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def build_projection_operator(l_x, n_dir): (X, Y) = _generate_center_coordinates(l_x) angles = np.linspace(0, np.pi, n_dir, endpoint=False) (data_inds, weights, camera_inds) = ([], [], []) data_unravel_indices = np.arange((l_x ** 2)) data_unravel_indices = np.hstack((data_unravel_indices, data_unravel_indices)) for (i, angle) in enumerate(angles): Xrot = ((np.cos(angle) * X) - (np.sin(angle) * Y)) (inds, w) = _weights(Xrot, dx=1, orig=X.min()) mask = np.logical_and((inds >= 0), (inds < l_x)) weights += list(w[mask]) camera_inds += list((inds[mask] + (i * l_x))) data_inds += list(data_unravel_indices[mask]) proj_operator = sparse.coo_matrix((weights, (camera_inds, data_inds))) return proj_operator
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compute the tomography design matrix .
train
false
14,076
def delete_rax_clb(args): print ("--- Cleaning Cloud Load Balancers matching '%s'" % args.match_re) for region in pyrax.identity.services.load_balancer.regions: clb = pyrax.connect_to_cloud_loadbalancers(region=region) for lb in rax_list_iterator(clb): if re.search(args.match_re, lb.name): prompt_and_delete(lb, ('Delete matching %s? [y/n]: ' % lb), args.assumeyes)
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function for deleting cloud load balancers .
train
false
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@_ensure_exists def pid(name): try: return int(info(name).get('PID')) except (TypeError, ValueError) as exc: raise CommandExecutionError("Unable to get PID for container '{0}': {1}".format(name, exc))
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returns the pid of a container name container name or id cli example: .
train
true
14,080
def extra_padding_x_keep_ratio(original_size, padding): return _resize(original_size, 0, padding=padding, keep_aspect_ratio=True)
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reduce the width of original_size by padding .
train
false
14,082
def test_distance_to_quantity_when_not_units_of_length(): d = Distance((15 * u.kpc)) twice = (2.0 * d) assert isinstance(twice, Distance) area = ((4.0 * np.pi) * (d ** 2)) assert area.unit.is_equivalent((u.m ** 2)) assert (not isinstance(area, Distance)) assert (type(area) is u.Quantity)
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any operatation that leaves units other than those of length should turn a distance into a quantity .
train
false
14,083
def tableload(datafile, cdfile, hfile=None): return BinTableHDU.load(datafile, cdfile, hfile, replace=True)
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create a table from the input ascii files .
train
false
14,084
def _unpack_simple(fid, dtype, out_dtype): dtype = np.dtype(dtype) string = fid.read(dtype.itemsize) out = np.fromstring(string, dtype=dtype).astype(out_dtype) if (len(out) > 0): out = out[0] return out
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unpack a numpy type .
train
false
14,086
@gen.engine def HandleOneUser(client_store, user_id, callback): logs_paths = logs_util.UserAnalyticsLogsPaths(user_id) base_path = logs_paths.RawDirectory() marker = (os.path.join(base_path, options.options.start_date) if (options.options.start_date is not None) else None) files = (yield gen.Task(store_utils.ListAllKeys, client_store, prefix=base_path, marker=marker)) analytics_files = [] crash_files = [] for f in sorted(files): if f.endswith('.analytics.gz'): analytics_files.append(f) elif (f.endswith('.crash') or f.endswith('.crash.gz')): crash_files.append(f) if (analytics_files and options.options.process_analytics): (yield gen.Task(HandleAnalytics, client_store, user_id, logs_paths, analytics_files)) if (crash_files and options.options.process_crashes): (yield gen.Task(HandleCrashes, client_store, user_id, crash_files)) callback()
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process client logs for a single user .
train
false
14,087
def getTile(layer, coord, extension, ignore_cached=False): (status_code, headers, body) = layer.getTileResponse(coord, extension, ignore_cached) mime = headers.get('Content-Type') return (mime, body)
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get a type string and tile binary for a given request layer tile .
train
false
14,088
def getobj(txt, last=False): txt_end = '' for (startchar, endchar) in ['[]', '()']: if txt.endswith(endchar): pos = txt.rfind(startchar) if pos: txt_end = txt[pos:] txt = txt[:pos] tokens = re.split(SYMBOLS, txt) token = None try: while ((token is None) or re.match(SYMBOLS, token)): token = tokens.pop() if token.endswith('.'): token = token[:(-1)] if token.startswith('.'): return None if last: token += txt[(txt.rfind(token) + len(token))] token += txt_end if token: return token except IndexError: return None
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return the last valid object name in string .
train
true
14,091
def dmp_sqf_list_include(f, u, K, all=False): if (not u): return dup_sqf_list_include(f, K, all=all) (coeff, factors) = dmp_sqf_list(f, u, K, all=all) if (factors and (factors[0][1] == 1)): g = dmp_mul_ground(factors[0][0], coeff, u, K) return ([(g, 1)] + factors[1:]) else: g = dmp_ground(coeff, u) return ([(g, 1)] + factors)
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return square-free decomposition of a polynomial in k[x] .
train
false
14,092
def form_for_model(model): parts = model.__module__.split('.') parts[parts.index('models')] = 'forms' module_name = '.'.join(parts) form_name = (model.__name__ + 'Form') module = try_import(module_name) if (module is not None): form = getattr(module, form_name, None) if (form is not None): return form meta_dict = LocationForm.Meta.__dict__ meta_dict['model'] = model return type(form_name, (LocationForm,), {'Meta': type('Meta', (), meta_dict)})
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returns a form class for the given django model class .
train
false
14,093
def get_file_client(opts, pillar=False): client = opts.get('file_client', 'remote') if (pillar and (client == 'local')): client = 'pillar' return {'remote': RemoteClient, 'local': FSClient, 'pillar': LocalClient}.get(client, RemoteClient)(opts)
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read in the file_client option and return the correct type of file server .
train
true
14,094
def volume_metadata_delete(context, volume_id, key, meta_type=common.METADATA_TYPES.user): return IMPL.volume_metadata_delete(context, volume_id, key, meta_type)
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delete the given metadata item .
train
false
14,096
def add_introspection_rules(rules=[], patterns=[]): assert isinstance(rules, (list, tuple)) assert isinstance(patterns, (list, tuple)) allowed_fields.extend(patterns) introspection_details.extend(rules)
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allows you to add some introspection rules at runtime .
train
false
14,098
def _write_morph_map(fname, subject_from, subject_to, mmap_1, mmap_2): fid = start_file(fname) assert (len(mmap_1) == 2) assert (len(mmap_2) == 2) hemis = [FIFF.FIFFV_MNE_SURF_LEFT_HEMI, FIFF.FIFFV_MNE_SURF_RIGHT_HEMI] for (m, hemi) in zip(mmap_1, hemis): start_block(fid, FIFF.FIFFB_MNE_MORPH_MAP) write_string(fid, FIFF.FIFF_MNE_MORPH_MAP_FROM, subject_from) write_string(fid, FIFF.FIFF_MNE_MORPH_MAP_TO, subject_to) write_int(fid, FIFF.FIFF_MNE_HEMI, hemi) write_float_sparse_rcs(fid, FIFF.FIFF_MNE_MORPH_MAP, m) end_block(fid, FIFF.FIFFB_MNE_MORPH_MAP) for (m, hemi) in zip(mmap_2, hemis): start_block(fid, FIFF.FIFFB_MNE_MORPH_MAP) write_string(fid, FIFF.FIFF_MNE_MORPH_MAP_FROM, subject_to) write_string(fid, FIFF.FIFF_MNE_MORPH_MAP_TO, subject_from) write_int(fid, FIFF.FIFF_MNE_HEMI, hemi) write_float_sparse_rcs(fid, FIFF.FIFF_MNE_MORPH_MAP, m) end_block(fid, FIFF.FIFFB_MNE_MORPH_MAP) end_file(fid)
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write a morph map to disk .
train
false
14,099
def getNewRepository(): return ExportRepository()
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get the repository constructor .
train
false
14,100
def _read_uint32(f): return np.uint32(struct.unpack('>I', f.read(4))[0])
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read an unsigned 32-bit integer .
train
false
14,101
def chmod_plus_x(path): path_mode = os.stat(path).st_mode path_mode &= int(u'777', 8) if (path_mode & stat.S_IRUSR): path_mode |= stat.S_IXUSR if (path_mode & stat.S_IRGRP): path_mode |= stat.S_IXGRP if (path_mode & stat.S_IROTH): path_mode |= stat.S_IXOTH os.chmod(path, path_mode)
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equivalent of unix chmod a+x path .
train
true
14,102
def _update_perf_events_xml(xml_doc, migrate_data): supported_perf_events = [] old_xml_has_perf = True if ('supported_perf_events' in migrate_data): supported_perf_events = migrate_data.supported_perf_events perf_events = xml_doc.findall('./perf') if (not perf_events): perf_events = etree.Element('perf') old_xml_has_perf = False else: perf_events = perf_events[0] for (_, event) in enumerate(perf_events): perf_events.remove(event) if (not supported_perf_events): return xml_doc for e in supported_perf_events: new_event = etree.Element('event', enabled='yes', name=e) perf_events.append(new_event) if (not old_xml_has_perf): xml_doc.append(perf_events) return xml_doc
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update xml by the supported events of destination host .
train
false
14,103
def gid_to_group(gid): try: gid = int(gid) except ValueError: gid = group_to_gid(gid) if (gid == ''): return '' try: return grp.getgrgid(gid).gr_name except (KeyError, NameError): return gid
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convert the group id to the group name on this system under windows .
train
true
14,104
def _uncache_ours_upto(fd, offset, first_region, remaining_regions): (rstart, rlen) = first_region while ((rstart is not None) and (((rstart + rlen) * sc_page_size) <= offset)): _fadvise_pages_done(fd, rstart, rlen) (rstart, rlen) = next(remaining_regions, (None, None)) return (rstart, rlen)
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uncache the pages of fd indicated by first_region and remaining_regions that are before offset .
train
false
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def _make_transform_card(fro, to, r_lpa, r_nasion, r_rpa): diff_1 = (r_nasion - r_lpa) ex = (r_rpa - r_lpa) alpha = (np.dot(diff_1, ex) / np.dot(ex, ex)) ex /= np.sqrt(np.sum((ex * ex))) trans = np.eye(4) move = (((1.0 - alpha) * r_lpa) + (alpha * r_rpa)) trans[:3, 3] = move trans[:3, 0] = ex ey = (r_nasion - move) ey /= np.sqrt(np.sum((ey * ey))) trans[:3, 1] = ey trans[:3, 2] = np.cross(ex, ey) return Transform(fro, to, trans)
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make a transform from cardinal landmarks .
train
false
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@register.filter(name='crispy') def as_crispy_form(form, template_pack=TEMPLATE_PACK, label_class='', field_class=''): if isinstance(form, BaseFormSet): template = uni_formset_template(template_pack) c = Context({'formset': form, 'form_show_errors': True, 'form_show_labels': True, 'label_class': label_class, 'field_class': field_class}).flatten() else: template = uni_form_template(template_pack) c = Context({'form': form, 'form_show_errors': True, 'form_show_labels': True, 'label_class': label_class, 'field_class': field_class}).flatten() return template.render(c)
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the original and still very useful way to generate a div elegant form/formset:: {% load crispy_forms_tags %} <form class="uniform" method="post"> {% csrf_token %} {{ myform|crispy }} </form> or .
train
true
14,109
def iterencode(iter): return ','.join((as_unicode(v).replace(CHAR_ESCAPE, (CHAR_ESCAPE + CHAR_ESCAPE)).replace(CHAR_SEPARATOR, (CHAR_ESCAPE + CHAR_SEPARATOR)) for v in iter))
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encoding iterator .
train
false
14,110
def record_stat(key, request, **data): if ('__recorded' in data): recorded = data.pop('__recorded') else: recorded = datetime.datetime.utcnow() if (not data): raise ValueError('You should at least define one value') record = MonolithRecord(key=key, user_hash=get_user_hash(request), recorded=recorded, value=json.dumps(data)) record.save() return record
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create a new record in the database with the given values .
train
false
14,111
def p_postfix_expression_1(t): pass
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postfix_expression : primary_expression .
train
false
14,112
def indicator_data(): return s3_rest_controller()
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restful crud controller .
train
false
14,114
def organization_autocomplete(context, data_dict): _check_access('organization_autocomplete', context, data_dict) q = data_dict['q'] limit = data_dict.get('limit', 20) model = context['model'] query = model.Group.search_by_name_or_title(q, group_type=None, is_org=True) organization_list = [] for organization in query.all(): result_dict = {} for k in ['id', 'name', 'title']: result_dict[k] = getattr(organization, k) organization_list.append(result_dict) return organization_list
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return a list of organization names that contain a string .
train
false
14,115
def maxabs_scale(X, axis=0, copy=True): X = check_array(X, accept_sparse=('csr', 'csc'), copy=False, ensure_2d=False, dtype=FLOAT_DTYPES) original_ndim = X.ndim if (original_ndim == 1): X = X.reshape(X.shape[0], 1) s = MaxAbsScaler(copy=copy) if (axis == 0): X = s.fit_transform(X) else: X = s.fit_transform(X.T).T if (original_ndim == 1): X = X.ravel() return X
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scale each feature to the [-1 .
train
false
14,116
def dmp_quo_ground(f, c, u, K): if (not u): return dup_quo_ground(f, c, K) v = (u - 1) return [dmp_quo_ground(cf, c, v, K) for cf in f]
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quotient by a constant in k[x] .
train
false
14,118
def topic_weight(d, word, k): return (p_word_given_topic(word, k) * p_topic_given_document(k, d))
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given a document and a word in that document .
train
false
14,119
def _GenerateActionsForMSBuild(spec, actions_to_add): sources_handled_by_action = OrderedSet() actions_spec = [] for (primary_input, actions) in actions_to_add.iteritems(): inputs = OrderedSet() outputs = OrderedSet() descriptions = [] commands = [] for action in actions: inputs.update(OrderedSet(action['inputs'])) outputs.update(OrderedSet(action['outputs'])) descriptions.append(action['description']) cmd = action['command'] if action.get('msbuild_use_call', True): cmd = ('call ' + cmd) commands.append(cmd) description = ', and also '.join(descriptions) command = '\r\n'.join([(c + '\r\nif %errorlevel% neq 0 exit /b %errorlevel%') for c in commands]) _AddMSBuildAction(spec, primary_input, inputs, outputs, command, description, sources_handled_by_action, actions_spec) return (actions_spec, sources_handled_by_action)
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add actions accumulated into an actions_to_add .
train
false
14,120
def drilldown_tree_for_node(node, rel_cls=None, rel_field=None, count_attr=None, cumulative=False): if (rel_cls and rel_field and count_attr): children = node._tree_manager.add_related_count(node.get_children(), rel_cls, rel_field, count_attr, cumulative) else: children = node.get_children() return itertools.chain(node.get_ancestors(), [node], children)
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creates a drilldown tree for the given node .
train
false
14,121
def _retrieve_dbxrefs(adaptor, primary_id): _dbxrefs = [] dbxrefs = adaptor.execute_and_fetchall('SELECT dbname, accession, version FROM bioentry_dbxref join dbxref using (dbxref_id) WHERE bioentry_id = %s ORDER BY rank', (primary_id,)) for (dbname, accession, version) in dbxrefs: if (version and (version != '0')): v = ('%s.%s' % (accession, version)) else: v = accession _dbxrefs.append(('%s:%s' % (dbname, v))) return _dbxrefs
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retrieve the database cross references for the sequence .
train
false
14,122
def test_tabs(): ignore = _tab_ignores[:] try: import mayavi except ImportError: ignore.extend((('mne.gui.' + name) for name in ('_coreg_gui', '_fiducials_gui', '_file_traits', '_help', '_kit2fiff_gui', '_marker_gui', '_viewer'))) for (importer, modname, ispkg) in walk_packages(mne.__path__, prefix='mne.'): if ((not ispkg) and (modname not in ignore)): try: __import__(modname) except Exception: continue mod = sys.modules[modname] source = getsource(mod) assert_true((' DCTB ' not in source), ('"%s" has tabs, please remove them or add it to theignore list' % modname))
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test that there are no tabs in our source files .
train
false
14,124
def compute_item_matrix(items, row_first=False, empty=None, *args, **kwargs): info = _find_optimal(list(map(len, items)), row_first, *args, **kwargs) (nrow, ncol) = (info['max_rows'], info['num_columns']) if row_first: return ([[_get_or_default(items, ((r * ncol) + c), default=empty) for c in range(ncol)] for r in range(nrow)], info) else: return ([[_get_or_default(items, ((c * nrow) + r), default=empty) for c in range(ncol)] for r in range(nrow)], info)
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returns a nested list .
train
false
14,125
def setupWorkerTransition(): default_warn_method = getWarningMethod() def custom_warn_method(message, category, stacklevel): if (stacklevel is not None): stacklevel += 1 if (_WORKER_WARNING_MARK in message): message = message.replace(_WORKER_WARNING_MARK, '') warnings.warn(DeprecatedWorkerNameWarning(message), message, stacklevel) else: default_warn_method(message, category, stacklevel) setWarningMethod(custom_warn_method)
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hook twisted deprecation machinery to use custom warning class for worker api deprecation warnings .
train
true
14,126
def complain(message): print >>sys.__stderr__, ((isinstance(message, str) and message) or repr(message))
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if any exception occurs in this file .
train
false
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@with_setup(step_runner_environ) def test_steps_that_match_groups_takes_them_as_parameters(): @step('Given a ([^\\s]+) called "(.*)"') def given_what_named(step, what, name): assert_equals(what, 'person') assert_equals(name, 'John Doe') f = Feature.from_string(FEATURE4) feature_result = f.run() scenario_result = feature_result.scenario_results[0] assert_equals(len(scenario_result.steps_passed), 1) assert_equals(scenario_result.total_steps, 1)
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steps that match groups takes them as parameters .
train
false
14,128
def instance_fault_get_by_instance_uuids(context, instance_uuids): rows = model_query(context, models.InstanceFault, read_deleted='no').filter(models.InstanceFault.instance_uuid.in_(instance_uuids)).order_by(desc('created_at'), desc('id')).all() output = {} for instance_uuid in instance_uuids: output[instance_uuid] = [] for row in rows: data = dict(row.iteritems()) output[row['instance_uuid']].append(data) return output
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get all instance faults for the provided instance_uuids .
train
false
14,130
def _new_Index(cls, d): return cls.__new__(cls, **d)
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this is called upon unpickling .
train
false
14,131
@pytest.mark.django_db def test_project_save_no_fullname(project0): project0.fullname = '' with pytest.raises(ValidationError): project0.save()
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test that an existing project cant be removed its fullname .
train
false
14,132
def init(mpstate): return SerialModule(mpstate)
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initialise module .
train
false
14,133
def reversed_lower_upper_bounded_changelog(repo, excluded_lower_bounds_changeset_revision, included_upper_bounds_changeset_revision): if (excluded_lower_bounds_changeset_revision == INITIAL_CHANGELOG_HASH): appending_started = True else: appending_started = False reversed_changelog = [] for changeset in repo.changelog: changeset_hash = str(repo.changectx(changeset)) if appending_started: reversed_changelog.insert(0, changeset) if ((changeset_hash == excluded_lower_bounds_changeset_revision) and (not appending_started)): appending_started = True if (changeset_hash == included_upper_bounds_changeset_revision): break return reversed_changelog
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return a reversed list of changesets in the repository changelog after the excluded_lower_bounds_changeset_revision .
train
false
14,134
def find_submodule_git_dir(d): if is_git_dir(d): return d try: with open(d) as fp: content = fp.read().rstrip() except (IOError, OSError): pass else: if content.startswith('gitdir: '): path = content[8:] if Git.is_cygwin(): path = decygpath(path) if (not osp.isabs(path)): path = osp.join(osp.dirname(d), path) return find_submodule_git_dir(path) return None
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search for a submodule repo .
train
true
14,135
def common_meta_backup_mocks(f): def _common_inner_inner1(inst, *args, **kwargs): @mock.patch('cinder.backup.drivers.ceph.rbd') @mock.patch('cinder.backup.drivers.ceph.rados') def _common_inner_inner2(mock_rados, mock_rbd): inst.mock_rados = mock_rados inst.mock_rbd = mock_rbd inst.mock_rados.ObjectNotFound = MockObjectNotFoundException return f(inst, *args, **kwargs) return _common_inner_inner2() return _common_inner_inner1
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decorator to set mocks common to all metadata backup tests .
train
false
14,136
def determineDefaultFunctionName(): try: (1 / 0) except: return traceback.extract_stack()[(-2)][2]
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return the string used by python as the name for code objects which are compiled from interactive input or at the top-level of modules .
train
false
14,137
def get_rect_ymax(data): return max(data[0][1], data[1][1], data[2][1], data[3][1])
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find maximum y value from four vertices .
train
false
14,138
def pytest_generate_tests(metafunc): test_files = dict(map(parse_test_files_option, metafunc.config.option.test_files)) if ('case' in metafunc.fixturenames): base_dir = metafunc.config.option.integration_case_dir thirdparty = metafunc.config.option.thirdparty cases = list(run.collect_dir_tests(base_dir, test_files)) if thirdparty: cases.extend(run.collect_dir_tests(os.path.join(base_dir, 'thirdparty'), test_files, True)) ids = [('%s:%s' % (c.module_name, c.line_nr_test)) for c in cases] metafunc.parametrize('case', cases, ids=ids) if ('refactor_case' in metafunc.fixturenames): base_dir = metafunc.config.option.refactor_case_dir metafunc.parametrize('refactor_case', refactor.collect_dir_tests(base_dir, test_files)) if ('static_analysis_case' in metafunc.fixturenames): base_dir = os.path.join(os.path.dirname(__file__), 'static_analysis') metafunc.parametrize('static_analysis_case', collect_static_analysis_tests(base_dir, test_files))
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build a list of test arguments for test_copy_transpose .
train
false
14,139
def getUserSid(username): domain = win32api.GetComputerName() if (username.find(u'\\') != (-1)): domain = username.split(u'\\')[0] username = username.split(u'\\')[(-1)] domain = domain.upper() return win32security.ConvertSidToStringSid(win32security.LookupAccountName(None, ((domain + u'\\') + username))[0])
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get the security id for the user .
train
false
14,140
def test_if_marathon_app_can_be_deployed(dcos_api_session): dcos_api_session.marathon.deploy_test_app_and_check(*get_test_app())
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marathon app deployment integration test this test verifies that marathon app can be deployed .
train
false
14,141
def sync_job_reset(r, **attr): if r.interactive: if (r.component and (r.component.alias == 'job')): job_id = r.component_id if job_id: S3Task.reset(job_id) current.session.confirmation = current.T('Job reactivated') r.component_id = None redirect(r.url(method=''))
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restful method to reset a job status from failed to queued .
train
false
14,142
def Pareto(name, xm, alpha): return rv(name, ParetoDistribution, (xm, alpha))
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create a continuous random variable with the pareto distribution .
train
false
14,144
def load_after_create(request, database): tablename = request.REQUEST.get('table') path = request.REQUEST.get('path') if ((not tablename) or (not path)): msg = _('Internal error: Missing needed parameter to load data into table.') LOG.error(msg) raise PopupException(msg) LOG.debug(('Auto loading data from %s into table %s' % (path, tablename))) hql = ("LOAD DATA INPATH '%s' INTO TABLE `%s.%s`" % (path, database, tablename)) query = hql_query(hql) on_success_url = reverse('metastore:describe_table', kwargs={'database': database, 'table': tablename}) try: return execute_directly(request, query, on_success_url=on_success_url) except Exception as e: message = 'The table data could not be loaded' LOG.exception(message) detail = (e.message if (hasattr(e, 'message') and e.message) else None) raise PopupException(_(message), detail=detail)
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automatically load data into a newly created table .
train
false
14,145
def load_language(cr, lang): env = odoo.api.Environment(cr, SUPERUSER_ID, {}) installer = env['base.language.install'].create({'lang': lang}) installer.lang_install()
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loads a translation terms for a language .
train
false
14,146
def register_atexit_function(func): atexit.register(func)
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register a function for processing at program exit .
train
false
14,147
def _valid_composer(composer): if salt.utils.which(composer): return True return False
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validate the composer file is indeed there .
train
false
14,148
def get_text_list(list_, last_word='or'): if (len(list_) == 0): return '' if (len(list_) == 1): return list_[0] return ('%s %s %s' % (', '.join([str(i) for i in list_][:(-1)]), last_word, list_[(-1)]))
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return a string with a natural enumeration of items .
train
false
14,149
def update_classpath(path): for (prefix, replacement) in DEPRECATION_RULES: if path.startswith(prefix): new_path = path.replace(prefix, replacement, 1) warnings.warn('`{}` class is deprecated, use `{}` instead'.format(path, new_path), ScrapyDeprecationWarning) return new_path return path
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update a deprecated path from an object with its new location .
train
false
14,150
def test_batch_normalized_mlp_learn_shift_propagated_at_alloc(): mlp = BatchNormalizedMLP([Tanh(), Tanh()], [5, 7, 9], learn_shift=False) assert (not mlp.learn_shift) assert all((act.children[0].learn_shift for act in mlp.activations)) mlp.allocate() assert (not any((act.children[0].learn_shift for act in mlp.activations)))
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test that setting learn_shift on a batchnormalizedmlp works .
train
false
14,151
def compare_lists(old=None, new=None): ret = dict() for item in new: if (item not in old): ret['new'] = item for item in old: if (item not in new): ret['old'] = item return ret
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compare before and after results from various salt functions .
train
true
14,152
def disable_failed_job(registry, xml_parent, data): xml_element = XML.SubElement(xml_parent, 'disableFailedJob.disableFailedJob.DisableFailedJob', {'plugin': 'disable-failed-job'}) valid_conditions = ['Only Failure', 'Failure and Unstable', 'Only Unstable'] mapping = [('when-to-disable', 'whenDisable', None, valid_conditions)] helpers.convert_mapping_to_xml(xml_element, data, mapping, fail_required=True) if ('no-of-failures' in data): XML.SubElement(xml_element, 'failureTimes').text = str(data.get('no-of-failures')) XML.SubElement(xml_element, 'optionalBrockChecked').text = 'true' else: XML.SubElement(xml_element, 'optionalBrockChecked').text = 'false'
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yaml: disable-failed-job automatically disable failed jobs .
train
false
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def sdm_nf_buchberger(f, G, O, K, phantom=None): from itertools import repeat h = f T = list(G) if (phantom is not None): hp = phantom[0] Tp = list(phantom[1]) phantom = True else: Tp = repeat([]) phantom = False while h: try: (g, gp) = next(((g, gp) for (g, gp) in zip(T, Tp) if sdm_monomial_divides(sdm_LM(g), sdm_LM(h)))) except StopIteration: break if phantom: (h, hp) = sdm_spoly(h, g, O, K, phantom=(hp, gp)) else: h = sdm_spoly(h, g, O, K) if phantom: return (h, hp) return h
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compute a weak normal form of f with respect to g and order o .
train
false
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def lookupResponsibility(name, timeout=None): return getResolver().lookupResponsibility(name, timeout)
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perform an rp record lookup .
train
false
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def to_bokeh(fig=None, tools=DEFAULT_TOOLS, use_pandas=True, xkcd=False): if (fig is None): fig = plt.gcf() renderer = BokehRenderer(tools, use_pandas, xkcd) exporter = BokehExporter(renderer) exporter.run(fig) return renderer.fig
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uses bokeh to display a matplotlib figure .
train
false
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def require_level(level): if (level not in ['instructor', 'staff']): raise ValueError("unrecognized level '{}'".format(level)) def decorator(func): def wrapped(*args, **kwargs): request = args[0] course = get_course_by_id(CourseKey.from_string(kwargs['course_id'])) if has_access(request.user, level, course): return func(*args, **kwargs) else: return HttpResponseForbidden() return wrapped return decorator
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decorator with argument that requires an access level of the requesting user .
train
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def _iter_service_names(): found = set() for line in glob.glob('/etc/init.d/*'): name = os.path.basename(line) found.add(name) (yield name) init_root = '/etc/init/' for (root, dirnames, filenames) in os.walk(init_root): relpath = os.path.relpath(root, init_root) for filename in fnmatch.filter(filenames, '*.conf'): if (relpath == '.'): name = filename[:(-5)] else: name = os.path.join(relpath, filename[:(-5)]) if (name in found): continue (yield name)
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detect all of the service names available to upstart via init configuration files and via classic sysv init scripts .
train
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def map_unreachable_exception(e): exception_class = FacebookUnreachable if isinstance(e, ssl.SSLError): exception_class = FacebookSSLError elif isinstance(e, HTTPError): exception_class = FacebookHTTPError elif isinstance(e, URLError): exception_class = FacebookURLError return exception_class
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we always raise the original and new subclass to - preserve backwards compatibility .
train
false
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@FileSystem.in_directory(current_directory, 'django', 'bamboo') def test_mail_content(): (status, out) = run_scenario('leaves', 'content', 1) assert_equals(status, 0, out) (status, out) = run_scenario('leaves', 'content', 2) assert_equals(status, 0, out) (status, out) = run_scenario('leaves', 'content', 3) assert_not_equals(status, 0) assert ('An email contained expected text in the body' in out)
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mail content is checked through lettuce steps .
train
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def get_tax_summary(source): all_line_taxes = [] untaxed = TaxlessPrice(source.create_price(0).amount) for line in source.get_final_lines(): line_taxes = list(line.taxes) all_line_taxes.extend(line_taxes) if (not line_taxes): untaxed += line.taxless_price return TaxSummary.from_line_taxes(all_line_taxes, untaxed)
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get tax summary of given source lines .
train
false
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def check_for_multiple(files): for regex in _RE_MULTIPLE: matched_files = check_for_sequence(regex, files) if matched_files: return matched_files return ''
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return list of files that looks like a multi-part post .
train
false
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def gcp_connect(module, provider, get_driver, user_agent_product, user_agent_version): if (not HAS_LIBCLOUD_BASE): module.fail_json(msg='libcloud must be installed to use this module') creds = _get_gcp_credentials(module, require_valid_json=False, check_libcloud=True) try: gcp = get_driver(provider)(creds['service_account_email'], creds['credentials_file'], datacenter=module.params.get('zone', None), project=creds['project_id']) gcp.connection.user_agent_append(('%s/%s' % (user_agent_product, user_agent_version))) except (RuntimeError, ValueError) as e: module.fail_json(msg=str(e), changed=False) except Exception as e: module.fail_json(msg=unexpected_error_msg(e), changed=False) return gcp
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return a google libcloud driver connection .
train
false
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@handle_response_format @treeio_login_required def queue_edit(request, queue_id, response_format='html'): queue = get_object_or_404(TicketQueue, pk=queue_id) if (not request.user.profile.has_permission(queue, mode='w')): return user_denied(request, message="You don't have access to this Queue") if request.POST: if ('cancel' not in request.POST): form = QueueForm(request.user.profile, request.POST, instance=queue) if form.is_valid(): queue = form.save() return HttpResponseRedirect(reverse('services_queue_view', args=[queue.id])) else: return HttpResponseRedirect(reverse('services_queue_view', args=[queue.id])) else: form = QueueForm(request.user.profile, instance=queue) context = _get_default_context(request) context.update({'queue': queue, 'form': form}) return render_to_response('services/queue_edit', context, context_instance=RequestContext(request), response_format=response_format)
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queue edit .
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false
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def onLoseChargeCB(ordersID, dbid, success, datas): DEBUG_MSG(('onLoseChargeCB: ordersID=%s, dbid=%i, success=%i, datas=%s' % (ordersID, dbid, success, datas)))
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kbengine method .
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def parse_exclude_devices(exclude_list): exclude_mapping = {} for dev_mapping in exclude_list: try: (dev_name, exclude_devices) = dev_mapping.split(':', 1) except ValueError: raise ValueError((_("Invalid mapping: '%s'") % dev_mapping)) dev_name = dev_name.strip() if (not dev_name): raise ValueError((_("Missing key in mapping: '%s'") % dev_mapping)) if (dev_name in exclude_mapping): raise ValueError((_('Device %(dev_name)s in mapping: %(mapping)s not unique') % {'dev_name': dev_name, 'mapping': dev_mapping})) exclude_devices_list = exclude_devices.split(';') exclude_devices_set = set() for dev in exclude_devices_list: dev = dev.strip() if dev: exclude_devices_set.add(dev) exclude_mapping[dev_name] = exclude_devices_set return exclude_mapping
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parse exclude devices list parses excluded device list in the form: dev_name:pci_dev_1;pci_dev_2 .
train
false
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def bulk_stop(workers, lbn, profile='default'): ret = {} if isinstance(workers, str): workers = workers.split(',') for worker in workers: try: ret[worker] = worker_stop(worker, lbn, profile) except Exception: ret[worker] = False return ret
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stop all the given workers in the specific load balancer cli examples: .
train
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def worker_stopped(name, workers=None, profile='default'): if (workers is None): workers = [] return _bulk_state('modjk.bulk_stop', name, workers, profile)
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stop all the workers in the modjk load balancer example: .
train
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def coerce_to_list(val): if val: if (not isinstance(val, (list, tuple))): val = [val] else: val = [] return val
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for parameters that can take either a single string or a list of strings .
train
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def course_start_date_is_default(start, advertised_start): return ((advertised_start is None) and (start == DEFAULT_START_DATE))
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returns whether a courses start date hasnt yet been set .
train
false
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def major_version(best=False): return _distro.major_version(best)
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return the major version of the current linux distribution .
train
false
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def _plot_update_evoked(params, bools): (picks, evoked) = [params[k] for k in ('picks', 'evoked')] times = (evoked.times * 1000.0) projs = [proj for (ii, proj) in enumerate(params['projs']) if (ii in np.where(bools)[0])] params['proj_bools'] = bools new_evoked = evoked.copy() new_evoked.info['projs'] = [] new_evoked.add_proj(projs) new_evoked.apply_proj() for (ax, t) in zip(params['axes'], params['ch_types_used']): this_scaling = params['scalings'][t] idx = [picks[i] for i in range(len(picks)) if (params['types'][i] == t)] D = (this_scaling * new_evoked.data[idx, :]) if (params['plot_type'] == 'butterfly'): for (line, di) in zip(ax.lines, D): line.set_data(times, di) else: ax.images[0].set_data(D) params['fig'].canvas.draw()
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update the plot evoked lines .
train
false
14,178
def add_serializer_errors(serializer, data, field_errors): if (not serializer.is_valid()): errors = serializer.errors for (key, error) in errors.iteritems(): field_errors[key] = {'developer_message': u"Value '{field_value}' is not valid for field '{field_name}': {error}".format(field_value=data.get(key, ''), field_name=key, error=error), 'user_message': _(u'This value is invalid.')} return field_errors
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adds errors from serializer validation to field_errors .
train
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def ipexec(fname, options=None, commands=()): if (options is None): options = [] cmdargs = (default_argv() + options) test_dir = os.path.dirname(__file__) ipython_cmd = get_ipython_cmd() full_fname = os.path.join(test_dir, fname) full_cmd = ((ipython_cmd + cmdargs) + [full_fname]) env = os.environ.copy() env['PYTHONWARNINGS'] = 'ignore' for (k, v) in env.items(): if (not isinstance(v, str)): print (k, v) p = Popen(full_cmd, stdout=PIPE, stderr=PIPE, stdin=PIPE, env=env) (out, err) = p.communicate(input=(py3compat.str_to_bytes('\n'.join(commands)) or None)) (out, err) = (py3compat.bytes_to_str(out), py3compat.bytes_to_str(err)) if out: out = re.sub('\\x1b\\[[^h]+h', '', out) return (out, err)
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utility to call ipython filename .
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false
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@parallel def logs(): sudo('tail -f {logdir}* /var/log/nginx/*.log'.format(logdir=LOG_DIR))
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returns the logs for the container .
train
false
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def default_keychain(name, domain='user', user=None): ret = {'name': name, 'result': True, 'comment': '', 'changes': {}} if (not os.path.exists(name)): ret['result'] = False ret['comment'] += 'Keychain not found at {0}'.format(name) else: out = __salt__['keychain.get_default_keychain'](user, domain) if (name in out): ret['comment'] += '{0} was already the default keychain.'.format(name) else: out = __salt__['keychain.set_default_keychain'](name, domain, user) if (len(out) == 0): ret['changes']['default'] = name else: ret['result'] = False ret['comment'] = 'Failed to install keychain. {0}'.format(out) return ret
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set the default keychain to use name the chain in which to use as the default domain the domain to use valid values are user|system|common|dynamic .
train
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def create_temporary_ca_path(anchor_list, folder): try: if (not os.path.isdir(folder)): os.makedirs(folder) except: return None l = len(anchor_list) if (l == 0): return None fmtstr = ('%%0%sd.pem' % math.ceil(math.log(l, 10))) i = 0 try: for a in anchor_list: fname = os.path.join(folder, (fmtstr % i)) f = open(fname, 'w') s = a.output(fmt='PEM') f.write(s) f.close() i += 1 except: return None (r, w) = popen2.popen2(('c_rehash %s' % folder)) r.close() w.close() return l
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create a ca path folder as defined in openssl terminology .
train
true
14,184
def rowcol_to_a1(row, col): row = int(row) col = int(col) if ((row < 1) or (col < 1)): raise IncorrectCellLabel(('(%s, %s)' % (row, col))) div = col column_label = '' while div: (div, mod) = divmod(div, 26) if (mod == 0): mod = 26 div -= 1 column_label = (chr((mod + MAGIC_NUMBER)) + column_label) label = ('%s%s' % (column_label, row)) return label
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translates a row and column cell address to a1 notation .
train
true
14,185
def reset(): _runtime.reset()
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reset the registry of providers .
train
false
14,187
def object_compat(function): @functools.wraps(function) def decorated_function(self, context, *args, **kwargs): def _load_instance(instance_or_dict): if isinstance(instance_or_dict, dict): metas = [meta for meta in ('metadata', 'system_metadata') if (meta in instance_or_dict)] instance = objects.Instance._from_db_object(context, objects.Instance(), instance_or_dict, expected_attrs=metas) instance._context = context return instance return instance_or_dict try: kwargs['instance'] = _load_instance(kwargs['instance']) except KeyError: args = ((_load_instance(args[0]),) + args[1:]) migration = kwargs.get('migration') if isinstance(migration, dict): migration = objects.Migration._from_db_object(context.elevated(), objects.Migration(), migration) kwargs['migration'] = migration return function(self, context, *args, **kwargs) return decorated_function
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train
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@pytest.mark.parametrize('i', range(len(ITEMS))) def test_no_userdata(objects, i): assert (objects.history.itemAt(i).userData() is None)
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check if all items have no user data .
train
false
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@register.tag('static') def do_static(parser, token): return StaticNode.handle_token(parser, token)
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a template tag that returns the url to a file using staticfiles storage backend usage:: {% static path [as varname] %} examples:: {% static "myapp/css/base .
train
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def module_path(local_function): return os.path.abspath(inspect.getsourcefile(local_function))
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returns the module path without the use of __file__ .
train
false
14,192
def p_constant_expression_opt_1(t): pass
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constant_expression_opt : empty .
train
false
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def _dict_values_match(*args, **kwargs): matchers = dict(*args, **kwargs) def extract_val(key): def extract_val_for_key(d): return d.get(key) return extract_val_for_key return MatchesAll(*list((AfterPreprocessing(extract_val(key), value) for (key, value) in matchers.iteritems())))
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matcher that matches a dict where each of they keys match the matcher passed in .
train
false
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def should_bypass_proxies(url): get_proxy = (lambda k: (os.environ.get(k) or os.environ.get(k.upper()))) no_proxy = get_proxy('no_proxy') netloc = urlparse(url).netloc if no_proxy: no_proxy = no_proxy.replace(' ', '').split(',') ip = netloc.split(':')[0] if is_ipv4_address(ip): for proxy_ip in no_proxy: if is_valid_cidr(proxy_ip): if address_in_network(ip, proxy_ip): return True else: for host in no_proxy: if (netloc.endswith(host) or netloc.split(':')[0].endswith(host)): return True try: bypass = proxy_bypass(netloc) except (TypeError, socket.gaierror): bypass = False if bypass: return True return False
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returns whether we should bypass proxies or not .
train
true
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def is_mm_32_format(msg_string): return (msg_string.startswith('mm') and (len(msg_string) == 34))
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missed message strings are formatted with a little "mm" prefix followed by a randomly generated 32-character string .
train
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def unescape_entities(value): safe_characters = {'&amp;': '&'} if isinstance(value, dict): return {key: unescape_entities(value) for (key, value) in value.iteritems()} if is_iterable_but_not_string(value): return [unescape_entities(each) for each in value] if isinstance(value, basestring): for (escape_sequence, character) in safe_characters.items(): value = value.replace(escape_sequence, character) return value return value
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convert html-encoded data to literal characters .
train
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def get_debtpaying_data(year, quarter): if (ct._check_input(year, quarter) is True): ct._write_head() df = _get_debtpaying_data(year, quarter, 1, pd.DataFrame()) if (df is not None): df['code'] = df['code'].map((lambda x: str(x).zfill(6))) return df
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parameters year:int 年度 e .
train
false
14,201
def _find_missing_edge(G): nodes = set(G) for u in G: missing = (nodes - set((list(G[u].keys()) + [u]))) if missing: return (u, missing.pop())
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given a non-complete graph g .
train
false