sequence stringlengths 1.27k 35.1k | code stringlengths 75 8.58k |
|---|---|
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_sh_ids'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def get_sh_ids(self, identity, backend_name):
identity_tuple = tuple(identity.items())
sh_ids = self.__get_sh_ids_cache(identity_tuple, backend_name)
return sh_ids |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_sh_identity'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def get_sh_identity(self, item, identity_field=None):
def fill_list_identity(identity, user_list_data):
identity['username'] = user_list_data[0]['__text__']
if '@' in identity['username']:
identity['email'] = identity['username']
if 'name' in user_list_data[0]... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '23']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'feed'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20']}; {'id': '4', 'type': 'identifier', 'ch... | def feed(self, from_date=None, from_offset=None, category=None,
latest_items=None, arthur_items=None, filter_classified=None):
if self.fetch_archive:
items = self.perceval_backend.fetch_from_archive()
self.feed_items(items)
return
elif arthur_items:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_identities'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def get_identities(self, item):
def add_sh_github_identity(user, user_field, rol):
github_repo = None
if GITHUB in item['origin']:
github_repo = item['origin'].replace(GITHUB, '')
github_repo = re.sub('.git$', '', github_repo)
if not github_rep... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'areas_of_code'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': [... | def areas_of_code(git_enrich, in_conn, out_conn, block_size=100):
aoc = AreasOfCode(in_connector=in_conn, out_connector=out_conn, block_size=block_size,
git_enrich=git_enrich)
ndocs = aoc.analyze()
return ndocs |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_make_serializer'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']}; {'id': '4', 'type': 'identifier', 'child... | def _make_serializer(meas, schema, rm_none, extra_tags, placeholder):
_validate_schema(schema, placeholder)
tags = []
fields = []
ts = None
meas = meas
for k, t in schema.items():
if t is MEASUREMENT:
meas = f"{{i.{k}}}"
elif t is TIMEINT:
ts = f"{{i.{k}}}... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '17', '23']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'iterpoints'}; {'id': '3', 'type': 'parameters', 'children': ['4', '8']}; {'id': '4', 'type': 'typed_parameter', 'children': ['5... | def iterpoints(resp: dict, parser: Optional[Callable] = None) -> Iterator[Any]:
for statement in resp['results']:
if 'series' not in statement:
continue
for series in statement['series']:
if parser is None:
return (x for x in series['values'])
elif... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11', '13']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'serialize'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children':... | def serialize(df, measurement, tag_columns=None, **extra_tags) -> bytes:
if measurement is None:
raise ValueError("Missing 'measurement'")
if not isinstance(df.index, pd.DatetimeIndex):
raise ValueError('DataFrame index is not DatetimeIndex')
tag_columns = set(tag_columns or [])
isnull =... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '17']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_my_feed'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14']}; {'id': '4', 'type': 'identifier', 'childre... | def get_my_feed(self, limit=150, offset=20, sort="updated", nid=None):
r = self.request(
method="network.get_my_feed",
nid=nid,
data=dict(
limit=limit,
offset=offset,
sort=sort
)
)
return self._handle... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '23']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'filter_feed'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20']}; {'id': '4', 'type': 'identifie... | def filter_feed(self, updated=False, following=False, folder=False,
filter_folder="", sort="updated", nid=None):
assert sum([updated, following, folder]) == 1
if folder:
assert filter_folder
if updated:
filter_type = dict(updated=1)
elif follow... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_dataset'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def get_dataset(self, dataset):
success = True
dataset_path = self.base_dataset_path + dataset
if not isdir(dataset_path):
was_error = False
for iteration in range(5):
if iteration == 0 or was_error is True:
zip_path = dataset_path + ".... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '32']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'install'}; {'id': '3', 'type': 'parameters', 'children': ['4', '7', '27', '30']}; {'id': '4', 'type': 'default_parameter', 'children'... | def install(verbose=True,
verbose_destination=sys.__stderr__.fileno() if hasattr(sys.__stderr__, 'fileno') else sys.__stderr__,
strict=True,
**kwargs):
global _MANHOLE
with _LOCK:
if _MANHOLE is None:
_MANHOLE = Manhole()
else:
if stric... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '37']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'update'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10', '13', '16', '19', '22', '25', '28', '31', '34']}; ... | def update(
self, alert_condition_nrql_id, policy_id, name=None, threshold_type=None, query=None,
since_value=None, terms=None, expected_groups=None, value_function=None,
runbook_url=None, ignore_overlap=None, enabled=True):
conditions_nrql_dict = self.list(policy_id)
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '26']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'create'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10', '11', '14', '17', '20', '23']}; {'id': '... | def create(
self, policy_id, name, threshold_type, query, since_value, terms,
expected_groups=None, value_function=None, runbook_url=None,
ignore_overlap=None, enabled=True):
data = {
'nrql_condition': {
'type': threshold_type,
'nam... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '34']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'update'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10', '13', '16', '19', '22', '25', '28', '31']}; {'id':... | def update(
self, alert_condition_id, policy_id,
type=None,
condition_scope=None,
name=None,
entities=None,
metric=None,
runbook_url=None,
terms=None,
user_defined=None,
enabled=None):
conditi... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'operatorPrecedence'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def operatorPrecedence(base, operators):
expression = Forward()
last = base | Suppress('(') + expression + Suppress(')')
def parse_operator(expr, arity, association, action=None, extra=None):
return expr, arity, association, action, extra
for op in operators:
expr, arity, association, ac... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'readGraph'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifier', 'chi... | def readGraph(edgeList, nodeList = None, directed = False, idKey = 'ID', eSource = 'From', eDest = 'To'):
progArgs = (0, "Starting to reading graphs")
if metaknowledge.VERBOSE_MODE:
progKwargs = {'dummy' : False}
else:
progKwargs = {'dummy' : True}
with _ProgressBar(*progArgs, **progKwar... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '21']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'writeGraph'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15', '18']}; {'id': '4', 'type': 'identifier'... | def writeGraph(grph, name, edgeInfo = True, typing = False, suffix = 'csv', overwrite = True, allSameAttribute = False):
progArgs = (0, "Writing the graph to files starting with: {}".format(name))
if metaknowledge.VERBOSE_MODE:
progKwargs = {'dummy' : False}
else:
progKwargs = {'dummy' : Tru... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'mergeGraphs'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [],... | def mergeGraphs(targetGraph, addedGraph, incrementedNodeVal = 'count', incrementedEdgeVal = 'weight'):
for addedNode, attribs in addedGraph.nodes(data = True):
if incrementedNodeVal:
try:
targetGraph.node[addedNode][incrementedNodeVal] += attribs[incrementedNodeVal]
e... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'writeRecord'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def writeRecord(self, f):
if self.bad:
raise BadPubmedRecord("This record cannot be converted to a file as the input was malformed.\nThe original line number (if any) is: {} and the original file is: '{}'".format(self._sourceLine, self._sourceFile))
else:
authTags = {}
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '32']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'graphDensityContourPlot'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26', '29']}; ... | def graphDensityContourPlot(G, iters = 50, layout = None, layoutScaleFactor = 1, overlay = False, nodeSize = 10, axisSamples = 100, blurringFactor = .1, contours = 15, graphType = 'coloured'):
from mpl_toolkits.mplot3d import Axes3D
if not isinstance(G, nx.classes.digraph.DiGraph) and not isinstance(G, nx.class... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'makeNodeTuple'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10', '11', '12', '13']}; {'id': '4', '... | def makeNodeTuple(citation, idVal, nodeInfo, fullInfo, nodeType, count, coreCitesDict, coreValues, detailedValues, addCR):
d = {}
if nodeInfo:
if nodeType == 'full':
if coreValues:
if citation in coreCitesDict:
R = coreCitesDict[citation]
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'expandRecs'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def expandRecs(G, RecCollect, nodeType, weighted):
for Rec in RecCollect:
fullCiteList = [makeID(c, nodeType) for c in Rec.createCitation(multiCite = True)]
if len(fullCiteList) > 1:
for i, citeID1 in enumerate(fullCiteList):
if citeID1 in G:
for citeI... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'writeBib'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifier', 'chil... | def writeBib(self, fname = None, maxStringLength = 1000, wosMode = False, reducedOutput = False, niceIDs = True):
if fname:
f = open(fname, mode = 'w', encoding = 'utf-8')
else:
f = open(self.name[:200] + '.bib', mode = 'w', encoding = 'utf-8')
f.write("%This file was gen... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'makeDict'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifier', 'chil... | def makeDict(self, onlyTheseTags = None, longNames = False, raw = False, numAuthors = True, genderCounts = True):
if onlyTheseTags:
for i in range(len(onlyTheseTags)):
if onlyTheseTags[i] in fullToTagDict:
onlyTheseTags[i] = fullToTagDict[onlyTheseTags[i]]
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '44']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'networkCoCitation'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26', '29', '32', '3... | def networkCoCitation(self, dropAnon = True, nodeType = "full", nodeInfo = True, fullInfo = False, weighted = True, dropNonJournals = False, count = True, keyWords = None, detailedCore = True, detailedCoreAttributes = False, coreOnly = False, expandedCore = False, addCR = False):
allowedTypes = ["full", "origin... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'networkBibCoupling'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']}; {'id': '4', 'type': 'identifier', 'childr... | def networkBibCoupling(self, weighted = True, fullInfo = False, addCR = False):
progArgs = (0, "Make a citation network for coupling")
if metaknowledge.VERBOSE_MODE:
progKwargs = {'dummy' : False}
else:
progKwargs = {'dummy' : True}
with _ProgressBar(*progArgs, **... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'localCiteStats'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def localCiteStats(self, pandasFriendly = False, keyType = "citation"):
count = 0
recCount = len(self)
progArgs = (0, "Starting to get the local stats on {}s.".format(keyType))
if metaknowledge.VERBOSE_MODE:
progKwargs = {'dummy' : False}
else:
progKwargs ... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '17']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'citeFilter'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14']}; {'id': '4', 'type': 'identifier', 'children... | def citeFilter(self, keyString = '', field = 'all', reverse = False, caseSensitive = False):
retRecs = []
keyString = str(keyString)
for R in self:
try:
if field == 'all':
for cite in R.get('citations'):
if caseSensitive:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '24']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'rankedSeries'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15', '18', '21']}; {'id': '4', 'type': 'ide... | def rankedSeries(self, tag, outputFile = None, giveCounts = True, giveRanks = False, greatestFirst = True, pandasMode = True, limitTo = None):
if giveRanks and giveCounts:
raise mkException("rankedSeries cannot return counts and ranks only one of giveRanks or giveCounts can be True.")
series... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '23']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'timeSeries'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20']}; {'id': '4', 'type': 'identifier... | def timeSeries(self, tag = None, outputFile = None, giveYears = True, greatestFirst = True, limitTo = False, pandasMode = True):
seriesDict = {}
for R in self:
try:
year = R['year']
except KeyError:
continue
if tag is None:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'cooccurrenceCounts'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': []... | def cooccurrenceCounts(self, keyTag, *countedTags):
if not isinstance(keyTag, str):
raise TagError("'{}' is not a string it cannot be used as a tag.".format(keyTag))
if len(countedTags) < 1:
TagError("You need to provide atleast one tag")
for tag in countedTags:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'getCitations'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']}; {'id': '4', 'type': 'identifier', 'children': [... | def getCitations(self, field = None, values = None, pandasFriendly = True):
retCites = []
if values is not None:
if isinstance(values, (str, int, float)) or not isinstance(values, collections.abc.Container):
values = [values]
if field is not None:
for cite... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'proQuestParser'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'pr... | def proQuestParser(proFile):
nameDict = {}
recSet = set()
error = None
lineNum = 0
try:
with open(proFile, 'r', encoding = 'utf-8') as openfile:
f = enumerate(openfile, start = 1)
for i in range(12):
lineNum, line = next(f)
while True:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'minus'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'repo_l... | def minus(repo_list_a, repo_list_b):
included = defaultdict(lambda: False)
for repo in repo_list_b:
included[repo.full_name] = True
a_minus_b = list()
for repo in repo_list_a:
if not included[repo.full_name]:
included[repo.full_name] = True
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '__clean_and_tokenize'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def __clean_and_tokenize(self, doc_list):
doc_list = filter(
lambda x: x is not None and len(x) <= GitSuggest.MAX_DESC_LEN,
doc_list,
)
cleaned_doc_list = list()
tokenizer = RegexpTokenizer(r"[a-zA-Z]+")
stopwords = self.__get_words_to_ignore()
dic... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '__get_search_results'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9']}; {'id': '4', 'type': 'identifie... | def __get_search_results(self, url, limit, order_by, sort_order, filter):
order_by_options = ['search_rank', 'series_id', 'title', 'units', 'frequency',
'seasonal_adjustment', 'realtime_start', 'realtime_end', 'last_updated',
'observation_start', 'observat... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '18']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'search'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15']}; {'id': '4', 'type': 'identifier', 'childre... | def search(self, text, limit=1000, order_by=None, sort_order=None, filter=None):
url = "%s/series/search?search_text=%s&" % (self.root_url,
quote_plus(text))
info = self.__get_search_results(url, limit, order_by, sort_order, filter)
return info |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '18']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'search_by_release'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15']}; {'id': '4', 'type': 'identifier... | def search_by_release(self, release_id, limit=0, order_by=None, sort_order=None, filter=None):
url = "%s/release/series?release_id=%d" % (self.root_url, release_id)
info = self.__get_search_results(url, limit, order_by, sort_order, filter)
if info is None:
raise ValueError('No series... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '18']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'search_by_category'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15']}; {'id': '4', 'type': 'identifie... | def search_by_category(self, category_id, limit=0, order_by=None, sort_order=None, filter=None):
url = "%s/category/series?category_id=%d&" % (self.root_url,
category_id)
info = self.__get_search_results(url, limit, order_by, sort_order, filter)
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'format_name'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'subje... | def format_name(subject):
if isinstance(subject, x509.Name):
subject = [(OID_NAME_MAPPINGS[s.oid], s.value) for s in subject]
return '/%s' % ('/'.join(['%s=%s' % (force_text(k), force_text(v)) for k, v in subject])) |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse_name'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'name'}... | def parse_name(name):
name = name.strip()
if not name:
return []
try:
items = [(NAME_CASE_MAPPINGS[t[0].upper()], force_text(t[2])) for t in NAME_RE.findall(name)]
except KeyError as e:
raise ValueError('Unknown x509 name field: %s' % e.args[0])
for key, oid in NAME_OID_MAPPI... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse_general_name'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value':... | def parse_general_name(name):
name = force_text(name)
typ = None
match = GENERAL_NAME_RE.match(name)
if match is not None:
typ, name = match.groups()
typ = typ.lower()
if typ is None:
if re.match('[a-z0-9]{2,}://', name):
try:
return x509.UniformRe... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'render'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '7']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def render(self, *args, **kwargs):
pretty = kwargs.pop("pretty", False)
if pretty and self._stable != "pretty":
self._stable = False
for arg in args:
self._stable = False
if isinstance(arg, dict):
self.inject(arg)
if kwargs:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_insert'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12']}; {'id': '4', 'type': 'identifier', 'children': [... | def _insert(self, dom_group, idx=None, prepend=False, name=None):
if idx and idx < 0:
idx = 0
if prepend:
idx = 0
else:
idx = idx if idx is not None else len(self.childs)
if dom_group is not None:
if not isinstance(dom_group, Iterable) or i... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'check_label'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def check_label(labels, required, value_regex, target_labels):
present = target_labels is not None and not set(labels).isdisjoint(set(target_labels))
if present:
if required and not value_regex:
return True
elif value_regex:
pattern = re.compile(value_regex)
p... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'receive_fmf_metadata'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': ... | def receive_fmf_metadata(name, path, object_list=False):
output = {}
fmf_tree = ExtendedTree(path)
logger.debug("get FMF metadata for test (path:%s name=%s)", path, name)
items = [x for x in fmf_tree.climb() if x.name.endswith("/" + name) and "@" not in x.name]
if object_list:
return items
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'prune_overridden'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def prune_overridden(ansi_string):
multi_seqs = set(p for p in RE_ANSI.findall(ansi_string) if ';' in p[1])
for escape, codes in multi_seqs:
r_codes = list(reversed(codes.split(';')))
try:
r_codes = r_codes[:r_codes.index('0') + 1]
except ValueError:
pass
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse_input'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def parse_input(tagged_string, disable_colors, keep_tags):
codes = ANSICodeMapping(tagged_string)
output_colors = getattr(tagged_string, 'value_colors', tagged_string)
if not keep_tags:
for tag, replacement in (('{' + k + '}', '' if v is None else '\033[%dm' % v) for k, v in codes.items()):
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'memoize'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'method'};... | def memoize(method):
cache = method.cache = collections.OrderedDict()
_get = cache.get
_popitem = cache.popitem
@functools.wraps(method)
def memoizer(instance, x, *args, **kwargs):
if not _WITH_MEMOIZATION or isinstance(x, u.Quantity):
return method(instance, x, *args, **kwargs)
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_set_value'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def _set_value(self, new_value):
if self.min_value is not None and new_value < self.min_value:
raise SettingOutOfBounds(
"Trying to set parameter {0} = {1}, which is less than the minimum allowed {2}".format(
self.name, new_value, self.min_value))
if self.... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'set_uninformative_prior'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': []... | def set_uninformative_prior(self, prior_class):
prior_instance = prior_class()
if self.min_value is None:
raise ParameterMustHaveBounds("Parameter %s does not have a defined minimum. Set one first, then re-run "
"set_uninformative_prior" % self.path)... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'find_library'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def find_library(library_root, additional_places=None):
first_guess = ctypes.util.find_library(library_root)
if first_guess is not None:
if sys.platform.lower().find("linux") >= 0:
return sanitize_lib_name(first_guess), None
elif sys.platform.lower().find("darwin") >= 0:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'LDA_discriminants'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def LDA_discriminants(x, labels):
try:
x = np.array(x)
except:
raise ValueError('Impossible to convert x to a numpy array.')
eigen_values, eigen_vectors = LDA_base(x, labels)
return eigen_values[(-eigen_values).argsort()] |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '13']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'train'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10']}; {'id': '4', 'type': 'identifier', 'children': [],... | def train(self, x, d, epochs=10, shuffle=False):
N = len(x)
if not len(d) == N:
raise ValueError('The length of vector d and matrix x must agree.')
if not len(x[0]) == self.n_input:
raise ValueError('The number of network inputs is not correct.')
if self.outputs... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'PCA_components'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'x'... | def PCA_components(x):
try:
x = np.array(x)
except:
raise ValueError('Impossible to convert x to a numpy array.')
eigen_values, eigen_vectors = np.linalg.eig(np.cov(x.T))
eigen_order = eigen_vectors.T[(-eigen_values).argsort()]
return eigen_values[(-eigen_values).argsort()] |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'add_mpl_colorbar'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']}; {'id': '4', 'type': 'identifier', 'chil... | def add_mpl_colorbar(dfr, fig, dend, params, orientation="row"):
for name in dfr.index[dend["dendrogram"]["leaves"]]:
if name not in params.classes:
params.classes[name] = name
classdict = {cls: idx for (idx, cls) in enumerate(params.classes.values())}
cblist = []
for name in dfr.ind... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'calculate_anim'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def calculate_anim(infiles, org_lengths):
logger.info("Running ANIm")
logger.info("Generating NUCmer command-lines")
deltadir = os.path.join(args.outdirname, ALIGNDIR["ANIm"])
logger.info("Writing nucmer output to %s", deltadir)
if not args.skip_nucmer:
joblist = anim.generate_nucmer_jobs(
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'unified_anib'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def unified_anib(infiles, org_lengths):
logger.info("Running %s", args.method)
blastdir = os.path.join(args.outdirname, ALIGNDIR[args.method])
logger.info("Writing BLAST output to %s", blastdir)
if not args.skip_blastn:
logger.info("Fragmenting input files, and writing to %s", args.outdirname)
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'process_deltadir'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def process_deltadir(delta_dir, org_lengths, logger=None):
deltafiles = pyani_files.get_input_files(delta_dir, ".filter")
results = ANIResults(list(org_lengths.keys()), "ANIm")
for org, length in list(org_lengths.items()):
results.alignment_lengths[org][org] = length
for deltafile in deltafiles:... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'write_contigs'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def write_contigs(asm_uid, contig_uids, batchsize=10000):
logger.info("Collecting contig data for %s", asm_uid)
asm_record = Entrez.read(
entrez_retry(
Entrez.esummary, db='assembly', id=asm_uid, rettype='text'),
validate=False)
asm_organism = asm_record['DocumentSummarySet']['Do... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'calculate_tetra_zscore'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def calculate_tetra_zscore(filename):
counts = (collections.defaultdict(int), collections.defaultdict(int),
collections.defaultdict(int), collections.defaultdict(int))
for rec in SeqIO.parse(filename, 'fasta'):
for seq in [str(rec.seq).upper(),
str(rec.seq.reverse_compl... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'calculate_correlations'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def calculate_correlations(tetra_z):
orgs = sorted(tetra_z.keys())
correlations = pd.DataFrame(index=orgs, columns=orgs,
dtype=float).fillna(1.0)
for idx, org1 in enumerate(orgs[:-1]):
for org2 in orgs[idx+1:]:
assert sorted(tetra_z[org1].keys()) == sorted... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '21']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'process_blast'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15', '18']}; {'id': '4', 'type': 'identifi... | def process_blast(
blast_dir,
org_lengths,
fraglengths=None,
mode="ANIb",
identity=0.3,
coverage=0.7,
logger=None,
):
blastfiles = pyani_files.get_input_files(blast_dir, ".blast_tab")
results = ANIResults(list(org_lengths.keys()), mode)
for org, length in list(org_lengths.items()... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '17']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'run_dependency_graph'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14']}; {'id': '4', 'type': 'identifier',... | def run_dependency_graph(jobgraph, logger=None, jgprefix="ANIm_SGE_JG",
sgegroupsize=10000, sgeargs=None):
joblist = build_joblist(jobgraph)
dep_count = 0
if logger:
logger.info("Jobs to run with scheduler")
for job in joblist:
logger.info("{0}: {1}".form... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '21']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'outputpairedstats'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10', '11', '12', '13', '14', '15',... | def outputpairedstats(fname,writemode,name1,n1,m1,se1,min1,max1,name2,n2,m2,se2,min2,max2,statname,stat,prob):
suffix = ''
try:
x = prob.shape
prob = prob[0]
except:
pass
if prob < 0.001: suffix = ' ***'
elif prob < 0.01: suffix = ' **'
elif prob < 0.05: suffix = ' ... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'GeneReader'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'f... | def GeneReader( fh, format='gff' ):
known_formats = ( 'gff', 'gtf', 'bed')
if format not in known_formats:
print('%s format not in %s' % (format, ",".join( known_formats )), file=sys.stderr)
raise Exception('?')
if format == 'bed':
for line in fh:
f = line.strip().sp... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'read_next_maf'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def read_next_maf( file, species_to_lengths=None, parse_e_rows=False ):
alignment = Alignment(species_to_lengths=species_to_lengths)
line = readline( file, skip_blank=True )
if not line: return None
fields = line.split()
if fields[0] != 'a': raise Exception("Expected 'a ...' line")
alignment.at... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse_record'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def parse_record( self, lines ):
temp_lines = []
for line in lines:
fields = line.rstrip( "\r\n" ).split( None, 1 )
if len( fields ) == 1:
fields.append( "" )
temp_lines.append( fields )
lines = temp_lines
motif = TransfacMotif()
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'tile_interval'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9']}; {'id': '4', 'type': 'identifier', 'ch... | def tile_interval( sources, index, ref_src, start, end, seq_db=None ):
assert sources[0].split('.')[0] == ref_src.split('.')[0], \
"%s != %s" % ( sources[0].split('.')[0], ref_src.split('.')[0] )
base_len = end - start
blocks = index.get( ref_src, start, end )
blocks.sort(key=lambda t: t.score)
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '23']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'binned_bitsets_proximity'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20']}; {'id': '4', 'type... | def binned_bitsets_proximity( f, chrom_col=0, start_col=1, end_col=2, strand_col=5, upstream=0, downstream=0 ):
last_chrom = None
last_bitset = None
bitsets = dict()
for line in f:
if line.startswith("
fields = line.split()
strand = "+"
if len(fields) >= strand_col + 1:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'to_file'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def to_file( Class, dict, file, is_little_endian=True ):
io = BinaryFileWriter( file, is_little_endian=is_little_endian )
start_offset = io.tell()
io.seek( start_offset + ( 8 * 256 ) )
subtables = [ [] for i in range(256) ]
for key, value in dict.items():
pair_offset ... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'transform'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def transform(elem, chain_CT_CQ, max_gap):
(chain, CT, CQ) = chain_CT_CQ
start, end = max(elem['start'], chain.tStart) - chain.tStart, min(elem['end'], chain.tEnd) - chain.tStart
assert np.all( (CT[:,1] - CT[:,0]) == (CQ[:,1] - CQ[:,0]) )
to_chrom = chain.qName
to_gab_start = chain.qStart
start_... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'visit_Method'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def visit_Method(self, method):
resolved_method = method.resolved.type
def get_params(method, extra_bindings):
result = []
for param in method.params:
resolved_param = texpr(param.resolved.type, param.resolved.bindings, extra_bindings)
result.appen... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'file_search'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [],... | def file_search(self, query, offset=None, timeout=None):
params = dict(apikey=self.api_key, query=query, offset=offset)
try:
response = requests.get(self.base + 'file/search', params=params, proxies=self.proxies, timeout=timeout)
except requests.RequestException as e:
ret... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_handle_retry'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value':... | def _handle_retry(self, resp):
exc_t, exc_v, exc_tb = sys.exc_info()
if exc_t is None:
raise TypeError('Must be called in except block.')
retry_on_exc = tuple(
(x for x in self._retry_on if inspect.isclass(x)))
retry_on_codes = tuple(
(x for x in self.... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_event_triggers'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value':... | def get_event_triggers(self):
events = {}
nvrflag = False
event_xml = []
url = '%s/ISAPI/Event/triggers' % self.root_url
try:
response = self.hik_request.get(url, timeout=CONNECT_TIMEOUT)
if response.status_code == requests.codes.not_found:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_device_info'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def get_device_info(self):
device_info = {}
url = '%s/ISAPI/System/deviceInfo' % self.root_url
using_digest = False
try:
response = self.hik_request.get(url, timeout=CONNECT_TIMEOUT)
if response.status_code == requests.codes.unauthorized:
_LOGGING.... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'alert_stream'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def alert_stream(self, reset_event, kill_event):
_LOGGING.debug('Stream Thread Started: %s, %s', self.name, self.cam_id)
start_event = False
parse_string = ""
fail_count = 0
url = '%s/ISAPI/Event/notification/alertStream' % self.root_url
while True:
try:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'construct_request'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifie... | def construct_request(ticker, fields=None, date=None,
date_from=None, date_to=None, freq=None):
if isinstance(ticker, basestring):
request = ticker
elif hasattr(ticker, '__len__'):
request = ','.join(ticker)
else:
raise ValueError('ti... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'set'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def set(self, name, value, index=-1):
if isinstance(value, ElementProxy):
value = value[0].to_er7()
name = name.upper()
reference = None if name is None else self.element.find_child_reference(name)
child_ref, child_name = (None, None) if reference is None else (reference['ref... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'init_app'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value':... | def init_app(self, app, config_prefix=None):
if 'redis' not in app.extensions:
app.extensions['redis'] = {}
self.config_prefix = config_prefix = config_prefix or 'REDIS'
if config_prefix in app.extensions['redis']:
raise ValueError('Already registered config prefix {0!r}.... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'ERROR', 'children': ['2', '348']}; {'id': '2', 'type': 'function_definition', 'children': ['3', '4', '6']}; {'id': '3', 'type': 'function_name', 'children': [], 'value': '__setup_native_run'}; {'id': '4', 'type': 'parameters', 'children': ['5']}; {'... | def __setup_native_run(self):
self.vol_opts = ['z']
self.add_env('SCUBAINIT_UMASK', '{:04o}'.format(get_umask()))
if not self.as_root:
self.add_env('SCUBAINIT_UID', os.getuid())
self.add_env('SCUBAINIT_GID', os.getgid())
if self.verbose:
self.add_env('... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12', '18']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'typed_parameter', 'children': ['5', '6']}; {... | def sort(records: Sequence[Record]) -> List[Record]:
"Sort records into a canonical order, suitable for comparison."
return sorted(records, key=_record_key) |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_issubclass_Mapping_covariant'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8', '9', '10']}; {'id': '4', 'ty... | def _issubclass_Mapping_covariant(subclass, superclass, bound_Generic, bound_typevars,
bound_typevars_readonly, follow_fwd_refs, _recursion_check):
if is_Generic(subclass):
if subclass.__origin__ is None or not issubclass(subclass.__origin__, Mapping):
return _issubclass_Generic(subc... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '21']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_isinstance'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15', '18']}; {'id': '4', 'type': 'identifier... | def _isinstance(obj, cls, bound_Generic=None, bound_typevars=None,
bound_typevars_readonly=False, follow_fwd_refs=True, _recursion_check=None):
if bound_typevars is None:
bound_typevars = {}
if is_Generic(cls) and cls.__origin__ is typing.Iterable:
if not is_iterable(obj):
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'typelogged_module'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def typelogged_module(md):
if not pytypes.typelogging_enabled:
return md
if isinstance(md, str):
if md in sys.modules:
md = sys.modules[md]
if md is None:
return md
elif md in pytypes.typechecker._pending_modules:
pytypes.typechecker._p... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'import_process_elements'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']}; {'id': '4', 'type': 'identifier',... | def import_process_elements(document, diagram_graph, sequence_flows, process_elements_dict, plane_element):
for process_element in document.getElementsByTagNameNS("*", consts.Consts.process):
BpmnDiagramGraphImport.import_process_element(process_elements_dict, process_element)
process_id... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'generate_nodes_clasification'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': []... | def generate_nodes_clasification(bpmn_diagram):
nodes_classification = {}
classification_element = "Element"
classification_start_event = "Start Event"
classification_end_event = "End Event"
task_list = bpmn_diagram.get_nodes(consts.Consts.task)
for element in task_list:
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'hclust_linearize'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def hclust_linearize(U):
from scipy.cluster import hierarchy
Z = hierarchy.ward(U)
return hierarchy.leaves_list(hierarchy.optimal_leaf_ordering(Z, U)) |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'kruskal_align'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [... | def kruskal_align(U, V, permute_U=False, permute_V=False):
unrm = [f / np.linalg.norm(f, axis=0) for f in U.factors]
vnrm = [f / np.linalg.norm(f, axis=0) for f in V.factors]
sim_matrices = [np.dot(u.T, v) for u, v in zip(unrm, vnrm)]
cost = 1 - np.mean(np.abs(sim_matrices), axis=0)
indices = Munkre... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'randn_ktensor'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [... | def randn_ktensor(shape, rank, norm=None, random_state=None):
rns = _check_random_state(random_state)
factors = KTensor([rns.standard_normal((i, rank)) for i in shape])
return _rescale_tensor(factors, norm) |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '13']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'fit'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def fit(self, X, ranks, replicates=1, verbose=True):
if not isinstance(ranks, collections.Iterable):
ranks = (ranks,)
for r in ranks:
if r not in self.results:
self.results[r] = []
if verbose:
itr = trange(replicates,
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_create_model_class'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def _create_model_class(self, model):
cls_name = model.replace('.', '_')
if sys.version_info[0] < 3:
if isinstance(cls_name, unicode):
cls_name = cls_name.encode('utf-8')
attrs = {
'_env': self,
'_odoo': self._odoo,
'_name': model,
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_init_values'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def _init_values(self, context=None):
if context is None:
context = self.env.context
basic_fields = []
for field_name in self._columns:
field = self._columns[field_name]
if not getattr(field, 'relation', False):
basic_fields.append(field_name)
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'parse_resource_id'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def parse_resource_id(rid):
if not rid:
return {}
match = _ARMID_RE.match(rid)
if match:
result = match.groupdict()
children = _CHILDREN_RE.finditer(result['children'] or '')
count = None
for count, child in enumerate(children):
result.update({
... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '26']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'lookup_instance'}; {'id': '3', 'type': 'parameters', 'children': ['4', '8', '13', '18']}; {'id': '4', 'type': 'typed_parameter', 'chi... | def lookup_instance(name: str, instance_type: str = '', image_name: str = '',
states: tuple = ('running', 'stopped', 'initializing')):
ec2 = get_ec2_resource()
instances = ec2.instances.filter(
Filters=[{'Name': 'instance-state-name', 'Values': states}])
prefix = get_prefix()
username = ... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'extract_attr_for_match'}; {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [],... | def extract_attr_for_match(items, **kwargs):
query_arg = None
for arg, value in kwargs.items():
if value == -1:
assert query_arg is None, "Only single query arg (-1 valued) is allowed"
query_arg = arg
result = []
filterset = set(kwargs.keys())
for item in items:
match = True
assert fil... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_maybe_create_resources'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'typed_default_parameter', 'child... | def _maybe_create_resources(logging_task: Task = None):
def log(*args):
if logging_task:
logging_task.log(*args)
else:
util.log(*args)
def should_create_resources():
prefix = u.get_prefix()
if u.get_keypair_name() not in u.get_keypair_dict():
log(f"Missing {u.get_keypair_name()} ke... |
{'id': '0', 'type': 'module', 'children': ['1']}; {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_set_aws_environment'}; {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'typed_default_parameter', 'children... | def _set_aws_environment(task: Task = None):
current_zone = os.environ.get('NCLUSTER_ZONE', '')
current_region = os.environ.get('AWS_DEFAULT_REGION', '')
def log(*args):
if task:
task.log(*args)
else:
util.log(*args)
if current_region and current_zone:
assert current_zone.startswith(
... |
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