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def _calc_errors(actual, expected): base = max(abs(actual), abs(expected)) abs_err = abs((actual - expected)) rel_err = ((abs_err / base) if base else float('inf')) return (abs_err, rel_err)
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return the absolute and relative errors between two numbers .
train
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def output(): return s3_rest_controller()
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format the data for printing stage information from the overstate system .
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def test_contravariance(): print 'TODO'
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URL - generic interface - generic delegate only reference types should work .
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false
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def user_followee_count(context, data_dict): return _followee_count(context, data_dict, context['model'].UserFollowingUser)
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return the number of users that are followed by the given user .
train
false
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@flake8ext def check_no_contextlib_nested(logical_line, filename): msg = 'N324: contextlib.nested is deprecated. With Python 2.7 and later the with-statement supports multiple nested objects. See https://docs.python.org/2/library/contextlib.html#contextlib.nested for more information.' if checks.contextlib_nested.match(logical_line): (yield (0, msg))
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n324 - dont use contextlib .
train
false
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def volume_admin_metadata_get(context, volume_id): return IMPL.volume_admin_metadata_get(context, volume_id)
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get all administration metadata for a volume .
train
false
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def enable_mpl_offline(resize=False, strip_style=False, verbose=False, show_link=True, link_text='Export to plot.ly', validate=True): init_notebook_mode() ip = ipython.core.getipython.get_ipython() formatter = ip.display_formatter.formatters['text/html'] formatter.for_type(matplotlib.figure.Figure, (lambda fig: iplot_mpl(fig, resize, strip_style, verbose, show_link, link_text, validate)))
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convert mpl plots to locally hosted html documents .
train
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def server_poweroff(host=None, admin_username=None, admin_password=None, module=None): return __execute_cmd('serveraction powerdown', host=host, admin_username=admin_username, admin_password=admin_password, module=module)
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powers down the managed server .
train
true
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@download_tool('urllib2') def urllib2_download(client, download_url, filename, resuming=False): assert (not resuming) print 'Downloading', download_url, 'to', filename, '...' request = urllib2.Request(download_url, headers={'Cookie': ('gdriveid=' + client.get_gdriveid())}) response = urllib2.urlopen(request) import shutil with open(filename, 'wb') as output: shutil.copyfileobj(response, output)
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in the case you dont even have wget .
train
false
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def PRE(text): return (('<pre>' + escape(text)) + '</pre>')
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munging to turn a method name into a pre-hook-method-name .
train
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def test_ordered_dict_order(): schema = vol.Schema(cv.ordered_dict(int, cv.string)) val = OrderedDict() val['first'] = 1 val['second'] = 2 validated = schema(val) assert isinstance(validated, OrderedDict) assert (['first', 'second'] == list(validated.keys()))
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test ordered_dict validator .
train
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def print_to_stdout(color, str_out): col = getattr(Fore, color) _lazy_colorama_init() if (not is_py3): str_out = str_out.encode(encoding, 'replace') print ((col + str_out) + Fore.RESET)
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the default debug function that prints to standard out .
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false
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def make_templates(): if (not os.path.exists('email')): os.makedirs('email') for path in glob.glob(os.path.join(MO_DIR, '*')): lng = os.path.split(path)[1] if (lng != 'en'): print ('Create email template for %s' % lng) trans = gettext.translation(DOMAIN_E, MO_DIR, [lng], fallback=False, codeset='latin-1') trans.install(unicode=True, names=['lgettext']) translate_tmpl('email', lng) translate_tmpl('rss', lng) translate_tmpl('badfetch', lng) mo_path = os.path.normpath(('%s/%s%s/%s.mo' % (MO_DIR, path, MO_LOCALE, DOMAIN_E))) if os.path.exists(mo_path): os.remove(mo_path)
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create email templates .
train
false
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@not_implemented_for('directed') @not_implemented_for('multigraph') def min_edge_cover(G, matching_algorithm=None): if (nx.number_of_isolates(G) > 0): raise nx.NetworkXException('Graph has a node with no edge incident on it, so no edge cover exists.') if (matching_algorithm is None): matching_algorithm = partial(nx.max_weight_matching, maxcardinality=True) maximum_matching = matching_algorithm(G) min_cover = set(maximum_matching.items()) uncovered_nodes = (set(G) - {v for (u, v) in min_cover}) for v in uncovered_nodes: u = arbitrary_element(G[v]) min_cover.add((u, v)) min_cover.add((v, u)) return min_cover
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returns a set of edges which constitutes the minimum edge cover of the graph .
train
false
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@hook.command def imdb(text, bot): headers = {'User-Agent': bot.user_agent} strip = text.strip() if id_re.match(strip): params = {'i': strip} else: params = {'t': strip} request = requests.get('http://www.omdbapi.com/', params=params, headers=headers) content = request.json() if (content.get('Error', None) == 'Movie not found!'): return 'Movie not found!' elif (content['Response'] == 'True'): content['URL'] = 'http://www.imdb.com/title/{}'.format(content['imdbID']) out = '\x02%(Title)s\x02 (%(Year)s) (%(Genre)s): %(Plot)s' if (content['Runtime'] != 'N/A'): out += ' \x02%(Runtime)s\x02.' if ((content['imdbRating'] != 'N/A') and (content['imdbVotes'] != 'N/A')): out += ' \x02%(imdbRating)s/10\x02 with \x02%(imdbVotes)s\x02 votes.' out += ' %(URL)s' return (out % content) else: return 'Unknown error.'
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imdb <movie> - gets information about <movie> from imdb .
train
false
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def should_ignore_paypal(): return (settings.DEBUG and ('sandbox' not in settings.PAYPAL_PERMISSIONS_URL))
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returns whether to skip paypal communications for development purposes or not .
train
false
31,511
def emf_unwrap(raw, verbose=0): w = EMF(raw, verbose=verbose) if (not w.has_raster_image): raise ValueError(u'No raster image found in the EMF') return w.to_png()
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return the largest embedded raster image in the emf .
train
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def libvlc_vlm_set_mux(p_instance, psz_name, psz_mux): f = (_Cfunctions.get('libvlc_vlm_set_mux', None) or _Cfunction('libvlc_vlm_set_mux', ((1,), (1,), (1,)), None, ctypes.c_int, Instance, ctypes.c_char_p, ctypes.c_char_p)) return f(p_instance, psz_name, psz_mux)
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set a medias vod muxer .
train
true
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def rmtree(dirname): excs = [] try: os.chmod(dirname, ((stat.S_IWRITE | stat.S_IEXEC) | stat.S_IREAD)) for f in os.listdir(dirname): fullname = os.path.join(dirname, f) if os.path.isdir(fullname): rm_dir(fullname) else: remove(fullname) os.rmdir(dirname) except EnvironmentError as le: if (((le.args[0] != 2) and (le.args[0] != 3)) or (le.args[0] != errno.ENOENT)): excs.append(le) except Exception as le: excs.append(le) if os.path.exists(dirname): if (len(excs) == 1): raise excs[0] if (len(excs) == 0): raise OSError, 'Failed to remove dir for unknown reason.' raise OSError, excs
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recursively delete a directory tree .
train
false
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def pslist(addr_space): for p in get_kdbg(addr_space).processes(): (yield p)
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a generator for _eprocess objects .
train
false
31,517
def Pdfs(pdfs, **options): for pdf in pdfs: Pdf(pdf, **options)
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plots a sequence of pdfs .
train
false
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def post_process_filtered_equals(opcodes): cur_chunk = None for (tag, i1, i2, j1, j2, meta) in opcodes: if (((tag == u'equal') and (not meta.get(u'indentation_changes'))) or (tag == u'filtered-equal')): if cur_chunk: i1 = cur_chunk[1] j1 = cur_chunk[3] meta = cur_chunk[5] cur_chunk = (u'equal', i1, i2, j1, j2, meta) else: if cur_chunk: (yield cur_chunk) cur_chunk = None (yield (tag, i1, i2, j1, j2, meta)) if cur_chunk: (yield cur_chunk)
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post-processes filtered-equal and equal chunks from interdiffs .
train
false
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def _MakeDosListIntoYaml(dos_list): statements = ['blacklist:'] for entry in dos_list: statements += entry.ToYaml() return ('\n'.join(statements) + '\n')
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converts yaml statement list of blacklisted ips into a string .
train
false
31,523
def tree2conllstr(t): lines = [u' '.join(token) for token in tree2conlltags(t)] return u'\n'.join(lines)
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return a multiline string where each line contains a word .
train
false
31,524
def getSegmentsFromLoopListsPoints(loopLists, pointBegin, pointEnd): normalizedSegment = (pointEnd - pointBegin) normalizedSegmentLength = abs(normalizedSegment) if (normalizedSegmentLength == 0.0): return [] normalizedSegment /= normalizedSegmentLength segmentYMirror = complex(normalizedSegment.real, (- normalizedSegment.imag)) pointBeginRotated = (segmentYMirror * pointBegin) pointEndRotated = (segmentYMirror * pointEnd) rotatedLoopLists = [] for loopList in loopLists: rotatedLoopList = [] rotatedLoopLists.append(rotatedLoopList) for loop in loopList: rotatedLoop = euclidean.getPointsRoundZAxis(segmentYMirror, loop) rotatedLoopList.append(rotatedLoop) xIntersectionIndexList = [] xIntersectionIndexList.append(euclidean.XIntersectionIndex((-1), pointBeginRotated.real)) xIntersectionIndexList.append(euclidean.XIntersectionIndex((-1), pointEndRotated.real)) euclidean.addXIntersectionIndexesFromLoopListsY(rotatedLoopLists, xIntersectionIndexList, pointBeginRotated.imag) segments = euclidean.getSegmentsFromXIntersectionIndexes(xIntersectionIndexList, pointBeginRotated.imag) for segment in segments: for endpoint in segment: endpoint.point *= normalizedSegment return segments
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get endpoint segments from the beginning and end of a line segment .
train
false
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def test_strange_inheritance(): class m(StrangeOverrides, ): def SomeMethodWithContext(self, arg): AreEqual(arg, 'abc') def ParamsMethodWithContext(self, *arg): AreEqual(arg, ('abc', 'def')) def ParamsIntMethodWithContext(self, *arg): AreEqual(arg, (2, 3)) a = m() a.CallWithContext('abc') a.CallParamsWithContext('abc', 'def') a.CallIntParamsWithContext(2, 3)
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verify that overriding strange methods doesnt flow caller context through .
train
false
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def bincount(x, weights=None, minlength=None, assert_nonneg=False): if (x.ndim != 1): raise TypeError('Inputs must be of dimension 1.') if assert_nonneg: from theano.tensor.opt import Assert assert_op = Assert('Input to bincount has negative values!') x = assert_op(x, theano.tensor.all((x >= 0))) max_value = theano.tensor.cast((x.max() + 1), 'int64') if (minlength is not None): max_value = theano.tensor.maximum(max_value, minlength) if (weights is None): out = theano.tensor.zeros([max_value], dtype=x.dtype) out = theano.tensor.advanced_inc_subtensor1(out, 1, x) else: out = theano.tensor.zeros([max_value], dtype=weights.dtype) out = theano.tensor.advanced_inc_subtensor1(out, weights, x) return out
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count number of occurrences of each value in array of ints .
train
false
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def randu(nchars): return ''.join(np.random.choice(RANDU_CHARS, nchars))
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generate one random unicode string .
train
false
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def swig_library(name, srcs=[], deps=[], warning='', java_package='', java_lib_packed=False, optimize=[], extra_swigflags=[], **kwargs): target = SwigLibrary(name, srcs, deps, warning, java_package, java_lib_packed, optimize, extra_swigflags, blade.blade, kwargs) blade.blade.register_target(target)
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swig_library target .
train
false
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def build_summary(layout, level=1): assert (level > 0) level -= 1 summary = List(klass=u'summary') for child in layout.children: if (not isinstance(child, Section)): continue label = layout_title(child) if ((not label) and (not child.id)): continue if (not child.id): child.id = label.replace(' ', '-') node = Link((u'#' + child.id), label=(label or child.id)) if (level and [n for n in child.children if isinstance(n, Section)]): node = Paragraph([node, build_summary(child, level)]) summary.append(node) return summary
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make a summary for the report .
train
false
31,532
def string_to_rank(text, maxint=sys.maxint): rs = CleanText(text, banned=CleanText.NONALNUM).clean.lower() rank = 0.0 frac = 1.0 for pos in range(0, min(15, len(rs))): rank += (frac * (int(rs[pos], 36) / (36.0 + (0.09 * pos)))) frac *= (1.0 / (36 - pos)) return (long((rank * (maxint - 100))) + min(100, len(text)))
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approximate lexographical order with an int .
train
false
31,533
def get_int_property(device_type, property, cf_number_type): key = cf.CFStringCreateWithCString(kCFAllocatorDefault, property.encode('mac_roman'), kCFStringEncodingMacRoman) CFContainer = iokit.IORegistryEntryCreateCFProperty(device_type, key, kCFAllocatorDefault, 0) if CFContainer: if (cf_number_type == kCFNumberSInt32Type): number = ctypes.c_uint32() elif (cf_number_type == kCFNumberSInt16Type): number = ctypes.c_uint16() cf.CFNumberGetValue(CFContainer, cf_number_type, ctypes.byref(number)) cf.CFRelease(CFContainer) return number.value return None
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search the given device for the specified string property .
train
false
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def write_string_table(string_table): temp_buffer = StringIO() doc = XMLGenerator(temp_buffer, 'utf-8') start_tag(doc, 'sst', {'xmlns': 'http://schemas.openxmlformats.org/spreadsheetml/2006/main', 'uniqueCount': ('%d' % len(string_table))}) strings_to_write = sorted(iter(string_table.items()), key=(lambda pair: pair[1])) for key in [pair[0] for pair in strings_to_write]: start_tag(doc, 'si') if (key.strip() != key): attr = {'xml:space': 'preserve'} else: attr = {} tag(doc, 't', attr, key) end_tag(doc, 'si') end_tag(doc, 'sst') string_table_xml = temp_buffer.getvalue() temp_buffer.close() return string_table_xml
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write the string table xml .
train
false
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def _tgrep_node_literal_value(node): return (node.label() if _istree(node) else text_type(node))
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gets the string value of a given parse tree node .
train
false
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def share_transfer(cookie, tokens, shareid, uk, filelist, dest, upload_mode): ondup = const.UPLOAD_ONDUP[upload_mode] url = ''.join([const.PAN_URL, 'share/transfer?app_id=250528&channel=chunlei&clienttype=0&web=1', '&bdstoken=', tokens['bdstoken'], '&from=', uk, '&shareid=', shareid, '&ondup=', ondup, '&async=1']) data = ''.join(['path=', encoder.encode_uri_component(dest), '&filelist=', encoder.encode_uri_component(json.dumps(filelist))]) req = net.urlopen(url, headers={'Cookie': cookie.header_output(), 'Content-Type': const.CONTENT_FORM_UTF8}, data=data.encode()) if req: content = req.data.decode() return json.loads(content) else: return None
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uk - 其他用户的uk filelist - 要转移文件的列表 .
train
true
31,539
def strip_sys_meta_prefix(server_type, key): return key[len(get_sys_meta_prefix(server_type)):]
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removes the system metadata prefix for a given server type from the start of a header key .
train
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@user_registered.connect def replace_unclaimed_user_with_registered(user): unreg_user_info = session.data.get('unreg_user') if unreg_user_info: unreg_user = User.load(unreg_user_info['uid']) pid = unreg_user_info['pid'] node = Node.load(pid) node.replace_contributor(old=unreg_user, new=user) node.save() status.push_status_message('Successfully claimed contributor.', kind='success', trust=False)
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listens for the user_registered signal .
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def _calculate_meta(meta, bases): winner = meta for base in bases: base_meta = type(base) if issubclass(winner, base_meta): continue if issubclass(base_meta, winner): winner = base_meta continue raise TypeError('metaclass conflict: the metaclass of a derived class must be a (non-strict) subclass of the metaclasses of all its bases') return winner
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calculate the most derived metaclass .
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def dist_sum(D1, D2): (X1, W1) = D1 (X2, W2) = D2 X = numpy.r_[(X1, X2)] W = numpy.r_[(W1, W2)] sort_ind = numpy.argsort(X) (X, W) = (X[sort_ind], W[sort_ind]) (unique, uniq_index) = numpy.unique(X, return_index=True) spans = numpy.diff(numpy.r_[(uniq_index, len(X))]) W = [numpy.sum(W[start:(start + span)]) for (start, span) in zip(uniq_index, spans)] W = numpy.array(W) assert (W.shape[0] == unique.shape[0]) return (unique, W)
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a sum of two continuous distributions .
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def egd(path, bytes=_unspecified): if (not isinstance(path, _builtin_bytes)): raise TypeError('path must be a byte string') if (bytes is _unspecified): bytes = 255 elif (not isinstance(bytes, int)): raise TypeError('bytes must be an integer') return _lib.RAND_egd_bytes(path, bytes)
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query an entropy gathering daemon for random data and add it to the prng .
train
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def _ToDbApiException(sql_exception): exception = _ERROR_CODE_TO_EXCEPTION.get(sql_exception.code) if (not exception): if (sql_exception.code < 1000): exception = InternalError else: exception = OperationalError return exception(sql_exception.code, sql_exception.message)
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returns a db-api exception type appropriate for the given sql_exception .
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def _asarray_square(A): A = np.asarray(A) if ((len(A.shape) != 2) or (A.shape[0] != A.shape[1])): raise ValueError('expected square array_like input') return A
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wraps asarray with the extra requirement that the input be a square matrix .
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def register_shape_i_c_code(typ, code, check_input, version=()): Shape_i.c_code_and_version[typ] = (code, check_input, version)
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tell shape_i how to generate c code for a theano type .
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def test_unsafe_url(): eq_('All your{"<a href="http://xx.yy.com/grover.png" rel="nofollow">xx.yy.com/grover.png</a>"}base are', linkify('All your{"xx.yy.com/grover.png"}base are'))
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any unsafe char in the path should end url scanning .
train
false
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def right_multiply(J, d, copy=True): if (copy and (not isinstance(J, LinearOperator))): J = J.copy() if issparse(J): J.data *= d.take(J.indices, mode='clip') elif isinstance(J, LinearOperator): J = right_multiplied_operator(J, d) else: J *= d return J
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compute j diag(d) .
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def get_access_token_from_code(code, redirect_uri, app_id, app_secret): args = {'code': code, 'redirect_uri': redirect_uri, 'client_id': app_id, 'client_secret': app_secret} response = urllib.urlopen((('https://graph.facebook.com/oauth/access_token' + '?') + urllib.urlencode(args))).read() query_str = parse_qs(response) if ('access_token' in query_str): result = {'access_token': query_str['access_token'][0]} if ('expires' in query_str): result['expires'] = query_str['expires'][0] return result else: response = json.loads(response) raise GraphAPIError(response)
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get an access token from the "code" returned from an oauth dialog .
train
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def get_thumbnailer(obj, relative_name=None): if hasattr(obj, 'easy_thumbnails_thumbnailer'): return obj.easy_thumbnails_thumbnailer if isinstance(obj, Thumbnailer): return obj elif isinstance(obj, FieldFile): if (not relative_name): relative_name = obj.name return ThumbnailerFieldFile(obj.instance, obj.field, relative_name) source_storage = None if isinstance(obj, six.string_types): relative_name = obj obj = None if (not relative_name): raise ValueError('If object is not a FieldFile or Thumbnailer instance, the relative name must be provided') if isinstance(obj, File): obj = obj.file if (isinstance(obj, Storage) or (obj == default_storage)): source_storage = obj obj = None return Thumbnailer(file=obj, name=relative_name, source_storage=source_storage, remote_source=(obj is not None))
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get a :class:thumbnailer for a source file .
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def programme(): mode = session.s3.hrm.mode if (not auth.s3_has_role(ADMIN)): s3.filter = auth.filter_by_root_org(s3db.hrm_programme) def prep(r): if (mode is not None): auth.permission.fail() if (r.component_name == 'person'): s3db.configure('hrm_programme_hours', list_fields=['person_id', 'training', 'programme_id', 'date', 'hours']) return True s3.prep = prep return s3_rest_controller('hrm', resourcename, csv_stylesheet=('hrm', 'programme.xsl'), csv_template=('hrm', 'programme'), rheader=s3db.hrm_rheader)
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volunteer programmes controller .
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def addAlongWay(begin, distance, end, loop): endMinusBegin = (end - begin) endMinusBeginLength = abs(endMinusBegin) if (endMinusBeginLength <= 0.0): return alongWayMultiplier = (distance / endMinusBeginLength) loop.append((begin + (alongWayMultiplier * endMinusBegin)))
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get the beveled rectangle .
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def maximum_independent_set(G): (iset, _) = clique_removal(G) return iset
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return an approximate maximum independent set .
train
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@parametrize('table', tables.mapped_classes) def test_identifiers_with_names(table): for translation_class in table.translation_classes: if hasattr(translation_class, 'name'): assert hasattr(table, 'identifier'), table
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test that named tables have identifiers .
train
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def resolve_variable(path, context): return Variable(path).resolve(context)
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returns the resolved variable .
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def _update_image(facebook_id, image_url): image_name = ('fb_image_%s.jpg' % facebook_id) image_temp = NamedTemporaryFile() try: image_response = urllib2.urlopen(image_url) except AttributeError: image_response = urllib.request.urlopen(image_url) image_content = image_response.read() image_temp.write(image_content) http_message = image_response.info() image_size = len(image_content) try: content_type = http_message.type except AttributeError: content_type = http_message.get_content_type() image_file = InMemoryUploadedFile(file=image_temp, name=image_name, field_name='image', content_type=content_type, size=image_size, charset=None) image_file.seek(0) image_temp.flush() return (image_name, image_file)
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updates the user profiles image to the given image url unfortunately this is quite a pain to get right with django suggestions to improve this are welcome .
train
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def _parse_dist_kw(dist, enforce_subclass=True): if isinstance(dist, rv_generic): pass elif isinstance(dist, string_types): try: dist = getattr(distributions, dist) except AttributeError: raise ValueError(('%s is not a valid distribution name' % dist)) elif enforce_subclass: msg = '`dist` should be a stats.distributions instance or a string with the name of such a distribution.' raise ValueError(msg) return dist
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parse dist keyword .
train
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def _find_impl(cls, registry): mro = _compose_mro(cls, registry.keys()) match = None for t in mro: if (match is not None): if ((t in registry) and (t not in cls.__mro__) and (match not in cls.__mro__) and (not issubclass(match, t))): raise RuntimeError(u'Ambiguous dispatch: {0} or {1}'.format(match, t)) break if (t in registry): match = t return registry.get(match)
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returns the best matching implementation from *registry* for type *cls* .
train
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def do_crypt_parameters_and_properties(): ctxt = context.get_admin_context() prev_encryption_key = CONF.command.previous_encryption_key if (CONF.command.crypt_operation == 'encrypt'): db_api.encrypt_parameters_and_properties(ctxt, prev_encryption_key, CONF.command.verbose_update_params) elif (CONF.command.crypt_operation == 'decrypt'): db_api.decrypt_parameters_and_properties(ctxt, prev_encryption_key, CONF.command.verbose_update_params)
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encrypt/decrypt hidden parameters and resource properties data .
train
false
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def add_bought_with_relations_for_product(product_id, max_quantity=10): order_ids_to_check = OrderLine.objects.filter(product_id=product_id).values_list('order_id', flat=True) related_product_ids_and_quantities = OrderLine.objects.exclude(product_id=product_id).filter(type=OrderLineType.PRODUCT, order_id__in=set(order_ids_to_check)).values('product_id').annotate(total_quantity=Sum('quantity')).order_by('-total_quantity')[:max_quantity] for product_data in related_product_ids_and_quantities: ProductCrossSell.objects.create(product1_id=product_id, product2_id=product_data['product_id'], weight=product_data['total_quantity'], type=ProductCrossSellType.BOUGHT_WITH)
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add productcrosssell objects with type productcrossselltype .
train
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def print_line(line, highlight=False): global lineno try: if highlight: line += (' ' * (win.getmaxyx()[1] - len(line))) win.addstr(lineno, 0, line, curses.A_REVERSE) else: win.addstr(lineno, 0, line, 0) except curses.error: lineno = 0 win.refresh() raise else: lineno += 1
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a thin wrapper around cursess addstr() .
train
false
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def _csc_gen_triples(A): ncols = A.shape[1] (data, indices, indptr) = (A.data, A.indices, A.indptr) for i in range(ncols): for j in range(indptr[i], indptr[(i + 1)]): (yield (indices[j], i, data[j]))
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converts a scipy sparse matrix in **compressed sparse column** format to an iterable of weighted edge triples .
train
false
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def class_mock(request, q_class_name, autospec=True, **kwargs): _patch = patch(q_class_name, autospec=autospec, **kwargs) request.addfinalizer(_patch.stop) return _patch.start()
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return a mock patching the class with qualified name *q_class_name* .
train
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def _add_flags(flags, new_flags): flags = _get_flags(flags) new_flags = _get_flags(new_flags) return (flags | new_flags)
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combine flags and new_flags .
train
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def get_tag_from_other_config(bridge, port_name): other_config = None try: other_config = bridge.db_get_val('Port', port_name, 'other_config') return int(other_config['tag']) except (KeyError, TypeError, ValueError): raise exceptions.OVSFWTagNotFound(port_name=port_name, other_config=other_config)
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return tag stored in ovsdb other_config metadata .
train
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def increment_odd(x): raise NotImplementedError('TODO: implement the function.')
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x: a theano vector returns: y: a theano vector equal to x .
train
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def convertContainerElementNode(elementNode, geometryOutput, xmlObject): elementNode.linkObject(xmlObject) matrix.getBranchMatrixSetElementNode(elementNode) elementNode.getXMLProcessor().createChildNodes(geometryOutput['shapes'], elementNode)
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convert the xml element to a group xml element .
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def _ra_pid_for(dev): pid_file = _ra_file(dev, 'pid') if os.path.exists(pid_file): with open(pid_file, 'r') as f: return int(f.read())
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returns the pid for prior radvd instance for a bridge/device .
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def sm_backend_conf_get_all(context): return IMPL.sm_backend_conf_get_all(context)
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get all sm backend configs .
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def global_avg_pool(incoming, name='GlobalAvgPool'): input_shape = utils.get_incoming_shape(incoming) assert (len(input_shape) == 4), 'Incoming Tensor shape must be 4-D' with tf.name_scope(name): inference = tf.reduce_mean(incoming, [1, 2]) tf.add_to_collection(((tf.GraphKeys.LAYER_TENSOR + '/') + name), inference) return inference
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global average pooling .
train
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def BatchedSparseToDense(sparse_indices, output_size): eye = tf.diag(tf.fill([output_size], tf.constant(1, tf.float32))) return tf.nn.embedding_lookup(eye, sparse_indices)
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batch compatible sparse to dense conversion .
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def _get_builtin_permissions(opts): perms = [] for action in (u'add', u'change', u'delete'): perms.append((get_permission_codename(action, opts), (u'Can %s %s' % (action, opts.verbose_name_raw)))) return perms
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returns for all autogenerated permissions .
train
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def save_products(shop, products_pk): configuration.set(shop, SAMPLE_PRODUCTS_KEY, products_pk)
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save a list of pk as a list of sample products for a shop .
train
false
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@register_specialize @gof.local_optimizer([T.Elemwise]) def local_elemwise_sub_zeros(node): if (isinstance(node.op, T.Elemwise) and (node.op.scalar_op.nin == 2) and (node.op.scalar_op == scalar.sub) and (node.inputs[0] == node.inputs[1])): res = T.zeros_like(node.inputs[0]) copy_stack_trace(node.outputs, res) return [res]
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elemwise{sub} -> zeros_like(x) .
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def _basic_auth_str(username, password): return ('Basic ' + b64encode(('%s:%s' % (username, password)).encode('latin1')).strip().decode('latin1'))
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returns a basic auth string .
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def format_explanation(explanation): explanation = ecu(explanation) lines = _split_explanation(explanation) result = _format_lines(lines) return u('\n').join(result)
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this formats an explanation normally all embedded newlines are escaped .
train
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def ellipse(x, y, a, b, resolution, fillDensity=False): poly = toolpath.Polygon() if (not resolution): resolution = self.circleResolution if fillDensity: if (a > b): largerDimension = a else: largerDimension = b numFills = int((float(fillDensity) * float(largerDimension))) else: numFills = 1 (startAngle, endAngle) = (0, 360) circumference = ((float(2) * math.pi) * float((float((a + b)) / 2))) angleDiv = (float(360) / float((circumference * resolution))) (lastX, lastY) = _calcEllipse(startAngle, a, b) if (startAngle > endAngle): endAngle += 360 for d in range(1, (numFills + 1)): ra = ((float(d) / float(numFills)) * float(a)) rb = ((float(d) / float(numFills)) * float(b)) for theta in _frange(startAngle, (endAngle + angleDiv), angleDiv): (newX, newY) = _calcEllipse(theta, ra, rb) aLine = poly.addPoint(toolpath.Point((newX + x), (newY + y))) if debug: print 'aLine', aLine return poly
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generates a flat .
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def ward(y): return linkage(y, method='ward', metric='euclidean')
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performs wards linkage on a condensed distance matrix .
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def get_doc_version(version): parsed_version = parse_version(version) if (is_release(version) and (parsed_version.documentation_revision is not None)): return parsed_version.release else: return version
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get the version string of flocker to display in documentation .
train
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def get_row_nnz(mat, row): return (mat.indptr[(row + 1)] - mat.indptr[row])
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return the number of nonzeros in row .
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def int2bytes(number): if (not ((type(number) is types.LongType) or (type(number) is types.IntType))): raise TypeError('You must pass a long or an int') string = '' while (number > 0): string = ('%s%s' % (byte((number & 255)), string)) number /= 256 return string
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converts a number to a string of bytes .
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def disable_plugin(name, runas=None): if ((runas is None) and (not salt.utils.is_windows())): runas = salt.utils.get_user() cmd = [_get_rabbitmq_plugin(), 'disable', name] ret = __salt__['cmd.run_all'](cmd, runas=runas, python_shell=False) return _format_response(ret, 'Disabled')
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disable a rabbitmq plugin via the rabbitmq-plugins command .
train
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def p_pointer_2(t): pass
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pointer : times .
train
false
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def check_fiff_length(fid, close=True): if (fid.tell() > 2147483648): if close: fid.close() raise IOError('FIFF file exceeded 2GB limit, please split file or save to a different format')
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ensure our file hasnt grown too large to work properly .
train
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def dup_convert(f, K0, K1): if ((K0 is not None) and (K0 == K1)): return f else: return dup_strip([K1.convert(c, K0) for c in f])
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convert the ground domain of f from k0 to k1 .
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def get_cfg_args(): if (not os.path.exists('setup.cfg')): return {} cfg = ConfigParser() cfg.read('setup.cfg') cfg = cfg2dict(cfg) g = cfg.setdefault('global', {}) for key in ['libzmq_extension', 'bundle_libzmq_dylib', 'no_libzmq_extension', 'have_sys_un_h', 'skip_check_zmq', 'bundle_msvcp']: if (key in g): g[key] = eval(g[key]) cfg.update(cfg.pop('global')) return cfg
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look for options in setup .
train
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def crossentropy_softmax_max_and_argmax_1hot_with_bias(x, b, y_idx, **kwargs): (xent, softmax) = crossentropy_softmax_1hot_with_bias(x, b, y_idx, **kwargs) (max_pr, argmax) = tensor.max_and_argmax(softmax, axis=(-1)) return (xent, softmax, max_pr, argmax)
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returns object the cross-entropy .
train
false
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def enqueue(method, queue=u'default', timeout=300, event=None, async=True, job_name=None, **kwargs): q = get_queue(queue, async=async) if (not timeout): timeout = (queue_timeout.get(queue) or 300) return q.enqueue_call(execute_job, timeout=timeout, kwargs={u'site': frappe.local.site, u'user': frappe.session.user, u'method': method, u'event': event, u'job_name': (job_name or cstr(method)), u'async': async, u'kwargs': kwargs})
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enqueue method to be executed using a background worker .
train
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def humanbytes(s): return next((u'{0}{1}'.format(hfloat(((s / div) if div else s)), unit) for (div, unit) in UNITS if (s >= div)))
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convert bytes to human-readable form .
train
false
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def get_phylogenetic_metric(name): try: return getattr(qiime.beta_metrics, ('dist_' + name.lower())) except AttributeError: try: return getattr(qiime.beta_metrics, name.replace('binary', 'binary_dist').lower()) except AttributeError: return getattr(qiime.beta_metrics, name.lower())
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gets metric by name from list in this module .
train
false
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def get_system_packs_base_path(): return cfg.CONF.content.system_packs_base_path
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return a path to the directory where system packs are stored .
train
false
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def has_value(key): return (True if salt.utils.traverse_dict_and_list(__grains__, key, False) else False)
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determine whether a named value exists in the grains dictionary .
train
true
31,614
@removals.remove(message='Use is_asn1_token() instead.', version='1.7.0', removal_version='2.0.0') def is_ans1_token(token): return is_asn1_token(token)
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thx to ayoung for sorting this out .
train
false
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def _get_mac_address(ip_address): from subprocess import Popen, PIPE pid = Popen(['arp', '-n', ip_address], stdout=PIPE) pid_component = pid.communicate()[0] match = re.search('(([a-f\\d]{1,2}\\:){5}[a-f\\d]{1,2})'.encode('UTF-8'), pid_component) if (match is not None): return match.groups()[0] else: return None
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get the mac address of the device .
train
false
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def xlabel(s, *args, **kwargs): l = gca().set_xlabel(s, *args, **kwargs) draw_if_interactive() return l
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set the *x* axis label of the current axis .
train
false
31,619
def get_moon(time, location=None, ephemeris=None): return get_body(u'moon', time, location=location, ephemeris=ephemeris)
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get a ~astropy .
train
false
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def p_direct_declarator_5(t): pass
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direct_declarator : direct_declarator lparen identifier_list rparen .
train
false
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def newid(length=16): l = int(math.ceil(((float(length) * 6.0) / 8.0))) return base64.b64encode(os.urandom(l))[:length].decode('ascii')
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generate a new random string id .
train
false
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def quaternion_inverse(quaternion): q = numpy.array(quaternion, dtype=numpy.float64, copy=True) numpy.negative(q[1:], q[1:]) return (q / numpy.dot(q, q))
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return inverse of quaternion .
train
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def expire(key, seconds, host=None, port=None, db=None, password=None): server = _connect(host, port, db, password) return server.expire(key, seconds)
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expire the current session cookie .
train
true
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def read_cz_lsm_positions(fh): size = struct.unpack('<I', fh.read(4))[0] return fh.read_array('<2f8', count=size)
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read lsm positions from file and return as list .
train
false
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def getCraftModule(fileName): return archive.getModuleWithDirectoryPath(getPluginsDirectoryPath(), fileName)
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get craft module .
train
false
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def get_venv_path(venv): sys_path = _get_venv_path_dirs(venv) with common.ignored(ValueError): sys_path.remove('') sys_path = _get_sys_path_with_egglinks(sys_path) return (sys_path + sys.path)
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get sys .
train
false