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Jajcus/pyxmpp2
|
59e5fd7c8837991ac265dc6aad23a6bd256768a7
|
pyxmpp2/streambase.py
|
python
|
StreamBase.write_element
|
(self, element)
|
Write XML `element` to the stream.
:Parameters:
- `element`: Element node to send.
:Types:
- `element`: :etree:`ElementTree.Element`
|
Write XML `element` to the stream.
|
[
"Write",
"XML",
"element",
"to",
"the",
"stream",
"."
] |
def write_element(self, element):
"""Write XML `element` to the stream.
:Parameters:
- `element`: Element node to send.
:Types:
- `element`: :etree:`ElementTree.Element`
"""
with self.lock:
self._write_element(element)
|
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https://github.com/Jajcus/pyxmpp2/blob/59e5fd7c8837991ac265dc6aad23a6bd256768a7/pyxmpp2/streambase.py#L451-L460
|
||
caiiiac/Machine-Learning-with-Python
|
1a26c4467da41ca4ebc3d5bd789ea942ef79422f
|
MachineLearning/venv/lib/python3.5/site-packages/sklearn/multiclass.py
|
python
|
OneVsOneClassifier.decision_function
|
(self, X)
|
return Y
|
Decision function for the OneVsOneClassifier.
The decision values for the samples are computed by adding the
normalized sum of pair-wise classification confidence levels to the
votes in order to disambiguate between the decision values when the
votes for all the classes are equal leading to a tie.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
Y : array-like, shape = [n_samples, n_classes]
|
Decision function for the OneVsOneClassifier.
|
[
"Decision",
"function",
"for",
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"."
] |
def decision_function(self, X):
"""Decision function for the OneVsOneClassifier.
The decision values for the samples are computed by adding the
normalized sum of pair-wise classification confidence levels to the
votes in order to disambiguate between the decision values when the
votes for all the classes are equal leading to a tie.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
Y : array-like, shape = [n_samples, n_classes]
"""
check_is_fitted(self, 'estimators_')
indices = self.pairwise_indices_
if indices is None:
Xs = [X] * len(self.estimators_)
else:
Xs = [X[:, idx] for idx in indices]
predictions = np.vstack([est.predict(Xi)
for est, Xi in zip(self.estimators_, Xs)]).T
confidences = np.vstack([_predict_binary(est, Xi)
for est, Xi in zip(self.estimators_, Xs)]).T
Y = _ovr_decision_function(predictions,
confidences, len(self.classes_))
return Y
|
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|
|
theotherp/nzbhydra
|
4b03d7f769384b97dfc60dade4806c0fc987514e
|
libs/inspect.py
|
python
|
cleandoc
|
(doc)
|
Clean up indentation from docstrings.
Any whitespace that can be uniformly removed from the second line
onwards is removed.
|
Clean up indentation from docstrings.
|
[
"Clean",
"up",
"indentation",
"from",
"docstrings",
"."
] |
def cleandoc(doc):
"""Clean up indentation from docstrings.
Any whitespace that can be uniformly removed from the second line
onwards is removed."""
try:
lines = string.split(string.expandtabs(doc), '\n')
except UnicodeError:
return None
else:
# Find minimum indentation of any non-blank lines after first line.
margin = sys.maxint
for line in lines[1:]:
content = len(string.lstrip(line))
if content:
indent = len(line) - content
margin = min(margin, indent)
# Remove indentation.
if lines:
lines[0] = lines[0].lstrip()
if margin < sys.maxint:
for i in range(1, len(lines)): lines[i] = lines[i][margin:]
# Remove any trailing or leading blank lines.
while lines and not lines[-1]:
lines.pop()
while lines and not lines[0]:
lines.pop(0)
return string.join(lines, '\n')
|
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https://github.com/theotherp/nzbhydra/blob/4b03d7f769384b97dfc60dade4806c0fc987514e/libs/inspect.py#L369-L396
|
||
PrefectHQ/prefect
|
67bdc94e2211726d99561f6f52614bec8970e981
|
src/prefect/schedules/clocks.py
|
python
|
CronClock.events
|
(self, after: datetime = None)
|
Generator that emits clock events
Args:
- after (datetime, optional): the first result will be after this date
Returns:
- Iterable[ClockEvent]: the next scheduled events
|
Generator that emits clock events
|
[
"Generator",
"that",
"emits",
"clock",
"events"
] |
def events(self, after: datetime = None) -> Iterable[ClockEvent]:
"""
Generator that emits clock events
Args:
- after (datetime, optional): the first result will be after this date
Returns:
- Iterable[ClockEvent]: the next scheduled events
"""
tz = getattr(self.start_date, "tz", "UTC")
if after is None:
after = pendulum.now(tz)
else:
after = pendulum.instance(after).in_tz(tz)
# if there is a start date, advance to at least one second before the start (so that
# the start date itself will be registered as a valid clock date)
if self.start_date is not None:
after = max(after, self.start_date - timedelta(seconds=1)) # type: ignore
assert isinstance(after, datetime) # mypy assertion
after = pendulum.instance(after)
assert isinstance(after, pendulum.DateTime) # mypy assertion
assert isinstance(after.tz, pendulum.tz._Timezone) # mypy assertion
# croniter's DST logic interferes with all other datetime libraries except pytz
after_localized = pytz.timezone(after.tz.name).localize(
datetime(
year=after.year,
month=after.month,
day=after.day,
hour=after.hour,
minute=after.minute,
second=after.second,
microsecond=after.microsecond,
)
)
# Respect microseconds by rounding up
if after_localized.microsecond:
after_localized = after_localized + timedelta(seconds=1)
cron = croniter(self.cron, after_localized, day_or=self.day_or) # type: ignore
dates = set() # type: Set[datetime]
while True:
next_date = pendulum.instance(cron.get_next(datetime))
# because of croniter's rounding behavior, we want to avoid
# issuing the after date; we also want to avoid duplicates caused by
# DST boundary issues
if next_date.in_tz("UTC") == after.in_tz("UTC") or next_date in dates:
next_date = pendulum.instance(cron.get_next(datetime))
if self.end_date and next_date > self.end_date:
break
dates.add(next_date)
yield ClockEvent(
start_time=next_date,
parameter_defaults=self.parameter_defaults,
labels=self.labels,
)
|
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https://github.com/PrefectHQ/prefect/blob/67bdc94e2211726d99561f6f52614bec8970e981/src/prefect/schedules/clocks.py#L274-L335
|
||
andresriancho/w3af
|
cd22e5252243a87aaa6d0ddea47cf58dacfe00a9
|
w3af/core/data/dc/generic/form.py
|
python
|
Form.get_autocomplete
|
(self)
|
return self.form_params.get_autocomplete()
|
[] |
def get_autocomplete(self):
return self.form_params.get_autocomplete()
|
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] |
https://github.com/andresriancho/w3af/blob/cd22e5252243a87aaa6d0ddea47cf58dacfe00a9/w3af/core/data/dc/generic/form.py#L68-L69
|
|||
pysmt/pysmt
|
ade4dc2a825727615033a96d31c71e9f53ce4764
|
pysmt/solvers/z3.py
|
python
|
Z3Converter.__del__
|
(self)
|
[] |
def __del__(self):
# Cleaning-up Z3Converter requires dec-ref'ing the terms in the cache
if self.ctx.ref():
# Check that there is still a context object
# This might not be the case if we are using the global context
# and the interpreter is shutting down
for t in self.memoization.values():
z3.Z3_dec_ref(self.ctx.ref(), t)
|
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https://github.com/pysmt/pysmt/blob/ade4dc2a825727615033a96d31c71e9f53ce4764/pysmt/solvers/z3.py#L920-L927
|
||||
jgyates/genmon
|
2cb2ed2945f55cd8c259b09ccfa9a51e23f1341e
|
genmonlib/mymodem.py
|
python
|
MyModem.Close
|
(self)
|
[] |
def Close(self):
try:
try:
self.KillThread("SendMessageThread")
except:
pass
try:
self.SerialDevice.Close()
except:
pass
except Exception as e1:
self.LogErrorLine("Error Closing Modem: " + str(e1))
|
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https://github.com/jgyates/genmon/blob/2cb2ed2945f55cd8c259b09ccfa9a51e23f1341e/genmonlib/mymodem.py#L557-L568
|
||||
MozillaSecurity/grizzly
|
1c41478e32f323189a2c322ec041c3e0902a158a
|
grizzly/common/reporter.py
|
python
|
FuzzManagerReporter._post_submit
|
(self)
|
[] |
def _post_submit(self):
self._extra_metadata.clear()
|
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"def",
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] |
https://github.com/MozillaSecurity/grizzly/blob/1c41478e32f323189a2c322ec041c3e0902a158a/grizzly/common/reporter.py#L185-L186
|
||||
mlcommons/training
|
4a4d5a0b7efe99c680306b1940749211d4238a84
|
language_model/tensorflow/bert/cleanup_scripts/create_pretraining_data.py
|
python
|
create_masked_lm_predictions
|
(tokens, masked_lm_prob,
max_predictions_per_seq, vocab_words, rng)
|
return (output_tokens, masked_lm_positions, masked_lm_labels)
|
Creates the predictions for the masked LM objective.
|
Creates the predictions for the masked LM objective.
|
[
"Creates",
"the",
"predictions",
"for",
"the",
"masked",
"LM",
"objective",
"."
] |
def create_masked_lm_predictions(tokens, masked_lm_prob,
max_predictions_per_seq, vocab_words, rng):
"""Creates the predictions for the masked LM objective."""
cand_indexes = []
for (i, token) in enumerate(tokens):
if token == "[CLS]" or token == "[SEP]":
continue
cand_indexes.append(i)
rng.shuffle(cand_indexes)
output_tokens = list(tokens)
num_to_predict = min(max_predictions_per_seq,
max(1, int(round(len(tokens) * masked_lm_prob))))
masked_lms = []
covered_indexes = set()
for index in cand_indexes:
if len(masked_lms) >= num_to_predict:
break
if index in covered_indexes:
continue
covered_indexes.add(index)
masked_token = None
# 80% of the time, replace with [MASK]
if rng.random() < 0.8:
masked_token = "[MASK]"
else:
# 10% of the time, keep original
if rng.random() < 0.5:
masked_token = tokens[index]
# 10% of the time, replace with random word
else:
masked_token = vocab_words[rng.randint(0, len(vocab_words) - 1)]
output_tokens[index] = masked_token
masked_lms.append(MaskedLmInstance(index=index, label=tokens[index]))
masked_lms = sorted(masked_lms, key=lambda x: x.index)
masked_lm_positions = []
masked_lm_labels = []
for p in masked_lms:
masked_lm_positions.append(p.index)
masked_lm_labels.append(p.label)
return (output_tokens, masked_lm_positions, masked_lm_labels)
|
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"# 80% of the time, replace with [MASK]",
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"masked_token",
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"(",
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"-",
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")",
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"]",
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"masked_token",
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"append",
"(",
"MaskedLmInstance",
"(",
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"label",
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"(",
"masked_lms",
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":",
"x",
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"index",
")",
"masked_lm_positions",
"=",
"[",
"]",
"masked_lm_labels",
"=",
"[",
"]",
"for",
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"masked_lms",
":",
"masked_lm_positions",
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"(",
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"(",
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"label",
")",
"return",
"(",
"output_tokens",
",",
"masked_lm_positions",
",",
"masked_lm_labels",
")"
] |
https://github.com/mlcommons/training/blob/4a4d5a0b7efe99c680306b1940749211d4238a84/language_model/tensorflow/bert/cleanup_scripts/create_pretraining_data.py#L324-L374
|
|
espnet/espnet
|
ea411f3f627b8f101c211e107d0ff7053344ac80
|
espnet/nets/pytorch_backend/nets_utils.py
|
python
|
pad_list
|
(xs, pad_value)
|
return pad
|
Perform padding for the list of tensors.
Args:
xs (List): List of Tensors [(T_1, `*`), (T_2, `*`), ..., (T_B, `*`)].
pad_value (float): Value for padding.
Returns:
Tensor: Padded tensor (B, Tmax, `*`).
Examples:
>>> x = [torch.ones(4), torch.ones(2), torch.ones(1)]
>>> x
[tensor([1., 1., 1., 1.]), tensor([1., 1.]), tensor([1.])]
>>> pad_list(x, 0)
tensor([[1., 1., 1., 1.],
[1., 1., 0., 0.],
[1., 0., 0., 0.]])
|
Perform padding for the list of tensors.
|
[
"Perform",
"padding",
"for",
"the",
"list",
"of",
"tensors",
"."
] |
def pad_list(xs, pad_value):
"""Perform padding for the list of tensors.
Args:
xs (List): List of Tensors [(T_1, `*`), (T_2, `*`), ..., (T_B, `*`)].
pad_value (float): Value for padding.
Returns:
Tensor: Padded tensor (B, Tmax, `*`).
Examples:
>>> x = [torch.ones(4), torch.ones(2), torch.ones(1)]
>>> x
[tensor([1., 1., 1., 1.]), tensor([1., 1.]), tensor([1.])]
>>> pad_list(x, 0)
tensor([[1., 1., 1., 1.],
[1., 1., 0., 0.],
[1., 0., 0., 0.]])
"""
n_batch = len(xs)
max_len = max(x.size(0) for x in xs)
pad = xs[0].new(n_batch, max_len, *xs[0].size()[1:]).fill_(pad_value)
for i in range(n_batch):
pad[i, : xs[i].size(0)] = xs[i]
return pad
|
[
"def",
"pad_list",
"(",
"xs",
",",
"pad_value",
")",
":",
"n_batch",
"=",
"len",
"(",
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"max_len",
"=",
"max",
"(",
"x",
".",
"size",
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"0",
")",
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"(",
"0",
")",
"]",
"=",
"xs",
"[",
"i",
"]",
"return",
"pad"
] |
https://github.com/espnet/espnet/blob/ea411f3f627b8f101c211e107d0ff7053344ac80/espnet/nets/pytorch_backend/nets_utils.py#L34-L61
|
|
sysdream/pysqli
|
37418c9b3fbb760b97f28f6583f0d84f66bbff45
|
pysqli/core/forge.py
|
python
|
SQLForge.take
|
(self,records, index)
|
return "(%s LIMIT %d,1)" % (records, index)
|
Forge a piece of SQL returning the n-th record of a set.
|
Forge a piece of SQL returning the n-th record of a set.
|
[
"Forge",
"a",
"piece",
"of",
"SQL",
"returning",
"the",
"n",
"-",
"th",
"record",
"of",
"a",
"set",
"."
] |
def take(self,records, index):
"""
Forge a piece of SQL returning the n-th record of a set.
"""
return "(%s LIMIT %d,1)" % (records, index)
|
[
"def",
"take",
"(",
"self",
",",
"records",
",",
"index",
")",
":",
"return",
"\"(%s LIMIT %d,1)\"",
"%",
"(",
"records",
",",
"index",
")"
] |
https://github.com/sysdream/pysqli/blob/37418c9b3fbb760b97f28f6583f0d84f66bbff45/pysqli/core/forge.py#L135-L139
|
|
civicsoft/ieddit
|
2d85fe6655d0a6c9e41a098cf8dad894566e2b87
|
app/functions/db_functions.py
|
python
|
user_id_from_username
|
(username)
|
return db.session.query(Iuser.id).filter_by(username=username).first()[0]
|
returns just the id of an user
|
returns just the id of an user
|
[
"returns",
"just",
"the",
"id",
"of",
"an",
"user"
] |
def user_id_from_username(username):
"""
returns just the id of an user
"""
return db.session.query(Iuser.id).filter_by(username=username).first()[0]
|
[
"def",
"user_id_from_username",
"(",
"username",
")",
":",
"return",
"db",
".",
"session",
".",
"query",
"(",
"Iuser",
".",
"id",
")",
".",
"filter_by",
"(",
"username",
"=",
"username",
")",
".",
"first",
"(",
")",
"[",
"0",
"]"
] |
https://github.com/civicsoft/ieddit/blob/2d85fe6655d0a6c9e41a098cf8dad894566e2b87/app/functions/db_functions.py#L376-L380
|
|
DataDog/integrations-core
|
934674b29d94b70ccc008f76ea172d0cdae05e1e
|
gitlab_runner/datadog_checks/gitlab_runner/config_models/defaults.py
|
python
|
instance_kerberos_keytab
|
(field, value)
|
return get_default_field_value(field, value)
|
[] |
def instance_kerberos_keytab(field, value):
return get_default_field_value(field, value)
|
[
"def",
"instance_kerberos_keytab",
"(",
"field",
",",
"value",
")",
":",
"return",
"get_default_field_value",
"(",
"field",
",",
"value",
")"
] |
https://github.com/DataDog/integrations-core/blob/934674b29d94b70ccc008f76ea172d0cdae05e1e/gitlab_runner/datadog_checks/gitlab_runner/config_models/defaults.py#L125-L126
|
|||
knownsec/ZoomEye-python
|
30b4a69e5724fce91c1dbd7afa1b04dafb048a58
|
zoomeye/data.py
|
python
|
CliZoomEye.request_data
|
(self)
|
[] |
def request_data(self):
if os.path.exists(self.dork):
self.load()
else:
page_count = self.handle_page()
for page in range(page_count):
cache_file = Cache(self.dork, self.resource, page)
if cache_file.check() and self.force is False:
dork_data_list, self.facet_data, self.total = cache_file.load()
self.dork_data.extend(dork_data_list)
else:
if self.resource == 'host':
self.facet = ['app', 'device', 'service', 'os', 'port', 'country', 'city']
if self.resource == 'web':
self.facet = ['webapp', 'component', 'framework', 'frontend',
'server', 'waf', 'os', 'country', 'city']
try:
dork_data_list = self.zoomeye.dork_search(
dork=self.dork,
page=page + 1,
resource=self.resource,
facets=self.facet
)
except ValueError:
print("the access token expires, please re-run [zoomeye init] command."
"it is recommended to use API KEY for initialization!")
exit(0)
self.facet_data = self.zoomeye.facet_data
self.total = self.zoomeye.total
self.dork_data.extend(dork_data_list)
self.cache_dork(page, self.zoomeye.raw_data)
|
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"def",
"request_data",
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"self",
")",
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".",
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".",
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"dork",
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"'port'",
",",
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",",
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"]",
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"self",
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"(",
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".",
"dork",
",",
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",",
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"ValueError",
":",
"print",
"(",
"\"the access token expires, please re-run [zoomeye init] command.\"",
"\"it is recommended to use API KEY for initialization!\"",
")",
"exit",
"(",
"0",
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"self",
".",
"facet_data",
"=",
"self",
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"zoomeye",
".",
"facet_data",
"self",
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"self",
".",
"zoomeye",
".",
"total",
"self",
".",
"dork_data",
".",
"extend",
"(",
"dork_data_list",
")",
"self",
".",
"cache_dork",
"(",
"page",
",",
"self",
".",
"zoomeye",
".",
"raw_data",
")"
] |
https://github.com/knownsec/ZoomEye-python/blob/30b4a69e5724fce91c1dbd7afa1b04dafb048a58/zoomeye/data.py#L391-L421
|
||||
microsoft/botbuilder-python
|
3d410365461dc434df59bdfeaa2f16d28d9df868
|
libraries/botbuilder-dialogs/botbuilder/dialogs/object_path.py
|
python
|
ObjectPath.get_path_value
|
(
obj, path: str, default: Union[Callable, object] = None
)
|
return default() if callable(default) else copy.deepcopy(default)
|
Get the value for a path relative to an object.
|
Get the value for a path relative to an object.
|
[
"Get",
"the",
"value",
"for",
"a",
"path",
"relative",
"to",
"an",
"object",
"."
] |
def get_path_value(
obj, path: str, default: Union[Callable, object] = None
) -> object:
"""
Get the value for a path relative to an object.
"""
value = ObjectPath.try_get_path_value(obj, path)
if value:
return value
if default is None:
raise KeyError(f"Key {path} not found")
return default() if callable(default) else copy.deepcopy(default)
|
[
"def",
"get_path_value",
"(",
"obj",
",",
"path",
":",
"str",
",",
"default",
":",
"Union",
"[",
"Callable",
",",
"object",
"]",
"=",
"None",
")",
"->",
"object",
":",
"value",
"=",
"ObjectPath",
".",
"try_get_path_value",
"(",
"obj",
",",
"path",
")",
"if",
"value",
":",
"return",
"value",
"if",
"default",
"is",
"None",
":",
"raise",
"KeyError",
"(",
"f\"Key {path} not found\"",
")",
"return",
"default",
"(",
")",
"if",
"callable",
"(",
"default",
")",
"else",
"copy",
".",
"deepcopy",
"(",
"default",
")"
] |
https://github.com/microsoft/botbuilder-python/blob/3d410365461dc434df59bdfeaa2f16d28d9df868/libraries/botbuilder-dialogs/botbuilder/dialogs/object_path.py#L109-L122
|
|
sxjscience/HKO-7
|
adeb05a366d4b57f94a5ddb814af57cc62ffe3c5
|
nowcasting/operators/base_rnn.py
|
python
|
BaseStackRNN.split_to_concat
|
(self, split_states)
|
return concat_states
|
[] |
def split_to_concat(self, split_states):
# Concat the states together
concat_states = []
for i in range(len(self.state_info)):
channel_axis = self.state_info[i]['__layout__'].lower().find('c')
concat_states.append(mx.sym.concat(*[ele[i] for ele in split_states],
dim=channel_axis))
return concat_states
|
[
"def",
"split_to_concat",
"(",
"self",
",",
"split_states",
")",
":",
"# Concat the states together",
"concat_states",
"=",
"[",
"]",
"for",
"i",
"in",
"range",
"(",
"len",
"(",
"self",
".",
"state_info",
")",
")",
":",
"channel_axis",
"=",
"self",
".",
"state_info",
"[",
"i",
"]",
"[",
"'__layout__'",
"]",
".",
"lower",
"(",
")",
".",
"find",
"(",
"'c'",
")",
"concat_states",
".",
"append",
"(",
"mx",
".",
"sym",
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"(",
"*",
"[",
"ele",
"[",
"i",
"]",
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"in",
"split_states",
"]",
",",
"dim",
"=",
"channel_axis",
")",
")",
"return",
"concat_states"
] |
https://github.com/sxjscience/HKO-7/blob/adeb05a366d4b57f94a5ddb814af57cc62ffe3c5/nowcasting/operators/base_rnn.py#L142-L149
|
|||
python/cpython
|
e13cdca0f5224ec4e23bdd04bb3120506964bc8b
|
Mac/BuildScript/build-installer.py
|
python
|
shellQuote
|
(value)
|
return "'%s'"%(value.replace("'", "'\"'\"'"))
|
Return the string value in a form that can safely be inserted into
a shell command.
|
Return the string value in a form that can safely be inserted into
a shell command.
|
[
"Return",
"the",
"string",
"value",
"in",
"a",
"form",
"that",
"can",
"safely",
"be",
"inserted",
"into",
"a",
"shell",
"command",
"."
] |
def shellQuote(value):
"""
Return the string value in a form that can safely be inserted into
a shell command.
"""
return "'%s'"%(value.replace("'", "'\"'\"'"))
|
[
"def",
"shellQuote",
"(",
"value",
")",
":",
"return",
"\"'%s'\"",
"%",
"(",
"value",
".",
"replace",
"(",
"\"'\"",
",",
"\"'\\\"'\\\"'\"",
")",
")"
] |
https://github.com/python/cpython/blob/e13cdca0f5224ec4e23bdd04bb3120506964bc8b/Mac/BuildScript/build-installer.py#L66-L71
|
|
quip/quip-api
|
19f3b32a05ed092a70dc2c616e214aaff8a06de2
|
samples/wordpress/quip.py
|
python
|
QuipClient.get_first_list_item_id
|
(self, list_tree)
|
return None
|
Like `get_last_list_item_id`, but the first item in the list.
|
Like `get_last_list_item_id`, but the first item in the list.
|
[
"Like",
"get_last_list_item_id",
"but",
"the",
"first",
"item",
"in",
"the",
"list",
"."
] |
def get_first_list_item_id(self, list_tree):
"""Like `get_last_list_item_id`, but the first item in the list."""
for item in list_tree.iter("li"):
return item.attrib["id"]
return None
|
[
"def",
"get_first_list_item_id",
"(",
"self",
",",
"list_tree",
")",
":",
"for",
"item",
"in",
"list_tree",
".",
"iter",
"(",
"\"li\"",
")",
":",
"return",
"item",
".",
"attrib",
"[",
"\"id\"",
"]",
"return",
"None"
] |
https://github.com/quip/quip-api/blob/19f3b32a05ed092a70dc2c616e214aaff8a06de2/samples/wordpress/quip.py#L612-L616
|
|
cea-hpc/clustershell
|
c421133ed4baa69e35ff76c476d4097201485344
|
lib/ClusterShell/NodeUtils.py
|
python
|
GroupResolver.all_nodes
|
(self, namespace=None)
|
return self._list_nodes(source, 'all')
|
Find all nodes. You may specify an optional namespace.
|
Find all nodes. You may specify an optional namespace.
|
[
"Find",
"all",
"nodes",
".",
"You",
"may",
"specify",
"an",
"optional",
"namespace",
"."
] |
def all_nodes(self, namespace=None):
"""
Find all nodes. You may specify an optional namespace.
"""
source = self._source(namespace)
return self._list_nodes(source, 'all')
|
[
"def",
"all_nodes",
"(",
"self",
",",
"namespace",
"=",
"None",
")",
":",
"source",
"=",
"self",
".",
"_source",
"(",
"namespace",
")",
"return",
"self",
".",
"_list_nodes",
"(",
"source",
",",
"'all'",
")"
] |
https://github.com/cea-hpc/clustershell/blob/c421133ed4baa69e35ff76c476d4097201485344/lib/ClusterShell/NodeUtils.py#L492-L497
|
|
mjpost/sacrebleu
|
65a8a9eeccd8c0c7875e875e12edf10db33ab0ba
|
sacrebleu/utils.py
|
python
|
get_reference_files
|
(test_set: str, langpair: str)
|
return get_files(test_set, langpair)[1:]
|
Returns a list of one or more reference file paths for the given testset/langpair.
Downloads the references first if they are not already local.
:param test_set: The test set (e.g., "wmt19")
:param langpair: The language pair (e.g., "de-en")
:return: a list of one or more reference file paths
|
Returns a list of one or more reference file paths for the given testset/langpair.
Downloads the references first if they are not already local.
|
[
"Returns",
"a",
"list",
"of",
"one",
"or",
"more",
"reference",
"file",
"paths",
"for",
"the",
"given",
"testset",
"/",
"langpair",
".",
"Downloads",
"the",
"references",
"first",
"if",
"they",
"are",
"not",
"already",
"local",
"."
] |
def get_reference_files(test_set: str, langpair: str) -> List[str]:
"""
Returns a list of one or more reference file paths for the given testset/langpair.
Downloads the references first if they are not already local.
:param test_set: The test set (e.g., "wmt19")
:param langpair: The language pair (e.g., "de-en")
:return: a list of one or more reference file paths
"""
return get_files(test_set, langpair)[1:]
|
[
"def",
"get_reference_files",
"(",
"test_set",
":",
"str",
",",
"langpair",
":",
"str",
")",
"->",
"List",
"[",
"str",
"]",
":",
"return",
"get_files",
"(",
"test_set",
",",
"langpair",
")",
"[",
"1",
":",
"]"
] |
https://github.com/mjpost/sacrebleu/blob/65a8a9eeccd8c0c7875e875e12edf10db33ab0ba/sacrebleu/utils.py#L353-L362
|
|
zake7749/Chatbot
|
209d8b9fc68958e21bf9cae262727c2629527efd
|
Chatbot/task_modules/medicine/combineData.py
|
python
|
writeDDPair2file
|
(filename,dic)
|
輸出疾病與部門的配對列表
|
輸出疾病與部門的配對列表
|
[
"輸出疾病與部門的配對列表"
] |
def writeDDPair2file(filename,dic):
'''輸出疾病與部門的配對列表
'''
with open(filename,'w',encoding='utf-8') as output:
for department,diseaseSet in dic.items():
output.write(department+":")
for disease in diseaseSet:
output.write(disease+",")
output.write('\n')
|
[
"def",
"writeDDPair2file",
"(",
"filename",
",",
"dic",
")",
":",
"with",
"open",
"(",
"filename",
",",
"'w'",
",",
"encoding",
"=",
"'utf-8'",
")",
"as",
"output",
":",
"for",
"department",
",",
"diseaseSet",
"in",
"dic",
".",
"items",
"(",
")",
":",
"output",
".",
"write",
"(",
"department",
"+",
"\":\"",
")",
"for",
"disease",
"in",
"diseaseSet",
":",
"output",
".",
"write",
"(",
"disease",
"+",
"\",\"",
")",
"output",
".",
"write",
"(",
"'\\n'",
")"
] |
https://github.com/zake7749/Chatbot/blob/209d8b9fc68958e21bf9cae262727c2629527efd/Chatbot/task_modules/medicine/combineData.py#L87-L96
|
||
xtiankisutsa/MARA_Framework
|
ac4ac88bfd38f33ae8780a606ed09ab97177c562
|
tools/AndroBugs/tools/modified/androguard/patch/zipfile.py
|
python
|
ZipFile._GetContents
|
(self)
|
Read the directory, making sure we close the file if the format
is bad.
|
Read the directory, making sure we close the file if the format
is bad.
|
[
"Read",
"the",
"directory",
"making",
"sure",
"we",
"close",
"the",
"file",
"if",
"the",
"format",
"is",
"bad",
"."
] |
def _GetContents(self):
"""Read the directory, making sure we close the file if the format
is bad."""
try:
self._RealGetContents()
except BadZipfile:
if not self._filePassed:
self.fp.close()
self.fp = None
raise
|
[
"def",
"_GetContents",
"(",
"self",
")",
":",
"try",
":",
"self",
".",
"_RealGetContents",
"(",
")",
"except",
"BadZipfile",
":",
"if",
"not",
"self",
".",
"_filePassed",
":",
"self",
".",
"fp",
".",
"close",
"(",
")",
"self",
".",
"fp",
"=",
"None",
"raise"
] |
https://github.com/xtiankisutsa/MARA_Framework/blob/ac4ac88bfd38f33ae8780a606ed09ab97177c562/tools/AndroBugs/tools/modified/androguard/patch/zipfile.py#L740-L749
|
||
cosmin/stashy
|
bc627e6e2889d6df7b35f710a1944699abcf9d5f
|
stashy/repos.py
|
python
|
Repository.update
|
(self, name)
|
return self._client.put(self.url(), data=dict(name=name))
|
Update the name of a repository.
The repository's slug is derived from its name. If the name changes the slug may also change.
|
Update the name of a repository.
|
[
"Update",
"the",
"name",
"of",
"a",
"repository",
"."
] |
def update(self, name):
"""
Update the name of a repository.
The repository's slug is derived from its name. If the name changes the slug may also change.
"""
return self._client.put(self.url(), data=dict(name=name))
|
[
"def",
"update",
"(",
"self",
",",
"name",
")",
":",
"return",
"self",
".",
"_client",
".",
"put",
"(",
"self",
".",
"url",
"(",
")",
",",
"data",
"=",
"dict",
"(",
"name",
"=",
"name",
")",
")"
] |
https://github.com/cosmin/stashy/blob/bc627e6e2889d6df7b35f710a1944699abcf9d5f/stashy/repos.py#L103-L109
|
|
pytorch/contrib
|
c545fedf4f73c8e95f91fd81f2d5bf7fa9c62a61
|
torchcontrib/optim/swa.py
|
python
|
SWA.bn_update
|
(loader, model, device=None)
|
r"""Updates BatchNorm running_mean, running_var buffers in the model.
It performs one pass over data in `loader` to estimate the activation
statistics for BatchNorm layers in the model.
Args:
loader (torch.utils.data.DataLoader): dataset loader to compute the
activation statistics on. Each data batch should be either a
tensor, or a list/tuple whose first element is a tensor
containing data.
model (torch.nn.Module): model for which we seek to update BatchNorm
statistics.
device (torch.device, optional): If set, data will be trasferred to
:attr:`device` before being passed into :attr:`model`.
|
r"""Updates BatchNorm running_mean, running_var buffers in the model.
|
[
"r",
"Updates",
"BatchNorm",
"running_mean",
"running_var",
"buffers",
"in",
"the",
"model",
"."
] |
def bn_update(loader, model, device=None):
r"""Updates BatchNorm running_mean, running_var buffers in the model.
It performs one pass over data in `loader` to estimate the activation
statistics for BatchNorm layers in the model.
Args:
loader (torch.utils.data.DataLoader): dataset loader to compute the
activation statistics on. Each data batch should be either a
tensor, or a list/tuple whose first element is a tensor
containing data.
model (torch.nn.Module): model for which we seek to update BatchNorm
statistics.
device (torch.device, optional): If set, data will be trasferred to
:attr:`device` before being passed into :attr:`model`.
"""
if not _check_bn(model):
return
was_training = model.training
model.train()
momenta = {}
model.apply(_reset_bn)
model.apply(lambda module: _get_momenta(module, momenta))
n = 0
for input in loader:
if isinstance(input, (list, tuple)):
input = input[0]
b = input.size(0)
momentum = b / float(n + b)
for module in momenta.keys():
module.momentum = momentum
if device is not None:
input = input.to(device)
model(input)
n += b
model.apply(lambda module: _set_momenta(module, momenta))
model.train(was_training)
|
[
"def",
"bn_update",
"(",
"loader",
",",
"model",
",",
"device",
"=",
"None",
")",
":",
"if",
"not",
"_check_bn",
"(",
"model",
")",
":",
"return",
"was_training",
"=",
"model",
".",
"training",
"model",
".",
"train",
"(",
")",
"momenta",
"=",
"{",
"}",
"model",
".",
"apply",
"(",
"_reset_bn",
")",
"model",
".",
"apply",
"(",
"lambda",
"module",
":",
"_get_momenta",
"(",
"module",
",",
"momenta",
")",
")",
"n",
"=",
"0",
"for",
"input",
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"loader",
":",
"if",
"isinstance",
"(",
"input",
",",
"(",
"list",
",",
"tuple",
")",
")",
":",
"input",
"=",
"input",
"[",
"0",
"]",
"b",
"=",
"input",
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"size",
"(",
"0",
")",
"momentum",
"=",
"b",
"/",
"float",
"(",
"n",
"+",
"b",
")",
"for",
"module",
"in",
"momenta",
".",
"keys",
"(",
")",
":",
"module",
".",
"momentum",
"=",
"momentum",
"if",
"device",
"is",
"not",
"None",
":",
"input",
"=",
"input",
".",
"to",
"(",
"device",
")",
"model",
"(",
"input",
")",
"n",
"+=",
"b",
"model",
".",
"apply",
"(",
"lambda",
"module",
":",
"_set_momenta",
"(",
"module",
",",
"momenta",
")",
")",
"model",
".",
"train",
"(",
"was_training",
")"
] |
https://github.com/pytorch/contrib/blob/c545fedf4f73c8e95f91fd81f2d5bf7fa9c62a61/torchcontrib/optim/swa.py#L274-L316
|
||
rizkiarm/LipNet
|
bec592aa1e66378bc7ab33f6110f1c8a431b3b9a
|
lipnet/utils/spell.py
|
python
|
Spell.correction
|
(self, word)
|
return max(self.candidates(word), key=self.P)
|
Most probable spelling correction for word.
|
Most probable spelling correction for word.
|
[
"Most",
"probable",
"spelling",
"correction",
"for",
"word",
"."
] |
def correction(self, word):
"Most probable spelling correction for word."
return max(self.candidates(word), key=self.P)
|
[
"def",
"correction",
"(",
"self",
",",
"word",
")",
":",
"return",
"max",
"(",
"self",
".",
"candidates",
"(",
"word",
")",
",",
"key",
"=",
"self",
".",
"P",
")"
] |
https://github.com/rizkiarm/LipNet/blob/bec592aa1e66378bc7ab33f6110f1c8a431b3b9a/lipnet/utils/spell.py#L41-L43
|
|
ikergarcia1996/Self-Driving-Car-in-Video-Games
|
ee59b721b9590df774e553aea0bc694406894407
|
keyboard/inputsHandler.py
|
python
|
W
|
()
|
Release all keys and push W
|
Release all keys and push W
|
[
"Release",
"all",
"keys",
"and",
"push",
"W"
] |
def W() -> None:
"""
Release all keys and push W
"""
PressKey(0x11)
ReleaseKey(0x1E)
ReleaseKey(0x1F)
ReleaseKey(0x20)
|
[
"def",
"W",
"(",
")",
"->",
"None",
":",
"PressKey",
"(",
"0x11",
")",
"ReleaseKey",
"(",
"0x1E",
")",
"ReleaseKey",
"(",
"0x1F",
")",
"ReleaseKey",
"(",
"0x20",
")"
] |
https://github.com/ikergarcia1996/Self-Driving-Car-in-Video-Games/blob/ee59b721b9590df774e553aea0bc694406894407/keyboard/inputsHandler.py#L18-L25
|
||
mininet/mininet
|
8a50d3867c49781c60b6171acc6e4b46954b4281
|
examples/mobility.py
|
python
|
MobilitySwitch.addIntf
|
( self, intf, rename=False, **kwargs )
|
Add (and reparent) an interface
|
Add (and reparent) an interface
|
[
"Add",
"(",
"and",
"reparent",
")",
"an",
"interface"
] |
def addIntf( self, intf, rename=False, **kwargs ):
"Add (and reparent) an interface"
OVSSwitch.addIntf( self, intf, **kwargs )
intf.node = self
if rename:
self.renameIntf( intf )
|
[
"def",
"addIntf",
"(",
"self",
",",
"intf",
",",
"rename",
"=",
"False",
",",
"*",
"*",
"kwargs",
")",
":",
"OVSSwitch",
".",
"addIntf",
"(",
"self",
",",
"intf",
",",
"*",
"*",
"kwargs",
")",
"intf",
".",
"node",
"=",
"self",
"if",
"rename",
":",
"self",
".",
"renameIntf",
"(",
"intf",
")"
] |
https://github.com/mininet/mininet/blob/8a50d3867c49781c60b6171acc6e4b46954b4281/examples/mobility.py#L41-L46
|
||
NTMC-Community/MatchZoo
|
8a487ee5a574356fc91e4f48e219253dc11bcff2
|
matchzoo/contrib/layers/multi_perspective_layer.py
|
python
|
_mask_relevancy_matrix
|
(relevancy_matrix, mask_lt, mask_rt)
|
return relevancy_matrix
|
Mask relevancy matrix.
:param relevancy_matrix: [b, len_rt, len_lt]
:param mask_lt: [b, len_lt]
:param mask_rt: [b, len_rt]
:return: masked_matrix: [b, len_rt, len_lt]
|
Mask relevancy matrix.
|
[
"Mask",
"relevancy",
"matrix",
"."
] |
def _mask_relevancy_matrix(relevancy_matrix, mask_lt, mask_rt):
"""
Mask relevancy matrix.
:param relevancy_matrix: [b, len_rt, len_lt]
:param mask_lt: [b, len_lt]
:param mask_rt: [b, len_rt]
:return: masked_matrix: [b, len_rt, len_lt]
"""
if mask_lt is not None:
relevancy_matrix = relevancy_matrix * tf.expand_dims(mask_lt, 1)
relevancy_matrix = relevancy_matrix * tf.expand_dims(mask_rt, 2)
return relevancy_matrix
|
[
"def",
"_mask_relevancy_matrix",
"(",
"relevancy_matrix",
",",
"mask_lt",
",",
"mask_rt",
")",
":",
"if",
"mask_lt",
"is",
"not",
"None",
":",
"relevancy_matrix",
"=",
"relevancy_matrix",
"*",
"tf",
".",
"expand_dims",
"(",
"mask_lt",
",",
"1",
")",
"relevancy_matrix",
"=",
"relevancy_matrix",
"*",
"tf",
".",
"expand_dims",
"(",
"mask_rt",
",",
"2",
")",
"return",
"relevancy_matrix"
] |
https://github.com/NTMC-Community/MatchZoo/blob/8a487ee5a574356fc91e4f48e219253dc11bcff2/matchzoo/contrib/layers/multi_perspective_layer.py#L438-L450
|
|
rainofmine/Face_Attention_Network
|
68393da155da02d365e50e4118ca428eb9d24eb7
|
dataloader.py
|
python
|
AspectRatioBasedSampler.__iter__
|
(self)
|
[] |
def __iter__(self):
random.shuffle(self.groups)
for group in self.groups:
yield group
|
[
"def",
"__iter__",
"(",
"self",
")",
":",
"random",
".",
"shuffle",
"(",
"self",
".",
"groups",
")",
"for",
"group",
"in",
"self",
".",
"groups",
":",
"yield",
"group"
] |
https://github.com/rainofmine/Face_Attention_Network/blob/68393da155da02d365e50e4118ca428eb9d24eb7/dataloader.py#L452-L455
|
||||
lohriialo/photoshop-scripting-python
|
6b97da967a5d0a45e54f7c99631b29773b923f09
|
api_reference/photoshop_2021.py
|
python
|
ArtLayer.ApplyBlur
|
(self)
|
return self._oleobj_.InvokeTypes(1177563185, LCID, 1, (24, 0), (),)
|
apply the blur filter
|
apply the blur filter
|
[
"apply",
"the",
"blur",
"filter"
] |
def ApplyBlur(self):
'apply the blur filter'
return self._oleobj_.InvokeTypes(1177563185, LCID, 1, (24, 0), (),)
|
[
"def",
"ApplyBlur",
"(",
"self",
")",
":",
"return",
"self",
".",
"_oleobj_",
".",
"InvokeTypes",
"(",
"1177563185",
",",
"LCID",
",",
"1",
",",
"(",
"24",
",",
"0",
")",
",",
"(",
")",
",",
")"
] |
https://github.com/lohriialo/photoshop-scripting-python/blob/6b97da967a5d0a45e54f7c99631b29773b923f09/api_reference/photoshop_2021.py#L797-L799
|
|
twilio/twilio-python
|
6e1e811ea57a1edfadd5161ace87397c563f6915
|
twilio/rest/wireless/v1/rate_plan.py
|
python
|
RatePlanInstance.date_updated
|
(self)
|
return self._properties['date_updated']
|
:returns: The date when the resource was last updated, given as GMT in ISO 8601 format
:rtype: datetime
|
:returns: The date when the resource was last updated, given as GMT in ISO 8601 format
:rtype: datetime
|
[
":",
"returns",
":",
"The",
"date",
"when",
"the",
"resource",
"was",
"last",
"updated",
"given",
"as",
"GMT",
"in",
"ISO",
"8601",
"format",
":",
"rtype",
":",
"datetime"
] |
def date_updated(self):
"""
:returns: The date when the resource was last updated, given as GMT in ISO 8601 format
:rtype: datetime
"""
return self._properties['date_updated']
|
[
"def",
"date_updated",
"(",
"self",
")",
":",
"return",
"self",
".",
"_properties",
"[",
"'date_updated'",
"]"
] |
https://github.com/twilio/twilio-python/blob/6e1e811ea57a1edfadd5161ace87397c563f6915/twilio/rest/wireless/v1/rate_plan.py#L455-L460
|
|
jython/frozen-mirror
|
b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99
|
lib-python/2.7/modulefinder.py
|
python
|
ModuleFinder.any_missing
|
(self)
|
return missing + maybe
|
Return a list of modules that appear to be missing. Use
any_missing_maybe() if you want to know which modules are
certain to be missing, and which *may* be missing.
|
Return a list of modules that appear to be missing. Use
any_missing_maybe() if you want to know which modules are
certain to be missing, and which *may* be missing.
|
[
"Return",
"a",
"list",
"of",
"modules",
"that",
"appear",
"to",
"be",
"missing",
".",
"Use",
"any_missing_maybe",
"()",
"if",
"you",
"want",
"to",
"know",
"which",
"modules",
"are",
"certain",
"to",
"be",
"missing",
"and",
"which",
"*",
"may",
"*",
"be",
"missing",
"."
] |
def any_missing(self):
"""Return a list of modules that appear to be missing. Use
any_missing_maybe() if you want to know which modules are
certain to be missing, and which *may* be missing.
"""
missing, maybe = self.any_missing_maybe()
return missing + maybe
|
[
"def",
"any_missing",
"(",
"self",
")",
":",
"missing",
",",
"maybe",
"=",
"self",
".",
"any_missing_maybe",
"(",
")",
"return",
"missing",
"+",
"maybe"
] |
https://github.com/jython/frozen-mirror/blob/b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99/lib-python/2.7/modulefinder.py#L526-L532
|
|
ganeti/ganeti
|
d340a9ddd12f501bef57da421b5f9b969a4ba905
|
lib/hypervisor/hv_base.py
|
python
|
BaseHypervisor.VersionsSafeForMigration
|
(src, target)
|
return False
|
Decide if migration between those version is likely to suceed.
Given two versions of a hypervisor, give a guess whether live migration
from the one version to the other version is likely to succeed. The current
|
Decide if migration between those version is likely to suceed.
|
[
"Decide",
"if",
"migration",
"between",
"those",
"version",
"is",
"likely",
"to",
"suceed",
"."
] |
def VersionsSafeForMigration(src, target):
"""Decide if migration between those version is likely to suceed.
Given two versions of a hypervisor, give a guess whether live migration
from the one version to the other version is likely to succeed. The current
"""
if src == target:
return True
return False
|
[
"def",
"VersionsSafeForMigration",
"(",
"src",
",",
"target",
")",
":",
"if",
"src",
"==",
"target",
":",
"return",
"True",
"return",
"False"
] |
https://github.com/ganeti/ganeti/blob/d340a9ddd12f501bef57da421b5f9b969a4ba905/lib/hypervisor/hv_base.py#L458-L468
|
|
statsmodels/statsmodels
|
debbe7ea6ba28fe5bdb78f09f8cac694bef98722
|
statsmodels/base/model.py
|
python
|
LikelihoodModel._fit_collinear
|
(self, atol=1e-14, rtol=1e-13, **kwds)
|
return self._fit_zeros(keep_index=idx_keep, **kwds)
|
experimental, fit of the model without collinear variables
This currently uses QR to drop variables based on the given
sequence.
Options will be added in future, when the supporting functions
to identify collinear variables become available.
|
experimental, fit of the model without collinear variables
|
[
"experimental",
"fit",
"of",
"the",
"model",
"without",
"collinear",
"variables"
] |
def _fit_collinear(self, atol=1e-14, rtol=1e-13, **kwds):
"""experimental, fit of the model without collinear variables
This currently uses QR to drop variables based on the given
sequence.
Options will be added in future, when the supporting functions
to identify collinear variables become available.
"""
# ------ copied from PR #2380 remove when merged
x = self.exog
tol = atol + rtol * x.var(0)
r = np.linalg.qr(x, mode='r')
mask = np.abs(r.diagonal()) < np.sqrt(tol)
# TODO add to results instance
# idx_collinear = np.where(mask)[0]
idx_keep = np.where(~mask)[0]
return self._fit_zeros(keep_index=idx_keep, **kwds)
|
[
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"atol",
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"1e-14",
",",
"rtol",
"=",
"1e-13",
",",
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":",
"# ------ copied from PR #2380 remove when merged",
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"=",
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"_fit_zeros",
"(",
"keep_index",
"=",
"idx_keep",
",",
"*",
"*",
"kwds",
")"
] |
https://github.com/statsmodels/statsmodels/blob/debbe7ea6ba28fe5bdb78f09f8cac694bef98722/statsmodels/base/model.py#L753-L770
|
|
Source-Python-Dev-Team/Source.Python
|
d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb
|
addons/source-python/Python3/distutils/command/register.py
|
python
|
register._set_config
|
(self)
|
Reads the configuration file and set attributes.
|
Reads the configuration file and set attributes.
|
[
"Reads",
"the",
"configuration",
"file",
"and",
"set",
"attributes",
"."
] |
def _set_config(self):
''' Reads the configuration file and set attributes.
'''
config = self._read_pypirc()
if config != {}:
self.username = config['username']
self.password = config['password']
self.repository = config['repository']
self.realm = config['realm']
self.has_config = True
else:
if self.repository not in ('pypi', self.DEFAULT_REPOSITORY):
raise ValueError('%s not found in .pypirc' % self.repository)
if self.repository == 'pypi':
self.repository = self.DEFAULT_REPOSITORY
self.has_config = False
|
[
"def",
"_set_config",
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"self",
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":",
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"=",
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".",
"_read_pypirc",
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"config",
"!=",
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"=",
"self",
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"DEFAULT_REPOSITORY",
"self",
".",
"has_config",
"=",
"False"
] |
https://github.com/Source-Python-Dev-Team/Source.Python/blob/d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb/addons/source-python/Python3/distutils/command/register.py#L68-L83
|
||
TeamErlich/dna-fountain
|
4b2338b64db48ef648926748ca079ab9fbfd5dfd
|
other_screens.py
|
python
|
_toDigits
|
(n, b, width)
|
return digits.rjust(width, "0")
|
Convert a positive number n to its digit representation in base b.
width is the number of overall digits.
base MUST BE SMALLER THAN 10.
|
Convert a positive number n to its digit representation in base b.
width is the number of overall digits.
base MUST BE SMALLER THAN 10.
|
[
"Convert",
"a",
"positive",
"number",
"n",
"to",
"its",
"digit",
"representation",
"in",
"base",
"b",
".",
"width",
"is",
"the",
"number",
"of",
"overall",
"digits",
".",
"base",
"MUST",
"BE",
"SMALLER",
"THAN",
"10",
"."
] |
def _toDigits(n, b, width):
"""Convert a positive number n to its digit representation in base b.
width is the number of overall digits.
base MUST BE SMALLER THAN 10.
"""
digits = ''
while n > 0:
digits += str(n % b)
n = n // b
digits = digits[::-1] #revsersing to little endian
return digits.rjust(width, "0")
|
[
"def",
"_toDigits",
"(",
"n",
",",
"b",
",",
"width",
")",
":",
"digits",
"=",
"''",
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"0",
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"digits",
"+=",
"str",
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"n",
"%",
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"//",
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"[",
":",
":",
"-",
"1",
"]",
"#revsersing to little endian",
"return",
"digits",
".",
"rjust",
"(",
"width",
",",
"\"0\"",
")"
] |
https://github.com/TeamErlich/dna-fountain/blob/4b2338b64db48ef648926748ca079ab9fbfd5dfd/other_screens.py#L141-L153
|
|
python-telegram-bot/python-telegram-bot
|
ade1529986f5b6d394a65372d6a27045a70725b2
|
telegram/ext/contexttypes.py
|
python
|
ContextTypes.__init__
|
(
self: 'ContextTypes[CallbackContext[Dict, CD, BD], Dict, CD, BD]',
chat_data: Type[CD],
bot_data: Type[BD],
)
|
[] |
def __init__(
self: 'ContextTypes[CallbackContext[Dict, CD, BD], Dict, CD, BD]',
chat_data: Type[CD],
bot_data: Type[BD],
):
...
|
[
"def",
"__init__",
"(",
"self",
":",
"'ContextTypes[CallbackContext[Dict, CD, BD], Dict, CD, BD]'",
",",
"chat_data",
":",
"Type",
"[",
"CD",
"]",
",",
"bot_data",
":",
"Type",
"[",
"BD",
"]",
",",
")",
":",
"..."
] |
https://github.com/python-telegram-bot/python-telegram-bot/blob/ade1529986f5b6d394a65372d6a27045a70725b2/telegram/ext/contexttypes.py#L118-L123
|
||||
oracle/graalpython
|
577e02da9755d916056184ec441c26e00b70145c
|
graalpython/lib-python/3/importlib/_bootstrap_external.py
|
python
|
_validate_hash_pyc
|
(data, source_hash, name, exc_details)
|
Validate a hash-based pyc by checking the real source hash against the one in
the pyc header.
*data* is the contents of the pyc file. (Only the first 16 bytes are
required.)
*source_hash* is the importlib.util.source_hash() of the source file.
*name* is the name of the module being imported. It is used for logging.
*exc_details* is a dictionary passed to ImportError if it raised for
improved debugging.
An ImportError is raised if the bytecode is stale.
|
Validate a hash-based pyc by checking the real source hash against the one in
the pyc header.
|
[
"Validate",
"a",
"hash",
"-",
"based",
"pyc",
"by",
"checking",
"the",
"real",
"source",
"hash",
"against",
"the",
"one",
"in",
"the",
"pyc",
"header",
"."
] |
def _validate_hash_pyc(data, source_hash, name, exc_details):
"""Validate a hash-based pyc by checking the real source hash against the one in
the pyc header.
*data* is the contents of the pyc file. (Only the first 16 bytes are
required.)
*source_hash* is the importlib.util.source_hash() of the source file.
*name* is the name of the module being imported. It is used for logging.
*exc_details* is a dictionary passed to ImportError if it raised for
improved debugging.
An ImportError is raised if the bytecode is stale.
"""
if data[8:16] != source_hash:
raise ImportError(
f'hash in bytecode doesn\'t match hash of source {name!r}',
**exc_details,
)
|
[
"def",
"_validate_hash_pyc",
"(",
"data",
",",
"source_hash",
",",
"name",
",",
"exc_details",
")",
":",
"if",
"data",
"[",
"8",
":",
"16",
"]",
"!=",
"source_hash",
":",
"raise",
"ImportError",
"(",
"f'hash in bytecode doesn\\'t match hash of source {name!r}'",
",",
"*",
"*",
"exc_details",
",",
")"
] |
https://github.com/oracle/graalpython/blob/577e02da9755d916056184ec441c26e00b70145c/graalpython/lib-python/3/importlib/_bootstrap_external.py#L559-L580
|
||
windelbouwman/ppci
|
915c069e0667042c085ec42c78e9e3c9a5295324
|
ppci/build/tasks.py
|
python
|
TaskRunner.run
|
(self, project, targets=[])
|
Try to run a project
|
Try to run a project
|
[
"Try",
"to",
"run",
"a",
"project"
] |
def run(self, project, targets=[]):
""" Try to run a project """
# Determine what targets to run:
if targets:
target_list = targets
else:
if project.default:
target_list = [project.default]
else:
target_list = []
if not target_list:
self.logger.info('No targets to run!')
return
# Check for loops:
for target in target_list:
project.check_target(target)
# Calculate all dependencies:
# TODO: make this understandable:
target_list = set.union(
*[project.dependencies(t) for t in target_list])\
.union(set(target_list))
# Lookup actual targets:
target_list = [project.get_target(target_name)
for target_name in target_list]
target_list.sort()
self.logger.info('Target sequence: {}'.format(target_list))
# Run tasks:
for target in target_list:
self.logger.info('Target {} Started'.format(target.name))
for tname, props in target.tasks:
for arg in props:
props[arg] = project.expand_macros(props[arg])
task = self.get_task(tname)(target, props)
self.logger.info('Running {}'.format(task))
task.run()
self.logger.info('Target {} Ready'.format(target.name))
self.logger.info('All targets done!')
|
[
"def",
"run",
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"self",
",",
"project",
",",
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"=",
"[",
"]",
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"# Determine what targets to run:",
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"name",
")",
")",
"self",
".",
"logger",
".",
"info",
"(",
"'All targets done!'",
")"
] |
https://github.com/windelbouwman/ppci/blob/915c069e0667042c085ec42c78e9e3c9a5295324/ppci/build/tasks.py#L182-L224
|
||
whtlkeep/BAT-algorithms
|
1a339effd3719be5e94e742490e582bf4a03b7c0
|
Array & String/S_划分字母区间.py
|
python
|
partition_labels_return_len
|
(string)
|
return result
|
[] |
def partition_labels_return_len(string):
order = []
start_end = dict() # 统计每个字符的起始位置
for i, c in enumerate(string):
if c not in order:
order.append(c)
start_end[c] = [i, i]
else:
start_end[c][-1] = i
result = list()
temp = start_end[order[0]]
for k in order[1:]:
aft_se = start_end[k]
if aft_se[0] > temp[1]:
result.append(temp[1] - temp[0] + 1)
temp = aft_se
else:
temp[1] = max(temp[1], aft_se[1])
result.append(temp[1] - temp[0] + 1)
return result
|
[
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"(",
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"]",
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"-",
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"[",
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"]",
"+",
"1",
")",
"return",
"result"
] |
https://github.com/whtlkeep/BAT-algorithms/blob/1a339effd3719be5e94e742490e582bf4a03b7c0/Array & String/S_划分字母区间.py#L71-L90
|
|||
dmnfarrell/tkintertable
|
f3fc8950aaa0f087de100d671ce13c24006d9639
|
tkintertable/Plot.py
|
python
|
pylabPlotter.plotXY
|
(self, x, y, title='', xlabel=None, ylabel=None, shape=None,
clr=None, lw=1)
|
return line
|
Do x-y plot of 2 lists
|
Do x-y plot of 2 lists
|
[
"Do",
"x",
"-",
"y",
"plot",
"of",
"2",
"lists"
] |
def plotXY(self, x, y, title='', xlabel=None, ylabel=None, shape=None,
clr=None, lw=1):
"""Do x-y plot of 2 lists"""
if shape == None:
shape = self.shape
if clr == None:
clr = 'b'
if self.xscale == 1:
if self.yscale == 1:
line, = pylab.loglog(x, y, shape, color=clr, linewidth=lw)
else:
line, = pylab.semilogx(x, y, shape, color=clr, linewidth=lw)
elif self.yscale == 1:
line, = pylab.semilogy(x, y, shape, color=clr, linewidth=lw)
else:
line, = pylab.plot(x, y, shape, color=clr, linewidth=lw)
return line
|
[
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] |
https://github.com/dmnfarrell/tkintertable/blob/f3fc8950aaa0f087de100d671ce13c24006d9639/tkintertable/Plot.py#L92-L108
|
|
graalvm/mx
|
29c0debab406352df3af246be2f8973be5db69ae
|
mx_ide_eclipse.py
|
python
|
_source_locator_memento
|
(deps, jdk=None)
|
return slm, sources
|
[] |
def _source_locator_memento(deps, jdk=None):
slm = mx.XMLDoc()
slm.open('sourceLookupDirector')
slm.open('sourceContainers', {'duplicates' : 'false'})
javaCompliance = None
sources = []
for dep in deps:
if dep.isLibrary():
if hasattr(dep, 'eclipse.container'):
memento = mx.XMLDoc().element('classpathContainer', {'path' : getattr(dep, 'eclipse.container')}).xml(standalone='no')
slm.element('classpathContainer', {'memento' : memento, 'typeId':'org.eclipse.jdt.launching.sourceContainer.classpathContainer'})
sources.append(getattr(dep, 'eclipse.container') +' [classpathContainer]')
elif dep.get_source_path(resolve=True):
memento = mx.XMLDoc().element('archive', {'detectRoot' : 'true', 'path' : dep.get_source_path(resolve=True)}).xml(standalone='no')
slm.element('container', {'memento' : memento, 'typeId':'org.eclipse.debug.core.containerType.externalArchive'})
sources.append(dep.get_source_path(resolve=True) + ' [externalArchive]')
elif dep.isJdkLibrary():
if jdk is None:
jdk = mx.get_jdk(tag='default')
path = dep.get_source_path(jdk)
if path:
if os.path.isdir(path):
memento = mx.XMLDoc().element('directory', {'nest' : 'false', 'path' : path}).xml(standalone='no')
slm.element('container', {'memento' : memento, 'typeId':'org.eclipse.debug.core.containerType.directory'})
sources.append(path + ' [directory]')
else:
memento = mx.XMLDoc().element('archive', {'detectRoot' : 'true', 'path' : path}).xml(standalone='no')
slm.element('container', {'memento' : memento, 'typeId':'org.eclipse.debug.core.containerType.externalArchive'})
sources.append(path + ' [externalArchive]')
elif dep.isProject():
if not dep.isJavaProject():
continue
memento = mx.XMLDoc().element('javaProject', {'name' : dep.name}).xml(standalone='no')
slm.element('container', {'memento' : memento, 'typeId':'org.eclipse.jdt.launching.sourceContainer.javaProject'})
sources.append(dep.name + ' [javaProject]')
if javaCompliance is None or dep.javaCompliance > javaCompliance:
javaCompliance = dep.javaCompliance
if javaCompliance:
jdkContainer = 'org.eclipse.jdt.launching.JRE_CONTAINER/org.eclipse.jdt.internal.debug.ui.launcher.StandardVMType/' + _to_EclipseJRESystemLibrary(javaCompliance)
memento = mx.XMLDoc().element('classpathContainer', {'path' : jdkContainer}).xml(standalone='no')
slm.element('classpathContainer', {'memento' : memento, 'typeId':'org.eclipse.jdt.launching.sourceContainer.classpathContainer'})
sources.append(jdkContainer + ' [classpathContainer]')
else:
memento = mx.XMLDoc().element('classpathContainer', {'path' : 'org.eclipse.jdt.launching.JRE_CONTAINER'}).xml(standalone='no')
slm.element('classpathContainer', {'memento' : memento, 'typeId':'org.eclipse.jdt.launching.sourceContainer.classpathContainer'})
sources.append('org.eclipse.jdt.launching.JRE_CONTAINER [classpathContainer]')
slm.close('sourceContainers')
slm.close('sourceLookupDirector')
return slm, sources
|
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] |
https://github.com/graalvm/mx/blob/29c0debab406352df3af246be2f8973be5db69ae/mx_ide_eclipse.py#L261-L313
|
|||
PowerScript/KatanaFramework
|
0f6ad90a88de865d58ec26941cb4460501e75496
|
lib/IPy/IPy.py
|
python
|
IPint.__str__
|
(self)
|
return self.strCompressed()
|
Dispatch to the prefered String Representation.
Used to implement str(IP).
|
Dispatch to the prefered String Representation.
|
[
"Dispatch",
"to",
"the",
"prefered",
"String",
"Representation",
"."
] |
def __str__(self):
"""Dispatch to the prefered String Representation.
Used to implement str(IP)."""
return self.strCompressed()
|
[
"def",
"__str__",
"(",
"self",
")",
":",
"return",
"self",
".",
"strCompressed",
"(",
")"
] |
https://github.com/PowerScript/KatanaFramework/blob/0f6ad90a88de865d58ec26941cb4460501e75496/lib/IPy/IPy.py#L684-L689
|
|
NoGameNoLife00/mybolg
|
afe17ea5bfe405e33766e5682c43a4262232ee12
|
libs/werkzeug/urls.py
|
python
|
url_encode_stream
|
(obj, stream=None, charset='utf-8', encode_keys=False,
sort=False, key=None, separator=b'&')
|
Like :meth:`url_encode` but writes the results to a stream
object. If the stream is `None` a generator over all encoded
pairs is returned.
.. versionadded:: 0.8
:param obj: the object to encode into a query string.
:param stream: a stream to write the encoded object into or `None` if
an iterator over the encoded pairs should be returned. In
that case the separator argument is ignored.
:param charset: the charset of the query string.
:param encode_keys: set to `True` if you have unicode keys. (Ignored on
Python 3.x)
:param sort: set to `True` if you want parameters to be sorted by `key`.
:param separator: the separator to be used for the pairs.
:param key: an optional function to be used for sorting. For more details
check out the :func:`sorted` documentation.
|
Like :meth:`url_encode` but writes the results to a stream
object. If the stream is `None` a generator over all encoded
pairs is returned.
|
[
"Like",
":",
"meth",
":",
"url_encode",
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"to",
"a",
"stream",
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"is",
"None",
"a",
"generator",
"over",
"all",
"encoded",
"pairs",
"is",
"returned",
"."
] |
def url_encode_stream(obj, stream=None, charset='utf-8', encode_keys=False,
sort=False, key=None, separator=b'&'):
"""Like :meth:`url_encode` but writes the results to a stream
object. If the stream is `None` a generator over all encoded
pairs is returned.
.. versionadded:: 0.8
:param obj: the object to encode into a query string.
:param stream: a stream to write the encoded object into or `None` if
an iterator over the encoded pairs should be returned. In
that case the separator argument is ignored.
:param charset: the charset of the query string.
:param encode_keys: set to `True` if you have unicode keys. (Ignored on
Python 3.x)
:param sort: set to `True` if you want parameters to be sorted by `key`.
:param separator: the separator to be used for the pairs.
:param key: an optional function to be used for sorting. For more details
check out the :func:`sorted` documentation.
"""
separator = to_native(separator, 'ascii')
gen = _url_encode_impl(obj, charset, encode_keys, sort, key)
if stream is None:
return gen
for idx, chunk in enumerate(gen):
if idx:
stream.write(separator)
stream.write(chunk)
|
[
"def",
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https://github.com/NoGameNoLife00/mybolg/blob/afe17ea5bfe405e33766e5682c43a4262232ee12/libs/werkzeug/urls.py#L811-L838
|
||
realpython/book2-exercises
|
cde325eac8e6d8cff2316601c2e5b36bb46af7d0
|
web2py/venv/lib/python2.7/site-packages/pip/_vendor/distlib/metadata.py
|
python
|
LegacyMetadata.read
|
(self, filepath)
|
Read the metadata values from a file path.
|
Read the metadata values from a file path.
|
[
"Read",
"the",
"metadata",
"values",
"from",
"a",
"file",
"path",
"."
] |
def read(self, filepath):
"""Read the metadata values from a file path."""
fp = codecs.open(filepath, 'r', encoding='utf-8')
try:
self.read_file(fp)
finally:
fp.close()
|
[
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] |
https://github.com/realpython/book2-exercises/blob/cde325eac8e6d8cff2316601c2e5b36bb46af7d0/web2py/venv/lib/python2.7/site-packages/pip/_vendor/distlib/metadata.py#L330-L336
|
||
UCL-INGI/INGInious
|
60f10cb4c375ce207471043e76bd813220b95399
|
inginious/frontend/pages/api/_api_page.py
|
python
|
APIPage.POST
|
(self, *args, **kwargs)
|
return self._handle_api(self.API_POST, args, kwargs)
|
POST request
|
POST request
|
[
"POST",
"request"
] |
def POST(self, *args, **kwargs):
""" POST request """
return self._handle_api(self.API_POST, args, kwargs)
|
[
"def",
"POST",
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"_handle_api",
"(",
"self",
".",
"API_POST",
",",
"args",
",",
"kwargs",
")"
] |
https://github.com/UCL-INGI/INGInious/blob/60f10cb4c375ce207471043e76bd813220b95399/inginious/frontend/pages/api/_api_page.py#L27-L29
|
|
francisck/DanderSpritz_docs
|
86bb7caca5a957147f120b18bb5c31f299914904
|
Python/Core/Lib/decimal.py
|
python
|
Decimal.logical_and
|
(self, other, context=None)
|
Applies an 'and' operation between self and other's digits.
|
Applies an 'and' operation between self and other's digits.
|
[
"Applies",
"an",
"and",
"operation",
"between",
"self",
"and",
"other",
"s",
"digits",
"."
] |
def logical_and(self, other, context=None):
"""Applies an 'and' operation between self and other's digits."""
if context is None:
context = getcontext()
other = _convert_other(other, raiseit=True)
if not self._islogical() or not other._islogical():
return context._raise_error(InvalidOperation)
else:
opa, opb = self._fill_logical(context, self._int, other._int)
result = ''.join([ str(int(a) & int(b)) for a, b in zip(opa, opb) ])
return _dec_from_triple(0, result.lstrip('0') or '0', 0)
|
[
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https://github.com/francisck/DanderSpritz_docs/blob/86bb7caca5a957147f120b18bb5c31f299914904/Python/Core/Lib/decimal.py#L2588-L2598
|
||
agronholm/anyio
|
ac3e7c619913bd0ddf9c36b6e633b278d07405b7
|
src/anyio/_core/_synchronization.py
|
python
|
Condition.statistics
|
(self)
|
return ConditionStatistics(len(self._waiters), self._lock.statistics())
|
Return statistics about the current state of this condition.
.. versionadded:: 3.0
|
Return statistics about the current state of this condition.
|
[
"Return",
"statistics",
"about",
"the",
"current",
"state",
"of",
"this",
"condition",
"."
] |
def statistics(self) -> ConditionStatistics:
"""
Return statistics about the current state of this condition.
.. versionadded:: 3.0
"""
return ConditionStatistics(len(self._waiters), self._lock.statistics())
|
[
"def",
"statistics",
"(",
"self",
")",
"->",
"ConditionStatistics",
":",
"return",
"ConditionStatistics",
"(",
"len",
"(",
"self",
".",
"_waiters",
")",
",",
"self",
".",
"_lock",
".",
"statistics",
"(",
")",
")"
] |
https://github.com/agronholm/anyio/blob/ac3e7c619913bd0ddf9c36b6e633b278d07405b7/src/anyio/_core/_synchronization.py#L264-L270
|
|
cltk/cltk
|
1a8c2f5ef72389e2579dfce1fa5af8e59ebc9ec1
|
src/cltk/lemmatize/lat.py
|
python
|
LatinBackoffLemmatizer.__repr__
|
(self: object)
|
return f"<BackoffLatinLemmatizer v0.2>"
|
[] |
def __repr__(self: object):
return f"<BackoffLatinLemmatizer v0.2>"
|
[
"def",
"__repr__",
"(",
"self",
":",
"object",
")",
":",
"return",
"f\"<BackoffLatinLemmatizer v0.2>\""
] |
https://github.com/cltk/cltk/blob/1a8c2f5ef72389e2579dfce1fa5af8e59ebc9ec1/src/cltk/lemmatize/lat.py#L601-L602
|
|||
pyqt/examples
|
843bb982917cecb2350b5f6d7f42c9b7fb142ec1
|
src/pyqt-official/qml/referenceexamples/default.py
|
python
|
BirthdayParty.guests
|
(self)
|
return QQmlListProperty(Person, self, self._guests)
|
[] |
def guests(self):
return QQmlListProperty(Person, self, self._guests)
|
[
"def",
"guests",
"(",
"self",
")",
":",
"return",
"QQmlListProperty",
"(",
"Person",
",",
"self",
",",
"self",
".",
"_guests",
")"
] |
https://github.com/pyqt/examples/blob/843bb982917cecb2350b5f6d7f42c9b7fb142ec1/src/pyqt-official/qml/referenceexamples/default.py#L119-L120
|
|||
LudovicRousseau/pyscard
|
c0a5e2f626be69a0fc7b530631471cf014e4b20e
|
smartcard/System.py
|
python
|
readers
|
(groups=[])
|
return smartcard.reader.ReaderFactory.ReaderFactory.readers(groups)
|
Returns the list of smartcard readers in groups.
If group is not specified, returns the list of all smartcard readers.
import smartcard
r=smartcard.readers()
r=smartcard.readers(['SCard$DefaultReaders', 'MyReaderGroup'])
|
Returns the list of smartcard readers in groups.
|
[
"Returns",
"the",
"list",
"of",
"smartcard",
"readers",
"in",
"groups",
"."
] |
def readers(groups=[]):
"""Returns the list of smartcard readers in groups.
If group is not specified, returns the list of all smartcard readers.
import smartcard
r=smartcard.readers()
r=smartcard.readers(['SCard$DefaultReaders', 'MyReaderGroup'])
"""
return smartcard.reader.ReaderFactory.ReaderFactory.readers(groups)
|
[
"def",
"readers",
"(",
"groups",
"=",
"[",
"]",
")",
":",
"return",
"smartcard",
".",
"reader",
".",
"ReaderFactory",
".",
"ReaderFactory",
".",
"readers",
"(",
"groups",
")"
] |
https://github.com/LudovicRousseau/pyscard/blob/c0a5e2f626be69a0fc7b530631471cf014e4b20e/smartcard/System.py#L31-L41
|
|
quantumblacklabs/causalnex
|
127d9324a3d68c1795299c7522f22cdea880f344
|
causalnex/network/network.py
|
python
|
BayesianNetwork.cpds
|
(self)
|
return cpds
|
Conditional Probability Distributions of each node within the Bayesian Network.
The row-index of each dataframe is all possible states for the node.
The col-index of each dataframe is a MultiIndex that describes all possible permutations of parent states.
For example, for a node :math:`P(A | B, D)`, where
.. math::
- A \\in \\text{{"a", "b", "c", "d"}}
- B \\in \\text{{"x", "y", "z"}}
- C \\in \\text{{False, True}}
>>> b x y z
>>> d False True False True False True
>>> a
>>> a 0.265306 0.214286 0.066667 0.25 0.444444 0.000000
>>> b 0.183673 0.214286 0.200000 0.25 0.222222 0.666667
>>> c 0.285714 0.285714 0.400000 0.25 0.333333 0.333333
>>> d 0.265306 0.285714 0.333333 0.25 0.000000 0.000000
Returns:
Conditional Probability Distributions of each node within the Bayesian Network.
|
Conditional Probability Distributions of each node within the Bayesian Network.
|
[
"Conditional",
"Probability",
"Distributions",
"of",
"each",
"node",
"within",
"the",
"Bayesian",
"Network",
"."
] |
def cpds(self) -> Dict[str, pd.DataFrame]:
"""
Conditional Probability Distributions of each node within the Bayesian Network.
The row-index of each dataframe is all possible states for the node.
The col-index of each dataframe is a MultiIndex that describes all possible permutations of parent states.
For example, for a node :math:`P(A | B, D)`, where
.. math::
- A \\in \\text{{"a", "b", "c", "d"}}
- B \\in \\text{{"x", "y", "z"}}
- C \\in \\text{{False, True}}
>>> b x y z
>>> d False True False True False True
>>> a
>>> a 0.265306 0.214286 0.066667 0.25 0.444444 0.000000
>>> b 0.183673 0.214286 0.200000 0.25 0.222222 0.666667
>>> c 0.285714 0.285714 0.400000 0.25 0.333333 0.333333
>>> d 0.265306 0.285714 0.333333 0.25 0.000000 0.000000
Returns:
Conditional Probability Distributions of each node within the Bayesian Network.
"""
cpds = {}
for cpd in self._model.cpds:
names = cpd.variables[1:]
cols = [""]
if names:
cols = pd.MultiIndex.from_product(
[sorted(self._node_states[var].keys()) for var in names],
names=names,
)
cpds[cpd.variable] = pd.DataFrame(
cpd.values.reshape(
len(self._node_states[cpd.variable]), max(1, len(cols))
)
)
cpds[cpd.variable][cpd.variable] = sorted(
self._node_states[cpd.variable].keys()
)
cpds[cpd.variable].set_index([cpd.variable], inplace=True)
cpds[cpd.variable].columns = cols
return cpds
|
[
"def",
"cpds",
"(",
"self",
")",
"->",
"Dict",
"[",
"str",
",",
"pd",
".",
"DataFrame",
"]",
":",
"cpds",
"=",
"{",
"}",
"for",
"cpd",
"in",
"self",
".",
"_model",
".",
"cpds",
":",
"names",
"=",
"cpd",
".",
"variables",
"[",
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":",
"]",
"cols",
"=",
"[",
"\"\"",
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"if",
"names",
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"MultiIndex",
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"from_product",
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"[",
"sorted",
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"var",
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".",
"keys",
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",",
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"=",
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",",
")",
"cpds",
"[",
"cpd",
".",
"variable",
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"=",
"pd",
".",
"DataFrame",
"(",
"cpd",
".",
"values",
".",
"reshape",
"(",
"len",
"(",
"self",
".",
"_node_states",
"[",
"cpd",
".",
"variable",
"]",
")",
",",
"max",
"(",
"1",
",",
"len",
"(",
"cols",
")",
")",
")",
")",
"cpds",
"[",
"cpd",
".",
"variable",
"]",
"[",
"cpd",
".",
"variable",
"]",
"=",
"sorted",
"(",
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".",
"_node_states",
"[",
"cpd",
".",
"variable",
"]",
".",
"keys",
"(",
")",
")",
"cpds",
"[",
"cpd",
".",
"variable",
"]",
".",
"set_index",
"(",
"[",
"cpd",
".",
"variable",
"]",
",",
"inplace",
"=",
"True",
")",
"cpds",
"[",
"cpd",
".",
"variable",
"]",
".",
"columns",
"=",
"cols",
"return",
"cpds"
] |
https://github.com/quantumblacklabs/causalnex/blob/127d9324a3d68c1795299c7522f22cdea880f344/causalnex/network/network.py#L225-L272
|
|
HSLCY/ABSA-BERT-pair
|
7d238eb8c772946b9e572373c144b11151e4187f
|
processor.py
|
python
|
Semeval_NLI_B_Processor.get_train_examples
|
(self, data_dir)
|
return self._create_examples(train_data, "train")
|
See base class.
|
See base class.
|
[
"See",
"base",
"class",
"."
] |
def get_train_examples(self, data_dir):
"""See base class."""
train_data = pd.read_csv(os.path.join(data_dir, "train_NLI_B.csv"),header=None,sep="\t").values
return self._create_examples(train_data, "train")
|
[
"def",
"get_train_examples",
"(",
"self",
",",
"data_dir",
")",
":",
"train_data",
"=",
"pd",
".",
"read_csv",
"(",
"os",
".",
"path",
".",
"join",
"(",
"data_dir",
",",
"\"train_NLI_B.csv\"",
")",
",",
"header",
"=",
"None",
",",
"sep",
"=",
"\"\\t\"",
")",
".",
"values",
"return",
"self",
".",
"_create_examples",
"(",
"train_data",
",",
"\"train\"",
")"
] |
https://github.com/HSLCY/ABSA-BERT-pair/blob/7d238eb8c772946b9e572373c144b11151e4187f/processor.py#L397-L400
|
|
ni/nidaqmx-python
|
62fc6b48cbbb330fe1bcc9aedadc86610a1269b6
|
nidaqmx/_task_modules/channels/ai_channel.py
|
python
|
AIChannel.ai_accel_4_wire_dc_voltage_sensitivity_units
|
(self)
|
[] |
def ai_accel_4_wire_dc_voltage_sensitivity_units(self):
cfunc = (lib_importer.windll.
DAQmxResetAIAccel4WireDCVoltageSensitivityUnits)
if cfunc.argtypes is None:
with cfunc.arglock:
if cfunc.argtypes is None:
cfunc.argtypes = [
lib_importer.task_handle, ctypes_byte_str]
error_code = cfunc(
self._handle, self._name)
check_for_error(error_code)
|
[
"def",
"ai_accel_4_wire_dc_voltage_sensitivity_units",
"(",
"self",
")",
":",
"cfunc",
"=",
"(",
"lib_importer",
".",
"windll",
".",
"DAQmxResetAIAccel4WireDCVoltageSensitivityUnits",
")",
"if",
"cfunc",
".",
"argtypes",
"is",
"None",
":",
"with",
"cfunc",
".",
"arglock",
":",
"if",
"cfunc",
".",
"argtypes",
"is",
"None",
":",
"cfunc",
".",
"argtypes",
"=",
"[",
"lib_importer",
".",
"task_handle",
",",
"ctypes_byte_str",
"]",
"error_code",
"=",
"cfunc",
"(",
"self",
".",
"_handle",
",",
"self",
".",
"_name",
")",
"check_for_error",
"(",
"error_code",
")"
] |
https://github.com/ni/nidaqmx-python/blob/62fc6b48cbbb330fe1bcc9aedadc86610a1269b6/nidaqmx/_task_modules/channels/ai_channel.py#L289-L300
|
||||
naftaliharris/tauthon
|
5587ceec329b75f7caf6d65a036db61ac1bae214
|
Lib/site.py
|
python
|
aliasmbcs
|
()
|
On Windows, some default encodings are not provided by Python,
while they are always available as "mbcs" in each locale. Make
them usable by aliasing to "mbcs" in such a case.
|
On Windows, some default encodings are not provided by Python,
while they are always available as "mbcs" in each locale. Make
them usable by aliasing to "mbcs" in such a case.
|
[
"On",
"Windows",
"some",
"default",
"encodings",
"are",
"not",
"provided",
"by",
"Python",
"while",
"they",
"are",
"always",
"available",
"as",
"mbcs",
"in",
"each",
"locale",
".",
"Make",
"them",
"usable",
"by",
"aliasing",
"to",
"mbcs",
"in",
"such",
"a",
"case",
"."
] |
def aliasmbcs():
"""On Windows, some default encodings are not provided by Python,
while they are always available as "mbcs" in each locale. Make
them usable by aliasing to "mbcs" in such a case."""
if sys.platform == 'win32':
import locale, codecs
enc = locale.getdefaultlocale()[1]
if enc.startswith('cp'): # "cp***" ?
try:
codecs.lookup(enc)
except LookupError:
import encodings
encodings._cache[enc] = encodings._unknown
encodings.aliases.aliases[enc] = 'mbcs'
|
[
"def",
"aliasmbcs",
"(",
")",
":",
"if",
"sys",
".",
"platform",
"==",
"'win32'",
":",
"import",
"locale",
",",
"codecs",
"enc",
"=",
"locale",
".",
"getdefaultlocale",
"(",
")",
"[",
"1",
"]",
"if",
"enc",
".",
"startswith",
"(",
"'cp'",
")",
":",
"# \"cp***\" ?",
"try",
":",
"codecs",
".",
"lookup",
"(",
"enc",
")",
"except",
"LookupError",
":",
"import",
"encodings",
"encodings",
".",
"_cache",
"[",
"enc",
"]",
"=",
"encodings",
".",
"_unknown",
"encodings",
".",
"aliases",
".",
"aliases",
"[",
"enc",
"]",
"=",
"'mbcs'"
] |
https://github.com/naftaliharris/tauthon/blob/5587ceec329b75f7caf6d65a036db61ac1bae214/Lib/site.py#L517-L530
|
||
martin68/apt-smart
|
7085f398e08a703759d7e81a898f1e237796f232
|
apt_smart/backends/ubuntu.py
|
python
|
discover_mirrors_old
|
()
|
return mirrors
|
Discover available Ubuntu mirrors. (fallback)
:returns: A set of :class:`.CandidateMirror` objects that have their
:attr:`~.CandidateMirror.mirror_url` property set and may have
the :attr:`~.CandidateMirror.last_updated` property set.
:raises: If no mirrors are discovered an exception is raised.
This queries :data:`MIRRORS_URL`to discover available Ubuntu mirrors.
Here's an example run:
>>> from apt_smart.backends.ubuntu import discover_mirrors_old
>>> from pprint import pprint
>>> pprint(discover_mirrors_old())
set([CandidateMirror(mirror_url='http://archive.ubuntu.com/ubuntu/'),
CandidateMirror(mirror_url='http://ftp.nluug.nl/os/Linux/distr/ubuntu/'),
CandidateMirror(mirror_url='http://ftp.snt.utwente.nl/pub/os/linux/ubuntu/'),
CandidateMirror(mirror_url='http://ftp.tudelft.nl/archive.ubuntu.com/'),
CandidateMirror(mirror_url='http://mirror.1000mbps.com/ubuntu/'),
CandidateMirror(mirror_url='http://mirror.amsiohosting.net/archive.ubuntu.com/'),
CandidateMirror(mirror_url='http://mirror.i3d.net/pub/ubuntu/'),
CandidateMirror(mirror_url='http://mirror.nforce.com/pub/linux/ubuntu/'),
CandidateMirror(mirror_url='http://mirror.nl.leaseweb.net/ubuntu/'),
CandidateMirror(mirror_url='http://mirror.transip.net/ubuntu/ubuntu/'),
...])
It may be super-slow somewhere ( with 100Mbps fibre though ) in the world to access launchpad.net (see below),
so we have to no longer rely on MIRRORS_URL .
time curl -o/dev/null 'https://launchpad.net/ubuntu/+archivemirrors'
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 263k 100 263k 0 0 5316 0 0:00:50 0:00:50 --:--:-- 6398
real 0m50.869s
user 0m0.045s
sys 0m0.039s
But it can be a fallback when MIRROR_SELECTION_URL is down.
|
Discover available Ubuntu mirrors. (fallback)
|
[
"Discover",
"available",
"Ubuntu",
"mirrors",
".",
"(",
"fallback",
")"
] |
def discover_mirrors_old():
"""
Discover available Ubuntu mirrors. (fallback)
:returns: A set of :class:`.CandidateMirror` objects that have their
:attr:`~.CandidateMirror.mirror_url` property set and may have
the :attr:`~.CandidateMirror.last_updated` property set.
:raises: If no mirrors are discovered an exception is raised.
This queries :data:`MIRRORS_URL`to discover available Ubuntu mirrors.
Here's an example run:
>>> from apt_smart.backends.ubuntu import discover_mirrors_old
>>> from pprint import pprint
>>> pprint(discover_mirrors_old())
set([CandidateMirror(mirror_url='http://archive.ubuntu.com/ubuntu/'),
CandidateMirror(mirror_url='http://ftp.nluug.nl/os/Linux/distr/ubuntu/'),
CandidateMirror(mirror_url='http://ftp.snt.utwente.nl/pub/os/linux/ubuntu/'),
CandidateMirror(mirror_url='http://ftp.tudelft.nl/archive.ubuntu.com/'),
CandidateMirror(mirror_url='http://mirror.1000mbps.com/ubuntu/'),
CandidateMirror(mirror_url='http://mirror.amsiohosting.net/archive.ubuntu.com/'),
CandidateMirror(mirror_url='http://mirror.i3d.net/pub/ubuntu/'),
CandidateMirror(mirror_url='http://mirror.nforce.com/pub/linux/ubuntu/'),
CandidateMirror(mirror_url='http://mirror.nl.leaseweb.net/ubuntu/'),
CandidateMirror(mirror_url='http://mirror.transip.net/ubuntu/ubuntu/'),
...])
It may be super-slow somewhere ( with 100Mbps fibre though ) in the world to access launchpad.net (see below),
so we have to no longer rely on MIRRORS_URL .
time curl -o/dev/null 'https://launchpad.net/ubuntu/+archivemirrors'
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 263k 100 263k 0 0 5316 0 0:00:50 0:00:50 --:--:-- 6398
real 0m50.869s
user 0m0.045s
sys 0m0.039s
But it can be a fallback when MIRROR_SELECTION_URL is down.
"""
mirrors = set()
logger.info("Discovering Ubuntu mirrors at %s ..", MIRRORS_URL)
# Find which country the user is in to get mirrors in that country
try:
url = 'https://ipapi.co/json'
response = fetch_url(url, timeout=2)
# On py3 response is bytes and json.loads throws TypeError in py3.4 and 3.5,
# so decode it to str
if isinstance(response, six.binary_type):
response = response.decode('utf-8')
data = json.loads(response)
country = data['country_name']
logger.info("Found your location: %s by %s", country, url)
except Exception:
url = 'http://ip-api.com/json'
response = fetch_url(url, timeout=5)
if isinstance(response, six.binary_type):
response = response.decode('utf-8')
data = json.loads(response)
country = data['country']
logger.info("Found your location: %s by %s", country, url)
data = fetch_url(MIRRORS_URL, timeout=70, retry=True)
soup = BeautifulSoup(data, 'html.parser')
tables = soup.findAll('table')
flag = False # flag is True when find the row's text is that country
if not tables:
raise Exception("Failed to locate <table> element in Ubuntu mirror page! (%s)" % MIRRORS_URL)
else:
for row in tables[0].findAll("tr"):
if flag:
if not row.a: # End of mirrors located in that country
break
else:
for a in row.findAll('a', href=True):
# Check if the link looks like a mirror URL.
if a['href'].startswith(('http://', 'https://')):
mirrors.add(CandidateMirror(mirror_url=a['href']))
if row.th and row.th.get_text() == country:
flag = True
if not mirrors:
raise Exception("Failed to discover any Ubuntu mirrors! (using %s)" % MIRRORS_URL)
return mirrors
|
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",",
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"\"Failed to discover any Ubuntu mirrors! (using %s)\"",
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"MIRRORS_URL",
")",
"return",
"mirrors"
] |
https://github.com/martin68/apt-smart/blob/7085f398e08a703759d7e81a898f1e237796f232/apt_smart/backends/ubuntu.py#L63-L147
|
|
Emptyset110/dHydra
|
8ec44994ff4dda8bf1ec40e38dd068b757945933
|
dHydra/core/util.py
|
python
|
symbol_list_to_code
|
(symbolList)
|
return codeList
|
[] |
def symbol_list_to_code(symbolList):
codeList = []
for symbol in symbolList:
codeList.append(symbol[2:8])
return codeList
|
[
"def",
"symbol_list_to_code",
"(",
"symbolList",
")",
":",
"codeList",
"=",
"[",
"]",
"for",
"symbol",
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"symbolList",
":",
"codeList",
".",
"append",
"(",
"symbol",
"[",
"2",
":",
"8",
"]",
")",
"return",
"codeList"
] |
https://github.com/Emptyset110/dHydra/blob/8ec44994ff4dda8bf1ec40e38dd068b757945933/dHydra/core/util.py#L164-L168
|
|||
demisto/content
|
5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07
|
Packs/Anomali_ThreatStream/Integrations/Anomali_ThreatStream_v2/Anomali_ThreatStream_v2.py
|
python
|
get_passive_dns
|
(client: Client, value, type="ip", limit=50)
|
Receives value and type of indicator and returns
enrichment data for domain or ip.
|
Receives value and type of indicator and returns
enrichment data for domain or ip.
|
[
"Receives",
"value",
"and",
"type",
"of",
"indicator",
"and",
"returns",
"enrichment",
"data",
"for",
"domain",
"or",
"ip",
"."
] |
def get_passive_dns(client: Client, value, type="ip", limit=50):
"""
Receives value and type of indicator and returns
enrichment data for domain or ip.
"""
dns_results = client.http_request("GET", F"v1/pdns/{type}/{value}/", params=CREDENTIALS).get('results', None)
if not dns_results:
demisto.results(F"No Passive DNS enrichment data found for {value}")
sys.exit()
dns_results = dns_results[:int(limit)]
output = camelize(dns_results, delim='_')
ec = ({
'ThreatStream.PassiveDNS': output
})
human_readable = tableToMarkdown(F"Passive DNS enrichment data for: {value}", output)
return_outputs(human_readable, ec, dns_results)
|
[
"def",
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"value",
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")",
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"(",
"human_readable",
",",
"ec",
",",
"dns_results",
")"
] |
https://github.com/demisto/content/blob/5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07/Packs/Anomali_ThreatStream/Integrations/Anomali_ThreatStream_v2/Anomali_ThreatStream_v2.py#L639-L658
|
||
apple/ccs-calendarserver
|
13c706b985fb728b9aab42dc0fef85aae21921c3
|
twistedcaldav/resource.py
|
python
|
CalendarPrincipalResource.liveProperties
|
(self)
|
return super(CalendarPrincipalResource, self).liveProperties() + baseProperties
|
[] |
def liveProperties(self):
baseProperties = ()
if self.calendarsEnabled():
baseProperties += (
(caldav_namespace, "calendar-home-set"),
(caldav_namespace, "calendar-user-address-set"),
(caldav_namespace, "schedule-inbox-URL"),
(caldav_namespace, "schedule-outbox-URL"),
(caldav_namespace, "calendar-user-type"),
(calendarserver_namespace, "calendar-proxy-read-for"),
(calendarserver_namespace, "calendar-proxy-write-for"),
(calendarserver_namespace, "auto-schedule-mode"),
)
if self.addressBooksEnabled():
baseProperties += (carddavxml.AddressBookHomeSet.qname(),)
if self.directoryAddressBookEnabled():
baseProperties += (carddavxml.DirectoryGateway.qname(),)
if config.EnableDropBox or config.EnableManagedAttachments:
baseProperties += (customxml.DropBoxHomeURL.qname(),)
if config.Sharing.Enabled:
baseProperties += (customxml.NotificationURL.qname(),)
return super(CalendarPrincipalResource, self).liveProperties() + baseProperties
|
[
"def",
"liveProperties",
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"self",
")",
":",
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"\"calendar-home-set\"",
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",",
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",",
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",",
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",",
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"(",
"CalendarPrincipalResource",
",",
"self",
")",
".",
"liveProperties",
"(",
")",
"+",
"baseProperties"
] |
https://github.com/apple/ccs-calendarserver/blob/13c706b985fb728b9aab42dc0fef85aae21921c3/twistedcaldav/resource.py#L1681-L1708
|
|||
Spacelog/Spacelog
|
92df308be5923765607a89b022acb57c041c86b3
|
ext/redis-py/redis/client.py
|
python
|
Redis.ltrim
|
(self, name, start, end)
|
return self.execute_command('LTRIM', name, start, end)
|
Trim the list ``name``, removing all values not within the slice
between ``start`` and ``end``
``start`` and ``end`` can be negative numbers just like
Python slicing notation
|
Trim the list ``name``, removing all values not within the slice
between ``start`` and ``end``
|
[
"Trim",
"the",
"list",
"name",
"removing",
"all",
"values",
"not",
"within",
"the",
"slice",
"between",
"start",
"and",
"end"
] |
def ltrim(self, name, start, end):
"""
Trim the list ``name``, removing all values not within the slice
between ``start`` and ``end``
``start`` and ``end`` can be negative numbers just like
Python slicing notation
"""
return self.execute_command('LTRIM', name, start, end)
|
[
"def",
"ltrim",
"(",
"self",
",",
"name",
",",
"start",
",",
"end",
")",
":",
"return",
"self",
".",
"execute_command",
"(",
"'LTRIM'",
",",
"name",
",",
"start",
",",
"end",
")"
] |
https://github.com/Spacelog/Spacelog/blob/92df308be5923765607a89b022acb57c041c86b3/ext/redis-py/redis/client.py#L784-L792
|
|
jython/frozen-mirror
|
b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99
|
lib-python/2.7/lib-tk/Tkinter.py
|
python
|
Misc.grab_set_global
|
(self)
|
Set global grab for this widget.
A global grab directs all events to this and
descendant widgets on the display. Use with caution -
other applications do not get events anymore.
|
Set global grab for this widget.
|
[
"Set",
"global",
"grab",
"for",
"this",
"widget",
"."
] |
def grab_set_global(self):
"""Set global grab for this widget.
A global grab directs all events to this and
descendant widgets on the display. Use with caution -
other applications do not get events anymore."""
self.tk.call('grab', 'set', '-global', self._w)
|
[
"def",
"grab_set_global",
"(",
"self",
")",
":",
"self",
".",
"tk",
".",
"call",
"(",
"'grab'",
",",
"'set'",
",",
"'-global'",
",",
"self",
".",
"_w",
")"
] |
https://github.com/jython/frozen-mirror/blob/b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99/lib-python/2.7/lib-tk/Tkinter.py#L620-L626
|
||
aws/aws-parallelcluster
|
f1fe5679a01c524e7ea904c329bd6d17318c6cd9
|
cli/src/pcluster/schemas/imagebuilder_schema.py
|
python
|
BuildSchema.validate_security_group_ids
|
(self, value)
|
Validate security group ids.
|
Validate security group ids.
|
[
"Validate",
"security",
"group",
"ids",
"."
] |
def validate_security_group_ids(self, value):
"""Validate security group ids."""
if value and not all(
re.match(ALLOWED_VALUES["security_group_id"], security_group_id) for security_group_id in value
):
raise ValidationError(message="The SecurityGroupIds contains invalid security group id.")
|
[
"def",
"validate_security_group_ids",
"(",
"self",
",",
"value",
")",
":",
"if",
"value",
"and",
"not",
"all",
"(",
"re",
".",
"match",
"(",
"ALLOWED_VALUES",
"[",
"\"security_group_id\"",
"]",
",",
"security_group_id",
")",
"for",
"security_group_id",
"in",
"value",
")",
":",
"raise",
"ValidationError",
"(",
"message",
"=",
"\"The SecurityGroupIds contains invalid security group id.\"",
")"
] |
https://github.com/aws/aws-parallelcluster/blob/f1fe5679a01c524e7ea904c329bd6d17318c6cd9/cli/src/pcluster/schemas/imagebuilder_schema.py#L185-L190
|
||
golbin/TensorFlow-Tutorials
|
909a8b77d5bb1db4732febee9ed68ab218478b97
|
11 - Inception/retrain.py
|
python
|
read_list_of_floats_from_file
|
(file_path)
|
Reads list of floats from a given file.
Args:
file_path: Path to a file where list of floats was stored.
Returns:
Array of bottleneck values (list of floats).
|
Reads list of floats from a given file.
|
[
"Reads",
"list",
"of",
"floats",
"from",
"a",
"given",
"file",
"."
] |
def read_list_of_floats_from_file(file_path):
"""Reads list of floats from a given file.
Args:
file_path: Path to a file where list of floats was stored.
Returns:
Array of bottleneck values (list of floats).
"""
with open(file_path, 'rb') as f:
s = struct.unpack('d' * BOTTLENECK_TENSOR_SIZE, f.read())
return list(s)
|
[
"def",
"read_list_of_floats_from_file",
"(",
"file_path",
")",
":",
"with",
"open",
"(",
"file_path",
",",
"'rb'",
")",
"as",
"f",
":",
"s",
"=",
"struct",
".",
"unpack",
"(",
"'d'",
"*",
"BOTTLENECK_TENSOR_SIZE",
",",
"f",
".",
"read",
"(",
")",
")",
"return",
"list",
"(",
"s",
")"
] |
https://github.com/golbin/TensorFlow-Tutorials/blob/909a8b77d5bb1db4732febee9ed68ab218478b97/11 - Inception/retrain.py#L332-L344
|
||
triaquae/triaquae
|
bbabf736b3ba56a0c6498e7f04e16c13b8b8f2b9
|
TriAquae/models/django/contrib/gis/db/models/query.py
|
python
|
GeoQuerySet.kml
|
(self, **kwargs)
|
return self._spatial_attribute('kml', s, **kwargs)
|
Returns KML representation of the geometry field in a `kml`
attribute on each element of this GeoQuerySet.
|
Returns KML representation of the geometry field in a `kml`
attribute on each element of this GeoQuerySet.
|
[
"Returns",
"KML",
"representation",
"of",
"the",
"geometry",
"field",
"in",
"a",
"kml",
"attribute",
"on",
"each",
"element",
"of",
"this",
"GeoQuerySet",
"."
] |
def kml(self, **kwargs):
"""
Returns KML representation of the geometry field in a `kml`
attribute on each element of this GeoQuerySet.
"""
s = {'desc' : 'KML',
'procedure_fmt' : '%(geo_col)s,%(precision)s',
'procedure_args' : {'precision' : kwargs.pop('precision', 8)},
}
return self._spatial_attribute('kml', s, **kwargs)
|
[
"def",
"kml",
"(",
"self",
",",
"*",
"*",
"kwargs",
")",
":",
"s",
"=",
"{",
"'desc'",
":",
"'KML'",
",",
"'procedure_fmt'",
":",
"'%(geo_col)s,%(precision)s'",
",",
"'procedure_args'",
":",
"{",
"'precision'",
":",
"kwargs",
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"(",
"'precision'",
",",
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")",
"}",
",",
"}",
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"self",
".",
"_spatial_attribute",
"(",
"'kml'",
",",
"s",
",",
"*",
"*",
"kwargs",
")"
] |
https://github.com/triaquae/triaquae/blob/bbabf736b3ba56a0c6498e7f04e16c13b8b8f2b9/TriAquae/models/django/contrib/gis/db/models/query.py#L213-L222
|
|
AstroPrint/AstroBox
|
e7e3b8a7d33ea85fcb6b2696869c0d719ceb8b75
|
src/octoprint/server/util.py
|
python
|
PrinterStateConnection._onEvent
|
(self, event, payload)
|
[] |
def _onEvent(self, event, payload):
self.sendEvent(event, payload)
|
[
"def",
"_onEvent",
"(",
"self",
",",
"event",
",",
"payload",
")",
":",
"self",
".",
"sendEvent",
"(",
"event",
",",
"payload",
")"
] |
https://github.com/AstroPrint/AstroBox/blob/e7e3b8a7d33ea85fcb6b2696869c0d719ceb8b75/src/octoprint/server/util.py#L244-L245
|
||||
wucng/TensorExpand
|
4ea58f64f5c5082b278229b799c9f679536510b7
|
TensorExpand/图片项目/5、迁移学习/TF-slim/slim/deployment/model_deploy.py
|
python
|
DeploymentConfig.clone_device
|
(self, clone_index)
|
return device
|
Device used to create the clone and all the ops inside the clone.
Args:
clone_index: Int, representing the clone_index.
Returns:
A value suitable for `tf.device()`.
Raises:
ValueError: if `clone_index` is greater or equal to the number of clones".
|
Device used to create the clone and all the ops inside the clone.
Args:
clone_index: Int, representing the clone_index.
Returns:
A value suitable for `tf.device()`.
Raises:
ValueError: if `clone_index` is greater or equal to the number of clones".
|
[
"Device",
"used",
"to",
"create",
"the",
"clone",
"and",
"all",
"the",
"ops",
"inside",
"the",
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".",
"Args",
":",
"clone_index",
":",
"Int",
"representing",
"the",
"clone_index",
".",
"Returns",
":",
"A",
"value",
"suitable",
"for",
"tf",
".",
"device",
"()",
".",
"Raises",
":",
"ValueError",
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"if",
"clone_index",
"is",
"greater",
"or",
"equal",
"to",
"the",
"number",
"of",
"clones",
"."
] |
def clone_device(self, clone_index):
"""Device used to create the clone and all the ops inside the clone.
Args:
clone_index: Int, representing the clone_index.
Returns:
A value suitable for `tf.device()`.
Raises:
ValueError: if `clone_index` is greater or equal to the number of clones".
"""
if clone_index >= self._num_clones:
raise ValueError('clone_index must be less than num_clones')
device = ''
if self._num_ps_tasks > 0:
device += self._worker_device
if self._clone_on_cpu:
device += '/device:CPU:0'
else:
device += '/device:GPU:%d' % clone_index
return device
|
[
"def",
"clone_device",
"(",
"self",
",",
"clone_index",
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":",
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"clone_index",
">=",
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"(",
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"_clone_on_cpu",
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"device",
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"else",
":",
"device",
"+=",
"'/device:GPU:%d'",
"%",
"clone_index",
"return",
"device"
] |
https://github.com/wucng/TensorExpand/blob/4ea58f64f5c5082b278229b799c9f679536510b7/TensorExpand/图片项目/5、迁移学习/TF-slim/slim/deployment/model_deploy.py#L522-L540
|
|
beetbox/confuse
|
c328e810f7a31412e0650235f71728e983edd18e
|
confuse/core.py
|
python
|
Configuration.user_config_path
|
(self)
|
return os.path.join(self.config_dir(), CONFIG_FILENAME)
|
Points to the location of the user configuration.
The file may not exist.
|
Points to the location of the user configuration.
|
[
"Points",
"to",
"the",
"location",
"of",
"the",
"user",
"configuration",
"."
] |
def user_config_path(self):
"""Points to the location of the user configuration.
The file may not exist.
"""
return os.path.join(self.config_dir(), CONFIG_FILENAME)
|
[
"def",
"user_config_path",
"(",
"self",
")",
":",
"return",
"os",
".",
"path",
".",
"join",
"(",
"self",
".",
"config_dir",
"(",
")",
",",
"CONFIG_FILENAME",
")"
] |
https://github.com/beetbox/confuse/blob/c328e810f7a31412e0650235f71728e983edd18e/confuse/core.py#L517-L522
|
|
Pyomo/pyomo
|
dbd4faee151084f343b893cc2b0c04cf2b76fd92
|
pyomo/network/decomposition.py
|
python
|
SequentialDecomposition.pass_tear_direct
|
(self, G, tears)
|
Pass values across all tears in the given tear set
|
Pass values across all tears in the given tear set
|
[
"Pass",
"values",
"across",
"all",
"tears",
"in",
"the",
"given",
"tear",
"set"
] |
def pass_tear_direct(self, G, tears):
"""Pass values across all tears in the given tear set"""
fixed_outputs = ComponentSet()
edge_list = self.idx_to_edge(G)
for tear in tears:
# fix everything then call pass values
arc = G.edges[edge_list[tear]]["arc"]
for var in arc.src.iter_vars(expr_vars=True, fixed=False):
fixed_outputs.add(var)
var.fix()
self.pass_values(arc, fixed_inputs=self.fixed_inputs())
for var in fixed_outputs:
var.free()
fixed_outputs.clear()
|
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https://github.com/Pyomo/pyomo/blob/dbd4faee151084f343b893cc2b0c04cf2b76fd92/pyomo/network/decomposition.py#L862-L876
|
||
idanr1986/cuckoo-droid
|
1350274639473d3d2b0ac740cae133ca53ab7444
|
analyzer/android_on_linux/lib/api/androguard/apk.py
|
python
|
APK.get_files_information
|
(self)
|
Return the files inside the APK with their associated types and crc32
:rtype: string, string, int
|
Return the files inside the APK with their associated types and crc32
|
[
"Return",
"the",
"files",
"inside",
"the",
"APK",
"with",
"their",
"associated",
"types",
"and",
"crc32"
] |
def get_files_information(self):
"""
Return the files inside the APK with their associated types and crc32
:rtype: string, string, int
"""
if self.files == {}:
self.get_files_types()
for i in self.get_files():
try:
yield i, self.files[i], self.files_crc32[i]
except KeyError:
yield i, "", ""
|
[
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"files",
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"[",
"i",
"]",
"except",
"KeyError",
":",
"yield",
"i",
",",
"\"\"",
",",
"\"\""
] |
https://github.com/idanr1986/cuckoo-droid/blob/1350274639473d3d2b0ac740cae133ca53ab7444/analyzer/android_on_linux/lib/api/androguard/apk.py#L352-L365
|
||
pythonzm/Ops
|
e6fdddad2cd6bc697805a2bdba521a26bacada50
|
assets/utils/ali_api.py
|
python
|
AliAPI.get_response
|
(self)
|
return str(response, encoding='utf-8')
|
获取返回值
:return:
|
获取返回值
:return:
|
[
"获取返回值",
":",
"return",
":"
] |
def get_response(self):
"""
获取返回值
:return:
"""
request = self.set_request()
response = self.client.do_action_with_exception(request)
return str(response, encoding='utf-8')
|
[
"def",
"get_response",
"(",
"self",
")",
":",
"request",
"=",
"self",
".",
"set_request",
"(",
")",
"response",
"=",
"self",
".",
"client",
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"do_action_with_exception",
"(",
"request",
")",
"return",
"str",
"(",
"response",
",",
"encoding",
"=",
"'utf-8'",
")"
] |
https://github.com/pythonzm/Ops/blob/e6fdddad2cd6bc697805a2bdba521a26bacada50/assets/utils/ali_api.py#L43-L50
|
|
pwnieexpress/pwn_plug_sources
|
1a23324f5dc2c3de20f9c810269b6a29b2758cad
|
src/voiper/sulley/impacket/dcerpc/dcerpc.py
|
python
|
MSRPCBindAck.get_results_num
|
(self)
|
return self.get_byte(self._get_results_offset()-2)
|
[] |
def get_results_num(self):
return self.get_byte(self._get_results_offset()-2)
|
[
"def",
"get_results_num",
"(",
"self",
")",
":",
"return",
"self",
".",
"get_byte",
"(",
"self",
".",
"_get_results_offset",
"(",
")",
"-",
"2",
")"
] |
https://github.com/pwnieexpress/pwn_plug_sources/blob/1a23324f5dc2c3de20f9c810269b6a29b2758cad/src/voiper/sulley/impacket/dcerpc/dcerpc.py#L523-L524
|
|||
angr/claripy
|
4c961b4dc664706be8142fe4868f27655bc8da77
|
claripy/vsa/valueset.py
|
python
|
RegionAnnotation.relocatable
|
(self)
|
return False
|
A Region annotation is not relocatable in simplifications.
:return: False
:rtype: bool
|
A Region annotation is not relocatable in simplifications.
|
[
"A",
"Region",
"annotation",
"is",
"not",
"relocatable",
"in",
"simplifications",
"."
] |
def relocatable(self):
"""
A Region annotation is not relocatable in simplifications.
:return: False
:rtype: bool
"""
return False
|
[
"def",
"relocatable",
"(",
"self",
")",
":",
"return",
"False"
] |
https://github.com/angr/claripy/blob/4c961b4dc664706be8142fe4868f27655bc8da77/claripy/vsa/valueset.py#L72-L80
|
|
leo-editor/leo-editor
|
383d6776d135ef17d73d935a2f0ecb3ac0e99494
|
leo/core/leoAst.py
|
python
|
Tokenizer.add_token
|
(self, kind, five_tuple, line, s_row, value)
|
Add a token to the results list.
Subclasses could override this method to filter out specific tokens.
|
Add a token to the results list.
|
[
"Add",
"a",
"token",
"to",
"the",
"results",
"list",
"."
] |
def add_token(self, kind, five_tuple, line, s_row, value):
"""
Add a token to the results list.
Subclasses could override this method to filter out specific tokens.
"""
tok = Token(kind, value)
tok.five_tuple = five_tuple
tok.index = self.token_index
# Bump the token index.
self.token_index += 1
tok.line = line
tok.line_number = s_row
self.results.append(tok)
|
[
"def",
"add_token",
"(",
"self",
",",
"kind",
",",
"five_tuple",
",",
"line",
",",
"s_row",
",",
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":",
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".",
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"(",
"tok",
")"
] |
https://github.com/leo-editor/leo-editor/blob/383d6776d135ef17d73d935a2f0ecb3ac0e99494/leo/core/leoAst.py#L4051-L4064
|
||
scikit-learn/scikit-learn
|
1d1aadd0711b87d2a11c80aad15df6f8cf156712
|
sklearn/pipeline.py
|
python
|
make_pipeline
|
(*steps, memory=None, verbose=False)
|
return Pipeline(_name_estimators(steps), memory=memory, verbose=verbose)
|
Construct a :class:`Pipeline` from the given estimators.
This is a shorthand for the :class:`Pipeline` constructor; it does not
require, and does not permit, naming the estimators. Instead, their names
will be set to the lowercase of their types automatically.
Parameters
----------
*steps : list of Estimator objects
List of the scikit-learn estimators that are chained together.
memory : str or object with the joblib.Memory interface, default=None
Used to cache the fitted transformers of the pipeline. By default,
no caching is performed. If a string is given, it is the path to
the caching directory. Enabling caching triggers a clone of
the transformers before fitting. Therefore, the transformer
instance given to the pipeline cannot be inspected
directly. Use the attribute ``named_steps`` or ``steps`` to
inspect estimators within the pipeline. Caching the
transformers is advantageous when fitting is time consuming.
verbose : bool, default=False
If True, the time elapsed while fitting each step will be printed as it
is completed.
Returns
-------
p : Pipeline
Returns a scikit-learn :class:`Pipeline` object.
See Also
--------
Pipeline : Class for creating a pipeline of transforms with a final
estimator.
Examples
--------
>>> from sklearn.naive_bayes import GaussianNB
>>> from sklearn.preprocessing import StandardScaler
>>> from sklearn.pipeline import make_pipeline
>>> make_pipeline(StandardScaler(), GaussianNB(priors=None))
Pipeline(steps=[('standardscaler', StandardScaler()),
('gaussiannb', GaussianNB())])
|
Construct a :class:`Pipeline` from the given estimators.
|
[
"Construct",
"a",
":",
"class",
":",
"Pipeline",
"from",
"the",
"given",
"estimators",
"."
] |
def make_pipeline(*steps, memory=None, verbose=False):
"""Construct a :class:`Pipeline` from the given estimators.
This is a shorthand for the :class:`Pipeline` constructor; it does not
require, and does not permit, naming the estimators. Instead, their names
will be set to the lowercase of their types automatically.
Parameters
----------
*steps : list of Estimator objects
List of the scikit-learn estimators that are chained together.
memory : str or object with the joblib.Memory interface, default=None
Used to cache the fitted transformers of the pipeline. By default,
no caching is performed. If a string is given, it is the path to
the caching directory. Enabling caching triggers a clone of
the transformers before fitting. Therefore, the transformer
instance given to the pipeline cannot be inspected
directly. Use the attribute ``named_steps`` or ``steps`` to
inspect estimators within the pipeline. Caching the
transformers is advantageous when fitting is time consuming.
verbose : bool, default=False
If True, the time elapsed while fitting each step will be printed as it
is completed.
Returns
-------
p : Pipeline
Returns a scikit-learn :class:`Pipeline` object.
See Also
--------
Pipeline : Class for creating a pipeline of transforms with a final
estimator.
Examples
--------
>>> from sklearn.naive_bayes import GaussianNB
>>> from sklearn.preprocessing import StandardScaler
>>> from sklearn.pipeline import make_pipeline
>>> make_pipeline(StandardScaler(), GaussianNB(priors=None))
Pipeline(steps=[('standardscaler', StandardScaler()),
('gaussiannb', GaussianNB())])
"""
return Pipeline(_name_estimators(steps), memory=memory, verbose=verbose)
|
[
"def",
"make_pipeline",
"(",
"*",
"steps",
",",
"memory",
"=",
"None",
",",
"verbose",
"=",
"False",
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":",
"return",
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"(",
"_name_estimators",
"(",
"steps",
")",
",",
"memory",
"=",
"memory",
",",
"verbose",
"=",
"verbose",
")"
] |
https://github.com/scikit-learn/scikit-learn/blob/1d1aadd0711b87d2a11c80aad15df6f8cf156712/sklearn/pipeline.py#L827-L872
|
|
holzschu/Carnets
|
44effb10ddfc6aa5c8b0687582a724ba82c6b547
|
Library/lib/python3.7/site-packages/sympy/discrete/transforms.py
|
python
|
fft
|
(seq, dps=None)
|
return _fourier_transform(seq, dps=dps)
|
r"""
Performs the Discrete Fourier Transform (**DFT**) in the complex domain.
The sequence is automatically padded to the right with zeros, as the
*radix-2 FFT* requires the number of sample points to be a power of 2.
This method should be used with default arguments only for short sequences
as the complexity of expressions increases with the size of the sequence.
Parameters
==========
seq : iterable
The sequence on which **DFT** is to be applied.
dps : Integer
Specifies the number of decimal digits for precision.
Examples
========
>>> from sympy import fft, ifft
>>> fft([1, 2, 3, 4])
[10, -2 - 2*I, -2, -2 + 2*I]
>>> ifft(_)
[1, 2, 3, 4]
>>> ifft([1, 2, 3, 4])
[5/2, -1/2 + I/2, -1/2, -1/2 - I/2]
>>> fft(_)
[1, 2, 3, 4]
>>> ifft([1, 7, 3, 4], dps=15)
[3.75, -0.5 - 0.75*I, -1.75, -0.5 + 0.75*I]
>>> fft(_)
[1.0, 7.0, 3.0, 4.0]
References
==========
.. [1] https://en.wikipedia.org/wiki/Cooley%E2%80%93Tukey_FFT_algorithm
.. [2] http://mathworld.wolfram.com/FastFourierTransform.html
|
r"""
Performs the Discrete Fourier Transform (**DFT**) in the complex domain.
|
[
"r",
"Performs",
"the",
"Discrete",
"Fourier",
"Transform",
"(",
"**",
"DFT",
"**",
")",
"in",
"the",
"complex",
"domain",
"."
] |
def fft(seq, dps=None):
r"""
Performs the Discrete Fourier Transform (**DFT**) in the complex domain.
The sequence is automatically padded to the right with zeros, as the
*radix-2 FFT* requires the number of sample points to be a power of 2.
This method should be used with default arguments only for short sequences
as the complexity of expressions increases with the size of the sequence.
Parameters
==========
seq : iterable
The sequence on which **DFT** is to be applied.
dps : Integer
Specifies the number of decimal digits for precision.
Examples
========
>>> from sympy import fft, ifft
>>> fft([1, 2, 3, 4])
[10, -2 - 2*I, -2, -2 + 2*I]
>>> ifft(_)
[1, 2, 3, 4]
>>> ifft([1, 2, 3, 4])
[5/2, -1/2 + I/2, -1/2, -1/2 - I/2]
>>> fft(_)
[1, 2, 3, 4]
>>> ifft([1, 7, 3, 4], dps=15)
[3.75, -0.5 - 0.75*I, -1.75, -0.5 + 0.75*I]
>>> fft(_)
[1.0, 7.0, 3.0, 4.0]
References
==========
.. [1] https://en.wikipedia.org/wiki/Cooley%E2%80%93Tukey_FFT_algorithm
.. [2] http://mathworld.wolfram.com/FastFourierTransform.html
"""
return _fourier_transform(seq, dps=dps)
|
[
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"None",
")",
":",
"return",
"_fourier_transform",
"(",
"seq",
",",
"dps",
"=",
"dps",
")"
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https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/sympy/discrete/transforms.py#L71-L117
|
|
p4-team/ctf
|
05ab90cd04ea26f0fca860579939617f57961a1a
|
2015-09-26-trendmicro/calculator/calculator.py
|
python
|
fromRoman
|
(s)
|
return result
|
convert Roman numeral to integer
|
convert Roman numeral to integer
|
[
"convert",
"Roman",
"numeral",
"to",
"integer"
] |
def fromRoman(s):
"""convert Roman numeral to integer"""
if not s:
raise InvalidRomanNumeralError, 'Input can not be blank'
if not romanNumeralPattern.search(s):
raise InvalidRomanNumeralError, 'Invalid Roman numeral: %s' % s
result = 0
index = 0
for numeral, integer in romanNumeralMap:
while s[index:index + len(numeral)] == numeral:
result += integer
index += len(numeral)
return result
|
[
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https://github.com/p4-team/ctf/blob/05ab90cd04ea26f0fca860579939617f57961a1a/2015-09-26-trendmicro/calculator/calculator.py#L94-L107
|
|
quantumlib/OpenFermion
|
6187085f2a7707012b68370b625acaeed547e62b
|
src/openfermion/ops/operators/symbolic_operator.py
|
python
|
SymbolicOperator.__repr__
|
(self)
|
return str(self)
|
[] |
def __repr__(self):
return str(self)
|
[
"def",
"__repr__",
"(",
"self",
")",
":",
"return",
"str",
"(",
"self",
")"
] |
https://github.com/quantumlib/OpenFermion/blob/6187085f2a7707012b68370b625acaeed547e62b/src/openfermion/ops/operators/symbolic_operator.py#L347-L348
|
|||
facebookresearch/ReAgent
|
52f666670a7fa03206812ef48949f6b934d400f7
|
reagent/ope/datasets/logged_dataset.py
|
python
|
BanditsDataset.num_features
|
(self)
|
Returns:
number of features
|
Returns:
number of features
|
[
"Returns",
":",
"number",
"of",
"features"
] |
def num_features(self) -> int:
"""
Returns:
number of features
"""
pass
|
[
"def",
"num_features",
"(",
"self",
")",
"->",
"int",
":",
"pass"
] |
https://github.com/facebookresearch/ReAgent/blob/52f666670a7fa03206812ef48949f6b934d400f7/reagent/ope/datasets/logged_dataset.py#L36-L41
|
||
demisto/content
|
5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07
|
Packs/CofenseTriage/Integrations/CofenseTriagev3/CofenseTriagev3.py
|
python
|
Client.exception_handler
|
(response: requests.models.Response)
|
Handle error in the response and display error message based on status code.
:type response: ``requests.models.Response``
:param response: response from API.
:raises: raise DemistoException based on status code abd response.
|
Handle error in the response and display error message based on status code.
|
[
"Handle",
"error",
"in",
"the",
"response",
"and",
"display",
"error",
"message",
"based",
"on",
"status",
"code",
"."
] |
def exception_handler(response: requests.models.Response):
"""
Handle error in the response and display error message based on status code.
:type response: ``requests.models.Response``
:param response: response from API.
:raises: raise DemistoException based on status code abd response.
"""
err_msg = ""
if response.status_code in HTTP_ERRORS:
err_msg = HTTP_ERRORS[response.status_code]
if response.status_code not in HTTP_ERRORS or response.status_code in [400, 404]:
if response.status_code not in [400, 404]:
err_msg = response.reason
try:
# Try to parse json error response
error_entry = response.json().get("errors")
if error_entry:
err_details = ','.join([entry.get('detail') for entry in error_entry if entry.get('detail')])
if err_details:
err_msg = f"{err_msg}\nDetails: {err_details}"
except (ValueError, AttributeError):
if response.text:
err_msg = f"{err_msg}\nDetails: {response.text}"
raise DemistoException(err_msg)
|
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"[",
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".",
"status_code",
"]",
"if",
"response",
".",
"status_code",
"not",
"in",
"HTTP_ERRORS",
"or",
"response",
".",
"status_code",
"in",
"[",
"400",
",",
"404",
"]",
":",
"if",
"response",
".",
"status_code",
"not",
"in",
"[",
"400",
",",
"404",
"]",
":",
"err_msg",
"=",
"response",
".",
"reason",
"try",
":",
"# Try to parse json error response",
"error_entry",
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"response",
".",
"json",
"(",
")",
".",
"get",
"(",
"\"errors\"",
")",
"if",
"error_entry",
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"[",
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"(",
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"(",
"'detail'",
")",
"]",
")",
"if",
"err_details",
":",
"err_msg",
"=",
"f\"{err_msg}\\nDetails: {err_details}\"",
"except",
"(",
"ValueError",
",",
"AttributeError",
")",
":",
"if",
"response",
".",
"text",
":",
"err_msg",
"=",
"f\"{err_msg}\\nDetails: {response.text}\"",
"raise",
"DemistoException",
"(",
"err_msg",
")"
] |
https://github.com/demisto/content/blob/5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07/Packs/CofenseTriage/Integrations/CofenseTriagev3/CofenseTriagev3.py#L150-L180
|
||
python-provy/provy
|
ca3d5e96a2210daf3c1fd4b96e047efff152db14
|
provy/more/debian/package/pip.py
|
python
|
PipRole.provision
|
(self)
|
Installs pip dependencies. This method should be called upon if overriden in base classes, or PIP won't work properly in the remote server.
Example:
::
class MySampleRole(Role):
def provision(self):
self.provision_role(PipRole) # does not need to be called if using with block.
|
Installs pip dependencies. This method should be called upon if overriden in base classes, or PIP won't work properly in the remote server.
|
[
"Installs",
"pip",
"dependencies",
".",
"This",
"method",
"should",
"be",
"called",
"upon",
"if",
"overriden",
"in",
"base",
"classes",
"or",
"PIP",
"won",
"t",
"work",
"properly",
"in",
"the",
"remote",
"server",
"."
] |
def provision(self):
'''
Installs pip dependencies. This method should be called upon if overriden in base classes, or PIP won't work properly in the remote server.
Example:
::
class MySampleRole(Role):
def provision(self):
self.provision_role(PipRole) # does not need to be called if using with block.
'''
with self.using(AptitudeRole) as role:
role.ensure_up_to_date()
role.ensure_package_installed('python-setuptools')
role.ensure_package_installed('python-dev')
self.execute("easy_install pip", sudo=True, stdout=False, user=None)
|
[
"def",
"provision",
"(",
"self",
")",
":",
"with",
"self",
".",
"using",
"(",
"AptitudeRole",
")",
"as",
"role",
":",
"role",
".",
"ensure_up_to_date",
"(",
")",
"role",
".",
"ensure_package_installed",
"(",
"'python-setuptools'",
")",
"role",
".",
"ensure_package_installed",
"(",
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",",
"sudo",
"=",
"True",
",",
"stdout",
"=",
"False",
",",
"user",
"=",
"None",
")"
] |
https://github.com/python-provy/provy/blob/ca3d5e96a2210daf3c1fd4b96e047efff152db14/provy/more/debian/package/pip.py#L44-L59
|
||
konomae/lastpass-python
|
41af73adecda1fbf48b83e53ed198e128e505405
|
lastpass/parser.py
|
python
|
skip_item
|
(stream, times=1)
|
Skips an item in a stream.
|
Skips an item in a stream.
|
[
"Skips",
"an",
"item",
"in",
"a",
"stream",
"."
] |
def skip_item(stream, times=1):
"""Skips an item in a stream."""
for i in range(times):
read_item(stream)
|
[
"def",
"skip_item",
"(",
"stream",
",",
"times",
"=",
"1",
")",
":",
"for",
"i",
"in",
"range",
"(",
"times",
")",
":",
"read_item",
"(",
"stream",
")"
] |
https://github.com/konomae/lastpass-python/blob/41af73adecda1fbf48b83e53ed198e128e505405/lastpass/parser.py#L164-L167
|
||
openstack/barbican
|
a9d2b133c8dc3307974f119f9a2b23a4ba82e8ce
|
barbican/tasks/certificate_resources.py
|
python
|
is_last_project_ca
|
(project_id)
|
return total == 1
|
Returns True iff project has exactly one project CA
:param project_id: internal project ID
:return: Boolean
|
Returns True iff project has exactly one project CA
|
[
"Returns",
"True",
"iff",
"project",
"has",
"exactly",
"one",
"project",
"CA"
] |
def is_last_project_ca(project_id):
"""Returns True iff project has exactly one project CA
:param project_id: internal project ID
:return: Boolean
"""
project_ca_repo = repos.get_project_ca_repository()
_, _, _, total = project_ca_repo.get_by_create_date(
project_id=project_id,
suppress_exception=True
)
return total == 1
|
[
"def",
"is_last_project_ca",
"(",
"project_id",
")",
":",
"project_ca_repo",
"=",
"repos",
".",
"get_project_ca_repository",
"(",
")",
"_",
",",
"_",
",",
"_",
",",
"total",
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"project_ca_repo",
".",
"get_by_create_date",
"(",
"project_id",
"=",
"project_id",
",",
"suppress_exception",
"=",
"True",
")",
"return",
"total",
"==",
"1"
] |
https://github.com/openstack/barbican/blob/a9d2b133c8dc3307974f119f9a2b23a4ba82e8ce/barbican/tasks/certificate_resources.py#L290-L301
|
|
gramps-project/gramps
|
04d4651a43eb210192f40a9f8c2bad8ee8fa3753
|
gramps/gui/widgets/fanchart.py
|
python
|
FanChartGrampsGUI.set_fan
|
(self, fan)
|
Set the fanchartwidget to work on
|
Set the fanchartwidget to work on
|
[
"Set",
"the",
"fanchartwidget",
"to",
"work",
"on"
] |
def set_fan(self, fan):
"""
Set the fanchartwidget to work on
"""
self.fan = fan
self.fan.format_helper = self.format_helper
self.fan.goto = self.on_childmenu_changed
|
[
"def",
"set_fan",
"(",
"self",
",",
"fan",
")",
":",
"self",
".",
"fan",
"=",
"fan",
"self",
".",
"fan",
".",
"format_helper",
"=",
"self",
".",
"format_helper",
"self",
".",
"fan",
".",
"goto",
"=",
"self",
".",
"on_childmenu_changed"
] |
https://github.com/gramps-project/gramps/blob/04d4651a43eb210192f40a9f8c2bad8ee8fa3753/gramps/gui/widgets/fanchart.py#L1774-L1780
|
||
kubernetes-client/python
|
47b9da9de2d02b2b7a34fbe05afb44afd130d73a
|
kubernetes/client/models/v1beta1_pod_disruption_budget.py
|
python
|
V1beta1PodDisruptionBudget.spec
|
(self)
|
return self._spec
|
Gets the spec of this V1beta1PodDisruptionBudget. # noqa: E501
:return: The spec of this V1beta1PodDisruptionBudget. # noqa: E501
:rtype: V1beta1PodDisruptionBudgetSpec
|
Gets the spec of this V1beta1PodDisruptionBudget. # noqa: E501
|
[
"Gets",
"the",
"spec",
"of",
"this",
"V1beta1PodDisruptionBudget",
".",
"#",
"noqa",
":",
"E501"
] |
def spec(self):
"""Gets the spec of this V1beta1PodDisruptionBudget. # noqa: E501
:return: The spec of this V1beta1PodDisruptionBudget. # noqa: E501
:rtype: V1beta1PodDisruptionBudgetSpec
"""
return self._spec
|
[
"def",
"spec",
"(",
"self",
")",
":",
"return",
"self",
".",
"_spec"
] |
https://github.com/kubernetes-client/python/blob/47b9da9de2d02b2b7a34fbe05afb44afd130d73a/kubernetes/client/models/v1beta1_pod_disruption_budget.py#L143-L150
|
|
TuSimple/simpledet
|
97413463f0bc3116f684eaf7031fd3dd6ded3149
|
operator_py/cython/setup.py
|
python
|
locate_cuda
|
()
|
return cudaconfig
|
Locate the CUDA environment on the system
Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
and values giving the absolute path to each directory.
Starts by looking for the CUDAHOME env variable. If not found, everything
is based on finding 'nvcc' in the PATH.
|
Locate the CUDA environment on the system
|
[
"Locate",
"the",
"CUDA",
"environment",
"on",
"the",
"system"
] |
def locate_cuda():
"""Locate the CUDA environment on the system
Returns a dict with keys 'home', 'nvcc', 'include', and 'lib64'
and values giving the absolute path to each directory.
Starts by looking for the CUDAHOME env variable. If not found, everything
is based on finding 'nvcc' in the PATH.
"""
# first check if the CUDAHOME env variable is in use
if 'CUDAHOME' in os.environ:
home = os.environ['CUDAHOME']
nvcc = pjoin(home, 'bin', 'nvcc')
else:
# otherwise, search the PATH for NVCC
default_path = pjoin(os.sep, 'usr', 'local', 'cuda', 'bin')
nvcc = find_in_path('nvcc', os.environ['PATH'] + os.pathsep + default_path)
if nvcc is None:
raise EnvironmentError('The nvcc binary could not be '
'located in your $PATH. Either add it to your path, or set $CUDAHOME')
home = os.path.dirname(os.path.dirname(nvcc))
cudaconfig = {'home':home, 'nvcc':nvcc,
'include': pjoin(home, 'include'),
'lib64': pjoin(home, 'lib64')}
for k, v in cudaconfig.items():
if not os.path.exists(v):
raise EnvironmentError('The CUDA %s path could not be located in %s' % (k, v))
return cudaconfig
|
[
"def",
"locate_cuda",
"(",
")",
":",
"# first check if the CUDAHOME env variable is in use",
"if",
"'CUDAHOME'",
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"environ",
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"'The nvcc binary could not be '",
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"cudaconfig",
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"'The CUDA %s path could not be located in %s'",
"%",
"(",
"k",
",",
"v",
")",
")",
"return",
"cudaconfig"
] |
https://github.com/TuSimple/simpledet/blob/97413463f0bc3116f684eaf7031fd3dd6ded3149/operator_py/cython/setup.py#L27-L57
|
|
almarklein/visvis
|
766ed97767b44a55a6ff72c742d7385e074d3d55
|
utils/pypoints.py
|
python
|
Point.yi
|
(self)
|
return int(self._data[1]+0.5)
|
Get p[1] rounded to the nearest integer, for indexing.
|
Get p[1] rounded to the nearest integer, for indexing.
|
[
"Get",
"p",
"[",
"1",
"]",
"rounded",
"to",
"the",
"nearest",
"integer",
"for",
"indexing",
"."
] |
def yi(self):
""" Get p[1] rounded to the nearest integer, for indexing. """
return int(self._data[1]+0.5)
|
[
"def",
"yi",
"(",
"self",
")",
":",
"return",
"int",
"(",
"self",
".",
"_data",
"[",
"1",
"]",
"+",
"0.5",
")"
] |
https://github.com/almarklein/visvis/blob/766ed97767b44a55a6ff72c742d7385e074d3d55/utils/pypoints.py#L795-L797
|
|
partho-maple/coding-interview-gym
|
f9b28916da31935a27900794cfb8b91be3b38b9b
|
leetcode.com/python/378_Kth_Smallest_Element_in_a_Sorted_Matrix.py
|
python
|
Solution.kthSmallest
|
(self, matrix, k)
|
return currentNumber
|
:type matrix: List[List[int]]
:type k: int
:rtype: int
|
:type matrix: List[List[int]]
:type k: int
:rtype: int
|
[
":",
"type",
"matrix",
":",
"List",
"[",
"List",
"[",
"int",
"]]",
":",
"type",
"k",
":",
"int",
":",
"rtype",
":",
"int"
] |
def kthSmallest(self, matrix, k):
"""
:type matrix: List[List[int]]
:type k: int
:rtype: int
"""
minHeap = []
# put the 1st element of each row in the min heap
# we don't need to push more than 'k' elements in the heap
for rowIdx in range(min(k, len(matrix))):
heapq.heappush(minHeap, (matrix[rowIdx][0], 0, rowIdx))
currentNumber, currentNumerCount = 0, 0
while minHeap:
currentNumber, columnIdx, rowIdx = heapq.heappop(minHeap)
currentNumerCount += 1
if currentNumerCount == k:
break
else:
if len(matrix[rowIdx]) > columnIdx + 1:
heapq.heappush(minHeap, (matrix[rowIdx][columnIdx + 1], columnIdx + 1, rowIdx))
return currentNumber
|
[
"def",
"kthSmallest",
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",",
"matrix",
",",
"k",
")",
":",
"minHeap",
"=",
"[",
"]",
"# put the 1st element of each row in the min heap",
"# we don't need to push more than 'k' elements in the heap",
"for",
"rowIdx",
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"(",
"min",
"(",
"k",
",",
"len",
"(",
"matrix",
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")",
")",
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"heapq",
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"heappush",
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",",
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"matrix",
"[",
"rowIdx",
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"[",
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",",
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")",
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",",
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",",
"0",
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"currentNumerCount",
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"1",
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"==",
"k",
":",
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":",
"if",
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"(",
"matrix",
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"rowIdx",
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"(",
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",",
"(",
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"[",
"rowIdx",
"]",
"[",
"columnIdx",
"+",
"1",
"]",
",",
"columnIdx",
"+",
"1",
",",
"rowIdx",
")",
")",
"return",
"currentNumber"
] |
https://github.com/partho-maple/coding-interview-gym/blob/f9b28916da31935a27900794cfb8b91be3b38b9b/leetcode.com/python/378_Kth_Smallest_Element_in_a_Sorted_Matrix.py#L4-L26
|
|
jkszw2014/bert-kbqa-NLPCC2017
|
c09511829377b959a8ad5c81f5581e742ba13dc9
|
AttributeMap-BERT-Classification/run_classifier.py
|
python
|
MrpcProcessor.get_test_examples
|
(self, data_dir)
|
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "test.tsv")), "test")
|
See base class.
|
See base class.
|
[
"See",
"base",
"class",
"."
] |
def get_test_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "test.tsv")), "test")
|
[
"def",
"get_test_examples",
"(",
"self",
",",
"data_dir",
")",
":",
"return",
"self",
".",
"_create_examples",
"(",
"self",
".",
"_read_tsv",
"(",
"os",
".",
"path",
".",
"join",
"(",
"data_dir",
",",
"\"test.tsv\"",
")",
")",
",",
"\"test\"",
")"
] |
https://github.com/jkszw2014/bert-kbqa-NLPCC2017/blob/c09511829377b959a8ad5c81f5581e742ba13dc9/AttributeMap-BERT-Classification/run_classifier.py#L309-L312
|
|
raffaele-forte/climber
|
5530a780446e35b1ce977bae140557050fe0b47c
|
Exscript/protocols/Protocol.py
|
python
|
Protocol.app_authorize
|
(self, account = None, flush = True, bailout = False)
|
Like app_authenticate(), but uses the authorization password
of the account.
For the difference between authentication and authorization
please google for AAA.
@type account: Account
@param account: An account object, like login().
@type flush: bool
@param flush: Whether to flush the last prompt from the buffer.
@type bailout: bool
@param bailout: Whether to wait for a prompt after sending the password.
|
Like app_authenticate(), but uses the authorization password
of the account.
|
[
"Like",
"app_authenticate",
"()",
"but",
"uses",
"the",
"authorization",
"password",
"of",
"the",
"account",
"."
] |
def app_authorize(self, account = None, flush = True, bailout = False):
"""
Like app_authenticate(), but uses the authorization password
of the account.
For the difference between authentication and authorization
please google for AAA.
@type account: Account
@param account: An account object, like login().
@type flush: bool
@param flush: Whether to flush the last prompt from the buffer.
@type bailout: bool
@param bailout: Whether to wait for a prompt after sending the password.
"""
with self._get_account(account) as account:
user = account.get_name()
password = account.get_authorization_password()
if password is None:
password = account.get_password()
self._dbg(1, "Attempting to app-authorize %s." % user)
self._app_authenticate(account, password, flush, bailout)
self.app_authorized = True
|
[
"def",
"app_authorize",
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"self",
",",
"account",
"=",
"None",
",",
"flush",
"=",
"True",
",",
"bailout",
"=",
"False",
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":",
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".",
"_get_account",
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"account",
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".",
"get_name",
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")",
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"get_authorization_password",
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"_dbg",
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",",
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"%",
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"_app_authenticate",
"(",
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",",
"password",
",",
"flush",
",",
"bailout",
")",
"self",
".",
"app_authorized",
"=",
"True"
] |
https://github.com/raffaele-forte/climber/blob/5530a780446e35b1ce977bae140557050fe0b47c/Exscript/protocols/Protocol.py#L832-L854
|
||
avrae/avrae
|
6ebe46a1ec3d4dfaa2f9b18fac948325f39f87de
|
cogsmisc/customization.py
|
python
|
Customization.gvar_create
|
(self, ctx, *, value)
|
Creates a global variable.
A name will be randomly assigned upon creation.
|
Creates a global variable.
A name will be randomly assigned upon creation.
|
[
"Creates",
"a",
"global",
"variable",
".",
"A",
"name",
"will",
"be",
"randomly",
"assigned",
"upon",
"creation",
"."
] |
async def gvar_create(self, ctx, *, value):
"""Creates a global variable.
A name will be randomly assigned upon creation."""
name = await helpers.create_gvar(ctx, value)
await ctx.send(f"Created global variable `{name}`.")
|
[
"async",
"def",
"gvar_create",
"(",
"self",
",",
"ctx",
",",
"*",
",",
"value",
")",
":",
"name",
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",",
"value",
")",
"await",
"ctx",
".",
"send",
"(",
"f\"Created global variable `{name}`.\"",
")"
] |
https://github.com/avrae/avrae/blob/6ebe46a1ec3d4dfaa2f9b18fac948325f39f87de/cogsmisc/customization.py#L949-L953
|
||
CastagnaIT/plugin.video.netflix
|
5cf5fa436eb9956576c0f62aa31a4c7d6c5b8a4a
|
packages/httpcore/_async/http11.py
|
python
|
AsyncHTTP11Connection._server_disconnected
|
(self)
|
return self._state == ConnectionState.IDLE and self.socket.is_readable()
|
Return True if the connection is idle, and the underlying socket is readable.
The only valid state the socket can be readable here is when the b""
EOF marker is about to be returned, indicating a server disconnect.
|
Return True if the connection is idle, and the underlying socket is readable.
The only valid state the socket can be readable here is when the b""
EOF marker is about to be returned, indicating a server disconnect.
|
[
"Return",
"True",
"if",
"the",
"connection",
"is",
"idle",
"and",
"the",
"underlying",
"socket",
"is",
"readable",
".",
"The",
"only",
"valid",
"state",
"the",
"socket",
"can",
"be",
"readable",
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"the",
"b",
"EOF",
"marker",
"is",
"about",
"to",
"be",
"returned",
"indicating",
"a",
"server",
"disconnect",
"."
] |
def _server_disconnected(self) -> bool:
"""
Return True if the connection is idle, and the underlying socket is readable.
The only valid state the socket can be readable here is when the b""
EOF marker is about to be returned, indicating a server disconnect.
"""
return self._state == ConnectionState.IDLE and self.socket.is_readable()
|
[
"def",
"_server_disconnected",
"(",
"self",
")",
"->",
"bool",
":",
"return",
"self",
".",
"_state",
"==",
"ConnectionState",
".",
"IDLE",
"and",
"self",
".",
"socket",
".",
"is_readable",
"(",
")"
] |
https://github.com/CastagnaIT/plugin.video.netflix/blob/5cf5fa436eb9956576c0f62aa31a4c7d6c5b8a4a/packages/httpcore/_async/http11.py#L53-L59
|
|
IJDykeman/wangTiles
|
7c1ee2095ebdf7f72bce07d94c6484915d5cae8b
|
experimental_code/tiles_3d/venv_mac_py3/lib/python2.7/site-packages/pip/_vendor/urllib3/connectionpool.py
|
python
|
HTTPConnectionPool._new_conn
|
(self)
|
return conn
|
Return a fresh :class:`HTTPConnection`.
|
Return a fresh :class:`HTTPConnection`.
|
[
"Return",
"a",
"fresh",
":",
"class",
":",
"HTTPConnection",
"."
] |
def _new_conn(self):
"""
Return a fresh :class:`HTTPConnection`.
"""
self.num_connections += 1
log.debug("Starting new HTTP connection (%d): %s:%s",
self.num_connections, self.host, self.port or "80")
conn = self.ConnectionCls(host=self.host, port=self.port,
timeout=self.timeout.connect_timeout,
strict=self.strict, **self.conn_kw)
return conn
|
[
"def",
"_new_conn",
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":",
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"strict",
",",
"*",
"*",
"self",
".",
"conn_kw",
")",
"return",
"conn"
] |
https://github.com/IJDykeman/wangTiles/blob/7c1ee2095ebdf7f72bce07d94c6484915d5cae8b/experimental_code/tiles_3d/venv_mac_py3/lib/python2.7/site-packages/pip/_vendor/urllib3/connectionpool.py#L199-L210
|
|
buke/GreenOdoo
|
3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df
|
runtime/python/lib/python2.7/site-packages/PyWebDAV-0.9.8-py2.7.egg/pywebdav/lib/propfind.py
|
python
|
PROPFIND.createResponse
|
(self)
|
return df
|
Create the multistatus response
This will be delegated to the specific method
depending on which request (allprop, propname, prop)
was found.
If we get a PROPNAME then we simply return the list with empty
values which we get from the interface class
If we get an ALLPROP we first get the list of properties and then
we do the same as with a PROP method.
|
Create the multistatus response
|
[
"Create",
"the",
"multistatus",
"response"
] |
def createResponse(self):
""" Create the multistatus response
This will be delegated to the specific method
depending on which request (allprop, propname, prop)
was found.
If we get a PROPNAME then we simply return the list with empty
values which we get from the interface class
If we get an ALLPROP we first get the list of properties and then
we do the same as with a PROP method.
"""
# check if resource exists
if not self._dataclass.exists(self._uri):
raise DAV_NotFound
df = None
if self.request_type == RT_ALLPROP:
df = self.create_allprop()
if self.request_type == RT_PROPNAME:
df = self.create_propname()
if self.request_type == RT_PROP:
df = self.create_prop()
if df != None:
return df
# no body means ALLPROP!
df = self.create_allprop()
return df
|
[
"def",
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"create_allprop",
"(",
")",
"return",
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] |
https://github.com/buke/GreenOdoo/blob/3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df/runtime/python/lib/python2.7/site-packages/PyWebDAV-0.9.8-py2.7.egg/pywebdav/lib/propfind.py#L48-L82
|
|
home-assistant/core
|
265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1
|
homeassistant/components/decora_wifi/light.py
|
python
|
DecoraWifiLight.__init__
|
(self, switch)
|
Initialize the switch.
|
Initialize the switch.
|
[
"Initialize",
"the",
"switch",
"."
] |
def __init__(self, switch):
"""Initialize the switch."""
self._switch = switch
|
[
"def",
"__init__",
"(",
"self",
",",
"switch",
")",
":",
"self",
".",
"_switch",
"=",
"switch"
] |
https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/decora_wifi/light.py#L96-L98
|
||
lovelylain/pyctp
|
fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d
|
example/ctp/futures/__init__.py
|
python
|
TraderApi.OnRspQryCFMMCTradingAccountKey
|
(self, pCFMMCTradingAccountKey, pRspInfo, nRequestID, bIsLast)
|
查询保证金监管系统经纪公司资金账户密钥响应
|
查询保证金监管系统经纪公司资金账户密钥响应
|
[
"查询保证金监管系统经纪公司资金账户密钥响应"
] |
def OnRspQryCFMMCTradingAccountKey(self, pCFMMCTradingAccountKey, pRspInfo, nRequestID, bIsLast):
"""查询保证金监管系统经纪公司资金账户密钥响应"""
|
[
"def",
"OnRspQryCFMMCTradingAccountKey",
"(",
"self",
",",
"pCFMMCTradingAccountKey",
",",
"pRspInfo",
",",
"nRequestID",
",",
"bIsLast",
")",
":"
] |
https://github.com/lovelylain/pyctp/blob/fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d/example/ctp/futures/__init__.py#L629-L630
|
||
google-research/language
|
61fa7260ac7d690d11ef72ca863e45a37c0bdc80
|
language/labs/drkit/model_fns.py
|
python
|
create_hotpotqa_model
|
(bert_config,
qa_config,
mips_config,
is_training,
features,
ent2ment_ind,
ent2ment_val,
ment2ent_map,
entity_ids,
entity_mask,
use_one_hot_embeddings,
summary_obj,
num_hops=2)
|
return total_loss, predictions
|
Creates a classification model.
|
Creates a classification model.
|
[
"Creates",
"a",
"classification",
"model",
"."
] |
def create_hotpotqa_model(bert_config,
qa_config,
mips_config,
is_training,
features,
ent2ment_ind,
ent2ment_val,
ment2ent_map,
entity_ids,
entity_mask,
use_one_hot_embeddings,
summary_obj,
num_hops=2):
"""Creates a classification model."""
qas_ids = features["qas_ids"]
qry_input_ids = features["qry_input_ids"]
qry_input_mask = features["qry_input_mask"]
batch_size = tf.shape(qry_input_ids)[0]
qry_entity_ids = features["qry_entity_id"]
if not isinstance(qry_entity_ids, tf.SparseTensor):
# This assumes batch_size == 1.
num_ents = features["num_entities"][0]
qry_entity_ids = tf.SparseTensor(
indices=tf.concat([
tf.zeros((num_ents, 1), dtype=tf.int64),
tf.expand_dims(tf.range(num_ents, dtype=tf.int64), 1)
],
axis=1),
values=qry_entity_ids[0, :num_ents],
dense_shape=[1, qa_config.num_entities])
answer_entities = None
if is_training:
answer_entities = features["answer_entities"]
answer_index = tf.SparseTensor(
indices=tf.concat([
answer_entities.indices[:, 0:1],
tf.cast(tf.expand_dims(answer_entities.values, 1), tf.int64)
],
axis=1),
values=tf.ones_like(answer_entities.values, dtype=tf.float32),
dense_shape=[batch_size, qa_config.num_entities])
layer_entities, _, _, _, el, qry_seq_emb = multi_hop(
qry_input_ids,
qry_input_mask,
qry_entity_ids,
entity_ids,
entity_mask,
ent2ment_ind,
ent2ment_val,
ment2ent_map,
is_training,
use_one_hot_embeddings,
bert_config,
qa_config,
mips_config,
num_hops=num_hops,
exclude_set=None)
layer_entities = [el] + layer_entities
# Compute weights for each layer.
with tf.name_scope("classifier"):
qry_emb, _ = layer_qry_encoder(
qry_seq_emb,
qry_input_ids,
qry_input_mask,
is_training,
bert_config,
qa_config,
suffix="_cl")
output_weights = tf.get_variable(
"cl_weights", [qa_config.projection_dim,
len(layer_entities)],
initializer=tf.truncated_normal_initializer(stddev=0.02))
output_bias = tf.get_variable(
"cl_bias", [len(layer_entities)], initializer=tf.zeros_initializer())
logits = tf.matmul(qry_emb, output_weights)
logits = tf.nn.bias_add(logits, output_bias)
probabilities = tf.nn.softmax(logits, axis=-1)
if is_training:
nrows = qa_config.train_batch_size
else:
nrows = qa_config.predict_batch_size
def _to_ragged(sp_tensor):
r_ind = tf.RaggedTensor.from_value_rowids(
value_rowids=sp_tensor.indices[:, 0],
values=sp_tensor.indices[:, 1],
nrows=nrows)
r_val = tf.RaggedTensor.from_value_rowids(
value_rowids=sp_tensor.indices[:, 0],
values=sp_tensor.values,
nrows=nrows)
return r_ind, r_val
def _layer_softmax(entities):
uniq_entity_ids, uniq_entity_scs = aggregate_sparse_indices(
entities.indices, entities.values, entities.dense_shape,
qa_config.entity_score_aggregation_fn)
uniq_entity_scs /= qa_config.softmax_temperature
logits = tf.SparseTensor(uniq_entity_ids, uniq_entity_scs,
entities.dense_shape)
return tf.sparse.softmax(tf.sparse.reorder(logits))
predictions = {"qas_ids": qas_ids}
layer_entities_weighted = []
for i, layer_entity in enumerate(layer_entities):
ent_ind, ent_val = _to_ragged(layer_entity)
predictions.update({
"layer_%d_ent" % i: ent_ind.to_tensor(default_value=-1),
"layer_%d_scs" % i: ent_val.to_tensor(default_value=-1),
})
layer_entities_weighted.append(
batch_multiply(_layer_softmax(layer_entity), probabilities[:, i]))
probs = tf.sparse.add(layer_entities_weighted[0], layer_entities_weighted[1])
for i in range(2, len(layer_entities_weighted)):
probs = tf.sparse.add(probs, layer_entities_weighted[i])
probs_dense = tf.sparse.to_dense(
probs, default_value=DEFAULT_VALUE, validate_indices=False)
answer_preds = tf.argmax(probs_dense, axis=1)
top_vals, top_idx = tf.nn.top_k(probs_dense, k=100, sorted=True)
total_loss = None
if is_training:
sp_loss = compute_loss_from_sptensors(probs, answer_index)
total_loss = tf.reduce_sum(sp_loss.values) / tf.cast(batch_size, tf.float32)
num_answers_ret = tf.shape(sp_loss.values)[0]
if summary_obj is not None:
for i in range(len(layer_entities)):
num_ents = tf.cast(tf.shape(layer_entities[i].indices)[0],
tf.float32) / tf.cast(batch_size, tf.float32)
summary_obj.scalar("train/layer_weight_%d" % i,
tf.reduce_mean(probabilities[:, i], keepdims=True))
summary_obj.scalar("train/num_entities_%d" % i,
tf.expand_dims(num_ents, 0))
summary_obj.scalar("train/total_loss", tf.expand_dims(total_loss, 0))
summary_obj.scalar("train/ans_in_ret", tf.expand_dims(num_answers_ret, 0))
summary_obj.scalar("train/total_prob_mass",
tf.reduce_sum(probs.values, keepdims=True))
predictions.update({
"layer_probs": probabilities,
"top_vals": top_vals,
"top_idx": top_idx,
"predictions": answer_preds,
})
return total_loss, predictions
|
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"(",
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",",
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"(",
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",",
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")",
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"summary_obj",
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"scalar",
"(",
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",",
"tf",
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"expand_dims",
"(",
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",",
"0",
")",
")",
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"scalar",
"(",
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",",
"tf",
".",
"reduce_sum",
"(",
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"values",
",",
"keepdims",
"=",
"True",
")",
")",
"predictions",
".",
"update",
"(",
"{",
"\"layer_probs\"",
":",
"probabilities",
",",
"\"top_vals\"",
":",
"top_vals",
",",
"\"top_idx\"",
":",
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",",
"\"predictions\"",
":",
"answer_preds",
",",
"}",
")",
"return",
"total_loss",
",",
"predictions"
] |
https://github.com/google-research/language/blob/61fa7260ac7d690d11ef72ca863e45a37c0bdc80/language/labs/drkit/model_fns.py#L1401-L1552
|
|
googleads/google-ads-python
|
2a1d6062221f6aad1992a6bcca0e7e4a93d2db86
|
google/ads/googleads/v8/services/services/campaign_draft_service/client.py
|
python
|
CampaignDraftServiceClient.parse_campaign_draft_path
|
(path: str)
|
return m.groupdict() if m else {}
|
Parse a campaign_draft path into its component segments.
|
Parse a campaign_draft path into its component segments.
|
[
"Parse",
"a",
"campaign_draft",
"path",
"into",
"its",
"component",
"segments",
"."
] |
def parse_campaign_draft_path(path: str) -> Dict[str, str]:
"""Parse a campaign_draft path into its component segments."""
m = re.match(
r"^customers/(?P<customer_id>.+?)/campaignDrafts/(?P<base_campaign_id>.+?)~(?P<draft_id>.+?)$",
path,
)
return m.groupdict() if m else {}
|
[
"def",
"parse_campaign_draft_path",
"(",
"path",
":",
"str",
")",
"->",
"Dict",
"[",
"str",
",",
"str",
"]",
":",
"m",
"=",
"re",
".",
"match",
"(",
"r\"^customers/(?P<customer_id>.+?)/campaignDrafts/(?P<base_campaign_id>.+?)~(?P<draft_id>.+?)$\"",
",",
"path",
",",
")",
"return",
"m",
".",
"groupdict",
"(",
")",
"if",
"m",
"else",
"{",
"}"
] |
https://github.com/googleads/google-ads-python/blob/2a1d6062221f6aad1992a6bcca0e7e4a93d2db86/google/ads/googleads/v8/services/services/campaign_draft_service/client.py#L193-L199
|
|
nathanlopez/Stitch
|
8e22e91c94237959c02d521aab58dc7e3d994cea
|
Application/stitch_winshell.py
|
python
|
st_winshell.do_avscan
|
(self,line)
|
[] |
def do_avscan(self,line): self.stlib.avscan()
|
[
"def",
"do_avscan",
"(",
"self",
",",
"line",
")",
":",
"self",
".",
"stlib",
".",
"avscan",
"(",
")"
] |
https://github.com/nathanlopez/Stitch/blob/8e22e91c94237959c02d521aab58dc7e3d994cea/Application/stitch_winshell.py#L73-L73
|
||||
ralphbean/bugwarrior
|
aa660b258f95e29b07508f555ddc639e9cbdab82
|
bugwarrior/services/trello.py
|
python
|
TrelloService.annotations
|
(self, card_json)
|
return annotations
|
A wrapper around get_comments that build the taskwarrior
annotations.
|
A wrapper around get_comments that build the taskwarrior
annotations.
|
[
"A",
"wrapper",
"around",
"get_comments",
"that",
"build",
"the",
"taskwarrior",
"annotations",
"."
] |
def annotations(self, card_json):
""" A wrapper around get_comments that build the taskwarrior
annotations. """
comments = self.get_comments(card_json['id'])
annotations = self.build_annotations(
((c['memberCreator']['username'], c['data']['text']) for c in comments),
card_json["shortUrl"])
return annotations
|
[
"def",
"annotations",
"(",
"self",
",",
"card_json",
")",
":",
"comments",
"=",
"self",
".",
"get_comments",
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"card_json",
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"'id'",
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")",
"annotations",
"=",
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".",
"build_annotations",
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"c",
"[",
"'memberCreator'",
"]",
"[",
"'username'",
"]",
",",
"c",
"[",
"'data'",
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"[",
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"]",
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"for",
"c",
"in",
"comments",
")",
",",
"card_json",
"[",
"\"shortUrl\"",
"]",
")",
"return",
"annotations"
] |
https://github.com/ralphbean/bugwarrior/blob/aa660b258f95e29b07508f555ddc639e9cbdab82/bugwarrior/services/trello.py#L137-L144
|
|
openedx/edx-platform
|
68dd185a0ab45862a2a61e0f803d7e03d2be71b5
|
openedx/core/djangoapps/content_libraries/api.py
|
python
|
EdxApiImportClient.get_block_static_data
|
(self, asset_file)
|
return resp.content
|
See parent's docstring.
|
See parent's docstring.
|
[
"See",
"parent",
"s",
"docstring",
"."
] |
def get_block_static_data(self, asset_file):
"""
See parent's docstring.
"""
if (asset_file['url'].startswith(self.studio_url)
and 'export-file' in asset_file['url']):
# We must call download this file with authentication. But
# we only want to pass the auth headers if this is the same
# studio instance, or else we could leak credentials to a
# third party.
path = asset_file['url'][len(self.studio_url):]
resp = self._call('get', path)
else:
resp = requests.get(asset_file['url'])
resp.raise_for_status()
return resp.content
|
[
"def",
"get_block_static_data",
"(",
"self",
",",
"asset_file",
")",
":",
"if",
"(",
"asset_file",
"[",
"'url'",
"]",
".",
"startswith",
"(",
"self",
".",
"studio_url",
")",
"and",
"'export-file'",
"in",
"asset_file",
"[",
"'url'",
"]",
")",
":",
"# We must call download this file with authentication. But",
"# we only want to pass the auth headers if this is the same",
"# studio instance, or else we could leak credentials to a",
"# third party.",
"path",
"=",
"asset_file",
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"studio_url",
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"resp",
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"raise_for_status",
"(",
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"return",
"resp",
".",
"content"
] |
https://github.com/openedx/edx-platform/blob/68dd185a0ab45862a2a61e0f803d7e03d2be71b5/openedx/core/djangoapps/content_libraries/api.py#L1335-L1350
|
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