in=expires_in, scopes=['user_id', 'email', 'profile'],\n )\n return create_jwt_from_token(access_token, DOTAdapter(), use_asymmetric_key=True)","def generateAuthToken(self):\n try:\n payload = {\n 'exp': datetime.utcnow() + timedelta(days=0, minutes=30),\n 'iat': datetime.utcnow(),\n 'sub': self.id\n }\n return jwt.encode(payload, current_app.config['SECRET_KEY'], algorithm='HS256').decode()\n except Exception as error:\n print(error)\n return error","def post(self):\n current_user = get_jwt_identity()\n return {\n # Mark the token as un-fresh since we used the refresh token to regenerate this\n \"accessToken\": create_access_token(identity=current_user, fresh=False),\n \"userId\": current_user\n }","def test_make_token(self):\n user = self.create_user()\n\n token_generator = EmailActivationTokenGenerator()\n token = token_generator.make_token(user)\n self.assertTrue(token_generator.check_token(user, token))","def auth_token(self):","def token(self):\n token = jwt.encode(\n {\n \"id\": self.pk,\n \"username\": self.get_full_name,\n \"email\": self.email,\n \"iat\": datetime.utcnow(),\n \"exp\": datetime.utcnow() + timedelta(minutes=int(os.getenv('TIME_DELTA')))\n },\n settings.SECRET_KEY, algorithm='HS256').decode()\n return token","def createAccessTokenReplacement(self):\r\n\r\n url = self._config['OAUTH2ENDPOINT']['huddleAuthServer'] + \"request?response_type=code\" + \\\r\n \"&client_id=\" + self._config['OAUTH2']['clientID'] + \\\r\n \"&redirect_uri=\" + self._config['OAUTH2']['redirectUri']\r\n webbrowser.open_new(url)\r\n code = input('Please enter the code from your web browser:')\r\n\r\n response = self._oauth.obtainAccessTokenBy3LeggedOAuth(code)\r\n responseBody = json.loads(response['Body'])\r\n\r\n try:\r\n oauthToken = Token(responseBody)\r\n except TypeError as e:\r\n print (\"Bad response when requesting a token \" + str(response))\r\n sys.exit()\r\n\r\n return oauthToken","def get_auth_token_teacher():\n\n token = g.user.generate_auth_token(600)\n return jsonify({'token': token.decode('ascii'), 'duration': 600})","def generate_auth_token(self, expires_in=600):\n return jwt.encode(\n {'STULOGINID': self.STULOGINID, 'exp': time.time() + expires_in},\n app.config['SECRET_KEY'], algorithm='HS256')","def create(self, user, token):\n\n session['user'] = {\n 'id': str(user.id),\n 'login': user.login,\n 'token': token\n }\n\n return UserSession.create(session['user'])","def create_token_no_user(self):\n payload = {'email': 'test@test.com', 'password': 'testpass'}\n res = self.client.post(TOKEN_URL, payload)\n self.assertNotIn('token', res.data)\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def for_user(cls, user):\n\n token = super().for_user(user)\n\n TokenMeta.objects.get_or_create(\n jti=token['jti'],\n token=str(token),\n )\n\n return token","def create(self, validated_data):\n request = self._kwargs['context']['request']\n user = User.objects.create(**validated_data)\n user.set_password(validated_data[\"password\"])\n user.save()\n category_list = ['Fuel', 'Bill', 'Entertainment', 'Education', 'Food']\n for category in category_list:\n user.user_categories.create(name=category)\n login(request, user)\n token, created = Token.objects.get_or_create(user=user)\n validated_data[\"token\"] = token.key\n return validated_data","def get_token():\n\n def token_helper():\n token = util.prompt_for_user_token(username=\"robbo1992\",\n scope='user-library-read playlist-modify-private playlist-modify',\n client_id=config[\"spotify\"][\"client_id\"],\n client_secret=config[\"spotify\"][\"secret_id\"],\n redirect_uri='http://localhost:8080', cache_path=spotify_cache)\n return token\n\n if token_helper():\n log.debug(\"Succesfully generated a spotify token for authentication\")\n return spotipy.Spotify(auth=token_helper())\n else:\n if motley.internet:\n if token_helper():\n log.debug(\"Succesfully generated a spotify token for authentication\")\n return spotipy.Spotify(auth=token_helper())\n else:\n log.error(\"Authentication error in create_token method.\")\n raise Exception","def post(self):\r\n try:\r\n\r\n data = request.get_json()\r\n user = user_login.find_by_username(data['username'])\r\n if user and safe_str_cmp(user.password, data['password']):\r\n access_token = create_access_token(\r\n identity=user.id, fresh=True)\r\n return {\r\n 'access_token': \"Bearer \" + access_token,\r\n }, 200\r\n return {\"message\": \"Invalid Credentials!\"}, 401\r\n except Exception as e:\r\n return {\"message\": str(e)}","def create_token(self, token_type=DEFAULT_TOKEN, extra_data='{}'):\n if token_type not in dict(TOKEN_TYPES).keys():\n raise ValueError(\"Unable to create token, unknown type\")\n\n value = calc_checksum(self.email, salt=randint(0, maxint))\n\n return LoginToken.objects.create(user=self, value=value, token_type=token_type, extra_data=extra_data)","def create_user(self):\n username = \"\".join(choice(\n string.ascii_letters) for x in range (randint(7,10)))\n params = {\n \"first_name\":\"ugali\",\n \"last_name\":\"mayai\",\n \"email\":\"ugalimayai@gmail.com\",\n \"username\":username,\n \"password\":\"password\"\n }\n path = \"/api/v2/auth/signup\"\n user = self.client.post(path,\n data=json.dumps(params),\n content_type=\"application/json\")\n \n user_id = user.json['user_id']\n auth_token = user.json['AuthToken']\n return int(user_id), auth_token","def create_token(self, token_id, data):\n raise exception.NotImplemented() # pragma: no cover","async def login_access_token(\n form_data: OAuth2PasswordRequestForm = Depends()\n):\n user = await crud.user.authenticate(\n username=form_data.username, password=form_data.password\n )\n if not user:\n raise HTTPException(status_code=HTTP_404_NOT_FOUND, detail=\"Incorrect credentials\")\n elif not user.is_active:\n raise HTTPException(status_code=HTTP_403_FORBIDDEN, detail=\"Inactive user\")\n elif not user.is_email_verified:\n raise HTTPException(status_code=HTTP_403_FORBIDDEN, detail=\"Please verify your account via email\")\n access_token_expires = timedelta(minutes=config.ACCESS_TOKEN_EXPIRE_MINUTES)\n return {\n \"access_token\": create_access_token(\n data={\"user_id\": user.id}, expires_delta=access_token_expires\n ),\n \"token_type\": \"bearer\",\n }","def create(self, validated_data):\n\t\tinstance = super(UserSerializer, self).create(validated_data)\n\t\tinstance.set_password(validated_data['password'])\n\t\ttoken = Token.objects.create(user=instance)\n\t\tinstance.token = token\n\t\treturn instance","def make_token(self, user):\n return super()._make_token_with_timestamp(user, int(time.time()))","def create_token(user, title, expiration=_default_expiration_duration_opt):\n if expiration == _default_expiration_duration_opt:\n duration = _default_expiration_duration()\n expiration = duration + datetime.now() if duration else None\n\n token_code = random_string_generator(TOKEN_NAME_PREFIX_LENGTH + MINIMUM_TOKEN_SUFFIX_LENGTH)()\n token_name = token_code[:TOKEN_NAME_PREFIX_LENGTH]\n token_secret = token_code[TOKEN_NAME_PREFIX_LENGTH:]\n\n assert token_name\n assert token_secret\n\n return AppSpecificAuthToken.create(\n user=user,\n title=title,\n expiration=expiration,\n token_name=token_name,\n token_secret=DecryptedValue(token_secret),\n )"],"string":"[\n \"def _create_auth_token(self, user=None):\\n token, created = Token.objects.get_or_create(user=user)\\n return token\",\n \"def token_auth(self):\\n self.client = APIClient()\\n self.user = User.objects.create_user(username='testuser', email='test@test.com', password='testpassword')\\n self.token = Token.objects.create(user=self.user)\\n self.client.credentials(HTTP_AUTHORIZATION='Token ' + self.token.key)\",\n \"def create_token(request, user):\\n\\n key = get_random_string(100)\\n data = {}\\n ip = get_client_ip_address(request)\\n\\n return Token.objects.create(user=user, key=key, data=json.dumps(data), ip=ip)\",\n \"def create_auth_token():\\n data = get_request_data(request)\\n address = data.get(\\\"address\\\")\\n expiration = int(data.get(\\\"expiration\\\"))\\n\\n pk = get_provider_private_key(use_universal_key=True)\\n token = jwt.encode({\\\"exp\\\": expiration, \\\"address\\\": address}, pk, algorithm=\\\"HS256\\\")\\n token = token.decode(\\\"utf-8\\\") if isinstance(token, bytes) else token\\n\\n valid, message = is_token_valid(token, address)\\n if not valid:\\n if message == \\\"Token is deleted.\\\":\\n force_restore_token(token)\\n else:\\n return jsonify(error=message), 400\\n\\n return jsonify(token=token)\",\n \"def create_token(user):\\n access_token = create_access_token(user)\\n payload = jwt.decode(\\n access_token,\\n app.config['JWT_SECRET_KEY'],\\n algorithms=app.config['JWT_DECODE_ALGORITHMS'])\\n data = {\\n 'token':access_token,\\n 'username': user.username,\\n }\\n data.update(payload)\\n data['exp'] = datetime.fromtimestamp(data['exp'])\\n app.logger.debug(str(data))\\n if app.config.get('KEEP_TOKEN'):\\n # deletes old tokens\\n tokens = app.data.driver.db[config.DOMAIN['token']['datasource']['source']]\\n tokens.delete_many({'username': user.username})\\n # insets new token\\n result = app.data.insert('token', data)\\n return access_token, str(result[0])\\n\\n return access_token, None\",\n \"def test_create_o_auth_access_token(self):\\n pass\",\n \"def generate_token(user):\\n if JWT_AUTH:\\n payload = JWT_PAYLOAD_HANDLER(user)\\n return JWT_ENCODE_HANDLER(payload)\\n else:\\n token = Token.objects.create(user=user)\\n token.save()\\n return token\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n if created:\\n Token.objects.create(user=instance)\",\n \"def post(self, **kwargs):\\n username: str = request.json.get(\\\"username\\\", None)\\n password: str = request.json.get(\\\"password\\\", None)\\n user = get_user_instance(username, password)\\n return {\\\"access_token\\\": create_access_token(identity=user)}, 200\",\n \"def create_token():\\n def token_helper():\\n token = util.prompt_for_user_token(username=\\\"robbo1992\\\", scope='user-library-read playlist-modify-private playlist-modify',\\n client_id=config[\\\"spotify\\\"][\\\"client_id\\\"], client_secret=config[\\\"spotify\\\"][\\\"secret_id\\\"],\\n redirect_uri='http://localhost:8080', cache_path=spotify_cache)\\n return token\\n if token_helper():\\n log.debug(\\\"Succesfully generated a spotify token for authentication\\\")\\n return spotipy.Spotify(auth=token_helper())\\n else:\\n if motley.internet:\\n if token_helper():\\n log.debug(\\\"Succesfully generated a spotify token for authentication\\\")\\n return spotipy.Spotify(auth=token_helper())\\n else:\\n log.error(\\\"Authentication error in create_token method.\\\")\",\n \"def create(self, request):\\n token = AuthTokenClass().post(request)\\n return token\",\n \"def post(self):\\n _purge_expired_user_tokens()\\n\\n request_dict = get_json_and_verify_params({\\n 'description': {'type': str, 'optional': True},\\n 'expiration_date': {'optional': True},\\n })\\n\\n expiration_date = request_dict.get('expiration_date')\\n if expiration_date:\\n expiration_date = parse_utc_datetime(\\n expiration_date, timezone=\\\"UTC\\\")\\n\\n return current_user.create_auth_token(request_dict.get('description'),\\n expiration_date)\",\n \"def generate_token(user):\\n try:\\n # generate the auth token\\n auth_token = User.encode_auth_token(user.id)\\n response_object = {\\n \\\"status\\\": \\\"success\\\",\\n \\\"message\\\": \\\"Successfully registered.\\\",\\n \\\"Authorization\\\": auth_token.decode(),\\n }\\n return response_object, 201\\n except Exception as e:\\n response_object = {\\n \\\"status\\\": \\\"fail\\\",\\n \\\"message\\\": \\\"Some error occurred. Please try again.\\\",\\n }\\n return response_object, 401\",\n \"async def create_token(self, *args, **kwargs) -> OAuth2Token:\\n token = await super().create_token(*args, **kwargs)\\n # NOTE: Save data from token to db here.\\n return token\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs): # pylint: disable=unused-argument\\n if created:\\n Token.objects.create(user=instance) # pylint: disable=no-member\",\n \"def create(self,request):\\n return CustomAuthToken().post(request)\",\n \"def generate_token(usr):\\n token = jwt.encode({\\\"user\\\":usr, \\\"exp\\\":datetime.datetime.utcnow()\\n + datetime.timedelta(minutes=30)}, KEY)\\n user = User.update(token=token).where(User.username == usr)\\n user.execute()\\n return token\",\n \"def test_create_token_for_user(self):\\n\\n credentials = {'email': 'testuser@gmail.com', 'password': 'Testpass12'}\\n get_user_model().objects.create_user(**credentials)\\n\\n response = self.client.post(URL_TOKEN, credentials)\\n\\n # Check that the response is HTTP 200, and contains a token.\\n self.assertIn('token', response.data)\\n self.assertEqual(response.status_code, status.HTTP_200_OK)\",\n \"def create(self, request):\\n return ObtainAuthToken().post(request)\",\n \"def generate_token(self):\\n self.__get_auth_token_and_secret()\\n return self.get_token()\",\n \"def create(self, request, *args, **kwargs):\\n serializer = self.get_serializer(data=request.data)\\n serializer.is_valid(raise_exception=True)\\n user = serializer.save()\\n headers = self.get_success_headers(serializer.data)\\n return Response(\\n dict(serializer.data, token=str(user.auth_token)),\\n status=status.HTTP_201_CREATED,\\n headers=headers\\n )\",\n \"def create_bearer_token(self):\\n headers = {\\\"Content-Type\\\": \\\"application/x-www-form-urlencoded\\\"}\\n\\n data = {\\n \\\"grant_type\\\": \\\"refresh_token\\\",\\n \\\"refresh_token\\\": self.refresh_token,\\n \\\"client_id\\\": self.client_id,\\n \\\"client_secret\\\": self.client_secret,\\n }\\n\\n r = requests.post(self.token_endpoint, headers=headers, data=data)\\n\\n if r.status_code == 200:\\n logging.info(\\\"Successfully obtained bearer token\\\")\\n self.bearer_token = r.json()[\\\"access_token\\\"]\\n else:\\n logging.warning(\\\"HTTP Error {}\\\".format(r.status_code))\",\n \"def post(self, request, *args, **kwargs):\\n self.create(request, *args, **kwargs)\\n token, created = Token.objects.get_or_create(user=self.user)\\n return Response({'token': token.key}, status=201)\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create(self, data):\\n token, created = Token.objects.get_or_create(user=self.context['user'])\\n return self.context['user'], token.key\",\n \"def create_auth_token(\\n username: str,\\n admin: t.Optional[bool] = False,\\n spotify: t.Optional[bool] = False,\\n) -> JWT:\\n auth_token: JWT = auth_manager.auth_token(\\n username, {\\\"admin\\\": admin, \\\"spotify\\\": spotify}\\n )\\n return auth_token\",\n \"def test_create_o_auth_authorize_token(self):\\n pass\",\n \"def test_create_token_for_user(self):\\n payload = {'email': 'test1@test1.ri',\\n 'password': 'testPassWord',\\n 'time_zone': 'Europe/Dublin'}\\n create_user(**payload)\\n res = self.client.post(TOKEN_URL, payload)\\n\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def create(self, request):\\n\\n return ObtainAuthToken().post(request)\",\n \"def test_create_token_for_user(self):\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'abcd1234',\\n }\\n\\n create_user(**payload)\\n response = self.client.post(TOKEN_URL, payload)\\n\\n # We expect a token and should get a HTTP 200\\n self.assertIn('token', response.data)\\n self.assertEqual(response.status_code, status.HTTP_200_OK)\",\n \"def get_token(self):\\n client_auth = requests.auth.HTTPBasicAuth(self.client, self.secret)\\n post_data = {'grant_type': 'password', 'username': self.user, 'password': self.password}\\n headers = {'User-Agent': self.user_agent}\\n response = requests.Session()\\n response2 = response.post(self.token_url, auth=client_auth, data=post_data, headers=headers)\\n self.token = response2.json()['access_token']\\n self.t_type = response2.json()['token_type']\",\n \"def get_token(self):\\n client_auth = requests.auth.HTTPBasicAuth(self.client, self.secret)\\n post_data = {'grant_type': 'password', 'username': self.user, 'password': self.password}\\n headers = {'User-Agent': self.user_agent}\\n response = requests.Session()\\n response2 = response.post(self.token_url, auth=client_auth, data=post_data, headers=headers)\\n self.token = response2.json()['access_token']\\n self.t_type = response2.json()['token_type']\",\n \"def test_create_token_for_user(self):\\r\\n payload = {\\r\\n 'email': 'test@max.net',\\r\\n 'password': 'Testpass123',\\r\\n 'name': 'Maks'\\r\\n }\\r\\n create_user(**payload)\\r\\n\\r\\n res = self.client.post(TOKEN_URL, payload)\\r\\n\\r\\n self.assertIn('token', res.data)\\r\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def create_access_token(oauth):\\n #create parameters for API authorization\\n\\tredirect_uri = 'oob'\\n\\tparams = {'client_secret': oauth.client_secret,\\n\\t\\t\\t 'redirect_uri': redirect_uri,\\n\\t\\t\\t 'response_type': 'code'}\\n\\t#store the access code\\n\\turl = oauth.get_authorize_url(**params)\\n\\n\\t#open a web browser to get access token and then store it via manual input\\n\\twebbrowser.open(url)\\n\\tcode = input('Enter code: ')\\n\\t#create credentials item\\n\\tstart_time = time.time()\\n\\t#create dictionary to hold credentials and store beginning time\\n\\tcredentials = {'token_time': start_time}\\n\\n\\t#NEED TO ADD IN 'REFRESH TOKEN' FUNCTION HERE SOMEWHERE\\n\\t#\\n\\t\\n\\t#create parameters\\n\\tdata = {'code': code,\\n\\t\\t\\t'redirect_uri': redirect_uri,\\n\\t\\t\\t'grant_type': 'authorization_code'}\\n\\t#build the headers\\n\\theaders = oauth_headers(oauth)\\n\\t#create the raw access token\\n\\traw_access = oauth.get_raw_access_token(data=data, headers=headers)\\n\\t#parse the raw access token and add to credentials variable\\n\\tcredentials.update(access_parse(raw_access))\\n\\n\\t#parse access token from credentials\\n\\taccess_token = credentials['access_token']\\n\\t#return access token\\n\\treturn access_token\",\n \"def build_access_token_normal_user():\\n return do_build_access_token(tenant_id='intility_tenant_id', admin=False)\",\n \"def grant_token(request):\\n\\n grant_token_svc = request.find_service(name=\\\"grant_token\\\")\\n h_user = request.lti_user.h_user\\n\\n return {\\\"grant_token\\\": grant_token_svc.generate_token(h_user)}\",\n \"def get_token(self):\\n\\t\\tself.client.post('/api/v1/auth/signup', data=json.dumps(self.signup_user), content_type='application/json')\\n\\t\\tresponse = self.client.post('/api/v1/auth/login', data=json.dumps(self.login_user), content_type='application/json')\\n\\t\\tresp = json.loads(response.data.decode())\\n\\t\\treturn 'Bearer ' + resp['access_token']\",\n \"def create_token(self):\\n ts_datetime = self.logged_at or self.created_at\\n ts = int(mktime(ts_datetime.timetuple()))\\n key = base64.encodestring(self.email)\\n base = \\\"{}{}\\\".format(key, ts)\\n salt, hsh = self.password.split('$')\\n return \\\"{}$${}\\\".format(key, get_hexdigest(salt, base))\",\n \"def test_create_token_for_user(self):\\n payload = {'email': 'test@test.com', 'password': 'testpass'}\\n create_user(**payload)\\n res = self.client.post(TOKEN_URL, payload)\\n\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def UserToken(self) -> object:\",\n \"def test_create_token_for_user(self):\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'testpass'\\n }\\n create_user(**payload)\\n res = self.client.post(TOKEN_URI, payload)\\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def create_token(user):\\n payload = {\\n 'sub': user.id,\\n 'iat': datetime.utcnow(),\\n 'exp': datetime.utcnow() + timedelta(days=1)\\n }\\n token = jwt.encode(payload, config.SECRET_KEY, algorithm='HS256')\\n return token.decode('unicode_escape')\",\n \"def set_auth_token_header(self):\\n\\n username = 'test-user'\\n passwd = 'testuserpass1234'\\n user = User.objects.create(username=username)\\n user.set_password(passwd)\\n user.save()\\n\\n assert Account.objects.get(user=user) is not None\\n url = reverse('token_obtain_pair')\\n res = self.client.post(url,\\n data={'username': username, 'password': passwd})\\n self.client.credentials(HTTP_AUTHORIZATION=\\n f\\\"Bearer {res.data['access']}\\\")\\n return user\",\n \"def create_token_response(self):\\n client = self.request.client\\n scope = self.request.credential.get_scope()\\n token = self.generate_token(\\n user=self.request.user,\\n scope=scope,\\n include_refresh_token=client.check_grant_type('refresh_token'),\\n )\\n log.debug('Issue token %r to %r', token, client)\\n self.save_token(token)\\n self.execute_hook('process_token', token=token)\\n return 200, token, self.TOKEN_RESPONSE_HEADER\",\n \"def create_token(self, consumer, token_type, timestamp, scope,\\n user=None, callback=None, callback_confirmed=False):\\n token = self.create(consumer=consumer, \\n token_type=token_type, \\n timestamp=timestamp,\\n scope=scope,\\n user=user,\\n callback=callback,\\n callback_confirmed=callback_confirmed,\\n key=uuid.uuid4().hex,\\n secret=get_random_string(length=SECRET_SIZE))\\n\\n return token\",\n \"def create_auth_token(sender, instance=None, created=False, **kwargs):\\n\\n if created:\\n # Generate API token for user.\\n api_token = Token.objects.create(user=instance)\\n\\n # Only create agent using username and API token for non-admin users.\\n if instance.is_superuser is False:\\n Agent.objects.create(scan_agent=instance, api_token=api_token)\",\n \"def get_user_token(username, expires_at=None):\\n issued_at = datetime.utcnow()\\n token = AccessToken()\\n token.payload.update(\\n {\\n \\\"email\\\": f\\\"{username}@funmooc.fr\\\",\\n \\\"exp\\\": expires_at or issued_at + timedelta(days=2),\\n \\\"iat\\\": issued_at,\\n \\\"language\\\": settings.LANGUAGE_CODE,\\n \\\"username\\\": username,\\n }\\n )\\n return token\",\n \"def token_gen_call(username, password, exp=None):\\n #pdb.set_trace()\\n \\n #username_set = params['AUTH']['username_set']\\n #password_set = params['AUTH']['password_set']\\n username_set = username\\n password_set = password\\n \\\"\\\"\\\"\\n Creates JWT Token\\n :return:\\n \\\"\\\"\\\"\\n if exp is None:\\n exp = datetime.utcnow() + timedelta(seconds=3600)\\n _token = {\\n 'aud': JWT_AUDIENCE,\\n 'exp': exp,\\n 'iss': JWT_ISSUER,\\n 'user': username,\\n 'role': 'admin',\\n 'time':time.time()\\n }\\n _token.update(_token)\\n \\n if password_set == password and username_set == username: # example, don't do this in production\\n return {\\\"token\\\" : jwt.encode(_token, SECRET_KEY, algorithm=JWT_OPTIONS_ALGORITHM).decode('utf-8') }\\n return 'Invalid username and/or password for user: {0}'.format(username)\",\n \"def get_token():\\n if g.current_user.is_anonymous or g.token_used:\\n return unauthorized('Invalid credentials')\\n return jsonify({'token': g.current_user.generate_auth_token(\\n expiration=3600), 'expiration': 3600})\",\n \"def get_token():\\n if g.current_user.is_anonymous or g.token_used:\\n return unauthorized('Invalid credentials')\\n return jsonify({'token': g.current_user.generate_auth_token(\\n expiration=3600), 'expiration': 3600})\",\n \"def generate_token(email):\\n access_token = create_access_token(email)\\n return access_token\",\n \"def create_oauth(self, user):\\r\\n from oauth_provider.models import Consumer, Token, Resource\\r\\n\\r\\n # Necessary setup for ``oauth_provider``.\\r\\n resource, _ = Resource.objects.get_or_create(url='test', defaults={\\r\\n 'name': 'Test Resource'\\r\\n })\\r\\n consumer, _ = Consumer.objects.get_or_create(key='123', defaults={\\r\\n 'name': 'Test',\\r\\n 'description': 'Testing...'\\r\\n })\\r\\n token, _ = Token.objects.get_or_create(key='foo', token_type=Token.ACCESS, defaults={\\r\\n 'consumer': consumer,\\r\\n 'resource': resource,\\r\\n 'secret': '',\\r\\n 'user': user,\\r\\n })\\r\\n\\r\\n # Then generate the header.\\r\\n oauth_data = {\\r\\n 'oauth_consumer_key': '123',\\r\\n 'oauth_nonce': 'abc',\\r\\n 'oauth_signature': '&',\\r\\n 'oauth_signature_method': 'PLAINTEXT',\\r\\n 'oauth_timestamp': str(int(time.time())),\\r\\n 'oauth_token': 'foo',\\r\\n }\\r\\n return 'OAuth %s' % ','.join([key + '=' + value for key, value in oauth_data.items()])\",\n \"def post(self):\\n current_user_id = get_jwt_identity()\\n new_token = create_access_token(identity=current_user_id)\\n response, status = {\\n 'message': 'Access token was successfully refreshed',\\n 'access_token': new_token\\n }, 200\\n return Response(dumps(response), status=status, mimetype='application/json')\",\n \"def test_create_token_to_user(self):\\n data = {\\n 'email': 'test@test.com', \\n 'password': \\\"testtest\\\"\\n }\\n res = self.client.post(TOKEN_URL, data)\\n\\n self.assertNotIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def get_token():\\n if not request.is_json:\\n return jsonify({\\\"msg\\\": \\\"Missing JSON in request\\\"}), 400\\n username = request.json.get('username', None)\\n password = request.json.get('password', None)\\n\\n if not username:\\n abort(400, \\\"Invalid username or password\\\")\\n if not password:\\n abort(400, \\\"Invalid username or password\\\")\\n users = app.data.driver.db[config.DOMAIN['user']['datasource']['source']]\\n user = users.find_one({'email':username})\\n # validate the user in the user's service\\n if not user:\\n abort(401, \\\"Invalid username or password\\\")\\n if not check_password_hash(user.get('password'), password):\\n abort(401, \\\"Invalid username or password\\\")\\n role = user.get('role', 'user')\\n user_id = str(user.get('_id'))\\n user = User(user_id, username, role)\\n access_token, refresh_token = create_token(user)\\n return jsonify(\\n token=access_token,\\n type='bearer',\\n roles=role,\\n user=username,\\n refreshToken=refresh_token), 200\",\n \"def get_token(cls, user, full_result=False):\\n if user is None:\\n return EMPTY_KNOX_TOKEN\\n result = AuthToken.objects.create(user=user)\\n return result if full_result else result[1]\",\n \"def test_create_token(self):\\n data = {'email': 'test@test.com', 'password': 'testtest'}\\n sigin_in_user(**data)\\n payload = {\\n 'username': 'test@test.com',\\n 'password': 'testtest'\\n }\\n res = self.client.post(TOKEN_URL, payload)\\n \\n self.assertIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_200_OK)\",\n \"def create_access_token(identity: Union[str,int], type_token: str, fresh: Optional[bool] = False) -> bytes:\\n return AuthJWT.create_token(\\n identity=identity,\\n type_token=type_token,\\n fresh=fresh,\\n exp_time=timedelta(minutes=AuthJWT._ACCESS_TOKEN_EXPIRES)\\n )\",\n \"def generate_token_from_user(user, expires_at=None):\\n issued_at = datetime.utcnow()\\n token = AccessToken()\\n token.payload.update(\\n {\\n \\\"email\\\": user.email,\\n \\\"exp\\\": expires_at or issued_at + timedelta(days=2),\\n \\\"iat\\\": issued_at,\\n \\\"language\\\": user.language,\\n \\\"username\\\": user.username,\\n \\\"full_name\\\": user.get_full_name(),\\n }\\n )\\n return token\",\n \"def auth_token_generate(identity_param_val, expires_delta=False):\\n access_token = ''\\n try:\\n if expires_delta is not False:\\n expires_delta = timedelta(minutes=expires_delta)\\n access_token = create_access_token(identity=identity_param_val, expires_delta=expires_delta)\\n except Exception as e:\\n print(e)\\n\\n return access_token\",\n \"async def oauth2_token(\\n request: Request, oauth2_request=Depends(_oauth2_request)\\n):\",\n \"def create_access_token(self):\\n\\t\\t# Wraper for also caching invalid results\\n #def getMetadataRofs(path):\\n #\\ttry:\\n # \\treturn self.client.metadata(path)\\n # except Exception, e:\\n # log.write('Exception at getMetadataRofs for path '+ path + '\\\\n')\\n # pprint(e, log)\\n # return False\\n\\n\\t\\ttry:\\n\\t\\t\\trequest_token = self.session.obtain_request_token()\\n\\t\\t\\turl = self.session.build_authorize_url(request_token)\\n\\t\\t\\tprint url\\n\\t\\t\\traw_input()\\n\\t\\t\\taccess_token = self.session.obtain_access_token(request_token)\\n\\t\\t\\tself.client = client.DropboxClient(self.session)\\n\\t\\t\\t\\n\\t\\t\\t# Build cache for metadata querying\\n\\n\\t\\t\\t# Wraper for also caching invalid results\\n\\t\\t\\tdef getMetadataRofs(path):\\n\\t\\t\\t\\ttry:\\n\\t\\t\\t\\t\\treturn self.client.metadata(path)\\n\\t\\t\\t\\texcept Exception, e:\\n\\t\\t\\t\\t\\tlogger.error('Exception at getMetadataRofs for path '+ path + '\\\\n')\\n\\t\\t logger.debug(sys.exc_info()[0])\\n\\t\\t\\t\\t\\treturn False\\n\\n\\t\\t\\tself.cache_metadata = Cache(getMetadataRofs)\\n\\t\\t\\tself.cache_files = {}\\n\\n\\t\\texcept Exception, e:\\n\\t\\t\\tlogger.error('Exception %s at create_access_token' % (sys.exc_info()[0]))\\n\\t\\t\\tlogger.debug(pformat(sys.exc_info()))\",\n \"def _generate_jwt_token(self):\\n import jwt\\n from datetime import datetime, timedelta\\n from django.conf import settings\\n\\n dt = datetime.now() + timedelta(days=60)\\n\\n token = jwt.encode({\\n 'id': self.pk,\\n 'username': self.username,\\n 'exp': int(dt.strftime('%s')),\\n }, settings.SECRET_KEY, algorithm='HS256')\\n # print(token)\\n return token\",\n \"def post(self):\\n data = request.get_json()\\n is_verified = actions.verify(data['username'], data['password'])\\n if not is_verified:\\n abort(404, message='A user with matching credentials does not exist.')\\n else:\\n token = actions.create_token(data['username'], data['password'])\\n token = token.decode('utf-8')\\n return{'token': token}, 200\\n pass\",\n \"def get_auth_token():\\n token = g.user.generate_auth_token(24*3600)\\n return jsonify({'user_id': g.user.id, 'token': token.decode('ascii')})\",\n \"def _request_token(self):\\n response = requests.post(\\n \\\"%s/generateToken\\\" % self.root_uri.rstrip(\\\"/\\\"), {\\n \\\"username\\\": self.username,\\n \\\"password\\\": self.password,\\n \\\"expiration\\\": '60',\\n \\\"referer\\\": 'https://wsdot.maps.arcgis.com',\\n \\\"f\\\": 'json'\\n })\\n\\n token_info = response.json()\\n if \\\"error\\\" in token_info:\\n raise TokenError(token_info[\\\"error\\\"])\\n self._token = token_info[\\\"token\\\"]\\n self._expires = datetime.fromtimestamp(token_info[\\\"expires\\\"] / 1000)\",\n \"def test_create_token_for_user(setup_client):\\n client = setup_client\\n payload = {\\n 'email': 'test@gmail.com',\\n 'password': 'testpass',\\n }\\n create_user(**payload, **{'role': 'Supplier'})\\n res = client.post(TOKEN_URL, payload)\\n assert \\\"token\\\" in res.data\\n assert res.status_code == status.HTTP_200_OK\",\n \"def create_token(self, consumer, token_type, timestamp, user=None):\\n token, created = self.first_or_create(consumer=consumer, \\n token_type=token_type, \\n timestamp=timestamp,\\n user=user)\\n\\n if created:\\n token.key, token.secret = self.generate_random_codes()\\n token.save()\\n\\n return token\",\n \"def create_auth_token(self, create_auth_token_details, user_id, **kwargs):\\n resource_path = \\\"/users/{userId}/authTokens\\\"\\n method = \\\"POST\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"opc_retry_token\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"create_auth_token got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"userId\\\": user_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"opc-retry-token\\\": kwargs.get(\\\"opc_retry_token\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\\n self.base_client.add_opc_retry_token_if_needed(header_params)\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=create_auth_token_details,\\n response_type=\\\"AuthToken\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=create_auth_token_details,\\n response_type=\\\"AuthToken\\\")\",\n \"def get_access_token(self, path='/oauth/token', data={}):\\n if data.keys():\\n data.update(self.data)\\n else:\\n data = self.data.copy()\\n data.update({\\n 'grant_type': 'password',\\n 'email': self.env.get('TESLA_EMAIL'),\\n 'password': self.env.get('TESLA_PASSWORD')\\n })\\n try:\\n req = requests.post(url='%s%s' % (self.url, path), data=data)\\n # print(req.status_code)\\n # print(req.content)\\n self.token.update(req.json())\\n except:\\n raise 'invalid credentials'\\n return self.token\",\n \"def _get_token(self, client):\\n\\n url = self._url('token')\\n data = {'grant_type': 'password',\\n 'username': self.user,\\n 'password': self.password,\\n 'scope': 'PRODUCTION'}\\n client_data = self.clients[client]\\n consumer_key = client_data['response']['consumerKey']\\n consumer_secret = client_data['response']['consumerSecret']\\n auth = requests.auth.HTTPBasicAuth(consumer_key, consumer_secret)\\n return self.POST(url, data=data, auth=auth)\",\n \"def get_new_token(self):\\n self.register_user(self.user_data2)\\n result = self.login_user(self.login_data2)\\n header_access_token = json.loads(result.data.decode())['header_access_token']\\n return header_access_token\",\n \"def get_oauth_token():\\n\\n # make a request to goodreads authorization url, and pass in request tokens\\n gr_session = goodreads.get_auth_session(session['request_token'],\\n session['request_token_secret'])\\n\\n ACCESS_TOKEN = gr_session.access_token\\n ACCESS_TOKEN_SECRET = gr_session.access_token_secret\\n\\n # add OAuth tokens to Account object.\\n acct = Account.query.get(session[\\\"acct\\\"])\\n acct.access_token = ACCESS_TOKEN\\n acct.access_token_secret = ACCESS_TOKEN_SECRET\\n # get goodreads ID and url for a user and assign to user record.\\n gr_id, gr_url, name, image_url = get_acct_id(acct, GR_KEY, GR_SECRET)\\n acct.user.gr_id = gr_id\\n acct.user.gr_url = gr_url\\n acct.user.gr_name = name\\n acct.user.image_url = image_url\\n # commit changes to db.\\n db.session.commit()\\n\\n return redirect(\\\"/\\\")\",\n \"def _create_jwt(request, user, expires_in):\\n oauth_application = _get_login_oauth_client()\\n access_token = create_dot_access_token(\\n # Note: Scopes for JWT cookies do not require additional permissions\\n request, user, oauth_application, expires_in=expires_in, scopes=['user_id', 'email', 'profile'],\\n )\\n return create_jwt_from_token(access_token, DOTAdapter(), use_asymmetric_key=True)\",\n \"def generateAuthToken(self):\\n try:\\n payload = {\\n 'exp': datetime.utcnow() + timedelta(days=0, minutes=30),\\n 'iat': datetime.utcnow(),\\n 'sub': self.id\\n }\\n return jwt.encode(payload, current_app.config['SECRET_KEY'], algorithm='HS256').decode()\\n except Exception as error:\\n print(error)\\n return error\",\n \"def post(self):\\n current_user = get_jwt_identity()\\n return {\\n # Mark the token as un-fresh since we used the refresh token to regenerate this\\n \\\"accessToken\\\": create_access_token(identity=current_user, fresh=False),\\n \\\"userId\\\": current_user\\n }\",\n \"def test_make_token(self):\\n user = self.create_user()\\n\\n token_generator = EmailActivationTokenGenerator()\\n token = token_generator.make_token(user)\\n self.assertTrue(token_generator.check_token(user, token))\",\n \"def auth_token(self):\",\n \"def token(self):\\n token = jwt.encode(\\n {\\n \\\"id\\\": self.pk,\\n \\\"username\\\": self.get_full_name,\\n \\\"email\\\": self.email,\\n \\\"iat\\\": datetime.utcnow(),\\n \\\"exp\\\": datetime.utcnow() + timedelta(minutes=int(os.getenv('TIME_DELTA')))\\n },\\n settings.SECRET_KEY, algorithm='HS256').decode()\\n return token\",\n \"def createAccessTokenReplacement(self):\\r\\n\\r\\n url = self._config['OAUTH2ENDPOINT']['huddleAuthServer'] + \\\"request?response_type=code\\\" + \\\\\\r\\n \\\"&client_id=\\\" + self._config['OAUTH2']['clientID'] + \\\\\\r\\n \\\"&redirect_uri=\\\" + self._config['OAUTH2']['redirectUri']\\r\\n webbrowser.open_new(url)\\r\\n code = input('Please enter the code from your web browser:')\\r\\n\\r\\n response = self._oauth.obtainAccessTokenBy3LeggedOAuth(code)\\r\\n responseBody = json.loads(response['Body'])\\r\\n\\r\\n try:\\r\\n oauthToken = Token(responseBody)\\r\\n except TypeError as e:\\r\\n print (\\\"Bad response when requesting a token \\\" + str(response))\\r\\n sys.exit()\\r\\n\\r\\n return oauthToken\",\n \"def get_auth_token_teacher():\\n\\n token = g.user.generate_auth_token(600)\\n return jsonify({'token': token.decode('ascii'), 'duration': 600})\",\n \"def generate_auth_token(self, expires_in=600):\\n return jwt.encode(\\n {'STULOGINID': self.STULOGINID, 'exp': time.time() + expires_in},\\n app.config['SECRET_KEY'], algorithm='HS256')\",\n \"def create(self, user, token):\\n\\n session['user'] = {\\n 'id': str(user.id),\\n 'login': user.login,\\n 'token': token\\n }\\n\\n return UserSession.create(session['user'])\",\n \"def create_token_no_user(self):\\n payload = {'email': 'test@test.com', 'password': 'testpass'}\\n res = self.client.post(TOKEN_URL, payload)\\n self.assertNotIn('token', res.data)\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def for_user(cls, user):\\n\\n token = super().for_user(user)\\n\\n TokenMeta.objects.get_or_create(\\n jti=token['jti'],\\n token=str(token),\\n )\\n\\n return token\",\n \"def create(self, validated_data):\\n request = self._kwargs['context']['request']\\n user = User.objects.create(**validated_data)\\n user.set_password(validated_data[\\\"password\\\"])\\n user.save()\\n category_list = ['Fuel', 'Bill', 'Entertainment', 'Education', 'Food']\\n for category in category_list:\\n user.user_categories.create(name=category)\\n login(request, user)\\n token, created = Token.objects.get_or_create(user=user)\\n validated_data[\\\"token\\\"] = token.key\\n return validated_data\",\n \"def get_token():\\n\\n def token_helper():\\n token = util.prompt_for_user_token(username=\\\"robbo1992\\\",\\n scope='user-library-read playlist-modify-private playlist-modify',\\n client_id=config[\\\"spotify\\\"][\\\"client_id\\\"],\\n client_secret=config[\\\"spotify\\\"][\\\"secret_id\\\"],\\n redirect_uri='http://localhost:8080', cache_path=spotify_cache)\\n return token\\n\\n if token_helper():\\n log.debug(\\\"Succesfully generated a spotify token for authentication\\\")\\n return spotipy.Spotify(auth=token_helper())\\n else:\\n if motley.internet:\\n if token_helper():\\n log.debug(\\\"Succesfully generated a spotify token for authentication\\\")\\n return spotipy.Spotify(auth=token_helper())\\n else:\\n log.error(\\\"Authentication error in create_token method.\\\")\\n raise Exception\",\n \"def post(self):\\r\\n try:\\r\\n\\r\\n data = request.get_json()\\r\\n user = user_login.find_by_username(data['username'])\\r\\n if user and safe_str_cmp(user.password, data['password']):\\r\\n access_token = create_access_token(\\r\\n identity=user.id, fresh=True)\\r\\n return {\\r\\n 'access_token': \\\"Bearer \\\" + access_token,\\r\\n }, 200\\r\\n return {\\\"message\\\": \\\"Invalid Credentials!\\\"}, 401\\r\\n except Exception as e:\\r\\n return {\\\"message\\\": str(e)}\",\n \"def create_token(self, token_type=DEFAULT_TOKEN, extra_data='{}'):\\n if token_type not in dict(TOKEN_TYPES).keys():\\n raise ValueError(\\\"Unable to create token, unknown type\\\")\\n\\n value = calc_checksum(self.email, salt=randint(0, maxint))\\n\\n return LoginToken.objects.create(user=self, value=value, token_type=token_type, extra_data=extra_data)\",\n \"def create_user(self):\\n username = \\\"\\\".join(choice(\\n string.ascii_letters) for x in range (randint(7,10)))\\n params = {\\n \\\"first_name\\\":\\\"ugali\\\",\\n \\\"last_name\\\":\\\"mayai\\\",\\n \\\"email\\\":\\\"ugalimayai@gmail.com\\\",\\n \\\"username\\\":username,\\n \\\"password\\\":\\\"password\\\"\\n }\\n path = \\\"/api/v2/auth/signup\\\"\\n user = self.client.post(path,\\n data=json.dumps(params),\\n content_type=\\\"application/json\\\")\\n \\n user_id = user.json['user_id']\\n auth_token = user.json['AuthToken']\\n return int(user_id), auth_token\",\n \"def create_token(self, token_id, data):\\n raise exception.NotImplemented() # pragma: no cover\",\n \"async def login_access_token(\\n form_data: OAuth2PasswordRequestForm = Depends()\\n):\\n user = await crud.user.authenticate(\\n username=form_data.username, password=form_data.password\\n )\\n if not user:\\n raise HTTPException(status_code=HTTP_404_NOT_FOUND, detail=\\\"Incorrect credentials\\\")\\n elif not user.is_active:\\n raise HTTPException(status_code=HTTP_403_FORBIDDEN, detail=\\\"Inactive user\\\")\\n elif not user.is_email_verified:\\n raise HTTPException(status_code=HTTP_403_FORBIDDEN, detail=\\\"Please verify your account via email\\\")\\n access_token_expires = timedelta(minutes=config.ACCESS_TOKEN_EXPIRE_MINUTES)\\n return {\\n \\\"access_token\\\": create_access_token(\\n data={\\\"user_id\\\": user.id}, expires_delta=access_token_expires\\n ),\\n \\\"token_type\\\": \\\"bearer\\\",\\n }\",\n \"def create(self, validated_data):\\n\\t\\tinstance = super(UserSerializer, self).create(validated_data)\\n\\t\\tinstance.set_password(validated_data['password'])\\n\\t\\ttoken = Token.objects.create(user=instance)\\n\\t\\tinstance.token = token\\n\\t\\treturn instance\",\n \"def make_token(self, user):\\n return super()._make_token_with_timestamp(user, int(time.time()))\",\n \"def create_token(user, title, expiration=_default_expiration_duration_opt):\\n if expiration == _default_expiration_duration_opt:\\n duration = _default_expiration_duration()\\n expiration = duration + datetime.now() if duration else None\\n\\n token_code = random_string_generator(TOKEN_NAME_PREFIX_LENGTH + MINIMUM_TOKEN_SUFFIX_LENGTH)()\\n token_name = token_code[:TOKEN_NAME_PREFIX_LENGTH]\\n token_secret = token_code[TOKEN_NAME_PREFIX_LENGTH:]\\n\\n assert token_name\\n assert token_secret\\n\\n return AppSpecificAuthToken.create(\\n user=user,\\n title=title,\\n expiration=expiration,\\n token_name=token_name,\\n token_secret=DecryptedValue(token_secret),\\n )\"\n]"},"negative_scores":{"kind":"list like","value":["0.7509521","0.7463173","0.7187646","0.71259236","0.70469594","0.7042824","0.70313114","0.6959093","0.6959093","0.6959093","0.6947535","0.6934357","0.6917978","0.6896815","0.68936986","0.6844643","0.68159","0.6812227","0.6790298","0.67814326","0.675172","0.6751377","0.67371583","0.6735068","0.67300373","0.67291194","0.67291194","0.67291194","0.67291194","0.67291194","0.67291194","0.67079645","0.6673444","0.66593754","0.664754","0.66255367","0.6624569","0.6624569","0.6607051","0.6604992","0.65988153","0.6593991","0.6593711","0.65904385","0.65883553","0.6585978","0.65778464","0.65762115","0.6552758","0.65285766","0.6519594","0.65166324","0.65114325","0.65051717","0.6500287","0.6500287","0.64830935","0.6475816","0.6475138","0.6450183","0.6444151","0.6438238","0.6417175","0.6388555","0.63820964","0.6377309","0.6376585","0.63749474","0.63616765","0.6353155","0.63450414","0.63405067","0.63392514","0.6309068","0.6281367","0.6278989","0.62733704","0.62673265","0.6257974","0.6257464","0.6252693","0.62483406","0.6236621","0.62289774","0.62230295","0.6221835","0.6210455","0.6205603","0.6204855","0.6198846","0.61822766","0.6181796","0.61816025","0.617358","0.6167889","0.61660755","0.61611605","0.61531997","0.6152631","0.6149302","0.61487377"],"string":"[\n \"0.7509521\",\n \"0.7463173\",\n \"0.7187646\",\n \"0.71259236\",\n \"0.70469594\",\n \"0.7042824\",\n \"0.70313114\",\n \"0.6959093\",\n \"0.6959093\",\n \"0.6959093\",\n \"0.6947535\",\n \"0.6934357\",\n \"0.6917978\",\n \"0.6896815\",\n \"0.68936986\",\n \"0.6844643\",\n \"0.68159\",\n \"0.6812227\",\n \"0.6790298\",\n \"0.67814326\",\n \"0.675172\",\n \"0.6751377\",\n \"0.67371583\",\n \"0.6735068\",\n \"0.67300373\",\n \"0.67291194\",\n \"0.67291194\",\n \"0.67291194\",\n \"0.67291194\",\n \"0.67291194\",\n \"0.67291194\",\n \"0.67079645\",\n \"0.6673444\",\n \"0.66593754\",\n \"0.664754\",\n \"0.66255367\",\n \"0.6624569\",\n \"0.6624569\",\n \"0.6607051\",\n \"0.6604992\",\n \"0.65988153\",\n \"0.6593991\",\n \"0.6593711\",\n \"0.65904385\",\n \"0.65883553\",\n \"0.6585978\",\n \"0.65778464\",\n \"0.65762115\",\n \"0.6552758\",\n \"0.65285766\",\n \"0.6519594\",\n \"0.65166324\",\n \"0.65114325\",\n \"0.65051717\",\n \"0.6500287\",\n \"0.6500287\",\n \"0.64830935\",\n \"0.6475816\",\n \"0.6475138\",\n \"0.6450183\",\n \"0.6444151\",\n \"0.6438238\",\n \"0.6417175\",\n \"0.6388555\",\n \"0.63820964\",\n \"0.6377309\",\n \"0.6376585\",\n \"0.63749474\",\n \"0.63616765\",\n \"0.6353155\",\n \"0.63450414\",\n \"0.63405067\",\n \"0.63392514\",\n \"0.6309068\",\n \"0.6281367\",\n \"0.6278989\",\n \"0.62733704\",\n \"0.62673265\",\n \"0.6257974\",\n \"0.6257464\",\n \"0.6252693\",\n \"0.62483406\",\n \"0.6236621\",\n \"0.62289774\",\n \"0.62230295\",\n \"0.6221835\",\n \"0.6210455\",\n \"0.6205603\",\n \"0.6204855\",\n \"0.6198846\",\n \"0.61822766\",\n \"0.6181796\",\n \"0.61816025\",\n \"0.617358\",\n \"0.6167889\",\n \"0.61660755\",\n \"0.61611605\",\n \"0.61531997\",\n \"0.6152631\",\n \"0.6149302\",\n \"0.61487377\"\n]"},"document_score":{"kind":"string","value":"0.0"},"document_rank":{"kind":"string","value":"-1"}}},{"rowIdx":8581,"cells":{"query":{"kind":"string","value":"Creates a new Console onetime password for the specified user. For more information about user credentials, see `User Credentials`__. Use this operation after creating a new user, or if a user forgets their password. The new onetime password is returned to you in the response, and you must securely deliver it to the user. They'll be prompted to change this password the next time they sign in to the Console. If they don't change it within 7 days, the password will expire and you'll need to create a new onetime password for the user."},"document":{"kind":"string","value":"def create_or_reset_ui_password(self, user_id, **kwargs):\n resource_path = \"/users/{userId}/uiPassword\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_or_reset_ui_password got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"UIPassword\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"UIPassword\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create(self, user):\r\n\r\n if not (PasswordHistory.is_student_password_reuse_restricted() or\r\n PasswordHistory.is_staff_password_reuse_restricted() or\r\n PasswordHistory.is_password_reset_frequency_restricted() or\r\n PasswordHistory.is_staff_forced_password_reset_enabled() or\r\n PasswordHistory.is_student_forced_password_reset_enabled()):\r\n\r\n return\r\n\r\n self.user = user\r\n self.password = user.password\r\n self.save()","def post(self, user_id):\n user = User.query.get(user_id)\n if user is None:\n return mk_response(\"User does not exist\", 422)\n password = user.generate_new_pass()\n return {'password': password}","def post(self, user_id):\n user = User.query.get(user_id)\n if user is None:\n return abort(422, message=\"User does not exist\")\n password = user.generate_new_pass()\n return { 'password' : password }","def update_password(self, user, password):\n user.password = hashers.make_password(password)","def _change_password(self, user, password):\r\n user.set_password(password)\r\n user.save()\r\n history = PasswordHistory()\r\n history.create(user)","def new_password(self):\n # create new password\n return password_generator.create_password()\n # have password reset","def test_creation_with_password(self, user):\n user.password = \"is_god\"\n user.save()","def reset_password(user: User) -> Result[Password]:\n passwd = Password.new()\n command([\"/usr/sbin/chpasswd\"], passwd.wrap(\"{}:{{}}\".format(user.pw_name)))\n return Result(State.success, passwd)","def userPassword(self, password=None):\n\n\t\tdisplay = False\n\n\t\tif password is None:\n\t\t\tdisplay = True\n\t\t\tpassword = hlstr.generate_password(\n\t\t\t\t\t\t\t\tLMC.configuration.users.min_passwd_size)\n\t\telif password == '':\n\t\t\tlogging.warning(_(u'Setting an empty password for user {0}. '\n\t\t\t\t'This is dangerous and totally insecure!').format(\n\t\t\t\t\tstylize(ST_LOGIN, self.__login)))\n\n\t\twith self.lock:\n\t\t\tif self.__already_created:\n\t\t\t\tLicornEvent('user_pre_change_password', user=self.proxy, password=password).emit(synchronous=True)\n\n\t\t\tprefix = '!' if self.__locked else ''\n\n\t\t\tif password == '':\n\t\t\t\tself.__userPassword = prefix\n\t\t\telse:\n\t\t\t\tself.__userPassword = '%s%s' % (prefix,\n\t\t\t\t\t\t\t\t\tself.backend.compute_password(password))\n\n\t\t\t# 3600*24 get us to the number of days since epoch.\n\t\t\tself.__shadowLastChange = int(time.time() / 86400)\n\n\t\t\tif self.__already_created:\n\t\t\t\tself.serialize()\n\t\t\t\tLicornEvent('user_post_change_password', user=self.proxy, password=password).emit(synchronous=True)\n\n\t\t\t\tif self.__already_created:\n\t\t\t\t\t# don't forward this event on user creation, because we\n\t\t\t\t\t# already have the \"user_added\" for this case.\n\t\t\t\t\tLicornEvent('user_userPassword_changed', user=self.proxy).emit(priorities.LOW)\n\n\t\t\tif display:\n\t\t\t\tlogging.notice(_(u'Set password for user {0} to {1}.').format(\n\t\t\t\t\tstylize(ST_NAME, self.__login),\n\t\t\t\t\tstylize(ST_IMPORTANT, password)),\n\t\t\t\t\t# don't display the clear-text password in the daemon's log.\n\t\t\t\t\tto_local=False)\n\t\t\telse:\n\t\t\t\tif self.__already_created:\n\t\t\t\t\tlogging.notice(_(u'Changed password for user {0}.').format(\n\t\t\t\t\t\t\t\t\t\t\tstylize(ST_NAME, self.__login)))","async def create_new_user(*, user: User):\n with Session(engine) as session:\n user.password = simple_hash(user.name, user.password) #Hashing password for security\n session.add(user)\n session.commit()\n return {\"message\": \"User {user_id} created\".format(user_id = user.id)}","def add_user(self, user, pw):\n self.db.execute(\"INSERT INTO user_credentials VALUES (?, ?)\", [user, pw])\n self.db.commit()","def one_time_password(self, delay_time: float = 30.0) -> str:\n\n secret_without_spaces = self.remove_spaces(self._secret)\n upper_case_secret = self.to_upper_case(secret_without_spaces)\n secret = self.decode_with_base32(upper_case_secret)\n input = self.current_timestamp() / delay_time\n hmac = self.create_hmac(secret, input)\n offset = ord(hmac[len(hmac) - 1]) & 0x0F\n hex_four_characters = binascii.hexlify(hmac[offset : offset + 4].encode())\n password = int(hex_four_characters, 32) % 1000000\n return password","def user_created(self, user, password):\n\n if not self.check_prereqs():\n return False\n\n if self.has_user(user):\n return False\n\n hash = self.hash_method.generate_hash(user,password)\n db = self.env.get_db_cnx()\n cursor = db.cursor()\n res=self.set_password(user,password,create_user=True)\n self.log.debug(\"sqlflexibleauthstore: user_created: %s, %s\" % (user,res))\n return res","def reset_user_password_service(user: User, password: str) -> None:\n hashed_password = bcrypt.generate_password_hash(password).decode('UTF-8')\n user.password = hashed_password\n db.session.commit()","def change_password(self, user):\n if not self.is_valid():\n return None\n password = self.clean_password2()\n user.set_password(password)\n user.save()\n return user","def create_user(self, password=None, **data):\n\n user = self.model(**data)\n user.set_password(password)\n user.is_active = False\n user.save()\n\n return user","def save(self, *args, **kwargs):\n kwargs[\"commit\"] = False\n user = super(JOSNewPasswordForm, self).save(*args, **kwargs)\n\n password = self.cleaned_data.get(\"password1\")\n\n user.set_password(password)\n user.save()\n\n return user","def set_password(user_id):\n user = _get_user_or_404(user_id)\n\n form = SetPasswordForm(request.form)\n if not form.validate():\n return set_password_form(user.id, form)\n\n new_password = form.password.data\n initiator_id = g.user.id\n\n password_service.update_password_hash(user.id, new_password, initiator_id)\n\n flash_success(\n gettext(\n \"New password has been set for user '%(screen_name)s'.\",\n screen_name=user.screen_name,\n )\n )\n\n return redirect_to('.view', user_id=user.id)","def generate_password(c, user=\"root\"):\n passw = subprocess.run(\n [\n \"nix\",\n \"run\",\n \"--inputs-from\",\n \".#\",\n \"nixpkgs#xkcdpass\",\n \"--\",\n \"-d-\",\n \"-n3\",\n \"-C\",\n \"capitalize\",\n ],\n text=True,\n check=True,\n stdout=subprocess.PIPE,\n ).stdout.strip()\n hash = subprocess.run(\n [\n \"nix\",\n \"run\",\n \"--inputs-from\",\n \".#\",\n \"nixpkgs#mkpasswd\",\n \"--\",\n \"-m\",\n \"sha-512\",\n \"-s\",\n ],\n text=True,\n check=True,\n stdout=subprocess.PIPE,\n input=passw,\n ).stdout.strip()\n print(\"# Add the following secrets\")\n print(f\"{user}-password: {passw}\")\n print(f\"{user}-password-hash: {hash}\")","def _authorize_new_user(self, user_name, password):\n\n auth_params = {\n 'USERNAME': user_name,\n 'PASSWORD': password + 'temp'\n }\n\n challenges = {\n 'USERNAME': user_name,\n 'NEW_PASSWORD': password\n }\n\n # do a first time login to obtain the challenge session\n response = self.client.initiate_auth(AuthFlow='USER_PASSWORD_AUTH', AuthParameters=auth_params,\n ClientId=self.client_id)\n\n session = response['Session']\n\n # change user password to automate the status transitioning to CONFIRMED\n auth_response = self.client.respond_to_auth_challenge(ClientId=self.client_id,\n ChallengeName='NEW_PASSWORD_REQUIRED',\n Session=session, ChallengeResponses=challenges)\n\n # no need to return user information, its in the IdToken\n return auth_response","def put_password():\n # pylint: disable=too-many-branches\n\n # get user\n user = g.user\n\n # prep regex\n re_password = re.compile(AdministratorAdminSchema.re_password)\n\n # validate data\n errors = {}\n if ('previous_password' not in request.json or\n not request.json['previous_password']):\n if 'previous_password' not in errors:\n errors['previous_password'] = []\n errors['previous_password'].append(\"Missing data for required field.\")\n elif ('previous_password' in request.json and\n not user.check_password(request.json['previous_password'])):\n if 'previous_password' not in errors:\n errors['previous_password'] = []\n errors['previous_password'].append(\"Incorrect password.\")\n\n if 'password1' not in request.json or not request.json['password1']:\n if 'password1' not in errors:\n errors['password1'] = []\n errors['password1'].append(\"Missing data for required field.\")\n if ('password1' in request.json and\n not re_password.match(request.json['password1'])):\n if 'password1' not in errors:\n errors['password1'] = []\n errors['password1'].append(\"Please choose a more complex password.\")\n\n if 'password2' not in request.json or not request.json['password2']:\n if 'password2' not in errors:\n errors['password2'] = []\n errors['password2'].append(\"Missing data for required field.\")\n if 'password1' in request.json and 'password2' in request.json:\n if request.json['password1'] != request.json['password2']:\n if 'password2' not in errors:\n errors['password2'] = []\n errors['password2'].append(\"New passwords must match.\")\n\n if errors:\n return jsonify({\"error\": errors}), 400\n\n # check previous passwords\n if user.roles[0].password_policy and user.roles[0].password_reuse_history:\n prev_passwords = AdministratorPasswordHistory.query.\\\n filter(AdministratorPasswordHistory.administrator_id == user.id).\\\n order_by(AdministratorPasswordHistory.set_date.desc()).\\\n limit(user.roles[0].password_reuse_history)\n for record in prev_passwords:\n print(\"TEST \", record.password)\n if bcrypt.checkpw(request.json.get('password1').encode('utf-8'),\n record.password.encode('utf-8')):\n errors['password1'] = [\"This password has recently been used.\"]\n break\n\n if errors:\n return jsonify({\"error\": errors}), 400\n\n # save user and password history\n user.password = request.json.get('password1')\n pass_history = AdministratorPasswordHistory(administrator=user,\n password=user.password,\n set_date=datetime.now())\n db.session.add(pass_history)\n db.session.commit()\n\n # response\n return jsonify({'success': 'true'}), 200","def set_password(self, value):\n # Salt need to be generated before set password\n m = hashlib.sha256()\n m.update('-'.join([\n str(datetime.now()),\n config.get('security.password_salt')\n ]))\n self.salt = m.hexdigest()\n self.password_pending = False\n self.password = self.__encrypt(value)","def update_user_password(self, user_id, password, original_password):\n update_user = {\n 'password': password,\n 'original_password': original_password\n }\n update_user = json.dumps({'user': update_user})\n resp, _ = self.post('users/%s/password' % user_id, update_user)\n self.expected_success(204, resp.status)\n return service_client.ResponseBody(resp)","def post(self):\n user_data = request.get_json()\n user = User.query.filter_by(email=user_data.get('email')).first()\n\n if user:\n new_password = uuid.uuid4().hex\n user.password = generate_password_hash(new_password)\n user.save()\n\n responseObject = {\n \"message\": \"Password reset successful!\",\n \"New password\": new_password}\n return make_response(jsonify(responseObject)), 200\n else:\n response = {\"error\": \"Email does not exist\"}\n return make_response(jsonify(response)), 401","def change_password(self):\n self.test_user.set_password(self.create_user_data()['password1'])\n self.test_user.save()","def create_new_credential(account,userName,password):\n new_credential = Credentials(account,userName,password)\n return new_credential","def set_password(self, user, password):\n hashed_password = self.hash_password(password)\n server_name = self.get_server_name()\n hookenv.log(\"Storing hash: {}\".format(hashed_password), hookenv.DEBUG)\n result = self.pgsql_query(\n \"UPDATE users SET password_hash = '{}' WHERE name = '@{}:{}';\".format(\n hashed_password, user, server_name\n )\n )\n return result","def create_service_credentials(user, new_roles=None):\n tenant = config('service-tenant')\n if not tenant:\n raise Exception(\"No service tenant provided in config\")\n\n domain = None\n if get_api_version() > 2:\n domain = DEFAULT_DOMAIN\n passwd = create_user_credentials(user, get_service_password,\n set_service_password,\n tenant=tenant, new_roles=new_roles,\n grants=[config('admin-role')],\n domain=domain)\n if get_api_version() > 2:\n # Create account in SERVICE_DOMAIN as well using same password\n domain = SERVICE_DOMAIN\n passwd = create_user_credentials(user, get_service_password,\n set_service_password,\n tenant=tenant, new_roles=new_roles,\n grants=[config('admin-role')],\n domain=domain)\n return passwd","def new_password():\n new_pass = generate_password()\n entry_pass.delete(0, END)\n entry_pass.insert(0, new_pass)","def generate_password_hash(event=None, user_id=None):\n\n suffix_key = f'password{event}'\n hexkey = str.encode(f'{user_id}{suffix_key}')\n\n # md5 value[1:10] + 1\n passwd = '{0}{1}'.format(hashlib.md5(hexkey).hexdigest()[1:10], 1)\n\n return passwd","def set_password(self, user, password, create_user=True):\n\n if not self.check_prereqs():\n return False\n\n hash = self.hash_method.generate_hash(user,password)\n db = self.env.get_db_cnx()\n cursor = db.cursor()\n\n query=self.create_query(self.sql_update_password_query,{'username_field':self.sql_username_field,'password_field':self.sql_password_field,'username':user,'password':hash})\n self.log.debug(\"sqlflexibleauthstore: set_password: %s\" % (query,))\n cursor.execute(query)\n\n if cursor.rowcount > 0:\n self.log.debug('sqlflexibleauthstore: set_password: an existing user was updated')\n db.commit()\n if create_user:\n '''only return False when a user was updated, and create_user is true, because a user was not created'''\n return False\n else:\n '''the user was succesfully updated and no user should be created'''\n return True\n elif not create_user:\n self.log.debug('sqlflexibleauthstore: set_password: user doesnt exist, and none should be created')\n '''no existing user was updated, an none should be created either'''\n return False\n query=self.create_query(self.sql_create_user_query,{'username_field':self.sql_username_field,'password_field':self.sql_password_field,'username':user,'password':hash})\n self.log.debug(\"sqlflexibleauthstore: set_password: %s\" % (query,))\n cursor.execute(query)\n\n db.commit()\n return True","def change_user_password(self, user, new_pass):\n return self.update(user, password=new_pass)","def change_user_password(self, instance, user, new_pass):\n return instance.change_user_password(user, new_pass)","def on_POST(self, request, target_user_id):\n UserID.from_string(target_user_id)\n requester = yield self.auth.get_user_by_req(request)\n is_admin = yield self.auth.is_server_admin(requester.user)\n\n if not is_admin:\n raise AuthError(403, \"You are not a server admin\")\n\n params = parse_json_object_from_request(request)\n new_password = params['new_password']\n if not new_password:\n raise SynapseError(400, \"Missing 'new_password' arg\")\n\n logger.info(\"new_password: %r\", new_password)\n\n yield self.auth_handler.set_password(\n target_user_id, new_password, requester\n )\n defer.returnValue((200, {}))","def _set_user_password(self, v, load=False):\n if hasattr(v, \"_utype\"):\n v = v._utype(v)\n try:\n t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'1..40']}), is_leaf=True, yang_name=\"user-password\", rest_name=\"password\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Password of the user', u'alt-name': u'password'}}, namespace='urn:brocade.com:mgmt:brocade-aaa', defining_module='brocade-aaa', yang_type='user-passwd', is_config=True)\n except (TypeError, ValueError):\n raise ValueError({\n 'error-string': \"\"\"user_password must be of a type compatible with user-passwd\"\"\",\n 'defined-type': \"brocade-aaa:user-passwd\",\n 'generated-type': \"\"\"YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'1..40']}), is_leaf=True, yang_name=\"user-password\", rest_name=\"password\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Password of the user', u'alt-name': u'password'}}, namespace='urn:brocade.com:mgmt:brocade-aaa', defining_module='brocade-aaa', yang_type='user-passwd', is_config=True)\"\"\",\n })\n\n self.__user_password = t\n if hasattr(self, '_set'):\n self._set()","def view_update_user(self, user, username, password):\r\n user.realm._checker.passwd(username, password, True)","async def password(self, ctx):\n pass","def post(self):\n\n user_data, error = user_schema.load(api.payload)\n user_data[\"public_id\"] = uuid.uuid4()\n\n try:\n pswd = user_data[\"password\"]\n except KeyError as e:\n return {\"msg\": \"Password required.\"}, 400\n else:\n user_data[\"password\"] = bcrypt.generate_password_hash(pswd).decode('utf-8')\n\n try:\n new_user = User(**user_data).save()\n except Exception as e:\n return str(e), 400\n \n return user_schema.dump(new_user), 200","def _create_user(self, password, **extra_fields):\n try:\n user = self.model(**extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n return user\n except:\n raise ValueError('ValueError: Cannot create new user')","def post(self):\n try:\n identity = get_jwt_identity()\n body = request.get_json()\n if identity:\n user = User.objects.get(id=identity['user_id'])\n user.modify(password=body.get('password'))\n user.hash_password()\n user.save()\n res = make_response({\n \"response\": \"You have changed your password successfully.\",\n 'status': 200\n }, 200)\n return res\n except SchemaValidationError:\n raise SchemaValidationError\n except ExpiredSignatureError:\n raise ExpiredTokenError\n except (DecodeError, InvalidTokenError):\n raise BadTokenError\n except Exception as e:\n raise InternalServerError","def timestamp_server_user_password(self, timestamp_server_user_password):\n\n self._timestamp_server_user_password = timestamp_server_user_password","def create(self, validated_data):\n\n obj = super(UserSerializer, self).create(validated_data=validated_data)\n obj.set_password(obj.password)\n obj.save()\n\n return obj","def new_user(cls, user):\n pass","def create_user(uname,password):\n new_user = User(uname,password)\n return new_user","def new_user(cls, user):\r\n pass","def create_passlocker(username, userpasslock, email):\n new_passlocker = passlocker(username, userpasslock, email)","def set_password(ctx, new_password, remember):\n ensure_validated(ctx, prompt='Enter your current password')\n if not new_password:\n new_password = click.prompt(\n 'Enter your new password',\n hide_input=True,\n confirmation_prompt=True,\n err=True)\n\n controller = ctx.obj['controller']\n settings = ctx.obj['settings']\n keys = settings.setdefault('keys', {})\n key = controller.set_password(new_password)\n click.echo('Password updated.')\n if remember:\n keys[controller.id] = b2a_hex(key).decode()\n settings.write()\n click.echo('Password remembered')\n elif controller.id in keys:\n del keys[controller.id]\n settings.write()","def create_user(user_id, password_16char, public_key_32char):\n headers = {'Content-type': 'application/json'}\n payload = {'user_id': user_id\n , 'user_password': password_16char\n , 'public_key': public_key_32char}\n response = requests.post(\"http://localhost:5000/user/createUser\", data=json.dumps(payload), headers=headers)\n return response.text","def create_new_user(self, userName, password):\n if serverUtils.validate_password(password):\n database = self.read_database()\n users = database['users']\n\n if userName not in users:\n salt = utils.random(pwhash.argon2id.SALTBYTES)\n hashed_password = pwhash.argon2id.kdf(secret.SecretBox.KEY_SIZE, password.encode('utf-8'), salt)\n users[userName] = dict(hashedPassword=hashed_password.hex(),\n salt=salt.hex(),\n masterKey=self.generate_master_key().decode('cp855'))\n\n self.write_database(database)\n\n else:\n raise UserAlreadyExistsException(\"User already exists\")\n else:\n raise PasswordTooWeakException(\"supply a stronger password\")","def create_user_credentials(user, passwd_get_callback, passwd_set_callback,\n tenant=None, new_roles=None,\n grants=None, domain=None):\n passwd = passwd_get_callback(user)\n if not passwd:\n log(\"Unable to retrieve password for user '{}'\".format(user),\n level=INFO)\n return\n\n log(\"Creating service credentials for '%s'\" % user, level=DEBUG)\n if user_exists(user, domain=domain):\n log(\"User '%s' already exists\" % (user), level=DEBUG)\n # NOTE(dosaboy): see LP #1648677\n if is_password_changed(user, passwd):\n update_user_password(user, passwd, domain)\n else:\n create_user(user, passwd, tenant=tenant, domain=domain)\n\n passwd_set_callback(passwd, user=user)\n\n if grants:\n for role in grants:\n # grant role on project\n grant_role(user, role, tenant=tenant, user_domain=domain,\n project_domain=domain)\n else:\n log(\"No role grants requested for user '%s'\" % (user), level=DEBUG)\n\n if new_roles:\n # Allow the remote service to request creation of any additional roles.\n # Currently used by Swift and Ceilometer.\n for role in new_roles:\n log(\"Creating requested role '%s'\" % role, level=DEBUG)\n create_role(role, user=user, tenant=tenant, domain=domain)\n\n return passwd","def password(self, value):\n self.password_hashed = func.crypt(value, func.gen_salt('bf'))","def set_password(self, password):\n self.password = generate_password_hash(password, method='pbkdf2:sha256')","def view_update_user(self, user, new_pw, old_pw):\r\n user.realm._checker.passwd(user.userID, new_pw, old_pw)","def password(self, password):\n self.password_hash = generate_password_hash(password)","def get_new_password(self, user):\r\n print (_NEW_PASS_PROMPT)\r\n msg_pw = \"Enter a password for the user '{0}': \".format(user)\r\n msg_cf = \"Please confirm the password for the user '{0}': \".format(user)\r\n\r\n while True:\r\n passwd = raw_input(msg_pw).strip()\r\n if passwd == raw_input(msg_cf).strip():\r\n if ' ' not in passwd and self.pass_validator(passwd):\r\n return passwd\r\n else:\r\n print('Password does not contain appropriate characters.')\r\n else:\r\n print('Passwords do not match.')","def create(self, validated_data):\n user = super(UserSerializer, self).create(validated_data)\n user.set_password(validated_data['password'])\n user.save()\n return user","def change_user():\n _ = db.change_password(auth.username(), generate_password_hash(request.json['password']))\n return str(_)","def post(self):\n # userId is retrieved from jwt identity\n userId = get_jwt_identity()\n data = ChangePasswordInputSchema().load(request.json)\n UserLoginService.change_password(userId,\n existing_password=data[\"existingPassword\"],\n new_password=data[\"newPassword\"])\n return {}, 200","def password_builder():\n password = Credentials.password_buidler()\n return password","def change_password(host, username, password):\r\n # type: (Docker, str, str) -> None\r\n host.cmd(\"echo '%s:%s' | chpasswd\" % (username, password))","def new_user(request):\r\n rdict = request.params\r\n\r\n u = User()\r\n\r\n u.username = unicode(rdict.get('username'))\r\n if u.username:\r\n u.username = u.username.lower()\r\n u.email = unicode(rdict.get('email')).lower()\r\n passwd = get_random_word(8)\r\n u.password = passwd\r\n u.activated = True\r\n u.is_admin = False\r\n u.api_key = User.gen_api_key()\r\n\r\n try:\r\n DBSession.add(u)\r\n DBSession.flush()\r\n # We need to return the password since the admin added the user\r\n # manually. This is only time we should have/give the original\r\n # password.\r\n ret = dict(u)\r\n ret['random_pass'] = passwd\r\n return _api_response(request, ret)\r\n\r\n except IntegrityError, exc:\r\n # We might try to add a user that already exists.\r\n LOG.error(exc)\r\n request.response.status_int = 400\r\n return _api_response(request, {\r\n 'error': 'Bad Request: User exists.',\r\n })","def create_user(**kwargs):\n User = apps.get_model(settings.AUTH_USER_MODEL)\n user = G(User, **kwargs)\n user.set_password(kwargs.get(\"password\", \"test\"))\n user.save()\n return user","def _update_password(self, email, new_password):\r\n user = User.objects.get(email=email)\r\n user.set_password(new_password)\r\n user.save()\r\n history = PasswordHistory()\r\n history.create(user)","def create():\n user_dict = request.json\n\n try:\n user = UserController.create(user_dict)\n except UserController as e:\n return jsonify(error=e.error), 500\n\n return jsonify(id=user.id, pw_hash=user.pw_hash)","def step_impl(context):\n\n from django.contrib.auth.models import User\n u = User(username='test_user', email='testuser@test.com')\n u.set_password('admin')","def CreateNewSmtpUser(s):\n payload = ['adduser %s %s\\n' % (FLAGS.exploit_user, FLAGS.exploit_password),\n 'quit\\n']\n SendPayload(s, payload)\n logging.info('Created new user %s/%s' % (\n FLAGS.exploit_user, FLAGS.exploit_password))\n s.close()","def create_user(self):\n # TODO-ROB: This is used ONLY when the user registers in flask\n # TODO-ROB: Create the cookiecutter.json file\n # extra_context overrides user and default configs\n cookiecutter(self.user_cookie, no_input=True, extra_context={\"user_name\": self.user}, output_dir=self.users)","def add_user(host, username, password=None):\r\n # type: (Docker, str, str) -> None\r\n\r\n host.cmd(\"adduser --disabled-password --gecos \\\"\\\"\", username)\r\n if password:\r\n change_password(host, username, password)","def register_new_user(user):\n user.is_active = False\n user.set_unusable_password()\n user.save()\n\n url = generate_url_reset(user)\n #TODO: mettere un body decente per l'email\n send_email(user.email, url, 'aMUX Registration Confirm')","def write_pass(service, password, user_id):\r\n global sql_cursor\r\n global database\r\n global passwords\r\n\r\n query = f'INSERT INTO passwords(service,pass,user_id) values(\"{service}\",\"{password}\",\"{user_id}\");'\r\n sql_cursor.execute(query)\r\n print(\"Saving ...\")\r\n database.commit()\r\n\r\n passwords = fetch_data(sql_cursor, \"passwords\")\r\n\r\n print(\"Password saved successfully\\n\")","def passwd(self, plaintext):\n self._password = bcrypt.generate_password_hash(plaintext.encode('utf8')).decode('utf8')","def test_mod_password(self, mapp, existing_user_id):\n mapp.logoff()\n mapp.login(user=existing_user_id, password=\"1234\")\n mapp.modify_user(user = existing_user_id, password = id(self))\n # Verify that the password was indeed changed.\n mapp.logoff()\n mapp.login(user=existing_user_id,\n password=\"1234\", code = 401)\n mapp.login(user=existing_user_id, password=id(self))","def generate_token(user, expire_time=86400):\n session = Session()\n token = session.query(PasswordRecoveryToken)\\\n .filter(PasswordRecoveryToken.user_id == user.user_id)\\\n .first()\n\n if token is not None:\n self.expire(token)\n \n token = PasswordRecoveryToken()\n token.user_id = user.user_id\n session.add(token)\n \n token.expiration = datetime.now() + timedelta(seconds=expire_time)\n \n sha_token = hashlib.sha224(user.login)\n sha_token.update(user.password)\n sha_token.update(str(token.expiration))\n \n token.token = sha_token.hexdigest()\n print token.token\n return token","def create_password(self):\r\n alphabet = string.ascii_letters + string.digits\r\n password = ''.join(secrets.choice(alphabet) for i in range(30))\r\n\r\n QtWidgets.QMessageBox.information(self, \"Password generated\", \r\n \"{}\".format(password))","def create(self, validated_data):\n password = validated_data.pop('password')\n new_user = User.objects.create(**validated_data)\n new_user.set_password(password)\n new_user.save()\n return new_user","def test_010_change_user_password(self):\n\n testflow.step(\"Resetting password for user %s\", TEST_USER1)\n assert USER_CLI.run(\n 'password-reset',\n TEST_USER1,\n password='pass:%s' % self.user_password,\n password_valid_to='2100-01-01 11:11:11Z',\n )[0], \"Failed to change user's '%s' password\" % TEST_USER1","def _create_user_Api(self,password,username, **extra_fields):\r\n if not username:\r\n raise ValueError('The given username must be set')\r\n user = self.model(email=username,username=str.strip(username), **extra_fields)\r\n user.set_password(password)\r\n user.save(using=self._db)","def new_credentials(site_name, user_name, password):\n new_credentials = Credentials(site_name, user_name, password)\n return new_credentials","def store_passwd(self, clr_passwd):\n aes_cipher = AESCipher()\n self.__aes_key = aes_cipher.AES_KEY\n self.__password = aes_cipher.encrypt(clr_passwd)","def sipserver_user_add(self, user: str, password: str = None) -> None:\n self.add_endpoint_to_sipserver(endpoint=user, password=password)","def updateWebAppUserPwd( self, username, password ):\n try:\n crypt_pass = crypt(password, username)\n con = self.getMetadataDatabaseConnection()\n user_data = con.cursor()\n con.cursor().callproc('update_web_app_user_password', [username, crypt_pass])\n except Exception, e:\n print 'Exception caught: %s.\\nThe error is: %s' % (type(e), e)\n return False","def _create_user(self, new_user):\n new_user = User(user_name=new_user['user_name'], pin=new_user['pin'], user_type='customer')\n self.session.output(new_user.get_user_info(), '\\n[ New user created ]')","def create_user(self):\n u = USER.objects.create(username='test_user1',\n email='test_email@example.com', )\n u.set_password('test_password')\n u.save()\n self.user = u\n return u","def save_password():\n title = core.get_value(TITLE_ID)\n identifier = core.get_value(IDENTIFIER_ID)\n password = core.get_value(PASSWORD_ID)\n note = core.get_value(NOTE_ID)\n\n is_valid = True\n if not title:\n logger.add_error_message('Title is required. Please set the Title.')\n is_valid = False\n if not identifier:\n logger.add_error_message('Identifier is required. Please set the Identifier.')\n is_valid = False\n if not password:\n logger.add_error_message('Password is required. Please set the Password')\n is_valid = False\n\n if not is_valid:\n return\n\n password_info = model.PasswordInfo(\n title=title,\n identifier=identifier,\n password=encrypt(password),\n note=note\n )\n\n try:\n model.insert_one_item(password_info)\n except Exception:\n core.add_error_message('Failed to save password.')\n return\n\n logger.add_info_message('Password was saved successfully.')\n table.update_password_table()","def set_user_passwd(self, sUserName, sUserPasswd, nFlags = 0):\n\t\treturn Job(SDK.PrlVm_SetUserPasswd(self.handle, sUserName, sUserPasswd, nFlags)[0])","def set_password(self, request, pk=None):\n user = User.objects.get(id=pk)\n serializer = PasswordSerializer(data=request.data)\n\n if serializer.is_valid():\n if not user.check_password(serializer.data.get('old_password')):\n return Response({'old_password': ['Wrong password.']},\n status=status.HTTP_400_BAD_REQUEST)\n # set_password also hashes the password that the user will get\n user.set_password(serializer.data.get('new_password'))\n user.save()\n return Response({'status': 'password set'}, status=status.HTTP_200_OK)\n\n return Response(serializer.errors,\n status=status.HTTP_400_BAD_REQUEST)","def create_payment_password(self, header, body):\n\n req_dir = \"payment_passwd\"\n method = self.__client.do_post\n req_params = self.__set_params(\n header,\n req_dir,\n body=body\n )\n return self.__client.do_request(\n req_params,\n method,\n )","def create(self, data):\n # Make User\n code = (random.randint(1000, 9999))\n user = User.objects.get(pk=self.context['user'].pk)\n new = str(code).strip()\n hs = hashlib.sha1(new.encode()).hexdigest()\n user.password = hs\n user.save()\n send_verification_email.delay(email=data['email'], code=code)\n return user","def set_password(self, service, username, password):\n segments = range(0, len(password), self._max_password_size)\n password_parts = [password[i : i + self._max_password_size] for i in segments]\n for i, password_part in enumerate(password_parts):\n curr_username = username\n if i > 0:\n curr_username += '{{part_%d}}' % i\n self._keyring.set_password(service, curr_username, password_part)","def create_user():\n\n username = str(request.parsed_json['username'])\n email = str(request.parsed_json['email'])\n password = str(request.parsed_json['password'])\n\n res = auth.create_user(username, email, password)\n if not res:\n return create_error(400, str(res))\n\n globalopts.appdata[username] = {\n 'user': username,\n 'Appdata': {'Total': globalopts.DEFAULT_WEEKLY_TIMES},\n 'Goals': [globalopts.DEFAULT_GOALS]\n }\n\n print(globalopts.appdata[username])\n\n return \"\", 200","def create_admin(password: Optional[str] = None):\n if password is None:\n password = \"\".join(random.choice(string.ascii_lowercase) for i in range(20))\n is_temp_password = True\n else:\n is_temp_password = False\n\n admin_user = m.User(\n username=\"admin\",\n password=password,\n role=m.UserRole.ADMIN,\n token=m.get_uuid(),\n temp_password=is_temp_password,\n )\n db.session.add(admin_user)\n print(f\"User {admin_user.username!r} added with password: {password!r}\")\n db.session.commit()","def create_user(self) -> None:\n # update when the account was created\n self.account_created = datetime.now().date()\n self.insert_to_db()\n log(f\"An account for User:{self.id} has been created.\")","def create_user(username):\n\n password = getpass.getpass('Password for {0}: '.format(username))\n confirm = getpass.getpass('Again: ')\n\n if password != confirm:\n print >> sys.stderr, \"Passwords don't match\"\n\n sys.exit(1)\n\n with transaction.manager:\n Users(username, password).save()","def new_user(client, username, password, apikey=None, docs=None):\n if apikey is None:\n apikey = str(uuid.uuid4())\n passhash = generate_password_hash(password, method='sha1')\n user = User(username, passhash, apikey, docs=docs)\n user.create(client)\n return user","def change_user(self, username, password):\n self.creds['username'] = username\n self.creds['password'] = password","def update_user_password(self, username):\n parser_password.add_argument('password',\n type=validate_password, required=True,\n nullable=False,\n help=\"Password must be at least 6 characters\"\n )\n args = parser_password.parse_args()\n password = self.set_password(request.json.get('password'))\n\n query = \"\"\"UPDATE users SET password=%s WHERE username=%s\"\"\"\n values = password, username\n\n conn = self.db\n cursor = conn.cursor()\n cursor.execute(query, values)\n conn.commit()\n return True","def sipserver_user_update(self, user: str, password: str) -> None:\n self.update_endpoint_in_sipserver(endpoint=user, password=password)","def update(self, instance, data):\n password = data.pop('password', None)\n user = super().update(instance, data)\n\n if password:\n user.set_password(password)\n user.save()\n\n return user","def test_32_oauth_password(self):\r\n user = User(email_addr=\"johndoe@johndoe.com\",\r\n name=self.user.username,\r\n passwd_hash=None,\r\n fullname=self.user.fullname,\r\n api_key=\"api-key\")\r\n db.session.add(user)\r\n db.session.commit()\r\n res = self.signin()\r\n assert \"Ooops, we didn't find you in the system\" in res.data, res.data","def bdev_opal_new_user(client, bdev_name, admin_password, user_id, user_password):\n params = {\n 'bdev_name': bdev_name,\n 'admin_password': admin_password,\n 'user_id': user_id,\n 'user_password': user_password,\n }\n\n return client.call('bdev_opal_new_user', params)"],"string":"[\n \"def create(self, user):\\r\\n\\r\\n if not (PasswordHistory.is_student_password_reuse_restricted() or\\r\\n PasswordHistory.is_staff_password_reuse_restricted() or\\r\\n PasswordHistory.is_password_reset_frequency_restricted() or\\r\\n PasswordHistory.is_staff_forced_password_reset_enabled() or\\r\\n PasswordHistory.is_student_forced_password_reset_enabled()):\\r\\n\\r\\n return\\r\\n\\r\\n self.user = user\\r\\n self.password = user.password\\r\\n self.save()\",\n \"def post(self, user_id):\\n user = User.query.get(user_id)\\n if user is None:\\n return mk_response(\\\"User does not exist\\\", 422)\\n password = user.generate_new_pass()\\n return {'password': password}\",\n \"def post(self, user_id):\\n user = User.query.get(user_id)\\n if user is None:\\n return abort(422, message=\\\"User does not exist\\\")\\n password = user.generate_new_pass()\\n return { 'password' : password }\",\n \"def update_password(self, user, password):\\n user.password = hashers.make_password(password)\",\n \"def _change_password(self, user, password):\\r\\n user.set_password(password)\\r\\n user.save()\\r\\n history = PasswordHistory()\\r\\n history.create(user)\",\n \"def new_password(self):\\n # create new password\\n return password_generator.create_password()\\n # have password reset\",\n \"def test_creation_with_password(self, user):\\n user.password = \\\"is_god\\\"\\n user.save()\",\n \"def reset_password(user: User) -> Result[Password]:\\n passwd = Password.new()\\n command([\\\"/usr/sbin/chpasswd\\\"], passwd.wrap(\\\"{}:{{}}\\\".format(user.pw_name)))\\n return Result(State.success, passwd)\",\n \"def userPassword(self, password=None):\\n\\n\\t\\tdisplay = False\\n\\n\\t\\tif password is None:\\n\\t\\t\\tdisplay = True\\n\\t\\t\\tpassword = hlstr.generate_password(\\n\\t\\t\\t\\t\\t\\t\\t\\tLMC.configuration.users.min_passwd_size)\\n\\t\\telif password == '':\\n\\t\\t\\tlogging.warning(_(u'Setting an empty password for user {0}. '\\n\\t\\t\\t\\t'This is dangerous and totally insecure!').format(\\n\\t\\t\\t\\t\\tstylize(ST_LOGIN, self.__login)))\\n\\n\\t\\twith self.lock:\\n\\t\\t\\tif self.__already_created:\\n\\t\\t\\t\\tLicornEvent('user_pre_change_password', user=self.proxy, password=password).emit(synchronous=True)\\n\\n\\t\\t\\tprefix = '!' if self.__locked else ''\\n\\n\\t\\t\\tif password == '':\\n\\t\\t\\t\\tself.__userPassword = prefix\\n\\t\\t\\telse:\\n\\t\\t\\t\\tself.__userPassword = '%s%s' % (prefix,\\n\\t\\t\\t\\t\\t\\t\\t\\t\\tself.backend.compute_password(password))\\n\\n\\t\\t\\t# 3600*24 get us to the number of days since epoch.\\n\\t\\t\\tself.__shadowLastChange = int(time.time() / 86400)\\n\\n\\t\\t\\tif self.__already_created:\\n\\t\\t\\t\\tself.serialize()\\n\\t\\t\\t\\tLicornEvent('user_post_change_password', user=self.proxy, password=password).emit(synchronous=True)\\n\\n\\t\\t\\t\\tif self.__already_created:\\n\\t\\t\\t\\t\\t# don't forward this event on user creation, because we\\n\\t\\t\\t\\t\\t# already have the \\\"user_added\\\" for this case.\\n\\t\\t\\t\\t\\tLicornEvent('user_userPassword_changed', user=self.proxy).emit(priorities.LOW)\\n\\n\\t\\t\\tif display:\\n\\t\\t\\t\\tlogging.notice(_(u'Set password for user {0} to {1}.').format(\\n\\t\\t\\t\\t\\tstylize(ST_NAME, self.__login),\\n\\t\\t\\t\\t\\tstylize(ST_IMPORTANT, password)),\\n\\t\\t\\t\\t\\t# don't display the clear-text password in the daemon's log.\\n\\t\\t\\t\\t\\tto_local=False)\\n\\t\\t\\telse:\\n\\t\\t\\t\\tif self.__already_created:\\n\\t\\t\\t\\t\\tlogging.notice(_(u'Changed password for user {0}.').format(\\n\\t\\t\\t\\t\\t\\t\\t\\t\\t\\t\\tstylize(ST_NAME, self.__login)))\",\n \"async def create_new_user(*, user: User):\\n with Session(engine) as session:\\n user.password = simple_hash(user.name, user.password) #Hashing password for security\\n session.add(user)\\n session.commit()\\n return {\\\"message\\\": \\\"User {user_id} created\\\".format(user_id = user.id)}\",\n \"def add_user(self, user, pw):\\n self.db.execute(\\\"INSERT INTO user_credentials VALUES (?, ?)\\\", [user, pw])\\n self.db.commit()\",\n \"def one_time_password(self, delay_time: float = 30.0) -> str:\\n\\n secret_without_spaces = self.remove_spaces(self._secret)\\n upper_case_secret = self.to_upper_case(secret_without_spaces)\\n secret = self.decode_with_base32(upper_case_secret)\\n input = self.current_timestamp() / delay_time\\n hmac = self.create_hmac(secret, input)\\n offset = ord(hmac[len(hmac) - 1]) & 0x0F\\n hex_four_characters = binascii.hexlify(hmac[offset : offset + 4].encode())\\n password = int(hex_four_characters, 32) % 1000000\\n return password\",\n \"def user_created(self, user, password):\\n\\n if not self.check_prereqs():\\n return False\\n\\n if self.has_user(user):\\n return False\\n\\n hash = self.hash_method.generate_hash(user,password)\\n db = self.env.get_db_cnx()\\n cursor = db.cursor()\\n res=self.set_password(user,password,create_user=True)\\n self.log.debug(\\\"sqlflexibleauthstore: user_created: %s, %s\\\" % (user,res))\\n return res\",\n \"def reset_user_password_service(user: User, password: str) -> None:\\n hashed_password = bcrypt.generate_password_hash(password).decode('UTF-8')\\n user.password = hashed_password\\n db.session.commit()\",\n \"def change_password(self, user):\\n if not self.is_valid():\\n return None\\n password = self.clean_password2()\\n user.set_password(password)\\n user.save()\\n return user\",\n \"def create_user(self, password=None, **data):\\n\\n user = self.model(**data)\\n user.set_password(password)\\n user.is_active = False\\n user.save()\\n\\n return user\",\n \"def save(self, *args, **kwargs):\\n kwargs[\\\"commit\\\"] = False\\n user = super(JOSNewPasswordForm, self).save(*args, **kwargs)\\n\\n password = self.cleaned_data.get(\\\"password1\\\")\\n\\n user.set_password(password)\\n user.save()\\n\\n return user\",\n \"def set_password(user_id):\\n user = _get_user_or_404(user_id)\\n\\n form = SetPasswordForm(request.form)\\n if not form.validate():\\n return set_password_form(user.id, form)\\n\\n new_password = form.password.data\\n initiator_id = g.user.id\\n\\n password_service.update_password_hash(user.id, new_password, initiator_id)\\n\\n flash_success(\\n gettext(\\n \\\"New password has been set for user '%(screen_name)s'.\\\",\\n screen_name=user.screen_name,\\n )\\n )\\n\\n return redirect_to('.view', user_id=user.id)\",\n \"def generate_password(c, user=\\\"root\\\"):\\n passw = subprocess.run(\\n [\\n \\\"nix\\\",\\n \\\"run\\\",\\n \\\"--inputs-from\\\",\\n \\\".#\\\",\\n \\\"nixpkgs#xkcdpass\\\",\\n \\\"--\\\",\\n \\\"-d-\\\",\\n \\\"-n3\\\",\\n \\\"-C\\\",\\n \\\"capitalize\\\",\\n ],\\n text=True,\\n check=True,\\n stdout=subprocess.PIPE,\\n ).stdout.strip()\\n hash = subprocess.run(\\n [\\n \\\"nix\\\",\\n \\\"run\\\",\\n \\\"--inputs-from\\\",\\n \\\".#\\\",\\n \\\"nixpkgs#mkpasswd\\\",\\n \\\"--\\\",\\n \\\"-m\\\",\\n \\\"sha-512\\\",\\n \\\"-s\\\",\\n ],\\n text=True,\\n check=True,\\n stdout=subprocess.PIPE,\\n input=passw,\\n ).stdout.strip()\\n print(\\\"# Add the following secrets\\\")\\n print(f\\\"{user}-password: {passw}\\\")\\n print(f\\\"{user}-password-hash: {hash}\\\")\",\n \"def _authorize_new_user(self, user_name, password):\\n\\n auth_params = {\\n 'USERNAME': user_name,\\n 'PASSWORD': password + 'temp'\\n }\\n\\n challenges = {\\n 'USERNAME': user_name,\\n 'NEW_PASSWORD': password\\n }\\n\\n # do a first time login to obtain the challenge session\\n response = self.client.initiate_auth(AuthFlow='USER_PASSWORD_AUTH', AuthParameters=auth_params,\\n ClientId=self.client_id)\\n\\n session = response['Session']\\n\\n # change user password to automate the status transitioning to CONFIRMED\\n auth_response = self.client.respond_to_auth_challenge(ClientId=self.client_id,\\n ChallengeName='NEW_PASSWORD_REQUIRED',\\n Session=session, ChallengeResponses=challenges)\\n\\n # no need to return user information, its in the IdToken\\n return auth_response\",\n \"def put_password():\\n # pylint: disable=too-many-branches\\n\\n # get user\\n user = g.user\\n\\n # prep regex\\n re_password = re.compile(AdministratorAdminSchema.re_password)\\n\\n # validate data\\n errors = {}\\n if ('previous_password' not in request.json or\\n not request.json['previous_password']):\\n if 'previous_password' not in errors:\\n errors['previous_password'] = []\\n errors['previous_password'].append(\\\"Missing data for required field.\\\")\\n elif ('previous_password' in request.json and\\n not user.check_password(request.json['previous_password'])):\\n if 'previous_password' not in errors:\\n errors['previous_password'] = []\\n errors['previous_password'].append(\\\"Incorrect password.\\\")\\n\\n if 'password1' not in request.json or not request.json['password1']:\\n if 'password1' not in errors:\\n errors['password1'] = []\\n errors['password1'].append(\\\"Missing data for required field.\\\")\\n if ('password1' in request.json and\\n not re_password.match(request.json['password1'])):\\n if 'password1' not in errors:\\n errors['password1'] = []\\n errors['password1'].append(\\\"Please choose a more complex password.\\\")\\n\\n if 'password2' not in request.json or not request.json['password2']:\\n if 'password2' not in errors:\\n errors['password2'] = []\\n errors['password2'].append(\\\"Missing data for required field.\\\")\\n if 'password1' in request.json and 'password2' in request.json:\\n if request.json['password1'] != request.json['password2']:\\n if 'password2' not in errors:\\n errors['password2'] = []\\n errors['password2'].append(\\\"New passwords must match.\\\")\\n\\n if errors:\\n return jsonify({\\\"error\\\": errors}), 400\\n\\n # check previous passwords\\n if user.roles[0].password_policy and user.roles[0].password_reuse_history:\\n prev_passwords = AdministratorPasswordHistory.query.\\\\\\n filter(AdministratorPasswordHistory.administrator_id == user.id).\\\\\\n order_by(AdministratorPasswordHistory.set_date.desc()).\\\\\\n limit(user.roles[0].password_reuse_history)\\n for record in prev_passwords:\\n print(\\\"TEST \\\", record.password)\\n if bcrypt.checkpw(request.json.get('password1').encode('utf-8'),\\n record.password.encode('utf-8')):\\n errors['password1'] = [\\\"This password has recently been used.\\\"]\\n break\\n\\n if errors:\\n return jsonify({\\\"error\\\": errors}), 400\\n\\n # save user and password history\\n user.password = request.json.get('password1')\\n pass_history = AdministratorPasswordHistory(administrator=user,\\n password=user.password,\\n set_date=datetime.now())\\n db.session.add(pass_history)\\n db.session.commit()\\n\\n # response\\n return jsonify({'success': 'true'}), 200\",\n \"def set_password(self, value):\\n # Salt need to be generated before set password\\n m = hashlib.sha256()\\n m.update('-'.join([\\n str(datetime.now()),\\n config.get('security.password_salt')\\n ]))\\n self.salt = m.hexdigest()\\n self.password_pending = False\\n self.password = self.__encrypt(value)\",\n \"def update_user_password(self, user_id, password, original_password):\\n update_user = {\\n 'password': password,\\n 'original_password': original_password\\n }\\n update_user = json.dumps({'user': update_user})\\n resp, _ = self.post('users/%s/password' % user_id, update_user)\\n self.expected_success(204, resp.status)\\n return service_client.ResponseBody(resp)\",\n \"def post(self):\\n user_data = request.get_json()\\n user = User.query.filter_by(email=user_data.get('email')).first()\\n\\n if user:\\n new_password = uuid.uuid4().hex\\n user.password = generate_password_hash(new_password)\\n user.save()\\n\\n responseObject = {\\n \\\"message\\\": \\\"Password reset successful!\\\",\\n \\\"New password\\\": new_password}\\n return make_response(jsonify(responseObject)), 200\\n else:\\n response = {\\\"error\\\": \\\"Email does not exist\\\"}\\n return make_response(jsonify(response)), 401\",\n \"def change_password(self):\\n self.test_user.set_password(self.create_user_data()['password1'])\\n self.test_user.save()\",\n \"def create_new_credential(account,userName,password):\\n new_credential = Credentials(account,userName,password)\\n return new_credential\",\n \"def set_password(self, user, password):\\n hashed_password = self.hash_password(password)\\n server_name = self.get_server_name()\\n hookenv.log(\\\"Storing hash: {}\\\".format(hashed_password), hookenv.DEBUG)\\n result = self.pgsql_query(\\n \\\"UPDATE users SET password_hash = '{}' WHERE name = '@{}:{}';\\\".format(\\n hashed_password, user, server_name\\n )\\n )\\n return result\",\n \"def create_service_credentials(user, new_roles=None):\\n tenant = config('service-tenant')\\n if not tenant:\\n raise Exception(\\\"No service tenant provided in config\\\")\\n\\n domain = None\\n if get_api_version() > 2:\\n domain = DEFAULT_DOMAIN\\n passwd = create_user_credentials(user, get_service_password,\\n set_service_password,\\n tenant=tenant, new_roles=new_roles,\\n grants=[config('admin-role')],\\n domain=domain)\\n if get_api_version() > 2:\\n # Create account in SERVICE_DOMAIN as well using same password\\n domain = SERVICE_DOMAIN\\n passwd = create_user_credentials(user, get_service_password,\\n set_service_password,\\n tenant=tenant, new_roles=new_roles,\\n grants=[config('admin-role')],\\n domain=domain)\\n return passwd\",\n \"def new_password():\\n new_pass = generate_password()\\n entry_pass.delete(0, END)\\n entry_pass.insert(0, new_pass)\",\n \"def generate_password_hash(event=None, user_id=None):\\n\\n suffix_key = f'password{event}'\\n hexkey = str.encode(f'{user_id}{suffix_key}')\\n\\n # md5 value[1:10] + 1\\n passwd = '{0}{1}'.format(hashlib.md5(hexkey).hexdigest()[1:10], 1)\\n\\n return passwd\",\n \"def set_password(self, user, password, create_user=True):\\n\\n if not self.check_prereqs():\\n return False\\n\\n hash = self.hash_method.generate_hash(user,password)\\n db = self.env.get_db_cnx()\\n cursor = db.cursor()\\n\\n query=self.create_query(self.sql_update_password_query,{'username_field':self.sql_username_field,'password_field':self.sql_password_field,'username':user,'password':hash})\\n self.log.debug(\\\"sqlflexibleauthstore: set_password: %s\\\" % (query,))\\n cursor.execute(query)\\n\\n if cursor.rowcount > 0:\\n self.log.debug('sqlflexibleauthstore: set_password: an existing user was updated')\\n db.commit()\\n if create_user:\\n '''only return False when a user was updated, and create_user is true, because a user was not created'''\\n return False\\n else:\\n '''the user was succesfully updated and no user should be created'''\\n return True\\n elif not create_user:\\n self.log.debug('sqlflexibleauthstore: set_password: user doesnt exist, and none should be created')\\n '''no existing user was updated, an none should be created either'''\\n return False\\n query=self.create_query(self.sql_create_user_query,{'username_field':self.sql_username_field,'password_field':self.sql_password_field,'username':user,'password':hash})\\n self.log.debug(\\\"sqlflexibleauthstore: set_password: %s\\\" % (query,))\\n cursor.execute(query)\\n\\n db.commit()\\n return True\",\n \"def change_user_password(self, user, new_pass):\\n return self.update(user, password=new_pass)\",\n \"def change_user_password(self, instance, user, new_pass):\\n return instance.change_user_password(user, new_pass)\",\n \"def on_POST(self, request, target_user_id):\\n UserID.from_string(target_user_id)\\n requester = yield self.auth.get_user_by_req(request)\\n is_admin = yield self.auth.is_server_admin(requester.user)\\n\\n if not is_admin:\\n raise AuthError(403, \\\"You are not a server admin\\\")\\n\\n params = parse_json_object_from_request(request)\\n new_password = params['new_password']\\n if not new_password:\\n raise SynapseError(400, \\\"Missing 'new_password' arg\\\")\\n\\n logger.info(\\\"new_password: %r\\\", new_password)\\n\\n yield self.auth_handler.set_password(\\n target_user_id, new_password, requester\\n )\\n defer.returnValue((200, {}))\",\n \"def _set_user_password(self, v, load=False):\\n if hasattr(v, \\\"_utype\\\"):\\n v = v._utype(v)\\n try:\\n t = YANGDynClass(v,base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'1..40']}), is_leaf=True, yang_name=\\\"user-password\\\", rest_name=\\\"password\\\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Password of the user', u'alt-name': u'password'}}, namespace='urn:brocade.com:mgmt:brocade-aaa', defining_module='brocade-aaa', yang_type='user-passwd', is_config=True)\\n except (TypeError, ValueError):\\n raise ValueError({\\n 'error-string': \\\"\\\"\\\"user_password must be of a type compatible with user-passwd\\\"\\\"\\\",\\n 'defined-type': \\\"brocade-aaa:user-passwd\\\",\\n 'generated-type': \\\"\\\"\\\"YANGDynClass(base=RestrictedClassType(base_type=unicode, restriction_dict={'length': [u'1..40']}), is_leaf=True, yang_name=\\\"user-password\\\", rest_name=\\\"password\\\", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Password of the user', u'alt-name': u'password'}}, namespace='urn:brocade.com:mgmt:brocade-aaa', defining_module='brocade-aaa', yang_type='user-passwd', is_config=True)\\\"\\\"\\\",\\n })\\n\\n self.__user_password = t\\n if hasattr(self, '_set'):\\n self._set()\",\n \"def view_update_user(self, user, username, password):\\r\\n user.realm._checker.passwd(username, password, True)\",\n \"async def password(self, ctx):\\n pass\",\n \"def post(self):\\n\\n user_data, error = user_schema.load(api.payload)\\n user_data[\\\"public_id\\\"] = uuid.uuid4()\\n\\n try:\\n pswd = user_data[\\\"password\\\"]\\n except KeyError as e:\\n return {\\\"msg\\\": \\\"Password required.\\\"}, 400\\n else:\\n user_data[\\\"password\\\"] = bcrypt.generate_password_hash(pswd).decode('utf-8')\\n\\n try:\\n new_user = User(**user_data).save()\\n except Exception as e:\\n return str(e), 400\\n \\n return user_schema.dump(new_user), 200\",\n \"def _create_user(self, password, **extra_fields):\\n try:\\n user = self.model(**extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\\n except:\\n raise ValueError('ValueError: Cannot create new user')\",\n \"def post(self):\\n try:\\n identity = get_jwt_identity()\\n body = request.get_json()\\n if identity:\\n user = User.objects.get(id=identity['user_id'])\\n user.modify(password=body.get('password'))\\n user.hash_password()\\n user.save()\\n res = make_response({\\n \\\"response\\\": \\\"You have changed your password successfully.\\\",\\n 'status': 200\\n }, 200)\\n return res\\n except SchemaValidationError:\\n raise SchemaValidationError\\n except ExpiredSignatureError:\\n raise ExpiredTokenError\\n except (DecodeError, InvalidTokenError):\\n raise BadTokenError\\n except Exception as e:\\n raise InternalServerError\",\n \"def timestamp_server_user_password(self, timestamp_server_user_password):\\n\\n self._timestamp_server_user_password = timestamp_server_user_password\",\n \"def create(self, validated_data):\\n\\n obj = super(UserSerializer, self).create(validated_data=validated_data)\\n obj.set_password(obj.password)\\n obj.save()\\n\\n return obj\",\n \"def new_user(cls, user):\\n pass\",\n \"def create_user(uname,password):\\n new_user = User(uname,password)\\n return new_user\",\n \"def new_user(cls, user):\\r\\n pass\",\n \"def create_passlocker(username, userpasslock, email):\\n new_passlocker = passlocker(username, userpasslock, email)\",\n \"def set_password(ctx, new_password, remember):\\n ensure_validated(ctx, prompt='Enter your current password')\\n if not new_password:\\n new_password = click.prompt(\\n 'Enter your new password',\\n hide_input=True,\\n confirmation_prompt=True,\\n err=True)\\n\\n controller = ctx.obj['controller']\\n settings = ctx.obj['settings']\\n keys = settings.setdefault('keys', {})\\n key = controller.set_password(new_password)\\n click.echo('Password updated.')\\n if remember:\\n keys[controller.id] = b2a_hex(key).decode()\\n settings.write()\\n click.echo('Password remembered')\\n elif controller.id in keys:\\n del keys[controller.id]\\n settings.write()\",\n \"def create_user(user_id, password_16char, public_key_32char):\\n headers = {'Content-type': 'application/json'}\\n payload = {'user_id': user_id\\n , 'user_password': password_16char\\n , 'public_key': public_key_32char}\\n response = requests.post(\\\"http://localhost:5000/user/createUser\\\", data=json.dumps(payload), headers=headers)\\n return response.text\",\n \"def create_new_user(self, userName, password):\\n if serverUtils.validate_password(password):\\n database = self.read_database()\\n users = database['users']\\n\\n if userName not in users:\\n salt = utils.random(pwhash.argon2id.SALTBYTES)\\n hashed_password = pwhash.argon2id.kdf(secret.SecretBox.KEY_SIZE, password.encode('utf-8'), salt)\\n users[userName] = dict(hashedPassword=hashed_password.hex(),\\n salt=salt.hex(),\\n masterKey=self.generate_master_key().decode('cp855'))\\n\\n self.write_database(database)\\n\\n else:\\n raise UserAlreadyExistsException(\\\"User already exists\\\")\\n else:\\n raise PasswordTooWeakException(\\\"supply a stronger password\\\")\",\n \"def create_user_credentials(user, passwd_get_callback, passwd_set_callback,\\n tenant=None, new_roles=None,\\n grants=None, domain=None):\\n passwd = passwd_get_callback(user)\\n if not passwd:\\n log(\\\"Unable to retrieve password for user '{}'\\\".format(user),\\n level=INFO)\\n return\\n\\n log(\\\"Creating service credentials for '%s'\\\" % user, level=DEBUG)\\n if user_exists(user, domain=domain):\\n log(\\\"User '%s' already exists\\\" % (user), level=DEBUG)\\n # NOTE(dosaboy): see LP #1648677\\n if is_password_changed(user, passwd):\\n update_user_password(user, passwd, domain)\\n else:\\n create_user(user, passwd, tenant=tenant, domain=domain)\\n\\n passwd_set_callback(passwd, user=user)\\n\\n if grants:\\n for role in grants:\\n # grant role on project\\n grant_role(user, role, tenant=tenant, user_domain=domain,\\n project_domain=domain)\\n else:\\n log(\\\"No role grants requested for user '%s'\\\" % (user), level=DEBUG)\\n\\n if new_roles:\\n # Allow the remote service to request creation of any additional roles.\\n # Currently used by Swift and Ceilometer.\\n for role in new_roles:\\n log(\\\"Creating requested role '%s'\\\" % role, level=DEBUG)\\n create_role(role, user=user, tenant=tenant, domain=domain)\\n\\n return passwd\",\n \"def password(self, value):\\n self.password_hashed = func.crypt(value, func.gen_salt('bf'))\",\n \"def set_password(self, password):\\n self.password = generate_password_hash(password, method='pbkdf2:sha256')\",\n \"def view_update_user(self, user, new_pw, old_pw):\\r\\n user.realm._checker.passwd(user.userID, new_pw, old_pw)\",\n \"def password(self, password):\\n self.password_hash = generate_password_hash(password)\",\n \"def get_new_password(self, user):\\r\\n print (_NEW_PASS_PROMPT)\\r\\n msg_pw = \\\"Enter a password for the user '{0}': \\\".format(user)\\r\\n msg_cf = \\\"Please confirm the password for the user '{0}': \\\".format(user)\\r\\n\\r\\n while True:\\r\\n passwd = raw_input(msg_pw).strip()\\r\\n if passwd == raw_input(msg_cf).strip():\\r\\n if ' ' not in passwd and self.pass_validator(passwd):\\r\\n return passwd\\r\\n else:\\r\\n print('Password does not contain appropriate characters.')\\r\\n else:\\r\\n print('Passwords do not match.')\",\n \"def create(self, validated_data):\\n user = super(UserSerializer, self).create(validated_data)\\n user.set_password(validated_data['password'])\\n user.save()\\n return user\",\n \"def change_user():\\n _ = db.change_password(auth.username(), generate_password_hash(request.json['password']))\\n return str(_)\",\n \"def post(self):\\n # userId is retrieved from jwt identity\\n userId = get_jwt_identity()\\n data = ChangePasswordInputSchema().load(request.json)\\n UserLoginService.change_password(userId,\\n existing_password=data[\\\"existingPassword\\\"],\\n new_password=data[\\\"newPassword\\\"])\\n return {}, 200\",\n \"def password_builder():\\n password = Credentials.password_buidler()\\n return password\",\n \"def change_password(host, username, password):\\r\\n # type: (Docker, str, str) -> None\\r\\n host.cmd(\\\"echo '%s:%s' | chpasswd\\\" % (username, password))\",\n \"def new_user(request):\\r\\n rdict = request.params\\r\\n\\r\\n u = User()\\r\\n\\r\\n u.username = unicode(rdict.get('username'))\\r\\n if u.username:\\r\\n u.username = u.username.lower()\\r\\n u.email = unicode(rdict.get('email')).lower()\\r\\n passwd = get_random_word(8)\\r\\n u.password = passwd\\r\\n u.activated = True\\r\\n u.is_admin = False\\r\\n u.api_key = User.gen_api_key()\\r\\n\\r\\n try:\\r\\n DBSession.add(u)\\r\\n DBSession.flush()\\r\\n # We need to return the password since the admin added the user\\r\\n # manually. This is only time we should have/give the original\\r\\n # password.\\r\\n ret = dict(u)\\r\\n ret['random_pass'] = passwd\\r\\n return _api_response(request, ret)\\r\\n\\r\\n except IntegrityError, exc:\\r\\n # We might try to add a user that already exists.\\r\\n LOG.error(exc)\\r\\n request.response.status_int = 400\\r\\n return _api_response(request, {\\r\\n 'error': 'Bad Request: User exists.',\\r\\n })\",\n \"def create_user(**kwargs):\\n User = apps.get_model(settings.AUTH_USER_MODEL)\\n user = G(User, **kwargs)\\n user.set_password(kwargs.get(\\\"password\\\", \\\"test\\\"))\\n user.save()\\n return user\",\n \"def _update_password(self, email, new_password):\\r\\n user = User.objects.get(email=email)\\r\\n user.set_password(new_password)\\r\\n user.save()\\r\\n history = PasswordHistory()\\r\\n history.create(user)\",\n \"def create():\\n user_dict = request.json\\n\\n try:\\n user = UserController.create(user_dict)\\n except UserController as e:\\n return jsonify(error=e.error), 500\\n\\n return jsonify(id=user.id, pw_hash=user.pw_hash)\",\n \"def step_impl(context):\\n\\n from django.contrib.auth.models import User\\n u = User(username='test_user', email='testuser@test.com')\\n u.set_password('admin')\",\n \"def CreateNewSmtpUser(s):\\n payload = ['adduser %s %s\\\\n' % (FLAGS.exploit_user, FLAGS.exploit_password),\\n 'quit\\\\n']\\n SendPayload(s, payload)\\n logging.info('Created new user %s/%s' % (\\n FLAGS.exploit_user, FLAGS.exploit_password))\\n s.close()\",\n \"def create_user(self):\\n # TODO-ROB: This is used ONLY when the user registers in flask\\n # TODO-ROB: Create the cookiecutter.json file\\n # extra_context overrides user and default configs\\n cookiecutter(self.user_cookie, no_input=True, extra_context={\\\"user_name\\\": self.user}, output_dir=self.users)\",\n \"def add_user(host, username, password=None):\\r\\n # type: (Docker, str, str) -> None\\r\\n\\r\\n host.cmd(\\\"adduser --disabled-password --gecos \\\\\\\"\\\\\\\"\\\", username)\\r\\n if password:\\r\\n change_password(host, username, password)\",\n \"def register_new_user(user):\\n user.is_active = False\\n user.set_unusable_password()\\n user.save()\\n\\n url = generate_url_reset(user)\\n #TODO: mettere un body decente per l'email\\n send_email(user.email, url, 'aMUX Registration Confirm')\",\n \"def write_pass(service, password, user_id):\\r\\n global sql_cursor\\r\\n global database\\r\\n global passwords\\r\\n\\r\\n query = f'INSERT INTO passwords(service,pass,user_id) values(\\\"{service}\\\",\\\"{password}\\\",\\\"{user_id}\\\");'\\r\\n sql_cursor.execute(query)\\r\\n print(\\\"Saving ...\\\")\\r\\n database.commit()\\r\\n\\r\\n passwords = fetch_data(sql_cursor, \\\"passwords\\\")\\r\\n\\r\\n print(\\\"Password saved successfully\\\\n\\\")\",\n \"def passwd(self, plaintext):\\n self._password = bcrypt.generate_password_hash(plaintext.encode('utf8')).decode('utf8')\",\n \"def test_mod_password(self, mapp, existing_user_id):\\n mapp.logoff()\\n mapp.login(user=existing_user_id, password=\\\"1234\\\")\\n mapp.modify_user(user = existing_user_id, password = id(self))\\n # Verify that the password was indeed changed.\\n mapp.logoff()\\n mapp.login(user=existing_user_id,\\n password=\\\"1234\\\", code = 401)\\n mapp.login(user=existing_user_id, password=id(self))\",\n \"def generate_token(user, expire_time=86400):\\n session = Session()\\n token = session.query(PasswordRecoveryToken)\\\\\\n .filter(PasswordRecoveryToken.user_id == user.user_id)\\\\\\n .first()\\n\\n if token is not None:\\n self.expire(token)\\n \\n token = PasswordRecoveryToken()\\n token.user_id = user.user_id\\n session.add(token)\\n \\n token.expiration = datetime.now() + timedelta(seconds=expire_time)\\n \\n sha_token = hashlib.sha224(user.login)\\n sha_token.update(user.password)\\n sha_token.update(str(token.expiration))\\n \\n token.token = sha_token.hexdigest()\\n print token.token\\n return token\",\n \"def create_password(self):\\r\\n alphabet = string.ascii_letters + string.digits\\r\\n password = ''.join(secrets.choice(alphabet) for i in range(30))\\r\\n\\r\\n QtWidgets.QMessageBox.information(self, \\\"Password generated\\\", \\r\\n \\\"{}\\\".format(password))\",\n \"def create(self, validated_data):\\n password = validated_data.pop('password')\\n new_user = User.objects.create(**validated_data)\\n new_user.set_password(password)\\n new_user.save()\\n return new_user\",\n \"def test_010_change_user_password(self):\\n\\n testflow.step(\\\"Resetting password for user %s\\\", TEST_USER1)\\n assert USER_CLI.run(\\n 'password-reset',\\n TEST_USER1,\\n password='pass:%s' % self.user_password,\\n password_valid_to='2100-01-01 11:11:11Z',\\n )[0], \\\"Failed to change user's '%s' password\\\" % TEST_USER1\",\n \"def _create_user_Api(self,password,username, **extra_fields):\\r\\n if not username:\\r\\n raise ValueError('The given username must be set')\\r\\n user = self.model(email=username,username=str.strip(username), **extra_fields)\\r\\n user.set_password(password)\\r\\n user.save(using=self._db)\",\n \"def new_credentials(site_name, user_name, password):\\n new_credentials = Credentials(site_name, user_name, password)\\n return new_credentials\",\n \"def store_passwd(self, clr_passwd):\\n aes_cipher = AESCipher()\\n self.__aes_key = aes_cipher.AES_KEY\\n self.__password = aes_cipher.encrypt(clr_passwd)\",\n \"def sipserver_user_add(self, user: str, password: str = None) -> None:\\n self.add_endpoint_to_sipserver(endpoint=user, password=password)\",\n \"def updateWebAppUserPwd( self, username, password ):\\n try:\\n crypt_pass = crypt(password, username)\\n con = self.getMetadataDatabaseConnection()\\n user_data = con.cursor()\\n con.cursor().callproc('update_web_app_user_password', [username, crypt_pass])\\n except Exception, e:\\n print 'Exception caught: %s.\\\\nThe error is: %s' % (type(e), e)\\n return False\",\n \"def _create_user(self, new_user):\\n new_user = User(user_name=new_user['user_name'], pin=new_user['pin'], user_type='customer')\\n self.session.output(new_user.get_user_info(), '\\\\n[ New user created ]')\",\n \"def create_user(self):\\n u = USER.objects.create(username='test_user1',\\n email='test_email@example.com', )\\n u.set_password('test_password')\\n u.save()\\n self.user = u\\n return u\",\n \"def save_password():\\n title = core.get_value(TITLE_ID)\\n identifier = core.get_value(IDENTIFIER_ID)\\n password = core.get_value(PASSWORD_ID)\\n note = core.get_value(NOTE_ID)\\n\\n is_valid = True\\n if not title:\\n logger.add_error_message('Title is required. Please set the Title.')\\n is_valid = False\\n if not identifier:\\n logger.add_error_message('Identifier is required. Please set the Identifier.')\\n is_valid = False\\n if not password:\\n logger.add_error_message('Password is required. Please set the Password')\\n is_valid = False\\n\\n if not is_valid:\\n return\\n\\n password_info = model.PasswordInfo(\\n title=title,\\n identifier=identifier,\\n password=encrypt(password),\\n note=note\\n )\\n\\n try:\\n model.insert_one_item(password_info)\\n except Exception:\\n core.add_error_message('Failed to save password.')\\n return\\n\\n logger.add_info_message('Password was saved successfully.')\\n table.update_password_table()\",\n \"def set_user_passwd(self, sUserName, sUserPasswd, nFlags = 0):\\n\\t\\treturn Job(SDK.PrlVm_SetUserPasswd(self.handle, sUserName, sUserPasswd, nFlags)[0])\",\n \"def set_password(self, request, pk=None):\\n user = User.objects.get(id=pk)\\n serializer = PasswordSerializer(data=request.data)\\n\\n if serializer.is_valid():\\n if not user.check_password(serializer.data.get('old_password')):\\n return Response({'old_password': ['Wrong password.']},\\n status=status.HTTP_400_BAD_REQUEST)\\n # set_password also hashes the password that the user will get\\n user.set_password(serializer.data.get('new_password'))\\n user.save()\\n return Response({'status': 'password set'}, status=status.HTTP_200_OK)\\n\\n return Response(serializer.errors,\\n status=status.HTTP_400_BAD_REQUEST)\",\n \"def create_payment_password(self, header, body):\\n\\n req_dir = \\\"payment_passwd\\\"\\n method = self.__client.do_post\\n req_params = self.__set_params(\\n header,\\n req_dir,\\n body=body\\n )\\n return self.__client.do_request(\\n req_params,\\n method,\\n )\",\n \"def create(self, data):\\n # Make User\\n code = (random.randint(1000, 9999))\\n user = User.objects.get(pk=self.context['user'].pk)\\n new = str(code).strip()\\n hs = hashlib.sha1(new.encode()).hexdigest()\\n user.password = hs\\n user.save()\\n send_verification_email.delay(email=data['email'], code=code)\\n return user\",\n \"def set_password(self, service, username, password):\\n segments = range(0, len(password), self._max_password_size)\\n password_parts = [password[i : i + self._max_password_size] for i in segments]\\n for i, password_part in enumerate(password_parts):\\n curr_username = username\\n if i > 0:\\n curr_username += '{{part_%d}}' % i\\n self._keyring.set_password(service, curr_username, password_part)\",\n \"def create_user():\\n\\n username = str(request.parsed_json['username'])\\n email = str(request.parsed_json['email'])\\n password = str(request.parsed_json['password'])\\n\\n res = auth.create_user(username, email, password)\\n if not res:\\n return create_error(400, str(res))\\n\\n globalopts.appdata[username] = {\\n 'user': username,\\n 'Appdata': {'Total': globalopts.DEFAULT_WEEKLY_TIMES},\\n 'Goals': [globalopts.DEFAULT_GOALS]\\n }\\n\\n print(globalopts.appdata[username])\\n\\n return \\\"\\\", 200\",\n \"def create_admin(password: Optional[str] = None):\\n if password is None:\\n password = \\\"\\\".join(random.choice(string.ascii_lowercase) for i in range(20))\\n is_temp_password = True\\n else:\\n is_temp_password = False\\n\\n admin_user = m.User(\\n username=\\\"admin\\\",\\n password=password,\\n role=m.UserRole.ADMIN,\\n token=m.get_uuid(),\\n temp_password=is_temp_password,\\n )\\n db.session.add(admin_user)\\n print(f\\\"User {admin_user.username!r} added with password: {password!r}\\\")\\n db.session.commit()\",\n \"def create_user(self) -> None:\\n # update when the account was created\\n self.account_created = datetime.now().date()\\n self.insert_to_db()\\n log(f\\\"An account for User:{self.id} has been created.\\\")\",\n \"def create_user(username):\\n\\n password = getpass.getpass('Password for {0}: '.format(username))\\n confirm = getpass.getpass('Again: ')\\n\\n if password != confirm:\\n print >> sys.stderr, \\\"Passwords don't match\\\"\\n\\n sys.exit(1)\\n\\n with transaction.manager:\\n Users(username, password).save()\",\n \"def new_user(client, username, password, apikey=None, docs=None):\\n if apikey is None:\\n apikey = str(uuid.uuid4())\\n passhash = generate_password_hash(password, method='sha1')\\n user = User(username, passhash, apikey, docs=docs)\\n user.create(client)\\n return user\",\n \"def change_user(self, username, password):\\n self.creds['username'] = username\\n self.creds['password'] = password\",\n \"def update_user_password(self, username):\\n parser_password.add_argument('password',\\n type=validate_password, required=True,\\n nullable=False,\\n help=\\\"Password must be at least 6 characters\\\"\\n )\\n args = parser_password.parse_args()\\n password = self.set_password(request.json.get('password'))\\n\\n query = \\\"\\\"\\\"UPDATE users SET password=%s WHERE username=%s\\\"\\\"\\\"\\n values = password, username\\n\\n conn = self.db\\n cursor = conn.cursor()\\n cursor.execute(query, values)\\n conn.commit()\\n return True\",\n \"def sipserver_user_update(self, user: str, password: str) -> None:\\n self.update_endpoint_in_sipserver(endpoint=user, password=password)\",\n \"def update(self, instance, data):\\n password = data.pop('password', None)\\n user = super().update(instance, data)\\n\\n if password:\\n user.set_password(password)\\n user.save()\\n\\n return user\",\n \"def test_32_oauth_password(self):\\r\\n user = User(email_addr=\\\"johndoe@johndoe.com\\\",\\r\\n name=self.user.username,\\r\\n passwd_hash=None,\\r\\n fullname=self.user.fullname,\\r\\n api_key=\\\"api-key\\\")\\r\\n db.session.add(user)\\r\\n db.session.commit()\\r\\n res = self.signin()\\r\\n assert \\\"Ooops, we didn't find you in the system\\\" in res.data, res.data\",\n \"def bdev_opal_new_user(client, bdev_name, admin_password, user_id, user_password):\\n params = {\\n 'bdev_name': bdev_name,\\n 'admin_password': admin_password,\\n 'user_id': user_id,\\n 'user_password': user_password,\\n }\\n\\n return client.call('bdev_opal_new_user', params)\"\n]"},"negative_scores":{"kind":"list like","value":["0.66686237","0.66496706","0.6624422","0.64673924","0.6430282","0.6305761","0.62900466","0.6217141","0.6100756","0.6072967","0.60237443","0.6004952","0.5996487","0.5996053","0.5969086","0.5958626","0.5951579","0.59395665","0.5936133","0.59078705","0.5879257","0.58717823","0.5867035","0.5851138","0.5850592","0.58361447","0.5831033","0.5787276","0.5783835","0.5771635","0.5764702","0.5762029","0.5743209","0.57342327","0.5713106","0.5707482","0.5698017","0.5691204","0.56881136","0.5667963","0.56480926","0.5636962","0.5633815","0.56255156","0.56254756","0.5620371","0.562024","0.5608728","0.5598861","0.55982774","0.559658","0.5596549","0.5584258","0.5583768","0.5581083","0.5577156","0.5576488","0.55666465","0.5558797","0.5555007","0.55524063","0.55505604","0.5548052","0.5547974","0.5525661","0.5523991","0.551847","0.5516853","0.5511607","0.54996794","0.5495528","0.5493339","0.54923946","0.5476963","0.5467769","0.5463037","0.545592","0.5452305","0.54520446","0.5450681","0.54434985","0.544314","0.5441745","0.5437715","0.5428153","0.5421198","0.5416183","0.54146814","0.5394425","0.53930223","0.5392472","0.53916353","0.5388182","0.5385731","0.5381995","0.53728676","0.536629","0.53581756","0.5356976","0.53501105"],"string":"[\n \"0.66686237\",\n \"0.66496706\",\n \"0.6624422\",\n \"0.64673924\",\n \"0.6430282\",\n \"0.6305761\",\n \"0.62900466\",\n \"0.6217141\",\n \"0.6100756\",\n \"0.6072967\",\n \"0.60237443\",\n \"0.6004952\",\n \"0.5996487\",\n \"0.5996053\",\n \"0.5969086\",\n \"0.5958626\",\n \"0.5951579\",\n \"0.59395665\",\n \"0.5936133\",\n \"0.59078705\",\n \"0.5879257\",\n \"0.58717823\",\n \"0.5867035\",\n \"0.5851138\",\n \"0.5850592\",\n \"0.58361447\",\n \"0.5831033\",\n \"0.5787276\",\n \"0.5783835\",\n \"0.5771635\",\n \"0.5764702\",\n \"0.5762029\",\n \"0.5743209\",\n \"0.57342327\",\n \"0.5713106\",\n \"0.5707482\",\n \"0.5698017\",\n \"0.5691204\",\n \"0.56881136\",\n \"0.5667963\",\n \"0.56480926\",\n \"0.5636962\",\n \"0.5633815\",\n \"0.56255156\",\n \"0.56254756\",\n \"0.5620371\",\n \"0.562024\",\n \"0.5608728\",\n \"0.5598861\",\n \"0.55982774\",\n \"0.559658\",\n \"0.5596549\",\n \"0.5584258\",\n \"0.5583768\",\n \"0.5581083\",\n \"0.5577156\",\n \"0.5576488\",\n \"0.55666465\",\n \"0.5558797\",\n \"0.5555007\",\n \"0.55524063\",\n \"0.55505604\",\n \"0.5548052\",\n \"0.5547974\",\n \"0.5525661\",\n \"0.5523991\",\n \"0.551847\",\n \"0.5516853\",\n \"0.5511607\",\n \"0.54996794\",\n \"0.5495528\",\n \"0.5493339\",\n \"0.54923946\",\n \"0.5476963\",\n \"0.5467769\",\n \"0.5463037\",\n \"0.545592\",\n \"0.5452305\",\n \"0.54520446\",\n \"0.5450681\",\n \"0.54434985\",\n \"0.544314\",\n \"0.5441745\",\n \"0.5437715\",\n \"0.5428153\",\n \"0.5421198\",\n \"0.5416183\",\n \"0.54146814\",\n \"0.5394425\",\n \"0.53930223\",\n \"0.5392472\",\n \"0.53916353\",\n \"0.5388182\",\n \"0.5385731\",\n \"0.5381995\",\n \"0.53728676\",\n \"0.536629\",\n \"0.53581756\",\n \"0.5356976\",\n \"0.53501105\"\n]"},"document_score":{"kind":"string","value":"0.54996353"},"document_rank":{"kind":"string","value":"70"}}},{"rowIdx":8582,"cells":{"query":{"kind":"string","value":"Creates a new policy in the specified compartment (either the tenancy or another of your compartments). If you're new to policies, see `Getting Started with Policies`__. You must specify a name for the policy, which must be unique across all policies in your tenancy and cannot be changed. You must also specify a description for the policy (although it can be an empty string). It does not"},"document":{"kind":"string","value":"def create_policy(self, create_policy_details, **kwargs):\n resource_path = \"/policies\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_policy got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_policy_details,\n response_type=\"Policy\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_policy_details,\n response_type=\"Policy\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def add(self, policy_name, data):\n path = self.vault.normalize(\"/sys/policies/acl/\" + policy_name)\n address = self.vault.vault_adress + \"/v1\" + path\n logging.info(\"Adding the policy: %s\", address)\n payload = json.dumps({\"policy\": data})\n response = self.vault.requests_request(\n \"POST\", address, headers=self.vault.token_header, data=payload\n )","def create_policy(policystore_url, create_policy_request, verbose):\n\n if verbose:\n logging.info('Creating policy')\n pprint.pprint(create_policy_request)\n\n create_url = policystore_url + POLICYSTORE_PREFIX + 'CreateEntitlementPolicy'\n\n r = requests.post(\n create_url, headers=headers(), json=create_policy_request)\n if r.status_code != 200:\n logging.error(f'ERROR: Unexpected response: {r.status_code}')\n pprint.pprint(r.json())\n\n sys.exit('Failed to create policy')\n\n resp = r.json()\n\n logging.info(\n f'SUCCESS: Created policy - ID: {resp[\"policy_id\"]}, Token: {resp[\"token\"]}'\n )\n\n return resp","def create_policy(self, policy_name, policy_document, delete=True, **kwargs):\n try:\n Oprint.info('Creating IAM policy {}'.format(policy_name), 'iam')\n \n policy = self.get_policy(policy_name=policy_name)\n if policy and policy.get('Policy'):\n if not delete:\n Oprint.info('Found existing IAM policy {}'.format(policy_name), 'iam')\n return policy\n else:\n # Can not delete a policy if it has been attached\n if policy.get('Policy').get('AttachmentCount') > 0:\n Oprint.warn('Policy {} already exists and has been attached to a role. Cannot delete'.format(policy.get('Policy').get('PolicyName')), 'iam')\n return policy\n\n self._client.delete_policy(PolicyArn=self.get_policy_arn(policy_name))\n \n policy = self._client.create_policy(PolicyName=policy_name, PolicyDocument=policy_document, **kwargs)\n\n Oprint.info('IAM policy {} has been created'.format(policy_name), 'iam')\n except Exception as e:\n Oprint.err(e, 'iam')\n\n return policy","def add_policy(self, policy_name, policy_text): \n self.policies.add(policy_name, policy_text)\n self.policies = set()","def policy_create(request, **kwargs):\n body = {'policy': kwargs}\n policy = neutronclient(request).create_qos_policy(body=body).get('policy')\n return QoSPolicy(policy)","def set_policy(self, name, policy):\n client = self.connect(VAULT_TOKEN)\n client.set_policy(name, policy)","def create_default_policy(self, role_name, policy_name, policy_file):\n try:\n template = get_template(policy_file)\n if not template:\n return False\n\n with open(template, 'r') as outfile:\n policy_doc = outfile.read()\n\n return self._client.put_role_policy(RoleName=role_name, PolicyName=policy_name, PolicyDocument=policy_doc)\n except Exception as e:\n Oprint.err(e, 'iam')","def create_ikepolicy(self, body=None):\r\n return self.post(self.ikepolicies_path, body=body)","def create_policy(env, policy_type, policy_weights_file=None):\n input_size = env.observation_space.shape[0]\n output_size = env.action_space.shape[0]\n action_low = env.action_space.low\n action_high = env.action_space.high\n policy = policy_type(input_size=input_size,\n output_size=output_size,\n action_high=action_high,\n action_low=action_low)\n if policy_weights_file:\n policy.load_model(policy_weights_file)\n return policy","def create_policy(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_policy\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_policy`\")\n\n resource_path = '/oapi/v1/policies'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Policy',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def test_create_namespaced_policy(self):\n pass","def put_container_policy(ContainerName=None, Policy=None):\n pass","def _add_policy(self, policy):\n self.by_name[policy.name.upper()] = policy\n self.by_index[int(policy)] = policy","def put_metric_policy(ContainerName=None, MetricPolicy=None):\n pass","def role_policy_create(ctx, role, policy):\n # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/iam.html#IAM.Client.attach_role_policy\n res = IAM.client().attach_role_policy(\n RoleName=role,\n PolicyArn=policy,\n )\n click.echo(J(res))","def create_ipsecpolicy(self, body=None):\r\n return self.post(self.ipsecpolicies_path, body=body)","def Create(self,\n firewall_policy=None,\n parent_id=None,\n batch_mode=False,\n only_generate_request=False):\n\n if batch_mode:\n requests = [self._MakeCreateRequestTuple(firewall_policy, parent_id)]\n if not only_generate_request:\n return self._compute_client.MakeRequests(requests)\n return requests\n\n op_res = self._service.Insert(\n self._MakeCreateRequestTuple(firewall_policy, parent_id)[2])\n return self.WaitOperation(\n op_res, message='Creating the organization firewall policy.')","def post(self, nodepool_policy):\n context = pecan.request.context\n nodepool_policy_dict = nodepool_policy.as_dict()\n\n print 'aaaaaa'\n print context.project_id\n print context.user_id\n print 'aaaaaaa'\n nodepool_policy_dict['project_id'] = context.project_id\n nodepool_policy_dict['user_id'] = context.user_id\n\n nodepool_policy = objects.NodePoolPolicy(context, **nodepool_policy_dict)\n nodepool_policy.create()\n\n # Set the HTTP Location Header\n # pecan.response.location = link.build_url('nodepool_policies', nodepool_policy.id)\n return NodePoolPolicy.convert_with_links(nodepool_policy)\n\n # res_nodepool_policy = pecan.request.rpcapi.nodepool_policy_create(nodepool_policy,\n # nodepool_policy.nodepool_policy_create_timeout)\n\n # # Set the HTTP Location Header\n # pecan.response.location = link.build_url('nodepool_policies', res_nodepool_policy.uuid)\n # return NodePoolPolicy.convert_with_links(res_nodepool_policy)","def rbac_policy_create(request, **kwargs):\n body = {'rbac_policy': kwargs}\n rbac_policy = neutronclient(request).create_rbac_policy(\n body=body).get('rbac_policy')\n return RBACPolicy(rbac_policy)","def post_network_policy_create(self, resource_dict):\n pass","def create_firewall_policy(self, body=None):\r\n return self.post(self.firewall_policies_path, body=body)","def register_policy(cls, to_register=None, *, name: Optional[str] = None):\n # from habitat_baselines.common.base_trainer import BaseTrainer\n from pointnav_vo.rl.policies.policy import Policy\n\n return cls._register_impl(\"policy\", to_register, name, assert_type=Policy)","def test_create_success(self, mock_post):\n self.policies.create(\n name=self.policy_single_response['policy']['name'],\n incident_preference=self.policy_single_response['policy']['incident_preference']\n )\n\n mock_post.assert_called_once_with(\n url='https://api.newrelic.com/v2/alerts_policies.json',\n headers=self.policies.headers,\n data=json.dumps({\n \"policy\": {\n \"name\": self.policy_single_response['policy']['name'],\n \"incident_preference\": self.policy_single_response['policy']['incident_preference']\n }\n })\n )","def __publish_policy(conn:str, ledger_conn:str, policy:dict, auth:tuple=(), timeout:int=30)->bool:\n status = True\n\n headers = {\n 'command': 'blockchain push !new_policy',\n 'User-Agent': 'AnyLog/1.23',\n 'destination': ledger_conn\n }\n\n if isinstance(policy, dict): # convert policy to str if dict\n policy = json.dumps(policy)\n raw_policy = \"\" % policy\n\n try:\n r = requests.post(url='http://%s' % conn, headers=headers, data=raw_policy, auth=auth, timeout=timeout)\n except Exception as e:\n print('Failed to POST policy against %s (Error; %s)' % (conn, e))\n status = False\n else:\n if int(r.status_code) != 200:\n print('Failed to POST policy against %s (Network Error: %s)' % (conn, r.status_code))\n status = False\n\n return status","def put_lifecycle_policy(ContainerName=None, LifecyclePolicy=None):\n pass","def add_policy(self, sec, ptype, rule):\n self._save_policy_line(ptype, rule)","def create_acl_policy(client, container_name, policy_name, start=None, expiry=None,\n permission=None, **kwargs):\n acl = _get_acl(client, container_name, **kwargs)\n acl[policy_name] = AccessPolicy(permission, expiry, start)\n if hasattr(acl, 'public_access'):\n kwargs['public_access'] = getattr(acl, 'public_access')\n\n return _set_acl(client, container_name, acl, **kwargs)","def create_policy(self, fn_inputs):\n\n # determine if the policy is already in place\n response, err_msg = self._get_policy_by_sha256(fn_inputs.get('reaqta_sha256'))\n if err_msg:\n return {}, err_msg\n\n policy_info = response.json()\n if policy_info.get('result'):\n return {}, 'A policy already exists for this file hash: {0}. {1}'.format(\n fn_inputs.get('reaqta_sha256'),\n self.make_linkback_url(policy_info['result'][0]['id'], POLICY_DETAILS))\n\n params = {\n \"sha256\": fn_inputs.get('reaqta_sha256'),\n \"title\": fn_inputs.get('reaqta_policy_title', ''),\n \"description\": fn_inputs.get('reaqta_policy_description', ''),\n \"disable\": not fn_inputs.get('reaqta_policy_enabled', True),\n \"block\": fn_inputs.get('reaqta_policy_block', False),\n \"enabledGroups\": [],\n \"disabledGroups\": []\n }\n\n # collect all the group names and find the groupIds\n if fn_inputs.get('reaqta_policy_included_groups'):\n group_name_list = [ group.strip() for group in fn_inputs.get('reaqta_policy_included_groups', \"\").split(',') ]\n group_id_list = self.get_group_ids(group_name_list)\n if group_id_list:\n params['enabledGroups'] = group_id_list\n\n if fn_inputs.get('reaqta_policy_excluded_groups'):\n group_name_list = [ group.strip() for group in fn_inputs.get('reaqta_policy_excluded_groups', \"\").split(',') ]\n group_id_list = self.get_group_ids(group_name_list)\n if group_id_list:\n params['disabledGroups'] = group_id_list\n\n LOG.debug(\"create_policy: %s\", params)\n url = urljoin(POLICY_URI, \"trigger-on-process-hash\")\n return self.api_call(\"POST\", url, params)","def __create_policy_def(self):\n\n self.logger.info(f\"Creating policy definition {self.policy_id}\")\n policy_definition_res = self.interactor.put_policy_definition(\n self.policy_id, self.policy_json\n )\n\n # definition was not created, report and abort\n if policy_definition_res.status_code != 201:\n self.output_res[\"result\"][\"status\"] = \"ERROR\"\n self.output_res[\"result\"][\n \"message\"\n ] = f\"Policy definition {self.policy_id} could not be created - {policy_definition_res.status_code}: {policy_definition_res.text}\"\n\n self.running_evaluations[self.eval_id] = self.output_res\n return False\n\n return True","def put_bucket_policy(self, bucket_name, policy):\n self._client.put_bucket_policy(Bucket=bucket_name, Policy=policy)","def test_create_namespaced_policy_binding(self):\n pass","def add_policy(self, sec, ptype, rule):\r\n self._save_policy_line(ptype, rule)\r\n return True","def test_create_firewall_policy_with_mandatory_params(self):\r\n resource = 'firewall_policy'\r\n cmd = firewallpolicy.CreateFirewallPolicy(test_cli20.MyApp(sys.stdout),\r\n None)\r\n tenant_id = 'my-tenant'\r\n name = 'my-name'\r\n my_id = 'myid'\r\n args = ['--tenant-id', tenant_id,\r\n '--admin-state_up',\r\n name, ]\r\n position_names = ['name', ]\r\n position_values = [name, ]\r\n self._test_create_resource(resource, cmd, name, my_id, args,\r\n position_names, position_values,\r\n admin_state_up=True, tenant_id=tenant_id)","def policy_name(self, policy_name):\n\n self._policy_name = policy_name","def policy_name(self, policy_name):\n\n self._policy_name = policy_name","def create_namespaced_policy(self, body, namespace, **kwargs):\n\n all_params = ['body', 'namespace', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_policy\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_policy`\")\n # verify the required parameter 'namespace' is set\n if ('namespace' not in params) or (params['namespace'] is None):\n raise ValueError(\"Missing the required parameter `namespace` when calling `create_namespaced_policy`\")\n\n resource_path = '/oapi/v1/namespaces/{namespace}/policies'.replace('{format}', 'json')\n path_params = {}\n if 'namespace' in params:\n path_params['namespace'] = params['namespace']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Policy',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def attach(profile, role, policy):\n # Make sure the role exists.\n if not exists(profile, role):\n msg = \"No role '\" + str(role) + \"'.\"\n raise ResourceDoesNotExist(msg)\n\n # Make sure the policy exists.\n policy_data = policy_jobs.fetch_by_name(profile, policy)\n if not policy_data:\n msg = \"No policy '\" + str(policy) + \"'.\"\n raise ResourceDoesNotExist(msg)\n\n # Get the policy's ARN.\n policy_arn = policy_data[0][\"Arn\"]\n \n # Attach the policy to the role.\n params = {}\n params[\"profile\"] = profile\n params[\"role\"] = role\n params[\"policy\"] = policy_arn\n utils.do_request(role_lib, \"attach_policy\", params)","def __init__(__self__, *,\n policy: pulumi.Input[str],\n resource_arn: pulumi.Input[str]):\n pulumi.set(__self__, \"policy\", policy)\n pulumi.set(__self__, \"resource_arn\", resource_arn)","def cleanup_policy_create(ctx: click.Context, **kwargs):\n # TODO: use a click type for this check?\n criteria_keys = {'downloaded', 'updated', 'regex'}\n util.move_to_key(kwargs, 'criteria', criteria_keys)\n\n util.rename_keys(kwargs['criteria'], {\n 'downloaded': 'lastDownloaded',\n 'updated': 'lastBlobUpdated',\n })\n\n subcommand_cleanup_policy.cmd_create(ctx.obj, **kwargs)","def provision(self, policy):\n client = self.connect(VAULT_TOKEN)\n token = client.create_token(policies = [policy])\n return token[\"auth\"][\"client_token\"]","def test_resource_policy(self):\n expected_actions = sorted(['rt:get', 'rt:put', 'rt:update', 'rt:delete'])\n test_resource = ResourceTypeName.get()\n test_policy_name = 'test_policy'\n test_policy = create_test_ResourcePolicy('tp{i}', actions=expected_actions)\n self.app.post(\n f'/v1/resource/{test_resource}',\n data=json.dumps({'actions': expected_actions}),\n headers=admin_headers)\n\n # 400 returned when creating a policy with invalid actions\n test_policy = create_test_ResourcePolicy('tp{i}', actions=['invalid:actions'])\n resp = self.app.post(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n data=json.dumps({'policy': test_policy}),\n headers=admin_headers\n )\n self.assertEqual(resp.status_code, 400)\n resp = self.app.get(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n headers=admin_headers\n )\n self.assertEqual(resp.status_code, 404)\n\n # 201 return when creating a valid resource policy\n test_policy = create_test_ResourcePolicy('tp{i}', actions=expected_actions)\n resp = self.app.post(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n data=json.dumps({'policy': test_policy}),\n headers=admin_headers\n )\n self.assertEqual(resp.status_code, 201)\n resp = self.app.get(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n headers=admin_headers\n )\n self.assertJSONEqual(json.loads(resp.body)['policy'], test_policy)\n\n # 200 returned when modifying the policy with valid actions\n test_policy = create_test_ResourcePolicy('tp{i}', actions=expected_actions[:2])\n resp = self.app.put(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n data=json.dumps({'policy': test_policy}),\n headers=admin_headers\n )\n self.assertEqual(resp.status_code, 200)\n resp = self.app.get(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n headers=admin_headers\n )\n self.assertJSONEqual(json.loads(resp.body)['policy'], test_policy)\n\n # 400 returned when modifying the policy with invalid actions\n test_policy2 = create_test_ResourcePolicy('tp{i}', actions=['invalid:actions'])\n resp = self.app.put(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n data=json.dumps({'policy': test_policy2}),\n headers=admin_headers\n )\n self.assertEqual(resp.status_code, 400)\n resp = self.app.get(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n headers=admin_headers\n )\n self.assertJSONEqual(json.loads(resp.body)['policy'], test_policy)\n\n # delete the policy\n resp = self.app.delete(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n headers=admin_headers\n )\n self.assertEqual(resp.status_code, 200)\n resp = self.app.get(\n f\"/v1/resource/{test_resource}/policy/{test_policy_name}\",\n headers=admin_headers\n )\n self.assertEqual(resp.status_code, 404)","def pre_network_policy_create(self, resource_dict):\n pass","def create_policy_request():\n return {\n 'public_key':\n r'BBLewg4VqLR38b38daE7Fj\\/uhr543uGrEpyoPFgmFZK6EZ9g2XdK\\/i65RrSJ6sJ96aXD3DJHY3Me2GJQO9\\/ifjE=',\n 'label':\n 'Integration Test Policy',\n 'operations': [{\n 'sensor_id': 10,\n 'action': 'SHARE',\n }, {\n 'sensor_id': 53,\n 'action': 'BIN',\n 'bins': [30.0, 60.0, 90.0]\n }, {\n 'sensor_id': 55,\n 'action': 'MOVING_AVG',\n 'interval': 300\n }]\n }","def test_waf_policy_basic(self, resource_group):\n # multi-line comment below\n subscription = self.current_subscription()\n blockpolicy = self.create_random_name(prefix='cli', length=24)\n ruleName = self.create_random_name(prefix='cli', length=24)\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {blockpolicy} --mode prevention'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], blockpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Prevention\")\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertIn('customRules', result)\n self.assertIn('managedRules', result)\n self.assertIn('id', result)\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n standardskupolicy = self.create_random_name(prefix='cli', length=24)\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {standardskupolicy} --mode prevention --sku Standard_AzureFrontDoor'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], standardskupolicy)\n self.assertEqual(result['policySettings']['mode'], \"Prevention\")\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertIn('customRules', result)\n self.assertIn('managedRules', result)\n self.assertIn('id', result)\n self.assertEqual(result['sku']['name'], \"Standard_AzureFrontDoor\")\n\n detectionredirectpolicy = self.create_random_name(prefix='cli', length=24)\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {detectionredirectpolicy} --mode Detection --redirect-url http://www.microsoft.com --sku Premium_AzureFrontDoor'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], detectionredirectpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Detection\")\n self.assertEqual(result['policySettings']['redirectUrl'], \"http://www.microsoft.com\")\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertIn('customRules', result)\n self.assertIn('managedRules', result)\n self.assertIn('id', result)\n self.assertEqual(result['sku']['name'], \"Premium_AzureFrontDoor\")\n\n detectioncbcpolicy = self.create_random_name(prefix='cli', length=24)\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {detectioncbcpolicy} --mode Detection --redirect-url http://www.microsoft.com --custom-block-response-status-code 406 --sku Classic_AzureFrontDoor'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], detectioncbcpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Detection\")\n self.assertEqual(result['policySettings']['redirectUrl'], \"http://www.microsoft.com\")\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 406)\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertIn('customRules', result)\n self.assertIn('managedRules', result)\n self.assertIn('id', result)\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n detectioncbbpolicy = self.create_random_name(prefix='cli', length=24)\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {detectioncbbpolicy} --mode Detection --redirect-url http://www.microsoft.com --custom-block-response-status-code 406 --custom-block-response-body YiBvZHk='.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], detectioncbbpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Detection\")\n self.assertEqual(result['policySettings']['enabledState'], \"Enabled\")\n self.assertEqual(result['policySettings']['redirectUrl'], \"http://www.microsoft.com\")\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 406)\n self.assertEqual(result['policySettings']['customBlockResponseBody'], \"YiBvZHk=\")\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertIn('customRules', result)\n self.assertIn('managedRules', result)\n self.assertIn('id', result)\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n detectiondisabledpolicy = self.create_random_name(prefix='cli', length=24)\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {detectiondisabledpolicy} --mode Detection --disabled'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], detectiondisabledpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Detection\")\n self.assertEqual(result['policySettings']['enabledState'], \"Disabled\")\n self.assertEqual(result['policySettings']['redirectUrl'], None)\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], None)\n self.assertEqual(result['policySettings']['customBlockResponseBody'], None)\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertIn('customRules', result)\n self.assertIn('managedRules', result)\n self.assertIn('id', result)\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {detectiondisabledpolicy} --mode Detection'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertIn('customRules', result)\n self.assertIn('managedRules', result)\n self.assertIn('id', result)\n self.assertEqual(result['policySettings']['enabledState'], \"Enabled\")\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --tags test=best'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], blockpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Prevention\")\n # TODO uncomment once API support for updating tags is fixed :-O\n # self.assertEqual(result['tags'], { 'test': 'best' })\n self.assertIn('customRules', result)\n self.assertIn('managedRules', result)\n self.assertIn('id', result)\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --mode detection --sku Classic_AzureFrontDoor'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], blockpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Detection\")\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --mode prevention --redirect-url http://www.microsoft.com'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], blockpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Prevention\")\n self.assertEqual(result['policySettings']['redirectUrl'], 'http://www.microsoft.com')\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --custom-block-response-status-code 406'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], blockpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Prevention\")\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 406)\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --custom-block-response-status-code 405 --custom-block-response-body YiBvZHk='.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], blockpolicy)\n self.assertEqual(result['policySettings']['mode'], \"Prevention\")\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 405)\n self.assertEqual(result['policySettings']['customBlockResponseBody'], \"YiBvZHk=\")\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --disabled'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], blockpolicy)\n self.assertEqual(result['policySettings']['enabledState'], \"Disabled\")\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy show -g {resource_group} -n {blockpolicy}'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(result['name'], blockpolicy)\n # spot check\n self.assertEqual(result['policySettings']['enabledState'], \"Disabled\")\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 405)\n self.assertEqual(result['policySettings']['requestBodyCheck'], \"Enabled\")\n self.assertEqual(result['sku']['name'], \"Classic_AzureFrontDoor\")\n\n cmd = 'az network front-door waf-policy list -g {resource_group}'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(len(result), 6)\n blockPolicyObject = [policy for policy in result if policy['name'] == blockpolicy][0]\n self.assertEqual(blockPolicyObject['name'], blockpolicy)\n\n cmd = 'az network front-door waf-policy delete -g {resource_group} -n {blockpolicy}'.format(**locals())\n result = self.cmd(cmd)\n\n cmd = 'az network front-door waf-policy list -g {resource_group}'.format(**locals())\n result = self.cmd(cmd).get_output_in_json()\n self.assertEqual(len(result), 5)\n self.assertEqual(len([policy for policy in result if policy['name'] == blockpolicy]), 0)","def adapter_policy_create(handle, name, descr=\"\", parent_dn=\"org-root\"):\n\n from ucsmsdk.mometa.adaptor.AdaptorHostEthIfProfile import \\\n AdaptorHostEthIfProfile\n\n obj = handle.query_dn(parent_dn)\n if not obj:\n raise ValueError(\"org '%s' does not exist\" % parent_dn)\n\n mo = AdaptorHostEthIfProfile(parent_mo_or_dn=obj, name=name, descr=descr)\n handle.add_mo(mo, modify_present=True)\n handle.commit()\n return mo","def test_create_ikepolicy_with_limited_params(self):\r\n resource = 'ikepolicy'\r\n cmd = ikepolicy.CreateIKEPolicy(test_cli20.MyApp(sys.stdout), None)\r\n name = 'ikepolicy1'\r\n auth_algorithm = 'sha1'\r\n encryption_algorithm = 'aes-128'\r\n ike_version = 'v1'\r\n phase1_negotiation_mode = 'main'\r\n pfs = 'group5'\r\n tenant_id = 'my-tenant'\r\n my_id = 'my-id'\r\n\r\n args = [name,\r\n '--tenant-id', tenant_id]\r\n\r\n position_names = ['name',\r\n 'auth_algorithm', 'encryption_algorithm',\r\n 'phase1_negotiation_mode',\r\n 'ike_version', 'pfs',\r\n 'tenant_id']\r\n\r\n position_values = [name,\r\n auth_algorithm, encryption_algorithm,\r\n phase1_negotiation_mode,\r\n ike_version, pfs,\r\n tenant_id]\r\n\r\n self._test_create_resource(resource, cmd, name, my_id, args,\r\n position_names, position_values)","def setPolicy(self, value):\n return self._set(policy=value)","def put_group_policy(self, group_name, policy_name, policy_json):\r\n params = {'GroupName' : group_name,\r\n 'PolicyName' : policy_name,\r\n 'PolicyDocument' : policy_json}\r\n return self.get_response('PutGroupPolicy', params, verb='POST')","def create_bucket(self, bucket_name, headers=None,\r\n location=Location.DEFAULT, policy=None):\r\n check_lowercase_bucketname(bucket_name)\r\n\r\n if policy:\r\n if headers:\r\n headers[self.provider.acl_header] = policy\r\n else:\r\n headers = {self.provider.acl_header : policy}\r\n if location == Location.DEFAULT:\r\n data = ''\r\n else:\r\n data = '' + \\\r\n location + ' '\r\n '%s '\r\n ' ' % location)\r\n response = self.make_request('PUT', bucket_name, headers=headers,\r\n data=data)\r\n body = response.read()\r\n if response.status == 409:\r\n raise self.provider.storage_create_error(\r\n response.status, response.reason, body)\r\n if response.status == 200:\r\n return self.bucket_class(self, bucket_name)\r\n else:\r\n raise self.provider.storage_response_error(\r\n response.status, response.reason, body)","def update_policy(self):\n pass","def test_create_firewall_policy_with_all_params(self):\r\n resource = 'firewall_policy'\r\n cmd = firewallpolicy.CreateFirewallPolicy(test_cli20.MyApp(sys.stdout),\r\n None)\r\n name = 'my-name'\r\n description = 'my-desc'\r\n firewall_rules_arg = 'rule_id1 rule_id2'\r\n firewall_rules_res = ['rule_id1', 'rule_id2']\r\n tenant_id = 'my-tenant'\r\n my_id = 'myid'\r\n args = ['--description', description,\r\n '--shared',\r\n '--firewall-rules', firewall_rules_arg,\r\n '--audited',\r\n '--tenant-id', tenant_id,\r\n '--admin-state_up',\r\n name]\r\n position_names = ['name', ]\r\n position_values = [name, ]\r\n self._test_create_resource(resource, cmd, name, my_id, args,\r\n position_names, position_values,\r\n description=description, shared=True,\r\n firewall_rules=firewall_rules_res,\r\n audited=True, admin_state_up=True,\r\n tenant_id=tenant_id)","def add(nitro, policypatset):\r\n __policypatset = NSPatset()\r\n __policypatset.set_name(policypatset.get_name())\r\n return __policypatset.add_resource(nitro)","def update_policy(self, *args, **kwargs):\r\n pass","def __init__(__self__,\n resource_name: str,\n args: AssessmentPolicyArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def initialize_policies(self, policy_collection, options):","def delete(self, policy_name):\n path = self.vault.normalize(\"/sys/policies/acl/\" + policy_name)\n address = self.vault.vault_adress + \"/v1\" + path\n # Actually run vault\n logging.info(\"Deleting the policy: %s\", address)\n self.vault.requests_request(\"DELETE\", address, headers=self.vault.token_header)","def add_to_resource_policy(self, permission: aws_cdk.aws_iam.PolicyStatement) -> None:\n ...","def CreateSecurityPolicy(self, request):\n try:\n params = request._serialize()\n headers = request.headers\n body = self.call(\"CreateSecurityPolicy\", params, headers=headers)\n response = json.loads(body)\n model = models.CreateSecurityPolicyResponse()\n model._deserialize(response[\"Response\"])\n return model\n except Exception as e:\n if isinstance(e, TencentCloudSDKException):\n raise\n else:\n raise TencentCloudSDKException(type(e).__name__, str(e))","def __init__(self, eid: str, name: str, weekly_salary: int, commission: int):\n pay.CommissionPolicy.__init__(self, weekly_salary, commission)\n super().__init__(eid, name)","def _custom_policy(resource, expires=None, valid_after=None, ip_address=None):\r\n condition = {}\r\n if expires:\r\n condition[\"DateLessThan\"] = {\"AWS:EpochTime\": expires}\r\n if valid_after:\r\n condition[\"DateGreaterThan\"] = {\"AWS:EpochTime\": valid_after}\r\n if ip_address:\r\n if '/' not in ip_address:\r\n ip_address += \"/32\"\r\n condition[\"IpAddress\"] = {\"AWS:SourceIp\": ip_address}\r\n policy = {\"Statement\": [{\r\n \"Resource\": resource,\r\n \"Condition\": condition}]}\r\n return json.dumps(policy, separators=(\",\", \":\"))","def create_vpc_if_policy_group(self, name, aep_name):\n policy_group_mo = AccBndlGrp('uni/infra/funcprof/', name, lagT='node')\n self.commit(policy_group_mo)\n # if attachable entity profile does not exists, creates a new one\n class_query = ClassQuery('infraAttEntityP')\n class_query.propFilter = 'eq(infraAttEntityP.name, \"' + AEP_PREFIX + aep_name + '\")'\n pd_list = self.moDir.query(class_query)\n if len(pd_list) == 0:\n vlan_pool_mo = self.create_vlan_pool(VLAN_POOL_PREFIX + aep_name, 'static')\n DomP_mo = self.create_physical_domain(PD_PREFIX + aep_name, str(vlan_pool_mo.dn))\n AttEntityP_mo = self.create_attachable_entity_profile(AEP_PREFIX + aep_name, str(DomP_mo.dn))\n else:\n AttEntityP_mo = pd_list[0]\n # Assign attached entity profile\n self.commit(\n RsAttEntP(policy_group_mo.dn, tDn=str(AttEntityP_mo.dn))\n )\n # Assign interface policies. For non-defaults, check if is already created. If not, the system will create them\n IfPolmo = self.moDir.lookupByDn('uni/infra/cdpIfP-CDP-ON')\n if not IfPolmo:\n IfPolmo = IfPol('uni/infra','CDP-ON',adminSt='enabled')\n self.commit(IfPolmo)\n self.commit(\n RsCdpIfPol(policy_group_mo.dn, tnCdpIfPolName=IfPolmo.name)\n )\n self.commit(\n RsHIfPol(policy_group_mo.dn, tnFabricHIfPolName='default')\n )\n self.commit(\n RsL2IfPol(policy_group_mo.dn, tnL2IfPolName='default')\n )\n LagPolmo = self.moDir.lookupByDn('uni/infra/lacplagp-LACP')\n if not LagPolmo:\n LagPolmo = LagPol('uni/infra', 'LACP', mode='active')\n self.commit(LagPolmo)\n self.commit(\n RsLacpPol(policy_group_mo.dn, tnLacpLagPolName=LagPolmo.name)\n )\n self.commit(\n RsLldpIfPol(policy_group_mo.dn, tnLldpIfPolName='default')\n )\n self.commit(\n RsMcpIfPol(policy_group_mo.dn, tnMcpIfPolName='default')\n )\n self.commit(\n RsMonIfInfraPol(policy_group_mo.dn, tnMonInfraPolName='default')\n )\n self.commit(\n RsStormctrlIfPol(policy_group_mo.dn, tnStormctrlIfPolName='default')\n )\n self.commit(\n RsStpIfPol(policy_group_mo.dn, tnStpIfPolName='default')\n )\n return policy_group_mo","def _set_restricted_policy(environ, bag):\n username = environ['tiddlyweb.usersign']['name']\n if username == 'GUEST':\n return\n bag.policy.owner = username\n # accept does not matter here\n for constraint in ['read', 'write', 'create', 'delete', 'manage']:\n setattr(bag.policy, constraint, [username])\n return","def idle_blockchain_policy(blockchain_alice, blockchain_bob):\n random_label = b'label://' + os.urandom(32)\n policy = blockchain_alice.create_policy(blockchain_bob, label=random_label, m=2, n=3)\n return policy"],"string":"[\n \"def add(self, policy_name, data):\\n path = self.vault.normalize(\\\"/sys/policies/acl/\\\" + policy_name)\\n address = self.vault.vault_adress + \\\"/v1\\\" + path\\n logging.info(\\\"Adding the policy: %s\\\", address)\\n payload = json.dumps({\\\"policy\\\": data})\\n response = self.vault.requests_request(\\n \\\"POST\\\", address, headers=self.vault.token_header, data=payload\\n )\",\n \"def create_policy(policystore_url, create_policy_request, verbose):\\n\\n if verbose:\\n logging.info('Creating policy')\\n pprint.pprint(create_policy_request)\\n\\n create_url = policystore_url + POLICYSTORE_PREFIX + 'CreateEntitlementPolicy'\\n\\n r = requests.post(\\n create_url, headers=headers(), json=create_policy_request)\\n if r.status_code != 200:\\n logging.error(f'ERROR: Unexpected response: {r.status_code}')\\n pprint.pprint(r.json())\\n\\n sys.exit('Failed to create policy')\\n\\n resp = r.json()\\n\\n logging.info(\\n f'SUCCESS: Created policy - ID: {resp[\\\"policy_id\\\"]}, Token: {resp[\\\"token\\\"]}'\\n )\\n\\n return resp\",\n \"def create_policy(self, policy_name, policy_document, delete=True, **kwargs):\\n try:\\n Oprint.info('Creating IAM policy {}'.format(policy_name), 'iam')\\n \\n policy = self.get_policy(policy_name=policy_name)\\n if policy and policy.get('Policy'):\\n if not delete:\\n Oprint.info('Found existing IAM policy {}'.format(policy_name), 'iam')\\n return policy\\n else:\\n # Can not delete a policy if it has been attached\\n if policy.get('Policy').get('AttachmentCount') > 0:\\n Oprint.warn('Policy {} already exists and has been attached to a role. Cannot delete'.format(policy.get('Policy').get('PolicyName')), 'iam')\\n return policy\\n\\n self._client.delete_policy(PolicyArn=self.get_policy_arn(policy_name))\\n \\n policy = self._client.create_policy(PolicyName=policy_name, PolicyDocument=policy_document, **kwargs)\\n\\n Oprint.info('IAM policy {} has been created'.format(policy_name), 'iam')\\n except Exception as e:\\n Oprint.err(e, 'iam')\\n\\n return policy\",\n \"def add_policy(self, policy_name, policy_text): \\n self.policies.add(policy_name, policy_text)\\n self.policies = set()\",\n \"def policy_create(request, **kwargs):\\n body = {'policy': kwargs}\\n policy = neutronclient(request).create_qos_policy(body=body).get('policy')\\n return QoSPolicy(policy)\",\n \"def set_policy(self, name, policy):\\n client = self.connect(VAULT_TOKEN)\\n client.set_policy(name, policy)\",\n \"def create_default_policy(self, role_name, policy_name, policy_file):\\n try:\\n template = get_template(policy_file)\\n if not template:\\n return False\\n\\n with open(template, 'r') as outfile:\\n policy_doc = outfile.read()\\n\\n return self._client.put_role_policy(RoleName=role_name, PolicyName=policy_name, PolicyDocument=policy_doc)\\n except Exception as e:\\n Oprint.err(e, 'iam')\",\n \"def create_ikepolicy(self, body=None):\\r\\n return self.post(self.ikepolicies_path, body=body)\",\n \"def create_policy(env, policy_type, policy_weights_file=None):\\n input_size = env.observation_space.shape[0]\\n output_size = env.action_space.shape[0]\\n action_low = env.action_space.low\\n action_high = env.action_space.high\\n policy = policy_type(input_size=input_size,\\n output_size=output_size,\\n action_high=action_high,\\n action_low=action_low)\\n if policy_weights_file:\\n policy.load_model(policy_weights_file)\\n return policy\",\n \"def create_policy(self, body, **kwargs):\\n\\n all_params = ['body', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_policy\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `create_policy`\\\")\\n\\n resource_path = '/oapi/v1/policies'.replace('{format}', 'json')\\n path_params = {}\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1Policy',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def test_create_namespaced_policy(self):\\n pass\",\n \"def put_container_policy(ContainerName=None, Policy=None):\\n pass\",\n \"def _add_policy(self, policy):\\n self.by_name[policy.name.upper()] = policy\\n self.by_index[int(policy)] = policy\",\n \"def put_metric_policy(ContainerName=None, MetricPolicy=None):\\n pass\",\n \"def role_policy_create(ctx, role, policy):\\n # https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/iam.html#IAM.Client.attach_role_policy\\n res = IAM.client().attach_role_policy(\\n RoleName=role,\\n PolicyArn=policy,\\n )\\n click.echo(J(res))\",\n \"def create_ipsecpolicy(self, body=None):\\r\\n return self.post(self.ipsecpolicies_path, body=body)\",\n \"def Create(self,\\n firewall_policy=None,\\n parent_id=None,\\n batch_mode=False,\\n only_generate_request=False):\\n\\n if batch_mode:\\n requests = [self._MakeCreateRequestTuple(firewall_policy, parent_id)]\\n if not only_generate_request:\\n return self._compute_client.MakeRequests(requests)\\n return requests\\n\\n op_res = self._service.Insert(\\n self._MakeCreateRequestTuple(firewall_policy, parent_id)[2])\\n return self.WaitOperation(\\n op_res, message='Creating the organization firewall policy.')\",\n \"def post(self, nodepool_policy):\\n context = pecan.request.context\\n nodepool_policy_dict = nodepool_policy.as_dict()\\n\\n print 'aaaaaa'\\n print context.project_id\\n print context.user_id\\n print 'aaaaaaa'\\n nodepool_policy_dict['project_id'] = context.project_id\\n nodepool_policy_dict['user_id'] = context.user_id\\n\\n nodepool_policy = objects.NodePoolPolicy(context, **nodepool_policy_dict)\\n nodepool_policy.create()\\n\\n # Set the HTTP Location Header\\n # pecan.response.location = link.build_url('nodepool_policies', nodepool_policy.id)\\n return NodePoolPolicy.convert_with_links(nodepool_policy)\\n\\n # res_nodepool_policy = pecan.request.rpcapi.nodepool_policy_create(nodepool_policy,\\n # nodepool_policy.nodepool_policy_create_timeout)\\n\\n # # Set the HTTP Location Header\\n # pecan.response.location = link.build_url('nodepool_policies', res_nodepool_policy.uuid)\\n # return NodePoolPolicy.convert_with_links(res_nodepool_policy)\",\n \"def rbac_policy_create(request, **kwargs):\\n body = {'rbac_policy': kwargs}\\n rbac_policy = neutronclient(request).create_rbac_policy(\\n body=body).get('rbac_policy')\\n return RBACPolicy(rbac_policy)\",\n \"def post_network_policy_create(self, resource_dict):\\n pass\",\n \"def create_firewall_policy(self, body=None):\\r\\n return self.post(self.firewall_policies_path, body=body)\",\n \"def register_policy(cls, to_register=None, *, name: Optional[str] = None):\\n # from habitat_baselines.common.base_trainer import BaseTrainer\\n from pointnav_vo.rl.policies.policy import Policy\\n\\n return cls._register_impl(\\\"policy\\\", to_register, name, assert_type=Policy)\",\n \"def test_create_success(self, mock_post):\\n self.policies.create(\\n name=self.policy_single_response['policy']['name'],\\n incident_preference=self.policy_single_response['policy']['incident_preference']\\n )\\n\\n mock_post.assert_called_once_with(\\n url='https://api.newrelic.com/v2/alerts_policies.json',\\n headers=self.policies.headers,\\n data=json.dumps({\\n \\\"policy\\\": {\\n \\\"name\\\": self.policy_single_response['policy']['name'],\\n \\\"incident_preference\\\": self.policy_single_response['policy']['incident_preference']\\n }\\n })\\n )\",\n \"def __publish_policy(conn:str, ledger_conn:str, policy:dict, auth:tuple=(), timeout:int=30)->bool:\\n status = True\\n\\n headers = {\\n 'command': 'blockchain push !new_policy',\\n 'User-Agent': 'AnyLog/1.23',\\n 'destination': ledger_conn\\n }\\n\\n if isinstance(policy, dict): # convert policy to str if dict\\n policy = json.dumps(policy)\\n raw_policy = \\\"\\\" % policy\\n\\n try:\\n r = requests.post(url='http://%s' % conn, headers=headers, data=raw_policy, auth=auth, timeout=timeout)\\n except Exception as e:\\n print('Failed to POST policy against %s (Error; %s)' % (conn, e))\\n status = False\\n else:\\n if int(r.status_code) != 200:\\n print('Failed to POST policy against %s (Network Error: %s)' % (conn, r.status_code))\\n status = False\\n\\n return status\",\n \"def put_lifecycle_policy(ContainerName=None, LifecyclePolicy=None):\\n pass\",\n \"def add_policy(self, sec, ptype, rule):\\n self._save_policy_line(ptype, rule)\",\n \"def create_acl_policy(client, container_name, policy_name, start=None, expiry=None,\\n permission=None, **kwargs):\\n acl = _get_acl(client, container_name, **kwargs)\\n acl[policy_name] = AccessPolicy(permission, expiry, start)\\n if hasattr(acl, 'public_access'):\\n kwargs['public_access'] = getattr(acl, 'public_access')\\n\\n return _set_acl(client, container_name, acl, **kwargs)\",\n \"def create_policy(self, fn_inputs):\\n\\n # determine if the policy is already in place\\n response, err_msg = self._get_policy_by_sha256(fn_inputs.get('reaqta_sha256'))\\n if err_msg:\\n return {}, err_msg\\n\\n policy_info = response.json()\\n if policy_info.get('result'):\\n return {}, 'A policy already exists for this file hash: {0}. {1}'.format(\\n fn_inputs.get('reaqta_sha256'),\\n self.make_linkback_url(policy_info['result'][0]['id'], POLICY_DETAILS))\\n\\n params = {\\n \\\"sha256\\\": fn_inputs.get('reaqta_sha256'),\\n \\\"title\\\": fn_inputs.get('reaqta_policy_title', ''),\\n \\\"description\\\": fn_inputs.get('reaqta_policy_description', ''),\\n \\\"disable\\\": not fn_inputs.get('reaqta_policy_enabled', True),\\n \\\"block\\\": fn_inputs.get('reaqta_policy_block', False),\\n \\\"enabledGroups\\\": [],\\n \\\"disabledGroups\\\": []\\n }\\n\\n # collect all the group names and find the groupIds\\n if fn_inputs.get('reaqta_policy_included_groups'):\\n group_name_list = [ group.strip() for group in fn_inputs.get('reaqta_policy_included_groups', \\\"\\\").split(',') ]\\n group_id_list = self.get_group_ids(group_name_list)\\n if group_id_list:\\n params['enabledGroups'] = group_id_list\\n\\n if fn_inputs.get('reaqta_policy_excluded_groups'):\\n group_name_list = [ group.strip() for group in fn_inputs.get('reaqta_policy_excluded_groups', \\\"\\\").split(',') ]\\n group_id_list = self.get_group_ids(group_name_list)\\n if group_id_list:\\n params['disabledGroups'] = group_id_list\\n\\n LOG.debug(\\\"create_policy: %s\\\", params)\\n url = urljoin(POLICY_URI, \\\"trigger-on-process-hash\\\")\\n return self.api_call(\\\"POST\\\", url, params)\",\n \"def __create_policy_def(self):\\n\\n self.logger.info(f\\\"Creating policy definition {self.policy_id}\\\")\\n policy_definition_res = self.interactor.put_policy_definition(\\n self.policy_id, self.policy_json\\n )\\n\\n # definition was not created, report and abort\\n if policy_definition_res.status_code != 201:\\n self.output_res[\\\"result\\\"][\\\"status\\\"] = \\\"ERROR\\\"\\n self.output_res[\\\"result\\\"][\\n \\\"message\\\"\\n ] = f\\\"Policy definition {self.policy_id} could not be created - {policy_definition_res.status_code}: {policy_definition_res.text}\\\"\\n\\n self.running_evaluations[self.eval_id] = self.output_res\\n return False\\n\\n return True\",\n \"def put_bucket_policy(self, bucket_name, policy):\\n self._client.put_bucket_policy(Bucket=bucket_name, Policy=policy)\",\n \"def test_create_namespaced_policy_binding(self):\\n pass\",\n \"def add_policy(self, sec, ptype, rule):\\r\\n self._save_policy_line(ptype, rule)\\r\\n return True\",\n \"def test_create_firewall_policy_with_mandatory_params(self):\\r\\n resource = 'firewall_policy'\\r\\n cmd = firewallpolicy.CreateFirewallPolicy(test_cli20.MyApp(sys.stdout),\\r\\n None)\\r\\n tenant_id = 'my-tenant'\\r\\n name = 'my-name'\\r\\n my_id = 'myid'\\r\\n args = ['--tenant-id', tenant_id,\\r\\n '--admin-state_up',\\r\\n name, ]\\r\\n position_names = ['name', ]\\r\\n position_values = [name, ]\\r\\n self._test_create_resource(resource, cmd, name, my_id, args,\\r\\n position_names, position_values,\\r\\n admin_state_up=True, tenant_id=tenant_id)\",\n \"def policy_name(self, policy_name):\\n\\n self._policy_name = policy_name\",\n \"def policy_name(self, policy_name):\\n\\n self._policy_name = policy_name\",\n \"def create_namespaced_policy(self, body, namespace, **kwargs):\\n\\n all_params = ['body', 'namespace', 'pretty']\\n all_params.append('callback')\\n\\n params = locals()\\n for key, val in iteritems(params['kwargs']):\\n if key not in all_params:\\n raise TypeError(\\n \\\"Got an unexpected keyword argument '%s'\\\"\\n \\\" to method create_namespaced_policy\\\" % key\\n )\\n params[key] = val\\n del params['kwargs']\\n\\n # verify the required parameter 'body' is set\\n if ('body' not in params) or (params['body'] is None):\\n raise ValueError(\\\"Missing the required parameter `body` when calling `create_namespaced_policy`\\\")\\n # verify the required parameter 'namespace' is set\\n if ('namespace' not in params) or (params['namespace'] is None):\\n raise ValueError(\\\"Missing the required parameter `namespace` when calling `create_namespaced_policy`\\\")\\n\\n resource_path = '/oapi/v1/namespaces/{namespace}/policies'.replace('{format}', 'json')\\n path_params = {}\\n if 'namespace' in params:\\n path_params['namespace'] = params['namespace']\\n\\n query_params = {}\\n if 'pretty' in params:\\n query_params['pretty'] = params['pretty']\\n\\n header_params = {}\\n\\n form_params = []\\n local_var_files = {}\\n\\n body_params = None\\n if 'body' in params:\\n body_params = params['body']\\n\\n # HTTP header `Accept`\\n header_params['Accept'] = self.api_client.\\\\\\n select_header_accept(['application/json', 'application/yaml'])\\n if not header_params['Accept']:\\n del header_params['Accept']\\n\\n # HTTP header `Content-Type`\\n header_params['Content-Type'] = self.api_client.\\\\\\n select_header_content_type(['*/*'])\\n\\n # Authentication setting\\n auth_settings = []\\n\\n response = self.api_client.call_api(resource_path, 'POST',\\n path_params,\\n query_params,\\n header_params,\\n body=body_params,\\n post_params=form_params,\\n files=local_var_files,\\n response_type='V1Policy',\\n auth_settings=auth_settings,\\n callback=params.get('callback'))\\n return response\",\n \"def attach(profile, role, policy):\\n # Make sure the role exists.\\n if not exists(profile, role):\\n msg = \\\"No role '\\\" + str(role) + \\\"'.\\\"\\n raise ResourceDoesNotExist(msg)\\n\\n # Make sure the policy exists.\\n policy_data = policy_jobs.fetch_by_name(profile, policy)\\n if not policy_data:\\n msg = \\\"No policy '\\\" + str(policy) + \\\"'.\\\"\\n raise ResourceDoesNotExist(msg)\\n\\n # Get the policy's ARN.\\n policy_arn = policy_data[0][\\\"Arn\\\"]\\n \\n # Attach the policy to the role.\\n params = {}\\n params[\\\"profile\\\"] = profile\\n params[\\\"role\\\"] = role\\n params[\\\"policy\\\"] = policy_arn\\n utils.do_request(role_lib, \\\"attach_policy\\\", params)\",\n \"def __init__(__self__, *,\\n policy: pulumi.Input[str],\\n resource_arn: pulumi.Input[str]):\\n pulumi.set(__self__, \\\"policy\\\", policy)\\n pulumi.set(__self__, \\\"resource_arn\\\", resource_arn)\",\n \"def cleanup_policy_create(ctx: click.Context, **kwargs):\\n # TODO: use a click type for this check?\\n criteria_keys = {'downloaded', 'updated', 'regex'}\\n util.move_to_key(kwargs, 'criteria', criteria_keys)\\n\\n util.rename_keys(kwargs['criteria'], {\\n 'downloaded': 'lastDownloaded',\\n 'updated': 'lastBlobUpdated',\\n })\\n\\n subcommand_cleanup_policy.cmd_create(ctx.obj, **kwargs)\",\n \"def provision(self, policy):\\n client = self.connect(VAULT_TOKEN)\\n token = client.create_token(policies = [policy])\\n return token[\\\"auth\\\"][\\\"client_token\\\"]\",\n \"def test_resource_policy(self):\\n expected_actions = sorted(['rt:get', 'rt:put', 'rt:update', 'rt:delete'])\\n test_resource = ResourceTypeName.get()\\n test_policy_name = 'test_policy'\\n test_policy = create_test_ResourcePolicy('tp{i}', actions=expected_actions)\\n self.app.post(\\n f'/v1/resource/{test_resource}',\\n data=json.dumps({'actions': expected_actions}),\\n headers=admin_headers)\\n\\n # 400 returned when creating a policy with invalid actions\\n test_policy = create_test_ResourcePolicy('tp{i}', actions=['invalid:actions'])\\n resp = self.app.post(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n data=json.dumps({'policy': test_policy}),\\n headers=admin_headers\\n )\\n self.assertEqual(resp.status_code, 400)\\n resp = self.app.get(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n headers=admin_headers\\n )\\n self.assertEqual(resp.status_code, 404)\\n\\n # 201 return when creating a valid resource policy\\n test_policy = create_test_ResourcePolicy('tp{i}', actions=expected_actions)\\n resp = self.app.post(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n data=json.dumps({'policy': test_policy}),\\n headers=admin_headers\\n )\\n self.assertEqual(resp.status_code, 201)\\n resp = self.app.get(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n headers=admin_headers\\n )\\n self.assertJSONEqual(json.loads(resp.body)['policy'], test_policy)\\n\\n # 200 returned when modifying the policy with valid actions\\n test_policy = create_test_ResourcePolicy('tp{i}', actions=expected_actions[:2])\\n resp = self.app.put(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n data=json.dumps({'policy': test_policy}),\\n headers=admin_headers\\n )\\n self.assertEqual(resp.status_code, 200)\\n resp = self.app.get(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n headers=admin_headers\\n )\\n self.assertJSONEqual(json.loads(resp.body)['policy'], test_policy)\\n\\n # 400 returned when modifying the policy with invalid actions\\n test_policy2 = create_test_ResourcePolicy('tp{i}', actions=['invalid:actions'])\\n resp = self.app.put(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n data=json.dumps({'policy': test_policy2}),\\n headers=admin_headers\\n )\\n self.assertEqual(resp.status_code, 400)\\n resp = self.app.get(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n headers=admin_headers\\n )\\n self.assertJSONEqual(json.loads(resp.body)['policy'], test_policy)\\n\\n # delete the policy\\n resp = self.app.delete(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n headers=admin_headers\\n )\\n self.assertEqual(resp.status_code, 200)\\n resp = self.app.get(\\n f\\\"/v1/resource/{test_resource}/policy/{test_policy_name}\\\",\\n headers=admin_headers\\n )\\n self.assertEqual(resp.status_code, 404)\",\n \"def pre_network_policy_create(self, resource_dict):\\n pass\",\n \"def create_policy_request():\\n return {\\n 'public_key':\\n r'BBLewg4VqLR38b38daE7Fj\\\\/uhr543uGrEpyoPFgmFZK6EZ9g2XdK\\\\/i65RrSJ6sJ96aXD3DJHY3Me2GJQO9\\\\/ifjE=',\\n 'label':\\n 'Integration Test Policy',\\n 'operations': [{\\n 'sensor_id': 10,\\n 'action': 'SHARE',\\n }, {\\n 'sensor_id': 53,\\n 'action': 'BIN',\\n 'bins': [30.0, 60.0, 90.0]\\n }, {\\n 'sensor_id': 55,\\n 'action': 'MOVING_AVG',\\n 'interval': 300\\n }]\\n }\",\n \"def test_waf_policy_basic(self, resource_group):\\n # multi-line comment below\\n subscription = self.current_subscription()\\n blockpolicy = self.create_random_name(prefix='cli', length=24)\\n ruleName = self.create_random_name(prefix='cli', length=24)\\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {blockpolicy} --mode prevention'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], blockpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Prevention\\\")\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertIn('customRules', result)\\n self.assertIn('managedRules', result)\\n self.assertIn('id', result)\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n standardskupolicy = self.create_random_name(prefix='cli', length=24)\\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {standardskupolicy} --mode prevention --sku Standard_AzureFrontDoor'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], standardskupolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Prevention\\\")\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertIn('customRules', result)\\n self.assertIn('managedRules', result)\\n self.assertIn('id', result)\\n self.assertEqual(result['sku']['name'], \\\"Standard_AzureFrontDoor\\\")\\n\\n detectionredirectpolicy = self.create_random_name(prefix='cli', length=24)\\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {detectionredirectpolicy} --mode Detection --redirect-url http://www.microsoft.com --sku Premium_AzureFrontDoor'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], detectionredirectpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Detection\\\")\\n self.assertEqual(result['policySettings']['redirectUrl'], \\\"http://www.microsoft.com\\\")\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertIn('customRules', result)\\n self.assertIn('managedRules', result)\\n self.assertIn('id', result)\\n self.assertEqual(result['sku']['name'], \\\"Premium_AzureFrontDoor\\\")\\n\\n detectioncbcpolicy = self.create_random_name(prefix='cli', length=24)\\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {detectioncbcpolicy} --mode Detection --redirect-url http://www.microsoft.com --custom-block-response-status-code 406 --sku Classic_AzureFrontDoor'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], detectioncbcpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Detection\\\")\\n self.assertEqual(result['policySettings']['redirectUrl'], \\\"http://www.microsoft.com\\\")\\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 406)\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertIn('customRules', result)\\n self.assertIn('managedRules', result)\\n self.assertIn('id', result)\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n detectioncbbpolicy = self.create_random_name(prefix='cli', length=24)\\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {detectioncbbpolicy} --mode Detection --redirect-url http://www.microsoft.com --custom-block-response-status-code 406 --custom-block-response-body YiBvZHk='.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], detectioncbbpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Detection\\\")\\n self.assertEqual(result['policySettings']['enabledState'], \\\"Enabled\\\")\\n self.assertEqual(result['policySettings']['redirectUrl'], \\\"http://www.microsoft.com\\\")\\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 406)\\n self.assertEqual(result['policySettings']['customBlockResponseBody'], \\\"YiBvZHk=\\\")\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertIn('customRules', result)\\n self.assertIn('managedRules', result)\\n self.assertIn('id', result)\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n detectiondisabledpolicy = self.create_random_name(prefix='cli', length=24)\\n cmd = 'az network front-door waf-policy create -g {resource_group} -n {detectiondisabledpolicy} --mode Detection --disabled'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], detectiondisabledpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Detection\\\")\\n self.assertEqual(result['policySettings']['enabledState'], \\\"Disabled\\\")\\n self.assertEqual(result['policySettings']['redirectUrl'], None)\\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], None)\\n self.assertEqual(result['policySettings']['customBlockResponseBody'], None)\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertIn('customRules', result)\\n self.assertIn('managedRules', result)\\n self.assertIn('id', result)\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {detectiondisabledpolicy} --mode Detection'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertIn('customRules', result)\\n self.assertIn('managedRules', result)\\n self.assertIn('id', result)\\n self.assertEqual(result['policySettings']['enabledState'], \\\"Enabled\\\")\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --tags test=best'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], blockpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Prevention\\\")\\n # TODO uncomment once API support for updating tags is fixed :-O\\n # self.assertEqual(result['tags'], { 'test': 'best' })\\n self.assertIn('customRules', result)\\n self.assertIn('managedRules', result)\\n self.assertIn('id', result)\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --mode detection --sku Classic_AzureFrontDoor'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], blockpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Detection\\\")\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --mode prevention --redirect-url http://www.microsoft.com'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], blockpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Prevention\\\")\\n self.assertEqual(result['policySettings']['redirectUrl'], 'http://www.microsoft.com')\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --custom-block-response-status-code 406'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], blockpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Prevention\\\")\\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 406)\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --custom-block-response-status-code 405 --custom-block-response-body YiBvZHk='.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], blockpolicy)\\n self.assertEqual(result['policySettings']['mode'], \\\"Prevention\\\")\\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 405)\\n self.assertEqual(result['policySettings']['customBlockResponseBody'], \\\"YiBvZHk=\\\")\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy update -g {resource_group} -n {blockpolicy} --disabled'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], blockpolicy)\\n self.assertEqual(result['policySettings']['enabledState'], \\\"Disabled\\\")\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy show -g {resource_group} -n {blockpolicy}'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(result['name'], blockpolicy)\\n # spot check\\n self.assertEqual(result['policySettings']['enabledState'], \\\"Disabled\\\")\\n self.assertEqual(result['policySettings']['customBlockResponseStatusCode'], 405)\\n self.assertEqual(result['policySettings']['requestBodyCheck'], \\\"Enabled\\\")\\n self.assertEqual(result['sku']['name'], \\\"Classic_AzureFrontDoor\\\")\\n\\n cmd = 'az network front-door waf-policy list -g {resource_group}'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(len(result), 6)\\n blockPolicyObject = [policy for policy in result if policy['name'] == blockpolicy][0]\\n self.assertEqual(blockPolicyObject['name'], blockpolicy)\\n\\n cmd = 'az network front-door waf-policy delete -g {resource_group} -n {blockpolicy}'.format(**locals())\\n result = self.cmd(cmd)\\n\\n cmd = 'az network front-door waf-policy list -g {resource_group}'.format(**locals())\\n result = self.cmd(cmd).get_output_in_json()\\n self.assertEqual(len(result), 5)\\n self.assertEqual(len([policy for policy in result if policy['name'] == blockpolicy]), 0)\",\n \"def adapter_policy_create(handle, name, descr=\\\"\\\", parent_dn=\\\"org-root\\\"):\\n\\n from ucsmsdk.mometa.adaptor.AdaptorHostEthIfProfile import \\\\\\n AdaptorHostEthIfProfile\\n\\n obj = handle.query_dn(parent_dn)\\n if not obj:\\n raise ValueError(\\\"org '%s' does not exist\\\" % parent_dn)\\n\\n mo = AdaptorHostEthIfProfile(parent_mo_or_dn=obj, name=name, descr=descr)\\n handle.add_mo(mo, modify_present=True)\\n handle.commit()\\n return mo\",\n \"def test_create_ikepolicy_with_limited_params(self):\\r\\n resource = 'ikepolicy'\\r\\n cmd = ikepolicy.CreateIKEPolicy(test_cli20.MyApp(sys.stdout), None)\\r\\n name = 'ikepolicy1'\\r\\n auth_algorithm = 'sha1'\\r\\n encryption_algorithm = 'aes-128'\\r\\n ike_version = 'v1'\\r\\n phase1_negotiation_mode = 'main'\\r\\n pfs = 'group5'\\r\\n tenant_id = 'my-tenant'\\r\\n my_id = 'my-id'\\r\\n\\r\\n args = [name,\\r\\n '--tenant-id', tenant_id]\\r\\n\\r\\n position_names = ['name',\\r\\n 'auth_algorithm', 'encryption_algorithm',\\r\\n 'phase1_negotiation_mode',\\r\\n 'ike_version', 'pfs',\\r\\n 'tenant_id']\\r\\n\\r\\n position_values = [name,\\r\\n auth_algorithm, encryption_algorithm,\\r\\n phase1_negotiation_mode,\\r\\n ike_version, pfs,\\r\\n tenant_id]\\r\\n\\r\\n self._test_create_resource(resource, cmd, name, my_id, args,\\r\\n position_names, position_values)\",\n \"def setPolicy(self, value):\\n return self._set(policy=value)\",\n \"def put_group_policy(self, group_name, policy_name, policy_json):\\r\\n params = {'GroupName' : group_name,\\r\\n 'PolicyName' : policy_name,\\r\\n 'PolicyDocument' : policy_json}\\r\\n return self.get_response('PutGroupPolicy', params, verb='POST')\",\n \"def create_bucket(self, bucket_name, headers=None,\\r\\n location=Location.DEFAULT, policy=None):\\r\\n check_lowercase_bucketname(bucket_name)\\r\\n\\r\\n if policy:\\r\\n if headers:\\r\\n headers[self.provider.acl_header] = policy\\r\\n else:\\r\\n headers = {self.provider.acl_header : policy}\\r\\n if location == Location.DEFAULT:\\r\\n data = ''\\r\\n else:\\r\\n data = '' + \\\\\\r\\n location + ' '\\r\\n '%s '\\r\\n ' ' % location)\\r\\n response = self.make_request('PUT', bucket_name, headers=headers,\\r\\n data=data)\\r\\n body = response.read()\\r\\n if response.status == 409:\\r\\n raise self.provider.storage_create_error(\\r\\n response.status, response.reason, body)\\r\\n if response.status == 200:\\r\\n return self.bucket_class(self, bucket_name)\\r\\n else:\\r\\n raise self.provider.storage_response_error(\\r\\n response.status, response.reason, body)\",\n \"def update_policy(self):\\n pass\",\n \"def test_create_firewall_policy_with_all_params(self):\\r\\n resource = 'firewall_policy'\\r\\n cmd = firewallpolicy.CreateFirewallPolicy(test_cli20.MyApp(sys.stdout),\\r\\n None)\\r\\n name = 'my-name'\\r\\n description = 'my-desc'\\r\\n firewall_rules_arg = 'rule_id1 rule_id2'\\r\\n firewall_rules_res = ['rule_id1', 'rule_id2']\\r\\n tenant_id = 'my-tenant'\\r\\n my_id = 'myid'\\r\\n args = ['--description', description,\\r\\n '--shared',\\r\\n '--firewall-rules', firewall_rules_arg,\\r\\n '--audited',\\r\\n '--tenant-id', tenant_id,\\r\\n '--admin-state_up',\\r\\n name]\\r\\n position_names = ['name', ]\\r\\n position_values = [name, ]\\r\\n self._test_create_resource(resource, cmd, name, my_id, args,\\r\\n position_names, position_values,\\r\\n description=description, shared=True,\\r\\n firewall_rules=firewall_rules_res,\\r\\n audited=True, admin_state_up=True,\\r\\n tenant_id=tenant_id)\",\n \"def add(nitro, policypatset):\\r\\n __policypatset = NSPatset()\\r\\n __policypatset.set_name(policypatset.get_name())\\r\\n return __policypatset.add_resource(nitro)\",\n \"def update_policy(self, *args, **kwargs):\\r\\n pass\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: AssessmentPolicyArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def initialize_policies(self, policy_collection, options):\",\n \"def delete(self, policy_name):\\n path = self.vault.normalize(\\\"/sys/policies/acl/\\\" + policy_name)\\n address = self.vault.vault_adress + \\\"/v1\\\" + path\\n # Actually run vault\\n logging.info(\\\"Deleting the policy: %s\\\", address)\\n self.vault.requests_request(\\\"DELETE\\\", address, headers=self.vault.token_header)\",\n \"def add_to_resource_policy(self, permission: aws_cdk.aws_iam.PolicyStatement) -> None:\\n ...\",\n \"def CreateSecurityPolicy(self, request):\\n try:\\n params = request._serialize()\\n headers = request.headers\\n body = self.call(\\\"CreateSecurityPolicy\\\", params, headers=headers)\\n response = json.loads(body)\\n model = models.CreateSecurityPolicyResponse()\\n model._deserialize(response[\\\"Response\\\"])\\n return model\\n except Exception as e:\\n if isinstance(e, TencentCloudSDKException):\\n raise\\n else:\\n raise TencentCloudSDKException(type(e).__name__, str(e))\",\n \"def __init__(self, eid: str, name: str, weekly_salary: int, commission: int):\\n pay.CommissionPolicy.__init__(self, weekly_salary, commission)\\n super().__init__(eid, name)\",\n \"def _custom_policy(resource, expires=None, valid_after=None, ip_address=None):\\r\\n condition = {}\\r\\n if expires:\\r\\n condition[\\\"DateLessThan\\\"] = {\\\"AWS:EpochTime\\\": expires}\\r\\n if valid_after:\\r\\n condition[\\\"DateGreaterThan\\\"] = {\\\"AWS:EpochTime\\\": valid_after}\\r\\n if ip_address:\\r\\n if '/' not in ip_address:\\r\\n ip_address += \\\"/32\\\"\\r\\n condition[\\\"IpAddress\\\"] = {\\\"AWS:SourceIp\\\": ip_address}\\r\\n policy = {\\\"Statement\\\": [{\\r\\n \\\"Resource\\\": resource,\\r\\n \\\"Condition\\\": condition}]}\\r\\n return json.dumps(policy, separators=(\\\",\\\", \\\":\\\"))\",\n \"def create_vpc_if_policy_group(self, name, aep_name):\\n policy_group_mo = AccBndlGrp('uni/infra/funcprof/', name, lagT='node')\\n self.commit(policy_group_mo)\\n # if attachable entity profile does not exists, creates a new one\\n class_query = ClassQuery('infraAttEntityP')\\n class_query.propFilter = 'eq(infraAttEntityP.name, \\\"' + AEP_PREFIX + aep_name + '\\\")'\\n pd_list = self.moDir.query(class_query)\\n if len(pd_list) == 0:\\n vlan_pool_mo = self.create_vlan_pool(VLAN_POOL_PREFIX + aep_name, 'static')\\n DomP_mo = self.create_physical_domain(PD_PREFIX + aep_name, str(vlan_pool_mo.dn))\\n AttEntityP_mo = self.create_attachable_entity_profile(AEP_PREFIX + aep_name, str(DomP_mo.dn))\\n else:\\n AttEntityP_mo = pd_list[0]\\n # Assign attached entity profile\\n self.commit(\\n RsAttEntP(policy_group_mo.dn, tDn=str(AttEntityP_mo.dn))\\n )\\n # Assign interface policies. For non-defaults, check if is already created. If not, the system will create them\\n IfPolmo = self.moDir.lookupByDn('uni/infra/cdpIfP-CDP-ON')\\n if not IfPolmo:\\n IfPolmo = IfPol('uni/infra','CDP-ON',adminSt='enabled')\\n self.commit(IfPolmo)\\n self.commit(\\n RsCdpIfPol(policy_group_mo.dn, tnCdpIfPolName=IfPolmo.name)\\n )\\n self.commit(\\n RsHIfPol(policy_group_mo.dn, tnFabricHIfPolName='default')\\n )\\n self.commit(\\n RsL2IfPol(policy_group_mo.dn, tnL2IfPolName='default')\\n )\\n LagPolmo = self.moDir.lookupByDn('uni/infra/lacplagp-LACP')\\n if not LagPolmo:\\n LagPolmo = LagPol('uni/infra', 'LACP', mode='active')\\n self.commit(LagPolmo)\\n self.commit(\\n RsLacpPol(policy_group_mo.dn, tnLacpLagPolName=LagPolmo.name)\\n )\\n self.commit(\\n RsLldpIfPol(policy_group_mo.dn, tnLldpIfPolName='default')\\n )\\n self.commit(\\n RsMcpIfPol(policy_group_mo.dn, tnMcpIfPolName='default')\\n )\\n self.commit(\\n RsMonIfInfraPol(policy_group_mo.dn, tnMonInfraPolName='default')\\n )\\n self.commit(\\n RsStormctrlIfPol(policy_group_mo.dn, tnStormctrlIfPolName='default')\\n )\\n self.commit(\\n RsStpIfPol(policy_group_mo.dn, tnStpIfPolName='default')\\n )\\n return policy_group_mo\",\n \"def _set_restricted_policy(environ, bag):\\n username = environ['tiddlyweb.usersign']['name']\\n if username == 'GUEST':\\n return\\n bag.policy.owner = username\\n # accept does not matter here\\n for constraint in ['read', 'write', 'create', 'delete', 'manage']:\\n setattr(bag.policy, constraint, [username])\\n return\",\n \"def idle_blockchain_policy(blockchain_alice, blockchain_bob):\\n random_label = b'label://' + os.urandom(32)\\n policy = blockchain_alice.create_policy(blockchain_bob, label=random_label, m=2, n=3)\\n return policy\"\n]"},"negative_scores":{"kind":"list like","value":["0.69018525","0.6894368","0.65139604","0.6491852","0.6477794","0.63088816","0.6284742","0.62571865","0.62571806","0.6177285","0.6173109","0.6170149","0.6067969","0.60238564","0.59549844","0.5883088","0.58814156","0.58473706","0.58184075","0.5796063","0.57722455","0.57471603","0.57362765","0.5713319","0.57090175","0.56990856","0.56546146","0.5627509","0.5626936","0.5598759","0.5597521","0.55584294","0.55499977","0.55325997","0.55325997","0.55248874","0.5519052","0.55089474","0.55054796","0.54517585","0.5433395","0.54170465","0.541502","0.54112375","0.5406207","0.5379803","0.53543746","0.53528816","0.53496337","0.5338841","0.5331283","0.5311001","0.5294338","0.52621955","0.5233963","0.52208394","0.52105176","0.52057374","0.52051646","0.51818144","0.5180329","0.51801825","0.51711315","0.51613706","0.5155746","0.5139749","0.5139183","0.5137825","0.51331604","0.5128421","0.5120713","0.511003","0.51072806","0.5096977","0.5074047","0.50724226","0.5068912","0.5064765","0.5061268","0.50567293","0.5056669","0.5056669","0.5033657","0.5020115","0.501315","0.5011721","0.5009706","0.50082237","0.50020254","0.49976635","0.4991622","0.4979632","0.4974872","0.4966805","0.49620032","0.49606735","0.4957861","0.49480036","0.49443802","0.49400082"],"string":"[\n \"0.69018525\",\n \"0.6894368\",\n \"0.65139604\",\n \"0.6491852\",\n \"0.6477794\",\n \"0.63088816\",\n \"0.6284742\",\n \"0.62571865\",\n \"0.62571806\",\n \"0.6177285\",\n \"0.6173109\",\n \"0.6170149\",\n \"0.6067969\",\n \"0.60238564\",\n \"0.59549844\",\n \"0.5883088\",\n \"0.58814156\",\n \"0.58473706\",\n \"0.58184075\",\n \"0.5796063\",\n \"0.57722455\",\n \"0.57471603\",\n \"0.57362765\",\n \"0.5713319\",\n \"0.57090175\",\n \"0.56990856\",\n \"0.56546146\",\n \"0.5627509\",\n \"0.5626936\",\n \"0.5598759\",\n \"0.5597521\",\n \"0.55584294\",\n \"0.55499977\",\n \"0.55325997\",\n \"0.55325997\",\n \"0.55248874\",\n \"0.5519052\",\n \"0.55089474\",\n \"0.55054796\",\n \"0.54517585\",\n \"0.5433395\",\n \"0.54170465\",\n \"0.541502\",\n \"0.54112375\",\n \"0.5406207\",\n \"0.5379803\",\n \"0.53543746\",\n \"0.53528816\",\n \"0.53496337\",\n \"0.5338841\",\n \"0.5331283\",\n \"0.5311001\",\n \"0.5294338\",\n \"0.52621955\",\n \"0.5233963\",\n \"0.52208394\",\n \"0.52105176\",\n \"0.52057374\",\n \"0.52051646\",\n \"0.51818144\",\n \"0.5180329\",\n \"0.51801825\",\n \"0.51711315\",\n \"0.51613706\",\n \"0.5155746\",\n \"0.5139749\",\n \"0.5139183\",\n \"0.5137825\",\n \"0.51331604\",\n \"0.5128421\",\n \"0.5120713\",\n \"0.511003\",\n \"0.51072806\",\n \"0.5096977\",\n \"0.5074047\",\n \"0.50724226\",\n \"0.5068912\",\n \"0.5064765\",\n \"0.5061268\",\n \"0.50567293\",\n \"0.5056669\",\n \"0.5056669\",\n \"0.5033657\",\n \"0.5020115\",\n \"0.501315\",\n \"0.5011721\",\n \"0.5009706\",\n \"0.50082237\",\n \"0.50020254\",\n \"0.49976635\",\n \"0.4991622\",\n \"0.4979632\",\n \"0.4974872\",\n \"0.4966805\",\n \"0.49620032\",\n \"0.49606735\",\n \"0.4957861\",\n \"0.49480036\",\n \"0.49443802\",\n \"0.49400082\"\n]"},"document_score":{"kind":"string","value":"0.600187"},"document_rank":{"kind":"string","value":"14"}}},{"rowIdx":8583,"cells":{"query":{"kind":"string","value":"Creates a subscription to a region for a tenancy."},"document":{"kind":"string","value":"def create_region_subscription(self, create_region_subscription_details, tenancy_id, **kwargs):\n resource_path = \"/tenancies/{tenancyId}/regionSubscriptions\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_region_subscription got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tenancyId\": tenancy_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_region_subscription_details,\n response_type=\"RegionSubscription\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_region_subscription_details,\n response_type=\"RegionSubscription\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_subscription(self,\n body):\n\n return super().new_api_call_builder.request(\n RequestBuilder().server('default')\n .path('/v2/subscriptions')\n .http_method(HttpMethodEnum.POST)\n .header_param(Parameter()\n .key('Content-Type')\n .value('application/json'))\n .body_param(Parameter()\n .value(body))\n .header_param(Parameter()\n .key('accept')\n .value('application/json'))\n .body_serializer(APIHelper.json_serialize)\n .auth(Single('global'))\n ).response(\n ResponseHandler()\n .deserializer(APIHelper.json_deserialize)\n .is_api_response(True)\n .convertor(ApiResponse.create)\n ).execute()","def test_create_subscription(self):\n pass","def post_create_subscription(\n self, response: pubsub.Subscription\n ) -> pubsub.Subscription:\n return response","def _create_subscription(self):\n try:\n self.client.create_subscription(\n name=self.subscription_path, topic=self.topic_path\n )\n except NotFound:\n # suitable topic does not exist in the Pitt-Google project\n raise ValueError(\n (\n f\"A subscription named {self.subscription_name} does not exist\"\n \"in the Google Cloud Platform project \"\n f\"{settings.GOOGLE_CLOUD_PROJECT}, \"\n \"and one cannot be automatically create because Pitt-Google \"\n \"does not publish a public topic with the same name.\"\n )\n )\n else:\n self._log_and_print(f\"Created subscription: {self.subscription_path}\")","def handle_create(self):\n subscription = self.client().subscription(\n self.properties[self.QUEUE_NAME],\n subscriber=self.properties[self.SUBSCRIBER],\n ttl=self.properties[self.TTL],\n options=self.properties[self.OPTIONS]\n )\n self.resource_id_set(subscription.id)","def create_subscription(connection, project_id, body, fields=None, error_msg=None):\n return connection.post(\n url=f'{connection.base_url}/api/subscriptions',\n params={'fields': fields},\n headers={'X-MSTR-ProjectID': project_id},\n json=body,\n )","def list_region_subscriptions(self, tenancy_id, **kwargs):\n resource_path = \"/tenancies/{tenancyId}/regionSubscriptions\"\n method = \"GET\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"list_region_subscriptions got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tenancyId\": tenancy_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"list[RegionSubscription]\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"list[RegionSubscription]\")","def do_create_subscription(csp: CloudProviderInterface, environment_id=None):\n environment = Environments.get(environment_id)\n payload = build_subscription_payload(environment)\n try:\n csp.create_subscription(payload)\n except GeneralCSPException as e:\n app.logger.warning(\n \"Unable to create subscription for environment %s.\", environment.id,\n )\n raise e","def add_subscription(self):\n schema = schemas.load(schemas.Subscription, self.request)\n subscription = self.customer.add_subscription(**schema)\n self.request.db.flush()\n self.request.response.status_int = 201\n return {'abonnement': subscription}","def create_subscription(self, client_URI_endpoint, event_destination_id,\n name, subscription_context):\n self.client_URI_endpoints[client_URI_endpoint] = \\\n Event(event_destination_id, name, subscription_context)\n self.write_subscriptions_to_tmp(self.client_URI_endpoints)","def create_subscription_in_snuba(query_subscription_id, **kwargs):\n try:\n subscription = QuerySubscription.objects.get(id=query_subscription_id)\n except QuerySubscription.DoesNotExist:\n metrics.incr(\"snuba.subscriptions.create.subscription_does_not_exist\")\n return\n if subscription.status != QuerySubscription.Status.CREATING.value:\n metrics.incr(\"snuba.subscriptions.create.incorrect_status\")\n return\n if subscription.subscription_id is not None:\n metrics.incr(\"snuba.subscriptions.create.already_created_in_snuba\")\n # This mostly shouldn't happen, but it's possible that a subscription can get\n # into this state. Just attempt to delete the existing subscription and then\n # create a new one.\n try:\n _delete_from_snuba(\n QueryDatasets(subscription.snuba_query.dataset), subscription.subscription_id\n )\n except SnubaError:\n logger.exception(\"Failed to delete subscription\")\n\n subscription_id = _create_in_snuba(subscription)\n subscription.update(\n status=QuerySubscription.Status.ACTIVE.value, subscription_id=subscription_id\n )","def test_create_subscription_template(self):\n pass","def subscribe(request):\n address = request.POST.get('address')\n\n new_sub = Subscription(**{\n \"address\": address\n })\n new_sub.save()\n\n return HttpResponse(json.dumps({\n \"status\": \"success\"\n }, default=helpers.json_custom_parser), content_type='application/json')","def subscribe(self, **subscription_request):\n return self.subscribe_impl(mode='subscribe', **subscription_request)","def create_subscription(self, user, standard):\r\n\r\n subscription = self.create(\r\n user=user,\r\n standard=standard,\r\n )\r\n\r\n return subscription","def create_subscription(self, organization, collaborations, contractors):\r\n\r\n subscription = self.create(\r\n organization=organization,\r\n collaborations=collaborations,\r\n contractors=contractors,\r\n partner_discovery=partner_discovery,\r\n )\r\n return subscription","def subscription(self, uuid):\r\n return subs.Subscription(self, uuid)","def CreateSubscribeTransaction(self, dest, once=False):\n c = Subscribe(dest, self.node_id, once)\n self.connections.append((\"REACTIVE\", c))\n return c","def subscription(self):\r\n return SubscriptionResource(self)","def subscribePost() -> object:\n log = logging.getLogger(__name__)\n db = Db()\n\n body = request.get_json()\n\n if body is None:\n return jsonify({\"error\": \"json body is required\"}), HTTPStatus.HTTPStatus.BAD_REQUEST\n\n if not('datasetId') in body:\n return jsonify({\"error\": \"datasetId is a required attribute\"}), HTTPStatus.HTTPStatus.BAD_REQUEST\n\n if not('notificationUrl') in body:\n return jsonify({\"error\": \"notificationUrl is a required attribute\"}), HTTPStatus.HTTPStatus.BAD_REQUEST\n\n\n subscription = db.Subscriptions(\n datasetId=body['datasetId'],\n notificationUrl=body['notificationUrl']\n )\n\n subscription.save()\n\n subscription = json.loads(subscription.to_json())\n subscription['id'] = subscription['_id'][\"$oid\"]\n subscription.pop(\"_id\")\n log.debug(\"subscription created\")\n\n return jsonify(subscription), HTTPStatus.CREATED","def post(self):\n data = request.json\n return new_subscription(data=data)","def post(self, orgname):\n permission = AdministerOrganizationPermission(orgname)\n request_data = request.get_json()\n subscription_id = request_data[\"subscription_id\"]\n if permission.can():\n organization = model.organization.get_organization(orgname)\n user = get_authenticated_user()\n account_number = marketplace_users.get_account_number(user)\n subscriptions = marketplace_subscriptions.get_list_of_subscriptions(account_number)\n\n if subscriptions is None:\n abort(401, message=\"no valid subscriptions present\")\n\n user_subscription_ids = [int(subscription[\"id\"]) for subscription in subscriptions]\n if int(subscription_id) in user_subscription_ids:\n try:\n model.organization_skus.bind_subscription_to_org(\n user_id=user.id, subscription_id=subscription_id, org_id=organization.id\n )\n return \"Okay\", 201\n except model.OrgSubscriptionBindingAlreadyExists:\n abort(400, message=\"subscription is already bound to an org\")\n else:\n abort(401, message=f\"subscription does not belong to {user.username}\")\n\n abort(401)","def create_subscription(chid, use_time=False, use_ctrl=False,\n mask=None, callback=None):\n mask = mask or DEFAULT_SUBSCRIPTION_MASK\n\n ftype = promote_type(chid, use_ctrl=use_ctrl, use_time=use_time)\n\n uarg = ctypes.py_object(callback)\n evid = ctypes.c_void_p()\n poll()\n ret = libca.ca_create_subscription(ftype, 0, chid, mask,\n _CB_EVENT, uarg, ctypes.byref(evid))\n PySEVCHK('create_subscription', ret)\n\n poll()\n return (_CB_EVENT, uarg, evid)","def createTenant(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def __call__(\n self,\n request: pubsub.Subscription,\n *,\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\n timeout: Optional[float] = None,\n metadata: Sequence[Tuple[str, str]] = (),\n ) -> pubsub.Subscription:\n\n http_options: List[Dict[str, str]] = [\n {\n \"method\": \"put\",\n \"uri\": \"/v1/{name=projects/*/subscriptions/*}\",\n \"body\": \"*\",\n },\n ]\n request, metadata = self._interceptor.pre_create_subscription(\n request, metadata\n )\n pb_request = pubsub.Subscription.pb(request)\n transcoded_request = path_template.transcode(http_options, pb_request)\n\n # Jsonify the request body\n\n body = json_format.MessageToJson(\n transcoded_request[\"body\"],\n including_default_value_fields=False,\n use_integers_for_enums=True,\n )\n uri = transcoded_request[\"uri\"]\n method = transcoded_request[\"method\"]\n\n # Jsonify the query params\n query_params = json.loads(\n json_format.MessageToJson(\n transcoded_request[\"query_params\"],\n including_default_value_fields=False,\n use_integers_for_enums=True,\n )\n )\n query_params.update(self._get_unset_required_fields(query_params))\n\n query_params[\"$alt\"] = \"json;enum-encoding=int\"\n\n # Send the request\n headers = dict(metadata)\n headers[\"Content-Type\"] = \"application/json\"\n response = getattr(self._session, method)(\n \"{host}{uri}\".format(host=self._host, uri=uri),\n timeout=timeout,\n headers=headers,\n params=rest_helpers.flatten_query_params(query_params, strict=True),\n data=body,\n )\n\n # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception\n # subclass.\n if response.status_code >= 400:\n raise core_exceptions.from_http_response(response)\n\n # Return the response\n resp = pubsub.Subscription()\n pb_resp = pubsub.Subscription.pb(resp)\n\n json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)\n resp = self._interceptor.post_create_subscription(resp)\n return resp","def create_subscription(self, device_type):\n url = '{}/v2/subscriptions'.format(self.url)\n device_type = device_type.split('.')[0]\n device_pattern = \"urn:ngsi-ld:{}:*\".format(device_type)\n description = \"Notify QuantumLeap with {}\".format(device_type)\n data = {\n \"description\": description,\n \"subject\": {\n \"entities\": [\n {\n \"idPattern\": device_pattern\n }\n ]\n },\n \"notification\": {\n \"http\": {\n \"url\": \"http://quantumleap:8668/v2/notify\"\n },\n \"metadata\": [\"dateCreated\", \"dateModified\"]\n },\n \"throttling\": 1\n }\n return self.post(url, data=json.dumps(data), headers=self.headers_json)","def create_pubsub_subscription(client, project, topic, name):\n topic_name = pubsub.topic_name(project, topic)\n full_name = pubsub.subscription_name(project, name)\n if client.get_subscription(full_name):\n return\n\n client.create_subscription(full_name, topic_name)","def register(self, region=None, payload=None):\n return self._put_response_body([], payload=payload)","def test_create_response_descriptor_subscriptions_subscription_subscription_resource(self):\n pass","def test_create_subscription(self):\n try:\n self.arb.create_subscription(\n trial_occurrences=4,\n interval_length=1,\n interval_unit=arb.MONTHS_INTERVAL,\n start_date=u\"2008-09-09\",\n amount=39.99,\n card_number=u\"4222222222222\",\n expiration_date=u\"2009-10\",\n bill_first_name=u\"Michael\",\n bill_last_name=u\"Pool\"\n )\n except KeyError:\n pass\n self.arb.create_subscription(\n trial_amount=5.00,\n trial_occurrences=4,\n interval_length=1,\n interval_unit=arb.MONTHS_INTERVAL,\n start_date=u\"2008-09-09\",\n amount=39.99,\n card_number=u\"4222222222222\",\n expiration_date=u\"2009-10\",\n bill_first_name=u\"Michael\",\n bill_last_name=u\"Pool\"\n )\n self.arb.create_subscription(\n trial_amount=5.00,\n trial_occurrences=4,\n interval_length=1,\n interval_unit=arb.MONTHS_INTERVAL,\n start_date=u\"2008-09-09\",\n amount=39.99,\n card_number=u\"4222222222222\",\n expiration_date=u\"2009-10\",\n ship_first_name=u\"valentino\",\n first_name=u\"valentino\",\n bill_first_name=u\"valentino\",\n bill_last_name=u\"Pool\",\n driver_number=u\"55555\",\n driver_state=u\"CA\",\n driver_birth=u\"1990-09-09\"\n )","def test_create_response_descriptor_subscriptions_subscription_subscription_resource_spaces(self):\n pass","def subscribe(self, request):\n email = self.cleaned_data.get('email')\n\n email_name, domain_part = email.rsplit('@', 1)\n domain_name = '@' + domain_part\n email_domain, created = Domain.objects.get_or_create(name=domain_name)\n\n subscriber, created = Subscriber.objects.get_or_create(email=email, mailing_list=self.mailing_list, defaults={\n 'domain': email_domain\n })\n subscriber.status = Status.PENDING\n subscriber.optin_ip_address = get_client_ip(request)\n subscriber.optin_date = timezone.now()\n subscriber.save()\n\n if not created:\n subscriber.tokens.filter(description='confirm_subscription').delete()\n\n token = subscriber.tokens.create(description='confirm_subscription')\n current_site = get_current_site(request)\n protocol = 'https' if request.is_secure() else 'http'\n domain = current_site.domain\n path = reverse('subscribers:confirm_double_optin_token', kwargs={\n 'mailing_list_uuid': self.mailing_list.uuid,\n 'token': token.text\n })\n confirm_link = '%s://%s%s' % (protocol, domain, path)\n\n confirm_email = self.mailing_list.get_confirm_email_template()\n confirm_email.send(subscriber.get_email(), {\n 'confirm_link': confirm_link\n })\n\n return subscriber","def _create_sub(name, rostype, topic_callback, *args, **kwargs):\n # counting subscriber instance per topic name\n if name in TopicBack.sub_instance_count.keys():\n TopicBack.sub_instance_count[name] += 1\n else:\n TopicBack.sub_instance_count[name] = 1\n\n return rospy.Subscriber(name, rostype, topic_callback, *args, **kwargs)","def post_get_subscription(\n self, response: pubsub.Subscription\n ) -> pubsub.Subscription:\n return response","def __init__(__self__,\n resource_name: str,\n args: EventSubscriptionArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def PostSubscription(self, request, context):\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\n context.set_details('Method not implemented!')\n raise NotImplementedError('Method not implemented!')","def subscription_factory_fixture():\n def _factory(capability):\n sub = Subscription()\n sub.capability = capability\n return sub\n return _factory","def get_subscription(self):\n if not hasattr(self, '_subscription'):\n self._subscription = self.admin.subscriptions.select_related('plan').get_overlapping(\n self.admin_id, DateRange(self.period, self.period_end, bounds='[]'))\n return self._subscription","def public_subscribe_subscription(\n user_id: str,\n body: Optional[SubscribeRequest] = None,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = PublicSubscribeSubscription.create(\n user_id=user_id,\n body=body,\n namespace=namespace,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","def subscribe(config, accounts, region, merge, debug):\n config = validate.callback(config)\n subscription = config.get('subscription')\n\n if subscription is None:\n log.error(\"config file: logs subscription missing\")\n sys.exit(1)\n\n def converge_destination_policy(client, config):\n destination_name = subscription['destination-arn'].rsplit(':', 1)[-1]\n try:\n extant_destinations = client.describe_destinations(\n DestinationNamePrefix=destination_name).get('destinations')\n except ClientError:\n log.error(\"Log group destination not found: %s\",\n subscription['destination-arn'])\n sys.exit(1)\n\n account_ids = set()\n for a in accounts:\n if isinstance(a['role'], list):\n account_ids.add(a['role'][-1].split(':')[4])\n else:\n account_ids.add(a['role'].split(':')[4])\n\n if merge:\n for d in extant_destinations:\n if d['destinationName'] == destination_name:\n for s in json.loads(d['accessPolicy']):\n if s['Sid'] == 'CrossAccountDelivery':\n account_ids.update(s['Principal']['AWS'])\n\n client.put_destination_policy(\n destinationName=destination_name,\n accessPolicy=json.dumps({\n 'Statement': [{\n 'Action': 'logs:PutSubscriptionFilter',\n 'Effect': 'Allow',\n 'Principal': {'AWS': list(account_ids)},\n 'Resource': subscription['destination-arn'],\n 'Sid': 'CrossAccountDelivery'}]}))\n\n def subscribe_account(t_account, subscription, region):\n session = get_session(t_account['role'], region)\n client = session.client('logs')\n distribution = subscription.get('distribution', 'ByLogStream')\n role_arn = account.get('subscription-role')\n\n for g in account.get('groups'):\n if (g.endswith('*')):\n g = g.replace('*', '')\n paginator = client.get_paginator('describe_log_groups')\n allLogGroups = paginator.paginate(logGroupNamePrefix=g).build_full_result()\n for l in allLogGroups['logGroups']:\n _process_subscribe_group(\n client, l['logGroupName'], subscription, distribution, role_arn)\n else:\n _process_subscribe_group(client, g, subscription, distribution, role_arn)\n\n if subscription.get('managed-policy'):\n if subscription.get('destination-role'):\n session = get_session(subscription['destination-role'], region)\n else:\n session = boto3.Session()\n converge_destination_policy(session.client('logs'), config)\n\n executor = debug and MainThreadExecutor or ThreadPoolExecutor\n\n with executor(max_workers=32) as w:\n futures = {}\n for account in config.get('accounts', ()):\n if accounts and account['name'] not in accounts:\n continue\n futures[w.submit(subscribe_account, account, subscription, region)] = account\n\n for f in as_completed(futures):\n account = futures[f]\n if f.exception():\n log.error(\"Error on account %s err: %s\",\n account['name'], f.exception())\n log.info(\"Completed %s\", account['name'])","def _InsertSubscription(self,\n id='python.gcal.test%40gmail.com'):\n print 'Subscribing to the calendar with ID: %s' % id\n calendar = gdata.calendar.data.CalendarEntry()\n calendar.id = atom.data.Id(text=id)\n returned_calendar = self.cal_client.InsertCalendarSubscription(calendar)\n return returned_calendar","def test_aws_service_api_validate_subscription_post(self):\n pass","async def public_subscribe_subscription_async(\n user_id: str,\n body: Optional[SubscribeRequest] = None,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = PublicSubscribeSubscription.create(\n user_id=user_id,\n body=body,\n namespace=namespace,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )","def get_subscription(self):\n return self.request({\n 'path': '/' + UUID + '/subscription'})","def setup_test_tenant(self):\n self.test_tenant = rand_name('test_tenant_')\n self.test_description = rand_name('desc_')\n resp, self.tenant = self.client.create_tenant(\n name=self.test_tenant,\n description=self.test_description)\n self.tenants.append(self.tenant)","def set_endpoint_subscription_id(\n *, login_manager: LoginManager, endpoint_id: str, subscription_id: Optional[str]\n) -> None:\n transfer_client = login_manager.get_transfer_client()\n\n res = transfer_client.put(\n f\"/endpoint/{endpoint_id}/subscription\",\n data={\"subscription_id\": subscription_id},\n )\n formatted_print(res, text_format=FORMAT_TEXT_RAW, response_key=\"message\")","def test_issue_add_subscription(self):\n pass","def create_topic ( sns_conn, topicname, subscription_email ) :\n t_result = sns_conn.create_topic( topicname )\n topic = t_result[ 'CreateTopicResponse' ][ 'CreateTopicResult' ][ 'TopicArn' ]\n sns_conn.subscribe( topic, 'email', subscription_email )\n\n return topic","def activate_subscription(**kwargs):\n sub, created = Subscription.objects.get_or_create(**kwargs)\n # check if it already existed and was deactivated\n if not created and not sub.active:\n sub.active = True\n sub.save()\n created = True\n return sub, created","def create(self, validated_data):\n subscription = super().create(validated_data)\n subscription.send_verification_email()\n return subscription","def email_subscription(self):\n from hubspot3.email_subscription import EmailSubscriptionClient\n\n return EmailSubscriptionClient(**self.auth, **self.options)","async def create_subscription(user: int, redis: RedisDB):\n subscription_data = {\n \"subscriber_id\": user.id,\n \"cost\": str(os.getenv(\"AMOUNT\")),\n \"currency\": \"NANO\",\n \"period\": int(os.getenv(\"PERIOD\"))\n }\n json_data = json.dumps(subscription_data)\n r = requests.post(f\"{os.getenv('API_ENDPOINT')}create_subscription?token={os.getenv('NR_TOKEN')}\", json_data)\n rx = r.json()\n await redis.set(user.id, rx['subscription_id'])\n return r.json()","async def create_subscription(self, installed_app_id: str, data: dict) -> dict:\r\n return await self.post(\r\n API_SUBSCRIPTIONS.format(installed_app_id=installed_app_id), data\r\n )","def create_region(self, region_ref):\n raise exception.NotImplemented() # pragma: no cover","def test_get_subscription(self):\n pass","def subscribe(self, request: Request) -> Response:\n ids = request.data.get(\"ids\", None)\n session_id = request.data.get(\"session_id\")\n content_type = ContentType.objects.get_for_model(self.get_queryset().model)\n user = request.user if request.user.is_authenticated else get_anonymous_user()\n subscription = Subscription.objects.create(user=user, session_id=session_id)\n\n if ids is None:\n # Subscribe to the whole table.\n subscription.subscribe(\n content_type, [Observer.ALL_IDS], (ChangeType.CREATE, ChangeType.DELETE)\n )\n else:\n # Verify all ids exists and user has permissions to view them.\n for id in ids:\n if not self.user_has_permission(id, request.user):\n raise NotFound(f\"Item {id} does not exist\")\n\n change_types = (ChangeType.UPDATE, ChangeType.DELETE, ChangeType.CREATE)\n subscription.subscribe(content_type, ids, change_types)\n\n resp = {\"subscription_id\": subscription.subscription_id}\n return Response(resp)","def subscribe(self, namespace, sub_strings=None):\n req = JSONRPCRequest('subscribe', [namespace, sub_strings])\n result = yield self._send(req)\n self._cache_jsonrpc_request(req)\n raise tornado.gen.Return(result)","def create_tenant(tenant_name, description, enabled, auth_admin_url, admin_token):\n keystone = get_client(auth_admin_url, admin_token)\n tenant = keystone.tenants.create(tenant_name=tenant_name, description=description, enabled=enabled)\n print tenant\n return tenant.to_dict()","def platform_subscribe_subscription(\n user_id: str,\n body: Optional[PlatformSubscribeRequest] = None,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = PlatformSubscribeSubscription.create(\n user_id=user_id,\n body=body,\n namespace=namespace,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","async def create_and_subscribe(user_id):\n client = gql(\n query=Query,\n mutation=Mutation,\n subscription=Subscription,\n consumer_attrs={\"strict_ordering\": True, \"confirm_subscriptions\": True},\n )\n await client.connect_and_init()\n\n sub_id = await client.send(\n msg_type=\"start\",\n payload={\n \"query\": textwrap.dedent(\n \"\"\"\n subscription op_name($user_id: UserId) {\n on_chat_message_sent(user_id: $user_id) { event }\n }\n \"\"\"\n ),\n \"variables\": {\"user_id\": user_id},\n \"operationName\": \"op_name\",\n },\n )\n\n # Receive the subscription confirmation message.\n resp = await client.receive(assert_id=sub_id, assert_type=\"data\")\n assert resp == {\"data\": None}\n\n return sub_id, client","def create_subscription(post, user, sub_type=None, update=False):\n subs = Subscription.objects.filter(post=post.root, user=user)\n sub = subs.first()\n\n default = Subscription.TYPE_MAP.get(user.profile.message_prefs,\n Subscription.LOCAL_MESSAGE)\n\n empty = sub_type is None\n # Get the current sub type from what's given or the existing sub\n sub_type = None if empty else sub_type\n # No type has been given so default\n sub_type = sub_type or default\n\n # Ensure the sub type is not set to something wrote\n if sub and update:\n # Update an existing subscription\n sub.type = sub_type\n sub.save()\n else:\n # Drop all existing subscriptions for the user by default.\n subs.delete()\n Subscription.objects.create(post=post.root, user=user, type=sub_type)\n\n # Recompute subscription count\n subs_count = Subscription.objects.filter(post=post.root).exclude(type=Subscription.NO_MESSAGES).count()\n\n # Update root subscription counts.\n Post.objects.filter(pk=post.root.pk).update(subs_count=subs_count)","def pre_create_subscription(\n self, request: pubsub.Subscription, metadata: Sequence[Tuple[str, str]]\n ) -> Tuple[pubsub.Subscription, Sequence[Tuple[str, str]]]:\n return request, metadata","def __init__(__self__, *,\n cognitive_service_region: Optional[pulumi.Input[str]] = None,\n cognitive_service_resource_id: Optional[pulumi.Input[str]] = None,\n cognitive_service_subscription_key: Optional[pulumi.Input[str]] = None,\n default_locale: Optional[pulumi.Input[str]] = None,\n id: Optional[pulumi.Input[str]] = None,\n provider_name: Optional[pulumi.Input[str]] = None):\n if cognitive_service_region is not None:\n pulumi.set(__self__, \"cognitive_service_region\", cognitive_service_region)\n if cognitive_service_resource_id is not None:\n pulumi.set(__self__, \"cognitive_service_resource_id\", cognitive_service_resource_id)\n if cognitive_service_subscription_key is not None:\n pulumi.set(__self__, \"cognitive_service_subscription_key\", cognitive_service_subscription_key)\n if default_locale is not None:\n pulumi.set(__self__, \"default_locale\", default_locale)\n if id is not None:\n pulumi.set(__self__, \"id\", id)\n if provider_name is not None:\n pulumi.set(__self__, \"provider_name\", provider_name)","def create_hosted_office(sub, pw): \r\n s1 = ims.hostedOfficeSubscriber(sub)\r\n session = {}\r\n session['emaSession'] = ema.emaLogin()\r\n session['sub_pw'] = pw # Get password from xls sheet and put here\r\n\r\n result = s1.subscriberCreate(session)\r\n ema.ema_logout(session['emaSession'])\r\n return result","def test_get_template_subscription(self):\n pass","def create(self, validated_data):\n\n region = CourierRegions.objects.create(\n courier_id=Courier.objects.get(courier_id=validated_data['courier_id']),\n region=validated_data['region']\n )\n return region","def test_get_subscription_template(self):\n pass","def event_create(tenant_id, user_id=None):","def get_tenant_id_resource_client(self):\n\n __logger__.info(\"Creating TenantIdResource\")\n\n return TenantIdResourceClient(protocol=self.api_protocol, host=self.api_host,\n port=self.api_port, resource=self.api_resource, headers=self.headers)","def create_tenant(tenant):\n exists = identity.Tenant.query.filter_by(name=tenant.name).first()\n if exists:\n abort(409, \"Tenant Already Exists\")\n db.session.add(tenant)\n db.session.commit()\n return tenant.id","async def platform_subscribe_subscription_async(\n user_id: str,\n body: Optional[PlatformSubscribeRequest] = None,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = PlatformSubscribeSubscription.create(\n user_id=user_id,\n body=body,\n namespace=namespace,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )","def test_index_response_descriptor_subscriptions_subscription_subscription_resource(self):\n pass","def test_subscribe(self):\n self.service.clientConnected()\n self.service.subscribe(u'url', None)\n pubsubClient = self.service.pubsubClient\n self.assertIn(u'url', pubsubClient.subscriptions)","def copy_to_region(self, region, name=None):\r\n if region.name == self.region:\r\n raise BotoClientError('Unable to copy to the same Region')\r\n conn_params = self.connection.get_params()\r\n rconn = region.connect(**conn_params)\r\n sg = rconn.create_security_group(name or self.name, self.description)\r\n source_groups = []\r\n for rule in self.rules:\r\n grant = rule.grants[0]\r\n for grant in rule.grants:\r\n if grant.name:\r\n if grant.name not in source_groups:\r\n source_groups.append(grant.name)\r\n sg.authorize(None, None, None, None, grant)\r\n else:\r\n sg.authorize(rule.ip_protocol, rule.from_port, rule.to_port,\r\n grant.cidr_ip)\r\n return sg","def fixture_make_bucket(request):\n def _make_bucket(resource, bucket_name, region_name=None):\n if not region_name:\n region_name = resource.meta.client.meta.region_name\n\n bucket = resource.create_bucket(\n Bucket=bucket_name,\n CreateBucketConfiguration={\n 'LocationConstraint': region_name\n }\n )\n\n def fin():\n bucket.objects.delete()\n bucket.delete()\n request.addfinalizer(fin)\n\n return bucket\n\n return _make_bucket","def create_spot_datafeed_subscription(self, bucket, prefix):\r\n params = {'Bucket' : bucket}\r\n if prefix:\r\n params['Prefix'] = prefix\r\n return self.get_object('CreateSpotDatafeedSubscription',\r\n params, SpotDatafeedSubscription, verb='POST')","def test_register_subscription_existing_type(self):\n mock_type = Mock()\n bus = event_bus._event_bus\n bus._subscriptions[mock_type] = [\n EventSubscription(mock_type, lambda _: None)]\n new_subscription = EventSubscription(mock_type, lambda _: True)\n\n reg_id = event_bus.register_subscription(new_subscription)\n\n self.assertTrue(new_subscription in bus._subscriptions[mock_type])\n self.assertTrue(reg_id in bus._registration_id_map.keys())","def touch_subscription(self):\n try:\n # check if subscription exists\n sub = self.client.get_subscription(subscription=self.subscription_path)\n\n except NotFound:\n self._create_subscription()\n\n else:\n self.topic_path = sub.topic\n print(f\"Subscription exists: {self.subscription_path}\")\n print(f\"Connected to topic: {self.topic_path}\")","def test_update_subscription_template(self):\n pass","def subnet_create(auth=None, **kwargs):\n cloud = get_operator_cloud(auth)\n kwargs = _clean_kwargs(**kwargs)\n return cloud.create_subnet(**kwargs)","def create(self):\n\n if self.call(method='addSubdomain', args=[self.domainname, self.subdomain]):\n return self","def request_subset_create(self, request):\n user_id = request['user_id']\n workspace_uuid = request['workspace_uuid']\n subset_uuid = request['subset_uuid']\n new_alias = request['alias']\n \n return_dict = self.copy_subset(user_id, \n workspace_uuid=workspace_uuid, \n subset_source_uuid=subset_uuid, \n subset_target_alias=new_alias)\n if return_dict:\n subset_uuid = return_dict['uuid']\n else:\n uuid_mapping = self._get_uuid_mapping_object(user_id)\n subset_uuid = uuid_mapping.get_uuid(alias=new_alias, user_id=user_id)\n response = self.dict_subset(workspace_unique_id=workspace_uuid, \n subset_unique_id=subset_uuid)\n \n return response","def putregion(self, *args, **kwargs):\n return _image.image_putregion(self, *args, **kwargs)","def recurring_charge_subscription(\n subscription_id: str,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = RecurringChargeSubscription.create(\n subscription_id=subscription_id,\n namespace=namespace,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","def __init__(__self__,\n resource_name: str,\n args: InterRegionTrafficQosPolicyArgs,\n opts: Optional[pulumi.ResourceOptions] = None):\n ...","def create_subscriber_for_development_events_v0(self, create_subscriber_request, **kwargs):\n # type: (CreateSubscriberRequest_a96d53b9, **Any) -> Union[ApiResponse, object, BadRequestError_a8ac8b44, Error_d660d58]\n operation_name = \"create_subscriber_for_development_events_v0\"\n params = locals()\n for key, val in six.iteritems(params['kwargs']):\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'create_subscriber_request' is set\n if ('create_subscriber_request' not in params) or (params['create_subscriber_request'] is None):\n raise ValueError(\n \"Missing the required parameter `create_subscriber_request` when calling `\" + operation_name + \"`\")\n\n resource_path = '/v0/developmentEvents/subscribers'\n resource_path = resource_path.replace('{format}', 'json')\n\n path_params = {} # type: Dict\n\n query_params = [] # type: List\n\n header_params = [] # type: List\n\n body_params = None\n if 'create_subscriber_request' in params:\n body_params = params['create_subscriber_request']\n header_params.append(('Content-type', 'application/json'))\n header_params.append(('User-Agent', self.user_agent))\n\n # Response Type\n full_response = False\n if 'full_response' in params:\n full_response = params['full_response']\n\n # Authentication setting\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\n authorization_value = \"Bearer \" + access_token\n header_params.append(('Authorization', authorization_value))\n\n error_definitions = [] # type: List\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=201, message=\"Created. Returns a URL to retrieve the subscriber in 'Location' header.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.bad_request_error.BadRequestError\", status_code=400, message=\"Server cannot process the request due to a client error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=401, message=\"The auth token is invalid/expired or doesn't have access to the resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=429, message=\"Exceed the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=500, message=\"Internal Server Error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=503, message=\"Service Unavailable.\"))\n\n api_response = self.invoke(\n method=\"POST\",\n endpoint=self._api_endpoint,\n path=resource_path,\n path_params=path_params,\n query_params=query_params,\n header_params=header_params,\n body=body_params,\n response_definitions=error_definitions,\n response_type=None)\n\n if full_response:\n return api_response\n \n return None","def subscribe(self, subscription_type, callback):\n if subscription_type in self._subscriptions.keys():\n self._subscriptions[subscription_type].append(callback)","def sns_conn ( self ) :\n if not self.sns :\n sns_regions = boto.sns.regions( )\n for reginfo in sns_regions :\n if reginfo.name == self.aws_region_name :\n sns_region = reginfo\n\n self.sns = boto.sns.SNSConnection( aws_access_key_id = self.access_key,\n aws_secret_access_key = self.access_key_secret,\n region = sns_region )\n return self.sns","def createOrcaTenant(self,payload):\n response = None\n # Check if tenant with that name already exists\n systemObj = self.getSystemByUid(payload[\"system\"])\n try:\n # Systemname and tenant description always determine a specific tenant\n response = self.getTenantByName(systemObj[\"name\"],payload[\"description\"].upper())\n except KeyError as e:\n if e.args[1] == \"CIC_TENANT_LOOKUP_ERROR\":\n response = None\n pass\n else:\n raise\n try:\n # TMS delivers always a non-empty body if something was found\n if response:\n if response[\"description\"] == payload[\"description\"].upper():\n raise RuntimeError(\"*** INFO *** Tenant already exists\",\"CIC_CREATE_TENANT_ERROR\")\n # TMS delivers an empty body if nothing is found\n elif response is None:\n print \"*** INFO *** Starting tenant creation\"\n response = self.httpHandler.sendHttpRequest(CIC_TENANT_ENDPOINT,payload,\"POST\")\n status = response.getcode()\n if status == 202:\n print \"*** INFO *** Tenant creation successfully triggered\"\n\n except RuntimeError as e:\n print e.args[0]\n except AttributeError as e:\n print \"*** INFO *** Discarding request.Please wait until tenant creation finishes before sending another request\"","def add_subscription(self, device, cb, event_type=None):\n device.subscribe(cb, event_type=event_type, run=False)\n self.subs[cb] = device","def subscribe():\n form = SubscribeForm()\n if form.validate_on_submit():\n subscription = Subscription(email=form.email.data)\n db.session.add(subscription)\n db.session.commit()\n return redirect(url_for('main.index'))\n\n return render_template('subscribes.html', form=form)","def send_subscription(\n connection, subscription_id, project_id, body, fields=None, error_msg=None\n):\n return connection.get(\n url=f'{connection.base_url}/api/subscriptions/{subscription_id}/send',\n params={'fields': fields},\n headers={'X-MSTR-ProjectID': project_id},\n json=body,\n )","def from_json(name, subscription_json):\n return CaseSubscription(name, subscriptions=subscription_json)","def create_subnet ( vpc_conn,\n ec2_conn,\n vpc_id,\n subnet_cidr,\n zone_name,\n subnet_basename ) :\n subnet = vpc_conn.create_subnet( vpc_id, subnet_cidr, zone_name )\n aws_cmd( ec2_conn.create_tags, [ subnet.id,\n { \"Name\": subnet_basename + \"-\" + zone_name[-1].upper( ) + \"-Subnet\" } ] )\n return subnet","def create_subscription_if_not_exists(self):\n create_subscription_if_not_exists(self.project_id, self.topic_name, self.subscription_name)","def select_subscription(profile=None, sub_name_or_id=None):\n if profile is None:\n profile = subscription_profile()\n\n if sub_name_or_id is None:\n sub_name_or_id = _prompt_sub_id_selection(profile)\n\n profile.set_active_subscription(sub_name_or_id)\n return profile","def subscribe(self, subscription):\n try:\n if isinstance(subscription, Subscription):\n sub = Subscribe(subscription, self.__pool, self.myAddress)\n self.send(self.__pool, sub)\n except Exception:\n handle_actor_system_fail()","def create_subscription_for_development_events_v0(self, **kwargs):\n # type: (**Any) -> Union[ApiResponse, object, BadRequestError_a8ac8b44, Error_d660d58]\n operation_name = \"create_subscription_for_development_events_v0\"\n params = locals()\n for key, val in six.iteritems(params['kwargs']):\n params[key] = val\n del params['kwargs']\n\n resource_path = '/v0/developmentEvents/subscriptions'\n resource_path = resource_path.replace('{format}', 'json')\n\n path_params = {} # type: Dict\n\n query_params = [] # type: List\n\n header_params = [] # type: List\n\n body_params = None\n if 'create_subscription_request' in params:\n body_params = params['create_subscription_request']\n header_params.append(('Content-type', 'application/json'))\n header_params.append(('User-Agent', self.user_agent))\n\n # Response Type\n full_response = False\n if 'full_response' in params:\n full_response = params['full_response']\n\n # Authentication setting\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\n authorization_value = \"Bearer \" + access_token\n header_params.append(('Authorization', authorization_value))\n\n error_definitions = [] # type: List\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=201, message=\"Created; Returns a URL to retrieve the subscription in 'Location' header.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.bad_request_error.BadRequestError\", status_code=400, message=\"Server cannot process the request due to a client error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=401, message=\"The auth token is invalid/expired or doesn't have access to the resource.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.bad_request_error.BadRequestError\", status_code=403, message=\"The operation being requested is not allowed.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=404, message=\"The resource being requested is not found.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=429, message=\"Exceed the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=500, message=\"Internal Server Error.\"))\n error_definitions.append(ServiceClientResponse(response_type=\"ask_smapi_model.v0.error.Error\", status_code=503, message=\"Service Unavailable.\"))\n\n api_response = self.invoke(\n method=\"POST\",\n endpoint=self._api_endpoint,\n path=resource_path,\n path_params=path_params,\n query_params=query_params,\n header_params=header_params,\n body=body_params,\n response_definitions=error_definitions,\n response_type=None)\n\n if full_response:\n return api_response\n \n return None","def customer_registration(request):\n \n data = request.data \n phone_number = generate_phn_number()\n \n try: \n try: \n # Create stripe account\n stripe_customer = stripe.Customer.create(\n email = data['email']\n )\n\n # Set a default card for account\n s_card = stripe.Customer.create_source(\n stripe_customer.id,\n source=\"tok_amex\",\n )\n \n plan_id = \"price_1JsHMxSDkRo5FXlkOsq2QHSV\"\n\n # if data[\"subscription_plan\"]== \"Globalnet Silver\":\n # plan_id = \"price_1JsHOJSDkRo5FXlkQmfEQzhN\"\n \n # if data[\"subscription_plan\"]== \"Globalnet Gold\":\n # plan_id = \"price_1JsHPFSDkRo5FXlk9VSl41rV\"\n\n # Create subscription for customer\n subscription = stripe.Subscription.create(\n customer = stripe_customer.id,\n items = [{'plan':plan_id}]\n )\n \n # Create User account\n user = User.objects.create(\n email = data['email'],\n password = make_password(data['password'] ) \n\n )\n\n start_date = datetime.datetime.now().strftime(\"%c\")\n end_date = (datetime.datetime.now() + datetime.timedelta(30)).strftime(\"%x\")\n\n subscription_plan = SubscriptionPlan.objects.get(subscription_plan_name=\"Globalnet Bronze\")\n \n # Create customer data\n customer_data = Customer.objects.create(\n user = user,\n primary_number = phone_number,\n subscription_plan = subscription_plan,\n stripe_id = stripe_customer.id,\n start_date = start_date,\n end_date = end_date,\n subscription_id = subscription.id\n \n )\n \n # Entry Subscription data\n SubscriptionData.objects.create(\n subscriber = phone_number,\n subscription = subscription_plan.subscription_plan_name,\n subscription_start = start_date,\n subscription_end = end_date \n \n ) \n \n serializer= CustomerSerializer(customer_data,many=False)\n return Response(serializer.data)\n\n except Exception as e:\n # delete user if any functionality fails\n u = User.objects.get(username = data['email'])\n u.delete()\n raise Exception(e)\n \n\n except Exception as e:\n message = {\"detail\":str(e)}\n print(e)\n return Response(message)","def setup_subscription(subscription, info: GraphQLResolveInfo, variables, complete_on_error=False):\n excluded_field_nodes = filter_selection_set(info)\n variables = frappe._dict(variables)\n subscription_id = frappe.generate_hash(f\"{subscription}-{frappe.session.user}\", length=8)\n\n subscription_data = frappe._dict(\n subscribed_at=now_datetime(),\n last_ping=now_datetime(),\n variables=variables,\n subscription_id=subscription_id,\n selection_set=excluded_field_nodes,\n user=frappe.session.user,\n complete_on_error=complete_on_error\n )\n\n frappe.cache().hset(\n get_subscription_redis_key(subscription), subscription_id, subscription_data)\n\n return frappe._dict(\n subscription_id=subscription_id\n )"],"string":"[\n \"def create_subscription(self,\\n body):\\n\\n return super().new_api_call_builder.request(\\n RequestBuilder().server('default')\\n .path('/v2/subscriptions')\\n .http_method(HttpMethodEnum.POST)\\n .header_param(Parameter()\\n .key('Content-Type')\\n .value('application/json'))\\n .body_param(Parameter()\\n .value(body))\\n .header_param(Parameter()\\n .key('accept')\\n .value('application/json'))\\n .body_serializer(APIHelper.json_serialize)\\n .auth(Single('global'))\\n ).response(\\n ResponseHandler()\\n .deserializer(APIHelper.json_deserialize)\\n .is_api_response(True)\\n .convertor(ApiResponse.create)\\n ).execute()\",\n \"def test_create_subscription(self):\\n pass\",\n \"def post_create_subscription(\\n self, response: pubsub.Subscription\\n ) -> pubsub.Subscription:\\n return response\",\n \"def _create_subscription(self):\\n try:\\n self.client.create_subscription(\\n name=self.subscription_path, topic=self.topic_path\\n )\\n except NotFound:\\n # suitable topic does not exist in the Pitt-Google project\\n raise ValueError(\\n (\\n f\\\"A subscription named {self.subscription_name} does not exist\\\"\\n \\\"in the Google Cloud Platform project \\\"\\n f\\\"{settings.GOOGLE_CLOUD_PROJECT}, \\\"\\n \\\"and one cannot be automatically create because Pitt-Google \\\"\\n \\\"does not publish a public topic with the same name.\\\"\\n )\\n )\\n else:\\n self._log_and_print(f\\\"Created subscription: {self.subscription_path}\\\")\",\n \"def handle_create(self):\\n subscription = self.client().subscription(\\n self.properties[self.QUEUE_NAME],\\n subscriber=self.properties[self.SUBSCRIBER],\\n ttl=self.properties[self.TTL],\\n options=self.properties[self.OPTIONS]\\n )\\n self.resource_id_set(subscription.id)\",\n \"def create_subscription(connection, project_id, body, fields=None, error_msg=None):\\n return connection.post(\\n url=f'{connection.base_url}/api/subscriptions',\\n params={'fields': fields},\\n headers={'X-MSTR-ProjectID': project_id},\\n json=body,\\n )\",\n \"def list_region_subscriptions(self, tenancy_id, **kwargs):\\n resource_path = \\\"/tenancies/{tenancyId}/regionSubscriptions\\\"\\n method = \\\"GET\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"list_region_subscriptions got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tenancyId\\\": tenancy_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"list[RegionSubscription]\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"list[RegionSubscription]\\\")\",\n \"def do_create_subscription(csp: CloudProviderInterface, environment_id=None):\\n environment = Environments.get(environment_id)\\n payload = build_subscription_payload(environment)\\n try:\\n csp.create_subscription(payload)\\n except GeneralCSPException as e:\\n app.logger.warning(\\n \\\"Unable to create subscription for environment %s.\\\", environment.id,\\n )\\n raise e\",\n \"def add_subscription(self):\\n schema = schemas.load(schemas.Subscription, self.request)\\n subscription = self.customer.add_subscription(**schema)\\n self.request.db.flush()\\n self.request.response.status_int = 201\\n return {'abonnement': subscription}\",\n \"def create_subscription(self, client_URI_endpoint, event_destination_id,\\n name, subscription_context):\\n self.client_URI_endpoints[client_URI_endpoint] = \\\\\\n Event(event_destination_id, name, subscription_context)\\n self.write_subscriptions_to_tmp(self.client_URI_endpoints)\",\n \"def create_subscription_in_snuba(query_subscription_id, **kwargs):\\n try:\\n subscription = QuerySubscription.objects.get(id=query_subscription_id)\\n except QuerySubscription.DoesNotExist:\\n metrics.incr(\\\"snuba.subscriptions.create.subscription_does_not_exist\\\")\\n return\\n if subscription.status != QuerySubscription.Status.CREATING.value:\\n metrics.incr(\\\"snuba.subscriptions.create.incorrect_status\\\")\\n return\\n if subscription.subscription_id is not None:\\n metrics.incr(\\\"snuba.subscriptions.create.already_created_in_snuba\\\")\\n # This mostly shouldn't happen, but it's possible that a subscription can get\\n # into this state. Just attempt to delete the existing subscription and then\\n # create a new one.\\n try:\\n _delete_from_snuba(\\n QueryDatasets(subscription.snuba_query.dataset), subscription.subscription_id\\n )\\n except SnubaError:\\n logger.exception(\\\"Failed to delete subscription\\\")\\n\\n subscription_id = _create_in_snuba(subscription)\\n subscription.update(\\n status=QuerySubscription.Status.ACTIVE.value, subscription_id=subscription_id\\n )\",\n \"def test_create_subscription_template(self):\\n pass\",\n \"def subscribe(request):\\n address = request.POST.get('address')\\n\\n new_sub = Subscription(**{\\n \\\"address\\\": address\\n })\\n new_sub.save()\\n\\n return HttpResponse(json.dumps({\\n \\\"status\\\": \\\"success\\\"\\n }, default=helpers.json_custom_parser), content_type='application/json')\",\n \"def subscribe(self, **subscription_request):\\n return self.subscribe_impl(mode='subscribe', **subscription_request)\",\n \"def create_subscription(self, user, standard):\\r\\n\\r\\n subscription = self.create(\\r\\n user=user,\\r\\n standard=standard,\\r\\n )\\r\\n\\r\\n return subscription\",\n \"def create_subscription(self, organization, collaborations, contractors):\\r\\n\\r\\n subscription = self.create(\\r\\n organization=organization,\\r\\n collaborations=collaborations,\\r\\n contractors=contractors,\\r\\n partner_discovery=partner_discovery,\\r\\n )\\r\\n return subscription\",\n \"def subscription(self, uuid):\\r\\n return subs.Subscription(self, uuid)\",\n \"def CreateSubscribeTransaction(self, dest, once=False):\\n c = Subscribe(dest, self.node_id, once)\\n self.connections.append((\\\"REACTIVE\\\", c))\\n return c\",\n \"def subscription(self):\\r\\n return SubscriptionResource(self)\",\n \"def subscribePost() -> object:\\n log = logging.getLogger(__name__)\\n db = Db()\\n\\n body = request.get_json()\\n\\n if body is None:\\n return jsonify({\\\"error\\\": \\\"json body is required\\\"}), HTTPStatus.HTTPStatus.BAD_REQUEST\\n\\n if not('datasetId') in body:\\n return jsonify({\\\"error\\\": \\\"datasetId is a required attribute\\\"}), HTTPStatus.HTTPStatus.BAD_REQUEST\\n\\n if not('notificationUrl') in body:\\n return jsonify({\\\"error\\\": \\\"notificationUrl is a required attribute\\\"}), HTTPStatus.HTTPStatus.BAD_REQUEST\\n\\n\\n subscription = db.Subscriptions(\\n datasetId=body['datasetId'],\\n notificationUrl=body['notificationUrl']\\n )\\n\\n subscription.save()\\n\\n subscription = json.loads(subscription.to_json())\\n subscription['id'] = subscription['_id'][\\\"$oid\\\"]\\n subscription.pop(\\\"_id\\\")\\n log.debug(\\\"subscription created\\\")\\n\\n return jsonify(subscription), HTTPStatus.CREATED\",\n \"def post(self):\\n data = request.json\\n return new_subscription(data=data)\",\n \"def post(self, orgname):\\n permission = AdministerOrganizationPermission(orgname)\\n request_data = request.get_json()\\n subscription_id = request_data[\\\"subscription_id\\\"]\\n if permission.can():\\n organization = model.organization.get_organization(orgname)\\n user = get_authenticated_user()\\n account_number = marketplace_users.get_account_number(user)\\n subscriptions = marketplace_subscriptions.get_list_of_subscriptions(account_number)\\n\\n if subscriptions is None:\\n abort(401, message=\\\"no valid subscriptions present\\\")\\n\\n user_subscription_ids = [int(subscription[\\\"id\\\"]) for subscription in subscriptions]\\n if int(subscription_id) in user_subscription_ids:\\n try:\\n model.organization_skus.bind_subscription_to_org(\\n user_id=user.id, subscription_id=subscription_id, org_id=organization.id\\n )\\n return \\\"Okay\\\", 201\\n except model.OrgSubscriptionBindingAlreadyExists:\\n abort(400, message=\\\"subscription is already bound to an org\\\")\\n else:\\n abort(401, message=f\\\"subscription does not belong to {user.username}\\\")\\n\\n abort(401)\",\n \"def create_subscription(chid, use_time=False, use_ctrl=False,\\n mask=None, callback=None):\\n mask = mask or DEFAULT_SUBSCRIPTION_MASK\\n\\n ftype = promote_type(chid, use_ctrl=use_ctrl, use_time=use_time)\\n\\n uarg = ctypes.py_object(callback)\\n evid = ctypes.c_void_p()\\n poll()\\n ret = libca.ca_create_subscription(ftype, 0, chid, mask,\\n _CB_EVENT, uarg, ctypes.byref(evid))\\n PySEVCHK('create_subscription', ret)\\n\\n poll()\\n return (_CB_EVENT, uarg, evid)\",\n \"def createTenant(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def __call__(\\n self,\\n request: pubsub.Subscription,\\n *,\\n retry: OptionalRetry = gapic_v1.method.DEFAULT,\\n timeout: Optional[float] = None,\\n metadata: Sequence[Tuple[str, str]] = (),\\n ) -> pubsub.Subscription:\\n\\n http_options: List[Dict[str, str]] = [\\n {\\n \\\"method\\\": \\\"put\\\",\\n \\\"uri\\\": \\\"/v1/{name=projects/*/subscriptions/*}\\\",\\n \\\"body\\\": \\\"*\\\",\\n },\\n ]\\n request, metadata = self._interceptor.pre_create_subscription(\\n request, metadata\\n )\\n pb_request = pubsub.Subscription.pb(request)\\n transcoded_request = path_template.transcode(http_options, pb_request)\\n\\n # Jsonify the request body\\n\\n body = json_format.MessageToJson(\\n transcoded_request[\\\"body\\\"],\\n including_default_value_fields=False,\\n use_integers_for_enums=True,\\n )\\n uri = transcoded_request[\\\"uri\\\"]\\n method = transcoded_request[\\\"method\\\"]\\n\\n # Jsonify the query params\\n query_params = json.loads(\\n json_format.MessageToJson(\\n transcoded_request[\\\"query_params\\\"],\\n including_default_value_fields=False,\\n use_integers_for_enums=True,\\n )\\n )\\n query_params.update(self._get_unset_required_fields(query_params))\\n\\n query_params[\\\"$alt\\\"] = \\\"json;enum-encoding=int\\\"\\n\\n # Send the request\\n headers = dict(metadata)\\n headers[\\\"Content-Type\\\"] = \\\"application/json\\\"\\n response = getattr(self._session, method)(\\n \\\"{host}{uri}\\\".format(host=self._host, uri=uri),\\n timeout=timeout,\\n headers=headers,\\n params=rest_helpers.flatten_query_params(query_params, strict=True),\\n data=body,\\n )\\n\\n # In case of error, raise the appropriate core_exceptions.GoogleAPICallError exception\\n # subclass.\\n if response.status_code >= 400:\\n raise core_exceptions.from_http_response(response)\\n\\n # Return the response\\n resp = pubsub.Subscription()\\n pb_resp = pubsub.Subscription.pb(resp)\\n\\n json_format.Parse(response.content, pb_resp, ignore_unknown_fields=True)\\n resp = self._interceptor.post_create_subscription(resp)\\n return resp\",\n \"def create_subscription(self, device_type):\\n url = '{}/v2/subscriptions'.format(self.url)\\n device_type = device_type.split('.')[0]\\n device_pattern = \\\"urn:ngsi-ld:{}:*\\\".format(device_type)\\n description = \\\"Notify QuantumLeap with {}\\\".format(device_type)\\n data = {\\n \\\"description\\\": description,\\n \\\"subject\\\": {\\n \\\"entities\\\": [\\n {\\n \\\"idPattern\\\": device_pattern\\n }\\n ]\\n },\\n \\\"notification\\\": {\\n \\\"http\\\": {\\n \\\"url\\\": \\\"http://quantumleap:8668/v2/notify\\\"\\n },\\n \\\"metadata\\\": [\\\"dateCreated\\\", \\\"dateModified\\\"]\\n },\\n \\\"throttling\\\": 1\\n }\\n return self.post(url, data=json.dumps(data), headers=self.headers_json)\",\n \"def create_pubsub_subscription(client, project, topic, name):\\n topic_name = pubsub.topic_name(project, topic)\\n full_name = pubsub.subscription_name(project, name)\\n if client.get_subscription(full_name):\\n return\\n\\n client.create_subscription(full_name, topic_name)\",\n \"def register(self, region=None, payload=None):\\n return self._put_response_body([], payload=payload)\",\n \"def test_create_response_descriptor_subscriptions_subscription_subscription_resource(self):\\n pass\",\n \"def test_create_subscription(self):\\n try:\\n self.arb.create_subscription(\\n trial_occurrences=4,\\n interval_length=1,\\n interval_unit=arb.MONTHS_INTERVAL,\\n start_date=u\\\"2008-09-09\\\",\\n amount=39.99,\\n card_number=u\\\"4222222222222\\\",\\n expiration_date=u\\\"2009-10\\\",\\n bill_first_name=u\\\"Michael\\\",\\n bill_last_name=u\\\"Pool\\\"\\n )\\n except KeyError:\\n pass\\n self.arb.create_subscription(\\n trial_amount=5.00,\\n trial_occurrences=4,\\n interval_length=1,\\n interval_unit=arb.MONTHS_INTERVAL,\\n start_date=u\\\"2008-09-09\\\",\\n amount=39.99,\\n card_number=u\\\"4222222222222\\\",\\n expiration_date=u\\\"2009-10\\\",\\n bill_first_name=u\\\"Michael\\\",\\n bill_last_name=u\\\"Pool\\\"\\n )\\n self.arb.create_subscription(\\n trial_amount=5.00,\\n trial_occurrences=4,\\n interval_length=1,\\n interval_unit=arb.MONTHS_INTERVAL,\\n start_date=u\\\"2008-09-09\\\",\\n amount=39.99,\\n card_number=u\\\"4222222222222\\\",\\n expiration_date=u\\\"2009-10\\\",\\n ship_first_name=u\\\"valentino\\\",\\n first_name=u\\\"valentino\\\",\\n bill_first_name=u\\\"valentino\\\",\\n bill_last_name=u\\\"Pool\\\",\\n driver_number=u\\\"55555\\\",\\n driver_state=u\\\"CA\\\",\\n driver_birth=u\\\"1990-09-09\\\"\\n )\",\n \"def test_create_response_descriptor_subscriptions_subscription_subscription_resource_spaces(self):\\n pass\",\n \"def subscribe(self, request):\\n email = self.cleaned_data.get('email')\\n\\n email_name, domain_part = email.rsplit('@', 1)\\n domain_name = '@' + domain_part\\n email_domain, created = Domain.objects.get_or_create(name=domain_name)\\n\\n subscriber, created = Subscriber.objects.get_or_create(email=email, mailing_list=self.mailing_list, defaults={\\n 'domain': email_domain\\n })\\n subscriber.status = Status.PENDING\\n subscriber.optin_ip_address = get_client_ip(request)\\n subscriber.optin_date = timezone.now()\\n subscriber.save()\\n\\n if not created:\\n subscriber.tokens.filter(description='confirm_subscription').delete()\\n\\n token = subscriber.tokens.create(description='confirm_subscription')\\n current_site = get_current_site(request)\\n protocol = 'https' if request.is_secure() else 'http'\\n domain = current_site.domain\\n path = reverse('subscribers:confirm_double_optin_token', kwargs={\\n 'mailing_list_uuid': self.mailing_list.uuid,\\n 'token': token.text\\n })\\n confirm_link = '%s://%s%s' % (protocol, domain, path)\\n\\n confirm_email = self.mailing_list.get_confirm_email_template()\\n confirm_email.send(subscriber.get_email(), {\\n 'confirm_link': confirm_link\\n })\\n\\n return subscriber\",\n \"def _create_sub(name, rostype, topic_callback, *args, **kwargs):\\n # counting subscriber instance per topic name\\n if name in TopicBack.sub_instance_count.keys():\\n TopicBack.sub_instance_count[name] += 1\\n else:\\n TopicBack.sub_instance_count[name] = 1\\n\\n return rospy.Subscriber(name, rostype, topic_callback, *args, **kwargs)\",\n \"def post_get_subscription(\\n self, response: pubsub.Subscription\\n ) -> pubsub.Subscription:\\n return response\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: EventSubscriptionArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def PostSubscription(self, request, context):\\n context.set_code(grpc.StatusCode.UNIMPLEMENTED)\\n context.set_details('Method not implemented!')\\n raise NotImplementedError('Method not implemented!')\",\n \"def subscription_factory_fixture():\\n def _factory(capability):\\n sub = Subscription()\\n sub.capability = capability\\n return sub\\n return _factory\",\n \"def get_subscription(self):\\n if not hasattr(self, '_subscription'):\\n self._subscription = self.admin.subscriptions.select_related('plan').get_overlapping(\\n self.admin_id, DateRange(self.period, self.period_end, bounds='[]'))\\n return self._subscription\",\n \"def public_subscribe_subscription(\\n user_id: str,\\n body: Optional[SubscribeRequest] = None,\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = PublicSubscribeSubscription.create(\\n user_id=user_id,\\n body=body,\\n namespace=namespace,\\n )\\n return run_request(request, additional_headers=x_additional_headers, **kwargs)\",\n \"def subscribe(config, accounts, region, merge, debug):\\n config = validate.callback(config)\\n subscription = config.get('subscription')\\n\\n if subscription is None:\\n log.error(\\\"config file: logs subscription missing\\\")\\n sys.exit(1)\\n\\n def converge_destination_policy(client, config):\\n destination_name = subscription['destination-arn'].rsplit(':', 1)[-1]\\n try:\\n extant_destinations = client.describe_destinations(\\n DestinationNamePrefix=destination_name).get('destinations')\\n except ClientError:\\n log.error(\\\"Log group destination not found: %s\\\",\\n subscription['destination-arn'])\\n sys.exit(1)\\n\\n account_ids = set()\\n for a in accounts:\\n if isinstance(a['role'], list):\\n account_ids.add(a['role'][-1].split(':')[4])\\n else:\\n account_ids.add(a['role'].split(':')[4])\\n\\n if merge:\\n for d in extant_destinations:\\n if d['destinationName'] == destination_name:\\n for s in json.loads(d['accessPolicy']):\\n if s['Sid'] == 'CrossAccountDelivery':\\n account_ids.update(s['Principal']['AWS'])\\n\\n client.put_destination_policy(\\n destinationName=destination_name,\\n accessPolicy=json.dumps({\\n 'Statement': [{\\n 'Action': 'logs:PutSubscriptionFilter',\\n 'Effect': 'Allow',\\n 'Principal': {'AWS': list(account_ids)},\\n 'Resource': subscription['destination-arn'],\\n 'Sid': 'CrossAccountDelivery'}]}))\\n\\n def subscribe_account(t_account, subscription, region):\\n session = get_session(t_account['role'], region)\\n client = session.client('logs')\\n distribution = subscription.get('distribution', 'ByLogStream')\\n role_arn = account.get('subscription-role')\\n\\n for g in account.get('groups'):\\n if (g.endswith('*')):\\n g = g.replace('*', '')\\n paginator = client.get_paginator('describe_log_groups')\\n allLogGroups = paginator.paginate(logGroupNamePrefix=g).build_full_result()\\n for l in allLogGroups['logGroups']:\\n _process_subscribe_group(\\n client, l['logGroupName'], subscription, distribution, role_arn)\\n else:\\n _process_subscribe_group(client, g, subscription, distribution, role_arn)\\n\\n if subscription.get('managed-policy'):\\n if subscription.get('destination-role'):\\n session = get_session(subscription['destination-role'], region)\\n else:\\n session = boto3.Session()\\n converge_destination_policy(session.client('logs'), config)\\n\\n executor = debug and MainThreadExecutor or ThreadPoolExecutor\\n\\n with executor(max_workers=32) as w:\\n futures = {}\\n for account in config.get('accounts', ()):\\n if accounts and account['name'] not in accounts:\\n continue\\n futures[w.submit(subscribe_account, account, subscription, region)] = account\\n\\n for f in as_completed(futures):\\n account = futures[f]\\n if f.exception():\\n log.error(\\\"Error on account %s err: %s\\\",\\n account['name'], f.exception())\\n log.info(\\\"Completed %s\\\", account['name'])\",\n \"def _InsertSubscription(self,\\n id='python.gcal.test%40gmail.com'):\\n print 'Subscribing to the calendar with ID: %s' % id\\n calendar = gdata.calendar.data.CalendarEntry()\\n calendar.id = atom.data.Id(text=id)\\n returned_calendar = self.cal_client.InsertCalendarSubscription(calendar)\\n return returned_calendar\",\n \"def test_aws_service_api_validate_subscription_post(self):\\n pass\",\n \"async def public_subscribe_subscription_async(\\n user_id: str,\\n body: Optional[SubscribeRequest] = None,\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = PublicSubscribeSubscription.create(\\n user_id=user_id,\\n body=body,\\n namespace=namespace,\\n )\\n return await run_request_async(\\n request, additional_headers=x_additional_headers, **kwargs\\n )\",\n \"def get_subscription(self):\\n return self.request({\\n 'path': '/' + UUID + '/subscription'})\",\n \"def setup_test_tenant(self):\\n self.test_tenant = rand_name('test_tenant_')\\n self.test_description = rand_name('desc_')\\n resp, self.tenant = self.client.create_tenant(\\n name=self.test_tenant,\\n description=self.test_description)\\n self.tenants.append(self.tenant)\",\n \"def set_endpoint_subscription_id(\\n *, login_manager: LoginManager, endpoint_id: str, subscription_id: Optional[str]\\n) -> None:\\n transfer_client = login_manager.get_transfer_client()\\n\\n res = transfer_client.put(\\n f\\\"/endpoint/{endpoint_id}/subscription\\\",\\n data={\\\"subscription_id\\\": subscription_id},\\n )\\n formatted_print(res, text_format=FORMAT_TEXT_RAW, response_key=\\\"message\\\")\",\n \"def test_issue_add_subscription(self):\\n pass\",\n \"def create_topic ( sns_conn, topicname, subscription_email ) :\\n t_result = sns_conn.create_topic( topicname )\\n topic = t_result[ 'CreateTopicResponse' ][ 'CreateTopicResult' ][ 'TopicArn' ]\\n sns_conn.subscribe( topic, 'email', subscription_email )\\n\\n return topic\",\n \"def activate_subscription(**kwargs):\\n sub, created = Subscription.objects.get_or_create(**kwargs)\\n # check if it already existed and was deactivated\\n if not created and not sub.active:\\n sub.active = True\\n sub.save()\\n created = True\\n return sub, created\",\n \"def create(self, validated_data):\\n subscription = super().create(validated_data)\\n subscription.send_verification_email()\\n return subscription\",\n \"def email_subscription(self):\\n from hubspot3.email_subscription import EmailSubscriptionClient\\n\\n return EmailSubscriptionClient(**self.auth, **self.options)\",\n \"async def create_subscription(user: int, redis: RedisDB):\\n subscription_data = {\\n \\\"subscriber_id\\\": user.id,\\n \\\"cost\\\": str(os.getenv(\\\"AMOUNT\\\")),\\n \\\"currency\\\": \\\"NANO\\\",\\n \\\"period\\\": int(os.getenv(\\\"PERIOD\\\"))\\n }\\n json_data = json.dumps(subscription_data)\\n r = requests.post(f\\\"{os.getenv('API_ENDPOINT')}create_subscription?token={os.getenv('NR_TOKEN')}\\\", json_data)\\n rx = r.json()\\n await redis.set(user.id, rx['subscription_id'])\\n return r.json()\",\n \"async def create_subscription(self, installed_app_id: str, data: dict) -> dict:\\r\\n return await self.post(\\r\\n API_SUBSCRIPTIONS.format(installed_app_id=installed_app_id), data\\r\\n )\",\n \"def create_region(self, region_ref):\\n raise exception.NotImplemented() # pragma: no cover\",\n \"def test_get_subscription(self):\\n pass\",\n \"def subscribe(self, request: Request) -> Response:\\n ids = request.data.get(\\\"ids\\\", None)\\n session_id = request.data.get(\\\"session_id\\\")\\n content_type = ContentType.objects.get_for_model(self.get_queryset().model)\\n user = request.user if request.user.is_authenticated else get_anonymous_user()\\n subscription = Subscription.objects.create(user=user, session_id=session_id)\\n\\n if ids is None:\\n # Subscribe to the whole table.\\n subscription.subscribe(\\n content_type, [Observer.ALL_IDS], (ChangeType.CREATE, ChangeType.DELETE)\\n )\\n else:\\n # Verify all ids exists and user has permissions to view them.\\n for id in ids:\\n if not self.user_has_permission(id, request.user):\\n raise NotFound(f\\\"Item {id} does not exist\\\")\\n\\n change_types = (ChangeType.UPDATE, ChangeType.DELETE, ChangeType.CREATE)\\n subscription.subscribe(content_type, ids, change_types)\\n\\n resp = {\\\"subscription_id\\\": subscription.subscription_id}\\n return Response(resp)\",\n \"def subscribe(self, namespace, sub_strings=None):\\n req = JSONRPCRequest('subscribe', [namespace, sub_strings])\\n result = yield self._send(req)\\n self._cache_jsonrpc_request(req)\\n raise tornado.gen.Return(result)\",\n \"def create_tenant(tenant_name, description, enabled, auth_admin_url, admin_token):\\n keystone = get_client(auth_admin_url, admin_token)\\n tenant = keystone.tenants.create(tenant_name=tenant_name, description=description, enabled=enabled)\\n print tenant\\n return tenant.to_dict()\",\n \"def platform_subscribe_subscription(\\n user_id: str,\\n body: Optional[PlatformSubscribeRequest] = None,\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = PlatformSubscribeSubscription.create(\\n user_id=user_id,\\n body=body,\\n namespace=namespace,\\n )\\n return run_request(request, additional_headers=x_additional_headers, **kwargs)\",\n \"async def create_and_subscribe(user_id):\\n client = gql(\\n query=Query,\\n mutation=Mutation,\\n subscription=Subscription,\\n consumer_attrs={\\\"strict_ordering\\\": True, \\\"confirm_subscriptions\\\": True},\\n )\\n await client.connect_and_init()\\n\\n sub_id = await client.send(\\n msg_type=\\\"start\\\",\\n payload={\\n \\\"query\\\": textwrap.dedent(\\n \\\"\\\"\\\"\\n subscription op_name($user_id: UserId) {\\n on_chat_message_sent(user_id: $user_id) { event }\\n }\\n \\\"\\\"\\\"\\n ),\\n \\\"variables\\\": {\\\"user_id\\\": user_id},\\n \\\"operationName\\\": \\\"op_name\\\",\\n },\\n )\\n\\n # Receive the subscription confirmation message.\\n resp = await client.receive(assert_id=sub_id, assert_type=\\\"data\\\")\\n assert resp == {\\\"data\\\": None}\\n\\n return sub_id, client\",\n \"def create_subscription(post, user, sub_type=None, update=False):\\n subs = Subscription.objects.filter(post=post.root, user=user)\\n sub = subs.first()\\n\\n default = Subscription.TYPE_MAP.get(user.profile.message_prefs,\\n Subscription.LOCAL_MESSAGE)\\n\\n empty = sub_type is None\\n # Get the current sub type from what's given or the existing sub\\n sub_type = None if empty else sub_type\\n # No type has been given so default\\n sub_type = sub_type or default\\n\\n # Ensure the sub type is not set to something wrote\\n if sub and update:\\n # Update an existing subscription\\n sub.type = sub_type\\n sub.save()\\n else:\\n # Drop all existing subscriptions for the user by default.\\n subs.delete()\\n Subscription.objects.create(post=post.root, user=user, type=sub_type)\\n\\n # Recompute subscription count\\n subs_count = Subscription.objects.filter(post=post.root).exclude(type=Subscription.NO_MESSAGES).count()\\n\\n # Update root subscription counts.\\n Post.objects.filter(pk=post.root.pk).update(subs_count=subs_count)\",\n \"def pre_create_subscription(\\n self, request: pubsub.Subscription, metadata: Sequence[Tuple[str, str]]\\n ) -> Tuple[pubsub.Subscription, Sequence[Tuple[str, str]]]:\\n return request, metadata\",\n \"def __init__(__self__, *,\\n cognitive_service_region: Optional[pulumi.Input[str]] = None,\\n cognitive_service_resource_id: Optional[pulumi.Input[str]] = None,\\n cognitive_service_subscription_key: Optional[pulumi.Input[str]] = None,\\n default_locale: Optional[pulumi.Input[str]] = None,\\n id: Optional[pulumi.Input[str]] = None,\\n provider_name: Optional[pulumi.Input[str]] = None):\\n if cognitive_service_region is not None:\\n pulumi.set(__self__, \\\"cognitive_service_region\\\", cognitive_service_region)\\n if cognitive_service_resource_id is not None:\\n pulumi.set(__self__, \\\"cognitive_service_resource_id\\\", cognitive_service_resource_id)\\n if cognitive_service_subscription_key is not None:\\n pulumi.set(__self__, \\\"cognitive_service_subscription_key\\\", cognitive_service_subscription_key)\\n if default_locale is not None:\\n pulumi.set(__self__, \\\"default_locale\\\", default_locale)\\n if id is not None:\\n pulumi.set(__self__, \\\"id\\\", id)\\n if provider_name is not None:\\n pulumi.set(__self__, \\\"provider_name\\\", provider_name)\",\n \"def create_hosted_office(sub, pw): \\r\\n s1 = ims.hostedOfficeSubscriber(sub)\\r\\n session = {}\\r\\n session['emaSession'] = ema.emaLogin()\\r\\n session['sub_pw'] = pw # Get password from xls sheet and put here\\r\\n\\r\\n result = s1.subscriberCreate(session)\\r\\n ema.ema_logout(session['emaSession'])\\r\\n return result\",\n \"def test_get_template_subscription(self):\\n pass\",\n \"def create(self, validated_data):\\n\\n region = CourierRegions.objects.create(\\n courier_id=Courier.objects.get(courier_id=validated_data['courier_id']),\\n region=validated_data['region']\\n )\\n return region\",\n \"def test_get_subscription_template(self):\\n pass\",\n \"def event_create(tenant_id, user_id=None):\",\n \"def get_tenant_id_resource_client(self):\\n\\n __logger__.info(\\\"Creating TenantIdResource\\\")\\n\\n return TenantIdResourceClient(protocol=self.api_protocol, host=self.api_host,\\n port=self.api_port, resource=self.api_resource, headers=self.headers)\",\n \"def create_tenant(tenant):\\n exists = identity.Tenant.query.filter_by(name=tenant.name).first()\\n if exists:\\n abort(409, \\\"Tenant Already Exists\\\")\\n db.session.add(tenant)\\n db.session.commit()\\n return tenant.id\",\n \"async def platform_subscribe_subscription_async(\\n user_id: str,\\n body: Optional[PlatformSubscribeRequest] = None,\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = PlatformSubscribeSubscription.create(\\n user_id=user_id,\\n body=body,\\n namespace=namespace,\\n )\\n return await run_request_async(\\n request, additional_headers=x_additional_headers, **kwargs\\n )\",\n \"def test_index_response_descriptor_subscriptions_subscription_subscription_resource(self):\\n pass\",\n \"def test_subscribe(self):\\n self.service.clientConnected()\\n self.service.subscribe(u'url', None)\\n pubsubClient = self.service.pubsubClient\\n self.assertIn(u'url', pubsubClient.subscriptions)\",\n \"def copy_to_region(self, region, name=None):\\r\\n if region.name == self.region:\\r\\n raise BotoClientError('Unable to copy to the same Region')\\r\\n conn_params = self.connection.get_params()\\r\\n rconn = region.connect(**conn_params)\\r\\n sg = rconn.create_security_group(name or self.name, self.description)\\r\\n source_groups = []\\r\\n for rule in self.rules:\\r\\n grant = rule.grants[0]\\r\\n for grant in rule.grants:\\r\\n if grant.name:\\r\\n if grant.name not in source_groups:\\r\\n source_groups.append(grant.name)\\r\\n sg.authorize(None, None, None, None, grant)\\r\\n else:\\r\\n sg.authorize(rule.ip_protocol, rule.from_port, rule.to_port,\\r\\n grant.cidr_ip)\\r\\n return sg\",\n \"def fixture_make_bucket(request):\\n def _make_bucket(resource, bucket_name, region_name=None):\\n if not region_name:\\n region_name = resource.meta.client.meta.region_name\\n\\n bucket = resource.create_bucket(\\n Bucket=bucket_name,\\n CreateBucketConfiguration={\\n 'LocationConstraint': region_name\\n }\\n )\\n\\n def fin():\\n bucket.objects.delete()\\n bucket.delete()\\n request.addfinalizer(fin)\\n\\n return bucket\\n\\n return _make_bucket\",\n \"def create_spot_datafeed_subscription(self, bucket, prefix):\\r\\n params = {'Bucket' : bucket}\\r\\n if prefix:\\r\\n params['Prefix'] = prefix\\r\\n return self.get_object('CreateSpotDatafeedSubscription',\\r\\n params, SpotDatafeedSubscription, verb='POST')\",\n \"def test_register_subscription_existing_type(self):\\n mock_type = Mock()\\n bus = event_bus._event_bus\\n bus._subscriptions[mock_type] = [\\n EventSubscription(mock_type, lambda _: None)]\\n new_subscription = EventSubscription(mock_type, lambda _: True)\\n\\n reg_id = event_bus.register_subscription(new_subscription)\\n\\n self.assertTrue(new_subscription in bus._subscriptions[mock_type])\\n self.assertTrue(reg_id in bus._registration_id_map.keys())\",\n \"def touch_subscription(self):\\n try:\\n # check if subscription exists\\n sub = self.client.get_subscription(subscription=self.subscription_path)\\n\\n except NotFound:\\n self._create_subscription()\\n\\n else:\\n self.topic_path = sub.topic\\n print(f\\\"Subscription exists: {self.subscription_path}\\\")\\n print(f\\\"Connected to topic: {self.topic_path}\\\")\",\n \"def test_update_subscription_template(self):\\n pass\",\n \"def subnet_create(auth=None, **kwargs):\\n cloud = get_operator_cloud(auth)\\n kwargs = _clean_kwargs(**kwargs)\\n return cloud.create_subnet(**kwargs)\",\n \"def create(self):\\n\\n if self.call(method='addSubdomain', args=[self.domainname, self.subdomain]):\\n return self\",\n \"def request_subset_create(self, request):\\n user_id = request['user_id']\\n workspace_uuid = request['workspace_uuid']\\n subset_uuid = request['subset_uuid']\\n new_alias = request['alias']\\n \\n return_dict = self.copy_subset(user_id, \\n workspace_uuid=workspace_uuid, \\n subset_source_uuid=subset_uuid, \\n subset_target_alias=new_alias)\\n if return_dict:\\n subset_uuid = return_dict['uuid']\\n else:\\n uuid_mapping = self._get_uuid_mapping_object(user_id)\\n subset_uuid = uuid_mapping.get_uuid(alias=new_alias, user_id=user_id)\\n response = self.dict_subset(workspace_unique_id=workspace_uuid, \\n subset_unique_id=subset_uuid)\\n \\n return response\",\n \"def putregion(self, *args, **kwargs):\\n return _image.image_putregion(self, *args, **kwargs)\",\n \"def recurring_charge_subscription(\\n subscription_id: str,\\n namespace: Optional[str] = None,\\n x_additional_headers: Optional[Dict[str, str]] = None,\\n **kwargs\\n):\\n if namespace is None:\\n namespace, error = get_services_namespace()\\n if error:\\n return None, error\\n request = RecurringChargeSubscription.create(\\n subscription_id=subscription_id,\\n namespace=namespace,\\n )\\n return run_request(request, additional_headers=x_additional_headers, **kwargs)\",\n \"def __init__(__self__,\\n resource_name: str,\\n args: InterRegionTrafficQosPolicyArgs,\\n opts: Optional[pulumi.ResourceOptions] = None):\\n ...\",\n \"def create_subscriber_for_development_events_v0(self, create_subscriber_request, **kwargs):\\n # type: (CreateSubscriberRequest_a96d53b9, **Any) -> Union[ApiResponse, object, BadRequestError_a8ac8b44, Error_d660d58]\\n operation_name = \\\"create_subscriber_for_development_events_v0\\\"\\n params = locals()\\n for key, val in six.iteritems(params['kwargs']):\\n params[key] = val\\n del params['kwargs']\\n # verify the required parameter 'create_subscriber_request' is set\\n if ('create_subscriber_request' not in params) or (params['create_subscriber_request'] is None):\\n raise ValueError(\\n \\\"Missing the required parameter `create_subscriber_request` when calling `\\\" + operation_name + \\\"`\\\")\\n\\n resource_path = '/v0/developmentEvents/subscribers'\\n resource_path = resource_path.replace('{format}', 'json')\\n\\n path_params = {} # type: Dict\\n\\n query_params = [] # type: List\\n\\n header_params = [] # type: List\\n\\n body_params = None\\n if 'create_subscriber_request' in params:\\n body_params = params['create_subscriber_request']\\n header_params.append(('Content-type', 'application/json'))\\n header_params.append(('User-Agent', self.user_agent))\\n\\n # Response Type\\n full_response = False\\n if 'full_response' in params:\\n full_response = params['full_response']\\n\\n # Authentication setting\\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\\n authorization_value = \\\"Bearer \\\" + access_token\\n header_params.append(('Authorization', authorization_value))\\n\\n error_definitions = [] # type: List\\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=201, message=\\\"Created. Returns a URL to retrieve the subscriber in 'Location' header.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.bad_request_error.BadRequestError\\\", status_code=400, message=\\\"Server cannot process the request due to a client error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=401, message=\\\"The auth token is invalid/expired or doesn't have access to the resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=429, message=\\\"Exceed the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=500, message=\\\"Internal Server Error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=503, message=\\\"Service Unavailable.\\\"))\\n\\n api_response = self.invoke(\\n method=\\\"POST\\\",\\n endpoint=self._api_endpoint,\\n path=resource_path,\\n path_params=path_params,\\n query_params=query_params,\\n header_params=header_params,\\n body=body_params,\\n response_definitions=error_definitions,\\n response_type=None)\\n\\n if full_response:\\n return api_response\\n \\n return None\",\n \"def subscribe(self, subscription_type, callback):\\n if subscription_type in self._subscriptions.keys():\\n self._subscriptions[subscription_type].append(callback)\",\n \"def sns_conn ( self ) :\\n if not self.sns :\\n sns_regions = boto.sns.regions( )\\n for reginfo in sns_regions :\\n if reginfo.name == self.aws_region_name :\\n sns_region = reginfo\\n\\n self.sns = boto.sns.SNSConnection( aws_access_key_id = self.access_key,\\n aws_secret_access_key = self.access_key_secret,\\n region = sns_region )\\n return self.sns\",\n \"def createOrcaTenant(self,payload):\\n response = None\\n # Check if tenant with that name already exists\\n systemObj = self.getSystemByUid(payload[\\\"system\\\"])\\n try:\\n # Systemname and tenant description always determine a specific tenant\\n response = self.getTenantByName(systemObj[\\\"name\\\"],payload[\\\"description\\\"].upper())\\n except KeyError as e:\\n if e.args[1] == \\\"CIC_TENANT_LOOKUP_ERROR\\\":\\n response = None\\n pass\\n else:\\n raise\\n try:\\n # TMS delivers always a non-empty body if something was found\\n if response:\\n if response[\\\"description\\\"] == payload[\\\"description\\\"].upper():\\n raise RuntimeError(\\\"*** INFO *** Tenant already exists\\\",\\\"CIC_CREATE_TENANT_ERROR\\\")\\n # TMS delivers an empty body if nothing is found\\n elif response is None:\\n print \\\"*** INFO *** Starting tenant creation\\\"\\n response = self.httpHandler.sendHttpRequest(CIC_TENANT_ENDPOINT,payload,\\\"POST\\\")\\n status = response.getcode()\\n if status == 202:\\n print \\\"*** INFO *** Tenant creation successfully triggered\\\"\\n\\n except RuntimeError as e:\\n print e.args[0]\\n except AttributeError as e:\\n print \\\"*** INFO *** Discarding request.Please wait until tenant creation finishes before sending another request\\\"\",\n \"def add_subscription(self, device, cb, event_type=None):\\n device.subscribe(cb, event_type=event_type, run=False)\\n self.subs[cb] = device\",\n \"def subscribe():\\n form = SubscribeForm()\\n if form.validate_on_submit():\\n subscription = Subscription(email=form.email.data)\\n db.session.add(subscription)\\n db.session.commit()\\n return redirect(url_for('main.index'))\\n\\n return render_template('subscribes.html', form=form)\",\n \"def send_subscription(\\n connection, subscription_id, project_id, body, fields=None, error_msg=None\\n):\\n return connection.get(\\n url=f'{connection.base_url}/api/subscriptions/{subscription_id}/send',\\n params={'fields': fields},\\n headers={'X-MSTR-ProjectID': project_id},\\n json=body,\\n )\",\n \"def from_json(name, subscription_json):\\n return CaseSubscription(name, subscriptions=subscription_json)\",\n \"def create_subnet ( vpc_conn,\\n ec2_conn,\\n vpc_id,\\n subnet_cidr,\\n zone_name,\\n subnet_basename ) :\\n subnet = vpc_conn.create_subnet( vpc_id, subnet_cidr, zone_name )\\n aws_cmd( ec2_conn.create_tags, [ subnet.id,\\n { \\\"Name\\\": subnet_basename + \\\"-\\\" + zone_name[-1].upper( ) + \\\"-Subnet\\\" } ] )\\n return subnet\",\n \"def create_subscription_if_not_exists(self):\\n create_subscription_if_not_exists(self.project_id, self.topic_name, self.subscription_name)\",\n \"def select_subscription(profile=None, sub_name_or_id=None):\\n if profile is None:\\n profile = subscription_profile()\\n\\n if sub_name_or_id is None:\\n sub_name_or_id = _prompt_sub_id_selection(profile)\\n\\n profile.set_active_subscription(sub_name_or_id)\\n return profile\",\n \"def subscribe(self, subscription):\\n try:\\n if isinstance(subscription, Subscription):\\n sub = Subscribe(subscription, self.__pool, self.myAddress)\\n self.send(self.__pool, sub)\\n except Exception:\\n handle_actor_system_fail()\",\n \"def create_subscription_for_development_events_v0(self, **kwargs):\\n # type: (**Any) -> Union[ApiResponse, object, BadRequestError_a8ac8b44, Error_d660d58]\\n operation_name = \\\"create_subscription_for_development_events_v0\\\"\\n params = locals()\\n for key, val in six.iteritems(params['kwargs']):\\n params[key] = val\\n del params['kwargs']\\n\\n resource_path = '/v0/developmentEvents/subscriptions'\\n resource_path = resource_path.replace('{format}', 'json')\\n\\n path_params = {} # type: Dict\\n\\n query_params = [] # type: List\\n\\n header_params = [] # type: List\\n\\n body_params = None\\n if 'create_subscription_request' in params:\\n body_params = params['create_subscription_request']\\n header_params.append(('Content-type', 'application/json'))\\n header_params.append(('User-Agent', self.user_agent))\\n\\n # Response Type\\n full_response = False\\n if 'full_response' in params:\\n full_response = params['full_response']\\n\\n # Authentication setting\\n access_token = self._lwa_service_client.get_access_token_from_refresh_token()\\n authorization_value = \\\"Bearer \\\" + access_token\\n header_params.append(('Authorization', authorization_value))\\n\\n error_definitions = [] # type: List\\n error_definitions.append(ServiceClientResponse(response_type=None, status_code=201, message=\\\"Created; Returns a URL to retrieve the subscription in 'Location' header.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.bad_request_error.BadRequestError\\\", status_code=400, message=\\\"Server cannot process the request due to a client error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=401, message=\\\"The auth token is invalid/expired or doesn't have access to the resource.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.bad_request_error.BadRequestError\\\", status_code=403, message=\\\"The operation being requested is not allowed.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=404, message=\\\"The resource being requested is not found.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=429, message=\\\"Exceed the permitted request limit. Throttling criteria includes total requests, per API, ClientId, and CustomerId.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=500, message=\\\"Internal Server Error.\\\"))\\n error_definitions.append(ServiceClientResponse(response_type=\\\"ask_smapi_model.v0.error.Error\\\", status_code=503, message=\\\"Service Unavailable.\\\"))\\n\\n api_response = self.invoke(\\n method=\\\"POST\\\",\\n endpoint=self._api_endpoint,\\n path=resource_path,\\n path_params=path_params,\\n query_params=query_params,\\n header_params=header_params,\\n body=body_params,\\n response_definitions=error_definitions,\\n response_type=None)\\n\\n if full_response:\\n return api_response\\n \\n return None\",\n \"def customer_registration(request):\\n \\n data = request.data \\n phone_number = generate_phn_number()\\n \\n try: \\n try: \\n # Create stripe account\\n stripe_customer = stripe.Customer.create(\\n email = data['email']\\n )\\n\\n # Set a default card for account\\n s_card = stripe.Customer.create_source(\\n stripe_customer.id,\\n source=\\\"tok_amex\\\",\\n )\\n \\n plan_id = \\\"price_1JsHMxSDkRo5FXlkOsq2QHSV\\\"\\n\\n # if data[\\\"subscription_plan\\\"]== \\\"Globalnet Silver\\\":\\n # plan_id = \\\"price_1JsHOJSDkRo5FXlkQmfEQzhN\\\"\\n \\n # if data[\\\"subscription_plan\\\"]== \\\"Globalnet Gold\\\":\\n # plan_id = \\\"price_1JsHPFSDkRo5FXlk9VSl41rV\\\"\\n\\n # Create subscription for customer\\n subscription = stripe.Subscription.create(\\n customer = stripe_customer.id,\\n items = [{'plan':plan_id}]\\n )\\n \\n # Create User account\\n user = User.objects.create(\\n email = data['email'],\\n password = make_password(data['password'] ) \\n\\n )\\n\\n start_date = datetime.datetime.now().strftime(\\\"%c\\\")\\n end_date = (datetime.datetime.now() + datetime.timedelta(30)).strftime(\\\"%x\\\")\\n\\n subscription_plan = SubscriptionPlan.objects.get(subscription_plan_name=\\\"Globalnet Bronze\\\")\\n \\n # Create customer data\\n customer_data = Customer.objects.create(\\n user = user,\\n primary_number = phone_number,\\n subscription_plan = subscription_plan,\\n stripe_id = stripe_customer.id,\\n start_date = start_date,\\n end_date = end_date,\\n subscription_id = subscription.id\\n \\n )\\n \\n # Entry Subscription data\\n SubscriptionData.objects.create(\\n subscriber = phone_number,\\n subscription = subscription_plan.subscription_plan_name,\\n subscription_start = start_date,\\n subscription_end = end_date \\n \\n ) \\n \\n serializer= CustomerSerializer(customer_data,many=False)\\n return Response(serializer.data)\\n\\n except Exception as e:\\n # delete user if any functionality fails\\n u = User.objects.get(username = data['email'])\\n u.delete()\\n raise Exception(e)\\n \\n\\n except Exception as e:\\n message = {\\\"detail\\\":str(e)}\\n print(e)\\n return Response(message)\",\n \"def setup_subscription(subscription, info: GraphQLResolveInfo, variables, complete_on_error=False):\\n excluded_field_nodes = filter_selection_set(info)\\n variables = frappe._dict(variables)\\n subscription_id = frappe.generate_hash(f\\\"{subscription}-{frappe.session.user}\\\", length=8)\\n\\n subscription_data = frappe._dict(\\n subscribed_at=now_datetime(),\\n last_ping=now_datetime(),\\n variables=variables,\\n subscription_id=subscription_id,\\n selection_set=excluded_field_nodes,\\n user=frappe.session.user,\\n complete_on_error=complete_on_error\\n )\\n\\n frappe.cache().hset(\\n get_subscription_redis_key(subscription), subscription_id, subscription_data)\\n\\n return frappe._dict(\\n subscription_id=subscription_id\\n )\"\n]"},"negative_scores":{"kind":"list like","value":["0.61023337","0.6050946","0.60171896","0.59941614","0.5989991","0.5985926","0.59581876","0.59402776","0.5903215","0.5853864","0.5773465","0.57645184","0.56852347","0.5659827","0.56107926","0.56008047","0.55303335","0.55104107","0.5472032","0.5425874","0.54192394","0.53581506","0.53247344","0.5322388","0.53061765","0.5292069","0.5279004","0.52674073","0.5249765","0.52019763","0.5198017","0.5175966","0.5171832","0.51689374","0.5168146","0.51438904","0.5142959","0.5137592","0.5134189","0.5100409","0.50891477","0.50731575","0.5070964","0.50676805","0.50479513","0.50363374","0.5032048","0.50319517","0.5016633","0.50107664","0.49994668","0.49715486","0.49703076","0.49533305","0.4940842","0.49406266","0.49120396","0.48976743","0.48892942","0.487961","0.48618424","0.48618406","0.48500064","0.48414382","0.4838828","0.4836289","0.48341388","0.4825017","0.4816161","0.48020372","0.47964674","0.47782236","0.47767514","0.4769817","0.47661552","0.47659084","0.47610092","0.47461936","0.47456816","0.47409838","0.47351706","0.4727323","0.4723183","0.47202155","0.47175145","0.47173515","0.4708658","0.4704728","0.47017816","0.4684261","0.46739313","0.46681038","0.46678844","0.46656835","0.466539","0.46623746","0.46597543","0.4659075","0.46526897","0.4650086"],"string":"[\n \"0.61023337\",\n \"0.6050946\",\n \"0.60171896\",\n \"0.59941614\",\n \"0.5989991\",\n \"0.5985926\",\n \"0.59581876\",\n \"0.59402776\",\n \"0.5903215\",\n \"0.5853864\",\n \"0.5773465\",\n \"0.57645184\",\n \"0.56852347\",\n \"0.5659827\",\n \"0.56107926\",\n \"0.56008047\",\n \"0.55303335\",\n \"0.55104107\",\n \"0.5472032\",\n \"0.5425874\",\n \"0.54192394\",\n \"0.53581506\",\n \"0.53247344\",\n \"0.5322388\",\n \"0.53061765\",\n \"0.5292069\",\n \"0.5279004\",\n \"0.52674073\",\n \"0.5249765\",\n \"0.52019763\",\n \"0.5198017\",\n \"0.5175966\",\n \"0.5171832\",\n \"0.51689374\",\n \"0.5168146\",\n \"0.51438904\",\n \"0.5142959\",\n \"0.5137592\",\n \"0.5134189\",\n \"0.5100409\",\n \"0.50891477\",\n \"0.50731575\",\n \"0.5070964\",\n \"0.50676805\",\n \"0.50479513\",\n \"0.50363374\",\n \"0.5032048\",\n \"0.50319517\",\n \"0.5016633\",\n \"0.50107664\",\n \"0.49994668\",\n \"0.49715486\",\n \"0.49703076\",\n \"0.49533305\",\n \"0.4940842\",\n \"0.49406266\",\n \"0.49120396\",\n \"0.48976743\",\n \"0.48892942\",\n \"0.487961\",\n \"0.48618424\",\n \"0.48618406\",\n \"0.48500064\",\n \"0.48414382\",\n \"0.4838828\",\n \"0.4836289\",\n \"0.48341388\",\n \"0.4825017\",\n \"0.4816161\",\n \"0.48020372\",\n \"0.47964674\",\n \"0.47782236\",\n \"0.47767514\",\n \"0.4769817\",\n \"0.47661552\",\n \"0.47659084\",\n \"0.47610092\",\n \"0.47461936\",\n \"0.47456816\",\n \"0.47409838\",\n \"0.47351706\",\n \"0.4727323\",\n \"0.4723183\",\n \"0.47202155\",\n \"0.47175145\",\n \"0.47173515\",\n \"0.4708658\",\n \"0.4704728\",\n \"0.47017816\",\n \"0.4684261\",\n \"0.46739313\",\n \"0.46681038\",\n \"0.46678844\",\n \"0.46656835\",\n \"0.466539\",\n \"0.46623746\",\n \"0.46597543\",\n \"0.4659075\",\n \"0.46526897\",\n \"0.4650086\"\n]"},"document_score":{"kind":"string","value":"0.74824893"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8584,"cells":{"query":{"kind":"string","value":"Creates a new SMTP credential for the specified user. An SMTP credential has an SMTP user name and an SMTP password. You must specify a description for the SMTP credential (although it can be an empty string). It does not have to be unique, and you can change it anytime with"},"document":{"kind":"string","value":"def create_smtp_credential(self, create_smtp_credential_details, user_id, **kwargs):\n resource_path = \"/users/{userId}/smtpCredentials\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_smtp_credential got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"userId\": user_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_smtp_credential_details,\n response_type=\"SmtpCredential\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_smtp_credential_details,\n response_type=\"SmtpCredential\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create_new_credential(account,userName,password):\n new_credential = Credentials(account,userName,password)\n return new_credential","def CreateNewSmtpUser(s):\n payload = ['adduser %s %s\\n' % (FLAGS.exploit_user, FLAGS.exploit_password),\n 'quit\\n']\n SendPayload(s, payload)\n logging.info('Created new user %s/%s' % (\n FLAGS.exploit_user, FLAGS.exploit_password))\n s.close()","def create_credential(self, body=None):\r\n return self.post(self.credentials_path, body=body)","def create_user(BrokerId=None, ConsoleAccess=None, Groups=None, Password=None, Username=None):\n pass","def create_user(UserName=None, MessageAction=None, FirstName=None, LastName=None, AuthenticationType=None):\n pass","def Create( profile_name,\r\n host,\r\n username=None,\r\n password=None,\r\n port=26,\r\n from_name=None,\r\n from_email=None,\r\n ssl=False,\r\n output_stream=sys.stdout,\r\n ):\r\n\r\n if not from_name and not from_email:\r\n raise CommandLine.UsageException(\"'from_name' or 'from_email' must be provided\")\r\n\r\n mailer = SmtpMailer( host,\r\n username=username,\r\n password=password,\r\n port=port,\r\n from_name=from_name,\r\n from_email=from_email,\r\n ssl=ssl,\r\n )\r\n mailer.Save(profile_name)\r\n\r\n output_stream.write(\"The profile '{}' has been created.\\n\".format(profile_name))","def create_user_credentials(storage_type, storage_id, space_name, client_ip,\n user_details):\n user_id = user_details[\"id\"]\n if user_id == \"0\":\n return PosixCredentials(0, 0)\n\n uid = gid = gen_storage_id(user_id)\n return PosixCredentials(uid, gid)","def send_new_credentials(email,name,password,phone,shop,address,lead_mail,fname,mem_mail,website):\n\n logger.info(\"in send lead mail task\")\n return send_lead_generate(email,name,password,phone,shop,address,lead_mail,fname,mem_mail,website)","def create_user(email, password, f_name, l_name):\n pass","def create_email(user):\n if 'research' in user.get_domains():\n domain = 'research'\n else: domain = 'academic'\n subject = \"ECE/CIS Account Created\"\n helprequest = \"https://www.eecis.udel.edu/service\"\n \n message = \"Your ECE/CIS %s account has been created with the username: %s\\n\\n\" % (domain, user.username)\n message += \"Please do not reply to this message. If you need assistance with your account, please visit:\\n\"\n message += \"%s\\n\\n\" % helprequest\n message += \"-- EE/CIS Labstaff\\n\"\n\n send('account@eecis.udel.edu', 'ECE/CIS Account System', \\\n [user.email], subject, message, MAILHOST)","def create(self, username, password, email):\n pass","def create_user(context, params):\n form_user = dict()\n # form_user['edited_by'] = context.user\n if params.get('username'):\n form_user['username'] = params.get('username')\n else:\n form_user['username'] = create_username(params) # 'email_user{}'.format(MISUser.objects.latest('id').id + 1\n form_user['first_name'] = params.get('first_name')\n form_user['last_name'] = params.get('last_name')\n form_person = create_person(params)\n form_user.update(form_person)\n user = User.objects.create(**form_user)\n user.set_password(params.get('password'))\n\n email = {'label': 'Work', 'val': params.get('email'), 'person': user, 'is_main': True}\n create_email(context, email)\n\n user.save()\n return user","def create_user(self, conn, name, password, group):\n user = conn.user.allocate(name, password, \"\", [group])\n return user","def m_credential_create(node_name, credential_hash, participantDID):\n pass","def create_server(host, port, uid, pwd):\r\n s = smtplib.SMTP(host, port)\r\n s.starttls()\r\n s.login(\r\n uid,\r\n pwd\r\n )\r\n return s","def create_service_credentials(user, new_roles=None):\n tenant = config('service-tenant')\n if not tenant:\n raise Exception(\"No service tenant provided in config\")\n\n domain = None\n if get_api_version() > 2:\n domain = DEFAULT_DOMAIN\n passwd = create_user_credentials(user, get_service_password,\n set_service_password,\n tenant=tenant, new_roles=new_roles,\n grants=[config('admin-role')],\n domain=domain)\n if get_api_version() > 2:\n # Create account in SERVICE_DOMAIN as well using same password\n domain = SERVICE_DOMAIN\n passwd = create_user_credentials(user, get_service_password,\n set_service_password,\n tenant=tenant, new_roles=new_roles,\n grants=[config('admin-role')],\n domain=domain)\n return passwd","async def create_new_user(*, user: User):\n with Session(engine) as session:\n user.password = simple_hash(user.name, user.password) #Hashing password for security\n session.add(user)\n session.commit()\n return {\"message\": \"User {user_id} created\".format(user_id = user.id)}","def add_user(self, user, pw):\n self.db.execute(\"INSERT INTO user_credentials VALUES (?, ?)\", [user, pw])\n self.db.commit()","def create(self, credentials):\n return User.objects.create_user(\n credentials['username'],\n credentials['email'],\n credentials['password']\n )","def newuser(lp, creds, username=None):\n\n names = guess_names_from_smbconf(lp, None, None)\n db = Ldb(url=get_ldb_url(lp, creds, names), session_info=system_session(), \n credentials=creds, lp=lp)\n user_dn = get_user_dn(db, \"CN=Users,%s\" % names.domaindn, username)\n if user_dn:\n extended_user = \"\"\"\ndn: %(user_dn)s\nchangetype: modify\nadd: mailNickName\nmailNickname: %(username)s\nadd: homeMDB\nhomeMDB: CN=Mailbox Store (%(netbiosname)s),CN=First Storage Group,CN=InformationStore,CN=%(netbiosname)s,CN=Servers,CN=First Administrative Group,CN=Administrative Groups,CN=%(firstorg)s,CN=Microsoft Exchange,CN=Services,CN=Configuration,%(domaindn)s\nadd: homeMTA\nhomeMTA: CN=Mailbox Store (%(netbiosname)s),CN=First Storage Group,CN=InformationStore,CN=%(netbiosname)s,CN=Servers,CN=First Administrative Group,CN=Administrative Groups,CN=%(firstorg)s,CN=Microsoft Exchange,CN=Services,CN=Configuration,%(domaindn)s\nadd: legacyExchangeDN\nlegacyExchangeDN: /o=%(firstorg)s/ou=First Administrative Group/cn=Recipients/cn=%(username)s\nadd: proxyAddresses\nproxyAddresses: =EX:/o=%(firstorg)s/ou=First Administrative Group/cn=Recipients/cn=%(username)s\nproxyAddresses: smtp:postmaster@%(dnsdomain)s\nproxyAddresses: X400:c=US;a= ;p=First Organizati;o=Exchange;s=%(username)s\nproxyAddresses: SMTP:%(username)s@%(dnsdomain)s\nreplace: msExchUserAccountControl\nmsExchUserAccountControl: 0\n\"\"\"\n ldif_value = extended_user % {\"user_dn\": user_dn,\n \"username\": username,\n \"netbiosname\": names.netbiosname,\n \"firstorg\": names.firstorg,\n \"domaindn\": names.domaindn,\n \"dnsdomain\": names.dnsdomain}\n db.modify_ldif(ldif_value)\n\n res = db.search(base=user_dn, scope=SCOPE_BASE, attrs=[\"*\"])\n if len(res) == 1:\n record = res[0]\n else:\n raise Exception, \\\n \"this should never happen as we just modified the record...\"\n record_keys = map(lambda x: x.lower(), record.keys())\n\n if \"displayname\" not in record_keys:\n extended_user = \"dn: %s\\nadd: displayName\\ndisplayName: %s\\n\" % (user_dn, username)\n db.modify_ldif(extended_user)\n\n if \"mail\" not in record_keys:\n extended_user = \"dn: %s\\nadd: mail\\nmail: %s@%s\\n\" % (user_dn, username, names.dnsdomain)\n db.modify_ldif(extended_user)\n\n print \"[+] User %s extended and enabled\" % username\n else:\n print \"[!] User '%s' not found\" % username","def new_credentials(site_name, user_name, password):\n new_credentials = Credentials(site_name, user_name, password)\n return new_credentials","def create_user_credentials(user, passwd_get_callback, passwd_set_callback,\n tenant=None, new_roles=None,\n grants=None, domain=None):\n passwd = passwd_get_callback(user)\n if not passwd:\n log(\"Unable to retrieve password for user '{}'\".format(user),\n level=INFO)\n return\n\n log(\"Creating service credentials for '%s'\" % user, level=DEBUG)\n if user_exists(user, domain=domain):\n log(\"User '%s' already exists\" % (user), level=DEBUG)\n # NOTE(dosaboy): see LP #1648677\n if is_password_changed(user, passwd):\n update_user_password(user, passwd, domain)\n else:\n create_user(user, passwd, tenant=tenant, domain=domain)\n\n passwd_set_callback(passwd, user=user)\n\n if grants:\n for role in grants:\n # grant role on project\n grant_role(user, role, tenant=tenant, user_domain=domain,\n project_domain=domain)\n else:\n log(\"No role grants requested for user '%s'\" % (user), level=DEBUG)\n\n if new_roles:\n # Allow the remote service to request creation of any additional roles.\n # Currently used by Swift and Ceilometer.\n for role in new_roles:\n log(\"Creating requested role '%s'\" % role, level=DEBUG)\n create_role(role, user=user, tenant=tenant, domain=domain)\n\n return passwd","def _create_user(self, username, password, domain_id, project_id):\n request = {\n \"user\": {\n \"name\": username,\n \"password\": password,\n \"domain_id\": domain_id,\n \"default_project_id\": project_id,\n \"description\": \"description\",\n \"email\": \"test@example.com\",\n \"enabled\": True,\n }\n }\n response = self.client.post(USER_PATH, data=json.dumps(request),\n headers=HEADERS)\n if response.status_code == 409:\n return\n elif response.status_code == 201:\n return response.json()\n else:\n raise SystemExit(\"Failed to create test user.\")","def create_user(self):\n u = USER.objects.create(username='test_user1',\n email='test_email@example.com', )\n u.set_password('test_password')\n u.save()\n self.user = u\n return u","def create_user(\n screen_name: str,\n email_address: str,\n password: str,\n first_names: Optional[str],\n last_name: Optional[str],\n site_id: SiteID,\n *,\n consents: Optional[Set[Consent]] = None,\n) -> Tuple[User, UserAccountCreated]:\n # user with details, password, and roles\n user, event = create_basic_user(\n screen_name,\n email_address,\n password,\n first_names=first_names,\n last_name=last_name,\n )\n\n # consents\n if consents:\n for consent in consents:\n # Insert missing user ID.\n consent = consent_service.build_consent(\n user.id,\n consent.subject_id,\n consent.expressed_at,\n )\n db.session.add(consent)\n\n db.session.commit()\n\n request_email_address_confirmation(user, email_address, site_id)\n\n return user, event","def createNewUser(name, account, auth, email, pwd, group, expiry, node):\n \n #Check if the user creation was succesful\n if hl.createUser(name, account, auth, email = email, passwd = pwd, group = group, expiry = expiry, node = node):\n user = hl.getUser(\"Email\", email)\n\n if(auth == \"Email\"):\n subjectTitle = \"OneGroup account keys\"\n recipientEmail =[email]\n bodyMessage = \"here are your keys\"\n attachmentName = user['Keys'] + '.ovpn'\n filename = \"{}/{}\".format(keys_dir,attachmentName)\n attachmentFilePath = filename\n emailMessage(subjectTitle, recipientEmail, bodyMessage,attachmentName, attachmentFilePath)\n\n elif(auth == \"Passphrase\"):\n subjectTitle = \"OneGroup account details\"\n recipientEmail = [email]\n bodyMessage = \"Your login details are\\n Email :\" + str(email) + \"\\nPassword :\" + str(pwd)\n emailMessage(subjectTitle, recipientEmail, bodyMessage)\n return True\n else:\n return False","def create_user(self, uname, name, password=None):\r\n\r\n if not uname:\r\n return _('Must provide username')\r\n if not name:\r\n return _('Must provide full name')\r\n\r\n email_domain = getattr(settings, 'SSL_AUTH_EMAIL_DOMAIN', 'MIT.EDU')\r\n\r\n msg = u''\r\n if settings.FEATURES['AUTH_USE_CERTIFICATES']:\r\n if not '@' in uname:\r\n email = '{0}@{1}'.format(uname, email_domain)\r\n else:\r\n email = uname\r\n if not email.endswith('@{0}'.format(email_domain)):\r\n msg += u'{0} @{1}'.format(_('email must end in'), email_domain)\r\n return msg\r\n mit_domain = 'ssl:MIT'\r\n if ExternalAuthMap.objects.filter(external_id=email,\r\n external_domain=mit_domain):\r\n msg += _('Failed - email {0} already exists as '\r\n 'external_id').format(email)\r\n return msg\r\n new_password = generate_password()\r\n else:\r\n if not password:\r\n return _('Password must be supplied if not using certificates')\r\n\r\n email = uname\r\n\r\n if not '@' in email:\r\n msg += _('email address required (not username)')\r\n return msg\r\n new_password = password\r\n\r\n user = User(username=uname, email=email, is_active=True)\r\n user.set_password(new_password)\r\n try:\r\n user.save()\r\n except IntegrityError:\r\n msg += _('Oops, failed to create user {0}, '\r\n 'IntegrityError').format(user)\r\n return msg\r\n\r\n reg = Registration()\r\n reg.register(user)\r\n\r\n profile = UserProfile(user=user)\r\n profile.name = name\r\n profile.save()\r\n\r\n if settings.FEATURES['AUTH_USE_CERTIFICATES']:\r\n credential_string = getattr(settings, 'SSL_AUTH_DN_FORMAT_STRING',\r\n '/C=US/ST=Massachusetts/O=Massachusetts Institute of Technology/OU=Client CA v1/CN={0}/emailAddress={1}')\r\n credentials = credential_string.format(name, email)\r\n eamap = ExternalAuthMap(\r\n external_id=email,\r\n external_email=email,\r\n external_domain=mit_domain,\r\n external_name=name,\r\n internal_password=new_password,\r\n external_credentials=json.dumps(credentials),\r\n )\r\n eamap.user = user\r\n eamap.dtsignup = timezone.now()\r\n eamap.save()\r\n\r\n msg += _('User {0} created successfully!').format(user)\r\n return msg","def setupUser(con, options, dbName, userName, userInfo):\n if checkUsername(userName):\n trace(\"For dbName='%s', create user '%s'\" % (dbName, userName))\n userPassword = userInfo[\"password\"]\n optionalDbExecute(con, options, \"create user %s with password '%s'\" % (userName, userPassword))","def create_user(user, first_name, last_name, major, bio):\n return userAccount.objects.create(user=user, first_name=first_name, last_name=last_name, major=major, bio=bio)","def send_email( user, password ):\n \n mail = Mailer( host = EMAIL['host'], \n port = EMAIL['port'],\n use_tls = EMAIL['use_tls'], \n usr = EMAIL['user'], \n pwd = EMAIL['password']\n )\n \n message = Message( From = 'help@rxmedaccess.com',\n To = [user.email],\n Subject = \"Password Reset\"\n )\n \n body = \"\"\"Your new password for {} is {}\n You can reset it to what you like on your settings page once you log in with\n this password\n \"\"\".format(__name__, password )\n\n message.Body = body\n try:\n mail.send(message)\n except Exception as e:\n log.error( 'Send mail error: {}'.format( str(e) ) )","def create_user(ctx, db_username, db_password, project_name):\n project = ctx.obj.groups.byName[project_name].get().data\n user = cmd.ensure_admin_user(\n client=ctx.obj, project_id=project.id, username=db_username,\n password=db_password)\n pprint(user)","def create_user(uname,password):\n new_user = User(uname,password)\n return new_user","def create_user(self, user, user_opt={}):\n assert user.id is None\n if self.dryrun:\n self.logger.debug(\"Would create user %s in zabbix\", user.alias)\n return\n\n random_passwd = ''.join(random.sample(string.ascii_letters + string.digits, 32))\n\n user_req = {\n 'autologin': 0,\n 'type': 1,\n 'usrgrps': [{'usrgrpid': str(id)} for id in user.groups],\n 'passwd': random_passwd,\n \"alias\": user.alias,\n \"name\": user.name,\n \"surname\": user.surname,\n }\n user_req.update(user_opt)\n\n result = self.conn.user.create(user_req)\n user.id = result[\"userids\"][0]\n self.logger.debug(\"Created user %s in zabbix, id: %s\", user.alias, user.id)","def create_user(self):\n User.objects.create_user('test', 'testing@test.com', 'testing')","def create_user(open_ldap, smtp, entries):\n try:\n if open_ldap.ldap_insert(entries):\n smtp.send_email(entries)\n return True\n else:\n return False\n except Exception as e:\n print('ERROR - ', e)\n return","def set_new_user(mailer: Mailer, user_data: Dict[str, Any], password: str, _tn: Translator) -> Dict[str, Any]:\n # copy the dict to not change the mutable structure\n temporary_user = dict(user_data)\n\n if DBDiscussionSession.query(User).filter(User.nickname == temporary_user['nickname']).first():\n LOG.debug(\"User already exists\")\n return {'success': False, 'error': _tn.get(Keywords.nickIsTaken), 'user': None}\n\n temporary_user['password'] = password\n temporary_user['db_group'] = Group.USER\n\n success, info, db_new_user = __create_new_user(temporary_user, _tn.get_lang())\n\n if db_new_user:\n # sending an email and message\n subject = _tn.get(Keywords.accountRegistration)\n body = _tn.get(Keywords.accountWasRegistered).format(temporary_user['firstname'], temporary_user['lastname'],\n temporary_user['email'])\n send_mail(mailer, subject, body, temporary_user['email'], _tn.get_lang())\n send_welcome_notification(db_new_user, _tn)\n\n LOG.debug(\"Set new user in db\")\n return {'success': success, 'error': '', 'user': db_new_user}\n\n LOG.debug(\"New user not found in db\")\n return {\n 'success': False,\n 'error': _tn.get(Keywords.errorTryLateOrContant),\n 'user': None\n }","def create(self, username, password):\n pass","def create_passlocker(username, userpasslock, email):\n new_passlocker = passlocker(username, userpasslock, email)","def create_user(email, password='test', **kwargs):\n user = get_user_model().objects.create(email=email, **kwargs)\n user.set_password(password)\n user.save()\n return user","def send_password_mail(user_name, password):\n from databoard.db_tools import send_password_mail\n send_password_mail(user_name, password)","def createUser(self, name, password, pwencoded=False, email=None):\n # Create user\n self.user = user.User(self.request)\n self.user.name = name\n self.user.email = email\n if not pwencoded:\n password = user.encodePassword(password)\n self.user.enc_password = password\n\n # Validate that we are not modifying existing user data file!\n if self.user.exists():\n self.user = None\n py.test.skip(\"Test user exists, will not override existing user data file!\")\n\n # Save test user\n self.user.save()\n\n # Validate user creation\n if not self.user.exists():\n self.user = None\n py.test.skip(\"Can't create test user\")","def create_email(username, provider):\n print(f\"Your new email is {username}@{provider}.com\")","def create_user(email='user@example.com', password='testpass123'):\n return get_user_model().objects.create_user(email=email, password=password)","def create_new_user(cls, user_email, user_password, user_phone):\n\n new_user = User(email=user_email, password=user_password, mobile_phone=user_phone)\n\n db.session.add(new_user)\n db.session.commit()\n\n print \"Successfully added new user with the email: %s\" % user_email","def create_keystone_v3_project_user(self, domain_name, domain_role,\n project_details, set_context=True):\n domain_id = self.get_keystone_v3_domain_id(domain_name)\n if not isinstance(domain_id, unicode):\n err_msg = (\"Get domain id is failed with reason %s\" % domain_id)\n LOG_OBJ.error(err_msg)\n return err_msg\n\n # Creation of project\n kwargs = {\"name\": project_details['project_name'],\n \"domain_id\": domain_id}\n project_id = self.create_keystone_v3_project(**kwargs)\n if not isinstance(project_id, unicode):\n err_msg = (\"Project creation failed with reason %s\" % project_id)\n LOG_OBJ.error(err_msg)\n return err_msg\n\n # creation of user with adding roles.\n user_id = self.create_keystone_v3_user_and_add_roles(\n project_details, domain_id, domain_role, project_id)\n if not isinstance(user_id, unicode):\n err_msg = (\"Problem while creating user and assigning role.\"\n \"Reason %s\" % user_id)\n LOG_OBJ.error(err_msg)\n return err_msg\n\n # Set the context to that of this new user of the tenant.\n if set_context:\n tokens = []\n for token_scope in [\"domain\", \"project\"]:\n token = self.get_keystone_v3_token(\n project_details['project_name'], domain_name,\n project_details['user_name'], project_details['password'],\n scope=token_scope)\n # NOTE: The token id is of type str not unicode, in v3 case.\n if not isinstance(token, str):\n err_msg = (\"Get v3 user token is failed with \"\n \"reason %s\" % token)\n LOG_OBJ.error(err_msg)\n return err_msg\n tokens.append(token)\n # Set the token\n self.set_tenant_info(project_details['project_name'], tokens[0],\n tokens[1], project_id)\n return project_id","def create(self, name, login, password, email, address=\"\", vat=\"\", jobguid=\"\", executionparams=None):","def create_user(**kwargs):\n User = apps.get_model(settings.AUTH_USER_MODEL)\n user = G(User, **kwargs)\n user.set_password(kwargs.get(\"password\", \"test\"))\n user.save()\n return user","def sample_user(email=user_v['email'], password=user_v['password']):\n return get_user_model().objects.create_user(email, password)","def create_user(self, username=None, email=None, password=None):\n\t\treturn self._create_user(username, email, password)","def task_create_user(task: Task, username, password, userclass='super-user', crypt_m=crypt.METHOD_MD5):\n logger = logging.getLogger(__name__)\n logger.debug('Create user')\n hash_password = crypt.crypt(password, crypt_m)\n config_commands = ['set system login user {} class {}'.format(username, userclass),\n 'set system login user {} authentication encrypted-password {}'.format(username, hash_password)]\n logger.debug(config_commands)\n result = {'completed': [], 'failed': []}\n out = task.run(task=netmiko_send_config, config_commands=config_commands)\n print_result(out)\n if out.failed:\n for host in out.failed_hosts.keys():\n logger.warning(f'Failed task on device {host}')\n task.inventory.hosts[host]['error'] = True\n result['failed'].append(host)\n for host, res in out.items():\n if not res.failed:\n logger.debug('Create user {} with device {} '.format(\n username, task.inventory.hosts[host].name))\n task.inventory.hosts[host]['error'] = False\n result['completed'].append(host)\n# result.append(parse_info(h,r.result))\n return result","def sample_user(email: str = \"test@gmail.com\", password: str = \"testpass\"):\n return get_user_model().objects.create_user(email, password)","def create_user(self, phone, password=None, **extra_fields):\n print(extra_fields)\n if not phone:\n raise ValueError('Users must have an phone number')\n if not password:\n raise ValueError('Users must have a password')\n try:\n extra_fields['role']\n except Exception:\n raise ValueError('Users must have a role')\n try:\n extra_fields['name']\n except Exception:\n raise ValueError('Users must have a name') \n user = self.model(phone=phone, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n\n return user","def create_user(name, email):\n user = register(name, email)\n add_message(user=user, text=config.MSG_WELCOME)\n add_message(user=user, text=config.MSG_UNVERIFIED, can_dismiss=False)\n return user","def create_user_email(user):\n if not user.is_authenticated:\n return False\n \n user.email = \"%s@%s\" % (user.username, settings.DEFAULT_EMAIL_HOST)\n user.save()\n \n return user.email","def cli_create(dbfile, username, email, password, group):\n with atomic(dbfile) as cursor:\n create_user(cursor, username=username, password=password, \n email=email, groups=group)\n click.echo(f\"Created user {username!r} with password {password!r}\")","def create_user(self, email, plan_type, password=None, **kwargs):\n if not email:\n raise ValueError('Users must have an email address!')\n if not plan_type:\n raise ValueError('Each user must have a plan!')\n user = self.model(email=self.normalize_email(email), **kwargs)\n user.set_password(password)\n user.plan = Plan.objects.get(id=plan_type)\n user.save(using=self._db)\n\n return user","def create_user(self, username=\"foo\", email=\"foo@foo.com\", pwd=\"password\"):\n with app.app_context():\n user = User(username=username,\n email=email,\n pwd=bcrypt.generate_password_hash(pwd))\n db.session.add(user)\n db.session.commit()","def user_create(client_id, email, password=None, first_name=None, last_name=None, user_info=None):\n # validate if email contains actually a valid email address:\n try:\n validate_email(email)\n except ValidationError:\n raise ex.UserError(\"please enter a valid email address\")\n # create account\n user = create_user(email)\n user.first_name = first_name\n user.last_name = last_name\n if password:\n user.set_password(password)\n if user_info:\n for (key, value) in user_info.iteritems():\n if key == \"social\" and value is not None: user.meta['social'] = value\n elif key == \"address\" and value is not None: user.meta['address'] = value\n elif key == \"crm\" and value is not None: user.meta['crm'] = value\n elif key == \"local\" and value is not None: user.meta['local'] = value\n \n user_info = user_to_dict(user, include_name=True)\n\n # build success result\n return user_info","def create_user(email, password):\n email_used = AuthUser.query.filter_by(email=email).first()\n if email_used:\n return False, \"Email address has already been used\"\n account = Account(email)\n account.plan_key = 'BASIC'\n account.is_active = True\n account.created = datetime.datetime.now()\n db.session.add(account)\n user = AuthUser(email, password, account)\n user.created = datetime.datetime.now()\n db.session.add(user)\n db.session.commit()\n return user.id, None","def sample_user(email='test@tslabs.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","def _create_user(self, email, password, **extra_fields):\n\n email = self.normalize_email(email)\n #username = self.model.normalize_username(username)\n user = self.model( email=email, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n return user","def create_user(self, email_or_phone, password=None, **extra_fields):\n return self._create_user(email_or_phone, password, False, False, **extra_fields)","def newuser(self, username, password,\n force_password_change_at_next_login_req=False,\n useusernameascn=False, userou=None, surname=None, givenname=None,\n initials=None, profilepath=None, scriptpath=None, homedrive=None,\n homedirectory=None, jobtitle=None, department=None, company=None,\n description=None, mailaddress=None, internetaddress=None,\n telephonenumber=None, physicaldeliveryoffice=None, sd=None,\n setpassword=True, uidnumber=None, gidnumber=None, gecos=None,\n loginshell=None, uid=None, nisdomain=None, unixhome=None,\n smartcard_required=False):\n\n displayname = \"\"\n if givenname is not None:\n displayname += givenname\n\n if initials is not None:\n displayname += ' %s.' % initials\n\n if surname is not None:\n displayname += ' %s' % surname\n\n cn = username\n if useusernameascn is None and displayname != \"\":\n cn = displayname\n\n user_dn = \"CN=%s,%s,%s\" % (cn, (userou or \"CN=Users\"), self.domain_dn())\n\n dnsdomain = ldb.Dn(self, self.domain_dn()).canonical_str().replace(\"/\", \"\")\n user_principal_name = \"%s@%s\" % (username, dnsdomain)\n # The new user record. Note the reliance on the SAMLDB module which\n # fills in the default informations\n ldbmessage = {\"dn\": user_dn,\n \"sAMAccountName\": username,\n \"userPrincipalName\": user_principal_name,\n \"objectClass\": \"user\"}\n\n if smartcard_required:\n ldbmessage[\"userAccountControl\"] = str(dsdb.UF_NORMAL_ACCOUNT |\n dsdb.UF_SMARTCARD_REQUIRED)\n setpassword = False\n\n if surname is not None:\n ldbmessage[\"sn\"] = surname\n\n if givenname is not None:\n ldbmessage[\"givenName\"] = givenname\n\n if displayname != \"\":\n ldbmessage[\"displayName\"] = displayname\n ldbmessage[\"name\"] = displayname\n\n if initials is not None:\n ldbmessage[\"initials\"] = '%s.' % initials\n\n if profilepath is not None:\n ldbmessage[\"profilePath\"] = profilepath\n\n if scriptpath is not None:\n ldbmessage[\"scriptPath\"] = scriptpath\n\n if homedrive is not None:\n ldbmessage[\"homeDrive\"] = homedrive\n\n if homedirectory is not None:\n ldbmessage[\"homeDirectory\"] = homedirectory\n\n if jobtitle is not None:\n ldbmessage[\"title\"] = jobtitle\n\n if department is not None:\n ldbmessage[\"department\"] = department\n\n if company is not None:\n ldbmessage[\"company\"] = company\n\n if description is not None:\n ldbmessage[\"description\"] = description\n\n if mailaddress is not None:\n ldbmessage[\"mail\"] = mailaddress\n\n if internetaddress is not None:\n ldbmessage[\"wWWHomePage\"] = internetaddress\n\n if telephonenumber is not None:\n ldbmessage[\"telephoneNumber\"] = telephonenumber\n\n if physicaldeliveryoffice is not None:\n ldbmessage[\"physicalDeliveryOfficeName\"] = physicaldeliveryoffice\n\n if sd is not None:\n ldbmessage[\"nTSecurityDescriptor\"] = ndr_pack(sd)\n\n ldbmessage2 = None\n if any(map(lambda b: b is not None, (uid, uidnumber, gidnumber, gecos,\n loginshell, nisdomain, unixhome))):\n ldbmessage2 = ldb.Message()\n ldbmessage2.dn = ldb.Dn(self, user_dn)\n if uid is not None:\n ldbmessage2[\"uid\"] = ldb.MessageElement(str(uid), ldb.FLAG_MOD_REPLACE, 'uid')\n if uidnumber is not None:\n ldbmessage2[\"uidNumber\"] = ldb.MessageElement(str(uidnumber), ldb.FLAG_MOD_REPLACE, 'uidNumber')\n if gidnumber is not None:\n ldbmessage2[\"gidNumber\"] = ldb.MessageElement(str(gidnumber), ldb.FLAG_MOD_REPLACE, 'gidNumber')\n if gecos is not None:\n ldbmessage2[\"gecos\"] = ldb.MessageElement(str(gecos), ldb.FLAG_MOD_REPLACE, 'gecos')\n if loginshell is not None:\n ldbmessage2[\"loginShell\"] = ldb.MessageElement(str(loginshell), ldb.FLAG_MOD_REPLACE, 'loginShell')\n if unixhome is not None:\n ldbmessage2[\"unixHomeDirectory\"] = ldb.MessageElement(\n str(unixhome), ldb.FLAG_MOD_REPLACE, 'unixHomeDirectory')\n if nisdomain is not None:\n ldbmessage2[\"msSFU30NisDomain\"] = ldb.MessageElement(\n str(nisdomain), ldb.FLAG_MOD_REPLACE, 'msSFU30NisDomain')\n ldbmessage2[\"msSFU30Name\"] = ldb.MessageElement(\n str(username), ldb.FLAG_MOD_REPLACE, 'msSFU30Name')\n ldbmessage2[\"unixUserPassword\"] = ldb.MessageElement(\n 'ABCD!efgh12345$67890', ldb.FLAG_MOD_REPLACE,\n 'unixUserPassword')\n\n self.transaction_start()\n try:\n self.add(ldbmessage)\n if ldbmessage2:\n self.modify(ldbmessage2)\n\n # Sets the password for it\n if setpassword:\n self.setpassword((\"(distinguishedName=%s)\" %\n ldb.binary_encode(user_dn)),\n password,\n force_password_change_at_next_login_req)\n except:\n self.transaction_cancel()\n raise\n else:\n self.transaction_commit()","def _create_user(self, password, **extra_fields):\n try:\n user = self.model(**extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n return user\n except:\n raise ValueError('ValueError: Cannot create new user')","def create_user(first_name,last_name,email,password):\n\n\tnew_user = User(first_name,last_name,email,password)\n\treturn new_user","def _create_user(self, email, password, first_name, last_name, **extra_fields):\n if not email:\n raise ValueError('The given email must be set')\n email = self.normalize_email(email)\n if not self.model:\n self.model = MHacksUser\n try:\n request = extra_fields.pop('request')\n except KeyError:\n request = None\n user = self.model(email=email, first_name=first_name, last_name=last_name, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n from django.contrib.auth.models import Group\n user.groups.add(Group.objects.get(name=GroupEnum.HACKER))\n user.save(using=self._db)\n from utils import send_verification_email\n if request:\n send_verification_email(user, request)\n return user","def _create_user(self, username, email, password, phone, **extra_fields):\n\n username = self.model.normalize_username(username)\n user = self.model(username=username, email=email, phone=phone, **extra_fields) # using email_id instead of email\n user.set_password(password)\n user.save(using=self._db)\n return user","def create_user(self, username, password):\n return self._user(username=username, password=password, create=True)","def sample_user(email='test@gmail.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","def sample_user(email='test@gmail.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","def sample_user(email='test@gmail.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","def create_user(entry):\n # only works for first + last name currently\n full_name = entry[5].split()\n email = '{first_name}-{client_id}@{domain}'.format(\n first_name=full_name[0].lower(),\n client_id=str(entry[4]).strip(), # unique email for clients with same name\n domain='example.com')\n password = 'test1234'\n dob = timezone.now() - timedelta(days=(365 * random.randint(18, 99)))\n try:\n user = get_user_model().objects.get(email=email)\n except get_user_model().DoesNotExist:\n user = get_user_model().objects.create_user(email=email, first_name=full_name[0],\n last_name=full_name[1], password=password, dob=dob)\n return user","def do_user_create(cs, args):\n cs.users.create(args.username, args.password, args.email, args.realname,\n args.comment)\n print(\"Create user '%s' successfully.\" % args.username)","def sample_user(email='john7ric@mail.com', password='open@123'):\n return get_user_model().objects.create_user(email, password)","def sample_user(email, password, is_doctor, is_hospital_admin):\n return MyUser.objects.create_user(email, is_hospital_admin, is_doctor, password)","def create_new_user():\n return get_user_model().objects.create_user(\n email='test@gmail.com',\n password='test@londodnjisdjfois',\n username='tempusername'\n )","def _create_user(self, ident, password, **extra_fields):\n if not ident:\n raise ValueError('The Email must be set')\n ident = self.normalize_email(ident)\n user = self.model(ident=ident, **extra_fields)\n user.set_password(password)\n\n user.save()\n return user","def create_user(\n self,\n name: str,\n email: str,\n password: str,\n daa_pdf: Optional[bytes],\n institution: str,\n website: str,\n budget: float,\n role: Dict[Any, Any],\n verify_key: VerifyKey,\n ) -> None:\n _private_key = SigningKey.generate()\n\n encoded_pk = _private_key.encode(encoder=HexEncoder).decode(\"utf-8\")\n encoded_vk = _private_key.verify_key.encode(encoder=HexEncoder).decode(\"utf-8\")\n added_by = self.get_user(verify_key).name # type: ignore\n\n # Register the user in the database\n self.signup(\n name=name,\n email=email,\n password=password,\n role=role,\n budget=budget,\n private_key=encoded_pk,\n verify_key=encoded_vk,\n daa_pdf=daa_pdf,\n added_by=added_by,\n institution=institution,\n website=website,\n )","def create_user_service(username: str, email: str, password: str) -> None:\n hashed_password = bcrypt.generate_password_hash(password).decode('UTF-8')\n user = User(username=username, email=email, password=hashed_password)\n db.session.add(user)\n db.session.commit()","def create_user(user_id, password_16char, public_key_32char):\n headers = {'Content-type': 'application/json'}\n payload = {'user_id': user_id\n , 'user_password': password_16char\n , 'public_key': public_key_32char}\n response = requests.post(\"http://localhost:5000/user/createUser\", data=json.dumps(payload), headers=headers)\n return response.text","def _create_user(self, email, password, **extra_fields):\n if not email:\n raise ValueError('The given email must be set')\n email = self.normalize_email(email)\n user = self.model(email=email, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n return user","def _create_user(self, email, first_name, last_name, password, **extra_fields):\n if not email:\n raise ValueError(_('Email Address is required'))\n email = self.normalize_email(email)\n user = self.model(\n email=email,\n first_name=first_name,\n last_name=last_name,\n **extra_fields\n )\n user.set_password(password)\n user.save(using=self._db)\n return user","def create_user(self, user_account, password=None):\n if not user_account:\n raise ValueError('Users must have an user_account')\n\n user = self.model(\n user_account=user_account\n )\n\n user.set_password(password)\n user.save(using=self._db)\n return user","def create_user_object():\n user = User.objects.get_or_create(username='testuser',\n first_name='Test',\n last_name='User',\n email='test@test.com')[0]\n user.set_password('testabc123')\n user.save()\n\n return user","def new_user(request):\r\n rdict = request.params\r\n\r\n u = User()\r\n\r\n u.username = unicode(rdict.get('username'))\r\n if u.username:\r\n u.username = u.username.lower()\r\n u.email = unicode(rdict.get('email')).lower()\r\n passwd = get_random_word(8)\r\n u.password = passwd\r\n u.activated = True\r\n u.is_admin = False\r\n u.api_key = User.gen_api_key()\r\n\r\n try:\r\n DBSession.add(u)\r\n DBSession.flush()\r\n # We need to return the password since the admin added the user\r\n # manually. This is only time we should have/give the original\r\n # password.\r\n ret = dict(u)\r\n ret['random_pass'] = passwd\r\n return _api_response(request, ret)\r\n\r\n except IntegrityError, exc:\r\n # We might try to add a user that already exists.\r\n LOG.error(exc)\r\n request.response.status_int = 400\r\n return _api_response(request, {\r\n 'error': 'Bad Request: User exists.',\r\n })","def create_user_object():\n user = User.objects.get_or_create(username='testuser',\n first_name='Test',\n last_name='User',\n email='test@test.com')[0]\n user.set_password('testabc123')\n user.save()\n return user","def create_user(\n self, email, \n user_name, \n first_name,\n password,\n **other_information):\n\n if not email:\n raise ValueError(\n _('You must be provide an email address!')\n )\n \n email = self.normalize_email(email)\n user = self.model(\n email=email,\n user_name=user_name,\n first_name=first_name,\n **other_information\n )\n\n user.set_password(password)\n user.save()\n\n return user","def create_user(name, password, tenant=None, domain=None):\n manager = get_manager()\n if user_exists(name, domain=domain):\n log(\"A user named '%s' already exists in domain '%s'\" % (name, domain),\n level=DEBUG)\n return\n\n tenant_id = None\n if tenant:\n tenant_id = manager.resolve_tenant_id(tenant, domain=domain)\n if not tenant_id:\n error_out(\"Could not resolve tenant_id for tenant '%s' in domain \"\n \"'%s'\" % (tenant, domain))\n\n domain_id = None\n if domain:\n domain_id = manager.resolve_domain_id(domain)\n if not domain_id:\n error_out('Could not resolve domain_id for domain %s when creating'\n ' user %s' % (domain, name))\n\n manager.create_user(name=name,\n password=password,\n email='juju@localhost',\n tenant_id=tenant_id,\n domain_id=domain_id)\n log(\"Created new user '%s' tenant: '%s' domain: '%s'\" % (name, tenant_id,\n domain_id), level=DEBUG)","def _create_user(self, email, password, **extra_fields):\n\t\tif not email:\n\t\t\traise ValueError('The given email must be set')\n\t\temail = self.normalize_email(email)\n\t\tuser = self.model(email=email, **extra_fields)\n\t\tuser.set_password(password)\n\t\tuser.save(using=self._db)\n\t\treturn user","def _create_user(self, email, password, **extra_fields):\n\t\tif not email:\n\t\t\traise ValueError('The given email must be set')\n\t\temail = self.normalize_email(email)\n\t\tuser = self.model(email=email, **extra_fields)\n\t\tuser.set_password(password)\n\t\tuser.save(using=self._db)\n\t\treturn user","def create_user(self, user_id):\n data = {\n 'email': self._email_for_user_id(user_id),\n 'username': user_id,\n 'password': str(uuid.uuid4()),\n 'name': user_id,\n }\n\n # create user and return it to caller\n return self._post('/users', data=data)","def create_user(self, email=None, name=None, password=None, phone=None):\n # if not email:\n # raise ValueError('Users must have an email address')\n\n user = self.model(\n email=email,\n name=name,\n phone=phone\n )\n\n user.set_password(password)\n user.save(using=self._db)\n return user","def create_user(user_name: str):\n user = User()\n user.username = user_name\n user.save()\n return user","def __init__(self, user, password, _recipients, templatedir='templates'):\n\n self.user = user\n self.password = password\n self.recipient = _recipients if type (_recipients) is list else [_recipients]\n self.server = 'smtp.gmail.com'\n self.port = 587\n\n if os.path.isdir(templatedir):\n self.templatedir = templatedir\n else:\n self.templatedir = os.path.join(os.path.abspath(os.path.dirname(__file__)), templatedir)\n\n self.env = Environment(loader=FileSystemLoader(self.templatedir))","def sample_user(email='scott@test.com', password='testpass'):\n return get_user_model().objects.create_user(email, password)","def user(**kwargs):\n defaults = {}\n if 'username' not in kwargs:\n defaults['username'] = ''.join(random.choice(letters)\n for x in xrange(15))\n if 'email' not in kwargs:\n defaults['email'] = ''.join(\n random.choice(letters) for x in xrange(10)) + '@example.com'\n defaults.update(kwargs)\n user = User(**defaults)\n user.set_password(kwargs.get('password', 'testpass'))\n return user","def _create_user(self, email, password, **extra_fields):\n if not email:\n raise ValueError('The given email must be set')\n email = self.normalize_email(email)\n user = self.model(email=email, **extra_fields)\n user.set_password(password)\n user.save(using=self._db)\n print(\"create user\")\n return user","def create_user(username):\n\n password = getpass.getpass('Password for {0}: '.format(username))\n confirm = getpass.getpass('Again: ')\n\n if password != confirm:\n print >> sys.stderr, \"Passwords don't match\"\n\n sys.exit(1)\n\n with transaction.manager:\n Users(username, password).save()","def create_a_user(self, username='fry', email='fry@futur.ama', password='Qwerty!234'):\n user = User.objects.create_user(username, email, password)\n user.save()\n return user","def create_user(fname, lname, email, password, phone_number):\n user = User(fname = fname, lname = lname , email = email ,password = password, phone_number = phone_number)\n #setting password hash\n user.set_password(password)\n db.session.add(user)\n db.session.commit()\n\n return user"],"string":"[\n \"def create_new_credential(account,userName,password):\\n new_credential = Credentials(account,userName,password)\\n return new_credential\",\n \"def CreateNewSmtpUser(s):\\n payload = ['adduser %s %s\\\\n' % (FLAGS.exploit_user, FLAGS.exploit_password),\\n 'quit\\\\n']\\n SendPayload(s, payload)\\n logging.info('Created new user %s/%s' % (\\n FLAGS.exploit_user, FLAGS.exploit_password))\\n s.close()\",\n \"def create_credential(self, body=None):\\r\\n return self.post(self.credentials_path, body=body)\",\n \"def create_user(BrokerId=None, ConsoleAccess=None, Groups=None, Password=None, Username=None):\\n pass\",\n \"def create_user(UserName=None, MessageAction=None, FirstName=None, LastName=None, AuthenticationType=None):\\n pass\",\n \"def Create( profile_name,\\r\\n host,\\r\\n username=None,\\r\\n password=None,\\r\\n port=26,\\r\\n from_name=None,\\r\\n from_email=None,\\r\\n ssl=False,\\r\\n output_stream=sys.stdout,\\r\\n ):\\r\\n\\r\\n if not from_name and not from_email:\\r\\n raise CommandLine.UsageException(\\\"'from_name' or 'from_email' must be provided\\\")\\r\\n\\r\\n mailer = SmtpMailer( host,\\r\\n username=username,\\r\\n password=password,\\r\\n port=port,\\r\\n from_name=from_name,\\r\\n from_email=from_email,\\r\\n ssl=ssl,\\r\\n )\\r\\n mailer.Save(profile_name)\\r\\n\\r\\n output_stream.write(\\\"The profile '{}' has been created.\\\\n\\\".format(profile_name))\",\n \"def create_user_credentials(storage_type, storage_id, space_name, client_ip,\\n user_details):\\n user_id = user_details[\\\"id\\\"]\\n if user_id == \\\"0\\\":\\n return PosixCredentials(0, 0)\\n\\n uid = gid = gen_storage_id(user_id)\\n return PosixCredentials(uid, gid)\",\n \"def send_new_credentials(email,name,password,phone,shop,address,lead_mail,fname,mem_mail,website):\\n\\n logger.info(\\\"in send lead mail task\\\")\\n return send_lead_generate(email,name,password,phone,shop,address,lead_mail,fname,mem_mail,website)\",\n \"def create_user(email, password, f_name, l_name):\\n pass\",\n \"def create_email(user):\\n if 'research' in user.get_domains():\\n domain = 'research'\\n else: domain = 'academic'\\n subject = \\\"ECE/CIS Account Created\\\"\\n helprequest = \\\"https://www.eecis.udel.edu/service\\\"\\n \\n message = \\\"Your ECE/CIS %s account has been created with the username: %s\\\\n\\\\n\\\" % (domain, user.username)\\n message += \\\"Please do not reply to this message. If you need assistance with your account, please visit:\\\\n\\\"\\n message += \\\"%s\\\\n\\\\n\\\" % helprequest\\n message += \\\"-- EE/CIS Labstaff\\\\n\\\"\\n\\n send('account@eecis.udel.edu', 'ECE/CIS Account System', \\\\\\n [user.email], subject, message, MAILHOST)\",\n \"def create(self, username, password, email):\\n pass\",\n \"def create_user(context, params):\\n form_user = dict()\\n # form_user['edited_by'] = context.user\\n if params.get('username'):\\n form_user['username'] = params.get('username')\\n else:\\n form_user['username'] = create_username(params) # 'email_user{}'.format(MISUser.objects.latest('id').id + 1\\n form_user['first_name'] = params.get('first_name')\\n form_user['last_name'] = params.get('last_name')\\n form_person = create_person(params)\\n form_user.update(form_person)\\n user = User.objects.create(**form_user)\\n user.set_password(params.get('password'))\\n\\n email = {'label': 'Work', 'val': params.get('email'), 'person': user, 'is_main': True}\\n create_email(context, email)\\n\\n user.save()\\n return user\",\n \"def create_user(self, conn, name, password, group):\\n user = conn.user.allocate(name, password, \\\"\\\", [group])\\n return user\",\n \"def m_credential_create(node_name, credential_hash, participantDID):\\n pass\",\n \"def create_server(host, port, uid, pwd):\\r\\n s = smtplib.SMTP(host, port)\\r\\n s.starttls()\\r\\n s.login(\\r\\n uid,\\r\\n pwd\\r\\n )\\r\\n return s\",\n \"def create_service_credentials(user, new_roles=None):\\n tenant = config('service-tenant')\\n if not tenant:\\n raise Exception(\\\"No service tenant provided in config\\\")\\n\\n domain = None\\n if get_api_version() > 2:\\n domain = DEFAULT_DOMAIN\\n passwd = create_user_credentials(user, get_service_password,\\n set_service_password,\\n tenant=tenant, new_roles=new_roles,\\n grants=[config('admin-role')],\\n domain=domain)\\n if get_api_version() > 2:\\n # Create account in SERVICE_DOMAIN as well using same password\\n domain = SERVICE_DOMAIN\\n passwd = create_user_credentials(user, get_service_password,\\n set_service_password,\\n tenant=tenant, new_roles=new_roles,\\n grants=[config('admin-role')],\\n domain=domain)\\n return passwd\",\n \"async def create_new_user(*, user: User):\\n with Session(engine) as session:\\n user.password = simple_hash(user.name, user.password) #Hashing password for security\\n session.add(user)\\n session.commit()\\n return {\\\"message\\\": \\\"User {user_id} created\\\".format(user_id = user.id)}\",\n \"def add_user(self, user, pw):\\n self.db.execute(\\\"INSERT INTO user_credentials VALUES (?, ?)\\\", [user, pw])\\n self.db.commit()\",\n \"def create(self, credentials):\\n return User.objects.create_user(\\n credentials['username'],\\n credentials['email'],\\n credentials['password']\\n )\",\n \"def newuser(lp, creds, username=None):\\n\\n names = guess_names_from_smbconf(lp, None, None)\\n db = Ldb(url=get_ldb_url(lp, creds, names), session_info=system_session(), \\n credentials=creds, lp=lp)\\n user_dn = get_user_dn(db, \\\"CN=Users,%s\\\" % names.domaindn, username)\\n if user_dn:\\n extended_user = \\\"\\\"\\\"\\ndn: %(user_dn)s\\nchangetype: modify\\nadd: mailNickName\\nmailNickname: %(username)s\\nadd: homeMDB\\nhomeMDB: CN=Mailbox Store (%(netbiosname)s),CN=First Storage Group,CN=InformationStore,CN=%(netbiosname)s,CN=Servers,CN=First Administrative Group,CN=Administrative Groups,CN=%(firstorg)s,CN=Microsoft Exchange,CN=Services,CN=Configuration,%(domaindn)s\\nadd: homeMTA\\nhomeMTA: CN=Mailbox Store (%(netbiosname)s),CN=First Storage Group,CN=InformationStore,CN=%(netbiosname)s,CN=Servers,CN=First Administrative Group,CN=Administrative Groups,CN=%(firstorg)s,CN=Microsoft Exchange,CN=Services,CN=Configuration,%(domaindn)s\\nadd: legacyExchangeDN\\nlegacyExchangeDN: /o=%(firstorg)s/ou=First Administrative Group/cn=Recipients/cn=%(username)s\\nadd: proxyAddresses\\nproxyAddresses: =EX:/o=%(firstorg)s/ou=First Administrative Group/cn=Recipients/cn=%(username)s\\nproxyAddresses: smtp:postmaster@%(dnsdomain)s\\nproxyAddresses: X400:c=US;a= ;p=First Organizati;o=Exchange;s=%(username)s\\nproxyAddresses: SMTP:%(username)s@%(dnsdomain)s\\nreplace: msExchUserAccountControl\\nmsExchUserAccountControl: 0\\n\\\"\\\"\\\"\\n ldif_value = extended_user % {\\\"user_dn\\\": user_dn,\\n \\\"username\\\": username,\\n \\\"netbiosname\\\": names.netbiosname,\\n \\\"firstorg\\\": names.firstorg,\\n \\\"domaindn\\\": names.domaindn,\\n \\\"dnsdomain\\\": names.dnsdomain}\\n db.modify_ldif(ldif_value)\\n\\n res = db.search(base=user_dn, scope=SCOPE_BASE, attrs=[\\\"*\\\"])\\n if len(res) == 1:\\n record = res[0]\\n else:\\n raise Exception, \\\\\\n \\\"this should never happen as we just modified the record...\\\"\\n record_keys = map(lambda x: x.lower(), record.keys())\\n\\n if \\\"displayname\\\" not in record_keys:\\n extended_user = \\\"dn: %s\\\\nadd: displayName\\\\ndisplayName: %s\\\\n\\\" % (user_dn, username)\\n db.modify_ldif(extended_user)\\n\\n if \\\"mail\\\" not in record_keys:\\n extended_user = \\\"dn: %s\\\\nadd: mail\\\\nmail: %s@%s\\\\n\\\" % (user_dn, username, names.dnsdomain)\\n db.modify_ldif(extended_user)\\n\\n print \\\"[+] User %s extended and enabled\\\" % username\\n else:\\n print \\\"[!] User '%s' not found\\\" % username\",\n \"def new_credentials(site_name, user_name, password):\\n new_credentials = Credentials(site_name, user_name, password)\\n return new_credentials\",\n \"def create_user_credentials(user, passwd_get_callback, passwd_set_callback,\\n tenant=None, new_roles=None,\\n grants=None, domain=None):\\n passwd = passwd_get_callback(user)\\n if not passwd:\\n log(\\\"Unable to retrieve password for user '{}'\\\".format(user),\\n level=INFO)\\n return\\n\\n log(\\\"Creating service credentials for '%s'\\\" % user, level=DEBUG)\\n if user_exists(user, domain=domain):\\n log(\\\"User '%s' already exists\\\" % (user), level=DEBUG)\\n # NOTE(dosaboy): see LP #1648677\\n if is_password_changed(user, passwd):\\n update_user_password(user, passwd, domain)\\n else:\\n create_user(user, passwd, tenant=tenant, domain=domain)\\n\\n passwd_set_callback(passwd, user=user)\\n\\n if grants:\\n for role in grants:\\n # grant role on project\\n grant_role(user, role, tenant=tenant, user_domain=domain,\\n project_domain=domain)\\n else:\\n log(\\\"No role grants requested for user '%s'\\\" % (user), level=DEBUG)\\n\\n if new_roles:\\n # Allow the remote service to request creation of any additional roles.\\n # Currently used by Swift and Ceilometer.\\n for role in new_roles:\\n log(\\\"Creating requested role '%s'\\\" % role, level=DEBUG)\\n create_role(role, user=user, tenant=tenant, domain=domain)\\n\\n return passwd\",\n \"def _create_user(self, username, password, domain_id, project_id):\\n request = {\\n \\\"user\\\": {\\n \\\"name\\\": username,\\n \\\"password\\\": password,\\n \\\"domain_id\\\": domain_id,\\n \\\"default_project_id\\\": project_id,\\n \\\"description\\\": \\\"description\\\",\\n \\\"email\\\": \\\"test@example.com\\\",\\n \\\"enabled\\\": True,\\n }\\n }\\n response = self.client.post(USER_PATH, data=json.dumps(request),\\n headers=HEADERS)\\n if response.status_code == 409:\\n return\\n elif response.status_code == 201:\\n return response.json()\\n else:\\n raise SystemExit(\\\"Failed to create test user.\\\")\",\n \"def create_user(self):\\n u = USER.objects.create(username='test_user1',\\n email='test_email@example.com', )\\n u.set_password('test_password')\\n u.save()\\n self.user = u\\n return u\",\n \"def create_user(\\n screen_name: str,\\n email_address: str,\\n password: str,\\n first_names: Optional[str],\\n last_name: Optional[str],\\n site_id: SiteID,\\n *,\\n consents: Optional[Set[Consent]] = None,\\n) -> Tuple[User, UserAccountCreated]:\\n # user with details, password, and roles\\n user, event = create_basic_user(\\n screen_name,\\n email_address,\\n password,\\n first_names=first_names,\\n last_name=last_name,\\n )\\n\\n # consents\\n if consents:\\n for consent in consents:\\n # Insert missing user ID.\\n consent = consent_service.build_consent(\\n user.id,\\n consent.subject_id,\\n consent.expressed_at,\\n )\\n db.session.add(consent)\\n\\n db.session.commit()\\n\\n request_email_address_confirmation(user, email_address, site_id)\\n\\n return user, event\",\n \"def createNewUser(name, account, auth, email, pwd, group, expiry, node):\\n \\n #Check if the user creation was succesful\\n if hl.createUser(name, account, auth, email = email, passwd = pwd, group = group, expiry = expiry, node = node):\\n user = hl.getUser(\\\"Email\\\", email)\\n\\n if(auth == \\\"Email\\\"):\\n subjectTitle = \\\"OneGroup account keys\\\"\\n recipientEmail =[email]\\n bodyMessage = \\\"here are your keys\\\"\\n attachmentName = user['Keys'] + '.ovpn'\\n filename = \\\"{}/{}\\\".format(keys_dir,attachmentName)\\n attachmentFilePath = filename\\n emailMessage(subjectTitle, recipientEmail, bodyMessage,attachmentName, attachmentFilePath)\\n\\n elif(auth == \\\"Passphrase\\\"):\\n subjectTitle = \\\"OneGroup account details\\\"\\n recipientEmail = [email]\\n bodyMessage = \\\"Your login details are\\\\n Email :\\\" + str(email) + \\\"\\\\nPassword :\\\" + str(pwd)\\n emailMessage(subjectTitle, recipientEmail, bodyMessage)\\n return True\\n else:\\n return False\",\n \"def create_user(self, uname, name, password=None):\\r\\n\\r\\n if not uname:\\r\\n return _('Must provide username')\\r\\n if not name:\\r\\n return _('Must provide full name')\\r\\n\\r\\n email_domain = getattr(settings, 'SSL_AUTH_EMAIL_DOMAIN', 'MIT.EDU')\\r\\n\\r\\n msg = u''\\r\\n if settings.FEATURES['AUTH_USE_CERTIFICATES']:\\r\\n if not '@' in uname:\\r\\n email = '{0}@{1}'.format(uname, email_domain)\\r\\n else:\\r\\n email = uname\\r\\n if not email.endswith('@{0}'.format(email_domain)):\\r\\n msg += u'{0} @{1}'.format(_('email must end in'), email_domain)\\r\\n return msg\\r\\n mit_domain = 'ssl:MIT'\\r\\n if ExternalAuthMap.objects.filter(external_id=email,\\r\\n external_domain=mit_domain):\\r\\n msg += _('Failed - email {0} already exists as '\\r\\n 'external_id').format(email)\\r\\n return msg\\r\\n new_password = generate_password()\\r\\n else:\\r\\n if not password:\\r\\n return _('Password must be supplied if not using certificates')\\r\\n\\r\\n email = uname\\r\\n\\r\\n if not '@' in email:\\r\\n msg += _('email address required (not username)')\\r\\n return msg\\r\\n new_password = password\\r\\n\\r\\n user = User(username=uname, email=email, is_active=True)\\r\\n user.set_password(new_password)\\r\\n try:\\r\\n user.save()\\r\\n except IntegrityError:\\r\\n msg += _('Oops, failed to create user {0}, '\\r\\n 'IntegrityError').format(user)\\r\\n return msg\\r\\n\\r\\n reg = Registration()\\r\\n reg.register(user)\\r\\n\\r\\n profile = UserProfile(user=user)\\r\\n profile.name = name\\r\\n profile.save()\\r\\n\\r\\n if settings.FEATURES['AUTH_USE_CERTIFICATES']:\\r\\n credential_string = getattr(settings, 'SSL_AUTH_DN_FORMAT_STRING',\\r\\n '/C=US/ST=Massachusetts/O=Massachusetts Institute of Technology/OU=Client CA v1/CN={0}/emailAddress={1}')\\r\\n credentials = credential_string.format(name, email)\\r\\n eamap = ExternalAuthMap(\\r\\n external_id=email,\\r\\n external_email=email,\\r\\n external_domain=mit_domain,\\r\\n external_name=name,\\r\\n internal_password=new_password,\\r\\n external_credentials=json.dumps(credentials),\\r\\n )\\r\\n eamap.user = user\\r\\n eamap.dtsignup = timezone.now()\\r\\n eamap.save()\\r\\n\\r\\n msg += _('User {0} created successfully!').format(user)\\r\\n return msg\",\n \"def setupUser(con, options, dbName, userName, userInfo):\\n if checkUsername(userName):\\n trace(\\\"For dbName='%s', create user '%s'\\\" % (dbName, userName))\\n userPassword = userInfo[\\\"password\\\"]\\n optionalDbExecute(con, options, \\\"create user %s with password '%s'\\\" % (userName, userPassword))\",\n \"def create_user(user, first_name, last_name, major, bio):\\n return userAccount.objects.create(user=user, first_name=first_name, last_name=last_name, major=major, bio=bio)\",\n \"def send_email( user, password ):\\n \\n mail = Mailer( host = EMAIL['host'], \\n port = EMAIL['port'],\\n use_tls = EMAIL['use_tls'], \\n usr = EMAIL['user'], \\n pwd = EMAIL['password']\\n )\\n \\n message = Message( From = 'help@rxmedaccess.com',\\n To = [user.email],\\n Subject = \\\"Password Reset\\\"\\n )\\n \\n body = \\\"\\\"\\\"Your new password for {} is {}\\n You can reset it to what you like on your settings page once you log in with\\n this password\\n \\\"\\\"\\\".format(__name__, password )\\n\\n message.Body = body\\n try:\\n mail.send(message)\\n except Exception as e:\\n log.error( 'Send mail error: {}'.format( str(e) ) )\",\n \"def create_user(ctx, db_username, db_password, project_name):\\n project = ctx.obj.groups.byName[project_name].get().data\\n user = cmd.ensure_admin_user(\\n client=ctx.obj, project_id=project.id, username=db_username,\\n password=db_password)\\n pprint(user)\",\n \"def create_user(uname,password):\\n new_user = User(uname,password)\\n return new_user\",\n \"def create_user(self, user, user_opt={}):\\n assert user.id is None\\n if self.dryrun:\\n self.logger.debug(\\\"Would create user %s in zabbix\\\", user.alias)\\n return\\n\\n random_passwd = ''.join(random.sample(string.ascii_letters + string.digits, 32))\\n\\n user_req = {\\n 'autologin': 0,\\n 'type': 1,\\n 'usrgrps': [{'usrgrpid': str(id)} for id in user.groups],\\n 'passwd': random_passwd,\\n \\\"alias\\\": user.alias,\\n \\\"name\\\": user.name,\\n \\\"surname\\\": user.surname,\\n }\\n user_req.update(user_opt)\\n\\n result = self.conn.user.create(user_req)\\n user.id = result[\\\"userids\\\"][0]\\n self.logger.debug(\\\"Created user %s in zabbix, id: %s\\\", user.alias, user.id)\",\n \"def create_user(self):\\n User.objects.create_user('test', 'testing@test.com', 'testing')\",\n \"def create_user(open_ldap, smtp, entries):\\n try:\\n if open_ldap.ldap_insert(entries):\\n smtp.send_email(entries)\\n return True\\n else:\\n return False\\n except Exception as e:\\n print('ERROR - ', e)\\n return\",\n \"def set_new_user(mailer: Mailer, user_data: Dict[str, Any], password: str, _tn: Translator) -> Dict[str, Any]:\\n # copy the dict to not change the mutable structure\\n temporary_user = dict(user_data)\\n\\n if DBDiscussionSession.query(User).filter(User.nickname == temporary_user['nickname']).first():\\n LOG.debug(\\\"User already exists\\\")\\n return {'success': False, 'error': _tn.get(Keywords.nickIsTaken), 'user': None}\\n\\n temporary_user['password'] = password\\n temporary_user['db_group'] = Group.USER\\n\\n success, info, db_new_user = __create_new_user(temporary_user, _tn.get_lang())\\n\\n if db_new_user:\\n # sending an email and message\\n subject = _tn.get(Keywords.accountRegistration)\\n body = _tn.get(Keywords.accountWasRegistered).format(temporary_user['firstname'], temporary_user['lastname'],\\n temporary_user['email'])\\n send_mail(mailer, subject, body, temporary_user['email'], _tn.get_lang())\\n send_welcome_notification(db_new_user, _tn)\\n\\n LOG.debug(\\\"Set new user in db\\\")\\n return {'success': success, 'error': '', 'user': db_new_user}\\n\\n LOG.debug(\\\"New user not found in db\\\")\\n return {\\n 'success': False,\\n 'error': _tn.get(Keywords.errorTryLateOrContant),\\n 'user': None\\n }\",\n \"def create(self, username, password):\\n pass\",\n \"def create_passlocker(username, userpasslock, email):\\n new_passlocker = passlocker(username, userpasslock, email)\",\n \"def create_user(email, password='test', **kwargs):\\n user = get_user_model().objects.create(email=email, **kwargs)\\n user.set_password(password)\\n user.save()\\n return user\",\n \"def send_password_mail(user_name, password):\\n from databoard.db_tools import send_password_mail\\n send_password_mail(user_name, password)\",\n \"def createUser(self, name, password, pwencoded=False, email=None):\\n # Create user\\n self.user = user.User(self.request)\\n self.user.name = name\\n self.user.email = email\\n if not pwencoded:\\n password = user.encodePassword(password)\\n self.user.enc_password = password\\n\\n # Validate that we are not modifying existing user data file!\\n if self.user.exists():\\n self.user = None\\n py.test.skip(\\\"Test user exists, will not override existing user data file!\\\")\\n\\n # Save test user\\n self.user.save()\\n\\n # Validate user creation\\n if not self.user.exists():\\n self.user = None\\n py.test.skip(\\\"Can't create test user\\\")\",\n \"def create_email(username, provider):\\n print(f\\\"Your new email is {username}@{provider}.com\\\")\",\n \"def create_user(email='user@example.com', password='testpass123'):\\n return get_user_model().objects.create_user(email=email, password=password)\",\n \"def create_new_user(cls, user_email, user_password, user_phone):\\n\\n new_user = User(email=user_email, password=user_password, mobile_phone=user_phone)\\n\\n db.session.add(new_user)\\n db.session.commit()\\n\\n print \\\"Successfully added new user with the email: %s\\\" % user_email\",\n \"def create_keystone_v3_project_user(self, domain_name, domain_role,\\n project_details, set_context=True):\\n domain_id = self.get_keystone_v3_domain_id(domain_name)\\n if not isinstance(domain_id, unicode):\\n err_msg = (\\\"Get domain id is failed with reason %s\\\" % domain_id)\\n LOG_OBJ.error(err_msg)\\n return err_msg\\n\\n # Creation of project\\n kwargs = {\\\"name\\\": project_details['project_name'],\\n \\\"domain_id\\\": domain_id}\\n project_id = self.create_keystone_v3_project(**kwargs)\\n if not isinstance(project_id, unicode):\\n err_msg = (\\\"Project creation failed with reason %s\\\" % project_id)\\n LOG_OBJ.error(err_msg)\\n return err_msg\\n\\n # creation of user with adding roles.\\n user_id = self.create_keystone_v3_user_and_add_roles(\\n project_details, domain_id, domain_role, project_id)\\n if not isinstance(user_id, unicode):\\n err_msg = (\\\"Problem while creating user and assigning role.\\\"\\n \\\"Reason %s\\\" % user_id)\\n LOG_OBJ.error(err_msg)\\n return err_msg\\n\\n # Set the context to that of this new user of the tenant.\\n if set_context:\\n tokens = []\\n for token_scope in [\\\"domain\\\", \\\"project\\\"]:\\n token = self.get_keystone_v3_token(\\n project_details['project_name'], domain_name,\\n project_details['user_name'], project_details['password'],\\n scope=token_scope)\\n # NOTE: The token id is of type str not unicode, in v3 case.\\n if not isinstance(token, str):\\n err_msg = (\\\"Get v3 user token is failed with \\\"\\n \\\"reason %s\\\" % token)\\n LOG_OBJ.error(err_msg)\\n return err_msg\\n tokens.append(token)\\n # Set the token\\n self.set_tenant_info(project_details['project_name'], tokens[0],\\n tokens[1], project_id)\\n return project_id\",\n \"def create(self, name, login, password, email, address=\\\"\\\", vat=\\\"\\\", jobguid=\\\"\\\", executionparams=None):\",\n \"def create_user(**kwargs):\\n User = apps.get_model(settings.AUTH_USER_MODEL)\\n user = G(User, **kwargs)\\n user.set_password(kwargs.get(\\\"password\\\", \\\"test\\\"))\\n user.save()\\n return user\",\n \"def sample_user(email=user_v['email'], password=user_v['password']):\\n return get_user_model().objects.create_user(email, password)\",\n \"def create_user(self, username=None, email=None, password=None):\\n\\t\\treturn self._create_user(username, email, password)\",\n \"def task_create_user(task: Task, username, password, userclass='super-user', crypt_m=crypt.METHOD_MD5):\\n logger = logging.getLogger(__name__)\\n logger.debug('Create user')\\n hash_password = crypt.crypt(password, crypt_m)\\n config_commands = ['set system login user {} class {}'.format(username, userclass),\\n 'set system login user {} authentication encrypted-password {}'.format(username, hash_password)]\\n logger.debug(config_commands)\\n result = {'completed': [], 'failed': []}\\n out = task.run(task=netmiko_send_config, config_commands=config_commands)\\n print_result(out)\\n if out.failed:\\n for host in out.failed_hosts.keys():\\n logger.warning(f'Failed task on device {host}')\\n task.inventory.hosts[host]['error'] = True\\n result['failed'].append(host)\\n for host, res in out.items():\\n if not res.failed:\\n logger.debug('Create user {} with device {} '.format(\\n username, task.inventory.hosts[host].name))\\n task.inventory.hosts[host]['error'] = False\\n result['completed'].append(host)\\n# result.append(parse_info(h,r.result))\\n return result\",\n \"def sample_user(email: str = \\\"test@gmail.com\\\", password: str = \\\"testpass\\\"):\\n return get_user_model().objects.create_user(email, password)\",\n \"def create_user(self, phone, password=None, **extra_fields):\\n print(extra_fields)\\n if not phone:\\n raise ValueError('Users must have an phone number')\\n if not password:\\n raise ValueError('Users must have a password')\\n try:\\n extra_fields['role']\\n except Exception:\\n raise ValueError('Users must have a role')\\n try:\\n extra_fields['name']\\n except Exception:\\n raise ValueError('Users must have a name') \\n user = self.model(phone=phone, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n\\n return user\",\n \"def create_user(name, email):\\n user = register(name, email)\\n add_message(user=user, text=config.MSG_WELCOME)\\n add_message(user=user, text=config.MSG_UNVERIFIED, can_dismiss=False)\\n return user\",\n \"def create_user_email(user):\\n if not user.is_authenticated:\\n return False\\n \\n user.email = \\\"%s@%s\\\" % (user.username, settings.DEFAULT_EMAIL_HOST)\\n user.save()\\n \\n return user.email\",\n \"def cli_create(dbfile, username, email, password, group):\\n with atomic(dbfile) as cursor:\\n create_user(cursor, username=username, password=password, \\n email=email, groups=group)\\n click.echo(f\\\"Created user {username!r} with password {password!r}\\\")\",\n \"def create_user(self, email, plan_type, password=None, **kwargs):\\n if not email:\\n raise ValueError('Users must have an email address!')\\n if not plan_type:\\n raise ValueError('Each user must have a plan!')\\n user = self.model(email=self.normalize_email(email), **kwargs)\\n user.set_password(password)\\n user.plan = Plan.objects.get(id=plan_type)\\n user.save(using=self._db)\\n\\n return user\",\n \"def create_user(self, username=\\\"foo\\\", email=\\\"foo@foo.com\\\", pwd=\\\"password\\\"):\\n with app.app_context():\\n user = User(username=username,\\n email=email,\\n pwd=bcrypt.generate_password_hash(pwd))\\n db.session.add(user)\\n db.session.commit()\",\n \"def user_create(client_id, email, password=None, first_name=None, last_name=None, user_info=None):\\n # validate if email contains actually a valid email address:\\n try:\\n validate_email(email)\\n except ValidationError:\\n raise ex.UserError(\\\"please enter a valid email address\\\")\\n # create account\\n user = create_user(email)\\n user.first_name = first_name\\n user.last_name = last_name\\n if password:\\n user.set_password(password)\\n if user_info:\\n for (key, value) in user_info.iteritems():\\n if key == \\\"social\\\" and value is not None: user.meta['social'] = value\\n elif key == \\\"address\\\" and value is not None: user.meta['address'] = value\\n elif key == \\\"crm\\\" and value is not None: user.meta['crm'] = value\\n elif key == \\\"local\\\" and value is not None: user.meta['local'] = value\\n \\n user_info = user_to_dict(user, include_name=True)\\n\\n # build success result\\n return user_info\",\n \"def create_user(email, password):\\n email_used = AuthUser.query.filter_by(email=email).first()\\n if email_used:\\n return False, \\\"Email address has already been used\\\"\\n account = Account(email)\\n account.plan_key = 'BASIC'\\n account.is_active = True\\n account.created = datetime.datetime.now()\\n db.session.add(account)\\n user = AuthUser(email, password, account)\\n user.created = datetime.datetime.now()\\n db.session.add(user)\\n db.session.commit()\\n return user.id, None\",\n \"def sample_user(email='test@tslabs.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"def _create_user(self, email, password, **extra_fields):\\n\\n email = self.normalize_email(email)\\n #username = self.model.normalize_username(username)\\n user = self.model( email=email, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"def create_user(self, email_or_phone, password=None, **extra_fields):\\n return self._create_user(email_or_phone, password, False, False, **extra_fields)\",\n \"def newuser(self, username, password,\\n force_password_change_at_next_login_req=False,\\n useusernameascn=False, userou=None, surname=None, givenname=None,\\n initials=None, profilepath=None, scriptpath=None, homedrive=None,\\n homedirectory=None, jobtitle=None, department=None, company=None,\\n description=None, mailaddress=None, internetaddress=None,\\n telephonenumber=None, physicaldeliveryoffice=None, sd=None,\\n setpassword=True, uidnumber=None, gidnumber=None, gecos=None,\\n loginshell=None, uid=None, nisdomain=None, unixhome=None,\\n smartcard_required=False):\\n\\n displayname = \\\"\\\"\\n if givenname is not None:\\n displayname += givenname\\n\\n if initials is not None:\\n displayname += ' %s.' % initials\\n\\n if surname is not None:\\n displayname += ' %s' % surname\\n\\n cn = username\\n if useusernameascn is None and displayname != \\\"\\\":\\n cn = displayname\\n\\n user_dn = \\\"CN=%s,%s,%s\\\" % (cn, (userou or \\\"CN=Users\\\"), self.domain_dn())\\n\\n dnsdomain = ldb.Dn(self, self.domain_dn()).canonical_str().replace(\\\"/\\\", \\\"\\\")\\n user_principal_name = \\\"%s@%s\\\" % (username, dnsdomain)\\n # The new user record. Note the reliance on the SAMLDB module which\\n # fills in the default informations\\n ldbmessage = {\\\"dn\\\": user_dn,\\n \\\"sAMAccountName\\\": username,\\n \\\"userPrincipalName\\\": user_principal_name,\\n \\\"objectClass\\\": \\\"user\\\"}\\n\\n if smartcard_required:\\n ldbmessage[\\\"userAccountControl\\\"] = str(dsdb.UF_NORMAL_ACCOUNT |\\n dsdb.UF_SMARTCARD_REQUIRED)\\n setpassword = False\\n\\n if surname is not None:\\n ldbmessage[\\\"sn\\\"] = surname\\n\\n if givenname is not None:\\n ldbmessage[\\\"givenName\\\"] = givenname\\n\\n if displayname != \\\"\\\":\\n ldbmessage[\\\"displayName\\\"] = displayname\\n ldbmessage[\\\"name\\\"] = displayname\\n\\n if initials is not None:\\n ldbmessage[\\\"initials\\\"] = '%s.' % initials\\n\\n if profilepath is not None:\\n ldbmessage[\\\"profilePath\\\"] = profilepath\\n\\n if scriptpath is not None:\\n ldbmessage[\\\"scriptPath\\\"] = scriptpath\\n\\n if homedrive is not None:\\n ldbmessage[\\\"homeDrive\\\"] = homedrive\\n\\n if homedirectory is not None:\\n ldbmessage[\\\"homeDirectory\\\"] = homedirectory\\n\\n if jobtitle is not None:\\n ldbmessage[\\\"title\\\"] = jobtitle\\n\\n if department is not None:\\n ldbmessage[\\\"department\\\"] = department\\n\\n if company is not None:\\n ldbmessage[\\\"company\\\"] = company\\n\\n if description is not None:\\n ldbmessage[\\\"description\\\"] = description\\n\\n if mailaddress is not None:\\n ldbmessage[\\\"mail\\\"] = mailaddress\\n\\n if internetaddress is not None:\\n ldbmessage[\\\"wWWHomePage\\\"] = internetaddress\\n\\n if telephonenumber is not None:\\n ldbmessage[\\\"telephoneNumber\\\"] = telephonenumber\\n\\n if physicaldeliveryoffice is not None:\\n ldbmessage[\\\"physicalDeliveryOfficeName\\\"] = physicaldeliveryoffice\\n\\n if sd is not None:\\n ldbmessage[\\\"nTSecurityDescriptor\\\"] = ndr_pack(sd)\\n\\n ldbmessage2 = None\\n if any(map(lambda b: b is not None, (uid, uidnumber, gidnumber, gecos,\\n loginshell, nisdomain, unixhome))):\\n ldbmessage2 = ldb.Message()\\n ldbmessage2.dn = ldb.Dn(self, user_dn)\\n if uid is not None:\\n ldbmessage2[\\\"uid\\\"] = ldb.MessageElement(str(uid), ldb.FLAG_MOD_REPLACE, 'uid')\\n if uidnumber is not None:\\n ldbmessage2[\\\"uidNumber\\\"] = ldb.MessageElement(str(uidnumber), ldb.FLAG_MOD_REPLACE, 'uidNumber')\\n if gidnumber is not None:\\n ldbmessage2[\\\"gidNumber\\\"] = ldb.MessageElement(str(gidnumber), ldb.FLAG_MOD_REPLACE, 'gidNumber')\\n if gecos is not None:\\n ldbmessage2[\\\"gecos\\\"] = ldb.MessageElement(str(gecos), ldb.FLAG_MOD_REPLACE, 'gecos')\\n if loginshell is not None:\\n ldbmessage2[\\\"loginShell\\\"] = ldb.MessageElement(str(loginshell), ldb.FLAG_MOD_REPLACE, 'loginShell')\\n if unixhome is not None:\\n ldbmessage2[\\\"unixHomeDirectory\\\"] = ldb.MessageElement(\\n str(unixhome), ldb.FLAG_MOD_REPLACE, 'unixHomeDirectory')\\n if nisdomain is not None:\\n ldbmessage2[\\\"msSFU30NisDomain\\\"] = ldb.MessageElement(\\n str(nisdomain), ldb.FLAG_MOD_REPLACE, 'msSFU30NisDomain')\\n ldbmessage2[\\\"msSFU30Name\\\"] = ldb.MessageElement(\\n str(username), ldb.FLAG_MOD_REPLACE, 'msSFU30Name')\\n ldbmessage2[\\\"unixUserPassword\\\"] = ldb.MessageElement(\\n 'ABCD!efgh12345$67890', ldb.FLAG_MOD_REPLACE,\\n 'unixUserPassword')\\n\\n self.transaction_start()\\n try:\\n self.add(ldbmessage)\\n if ldbmessage2:\\n self.modify(ldbmessage2)\\n\\n # Sets the password for it\\n if setpassword:\\n self.setpassword((\\\"(distinguishedName=%s)\\\" %\\n ldb.binary_encode(user_dn)),\\n password,\\n force_password_change_at_next_login_req)\\n except:\\n self.transaction_cancel()\\n raise\\n else:\\n self.transaction_commit()\",\n \"def _create_user(self, password, **extra_fields):\\n try:\\n user = self.model(**extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\\n except:\\n raise ValueError('ValueError: Cannot create new user')\",\n \"def create_user(first_name,last_name,email,password):\\n\\n\\tnew_user = User(first_name,last_name,email,password)\\n\\treturn new_user\",\n \"def _create_user(self, email, password, first_name, last_name, **extra_fields):\\n if not email:\\n raise ValueError('The given email must be set')\\n email = self.normalize_email(email)\\n if not self.model:\\n self.model = MHacksUser\\n try:\\n request = extra_fields.pop('request')\\n except KeyError:\\n request = None\\n user = self.model(email=email, first_name=first_name, last_name=last_name, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n from django.contrib.auth.models import Group\\n user.groups.add(Group.objects.get(name=GroupEnum.HACKER))\\n user.save(using=self._db)\\n from utils import send_verification_email\\n if request:\\n send_verification_email(user, request)\\n return user\",\n \"def _create_user(self, username, email, password, phone, **extra_fields):\\n\\n username = self.model.normalize_username(username)\\n user = self.model(username=username, email=email, phone=phone, **extra_fields) # using email_id instead of email\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"def create_user(self, username, password):\\n return self._user(username=username, password=password, create=True)\",\n \"def sample_user(email='test@gmail.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"def sample_user(email='test@gmail.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"def sample_user(email='test@gmail.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"def create_user(entry):\\n # only works for first + last name currently\\n full_name = entry[5].split()\\n email = '{first_name}-{client_id}@{domain}'.format(\\n first_name=full_name[0].lower(),\\n client_id=str(entry[4]).strip(), # unique email for clients with same name\\n domain='example.com')\\n password = 'test1234'\\n dob = timezone.now() - timedelta(days=(365 * random.randint(18, 99)))\\n try:\\n user = get_user_model().objects.get(email=email)\\n except get_user_model().DoesNotExist:\\n user = get_user_model().objects.create_user(email=email, first_name=full_name[0],\\n last_name=full_name[1], password=password, dob=dob)\\n return user\",\n \"def do_user_create(cs, args):\\n cs.users.create(args.username, args.password, args.email, args.realname,\\n args.comment)\\n print(\\\"Create user '%s' successfully.\\\" % args.username)\",\n \"def sample_user(email='john7ric@mail.com', password='open@123'):\\n return get_user_model().objects.create_user(email, password)\",\n \"def sample_user(email, password, is_doctor, is_hospital_admin):\\n return MyUser.objects.create_user(email, is_hospital_admin, is_doctor, password)\",\n \"def create_new_user():\\n return get_user_model().objects.create_user(\\n email='test@gmail.com',\\n password='test@londodnjisdjfois',\\n username='tempusername'\\n )\",\n \"def _create_user(self, ident, password, **extra_fields):\\n if not ident:\\n raise ValueError('The Email must be set')\\n ident = self.normalize_email(ident)\\n user = self.model(ident=ident, **extra_fields)\\n user.set_password(password)\\n\\n user.save()\\n return user\",\n \"def create_user(\\n self,\\n name: str,\\n email: str,\\n password: str,\\n daa_pdf: Optional[bytes],\\n institution: str,\\n website: str,\\n budget: float,\\n role: Dict[Any, Any],\\n verify_key: VerifyKey,\\n ) -> None:\\n _private_key = SigningKey.generate()\\n\\n encoded_pk = _private_key.encode(encoder=HexEncoder).decode(\\\"utf-8\\\")\\n encoded_vk = _private_key.verify_key.encode(encoder=HexEncoder).decode(\\\"utf-8\\\")\\n added_by = self.get_user(verify_key).name # type: ignore\\n\\n # Register the user in the database\\n self.signup(\\n name=name,\\n email=email,\\n password=password,\\n role=role,\\n budget=budget,\\n private_key=encoded_pk,\\n verify_key=encoded_vk,\\n daa_pdf=daa_pdf,\\n added_by=added_by,\\n institution=institution,\\n website=website,\\n )\",\n \"def create_user_service(username: str, email: str, password: str) -> None:\\n hashed_password = bcrypt.generate_password_hash(password).decode('UTF-8')\\n user = User(username=username, email=email, password=hashed_password)\\n db.session.add(user)\\n db.session.commit()\",\n \"def create_user(user_id, password_16char, public_key_32char):\\n headers = {'Content-type': 'application/json'}\\n payload = {'user_id': user_id\\n , 'user_password': password_16char\\n , 'public_key': public_key_32char}\\n response = requests.post(\\\"http://localhost:5000/user/createUser\\\", data=json.dumps(payload), headers=headers)\\n return response.text\",\n \"def _create_user(self, email, password, **extra_fields):\\n if not email:\\n raise ValueError('The given email must be set')\\n email = self.normalize_email(email)\\n user = self.model(email=email, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"def _create_user(self, email, first_name, last_name, password, **extra_fields):\\n if not email:\\n raise ValueError(_('Email Address is required'))\\n email = self.normalize_email(email)\\n user = self.model(\\n email=email,\\n first_name=first_name,\\n last_name=last_name,\\n **extra_fields\\n )\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"def create_user(self, user_account, password=None):\\n if not user_account:\\n raise ValueError('Users must have an user_account')\\n\\n user = self.model(\\n user_account=user_account\\n )\\n\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"def create_user_object():\\n user = User.objects.get_or_create(username='testuser',\\n first_name='Test',\\n last_name='User',\\n email='test@test.com')[0]\\n user.set_password('testabc123')\\n user.save()\\n\\n return user\",\n \"def new_user(request):\\r\\n rdict = request.params\\r\\n\\r\\n u = User()\\r\\n\\r\\n u.username = unicode(rdict.get('username'))\\r\\n if u.username:\\r\\n u.username = u.username.lower()\\r\\n u.email = unicode(rdict.get('email')).lower()\\r\\n passwd = get_random_word(8)\\r\\n u.password = passwd\\r\\n u.activated = True\\r\\n u.is_admin = False\\r\\n u.api_key = User.gen_api_key()\\r\\n\\r\\n try:\\r\\n DBSession.add(u)\\r\\n DBSession.flush()\\r\\n # We need to return the password since the admin added the user\\r\\n # manually. This is only time we should have/give the original\\r\\n # password.\\r\\n ret = dict(u)\\r\\n ret['random_pass'] = passwd\\r\\n return _api_response(request, ret)\\r\\n\\r\\n except IntegrityError, exc:\\r\\n # We might try to add a user that already exists.\\r\\n LOG.error(exc)\\r\\n request.response.status_int = 400\\r\\n return _api_response(request, {\\r\\n 'error': 'Bad Request: User exists.',\\r\\n })\",\n \"def create_user_object():\\n user = User.objects.get_or_create(username='testuser',\\n first_name='Test',\\n last_name='User',\\n email='test@test.com')[0]\\n user.set_password('testabc123')\\n user.save()\\n return user\",\n \"def create_user(\\n self, email, \\n user_name, \\n first_name,\\n password,\\n **other_information):\\n\\n if not email:\\n raise ValueError(\\n _('You must be provide an email address!')\\n )\\n \\n email = self.normalize_email(email)\\n user = self.model(\\n email=email,\\n user_name=user_name,\\n first_name=first_name,\\n **other_information\\n )\\n\\n user.set_password(password)\\n user.save()\\n\\n return user\",\n \"def create_user(name, password, tenant=None, domain=None):\\n manager = get_manager()\\n if user_exists(name, domain=domain):\\n log(\\\"A user named '%s' already exists in domain '%s'\\\" % (name, domain),\\n level=DEBUG)\\n return\\n\\n tenant_id = None\\n if tenant:\\n tenant_id = manager.resolve_tenant_id(tenant, domain=domain)\\n if not tenant_id:\\n error_out(\\\"Could not resolve tenant_id for tenant '%s' in domain \\\"\\n \\\"'%s'\\\" % (tenant, domain))\\n\\n domain_id = None\\n if domain:\\n domain_id = manager.resolve_domain_id(domain)\\n if not domain_id:\\n error_out('Could not resolve domain_id for domain %s when creating'\\n ' user %s' % (domain, name))\\n\\n manager.create_user(name=name,\\n password=password,\\n email='juju@localhost',\\n tenant_id=tenant_id,\\n domain_id=domain_id)\\n log(\\\"Created new user '%s' tenant: '%s' domain: '%s'\\\" % (name, tenant_id,\\n domain_id), level=DEBUG)\",\n \"def _create_user(self, email, password, **extra_fields):\\n\\t\\tif not email:\\n\\t\\t\\traise ValueError('The given email must be set')\\n\\t\\temail = self.normalize_email(email)\\n\\t\\tuser = self.model(email=email, **extra_fields)\\n\\t\\tuser.set_password(password)\\n\\t\\tuser.save(using=self._db)\\n\\t\\treturn user\",\n \"def _create_user(self, email, password, **extra_fields):\\n\\t\\tif not email:\\n\\t\\t\\traise ValueError('The given email must be set')\\n\\t\\temail = self.normalize_email(email)\\n\\t\\tuser = self.model(email=email, **extra_fields)\\n\\t\\tuser.set_password(password)\\n\\t\\tuser.save(using=self._db)\\n\\t\\treturn user\",\n \"def create_user(self, user_id):\\n data = {\\n 'email': self._email_for_user_id(user_id),\\n 'username': user_id,\\n 'password': str(uuid.uuid4()),\\n 'name': user_id,\\n }\\n\\n # create user and return it to caller\\n return self._post('/users', data=data)\",\n \"def create_user(self, email=None, name=None, password=None, phone=None):\\n # if not email:\\n # raise ValueError('Users must have an email address')\\n\\n user = self.model(\\n email=email,\\n name=name,\\n phone=phone\\n )\\n\\n user.set_password(password)\\n user.save(using=self._db)\\n return user\",\n \"def create_user(user_name: str):\\n user = User()\\n user.username = user_name\\n user.save()\\n return user\",\n \"def __init__(self, user, password, _recipients, templatedir='templates'):\\n\\n self.user = user\\n self.password = password\\n self.recipient = _recipients if type (_recipients) is list else [_recipients]\\n self.server = 'smtp.gmail.com'\\n self.port = 587\\n\\n if os.path.isdir(templatedir):\\n self.templatedir = templatedir\\n else:\\n self.templatedir = os.path.join(os.path.abspath(os.path.dirname(__file__)), templatedir)\\n\\n self.env = Environment(loader=FileSystemLoader(self.templatedir))\",\n \"def sample_user(email='scott@test.com', password='testpass'):\\n return get_user_model().objects.create_user(email, password)\",\n \"def user(**kwargs):\\n defaults = {}\\n if 'username' not in kwargs:\\n defaults['username'] = ''.join(random.choice(letters)\\n for x in xrange(15))\\n if 'email' not in kwargs:\\n defaults['email'] = ''.join(\\n random.choice(letters) for x in xrange(10)) + '@example.com'\\n defaults.update(kwargs)\\n user = User(**defaults)\\n user.set_password(kwargs.get('password', 'testpass'))\\n return user\",\n \"def _create_user(self, email, password, **extra_fields):\\n if not email:\\n raise ValueError('The given email must be set')\\n email = self.normalize_email(email)\\n user = self.model(email=email, **extra_fields)\\n user.set_password(password)\\n user.save(using=self._db)\\n print(\\\"create user\\\")\\n return user\",\n \"def create_user(username):\\n\\n password = getpass.getpass('Password for {0}: '.format(username))\\n confirm = getpass.getpass('Again: ')\\n\\n if password != confirm:\\n print >> sys.stderr, \\\"Passwords don't match\\\"\\n\\n sys.exit(1)\\n\\n with transaction.manager:\\n Users(username, password).save()\",\n \"def create_a_user(self, username='fry', email='fry@futur.ama', password='Qwerty!234'):\\n user = User.objects.create_user(username, email, password)\\n user.save()\\n return user\",\n \"def create_user(fname, lname, email, password, phone_number):\\n user = User(fname = fname, lname = lname , email = email ,password = password, phone_number = phone_number)\\n #setting password hash\\n user.set_password(password)\\n db.session.add(user)\\n db.session.commit()\\n\\n return user\"\n]"},"negative_scores":{"kind":"list like","value":["0.6836732","0.6782684","0.66625166","0.6148272","0.60939145","0.59752667","0.59635276","0.59110373","0.5898103","0.58977437","0.5887567","0.58812404","0.5815839","0.5802219","0.57664925","0.57609296","0.57314557","0.57081306","0.56840855","0.56605315","0.5635352","0.55870754","0.5580626","0.5579031","0.55513906","0.55480254","0.55424273","0.55354136","0.5533354","0.5503334","0.55005276","0.54932624","0.54926896","0.54723006","0.5450565","0.5441564","0.5440344","0.5439515","0.5438194","0.54380023","0.5435078","0.5431898","0.54048675","0.5392365","0.53726995","0.53661644","0.5346531","0.53464997","0.53321177","0.5328356","0.53235954","0.5319738","0.53175336","0.53153354","0.53116155","0.53108907","0.5300398","0.52967477","0.52964514","0.529536","0.52874035","0.5283937","0.5278095","0.5269913","0.5267814","0.52665734","0.52611","0.5254836","0.525264","0.525264","0.525264","0.5246726","0.52422947","0.5232217","0.52256924","0.52249885","0.522386","0.52221096","0.5220444","0.5219833","0.52183974","0.52182394","0.5210677","0.52060604","0.52055365","0.52044684","0.5202703","0.5200955","0.51921666","0.51921666","0.51884234","0.51873046","0.5180693","0.51801467","0.5179385","0.5179329","0.51765","0.5175611","0.5173978","0.5173285"],"string":"[\n \"0.6836732\",\n \"0.6782684\",\n \"0.66625166\",\n \"0.6148272\",\n \"0.60939145\",\n \"0.59752667\",\n \"0.59635276\",\n \"0.59110373\",\n \"0.5898103\",\n \"0.58977437\",\n \"0.5887567\",\n \"0.58812404\",\n \"0.5815839\",\n \"0.5802219\",\n \"0.57664925\",\n \"0.57609296\",\n \"0.57314557\",\n \"0.57081306\",\n \"0.56840855\",\n \"0.56605315\",\n \"0.5635352\",\n \"0.55870754\",\n \"0.5580626\",\n \"0.5579031\",\n \"0.55513906\",\n \"0.55480254\",\n \"0.55424273\",\n \"0.55354136\",\n \"0.5533354\",\n \"0.5503334\",\n \"0.55005276\",\n \"0.54932624\",\n \"0.54926896\",\n \"0.54723006\",\n \"0.5450565\",\n \"0.5441564\",\n \"0.5440344\",\n \"0.5439515\",\n \"0.5438194\",\n \"0.54380023\",\n \"0.5435078\",\n \"0.5431898\",\n \"0.54048675\",\n \"0.5392365\",\n \"0.53726995\",\n \"0.53661644\",\n \"0.5346531\",\n \"0.53464997\",\n \"0.53321177\",\n \"0.5328356\",\n \"0.53235954\",\n \"0.5319738\",\n \"0.53175336\",\n \"0.53153354\",\n \"0.53116155\",\n \"0.53108907\",\n \"0.5300398\",\n \"0.52967477\",\n \"0.52964514\",\n \"0.529536\",\n \"0.52874035\",\n \"0.5283937\",\n \"0.5278095\",\n \"0.5269913\",\n \"0.5267814\",\n \"0.52665734\",\n \"0.52611\",\n \"0.5254836\",\n \"0.525264\",\n \"0.525264\",\n \"0.525264\",\n \"0.5246726\",\n \"0.52422947\",\n \"0.5232217\",\n \"0.52256924\",\n \"0.52249885\",\n \"0.522386\",\n \"0.52221096\",\n \"0.5220444\",\n \"0.5219833\",\n \"0.52183974\",\n \"0.52182394\",\n \"0.5210677\",\n \"0.52060604\",\n \"0.52055365\",\n \"0.52044684\",\n \"0.5202703\",\n \"0.5200955\",\n \"0.51921666\",\n \"0.51921666\",\n \"0.51884234\",\n \"0.51873046\",\n \"0.5180693\",\n \"0.51801467\",\n \"0.5179385\",\n \"0.5179329\",\n \"0.51765\",\n \"0.5175611\",\n \"0.5173978\",\n \"0.5173285\"\n]"},"document_score":{"kind":"string","value":"0.72970504"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8585,"cells":{"query":{"kind":"string","value":"Creates a new tag in the specified tag namespace. The tag requires either the OCID or the name of the tag namespace that will contain this tag definition. You must specify a name for the tag, which must be unique across all tags in the tag namespace and cannot be changed. The name can contain any ASCII character except the space (_) or period (.) characters. Names are case insensitive. That means, for example, \\\"myTag\\\" and \\\"mytag\\\" are not allowed in the same namespace. If you specify a name that's already in use in the tag namespace, a 409 error is returned. The tag must have a description. It does not have to be unique, and you can change it with"},"document":{"kind":"string","value":"def create_tag(self, tag_namespace_id, create_tag_details, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}/tags\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_tag got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_tag_details,\n response_type=\"Tag\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_tag_details,\n response_type=\"Tag\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def create(self, name, tag):\n\n\t\turl_json = urllib.urlencode({\"name\": name, \"tag\": tag})\n\t\treturn self._create(\"/tag?json_hash=%s\" % url_json, \"tag\")","def create_tag(self, session, tags):\n self._tag(session.put, tags=tags, session=session)","def create_tag(self, entry_name, tag):\n return self.__datacatalog.create_tag(parent=entry_name, tag=tag)","def create_tag_namespace(self, create_tag_namespace_details, **kwargs):\n resource_path = \"/tagNamespaces\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_tag_namespace got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_tag_namespace_details,\n response_type=\"TagNamespace\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_tag_namespace_details,\n response_type=\"TagNamespace\")","def create_tag(name):\n name = name.strip().lower()\n tag = Tags(name)\n try:\n db_session.add(tag)\n db_session.commit()\n except exc.IntegrityError as err:\n db_session.rollback()\n return 'Tag \"%s\" has not been added - already exists: %s.' % (name, err), 'warning', None\n return 'Tag \"%s\" has been added.' % name, 'success', tag","def create_or_get_tag(self, tag_name: str, *args, **kwargs):\n\n tag_data = api.create_or_get_tag(\n tag_name,\n *args,\n api_key=self.__creds.api_key_v2, \n **kwargs)\n return en.Tag(tag_data)","def create_a_tag(self, tag_id, contact_id):\n data = {\"contactTag\":{\"contact\":str(contact_id),\"tag\":str(tag_id)}}\n\n return self.client._post(\"/contactTags\", json=data)","def createTag(self, authenticationToken, tag):\r\n pass","def createTag(self, authenticationToken, tag):\r\n self.send_createTag(authenticationToken, tag)\r\n return self.recv_createTag()","def create_tag():\n \n name = request.form['tag_name']\n\n if \"name\" in session:\n return redirect(\"/tags\")\n\n else:\n new_tag = Tag(name = name)\n db.session.add(new_tag)\n db.session.commit()\n return redirect(\"/tags\")","def _create_tag_request():\n\n key = helpers.get('Tag.1.Key')\n value = helpers.get('Tag.1.Value')\n resource_id = helpers.get('ResourceId.1')\n\n if resource_id in current_app.config['RESOURCE_TYPE_MAP']:\n resource_type = current_app.config['RESOURCE_TYPE_MAP'][resource_id]\n else:\n errors.invalid_request(\n str(resource_id) + \" not found in configuration\")\n\n args = {\n 'command': 'createTags',\n 'resourceids': resource_id,\n 'resourcetype': resource_type,\n 'tags[0].key': key,\n 'tags[0].value': value\n }\n\n response = requester.make_request_async(args)\n\n return response","def create(self, params={}, **options):\n return self.client.post(\"/tags\", params, **options)","def make_tag(tag_name, text='', tag_attr=None):\n if tag_attr is None:\n tag_attr = {}\n\n doc = xml.dom.minidom.Document()\n element = doc.createElement(tag_name)\n if tag_attr:\n for k, v in izip(list(tag_attr.keys()), list(tag_attr.values())):\n element.setAttribute(unicode(k), unicode(v))\n if text:\n text_node = doc.createTextNode(text.strip())\n element.appendChild(text_node)\n return element","def tag ():\n\n tagname = get_tag(comp_versions, 'ACE')\n\n if opts.tag:\n if opts.take_action:\n vprint (\"Placing tag %s on ACE_TAO\" % (tagname))\n ex (\"cd $DOC_ROOT/ACE_TAO && git tag -a \" + tagname + \" -m\\\"\" + tagname + \"\\\"\")\n\n vprint (\"Placing tag %s on MPC\" % (tagname))\n ex (\"cd $DOC_ROOT/MPC && git tag -a \" + tagname + \" -m\\\"\" + tagname + \"\\\"\")\n\n # Update release branches\n latest_branch_helper (update_latest_branch, opts.release_type)\n else:\n vprint (\"Placing tag %s on ACE_TAO\" % (tagname))\n vprint (\"Placing tag %s on MPC\" % (tagname))\n print (\"Creating tags:\\n\")\n print (\"Placing tag \" + tagname + \"\\n\")","def create_tag(tag, directory=None):\n execute_command('git tag {0}'.format(tag), shell=True, cwd=directory)","def create_in_workspace(self, workspace, params={}, **options):\n path = \"/workspaces/%s/tags\" % (workspace)\n return self.client.post(path, params, **options)","def add_tag(self, obj, tag_name):\r\n tag_names = parse_tag_input(tag_name)\r\n if not len(tag_names):\r\n raise AttributeError(_('No tags were given: \"%s\".') % tag_name)\r\n if len(tag_names) > 1:\r\n raise AttributeError(_('Multiple tags were given: \"%s\".') % tag_name)\r\n tag_name = tag_names[0]\r\n if settings.FORCE_LOWERCASE_TAGS:\r\n tag_name = tag_name.lower()\r\n tag, created = self.get_or_create(name=tag_name)\r\n ctype = ContentType.objects.get_for_model(obj)\r\n TaggedItem._default_manager.get_or_create(\r\n tag=tag, content_type=ctype, object_id=obj.pk)","def add_tag(filename, tag_name):\n storeapps = APP.config[\"storage\"]\n filename = filename.encode(\"utf-8\")\n print filename\n\n try:\n application = list(nativeapps.io.ls(storeapps, r\".*\" + filename + \"$\"))[0]\n meta_path = os.path.join(os.path.dirname(application), \"metadata.json\")\n metadata = json.loads(nativeapps.io.readfile(meta_path))\n tags = set(metadata.get(\"tags\", []))\n tags.add(tag_name)\n metadata[\"tags\"] = list(tags)\n nativeapps.io.writefile(meta_path, json.dumps(metadata))\n except IndexError:\n return \"Unknown application: %s\" % (application), 404\n\n return \"added\", 200","def add_tag(session, tag_name, user_id=None, username='system_user'):\n session = validate_session(session)\n date_created=datetime.now()\n try:\n add_tag = TagInfo(tag_name, date_created, user_id)\n session.add(add_tag)\n session.commit()\n return(True, \"Tag %s added\" % (tag_name), add_tag)\n except Exception as e:\n session.rollback()\n return(False, \"Tag %s failed to add\" % (tag_name))","def addNode(self, nTag, pkg, exe, args, name, namespace):\r\n try:\r\n validateName(nTag)\r\n except IllegalName:\r\n raise InvalidRequest('Node tag is not a valid.')\r\n\r\n if nTag in self._nodes:\r\n raise InvalidRequest(\"Can not use the same node tag '{0}' in the \"\r\n 'same container twice.'.format(nTag))\r\n\r\n node = self._obj.createNode(pkg, exe, args, name, namespace)\r\n self._nodes[nTag] = node\r\n node.notifyOnDeath(self._nodeDied)","def create(self, label_id):\n data = {\n 'type': 'tagit',\n 'rate_count': 0,\n 'rate_range': 'day',\n 'limit_count': 0,\n 'limit_range': 'day',\n 'schedule': [],\n 'enabled': True,\n 'args': {\n 'sn': label_id,\n 'tag_sn': label_id\n }\n }\n # Yes, it's confusing. the `/actions/` endpoint is used for tags, while\n # the /tags/ endpoint is used for labels.\n return self._post(\n request=ApiActions.CREATE.value,\n uri=ApiUri.ACTIONS.value,\n params=data\n )","def ex_create_tags(self, node, tags):\n if not tags:\n return\n\n params = { 'Action': 'CreateTags',\n 'ResourceId.0': node.id }\n for i, key in enumerate(tags):\n params['Tag.%d.Key' % i] = key\n params['Tag.%d.Value' % i] = tags[key]\n\n self.connection.request(self.path,\n params=params.copy()).object","def add_tag(self, session, tag):\n self._tag(session.put, key=tag, session=session)","def test_create_tag_invalid(self):\n tag_data = {'name': ''}\n res = self.client.post(TAGS_URL, data=tag_data)\n\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def create(self, name, description=None, color=None):\n data = {\n 'name': name,\n 'title': name,\n 'description': description or name,\n 'appearance': {\n 'color': color or random_color()\n }\n }\n # Yes, it's confusing. the `/tags/` endpoint is used for labels\n return self._post(\n request=ApiActions.CREATE.value,\n uri=ApiUri.TAGS.value,\n params=data\n )","def test_create_tag_invalid(self):\n payload = {'name': ''}\n res = self.client.post(TAGS_URL, payload)\n\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def test_create_tag_invalid(self):\n payload = {'name': ''}\n res = self.client.post(TAGS_URL, payload)\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def make_new_tag(tag_name, user_path, user_signed_in, current_user):\n if not user_signed_in:\n print('ALERT: -- User not logged in --')\n else:\n user = current_user[0]\n print(is_tag(tag_name, user_path, current_user))\n if is_tag(tag_name, user_path, current_user):\n print('Tag already exist')\n else:\n os.mkdir((user_path + '\\\\' + user + '\\\\' + tag_name).encode('unicode_escape'))\n print('Tag --' + tag_name + '-- Created')","def create_tag(case_dict, new_tag, username, password):\n # ---------------------------------------------------------------------\n logger.debug(\"create_tag\")\n\n # create a new trunk tag\n os.chdir(case_dict[\"archive_temp_dir\"])\n svn_repo = \"{0}/trunk\".format(case_dict[\"svn_repo_url\"])\n svn_repo_tag = \"{0}/trunk_tags/{1}\".format(case_dict[\"svn_repo_url\"], new_tag)\n msg = '\"create new trunk tag\"'\n cmd = [\n \"svn\",\n \"copy\",\n \"--username\",\n username,\n \"--password\",\n password,\n svn_repo,\n svn_repo_tag,\n \"--message\",\n msg,\n ]\n try:\n subprocess.check_call(cmd)\n except subprocess.CalledProcessError as error:\n cmd_nopasswd = [\n \"svn\",\n \"copy\",\n \"--username\",\n username,\n \"--password\",\n \"******\",\n svn_repo,\n svn_repo_tag,\n \"--message\",\n msg,\n ]\n msg = _call_template.substitute(\n function=\"checkin_trunk\",\n cmd=cmd_nopasswd,\n error=error.returncode,\n strerror=error.output,\n )\n logger.warning(msg)\n raise SVNException(msg)","def _create_element(tag, text=\"\", attr={}, namespace=Xmlns_path):\n element = Et.Element('.//' + namespace + tag, attr)\n element.text = text\n return element","def create(cls, ns, name, **kwargs):\n key_name = '%s:%s' % (ns, name)\n return cls(key_name=key_name, ns=ns, name=name, **kwargs)","def tag(self, tag):\n \n if isinstance(tag, six.integer_types):\n try:\n tag = Tag.objects.get(pk=tag, owner=self.owner)\n except Tag.DoesNotExist:\n #Handle this better?\n return\n \n if isinstance(tag, six.string_types):\n tname = tag\n try:\n tag = Tag(owner=self.owner, name=tag)\n tag.save()\n except IntegrityError:\n tag = Tag.objects.get(slug=makeslug(tname), owner=self.owner)\n \n tag.save() # If this isn't here there are crashes for some reason\n self.tags.add(tag)","def ensure_tag(name, vocabulary=None):\n obj = {'name': name}\n where_clause = tag_table.c.name == name\n\n if vocabulary is not None:\n ## Add vocabulary to filter / new object\n vocabulary_id = ensure_vocabulary(vocabulary)\n obj['vocabulary_id'] = vocabulary_id\n where_clause = and_(\n where_clause, tag_table.c.vocabulary_id == vocabulary_id)\n\n query = select([tag_table]).where(where_clause)\n tag_obj = query.execute().first()\n\n if tag_obj is not None:\n ## We already have the tag!\n return tag_obj['id']\n\n ## Create tag, return id\n return create_tag(obj)","def post_namespace_create(self, resource_dict):\n pass","def create_tag(self,\r\n access_token,\r\n tag_create_params):\r\n\r\n # Prepare query URL\r\n _url_path = '/tags'\r\n _query_builder = Configuration.base_uri\r\n _query_builder += _url_path\r\n _query_parameters = {\r\n 'access_token': access_token\r\n }\r\n _query_builder = APIHelper.append_url_with_query_parameters(_query_builder,\r\n _query_parameters, Configuration.array_serialization)\r\n _query_url = APIHelper.clean_url(_query_builder)\r\n\r\n # Prepare headers\r\n _headers = {\r\n 'accept': 'application/json',\r\n 'content-type': 'application/json; charset=utf-8'\r\n }\r\n\r\n # Prepare and execute request\r\n _request = self.http_client.post(_query_url, headers=_headers, parameters=APIHelper.json_serialize(tag_create_params))\r\n CustomQueryAuth.apply(_request)\r\n _context = self.execute_request(_request)\r\n\r\n # Endpoint and global error handling using HTTP status codes.\r\n if _context.response.status_code == 0:\r\n raise APIException('Unexpected error.', _context)\r\n self.validate_response(_context)\r\n\r\n # Return appropriate type\r\n return APIHelper.json_deserialize(_context.response.raw_body, Tag.from_dictionary)","def tag(self, tag_name):\r\n return Tag(self, tag_name)","def CreateTags(self, ResourceId, TagName, TagValue):\n\n Client = boto3.client(self.Service)\n\n if self.Service == 'ec2':\n response = Client.create_tags(\n Resources = [\n\t\t ResourceId\n\t\t],\n\t\tTags = [\n {\n\t\t 'Key': TagName,\n\t\t 'Value': TagValue\n }\n\t\t]\n\t )\n elif self.Service == 'efs':\n response = Client.create_tags(\n FileSystemId = ResourceId,\n\t\tTags = [\n {\n\t\t 'Key': TagName,\n\t\t 'Value': TagValue\n }\n\t\t]\n\t )\n elif self.Service == 'redshift':\n response = Client.create_tags(\n ResourceName = ResourceId,\n\t\tTags = [\n {\n\t\t 'Key': TagName,\n\t\t 'Value': TagValue\n }\n\t\t]\n\t )\n elif self.Service == 'workspaces':\n response = Client.create_tags(\n ResourceId = ResourceId,\n\t\tTags = [\n {\n\t\t 'Key': TagName,\n\t\t 'Value': TagValue\n }\n\t\t]\n\t )\n else:\n raise TagNotSupportedError(str(self.Service))\n\n return True","def create(self, session, prepend_key=True):\n if not self.allow_create:\n raise exceptions.MethodNotSupported(self, \"create\")\n\n endpoint_override = self.service.get_endpoint_override()\n if self.put_create:\n # create tag do not need requires_id\n request = self._prepare_request(requires_id=False,\n prepend_key=prepend_key)\n response = session.put(request.uri, endpoint_filter=self.service,\n endpoint_override=endpoint_override,\n json=request.body, headers=request.headers)\n self._translate_response(response)\n return self","def create_tag_with_entry(title):\n tag = Tag.objects.create(title=title)\n tag.save()\n tag.entry.add(1)\n return tag","def _add_tag(self, tag_name):\n tag = TagInfo()\n tag._name = tag_name\n self._tags.append(tag)\n return tag","def test_create_tag_with_invalid_details_invalid(self):\n\n payload = {\n 'name': ''\n }\n\n res = self.client.post(TAGS_URL, payload)\n\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def testAddTag(self):\n project = self.session.create_project()\n\n project.add_tag(\"test\")\n self.assertEqual(project.tags, [\"test\"], \"Can add a tag to a project.\")\n\n json_str = project.to_json()\n doc = json.loads(json_str)\n\n self.assertEqual(doc['meta']['tags'], [\"test\"],\n \"JSON representation had correct tags after add_tag().\")\n\n # Try adding the same tag yet again, shouldn't get a duplicate\n with self.assertRaises(ValueError):\n project.add_tag(\"test\")\n\n json_str = project.to_json()\n doc2 = json.loads(json_str)\n\n self.assertEqual(doc2['meta']['tags'], [\"test\"],\n \"JSON document did not end up with duplicate tags.\")","def test_add_tag_invalid(self):\n payload = {'name': ''}\n res = self.client.post(TAGS_URL, payload)\n\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)","def add_tag(convo_ID, tag_ID):\n # Make API request\n url = \"https://api2.frontapp.com/conversations/\" + convo_ID + \"/tags\"\n payload = json.dumps({\"tag_ids\": [tag_ID]})\n headers = {\"Authorization\": BEARER_TOKEN, \"Content-Type\": \"application/json\"}\n requests.request(\"POST\", url, headers=headers, data=payload)","def test_create_tag_invalid_payload(self):\n\n tag_payload = {'name': ''}\n response = self.client.post(URL_TAGS, tag_payload)\n\n self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)","def create_namespace(node, namespace, delete_before_create=True):\n if delete_before_create:\n Namespaces.delete_namespace(node, namespace)\n\n cmd = f\"ip netns add {namespace}\"\n exec_cmd_no_error(node, cmd, sudo=True)\n Namespaces.__namespaces.append(namespace)","def update_tag(self, tag_namespace_id, tag_name, update_tag_details, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}/tags/{tagName}\"\n method = \"PUT\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"if_match\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"update_tag got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id,\n \"tagName\": tag_name\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"if-match\": kwargs.get(\"if_match\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_details,\n response_type=\"Tag\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_details,\n response_type=\"Tag\")","def CreateForTag(cls, tag):\n parent_key = cls._GetParentKeyFromTag(tag)\n return cls(parent=parent_key)","def add_tag():\n\n tag_name = request.form[\"name\"]\n\n if not tag_name:\n flash(\"Please enter tag name\")\n return redirect(\"/tags/new\")\n\n tag = Tag(name=tag_name)\n db.session.add(tag)\n db.session.commit()\n\n return redirect(\"/tags\")","async def slashtag_add(\n self,\n ctx: commands.Context,\n tag_name: TagName(check_global=False),\n *,\n tagscript: TagScriptConverter,\n ):\n await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False)","def test_create_tag_invalid(self):\n payload = {'name':''}\n res = self.client.post(TAG_URL,payload)\n self.assertEqual(res.status_code,status.HTTP_400_BAD_REQUEST)","def add(self, tag):\n self.tags[tag.name] = tag","def create_tags(ResourceArn=None, Tags=None):\n pass","def _handle_new_tag(self, tag_name):\n log.debug(\"Handling new tag: %s\", tag_name)\n tag, created = Tag.get_or_create(name=tag_name)\n if tag not in self.doc.tags:\n self.listbox.body.insert(-1, MenuButton(tag_name, None))\n tag.documents.add(self.doc)\n self.new_tag.set_edit_text(\"\")","def test_create_tag(self):\n\n tag_payload = {'name': 'Test Tag'}\n self.client.post(URL_TAGS, tag_payload)\n\n is_tag_created = Tag.objects.filter(\n user=self.user,\n name=tag_payload['name']\n ).exists()\n\n self.assertTrue(is_tag_created)","def test_add_defined_tag_to_bucket(self, test, object_storage, with_or_without_compartment):\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\n session_factory = test.oci_session_factory()\n policy = test.load_policy(\n {\n \"name\": \"add-defined-tag-to-bucket\",\n \"resource\": \"oci.bucket\",\n \"query\": [\n {\"namespace_name\": namespace_name},\n ],\n \"filters\": [\n {\"type\": \"value\", \"key\": \"name\", \"value\": bucket_name},\n ],\n \"actions\": [{\"type\": \"update\", \"defined_tags\": self.get_defined_tag(\"add_tag\")}],\n },\n session_factory=session_factory,\n )\n policy.run()\n resource = self._fetch_bucket_validation_data(\n policy.resource_manager, namespace_name, bucket_name\n )\n test.assertEqual(resource[\"name\"], bucket_name)\n test.assertEqual(self.get_defined_tag_value(resource[\"defined_tags\"]), \"true\")","def create_tags(resource_id, key, value):\n response = EC2.create_tags(\n Resources=[\n resource_id,\n ],\n Tags=[\n {\n 'Key': key,\n 'Value': value\n },\n ]\n )\n return response","def GachaCraftNodeExcelAddTag_(builder, Tag_):\n return AddTag_(builder, Tag_)","def add_tag(self, *,\n id: str,\n tag: str,\n tag_type: str = 'default',\n resource_type: ResourceType = ResourceType.Table) -> None:\n LOGGER.info(f'New tag {tag} for id {id} with type {tag_type} and resource type {resource_type.name}')\n\n resource_table = f'{resource_type.name.lower()}_tag'\n resource_model = self._get_model_from_table_name(resource_table)\n if not resource_model:\n raise NotImplementedError(f'The resource type {resource_type.name} is not defined!')\n\n resource_key = f'{resource_type.name.lower()}_rk'\n\n tag_record = RDSTag(rk=tag, tag_type=tag_type)\n resource_tag_record = resource_model(tag_rk=tag)\n resource_tag_record.__setattr__(resource_key, id)\n try:\n with self.client.create_session() as session:\n session.merge(tag_record)\n session.merge(resource_tag_record)\n session.commit()\n except Exception as e:\n LOGGER.exception(f'Failed to add tag {tag} for {id}')\n raise e","def add_new_tag():\n\n name = request.form.get('name')\n\n new_tag = Tag(name=name)\n db.session.add(new_tag)\n db.session.commit()\n\n return redirect(f'/tags')","def add_tag(self, tag, attributes, extent):\n self.tags.append((tag, attributes, extent))","def _mk_tag(ns, tag):\n return '{%s}%s' % (ns, tag) if ns else tag","def make_new_tag():\n return render_template('tags/new_tag.html')","def test_create_tag_succesful(self):\n payload = {'name': 'Test tag'}\n res = self.client.post(TAGS_URL, payload)\n\n exists = Tag.objects.filter(\n user=self.user,\n name=payload['name']\n ).exists()\n self.assertTrue(exists)\n self.assertEqual(res.status_code, status.HTTP_201_CREATED)","def create_container(ContainerName=None, Tags=None):\n pass","def create_tag(self, name: str, revision: Optional[str] = None) -> None:\n if not revision:\n self._status.check_authority_for_commit()\n revision = self._status.commit_id\n\n post_data: Dict[str, Any] = {\"commit\": revision, \"name\": name}\n\n self._client.open_api_do(\"POST\", \"tags\", self.dataset_id, json=post_data)","def add_new_tag():\n\n return render_template('create-tag.html')","def add_tag(self, key, value=''):\r\n status = self.connection.create_tags([self.id], {key : value})\r\n if self.tags is None:\r\n self.tags = TagSet()\r\n self.tags[key] = value","def create(context, namespace_name, values, session):\n\n namespace = namespace_api.get(\n context, namespace_name, session)\n\n # if the resource_type does not exist, create it\n resource_type_name = values['name']\n metadef_utils.drop_protected_attrs(\n models.MetadefNamespaceResourceType, values)\n try:\n resource_type = resource_type_api.get(\n context, resource_type_name, session)\n except exc.NotFound:\n resource_type = None\n LOG.debug(\"Creating resource-type %s\", resource_type_name)\n\n if resource_type is None:\n resource_type_dict = {'name': resource_type_name, 'protected': False}\n resource_type = resource_type_api.create(\n context, resource_type_dict, session)\n\n # Create the association record, set the field values\n ns_resource_type_dict = _to_db_dict(\n namespace['id'], resource_type['id'], values)\n new_rec = _create_association(context, namespace_name, resource_type_name,\n ns_resource_type_dict, session)\n\n return _to_model_dict(resource_type_name, new_rec)","def add_tag(self, tag: str) -> None:\n tags = self.get_tag_index()\n tags.append(tag)\n self.write_tag_index(list(set(tags)))","def add_tag(self, cr, uid, ids, code=None, name=None, create=False, context=None):\n tag_obj = self.pool.get('res.tag')\n tag_ids = tag_obj.get_tag_ids(cr, uid, self._name, code=code, name=name, context=context)\n if not tag_ids and create:\n model_id = self.pool.get('res.tag.model').search(cr, uid, [('model', '=', self._name)])[0]\n tag_ids = [tag_obj.create(cr, uid, {'name': name, 'code': code, 'model_id': model_id}, context=context)]\n\n if tag_ids:\n self.write(cr, uid, ids, {'tag_ids': [(4, tid) for tid in tag_ids]}, context=context)\n\n return bool(tag_ids)","def tag(request, tag_name):\n raise NotImplementedError","def _createElement(self, identifier, request):\n try:\n decoder, contentType = self._getDecoder(request)\n state = decoder(request.body)\n\n element = self._collection.createElementFromState(state)\n\n actualIdentifier = getattr(element, element.identifyingAttribute)\n if actualIdentifier != identifier:\n raise errors.IdentifierError(identifier, actualIdentifier)\n\n self._collection.add(element)\n return Created()\n except errors.SerializableError, e:\n contentType = self.defaultContentType\n encoder = self.encoders[contentType]\n errorResource = RESTErrorPage(e, encoder, contentType)\n return errorResource","def tag(\n name: str, value: str, *, attributes: dict = {}, namespace: str = None\n ) -> str:\n attributes_str = \" \".join(f'{k}=\"{v}\"' for k, v in attributes.items())\n ns = f\"{namespace}:\" if namespace else \"\"\n if attributes_str:\n attributes_str = \" \" + attributes_str\n if value:\n return f\"<{ns}{name}{attributes_str}>{value}\"\n return f\"<{ns}{name}{attributes_str} />\"","def create_tags(self, resource_ids, tags):\r\n params = {}\r\n self.build_list_params(params, resource_ids, 'ResourceId')\r\n self.build_tag_param_list(params, tags)\r\n return self.get_status('CreateTags', params, verb='POST')","def add_tag(self, transaction, citation_handle, tag_handle):\n citation = self.dbstate.db.get_citation_from_handle(citation_handle)\n citation.add_tag(tag_handle)\n self.dbstate.db.commit_citation(citation, transaction)","def AddTag(self, tag):\n\n if not self.persistant:\n return\n\n self.db.ExecuteSql('insert into tags(tag, track_id) values(\"%s\", %d);'\n %(tag, self.persistant['id']))\n self.db.ExecuteSql('commit;')","def test_create_tag_successful(self):\n tag_data = {'name': 'Snack'}\n res = self.client.post(TAGS_URL, data=tag_data)\n\n exists = Tag.objects.filter(\n user=self.user,\n name=tag_data['name']\n ).exists()\n\n self.assertEqual(res.status_code, status.HTTP_201_CREATED)\n self.assertTrue(exists)","def create_test_node_tag(**kw):\n tag = get_test_node_tag(**kw)\n dbapi = db_api.get_instance()\n return dbapi.add_node_tag(tag['node_id'], tag['tag'])","def tag_add(self, remote_path, corpus_id, tag, storage_id=None):\n client, remote_path = self._get_storage(remote_path, storage_id=storage_id)\n return client.tag_add(corpus_id, tag)","def sample_tag(user, name='Service Tag'):\n return Tag.objects.create(user=user, name=name)","def create_resource(self, namespace: \"str\" = None):\n names = [\"create_namespaced_csistorage_capacity\", \"create_csistorage_capacity\"]\n\n _kube_api.execute(\n action=\"create\",\n resource=self,\n names=names,\n namespace=namespace,\n api_client=None,\n api_args={\"body\": self.to_dict()},\n )","def create_or_update_tags(self, Tags):\n tag = Tags[0]\n asg_name = tag['ResourceId']\n ec2_tag = {\n 'Key': tag['Key'],\n 'Value': tag['Value']\n }\n try:\n response = self.asg.create_or_update_tags(\n Tags=Tags\n )\n except Exception as e:\n logger.error('Unknown Error: %s', str(e))\n else:\n logger.info(response)\n\n asg_instances = self.get_asg_instance_ids(asg_name)\n return EC2Wrapper(self.session).create_tags(Resources=asg_instances, Tags=[ec2_tag])","def add_tag(self, tag_name, name = 'tag'):\r\n if self._only_whitespace.match(tag_name):\r\n # Don't allow an empty tag\r\n return\r\n\r\n try:\r\n tag = Tag._by_name(tag_name)\r\n except NotFound:\r\n tag = Tag._new(tag_name)\r\n tag._commit()\r\n\r\n # See if link already has this tag\r\n tags = LinkTag._fast_query(tup(self), tup(tag), name=name)\r\n link_tag = tags[(self, tag, name)]\r\n if not link_tag:\r\n link_tag = LinkTag(self, tag, name=name)\r\n link_tag._commit()\r\n\r\n return link_tag","def createElement(tagName):\n print(\"Warning: createElement is deprecated in favor of createComponent\")\n return createComponent(tagName)","def handle_add_new_tag():\n tag = Tag(name=request.form['name'])\n\n db.session.add(tag)\n db.session.commit()\n\n return redirect('/tags')","def update_tag_namespace(self, tag_namespace_id, update_tag_namespace_details, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}\"\n method = \"PUT\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"update_tag_namespace got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_namespace_details,\n response_type=\"TagNamespace\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_namespace_details,\n response_type=\"TagNamespace\")","def create_uuid3(namespace, name):\n return uuid.uuid3(namespace, six.ensure_str(name))","def set_tag(request):\n try:\n # Update existing Tag if tag_id exists, else create new Tag\n if \"tag_id\" not in request.POST or not request.POST[\"tag_id\"]:\n # Create new Tag\n tag = Tag.objects.create(title=request.form.cleaned_data[\"title\"])\n\n ActionLogger().log(request.user, \"created\", \"Knowledgebase Tag %s\" % tag)\n return format_ajax_response(True, \"Knowledgebase tag created successfully.\")\n else:\n # Update existing category\n tag = Tag.objects.get(pk=request.POST[\"tag_id\"])\n tag.title = request.form.cleaned_data[\"title\"]\n tag.save()\n\n ActionLogger().log(request.user, \"modified\", \"Knowledgebase Tag %s\" % tag)\n return format_ajax_response(True, \"Knowledgebase tag updated successfully.\")\n except Exception as ex:\n logger.error(\"Failed to set_tag: %s\" % ex)\n return format_ajax_response(False, \"There was an error setting the specified knowledgebase tag.\")","def createContainer(tag, data={}): #@NoSelf","def change_tag_namespace_compartment(self, tag_namespace_id, change_tag_namespace_compartment_detail, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}/actions/changeCompartment\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"change_tag_namespace_compartment got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=change_tag_namespace_compartment_detail)\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=change_tag_namespace_compartment_detail)","def initiate_new_tag (self,tag,key):\r\n\r\n #with shelf\r\n if self.using_shelf:\r\n self.tag_dict[tag] = {key}\r\n #with database\r\n\r\n if self.using_database:\r\n\r\n value_tuple = (notebookname, tag, key)\r\n db_cursor.execute(\"INSERT OR REPLACE\"\r\n +\" INTO tags_to_keys\"\r\n +\" (notebook, tag, keyword)\"\r\n +\" VALUES (?,?,?);\",\r\n value_tuple)","def tag(nodes, arg='', split=True, default=0, add_parent_space=True, add_default_spaces=True, zero_node=None, const_node=None):\n\n nodes = mc.ls(nodes)\n orig_const_node = const_node\n orig_zero_node = zero_node\n\n for node in nodes:\n\n # get zero if not specified\n if orig_zero_node:\n zero_node = orig_zero_node\n else:\n zero_node = node+'_ZERO'\n\n # get const node - this is what the parent constraint will be thrown onto\n if orig_const_node:\n const_node = orig_const_node\n else:\n const_node = node+'_CONST'\n\n if add_parent_space and not mc.objExists(zero_node):\n mc.warning('Cannot find a zero for '+node)\n continue\n\n if not mc.objExists(const_node):\n mc.warning('Cannot find a const for '+const_node)\n continue\n\n # build arg\n arg = arg.strip()\n if ' ' in arg:\n arg = re.sub(' +',' ', arg)\n\n arg_kwargs = {\n 'arg': arg,\n 'split': split,\n 'default': default,\n 'const_node': const_node,\n 'zero_node': zero_node,\n 'add_default_spaces': add_default_spaces,\n 'add_parent_space': add_parent_space\n }\n\n # create + set attr\n if not mc.objExists(node+'.tagSpaces'):\n mc.addAttr(node, ln='tagSpaces', dt='string', hidden=False)\n\n mc.setAttr(node+'.tagSpaces', str(arg_kwargs), type='string')\n\n # This convert all this legacy sloppy crap to the new hotness\n space_obj = Space(node)\n space_obj.set_data()\n\n return arg","def add_tag(self, tag):\n self.tags.append(tag)","def _AddCreatedNamespace(self, state_tracker, identifier, line_number,\n namespace=None):\n if not namespace:\n namespace = identifier\n\n if self._HasSuppression(state_tracker, 'missingProvide'):\n return\n\n self._created_namespaces.append([namespace, identifier, line_number])","def insert_tag(self, tagname, attrs=[], text=\"\",\n autoclose=False, newline=False):\n if autoclose:\n self.str += '\\n<%s%s%s>' % (tagname, string_for_attrs(attrs),\n ' /' if self.is_xml else '')\n else:\n self.push_tag(tagname, attrs)\n if text:\n if newline:\n self.insert_text('\\n' + indent(text, self.indent_level()))\n else:\n self.insert_text(text)\n self.pop_tag(newline=newline)","def test_add_tag(self):\n fc = self.read_feature(region='Adriatic_Sea')\n\n fc.tag(tags=['tag1', 'tag2', 'Mediterranean_Basin'])\n assert (fc.features[0]['properties']['tags'] ==\n 'Adriatic_Sea;Mediterranean_Basin;tag1;tag2')\n\n self.check_feature(fc.features[0])","def create_tags(tags_path: Path, email: str, password: str, host_url: str):\n with open(tags_path) as f:\n tags_json = json.load(f)\n\n client = client_util.make_client(host_url, email, password)\n\n # Build dictionary of tags as they exist on the server, mapped by slug.\n online_tags_resp = api_get_tags.sync_detailed(client=client)\n if online_tags_resp.status_code != HTTPStatus.OK:\n click.echo(f\"Request to get tags failed with status {online_tags_resp}\")\n exit(1)\n online_tags = {\n online_tag.slug: online_tag for online_tag in online_tags_resp.parsed\n }\n\n # Record slugs of tags that failed.\n failures = set()\n\n for tag in tags_json[\"tags\"]:\n slug = tag[\"slug\"]\n name = tag[\"name\"]\n description = tag[\"description\"]\n color = tag.get(\"color\")\n\n if slug in online_tags:\n # Update\n online_tag = online_tags[slug]\n if (\n name == online_tag.name\n and description == online_tag.description\n and (color is None or color == online_tag.color)\n ):\n click.echo(f\"Tag {slug} is already up to date.\")\n else:\n click.echo(f\"Updating tag {slug}\")\n res = api_update_tag.sync_detailed(\n slug,\n client=client,\n json_body=PutTagsTagJsonBody(\n name,\n description,\n color if color else online_tags[slug].color,\n ),\n )\n if res.status_code != HTTPStatus.OK:\n click.echo(f\"Request failed with content={res.content}\")\n failures.add(slug)\n else:\n # Create\n click.echo(f\"Creating tag {slug}\")\n res = api_create_tag.sync_detailed(\n client=client,\n json_body=PostTagsJsonBody(\n name,\n slug,\n description,\n color=color if color else UNSET,\n ),\n )\n if res.status_code != HTTPStatus.CREATED:\n click.echo(f\"Request failed with content={res.content}\", err=True)\n failures.add(slug)\n\n if failures:\n click.echo(f\"Completed with failures: {failures}\", err=True)\n sys.exit(1)","def create_tag(path, name, version, notes, test=False):\n\n tag_name = \"{}-{}\".format(name, version)\n tag_contents = \"Release %s for %s\\n\\n%s\" % (version, name, notes)\n\n if test:\n tag_name = \"test@\" + tag_name\n tag_contents = \"Test \" + tag_contents\n\n print(\"Creating annotated release tag: %s\" % tag_name)\n run_in_component(path, ['git', 'tag', '-a', '-F', '-', tag_name], stdin=tag_contents)","def create(self, name=None, description=None):\n uri = URITemplate(self.baseuri + '/{owner}').expand(\n owner=self.username)\n return self.session.post(uri, json=self._attribs(name, description))"],"string":"[\n \"def create(self, name, tag):\\n\\n\\t\\turl_json = urllib.urlencode({\\\"name\\\": name, \\\"tag\\\": tag})\\n\\t\\treturn self._create(\\\"/tag?json_hash=%s\\\" % url_json, \\\"tag\\\")\",\n \"def create_tag(self, session, tags):\\n self._tag(session.put, tags=tags, session=session)\",\n \"def create_tag(self, entry_name, tag):\\n return self.__datacatalog.create_tag(parent=entry_name, tag=tag)\",\n \"def create_tag_namespace(self, create_tag_namespace_details, **kwargs):\\n resource_path = \\\"/tagNamespaces\\\"\\n method = \\\"POST\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"opc_retry_token\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"create_tag_namespace got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"opc-retry-token\\\": kwargs.get(\\\"opc_retry_token\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\\n self.base_client.add_opc_retry_token_if_needed(header_params)\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n header_params=header_params,\\n body=create_tag_namespace_details,\\n response_type=\\\"TagNamespace\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n header_params=header_params,\\n body=create_tag_namespace_details,\\n response_type=\\\"TagNamespace\\\")\",\n \"def create_tag(name):\\n name = name.strip().lower()\\n tag = Tags(name)\\n try:\\n db_session.add(tag)\\n db_session.commit()\\n except exc.IntegrityError as err:\\n db_session.rollback()\\n return 'Tag \\\"%s\\\" has not been added - already exists: %s.' % (name, err), 'warning', None\\n return 'Tag \\\"%s\\\" has been added.' % name, 'success', tag\",\n \"def create_or_get_tag(self, tag_name: str, *args, **kwargs):\\n\\n tag_data = api.create_or_get_tag(\\n tag_name,\\n *args,\\n api_key=self.__creds.api_key_v2, \\n **kwargs)\\n return en.Tag(tag_data)\",\n \"def create_a_tag(self, tag_id, contact_id):\\n data = {\\\"contactTag\\\":{\\\"contact\\\":str(contact_id),\\\"tag\\\":str(tag_id)}}\\n\\n return self.client._post(\\\"/contactTags\\\", json=data)\",\n \"def createTag(self, authenticationToken, tag):\\r\\n pass\",\n \"def createTag(self, authenticationToken, tag):\\r\\n self.send_createTag(authenticationToken, tag)\\r\\n return self.recv_createTag()\",\n \"def create_tag():\\n \\n name = request.form['tag_name']\\n\\n if \\\"name\\\" in session:\\n return redirect(\\\"/tags\\\")\\n\\n else:\\n new_tag = Tag(name = name)\\n db.session.add(new_tag)\\n db.session.commit()\\n return redirect(\\\"/tags\\\")\",\n \"def _create_tag_request():\\n\\n key = helpers.get('Tag.1.Key')\\n value = helpers.get('Tag.1.Value')\\n resource_id = helpers.get('ResourceId.1')\\n\\n if resource_id in current_app.config['RESOURCE_TYPE_MAP']:\\n resource_type = current_app.config['RESOURCE_TYPE_MAP'][resource_id]\\n else:\\n errors.invalid_request(\\n str(resource_id) + \\\" not found in configuration\\\")\\n\\n args = {\\n 'command': 'createTags',\\n 'resourceids': resource_id,\\n 'resourcetype': resource_type,\\n 'tags[0].key': key,\\n 'tags[0].value': value\\n }\\n\\n response = requester.make_request_async(args)\\n\\n return response\",\n \"def create(self, params={}, **options):\\n return self.client.post(\\\"/tags\\\", params, **options)\",\n \"def make_tag(tag_name, text='', tag_attr=None):\\n if tag_attr is None:\\n tag_attr = {}\\n\\n doc = xml.dom.minidom.Document()\\n element = doc.createElement(tag_name)\\n if tag_attr:\\n for k, v in izip(list(tag_attr.keys()), list(tag_attr.values())):\\n element.setAttribute(unicode(k), unicode(v))\\n if text:\\n text_node = doc.createTextNode(text.strip())\\n element.appendChild(text_node)\\n return element\",\n \"def tag ():\\n\\n tagname = get_tag(comp_versions, 'ACE')\\n\\n if opts.tag:\\n if opts.take_action:\\n vprint (\\\"Placing tag %s on ACE_TAO\\\" % (tagname))\\n ex (\\\"cd $DOC_ROOT/ACE_TAO && git tag -a \\\" + tagname + \\\" -m\\\\\\\"\\\" + tagname + \\\"\\\\\\\"\\\")\\n\\n vprint (\\\"Placing tag %s on MPC\\\" % (tagname))\\n ex (\\\"cd $DOC_ROOT/MPC && git tag -a \\\" + tagname + \\\" -m\\\\\\\"\\\" + tagname + \\\"\\\\\\\"\\\")\\n\\n # Update release branches\\n latest_branch_helper (update_latest_branch, opts.release_type)\\n else:\\n vprint (\\\"Placing tag %s on ACE_TAO\\\" % (tagname))\\n vprint (\\\"Placing tag %s on MPC\\\" % (tagname))\\n print (\\\"Creating tags:\\\\n\\\")\\n print (\\\"Placing tag \\\" + tagname + \\\"\\\\n\\\")\",\n \"def create_tag(tag, directory=None):\\n execute_command('git tag {0}'.format(tag), shell=True, cwd=directory)\",\n \"def create_in_workspace(self, workspace, params={}, **options):\\n path = \\\"/workspaces/%s/tags\\\" % (workspace)\\n return self.client.post(path, params, **options)\",\n \"def add_tag(self, obj, tag_name):\\r\\n tag_names = parse_tag_input(tag_name)\\r\\n if not len(tag_names):\\r\\n raise AttributeError(_('No tags were given: \\\"%s\\\".') % tag_name)\\r\\n if len(tag_names) > 1:\\r\\n raise AttributeError(_('Multiple tags were given: \\\"%s\\\".') % tag_name)\\r\\n tag_name = tag_names[0]\\r\\n if settings.FORCE_LOWERCASE_TAGS:\\r\\n tag_name = tag_name.lower()\\r\\n tag, created = self.get_or_create(name=tag_name)\\r\\n ctype = ContentType.objects.get_for_model(obj)\\r\\n TaggedItem._default_manager.get_or_create(\\r\\n tag=tag, content_type=ctype, object_id=obj.pk)\",\n \"def add_tag(filename, tag_name):\\n storeapps = APP.config[\\\"storage\\\"]\\n filename = filename.encode(\\\"utf-8\\\")\\n print filename\\n\\n try:\\n application = list(nativeapps.io.ls(storeapps, r\\\".*\\\" + filename + \\\"$\\\"))[0]\\n meta_path = os.path.join(os.path.dirname(application), \\\"metadata.json\\\")\\n metadata = json.loads(nativeapps.io.readfile(meta_path))\\n tags = set(metadata.get(\\\"tags\\\", []))\\n tags.add(tag_name)\\n metadata[\\\"tags\\\"] = list(tags)\\n nativeapps.io.writefile(meta_path, json.dumps(metadata))\\n except IndexError:\\n return \\\"Unknown application: %s\\\" % (application), 404\\n\\n return \\\"added\\\", 200\",\n \"def add_tag(session, tag_name, user_id=None, username='system_user'):\\n session = validate_session(session)\\n date_created=datetime.now()\\n try:\\n add_tag = TagInfo(tag_name, date_created, user_id)\\n session.add(add_tag)\\n session.commit()\\n return(True, \\\"Tag %s added\\\" % (tag_name), add_tag)\\n except Exception as e:\\n session.rollback()\\n return(False, \\\"Tag %s failed to add\\\" % (tag_name))\",\n \"def addNode(self, nTag, pkg, exe, args, name, namespace):\\r\\n try:\\r\\n validateName(nTag)\\r\\n except IllegalName:\\r\\n raise InvalidRequest('Node tag is not a valid.')\\r\\n\\r\\n if nTag in self._nodes:\\r\\n raise InvalidRequest(\\\"Can not use the same node tag '{0}' in the \\\"\\r\\n 'same container twice.'.format(nTag))\\r\\n\\r\\n node = self._obj.createNode(pkg, exe, args, name, namespace)\\r\\n self._nodes[nTag] = node\\r\\n node.notifyOnDeath(self._nodeDied)\",\n \"def create(self, label_id):\\n data = {\\n 'type': 'tagit',\\n 'rate_count': 0,\\n 'rate_range': 'day',\\n 'limit_count': 0,\\n 'limit_range': 'day',\\n 'schedule': [],\\n 'enabled': True,\\n 'args': {\\n 'sn': label_id,\\n 'tag_sn': label_id\\n }\\n }\\n # Yes, it's confusing. the `/actions/` endpoint is used for tags, while\\n # the /tags/ endpoint is used for labels.\\n return self._post(\\n request=ApiActions.CREATE.value,\\n uri=ApiUri.ACTIONS.value,\\n params=data\\n )\",\n \"def ex_create_tags(self, node, tags):\\n if not tags:\\n return\\n\\n params = { 'Action': 'CreateTags',\\n 'ResourceId.0': node.id }\\n for i, key in enumerate(tags):\\n params['Tag.%d.Key' % i] = key\\n params['Tag.%d.Value' % i] = tags[key]\\n\\n self.connection.request(self.path,\\n params=params.copy()).object\",\n \"def add_tag(self, session, tag):\\n self._tag(session.put, key=tag, session=session)\",\n \"def test_create_tag_invalid(self):\\n tag_data = {'name': ''}\\n res = self.client.post(TAGS_URL, data=tag_data)\\n\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def create(self, name, description=None, color=None):\\n data = {\\n 'name': name,\\n 'title': name,\\n 'description': description or name,\\n 'appearance': {\\n 'color': color or random_color()\\n }\\n }\\n # Yes, it's confusing. the `/tags/` endpoint is used for labels\\n return self._post(\\n request=ApiActions.CREATE.value,\\n uri=ApiUri.TAGS.value,\\n params=data\\n )\",\n \"def test_create_tag_invalid(self):\\n payload = {'name': ''}\\n res = self.client.post(TAGS_URL, payload)\\n\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def test_create_tag_invalid(self):\\n payload = {'name': ''}\\n res = self.client.post(TAGS_URL, payload)\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def make_new_tag(tag_name, user_path, user_signed_in, current_user):\\n if not user_signed_in:\\n print('ALERT: -- User not logged in --')\\n else:\\n user = current_user[0]\\n print(is_tag(tag_name, user_path, current_user))\\n if is_tag(tag_name, user_path, current_user):\\n print('Tag already exist')\\n else:\\n os.mkdir((user_path + '\\\\\\\\' + user + '\\\\\\\\' + tag_name).encode('unicode_escape'))\\n print('Tag --' + tag_name + '-- Created')\",\n \"def create_tag(case_dict, new_tag, username, password):\\n # ---------------------------------------------------------------------\\n logger.debug(\\\"create_tag\\\")\\n\\n # create a new trunk tag\\n os.chdir(case_dict[\\\"archive_temp_dir\\\"])\\n svn_repo = \\\"{0}/trunk\\\".format(case_dict[\\\"svn_repo_url\\\"])\\n svn_repo_tag = \\\"{0}/trunk_tags/{1}\\\".format(case_dict[\\\"svn_repo_url\\\"], new_tag)\\n msg = '\\\"create new trunk tag\\\"'\\n cmd = [\\n \\\"svn\\\",\\n \\\"copy\\\",\\n \\\"--username\\\",\\n username,\\n \\\"--password\\\",\\n password,\\n svn_repo,\\n svn_repo_tag,\\n \\\"--message\\\",\\n msg,\\n ]\\n try:\\n subprocess.check_call(cmd)\\n except subprocess.CalledProcessError as error:\\n cmd_nopasswd = [\\n \\\"svn\\\",\\n \\\"copy\\\",\\n \\\"--username\\\",\\n username,\\n \\\"--password\\\",\\n \\\"******\\\",\\n svn_repo,\\n svn_repo_tag,\\n \\\"--message\\\",\\n msg,\\n ]\\n msg = _call_template.substitute(\\n function=\\\"checkin_trunk\\\",\\n cmd=cmd_nopasswd,\\n error=error.returncode,\\n strerror=error.output,\\n )\\n logger.warning(msg)\\n raise SVNException(msg)\",\n \"def _create_element(tag, text=\\\"\\\", attr={}, namespace=Xmlns_path):\\n element = Et.Element('.//' + namespace + tag, attr)\\n element.text = text\\n return element\",\n \"def create(cls, ns, name, **kwargs):\\n key_name = '%s:%s' % (ns, name)\\n return cls(key_name=key_name, ns=ns, name=name, **kwargs)\",\n \"def tag(self, tag):\\n \\n if isinstance(tag, six.integer_types):\\n try:\\n tag = Tag.objects.get(pk=tag, owner=self.owner)\\n except Tag.DoesNotExist:\\n #Handle this better?\\n return\\n \\n if isinstance(tag, six.string_types):\\n tname = tag\\n try:\\n tag = Tag(owner=self.owner, name=tag)\\n tag.save()\\n except IntegrityError:\\n tag = Tag.objects.get(slug=makeslug(tname), owner=self.owner)\\n \\n tag.save() # If this isn't here there are crashes for some reason\\n self.tags.add(tag)\",\n \"def ensure_tag(name, vocabulary=None):\\n obj = {'name': name}\\n where_clause = tag_table.c.name == name\\n\\n if vocabulary is not None:\\n ## Add vocabulary to filter / new object\\n vocabulary_id = ensure_vocabulary(vocabulary)\\n obj['vocabulary_id'] = vocabulary_id\\n where_clause = and_(\\n where_clause, tag_table.c.vocabulary_id == vocabulary_id)\\n\\n query = select([tag_table]).where(where_clause)\\n tag_obj = query.execute().first()\\n\\n if tag_obj is not None:\\n ## We already have the tag!\\n return tag_obj['id']\\n\\n ## Create tag, return id\\n return create_tag(obj)\",\n \"def post_namespace_create(self, resource_dict):\\n pass\",\n \"def create_tag(self,\\r\\n access_token,\\r\\n tag_create_params):\\r\\n\\r\\n # Prepare query URL\\r\\n _url_path = '/tags'\\r\\n _query_builder = Configuration.base_uri\\r\\n _query_builder += _url_path\\r\\n _query_parameters = {\\r\\n 'access_token': access_token\\r\\n }\\r\\n _query_builder = APIHelper.append_url_with_query_parameters(_query_builder,\\r\\n _query_parameters, Configuration.array_serialization)\\r\\n _query_url = APIHelper.clean_url(_query_builder)\\r\\n\\r\\n # Prepare headers\\r\\n _headers = {\\r\\n 'accept': 'application/json',\\r\\n 'content-type': 'application/json; charset=utf-8'\\r\\n }\\r\\n\\r\\n # Prepare and execute request\\r\\n _request = self.http_client.post(_query_url, headers=_headers, parameters=APIHelper.json_serialize(tag_create_params))\\r\\n CustomQueryAuth.apply(_request)\\r\\n _context = self.execute_request(_request)\\r\\n\\r\\n # Endpoint and global error handling using HTTP status codes.\\r\\n if _context.response.status_code == 0:\\r\\n raise APIException('Unexpected error.', _context)\\r\\n self.validate_response(_context)\\r\\n\\r\\n # Return appropriate type\\r\\n return APIHelper.json_deserialize(_context.response.raw_body, Tag.from_dictionary)\",\n \"def tag(self, tag_name):\\r\\n return Tag(self, tag_name)\",\n \"def CreateTags(self, ResourceId, TagName, TagValue):\\n\\n Client = boto3.client(self.Service)\\n\\n if self.Service == 'ec2':\\n response = Client.create_tags(\\n Resources = [\\n\\t\\t ResourceId\\n\\t\\t],\\n\\t\\tTags = [\\n {\\n\\t\\t 'Key': TagName,\\n\\t\\t 'Value': TagValue\\n }\\n\\t\\t]\\n\\t )\\n elif self.Service == 'efs':\\n response = Client.create_tags(\\n FileSystemId = ResourceId,\\n\\t\\tTags = [\\n {\\n\\t\\t 'Key': TagName,\\n\\t\\t 'Value': TagValue\\n }\\n\\t\\t]\\n\\t )\\n elif self.Service == 'redshift':\\n response = Client.create_tags(\\n ResourceName = ResourceId,\\n\\t\\tTags = [\\n {\\n\\t\\t 'Key': TagName,\\n\\t\\t 'Value': TagValue\\n }\\n\\t\\t]\\n\\t )\\n elif self.Service == 'workspaces':\\n response = Client.create_tags(\\n ResourceId = ResourceId,\\n\\t\\tTags = [\\n {\\n\\t\\t 'Key': TagName,\\n\\t\\t 'Value': TagValue\\n }\\n\\t\\t]\\n\\t )\\n else:\\n raise TagNotSupportedError(str(self.Service))\\n\\n return True\",\n \"def create(self, session, prepend_key=True):\\n if not self.allow_create:\\n raise exceptions.MethodNotSupported(self, \\\"create\\\")\\n\\n endpoint_override = self.service.get_endpoint_override()\\n if self.put_create:\\n # create tag do not need requires_id\\n request = self._prepare_request(requires_id=False,\\n prepend_key=prepend_key)\\n response = session.put(request.uri, endpoint_filter=self.service,\\n endpoint_override=endpoint_override,\\n json=request.body, headers=request.headers)\\n self._translate_response(response)\\n return self\",\n \"def create_tag_with_entry(title):\\n tag = Tag.objects.create(title=title)\\n tag.save()\\n tag.entry.add(1)\\n return tag\",\n \"def _add_tag(self, tag_name):\\n tag = TagInfo()\\n tag._name = tag_name\\n self._tags.append(tag)\\n return tag\",\n \"def test_create_tag_with_invalid_details_invalid(self):\\n\\n payload = {\\n 'name': ''\\n }\\n\\n res = self.client.post(TAGS_URL, payload)\\n\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def testAddTag(self):\\n project = self.session.create_project()\\n\\n project.add_tag(\\\"test\\\")\\n self.assertEqual(project.tags, [\\\"test\\\"], \\\"Can add a tag to a project.\\\")\\n\\n json_str = project.to_json()\\n doc = json.loads(json_str)\\n\\n self.assertEqual(doc['meta']['tags'], [\\\"test\\\"],\\n \\\"JSON representation had correct tags after add_tag().\\\")\\n\\n # Try adding the same tag yet again, shouldn't get a duplicate\\n with self.assertRaises(ValueError):\\n project.add_tag(\\\"test\\\")\\n\\n json_str = project.to_json()\\n doc2 = json.loads(json_str)\\n\\n self.assertEqual(doc2['meta']['tags'], [\\\"test\\\"],\\n \\\"JSON document did not end up with duplicate tags.\\\")\",\n \"def test_add_tag_invalid(self):\\n payload = {'name': ''}\\n res = self.client.post(TAGS_URL, payload)\\n\\n self.assertEqual(res.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def add_tag(convo_ID, tag_ID):\\n # Make API request\\n url = \\\"https://api2.frontapp.com/conversations/\\\" + convo_ID + \\\"/tags\\\"\\n payload = json.dumps({\\\"tag_ids\\\": [tag_ID]})\\n headers = {\\\"Authorization\\\": BEARER_TOKEN, \\\"Content-Type\\\": \\\"application/json\\\"}\\n requests.request(\\\"POST\\\", url, headers=headers, data=payload)\",\n \"def test_create_tag_invalid_payload(self):\\n\\n tag_payload = {'name': ''}\\n response = self.client.post(URL_TAGS, tag_payload)\\n\\n self.assertEqual(response.status_code, status.HTTP_400_BAD_REQUEST)\",\n \"def create_namespace(node, namespace, delete_before_create=True):\\n if delete_before_create:\\n Namespaces.delete_namespace(node, namespace)\\n\\n cmd = f\\\"ip netns add {namespace}\\\"\\n exec_cmd_no_error(node, cmd, sudo=True)\\n Namespaces.__namespaces.append(namespace)\",\n \"def update_tag(self, tag_namespace_id, tag_name, update_tag_details, **kwargs):\\n resource_path = \\\"/tagNamespaces/{tagNamespaceId}/tags/{tagName}\\\"\\n method = \\\"PUT\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"if_match\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"update_tag got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tagNamespaceId\\\": tag_namespace_id,\\n \\\"tagName\\\": tag_name\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"if-match\\\": kwargs.get(\\\"if_match\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_tag_details,\\n response_type=\\\"Tag\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_tag_details,\\n response_type=\\\"Tag\\\")\",\n \"def CreateForTag(cls, tag):\\n parent_key = cls._GetParentKeyFromTag(tag)\\n return cls(parent=parent_key)\",\n \"def add_tag():\\n\\n tag_name = request.form[\\\"name\\\"]\\n\\n if not tag_name:\\n flash(\\\"Please enter tag name\\\")\\n return redirect(\\\"/tags/new\\\")\\n\\n tag = Tag(name=tag_name)\\n db.session.add(tag)\\n db.session.commit()\\n\\n return redirect(\\\"/tags\\\")\",\n \"async def slashtag_add(\\n self,\\n ctx: commands.Context,\\n tag_name: TagName(check_global=False),\\n *,\\n tagscript: TagScriptConverter,\\n ):\\n await self.create_slash_tag(ctx, tag_name, tagscript, is_global=False)\",\n \"def test_create_tag_invalid(self):\\n payload = {'name':''}\\n res = self.client.post(TAG_URL,payload)\\n self.assertEqual(res.status_code,status.HTTP_400_BAD_REQUEST)\",\n \"def add(self, tag):\\n self.tags[tag.name] = tag\",\n \"def create_tags(ResourceArn=None, Tags=None):\\n pass\",\n \"def _handle_new_tag(self, tag_name):\\n log.debug(\\\"Handling new tag: %s\\\", tag_name)\\n tag, created = Tag.get_or_create(name=tag_name)\\n if tag not in self.doc.tags:\\n self.listbox.body.insert(-1, MenuButton(tag_name, None))\\n tag.documents.add(self.doc)\\n self.new_tag.set_edit_text(\\\"\\\")\",\n \"def test_create_tag(self):\\n\\n tag_payload = {'name': 'Test Tag'}\\n self.client.post(URL_TAGS, tag_payload)\\n\\n is_tag_created = Tag.objects.filter(\\n user=self.user,\\n name=tag_payload['name']\\n ).exists()\\n\\n self.assertTrue(is_tag_created)\",\n \"def test_add_defined_tag_to_bucket(self, test, object_storage, with_or_without_compartment):\\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\\n session_factory = test.oci_session_factory()\\n policy = test.load_policy(\\n {\\n \\\"name\\\": \\\"add-defined-tag-to-bucket\\\",\\n \\\"resource\\\": \\\"oci.bucket\\\",\\n \\\"query\\\": [\\n {\\\"namespace_name\\\": namespace_name},\\n ],\\n \\\"filters\\\": [\\n {\\\"type\\\": \\\"value\\\", \\\"key\\\": \\\"name\\\", \\\"value\\\": bucket_name},\\n ],\\n \\\"actions\\\": [{\\\"type\\\": \\\"update\\\", \\\"defined_tags\\\": self.get_defined_tag(\\\"add_tag\\\")}],\\n },\\n session_factory=session_factory,\\n )\\n policy.run()\\n resource = self._fetch_bucket_validation_data(\\n policy.resource_manager, namespace_name, bucket_name\\n )\\n test.assertEqual(resource[\\\"name\\\"], bucket_name)\\n test.assertEqual(self.get_defined_tag_value(resource[\\\"defined_tags\\\"]), \\\"true\\\")\",\n \"def create_tags(resource_id, key, value):\\n response = EC2.create_tags(\\n Resources=[\\n resource_id,\\n ],\\n Tags=[\\n {\\n 'Key': key,\\n 'Value': value\\n },\\n ]\\n )\\n return response\",\n \"def GachaCraftNodeExcelAddTag_(builder, Tag_):\\n return AddTag_(builder, Tag_)\",\n \"def add_tag(self, *,\\n id: str,\\n tag: str,\\n tag_type: str = 'default',\\n resource_type: ResourceType = ResourceType.Table) -> None:\\n LOGGER.info(f'New tag {tag} for id {id} with type {tag_type} and resource type {resource_type.name}')\\n\\n resource_table = f'{resource_type.name.lower()}_tag'\\n resource_model = self._get_model_from_table_name(resource_table)\\n if not resource_model:\\n raise NotImplementedError(f'The resource type {resource_type.name} is not defined!')\\n\\n resource_key = f'{resource_type.name.lower()}_rk'\\n\\n tag_record = RDSTag(rk=tag, tag_type=tag_type)\\n resource_tag_record = resource_model(tag_rk=tag)\\n resource_tag_record.__setattr__(resource_key, id)\\n try:\\n with self.client.create_session() as session:\\n session.merge(tag_record)\\n session.merge(resource_tag_record)\\n session.commit()\\n except Exception as e:\\n LOGGER.exception(f'Failed to add tag {tag} for {id}')\\n raise e\",\n \"def add_new_tag():\\n\\n name = request.form.get('name')\\n\\n new_tag = Tag(name=name)\\n db.session.add(new_tag)\\n db.session.commit()\\n\\n return redirect(f'/tags')\",\n \"def add_tag(self, tag, attributes, extent):\\n self.tags.append((tag, attributes, extent))\",\n \"def _mk_tag(ns, tag):\\n return '{%s}%s' % (ns, tag) if ns else tag\",\n \"def make_new_tag():\\n return render_template('tags/new_tag.html')\",\n \"def test_create_tag_succesful(self):\\n payload = {'name': 'Test tag'}\\n res = self.client.post(TAGS_URL, payload)\\n\\n exists = Tag.objects.filter(\\n user=self.user,\\n name=payload['name']\\n ).exists()\\n self.assertTrue(exists)\\n self.assertEqual(res.status_code, status.HTTP_201_CREATED)\",\n \"def create_container(ContainerName=None, Tags=None):\\n pass\",\n \"def create_tag(self, name: str, revision: Optional[str] = None) -> None:\\n if not revision:\\n self._status.check_authority_for_commit()\\n revision = self._status.commit_id\\n\\n post_data: Dict[str, Any] = {\\\"commit\\\": revision, \\\"name\\\": name}\\n\\n self._client.open_api_do(\\\"POST\\\", \\\"tags\\\", self.dataset_id, json=post_data)\",\n \"def add_new_tag():\\n\\n return render_template('create-tag.html')\",\n \"def add_tag(self, key, value=''):\\r\\n status = self.connection.create_tags([self.id], {key : value})\\r\\n if self.tags is None:\\r\\n self.tags = TagSet()\\r\\n self.tags[key] = value\",\n \"def create(context, namespace_name, values, session):\\n\\n namespace = namespace_api.get(\\n context, namespace_name, session)\\n\\n # if the resource_type does not exist, create it\\n resource_type_name = values['name']\\n metadef_utils.drop_protected_attrs(\\n models.MetadefNamespaceResourceType, values)\\n try:\\n resource_type = resource_type_api.get(\\n context, resource_type_name, session)\\n except exc.NotFound:\\n resource_type = None\\n LOG.debug(\\\"Creating resource-type %s\\\", resource_type_name)\\n\\n if resource_type is None:\\n resource_type_dict = {'name': resource_type_name, 'protected': False}\\n resource_type = resource_type_api.create(\\n context, resource_type_dict, session)\\n\\n # Create the association record, set the field values\\n ns_resource_type_dict = _to_db_dict(\\n namespace['id'], resource_type['id'], values)\\n new_rec = _create_association(context, namespace_name, resource_type_name,\\n ns_resource_type_dict, session)\\n\\n return _to_model_dict(resource_type_name, new_rec)\",\n \"def add_tag(self, tag: str) -> None:\\n tags = self.get_tag_index()\\n tags.append(tag)\\n self.write_tag_index(list(set(tags)))\",\n \"def add_tag(self, cr, uid, ids, code=None, name=None, create=False, context=None):\\n tag_obj = self.pool.get('res.tag')\\n tag_ids = tag_obj.get_tag_ids(cr, uid, self._name, code=code, name=name, context=context)\\n if not tag_ids and create:\\n model_id = self.pool.get('res.tag.model').search(cr, uid, [('model', '=', self._name)])[0]\\n tag_ids = [tag_obj.create(cr, uid, {'name': name, 'code': code, 'model_id': model_id}, context=context)]\\n\\n if tag_ids:\\n self.write(cr, uid, ids, {'tag_ids': [(4, tid) for tid in tag_ids]}, context=context)\\n\\n return bool(tag_ids)\",\n \"def tag(request, tag_name):\\n raise NotImplementedError\",\n \"def _createElement(self, identifier, request):\\n try:\\n decoder, contentType = self._getDecoder(request)\\n state = decoder(request.body)\\n\\n element = self._collection.createElementFromState(state)\\n\\n actualIdentifier = getattr(element, element.identifyingAttribute)\\n if actualIdentifier != identifier:\\n raise errors.IdentifierError(identifier, actualIdentifier)\\n\\n self._collection.add(element)\\n return Created()\\n except errors.SerializableError, e:\\n contentType = self.defaultContentType\\n encoder = self.encoders[contentType]\\n errorResource = RESTErrorPage(e, encoder, contentType)\\n return errorResource\",\n \"def tag(\\n name: str, value: str, *, attributes: dict = {}, namespace: str = None\\n ) -> str:\\n attributes_str = \\\" \\\".join(f'{k}=\\\"{v}\\\"' for k, v in attributes.items())\\n ns = f\\\"{namespace}:\\\" if namespace else \\\"\\\"\\n if attributes_str:\\n attributes_str = \\\" \\\" + attributes_str\\n if value:\\n return f\\\"<{ns}{name}{attributes_str}>{value}\\\"\\n return f\\\"<{ns}{name}{attributes_str} />\\\"\",\n \"def create_tags(self, resource_ids, tags):\\r\\n params = {}\\r\\n self.build_list_params(params, resource_ids, 'ResourceId')\\r\\n self.build_tag_param_list(params, tags)\\r\\n return self.get_status('CreateTags', params, verb='POST')\",\n \"def add_tag(self, transaction, citation_handle, tag_handle):\\n citation = self.dbstate.db.get_citation_from_handle(citation_handle)\\n citation.add_tag(tag_handle)\\n self.dbstate.db.commit_citation(citation, transaction)\",\n \"def AddTag(self, tag):\\n\\n if not self.persistant:\\n return\\n\\n self.db.ExecuteSql('insert into tags(tag, track_id) values(\\\"%s\\\", %d);'\\n %(tag, self.persistant['id']))\\n self.db.ExecuteSql('commit;')\",\n \"def test_create_tag_successful(self):\\n tag_data = {'name': 'Snack'}\\n res = self.client.post(TAGS_URL, data=tag_data)\\n\\n exists = Tag.objects.filter(\\n user=self.user,\\n name=tag_data['name']\\n ).exists()\\n\\n self.assertEqual(res.status_code, status.HTTP_201_CREATED)\\n self.assertTrue(exists)\",\n \"def create_test_node_tag(**kw):\\n tag = get_test_node_tag(**kw)\\n dbapi = db_api.get_instance()\\n return dbapi.add_node_tag(tag['node_id'], tag['tag'])\",\n \"def tag_add(self, remote_path, corpus_id, tag, storage_id=None):\\n client, remote_path = self._get_storage(remote_path, storage_id=storage_id)\\n return client.tag_add(corpus_id, tag)\",\n \"def sample_tag(user, name='Service Tag'):\\n return Tag.objects.create(user=user, name=name)\",\n \"def create_resource(self, namespace: \\\"str\\\" = None):\\n names = [\\\"create_namespaced_csistorage_capacity\\\", \\\"create_csistorage_capacity\\\"]\\n\\n _kube_api.execute(\\n action=\\\"create\\\",\\n resource=self,\\n names=names,\\n namespace=namespace,\\n api_client=None,\\n api_args={\\\"body\\\": self.to_dict()},\\n )\",\n \"def create_or_update_tags(self, Tags):\\n tag = Tags[0]\\n asg_name = tag['ResourceId']\\n ec2_tag = {\\n 'Key': tag['Key'],\\n 'Value': tag['Value']\\n }\\n try:\\n response = self.asg.create_or_update_tags(\\n Tags=Tags\\n )\\n except Exception as e:\\n logger.error('Unknown Error: %s', str(e))\\n else:\\n logger.info(response)\\n\\n asg_instances = self.get_asg_instance_ids(asg_name)\\n return EC2Wrapper(self.session).create_tags(Resources=asg_instances, Tags=[ec2_tag])\",\n \"def add_tag(self, tag_name, name = 'tag'):\\r\\n if self._only_whitespace.match(tag_name):\\r\\n # Don't allow an empty tag\\r\\n return\\r\\n\\r\\n try:\\r\\n tag = Tag._by_name(tag_name)\\r\\n except NotFound:\\r\\n tag = Tag._new(tag_name)\\r\\n tag._commit()\\r\\n\\r\\n # See if link already has this tag\\r\\n tags = LinkTag._fast_query(tup(self), tup(tag), name=name)\\r\\n link_tag = tags[(self, tag, name)]\\r\\n if not link_tag:\\r\\n link_tag = LinkTag(self, tag, name=name)\\r\\n link_tag._commit()\\r\\n\\r\\n return link_tag\",\n \"def createElement(tagName):\\n print(\\\"Warning: createElement is deprecated in favor of createComponent\\\")\\n return createComponent(tagName)\",\n \"def handle_add_new_tag():\\n tag = Tag(name=request.form['name'])\\n\\n db.session.add(tag)\\n db.session.commit()\\n\\n return redirect('/tags')\",\n \"def update_tag_namespace(self, tag_namespace_id, update_tag_namespace_details, **kwargs):\\n resource_path = \\\"/tagNamespaces/{tagNamespaceId}\\\"\\n method = \\\"PUT\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"update_tag_namespace got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tagNamespaceId\\\": tag_namespace_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_tag_namespace_details,\\n response_type=\\\"TagNamespace\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_tag_namespace_details,\\n response_type=\\\"TagNamespace\\\")\",\n \"def create_uuid3(namespace, name):\\n return uuid.uuid3(namespace, six.ensure_str(name))\",\n \"def set_tag(request):\\n try:\\n # Update existing Tag if tag_id exists, else create new Tag\\n if \\\"tag_id\\\" not in request.POST or not request.POST[\\\"tag_id\\\"]:\\n # Create new Tag\\n tag = Tag.objects.create(title=request.form.cleaned_data[\\\"title\\\"])\\n\\n ActionLogger().log(request.user, \\\"created\\\", \\\"Knowledgebase Tag %s\\\" % tag)\\n return format_ajax_response(True, \\\"Knowledgebase tag created successfully.\\\")\\n else:\\n # Update existing category\\n tag = Tag.objects.get(pk=request.POST[\\\"tag_id\\\"])\\n tag.title = request.form.cleaned_data[\\\"title\\\"]\\n tag.save()\\n\\n ActionLogger().log(request.user, \\\"modified\\\", \\\"Knowledgebase Tag %s\\\" % tag)\\n return format_ajax_response(True, \\\"Knowledgebase tag updated successfully.\\\")\\n except Exception as ex:\\n logger.error(\\\"Failed to set_tag: %s\\\" % ex)\\n return format_ajax_response(False, \\\"There was an error setting the specified knowledgebase tag.\\\")\",\n \"def createContainer(tag, data={}): #@NoSelf\",\n \"def change_tag_namespace_compartment(self, tag_namespace_id, change_tag_namespace_compartment_detail, **kwargs):\\n resource_path = \\\"/tagNamespaces/{tagNamespaceId}/actions/changeCompartment\\\"\\n method = \\\"POST\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"opc_retry_token\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"change_tag_namespace_compartment got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tagNamespaceId\\\": tag_namespace_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"opc-retry-token\\\": kwargs.get(\\\"opc_retry_token\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\\n self.base_client.add_opc_retry_token_if_needed(header_params)\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=change_tag_namespace_compartment_detail)\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=change_tag_namespace_compartment_detail)\",\n \"def initiate_new_tag (self,tag,key):\\r\\n\\r\\n #with shelf\\r\\n if self.using_shelf:\\r\\n self.tag_dict[tag] = {key}\\r\\n #with database\\r\\n\\r\\n if self.using_database:\\r\\n\\r\\n value_tuple = (notebookname, tag, key)\\r\\n db_cursor.execute(\\\"INSERT OR REPLACE\\\"\\r\\n +\\\" INTO tags_to_keys\\\"\\r\\n +\\\" (notebook, tag, keyword)\\\"\\r\\n +\\\" VALUES (?,?,?);\\\",\\r\\n value_tuple)\",\n \"def tag(nodes, arg='', split=True, default=0, add_parent_space=True, add_default_spaces=True, zero_node=None, const_node=None):\\n\\n nodes = mc.ls(nodes)\\n orig_const_node = const_node\\n orig_zero_node = zero_node\\n\\n for node in nodes:\\n\\n # get zero if not specified\\n if orig_zero_node:\\n zero_node = orig_zero_node\\n else:\\n zero_node = node+'_ZERO'\\n\\n # get const node - this is what the parent constraint will be thrown onto\\n if orig_const_node:\\n const_node = orig_const_node\\n else:\\n const_node = node+'_CONST'\\n\\n if add_parent_space and not mc.objExists(zero_node):\\n mc.warning('Cannot find a zero for '+node)\\n continue\\n\\n if not mc.objExists(const_node):\\n mc.warning('Cannot find a const for '+const_node)\\n continue\\n\\n # build arg\\n arg = arg.strip()\\n if ' ' in arg:\\n arg = re.sub(' +',' ', arg)\\n\\n arg_kwargs = {\\n 'arg': arg,\\n 'split': split,\\n 'default': default,\\n 'const_node': const_node,\\n 'zero_node': zero_node,\\n 'add_default_spaces': add_default_spaces,\\n 'add_parent_space': add_parent_space\\n }\\n\\n # create + set attr\\n if not mc.objExists(node+'.tagSpaces'):\\n mc.addAttr(node, ln='tagSpaces', dt='string', hidden=False)\\n\\n mc.setAttr(node+'.tagSpaces', str(arg_kwargs), type='string')\\n\\n # This convert all this legacy sloppy crap to the new hotness\\n space_obj = Space(node)\\n space_obj.set_data()\\n\\n return arg\",\n \"def add_tag(self, tag):\\n self.tags.append(tag)\",\n \"def _AddCreatedNamespace(self, state_tracker, identifier, line_number,\\n namespace=None):\\n if not namespace:\\n namespace = identifier\\n\\n if self._HasSuppression(state_tracker, 'missingProvide'):\\n return\\n\\n self._created_namespaces.append([namespace, identifier, line_number])\",\n \"def insert_tag(self, tagname, attrs=[], text=\\\"\\\",\\n autoclose=False, newline=False):\\n if autoclose:\\n self.str += '\\\\n<%s%s%s>' % (tagname, string_for_attrs(attrs),\\n ' /' if self.is_xml else '')\\n else:\\n self.push_tag(tagname, attrs)\\n if text:\\n if newline:\\n self.insert_text('\\\\n' + indent(text, self.indent_level()))\\n else:\\n self.insert_text(text)\\n self.pop_tag(newline=newline)\",\n \"def test_add_tag(self):\\n fc = self.read_feature(region='Adriatic_Sea')\\n\\n fc.tag(tags=['tag1', 'tag2', 'Mediterranean_Basin'])\\n assert (fc.features[0]['properties']['tags'] ==\\n 'Adriatic_Sea;Mediterranean_Basin;tag1;tag2')\\n\\n self.check_feature(fc.features[0])\",\n \"def create_tags(tags_path: Path, email: str, password: str, host_url: str):\\n with open(tags_path) as f:\\n tags_json = json.load(f)\\n\\n client = client_util.make_client(host_url, email, password)\\n\\n # Build dictionary of tags as they exist on the server, mapped by slug.\\n online_tags_resp = api_get_tags.sync_detailed(client=client)\\n if online_tags_resp.status_code != HTTPStatus.OK:\\n click.echo(f\\\"Request to get tags failed with status {online_tags_resp}\\\")\\n exit(1)\\n online_tags = {\\n online_tag.slug: online_tag for online_tag in online_tags_resp.parsed\\n }\\n\\n # Record slugs of tags that failed.\\n failures = set()\\n\\n for tag in tags_json[\\\"tags\\\"]:\\n slug = tag[\\\"slug\\\"]\\n name = tag[\\\"name\\\"]\\n description = tag[\\\"description\\\"]\\n color = tag.get(\\\"color\\\")\\n\\n if slug in online_tags:\\n # Update\\n online_tag = online_tags[slug]\\n if (\\n name == online_tag.name\\n and description == online_tag.description\\n and (color is None or color == online_tag.color)\\n ):\\n click.echo(f\\\"Tag {slug} is already up to date.\\\")\\n else:\\n click.echo(f\\\"Updating tag {slug}\\\")\\n res = api_update_tag.sync_detailed(\\n slug,\\n client=client,\\n json_body=PutTagsTagJsonBody(\\n name,\\n description,\\n color if color else online_tags[slug].color,\\n ),\\n )\\n if res.status_code != HTTPStatus.OK:\\n click.echo(f\\\"Request failed with content={res.content}\\\")\\n failures.add(slug)\\n else:\\n # Create\\n click.echo(f\\\"Creating tag {slug}\\\")\\n res = api_create_tag.sync_detailed(\\n client=client,\\n json_body=PostTagsJsonBody(\\n name,\\n slug,\\n description,\\n color=color if color else UNSET,\\n ),\\n )\\n if res.status_code != HTTPStatus.CREATED:\\n click.echo(f\\\"Request failed with content={res.content}\\\", err=True)\\n failures.add(slug)\\n\\n if failures:\\n click.echo(f\\\"Completed with failures: {failures}\\\", err=True)\\n sys.exit(1)\",\n \"def create_tag(path, name, version, notes, test=False):\\n\\n tag_name = \\\"{}-{}\\\".format(name, version)\\n tag_contents = \\\"Release %s for %s\\\\n\\\\n%s\\\" % (version, name, notes)\\n\\n if test:\\n tag_name = \\\"test@\\\" + tag_name\\n tag_contents = \\\"Test \\\" + tag_contents\\n\\n print(\\\"Creating annotated release tag: %s\\\" % tag_name)\\n run_in_component(path, ['git', 'tag', '-a', '-F', '-', tag_name], stdin=tag_contents)\",\n \"def create(self, name=None, description=None):\\n uri = URITemplate(self.baseuri + '/{owner}').expand(\\n owner=self.username)\\n return self.session.post(uri, json=self._attribs(name, description))\"\n]"},"negative_scores":{"kind":"list like","value":["0.668044","0.64789695","0.6425235","0.63370335","0.62885815","0.6265026","0.6156292","0.61304843","0.5985835","0.5902972","0.5860836","0.5857317","0.58103025","0.5736905","0.57278633","0.571501","0.5682197","0.56273866","0.5566556","0.5561892","0.5553828","0.5545572","0.55432534","0.55401194","0.5506235","0.5496501","0.54942423","0.5488063","0.54709196","0.5461829","0.54439485","0.54430693","0.534843","0.5336418","0.5329959","0.53045946","0.5299483","0.5289044","0.52645415","0.5256345","0.5242787","0.5235177","0.52324855","0.5228213","0.52257115","0.52217585","0.5217019","0.52148294","0.52096367","0.51985246","0.51750684","0.51694906","0.5152105","0.51327765","0.51304066","0.5129684","0.5129471","0.51263666","0.51209426","0.5112871","0.51111007","0.50970364","0.50949776","0.50764114","0.5073295","0.50582224","0.50435805","0.50413644","0.50357985","0.50257164","0.5009755","0.5008614","0.5001197","0.4998684","0.49962315","0.4994019","0.49904567","0.4981564","0.4978175","0.49770766","0.49429157","0.492379","0.49208084","0.48964944","0.48963678","0.48908284","0.489074","0.48853713","0.4880499","0.4879605","0.48764196","0.48630872","0.4861964","0.4846571","0.48441756","0.48438865","0.48361236","0.48346114","0.48341796","0.48242828"],"string":"[\n \"0.668044\",\n \"0.64789695\",\n \"0.6425235\",\n \"0.63370335\",\n \"0.62885815\",\n \"0.6265026\",\n \"0.6156292\",\n \"0.61304843\",\n \"0.5985835\",\n \"0.5902972\",\n \"0.5860836\",\n \"0.5857317\",\n \"0.58103025\",\n \"0.5736905\",\n \"0.57278633\",\n \"0.571501\",\n \"0.5682197\",\n \"0.56273866\",\n \"0.5566556\",\n \"0.5561892\",\n \"0.5553828\",\n \"0.5545572\",\n \"0.55432534\",\n \"0.55401194\",\n \"0.5506235\",\n \"0.5496501\",\n \"0.54942423\",\n \"0.5488063\",\n \"0.54709196\",\n \"0.5461829\",\n \"0.54439485\",\n \"0.54430693\",\n \"0.534843\",\n \"0.5336418\",\n \"0.5329959\",\n \"0.53045946\",\n \"0.5299483\",\n \"0.5289044\",\n \"0.52645415\",\n \"0.5256345\",\n \"0.5242787\",\n \"0.5235177\",\n \"0.52324855\",\n \"0.5228213\",\n \"0.52257115\",\n \"0.52217585\",\n \"0.5217019\",\n \"0.52148294\",\n \"0.52096367\",\n \"0.51985246\",\n \"0.51750684\",\n \"0.51694906\",\n \"0.5152105\",\n \"0.51327765\",\n \"0.51304066\",\n \"0.5129684\",\n \"0.5129471\",\n \"0.51263666\",\n \"0.51209426\",\n \"0.5112871\",\n \"0.51111007\",\n \"0.50970364\",\n \"0.50949776\",\n \"0.50764114\",\n \"0.5073295\",\n \"0.50582224\",\n \"0.50435805\",\n \"0.50413644\",\n \"0.50357985\",\n \"0.50257164\",\n \"0.5009755\",\n \"0.5008614\",\n \"0.5001197\",\n \"0.4998684\",\n \"0.49962315\",\n \"0.4994019\",\n \"0.49904567\",\n \"0.4981564\",\n \"0.4978175\",\n \"0.49770766\",\n \"0.49429157\",\n \"0.492379\",\n \"0.49208084\",\n \"0.48964944\",\n \"0.48963678\",\n \"0.48908284\",\n \"0.489074\",\n \"0.48853713\",\n \"0.4880499\",\n \"0.4879605\",\n \"0.48764196\",\n \"0.48630872\",\n \"0.4861964\",\n \"0.4846571\",\n \"0.48441756\",\n \"0.48438865\",\n \"0.48361236\",\n \"0.48346114\",\n \"0.48341796\",\n \"0.48242828\"\n]"},"document_score":{"kind":"string","value":"0.7148086"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8586,"cells":{"query":{"kind":"string","value":"Creates a new tag default in the specified compartment for the specified tag definition. If you specify that a value is required, a value is set during resource creation (either by the user creating the resource or another tag defualt). If no value is set, resource creation is blocked. If the `isRequired` flag is set to \\\"true\\\", the value is set during resource creation. If the `isRequired` flag is set to \\\"false\\\", the value you enter is set during resource creation."},"document":{"kind":"string","value":"def create_tag_default(self, create_tag_default_details, **kwargs):\n resource_path = \"/tagDefaults\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\",\n \"opc_request_id\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_tag_default got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing),\n \"opc-request-id\": kwargs.get(\"opc_request_id\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_tag_default_details,\n response_type=\"TagDefault\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_tag_default_details,\n response_type=\"TagDefault\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def Option(name: str, value: Union[str, int], default: Optional[bool] = None) -> Dict:\n doc = {'name': name, 'value': value}\n if default is not None:\n doc['isDefault'] = default\n return doc","def register_option_pair(key, default_value):\n\n _OPTION_TEMPLATE[key] = default_value","def createDevIDAttr(shapefileName, defaultVal):\n\n inputds = ogr.Open(shapefileName,update=True)\n if not inputds:\n sys.exit(\"Unable to open input file '{0}'\".format(shapefileName))\n\n inputlyr = inputds.GetLayer()\n\n # Create field definition(s)\n # Add input Layer Fields to the output Layer if defined in field_names arg.\n inLayerDefn = inputlyr.GetLayerDefn()\n if inLayerDefn.GetFieldIndex(cc.DEV_LAYER_ATTRIBUTE_NAME) == -1:\n print(\"\\tCreating an Attribute '{0}' in vector file '{1}'\".format(cc.DEV_LAYER_ATTRIBUTE_NAME,shapefileName))\n\n inputlyr.CreateField(ogr.FieldDefn(cc.DEV_LAYER_ATTRIBUTE_NAME, ogr.OFTInteger))\n\n for inFeature in inputlyr:\n inFeature.SetField(cc.DEV_LAYER_ATTRIBUTE_NAME,defaultVal)\n inputlyr.SetFeature(inFeature)\n\n inputds.Destroy()\n print(\"\\tCreated an Attribute '{0}' in vector file '{1}'\".format(cc.DEV_LAYER_ATTRIBUTE_NAME,shapefileName))","def update_tag_default(self, tag_default_id, update_tag_default_details, **kwargs):\n resource_path = \"/tagDefaults/{tagDefaultId}\"\n method = \"PUT\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"if_match\",\n \"opc_request_id\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"update_tag_default got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagDefaultId\": tag_default_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"if-match\": kwargs.get(\"if_match\", missing),\n \"opc-request-id\": kwargs.get(\"opc_request_id\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_default_details,\n response_type=\"TagDefault\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_default_details,\n response_type=\"TagDefault\")","def _add_default_tags(self):\n self.tags.add_tag('ban', required=True)","def create_object_parameter_from_default(obj, default):\n values = []\n if default.enum:\n for v in DefaultParameterVl.objects.filter(parameter=default).all():\n values.append({'value' : v.value,\n 'caption' : v.caption})\n return create_object_parameter(obj, 'user', False,\n tp = default.tp,\n name=default.name,\n descr=default.descr,\n values=values)","def __init__(self, default_value, description, register=None, name=None,\n is_key=False, **kwargs):\n self._default_value = default_value\n self._description = description\n self._register = register\n self._name = name\n self._is_key = is_key\n self._kwargs = kwargs\n\n self._value = default_value\n self._frozen = False","def set_default(self, name, default, group=None):\n opt_info = self._get_opt_info(name, group)\n opt_info['default'] = self._get_enforced_type_value(\n opt_info['opt'], default)\n opt_info['location'] = LocationInfo(\n Locations.set_default,\n _get_caller_detail(3), # this function has a decorator to skip\n )","def _create_tag_request():\n\n key = helpers.get('Tag.1.Key')\n value = helpers.get('Tag.1.Value')\n resource_id = helpers.get('ResourceId.1')\n\n if resource_id in current_app.config['RESOURCE_TYPE_MAP']:\n resource_type = current_app.config['RESOURCE_TYPE_MAP'][resource_id]\n else:\n errors.invalid_request(\n str(resource_id) + \" not found in configuration\")\n\n args = {\n 'command': 'createTags',\n 'resourceids': resource_id,\n 'resourcetype': resource_type,\n 'tags[0].key': key,\n 'tags[0].value': value\n }\n\n response = requester.make_request_async(args)\n\n return response","def addDefault(self, name, object):\n if name is None:\n raise ValueError(\"Name cannot be None\")\n self.defaultChoice = name\n self.addObject(name, object)","def __init__(self, name=None, values=None, default_value=None):\n self.swagger_types = {\n 'name': 'str',\n 'values': 'list[TagPropertyAllowedValue]',\n 'default_value': 'str'\n }\n\n self.attribute_map = {\n 'name': 'name',\n 'values': 'values',\n 'default_value': 'defaultValue'\n }\n\n self._name = name\n self._values = values\n self._default_value = default_value","def var(\n default: Any = RAISE,\n converter: Callable | None = None,\n name: str | None = None,\n validator: Callable | None = None,\n help: str | None = None,\n) -> Any:\n return attr.ib(\n default=default,\n metadata={CNF_KEY: _ConfigEntry(name, default, None, None, help)},\n converter=converter,\n validator=validator,\n )","def create(self, name, description=None, color=None):\n data = {\n 'name': name,\n 'title': name,\n 'description': description or name,\n 'appearance': {\n 'color': color or random_color()\n }\n }\n # Yes, it's confusing. the `/tags/` endpoint is used for labels\n return self._post(\n request=ApiActions.CREATE.value,\n uri=ApiUri.TAGS.value,\n params=data\n )","def validate_default_element(self, value):\n return self.validate_element(value)","def validate_default(self, value):\n return self.__validate(value, self.validate_default_element)","def test_string_default(self):\n tag = Tag()\n self.assertEqual(tag.value, 'default')","def delete_tag_default(self, tag_default_id, **kwargs):\n resource_path = \"/tagDefaults/{tagDefaultId}\"\n method = \"DELETE\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_request_id\",\n \"if_match\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"delete_tag_default got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagDefaultId\": tag_default_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-request-id\": kwargs.get(\"opc_request_id\", missing),\n \"if-match\": kwargs.get(\"if_match\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params)\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params)","def default_arg(default):\n class DefaultArg(argparse.Action):\n def __call__(self, parser, namespace, value, option_string):\n if value is None:\n setattr(namespace, self.dest, default)\n else:\n setattr(namespace, self.dest, value)\n\n return DefaultArg","def _set_default(name, value, context):\n if name not in context:\n context[name] = value","def __init__(self, name=None, value=None):\n default_attr = dict(name=str(),\n value=str())\n self.name = name\n self.value = value\n self._set_default_attr(default_attr)","def createTag(self, authenticationToken, tag):\r\n pass","def __init__(self,\n name=None,\n help_text=None,\n fallthroughs=None,\n completer=None,\n completion_request_params=None,\n completion_id_field=None,\n value_type=None,\n parameter_name=None):\n self.attribute_name = name\n self.help_text = help_text\n self.fallthroughs = fallthroughs or []\n # The completer is always None because neither the surface nor the yaml\n # schema allow for specifying completers currently.\n self.completer = completer\n self.completion_request_params = completion_request_params\n self.completion_id_field = completion_id_field\n self.value_type = value_type or six.text_type\n self.parameter_name = parameter_name","def get_default_value(self, tag, primitive_type, hint=None):\n # initialize\n default_value = self.get_default_value_of_type(primitive_type)\n\n # use example value as default (if exist)\n if self.use_examples_for_default and self.get_examples_values:\n examples_values = self.get_examples_values(tag)\n if examples_values:\n default_value = list(examples_values)[0]\n\n # use response value as default (if exist)\n if self.use_response_for_default and self.get_response_values:\n response_values = self.get_response_values(tag, hint)\n if response_values:\n default_value = response_values[0]\n\n return default_value","def make_tag(tag_name, text='', tag_attr=None):\n if tag_attr is None:\n tag_attr = {}\n\n doc = xml.dom.minidom.Document()\n element = doc.createElement(tag_name)\n if tag_attr:\n for k, v in izip(list(tag_attr.keys()), list(tag_attr.values())):\n element.setAttribute(unicode(k), unicode(v))\n if text:\n text_node = doc.createTextNode(text.strip())\n element.appendChild(text_node)\n return element","def create_or_get_tag(self, tag_name: str, *args, **kwargs):\n\n tag_data = api.create_or_get_tag(\n tag_name,\n *args,\n api_key=self.__creds.api_key_v2, \n **kwargs)\n return en.Tag(tag_data)","def _default(self, section, option, default):\r\n if not self.has_section(section):\r\n self.add_section(section)\r\n if not self.has_option(section, option):\r\n self.set(section, option, default)\r\n self.save()","def default(default_value, force=False):\n def default_setter(value):\n \"\"\"\n Sets the value to the given default value, assuming the original value\n is not set or the default value is set to forced.\n\n :param Any value: Injected by CKAN core\n :rtype: Any\n \"\"\"\n return value if value and not force else default_value\n\n return default_setter","def default_value(self, value: Any) -> None:\n self.sdc_resource.set_input_default_value(self, value)\n self._default_value = value","def createElement(tag,attrib={},text={}):\n element = ET.Element(tag,attrib)\n element.text = text\n return element","def setdefault(self, value: Any) -> None:\n self.default_factory = value \n return","def __init__(self, name, default=None, help=None):\n self._name = name.replace('-', '_')\n self._value = default\n self._default = default\n self._help = help","def validate_default_element(self, value):\n return self.validate_element(value)","def create_option(self) -> Optional[pulumi.Input[str]]:\n return pulumi.get(self, \"create_option\")","def __init__(self,\n number,\n required=False,\n repeated=False,\n variant=None,\n default=None):\n if not isinstance(number, int) or not 1 <= number <= constants.MAX_FIELD_NUMBER:\n raise InvalidNumberError('Invalid number for field: %s'\n '\\nNumber must be 1 or greater and %d or less' %\n (number, constants.MAX_FIELD_NUMBER))\n\n if constants.FIRST_RESERVED_FIELD_NUMBER <= number <= constants.LAST_RESERVED_FIELD_NUMBER:\n raise InvalidNumberError('Tag number %d is a reserved number.\\n'\n 'Numbers %d to %d are reserved' %\n (number, constants.FIRST_RESERVED_FIELD_NUMBER,\n constants.LAST_RESERVED_FIELD_NUMBER))\n\n if repeated and required:\n raise FieldDefinitionError('Cannot set both repeated and required')\n\n if variant is None:\n variant = self.DEFAULT_VARIANT\n\n if repeated and default is not None:\n raise FieldDefinitionError('Repeated fields may not have defaults')\n\n if variant not in self.VARIANTS:\n raise InvalidVariantError('Invalid variant: %s\\n'\n 'Valid variants for %s are %r' %\n (variant, type(self).__name__, sorted(self.VARIANTS)))\n\n self.number = number\n self.required = required\n self.repeated = repeated\n self.variant = variant\n\n if default is not None:\n try:\n self.validate_default(default)\n except ValidationError as err:\n try:\n name = self.name\n except AttributeError:\n # For when raising error before name initialization.\n raise InvalidDefaultError('Invalid default value for %s: %r: %s' %\n (self.__class__.__name__, default, err))\n else:\n raise InvalidDefaultError('Invalid default value for field %s:'\n '%r: %s' % (name, default, err))\n\n self.__default = default\n\n if not issubclass(self.__class__, ExpandedField):\n self.__initialized = True","def BoostDesc_create(desc=None, use_scale_orientation=None, scale_factor=None): # real signature unknown; restored from __doc__\n pass","def AddDefaultTags(resource_id, region):\n tags = {'owner': FLAGS.owner, 'perfkitbenchmarker-run': FLAGS.run_uri}\n AddTags(resource_id, region, **tags)","def setdefault(self, value: Any) -> None: # type: ignore\n self.default_factory = value \n return","def _create_option(\n key: str,\n description: Optional[str] = None,\n default_val: Optional[Any] = None,\n scriptable: bool = False,\n visibility: str = \"visible\",\n deprecated: bool = False,\n deprecation_text: Optional[str] = None,\n expiration_date: Optional[str] = None,\n replaced_by: Optional[str] = None,\n type_: type = str,\n sensitive: bool = False,\n) -> ConfigOption:\n option = ConfigOption(\n key,\n description=description,\n default_val=default_val,\n scriptable=scriptable,\n visibility=visibility,\n deprecated=deprecated,\n deprecation_text=deprecation_text,\n expiration_date=expiration_date,\n replaced_by=replaced_by,\n type_=type_,\n sensitive=sensitive,\n )\n assert (\n option.section in _section_descriptions\n ), 'Section \"%s\" must be one of %s.' % (\n option.section,\n \", \".join(_section_descriptions.keys()),\n )\n assert key not in _config_options_template, 'Cannot define option \"%s\" twice.' % key\n _config_options_template[key] = option\n return option","def test_with_default() -> None:\n soup = generate_case(\"with_default\")\n\n tests.html_schema_doc_asserts.assert_default_values(soup, ['\"Linux\"', '[\"white\", \"blue\"]', \"2\"])","def __init__(self,\n number,\n required=False,\n repeated=False,\n variant=None,\n default=None):\n if not isinstance(number, int) or not 1 <= number <= MAX_FIELD_NUMBER:\n raise InvalidNumberError(\n 'Invalid number for field: %s\\n'\n 'Number must be 1 or greater and %d or less' %\n (number, MAX_FIELD_NUMBER))\n\n if FIRST_RESERVED_FIELD_NUMBER <= number <= LAST_RESERVED_FIELD_NUMBER:\n raise InvalidNumberError('Tag number %d is a reserved number.\\n'\n 'Numbers %d to %d are reserved' %\n (number, FIRST_RESERVED_FIELD_NUMBER,\n LAST_RESERVED_FIELD_NUMBER))\n\n if repeated and required:\n raise FieldDefinitionError('Cannot set both repeated and required')\n\n if variant is None:\n variant = self.DEFAULT_VARIANT\n\n if repeated and default is not None:\n raise FieldDefinitionError('Repeated fields may not have defaults')\n\n if variant not in self.VARIANTS:\n raise InvalidVariantError(\n 'Invalid variant: %s\\nValid variants for %s are %r' %\n (variant, type(self).__name__, sorted(self.VARIANTS)))\n\n self.number = number\n self.required = required\n self.repeated = repeated\n self.variant = variant\n\n if default is not None:\n try:\n self.validate_default(default)\n except ValidationError as err:\n try:\n name = self.name\n except AttributeError:\n # For when raising error before name initialization.\n raise InvalidDefaultError(\n 'Invalid default value for %s: %r: %s' %\n (self.__class__.__name__, default, err))\n else:\n raise InvalidDefaultError(\n 'Invalid default value for field %s: '\n '%r: %s' % (name, default, err))\n\n self.__default = default\n self.__initialized = True","def __init__(self, name, values=None, exclusive=False, default=None):\n super(BooleanAttributeSchema, self).__init__(\n name, exclusive=exclusive, default=default\n )\n self.values = set(values or [])\n self.validate_default_value()","def _update_annotation_with_default(anno, name, default):\n # Create instance if is type class\n complete_annotation = anno\n if _is_dsl_type_cls(anno):\n complete_annotation = anno()\n complete_annotation.name = name\n if default is Input._EMPTY:\n return complete_annotation\n if isinstance(complete_annotation, Input):\n # Non-parameter Input has no default attribute\n if complete_annotation._is_parameter_type and complete_annotation.default is not None:\n # logger.warning(\n # f\"Warning: Default value of f{complete_annotation.name!r} is set twice: \"\n # f\"{complete_annotation.default!r} and {default!r}, will use {default!r}\"\n # )\n pass\n complete_annotation._update_default(default)\n return complete_annotation","def create(self, name, tag):\n\n\t\turl_json = urllib.urlencode({\"name\": name, \"tag\": tag})\n\t\treturn self._create(\"/tag?json_hash=%s\" % url_json, \"tag\")","def create_default(cls):\n raise NotImplementedError(common.OVERRIDE_MESSAGE)","def register_tag(name: str, config: Dict[str, Any], override: bool = False) -> Optional[Target]:\n if hasattr(_ffi_api, \"TargetTagAddTag\"):\n return _ffi_api.TargetTagAddTag(name, config, override)\n return None","def add_parameter(self, paramId, dataType, default, valRange=None, label=\"Parameter\"):\n self.inputs[paramId] = {\n 'label': label,\n 'entry': None,\n 'value': None,\n 'valRange': valRange,\n 'dataType': dataType,\n 'default': default\n }","def _create_element(tag, text=\"\", attr={}, namespace=Xmlns_path):\n element = Et.Element('.//' + namespace + tag, attr)\n element.text = text\n return element","def default(self, default):\n\n self._set_field(\"value\", default)","def default_spec(\n tag_or_pred: Union[Tag, SpecPredicate],\n *preds: SpecPredicate,\n default: Any = None,\n conformer: Optional[Conformer] = None,\n) -> Spec:\n tag, preds = tag_maybe(tag_or_pred, *preds)\n\n if len(preds) != 1:\n raise ValueError(\"Must provide exactly one Spec predicate for 'default' Specs\")\n\n return any_spec(\n tag or \"default\",\n preds[0],\n every_spec(conformer=lambda _: default),\n conformer=conformer,\n )","def validate_default(self, value):\n return self.__validate(value, self.validate_default_element)","def create_input_element(self, **kwargs):\r\n return None","def help_default_values():\n click.echo_via_pager(docgen.generate_default_value_help())","def createTagValue(creatorID, tagID, objectID, value):\n store = getMainStore()\n return store.add(TagValue(creatorID, tagID, objectID, value))","def BoolVariable(key, help, default):\n return (key, '%s (yes|no)' % help, default,\n _validator, _text2bool)","def set_default(self, default):\n\n\t\tif default is not None and not isinstance(default, bool):\n\t\t\traise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: default EXPECTED TYPE: bool', None, None)\n\t\t\n\t\tself.__default = default\n\t\tself.__key_modified['default'] = 1","def validate_default_value(self):\n if self.has_default_value:\n if not self.is_valid_value(self.default):\n raise AttributeSchemaError(\n \"Default value '%s' is not compliant with the schema\"\n )","def parameter(self, name, doc, default = None):\n self._parameters.append((name, doc.strip(), default))\n return self","def __init__(\n self,\n *,\n type: str = \"boolean\",\n default: bool = None,\n optional: bool = None,\n description: str = None,\n **kwargs,\n ):\n pass","def test_alright_when_required_field_is_missing_but_default_is_given():\n\n model_definition = {'language': {'type': 'fixed',\n 'required': True,\n 'persisted': True,\n 'default': 'portuguese'},\n 'source': {'type': 'list',\n 'required': False,\n 'persisted': True}}\n product1 = {'source': ['Whatever']}\n factory = ProductModelFactory(model_definition)\n factory.build('product1', product1)\n # Ok. No exceptions were raised.","def _update_annotation_with_default(\n anno: Union[Annotation, Input, Output], name: str, default: Any\n ) -> Union[Annotation, Input, Output]:\n # Create instance if is type class\n complete_annotation = anno\n if _is_dsl_type_cls(anno):\n complete_annotation = anno()\n complete_annotation._port_name = name\n if default is Input._EMPTY:\n return complete_annotation\n if isinstance(complete_annotation, Input):\n # Non-parameter Input has no default attribute\n if complete_annotation._is_primitive_type and complete_annotation.default is not None:\n # logger.warning(\n # f\"Warning: Default value of f{complete_annotation.name!r} is set twice: \"\n # f\"{complete_annotation.default!r} and {default!r}, will use {default!r}\"\n # )\n pass\n complete_annotation._update_default(default)\n if isinstance(complete_annotation, Output) and default is not None:\n msg = (\n f\"Default value of Output {complete_annotation._port_name!r} cannot be set:\"\n f\"Output has no default value.\"\n )\n raise UserErrorException(msg)\n return complete_annotation","def addElement(name, defaultUri=None, content=None):","def for_tag(self, tag):\n if not isinstance(tag, str):\n raise TypeError('Tag must be a string')\n\n self.token['requiredTag'] = tag\n\n return self","def _defaulted(cls, value, default):\n return default if value is None else value","def setdefault(self, k, d=None): # real signature unknown; restored from __doc__\n pass","def __init__(\n self,\n *,\n name: str,\n label: str,\n optional: bool = False,\n value: str = None,\n placeholder: str = None,\n ):\n super().__init__(\n name=name,\n label=label,\n optional=optional,\n value=value,\n placeholder=placeholder,\n )","def __init__(\n self,\n *,\n name: str,\n label: str,\n optional: bool = False,\n value: str = None,\n placeholder: str = None,\n ):\n super().__init__(\n name=name,\n label=label,\n optional=optional,\n value=value,\n placeholder=placeholder,\n )","def __init__(\n self,\n *,\n name: str,\n label: str,\n optional: bool = False,\n value: str = None,\n placeholder: str = None,\n ):\n super().__init__(\n name=name,\n label=label,\n optional=optional,\n value=value,\n placeholder=placeholder,\n )","def is_default(self):\n return self._tag == 'default'","def __init__(self, concept_ref='', value=''):\n self.concept_ref = concept_ref\n self.value = value","def __init__(__self__, *,\n default_resource_request: Optional[str] = None,\n vault_critical_operation: Optional[str] = None):\n if default_resource_request is not None:\n pulumi.set(__self__, \"default_resource_request\", default_resource_request)\n if vault_critical_operation is not None:\n pulumi.set(__self__, \"vault_critical_operation\", vault_critical_operation)","def default(self, value):\n # save {value} as the default\n self._default = value\n # all done\n return","def __init__(self, attr=None, default=None, help_text=None):\r\n\r\n self._attribute = attr\r\n self._field_name = None\r\n self._default = default\r\n\r\n if help_text:\r\n self.help_text = help_text","def create_option(self, label, value=None):\n option = Option(label, value)\n self.append(option)\n return option","def test_add_defined_tag_to_bucket(self, test, object_storage, with_or_without_compartment):\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\n session_factory = test.oci_session_factory()\n policy = test.load_policy(\n {\n \"name\": \"add-defined-tag-to-bucket\",\n \"resource\": \"oci.bucket\",\n \"query\": [\n {\"namespace_name\": namespace_name},\n ],\n \"filters\": [\n {\"type\": \"value\", \"key\": \"name\", \"value\": bucket_name},\n ],\n \"actions\": [{\"type\": \"update\", \"defined_tags\": self.get_defined_tag(\"add_tag\")}],\n },\n session_factory=session_factory,\n )\n policy.run()\n resource = self._fetch_bucket_validation_data(\n policy.resource_manager, namespace_name, bucket_name\n )\n test.assertEqual(resource[\"name\"], bucket_name)\n test.assertEqual(self.get_defined_tag_value(resource[\"defined_tags\"]), \"true\")","def create_option(self) -> Optional[pulumi.Input[Union[str, 'OsDiskCreateOption']]]:\n return pulumi.get(self, \"create_option\")","def __init__(self, definition=None, do_validate=False):\n\n if not definition:\n definition = {}\n self._definition = definition\n\n if 'version' not in self._definition:\n self._definition['version'] = DEFAULT_VERSION\n\n if self._definition['version'] != DEFAULT_VERSION:\n msg = '%s is an unsupported version number'\n raise InvalidDefinition('INVALID_DEFINITION', msg % self._definition['version'])\n\n self._populate_default_values()\n\n try:\n if do_validate:\n validate(definition, RECIPE_DEFINITION_SCHEMA)\n except ValidationError as ex:\n raise InvalidDefinition('INVALID_DEFINITION', 'Invalid recipe definition: %s' % unicode(ex))","def create_type(name, description, metadata, force):\n type_ = orm.DataFlagType()\n\n type_.name = name\n type_.description = description\n type_.metadata = metadata\n\n if force:\n type_.save()\n else:\n click.echo(\"Type to create:\\n\")\n click.echo(format_type(type_))\n if click.confirm(\"Create type?\"):\n type_.save()\n click.echo(\"Success.\")\n else:\n click.echo(\"Aborted.\")","def get_tag_default(self, tag_default_id, **kwargs):\n resource_path = \"/tagDefaults/{tagDefaultId}\"\n method = \"GET\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"get_tag_default got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagDefaultId\": tag_default_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"TagDefault\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n response_type=\"TagDefault\")","def getDefault():","def new(cls, default=None):\n return cls(default=default)","def __init__(__self__, *,\n name: Optional[str] = None,\n value: Optional[str] = None):\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if value is not None:\n pulumi.set(__self__, \"value\", value)","def __init__(__self__, *,\n name: Optional[str] = None,\n value: Optional[str] = None):\n if name is not None:\n pulumi.set(__self__, \"name\", name)\n if value is not None:\n pulumi.set(__self__, \"value\", value)","def __init__(self, tagged_sents, default_tag='nc0s000'):\n self._default_tag = default_tag","def create_tag(create_timestamps):\n ctx = dash.callback_context\n triggered_id, triggered_prop, triggered_value = utils.ctx_triggered_info(ctx)\n\n # When the button is initially added, it fires a callback.\n # We want to prevent this callback from making changes to the update signal.\n if triggered_value is None:\n raise PreventUpdate\n\n state.create_tag(\"\")\n return constants.OK_SIGNAL","def test_default_creation_2():\n actual = os.path.join('.', 'test_files', 'rc_test_default.input')\n times = list(range(0, 30, 5))\n params = {\"names\": ['V'],\n \"values\": [\n [1],\n [0],\n [-1],\n [0],\n [1]\n ]\n }\n input_creator = InputCreator(None, times, params)\n f_out = input_creator.default_creation_2()\n with open(actual) as f_actual:\n actual_content = f_actual.read()\n\n content = f_out.getvalue()\n\n assert_equal(content, actual_content)","def __init__(__self__, *,\n default_resource_request: Optional[pulumi.Input[str]] = None,\n vault_critical_operation: Optional[pulumi.Input[str]] = None):\n if default_resource_request is not None:\n pulumi.set(__self__, \"default_resource_request\", default_resource_request)\n if vault_critical_operation is not None:\n pulumi.set(__self__, \"vault_critical_operation\", vault_critical_operation)","def register_def(self, name, default, def_text):\n\n _type = self.type_by_name[name]\n _type.name = name\n _def = _type.register_def_raw(default, def_text)\n self.def_by_hash[_def.hash] = _def\n return _def","def tag(\n name: str, value: str, *, attributes: dict = {}, namespace: str = None\n ) -> str:\n attributes_str = \" \".join(f'{k}=\"{v}\"' for k, v in attributes.items())\n ns = f\"{namespace}:\" if namespace else \"\"\n if attributes_str:\n attributes_str = \" \" + attributes_str\n if value:\n return f\"<{ns}{name}{attributes_str}>{value}\"\n return f\"<{ns}{name}{attributes_str} />\"","def create_default_network(context):\n return [{\n 'type': 'templates/network.py',\n 'name': 'fc-network',\n 'properties': {\n 'resourceName': 'network',\n 'name': 'network',\n 'projectId': '$(ref.fc-project.projectId)',\n 'autoCreateSubnetworks': True,\n # We pass the dependsOn list into the network template as a\n # parameter. Deployment Manager doesn't support dependsOn for\n # template-call nodes, so we can't have this resource itself depend on\n # the project-wide resources.\n 'dependsOn': '$(ref.fc-project.resourceNames)',\n },\n }]","def create_tag(self, entry_name, tag):\n return self.__datacatalog.create_tag(parent=entry_name, tag=tag)","def f_default(self, default = 1) :\n pass","def default():","def make_new_tag(tag_name, user_path, user_signed_in, current_user):\n if not user_signed_in:\n print('ALERT: -- User not logged in --')\n else:\n user = current_user[0]\n print(is_tag(tag_name, user_path, current_user))\n if is_tag(tag_name, user_path, current_user):\n print('Tag already exist')\n else:\n os.mkdir((user_path + '\\\\' + user + '\\\\' + tag_name).encode('unicode_escape'))\n print('Tag --' + tag_name + '-- Created')","def add_tag(self, obj, tag_name):\r\n tag_names = parse_tag_input(tag_name)\r\n if not len(tag_names):\r\n raise AttributeError(_('No tags were given: \"%s\".') % tag_name)\r\n if len(tag_names) > 1:\r\n raise AttributeError(_('Multiple tags were given: \"%s\".') % tag_name)\r\n tag_name = tag_names[0]\r\n if settings.FORCE_LOWERCASE_TAGS:\r\n tag_name = tag_name.lower()\r\n tag, created = self.get_or_create(name=tag_name)\r\n ctype = ContentType.objects.get_for_model(obj)\r\n TaggedItem._default_manager.get_or_create(\r\n tag=tag, content_type=ctype, object_id=obj.pk)","def group(cls: type[T], optional: bool = False) -> T:\n default = None if optional else RAISE\n return attr.ib(\n default=default,\n metadata={CNF_KEY: _ConfigEntry(None, default, cls, True)},\n )","def test_no_default_value(self):\n dim = Real(\"yolo\", \"uniform\", -3, 4)\n assert dim.default_value is None","def test_no_default_value(self):\n dim = Dimension(\"yolo\", \"uniform\", -3, 4)\n assert dim.default_value is None","def pre_config_node_create(self, resource_dict):\n pass","def test_config_option_required_default():\n class Config(config.Config):\n a = config.option(int, required=True, default=12, help=\"\")\n\n c = config.structure({}, Config)\n assert c.a == 12\n\n c = config.structure({\"a\": 23}, Config)\n assert c.a == 23\n\n with pytest.raises(config.ConfigError):\n config.structure({\"a\": None}, Config)","def _ValueOrPlaceHolder(value_string, description):\n value_element = xml.etree.ElementTree.Element('value')\n value_element.set('xml:lang', _VALUE_LANGUAGE)\n\n if value_string:\n value_element.text = value_string\n else:\n value_element.text = '** INSERT %s **' % description\n\n return value_element"],"string":"[\n \"def Option(name: str, value: Union[str, int], default: Optional[bool] = None) -> Dict:\\n doc = {'name': name, 'value': value}\\n if default is not None:\\n doc['isDefault'] = default\\n return doc\",\n \"def register_option_pair(key, default_value):\\n\\n _OPTION_TEMPLATE[key] = default_value\",\n \"def createDevIDAttr(shapefileName, defaultVal):\\n\\n inputds = ogr.Open(shapefileName,update=True)\\n if not inputds:\\n sys.exit(\\\"Unable to open input file '{0}'\\\".format(shapefileName))\\n\\n inputlyr = inputds.GetLayer()\\n\\n # Create field definition(s)\\n # Add input Layer Fields to the output Layer if defined in field_names arg.\\n inLayerDefn = inputlyr.GetLayerDefn()\\n if inLayerDefn.GetFieldIndex(cc.DEV_LAYER_ATTRIBUTE_NAME) == -1:\\n print(\\\"\\\\tCreating an Attribute '{0}' in vector file '{1}'\\\".format(cc.DEV_LAYER_ATTRIBUTE_NAME,shapefileName))\\n\\n inputlyr.CreateField(ogr.FieldDefn(cc.DEV_LAYER_ATTRIBUTE_NAME, ogr.OFTInteger))\\n\\n for inFeature in inputlyr:\\n inFeature.SetField(cc.DEV_LAYER_ATTRIBUTE_NAME,defaultVal)\\n inputlyr.SetFeature(inFeature)\\n\\n inputds.Destroy()\\n print(\\\"\\\\tCreated an Attribute '{0}' in vector file '{1}'\\\".format(cc.DEV_LAYER_ATTRIBUTE_NAME,shapefileName))\",\n \"def update_tag_default(self, tag_default_id, update_tag_default_details, **kwargs):\\n resource_path = \\\"/tagDefaults/{tagDefaultId}\\\"\\n method = \\\"PUT\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"if_match\\\",\\n \\\"opc_request_id\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"update_tag_default got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tagDefaultId\\\": tag_default_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"if-match\\\": kwargs.get(\\\"if_match\\\", missing),\\n \\\"opc-request-id\\\": kwargs.get(\\\"opc_request_id\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_tag_default_details,\\n response_type=\\\"TagDefault\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n body=update_tag_default_details,\\n response_type=\\\"TagDefault\\\")\",\n \"def _add_default_tags(self):\\n self.tags.add_tag('ban', required=True)\",\n \"def create_object_parameter_from_default(obj, default):\\n values = []\\n if default.enum:\\n for v in DefaultParameterVl.objects.filter(parameter=default).all():\\n values.append({'value' : v.value,\\n 'caption' : v.caption})\\n return create_object_parameter(obj, 'user', False,\\n tp = default.tp,\\n name=default.name,\\n descr=default.descr,\\n values=values)\",\n \"def __init__(self, default_value, description, register=None, name=None,\\n is_key=False, **kwargs):\\n self._default_value = default_value\\n self._description = description\\n self._register = register\\n self._name = name\\n self._is_key = is_key\\n self._kwargs = kwargs\\n\\n self._value = default_value\\n self._frozen = False\",\n \"def set_default(self, name, default, group=None):\\n opt_info = self._get_opt_info(name, group)\\n opt_info['default'] = self._get_enforced_type_value(\\n opt_info['opt'], default)\\n opt_info['location'] = LocationInfo(\\n Locations.set_default,\\n _get_caller_detail(3), # this function has a decorator to skip\\n )\",\n \"def _create_tag_request():\\n\\n key = helpers.get('Tag.1.Key')\\n value = helpers.get('Tag.1.Value')\\n resource_id = helpers.get('ResourceId.1')\\n\\n if resource_id in current_app.config['RESOURCE_TYPE_MAP']:\\n resource_type = current_app.config['RESOURCE_TYPE_MAP'][resource_id]\\n else:\\n errors.invalid_request(\\n str(resource_id) + \\\" not found in configuration\\\")\\n\\n args = {\\n 'command': 'createTags',\\n 'resourceids': resource_id,\\n 'resourcetype': resource_type,\\n 'tags[0].key': key,\\n 'tags[0].value': value\\n }\\n\\n response = requester.make_request_async(args)\\n\\n return response\",\n \"def addDefault(self, name, object):\\n if name is None:\\n raise ValueError(\\\"Name cannot be None\\\")\\n self.defaultChoice = name\\n self.addObject(name, object)\",\n \"def __init__(self, name=None, values=None, default_value=None):\\n self.swagger_types = {\\n 'name': 'str',\\n 'values': 'list[TagPropertyAllowedValue]',\\n 'default_value': 'str'\\n }\\n\\n self.attribute_map = {\\n 'name': 'name',\\n 'values': 'values',\\n 'default_value': 'defaultValue'\\n }\\n\\n self._name = name\\n self._values = values\\n self._default_value = default_value\",\n \"def var(\\n default: Any = RAISE,\\n converter: Callable | None = None,\\n name: str | None = None,\\n validator: Callable | None = None,\\n help: str | None = None,\\n) -> Any:\\n return attr.ib(\\n default=default,\\n metadata={CNF_KEY: _ConfigEntry(name, default, None, None, help)},\\n converter=converter,\\n validator=validator,\\n )\",\n \"def create(self, name, description=None, color=None):\\n data = {\\n 'name': name,\\n 'title': name,\\n 'description': description or name,\\n 'appearance': {\\n 'color': color or random_color()\\n }\\n }\\n # Yes, it's confusing. the `/tags/` endpoint is used for labels\\n return self._post(\\n request=ApiActions.CREATE.value,\\n uri=ApiUri.TAGS.value,\\n params=data\\n )\",\n \"def validate_default_element(self, value):\\n return self.validate_element(value)\",\n \"def validate_default(self, value):\\n return self.__validate(value, self.validate_default_element)\",\n \"def test_string_default(self):\\n tag = Tag()\\n self.assertEqual(tag.value, 'default')\",\n \"def delete_tag_default(self, tag_default_id, **kwargs):\\n resource_path = \\\"/tagDefaults/{tagDefaultId}\\\"\\n method = \\\"DELETE\\\"\\n\\n # Don't accept unknown kwargs\\n expected_kwargs = [\\n \\\"retry_strategy\\\",\\n \\\"opc_request_id\\\",\\n \\\"if_match\\\"\\n ]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"delete_tag_default got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tagDefaultId\\\": tag_default_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\",\\n \\\"opc-request-id\\\": kwargs.get(\\\"opc_request_id\\\", missing),\\n \\\"if-match\\\": kwargs.get(\\\"if_match\\\", missing)\\n }\\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params)\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params)\",\n \"def default_arg(default):\\n class DefaultArg(argparse.Action):\\n def __call__(self, parser, namespace, value, option_string):\\n if value is None:\\n setattr(namespace, self.dest, default)\\n else:\\n setattr(namespace, self.dest, value)\\n\\n return DefaultArg\",\n \"def _set_default(name, value, context):\\n if name not in context:\\n context[name] = value\",\n \"def __init__(self, name=None, value=None):\\n default_attr = dict(name=str(),\\n value=str())\\n self.name = name\\n self.value = value\\n self._set_default_attr(default_attr)\",\n \"def createTag(self, authenticationToken, tag):\\r\\n pass\",\n \"def __init__(self,\\n name=None,\\n help_text=None,\\n fallthroughs=None,\\n completer=None,\\n completion_request_params=None,\\n completion_id_field=None,\\n value_type=None,\\n parameter_name=None):\\n self.attribute_name = name\\n self.help_text = help_text\\n self.fallthroughs = fallthroughs or []\\n # The completer is always None because neither the surface nor the yaml\\n # schema allow for specifying completers currently.\\n self.completer = completer\\n self.completion_request_params = completion_request_params\\n self.completion_id_field = completion_id_field\\n self.value_type = value_type or six.text_type\\n self.parameter_name = parameter_name\",\n \"def get_default_value(self, tag, primitive_type, hint=None):\\n # initialize\\n default_value = self.get_default_value_of_type(primitive_type)\\n\\n # use example value as default (if exist)\\n if self.use_examples_for_default and self.get_examples_values:\\n examples_values = self.get_examples_values(tag)\\n if examples_values:\\n default_value = list(examples_values)[0]\\n\\n # use response value as default (if exist)\\n if self.use_response_for_default and self.get_response_values:\\n response_values = self.get_response_values(tag, hint)\\n if response_values:\\n default_value = response_values[0]\\n\\n return default_value\",\n \"def make_tag(tag_name, text='', tag_attr=None):\\n if tag_attr is None:\\n tag_attr = {}\\n\\n doc = xml.dom.minidom.Document()\\n element = doc.createElement(tag_name)\\n if tag_attr:\\n for k, v in izip(list(tag_attr.keys()), list(tag_attr.values())):\\n element.setAttribute(unicode(k), unicode(v))\\n if text:\\n text_node = doc.createTextNode(text.strip())\\n element.appendChild(text_node)\\n return element\",\n \"def create_or_get_tag(self, tag_name: str, *args, **kwargs):\\n\\n tag_data = api.create_or_get_tag(\\n tag_name,\\n *args,\\n api_key=self.__creds.api_key_v2, \\n **kwargs)\\n return en.Tag(tag_data)\",\n \"def _default(self, section, option, default):\\r\\n if not self.has_section(section):\\r\\n self.add_section(section)\\r\\n if not self.has_option(section, option):\\r\\n self.set(section, option, default)\\r\\n self.save()\",\n \"def default(default_value, force=False):\\n def default_setter(value):\\n \\\"\\\"\\\"\\n Sets the value to the given default value, assuming the original value\\n is not set or the default value is set to forced.\\n\\n :param Any value: Injected by CKAN core\\n :rtype: Any\\n \\\"\\\"\\\"\\n return value if value and not force else default_value\\n\\n return default_setter\",\n \"def default_value(self, value: Any) -> None:\\n self.sdc_resource.set_input_default_value(self, value)\\n self._default_value = value\",\n \"def createElement(tag,attrib={},text={}):\\n element = ET.Element(tag,attrib)\\n element.text = text\\n return element\",\n \"def setdefault(self, value: Any) -> None:\\n self.default_factory = value \\n return\",\n \"def __init__(self, name, default=None, help=None):\\n self._name = name.replace('-', '_')\\n self._value = default\\n self._default = default\\n self._help = help\",\n \"def validate_default_element(self, value):\\n return self.validate_element(value)\",\n \"def create_option(self) -> Optional[pulumi.Input[str]]:\\n return pulumi.get(self, \\\"create_option\\\")\",\n \"def __init__(self,\\n number,\\n required=False,\\n repeated=False,\\n variant=None,\\n default=None):\\n if not isinstance(number, int) or not 1 <= number <= constants.MAX_FIELD_NUMBER:\\n raise InvalidNumberError('Invalid number for field: %s'\\n '\\\\nNumber must be 1 or greater and %d or less' %\\n (number, constants.MAX_FIELD_NUMBER))\\n\\n if constants.FIRST_RESERVED_FIELD_NUMBER <= number <= constants.LAST_RESERVED_FIELD_NUMBER:\\n raise InvalidNumberError('Tag number %d is a reserved number.\\\\n'\\n 'Numbers %d to %d are reserved' %\\n (number, constants.FIRST_RESERVED_FIELD_NUMBER,\\n constants.LAST_RESERVED_FIELD_NUMBER))\\n\\n if repeated and required:\\n raise FieldDefinitionError('Cannot set both repeated and required')\\n\\n if variant is None:\\n variant = self.DEFAULT_VARIANT\\n\\n if repeated and default is not None:\\n raise FieldDefinitionError('Repeated fields may not have defaults')\\n\\n if variant not in self.VARIANTS:\\n raise InvalidVariantError('Invalid variant: %s\\\\n'\\n 'Valid variants for %s are %r' %\\n (variant, type(self).__name__, sorted(self.VARIANTS)))\\n\\n self.number = number\\n self.required = required\\n self.repeated = repeated\\n self.variant = variant\\n\\n if default is not None:\\n try:\\n self.validate_default(default)\\n except ValidationError as err:\\n try:\\n name = self.name\\n except AttributeError:\\n # For when raising error before name initialization.\\n raise InvalidDefaultError('Invalid default value for %s: %r: %s' %\\n (self.__class__.__name__, default, err))\\n else:\\n raise InvalidDefaultError('Invalid default value for field %s:'\\n '%r: %s' % (name, default, err))\\n\\n self.__default = default\\n\\n if not issubclass(self.__class__, ExpandedField):\\n self.__initialized = True\",\n \"def BoostDesc_create(desc=None, use_scale_orientation=None, scale_factor=None): # real signature unknown; restored from __doc__\\n pass\",\n \"def AddDefaultTags(resource_id, region):\\n tags = {'owner': FLAGS.owner, 'perfkitbenchmarker-run': FLAGS.run_uri}\\n AddTags(resource_id, region, **tags)\",\n \"def setdefault(self, value: Any) -> None: # type: ignore\\n self.default_factory = value \\n return\",\n \"def _create_option(\\n key: str,\\n description: Optional[str] = None,\\n default_val: Optional[Any] = None,\\n scriptable: bool = False,\\n visibility: str = \\\"visible\\\",\\n deprecated: bool = False,\\n deprecation_text: Optional[str] = None,\\n expiration_date: Optional[str] = None,\\n replaced_by: Optional[str] = None,\\n type_: type = str,\\n sensitive: bool = False,\\n) -> ConfigOption:\\n option = ConfigOption(\\n key,\\n description=description,\\n default_val=default_val,\\n scriptable=scriptable,\\n visibility=visibility,\\n deprecated=deprecated,\\n deprecation_text=deprecation_text,\\n expiration_date=expiration_date,\\n replaced_by=replaced_by,\\n type_=type_,\\n sensitive=sensitive,\\n )\\n assert (\\n option.section in _section_descriptions\\n ), 'Section \\\"%s\\\" must be one of %s.' % (\\n option.section,\\n \\\", \\\".join(_section_descriptions.keys()),\\n )\\n assert key not in _config_options_template, 'Cannot define option \\\"%s\\\" twice.' % key\\n _config_options_template[key] = option\\n return option\",\n \"def test_with_default() -> None:\\n soup = generate_case(\\\"with_default\\\")\\n\\n tests.html_schema_doc_asserts.assert_default_values(soup, ['\\\"Linux\\\"', '[\\\"white\\\", \\\"blue\\\"]', \\\"2\\\"])\",\n \"def __init__(self,\\n number,\\n required=False,\\n repeated=False,\\n variant=None,\\n default=None):\\n if not isinstance(number, int) or not 1 <= number <= MAX_FIELD_NUMBER:\\n raise InvalidNumberError(\\n 'Invalid number for field: %s\\\\n'\\n 'Number must be 1 or greater and %d or less' %\\n (number, MAX_FIELD_NUMBER))\\n\\n if FIRST_RESERVED_FIELD_NUMBER <= number <= LAST_RESERVED_FIELD_NUMBER:\\n raise InvalidNumberError('Tag number %d is a reserved number.\\\\n'\\n 'Numbers %d to %d are reserved' %\\n (number, FIRST_RESERVED_FIELD_NUMBER,\\n LAST_RESERVED_FIELD_NUMBER))\\n\\n if repeated and required:\\n raise FieldDefinitionError('Cannot set both repeated and required')\\n\\n if variant is None:\\n variant = self.DEFAULT_VARIANT\\n\\n if repeated and default is not None:\\n raise FieldDefinitionError('Repeated fields may not have defaults')\\n\\n if variant not in self.VARIANTS:\\n raise InvalidVariantError(\\n 'Invalid variant: %s\\\\nValid variants for %s are %r' %\\n (variant, type(self).__name__, sorted(self.VARIANTS)))\\n\\n self.number = number\\n self.required = required\\n self.repeated = repeated\\n self.variant = variant\\n\\n if default is not None:\\n try:\\n self.validate_default(default)\\n except ValidationError as err:\\n try:\\n name = self.name\\n except AttributeError:\\n # For when raising error before name initialization.\\n raise InvalidDefaultError(\\n 'Invalid default value for %s: %r: %s' %\\n (self.__class__.__name__, default, err))\\n else:\\n raise InvalidDefaultError(\\n 'Invalid default value for field %s: '\\n '%r: %s' % (name, default, err))\\n\\n self.__default = default\\n self.__initialized = True\",\n \"def __init__(self, name, values=None, exclusive=False, default=None):\\n super(BooleanAttributeSchema, self).__init__(\\n name, exclusive=exclusive, default=default\\n )\\n self.values = set(values or [])\\n self.validate_default_value()\",\n \"def _update_annotation_with_default(anno, name, default):\\n # Create instance if is type class\\n complete_annotation = anno\\n if _is_dsl_type_cls(anno):\\n complete_annotation = anno()\\n complete_annotation.name = name\\n if default is Input._EMPTY:\\n return complete_annotation\\n if isinstance(complete_annotation, Input):\\n # Non-parameter Input has no default attribute\\n if complete_annotation._is_parameter_type and complete_annotation.default is not None:\\n # logger.warning(\\n # f\\\"Warning: Default value of f{complete_annotation.name!r} is set twice: \\\"\\n # f\\\"{complete_annotation.default!r} and {default!r}, will use {default!r}\\\"\\n # )\\n pass\\n complete_annotation._update_default(default)\\n return complete_annotation\",\n \"def create(self, name, tag):\\n\\n\\t\\turl_json = urllib.urlencode({\\\"name\\\": name, \\\"tag\\\": tag})\\n\\t\\treturn self._create(\\\"/tag?json_hash=%s\\\" % url_json, \\\"tag\\\")\",\n \"def create_default(cls):\\n raise NotImplementedError(common.OVERRIDE_MESSAGE)\",\n \"def register_tag(name: str, config: Dict[str, Any], override: bool = False) -> Optional[Target]:\\n if hasattr(_ffi_api, \\\"TargetTagAddTag\\\"):\\n return _ffi_api.TargetTagAddTag(name, config, override)\\n return None\",\n \"def add_parameter(self, paramId, dataType, default, valRange=None, label=\\\"Parameter\\\"):\\n self.inputs[paramId] = {\\n 'label': label,\\n 'entry': None,\\n 'value': None,\\n 'valRange': valRange,\\n 'dataType': dataType,\\n 'default': default\\n }\",\n \"def _create_element(tag, text=\\\"\\\", attr={}, namespace=Xmlns_path):\\n element = Et.Element('.//' + namespace + tag, attr)\\n element.text = text\\n return element\",\n \"def default(self, default):\\n\\n self._set_field(\\\"value\\\", default)\",\n \"def default_spec(\\n tag_or_pred: Union[Tag, SpecPredicate],\\n *preds: SpecPredicate,\\n default: Any = None,\\n conformer: Optional[Conformer] = None,\\n) -> Spec:\\n tag, preds = tag_maybe(tag_or_pred, *preds)\\n\\n if len(preds) != 1:\\n raise ValueError(\\\"Must provide exactly one Spec predicate for 'default' Specs\\\")\\n\\n return any_spec(\\n tag or \\\"default\\\",\\n preds[0],\\n every_spec(conformer=lambda _: default),\\n conformer=conformer,\\n )\",\n \"def validate_default(self, value):\\n return self.__validate(value, self.validate_default_element)\",\n \"def create_input_element(self, **kwargs):\\r\\n return None\",\n \"def help_default_values():\\n click.echo_via_pager(docgen.generate_default_value_help())\",\n \"def createTagValue(creatorID, tagID, objectID, value):\\n store = getMainStore()\\n return store.add(TagValue(creatorID, tagID, objectID, value))\",\n \"def BoolVariable(key, help, default):\\n return (key, '%s (yes|no)' % help, default,\\n _validator, _text2bool)\",\n \"def set_default(self, default):\\n\\n\\t\\tif default is not None and not isinstance(default, bool):\\n\\t\\t\\traise SDKException(Constants.DATA_TYPE_ERROR, 'KEY: default EXPECTED TYPE: bool', None, None)\\n\\t\\t\\n\\t\\tself.__default = default\\n\\t\\tself.__key_modified['default'] = 1\",\n \"def validate_default_value(self):\\n if self.has_default_value:\\n if not self.is_valid_value(self.default):\\n raise AttributeSchemaError(\\n \\\"Default value '%s' is not compliant with the schema\\\"\\n )\",\n \"def parameter(self, name, doc, default = None):\\n self._parameters.append((name, doc.strip(), default))\\n return self\",\n \"def __init__(\\n self,\\n *,\\n type: str = \\\"boolean\\\",\\n default: bool = None,\\n optional: bool = None,\\n description: str = None,\\n **kwargs,\\n ):\\n pass\",\n \"def test_alright_when_required_field_is_missing_but_default_is_given():\\n\\n model_definition = {'language': {'type': 'fixed',\\n 'required': True,\\n 'persisted': True,\\n 'default': 'portuguese'},\\n 'source': {'type': 'list',\\n 'required': False,\\n 'persisted': True}}\\n product1 = {'source': ['Whatever']}\\n factory = ProductModelFactory(model_definition)\\n factory.build('product1', product1)\\n # Ok. No exceptions were raised.\",\n \"def _update_annotation_with_default(\\n anno: Union[Annotation, Input, Output], name: str, default: Any\\n ) -> Union[Annotation, Input, Output]:\\n # Create instance if is type class\\n complete_annotation = anno\\n if _is_dsl_type_cls(anno):\\n complete_annotation = anno()\\n complete_annotation._port_name = name\\n if default is Input._EMPTY:\\n return complete_annotation\\n if isinstance(complete_annotation, Input):\\n # Non-parameter Input has no default attribute\\n if complete_annotation._is_primitive_type and complete_annotation.default is not None:\\n # logger.warning(\\n # f\\\"Warning: Default value of f{complete_annotation.name!r} is set twice: \\\"\\n # f\\\"{complete_annotation.default!r} and {default!r}, will use {default!r}\\\"\\n # )\\n pass\\n complete_annotation._update_default(default)\\n if isinstance(complete_annotation, Output) and default is not None:\\n msg = (\\n f\\\"Default value of Output {complete_annotation._port_name!r} cannot be set:\\\"\\n f\\\"Output has no default value.\\\"\\n )\\n raise UserErrorException(msg)\\n return complete_annotation\",\n \"def addElement(name, defaultUri=None, content=None):\",\n \"def for_tag(self, tag):\\n if not isinstance(tag, str):\\n raise TypeError('Tag must be a string')\\n\\n self.token['requiredTag'] = tag\\n\\n return self\",\n \"def _defaulted(cls, value, default):\\n return default if value is None else value\",\n \"def setdefault(self, k, d=None): # real signature unknown; restored from __doc__\\n pass\",\n \"def __init__(\\n self,\\n *,\\n name: str,\\n label: str,\\n optional: bool = False,\\n value: str = None,\\n placeholder: str = None,\\n ):\\n super().__init__(\\n name=name,\\n label=label,\\n optional=optional,\\n value=value,\\n placeholder=placeholder,\\n )\",\n \"def __init__(\\n self,\\n *,\\n name: str,\\n label: str,\\n optional: bool = False,\\n value: str = None,\\n placeholder: str = None,\\n ):\\n super().__init__(\\n name=name,\\n label=label,\\n optional=optional,\\n value=value,\\n placeholder=placeholder,\\n )\",\n \"def __init__(\\n self,\\n *,\\n name: str,\\n label: str,\\n optional: bool = False,\\n value: str = None,\\n placeholder: str = None,\\n ):\\n super().__init__(\\n name=name,\\n label=label,\\n optional=optional,\\n value=value,\\n placeholder=placeholder,\\n )\",\n \"def is_default(self):\\n return self._tag == 'default'\",\n \"def __init__(self, concept_ref='', value=''):\\n self.concept_ref = concept_ref\\n self.value = value\",\n \"def __init__(__self__, *,\\n default_resource_request: Optional[str] = None,\\n vault_critical_operation: Optional[str] = None):\\n if default_resource_request is not None:\\n pulumi.set(__self__, \\\"default_resource_request\\\", default_resource_request)\\n if vault_critical_operation is not None:\\n pulumi.set(__self__, \\\"vault_critical_operation\\\", vault_critical_operation)\",\n \"def default(self, value):\\n # save {value} as the default\\n self._default = value\\n # all done\\n return\",\n \"def __init__(self, attr=None, default=None, help_text=None):\\r\\n\\r\\n self._attribute = attr\\r\\n self._field_name = None\\r\\n self._default = default\\r\\n\\r\\n if help_text:\\r\\n self.help_text = help_text\",\n \"def create_option(self, label, value=None):\\n option = Option(label, value)\\n self.append(option)\\n return option\",\n \"def test_add_defined_tag_to_bucket(self, test, object_storage, with_or_without_compartment):\\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\\n session_factory = test.oci_session_factory()\\n policy = test.load_policy(\\n {\\n \\\"name\\\": \\\"add-defined-tag-to-bucket\\\",\\n \\\"resource\\\": \\\"oci.bucket\\\",\\n \\\"query\\\": [\\n {\\\"namespace_name\\\": namespace_name},\\n ],\\n \\\"filters\\\": [\\n {\\\"type\\\": \\\"value\\\", \\\"key\\\": \\\"name\\\", \\\"value\\\": bucket_name},\\n ],\\n \\\"actions\\\": [{\\\"type\\\": \\\"update\\\", \\\"defined_tags\\\": self.get_defined_tag(\\\"add_tag\\\")}],\\n },\\n session_factory=session_factory,\\n )\\n policy.run()\\n resource = self._fetch_bucket_validation_data(\\n policy.resource_manager, namespace_name, bucket_name\\n )\\n test.assertEqual(resource[\\\"name\\\"], bucket_name)\\n test.assertEqual(self.get_defined_tag_value(resource[\\\"defined_tags\\\"]), \\\"true\\\")\",\n \"def create_option(self) -> Optional[pulumi.Input[Union[str, 'OsDiskCreateOption']]]:\\n return pulumi.get(self, \\\"create_option\\\")\",\n \"def __init__(self, definition=None, do_validate=False):\\n\\n if not definition:\\n definition = {}\\n self._definition = definition\\n\\n if 'version' not in self._definition:\\n self._definition['version'] = DEFAULT_VERSION\\n\\n if self._definition['version'] != DEFAULT_VERSION:\\n msg = '%s is an unsupported version number'\\n raise InvalidDefinition('INVALID_DEFINITION', msg % self._definition['version'])\\n\\n self._populate_default_values()\\n\\n try:\\n if do_validate:\\n validate(definition, RECIPE_DEFINITION_SCHEMA)\\n except ValidationError as ex:\\n raise InvalidDefinition('INVALID_DEFINITION', 'Invalid recipe definition: %s' % unicode(ex))\",\n \"def create_type(name, description, metadata, force):\\n type_ = orm.DataFlagType()\\n\\n type_.name = name\\n type_.description = description\\n type_.metadata = metadata\\n\\n if force:\\n type_.save()\\n else:\\n click.echo(\\\"Type to create:\\\\n\\\")\\n click.echo(format_type(type_))\\n if click.confirm(\\\"Create type?\\\"):\\n type_.save()\\n click.echo(\\\"Success.\\\")\\n else:\\n click.echo(\\\"Aborted.\\\")\",\n \"def get_tag_default(self, tag_default_id, **kwargs):\\n resource_path = \\\"/tagDefaults/{tagDefaultId}\\\"\\n method = \\\"GET\\\"\\n\\n expected_kwargs = [\\\"retry_strategy\\\"]\\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\\n if extra_kwargs:\\n raise ValueError(\\n \\\"get_tag_default got unknown kwargs: {!r}\\\".format(extra_kwargs))\\n\\n path_params = {\\n \\\"tagDefaultId\\\": tag_default_id\\n }\\n\\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\\n\\n for (k, v) in six.iteritems(path_params):\\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\\n\\n header_params = {\\n \\\"accept\\\": \\\"application/json\\\",\\n \\\"content-type\\\": \\\"application/json\\\"\\n }\\n\\n retry_strategy = self.retry_strategy\\n if kwargs.get('retry_strategy'):\\n retry_strategy = kwargs.get('retry_strategy')\\n\\n if retry_strategy:\\n return retry_strategy.make_retrying_call(\\n self.base_client.call_api,\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"TagDefault\\\")\\n else:\\n return self.base_client.call_api(\\n resource_path=resource_path,\\n method=method,\\n path_params=path_params,\\n header_params=header_params,\\n response_type=\\\"TagDefault\\\")\",\n \"def getDefault():\",\n \"def new(cls, default=None):\\n return cls(default=default)\",\n \"def __init__(__self__, *,\\n name: Optional[str] = None,\\n value: Optional[str] = None):\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if value is not None:\\n pulumi.set(__self__, \\\"value\\\", value)\",\n \"def __init__(__self__, *,\\n name: Optional[str] = None,\\n value: Optional[str] = None):\\n if name is not None:\\n pulumi.set(__self__, \\\"name\\\", name)\\n if value is not None:\\n pulumi.set(__self__, \\\"value\\\", value)\",\n \"def __init__(self, tagged_sents, default_tag='nc0s000'):\\n self._default_tag = default_tag\",\n \"def create_tag(create_timestamps):\\n ctx = dash.callback_context\\n triggered_id, triggered_prop, triggered_value = utils.ctx_triggered_info(ctx)\\n\\n # When the button is initially added, it fires a callback.\\n # We want to prevent this callback from making changes to the update signal.\\n if triggered_value is None:\\n raise PreventUpdate\\n\\n state.create_tag(\\\"\\\")\\n return constants.OK_SIGNAL\",\n \"def test_default_creation_2():\\n actual = os.path.join('.', 'test_files', 'rc_test_default.input')\\n times = list(range(0, 30, 5))\\n params = {\\\"names\\\": ['V'],\\n \\\"values\\\": [\\n [1],\\n [0],\\n [-1],\\n [0],\\n [1]\\n ]\\n }\\n input_creator = InputCreator(None, times, params)\\n f_out = input_creator.default_creation_2()\\n with open(actual) as f_actual:\\n actual_content = f_actual.read()\\n\\n content = f_out.getvalue()\\n\\n assert_equal(content, actual_content)\",\n \"def __init__(__self__, *,\\n default_resource_request: Optional[pulumi.Input[str]] = None,\\n vault_critical_operation: Optional[pulumi.Input[str]] = None):\\n if default_resource_request is not None:\\n pulumi.set(__self__, \\\"default_resource_request\\\", default_resource_request)\\n if vault_critical_operation is not None:\\n pulumi.set(__self__, \\\"vault_critical_operation\\\", vault_critical_operation)\",\n \"def register_def(self, name, default, def_text):\\n\\n _type = self.type_by_name[name]\\n _type.name = name\\n _def = _type.register_def_raw(default, def_text)\\n self.def_by_hash[_def.hash] = _def\\n return _def\",\n \"def tag(\\n name: str, value: str, *, attributes: dict = {}, namespace: str = None\\n ) -> str:\\n attributes_str = \\\" \\\".join(f'{k}=\\\"{v}\\\"' for k, v in attributes.items())\\n ns = f\\\"{namespace}:\\\" if namespace else \\\"\\\"\\n if attributes_str:\\n attributes_str = \\\" \\\" + attributes_str\\n if value:\\n return f\\\"<{ns}{name}{attributes_str}>{value}\\\"\\n return f\\\"<{ns}{name}{attributes_str} />\\\"\",\n \"def create_default_network(context):\\n return [{\\n 'type': 'templates/network.py',\\n 'name': 'fc-network',\\n 'properties': {\\n 'resourceName': 'network',\\n 'name': 'network',\\n 'projectId': '$(ref.fc-project.projectId)',\\n 'autoCreateSubnetworks': True,\\n # We pass the dependsOn list into the network template as a\\n # parameter. Deployment Manager doesn't support dependsOn for\\n # template-call nodes, so we can't have this resource itself depend on\\n # the project-wide resources.\\n 'dependsOn': '$(ref.fc-project.resourceNames)',\\n },\\n }]\",\n \"def create_tag(self, entry_name, tag):\\n return self.__datacatalog.create_tag(parent=entry_name, tag=tag)\",\n \"def f_default(self, default = 1) :\\n pass\",\n \"def default():\",\n \"def make_new_tag(tag_name, user_path, user_signed_in, current_user):\\n if not user_signed_in:\\n print('ALERT: -- User not logged in --')\\n else:\\n user = current_user[0]\\n print(is_tag(tag_name, user_path, current_user))\\n if is_tag(tag_name, user_path, current_user):\\n print('Tag already exist')\\n else:\\n os.mkdir((user_path + '\\\\\\\\' + user + '\\\\\\\\' + tag_name).encode('unicode_escape'))\\n print('Tag --' + tag_name + '-- Created')\",\n \"def add_tag(self, obj, tag_name):\\r\\n tag_names = parse_tag_input(tag_name)\\r\\n if not len(tag_names):\\r\\n raise AttributeError(_('No tags were given: \\\"%s\\\".') % tag_name)\\r\\n if len(tag_names) > 1:\\r\\n raise AttributeError(_('Multiple tags were given: \\\"%s\\\".') % tag_name)\\r\\n tag_name = tag_names[0]\\r\\n if settings.FORCE_LOWERCASE_TAGS:\\r\\n tag_name = tag_name.lower()\\r\\n tag, created = self.get_or_create(name=tag_name)\\r\\n ctype = ContentType.objects.get_for_model(obj)\\r\\n TaggedItem._default_manager.get_or_create(\\r\\n tag=tag, content_type=ctype, object_id=obj.pk)\",\n \"def group(cls: type[T], optional: bool = False) -> T:\\n default = None if optional else RAISE\\n return attr.ib(\\n default=default,\\n metadata={CNF_KEY: _ConfigEntry(None, default, cls, True)},\\n )\",\n \"def test_no_default_value(self):\\n dim = Real(\\\"yolo\\\", \\\"uniform\\\", -3, 4)\\n assert dim.default_value is None\",\n \"def test_no_default_value(self):\\n dim = Dimension(\\\"yolo\\\", \\\"uniform\\\", -3, 4)\\n assert dim.default_value is None\",\n \"def pre_config_node_create(self, resource_dict):\\n pass\",\n \"def test_config_option_required_default():\\n class Config(config.Config):\\n a = config.option(int, required=True, default=12, help=\\\"\\\")\\n\\n c = config.structure({}, Config)\\n assert c.a == 12\\n\\n c = config.structure({\\\"a\\\": 23}, Config)\\n assert c.a == 23\\n\\n with pytest.raises(config.ConfigError):\\n config.structure({\\\"a\\\": None}, Config)\",\n \"def _ValueOrPlaceHolder(value_string, description):\\n value_element = xml.etree.ElementTree.Element('value')\\n value_element.set('xml:lang', _VALUE_LANGUAGE)\\n\\n if value_string:\\n value_element.text = value_string\\n else:\\n value_element.text = '** INSERT %s **' % description\\n\\n return value_element\"\n]"},"negative_scores":{"kind":"list like","value":["0.5894807","0.55696887","0.548009","0.52427024","0.5172015","0.5163364","0.5069004","0.50466603","0.50242513","0.5003325","0.4976948","0.49649096","0.49576932","0.49290386","0.4914476","0.49040148","0.49038035","0.48990166","0.48935652","0.48932627","0.48672876","0.4841067","0.48255783","0.4821933","0.48154172","0.47908288","0.4787615","0.47782978","0.47718528","0.47643954","0.47606185","0.4756601","0.47514093","0.47409117","0.4735763","0.47286236","0.47235686","0.4711209","0.470434","0.46912426","0.46839556","0.4676166","0.46750492","0.46737662","0.4664757","0.4662496","0.46623552","0.4660885","0.4638475","0.4638237","0.46371958","0.4630583","0.46270856","0.46233627","0.46211612","0.46194953","0.46092317","0.46084744","0.46082532","0.4588523","0.45783314","0.45750815","0.4572613","0.4570522","0.45654744","0.45654744","0.45654744","0.4557074","0.45506805","0.45341545","0.45288453","0.4528628","0.45263708","0.45211488","0.45160273","0.45140576","0.45130396","0.45086455","0.45001143","0.4492379","0.44881603","0.44881603","0.44860205","0.44826436","0.44822168","0.44717","0.44682777","0.44647133","0.44633415","0.44604358","0.44571733","0.44563684","0.44535297","0.44506803","0.44500577","0.44455424","0.44450638","0.4443447","0.44430986","0.4436986"],"string":"[\n \"0.5894807\",\n \"0.55696887\",\n \"0.548009\",\n \"0.52427024\",\n \"0.5172015\",\n \"0.5163364\",\n \"0.5069004\",\n \"0.50466603\",\n \"0.50242513\",\n \"0.5003325\",\n \"0.4976948\",\n \"0.49649096\",\n \"0.49576932\",\n \"0.49290386\",\n \"0.4914476\",\n \"0.49040148\",\n \"0.49038035\",\n \"0.48990166\",\n \"0.48935652\",\n \"0.48932627\",\n \"0.48672876\",\n \"0.4841067\",\n \"0.48255783\",\n \"0.4821933\",\n \"0.48154172\",\n \"0.47908288\",\n \"0.4787615\",\n \"0.47782978\",\n \"0.47718528\",\n \"0.47643954\",\n \"0.47606185\",\n \"0.4756601\",\n \"0.47514093\",\n \"0.47409117\",\n \"0.4735763\",\n \"0.47286236\",\n \"0.47235686\",\n \"0.4711209\",\n \"0.470434\",\n \"0.46912426\",\n \"0.46839556\",\n \"0.4676166\",\n \"0.46750492\",\n \"0.46737662\",\n \"0.4664757\",\n \"0.4662496\",\n \"0.46623552\",\n \"0.4660885\",\n \"0.4638475\",\n \"0.4638237\",\n \"0.46371958\",\n \"0.4630583\",\n \"0.46270856\",\n \"0.46233627\",\n \"0.46211612\",\n \"0.46194953\",\n \"0.46092317\",\n \"0.46084744\",\n \"0.46082532\",\n \"0.4588523\",\n \"0.45783314\",\n \"0.45750815\",\n \"0.4572613\",\n \"0.4570522\",\n \"0.45654744\",\n \"0.45654744\",\n \"0.45654744\",\n \"0.4557074\",\n \"0.45506805\",\n \"0.45341545\",\n \"0.45288453\",\n \"0.4528628\",\n \"0.45263708\",\n \"0.45211488\",\n \"0.45160273\",\n \"0.45140576\",\n \"0.45130396\",\n \"0.45086455\",\n \"0.45001143\",\n \"0.4492379\",\n \"0.44881603\",\n \"0.44881603\",\n \"0.44860205\",\n \"0.44826436\",\n \"0.44822168\",\n \"0.44717\",\n \"0.44682777\",\n \"0.44647133\",\n \"0.44633415\",\n \"0.44604358\",\n \"0.44571733\",\n \"0.44563684\",\n \"0.44535297\",\n \"0.44506803\",\n \"0.44500577\",\n \"0.44455424\",\n \"0.44450638\",\n \"0.4443447\",\n \"0.44430986\",\n \"0.4436986\"\n]"},"document_score":{"kind":"string","value":"0.64231205"},"document_rank":{"kind":"string","value":"0"}}},{"rowIdx":8587,"cells":{"query":{"kind":"string","value":"Creates a new tag namespace in the specified compartment. You must specify the compartment ID in the request object (remember that the tenancy is simply the root compartment). You must also specify a name for the namespace, which must be unique across all namespaces in your tenancy and cannot be changed. The name can contain any ASCII character except the space (_) or period (.). Names are case insensitive. That means, for example, \\\"myNamespace\\\" and \\\"mynamespace\\\" are not allowed in the same tenancy. Once you created a namespace, you cannot change the name. If you specify a name that's already in use in the tenancy, a 409 error is returned. You must also specify a description for the namespace. It does not have to be unique, and you can change it with"},"document":{"kind":"string","value":"def create_tag_namespace(self, create_tag_namespace_details, **kwargs):\n resource_path = \"/tagNamespaces\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_tag_namespace got unknown kwargs: {!r}\".format(extra_kwargs))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_tag_namespace_details,\n response_type=\"TagNamespace\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n header_params=header_params,\n body=create_tag_namespace_details,\n response_type=\"TagNamespace\")"},"metadata":{"kind":"string","value":"{\n \"objective\": {\n \"self\": [],\n \"paired\": [],\n \"triplet\": [\n [\n \"query\",\n \"document\",\n \"negatives\"\n ]\n ]\n }\n}"},"negatives":{"kind":"list like","value":["def post_namespace_create(self, resource_dict):\n pass","def create_namespace(node, namespace, delete_before_create=True):\n if delete_before_create:\n Namespaces.delete_namespace(node, namespace)\n\n cmd = f\"ip netns add {namespace}\"\n exec_cmd_no_error(node, cmd, sudo=True)\n Namespaces.__namespaces.append(namespace)","def createNamespace(self):\r\n raise NotImplementedError('Endpoint can not be used directly.')","def create_namespaced_net_namespace(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_net_namespace\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_net_namespace`\")\n\n resource_path = '/oapi/v1/netnamespaces'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1NetNamespace',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def change_tag_namespace_compartment(self, tag_namespace_id, change_tag_namespace_compartment_detail, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}/actions/changeCompartment\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"change_tag_namespace_compartment got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=change_tag_namespace_compartment_detail)\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=change_tag_namespace_compartment_detail)","def create_namespaced_namespace(self, body, **kwargs):\n kwargs['_return_http_data_only'] = True\n if kwargs.get('callback'):\n return self.create_namespaced_namespace_with_http_info(body, **kwargs)\n else:\n (data) = self.create_namespaced_namespace_with_http_info(body, **kwargs)\n return data","def create_namespaced_namespace_with_http_info(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n all_params.append('_return_http_data_only')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_namespace\" % key\n )\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_namespace`\")\n\n resource_path = '/api/v1/namespaces'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n return self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Namespace',\n auth_settings=auth_settings,\n callback=params.get('callback'),\n _return_http_data_only=params.get('_return_http_data_only'))","def create(cls, ns, name, **kwargs):\n key_name = '%s:%s' % (ns, name)\n return cls(key_name=key_name, ns=ns, name=name, **kwargs)","def create (self, name, dsspolicyguid, jobguid = \"\", executionparams = {}):\n params =dict()\n params['name'] = name\n params['dsspolicyguid'] = dsspolicyguid\n executionparams['rootobjecttype'] = 'dssnamespace'\n\n \n return q.workflowengine.actionmanager.startRootobjectAction('dssnamespace', 'create', params, jobguid=jobguid, executionparams=executionparams)","def create_tag(self, tag_namespace_id, create_tag_details, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}/tags\"\n method = \"POST\"\n\n # Don't accept unknown kwargs\n expected_kwargs = [\n \"retry_strategy\",\n \"opc_retry_token\"\n ]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"create_tag got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\",\n \"opc-retry-token\": kwargs.get(\"opc_retry_token\", missing)\n }\n header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n if not isinstance(retry_strategy, retry.NoneRetryStrategy):\n self.base_client.add_opc_retry_token_if_needed(header_params)\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_tag_details,\n response_type=\"Tag\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=create_tag_details,\n response_type=\"Tag\")","def _create_namespace(self):\n self.ocp.new_project(self.namespace)","def create_namespace(self) -> Optional[pulumi.Input[bool]]:\n return pulumi.get(self, \"create_namespace\")","def create_namespace(self) -> pulumi.Output[Optional[bool]]:\n return pulumi.get(self, \"create_namespace\")","def create_namespace(self, name, status_wait=True):\n name = name or self.generate_random_name()\n\n manifest = {\n \"apiVersion\": \"v1\",\n \"kind\": \"Namespace\",\n \"metadata\": {\n \"name\": name,\n \"labels\": {\n \"role\": name\n }\n }\n }\n self.v1_client.create_namespace(body=manifest)\n\n if status_wait:\n with atomic.ActionTimer(self,\n \"kubernetes.wait_for_nc_become_active\"):\n wait_for_status(name,\n status=\"Active\",\n read_method=self.get_namespace)\n return name","def test_namespace_bucket_creation_rpc(\n self, ns_resource_factory, bucket_factory, platform\n ):\n # Create the namespace resource and verify health\n ns_resource_name = ns_resource_factory(platform=platform)[1]\n\n # Create the namespace bucket on top of the namespace resource\n bucket_factory(\n amount=1,\n interface=\"mcg-namespace\",\n write_ns_resource=ns_resource_name,\n read_ns_resources=[ns_resource_name],\n )","def replace_namespaced_net_namespace(self, body, name, **kwargs):\n\n all_params = ['body', 'name', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method replace_namespaced_net_namespace\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `replace_namespaced_net_namespace`\")\n # verify the required parameter 'name' is set\n if ('name' not in params) or (params['name'] is None):\n raise ValueError(\"Missing the required parameter `name` when calling `replace_namespaced_net_namespace`\")\n\n resource_path = '/oapi/v1/netnamespaces/{name}'.replace('{format}', 'json')\n path_params = {}\n if 'name' in params:\n path_params['name'] = params['name']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'PUT',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1NetNamespace',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def test_create_namespaced_deployment_request_instantiate(self):\n pass","def test_namespace_bucket_creation_with_rgw_rpc(\n self, ns_resource_factory, bucket_factory, rgw_deployments\n ):\n # Create the namespace resource and verify health\n ns_resource_name = ns_resource_factory(platform=constants.RGW_PLATFORM)[1]\n\n # Create the namespace bucket on top of the namespace resource\n bucket_factory(\n amount=1,\n interface=\"mcg-namespace\",\n write_ns_resource=ns_resource_name,\n read_ns_resources=[ns_resource_name],\n )","def test_create_net_namespace(self):\n pass","def sync_namespace(alias, reg_code, authToken, space=None, action=None):\n if space == None:\n action = 'get'\n print(\" ACTION: GET\")\n elif action == None:\n if 'aeskey' not in space:\n print(\"Space not encrypted\")\n quit()\n action = 'update'\n print(\" ACTION: UPDATE\")\n elif action == 'delete':\n print(\" ACTION: DELETE\")\n url = endpoint('namespace')\n headers={'authorizationToken': authToken}\n data = json.dumps({'action': action, 'alias': alias, 'reg_code': reg_code, 'namespace': space})\n payload_size = sys.getsizeof(data)\n print(\" Size of payload is: %s\" % (convert_size(payload_size)))\n print(\" Max payload is: %s\" % (convert_size(max_payload_size)))\n if payload_size >= max_payload_size:\n print(\" OVER MAX PAYLOAD: %s\" % (convert_size(max_payload_size)))\n quit()\n r = requests.post(url, headers=headers, data=data) \n print(\" Request made\")\n if r.status_code == 403:\n print(\" Invalid registration code, exiting\")\n quit()\n elif r.status_code == 406:\n print(\" Namespace mismatch\")\n quit()\n else:\n print(\" └──statusCode:\" + str(r.status_code) )\n return r","def pre_namespace_create(self, resource_dict):\n pass","def create_resource(self, namespace: \"str\" = None):\n names = [\"create_namespaced_csistorage_capacity\", \"create_csistorage_capacity\"]\n\n _kube_api.execute(\n action=\"create\",\n resource=self,\n names=names,\n namespace=namespace,\n api_client=None,\n api_args={\"body\": self.to_dict()},\n )","def _AddCreatedNamespace(self, state_tracker, identifier, line_number,\n namespace=None):\n if not namespace:\n namespace = identifier\n\n if self._HasSuppression(state_tracker, 'missingProvide'):\n return\n\n self._created_namespaces.append([namespace, identifier, line_number])","def create_client_by_namespace(\n body: ClientmodelClientCreateRequest,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = CreateClientByNamespace.create(\n body=body,\n namespace=namespace,\n )\n return run_request(request, additional_headers=x_additional_headers, **kwargs)","def register_namespace(alias, reg_code, pubKey=None, password=None):\n print( \" Registering namespace: %s\" % (alias) )\n if pubKey == None:\n generate_keys()\n pubKey = os.environ[\"pubKey\"]\n\n if check_lspace() == True:\n print(\" Device already registred to a namespace\")\n return False\n \n url = endpoint('register')\n payload = json.dumps({\n \"action\": \"register\",\n \"alias\": alias,\n \"reg_code\": reg_code,\n \"pubKey\": pubKey\n })\n r = requests.post(url, data=payload) \n statusCode = r.status_code\n content = json.loads(r.content)\n\n if statusCode == 201:\n print(\" Namespace registered succesfully\")\n namespace = content[\"namespace\"]\n namespace[\"privKey\"] = os.environ[\"privKey\"]\n save_lspace(namespace, password)\n else:\n print(\" Something went wrong - %s\" % (statusCode))\n quit()\n\n return statusCode","def replace_namespaced_namespace_with_http_info(self, body, name, **kwargs):\n\n all_params = ['body', 'name', 'pretty']\n all_params.append('callback')\n all_params.append('_return_http_data_only')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method replace_namespaced_namespace\" % key\n )\n params[key] = val\n del params['kwargs']\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `replace_namespaced_namespace`\")\n # verify the required parameter 'name' is set\n if ('name' not in params) or (params['name'] is None):\n raise ValueError(\"Missing the required parameter `name` when calling `replace_namespaced_namespace`\")\n\n resource_path = '/api/v1/namespaces/{name}'.replace('{format}', 'json')\n path_params = {}\n if 'name' in params:\n path_params['name'] = params['name']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n return self.api_client.call_api(resource_path, 'PUT',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Namespace',\n auth_settings=auth_settings,\n callback=params.get('callback'),\n _return_http_data_only=params.get('_return_http_data_only'))","def new_namespace(key):\n\tif key in REGISTRY:\n\t\traise KeyError(\"key:{0} already exists\".format(key))\n\n\tREGISTRY[key] = Namespace()","def create_or_fetch_namespace(self):\n\n def _create_new_namespace():\n logger.info(\n f\"Creating a new namespace: {self.namespace_name} in {self.namespace_region}\"\n )\n\n data = {\n \"name\": self.namespace_name,\n \"resource_group_id\": self.resource_group_id,\n \"resource_plan_id\": \"functions-base-plan\",\n }\n\n res = requests.post(\n self.cf_namespaces_url, headers=self.get_headers(), json=data\n ).json()\n if res.status_code != 200:\n logger.error(res.text)\n namespace_id = res[\"id\"]\n logger.info(f\"Created new namespace with id: {namespace_id}\")\n return namespace_id\n\n def _get_cloud_function_namespaces_metadata(offset=0):\n \"\"\"returns meta data on namespaces of ibm cloud functions within a specified region\n :param offset - offset from the beginning of the list of results attained from the GET request,\n which may contain up to 200 namespaces per http response\"\"\"\n\n res = requests.get(\n f\"{self.cf_namespaces_url}?limit=200&offset={offset}\",\n headers=self.get_headers(),\n )\n return json.loads(res.text)\n\n def _get_cloud_function_namespaces():\n \"\"\"returns relevant metadata on existing namespaces within a given region.\"\"\"\n logger.info(\n f\"Obtaining Cloud Function namespaces in {self.namespace_region}\"\n )\n\n namespaces = []\n\n collecting_namespaces = True\n max_limit = 200\n offset = 0\n\n # request for namespaces is limited to 200 at a time, thus the request is fulfilled in increments of 200s.\n while collecting_namespaces:\n namespace_metadata = _get_cloud_function_namespaces_metadata(offset)\n if namespace_metadata[\"total_count\"] == max_limit:\n offset += max_limit\n else:\n collecting_namespaces = False\n\n for name_space in namespace_metadata[\"namespaces\"]:\n if \"name\" in name_space: # API based namespace\n namespaces.append(\n {\n \"name\": name_space[\"name\"],\n \"type\": \"API_based\",\n \"id\": name_space[\"id\"],\n \"region\": name_space[\"location\"],\n }\n )\n\n else: # cloud foundry based namespace\n namespaces.append(\n {\n \"name\": name_space[\"id\"],\n \"type\": \"CF_based\",\n \"region\": name_space[\"location\"],\n }\n )\n\n return namespaces\n\n namespaces_in_region = _get_cloud_function_namespaces()\n target_namespace_id = None\n if namespaces_in_region:\n target_namespace_id = next(\n (\n namespace[\"id\"]\n for namespace in namespaces_in_region\n if namespace[\"name\"] == self.namespace_name\n ),\n None,\n )\n if not target_namespace_id:\n target_namespace_id = _create_new_namespace()\n else:\n logger.info(f\"Reusing namespace: {target_namespace_id}\")\n return target_namespace_id","def createNamespace(self):\r\n if self._namespaces:\r\n raise InternalError('Can not have more than one namespace '\r\n 'in an Environment endpoint at a time.')\r\n\r\n return Environment(self)","async def create_client_by_namespace_async(\n body: ClientmodelClientCreateRequest,\n namespace: Optional[str] = None,\n x_additional_headers: Optional[Dict[str, str]] = None,\n **kwargs\n):\n if namespace is None:\n namespace, error = get_services_namespace()\n if error:\n return None, error\n request = CreateClientByNamespace.create(\n body=body,\n namespace=namespace,\n )\n return await run_request_async(\n request, additional_headers=x_additional_headers, **kwargs\n )","def __setattr__(self, name, value):\n if not isinstance(name, str):\n raise ValueError('Namespace label must be a string')\n if name.startswith('_'):\n raise ValueError('Namespace cannot start with an underscore')\n\n if name in self._namespaces:\n raise ValueError('Namespaces cannot be redefined')\n\n self._namespaces[name] = Namespace(name, label=value)","def test_create_namespaced_deployment_config(self):\n pass","def newNs(self, href, prefix):\n ret = libxml2mod.xmlNewNs(self._o, href, prefix)\n if ret is None:raise treeError('xmlNewNs() failed')\n __tmp = xmlNs(_obj=ret)\n return __tmp","def test_create_namespaced_template(self):\n pass","def patch_namespaced_net_namespace(self, body, name, **kwargs):\n\n all_params = ['body', 'name', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method patch_namespaced_net_namespace\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `patch_namespaced_net_namespace`\")\n # verify the required parameter 'name' is set\n if ('name' not in params) or (params['name'] is None):\n raise ValueError(\"Missing the required parameter `name` when calling `patch_namespaced_net_namespace`\")\n\n resource_path = '/oapi/v1/netnamespaces/{name}'.replace('{format}', 'json')\n path_params = {}\n if 'name' in params:\n path_params['name'] = params['name']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['application/json-patch+json', 'application/merge-patch+json', 'application/strategic-merge-patch+json'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'PATCH',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1NetNamespace',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def ReplaceNamespace(self, request, global_params=None):\n config = self.GetMethodConfig('ReplaceNamespace')\n return self._RunMethod(\n config, request, global_params=global_params)","def ReplaceNamespace(self, request, global_params=None):\n config = self.GetMethodConfig('ReplaceNamespace')\n return self._RunMethod(\n config, request, global_params=global_params)","def update():\n for namespace in metadata.get_namespaces():\n logging.info('Switching namespace: \\'%s\\'', namespace)\n namespace_manager.set_namespace(namespace)\n update_per_namespace()\n\n namespace_manager.set_namespace('')\n return ('', 204)","async def add_namespace(self, namespace: str, **kwargs) -> Union[str, None]:\n if namespace == self.get_namespace(): # if it belongs to this app's namespace\n raise ValueError(\"Cannot add namespace with the same name as operating namespace\")\n\n writeback = kwargs.get(\"writeback\", \"safe\")\n persist = kwargs.get(\"persist\", True)\n\n return await self.AD.state.add_namespace(namespace, writeback, persist, self.name)","def update_tag_namespace(self, tag_namespace_id, update_tag_namespace_details, **kwargs):\n resource_path = \"/tagNamespaces/{tagNamespaceId}\"\n method = \"PUT\"\n\n expected_kwargs = [\"retry_strategy\"]\n extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]\n if extra_kwargs:\n raise ValueError(\n \"update_tag_namespace got unknown kwargs: {!r}\".format(extra_kwargs))\n\n path_params = {\n \"tagNamespaceId\": tag_namespace_id\n }\n\n path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}\n\n for (k, v) in six.iteritems(path_params):\n if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):\n raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))\n\n header_params = {\n \"accept\": \"application/json\",\n \"content-type\": \"application/json\"\n }\n\n retry_strategy = self.retry_strategy\n if kwargs.get('retry_strategy'):\n retry_strategy = kwargs.get('retry_strategy')\n\n if retry_strategy:\n return retry_strategy.make_retrying_call(\n self.base_client.call_api,\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_namespace_details,\n response_type=\"TagNamespace\")\n else:\n return self.base_client.call_api(\n resource_path=resource_path,\n method=method,\n path_params=path_params,\n header_params=header_params,\n body=update_tag_namespace_details,\n response_type=\"TagNamespace\")","def _configure_namespaces(api):\n\t#{{cookiecutter.app_name}}_namespace\n\tapi.add_namespace({{cookiecutter.app_name}}_namespace)","def addNamespace(self, *args):\n return _libsbml.XMLToken_addNamespace(self, *args)","async def save_namespace(self, **kwargs) -> None:\n namespace = self._get_namespace(**kwargs)\n await self.AD.state.save_namespace(namespace)","def add_namespaces(specification):\n\n for ns in specification[\"namespaces\"]:\n specification[\"namespaces\"][ns][\"list\"] = []\n specification[\"namespaces\"][ns][\"list_long\"] = []\n specification[\"namespaces\"][ns][\"list_short\"] = []\n\n specification[\"namespaces\"][ns][\"to_short\"] = {}\n specification[\"namespaces\"][ns][\"to_long\"] = {}\n\n for obj in specification[\"namespaces\"][ns][\"info\"]:\n specification[\"namespaces\"][ns][\"list\"].extend([obj[\"name\"], obj[\"abbreviation\"]])\n specification[\"namespaces\"][ns][\"list_short\"].append(obj[\"abbreviation\"])\n specification[\"namespaces\"][ns][\"list_long\"].append(obj[\"name\"])\n\n specification[\"namespaces\"][ns][\"to_short\"][obj[\"abbreviation\"]] = obj[\"abbreviation\"]\n specification[\"namespaces\"][ns][\"to_short\"][obj[\"name\"]] = obj[\"abbreviation\"]\n\n specification[\"namespaces\"][ns][\"to_long\"][obj[\"abbreviation\"]] = obj[\"name\"]\n specification[\"namespaces\"][ns][\"to_long\"][obj[\"name\"]] = obj[\"name\"]\n\n # For AminoAcid namespace\n if \"abbrev1\" in obj:\n specification[\"namespaces\"][ns][\"to_short\"][obj[\"abbrev1\"]] = obj[\"abbreviation\"]\n specification[\"namespaces\"][ns][\"to_long\"][obj[\"abbrev1\"]] = obj[\"name\"]","def create_uuid3(namespace, name):\n return uuid.uuid3(namespace, six.ensure_str(name))","def test_create_namespaced_build_request_instantiate(self):\n pass","def create_namespaced_service(self, body, namespace, **kwargs):\n kwargs['_return_http_data_only'] = True\n if kwargs.get('callback'):\n return self.create_namespaced_service_with_http_info(body, namespace, **kwargs)\n else:\n (data) = self.create_namespaced_service_with_http_info(body, namespace, **kwargs)\n return data","def set_namespace(key, dic):\n\tnew_namespace(key)\n\tREGISTRY[key] = Namespace(dic)","def setup_namespace(zone, prefix, org, org_owner, verbose=False):\n\n # process args\n if org and not org_owner:\n if verbose:\n print('Must provide both organization name and organization owner arguments')\n return 2\n \n if not zone:\n zone = get_local_zone(verbose=verbose)\n if not zone:\n return 2\n\n if prefix and prefix.find('/' + zone) != 0:\n if verbose:\n print('Prefix %s not within zone %s' % (prefix, zone))\n return 2\n\n if prefix and org:\n path_prefix = os.path.join(prefix, org)\n elif org:\n path_prefix = os.path.join('/', zone, org)\n else:\n path_prefix = os.path.join('/', zone)\n\n if org:\n org_group = 'ids-%s#%s' % (org, zone)\n if org_owner and org_owner.find('#') != -1:\n org_user = org_owner\n elif org_owner:\n org_user = '%s#%s' % (org_owner, zone)\n else:\n org_group = None\n org_user = None\n\n\n # check if the anonymous user is defined within the zone\n # if so, it will be given a 'read' ACL on the same\n # collections as the 'public' group\n include_anonymous = False\n if irods_user_exists('anonymous#%s' % (zone,)) > 0:\n include_anonymous = True\n\n\n # top-level '/zone/organization' or '/prefix/organization' collection.\n # 'public' and 'anonymous' get read ACLs so browsing can work\n if org:\n if verbose:\n print(' creating collection %s' % (path_prefix,))\n rc = irods_mkdir(path_prefix, verbose)\n if rc:\n return rc\n acl_list = [['public#%s' % (zone,), 'read'], [org_user, 'own']]\n if include_anonymous:\n acl_list.append(['anonymous#%s' % (zone,), 'read'])\n if verbose:\n print(' setting default ACLs on %s' % (path_prefix,))\n rc = irods_setacls(path_prefix, acl_list, verbose)\n if rc:\n return rc\n else:\n # if we're setting up '/zone', then we need need to make sure\n # that 'public' and 'anonymous' can read and '/' and '/zone' so \n # browsing will work\n acl_list = [['public#%s' % (zone,), 'read'],]\n if include_anonymous:\n acl_list.append(['anonymous#%s' % (zone,), 'read'])\n if verbose:\n print(' setting default ACLs on %s' % (path_prefix,))\n rc = irods_setacls('/', acl_list, verbose)\n if rc:\n return rc\n rc = irods_setacls(path_prefix, acl_list, verbose)\n if rc:\n return rc\n\n\n # The following sub-collections are created, with the\n # listed ACLs:\n #\n # top-level/private - organizational group read ACL\n # top-level/shared - 'ids-user' gets read ACL\n # top-level/public - 'public' gets read ACL\n #\n\n # private\n path = os.path.join(path_prefix, 'private')\n if verbose:\n print(' creating collection %s' % (path,))\n rc = irods_mkdir(path, verbose)\n if rc:\n return rc\n if org:\n # won't add this ACL if we're doing /zone/private\n acl_list = [[org_group, 'read'], [org_user, 'own']]\n if verbose:\n print(' setting default ACLs on %s' % (path,))\n rc = irods_setacls(path, acl_list, verbose)\n if rc:\n return rc\n\n # shared\n path = os.path.join(path_prefix, 'shared')\n if verbose:\n print(' creating collection %s' % (path,))\n rc = irods_mkdir(path, verbose)\n if rc:\n return rc\n acl_list = [['ids-user#%s' % (zone,), 'read'],]\n if org:\n acl_list.append([org_user, 'own'])\n if verbose:\n print(' setting default ACLs on %s' % (path,))\n rc = irods_setacls(path, acl_list, verbose)\n if rc:\n return rc\n\n # public\n path = os.path.join(path_prefix, 'public')\n if verbose:\n print(' creating collection %s' % (path,))\n rc = irods_mkdir(path, verbose)\n if rc:\n return rc\n acl_list = [['public#%s' % (zone,), 'read'],]\n if include_anonymous:\n acl_list.append(['anonymous#%s' % (zone,), 'read'])\n if org:\n acl_list.append([org_user, 'own'])\n if verbose:\n print(' setting default ACLs on %s' % (path,))\n rc = irods_setacls(path, acl_list, verbose)\n if rc:\n return rc\n\n \n return 0","def __init__(self, default_ns, namespaces=[]):\n self.document = prov.ProvDocument ()\n self.default_ns = default_ns\n self.document.set_default_namespace (self.default_ns)\n self.namespaces = namespaces\n self.subspaces = {}\n for namespace in self.namespaces:\n self.subspaces[namespace] = self.add_namespace (self.default_ns, namespace)","def test_add_defined_tag_to_bucket(self, test, object_storage, with_or_without_compartment):\n namespace_name, bucket_name = self._get_bucket_details(object_storage)\n session_factory = test.oci_session_factory()\n policy = test.load_policy(\n {\n \"name\": \"add-defined-tag-to-bucket\",\n \"resource\": \"oci.bucket\",\n \"query\": [\n {\"namespace_name\": namespace_name},\n ],\n \"filters\": [\n {\"type\": \"value\", \"key\": \"name\", \"value\": bucket_name},\n ],\n \"actions\": [{\"type\": \"update\", \"defined_tags\": self.get_defined_tag(\"add_tag\")}],\n },\n session_factory=session_factory,\n )\n policy.run()\n resource = self._fetch_bucket_validation_data(\n policy.resource_manager, namespace_name, bucket_name\n )\n test.assertEqual(resource[\"name\"], bucket_name)\n test.assertEqual(self.get_defined_tag_value(resource[\"defined_tags\"]), \"true\")","def create_namespaced_identity(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_identity\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_identity`\")\n\n resource_path = '/oapi/v1/identities'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Identity',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def create_namespaced_group(self, body, **kwargs):\n\n all_params = ['body', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_group\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_group`\")\n\n resource_path = '/oapi/v1/groups'.replace('{format}', 'json')\n path_params = {}\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Group',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def create_namespaced_template(self, body, namespace, **kwargs):\n\n all_params = ['body', 'namespace', 'pretty']\n all_params.append('callback')\n\n params = locals()\n for key, val in iteritems(params['kwargs']):\n if key not in all_params:\n raise TypeError(\n \"Got an unexpected keyword argument '%s'\"\n \" to method create_namespaced_template\" % key\n )\n params[key] = val\n del params['kwargs']\n\n # verify the required parameter 'body' is set\n if ('body' not in params) or (params['body'] is None):\n raise ValueError(\"Missing the required parameter `body` when calling `create_namespaced_template`\")\n # verify the required parameter 'namespace' is set\n if ('namespace' not in params) or (params['namespace'] is None):\n raise ValueError(\"Missing the required parameter `namespace` when calling `create_namespaced_template`\")\n\n resource_path = '/oapi/v1/namespaces/{namespace}/processedtemplates'.replace('{format}', 'json')\n path_params = {}\n if 'namespace' in params:\n path_params['namespace'] = params['namespace']\n\n query_params = {}\n if 'pretty' in params:\n query_params['pretty'] = params['pretty']\n\n header_params = {}\n\n form_params = []\n local_var_files = {}\n\n body_params = None\n if 'body' in params:\n body_params = params['body']\n\n # HTTP header `Accept`\n header_params['Accept'] = self.api_client.\\\n select_header_accept(['application/json', 'application/yaml'])\n if not header_params['Accept']:\n del header_params['Accept']\n\n # HTTP header `Content-Type`\n header_params['Content-Type'] = self.api_client.\\\n select_header_content_type(['*/*'])\n\n # Authentication setting\n auth_settings = []\n\n response = self.api_client.call_api(resource_path, 'POST',\n path_params,\n query_params,\n header_params,\n body=body_params,\n post_params=form_params,\n files=local_var_files,\n response_type='V1Template',\n auth_settings=auth_settings,\n callback=params.get('callback'))\n return response","def test_createElementNS():\n\n assert not _do_test_raw(\"\"\"\n var x = \"foo\";\n x.createElementNS();\n x.createElementNS(\"foo\");\n x.createElementNS(\"foo\", \"bar\");\n \"\"\").failed()\n\n assert _do_test_raw(\"\"\"\n var x = \"foo\";\n x.createElementNS(\"foo\", \"script\");\n \"\"\").failed()\n\n assert _do_test_raw(\"\"\"\n var x = \"foo\";\n x.createElementNS(\"foo\", bar);\n \"\"\").failed()\n\n # Test for https://github.com/mozilla/amo-validator/issues/368\n assert not _do_test_raw(\"\"\"\n var x = \"foo\",\n nsXUL = \"http://www.mozilla.org/keymaster/gatekeeper/there.is.only.xul\";\n\n x.createElementNS(nsXUL, 'panelview')\n \"\"\").failed()\n\n # Creating a
'.join(log)\n error_msg = 'Exception caught attempting to store field \"%s\" with value \"%s\" into \\\n table \"%s\".
Method signature: %s
Full error log:
%s
Oracle says: %s' % \\\n (field_name, field_value, table_name, call_string, log_string, str(e))\n raise Exception(error_msg)\n finally:\n # Release the lock\n #lock.release()\n log.append('Lock released')","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def get_pymongo_type_string(\n self, field_type: Union[Type, str], collection_name: str\n ) -> str:\n try:\n type_string = PYMONGO_TYPE_TO_MONGO_TYPE[field_type]\n except KeyError:\n self.report.report_warning(\n collection_name, f\"unable to map type {field_type} to metadata schema\"\n )\n PYMONGO_TYPE_TO_MONGO_TYPE[field_type] = \"unknown\"\n type_string = \"unknown\"\n\n return type_string","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def dict_factory(cursor, row):\n d = {}\n for idx, col in enumerate(cursor.description):\n d[col[0]] = row[idx]\n return d","def db_type(self, field):\r\n if self.connection.settings_dict.get('STORE_RELATIONS_AS_DB_KEYS'):\r\n if field.primary_key or field.rel is not None:\r\n return 'key'\r\n\r\n # Primary keys were processed as db.Keys; for related fields\r\n # the db_type of primary key of the referenced model was used,\r\n # but RelatedAutoField type was not defined and resulted in\r\n # \"integer\" being used for relations to models with AutoFields.\r\n # TODO: Check with Positive/SmallIntegerField primary keys.\r\n else:\r\n if field.primary_key:\r\n return 'key'\r\n if field.rel is not None:\r\n related_field = field.rel.get_related_field()\r\n if related_field.get_internal_type() == 'AutoField':\r\n return 'integer'\r\n else:\r\n return related_field.db_type(connection=self.connection)\r\n\r\n db_type = field.db_type(connection=self.connection)\r\n\r\n # Override db_type of \"string\" fields according to indexing.\r\n if db_type in ('string', 'text'):\r\n indexes = get_model_indexes(field.model)\r\n if field.attname in indexes['indexed']:\r\n return 'string'\r\n elif field.attname in indexes['unindexed']:\r\n return 'text'\r\n\r\n return db_type","def dict_factory(cursor, row):\n rowdict = {}\n for idx, col in enumerate(cursor.description):\n rowdict[col[0]] = row[idx]\n return rowdict","def type_fields(self, res, op_item):\n result = []\n cast_func = {}\n header = res[0]\n for heading in header:\n cast_func[heading] = DataType.str\n\n if \"field_type\" in op_item:\n for f, p in findall(FIELD_TYPE_RE, op_item[\"field_type\"]):\n cast_func[p] = self.dt.get_func(f)\n first = True\n for row in res[1:]:\n new_row = []\n for idx in range(len(header)):\n\n heading = header[idx]\n cur_value = row[idx]\n if type(cur_value) is tuple:\n cur_value = cur_value[1]\n if heading == \"timespan\" and first:\n first = False\n new_row.append((cast_func[heading](cur_value), cur_value))\n\n result.append(new_row)\n\n return [header] + result","def get_column_type(cls, **kwargs: Any) -> Any: # pragma no cover\n return None","def extract_generic_credit_type(self, course_row):\n course_id = row[0]\n credit_type_res = {re.compile(\"Communication\"):\"CS\",\n re.compile(\"Natural Science\"):\"NS\",\n re.compile(\"Humanities\"):\"H\",\n re.compile(\"Performance\"):\"HP\",\n re.compile(\"Social\"):\"SS\",\n re.compile(\"Lab\"):\"NSL\",\n re.compile(\"Quant\"):\"QS\",\n re.compile(\"Elective\"):\"E\",\n re.compile(\"Diversity\"):\"DC\",\n re.compile(\"Prereq\"):\"PR\"}\n for credit_type_re in credit_type_res:\n if credit_type_re.search(course_id):\n type_string = credit_type_res[credit_type_re]\n credit_type = models.CreditType.objects.get(label_short=type_string)\n return credit_type","def specific(self):\n field_attr = field_registry.field_map[self.type]\n return getattr(self, field_attr, None)","def _fields(self, doclet):\n FIELD_TYPES = OrderedDict([('params', _params_formatter),\n ('properties', _params_formatter),\n ('exceptions', _exceptions_formatter),\n ('returns', _returns_formatter)])\n for field_name, callback in iteritems(FIELD_TYPES):\n for field in doclet.get(field_name, []):\n description = field.get('description', '')\n unwrapped = sub(r'[ \\t]*[\\r\\n]+[ \\t]*', ' ', description)\n yield callback(field, unwrapped)","def get_model_details(refobject):\n typename = type(refobject).__name__\n\n if typename in TYPES_TABLE:\n\n details = TYPES_TABLE[typename]\n\n elif isinstance(refobject, type):\n clrtype = clr.GetClrType(refobject)\n\n if clrtype.IsEnum:\n details = TYPES_TABLE['enumtype']\n\n elif clrtype.IsClass:\n if clrtype.FullName.startswith('Autodesk.Revit.DB'):\n details = TYPES_TABLE['revitclass']\n\n else:\n details = TYPES_TABLE['classtype']\n\n elif clrtype.IsInterface:\n details = TYPES_TABLE['interface']\n\n elif clrtype.FullName in SYS_TYPES:\n details = TYPES_TABLE['systype']\n\n elif clrtype.FullName in WIN_TYPES:\n details = TYPES_TABLE['wintype']\n\n else:\n details = TYPES_TABLE['unknown']\n logger.debug('TODO get_model_details for CLR/type: {} ({})'.format(\n typename, refobject))\n\n # match all list/collection types\n elif is_iterable(refobject):\n details = TYPES_TABLE['listtype']\n\n # match sub enum types\n elif clr.GetClrType(type(refobject)).IsEnum:\n details = TYPES_TABLE['subenumtype']\n\n # match sub class types\n elif clr.GetClrType(type(refobject)).IsClass:\n\n if clr.GetClrType(type(refobject)).FullName == 'Autodesk.Revit.DB.Parameter':\n details = TYPES_TABLE['revitparameter']\n\n elif clr.GetClrType(type(refobject)).FullName.startswith('Autodesk.Revit.DB'):\n details = TYPES_TABLE['revitclass']\n else:\n details = TYPES_TABLE['subclasstype']\n\n elif clr.GetClrType(type(refobject)).IsInterface:\n details = TYPES_TABLE['interface']\n\n elif clr.GetClrType(type(refobject)).FullName in SYS_TYPES:\n details = TYPES_TABLE['systype']\n\n elif clr.GetClrType(type(refobject)).FullName in WIN_TYPES:\n details = TYPES_TABLE['wintype']\n\n else:\n details = TYPES_TABLE['unknown']\n logger.debug('TODO get_model_details for : {} ({})'.format(\n typename, refobject))\n\n return details","def init_fields(self):\n result = self.connection.execute('pragma table_info(files)')\n rows = result.fetchall()\n self.fields = [Field(row) for row in rows[4:]]\n result = self.connection.execute('select _keyword from keywords')\n rows = result.fetchall()\n self.keywords = [row[0] for row in rows]","def field(self) -> 'outputs.PreventionStoredInfoTypeLargeCustomDictionaryBigQueryFieldField':\n return pulumi.get(self, \"field\")","def south_field_triple(self):\n # We'll just introspect ourselves, since we inherit.\n from south.modelsinspector import introspector\n field_class = \"django.db.models.fields.TextField\"\n args, kwargs = introspector(self)\n # That's our definition!\n return (field_class, args, kwargs)","async def get_schema_info(self, collection):\n await self.ensure_collection(collection)\n try:\n # Luke handler is not supported in API v2 yet.\n # /v2/collections/
'.join(log)\\n error_msg = 'Exception caught attempting to store field \\\"%s\\\" with value \\\"%s\\\" into \\\\\\n table \\\"%s\\\".
Method signature: %s
Full error log:
%s
Oracle says: %s' % \\\\\\n (field_name, field_value, table_name, call_string, log_string, str(e))\\n raise Exception(error_msg)\\n finally:\\n # Release the lock\\n #lock.release()\\n log.append('Lock released')\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def get_pymongo_type_string(\\n self, field_type: Union[Type, str], collection_name: str\\n ) -> str:\\n try:\\n type_string = PYMONGO_TYPE_TO_MONGO_TYPE[field_type]\\n except KeyError:\\n self.report.report_warning(\\n collection_name, f\\\"unable to map type {field_type} to metadata schema\\\"\\n )\\n PYMONGO_TYPE_TO_MONGO_TYPE[field_type] = \\\"unknown\\\"\\n type_string = \\\"unknown\\\"\\n\\n return type_string\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def dict_factory(cursor, row):\\n d = {}\\n for idx, col in enumerate(cursor.description):\\n d[col[0]] = row[idx]\\n return d\",\n \"def db_type(self, field):\\r\\n if self.connection.settings_dict.get('STORE_RELATIONS_AS_DB_KEYS'):\\r\\n if field.primary_key or field.rel is not None:\\r\\n return 'key'\\r\\n\\r\\n # Primary keys were processed as db.Keys; for related fields\\r\\n # the db_type of primary key of the referenced model was used,\\r\\n # but RelatedAutoField type was not defined and resulted in\\r\\n # \\\"integer\\\" being used for relations to models with AutoFields.\\r\\n # TODO: Check with Positive/SmallIntegerField primary keys.\\r\\n else:\\r\\n if field.primary_key:\\r\\n return 'key'\\r\\n if field.rel is not None:\\r\\n related_field = field.rel.get_related_field()\\r\\n if related_field.get_internal_type() == 'AutoField':\\r\\n return 'integer'\\r\\n else:\\r\\n return related_field.db_type(connection=self.connection)\\r\\n\\r\\n db_type = field.db_type(connection=self.connection)\\r\\n\\r\\n # Override db_type of \\\"string\\\" fields according to indexing.\\r\\n if db_type in ('string', 'text'):\\r\\n indexes = get_model_indexes(field.model)\\r\\n if field.attname in indexes['indexed']:\\r\\n return 'string'\\r\\n elif field.attname in indexes['unindexed']:\\r\\n return 'text'\\r\\n\\r\\n return db_type\",\n \"def dict_factory(cursor, row):\\n rowdict = {}\\n for idx, col in enumerate(cursor.description):\\n rowdict[col[0]] = row[idx]\\n return rowdict\",\n \"def type_fields(self, res, op_item):\\n result = []\\n cast_func = {}\\n header = res[0]\\n for heading in header:\\n cast_func[heading] = DataType.str\\n\\n if \\\"field_type\\\" in op_item:\\n for f, p in findall(FIELD_TYPE_RE, op_item[\\\"field_type\\\"]):\\n cast_func[p] = self.dt.get_func(f)\\n first = True\\n for row in res[1:]:\\n new_row = []\\n for idx in range(len(header)):\\n\\n heading = header[idx]\\n cur_value = row[idx]\\n if type(cur_value) is tuple:\\n cur_value = cur_value[1]\\n if heading == \\\"timespan\\\" and first:\\n first = False\\n new_row.append((cast_func[heading](cur_value), cur_value))\\n\\n result.append(new_row)\\n\\n return [header] + result\",\n \"def get_column_type(cls, **kwargs: Any) -> Any: # pragma no cover\\n return None\",\n \"def extract_generic_credit_type(self, course_row):\\n course_id = row[0]\\n credit_type_res = {re.compile(\\\"Communication\\\"):\\\"CS\\\",\\n re.compile(\\\"Natural Science\\\"):\\\"NS\\\",\\n re.compile(\\\"Humanities\\\"):\\\"H\\\",\\n re.compile(\\\"Performance\\\"):\\\"HP\\\",\\n re.compile(\\\"Social\\\"):\\\"SS\\\",\\n re.compile(\\\"Lab\\\"):\\\"NSL\\\",\\n re.compile(\\\"Quant\\\"):\\\"QS\\\",\\n re.compile(\\\"Elective\\\"):\\\"E\\\",\\n re.compile(\\\"Diversity\\\"):\\\"DC\\\",\\n re.compile(\\\"Prereq\\\"):\\\"PR\\\"}\\n for credit_type_re in credit_type_res:\\n if credit_type_re.search(course_id):\\n type_string = credit_type_res[credit_type_re]\\n credit_type = models.CreditType.objects.get(label_short=type_string)\\n return credit_type\",\n \"def specific(self):\\n field_attr = field_registry.field_map[self.type]\\n return getattr(self, field_attr, None)\",\n \"def _fields(self, doclet):\\n FIELD_TYPES = OrderedDict([('params', _params_formatter),\\n ('properties', _params_formatter),\\n ('exceptions', _exceptions_formatter),\\n ('returns', _returns_formatter)])\\n for field_name, callback in iteritems(FIELD_TYPES):\\n for field in doclet.get(field_name, []):\\n description = field.get('description', '')\\n unwrapped = sub(r'[ \\\\t]*[\\\\r\\\\n]+[ \\\\t]*', ' ', description)\\n yield callback(field, unwrapped)\",\n \"def get_model_details(refobject):\\n typename = type(refobject).__name__\\n\\n if typename in TYPES_TABLE:\\n\\n details = TYPES_TABLE[typename]\\n\\n elif isinstance(refobject, type):\\n clrtype = clr.GetClrType(refobject)\\n\\n if clrtype.IsEnum:\\n details = TYPES_TABLE['enumtype']\\n\\n elif clrtype.IsClass:\\n if clrtype.FullName.startswith('Autodesk.Revit.DB'):\\n details = TYPES_TABLE['revitclass']\\n\\n else:\\n details = TYPES_TABLE['classtype']\\n\\n elif clrtype.IsInterface:\\n details = TYPES_TABLE['interface']\\n\\n elif clrtype.FullName in SYS_TYPES:\\n details = TYPES_TABLE['systype']\\n\\n elif clrtype.FullName in WIN_TYPES:\\n details = TYPES_TABLE['wintype']\\n\\n else:\\n details = TYPES_TABLE['unknown']\\n logger.debug('TODO get_model_details for CLR/type: {} ({})'.format(\\n typename, refobject))\\n\\n # match all list/collection types\\n elif is_iterable(refobject):\\n details = TYPES_TABLE['listtype']\\n\\n # match sub enum types\\n elif clr.GetClrType(type(refobject)).IsEnum:\\n details = TYPES_TABLE['subenumtype']\\n\\n # match sub class types\\n elif clr.GetClrType(type(refobject)).IsClass:\\n\\n if clr.GetClrType(type(refobject)).FullName == 'Autodesk.Revit.DB.Parameter':\\n details = TYPES_TABLE['revitparameter']\\n\\n elif clr.GetClrType(type(refobject)).FullName.startswith('Autodesk.Revit.DB'):\\n details = TYPES_TABLE['revitclass']\\n else:\\n details = TYPES_TABLE['subclasstype']\\n\\n elif clr.GetClrType(type(refobject)).IsInterface:\\n details = TYPES_TABLE['interface']\\n\\n elif clr.GetClrType(type(refobject)).FullName in SYS_TYPES:\\n details = TYPES_TABLE['systype']\\n\\n elif clr.GetClrType(type(refobject)).FullName in WIN_TYPES:\\n details = TYPES_TABLE['wintype']\\n\\n else:\\n details = TYPES_TABLE['unknown']\\n logger.debug('TODO get_model_details for : {} ({})'.format(\\n typename, refobject))\\n\\n return details\",\n \"def init_fields(self):\\n result = self.connection.execute('pragma table_info(files)')\\n rows = result.fetchall()\\n self.fields = [Field(row) for row in rows[4:]]\\n result = self.connection.execute('select _keyword from keywords')\\n rows = result.fetchall()\\n self.keywords = [row[0] for row in rows]\",\n \"def field(self) -> 'outputs.PreventionStoredInfoTypeLargeCustomDictionaryBigQueryFieldField':\\n return pulumi.get(self, \\\"field\\\")\",\n \"def south_field_triple(self):\\n # We'll just introspect ourselves, since we inherit.\\n from south.modelsinspector import introspector\\n field_class = \\\"django.db.models.fields.TextField\\\"\\n args, kwargs = introspector(self)\\n # That's our definition!\\n return (field_class, args, kwargs)\",\n \"async def get_schema_info(self, collection):\\n await self.ensure_collection(collection)\\n try:\\n # Luke handler is not supported in API v2 yet.\\n # /v2/collections/
\n Hello %s. Please click the link to activate your account.
\n %s
\n\n Thank you,
\n\n The Team\n
\\n Hello %s. Please click the link to activate your account.
\\n %s
\\n\\n Thank you,
\\n\\n The Team\\n