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qutebrowser/qutebrowser
|
3a2aaaacbf97f4bf0c72463f3da94ed2822a5442
|
qutebrowser/completion/models/miscmodels.py
|
python
|
process
|
(*, info)
|
return model
|
A CompletionModel filled with processes.
|
A CompletionModel filled with processes.
|
[
"A",
"CompletionModel",
"filled",
"with",
"processes",
"."
] |
def process(*, info):
"""A CompletionModel filled with processes."""
utils.unused(info)
from qutebrowser.misc import guiprocess
model = completionmodel.CompletionModel(column_widths=(10, 10, 80))
for what, processes in itertools.groupby(
(p for p in guiprocess.all_processes.values() if p is not None),
lambda proc: proc.what):
# put successful processes last
sorted_processes = sorted(
processes,
key=lambda proc: proc.outcome.state_str() == 'successful',
)
entries = [(str(proc.pid), proc.outcome.state_str(), str(proc))
for proc in sorted_processes]
cat = listcategory.ListCategory(what.capitalize(), entries, sort=False)
model.add_category(cat)
return model
|
[
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https://github.com/qutebrowser/qutebrowser/blob/3a2aaaacbf97f4bf0c72463f3da94ed2822a5442/qutebrowser/completion/models/miscmodels.py#L306-L325
|
|
etetoolkit/ete
|
2b207357dc2a40ccad7bfd8f54964472c72e4726
|
ete3/phyloxml/_phyloxml.py
|
python
|
ProteinDomain.build
|
(self, node)
|
[] |
def build(self, node):
self.buildAttributes(node, node.attrib, [])
self.valueOf_ = get_all_text_(node)
for child in node:
nodeName_ = Tag_pattern_.match(child.tag).groups()[-1]
self.buildChildren(child, node, nodeName_)
|
[
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] |
https://github.com/etetoolkit/ete/blob/2b207357dc2a40ccad7bfd8f54964472c72e4726/ete3/phyloxml/_phyloxml.py#L1997-L2002
|
||||
RunestoneInteractive/RunestoneServer
|
b20fcca5f08350224f63838250302771656f0951
|
controllers/assignments.py
|
python
|
student_autograde
|
()
|
return json.dumps(res)
|
This is a safe endpoint that students can call from the assignment page
to get a preliminary grade on their assignment. If in coursera_mode,
the total for the assignment is calculated and stored in the db, and
sent via LTI (if LTI is configured).
|
This is a safe endpoint that students can call from the assignment page
to get a preliminary grade on their assignment. If in coursera_mode,
the total for the assignment is calculated and stored in the db, and
sent via LTI (if LTI is configured).
|
[
"This",
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"can",
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"from",
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"assignment",
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"LTI",
"(",
"if",
"LTI",
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"configured",
")",
"."
] |
def student_autograde():
"""
This is a safe endpoint that students can call from the assignment page
to get a preliminary grade on their assignment. If in coursera_mode,
the total for the assignment is calculated and stored in the db, and
sent via LTI (if LTI is configured).
"""
assignment_id = request.vars.assignment_id
timezoneoffset = session.timezoneoffset if "timezoneoffset" in session else None
is_timed = request.vars.is_timed
if assignment_id.isnumeric() is False:
aidrow = (
db(
(db.assignments.name == assignment_id)
& (db.assignments.course == auth.user.course_id)
)
.select()
.first()
)
if aidrow:
assignment_id = aidrow.id
else:
res = {"success": False, "message": "Could not find this assignment"}
return json.dumps(res)
res = _autograde(
student_rownum=auth.user.id,
assignment_id=assignment_id,
timezoneoffset=timezoneoffset,
)
if not res["success"]:
session.flash = (
"Failed to autograde questions for user id {} for assignment {}".format(
auth.user.id, assignment_id
)
)
res = {"success": False}
else:
if settings.coursera_mode or is_timed:
res2 = _calculate_totals(
student_rownum=auth.user.id, assignment_id=assignment_id
)
if not res2["success"]:
session.flash = (
"Failed to compute totals for user id {} for assignment {}".format(
auth.user.id, assignment_id
)
)
res = {"success": False}
else:
_try_to_send_lti_grade(auth.user.id, assignment_id)
return json.dumps(res)
|
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] |
https://github.com/RunestoneInteractive/RunestoneServer/blob/b20fcca5f08350224f63838250302771656f0951/controllers/assignments.py#L220-L273
|
|
omz/PythonistaAppTemplate
|
f560f93f8876d82a21d108977f90583df08d55af
|
PythonistaAppTemplate/PythonistaKit.framework/pylib_ext/matplotlib/lines.py
|
python
|
Line2D.get_markevery
|
(self)
|
return self._markevery
|
return the markevery setting
|
return the markevery setting
|
[
"return",
"the",
"markevery",
"setting"
] |
def get_markevery(self):
"""return the markevery setting"""
return self._markevery
|
[
"def",
"get_markevery",
"(",
"self",
")",
":",
"return",
"self",
".",
"_markevery"
] |
https://github.com/omz/PythonistaAppTemplate/blob/f560f93f8876d82a21d108977f90583df08d55af/PythonistaAppTemplate/PythonistaKit.framework/pylib_ext/matplotlib/lines.py#L361-L363
|
|
wistbean/learn_python3_spider
|
73c873f4845f4385f097e5057407d03dd37a117b
|
stackoverflow/venv/lib/python3.6/site-packages/OpenSSL/crypto.py
|
python
|
load_crl
|
(type, buffer)
|
return result
|
Load Certificate Revocation List (CRL) data from a string *buffer*.
*buffer* encoded with the type *type*.
:param type: The file type (one of FILETYPE_PEM, FILETYPE_ASN1)
:param buffer: The buffer the CRL is stored in
:return: The PKey object
|
Load Certificate Revocation List (CRL) data from a string *buffer*.
*buffer* encoded with the type *type*.
|
[
"Load",
"Certificate",
"Revocation",
"List",
"(",
"CRL",
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"data",
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".",
"*",
"buffer",
"*",
"encoded",
"with",
"the",
"type",
"*",
"type",
"*",
"."
] |
def load_crl(type, buffer):
"""
Load Certificate Revocation List (CRL) data from a string *buffer*.
*buffer* encoded with the type *type*.
:param type: The file type (one of FILETYPE_PEM, FILETYPE_ASN1)
:param buffer: The buffer the CRL is stored in
:return: The PKey object
"""
if isinstance(buffer, _text_type):
buffer = buffer.encode("ascii")
bio = _new_mem_buf(buffer)
if type == FILETYPE_PEM:
crl = _lib.PEM_read_bio_X509_CRL(bio, _ffi.NULL, _ffi.NULL, _ffi.NULL)
elif type == FILETYPE_ASN1:
crl = _lib.d2i_X509_CRL_bio(bio, _ffi.NULL)
else:
raise ValueError("type argument must be FILETYPE_PEM or FILETYPE_ASN1")
if crl == _ffi.NULL:
_raise_current_error()
result = CRL.__new__(CRL)
result._crl = _ffi.gc(crl, _lib.X509_CRL_free)
return result
|
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https://github.com/wistbean/learn_python3_spider/blob/73c873f4845f4385f097e5057407d03dd37a117b/stackoverflow/venv/lib/python3.6/site-packages/OpenSSL/crypto.py#L2971-L2998
|
|
linxid/Machine_Learning_Study_Path
|
558e82d13237114bbb8152483977806fc0c222af
|
Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/importlib/_bootstrap_external.py
|
python
|
_NamespaceLoader.create_module
|
(self, spec)
|
Use default semantics for module creation.
|
Use default semantics for module creation.
|
[
"Use",
"default",
"semantics",
"for",
"module",
"creation",
"."
] |
def create_module(self, spec):
"""Use default semantics for module creation."""
|
[
"def",
"create_module",
"(",
"self",
",",
"spec",
")",
":"
] |
https://github.com/linxid/Machine_Learning_Study_Path/blob/558e82d13237114bbb8152483977806fc0c222af/Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/importlib/_bootstrap_external.py#L1035-L1036
|
||
yongxinz/tech-blog
|
fb50b7d1abd218df41a937f662964d1d40684a7b
|
rabbitmq/src/rabbitmq_status.py
|
python
|
RabbitMQMoniter.check_server
|
(self, item, node_name)
|
return 'Not Found'
|
check server
|
check server
|
[
"check",
"server"
] |
def check_server(self, item, node_name):
"""
check server
"""
node_name = node_name.split('.')[0]
for nodeData in self.call_api('nodes'):
if node_name in nodeData['name']:
return nodeData.get(item, 0)
return 'Not Found'
|
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")",
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https://github.com/yongxinz/tech-blog/blob/fb50b7d1abd218df41a937f662964d1d40684a7b/rabbitmq/src/rabbitmq_status.py#L110-L118
|
|
toxinu/pyhn
|
c36090e33ae730daa16c276e5f54c49baef2d8fe
|
pyhn/hnapi.py
|
python
|
HackerNewsAPI.get_stories
|
(self, source)
|
return news_stories
|
Looks at source, makes stories from it, returns the stories.
|
Looks at source, makes stories from it, returns the stories.
|
[
"Looks",
"at",
"source",
"makes",
"stories",
"from",
"it",
"returns",
"the",
"stories",
"."
] |
def get_stories(self, source):
"""
Looks at source, makes stories from it, returns the stories.
"""
""" <td align=right valign=top class="title">31.</td> """
self.number_of_stories_on_front_page = source.count(
'span class="rank"')
# Create the empty stories.
news_stories = []
for i in range(0, self.number_of_stories_on_front_page):
story = HackerNewsStory()
news_stories.append(story)
soup = BeautifulSoup(source, "html.parser")
# Gives URLs, Domains and titles.
story_details = soup.findAll("td", {"class": "title"})
# Gives score, submitter, comment count and comment URL.
story_other_details = soup.findAll("td", {"class": "subtext"})
# Get story numbers.
story_numbers = []
for i in range(0, len(story_details) - 1, 2):
# Otherwise, story_details[i] is a BeautifulSoup-defined object.
story = str(story_details[i])
story_number = self.get_story_number(story)
story_numbers.append(story_number)
story_urls = []
story_domains = []
story_titles = []
story_scores = []
story_submitters = []
story_comment_counts = []
story_comment_urls = []
story_published_time = []
story_ids = []
# Every second cell contains a story.
for i in range(1, len(story_details), 2):
story = str(story_details[i])
story_urls.append(self.get_story_url(story))
story_domains.append(self.get_story_domain(story))
story_titles.append(self.get_story_title(story))
for s in story_other_details:
story = str(s)
story_scores.append(self.get_story_score(story))
story_submitters.append(self.get_submitter(story))
story_comment_counts.append(self.get_comment_count(story))
story_comment_urls.append(self.get_comments_url(story))
story_published_time.append(self.get_published_time(story))
story_ids.append(self.get_hn_id(story))
# Associate the values with our newsStories.
for i in range(0, self.number_of_stories_on_front_page):
news_stories[i].number = story_numbers[i]
news_stories[i].url = story_urls[i]
news_stories[i].domain = story_domains[i]
news_stories[i].title = story_titles[i]
news_stories[i].score = story_scores[i]
news_stories[i].submitter = story_submitters[i]
if news_stories[i].submitter:
news_stories[i].submitter_url = (
"https://news.ycombinator.com/user?id={}".format(
story_submitters[i]))
else:
news_stories[i].submitter_url = None
news_stories[i].comment_count = story_comment_counts[i]
news_stories[i].comments_url = story_comment_urls[i]
news_stories[i].published_time = story_published_time[i]
news_stories[i].id = story_ids[i]
if news_stories[i].id < 0:
news_stories[i].url.find('item?id=') + 8
news_stories[i].comments_url = ''
news_stories[i].submitter = None
news_stories[i].submitter_url = None
return news_stories
|
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] |
https://github.com/toxinu/pyhn/blob/c36090e33ae730daa16c276e5f54c49baef2d8fe/pyhn/hnapi.py#L224-L302
|
|
stratosphereips/StratosphereLinuxIPS
|
985ac0f141dd71fe9c6faa8307bcf95a3754951d
|
modules/ARP/ARP.py
|
python
|
Module.detect_unsolicited_arp
|
(self, profileid, twid, uid, ts, dst_mac, src_mac, dst_hw, src_hw)
|
Unsolicited ARP is used to update the neighbours' ARP caches but can also be used in ARP spoofing
|
Unsolicited ARP is used to update the neighbours' ARP caches but can also be used in ARP spoofing
|
[
"Unsolicited",
"ARP",
"is",
"used",
"to",
"update",
"the",
"neighbours",
"ARP",
"caches",
"but",
"can",
"also",
"be",
"used",
"in",
"ARP",
"spoofing"
] |
def detect_unsolicited_arp(self, profileid, twid, uid, ts, dst_mac, src_mac, dst_hw, src_hw):
""" Unsolicited ARP is used to update the neighbours' ARP caches but can also be used in ARP spoofing """
if dst_mac=="ff:ff:ff:ff:ff:ff" and dst_hw=="ff:ff:ff:ff:ff:ff" and src_mac != '00:00:00:00:00:00' and src_hw != '00:00:00:00:00:00':
# We're sure this is unsolicited arp
confidence = 0.8
threat_level = 'info'
description = f'detected sending unsolicited ARP'
type_evidence = 'UnsolicitedARP'
# This may be ARP spoofing
category = 'Information'
type_detection = 'srcip'
source_target_tag = 'Recon' # srcip description
detection_info = profileid.split("_")[1]
__database__.setEvidence(type_evidence, type_detection, detection_info, threat_level, confidence,
description, ts, category,source_target_tag=source_target_tag, profileid=profileid, twid=twid, uid=uid)
return True
|
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https://github.com/stratosphereips/StratosphereLinuxIPS/blob/985ac0f141dd71fe9c6faa8307bcf95a3754951d/modules/ARP/ARP.py#L176-L191
|
||
lisa-lab/pylearn2
|
af81e5c362f0df4df85c3e54e23b2adeec026055
|
pylearn2/datasets/dense_design_matrix.py
|
python
|
DenseDesignMatrix.get_batch_design
|
(self, batch_size, include_labels=False)
|
return rx
|
.. todo::
WRITEME
Parameters
----------
batch_size : int
WRITEME
include_labels : bool
WRITEME
|
.. todo::
|
[
"..",
"todo",
"::"
] |
def get_batch_design(self, batch_size, include_labels=False):
"""
.. todo::
WRITEME
Parameters
----------
batch_size : int
WRITEME
include_labels : bool
WRITEME
"""
try:
idx = self.rng.randint(self.X.shape[0] - batch_size + 1)
except ValueError:
if batch_size > self.X.shape[0]:
reraise_as(ValueError("Requested %d examples from a dataset "
"containing only %d." %
(batch_size, self.X.shape[0])))
raise
rx = self.X[idx:idx + batch_size, :]
if include_labels:
if self.y is None:
return rx, None
ry = self.y[idx:idx + batch_size]
return rx, ry
rx = np.cast[config.floatX](rx)
return rx
|
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https://github.com/lisa-lab/pylearn2/blob/af81e5c362f0df4df85c3e54e23b2adeec026055/pylearn2/datasets/dense_design_matrix.py#L835-L863
|
|
grantjenks/free-python-games
|
3f27c6555e2c72a9b1c668c4dd8506d7b8378d09
|
freegames/memory.py
|
python
|
index
|
(x, y)
|
return int((x + 200) // 50 + ((y + 200) // 50) * 8)
|
Convert (x, y) coordinates to tiles index.
|
Convert (x, y) coordinates to tiles index.
|
[
"Convert",
"(",
"x",
"y",
")",
"coordinates",
"to",
"tiles",
"index",
"."
] |
def index(x, y):
"""Convert (x, y) coordinates to tiles index."""
return int((x + 200) // 50 + ((y + 200) // 50) * 8)
|
[
"def",
"index",
"(",
"x",
",",
"y",
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":",
"return",
"int",
"(",
"(",
"x",
"+",
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"+",
"(",
"(",
"y",
"+",
"200",
")",
"//",
"50",
")",
"*",
"8",
")"
] |
https://github.com/grantjenks/free-python-games/blob/3f27c6555e2c72a9b1c668c4dd8506d7b8378d09/freegames/memory.py#L36-L38
|
|
CPJKU/madmom
|
3bc8334099feb310acfce884ebdb76a28e01670d
|
madmom/audio/signal.py
|
python
|
signal_frame
|
(signal, index, frame_size, hop_size, origin=0, pad=0)
|
return frame
|
This function returns frame at `index` of the `signal`.
Parameters
----------
signal : numpy array
Signal.
index : int
Index of the frame to return.
frame_size : int
Size of each frame in samples.
hop_size : float
Hop size in samples between adjacent frames.
origin : int
Location of the window center relative to the signal position.
pad : int, float or str, optional
Pad parts of the frame not covered by the signal with this value.
The literal 'repeat' can be used to indicate that the first/last value
should be repeated.
Returns
-------
frame : numpy array
Requested frame of the signal.
Notes
-----
The reference sample of the first frame (index == 0) refers to the first
sample of the `signal`, and each following frame is placed `hop_size`
samples after the previous one.
The window is always centered around this reference sample. Its location
relative to the reference sample can be set with the `origin` parameter.
Arbitrary integer values can be given:
- zero centers the window on its reference sample
- negative values shift the window to the right
- positive values shift the window to the left
An `origin` of half the size of the `frame_size` results in windows located
to the left of the reference sample, i.e. the first frame starts at the
first sample of the signal.
The part of the frame which is not covered by the signal is padded with
zeros.
This function is totally independent of the length of the signal. Thus,
contrary to common indexing, the index '-1' refers NOT to the last frame
of the signal, but instead the frame left of the first frame is returned.
|
This function returns frame at `index` of the `signal`.
|
[
"This",
"function",
"returns",
"frame",
"at",
"index",
"of",
"the",
"signal",
"."
] |
def signal_frame(signal, index, frame_size, hop_size, origin=0, pad=0):
"""
This function returns frame at `index` of the `signal`.
Parameters
----------
signal : numpy array
Signal.
index : int
Index of the frame to return.
frame_size : int
Size of each frame in samples.
hop_size : float
Hop size in samples between adjacent frames.
origin : int
Location of the window center relative to the signal position.
pad : int, float or str, optional
Pad parts of the frame not covered by the signal with this value.
The literal 'repeat' can be used to indicate that the first/last value
should be repeated.
Returns
-------
frame : numpy array
Requested frame of the signal.
Notes
-----
The reference sample of the first frame (index == 0) refers to the first
sample of the `signal`, and each following frame is placed `hop_size`
samples after the previous one.
The window is always centered around this reference sample. Its location
relative to the reference sample can be set with the `origin` parameter.
Arbitrary integer values can be given:
- zero centers the window on its reference sample
- negative values shift the window to the right
- positive values shift the window to the left
An `origin` of half the size of the `frame_size` results in windows located
to the left of the reference sample, i.e. the first frame starts at the
first sample of the signal.
The part of the frame which is not covered by the signal is padded with
zeros.
This function is totally independent of the length of the signal. Thus,
contrary to common indexing, the index '-1' refers NOT to the last frame
of the signal, but instead the frame left of the first frame is returned.
"""
# cast variables to int
frame_size = int(frame_size)
# length of the signal
num_samples = len(signal)
# seek to the correct position in the audio signal
ref_sample = int(index * hop_size)
# position the window
start = ref_sample - frame_size // 2 - int(origin)
stop = start + frame_size
# return the requested portion of the signal
# Note: use NumPy's advanced indexing (i.e. trailing comma) in order to
# avoid a memory leak (issue #321). This returns a copy of the data,
# however, returning a simple copy of the relevant portion of the
# signal also leaks memory
# Update: removing this hack again, since it seems that it is not needed
# any more with recent NumPy versions
if start >= 0 and stop <= num_samples:
# normal read operation, return appropriate section
return signal[start:stop]
# part of the frame falls outside the signal, padding needed
# Note: np.pad(signal[from: to], (pad_left, pad_right), mode='constant')
# always returns a ndarray, not the subclass (and is slower);
# usually np.zeros_like(signal[:frame_size]) is exactly what we want
# (i.e. zeros of frame_size length and the same type/class as the
# signal and not just the dtype), but since we have no guarantee that
# the signal is that long, we have to use the np.repeat workaround
frame = np.repeat(signal[:1], frame_size, axis=0)
# determine how many samples need to be padded from left/right
left, right = 0, 0
if start < 0:
left = min(stop, 0) - start
# repeat beginning of signal
frame[:left] = np.repeat(signal[:1], left, axis=0)
if pad != 'repeat':
frame[:left] = pad
start = 0
if stop > num_samples:
right = stop - max(start, num_samples)
# repeat end of signal
frame[-right:] = np.repeat(signal[-1:], right, axis=0)
if pad != 'repeat':
frame[-right:] = pad
stop = num_samples
# position signal inside frame
frame[left:frame_size - right] = signal[min(start, num_samples):
max(stop, 0)]
# return the frame
return frame
|
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"0",
")",
"if",
"pad",
"!=",
"'repeat'",
":",
"frame",
"[",
":",
"left",
"]",
"=",
"pad",
"start",
"=",
"0",
"if",
"stop",
">",
"num_samples",
":",
"right",
"=",
"stop",
"-",
"max",
"(",
"start",
",",
"num_samples",
")",
"# repeat end of signal",
"frame",
"[",
"-",
"right",
":",
"]",
"=",
"np",
".",
"repeat",
"(",
"signal",
"[",
"-",
"1",
":",
"]",
",",
"right",
",",
"axis",
"=",
"0",
")",
"if",
"pad",
"!=",
"'repeat'",
":",
"frame",
"[",
"-",
"right",
":",
"]",
"=",
"pad",
"stop",
"=",
"num_samples",
"# position signal inside frame",
"frame",
"[",
"left",
":",
"frame_size",
"-",
"right",
"]",
"=",
"signal",
"[",
"min",
"(",
"start",
",",
"num_samples",
")",
":",
"max",
"(",
"stop",
",",
"0",
")",
"]",
"# return the frame",
"return",
"frame"
] |
https://github.com/CPJKU/madmom/blob/3bc8334099feb310acfce884ebdb76a28e01670d/madmom/audio/signal.py#L859-L961
|
|
sagemath/sage
|
f9b2db94f675ff16963ccdefba4f1a3393b3fe0d
|
src/sage/rings/semirings/non_negative_integer_semiring.py
|
python
|
NonNegativeIntegerSemiring._repr_
|
(self)
|
return "Non negative integer semiring"
|
r"""
EXAMPLES::
sage: NonNegativeIntegerSemiring()
Non negative integer semiring
|
r"""
EXAMPLES::
|
[
"r",
"EXAMPLES",
"::"
] |
def _repr_(self):
r"""
EXAMPLES::
sage: NonNegativeIntegerSemiring()
Non negative integer semiring
"""
return "Non negative integer semiring"
|
[
"def",
"_repr_",
"(",
"self",
")",
":",
"return",
"\"Non negative integer semiring\""
] |
https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/rings/semirings/non_negative_integer_semiring.py#L75-L82
|
|
blmoistawinde/HarvestText
|
fae00fff2088f43a379726ef83d5c85567a9cd74
|
harvesttext/resources.py
|
python
|
get_english_senti_lexicon
|
(type="LH")
|
return senti_lexicon
|
获得英语情感词汇表
目前默认为来自这里的词汇表
https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html#lexicon
If you use this list, please cite the following paper:
Minqing Hu and Bing Liu. "Mining and Summarizing Customer Reviews."
Proceedings of the ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining (KDD-2004), Aug 22-25, 2004, Seattle,
Washington, USA,
:return: sent_dict = {"pos":[words],"neg":[words]}
|
获得英语情感词汇表
|
[
"获得英语情感词汇表"
] |
def get_english_senti_lexicon(type="LH"):
"""
获得英语情感词汇表
目前默认为来自这里的词汇表
https://www.cs.uic.edu/~liub/FBS/sentiment-analysis.html#lexicon
If you use this list, please cite the following paper:
Minqing Hu and Bing Liu. "Mining and Summarizing Customer Reviews."
Proceedings of the ACM SIGKDD International Conference on Knowledge
Discovery and Data Mining (KDD-2004), Aug 22-25, 2004, Seattle,
Washington, USA,
:return: sent_dict = {"pos":[words],"neg":[words]}
"""
pwd = os.path.abspath(os.path.dirname(__file__))
with open(pwd + "/resources/LH_senti_lexicon.json", "r", encoding="utf-8") as f:
senti_lexicon = json.load(f)
return senti_lexicon
|
[
"def",
"get_english_senti_lexicon",
"(",
"type",
"=",
"\"LH\"",
")",
":",
"pwd",
"=",
"os",
".",
"path",
".",
"abspath",
"(",
"os",
".",
"path",
".",
"dirname",
"(",
"__file__",
")",
")",
"with",
"open",
"(",
"pwd",
"+",
"\"/resources/LH_senti_lexicon.json\"",
",",
"\"r\"",
",",
"encoding",
"=",
"\"utf-8\"",
")",
"as",
"f",
":",
"senti_lexicon",
"=",
"json",
".",
"load",
"(",
"f",
")",
"return",
"senti_lexicon"
] |
https://github.com/blmoistawinde/HarvestText/blob/fae00fff2088f43a379726ef83d5c85567a9cd74/harvesttext/resources.py#L106-L125
|
|
winkidney/weixin2py
|
dd0fc951a592da5afc4fe010da4dc7472455db4b
|
weixin2py/__init__.py
|
python
|
get_atoken
|
(app_id, app_secret)
|
return None
|
Get AccessToken by appid and appsecret.
:param app_id:
:param app_secret: Tencent appsecret
:return: Access token.
:rtype str or unicode
|
Get AccessToken by appid and appsecret.
:param app_id:
:param app_secret: Tencent appsecret
:return: Access token.
:rtype str or unicode
|
[
"Get",
"AccessToken",
"by",
"appid",
"and",
"appsecret",
".",
":",
"param",
"app_id",
":",
":",
"param",
"app_secret",
":",
"Tencent",
"appsecret",
":",
"return",
":",
"Access",
"token",
".",
":",
"rtype",
"str",
"or",
"unicode"
] |
def get_atoken(app_id, app_secret):
"""
Get AccessToken by appid and appsecret.
:param app_id:
:param app_secret: Tencent appsecret
:return: Access token.
:rtype str or unicode
"""
url = """https://api.weixin.qq.com/cgi-bin/token?grant_type=client_credential&appid=%(appid)s&secret=%(appsecret)s""" \
% {'appid': app_id, 'appsecret': app_secret}
try:
result = urllib2.urlopen(url, timeout=20).read()
except urllib2.HTTPError, urllib2.URLError:
return None
if result:
if re.findall('"access_token":"(.*?)"', result):
return result[0]
return None
|
[
"def",
"get_atoken",
"(",
"app_id",
",",
"app_secret",
")",
":",
"url",
"=",
"\"\"\"https://api.weixin.qq.com/cgi-bin/token?grant_type=client_credential&appid=%(appid)s&secret=%(appsecret)s\"\"\"",
"%",
"{",
"'appid'",
":",
"app_id",
",",
"'appsecret'",
":",
"app_secret",
"}",
"try",
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"result",
"=",
"urllib2",
".",
"urlopen",
"(",
"url",
",",
"timeout",
"=",
"20",
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"read",
"(",
")",
"except",
"urllib2",
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"HTTPError",
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"urllib2",
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"URLError",
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"result",
":",
"if",
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".",
"findall",
"(",
"'\"access_token\":\"(.*?)\"'",
",",
"result",
")",
":",
"return",
"result",
"[",
"0",
"]",
"return",
"None"
] |
https://github.com/winkidney/weixin2py/blob/dd0fc951a592da5afc4fe010da4dc7472455db4b/weixin2py/__init__.py#L240-L258
|
|
iskandr/parakeet
|
d9089f999cc4a417d121970b2a447d5e524a3d3b
|
parakeet/lib/math.py
|
python
|
conjugate
|
(x)
|
return x
|
For now we don't have complex numbers so this is just the identity function
|
For now we don't have complex numbers so this is just the identity function
|
[
"For",
"now",
"we",
"don",
"t",
"have",
"complex",
"numbers",
"so",
"this",
"is",
"just",
"the",
"identity",
"function"
] |
def conjugate(x):
"""
For now we don't have complex numbers so this is just the identity function
"""
return x
|
[
"def",
"conjugate",
"(",
"x",
")",
":",
"return",
"x"
] |
https://github.com/iskandr/parakeet/blob/d9089f999cc4a417d121970b2a447d5e524a3d3b/parakeet/lib/math.py#L8-L12
|
|
pyouroboros/ouroboros
|
fee45f2dbf6eb3fc3ddab7473ca60df515aedc1f
|
pyouroboros/dataexporters.py
|
python
|
DataManager.add
|
(self, label, socket)
|
[] |
def add(self, label, socket):
if self.config.data_export == "prometheus" and self.enabled:
self.prometheus.update(label, socket)
elif self.config.data_export == "influxdb" and self.enabled:
if label == "all":
self.logger.debug("Total containers updated %s", self.total_updated[socket])
self.influx.write_points(label, socket)
|
[
"def",
"add",
"(",
"self",
",",
"label",
",",
"socket",
")",
":",
"if",
"self",
".",
"config",
".",
"data_export",
"==",
"\"prometheus\"",
"and",
"self",
".",
"enabled",
":",
"self",
".",
"prometheus",
".",
"update",
"(",
"label",
",",
"socket",
")",
"elif",
"self",
".",
"config",
".",
"data_export",
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"self",
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"logger",
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"debug",
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"\"Total containers updated %s\"",
",",
"self",
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"total_updated",
"[",
"socket",
"]",
")",
"self",
".",
"influx",
".",
"write_points",
"(",
"label",
",",
"socket",
")"
] |
https://github.com/pyouroboros/ouroboros/blob/fee45f2dbf6eb3fc3ddab7473ca60df515aedc1f/pyouroboros/dataexporters.py#L20-L28
|
||||
chromium/web-page-replay
|
472351e1122bb1beb936952c7e75ae58bf8a69f1
|
third_party/ipaddr/ipaddr.py
|
python
|
_BaseV6.is_unspecified
|
(self)
|
return self._ip == 0 and getattr(self, '_prefixlen', 128) == 128
|
Test if the address is unspecified.
Returns:
A boolean, True if this is the unspecified address as defined in
RFC 2373 2.5.2.
|
Test if the address is unspecified.
|
[
"Test",
"if",
"the",
"address",
"is",
"unspecified",
"."
] |
def is_unspecified(self):
"""Test if the address is unspecified.
Returns:
A boolean, True if this is the unspecified address as defined in
RFC 2373 2.5.2.
"""
return self._ip == 0 and getattr(self, '_prefixlen', 128) == 128
|
[
"def",
"is_unspecified",
"(",
"self",
")",
":",
"return",
"self",
".",
"_ip",
"==",
"0",
"and",
"getattr",
"(",
"self",
",",
"'_prefixlen'",
",",
"128",
")",
"==",
"128"
] |
https://github.com/chromium/web-page-replay/blob/472351e1122bb1beb936952c7e75ae58bf8a69f1/third_party/ipaddr/ipaddr.py#L1647-L1655
|
|
nolze/msoffcrypto-tool
|
01c5b23ee81bd39a37ea090af2656e6891767be7
|
msoffcrypto/format/ppt97.py
|
python
|
_parseCryptSession10Container
|
(blob)
|
return CryptSession10Container(
rh=rh,
data=data,
)
|
[] |
def _parseCryptSession10Container(blob):
# CryptSession10Container: https://docs.microsoft.com/en-us/openspecs/office_file_formats/ms-ppt/b0963334-4408-4621-879a-ef9c54551fd8
CryptSession10Container = namedtuple(
"CryptSession10Container",
[
"rh",
"data",
],
)
# rh (8 bytes): A RecordHeader structure...
buf = io.BytesIO(blob.read(8))
rh = _parseRecordHeader(buf)
# logger.debug(rh)
# ...Sub-fields are further specified in the following table.
assert rh.recVer == 0xF
# The specified value fails
# assert rh.recInstance == 0x000
assert rh.recType == 0x2F14
data = blob.read(rh.recLen)
return CryptSession10Container(
rh=rh,
data=data,
)
|
[
"def",
"_parseCryptSession10Container",
"(",
"blob",
")",
":",
"# CryptSession10Container: https://docs.microsoft.com/en-us/openspecs/office_file_formats/ms-ppt/b0963334-4408-4621-879a-ef9c54551fd8",
"CryptSession10Container",
"=",
"namedtuple",
"(",
"\"CryptSession10Container\"",
",",
"[",
"\"rh\"",
",",
"\"data\"",
",",
"]",
",",
")",
"# rh (8 bytes): A RecordHeader structure...",
"buf",
"=",
"io",
".",
"BytesIO",
"(",
"blob",
".",
"read",
"(",
"8",
")",
")",
"rh",
"=",
"_parseRecordHeader",
"(",
"buf",
")",
"# logger.debug(rh)",
"# ...Sub-fields are further specified in the following table.",
"assert",
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".",
"recVer",
"==",
"0xF",
"# The specified value fails",
"# assert rh.recInstance == 0x000",
"assert",
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"recType",
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"0x2F14",
"data",
"=",
"blob",
".",
"read",
"(",
"rh",
".",
"recLen",
")",
"return",
"CryptSession10Container",
"(",
"rh",
"=",
"rh",
",",
"data",
"=",
"data",
",",
")"
] |
https://github.com/nolze/msoffcrypto-tool/blob/01c5b23ee81bd39a37ea090af2656e6891767be7/msoffcrypto/format/ppt97.py#L413-L440
|
|||
oracle/oci-python-sdk
|
3c1604e4e212008fb6718e2f68cdb5ef71fd5793
|
src/oci/database_tools/database_tools_client.py
|
python
|
DatabaseToolsClient.create_database_tools_connection
|
(self, create_database_tools_connection_details, **kwargs)
|
Creates a new DatabaseToolsConnection.
:param oci.database_tools.models.CreateDatabaseToolsConnectionDetails create_database_tools_connection_details: (required)
Details for the new DatabaseToolsConnection.
:param str opc_retry_token: (optional)
A token that uniquely identifies a request so it can be retried in case of a timeout or
server error without risk of executing that same action again. Retry tokens expire after 24
hours, but can be invalidated before then due to conflicting operations. For example, if a resource
has been deleted and purged from the system, then a retry of the original creation request
might be rejected.
:param str opc_request_id: (optional)
The client request ID for tracing.
:param obj retry_strategy: (optional)
A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level.
This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it.
The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__.
To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`.
:return: A :class:`~oci.response.Response` object with data of type :class:`~oci.database_tools.models.DatabaseToolsConnection`
:rtype: :class:`~oci.response.Response`
:example:
Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/databasetools/create_database_tools_connection.py.html>`__ to see an example of how to use create_database_tools_connection API.
|
Creates a new DatabaseToolsConnection.
|
[
"Creates",
"a",
"new",
"DatabaseToolsConnection",
"."
] |
def create_database_tools_connection(self, create_database_tools_connection_details, **kwargs):
"""
Creates a new DatabaseToolsConnection.
:param oci.database_tools.models.CreateDatabaseToolsConnectionDetails create_database_tools_connection_details: (required)
Details for the new DatabaseToolsConnection.
:param str opc_retry_token: (optional)
A token that uniquely identifies a request so it can be retried in case of a timeout or
server error without risk of executing that same action again. Retry tokens expire after 24
hours, but can be invalidated before then due to conflicting operations. For example, if a resource
has been deleted and purged from the system, then a retry of the original creation request
might be rejected.
:param str opc_request_id: (optional)
The client request ID for tracing.
:param obj retry_strategy: (optional)
A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level.
This should be one of the strategies available in the :py:mod:`~oci.retry` module. This operation will not retry by default, users can also use the convenient :py:data:`~oci.retry.DEFAULT_RETRY_STRATEGY` provided by the SDK to enable retries for it.
The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__.
To have this operation explicitly not perform any retries, pass an instance of :py:class:`~oci.retry.NoneRetryStrategy`.
:return: A :class:`~oci.response.Response` object with data of type :class:`~oci.database_tools.models.DatabaseToolsConnection`
:rtype: :class:`~oci.response.Response`
:example:
Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/databasetools/create_database_tools_connection.py.html>`__ to see an example of how to use create_database_tools_connection API.
"""
resource_path = "/databaseToolsConnections"
method = "POST"
# Don't accept unknown kwargs
expected_kwargs = [
"retry_strategy",
"opc_retry_token",
"opc_request_id"
]
extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]
if extra_kwargs:
raise ValueError(
"create_database_tools_connection got unknown kwargs: {!r}".format(extra_kwargs))
header_params = {
"accept": "application/json",
"content-type": "application/json",
"opc-retry-token": kwargs.get("opc_retry_token", missing),
"opc-request-id": kwargs.get("opc_request_id", missing)
}
header_params = {k: v for (k, v) in six.iteritems(header_params) if v is not missing and v is not None}
retry_strategy = self.base_client.get_preferred_retry_strategy(
operation_retry_strategy=kwargs.get('retry_strategy'),
client_retry_strategy=self.retry_strategy
)
if retry_strategy:
if not isinstance(retry_strategy, retry.NoneRetryStrategy):
self.base_client.add_opc_retry_token_if_needed(header_params)
self.base_client.add_opc_client_retries_header(header_params)
retry_strategy.add_circuit_breaker_callback(self.circuit_breaker_callback)
return retry_strategy.make_retrying_call(
self.base_client.call_api,
resource_path=resource_path,
method=method,
header_params=header_params,
body=create_database_tools_connection_details,
response_type="DatabaseToolsConnection")
else:
return self.base_client.call_api(
resource_path=resource_path,
method=method,
header_params=header_params,
body=create_database_tools_connection_details,
response_type="DatabaseToolsConnection")
|
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",",
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":",
"resource_path",
"=",
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"=",
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"expected_kwargs",
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",",
"\"opc_retry_token\"",
",",
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"]",
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"[",
"_key",
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"(",
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"circuit_breaker_callback",
")",
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".",
"make_retrying_call",
"(",
"self",
".",
"base_client",
".",
"call_api",
",",
"resource_path",
"=",
"resource_path",
",",
"method",
"=",
"method",
",",
"header_params",
"=",
"header_params",
",",
"body",
"=",
"create_database_tools_connection_details",
",",
"response_type",
"=",
"\"DatabaseToolsConnection\"",
")",
"else",
":",
"return",
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"(",
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"=",
"resource_path",
",",
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",",
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"=",
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",",
"body",
"=",
"create_database_tools_connection_details",
",",
"response_type",
"=",
"\"DatabaseToolsConnection\"",
")"
] |
https://github.com/oracle/oci-python-sdk/blob/3c1604e4e212008fb6718e2f68cdb5ef71fd5793/src/oci/database_tools/database_tools_client.py#L315-L392
|
||
Alfanous-team/alfanous
|
594514729473c24efa3908e3107b45a38255de4b
|
src/alfanous/Support/whoosh/filedb/structfile.py
|
python
|
StructFile.read_8bitfloat
|
(self, mantissabits=5, zeroexp=2)
|
return byte_to_float(self.read_byte(), mantissabits, zeroexp)
|
Reads a byte-sized representation of a floating point value.
:param mantissabits: the number of bits to use for the mantissa
(with the rest used for the exponent).
:param zeroexp: the zero point for the exponent.
|
Reads a byte-sized representation of a floating point value.
:param mantissabits: the number of bits to use for the mantissa
(with the rest used for the exponent).
:param zeroexp: the zero point for the exponent.
|
[
"Reads",
"a",
"byte",
"-",
"sized",
"representation",
"of",
"a",
"floating",
"point",
"value",
".",
":",
"param",
"mantissabits",
":",
"the",
"number",
"of",
"bits",
"to",
"use",
"for",
"the",
"mantissa",
"(",
"with",
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"used",
"for",
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"exponent",
")",
".",
":",
"param",
"zeroexp",
":",
"the",
"zero",
"point",
"for",
"the",
"exponent",
"."
] |
def read_8bitfloat(self, mantissabits=5, zeroexp=2):
"""Reads a byte-sized representation of a floating point value.
:param mantissabits: the number of bits to use for the mantissa
(with the rest used for the exponent).
:param zeroexp: the zero point for the exponent.
"""
return byte_to_float(self.read_byte(), mantissabits, zeroexp)
|
[
"def",
"read_8bitfloat",
"(",
"self",
",",
"mantissabits",
"=",
"5",
",",
"zeroexp",
"=",
"2",
")",
":",
"return",
"byte_to_float",
"(",
"self",
".",
"read_byte",
"(",
")",
",",
"mantissabits",
",",
"zeroexp",
")"
] |
https://github.com/Alfanous-team/alfanous/blob/594514729473c24efa3908e3107b45a38255de4b/src/alfanous/Support/whoosh/filedb/structfile.py#L178-L185
|
|
davidfoerster/aptsources-cleanup
|
8ea6b410be2aa7c6fa9382ae25137be71639443d
|
src/aptsources_cleanup/util/relations.py
|
python
|
FrozensetAltRepr.__str__
|
(self)
|
return self._str_impl(self)
|
[] |
def __str__(self):
return self._str_impl(self)
|
[
"def",
"__str__",
"(",
"self",
")",
":",
"return",
"self",
".",
"_str_impl",
"(",
"self",
")"
] |
https://github.com/davidfoerster/aptsources-cleanup/blob/8ea6b410be2aa7c6fa9382ae25137be71639443d/src/aptsources_cleanup/util/relations.py#L15-L16
|
|||
rhinstaller/anaconda
|
63edc8680f1b05cbfe11bef28703acba808c5174
|
pyanaconda/ui/gui/spokes/installation_source.py
|
python
|
SourceSpoke._get_repo_by_id
|
(self, repo_id)
|
return None
|
Return a repository by given name
|
Return a repository by given name
|
[
"Return",
"a",
"repository",
"by",
"given",
"name"
] |
def _get_repo_by_id(self, repo_id):
""" Return a repository by given name
"""
for repo in self._repo_store:
if repo[REPO_OBJ].repo_id == repo_id:
return repo[REPO_OBJ]
return None
|
[
"def",
"_get_repo_by_id",
"(",
"self",
",",
"repo_id",
")",
":",
"for",
"repo",
"in",
"self",
".",
"_repo_store",
":",
"if",
"repo",
"[",
"REPO_OBJ",
"]",
".",
"repo_id",
"==",
"repo_id",
":",
"return",
"repo",
"[",
"REPO_OBJ",
"]",
"return",
"None"
] |
https://github.com/rhinstaller/anaconda/blob/63edc8680f1b05cbfe11bef28703acba808c5174/pyanaconda/ui/gui/spokes/installation_source.py#L1538-L1544
|
|
kanzure/nanoengineer
|
874e4c9f8a9190f093625b267f9767e19f82e6c4
|
cad/src/commands/BuildAtoms/BuildAtomsPropertyManager.py
|
python
|
BuildAtomsPropertyManager._moveSelectedAtom
|
(self, spinBoxValueJunk = None)
|
Move the selected atom position based on the value in the X, Y, Z
coordinate spinboxes in the Selection GroupBox.
@param spinBoxValueJunk: This is the Spinbox value from the valueChanged
signal. It is not used. We just want to know
that the spinbox value has changed.
@type spinBoxValueJunk: double or None
|
Move the selected atom position based on the value in the X, Y, Z
coordinate spinboxes in the Selection GroupBox.
|
[
"Move",
"the",
"selected",
"atom",
"position",
"based",
"on",
"the",
"value",
"in",
"the",
"X",
"Y",
"Z",
"coordinate",
"spinboxes",
"in",
"the",
"Selection",
"GroupBox",
"."
] |
def _moveSelectedAtom(self, spinBoxValueJunk = None):
"""
Move the selected atom position based on the value in the X, Y, Z
coordinate spinboxes in the Selection GroupBox.
@param spinBoxValueJunk: This is the Spinbox value from the valueChanged
signal. It is not used. We just want to know
that the spinbox value has changed.
@type spinBoxValueJunk: double or None
"""
if self.model_changed_from_glpane:
#Model is changed from glpane ,do nothing. Fixes bug 2545
print "bug: self.model_changed_from_glpane seen; should never happen after bug 2564 was fixed." #bruce 071015
return
totalAtoms, selectedAtom, atomPosn_junk = self._currentSelectionParams()
if not totalAtoms == 1:
return
#@NOTE: This is important to determine baggage and nobaggage atoms.
#Otherwise the bondpoints won't move! See also:
# selectMode.atomSetup where this is done.
# But that method gets called only when during atom left down.
#Its not useful here as user may select that atom using selection lasso
#or using other means (ctrl + A if only one atom is present) . Also,
#the lists command.baggage and command.nonbaggage seem to get
#cleared during left up. So that method is not useful.
#There needs to be a method in parentmode (Select_Command or
#BuildAtoms_Command)
#to do the following (next code cleanup?) -- ninad 2007-09-27
self.command.baggage, self.command.nonbaggage = \
selectedAtom.baggage_and_other_neighbors()
xPos= self.xCoordOfSelectedAtom.value()
yPos = self.yCoordOfSelectedAtom.value()
zPos = self.zCoordOfSelectedAtom.value()
newPosition = V(xPos, yPos, zPos)
delta = newPosition - selectedAtom.posn()
#Don't do selectedAtom.setposn() because it needs to handle
#cases where atom has bond points and/or monovalent atoms . It also
#needs to modify the neighboring atom baggage. This is already done in
#the following method in command so use that.
self.command.drag_selected_atom(selectedAtom, delta,
computeBaggage = True)
self.o.gl_update()
|
[
"def",
"_moveSelectedAtom",
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"self",
",",
"spinBoxValueJunk",
"=",
"None",
")",
":",
"if",
"self",
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"model_changed_from_glpane",
":",
"#Model is changed from glpane ,do nothing. Fixes bug 2545",
"print",
"\"bug: self.model_changed_from_glpane seen; should never happen after bug 2564 was fixed.\"",
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"# But that method gets called only when during atom left down.",
"#Its not useful here as user may select that atom using selection lasso",
"#or using other means (ctrl + A if only one atom is present) . Also,",
"#the lists command.baggage and command.nonbaggage seem to get",
"#cleared during left up. So that method is not useful.",
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",",
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"=",
"True",
")",
"self",
".",
"o",
".",
"gl_update",
"(",
")"
] |
https://github.com/kanzure/nanoengineer/blob/874e4c9f8a9190f093625b267f9767e19f82e6c4/cad/src/commands/BuildAtoms/BuildAtomsPropertyManager.py#L369-L416
|
||
buke/GreenOdoo
|
3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df
|
runtime/common/lib/python2.7/site-packages/libxml2.py
|
python
|
ValidCtxt.validatePopElement
|
(self, doc, elem, qname)
|
return ret
|
Pop the element end from the validation stack.
|
Pop the element end from the validation stack.
|
[
"Pop",
"the",
"element",
"end",
"from",
"the",
"validation",
"stack",
"."
] |
def validatePopElement(self, doc, elem, qname):
"""Pop the element end from the validation stack. """
if doc is None: doc__o = None
else: doc__o = doc._o
if elem is None: elem__o = None
else: elem__o = elem._o
ret = libxml2mod.xmlValidatePopElement(self._o, doc__o, elem__o, qname)
return ret
|
[
"def",
"validatePopElement",
"(",
"self",
",",
"doc",
",",
"elem",
",",
"qname",
")",
":",
"if",
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"doc__o",
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"self",
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"_o",
",",
"doc__o",
",",
"elem__o",
",",
"qname",
")",
"return",
"ret"
] |
https://github.com/buke/GreenOdoo/blob/3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df/runtime/common/lib/python2.7/site-packages/libxml2.py#L7121-L7128
|
|
kernel1983/NoMagic
|
4ad6e748cf1ba19857ecacad839a0ff9659e3c31
|
nomagic/torndb.py
|
python
|
Connection.close
|
(self)
|
Closes this database connection.
|
Closes this database connection.
|
[
"Closes",
"this",
"database",
"connection",
"."
] |
def close(self):
"""Closes this database connection."""
if getattr(self, "_db", None) is not None:
self._db.close()
self._db = None
|
[
"def",
"close",
"(",
"self",
")",
":",
"if",
"getattr",
"(",
"self",
",",
"\"_db\"",
",",
"None",
")",
"is",
"not",
"None",
":",
"self",
".",
"_db",
".",
"close",
"(",
")",
"self",
".",
"_db",
"=",
"None"
] |
https://github.com/kernel1983/NoMagic/blob/4ad6e748cf1ba19857ecacad839a0ff9659e3c31/nomagic/torndb.py#L104-L108
|
||
replit-archive/empythoned
|
977ec10ced29a3541a4973dc2b59910805695752
|
dist/lib/python2.7/lib2to3/fixer_util.py
|
python
|
String
|
(string, prefix=None)
|
return Leaf(token.STRING, string, prefix=prefix)
|
A string leaf
|
A string leaf
|
[
"A",
"string",
"leaf"
] |
def String(string, prefix=None):
"""A string leaf"""
return Leaf(token.STRING, string, prefix=prefix)
|
[
"def",
"String",
"(",
"string",
",",
"prefix",
"=",
"None",
")",
":",
"return",
"Leaf",
"(",
"token",
".",
"STRING",
",",
"string",
",",
"prefix",
"=",
"prefix",
")"
] |
https://github.com/replit-archive/empythoned/blob/977ec10ced29a3541a4973dc2b59910805695752/dist/lib/python2.7/lib2to3/fixer_util.py#L85-L87
|
|
kubernetes-client/python
|
47b9da9de2d02b2b7a34fbe05afb44afd130d73a
|
kubernetes/client/models/v1_subject_access_review_status.py
|
python
|
V1SubjectAccessReviewStatus.__ne__
|
(self, other)
|
return self.to_dict() != other.to_dict()
|
Returns true if both objects are not equal
|
Returns true if both objects are not equal
|
[
"Returns",
"true",
"if",
"both",
"objects",
"are",
"not",
"equal"
] |
def __ne__(self, other):
"""Returns true if both objects are not equal"""
if not isinstance(other, V1SubjectAccessReviewStatus):
return True
return self.to_dict() != other.to_dict()
|
[
"def",
"__ne__",
"(",
"self",
",",
"other",
")",
":",
"if",
"not",
"isinstance",
"(",
"other",
",",
"V1SubjectAccessReviewStatus",
")",
":",
"return",
"True",
"return",
"self",
".",
"to_dict",
"(",
")",
"!=",
"other",
".",
"to_dict",
"(",
")"
] |
https://github.com/kubernetes-client/python/blob/47b9da9de2d02b2b7a34fbe05afb44afd130d73a/kubernetes/client/models/v1_subject_access_review_status.py#L202-L207
|
|
clips/pattern
|
d25511f9ca7ed9356b801d8663b8b5168464e68f
|
pattern/web/__init__.py
|
python
|
DBPedia.search
|
(self, query, type=SPARQL, start=1, count=10, sort=RELEVANCY, size=None, cached=False, **kwargs)
|
return results
|
Returns a list of results from DBPedia for the given SPARQL query.
- type : SPARQL,
- start: no maximum,
- count: maximum 1000,
There is a limit of 10 requests/second.
Maximum query execution time is 120 seconds.
|
Returns a list of results from DBPedia for the given SPARQL query.
- type : SPARQL,
- start: no maximum,
- count: maximum 1000,
There is a limit of 10 requests/second.
Maximum query execution time is 120 seconds.
|
[
"Returns",
"a",
"list",
"of",
"results",
"from",
"DBPedia",
"for",
"the",
"given",
"SPARQL",
"query",
".",
"-",
"type",
":",
"SPARQL",
"-",
"start",
":",
"no",
"maximum",
"-",
"count",
":",
"maximum",
"1000",
"There",
"is",
"a",
"limit",
"of",
"10",
"requests",
"/",
"second",
".",
"Maximum",
"query",
"execution",
"time",
"is",
"120",
"seconds",
"."
] |
def search(self, query, type=SPARQL, start=1, count=10, sort=RELEVANCY, size=None, cached=False, **kwargs):
""" Returns a list of results from DBPedia for the given SPARQL query.
- type : SPARQL,
- start: no maximum,
- count: maximum 1000,
There is a limit of 10 requests/second.
Maximum query execution time is 120 seconds.
"""
if type not in (SPARQL,):
raise SearchEngineTypeError
if not query or count < 1 or start < 1:
return Results(DBPEDIA, query, type)
# 1) Construct request URL.
url = URL(DBPEDIA, method=GET)
url.query = {
"format": "json",
"query": "%s OFFSET %s LIMIT %s" % (query,
(start - 1) * min(count, 1000),
(start - 0) * min(count, 1000)
)
}
# 2) Parse JSON response.
try:
data = URL(url).download(cached=cached, timeout=30, **kwargs)
data = json.loads(data)
except HTTP400BadRequest as e:
raise DBPediaQueryError(e.src.read().splitlines()[0])
except HTTP403Forbidden:
raise SearchEngineLimitError
results = Results(DBPEDIA, url.query, type)
results.total = None
for x in data["results"]["bindings"]:
r = Result(url=None)
for k in data["head"]["vars"]:
t1 = x[k].get("type", "literal") # uri | literal | typed-literal
t2 = x[k].get("datatype", "?") # http://www.w3.org/2001/XMLSchema#float | int | date
v = x[k].get("value")
v = self.format(v)
if t1 == "uri":
v = DBPediaResource(v)
if t2.endswith("float"):
v = float(v)
if t2.endswith("int"):
v = int(v)
dict.__setitem__(r, k, v)
results.append(r)
return results
|
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"# http://www.w3.org/2001/XMLSchema#float | int | date",
"v",
"=",
"x",
"[",
"k",
"]",
".",
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] |
https://github.com/clips/pattern/blob/d25511f9ca7ed9356b801d8663b8b5168464e68f/pattern/web/__init__.py#L2986-L3032
|
|
coderholic/pyradio
|
cd3ee2d6b369fedfd009371a59aca23ab39b020f
|
pyradio/radio.py
|
python
|
PyRadio._move_cursor_one_down
|
(self)
|
[] |
def _move_cursor_one_down(self):
self._reset_status_bar_right()
if self.number_of_items > 0:
self.setStation(self.selection + 1)
self._handle_cursor_move_down()
|
[
"def",
"_move_cursor_one_down",
"(",
"self",
")",
":",
"self",
".",
"_reset_status_bar_right",
"(",
")",
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".",
"selection",
"+",
"1",
")",
"self",
".",
"_handle_cursor_move_down",
"(",
")"
] |
https://github.com/coderholic/pyradio/blob/cd3ee2d6b369fedfd009371a59aca23ab39b020f/pyradio/radio.py#L4481-L4485
|
||||
plasticityai/magnitude
|
7ac0baeaf181263b661c3ae00643d21e3fd90216
|
pymagnitude/third_party/allennlp/nn/regularizers/regularizer_applicator.py
|
python
|
RegularizerApplicator.__call__
|
(self, module )
|
return accumulator
|
u"""
Parameters
----------
module : torch.nn.Module, required
The module to regularize.
|
u"""
Parameters
----------
module : torch.nn.Module, required
The module to regularize.
|
[
"u",
"Parameters",
"----------",
"module",
":",
"torch",
".",
"nn",
".",
"Module",
"required",
"The",
"module",
"to",
"regularize",
"."
] |
def __call__(self, module ) :
u"""
Parameters
----------
module : torch.nn.Module, required
The module to regularize.
"""
accumulator = 0.0
# For each parameter find the first matching regex.
for name, parameter in module.named_parameters():
for regex, regularizer in self._regularizers:
if re.search(regex, name):
penalty = regularizer(parameter)
accumulator = accumulator + penalty
break
return accumulator
|
[
"def",
"__call__",
"(",
"self",
",",
"module",
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":",
"accumulator",
"=",
"0.0",
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https://github.com/plasticityai/magnitude/blob/7ac0baeaf181263b661c3ae00643d21e3fd90216/pymagnitude/third_party/allennlp/nn/regularizers/regularizer_applicator.py#L27-L43
|
|
bitcraze/crazyflie-lib-python
|
876f0dc003b91ba5e4de05daae9d0b79cf600f81
|
examples/swarm/hl-commander-swarm.py
|
python
|
activate_mellinger_controller
|
(scf, use_mellinger)
|
[] |
def activate_mellinger_controller(scf, use_mellinger):
controller = 1
if use_mellinger:
controller = 2
scf.cf.param.set_value('stabilizer.controller', controller)
|
[
"def",
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"(",
"scf",
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"=",
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".",
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".",
"param",
".",
"set_value",
"(",
"'stabilizer.controller'",
",",
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] |
https://github.com/bitcraze/crazyflie-lib-python/blob/876f0dc003b91ba5e4de05daae9d0b79cf600f81/examples/swarm/hl-commander-swarm.py#L46-L50
|
||||
crocs-muni/roca
|
df6071d502f68701427f8b1d409cab22055ad1b7
|
roca/detect.py
|
python
|
drop_empty
|
(arr)
|
return [x for x in arr if not isinstance(x, list) or len(x) > 0]
|
Drop empty array element
:param arr:
:return:
|
Drop empty array element
:param arr:
:return:
|
[
"Drop",
"empty",
"array",
"element",
":",
"param",
"arr",
":",
":",
"return",
":"
] |
def drop_empty(arr):
"""
Drop empty array element
:param arr:
:return:
"""
return [x for x in arr if not isinstance(x, list) or len(x) > 0]
|
[
"def",
"drop_empty",
"(",
"arr",
")",
":",
"return",
"[",
"x",
"for",
"x",
"in",
"arr",
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"(",
"x",
",",
"list",
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"or",
"len",
"(",
"x",
")",
">",
"0",
"]"
] |
https://github.com/crocs-muni/roca/blob/df6071d502f68701427f8b1d409cab22055ad1b7/roca/detect.py#L161-L167
|
|
dmlc/dgl
|
8d14a739bc9e446d6c92ef83eafe5782398118de
|
examples/pytorch/graph_matching/ged.py
|
python
|
validate_cost_functions
|
(G1, G2,
node_substitution_cost=None, edge_substitution_cost=None,
G1_node_deletion_cost=None, G1_edge_deletion_cost=None,
G2_node_insertion_cost=None, G2_edge_insertion_cost=None)
|
return node_substitution_cost, edge_substitution_cost, \
G1_node_deletion_cost, G1_edge_deletion_cost, \
G2_node_insertion_cost, G2_edge_insertion_cost
|
Validates cost functions (substitution, insertion, deletion) and initializes them with default=0 for substitution
and default=1 for insertion/deletion
if the provided ones are None.
Parameters : see graph_edit_distance
|
Validates cost functions (substitution, insertion, deletion) and initializes them with default=0 for substitution
and default=1 for insertion/deletion
if the provided ones are None.
|
[
"Validates",
"cost",
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"deletion",
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"for",
"insertion",
"/",
"deletion",
"if",
"the",
"provided",
"ones",
"are",
"None",
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] |
def validate_cost_functions(G1, G2,
node_substitution_cost=None, edge_substitution_cost=None,
G1_node_deletion_cost=None, G1_edge_deletion_cost=None,
G2_node_insertion_cost=None, G2_edge_insertion_cost=None):
"""Validates cost functions (substitution, insertion, deletion) and initializes them with default=0 for substitution
and default=1 for insertion/deletion
if the provided ones are None.
Parameters : see graph_edit_distance
"""
num_G1_nodes = G1.number_of_nodes()
num_G2_nodes = G2.number_of_nodes()
num_G1_edges = G1.number_of_edges()
num_G2_edges = G2.number_of_edges()
# if any cost matrix is None, initialize it with default costs
if node_substitution_cost is None:
node_substitution_cost = np.zeros((num_G1_nodes, num_G2_nodes), dtype=float)
else:
assert node_substitution_cost.shape == (num_G1_nodes, num_G2_nodes);
if edge_substitution_cost is None:
edge_substitution_cost = np.zeros((num_G1_edges, num_G2_edges), dtype=float)
else:
assert edge_substitution_cost.shape == (num_G1_edges, num_G2_edges);
if G1_node_deletion_cost is None:
G1_node_deletion_cost = np.ones(num_G1_nodes, dtype=float)
else:
assert G1_node_deletion_cost.shape[0] == num_G1_nodes;
if G1_edge_deletion_cost is None:
G1_edge_deletion_cost = np.ones(num_G1_edges, dtype=float)
else:
assert G1_edge_deletion_cost.shape[0] == num_G1_edges;
if G2_node_insertion_cost is None:
G2_node_insertion_cost = np.ones(num_G2_nodes, dtype=float)
else:
assert G2_node_insertion_cost.shape[0] == num_G2_nodes;
if G2_edge_insertion_cost is None:
G2_edge_insertion_cost = np.ones(num_G2_edges, dtype=float)
else:
assert G2_edge_insertion_cost.shape[0] == num_G2_edges;
return node_substitution_cost, edge_substitution_cost, \
G1_node_deletion_cost, G1_edge_deletion_cost, \
G2_node_insertion_cost, G2_edge_insertion_cost;
|
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",",
"G1_edge_deletion_cost",
",",
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",",
"G2_edge_insertion_cost"
] |
https://github.com/dmlc/dgl/blob/8d14a739bc9e446d6c92ef83eafe5782398118de/examples/pytorch/graph_matching/ged.py#L11-L62
|
|
hypothesis/h
|
25ef1b8d94889df86ace5a084f1aa0effd9f4e25
|
h/migrations/versions/467ea2898660_fix_document_uri_unique_constraint.py
|
python
|
delete_conflicting_document_uris
|
(session)
|
Delete NULL DocumentURIs where there's already an empty string one.
Later we're going to be finding all DocumentURIs with NULL for their type
or content_type and changing them to empty strings. But for each one of
these NULL DocumentURIs if there is already a matching DocumentURI - same
claimant_normalized, uri_normalized, type and content_type but that already
has an empty string instead of NULL for the type and/or content_type - then
trying to change the NULL DocumentURI to an empty string one will fail with
IntegrityError.
So find all the DocumentURIs with an empty string for their type and/or
content_type and for each one find any matching DocumentURIs but with
NULL for the type and/or content_type and delete them.
After this it should be safe to change all NULL types and content_types
in document_uri to empty strings.
|
Delete NULL DocumentURIs where there's already an empty string one.
|
[
"Delete",
"NULL",
"DocumentURIs",
"where",
"there",
"s",
"already",
"an",
"empty",
"string",
"one",
"."
] |
def delete_conflicting_document_uris(session):
"""
Delete NULL DocumentURIs where there's already an empty string one.
Later we're going to be finding all DocumentURIs with NULL for their type
or content_type and changing them to empty strings. But for each one of
these NULL DocumentURIs if there is already a matching DocumentURI - same
claimant_normalized, uri_normalized, type and content_type but that already
has an empty string instead of NULL for the type and/or content_type - then
trying to change the NULL DocumentURI to an empty string one will fail with
IntegrityError.
So find all the DocumentURIs with an empty string for their type and/or
content_type and for each one find any matching DocumentURIs but with
NULL for the type and/or content_type and delete them.
After this it should be safe to change all NULL types and content_types
in document_uri to empty strings.
"""
doc_uris = session.query(DocumentURI).filter(
sa.or_(DocumentURI.type == "", DocumentURI.content_type == "")
)
n = 0
for doc_uri in doc_uris:
conflicting_doc_uris = session.query(DocumentURI).filter(
DocumentURI.claimant_normalized == doc_uri.claimant_normalized,
DocumentURI.uri_normalized == doc_uri.uri_normalized,
DocumentURI.id != doc_uri.id,
)
if doc_uri.type == "" and doc_uri.content_type == "":
conflicting_doc_uris = conflicting_doc_uris.filter(
sa.or_(DocumentURI.type == "", DocumentURI.type.is_(None)),
sa.or_(
DocumentURI.content_type == "", DocumentURI.content_type.is_(None)
),
)
elif doc_uri.type == "":
conflicting_doc_uris = conflicting_doc_uris.filter(
sa.or_(DocumentURI.type == "", DocumentURI.type.is_(None)),
DocumentURI.content_type == doc_uri.content_type,
)
elif doc_uri.content_type == "":
conflicting_doc_uris = conflicting_doc_uris.filter(
DocumentURI.type == doc_uri.type,
sa.or_(
DocumentURI.content_type == "", DocumentURI.content_type.is_(None)
),
)
n += batch_delete(conflicting_doc_uris, session)
log.info("deleted %d duplicate rows from document_uri (empty string/NULL)" % n)
|
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https://github.com/hypothesis/h/blob/25ef1b8d94889df86ace5a084f1aa0effd9f4e25/h/migrations/versions/467ea2898660_fix_document_uri_unique_constraint.py#L116-L172
|
||
eternnoir/pyTelegramBotAPI
|
fdbc0e6a619f671c2ac97afa2f694c17c6dce7d9
|
telebot/__init__.py
|
python
|
TeleBot.add_chat_join_request_handler
|
(self, handler_dict)
|
Adds a chat_join_request handler
:param handler_dict:
:return:
|
Adds a chat_join_request handler
:param handler_dict:
:return:
|
[
"Adds",
"a",
"chat_join_request",
"handler",
":",
"param",
"handler_dict",
":",
":",
"return",
":"
] |
def add_chat_join_request_handler(self, handler_dict):
"""
Adds a chat_join_request handler
:param handler_dict:
:return:
"""
self.chat_join_request_handlers.append(handler_dict)
|
[
"def",
"add_chat_join_request_handler",
"(",
"self",
",",
"handler_dict",
")",
":",
"self",
".",
"chat_join_request_handlers",
".",
"append",
"(",
"handler_dict",
")"
] |
https://github.com/eternnoir/pyTelegramBotAPI/blob/fdbc0e6a619f671c2ac97afa2f694c17c6dce7d9/telebot/__init__.py#L3316-L3322
|
||
osmr/imgclsmob
|
f2993d3ce73a2f7ddba05da3891defb08547d504
|
tensorflow2/tf2cv/models/simplepose_coco.py
|
python
|
get_simplepose
|
(backbone,
backbone_out_channels,
keypoints,
model_name=None,
data_format="channels_last",
pretrained=False,
root=os.path.join("~", ".tensorflow", "models"),
**kwargs)
|
return net
|
Create SimplePose model with specific parameters.
Parameters:
----------
backbone : nn.Sequential
Feature extractor.
backbone_out_channels : int
Number of output channels for the backbone.
keypoints : int
Number of keypoints.
model_name : str or None, default None
Model name for loading pretrained model.
data_format : str, default 'channels_last'
The ordering of the dimensions in tensors.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.tensorflow/models'
Location for keeping the model parameters.
|
Create SimplePose model with specific parameters.
|
[
"Create",
"SimplePose",
"model",
"with",
"specific",
"parameters",
"."
] |
def get_simplepose(backbone,
backbone_out_channels,
keypoints,
model_name=None,
data_format="channels_last",
pretrained=False,
root=os.path.join("~", ".tensorflow", "models"),
**kwargs):
"""
Create SimplePose model with specific parameters.
Parameters:
----------
backbone : nn.Sequential
Feature extractor.
backbone_out_channels : int
Number of output channels for the backbone.
keypoints : int
Number of keypoints.
model_name : str or None, default None
Model name for loading pretrained model.
data_format : str, default 'channels_last'
The ordering of the dimensions in tensors.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.tensorflow/models'
Location for keeping the model parameters.
"""
channels = [256, 256, 256]
net = SimplePose(
backbone=backbone,
backbone_out_channels=backbone_out_channels,
channels=channels,
keypoints=keypoints,
data_format=data_format,
**kwargs)
if pretrained:
if (model_name is None) or (not model_name):
raise ValueError("Parameter `model_name` should be properly initialized for loading pretrained model.")
from .model_store import get_model_file
in_channels = kwargs["in_channels"] if ("in_channels" in kwargs) else 3
input_shape = (1,) + (in_channels,) + net.in_size if net.data_format == "channels_first" else\
(1,) + net.in_size + (in_channels,)
net.build(input_shape=input_shape)
net.load_weights(
filepath=get_model_file(
model_name=model_name,
local_model_store_dir_path=root))
return net
|
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] |
https://github.com/osmr/imgclsmob/blob/f2993d3ce73a2f7ddba05da3891defb08547d504/tensorflow2/tf2cv/models/simplepose_coco.py#L93-L144
|
|
smart-mobile-software/gitstack
|
d9fee8f414f202143eb6e620529e8e5539a2af56
|
python/Lib/urllib.py
|
python
|
thishost
|
()
|
return _thishost
|
Return the IP address of the current host.
|
Return the IP address of the current host.
|
[
"Return",
"the",
"IP",
"address",
"of",
"the",
"current",
"host",
"."
] |
def thishost():
"""Return the IP address of the current host."""
global _thishost
if _thishost is None:
_thishost = socket.gethostbyname(socket.gethostname())
return _thishost
|
[
"def",
"thishost",
"(",
")",
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"global",
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"if",
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"is",
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":",
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".",
"gethostbyname",
"(",
"socket",
".",
"gethostname",
"(",
")",
")",
"return",
"_thishost"
] |
https://github.com/smart-mobile-software/gitstack/blob/d9fee8f414f202143eb6e620529e8e5539a2af56/python/Lib/urllib.py#L816-L821
|
|
Yonv1943/Python
|
ecce2153892093d7a13686e4cbfd6b323cb59de8
|
ElegantRL/Beta/elegantrl/AgentZoo/ElegantRL-PER/agent.py
|
python
|
AgentD3QN.__init__
|
(self, net_dim, state_dim, action_dim, learning_rate=1e-4)
|
Contribution of D3QN (Dueling Double DQN)
There are not contribution of D3QN.
Obviously, DoubleDQN is compatible with DuelingDQN.
Any beginner can come up with this idea (D3QN) independently.
|
Contribution of D3QN (Dueling Double DQN)
There are not contribution of D3QN.
Obviously, DoubleDQN is compatible with DuelingDQN.
Any beginner can come up with this idea (D3QN) independently.
|
[
"Contribution",
"of",
"D3QN",
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"Dueling",
"Double",
"DQN",
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"There",
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"not",
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"can",
"come",
"up",
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"(",
"D3QN",
")",
"independently",
"."
] |
def __init__(self, net_dim, state_dim, action_dim, learning_rate=1e-4):
super().__init__(net_dim, state_dim, action_dim, learning_rate)
self.explore_rate = 0.25 # epsilon-greedy, the rate of choosing random action
self.act = QNetTwinDuel(net_dim, state_dim, action_dim).to(self.device)
self.act_target = deepcopy(self.act)
self.criterion = torch.nn.SmoothL1Loss()
self.optimizer = torch.optim.Adam(self.act.parameters(), lr=learning_rate)
"""Contribution of D3QN (Dueling Double DQN)
There are not contribution of D3QN.
Obviously, DoubleDQN is compatible with DuelingDQN.
Any beginner can come up with this idea (D3QN) independently.
"""
|
[
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",",
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] |
https://github.com/Yonv1943/Python/blob/ecce2153892093d7a13686e4cbfd6b323cb59de8/ElegantRL/Beta/elegantrl/AgentZoo/ElegantRL-PER/agent.py#L170-L183
|
||
ParmEd/ParmEd
|
cd763f2e83c98ba9e51676f6dbebf0eebfd5157e
|
parmed/unit/unit_operators.py
|
python
|
_unit_class_rdiv
|
(self, other)
|
Divide another object type by a Unit.
Returns a new Quantity with a value of other and units
of the inverse of self.
|
Divide another object type by a Unit.
|
[
"Divide",
"another",
"object",
"type",
"by",
"a",
"Unit",
"."
] |
def _unit_class_rdiv(self, other):
"""
Divide another object type by a Unit.
Returns a new Quantity with a value of other and units
of the inverse of self.
"""
if is_unit(other):
raise NotImplementedError('programmer is surprised __rtruediv__ was called instead of __truediv__')
else:
# print "R scalar / unit"
unit = pow(self, -1.0)
value = other
return Quantity(value, unit).reduce_unit(self)
|
[
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":",
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"is_unit",
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"'programmer is surprised __rtruediv__ was called instead of __truediv__'",
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"Quantity",
"(",
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",",
"unit",
")",
".",
"reduce_unit",
"(",
"self",
")"
] |
https://github.com/ParmEd/ParmEd/blob/cd763f2e83c98ba9e51676f6dbebf0eebfd5157e/parmed/unit/unit_operators.py#L61-L74
|
||
maqp/tfc
|
4bb13da1f19671e1e723db7e8a21be58847209af
|
src/transmitter/commands.py
|
python
|
propagate_setting_effects
|
(setting: str,
queues: 'QueueDict',
contact_list: 'ContactList',
group_list: 'GroupList',
settings: 'Settings',
window: 'TxWindow'
)
|
Propagate the effects of the setting.
|
Propagate the effects of the setting.
|
[
"Propagate",
"the",
"effects",
"of",
"the",
"setting",
"."
] |
def propagate_setting_effects(setting: str,
queues: 'QueueDict',
contact_list: 'ContactList',
group_list: 'GroupList',
settings: 'Settings',
window: 'TxWindow'
) -> None:
"""Propagate the effects of the setting."""
if setting == "max_number_of_contacts":
contact_list.store_contacts()
queues[KEY_MANAGEMENT_QUEUE].put((KDB_UPDATE_SIZE_HEADER, settings))
if setting in ['max_number_of_group_members', 'max_number_of_groups']:
group_list.store_groups()
if setting == 'traffic_masking':
queues[SENDER_MODE_QUEUE].put(settings)
queues[TRAFFIC_MASKING_QUEUE].put(settings.traffic_masking)
window.deselect()
if setting == 'log_file_masking':
queues[LOGFILE_MASKING_QUEUE].put(settings.log_file_masking)
|
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] |
https://github.com/maqp/tfc/blob/4bb13da1f19671e1e723db7e8a21be58847209af/src/transmitter/commands.py#L647-L668
|
||
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_hxb2/lib/python3.5/site-packages/django/db/backends/base/schema.py
|
python
|
BaseDatabaseSchemaEditor._rename_field_sql
|
(self, table, old_field, new_field, new_type)
|
return self.sql_rename_column % {
"table": self.quote_name(table),
"old_column": self.quote_name(old_field.column),
"new_column": self.quote_name(new_field.column),
"type": new_type,
}
|
[] |
def _rename_field_sql(self, table, old_field, new_field, new_type):
return self.sql_rename_column % {
"table": self.quote_name(table),
"old_column": self.quote_name(old_field.column),
"new_column": self.quote_name(new_field.column),
"type": new_type,
}
|
[
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https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_hxb2/lib/python3.5/site-packages/django/db/backends/base/schema.py#L883-L889
|
|||
apache/tvm
|
6eb4ed813ebcdcd9558f0906a1870db8302ff1e0
|
python/tvm/relay/op/strategy/generic.py
|
python
|
wrap_compute_multibox_prior
|
(topi_compute)
|
return _compute_multibox_prior
|
Wrap multibox_prior compute
|
Wrap multibox_prior compute
|
[
"Wrap",
"multibox_prior",
"compute"
] |
def wrap_compute_multibox_prior(topi_compute):
"""Wrap multibox_prior compute"""
def _compute_multibox_prior(attrs, inputs, _):
"""Compute definition of multibox_prior"""
sizes = get_float_tuple(attrs.sizes)
ratios = get_float_tuple(attrs.ratios)
steps = get_float_tuple(attrs.steps)
offsets = get_float_tuple(attrs.offsets)
clip = bool(get_const_int(attrs.clip))
return [topi_compute(inputs[0], sizes, ratios, steps, offsets, clip)]
return _compute_multibox_prior
|
[
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https://github.com/apache/tvm/blob/6eb4ed813ebcdcd9558f0906a1870db8302ff1e0/python/tvm/relay/op/strategy/generic.py#L1107-L1119
|
|
OmkarPathak/pyresparser
|
36f1242fbc0637a6633371ca81cf1aea4fa7497e
|
pyresparser/resume_parser.py
|
python
|
ResumeParser.__init__
|
(
self,
resume,
skills_file=None,
custom_regex=None
)
|
[] |
def __init__(
self,
resume,
skills_file=None,
custom_regex=None
):
nlp = spacy.load('en_core_web_sm')
custom_nlp = spacy.load(os.path.dirname(os.path.abspath(__file__)))
self.__skills_file = skills_file
self.__custom_regex = custom_regex
self.__matcher = Matcher(nlp.vocab)
self.__details = {
'name': None,
'email': None,
'mobile_number': None,
'skills': None,
'college_name': None,
'degree': None,
'designation': None,
'experience': None,
'company_names': None,
'no_of_pages': None,
'total_experience': None,
}
self.__resume = resume
if not isinstance(self.__resume, io.BytesIO):
ext = os.path.splitext(self.__resume)[1].split('.')[1]
else:
ext = self.__resume.name.split('.')[1]
self.__text_raw = utils.extract_text(self.__resume, '.' + ext)
self.__text = ' '.join(self.__text_raw.split())
self.__nlp = nlp(self.__text)
self.__custom_nlp = custom_nlp(self.__text_raw)
self.__noun_chunks = list(self.__nlp.noun_chunks)
self.__get_basic_details()
|
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":",
"ext",
"=",
"os",
".",
"path",
".",
"splitext",
"(",
"self",
".",
"__resume",
")",
"[",
"1",
"]",
".",
"split",
"(",
"'.'",
")",
"[",
"1",
"]",
"else",
":",
"ext",
"=",
"self",
".",
"__resume",
".",
"name",
".",
"split",
"(",
"'.'",
")",
"[",
"1",
"]",
"self",
".",
"__text_raw",
"=",
"utils",
".",
"extract_text",
"(",
"self",
".",
"__resume",
",",
"'.'",
"+",
"ext",
")",
"self",
".",
"__text",
"=",
"' '",
".",
"join",
"(",
"self",
".",
"__text_raw",
".",
"split",
"(",
")",
")",
"self",
".",
"__nlp",
"=",
"nlp",
"(",
"self",
".",
"__text",
")",
"self",
".",
"__custom_nlp",
"=",
"custom_nlp",
"(",
"self",
".",
"__text_raw",
")",
"self",
".",
"__noun_chunks",
"=",
"list",
"(",
"self",
".",
"__nlp",
".",
"noun_chunks",
")",
"self",
".",
"__get_basic_details",
"(",
")"
] |
https://github.com/OmkarPathak/pyresparser/blob/36f1242fbc0637a6633371ca81cf1aea4fa7497e/pyresparser/resume_parser.py#L14-L48
|
||||
Jenyay/outwiker
|
50530cf7b3f71480bb075b2829bc0669773b835b
|
plugins/markdown/markdown/markdown_plugin_libs/pygments/formatters/img.py
|
python
|
FontManager.get_char_size
|
(self)
|
return self.fonts['NORMAL'].getsize('M')
|
Get the character size.
|
Get the character size.
|
[
"Get",
"the",
"character",
"size",
"."
] |
def get_char_size(self):
"""
Get the character size.
"""
return self.fonts['NORMAL'].getsize('M')
|
[
"def",
"get_char_size",
"(",
"self",
")",
":",
"return",
"self",
".",
"fonts",
"[",
"'NORMAL'",
"]",
".",
"getsize",
"(",
"'M'",
")"
] |
https://github.com/Jenyay/outwiker/blob/50530cf7b3f71480bb075b2829bc0669773b835b/plugins/markdown/markdown/markdown_plugin_libs/pygments/formatters/img.py#L205-L209
|
|
trakt/Plex-Trakt-Scrobbler
|
aeb0bfbe62fad4b06c164f1b95581da7f35dce0b
|
Trakttv.bundle/Contents/Libraries/Shared/sortedcontainers/sortedlist.py
|
python
|
recursive_repr
|
(func)
|
return wrapper
|
Decorator to prevent infinite repr recursion.
|
Decorator to prevent infinite repr recursion.
|
[
"Decorator",
"to",
"prevent",
"infinite",
"repr",
"recursion",
"."
] |
def recursive_repr(func):
"""Decorator to prevent infinite repr recursion."""
repr_running = set()
@wraps(func)
def wrapper(self):
"Return ellipsis on recursive re-entry to function."
key = id(self), get_ident()
if key in repr_running:
return '...'
repr_running.add(key)
try:
return func(self)
finally:
repr_running.discard(key)
return wrapper
|
[
"def",
"recursive_repr",
"(",
"func",
")",
":",
"repr_running",
"=",
"set",
"(",
")",
"@",
"wraps",
"(",
"func",
")",
"def",
"wrapper",
"(",
"self",
")",
":",
"\"Return ellipsis on recursive re-entry to function.\"",
"key",
"=",
"id",
"(",
"self",
")",
",",
"get_ident",
"(",
")",
"if",
"key",
"in",
"repr_running",
":",
"return",
"'...'",
"repr_running",
".",
"add",
"(",
"key",
")",
"try",
":",
"return",
"func",
"(",
"self",
")",
"finally",
":",
"repr_running",
".",
"discard",
"(",
"key",
")",
"return",
"wrapper"
] |
https://github.com/trakt/Plex-Trakt-Scrobbler/blob/aeb0bfbe62fad4b06c164f1b95581da7f35dce0b/Trakttv.bundle/Contents/Libraries/Shared/sortedcontainers/sortedlist.py#L31-L50
|
|
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_flaskbb/lib/python2.7/site-packages/babel/support.py
|
python
|
LazyProxy.__rmod__
|
(self, other)
|
return other % self.value
|
[] |
def __rmod__(self, other):
return other % self.value
|
[
"def",
"__rmod__",
"(",
"self",
",",
"other",
")",
":",
"return",
"other",
"%",
"self",
".",
"value"
] |
https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/babel/support.py#L218-L219
|
|||
dpressel/mead-baseline
|
9987e6b37fa6525a4ddc187c305e292a718f59a9
|
layers/eight_mile/conlleval.py
|
python
|
main
|
()
|
Use as a cli tool like conlleval.pl
|
Use as a cli tool like conlleval.pl
|
[
"Use",
"as",
"a",
"cli",
"tool",
"like",
"conlleval",
".",
"pl"
] |
def main():
"""Use as a cli tool like conlleval.pl"""
usage = "usage: %(prog)s [--span_type {bio,iobes,iob}] [-d delimiterTag] [-v] < file"
parser = argparse.ArgumentParser(
description="Calculate Span level F1 from the CoNLL-2000 shared task.", usage=usage
)
parser.add_argument(
"--span_type",
default="iobes",
choices={"iobes", "iob", "bio"},
help="What tag annotation scheme is this file using.",
)
parser.add_argument("--delimiterTag", "-d", help="The separator between items in the file.")
parser.add_argument(
"--verbose", "-v", action="store_true", help="Output warnings when there is an illegal transition."
)
args = parser.parse_args()
golds, preds = _read_conll_file(sys.stdin, args.delimiterTag)
acc, tokens = _get_accuracy(golds, preds)
golds, preds = _get_entities(golds, preds, args.span_type, args.verbose)
metrics = per_entity_f1(golds, preds)
metrics["acc"] = acc
metrics["tokens"] = tokens
print(conlleval_output(metrics))
|
[
"def",
"main",
"(",
")",
":",
"usage",
"=",
"\"usage: %(prog)s [--span_type {bio,iobes,iob}] [-d delimiterTag] [-v] < file\"",
"parser",
"=",
"argparse",
".",
"ArgumentParser",
"(",
"description",
"=",
"\"Calculate Span level F1 from the CoNLL-2000 shared task.\"",
",",
"usage",
"=",
"usage",
")",
"parser",
".",
"add_argument",
"(",
"\"--span_type\"",
",",
"default",
"=",
"\"iobes\"",
",",
"choices",
"=",
"{",
"\"iobes\"",
",",
"\"iob\"",
",",
"\"bio\"",
"}",
",",
"help",
"=",
"\"What tag annotation scheme is this file using.\"",
",",
")",
"parser",
".",
"add_argument",
"(",
"\"--delimiterTag\"",
",",
"\"-d\"",
",",
"help",
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"\"The separator between items in the file.\"",
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"parser",
".",
"add_argument",
"(",
"\"--verbose\"",
",",
"\"-v\"",
",",
"action",
"=",
"\"store_true\"",
",",
"help",
"=",
"\"Output warnings when there is an illegal transition.\"",
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"args",
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"parser",
".",
"parse_args",
"(",
")",
"golds",
",",
"preds",
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"_read_conll_file",
"(",
"sys",
".",
"stdin",
",",
"args",
".",
"delimiterTag",
")",
"acc",
",",
"tokens",
"=",
"_get_accuracy",
"(",
"golds",
",",
"preds",
")",
"golds",
",",
"preds",
"=",
"_get_entities",
"(",
"golds",
",",
"preds",
",",
"args",
".",
"span_type",
",",
"args",
".",
"verbose",
")",
"metrics",
"=",
"per_entity_f1",
"(",
"golds",
",",
"preds",
")",
"metrics",
"[",
"\"acc\"",
"]",
"=",
"acc",
"metrics",
"[",
"\"tokens\"",
"]",
"=",
"tokens",
"print",
"(",
"conlleval_output",
"(",
"metrics",
")",
")"
] |
https://github.com/dpressel/mead-baseline/blob/9987e6b37fa6525a4ddc187c305e292a718f59a9/layers/eight_mile/conlleval.py#L87-L111
|
||
raveberry/raveberry
|
df0186c94b238b57de86d3fd5c595dcd08a7c708
|
backend/core/musiq/spotify_web.py
|
python
|
OAuthClient.__init__
|
(
self,
base_url,
refresh_url,
client_id=None,
client_secret=None,
proxy_config=None,
expiry_margin=60,
timeout=10,
retries=3,
retry_statuses=(500, 502, 503, 429),
)
|
[] |
def __init__(
self,
base_url,
refresh_url,
client_id=None,
client_secret=None,
proxy_config=None,
expiry_margin=60,
timeout=10,
retries=3,
retry_statuses=(500, 502, 503, 429),
):
if client_id and client_secret:
self._auth = (client_id, client_secret)
else:
self._auth = None
self._base_url = base_url
self._refresh_url = refresh_url
self._margin = expiry_margin
self._expires = 0
self._authorization_failed = False
self._timeout = timeout
self._number_of_retries = retries
self._retry_statuses = retry_statuses
self._backoff_factor = 0.5
self._headers = {"Content-Type": "application/json"}
self._session = get_requests_session(proxy_config or {})
|
[
"def",
"__init__",
"(",
"self",
",",
"base_url",
",",
"refresh_url",
",",
"client_id",
"=",
"None",
",",
"client_secret",
"=",
"None",
",",
"proxy_config",
"=",
"None",
",",
"expiry_margin",
"=",
"60",
",",
"timeout",
"=",
"10",
",",
"retries",
"=",
"3",
",",
"retry_statuses",
"=",
"(",
"500",
",",
"502",
",",
"503",
",",
"429",
")",
",",
")",
":",
"if",
"client_id",
"and",
"client_secret",
":",
"self",
".",
"_auth",
"=",
"(",
"client_id",
",",
"client_secret",
")",
"else",
":",
"self",
".",
"_auth",
"=",
"None",
"self",
".",
"_base_url",
"=",
"base_url",
"self",
".",
"_refresh_url",
"=",
"refresh_url",
"self",
".",
"_margin",
"=",
"expiry_margin",
"self",
".",
"_expires",
"=",
"0",
"self",
".",
"_authorization_failed",
"=",
"False",
"self",
".",
"_timeout",
"=",
"timeout",
"self",
".",
"_number_of_retries",
"=",
"retries",
"self",
".",
"_retry_statuses",
"=",
"retry_statuses",
"self",
".",
"_backoff_factor",
"=",
"0.5",
"self",
".",
"_headers",
"=",
"{",
"\"Content-Type\"",
":",
"\"application/json\"",
"}",
"self",
".",
"_session",
"=",
"get_requests_session",
"(",
"proxy_config",
"or",
"{",
"}",
")"
] |
https://github.com/raveberry/raveberry/blob/df0186c94b238b57de86d3fd5c595dcd08a7c708/backend/core/musiq/spotify_web.py#L52-L83
|
||||
beetbox/beets
|
2fea53c34dd505ba391cb345424e0613901c8025
|
beets/importer.py
|
python
|
ArchiveImportTask.extract
|
(self)
|
Extracts the archive to a temporary directory and sets
`toppath` to that directory.
|
Extracts the archive to a temporary directory and sets
`toppath` to that directory.
|
[
"Extracts",
"the",
"archive",
"to",
"a",
"temporary",
"directory",
"and",
"sets",
"toppath",
"to",
"that",
"directory",
"."
] |
def extract(self):
"""Extracts the archive to a temporary directory and sets
`toppath` to that directory.
"""
for path_test, handler_class in self.handlers():
if path_test(util.py3_path(self.toppath)):
break
extract_to = mkdtemp()
archive = handler_class(util.py3_path(self.toppath), mode='r')
try:
archive.extractall(extract_to)
finally:
archive.close()
self.extracted = True
self.toppath = extract_to
|
[
"def",
"extract",
"(",
"self",
")",
":",
"for",
"path_test",
",",
"handler_class",
"in",
"self",
".",
"handlers",
"(",
")",
":",
"if",
"path_test",
"(",
"util",
".",
"py3_path",
"(",
"self",
".",
"toppath",
")",
")",
":",
"break",
"extract_to",
"=",
"mkdtemp",
"(",
")",
"archive",
"=",
"handler_class",
"(",
"util",
".",
"py3_path",
"(",
"self",
".",
"toppath",
")",
",",
"mode",
"=",
"'r'",
")",
"try",
":",
"archive",
".",
"extractall",
"(",
"extract_to",
")",
"finally",
":",
"archive",
".",
"close",
"(",
")",
"self",
".",
"extracted",
"=",
"True",
"self",
".",
"toppath",
"=",
"extract_to"
] |
https://github.com/beetbox/beets/blob/2fea53c34dd505ba391cb345424e0613901c8025/beets/importer.py#L1081-L1096
|
||
kivy/plyer
|
7a71707bdf99979cdacf2240d823aefa13d18f00
|
plyer/platforms/linux/cpu.py
|
python
|
instance
|
()
|
return CPU()
|
Instance for facade proxy.
|
Instance for facade proxy.
|
[
"Instance",
"for",
"facade",
"proxy",
"."
] |
def instance():
'''
Instance for facade proxy.
'''
import sys
if whereis_exe('nproc'):
return LinuxCPU()
sys.stderr.write("nproc not found.")
return CPU()
|
[
"def",
"instance",
"(",
")",
":",
"import",
"sys",
"if",
"whereis_exe",
"(",
"'nproc'",
")",
":",
"return",
"LinuxCPU",
"(",
")",
"sys",
".",
"stderr",
".",
"write",
"(",
"\"nproc not found.\"",
")",
"return",
"CPU",
"(",
")"
] |
https://github.com/kivy/plyer/blob/7a71707bdf99979cdacf2240d823aefa13d18f00/plyer/platforms/linux/cpu.py#L108-L116
|
|
sloria/textblob-aptagger
|
fb98bbd16a83650cab4819c4b89f0973e60fb3fe
|
textblob_aptagger/_perceptron.py
|
python
|
AveragedPerceptron.load
|
(self, path)
|
return None
|
Load the pickled model weights.
|
Load the pickled model weights.
|
[
"Load",
"the",
"pickled",
"model",
"weights",
"."
] |
def load(self, path):
'''Load the pickled model weights.'''
self.weights = pickle.load(open(path))
return None
|
[
"def",
"load",
"(",
"self",
",",
"path",
")",
":",
"self",
".",
"weights",
"=",
"pickle",
".",
"load",
"(",
"open",
"(",
"path",
")",
")",
"return",
"None"
] |
https://github.com/sloria/textblob-aptagger/blob/fb98bbd16a83650cab4819c4b89f0973e60fb3fe/textblob_aptagger/_perceptron.py#L79-L82
|
|
holzschu/Carnets
|
44effb10ddfc6aa5c8b0687582a724ba82c6b547
|
Library/lib/python3.7/site-packages/pandas-0.24.2-py3.7-macosx-10.9-x86_64.egg/pandas/io/pytables.py
|
python
|
HDFStore.remove
|
(self, key, where=None, start=None, stop=None)
|
Remove pandas object partially by specifying the where condition
Parameters
----------
key : string
Node to remove or delete rows from
where : list of Term (or convertible) objects, optional
start : integer (defaults to None), row number to start selection
stop : integer (defaults to None), row number to stop selection
Returns
-------
number of rows removed (or None if not a Table)
Exceptions
----------
raises KeyError if key is not a valid store
|
Remove pandas object partially by specifying the where condition
|
[
"Remove",
"pandas",
"object",
"partially",
"by",
"specifying",
"the",
"where",
"condition"
] |
def remove(self, key, where=None, start=None, stop=None):
"""
Remove pandas object partially by specifying the where condition
Parameters
----------
key : string
Node to remove or delete rows from
where : list of Term (or convertible) objects, optional
start : integer (defaults to None), row number to start selection
stop : integer (defaults to None), row number to stop selection
Returns
-------
number of rows removed (or None if not a Table)
Exceptions
----------
raises KeyError if key is not a valid store
"""
where = _ensure_term(where, scope_level=1)
try:
s = self.get_storer(key)
except KeyError:
# the key is not a valid store, re-raising KeyError
raise
except Exception:
if where is not None:
raise ValueError(
"trying to remove a node with a non-None where clause!")
# we are actually trying to remove a node (with children)
s = self.get_node(key)
if s is not None:
s._f_remove(recursive=True)
return None
# remove the node
if com._all_none(where, start, stop):
s.group._f_remove(recursive=True)
# delete from the table
else:
if not s.is_table:
raise ValueError(
'can only remove with where on objects written as tables')
return s.delete(where=where, start=start, stop=stop)
|
[
"def",
"remove",
"(",
"self",
",",
"key",
",",
"where",
"=",
"None",
",",
"start",
"=",
"None",
",",
"stop",
"=",
"None",
")",
":",
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"=",
"_ensure_term",
"(",
"where",
",",
"scope_level",
"=",
"1",
")",
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":",
"s",
"=",
"self",
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"(",
"key",
")",
"except",
"KeyError",
":",
"# the key is not a valid store, re-raising KeyError",
"raise",
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":",
"if",
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"(",
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"=",
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")",
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"(",
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",",
"start",
",",
"stop",
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":",
"s",
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")",
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":",
"if",
"not",
"s",
".",
"is_table",
":",
"raise",
"ValueError",
"(",
"'can only remove with where on objects written as tables'",
")",
"return",
"s",
".",
"delete",
"(",
"where",
"=",
"where",
",",
"start",
"=",
"start",
",",
"stop",
"=",
"stop",
")"
] |
https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/pandas-0.24.2-py3.7-macosx-10.9-x86_64.egg/pandas/io/pytables.py#L891-L939
|
||
dmlc/gluon-cv
|
709bc139919c02f7454cb411311048be188cde64
|
scripts/datasets/ilsvrc_det.py
|
python
|
par_crop
|
(args)
|
Dataset curation,crop data and transform the format of a label
|
Dataset curation,crop data and transform the format of a label
|
[
"Dataset",
"curation",
"crop",
"data",
"and",
"transform",
"the",
"format",
"of",
"a",
"label"
] |
def par_crop(args):
"""
Dataset curation,crop data and transform the format of a label
"""
crop_path = os.path.join(args.download_dir, './crop{:d}'.format(args.instance_size))
if not os.path.isdir(crop_path): makedirs(crop_path)
VID_base_path = os.path.join(args.download_dir, './ILSVRC')
ann_base_path = os.path.join(VID_base_path, 'Annotations/DET/train/')
sub_sets = ('a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i')
for sub_set in sub_sets:
sub_set_base_path = os.path.join(ann_base_path, sub_set)
if 'a' == sub_set:
xmls = sorted(glob.glob(os.path.join(sub_set_base_path, '*', '*.xml')))
else:
xmls = sorted(glob.glob(os.path.join(sub_set_base_path, '*.xml')))
n_imgs = len(xmls)
sub_set_crop_path = os.path.join(crop_path, sub_set)
with futures.ProcessPoolExecutor(max_workers=args.num_threads) as executor:
fs = [executor.submit(crop_xml, args, xml, sub_set_crop_path, args.instance_size) for xml in xmls]
for i, f in enumerate(futures.as_completed(fs)):
printProgress(i, n_imgs, prefix=sub_set, suffix='Done ', barLength=80)
|
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https://github.com/dmlc/gluon-cv/blob/709bc139919c02f7454cb411311048be188cde64/scripts/datasets/ilsvrc_det.py#L77-L97
|
||
mrJean1/PyGeodesy
|
7da5ca71aa3edb7bc49e219e0b8190686e1a7965
|
pygeodesy/sphericalNvector.py
|
python
|
perimeterOf
|
(points, closed=False, radius=R_M)
|
return r if radius is None else (Radius(radius) * r)
|
Compute the perimeter of a (spherical) polygon (with great circle
arcs joining consecutive points).
@arg points: The polygon points (L{LatLon}[]).
@kwarg closed: Optionally, close the polygon (C{bool}).
@kwarg radius: Mean earth radius (C{meter}) or C{None}.
@return: Polygon perimeter (C{meter}, same units as B{C{radius}}
or C{radians} if B{C{radius}} is C{None}).
@raise PointsError: Insufficient number of B{C{points}}.
@raise TypeError: Some B{C{points}} are not L{LatLon}.
@see: Functions L{pygeodesy.perimeterOf}, L{sphericalTrigonometry.perimeterOf}
and L{ellipsoidalKarney.perimeterOf}.
|
Compute the perimeter of a (spherical) polygon (with great circle
arcs joining consecutive points).
|
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] |
def perimeterOf(points, closed=False, radius=R_M):
'''Compute the perimeter of a (spherical) polygon (with great circle
arcs joining consecutive points).
@arg points: The polygon points (L{LatLon}[]).
@kwarg closed: Optionally, close the polygon (C{bool}).
@kwarg radius: Mean earth radius (C{meter}) or C{None}.
@return: Polygon perimeter (C{meter}, same units as B{C{radius}}
or C{radians} if B{C{radius}} is C{None}).
@raise PointsError: Insufficient number of B{C{points}}.
@raise TypeError: Some B{C{points}} are not L{LatLon}.
@see: Functions L{pygeodesy.perimeterOf}, L{sphericalTrigonometry.perimeterOf}
and L{ellipsoidalKarney.perimeterOf}.
'''
def _rads(Ps, closed): # angular edge lengths in radians
v1 = Ps[0]._N_vector
for p in Ps.iterate(closed=closed):
v2 = p._N_vector
yield v1.angleTo(v2)
v1 = v2
r = fsum(_rads(_Nvll.PointsIter(points, loop=1), closed))
return r if radius is None else (Radius(radius) * r)
|
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https://github.com/mrJean1/PyGeodesy/blob/7da5ca71aa3edb7bc49e219e0b8190686e1a7965/pygeodesy/sphericalNvector.py#L1024-L1050
|
|
lovelylain/pyctp
|
fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d
|
example/ctp/futures/ApiStruct.py
|
python
|
QryCFMMCTradingAccountKey.__init__
|
(self, BrokerID='', InvestorID='')
|
[] |
def __init__(self, BrokerID='', InvestorID=''):
self.BrokerID = '' #经纪公司代码, char[11]
self.InvestorID = ''
|
[
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https://github.com/lovelylain/pyctp/blob/fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d/example/ctp/futures/ApiStruct.py#L4712-L4714
|
||||
fabioz/PyDev.Debugger
|
0f8c02a010fe5690405da1dd30ed72326191ce63
|
third_party/pep8/autopep8.py
|
python
|
_get_indentword
|
(source)
|
return indent_word
|
Return indentation type.
|
Return indentation type.
|
[
"Return",
"indentation",
"type",
"."
] |
def _get_indentword(source):
"""Return indentation type."""
indent_word = ' ' # Default in case source has no indentation
try:
for t in generate_tokens(source):
if t[0] == token.INDENT:
indent_word = t[1]
break
except (SyntaxError, tokenize.TokenError):
pass
return indent_word
|
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https://github.com/fabioz/PyDev.Debugger/blob/0f8c02a010fe5690405da1dd30ed72326191ce63/third_party/pep8/autopep8.py#L1417-L1427
|
|
openfisca/openfisca-france
|
207a58191be6830716693f94d37846f1e5037b51
|
openfisca_france/model/prelevements_obligatoires/isf.py
|
python
|
isf_inv_pme.formula_2008
|
(foyer_fiscal, period, parameters)
|
return holdings + fip + fcpi + inv_dir_soc
|
Réductions pour investissements dans les PME
à partir de 2008!
|
Réductions pour investissements dans les PME
à partir de 2008!
|
[
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] |
def formula_2008(foyer_fiscal, period, parameters):
'''
Réductions pour investissements dans les PME
à partir de 2008!
'''
b2mt = foyer_fiscal('b2mt', period)
b2ne = foyer_fiscal('b2ne', period)
b2mv = foyer_fiscal('b2mv', period)
b2nf = foyer_fiscal('b2nf', period)
b2mx = foyer_fiscal('b2mx', period)
b2na = foyer_fiscal('b2na', period)
P = parameters(period).taxation_capital.isf_ifi.reduc_invest_don
inv_dir_soc = b2mt * P.taux_don_interet_general + b2ne * P.taux_invest_direct_soc_holding
holdings = b2mv * P.taux_don_interet_general + b2nf * P.taux_invest_direct_soc_holding
fip = b2mx * P.taux_invest_direct_soc_holding
fcpi = b2na * P.taux_invest_direct_soc_holding
return holdings + fip + fcpi + inv_dir_soc
|
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https://github.com/openfisca/openfisca-france/blob/207a58191be6830716693f94d37846f1e5037b51/openfisca_france/model/prelevements_obligatoires/isf.py#L395-L413
|
|
davidemms/OrthoFinder
|
d92c016ccb17be39787614018694844a2c673173
|
scripts_of/tree.py
|
python
|
TreeNode.is_leaf
|
(self)
|
return len(self.children) == 0
|
Return True if current node is a leaf.
|
Return True if current node is a leaf.
|
[
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def is_leaf(self):
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return len(self.children) == 0
|
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https://github.com/davidemms/OrthoFinder/blob/d92c016ccb17be39787614018694844a2c673173/scripts_of/tree.py#L944-L948
|
|
Tautulli/Tautulli
|
2410eb33805aaac4bd1c5dad0f71e4f15afaf742
|
lib/idna/uts46data.py
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python
|
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] |
https://github.com/Tautulli/Tautulli/blob/2410eb33805aaac4bd1c5dad0f71e4f15afaf742/lib/idna/uts46data.py#L6563-L6665
|
|||
MrH0wl/Cloudmare
|
65e5bc9888f9d362ab2abfb103ea6c1e869d67aa
|
thirdparty/bs4/dammit.py
|
python
|
UnicodeDammit._to_unicode
|
(self, data, encoding, errors="strict")
|
return str(data, encoding, errors)
|
Given a string and its encoding, decodes the string into Unicode.
:param encoding: The name of an encoding.
|
Given a string and its encoding, decodes the string into Unicode.
|
[
"Given",
"a",
"string",
"and",
"its",
"encoding",
"decodes",
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"string",
"into",
"Unicode",
"."
] |
def _to_unicode(self, data, encoding, errors="strict"):
"""Given a string and its encoding, decodes the string into Unicode.
:param encoding: The name of an encoding.
"""
return str(data, encoding, errors)
|
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"_to_unicode",
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"data",
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https://github.com/MrH0wl/Cloudmare/blob/65e5bc9888f9d362ab2abfb103ea6c1e869d67aa/thirdparty/bs4/dammit.py#L521-L526
|
|
PaddlePaddle/Parakeet
|
8705a2a8405e3c63f2174d69880d2b5525a6c9fd
|
parakeet/modules/conv.py
|
python
|
Conv1dCell.start_sequence
|
(self)
|
Prepare the layer for a series of incremental forward.
Warnings
---------
This method should be called before a sequence of calls to
``add_input``.
Raises
------
Exception
If this method is called when the layer is in training mode.
|
Prepare the layer for a series of incremental forward.
Warnings
---------
This method should be called before a sequence of calls to
``add_input``.
|
[
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"the",
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] |
def start_sequence(self):
"""Prepare the layer for a series of incremental forward.
Warnings
---------
This method should be called before a sequence of calls to
``add_input``.
Raises
------
Exception
If this method is called when the layer is in training mode.
"""
if self.training:
raise Exception("only use start_sequence in evaluation")
self._buffer = None
# NOTE: call self's weight norm hook expliccitly since self.weight
# is visited directly in this method without calling self.__call__
# method. If we do not trigger the weight norm hook, the weight
# may be outdated. e.g. after loading from a saved checkpoint
# see also: https://github.com/pytorch/pytorch/issues/47588
for hook in self._forward_pre_hooks.values():
hook(self, None)
self._reshaped_weight = paddle.reshape(self.weight,
(self._out_channels, -1))
|
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https://github.com/PaddlePaddle/Parakeet/blob/8705a2a8405e3c63f2174d69880d2b5525a6c9fd/parakeet/modules/conv.py#L103-L128
|
||
PyTorchLightning/pytorch-lightning
|
5914fb748fb53d826ab337fc2484feab9883a104
|
pytorch_lightning/plugins/environments/lsf_environment.py
|
python
|
LSFEnvironment._read_hosts
|
()
|
return ret[1:]
|
Read compute hosts that are a part of the compute job.
LSF uses the Job Step Manager (JSM) to manage job steps. Job steps are executed by the JSM from "launch" nodes.
Each job is assigned a launch node. This launch node will be the first node in the list contained in
``LSB_DJOB_RANKFILE``.
|
Read compute hosts that are a part of the compute job.
|
[
"Read",
"compute",
"hosts",
"that",
"are",
"a",
"part",
"of",
"the",
"compute",
"job",
"."
] |
def _read_hosts() -> List[str]:
"""Read compute hosts that are a part of the compute job.
LSF uses the Job Step Manager (JSM) to manage job steps. Job steps are executed by the JSM from "launch" nodes.
Each job is assigned a launch node. This launch node will be the first node in the list contained in
``LSB_DJOB_RANKFILE``.
"""
var = "LSB_DJOB_RANKFILE"
rankfile = os.environ.get(var)
if rankfile is None:
raise ValueError("Did not find the environment variable `LSB_DJOB_RANKFILE`")
if not rankfile:
raise ValueError("The environment variable `LSB_DJOB_RANKFILE` is empty")
fs = get_filesystem(rankfile)
with fs.open(rankfile, "r") as f:
ret = [line.strip() for line in f]
# remove the launch node (i.e. the first node in LSB_DJOB_RANKFILE) from the list
return ret[1:]
|
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] |
https://github.com/PyTorchLightning/pytorch-lightning/blob/5914fb748fb53d826ab337fc2484feab9883a104/pytorch_lightning/plugins/environments/lsf_environment.py#L146-L164
|
|
gammapy/gammapy
|
735b25cd5bbed35e2004d633621896dcd5295e8b
|
gammapy/datasets/map.py
|
python
|
MapDataset.to_hdulist
|
(self)
|
return hdulist
|
Convert map dataset to list of HDUs.
Returns
-------
hdulist : `~astropy.io.fits.HDUList`
Map dataset list of HDUs.
|
Convert map dataset to list of HDUs.
|
[
"Convert",
"map",
"dataset",
"to",
"list",
"of",
"HDUs",
"."
] |
def to_hdulist(self):
"""Convert map dataset to list of HDUs.
Returns
-------
hdulist : `~astropy.io.fits.HDUList`
Map dataset list of HDUs.
"""
# TODO: what todo about the model and background model parameters?
exclude_primary = slice(1, None)
hdu_primary = fits.PrimaryHDU()
hdulist = fits.HDUList([hdu_primary])
if self.counts is not None:
hdulist += self.counts.to_hdulist(hdu="counts")[exclude_primary]
if self.exposure is not None:
hdulist += self.exposure.to_hdulist(hdu="exposure")[exclude_primary]
if self.background is not None:
hdulist += self.background.to_hdulist(hdu="background")[exclude_primary]
if self.edisp is not None:
hdulist += self.edisp.to_hdulist()[exclude_primary]
if self.psf is not None:
hdulist += self.psf.to_hdulist()[exclude_primary]
if self.mask_safe is not None:
hdulist += self.mask_safe.to_hdulist(hdu="mask_safe")[exclude_primary]
if self.mask_fit is not None:
hdulist += self.mask_fit.to_hdulist(hdu="mask_fit")[exclude_primary]
if self.gti is not None:
hdulist.append(fits.BinTableHDU(self.gti.table, name="GTI"))
return hdulist
|
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"table",
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"\"GTI\"",
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")",
"return",
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] |
https://github.com/gammapy/gammapy/blob/735b25cd5bbed35e2004d633621896dcd5295e8b/gammapy/datasets/map.py#L999-L1036
|
|
matplotlib/matplotlib
|
8d7a2b9d2a38f01ee0d6802dd4f9e98aec812322
|
lib/matplotlib/backend_bases.py
|
python
|
GraphicsContextBase.set_foreground
|
(self, fg, isRGBA=False)
|
Set the foreground color.
Parameters
----------
fg : color
isRGBA : bool
If *fg* is known to be an ``(r, g, b, a)`` tuple, *isRGBA* can be
set to True to improve performance.
|
Set the foreground color.
|
[
"Set",
"the",
"foreground",
"color",
"."
] |
def set_foreground(self, fg, isRGBA=False):
"""
Set the foreground color.
Parameters
----------
fg : color
isRGBA : bool
If *fg* is known to be an ``(r, g, b, a)`` tuple, *isRGBA* can be
set to True to improve performance.
"""
if self._forced_alpha and isRGBA:
self._rgb = fg[:3] + (self._alpha,)
elif self._forced_alpha:
self._rgb = colors.to_rgba(fg, self._alpha)
elif isRGBA:
self._rgb = fg
else:
self._rgb = colors.to_rgba(fg)
|
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https://github.com/matplotlib/matplotlib/blob/8d7a2b9d2a38f01ee0d6802dd4f9e98aec812322/lib/matplotlib/backend_bases.py#L930-L948
|
||
hzdg/django-enumfields
|
bda0a461657a87601d235d78176add73a8875832
|
enumfields/enums.py
|
python
|
Enum.choices
|
(cls)
|
return tuple((m.value, m.label) for m in cls)
|
Returns a list formatted for use as field choices.
(See https://docs.djangoproject.com/en/dev/ref/models/fields/#choices)
|
Returns a list formatted for use as field choices.
(See https://docs.djangoproject.com/en/dev/ref/models/fields/#choices)
|
[
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"/",
"ref",
"/",
"models",
"/",
"fields",
"/",
"#choices",
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] |
def choices(cls):
"""
Returns a list formatted for use as field choices.
(See https://docs.djangoproject.com/en/dev/ref/models/fields/#choices)
"""
return tuple((m.value, m.label) for m in cls)
|
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https://github.com/hzdg/django-enumfields/blob/bda0a461657a87601d235d78176add73a8875832/enumfields/enums.py#L34-L39
|
|
kubernetes-client/python
|
47b9da9de2d02b2b7a34fbe05afb44afd130d73a
|
kubernetes/client/models/v1_custom_resource_definition_names.py
|
python
|
V1CustomResourceDefinitionNames.kind
|
(self)
|
return self._kind
|
Gets the kind of this V1CustomResourceDefinitionNames. # noqa: E501
kind is the serialized kind of the resource. It is normally CamelCase and singular. Custom resource instances will use this value as the `kind` attribute in API calls. # noqa: E501
:return: The kind of this V1CustomResourceDefinitionNames. # noqa: E501
:rtype: str
|
Gets the kind of this V1CustomResourceDefinitionNames. # noqa: E501
|
[
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"V1CustomResourceDefinitionNames",
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def kind(self):
"""Gets the kind of this V1CustomResourceDefinitionNames. # noqa: E501
kind is the serialized kind of the resource. It is normally CamelCase and singular. Custom resource instances will use this value as the `kind` attribute in API calls. # noqa: E501
:return: The kind of this V1CustomResourceDefinitionNames. # noqa: E501
:rtype: str
"""
return self._kind
|
[
"def",
"kind",
"(",
"self",
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"return",
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"_kind"
] |
https://github.com/kubernetes-client/python/blob/47b9da9de2d02b2b7a34fbe05afb44afd130d73a/kubernetes/client/models/v1_custom_resource_definition_names.py#L102-L110
|
|
FederatedAI/FATE
|
32540492623568ecd1afcb367360133616e02fa3
|
python/federatedml/model_selection/stepwise/hetero_stepwise.py
|
python
|
HeteroStepwise.mask2string
|
(host_mask, guest_mask)
|
return string_repr
|
[] |
def mask2string(host_mask, guest_mask):
mask = np.append(host_mask, guest_mask)
string_repr = ''.join('1' if i else '0' for i in mask)
return string_repr
|
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https://github.com/FederatedAI/FATE/blob/32540492623568ecd1afcb367360133616e02fa3/python/federatedml/model_selection/stepwise/hetero_stepwise.py#L366-L369
|
|||
loli/medpy
|
39131b94f0ab5328ab14a874229320efc2f74d98
|
medpy/features/intensity.py
|
python
|
centerdistance_xdminus1
|
(image, dim, voxelspacing = None, mask = slice(None))
|
return intensities(o, mask)
|
r"""
Implementation of `centerdistance` that allows to compute sub-volume wise
centerdistances.
The same notes as for `centerdistance` apply.
Parameters
----------
image : array_like or list/tuple of array_like
A single image or a list/tuple of images (for multi-spectral case).
dim : int or sequence of ints
The dimension or dimensions along which to cut the image into sub-volumes.
voxelspacing : sequence of floats
The side-length of each voxel.
mask : array_like
A binary mask for the image.
Returns
-------
centerdistance_xdminus1 : ndarray
The distance of each voxel to the images center in the supplied dimensions.
Raises
------
ArgumentError
If a invalid dim index of number of dim indices were supplied
Examples
--------
Considering a 3D medical image we want to compute the axial slice-wise
centerdistances instead of the ones over the complete image volume. Assuming that
the third image dimension corresponds to the axial axes of the image, we call
>>> centerdistance_xdminus1(image, 2)
Note that the centerdistance of each slice will be equal.
|
r"""
Implementation of `centerdistance` that allows to compute sub-volume wise
centerdistances.
The same notes as for `centerdistance` apply.
Parameters
----------
image : array_like or list/tuple of array_like
A single image or a list/tuple of images (for multi-spectral case).
dim : int or sequence of ints
The dimension or dimensions along which to cut the image into sub-volumes.
voxelspacing : sequence of floats
The side-length of each voxel.
mask : array_like
A binary mask for the image.
Returns
-------
centerdistance_xdminus1 : ndarray
The distance of each voxel to the images center in the supplied dimensions.
Raises
------
ArgumentError
If a invalid dim index of number of dim indices were supplied
|
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def centerdistance_xdminus1(image, dim, voxelspacing = None, mask = slice(None)):
r"""
Implementation of `centerdistance` that allows to compute sub-volume wise
centerdistances.
The same notes as for `centerdistance` apply.
Parameters
----------
image : array_like or list/tuple of array_like
A single image or a list/tuple of images (for multi-spectral case).
dim : int or sequence of ints
The dimension or dimensions along which to cut the image into sub-volumes.
voxelspacing : sequence of floats
The side-length of each voxel.
mask : array_like
A binary mask for the image.
Returns
-------
centerdistance_xdminus1 : ndarray
The distance of each voxel to the images center in the supplied dimensions.
Raises
------
ArgumentError
If a invalid dim index of number of dim indices were supplied
Examples
--------
Considering a 3D medical image we want to compute the axial slice-wise
centerdistances instead of the ones over the complete image volume. Assuming that
the third image dimension corresponds to the axial axes of the image, we call
>>> centerdistance_xdminus1(image, 2)
Note that the centerdistance of each slice will be equal.
"""
# pre-process arguments
if type(image) == tuple or type(image) == list:
image = image[0]
if type(dim) is int:
dims = [dim]
else:
dims = list(dim)
# check arguments
if len(dims) >= image.ndim - 1:
raise ArgumentError('Applying a sub-volume extraction of depth {} on a image of dimensionality {} would lead to invalid images of dimensionality <= 1.'.format(len(dims), image.ndim))
for dim in dims:
if dim >= image.ndim:
raise ArgumentError('Invalid dimension index {} supplied for image(s) of shape {}.'.format(dim, image.shape))
# extract desired sub-volume
slicer = [slice(None)] * image.ndim
for dim in dims: slicer[dim] = slice(1)
subvolume = numpy.squeeze(image[slicer])
# compute centerdistance for sub-volume and reshape to original sub-volume shape (note that normalization and mask are not passed on in this step)
o = centerdistance(subvolume, voxelspacing).reshape(subvolume.shape)
# re-establish original shape by copying the resulting array multiple times
for dim in sorted(dims):
o = numpy.asarray([o] * image.shape[dim])
o = numpy.rollaxis(o, 0, dim + 1)
# extract intensities / centerdistance values, applying normalization and mask in this step
return intensities(o, mask)
|
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https://github.com/loli/medpy/blob/39131b94f0ab5328ab14a874229320efc2f74d98/medpy/features/intensity.py#L98-L167
|
|
Project-MONAI/MONAI
|
83f8b06372a3803ebe9281300cb794a1f3395018
|
monai/networks/nets/efficientnet.py
|
python
|
BlockArgs.to_string
|
(self)
|
return string
|
Return a block string notation for current BlockArgs object
Returns:
A string notation of BlockArgs object arguments.
Example: "r1_k3_s11_e1_i32_o16_se0.25_noskip".
|
Return a block string notation for current BlockArgs object
|
[
"Return",
"a",
"block",
"string",
"notation",
"for",
"current",
"BlockArgs",
"object"
] |
def to_string(self):
"""
Return a block string notation for current BlockArgs object
Returns:
A string notation of BlockArgs object arguments.
Example: "r1_k3_s11_e1_i32_o16_se0.25_noskip".
"""
string = "r{}_k{}_s{}{}_e{}_i{}_o{}_se{}".format(
self.num_repeat,
self.kernel_size,
self.stride,
self.stride,
self.expand_ratio,
self.input_filters,
self.output_filters,
self.se_ratio,
)
if not self.id_skip:
string += "_noskip"
return string
|
[
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https://github.com/Project-MONAI/MONAI/blob/83f8b06372a3803ebe9281300cb794a1f3395018/monai/networks/nets/efficientnet.py#L922-L943
|
|
mapnik/Cascadenik
|
82f66859340a31dfcb24af127274f262d4f3ad85
|
cascadenik/nonposix.py
|
python
|
add_drive_by_hash
|
(drive,valid_posix_path)
|
[] |
def add_drive_by_hash(drive,valid_posix_path):
# cache the drive so we can try to recreate later
global drives
hash = md5(valid_posix_path).hexdigest()[:8]
drives[hash] = drive
|
[
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":",
"# cache the drive so we can try to recreate later",
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"[",
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] |
https://github.com/mapnik/Cascadenik/blob/82f66859340a31dfcb24af127274f262d4f3ad85/cascadenik/nonposix.py#L30-L34
|
||||
Cadene/pretrained-models.pytorch
|
8aae3d8f1135b6b13fed79c1d431e3449fdbf6e0
|
pretrainedmodels/models/torchvision_models.py
|
python
|
update_state_dict
|
(state_dict)
|
return state_dict
|
[] |
def update_state_dict(state_dict):
# '.'s are no longer allowed in module names, but pervious _DenseLayer
# has keys 'norm.1', 'relu.1', 'conv.1', 'norm.2', 'relu.2', 'conv.2'.
# They are also in the checkpoints in model_urls. This pattern is used
# to find such keys.
pattern = re.compile(
r'^(.*denselayer\d+\.(?:norm|relu|conv))\.((?:[12])\.(?:weight|bias|running_mean|running_var))$')
for key in list(state_dict.keys()):
res = pattern.match(key)
if res:
new_key = res.group(1) + res.group(2)
state_dict[new_key] = state_dict[key]
del state_dict[key]
return state_dict
|
[
"def",
"update_state_dict",
"(",
"state_dict",
")",
":",
"# '.'s are no longer allowed in module names, but pervious _DenseLayer",
"# has keys 'norm.1', 'relu.1', 'conv.1', 'norm.2', 'relu.2', 'conv.2'.",
"# They are also in the checkpoints in model_urls. This pattern is used",
"# to find such keys.",
"pattern",
"=",
"re",
".",
"compile",
"(",
"r'^(.*denselayer\\d+\\.(?:norm|relu|conv))\\.((?:[12])\\.(?:weight|bias|running_mean|running_var))$'",
")",
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"state_dict",
"[",
"key",
"]",
"del",
"state_dict",
"[",
"key",
"]",
"return",
"state_dict"
] |
https://github.com/Cadene/pretrained-models.pytorch/blob/8aae3d8f1135b6b13fed79c1d431e3449fdbf6e0/pretrainedmodels/models/torchvision_models.py#L98-L111
|
|||
airbnb/streamalert
|
26cf1d08432ca285fd4f7410511a6198ca104bbb
|
streamalert_cli/athena/handler.py
|
python
|
rebuild_partitions
|
(table, bucket, config)
|
return True
|
Rebuild an Athena table's partitions
Steps:
- Get the list of current partitions
- Destroy existing table
- Re-create tables
- Re-create partitions
Args:
table (str): The name of the table being rebuilt
bucket (str): The s3 bucket to be used as the location for Athena data
table_type (str): The type of table being refreshed
Types of 'data' and 'alert' are accepted, but only 'data' is implemented
config (CLIConfig): Loaded StreamAlert config
Returns:
bool: False if errors occurred, True otherwise
|
Rebuild an Athena table's partitions
|
[
"Rebuild",
"an",
"Athena",
"table",
"s",
"partitions"
] |
def rebuild_partitions(table, bucket, config):
"""Rebuild an Athena table's partitions
Steps:
- Get the list of current partitions
- Destroy existing table
- Re-create tables
- Re-create partitions
Args:
table (str): The name of the table being rebuilt
bucket (str): The s3 bucket to be used as the location for Athena data
table_type (str): The type of table being refreshed
Types of 'data' and 'alert' are accepted, but only 'data' is implemented
config (CLIConfig): Loaded StreamAlert config
Returns:
bool: False if errors occurred, True otherwise
"""
sanitized_table_name = FirehoseClient.sanitized_value(table)
athena_client = get_athena_client(config)
# Get the current set of partitions
partitions = athena_client.get_table_partitions(sanitized_table_name)
if not partitions:
LOGGER.info('No partitions to rebuild for %s, nothing to do', sanitized_table_name)
return False
# Drop the table
LOGGER.info('Dropping table %s', sanitized_table_name)
if not athena_client.drop_table(sanitized_table_name):
return False
LOGGER.info('Creating table %s', sanitized_table_name)
# Re-create the table with previous partitions
if not create_table(table, bucket, config):
return False
new_partitions_statements = helpers.add_partition_statements(
partitions, bucket, sanitized_table_name)
LOGGER.info('Creating total %d new partitions for %s', len(partitions), sanitized_table_name)
for idx, statement in enumerate(new_partitions_statements):
success = athena_client.run_query(query=statement)
LOGGER.info('Rebuilt partitions part %d', idx+1)
if not success:
LOGGER.error('Error re-creating new partitions for %s', sanitized_table_name)
write_partitions_statements(new_partitions_statements, sanitized_table_name)
return False
LOGGER.info('Successfully rebuilt all partitions for %s', sanitized_table_name)
return True
|
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] |
https://github.com/airbnb/streamalert/blob/26cf1d08432ca285fd4f7410511a6198ca104bbb/streamalert_cli/athena/handler.py#L219-L273
|
|
plone/Products.CMFPlone
|
83137764e3e7e4fe60d03c36dfc6ba9c7c543324
|
Products/CMFPlone/interfaces/patterns.py
|
python
|
IPatternsSettings.__call__
|
(self)
|
Return a dict of pattern options
|
Return a dict of pattern options
|
[
"Return",
"a",
"dict",
"of",
"pattern",
"options"
] |
def __call__(self):
"""
Return a dict of pattern options
"""
pass
|
[
"def",
"__call__",
"(",
"self",
")",
":",
"pass"
] |
https://github.com/plone/Products.CMFPlone/blob/83137764e3e7e4fe60d03c36dfc6ba9c7c543324/Products/CMFPlone/interfaces/patterns.py#L8-L12
|
||
realpython/book2-exercises
|
cde325eac8e6d8cff2316601c2e5b36bb46af7d0
|
web2py/gluon/contrib/feedparser.py
|
python
|
_parse_date_iso8601
|
(dateString)
|
return time.localtime(time.mktime(tuple(tm)))
|
Parse a variety of ISO-8601-compatible formats like 20040105
|
Parse a variety of ISO-8601-compatible formats like 20040105
|
[
"Parse",
"a",
"variety",
"of",
"ISO",
"-",
"8601",
"-",
"compatible",
"formats",
"like",
"20040105"
] |
def _parse_date_iso8601(dateString):
'''Parse a variety of ISO-8601-compatible formats like 20040105'''
m = None
for _iso8601_match in _iso8601_matches:
m = _iso8601_match(dateString)
if m:
break
if not m:
return
if m.span() == (0, 0):
return
params = m.groupdict()
ordinal = params.get('ordinal', 0)
if ordinal:
ordinal = int(ordinal)
else:
ordinal = 0
year = params.get('year', '--')
if not year or year == '--':
year = time.gmtime()[0]
elif len(year) == 2:
# ISO 8601 assumes current century, i.e. 93 -> 2093, NOT 1993
year = 100 * int(time.gmtime()[0] / 100) + int(year)
else:
year = int(year)
month = params.get('month', '-')
if not month or month == '-':
# ordinals are NOT normalized by mktime, we simulate them
# by setting month=1, day=ordinal
if ordinal:
month = 1
else:
month = time.gmtime()[1]
month = int(month)
day = params.get('day', 0)
if not day:
# see above
if ordinal:
day = ordinal
elif params.get('century', 0) or \
params.get('year', 0) or params.get('month', 0):
day = 1
else:
day = time.gmtime()[2]
else:
day = int(day)
# special case of the century - is the first year of the 21st century
# 2000 or 2001 ? The debate goes on...
if 'century' in params:
year = (int(params['century']) - 1) * 100 + 1
# in ISO 8601 most fields are optional
for field in ['hour', 'minute', 'second', 'tzhour', 'tzmin']:
if not params.get(field, None):
params[field] = 0
hour = int(params.get('hour', 0))
minute = int(params.get('minute', 0))
second = int(float(params.get('second', 0)))
# weekday is normalized by mktime(), we can ignore it
weekday = 0
daylight_savings_flag = -1
tm = [year, month, day, hour, minute, second, weekday,
ordinal, daylight_savings_flag]
# ISO 8601 time zone adjustments
tz = params.get('tz')
if tz and tz != 'Z':
if tz[0] == '-':
tm[3] += int(params.get('tzhour', 0))
tm[4] += int(params.get('tzmin', 0))
elif tz[0] == '+':
tm[3] -= int(params.get('tzhour', 0))
tm[4] -= int(params.get('tzmin', 0))
else:
return None
# Python's time.mktime() is a wrapper around the ANSI C mktime(3c)
# which is guaranteed to normalize d/m/y/h/m/s.
# Many implementations have bugs, but we'll pretend they don't.
return time.localtime(time.mktime(tuple(tm)))
|
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https://github.com/realpython/book2-exercises/blob/cde325eac8e6d8cff2316601c2e5b36bb46af7d0/web2py/gluon/contrib/feedparser.py#L3004-L3080
|
|
spectacles/CodeComplice
|
8ca8ee4236f72b58caa4209d2fbd5fa56bd31d62
|
libs/elementtree/ElementTree.py
|
python
|
SubElement
|
(parent, tag, attrib={}, **extra)
|
return element
|
[] |
def SubElement(parent, tag, attrib={}, **extra):
attrib = attrib.copy()
attrib.update(extra)
element = parent.makeelement(tag, attrib)
parent.append(element)
return element
|
[
"def",
"SubElement",
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"(",
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https://github.com/spectacles/CodeComplice/blob/8ca8ee4236f72b58caa4209d2fbd5fa56bd31d62/libs/elementtree/ElementTree.py#L471-L476
|
|||
andresriancho/w3af
|
cd22e5252243a87aaa6d0ddea47cf58dacfe00a9
|
w3af/core/ui/gui/history.py
|
python
|
HistorySuggestion.get_texts
|
(self)
|
return [k for k, v in info]
|
Provides the texts, ordered by relevance.
:return: a generator with the texts
|
Provides the texts, ordered by relevance.
|
[
"Provides",
"the",
"texts",
"ordered",
"by",
"relevance",
"."
] |
def get_texts(self):
"""Provides the texts, ordered by relevance.
:return: a generator with the texts
"""
info = sorted(
self.history.items(), key=operator.itemgetter(1), reverse=True)
return [k for k, v in info]
|
[
"def",
"get_texts",
"(",
"self",
")",
":",
"info",
"=",
"sorted",
"(",
"self",
".",
"history",
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",",
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")",
"return",
"[",
"k",
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"k",
",",
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"in",
"info",
"]"
] |
https://github.com/andresriancho/w3af/blob/cd22e5252243a87aaa6d0ddea47cf58dacfe00a9/w3af/core/ui/gui/history.py#L71-L78
|
|
mypaint/mypaint
|
90b36dbc7b8bd2f323383f7edf608a5e0a3a1a33
|
gui/document.py
|
python
|
Document._update_undo_redo
|
(self, action, stack, cmd_str, plain_str)
|
Set label, tooltip and sensitivity
|
Set label, tooltip and sensitivity
|
[
"Set",
"label",
"tooltip",
"and",
"sensitivity"
] |
def _update_undo_redo(self, action, stack, cmd_str, plain_str):
"""Set label, tooltip and sensitivity"""
if len(stack) > 0:
cmd = stack[-1]
desc = cmd_str % cmd.display_name
else:
desc = plain_str
action.set_label(desc)
action.set_tooltip(desc)
action.set_sensitive(len(stack) > 0)
|
[
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"desc",
")",
"action",
".",
"set_sensitive",
"(",
"len",
"(",
"stack",
")",
">",
"0",
")"
] |
https://github.com/mypaint/mypaint/blob/90b36dbc7b8bd2f323383f7edf608a5e0a3a1a33/gui/document.py#L554-L563
|
||
makerbot/ReplicatorG
|
d6f2b07785a5a5f1e172fb87cb4303b17c575d5d
|
skein_engines/skeinforge-47/fabmetheus_utilities/geometry/creation/linear_bearing_cage.py
|
python
|
getGeometryOutput
|
(elementNode)
|
return extrude.getGeometryOutputByNegativesPositives(elementNode, negatives, positives)
|
Get vector3 vertexes from attribute dictionary.
|
Get vector3 vertexes from attribute dictionary.
|
[
"Get",
"vector3",
"vertexes",
"from",
"attribute",
"dictionary",
"."
] |
def getGeometryOutput(elementNode):
'Get vector3 vertexes from attribute dictionary.'
derivation = LinearBearingCageDerivation(elementNode)
negatives = []
positives = []
if derivation.typeStringFirstCharacter == 'a':
addAssemblyCage(derivation, negatives, positives)
else:
addCage(derivation, derivation.height, negatives, positives)
return extrude.getGeometryOutputByNegativesPositives(elementNode, negatives, positives)
|
[
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"getGeometryOutputByNegativesPositives",
"(",
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")"
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https://github.com/makerbot/ReplicatorG/blob/d6f2b07785a5a5f1e172fb87cb4303b17c575d5d/skein_engines/skeinforge-47/fabmetheus_utilities/geometry/creation/linear_bearing_cage.py#L114-L123
|
|
AppScale/gts
|
46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9
|
AppServer/lib/django-1.3/django/db/backends/mysql/introspection.py
|
python
|
DatabaseIntrospection.get_table_list
|
(self, cursor)
|
return [row[0] for row in cursor.fetchall()]
|
Returns a list of table names in the current database.
|
Returns a list of table names in the current database.
|
[
"Returns",
"a",
"list",
"of",
"table",
"names",
"in",
"the",
"current",
"database",
"."
] |
def get_table_list(self, cursor):
"Returns a list of table names in the current database."
cursor.execute("SHOW TABLES")
return [row[0] for row in cursor.fetchall()]
|
[
"def",
"get_table_list",
"(",
"self",
",",
"cursor",
")",
":",
"cursor",
".",
"execute",
"(",
"\"SHOW TABLES\"",
")",
"return",
"[",
"row",
"[",
"0",
"]",
"for",
"row",
"in",
"cursor",
".",
"fetchall",
"(",
")",
"]"
] |
https://github.com/AppScale/gts/blob/46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9/AppServer/lib/django-1.3/django/db/backends/mysql/introspection.py#L31-L34
|
|
pyparallel/pyparallel
|
11e8c6072d48c8f13641925d17b147bf36ee0ba3
|
Lib/lib2to3/fixer_base.py
|
python
|
BaseFix.start_tree
|
(self, tree, filename)
|
Some fixers need to maintain tree-wide state.
This method is called once, at the start of tree fix-up.
tree - the root node of the tree to be processed.
filename - the name of the file the tree came from.
|
Some fixers need to maintain tree-wide state.
This method is called once, at the start of tree fix-up.
|
[
"Some",
"fixers",
"need",
"to",
"maintain",
"tree",
"-",
"wide",
"state",
".",
"This",
"method",
"is",
"called",
"once",
"at",
"the",
"start",
"of",
"tree",
"fix",
"-",
"up",
"."
] |
def start_tree(self, tree, filename):
"""Some fixers need to maintain tree-wide state.
This method is called once, at the start of tree fix-up.
tree - the root node of the tree to be processed.
filename - the name of the file the tree came from.
"""
self.used_names = tree.used_names
self.set_filename(filename)
self.numbers = itertools.count(1)
self.first_log = True
|
[
"def",
"start_tree",
"(",
"self",
",",
"tree",
",",
"filename",
")",
":",
"self",
".",
"used_names",
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"used_names",
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"filename",
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"=",
"itertools",
".",
"count",
"(",
"1",
")",
"self",
".",
"first_log",
"=",
"True"
] |
https://github.com/pyparallel/pyparallel/blob/11e8c6072d48c8f13641925d17b147bf36ee0ba3/Lib/lib2to3/fixer_base.py#L148-L158
|
||
meraki/dashboard-api-python
|
aef5e6fe5d23a40d435d5c64ff30580a28af07f1
|
meraki_v0/aio/api/traffic_analysis_settings.py
|
python
|
AsyncTrafficAnalysisSettings.getNetworkTrafficAnalysisSettings
|
(self, networkId: str)
|
return await self._session.get(metadata, resource)
|
**Return the traffic analysis settings for a network**
https://developer.cisco.com/meraki/api/#!get-network-traffic-analysis-settings
- networkId (string)
|
**Return the traffic analysis settings for a network**
https://developer.cisco.com/meraki/api/#!get-network-traffic-analysis-settings
- networkId (string)
|
[
"**",
"Return",
"the",
"traffic",
"analysis",
"settings",
"for",
"a",
"network",
"**",
"https",
":",
"//",
"developer",
".",
"cisco",
".",
"com",
"/",
"meraki",
"/",
"api",
"/",
"#!get",
"-",
"network",
"-",
"traffic",
"-",
"analysis",
"-",
"settings",
"-",
"networkId",
"(",
"string",
")"
] |
async def getNetworkTrafficAnalysisSettings(self, networkId: str):
"""
**Return the traffic analysis settings for a network**
https://developer.cisco.com/meraki/api/#!get-network-traffic-analysis-settings
- networkId (string)
"""
metadata = {
'tags': ['Traffic analysis settings'],
'operation': 'getNetworkTrafficAnalysisSettings',
}
resource = f'/networks/{networkId}/trafficAnalysisSettings'
return await self._session.get(metadata, resource)
|
[
"async",
"def",
"getNetworkTrafficAnalysisSettings",
"(",
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",",
"networkId",
":",
"str",
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"metadata",
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",",
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"return",
"await",
"self",
".",
"_session",
".",
"get",
"(",
"metadata",
",",
"resource",
")"
] |
https://github.com/meraki/dashboard-api-python/blob/aef5e6fe5d23a40d435d5c64ff30580a28af07f1/meraki_v0/aio/api/traffic_analysis_settings.py#L6-L20
|
|
friends-of-freeswitch/switchio
|
dee6e9addcf881b2b411ec1dbb397b0acfbb78cf
|
switchio/apps/measure/__init__.py
|
python
|
Measurers.add
|
(self, app, name=None, operators={}, **kwargs)
|
return name
|
[] |
def add(self, app, name=None, operators={}, **kwargs):
name = name or utils.get_name(app)
prepost = getattr(app, 'prepost', None)
if not prepost:
raise AttributeError(
"'{}' must define a `prepost` method".format(name))
args, ppkwargs = utils.get_args(app.prepost)
if 'storer' not in ppkwargs:
raise TypeError("'{}' must define a 'storer' kwarg"
.format(app.prepost))
ppkwargs = {key: kwargs.pop(key) for key in ppkwargs if key in kwargs}
# acquire storer factory
factory = getattr(app, 'new_storer', None)
storer_kwargs = getattr(app, 'storer_kwargs', {})
storer_kwargs.update(kwargs)
storer_kwargs.setdefault('storetype', self.storetype)
# app may not define a storer factory method
storer = storage.DataStorer(
name, dtype=app.fields, **storer_kwargs
) if not factory else factory()
self._apps[name] = Measurer(app, ppkwargs, storer, {})
# provide attr access off `self.stores`
self._stores[name] = storer
setattr(
self.stores.__class__,
name,
# make instance lookups access the `data` attr
property(partial(storer.__class__.data.__get__, storer))
)
# add any app defined operator functions
ops = getattr(app, 'operators', {})
ops.update(operators)
for opname, func in ops.items():
self.add_operator(name, func, opname=opname)
return name
|
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",",
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https://github.com/friends-of-freeswitch/switchio/blob/dee6e9addcf881b2b411ec1dbb397b0acfbb78cf/switchio/apps/measure/__init__.py#L63-L100
|
|||
datamllab/rlcard
|
c21ea82519c453a42e3bdc6848bd3356e9b6ac43
|
rlcard/envs/limitholdem.py
|
python
|
LimitholdemEnv.get_payoffs
|
(self)
|
return self.game.get_payoffs()
|
Get the payoff of a game
Returns:
payoffs (list): list of payoffs
|
Get the payoff of a game
|
[
"Get",
"the",
"payoff",
"of",
"a",
"game"
] |
def get_payoffs(self):
''' Get the payoff of a game
Returns:
payoffs (list): list of payoffs
'''
return self.game.get_payoffs()
|
[
"def",
"get_payoffs",
"(",
"self",
")",
":",
"return",
"self",
".",
"game",
".",
"get_payoffs",
"(",
")"
] |
https://github.com/datamllab/rlcard/blob/c21ea82519c453a42e3bdc6848bd3356e9b6ac43/rlcard/envs/limitholdem.py#L73-L79
|
|
numenta/nupic
|
b9ebedaf54f49a33de22d8d44dff7c765cdb5548
|
src/nupic/algorithms/backtracking_tm_cpp.py
|
python
|
BacktrackingTMCPP.finishLearning
|
(self)
|
Overrides :meth:`nupic.algorithms.backtracking_tm.BacktrackingTM.finishLearning`.
|
Overrides :meth:`nupic.algorithms.backtracking_tm.BacktrackingTM.finishLearning`.
|
[
"Overrides",
":",
"meth",
":",
"nupic",
".",
"algorithms",
".",
"backtracking_tm",
".",
"BacktrackingTM",
".",
"finishLearning",
"."
] |
def finishLearning(self):
"""
Overrides :meth:`nupic.algorithms.backtracking_tm.BacktrackingTM.finishLearning`.
"""
# Keep weakly formed synapses around because they contain confidence scores
# for paths out of learned sequenced and produce a better prediction than
# chance.
self.trimSegments(minPermanence=0.0001)
|
[
"def",
"finishLearning",
"(",
"self",
")",
":",
"# Keep weakly formed synapses around because they contain confidence scores",
"# for paths out of learned sequenced and produce a better prediction than",
"# chance.",
"self",
".",
"trimSegments",
"(",
"minPermanence",
"=",
"0.0001",
")"
] |
https://github.com/numenta/nupic/blob/b9ebedaf54f49a33de22d8d44dff7c765cdb5548/src/nupic/algorithms/backtracking_tm_cpp.py#L444-L451
|
||
rowliny/DiffHelper
|
ab3a96f58f9579d0023aed9ebd785f4edf26f8af
|
Tool/SitePackages/nltk/cluster/util.py
|
python
|
VectorSpaceClusterer.likelihood_vectorspace
|
(self, vector, cluster)
|
return 1.0 if cluster == predicted else 0.0
|
Returns the likelihood of the vector belonging to the cluster.
|
Returns the likelihood of the vector belonging to the cluster.
|
[
"Returns",
"the",
"likelihood",
"of",
"the",
"vector",
"belonging",
"to",
"the",
"cluster",
"."
] |
def likelihood_vectorspace(self, vector, cluster):
"""
Returns the likelihood of the vector belonging to the cluster.
"""
predicted = self.classify_vectorspace(vector)
return 1.0 if cluster == predicted else 0.0
|
[
"def",
"likelihood_vectorspace",
"(",
"self",
",",
"vector",
",",
"cluster",
")",
":",
"predicted",
"=",
"self",
".",
"classify_vectorspace",
"(",
"vector",
")",
"return",
"1.0",
"if",
"cluster",
"==",
"predicted",
"else",
"0.0"
] |
https://github.com/rowliny/DiffHelper/blob/ab3a96f58f9579d0023aed9ebd785f4edf26f8af/Tool/SitePackages/nltk/cluster/util.py#L92-L97
|
|
OpenMined/PySyft
|
f181ca02d307d57bfff9477610358df1a12e3ac9
|
packages/syft/src/syft/core/common/serde/serialize.py
|
python
|
_serialize
|
(
obj: object,
to_proto: bool = True,
to_bytes: bool = False,
)
|
Serialize the object according to the parameters.
This method can be called directly on the syft module::
import syft as sy
serialized_obj = sy.serialize(obj=my_object_to_serialize)
This is the primary serialization method, which processes the above
flags in a particular order. In general, it is not expected that people
will set multiple to_<type> flags to True at the same time. We don't
currently have logic which prevents this, because this may affect
runtime performance, but if several flags are True, then we will simply
take return the type of latest supported flag from the following list:
- proto
- binary
TODO: we could also add "dict" to this list but it's not clear if it would be used.
:param to_proto: set this flag to TRUE if you want to return a protobuf object
:type to_proto: bool
:param to_bytes: set this flag to TRUE if you want to return a binary object
:type to_bytes: bool
:return: a serialized form of the object on which serialize() is called.
:rtype: Union[str, bytes, Message]
|
Serialize the object according to the parameters.
|
[
"Serialize",
"the",
"object",
"according",
"to",
"the",
"parameters",
"."
] |
def _serialize(
obj: object,
to_proto: bool = True,
to_bytes: bool = False,
) -> Union[str, bytes, Message]:
"""Serialize the object according to the parameters.
This method can be called directly on the syft module::
import syft as sy
serialized_obj = sy.serialize(obj=my_object_to_serialize)
This is the primary serialization method, which processes the above
flags in a particular order. In general, it is not expected that people
will set multiple to_<type> flags to True at the same time. We don't
currently have logic which prevents this, because this may affect
runtime performance, but if several flags are True, then we will simply
take return the type of latest supported flag from the following list:
- proto
- binary
TODO: we could also add "dict" to this list but it's not clear if it would be used.
:param to_proto: set this flag to TRUE if you want to return a protobuf object
:type to_proto: bool
:param to_bytes: set this flag to TRUE if you want to return a binary object
:type to_bytes: bool
:return: a serialized form of the object on which serialize() is called.
:rtype: Union[str, bytes, Message]
"""
# relative
from ....lib.python.primitive_factory import isprimitive
# we have an unboxed primitive type so we need to mirror that on deserialize
if isprimitive(obj):
# relative
from ....lib.python.primitive_factory import PrimitiveFactory
obj = PrimitiveFactory.generate_primitive(value=obj, temporary_box=True)
if hasattr(obj, "temporary_box"):
# TODO: can remove this once all of PrimitiveFactory.generate_primitive
# supports temporary_box and is tested
obj.temporary_box = True # type: ignore
if hasattr(obj, "_sy_serializable_wrapper_type"):
is_serializable = obj._sy_serializable_wrapper_type(value=obj) # type: ignore
else:
is_serializable = obj
# traceback_and_raise(
# Exception(
# f"Object {type(obj)} is not serializable and has no _sy_serializable_wrapper_type"
# )
# )
if to_bytes:
# debug(f"Serializing {type(is_serializable)}")
# indent=None means no white space or \n in the serialized version
# this is compatible with json.dumps(x, indent=None)
serialized_data = is_serializable._object2proto().SerializeToString()
blob: Message = DataMessage(
obj_type=get_fully_qualified_name(obj=is_serializable),
content=serialized_data,
)
return validate_type(blob.SerializeToString(), bytes)
elif to_proto:
return validate_type(is_serializable._object2proto(), Message)
else:
traceback_and_raise(
Exception(
"""You must specify at least one deserialization format using
one of the arguments of the serialize() method such as:
to_proto, to_bytes."""
)
)
|
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"# debug(f\"Serializing {type(is_serializable)}\")",
"# indent=None means no white space or \\n in the serialized version",
"# this is compatible with json.dumps(x, indent=None)",
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"(",
"\"\"\"You must specify at least one deserialization format using\n one of the arguments of the serialize() method such as:\n to_proto, to_bytes.\"\"\"",
")",
")"
] |
https://github.com/OpenMined/PySyft/blob/f181ca02d307d57bfff9477610358df1a12e3ac9/packages/syft/src/syft/core/common/serde/serialize.py#L14-L90
|
||
jython/frozen-mirror
|
b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99
|
lib-python/2.7/cookielib.py
|
python
|
escape_path
|
(path)
|
return path
|
Escape any invalid characters in HTTP URL, and uppercase all escapes.
|
Escape any invalid characters in HTTP URL, and uppercase all escapes.
|
[
"Escape",
"any",
"invalid",
"characters",
"in",
"HTTP",
"URL",
"and",
"uppercase",
"all",
"escapes",
"."
] |
def escape_path(path):
"""Escape any invalid characters in HTTP URL, and uppercase all escapes."""
# There's no knowing what character encoding was used to create URLs
# containing %-escapes, but since we have to pick one to escape invalid
# path characters, we pick UTF-8, as recommended in the HTML 4.0
# specification:
# http://www.w3.org/TR/REC-html40/appendix/notes.html#h-B.2.1
# And here, kind of: draft-fielding-uri-rfc2396bis-03
# (And in draft IRI specification: draft-duerst-iri-05)
# (And here, for new URI schemes: RFC 2718)
if isinstance(path, unicode):
path = path.encode("utf-8")
path = urllib.quote(path, HTTP_PATH_SAFE)
path = ESCAPED_CHAR_RE.sub(uppercase_escaped_char, path)
return path
|
[
"def",
"escape_path",
"(",
"path",
")",
":",
"# There's no knowing what character encoding was used to create URLs",
"# containing %-escapes, but since we have to pick one to escape invalid",
"# path characters, we pick UTF-8, as recommended in the HTML 4.0",
"# specification:",
"# http://www.w3.org/TR/REC-html40/appendix/notes.html#h-B.2.1",
"# And here, kind of: draft-fielding-uri-rfc2396bis-03",
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"uppercase_escaped_char",
",",
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")",
"return",
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https://github.com/jython/frozen-mirror/blob/b8d7aa4cee50c0c0fe2f4b235dd62922dd0f3f99/lib-python/2.7/cookielib.py#L639-L653
|
|
home-assistant/core
|
265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1
|
homeassistant/components/qnap/sensor.py
|
python
|
QNAPDriveSensor.extra_state_attributes
|
(self)
|
Return the state attributes.
|
Return the state attributes.
|
[
"Return",
"the",
"state",
"attributes",
"."
] |
def extra_state_attributes(self):
"""Return the state attributes."""
if self._api.data:
data = self._api.data["smart_drive_health"][self.monitor_device]
return {
ATTR_DRIVE: data["drive_number"],
ATTR_MODEL: data["model"],
ATTR_SERIAL: data["serial"],
ATTR_TYPE: data["type"],
}
|
[
"def",
"extra_state_attributes",
"(",
"self",
")",
":",
"if",
"self",
".",
"_api",
".",
"data",
":",
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https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/qnap/sensor.py#L462-L471
|
||
bcj/AttrDict
|
8c1883162178a124ee29144ca7abcd83cbd9d222
|
attrdict/default.py
|
python
|
AttrDefault.__len__
|
(self)
|
return len(self._mapping)
|
Check the length of the mapping.
|
Check the length of the mapping.
|
[
"Check",
"the",
"length",
"of",
"the",
"mapping",
"."
] |
def __len__(self):
"""
Check the length of the mapping.
"""
return len(self._mapping)
|
[
"def",
"__len__",
"(",
"self",
")",
":",
"return",
"len",
"(",
"self",
".",
"_mapping",
")"
] |
https://github.com/bcj/AttrDict/blob/8c1883162178a124ee29144ca7abcd83cbd9d222/attrdict/default.py#L63-L67
|
|
geekori/pyqt5
|
49b2538fa5afe43b3b2bdadaa0560d0d6ef4924c
|
src/dialogs/QColorDialog.py
|
python
|
QColorDialogDemo.getBGColor
|
(self)
|
[] |
def getBGColor(self):
color = QColorDialog.getColor()
p = QPalette()
p.setColor(QPalette.Window,color)
self.colorLabel.setAutoFillBackground(True)
self.colorLabel.setPalette(p)
|
[
"def",
"getBGColor",
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"self",
")",
":",
"color",
"=",
"QColorDialog",
".",
"getColor",
"(",
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"setAutoFillBackground",
"(",
"True",
")",
"self",
".",
"colorLabel",
".",
"setPalette",
"(",
"p",
")"
] |
https://github.com/geekori/pyqt5/blob/49b2538fa5afe43b3b2bdadaa0560d0d6ef4924c/src/dialogs/QColorDialog.py#L44-L49
|
||||
gramps-project/gramps
|
04d4651a43eb210192f40a9f8c2bad8ee8fa3753
|
gramps/gen/datehandler/_dateparser.py
|
python
|
DateParser.match_range
|
(self, text, cal, ny, qual, date)
|
return 0
|
Try matching range date.
On success, set the date and return 1. On failure return 0.
|
Try matching range date.
|
[
"Try",
"matching",
"range",
"date",
"."
] |
def match_range(self, text, cal, ny, qual, date):
"""
Try matching range date.
On success, set the date and return 1. On failure return 0.
"""
match = self._range.match(text)
if match:
text_parser = self.parser[cal]
(text1, bc1) = self.match_bce(match.group('start'))
start = self._parse_subdate(text1, text_parser, cal)
if start == Date.EMPTY and text1 != "":
return 0
if bc1:
start = self.invert_year(start)
(text2, bc2) = self.match_bce(match.group('stop'))
stop = self._parse_subdate(text2, text_parser, cal)
if stop == Date.EMPTY and text2 != "":
return 0
if bc2:
stop = self.invert_year(stop)
date.set(qual, Date.MOD_RANGE, cal, start + stop, newyear=ny)
return 1
return 0
|
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https://github.com/gramps-project/gramps/blob/04d4651a43eb210192f40a9f8c2bad8ee8fa3753/gramps/gen/datehandler/_dateparser.py#L812-L837
|
|
ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework
|
cb692f527e4e819b6c228187c5702d990a180043
|
external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/shutil.py
|
python
|
_make_zipfile
|
(base_name, base_dir, verbose=0, dry_run=0, logger=None)
|
return zip_filename
|
Create a zip file from all the files under 'base_dir'.
The output zip file will be named 'base_name' + ".zip". Uses either the
"zipfile" Python module (if available) or the InfoZIP "zip" utility
(if installed and found on the default search path). If neither tool is
available, raises ExecError. Returns the name of the output zip
file.
|
Create a zip file from all the files under 'base_dir'.
|
[
"Create",
"a",
"zip",
"file",
"from",
"all",
"the",
"files",
"under",
"base_dir",
"."
] |
def _make_zipfile(base_name, base_dir, verbose=0, dry_run=0, logger=None):
"""Create a zip file from all the files under 'base_dir'.
The output zip file will be named 'base_name' + ".zip". Uses either the
"zipfile" Python module (if available) or the InfoZIP "zip" utility
(if installed and found on the default search path). If neither tool is
available, raises ExecError. Returns the name of the output zip
file.
"""
zip_filename = base_name + ".zip"
archive_dir = os.path.dirname(base_name)
if not os.path.exists(archive_dir):
if logger is not None:
logger.info("creating %s", archive_dir)
if not dry_run:
os.makedirs(archive_dir)
# If zipfile module is not available, try spawning an external 'zip'
# command.
try:
import zipfile
except ImportError:
zipfile = None
if zipfile is None:
_call_external_zip(base_dir, zip_filename, verbose, dry_run)
else:
if logger is not None:
logger.info("creating '%s' and adding '%s' to it",
zip_filename, base_dir)
if not dry_run:
zip = zipfile.ZipFile(zip_filename, "w",
compression=zipfile.ZIP_DEFLATED)
for dirpath, dirnames, filenames in os.walk(base_dir):
for name in filenames:
path = os.path.normpath(os.path.join(dirpath, name))
if os.path.isfile(path):
zip.write(path, path)
if logger is not None:
logger.info("adding '%s'", path)
zip.close()
return zip_filename
|
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",",
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",",
"path",
")",
"zip",
".",
"close",
"(",
")",
"return",
"zip_filename"
] |
https://github.com/ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework/blob/cb692f527e4e819b6c228187c5702d990a180043/external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/shutil.py#L412-L457
|
|
apache/tvm
|
6eb4ed813ebcdcd9558f0906a1870db8302ff1e0
|
python/tvm/relay/op/tensor.py
|
python
|
concatenate
|
(data, axis)
|
return _make.concatenate(Tuple(data), axis)
|
Concatenate the input tensors along the given axis.
Parameters
----------
data : Union(List[relay.Expr], Tuple[relay.Expr])
A list of tensors.
axis : int
The axis along which the tensors are concatenated.
Returns
-------
result: relay.Expr
The concatenated tensor.
|
Concatenate the input tensors along the given axis.
|
[
"Concatenate",
"the",
"input",
"tensors",
"along",
"the",
"given",
"axis",
"."
] |
def concatenate(data, axis):
"""Concatenate the input tensors along the given axis.
Parameters
----------
data : Union(List[relay.Expr], Tuple[relay.Expr])
A list of tensors.
axis : int
The axis along which the tensors are concatenated.
Returns
-------
result: relay.Expr
The concatenated tensor.
"""
data = list(data)
if not data:
raise ValueError("relay.concatenate requires data to be non-empty.")
if not isinstance(axis, int):
raise ValueError("For now, we only support integer axis")
return _make.concatenate(Tuple(data), axis)
|
[
"def",
"concatenate",
"(",
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https://github.com/apache/tvm/blob/6eb4ed813ebcdcd9558f0906a1870db8302ff1e0/python/tvm/relay/op/tensor.py#L1093-L1113
|
|
sdaps/sdaps
|
51d1072185223f5e48512661e2c1e8399d63e876
|
sdaps/setup/buddies.py
|
python
|
Head.validate
|
(self)
|
[] |
def validate(self):
if not self.obj.title:
log.warn(_('Head %(l0)i got no title.') % {'l0': self.obj.id[0]})
|
[
"def",
"validate",
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"self",
")",
":",
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":",
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"obj",
".",
"id",
"[",
"0",
"]",
"}",
")"
] |
https://github.com/sdaps/sdaps/blob/51d1072185223f5e48512661e2c1e8399d63e876/sdaps/setup/buddies.py#L60-L62
|
||||
golismero/golismero
|
7d605b937e241f51c1ca4f47b20f755eeefb9d76
|
tools/sqlmap/thirdparty/odict/odict.py
|
python
|
_OrderedDict.insert
|
(self, index, key, value)
|
Takes ``index``, ``key``, and ``value`` as arguments.
Sets ``key`` to ``value``, so that ``key`` is at position ``index`` in
the OrderedDict.
>>> d = OrderedDict(((1, 3), (3, 2), (2, 1)))
>>> d.insert(0, 4, 0)
>>> d
OrderedDict([(4, 0), (1, 3), (3, 2), (2, 1)])
>>> d.insert(0, 2, 1)
>>> d
OrderedDict([(2, 1), (4, 0), (1, 3), (3, 2)])
>>> d.insert(8, 8, 1)
>>> d
OrderedDict([(2, 1), (4, 0), (1, 3), (3, 2), (8, 1)])
|
Takes ``index``, ``key``, and ``value`` as arguments.
|
[
"Takes",
"index",
"key",
"and",
"value",
"as",
"arguments",
"."
] |
def insert(self, index, key, value):
"""
Takes ``index``, ``key``, and ``value`` as arguments.
Sets ``key`` to ``value``, so that ``key`` is at position ``index`` in
the OrderedDict.
>>> d = OrderedDict(((1, 3), (3, 2), (2, 1)))
>>> d.insert(0, 4, 0)
>>> d
OrderedDict([(4, 0), (1, 3), (3, 2), (2, 1)])
>>> d.insert(0, 2, 1)
>>> d
OrderedDict([(2, 1), (4, 0), (1, 3), (3, 2)])
>>> d.insert(8, 8, 1)
>>> d
OrderedDict([(2, 1), (4, 0), (1, 3), (3, 2), (8, 1)])
"""
if key in self:
# FIXME: efficiency?
del self[key]
self._sequence.insert(index, key)
dict.__setitem__(self, key, value)
|
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"(",
"index",
",",
"key",
")",
"dict",
".",
"__setitem__",
"(",
"self",
",",
"key",
",",
"value",
")"
] |
https://github.com/golismero/golismero/blob/7d605b937e241f51c1ca4f47b20f755eeefb9d76/tools/sqlmap/thirdparty/odict/odict.py#L823-L845
|
||
peterbrittain/asciimatics
|
9a490faddf484ee5b9b845316f921f5888b23b18
|
samples/maps.py
|
python
|
Map._zoom_map
|
(self, zoom_out=True)
|
Animate the zoom in/out as appropriate for the displayed map tile.
|
Animate the zoom in/out as appropriate for the displayed map tile.
|
[
"Animate",
"the",
"zoom",
"in",
"/",
"out",
"as",
"appropriate",
"for",
"the",
"displayed",
"map",
"tile",
"."
] |
def _zoom_map(self, zoom_out=True):
"""Animate the zoom in/out as appropriate for the displayed map tile."""
size_step = 1 / _ZOOM_STEP if zoom_out else _ZOOM_STEP
self._next_update = 1
if self._satellite:
size_step **= _ZOOM_ANIMATION_STEPS
self._size *= size_step
if self._size <= _ZOOM_OUT_SIZE:
if self._zoom > 0:
self._zoom -= 1
self._size = _START_SIZE
else:
self._size = _ZOOM_OUT_SIZE
elif self._size >= _ZOOM_IN_SIZE:
if self._zoom < 20:
self._zoom += 1
self._size = _START_SIZE
else:
self._size = _ZOOM_IN_SIZE
|
[
"def",
"_zoom_map",
"(",
"self",
",",
"zoom_out",
"=",
"True",
")",
":",
"size_step",
"=",
"1",
"/",
"_ZOOM_STEP",
"if",
"zoom_out",
"else",
"_ZOOM_STEP",
"self",
".",
"_next_update",
"=",
"1",
"if",
"self",
".",
"_satellite",
":",
"size_step",
"**=",
"_ZOOM_ANIMATION_STEPS",
"self",
".",
"_size",
"*=",
"size_step",
"if",
"self",
".",
"_size",
"<=",
"_ZOOM_OUT_SIZE",
":",
"if",
"self",
".",
"_zoom",
">",
"0",
":",
"self",
".",
"_zoom",
"-=",
"1",
"self",
".",
"_size",
"=",
"_START_SIZE",
"else",
":",
"self",
".",
"_size",
"=",
"_ZOOM_OUT_SIZE",
"elif",
"self",
".",
"_size",
">=",
"_ZOOM_IN_SIZE",
":",
"if",
"self",
".",
"_zoom",
"<",
"20",
":",
"self",
".",
"_zoom",
"+=",
"1",
"self",
".",
"_size",
"=",
"_START_SIZE",
"else",
":",
"self",
".",
"_size",
"=",
"_ZOOM_IN_SIZE"
] |
https://github.com/peterbrittain/asciimatics/blob/9a490faddf484ee5b9b845316f921f5888b23b18/samples/maps.py#L406-L424
|
||
cloudera/impyla
|
0c736af4cad2bade9b8e313badc08ec50e81c948
|
impala/_thrift_gen/beeswax/ttypes.py
|
python
|
QueryHandle.__ne__
|
(self, other)
|
return not (self == other)
|
[] |
def __ne__(self, other):
return not (self == other)
|
[
"def",
"__ne__",
"(",
"self",
",",
"other",
")",
":",
"return",
"not",
"(",
"self",
"==",
"other",
")"
] |
https://github.com/cloudera/impyla/blob/0c736af4cad2bade9b8e313badc08ec50e81c948/impala/_thrift_gen/beeswax/ttypes.py#L219-L220
|
|||
ales-tsurko/cells
|
4cf7e395cd433762bea70cdc863a346f3a6fe1d0
|
packaging/macos/python/lib/python3.7/ipaddress.py
|
python
|
IPv6Address.is_private
|
(self)
|
return any(self in net for net in self._constants._private_networks)
|
Test if this address is allocated for private networks.
Returns:
A boolean, True if the address is reserved per
iana-ipv6-special-registry.
|
Test if this address is allocated for private networks.
|
[
"Test",
"if",
"this",
"address",
"is",
"allocated",
"for",
"private",
"networks",
"."
] |
def is_private(self):
"""Test if this address is allocated for private networks.
Returns:
A boolean, True if the address is reserved per
iana-ipv6-special-registry.
"""
return any(self in net for net in self._constants._private_networks)
|
[
"def",
"is_private",
"(",
"self",
")",
":",
"return",
"any",
"(",
"self",
"in",
"net",
"for",
"net",
"in",
"self",
".",
"_constants",
".",
"_private_networks",
")"
] |
https://github.com/ales-tsurko/cells/blob/4cf7e395cd433762bea70cdc863a346f3a6fe1d0/packaging/macos/python/lib/python3.7/ipaddress.py#L1966-L1974
|
|
home-assistant/core
|
265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1
|
homeassistant/components/climate/__init__.py
|
python
|
ClimateEntity.fan_modes
|
(self)
|
return self._attr_fan_modes
|
Return the list of available fan modes.
Requires SUPPORT_FAN_MODE.
|
Return the list of available fan modes.
|
[
"Return",
"the",
"list",
"of",
"available",
"fan",
"modes",
"."
] |
def fan_modes(self) -> list[str] | None:
"""Return the list of available fan modes.
Requires SUPPORT_FAN_MODE.
"""
return self._attr_fan_modes
|
[
"def",
"fan_modes",
"(",
"self",
")",
"->",
"list",
"[",
"str",
"]",
"|",
"None",
":",
"return",
"self",
".",
"_attr_fan_modes"
] |
https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/climate/__init__.py#L415-L420
|
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