sequence stringlengths 1.19k 35k | 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': 'register'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value':... | def register(self, func, order):
token = self.Token()
self._filter_order.append((order, token, func))
self._filter_order.sort(key=lambda x: x[0])
return token |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_features'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def get_features(self, jid):
response = yield from self._disco.query_info(jid)
result = set()
for feature in response.features:
try:
result.add(pubsub_xso.Feature(feature))
except ValueError:
continue
return result |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'intersect'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'se... | def intersect(self, other):
loc = self.locate_keys(other, strict=False)
return self.compress(loc, axis=0) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'locate_intersection_ranges'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'child... | def locate_intersection_ranges(self, starts, stops):
starts = asarray_ndim(starts, 1)
stops = asarray_ndim(stops, 1)
check_dim0_aligned(starts, stops)
start_indices = np.searchsorted(self, starts)
stop_indices = np.searchsorted(self, stops, side='right')
loc_ranges = star... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'locate_ranges'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': [... | def locate_ranges(self, starts, stops, strict=True):
loc, found = self.locate_intersection_ranges(starts, stops)
if strict and np.any(~found):
raise KeyError(starts[~found], stops[~found])
return loc |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'intersect_ranges'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def intersect_ranges(self, starts, stops):
loc = self.locate_ranges(starts, stops, strict=False)
return self.compress(loc, axis=0) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '25']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'from_gff3'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '15', '19', '22']}; {'id': '4', 'type': 'identifier'... | def from_gff3(path, attributes=None, region=None, score_fill=-1, phase_fill=-1,
attributes_fill='.', dtype=None):
a = gff3_to_recarray(path, attributes=attributes, region=region,
score_fill=score_fill, phase_fill=phase_fill,
attributes_... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '25']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'iter_gff3'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '15', '19', '22']}; {'id': '4', 'type': 'identifier'... | def iter_gff3(path, attributes=None, region=None, score_fill=-1,
phase_fill=-1, attributes_fill='.', tabix='tabix'):
if attributes is not None:
attributes = list(attributes)
if isinstance(attributes_fill, (list, tuple)):
if len(attributes) != len(attributes_fill):
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '28']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'gff3_to_recarray'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '15', '19', '22', '25']}; {'id': '4', 'type':... | def gff3_to_recarray(path, attributes=None, region=None, score_fill=-1,
phase_fill=-1, attributes_fill='.', tabix='tabix', dtype=None):
recs = list(iter_gff3(path, attributes=attributes, region=region,
score_fill=score_fill, phase_fill=phase_fill,
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '27']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'gff3_to_dataframe'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '15', '19', '22', '25']}; {'id': '4', 'type'... | def gff3_to_dataframe(path, attributes=None, region=None, score_fill=-1,
phase_fill=-1, attributes_fill='.', tabix='tabix', **kwargs):
import pandas
recs = list(iter_gff3(path, attributes=attributes, region=region,
score_fill=score_fill, phase_fill=phase_fill,
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'voight_painting'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'h... | def voight_painting(h):
h = HaplotypeArray(np.asarray(h), copy=False)
if h.max() > 1:
raise NotImplementedError('only biallelic variants are supported')
if h.min() < 0:
raise NotImplementedError('missing calls are not supported')
indices = h.prefix_argsort()
h = np.take(h, indices, a... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_model_perms'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'm... | def get_model_perms(model):
from django.contrib.auth.models import Permission
app_label = model._meta.app_label
model_name = model._meta.object_name.lower()
qs = Permission.objects.filter(content_type__app_label=app_label,
content_type__model=model_name)
perms = ('... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_trigger_set'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [],... | def sort_trigger_set(triggers, exclude_previous=True, say=None):
if say is None:
say = lambda x: x
trigger_object_list = []
for index, trig in enumerate(triggers):
if exclude_previous and trig[1]["previous"]:
continue
pattern = trig[0]
match, weight = re.search(RE... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_list'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'items'}... | def sort_list(items):
track = {}
def by_length(word1, word2):
return len(word2) - len(word1)
for item in items:
cword = utils.word_count(item, all=True)
if cword not in track:
track[cword] = []
track[cword].append(item)
output = []
for count in sorted(trac... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_replies'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def sort_replies(self, thats=False):
self._sorted["topics"] = {}
self._sorted["thats"] = {}
self._say("Sorting triggers...")
for topic in self._topics.keys():
self._say("Analyzing topic " + topic)
alltrig = inherit_utils.get_topic_triggers(self, topic, False)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'all'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def all(self, page=1, per_page=10, order_by="latest"):
return self._all("/photos", page=page, per_page=per_page, order_by=order_by) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'photos'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12']}; {'id': '4', 'type': 'identifier', 'children': []... | def photos(self, username, page=1, per_page=10, order_by="latest"):
url = "/users/{username}/photos".format(username=username)
result = self._photos(url, username, page=page, per_page=per_page, order_by=order_by)
return PhotoModel.parse_list(result) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'callable'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'sel... | def callable(self, nans=False):
jitfunc = nb.njit(self.func, nogil=True)
def _loop(sortidx, group_idx, a, ret):
size = len(ret)
group_idx_srt = group_idx[sortidx]
a_srt = a[sortidx]
indices = step_indices(group_idx_srt)
for i in range(len(indic... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'scores2recos'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'children': []... | def scores2recos(self, scores, candidates, rev=False):
sorted_indices = np.argsort(scores)
if rev:
sorted_indices = sorted_indices[::-1]
return candidates[sorted_indices], scores[sorted_indices] |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '16', '28']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'commutative_sequence_variable_partition_iter'}, {'id': '3', 'type': 'parameters', 'children': ['4', '8']}; {'id': '4', 'type': ... | def commutative_sequence_variable_partition_iter(values: Multiset, variables: List[VariableWithCount]
) -> Iterator[Dict[str, Multiset]]:
if len(variables) == 1:
yield from _commutative_single_variable_partiton_iter(values, variables[0])
return
gen... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'iter_cookie_browse_sorting'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def iter_cookie_browse_sorting(cookies):
'''
Get sorting-cookie from cookies dictionary.
:yields: tuple of path and sorting property
:ytype: 2-tuple of strings
'''
try:
data = cookies.get('browse-sorting', 'e30=').encode('ascii')
for path, prop in json.loads(base64.b64decode(data... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_cookie_browse_sorting'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': ... | def get_cookie_browse_sorting(path, default):
'''
Get sorting-cookie data for path of current request.
:returns: sorting property
:rtype: string
'''
if request:
for cpath, cprop in iter_cookie_browse_sorting(request.cookies):
if path == cpath:
return cprop
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'integral'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'req... | def integral(requestContext, seriesList):
results = []
for series in seriesList:
newValues = []
current = 0.0
for val in series:
if val is None:
newValues.append(None)
else:
current += val
newValues.append(current)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'map_metabolite2kegg'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def map_metabolite2kegg(metabolite):
logger.debug("Looking for KEGG compound identifier for %s.", metabolite.id)
kegg_annotation = metabolite.annotation.get("kegg.compound")
if kegg_annotation is None:
logger.warning("No kegg.compound annotation for metabolite %s.",
metabolite... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'preProcessForComparison'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children... | async def preProcessForComparison(results, target_size, size_tolerance_prct):
reference = None
for result in results:
if result.source_quality is CoverSourceQuality.REFERENCE:
if ((reference is None) or
(CoverSourceResult.compare(result,
reference... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},... | def sort(self, order="asc"):
self.__prepare()
if isinstance(self._json_data, list):
if order == "asc":
self._json_data = sorted(self._json_data)
else:
self._json_data = sorted(self._json_data, reverse=True)
return self |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_by'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def sort_by(self, property, order="asc"):
self.__prepare()
if isinstance(self._json_data, list):
if order == "asc":
self._json_data = sorted(
self._json_data,
key=lambda x: x.get(property)
)
else:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def get(dic, path, seps=PATH_SEPS, idx_reg=_JSNP_GET_ARRAY_IDX_REG):
items = [_jsnp_unescape(p) for p in _split_path(path, seps)]
if not items:
return (dic, '')
try:
if len(items) == 1:
return (dic[items[0]], '')
prnt = functools.reduce(operator.getitem, items[:-1], dic)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'groupby'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'itr'... | def groupby(itr, key_fn=None):
return itertools.groupby(sorted(itr, key=key_fn), key=key_fn) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '13']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'open'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def open(path, mode=None, ac_parser=None, **options):
psr = find(path, forced_type=ac_parser)
if mode is not None and mode.startswith('w'):
return psr.wopen(path, **options)
return psr.ropen(path, **options) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '16']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'single_load'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14']}; {'id': '4', 'type': 'identifier', 'childre... | def single_load(input_, ac_parser=None, ac_template=False,
ac_context=None, **options):
r
cnf = _single_load(input_, ac_parser=ac_parser, ac_template=ac_template,
ac_context=ac_context, **options)
schema = _maybe_schema(ac_template=ac_template, ac_context=ac_context,
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '16']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'multi_load'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14']}; {'id': '4', 'type': 'identifier', 'children... | def multi_load(inputs, ac_parser=None, ac_template=False, ac_context=None,
**options):
r
marker = options.setdefault("ac_marker", options.get("marker", '*'))
schema = _maybe_schema(ac_template=ac_template, ac_context=ac_context,
**options)
options["ac_schema"] =... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '19']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'load'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifier', 'children... | def load(path_specs, ac_parser=None, ac_dict=None, ac_template=False,
ac_context=None, **options):
r
marker = options.setdefault("ac_marker", options.get("marker", '*'))
if anyconfig.utils.is_path_like_object(path_specs, marker):
return single_load(path_specs, ac_parser=ac_parser, ac_dict=a... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'dump'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def dump(data, out, ac_parser=None, **options):
ioi = anyconfig.ioinfo.make(out)
psr = find(ioi, forced_type=ac_parser)
LOGGER.info("Dumping: %s", ioi.path)
psr.dump(data, ioi, **options) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '10']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'dumps'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def dumps(data, ac_parser=None, **options):
psr = find(None, forced_type=ac_parser)
return psr.dumps(data, **options) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14', '16']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_response'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'typed_parameter', 'children': ['5',... | def sort_response(response: Dict[str, Any]) -> OrderedDict:
root_order = ["jsonrpc", "result", "error", "id"]
error_order = ["code", "message", "data"]
req = OrderedDict(sorted(response.items(), key=lambda k: root_order.index(k[0])))
if "error" in response:
req["error"] = OrderedDict(
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14', '16']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_request'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'typed_parameter', 'children': ['5', ... | def sort_request(request: Dict[str, Any]) -> OrderedDict:
sort_order = ["jsonrpc", "method", "params", "id"]
return OrderedDict(sorted(request.items(), key=lambda k: sort_order.index(k[0]))) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '18']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'dump'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12', '15']}; {'id': '4', 'type': 'identifier', 'children'... | def dump(obj, fp, container_count=False, sort_keys=False, no_float32=True, default=None):
if not callable(fp.write):
raise TypeError('fp.write not callable')
fp_write = fp.write
__encode_value(fp_write, obj, {}, container_count, sort_keys, no_float32, default) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '7']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'torrents'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'sel... | def torrents(self, **filters):
params = {}
for name, value in filters.items():
name = 'filter' if name == 'status' else name
params[name] = value
return self._get('query/torrents', params=params) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_global_color_table'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def _get_global_color_table(colors):
global_color_table = b''.join(c[0] for c in colors.most_common())
full_table_size = 2**(1+int(get_color_table_size(len(colors)), 2))
repeats = 3 * (full_table_size - len(colors))
zeros = struct.pack('<{}x'.format(repeats))
return global_color_table + zeros |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'good_sequences_to_track'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': []... | def good_sequences_to_track(flow, motion_threshold=1.0):
endpoints = []
in_low = False
for i, val in enumerate(flow):
if val < motion_threshold:
if not in_low:
endpoints.append(i)
in_low = True
else:
if in_low:
endpoints... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_generate_comparator'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def _generate_comparator(cls, field_names):
field_names = list(field_names)
reverses = [1] * len(field_names)
for i, field_name in enumerate(field_names):
if field_name[0] == '-':
reverses[i] = -1
field_names[i] = field_name[1:]
field_names = [... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_segment_points'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def sort_segment_points(Aps, Bps):
mid = []
j = 0
mid.append(Aps[0])
for i in range(len(Aps)-1):
dist = distance_tt_point(Aps[i], Aps[i+1])
for m in range(j, len(Bps)):
distm = distance_tt_point(Aps[i], Bps[m])
if dist > distm:
direction = dot(norm... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '43']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'works'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26', '29', '32', '35', '38', '4... | def works(self, ids = None, query = None, filter = None, offset = None,
limit = None, sample = None, sort = None,
order = None, facet = None, select = None, cursor = None,
cursor_max = 5000, **kwargs):
'''
Search Crossref works
:param ids: [Array] DOIs (... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '43']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'prefixes'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26', '29', '32', '35', '38',... | def prefixes(self, ids = None, filter = None, offset = None,
limit = None, sample = None, sort = None,
order = None, facet = None, works = False, select = None,
cursor = None, cursor_max = 5000, **kwargs):
'''
Search Crossref prefixes
:param ids: [Array]... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '46']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'types'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26', '29', '32', '35', '38', '4... | def types(self, ids = None, query = None, filter = None, offset = None,
limit = None, sample = None, sort = None,
order = None, facet = None, works = False, select = None,
cursor = None, cursor_max = 5000, **kwargs):
'''
Search Crossref types
:param ids:... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '28']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'licenses'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23', '26']}; {'id': '4', 'type': '... | def licenses(self, query = None, offset = None,
limit = None, sample = None, sort = None,
order = None, facet = None, **kwargs):
'''
Search Crossref licenses
:param query: [String] A query string
:param offset: [Fixnum] Number of record to start at, from 1 to ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_graph_component'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def get_graph_component(graph):
components = map(partial(_visit, graph=graph), graph)
node_component = dict(_gen_node_component(components))
graph_component = {component: [] for component in components}
graph_component.update(
dict(_gen_graph_component(graph, node_component, _gen_graph_value)))
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'pipe_fetchdata'}, {'id': '3', 'type': 'parameters', 'children': ['4', '7', '10', '13']}; {'id': '4', 'type': 'default_parameter', 'ch... | def pipe_fetchdata(context=None, _INPUT=None, conf=None, **kwargs):
funcs = get_splits(None, conf, **cdicts(opts, kwargs))
parsed = get_parsed(_INPUT, funcs[0])
results = starmap(parse_result, parsed)
items = imap(utils.gen_items, results)
_OUTPUT = utils.multiplex(items)
return _OUTPUT |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'pipe_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '7', '10', '13']}; {'id': '4', 'type': 'default_parameter', 'childre... | def pipe_sort(context=None, _INPUT=None, conf=None, **kwargs):
test = kwargs.pop('pass_if', None)
_pass = utils.get_pass(test=test)
key_defs = imap(DotDict, utils.listize(conf['KEY']))
get_value = partial(utils.get_value, **kwargs)
parse_conf = partial(utils.parse_conf, parse_func=get_value, **kwarg... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'asyncPipeStringtokenizer'}, {'id': '3', 'type': 'parameters', 'children': ['4', '7', '10', '13']}; {'id': '4', 'type': 'default_param... | def asyncPipeStringtokenizer(context=None, _INPUT=None, conf=None, **kwargs):
conf['delimiter'] = conf.pop('to-str', dict.get(conf, 'delimiter'))
splits = yield asyncGetSplits(_INPUT, conf, **cdicts(opts, kwargs))
parsed = yield asyncDispatch(splits, *get_async_dispatch_funcs())
items = yield asyncStarM... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '24']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'alphabeta'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '17']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def alphabeta(game, alpha_beta=(-float('inf'), float('inf')),
player=dominoes.players.identity):
'''
Runs minimax search with alpha-beta pruning on the provided game.
:param Game game: game to search
:param tuple alpha_beta: a tuple of two floats that indicate
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '15']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'csv'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '12']}; {'id': '4', 'type': 'identifier', 'children': [], '... | def csv(cls,
d,
order=None,
header=None,
sort_keys=True):
first_element = list(d)[0]
def _keys():
return list(d[first_element])
def _get(element, key):
try:
tmp = str(d[element][key])
except:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'deauthorize_application'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def deauthorize_application(request):
if request.facebook:
user = User.objects.get(
facebook_id = request.facebook.signed_request.user.id
)
user.authorized = False
user.save()
return HttpResponse()
else:
return HttpResponse(status=400) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_handle_send_response'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7']}; {'id': '4', 'type': 'identifier', 'child... | def _handle_send_response(self, result, payloadsByTopicPart,
deferredsByTopicPart):
def _deliver_result(d_list, result=None):
for d in d_list:
if not isinstance(d, Deferred):
_deliver_result(d, result)
else:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'ordering_url'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': ... | def ordering_url(self, field_name):
path = self.request.path
direction = ""
query_params = self.request.GET.copy()
ordering = self.request.GET.get("order", "").split(",")
field = self._get_ordering_field_lookup(field_name)
if not ordering:
ordering = self.get_... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'load_maf'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifier', 'chil... | def load_maf(
path,
optional_cols=[],
sort_key=variant_ascending_position_sort_key,
distinct=True,
raise_on_error=True,
encoding=None):
maf_df = load_maf_dataframe(path, raise_on_error=raise_on_error, encoding=encoding)
if len(maf_df) == 0 and raise_on_error:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '34']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'load_vcf'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '25', '28', '31']}; {'id': '4', 'ty... | def load_vcf(
path,
genome=None,
reference_vcf_key="reference",
only_passing=True,
allow_extended_nucleotides=False,
include_info=True,
chunk_size=10 ** 5,
max_variants=None,
sort_key=variant_ascending_position_sort_key,
distinct=True):
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'top_expression_effect'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def top_expression_effect(self, expression_levels):
effect_expression_dict = self.effect_expression(expression_levels)
if len(effect_expression_dict) == 0:
return None
def key_fn(effect_fpkm_pair):
(effect, fpkm) = effect_fpkm_pair
return (fpkm, multi_gene_eff... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},... | def sort(self, callback=None):
items = self.items
if callback:
return self.__class__(sorted(items, key=callback))
else:
return self.__class__(sorted(items)) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'scan_for_spec'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'key... | def scan_for_spec(keyword):
keyword = keyword.lstrip('(').rstrip(')')
matches = release_line_re.findall(keyword)
if matches:
return Spec(">={}".format(matches[0]))
try:
return Spec(keyword)
except ValueError:
return None |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '26']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_students'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17', '20', '23']}; {'id': '4', 'type': 'id... | def get_students(
self,
gradebook_id='',
simple=False,
section_name='',
include_photo=False,
include_grade_info=False,
include_grade_history=False,
include_makeup_grades=False
):
params = dict(
includ... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_staff'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value'... | def get_staff(self, gradebook_id, simple=False):
staff_data = self.get(
'staff/{gradebookId}'.format(
gradebookId=gradebook_id or self.gradebook_id
),
params=None,
)
if simple:
simple_list = []
unraveled_list = self.unra... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_course_guide_staff'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [],... | def get_course_guide_staff(self, course_id=''):
staff_data = self.get(
'courseguide/course/{courseId}/staff'.format(
courseId=course_id or self.course_id
),
params=None
)
return staff_data['response']['docs'] |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '30']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'optimize'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9', '15', '18', '21', '24', '27']}; {'id': '4', 'type': 'i... | def optimize(self, problem, max_iterations=100, max_seconds=float('inf'),
cache_encoded=True, cache_solution=False, clear_cache=True,
logging_func=_print_fitnesses,
n_processes=0):
if not isinstance(problem, Problem):
raise TypeError('problem must b... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'inspect'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}, {... | def inspect(self):
inspector = stix2patterns.inspector.InspectionListener()
self.walk(inspector)
return inspector.pattern_data() |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '22']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'best_kmers'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '10', '13', '16', '19']}; {'id': '4', 'type': 'ident... | def best_kmers(dt, response, sequence, k=6, consider_shift=True, n_cores=1,
seq_align="start", trim_seq_len=None):
y = dt[response]
seq = dt[sequence]
if trim_seq_len is not None:
seq = pad_sequences(seq, align=seq_align, maxlen=trim_seq_len)
seq = [s.replace("N", "") for s in... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_custom_rdd_reduce'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def _custom_rdd_reduce(self, reduce_func):
def accumulating_iter(iterator):
acc = None
for obj in iterator:
if acc is None:
acc = obj
else:
acc = reduce_func(acc, obj)
if acc is not None:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '__sort_analyses'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 's... | def __sort_analyses(sentence):
''' Sorts analysis of all the words in the sentence.
This is required for consistency, because by default, analyses are
listed in arbitrary order; '''
for word in sentence:
if ANALYSIS not in word:
raise Exception( '(!) Error: no analysis foun... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'tag'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}, ... | def tag(self, text):
if self.search_method == 'ahocorasick':
events = self._find_keywords_ahocorasick(text.text)
elif self.search_method == 'naive':
events = self._find_keywords_naive(text.text)
events = self._resolve_conflicts(events)
if self.mapping:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'search'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def search(cls, term, fields=()):
if not any((cls._meta.search_fields, fields)):
raise AttributeError(
"A list of searchable fields must be provided in the class's "
"search_fields or provided to this function in the `fields` "
"kwarg."
)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'dependency_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'd... | def dependency_sort(dependency_tree):
sorted = []
processed = set()
for key, deps in dependency_tree.iteritems():
_sort_r(sorted, processed, key, deps, dependency_tree)
return sorted |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_sort_r'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '7', '8']}; {'id': '4', 'type': 'identifier', 'children': [],... | def _sort_r(sorted, processed, key, deps, dependency_tree):
if key in processed:
return
processed.add(key)
for dep_key in deps:
dep_deps = dependency_tree.get(dep_key)
if dep_deps is None:
log.debug('"%s" not found, skipped', Repr(dep_key))
continue
_s... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '20']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'list'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11', '14', '17']}; {'id': '4', 'type': 'identifier', 'children... | def list(self, count=30, order='user_ptime', asc=False, show_dir=True,
natsort=True):
if self.cid is None:
return False
self.reload()
kwargs = {}
kwargs['cid'] = self.cid
kwargs['asc'] = 1 if asc is True else 0
kwargs['show_dir'] = 1 if show_dir i... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'list_items'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def list_items(self, sort_key=None, reverse=False):
items = list(self.items.values())
if sort_key:
items.sort(key=sort_key, reverse=reverse)
return items |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_prepare_axes'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value':... | def _prepare_axes(node, sort_key):
links = node.links
o_links = node._overlapping_links
overlap = {ax2 for ax in links for ax2 in o_links.get(ax, [])}
axes = []
for axis in sorted(links.keys(), key=sort_key):
if axis in overlap: continue
tgt = links[axis]
if axis in o_links:
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_vid_split'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'vs... | def sort_vid_split(vs):
match = var_re.match(vs)
if match is None:
raise ValueError('Invalid variable string: {}'.format(str(vs)))
else:
return match.groups() |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'properties'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}... | def properties(self):
d = dict(self.sortinfo)
if CVARSORT in d:
del d[CVARSORT]
return d |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'build_messages_modules'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'val... | def build_messages_modules(messages):
data = collections.defaultdict(list)
for line in messages:
module_name = line.get('module')
module_path = line.get('path')
module_info = ModuleInfo(
module_name,
module_path,
)
data[module_info].append(line)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '12']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'write'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6', '9']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def write(nml, nml_path, force=False, sort=False):
if not isinstance(nml, Namelist) and isinstance(nml, dict):
nml_in = Namelist(nml)
else:
nml_in = nml
nml_in.write(nml_path, force=force, sort=sort) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'date_key'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'cls... | def date_key(cls, month_string):
month, year = month_string.split(',')
month_ord = cls.month_ordinal[month]
return year, month_ord |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'SynchronizedClassMethod'}, {'id': '3', 'type': 'parameters', 'children': ['4', '6']}; {'id': '4', 'type': 'list_splat_pattern', 'child... | def SynchronizedClassMethod(*locks_attr_names, **kwargs):
locks_attr_names = [
lock_name for lock_name in locks_attr_names if lock_name
]
if not locks_attr_names:
raise ValueError("The lock names list can't be empty")
if "sorted" not in kwargs or kwargs["sorted"]:
locks_attr_name... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '6']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '__sort_registry'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def __sort_registry(self, svc_ref):
with self.__svc_lock:
if svc_ref not in self.__svc_registry:
raise BundleException("Unknown service: {0}".format(svc_ref))
for spec in svc_ref.get_property(OBJECTCLASS):
spec_refs = self.__svc_specs[spec]
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '4']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sorted_timezones'}, {'id': '3', 'type': 'parameters', 'children': []}; {'id': '4', 'type': 'block', 'children': ['5', '59', '67', '71'... | def sorted_timezones():
def hourmin(delta):
if delta.days < 0:
hours, remaining = divmod(86400 - delta.seconds, 3600)
else:
hours, remaining = divmod(delta.seconds, 3600)
minutes, remaining = divmod(remaining, 60)
return hours, minutes
now = datetime.utcno... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'alphanum_order'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'tr... | def alphanum_order(triples):
return sorted(
triples,
key=lambda t: [
int(t) if t.isdigit() else t
for t in re.split(r'([0-9]+)', t.relation or '')
]
) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_encode_penman'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'children': [], 'v... | def _encode_penman(self, g, top=None):
if top is None:
top = g.top
remaining = set(g.triples())
variables = g.variables()
store = defaultdict(lambda: ([], []))
for t in g.triples():
if t.inverted:
store[t.target][0].append(t)
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'copy'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}, {'id... | def copy(self):
return self.__class__(self, key=self._key, load=self._load) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'copy'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'}, {'id... | def copy(self):
return self.__class__(self._key, self._load, self._iteritems()) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '8']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_group'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'd... | def sort_group(d, return_only_first=False):
''' Sort a dictionary of relative paths and cluster equal paths together at the same time '''
d_sort = sort_dict_of_paths(d)
base_elt = (-1, None)
while (base_elt[1] is None and d_sort):
base_elt = d_sort.pop(0)
if base_elt[1] is None:
retu... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'group_files_by_size_fast'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '6']}; {'id': '4', 'type': 'identifier', 'childre... | def group_files_by_size_fast(fileslist, nbgroups, mode=1):
'''Given a files list with sizes, output a list where the files are grouped in nbgroups per cluster.
Pseudo-code for algorithm in O(n log(g)) (thank's to insertion sort or binary search trees)
See for more infos: http://cs.stackexchange.com/question... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '14']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'print_'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8', '11']}; {'id': '4', 'type': 'identifier', 'children': [], 'va... | def print_(rows, limit=15, sort='size', order='descending'):
localrows = []
for row in rows:
localrows.append(list(row))
sortby = ['type', '
if sort not in sortby:
raise ValueError("invalid sort, should be one of" + str(sortby))
orders = ['ascending', 'descending']
if order not i... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'split_and_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'se... | def split_and_sort(self):
graphs = list(self.split())
graphs.sort(key=lambda x: -len(x.metadata))
for index, graph in enumerate(graphs):
graph.index = index
return graphs |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '31']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'profile'}, {'id': '3', 'type': 'parameters', 'children': ['4', '7', '10', '13', '16', '19', '22', '25']}; {'id': '4', 'type': 'defaul... | def profile(fn=None, skip=0, filename=None, immediate=False, dirs=False,
sort=None, entries=40,
profiler=('cProfile', 'profile', 'hotshot')):
if fn is None:
def decorator(fn):
return profile(fn, skip=skip, filename=filename,
immediate=immediate,... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_get_kernel_arguments'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'valu... | def _get_kernel_arguments(self):
declarations = []
for name, data in self._kernel_data.items():
declarations.extend(data.get_kernel_parameters('_' + name))
return declarations |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'topological_sort'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': '... | def topological_sort(data):
def check_self_dependencies(input_data):
for k, v in input_data.items():
if k in v:
raise ValueError('Self-dependency, {} depends on itself.'.format(k))
def prepare_input_data(input_data):
return {k: set(v) for k, v in input_data.items()}
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '11']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'get_posts'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '8']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def get_posts(self, include_draft=False, filter_functions=None):
def posts_generator(path):
if os.path.isdir(path):
for file in os.listdir(path):
filename, ext = os.path.splitext(file)
format_name = get_standard_format_name(ext[1:])
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'arbitrary_object_to_string'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], ... | def arbitrary_object_to_string(a_thing):
if a_thing is None:
return ''
if isinstance(a_thing, six.string_types):
return a_thing
if six.PY3 and isinstance(a_thing, six.binary_type):
try:
return a_thing.decode('utf-8')
except UnicodeDecodeError:
pass
... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '9']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'add_parser'}, {'id': '3', 'type': 'parameters', 'children': ['4', '5', '7']}; {'id': '4', 'type': 'identifier', 'children': [], 'value... | def add_parser(self, *args, **kwargs):
command_name = args[0]
new_kwargs = kwargs.copy()
new_kwargs['configman_subparsers_option'] = self._configman_option
new_kwargs['subparser_name'] = command_name
subparsers = self._configman_option.foreign_data.argparse.subparsers
a_s... |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': '_parse_and_sort_accept_header'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [... | def _parse_and_sort_accept_header(accept_header):
return sorted([_split_into_mimetype_and_priority(x) for x in accept_header.split(',')],
key=lambda x: x[1], reverse=True) |
{'id': '0', 'type': 'module', 'children': ['1']}, {'id': '1', 'type': 'function_definition', 'children': ['2', '3', '5']}; {'id': '2', 'type': 'function_name', 'children': [], 'value': 'sort_name'}, {'id': '3', 'type': 'parameters', 'children': ['4']}; {'id': '4', 'type': 'identifier', 'children': [], 'value': 'self'},... | def sort_name(self):
if self._record and self._record.sort_name:
return self._record.sort_name
return self.name |
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