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VitaliyRodnenko/geeknote | 6bc226133c0d4d2902a76d4d2ac85964aac9bae7 | geeknote/out.py | python | GetUserCredentials | () | return (login, password) | Prompts the user for a username and password. | Prompts the user for a username and password. | [
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"""Prompts the user for a username and password."""
try:
login = None
password = None
if login is None:
login = rawInput("Login: ")
if password is None:
password = rawInput("Password: ", True)
except (KeyboardInterrupt, SystemExit), e:
if e.message:
tools.exit(e.message)
else:
tools.exit
return (login, password) | [
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graphbrain/graphbrain | 96cb902d9e22d8dc8c2110ff3176b9aafdeba444 | graphbrain/scripts/generate-parser-training-data.py | python | TrainingDataGenerator.__init__ | (self, lang=None, parser_class=None) | [] | def __init__(self, lang=None, parser_class=None):
self.parser = create_parser(lang=lang, parser_class=parser_class)
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self.tokens = 0
self.correct_edges = 0
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self.token2atom = None | [
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learningequality/ka-lite | 571918ea668013dcf022286ea85eff1c5333fb8b | kalite/packages/bundled/django/core/files/uploadhandler.py | python | FileUploadHandler.handle_raw_input | (self, input_data, META, content_length, boundary, encoding=None) | Handle the raw input from the client.
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An object that supports reading via .read().
:META:
``request.META``.
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The (integer) value of the Content-Length header from the
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Handle the raw input from the client.
Parameters:
:input_data:
An object that supports reading via .read().
:META:
``request.META``.
:content_length:
The (integer) value of the Content-Length header from the
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:boundary: The boundary from the Content-Type header. Be sure to
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TDAmeritrade/stumpy | 7c97df98cb4095afae775ab71870d4d5a14776c7 | stumpy/maamp.py | python | _get_first_maamp_profile | (
start, T_A, T_B, m, excl_zone, T_B_subseq_isfinite, include=None, discords=False
) | return P, I | Multi-dimensional wrapper to compute the non-normalized (i.e., without
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----------
start : int
The window index to calculate the first multi-dimensional matrix profile,
multi-dimensional matrix profile indices, and multi-dimensional subspace.
T_A : numpy.ndarray
The time series or sequence for which the multi-dimensional matrix profile,
multi-dimensional matrix profile indices, and multi-dimensional subspace will be
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T_B : numpy.ndarray
The time series or sequence that contains your query subsequences
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Window size
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The half width for the exclusion zone relative to the `start`.
T_B_subseq_isfinite : numpy.ndarray
A boolean array that indicates whether a subsequence in `Q` contains a
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include : numpy.ndarray, default None
A list of (zero-based) indices corresponding to the dimensions in `T` that
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For more information, see Section IV D in:
`DOI: 10.1109/ICDM.2017.66 \
<https://www.cs.ucr.edu/~eamonn/Motif_Discovery_ICDM.pdf>`__
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Multi-dimensional matrix profile for the window with index equal to
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I : numpy.ndarray
Multi-dimensional matrix profile indices for the window with index
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"""
Multi-dimensional wrapper to compute the non-normalized (i.e., without
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A list of (zero-based) indices corresponding to the dimensions in `T` that
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`DOI: 10.1109/ICDM.2017.66 \
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discords : bool, default False
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Returns
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Multi-dimensional matrix profile for the window with index equal to
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I : numpy.ndarray
Multi-dimensional matrix profile indices for the window with index
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"""
D = _maamp_multi_distance_profile(
start, T_A, T_B, m, excl_zone, T_B_subseq_isfinite, include, discords
)
d = T_A.shape[0]
P = np.full(d, np.inf, dtype=np.float64)
I = np.full(d, -1, dtype=np.int64)
for i in range(d):
min_index = np.argmin(D[i])
I[i] = min_index
P[i] = D[i, min_index]
if np.isinf(P[i]): # pragma nocover
I[i] = -1
return P, I | [
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RaphielGang/Telegram-Paperplane | d9e6c466902dd573ddf8c805e9dc484f972a62f1 | userbot/modules/dbhelper.py | python | block_pm | (userid) | return True | [] | async def block_pm(userid):
if await approval(userid) is False:
return False
MONGO.pmpermit.update_one({"user_id": userid}, {"$set": {"approval": False}})
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UCL-INGI/INGInious | 60f10cb4c375ce207471043e76bd813220b95399 | inginious/frontend/pages/course_admin/utils.py | python | make_csv | (data) | return response | Returns the content of a CSV file with the data of the dict/list data | Returns the content of a CSV file with the data of the dict/list data | [
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""" Returns the content of a CSV file with the data of the dict/list data """
# Convert sub-dicts to news cols
for entry in data:
rval = entry
if isinstance(data, dict):
rval = data[entry]
todel = []
toadd = {}
for key, val in rval.items():
if isinstance(val, dict):
for key2, val2 in val.items():
toadd[str(key) + "[" + str(key2) + "]"] = val2
todel.append(key)
for k in todel:
del rval[k]
for k, v in toadd.items():
rval[k] = v
# Convert everything to CSV
columns = set()
output = [[]]
if isinstance(data, dict):
output[0].append("id")
for entry in data:
for col in data[entry]:
columns.add(col)
else:
for entry in data:
for col in entry:
columns.add(col)
columns = sorted(columns)
for col in columns:
output[0].append(col)
if isinstance(data, dict):
for entry in data:
new_output = [str(entry)]
for col in columns:
new_output.append(str(data[entry][col]) if col in data[entry] else "")
output.append(new_output)
else:
for entry in data:
new_output = []
for col in columns:
new_output.append(str(entry[col]) if col in entry else "")
output.append(new_output)
csv_string = io.StringIO()
csv_writer = UnicodeWriter(csv_string)
for row in output:
csv_writer.writerow(row)
csv_string.seek(0)
response = Response(response=csv_string.read(), content_type='text/csv; charset=utf-8')
response.headers['Content-disposition'] = 'attachment; filename=export.csv'
return response | [
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scipy/scipy | e0a749f01e79046642ccfdc419edbf9e7ca141ad | scipy/io/_idl.py | python | _read_arraydesc | (f) | return arraydesc | Function to read in an array descriptor | Function to read in an array descriptor | [
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arraydesc['nbytes'] = _read_long(f)
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arraydesc['nmax'] = _read_long(f)
arraydesc['dims'] = [_read_long(f) for _ in range(arraydesc['nmax'])]
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warnings.warn("Using experimental 64-bit array read")
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arraydesc['nbytes'] = _read_uint64(f)
arraydesc['nelements'] = _read_uint64(f)
arraydesc['ndims'] = _read_long(f)
_skip_bytes(f, 8)
arraydesc['nmax'] = 8
arraydesc['dims'] = []
for d in range(arraydesc['nmax']):
v = _read_long(f)
if v != 0:
raise Exception("Expected a zero in ARRAY_DESC")
arraydesc['dims'].append(_read_long(f))
else:
raise Exception("Unknown ARRSTART: %i" % arraydesc['arrstart'])
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PyCQA/astroid | a815443f62faae05249621a396dcf0afd884a619 | astroid/nodes/scoped_nodes/scoped_nodes.py | python | ClassDef.implicit_locals | (self) | return locals_ | Get implicitly defined class definition locals.
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"""
locals_ = (("__module__", self.special_attributes.attr___module__),)
# __qualname__ is defined in PEP3155
locals_ += (("__qualname__", self.special_attributes.attr___qualname__),)
return locals_ | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.4/django/utils/translation/trans_real.py | python | ngettext | (singular, plural, number) | return do_ntranslate(singular, plural, number, 'ngettext') | Returns a UTF-8 bytestring of the translation of either the singular or
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"""
Returns a UTF-8 bytestring of the translation of either the singular or
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return do_ntranslate(singular, plural, number, 'ngettext') | [
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gmate/gmate | 83312e64e0c115a9842500e4eb8617d3f5f4025b | plugins/gedit2/zencoding/zencoding/filters/html.py | python | make_attributes_string | (tag, profile) | return attrs | Creates HTML attributes string from tag according to profile settings
@type tag: ZenNode
@type profile: dict | Creates HTML attributes string from tag according to profile settings | [
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Creates HTML attributes string from tag according to profile settings
@type tag: ZenNode
@type profile: dict
"""
# make attribute string
attrs = ''
attr_quote = profile['attr_quotes'] == 'single' and "'" or '"'
cursor = profile['place_cursor'] and zen_coding.get_caret_placeholder() or ''
# process other attributes
for a in tag.attributes:
attr_name = profile['attr_case'] == 'upper' and a['name'].upper() or a['name'].lower()
attrs += ' ' + attr_name + '=' + attr_quote + (a['value'] or cursor) + attr_quote
return attrs | [
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openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | openedx/core/djangoapps/content/block_structure/transformer_registry.py | python | TransformerRegistry.get_write_version_hash | (cls) | return b64encode(hash_obj.digest()).decode('utf-8') | Returns a deterministic hash value of the WRITE_VERSION of all
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"""
Returns a deterministic hash value of the WRITE_VERSION of all
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"""
hash_obj = sha1()
sorted_transformers = sorted(cls.get_registered_transformers(), key=lambda t: t.name())
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hash_obj.update((transformer.name()).encode())
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JonathonLuiten/PReMVOS | 2666acaae0f1b4bd7d88a0cfb9b7cf5c5de12a4b | code/proposal_net/viz.py | python | draw_mask | (im, mask, alpha=0.5, color=None) | return im | Overlay a mask on top of the image.
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im: a 3-channel uint8 image in BGR
mask: a binary 1-channel image of the same size
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"""
Overlay a mask on top of the image.
Args:
im: a 3-channel uint8 image in BGR
mask: a binary 1-channel image of the same size
color: if None, will choose automatically
"""
if color is None:
color = PALETTE_RGB[np.random.choice(len(PALETTE_RGB))][::-1]
im = np.where(np.repeat((mask > 0)[:, :, None], 3, axis=2),
im * (1 - alpha) + color * alpha, im)
im = im.astype('uint8')
return im | [
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SforAiDl/Neural-Voice-Cloning-With-Few-Samples | 33fb609427657c9492f46507184ecba4dcc272b0 | train_dv3.py | python | TextDataSource.__init__ | (self, data_root, speaker_id=None) | [] | def __init__(self, data_root, speaker_id=None):
self.data_root = data_root
self.speaker_ids = None
self.multi_speaker = False
# If not None, filter by speaker_id
self.speaker_id = speaker_id | [
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trakt/Plex-Trakt-Scrobbler | aeb0bfbe62fad4b06c164f1b95581da7f35dce0b | Trakttv.bundle/Contents/Libraries/Linux/aarch64/ucs2/cryptography/hazmat/primitives/asymmetric/rsa.py | python | rsa_crt_dmp1 | (private_exponent, p) | return private_exponent % (p - 1) | Compute the CRT private_exponent % (p - 1) value from the RSA
private_exponent (d) and p. | Compute the CRT private_exponent % (p - 1) value from the RSA
private_exponent (d) and p. | [
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"""
return private_exponent % (p - 1) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/PIL/MpoImagePlugin.py | python | _accept | (prefix) | return JpegImagePlugin._accept(prefix) | [] | def _accept(prefix):
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/rings/polynomial/multi_polynomial_element.py | python | MPolynomial_element._lmul_ | (self, a) | return self.__class__(self.parent(),self.__element.scalar_lmult(a)) | Left Scalar Multiplication
EXAMPLES:
Note that it is not really possible to do a meaningful
example since sage mpoly rings refuse to have non-commutative
bases.
::
sage: R.<x,y> = QQbar[]
sage: f = (x + y)
sage: 3*f
3*x + 3*y | Left Scalar Multiplication | [
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"Scalar",
"Multiplication"
] | def _lmul_(self, a):
"""
Left Scalar Multiplication
EXAMPLES:
Note that it is not really possible to do a meaningful
example since sage mpoly rings refuse to have non-commutative
bases.
::
sage: R.<x,y> = QQbar[]
sage: f = (x + y)
sage: 3*f
3*x + 3*y
"""
return self.__class__(self.parent(),self.__element.scalar_lmult(a)) | [
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coderSkyChen/Action_Recognition_Zoo | 92ec5ec3efeee852aec5c057798298cd3a8e58ae | model_zoo/models/slim/deployment/model_deploy.py | python | DeploymentConfig.variables_device | (self) | Returns the device to use for variables created inside the clone.
Returns:
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"""Returns the device to use for variables created inside the clone.
Returns:
A value suitable for `tf.device()`.
"""
device = ''
if self._num_ps_tasks > 0:
device += self._ps_device
device += '/device:CPU:0'
class _PSDeviceChooser(object):
"""Slim device chooser for variables when using PS."""
def __init__(self, device, tasks):
self._device = device
self._tasks = tasks
self._task = 0
def choose(self, op):
if op.device:
return op.device
node_def = op if isinstance(op, tf.NodeDef) else op.node_def
if node_def.op == 'Variable':
t = self._task
self._task = (self._task + 1) % self._tasks
d = '%s/task:%d' % (self._device, t)
return d
else:
return op.device
if not self._num_ps_tasks:
return device
else:
chooser = _PSDeviceChooser(device, self._num_ps_tasks)
return chooser.choose | [
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atlassian-api/atlassian-python-api | 6d8545a790c3aae10b75bdc225fb5c3a0aee44db | atlassian/bamboo.py | python | Bamboo.get_groups | (self, start=0, limit=25) | return self.get(url, params=params) | Retrieve a paginated list of groups.
The authenticated user must have restricted administrative permission or higher to use this resource.
:param start:
:param limit:
:return: | Retrieve a paginated list of groups.
The authenticated user must have restricted administrative permission or higher to use this resource.
:param start:
:param limit:
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Retrieve a paginated list of groups.
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:param start:
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params = {"limit": limit, "start": start}
url = "rest/api/latest/admin/groups"
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subuser-security/subuser | 8072271f8fc3dded60b048c2dee878f9840c126a | subuserlib/classes/subuserSubmodules/run/runReadyImage.py | python | RunReadyImage.generateImagePreparationDockerfile | (self) | return dockerfileContents | There is still some preparation that needs to be done before an image is ready to be run. But this preparation requires run time information, so we cannot preform that preparation at build time. | There is still some preparation that needs to be done before an image is ready to be run. But this preparation requires run time information, so we cannot preform that preparation at build time. | [
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"""
There is still some preparation that needs to be done before an image is ready to be run. But this preparation requires run time information, so we cannot preform that preparation at build time.
"""
dockerfileContents = "FROM "+self.subuser.imageId+"\n"
dockerfileContents += "RUN useradd --uid="+str(self.user.endUser.uid)+" subuser ;export exitstatus=$? ; if [ $exitstatus -eq 4 ] ; then echo uid exists ; elif [ $exitstatus -eq 9 ]; then echo username exists. ; else exit $exitstatus ; fi\n"
dockerfileContents += "RUN test -d /home/subuser || mkdir /home/subuser && chown subuser /home/subuser\n"
if self.subuser.permissions["serial-devices"]:
dockerfileContents += "RUN groupadd dialout; export exitstatus=$? ; if [ $exitstatus -eq 4 ] ; then echo gid exists ; elif [ $exitstatus -eq 9 ]; then echo groupname exists. ; else exit $exitstatus ; fi\n"
dockerfileContents += "RUN groupadd uucp; export exitstatus=$? ; if [ $exitstatus -eq 4 ] ; then echo gid exists ; elif [ $exitstatus -eq 9 ]; then echo groupname exists. ; else exit $exitstatus ; fi\n"
dockerfileContents += "RUN usermod -a -G dialout "+self.user.endUser.name+"\n"
dockerfileContents += "RUN usermod -a -G uucp "+self.user.endUser.name+"\n"
if self.subuser.permissions["sudo"]:
dockerfileContents += "RUN (umask 337; echo \""+self.user.endUser.name+" ALL=(ALL) NOPASSWD: ALL\" > /etc/sudoers.d/allowsudo )\n"
return dockerfileContents | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/modules/free_module.py | python | FreeModule_submodule_field.has_user_basis | (self) | return False | Return ``True`` if the basis of this free module is
specified by the user, as opposed to being the default echelon
form.
EXAMPLES::
sage: V = QQ^3
sage: W = V.subspace([[2,'1/2', 1]])
sage: W.has_user_basis()
False
sage: W = V.subspace_with_basis([[2,'1/2',1]])
sage: W.has_user_basis()
True | Return ``True`` if the basis of this free module is
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Return ``True`` if the basis of this free module is
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EXAMPLES::
sage: V = QQ^3
sage: W = V.subspace([[2,'1/2', 1]])
sage: W.has_user_basis()
False
sage: W = V.subspace_with_basis([[2,'1/2',1]])
sage: W.has_user_basis()
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"""
return False | [
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nathanborror/django-basic-apps | 3a90090857549ea4198a72c44f45f6edb238e2a8 | basic/blog/templatetags/blog.py | python | get_blogroll | (parser, token) | return BlogRolls(var_name) | Gets all blogroll links.
Syntax::
{% get_blogroll as [var_name] %}
Example usage::
{% get_blogroll as blogroll_list %} | Gets all blogroll links. | [
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"""
Gets all blogroll links.
Syntax::
{% get_blogroll as [var_name] %}
Example usage::
{% get_blogroll as blogroll_list %}
"""
try:
tag_name, arg = token.contents.split(None, 1)
except ValueError:
raise template.TemplateSyntaxError, "%s tag requires arguments" % token.contents.split()[0]
m = re.search(r'as (\w+)', arg)
if not m:
raise template.TemplateSyntaxError, "%s tag had invalid arguments" % tag_name
var_name = m.groups()[0]
return BlogRolls(var_name) | [
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securesystemslab/zippy | ff0e84ac99442c2c55fe1d285332cfd4e185e089 | zippy/benchmarks/src/benchmarks/sympy/sympy/sets/sets.py | python | FiniteSet._eval_evalf | (self, prec) | return FiniteSet(elem.evalf(prec) for elem in self) | [] | def _eval_evalf(self, prec):
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wireservice/leather | a10c27e0c073a6307133a7a2ad4db0268f02bf4b | leather/chart.py | python | Chart.set_x_axis | (self, axis) | Set an :class:`.Axis` class for this chart. | Set an :class:`.Axis` class for this chart. | [
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Set an :class:`.Axis` class for this chart.
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graalvm/mx | 29c0debab406352df3af246be2f8973be5db69ae | mx_bisect.py | python | _update_cmd_if_stripped | (cmd_to_update) | return cmd_to_update | [] | def _update_cmd_if_stripped(cmd_to_update):
if mx._opts.strip_jars and cmd_to_update.find('--strip-jars') == -1:
cmd_to_update = re.sub(r'\b(mx)\b', 'mx --strip-jars', cmd_to_update)
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter8-Regression/venv/Lib/site-packages/pip-9.0.1-py3.6.egg/pip/commands/search.py | python | SearchCommand.__init__ | (self, *args, **kw) | [] | def __init__(self, *args, **kw):
super(SearchCommand, self).__init__(*args, **kw)
self.cmd_opts.add_option(
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dest='index',
metavar='URL',
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kennethreitz-archive/requests3 | 69eb662703b40db58fdc6c095d0fe130c56649bb | requests3/_hooks.py | python | dispatch_hook | (key, hooks, hook_data, **kwargs) | return hook_data | Dispatches a hook dictionary on a given piece of data. | Dispatches a hook dictionary on a given piece of data. | [
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Mingtzge/2019-CCF-BDCI-OCR-MCZJ-OCR-IdentificationIDElement | 42ad9686f3c3bde0d29a8bc6bcb0e3afb35fb3c3 | pytorch-CycleGAN-and-pix2pix/util/html.py | python | HTML.add_images | (self, ims, txts, links, width=400) | add images to the HTML file
Parameters:
ims (str list) -- a list of image paths
txts (str list) -- a list of image names shown on the website
links (str list) -- a list of hyperref links; when you click an image, it will redirect you to a new page | add images to the HTML file | [
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"""add images to the HTML file
Parameters:
ims (str list) -- a list of image paths
txts (str list) -- a list of image names shown on the website
links (str list) -- a list of hyperref links; when you click an image, it will redirect you to a new page
"""
self.t = table(border=1, style="table-layout: fixed;") # Insert a table
self.doc.add(self.t)
with self.t:
with tr():
for im, txt, link in zip(ims, txts, links):
with td(style="word-wrap: break-word;", halign="center", valign="top"):
with p():
with a(href=os.path.join('images', link)):
img(style="width:%dpx" % width, src=os.path.join('images', im))
br()
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pyRiemann/pyRiemann | 30c2cd7204d19f1a60d3b7945dfd8ee3c46a8df8 | pyriemann/utils/mean.py | python | mean_covariance | (covmats, metric='riemann', sample_weight=None, *args) | return C | Return the mean covariance matrix according to the metric
:param covmats: Covariance matrices, (n_matrices, n_channels, n_channels)
:param metric: the metric (default 'riemann'), can be : 'riemann',
'logeuclid', 'euclid', 'logdet', 'identity', 'wasserstein', 'ale',
'alm', 'harmonic', 'kullback_sym' or a callable function
:param sample_weight: the weight of each matrix
:param args: the argument passed to the sub function
:returns: the mean covariance matrix, (n_channels, n_channels) | Return the mean covariance matrix according to the metric | [
"Return",
"the",
"mean",
"covariance",
"matrix",
"according",
"to",
"the",
"metric"
] | def mean_covariance(covmats, metric='riemann', sample_weight=None, *args):
"""Return the mean covariance matrix according to the metric
:param covmats: Covariance matrices, (n_matrices, n_channels, n_channels)
:param metric: the metric (default 'riemann'), can be : 'riemann',
'logeuclid', 'euclid', 'logdet', 'identity', 'wasserstein', 'ale',
'alm', 'harmonic', 'kullback_sym' or a callable function
:param sample_weight: the weight of each matrix
:param args: the argument passed to the sub function
:returns: the mean covariance matrix, (n_channels, n_channels)
"""
if callable(metric):
C = metric(covmats, sample_weight=sample_weight, *args)
else:
C = mean_methods[metric](covmats, sample_weight=sample_weight, *args)
return C | [
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PyHDI/veriloggen | 2382d200deabf59cfcfd741f5eba371010aaf2bb | veriloggen/seq/seq.py | python | Seq.Delay | (self, delay) | return self | [] | def Delay(self, delay):
self.next_kwargs['delay'] = delay
return self | [
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pdm-project/pdm | 34ba2ea48bf079044b0ca8c0017f3c0e7d9e198b | pdm/models/specifiers.py | python | PySpecSet.is_impossible | (self) | return self._lower_bound >= self._upper_bound | Check whether the specifierset contains any valid versions. | Check whether the specifierset contains any valid versions. | [
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] | def is_impossible(self) -> bool:
"""Check whether the specifierset contains any valid versions."""
if self._lower_bound == Version.MIN or self._upper_bound == Version.MAX:
return False
return self._lower_bound >= self._upper_bound | [
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Diaoul/subliminal | e25589dbcc5b2455bf9f0b49cf2083bb0eae449f | subliminal/score.py | python | compute_score | (subtitle, video, hearing_impaired=None) | return score | Compute the score of the `subtitle` against the `video` with `hearing_impaired` preference.
:func:`compute_score` uses the :meth:`Subtitle.get_matches <subliminal.subtitle.Subtitle.get_matches>` method and
applies the scores (either from :data:`episode_scores` or :data:`movie_scores`) after some processing.
:param subtitle: the subtitle to compute the score of.
:type subtitle: :class:`~subliminal.subtitle.Subtitle`
:param video: the video to compute the score against.
:type video: :class:`~subliminal.video.Video`
:param bool hearing_impaired: hearing impaired preference.
:return: score of the subtitle.
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] | def compute_score(subtitle, video, hearing_impaired=None):
"""Compute the score of the `subtitle` against the `video` with `hearing_impaired` preference.
:func:`compute_score` uses the :meth:`Subtitle.get_matches <subliminal.subtitle.Subtitle.get_matches>` method and
applies the scores (either from :data:`episode_scores` or :data:`movie_scores`) after some processing.
:param subtitle: the subtitle to compute the score of.
:type subtitle: :class:`~subliminal.subtitle.Subtitle`
:param video: the video to compute the score against.
:type video: :class:`~subliminal.video.Video`
:param bool hearing_impaired: hearing impaired preference.
:return: score of the subtitle.
:rtype: int
"""
logger.info('Computing score of %r for video %r with %r', subtitle, video, dict(hearing_impaired=hearing_impaired))
# get the scores dict
scores = get_scores(video)
logger.debug('Using scores %r', scores)
# get the matches
matches = subtitle.get_matches(video)
logger.debug('Found matches %r', matches)
# on hash match, discard everything else
if 'hash' in matches:
logger.debug('Keeping only hash match')
matches &= {'hash'}
# handle equivalent matches
if isinstance(video, Episode):
if 'title' in matches:
logger.debug('Adding title match equivalent')
matches.add('episode')
if 'series_imdb_id' in matches:
logger.debug('Adding series_imdb_id match equivalent')
matches |= {'series', 'year', 'country'}
if 'imdb_id' in matches:
logger.debug('Adding imdb_id match equivalents')
matches |= {'series', 'year', 'country', 'season', 'episode'}
if 'tvdb_id' in matches:
logger.debug('Adding tvdb_id match equivalents')
matches |= {'series', 'year', 'country', 'season', 'episode'}
if 'series_tvdb_id' in matches:
logger.debug('Adding series_tvdb_id match equivalents')
matches |= {'series', 'year', 'country'}
elif isinstance(video, Movie):
if 'imdb_id' in matches:
logger.debug('Adding imdb_id match equivalents')
matches |= {'title', 'year', 'country'}
# handle hearing impaired
if hearing_impaired is not None and subtitle.hearing_impaired == hearing_impaired:
logger.debug('Matched hearing_impaired')
matches.add('hearing_impaired')
# compute the score
score = sum((scores.get(match, 0) for match in matches))
logger.info('Computed score %r with final matches %r', score, matches)
# ensure score is within valid bounds
assert 0 <= score <= scores['hash'] + scores['hearing_impaired']
return score | [
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cogeotiff/rio-tiler | d045ac953238a4246de3cab0361cd1755dab0e90 | rio_tiler/mosaic/methods/defaults.py | python | LastBandHigh.data | (self) | Return data and mask. | Return data and mask. | [
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"""Return data and mask."""
if self.tile is not None:
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sagemath/sagenb | 67a73cbade02639bc08265f28f3165442113ad4d | sagenb/notebook/worksheet.py | python | Worksheet.basic | (self) | return d | Output a dictionary of basic Python objects that defines the
configuration of this worksheet, except the actual cells and
the data files in the DATA directory and images and other data
in the individual cell directories.
EXAMPLES::
sage: import sagenb.notebook.worksheet
sage: W = sagenb.notebook.worksheet.Worksheet('test', 0, tmp_dir(), owner='sage')
sage: sorted((W.basic().items()))
[('auto_publish', False), ('collaborators', []), ('id_number', 0), ('last_change', ('sage', ...)), ('live_3D', False), ('name', u'test'), ('owner', 'sage'), ('pretty_print', False), ('published_id_number', None), ('ratings', []), ('saved_by_info', {}), ('system', None), ('tags', {'sage': [1]}), ('viewers', []), ('worksheet_that_was_published', ('sage', 0))] | Output a dictionary of basic Python objects that defines the
configuration of this worksheet, except the actual cells and
the data files in the DATA directory and images and other data
in the individual cell directories. | [
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"""
Output a dictionary of basic Python objects that defines the
configuration of this worksheet, except the actual cells and
the data files in the DATA directory and images and other data
in the individual cell directories.
EXAMPLES::
sage: import sagenb.notebook.worksheet
sage: W = sagenb.notebook.worksheet.Worksheet('test', 0, tmp_dir(), owner='sage')
sage: sorted((W.basic().items()))
[('auto_publish', False), ('collaborators', []), ('id_number', 0), ('last_change', ('sage', ...)), ('live_3D', False), ('name', u'test'), ('owner', 'sage'), ('pretty_print', False), ('published_id_number', None), ('ratings', []), ('saved_by_info', {}), ('system', None), ('tags', {'sage': [1]}), ('viewers', []), ('worksheet_that_was_published', ('sage', 0))]
"""
try:
published_id_number = int(os.path.split(self.__published_version)[1])
except AttributeError:
published_id_number = None
try:
ws_pub = self.__worksheet_came_from
except AttributeError:
ws_pub = (self.owner(), self.id_number())
try:
saved_by_info = self.__saved_by_info
except AttributeError:
saved_by_info = {}
d = {#############
# basic identification
'name': unicode(self.name()),
'id_number': int(self.id_number()),
#############
# default type of computation system that evaluates cells
'system': self.system(),
#############
# permission: who can look at the worksheet
'owner': self.owner(),
'viewers': self.viewers(),
'collaborators': self.collaborators(),
#############
# publishing worksheets (am I published?); auto-publish me?
# If this worksheet is published, then the published_id_number
# is the id of the published version of this worksheet. Otherwise,
# it is None.
'published_id_number': published_id_number,
# If this is a published worksheet, then ws_pub
# is a 2-tuple ('username', id_number) of a non-published
# worksheet. Otherwise ws_pub is None.
'worksheet_that_was_published': ws_pub,
# Whether or not this worksheet should automatically be
# republished when changed.
'auto_publish': self.is_auto_publish(),
# Appearance: e.g., whether to pretty print this
# worksheet by default
'pretty_print': self.pretty_print(),
# Whether to load 3-D live. Should only be set to
# true by the user as worksheets with more than 1 or 2
# live (interactive) 3-D plots may bog down because of
# javascript overload.
'live_3D': self.live_3D(),
# what other users think of this worksheet: list of
# triples
# (username, rating, comment)
'ratings': self.ratings(),
#???
'saved_by_info':saved_by_info,
# dictionary mapping usernames to list of tags that
# reflect what the tages are for that user. A tag can be
# an integer:
# 0,1,2 (=ARCHIVED,ACTIVE,TRASH),
# or a string (not yet supported).
# This is used for now to fill in the __user_views.
'tags': self.tags(),
# information about when this worksheet was last changed,
# and by whom:
# last_change = ('username', time.time())
'last_change': self.last_change(),
}
return d | [
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enzienaudio/hvcc | 30e47328958d600c54889e2a254c3f17f2b2fd06 | generators/ir2c/SignalLorenz.py | python | SignalLorenz.get_C_header_set | (clazz) | return {"HvSignalLorenz.h"} | [] | def get_C_header_set(clazz):
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Blockstream/satellite | ceb46a00e176c43a6b4170359f6948663a0616bb | blocksatcli/update.py | python | UpdateCache.has_update | (self) | return 'cli_update' in self.data and \
self.data['cli_update'] is not None | Returns whether there is an update available for the CLI | Returns whether there is an update available for the CLI | [
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return 'cli_update' in self.data and \
self.data['cli_update'] is not None | [
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NetEaseGame/iOS-private-api-checker | c9dc24bda7398c0d33553dce2c968d308ee968e7 | app/dbs/inc/Redis.py | python | RedisQueue.put | (self, item) | return self.__db.rpush(self.key, item) | Put item into the queue. | Put item into the queue. | [
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"""Put item into the queue."""
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home-assistant-libs/pytradfri | ef2614b0ccdf628abc3b9559dc00b95ec6e4bd72 | examples/debug_info.py | python | bold | (str) | return "\033[1;30m%s\033[0;0m" % str | Bold. | Bold. | [
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] | def bold(str):
"""Bold."""
return "\033[1;30m%s\033[0;0m" % str | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | ansible/roles/lib_openshift_3.2/library/oc_secret.py | python | Yedit.delete | (self, path) | return (True, self.yaml_dict) | remove path from a dict | remove path from a dict | [
"remove",
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] | def delete(self, path):
''' remove path from a dict'''
try:
entry = Yedit.get_entry(self.yaml_dict, path, self.separator)
except KeyError as _:
entry = None
if entry == None:
return (False, self.yaml_dict)
result = Yedit.remove_entry(self.yaml_dict, path, self.separator)
if not result:
return (False, self.yaml_dict)
return (True, self.yaml_dict) | [
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sciter-sdk/pysciter | f3f4cfe6fd774d2e045b23e79326086cd7288fc6 | sciter/dom.py | python | Element.clear | (self) | return self | Clear content of the element. | Clear content of the element. | [
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"""Clear content of the element."""
ok = _api.SciterSetElementText(self, None, 0)
self._throw_if(ok)
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evilhero/mylar | dbee01d7e48e8c717afa01b2de1946c5d0b956cb | lib/requests/models.py | python | Response.json | (self, **kwargs) | return json.loads(self.text, **kwargs) | Returns the json-encoded content of a response, if any.
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"""Returns the json-encoded content of a response, if any.
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"""
if not self.encoding and len(self.content) > 3:
# No encoding set. JSON RFC 4627 section 3 states we should expect
# UTF-8, -16 or -32. Detect which one to use; If the detection or
# decoding fails, fall back to `self.text` (using chardet to make
# a best guess).
encoding = guess_json_utf(self.content)
if encoding is not None:
try:
return json.loads(self.content.decode(encoding), **kwargs)
except UnicodeDecodeError:
# Wrong UTF codec detected; usually because it's not UTF-8
# but some other 8-bit codec. This is an RFC violation,
# and the server didn't bother to tell us what codec *was*
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pass
return json.loads(self.text, **kwargs) | [
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oracle/graalpython | 577e02da9755d916056184ec441c26e00b70145c | graalpython/lib-python/3/xml/dom/expatbuilder.py | python | FragmentBuilder.external_entity_ref_handler | (self, context, base, systemId, publicId) | [] | def external_entity_ref_handler(self, context, base, systemId, publicId):
if systemId == _FRAGMENT_BUILDER_INTERNAL_SYSTEM_ID:
# this entref is the one that we made to put the subtree
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self.document = self.originalDocument
self.fragment = self.document.createDocumentFragment()
self.curNode = self.fragment
try:
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finally:
self.curNode = old_cur_node
self.document = old_document
self._source = None
return -1
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return ExpatBuilder.external_entity_ref_handler(
self, context, base, systemId, publicId) | [
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amirzed/provisionpad | 51d2a886f46b5090b6fb8b91c18c3043ec36ae42 | src/provisionpad/aws/aws_sg.py | python | AWSsgFuncs.set_sg_http_egress | (self, sgid) | modifies the security group to only ssh ingress and
no egress
Parameters:
sgid (str): the id of the security group
Returns:
- | modifies the security group to only ssh ingress and
no egress | [
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] | def set_sg_http_egress(self, sgid):
'''
modifies the security group to only ssh ingress and
no egress
Parameters:
sgid (str): the id of the security group
Returns:
-
'''
securitygroup = self.ec2.SecurityGroup(sgid)
securitygroup.authorize_egress(
IpPermissions=[
{'IpProtocol': 'tcp',
'FromPort': 80,
'ToPort': 80,
'IpRanges': [{'CidrIp': '0.0.0.0/0'}],
'Ipv6Ranges': [{'CidrIpv6': '::/0'}]},
{'IpProtocol': 'tcp',
'FromPort': 443,
'ToPort': 443,
'IpRanges': [{'CidrIp': '0.0.0.0/0'}],
'Ipv6Ranges': [{'CidrIpv6': '::/0'}]},
]
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1012598167/flask_mongodb_game | 60c7e0351586656ec38f851592886338e50b4110 | python_flask/venv/Lib/site-packages/pip-19.0.3-py3.6.egg/pip/_vendor/urllib3/util/timeout.py | python | Timeout.connect_timeout | (self) | return min(self._connect, self.total) | Get the value to use when setting a connection timeout.
This will be a positive float or integer, the value None
(never timeout), or the default system timeout.
:return: Connect timeout.
:rtype: int, float, :attr:`Timeout.DEFAULT_TIMEOUT` or None | Get the value to use when setting a connection timeout. | [
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This will be a positive float or integer, the value None
(never timeout), or the default system timeout.
:return: Connect timeout.
:rtype: int, float, :attr:`Timeout.DEFAULT_TIMEOUT` or None
"""
if self.total is None:
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return self.total
return min(self._connect, self.total) | [
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FederatedAI/FATE | 32540492623568ecd1afcb367360133616e02fa3 | python/fate_arch/abc/_storage.py | python | StorageSessionABC.get_table | (self, name, namespace) | [] | def get_table(self, name, namespace) -> StorageTableABC:
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cylc/cylc-flow | 5ec221143476c7c616c156b74158edfbcd83794a | cylc/flow/network/graphql.py | python | AstDocArguments.has_arg_val | (self, arg_name, arg_value) | return False | Search through document definitions for argument value.
Args:
arg_name (str): Field argument to search for.
arg_value (Any): Argument value required.
Returns:
Boolean | Search through document definitions for argument value. | [
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] | def has_arg_val(self, arg_name, arg_value):
"""Search through document definitions for argument value.
Args:
arg_name (str): Field argument to search for.
arg_value (Any): Argument value required.
Returns:
Boolean
"""
for components in self.operation_defs.values():
defn = components['definition']
if (
defn.operation not in STRIP_OPS
or getattr(
defn.name, 'value', None) == 'IntrospectionQuery'
):
continue
if self.args_selection_search(
components['definition'].selection_set,
components['variables'],
components['parent_type'],
arg_name,
arg_value,
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return True
return False | [
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pynag/pynag | e72cf7ce2395263e2b3080cae0ece2b03dbbfa27 | pynag/Utils/states.py | python | service_state_to_int | (state) | Converts from strings like OK to states like 0.
Args:
State: string. Can be in the form of 'ok', 'warning', 'critical', '1', etc.
Returns:
Integer. A nagios corresponding to the free text state inputted.
Raises:
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Examples:
>>> service_state_to_int('ok')
0
>>> service_state_to_int('Warning')
1
>>> service_state_to_int('critical')
2
>>> service_state_to_int('UNKNOWN')
3
>>> service_state_to_int('0')
0
>>> service_state_to_int('1')
1
>>> service_state_to_int('2')
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>>> service_state_to_int('3')
3
>>> service_state_to_int('foo')
Traceback (most recent call last):
..
UnknownState: Do not know how to handle state foo | Converts from strings like OK to states like 0. | [
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] | def service_state_to_int(state):
"""Converts from strings like OK to states like 0.
Args:
State: string. Can be in the form of 'ok', 'warning', 'critical', '1', etc.
Returns:
Integer. A nagios corresponding to the free text state inputted.
Raises:
UnknownState: If no match can be found for 'state'.
Examples:
>>> service_state_to_int('ok')
0
>>> service_state_to_int('Warning')
1
>>> service_state_to_int('critical')
2
>>> service_state_to_int('UNKNOWN')
3
>>> service_state_to_int('0')
0
>>> service_state_to_int('1')
1
>>> service_state_to_int('2')
2
>>> service_state_to_int('3')
3
>>> service_state_to_int('foo')
Traceback (most recent call last):
..
UnknownState: Do not know how to handle state foo
"""
text = str(state).lower()
try:
return _SERVICE_TEXT_TO_INT[text]
except KeyError:
raise UnknownState('Do not know how to handle state %s' % state) | [
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krintoxi/NoobSec-Toolkit | 38738541cbc03cedb9a3b3ed13b629f781ad64f6 | NoobSecToolkit - MAC OSX/tools/sqli/plugins/dbms/access/enumeration.py | python | Enumeration.searchTable | (self) | return [] | [] | def searchTable(self):
warnMsg = "on Microsoft Access it is not possible to search tables"
logger.warn(warnMsg)
return [] | [
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DeepX-inc/machina | f93bb6f5aca1feccd71fc509bd6370d2015e2d85 | machina/logger.py | python | _type | (string, has_invisible=True) | The least generic type (type(None), int, float, str, unicode).
>>> _type(None) is type(None)
True
>>> _type("foo") is type("")
True
>>> _type("1") is type(1)
True
>>> _type('\x1b[31m42\x1b[0m') is type(42)
True
>>> _type('\x1b[31m42\x1b[0m') is type(42)
True | The least generic type (type(None), int, float, str, unicode). | [
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] | def _type(string, has_invisible=True):
"""The least generic type (type(None), int, float, str, unicode).
>>> _type(None) is type(None)
True
>>> _type("foo") is type("")
True
>>> _type("1") is type(1)
True
>>> _type('\x1b[31m42\x1b[0m') is type(42)
True
>>> _type('\x1b[31m42\x1b[0m') is type(42)
True
"""
if has_invisible and \
(isinstance(string, _text_type) or isinstance(string, _binary_type)):
string = _strip_invisible(string)
if string is None:
return _none_type
elif hasattr(string, "isoformat"): # datetime.datetime, date, and time
return _text_type
elif _isint(string):
return int
elif _isnumber(string):
return float
elif isinstance(string, _binary_type):
return _binary_type
else:
return _text_type | [
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pyqt/examples | 843bb982917cecb2350b5f6d7f42c9b7fb142ec1 | src/pyqt-official/richtext/textedit/textedit.py | python | TextEdit.closeEvent | (self, e) | [] | def closeEvent(self, e):
if self.maybeSave():
e.accept()
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.5/django/core/servers/basehttp.py | python | ServerHandler.write | (self, data) | write()' callable as specified by PEP 3333 | write()' callable as specified by PEP 3333 | [
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] | def write(self, data):
"""'write()' callable as specified by PEP 3333"""
assert isinstance(data, bytes), "write() argument must be bytestring"
if not self.status:
raise AssertionError("write() before start_response()")
elif not self.headers_sent:
# Before the first output, send the stored headers
self.bytes_sent = len(data) # make sure we know content-length
self.send_headers()
else:
self.bytes_sent += len(data)
# XXX check Content-Length and truncate if too many bytes written?
# If data is too large, socket will choke, so write chunks no larger
# than 32MB at a time.
length = len(data)
if length > 33554432:
offset = 0
while offset < length:
chunk_size = min(33554432, length)
self._write(data[offset:offset+chunk_size])
self._flush()
offset += chunk_size
else:
self._write(data)
self._flush() | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/re.py | python | _compile_repl | (repl, pattern) | return sre_parse.parse_template(repl, pattern) | [] | def _compile_repl(repl, pattern):
# internal: compile replacement pattern
return sre_parse.parse_template(repl, pattern) | [
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kanzure/nanoengineer | 874e4c9f8a9190f093625b267f9767e19f82e6c4 | cad/src/PM/PM_MolecularModelingKit.py | python | PM_MolecularModelingKit.updateElementViewer | (self) | return | Update the view in the element viewer (if present) | Update the view in the element viewer (if present) | [
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"""
Update the view in the element viewer (if present)
"""
if not self.elementViewer:
return
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assert isinstance(self.elementViewer, MMKitView)
self.elementViewer.resetView()
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self.elementViewer.refreshDisplay(self.element, self.viewerDisplay)
return | [
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chribsen/simple-machine-learning-examples | dc94e52a4cebdc8bb959ff88b81ff8cfeca25022 | venv/lib/python2.7/site-packages/sklearn/multiclass.py | python | _partial_fit_ovo_binary | (estimator, X, y, i, j) | return _partial_fit_binary(estimator, X[cond], y_binary) | Partially fit a single binary estimator(one-vs-one). | Partially fit a single binary estimator(one-vs-one). | [
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"""Partially fit a single binary estimator(one-vs-one)."""
cond = np.logical_or(y == i, y == j)
y = y[cond]
y_binary = np.zeros_like(y)
y_binary[y == j] = 1
return _partial_fit_binary(estimator, X[cond], y_binary) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/werkzeug/formparser.py | python | is_valid_multipart_boundary | (boundary) | return _multipart_boundary_re.match(boundary) is not None | Checks if the string given is a valid multipart boundary. | Checks if the string given is a valid multipart boundary. | [
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/site-packages/django/template/defaultfilters.py | python | last | (value) | Returns the last item in a list | Returns the last item in a list | [
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mozman/ezdxf | 59d0fc2ea63f5cf82293428f5931da7e9f9718e9 | src/ezdxf/entities/appdata.py | python | AppData.__contains__ | (self, appid: str) | return uniform_appid(appid) in self.data | Returns ``True`` if application-defined data exist for `appid`. | Returns ``True`` if application-defined data exist for `appid`. | [
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brendano/tweetmotif | 1b0b1e3a941745cd5a26eba01f554688b7c4b27e | everything_else/djfrontend/django-1.0.2/contrib/localflavor/is_/forms.py | python | ISIdNumberField._format | (self, value) | return smart_unicode(value[:6]+'-'+value[6:]) | Takes in the value in canonical form and returns it in the common
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"""
Takes in the value in canonical form and returns it in the common
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/powerwall/binary_sensor.py | python | PowerWallGridServicesActiveSensor.is_on | (self) | return self.coordinator.data[POWERWALL_API_GRID_SERVICES_ACTIVE] | Grid services is active. | Grid services is active. | [
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] | def is_on(self):
"""Grid services is active."""
return self.coordinator.data[POWERWALL_API_GRID_SERVICES_ACTIVE] | [
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exaile/exaile | a7b58996c5c15b3aa7b9975ac13ee8f784ef4689 | plugins/minimode/controls.py | python | RatingControl.do_rating_changed | (self, rating) | Updates the rating of the currently playing track | Updates the rating of the currently playing track | [
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"""
Updates the rating of the currently playing track
"""
if player.PLAYER.current is not None:
player.PLAYER.current.set_rating(rating)
maximum = settings.get_option('rating/maximum', 5)
event.log_event('rating_changed', self, 100 * rating / maximum) | [
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mcedit/pymclevel | 8bf7b3d76479e007a51f3055198a8bcddb626c84 | gprof2dot.py | python | Main.compress_function_name | (self, name) | return name | Compress function name according to the user preferences. | Compress function name according to the user preferences. | [
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if self.options.strip:
name = self.strip_function_name(name)
if self.options.wrap:
name = self.wrap_function_name(name)
# TODO: merge functions with same resulting name
return name | [
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huggingface/transformers | 623b4f7c63f60cce917677ee704d6c93ee960b4b | src/transformers/models/speech_to_text_2/processing_speech_to_text_2.py | python | Speech2Text2Processor.from_pretrained | (cls, pretrained_model_name_or_path, **kwargs) | return cls(feature_extractor=feature_extractor, tokenizer=tokenizer) | r"""
Instantiate a [`Speech2Text2Processor`] from a pretrained Speech2Text2 processor.
<Tip>
This class method is simply calling AutoFeatureExtractor's [`~PreTrainedFeatureExtractor.from_pretrained`] and
Speech2Text2Tokenizer's [`~tokenization_utils_base.PreTrainedTokenizer.from_pretrained`]. Please refer to the
docstrings of the methods above for more information.
</Tip>
Args:
pretrained_model_name_or_path (`str` or `os.PathLike`):
This can be either:
- a string, the *model id* of a pretrained feature_extractor hosted inside a model repo on
huggingface.co. Valid model ids can be located at the root-level, like `bert-base-uncased`, or
namespaced under a user or organization name, like `dbmdz/bert-base-german-cased`.
- a path to a *directory* containing a feature extractor file saved using the
[`~PreTrainedFeatureExtractor.save_pretrained`] method, e.g., `./my_model_directory/`.
- a path or url to a saved feature extractor JSON *file*, e.g.,
`./my_model_directory/preprocessor_config.json`.
**kwargs
Additional keyword arguments passed along to both [`PreTrainedFeatureExtractor`] and
[`PreTrainedTokenizer`] | r"""
Instantiate a [`Speech2Text2Processor`] from a pretrained Speech2Text2 processor. | [
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r"""
Instantiate a [`Speech2Text2Processor`] from a pretrained Speech2Text2 processor.
<Tip>
This class method is simply calling AutoFeatureExtractor's [`~PreTrainedFeatureExtractor.from_pretrained`] and
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Args:
pretrained_model_name_or_path (`str` or `os.PathLike`):
This can be either:
- a string, the *model id* of a pretrained feature_extractor hosted inside a model repo on
huggingface.co. Valid model ids can be located at the root-level, like `bert-base-uncased`, or
namespaced under a user or organization name, like `dbmdz/bert-base-german-cased`.
- a path to a *directory* containing a feature extractor file saved using the
[`~PreTrainedFeatureExtractor.save_pretrained`] method, e.g., `./my_model_directory/`.
- a path or url to a saved feature extractor JSON *file*, e.g.,
`./my_model_directory/preprocessor_config.json`.
**kwargs
Additional keyword arguments passed along to both [`PreTrainedFeatureExtractor`] and
[`PreTrainedTokenizer`]
"""
feature_extractor = AutoFeatureExtractor.from_pretrained(pretrained_model_name_or_path, **kwargs)
tokenizer = Speech2Text2Tokenizer.from_pretrained(pretrained_model_name_or_path, **kwargs)
return cls(feature_extractor=feature_extractor, tokenizer=tokenizer) | [
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AllenInstitute/bmtk | 9c02811a4e1e8695c25de658301d9477bb289298 | bmtk/simulator/core/simulation_config.py | python | SimulationConfig.build_env | (self, force=False) | Creates the folder(s) set in 'output' section, sets up logging and copies over the configuration | Creates the folder(s) set in 'output' section, sets up logging and copies over the configuration | [
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"""Creates the folder(s) set in 'output' section, sets up logging and copies over the configuration"""
if self.env_built and not force:
return
self._set_logging()
self.io.setup_output_dir(self.output_dir, self.log_file, self.overwrite_output)
self.copy_to_output()
self.env_built = True | [
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fab-jul/imgcomp-cvpr | f03ce0bfa846f7ba1bf9b7ba415b082efe5c192c | code/other_codecs.py | python | bpg_image_info | (p) | Relevant format spec:
magic number 4 bytes
header stuff 2 bytes
width variable, ue7
height variable, ue7
picture_data_length variable, ue7. If zero: remaining data is image | Relevant format spec:
magic number 4 bytes
header stuff 2 bytes
width variable, ue7
height variable, ue7
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] | def bpg_image_info(p):
"""
Relevant format spec:
magic number 4 bytes
header stuff 2 bytes
width variable, ue7
height variable, ue7
picture_data_length variable, ue7. If zero: remaining data is image
"""
with open(p, 'rb') as f:
magic = f.read(4)
expected_magic = bytearray.fromhex('425047fb')
assert magic == expected_magic, 'Not a BPG file it seems: {}'.format(p)
header_info = f.read(2)
width = _read_ue7(f)
height = _read_ue7(f)
picture_data_length = _read_ue7(f)
num_bytes_for_picture = _number_of_bytes_until_eof(f) if picture_data_length == 0 else picture_data_length
return BPGImageInfo(width, height, num_bytes_for_picture) | [
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pydata/xarray | 9226c7ac87b3eb246f7a7e49f8f0f23d68951624 | xarray/core/indexing.py | python | create_mask | (indexer, shape, data=None) | return mask | Create a mask for indexing with a fill-value.
Parameters
----------
indexer : ExplicitIndexer
Indexer with -1 in integer or ndarray value to indicate locations in
the result that should be masked.
shape : tuple
Shape of the array being indexed.
data : optional
Data for which mask is being created. If data is a dask arrays, its chunks
are used as a hint for chunks on the resulting mask. If data is a sparse
array, the returned mask is also a sparse array.
Returns
-------
mask : bool, np.ndarray, SparseArray or dask.array.Array with dtype=bool
Same type as data. Has the same shape as the indexing result. | Create a mask for indexing with a fill-value. | [
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"""Create a mask for indexing with a fill-value.
Parameters
----------
indexer : ExplicitIndexer
Indexer with -1 in integer or ndarray value to indicate locations in
the result that should be masked.
shape : tuple
Shape of the array being indexed.
data : optional
Data for which mask is being created. If data is a dask arrays, its chunks
are used as a hint for chunks on the resulting mask. If data is a sparse
array, the returned mask is also a sparse array.
Returns
-------
mask : bool, np.ndarray, SparseArray or dask.array.Array with dtype=bool
Same type as data. Has the same shape as the indexing result.
"""
if isinstance(indexer, OuterIndexer):
key = _outer_to_vectorized_indexer(indexer, shape).tuple
assert not any(isinstance(k, slice) for k in key)
mask = _masked_result_drop_slice(key, data)
elif isinstance(indexer, VectorizedIndexer):
key = indexer.tuple
base_mask = _masked_result_drop_slice(key, data)
slice_shape = tuple(
np.arange(*k.indices(size)).size
for k, size in zip(key, shape)
if isinstance(k, slice)
)
expanded_mask = base_mask[(Ellipsis,) + (np.newaxis,) * len(slice_shape)]
mask = duck_array_ops.broadcast_to(expanded_mask, base_mask.shape + slice_shape)
elif isinstance(indexer, BasicIndexer):
mask = any(k == -1 for k in indexer.tuple)
else:
raise TypeError("unexpected key type: {}".format(type(indexer)))
return mask | [
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USEPA/WNTR | 2f92bab5736da6ef3591fc4b0229ec1ac6cd6fcc | wntr/network/model.py | python | LinkRegistry.psvs | (self) | Generator to get all PSVs
Yields
------
name : str
The name of the valve
link : PSValve
The valve object | Generator to get all PSVs
Yields
------
name : str
The name of the valve
link : PSValve
The valve object | [
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"""Generator to get all PSVs
Yields
------
name : str
The name of the valve
link : PSValve
The valve object
"""
for name in self._psvs:
yield name, self._data[name] | [
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wistbean/learn_python3_spider | 73c873f4845f4385f097e5057407d03dd37a117b | stackoverflow/venv/lib/python3.6/site-packages/twisted/python/util.py | python | IntervalDifferential.__init__ | (self, intervals, default=60) | @type intervals: C{list} of C{int}, C{long}, or C{float} param
@param intervals: The intervals between instants.
@type default: C{int}, C{long}, or C{float}
@param default: The duration to generate if the intervals list
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"""
@type intervals: C{list} of C{int}, C{long}, or C{float} param
@param intervals: The intervals between instants.
@type default: C{int}, C{long}, or C{float}
@param default: The duration to generate if the intervals list
becomes empty.
"""
self.intervals = intervals[:]
self.default = default | [
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dpressel/mead-baseline | 9987e6b37fa6525a4ddc187c305e292a718f59a9 | baseline/reader.py | python | IndexPairLabelReader.convert_to_example_single | (self, vocabs: Dict[str, str], text1: List[str], text2: List[str]) | return example_dict | Convert to a concatenated vector. Useful for BERT-style models
:param vocabs: Vocabs to use
:param text1: First text
:param text2: Second text
:return: An example dict | Convert to a concatenated vector. Useful for BERT-style models | [
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"""Convert to a concatenated vector. Useful for BERT-style models
:param vocabs: Vocabs to use
:param text1: First text
:param text2: Second text
:return: An example dict
"""
example_dict = dict()
for key, vectorizer in self.vectorizers.items():
v = vocabs[key]
vec_1, lengths = vectorizer.run(text1, v)
vec_1 = vec_1[:lengths]
vec_2, lengths = vectorizer.run(text2, v)
vec_2 = vec_2[:lengths]
if self.start_tokens_1:
vec_1 = np.concatenate([np.array([v[x] for x in self.start_tokens_1]), vec_1])
if self.end_tokens_1:
vec_1 = np.concatenate([vec_1, np.array([v[x] for x in self.end_tokens_1])])
if self.start_tokens_2:
vec_2 = np.concatenate([np.array([v[x] for x in self.start_tokens_2]), vec_2])
if self.end_tokens_2:
vec_2 = np.concatenate([vec_2, np.array([v[x] for x in self.end_tokens_2])])
lengths_1 = vec_1.shape[-1]
lengths_2 = vec_2.shape[-1]
total_length = lengths_1 + lengths_2
vec = np.concatenate([vec_1, vec_2])
extend = vectorizer.mxlen - total_length
if extend < 0:
logger.warning(f"total length {total_length} exceeds allocated vectorizer width of {vectorizer.mxlen}")
vec = vec[:vectorizer.mxlen]
elif extend > 0:
vec = np.concatenate([vec, np.full(extend, Offsets.PAD, vec.dtype)])
example_dict[key] = vec
if self.use_token_type:
token_type = np.zeros_like(vec)
token_type[lengths_1:] = 1
example_dict[f"{key}_tt"] = token_type
return example_dict | [
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bslatkin/effectivepython | 4ae6f3141291ea137eb29a245bf889dbc8091713 | example_code/item_39.py | python | PathInputData.read | (self) | [] | def read(self):
with open(self.path) as f:
return f.read() | [
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pyparallel/pyparallel | 11e8c6072d48c8f13641925d17b147bf36ee0ba3 | Lib/site-packages/pandas-0.17.0-py3.3-win-amd64.egg/pandas/computation/pytables.py | python | Expr.evaluate | (self) | return self.condition, self.filter | create and return the numexpr condition and filter | create and return the numexpr condition and filter | [
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raise ValueError("cannot process expression [{0}], [{1}] is not a "
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try:
self.filter = self.terms.prune(FilterBinOp)
except AttributeError:
raise ValueError("cannot process expression [{0}], [{1}] is not a "
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return self.condition, self.filter | [
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mesalock-linux/mesapy | ed546d59a21b36feb93e2309d5c6b75aa0ad95c9 | pypy/module/cpyext/cdatetime.py | python | _PyDate_FromDate | (space, year, month, day, w_type) | return space.call_function(
w_type,
space.newint(year), space.newint(month), space.newint(day)) | Return a datetime.date object with the specified year, month and day. | Return a datetime.date object with the specified year, month and day. | [
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"""Return a datetime.date object with the specified year, month and day.
"""
year = rffi.cast(lltype.Signed, year)
month = rffi.cast(lltype.Signed, month)
day = rffi.cast(lltype.Signed, day)
return space.call_function(
w_type,
space.newint(year), space.newint(month), space.newint(day)) | [
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kaaedit/kaa | e6a8819a5ecba04b7db8303bd5736b5a7c9b822d | kaa/cursor.py | python | Cursor.refresh | (self, top=None, middle=None, bottom=None,
align_always=False) | [] | def refresh(self, top=None, middle=None, bottom=None,
align_always=False):
self.pos, y, x = self.wnd.locate_cursor(
self.pos, top=top, middle=middle, bottom=bottom,
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assert self.pos is not None
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Kozea/pygal | 8267b03535ff55789a30bf66b798302adad88623 | pygal/svg.py | python | Svg.serie | (self, serie) | return dict(
plot=self.node(
self.graph.nodes['plot'],
class_='series serie-%d color-%d' % (serie.index, serie.index)
),
overlay=self.node(
self.graph.nodes['overlay'],
class_='series serie-%d color-%d' % (serie.index, serie.index)
),
text_overlay=self.node(
self.graph.nodes['text_overlay'],
class_='series serie-%d color-%d' % (serie.index, serie.index)
)
) | Make serie node | Make serie node | [
"Make",
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] | def serie(self, serie):
"""Make serie node"""
return dict(
plot=self.node(
self.graph.nodes['plot'],
class_='series serie-%d color-%d' % (serie.index, serie.index)
),
overlay=self.node(
self.graph.nodes['overlay'],
class_='series serie-%d color-%d' % (serie.index, serie.index)
),
text_overlay=self.node(
self.graph.nodes['text_overlay'],
class_='series serie-%d color-%d' % (serie.index, serie.index)
)
) | [
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floooh/fips | 5ce5aebfc7c69778cab03ef5f8830928f2bad6d4 | mod/tools/clion.py | python | write_workspace_settings | (fips_dir, proj_dir, cfg) | write the CLion *.xml files required to open the project | write the CLion *.xml files required to open the project | [
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'''write the CLion *.xml files required to open the project
'''
log.info("=== writing JetBrains CLion config files...")
clion_dir = proj_dir + '/.idea'
if not os.path.isdir(clion_dir):
os.makedirs(clion_dir)
write_clion_module_files(fips_dir, proj_dir, cfg)
write_clion_workspace_file(fips_dir, proj_dir, cfg) | [
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Qiskit/qiskit-terra | b66030e3b9192efdd3eb95cf25c6545fe0a13da4 | qiskit/transpiler/coupling.py | python | CouplingMap.largest_connected_component | (self) | return max(rx.weakly_connected_components(self.graph), key=len) | Return a set of qubits in the largest connected component. | Return a set of qubits in the largest connected component. | [
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"""Return a set of qubits in the largest connected component."""
return max(rx.weakly_connected_components(self.graph), key=len) | [
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freqtrade/freqtrade | 13651fd3be8d5ce8dcd7c94b920bda4e00b75aca | freqtrade/exchange/exchange.py | python | Exchange._init_ccxt | (self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt,
ccxt_kwargs: Dict = {}) | return api | Initialize ccxt with given config and return valid
ccxt instance. | Initialize ccxt with given config and return valid
ccxt instance. | [
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] | def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt,
ccxt_kwargs: Dict = {}) -> ccxt.Exchange:
"""
Initialize ccxt with given config and return valid
ccxt instance.
"""
# Find matching class for the given exchange name
name = exchange_config['name']
if not is_exchange_known_ccxt(name, ccxt_module):
raise OperationalException(f'Exchange {name} is not supported by ccxt')
ex_config = {
'apiKey': exchange_config.get('key'),
'secret': exchange_config.get('secret'),
'password': exchange_config.get('password'),
'uid': exchange_config.get('uid', ''),
}
if ccxt_kwargs:
logger.info('Applying additional ccxt config: %s', ccxt_kwargs)
if self._headers:
# Inject static headers after the above output to not confuse users.
ccxt_kwargs = deep_merge_dicts({'headers': self._headers}, ccxt_kwargs)
if ccxt_kwargs:
ex_config.update(ccxt_kwargs)
try:
api = getattr(ccxt_module, name.lower())(ex_config)
except (KeyError, AttributeError) as e:
raise OperationalException(f'Exchange {name} is not supported') from e
except ccxt.BaseError as e:
raise OperationalException(f"Initialization of ccxt failed. Reason: {e}") from e
self.set_sandbox(api, exchange_config, name)
return api | [
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/Lib/smtplib.py | python | SMTP.rcpt | (self, recip, options=[]) | return self.getreply() | SMTP 'rcpt' command -- indicates 1 recipient for this mail. | SMTP 'rcpt' command -- indicates 1 recipient for this mail. | [
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] | def rcpt(self, recip, options=[]):
"""SMTP 'rcpt' command -- indicates 1 recipient for this mail."""
optionlist = ''
if options and self.does_esmtp:
optionlist = ' ' + ' '.join(options)
self.putcmd("rcpt", "TO:%s%s" % (quoteaddr(recip), optionlist))
return self.getreply() | [
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AlessandroZ/LaZagne | 30623c9138e2387d10f6631007f954f2a4ead06d | Windows/lazagne/config/DPAPI/masterkey.py | python | MasterKeyPool.get_password | (self, guid) | return self.keys.get(guid, {}).get('password') | Returns the password found corresponding to the given GUID. | Returns the password found corresponding to the given GUID. | [
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] | def get_password(self, guid):
"""
Returns the password found corresponding to the given GUID.
"""
return self.keys.get(guid, {}).get('password') | [
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jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/scipy/ndimage/_ni_support.py | python | _normalize_sequence | (input, rank) | return normalized | If input is a scalar, create a sequence of length equal to the
rank by duplicating the input. If input is a sequence,
check if its length is equal to the length of array. | If input is a scalar, create a sequence of length equal to the
rank by duplicating the input. If input is a sequence,
check if its length is equal to the length of array. | [
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"""If input is a scalar, create a sequence of length equal to the
rank by duplicating the input. If input is a sequence,
check if its length is equal to the length of array.
"""
is_str = isinstance(input, string_types)
if hasattr(input, '__iter__') and not is_str:
normalized = list(input)
if len(normalized) != rank:
err = "sequence argument must have length equal to input rank"
raise RuntimeError(err)
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return normalized | [
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aiidateam/aiida-core | c743a335480f8bb3a5e4ebd2463a31f9f3b9f9b2 | aiida/orm/nodes/data/array/projection.py | python | ProjectionData.set_orbitals | (self, **kwargs) | This method is inherited from OrbitalData, but is blocked here.
If used will raise a NotImplementedError | This method is inherited from OrbitalData, but is blocked here.
If used will raise a NotImplementedError | [
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] | def set_orbitals(self, **kwargs): # pylint: disable=arguments-differ
"""
This method is inherited from OrbitalData, but is blocked here.
If used will raise a NotImplementedError
"""
raise NotImplementedError(
'You cannot set orbitals using this class!'
' This class is for setting orbitals and '
' projections only!'
) | [
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jbjorne/TEES | caf19a4a1352ac59f5dc13a8684cc42ce4342d9d | configure.py | python | buildMenus | () | return "Configure TEES" | [] | def buildMenus():
Menu("Classifier", None, [
Option("1", "Compile from source", toggle=False),
Option("i", "Install", handler=Classifiers.SVMMultiClassClassifier.install),
Option("s", "Skip")],
svmMenuInitializer)
Menu("Install Directory", None, [
Option("1", "Change DATAPATH", dataInput="defaultInstallDir"),
Option("2", "Change TEES_SETTINGS", dataInput="configFilePath"),
Option("c", "Continue", "Classifier", isDefault=True, handler=initLocalSettings)],
pathMenuInitializer)
Menu("Configure TEES",
"""
Welcome to using the Turku Event Extraction System (TEES)! In order to work, TEES
depends on a number of other programs, which have to be set up before use.
The classifier (1) is required for all uses of the system. The models (2) are
required for predicting events and together with the preprocessing tools (4)
can be used on any unprocessed text. The corpora (3) are used for testing the
performance of a model or for training a new model.
If you are unsure which components you need, just install everything (the default choice).
You can also rerun configure.py at any time later to install missing components.
To make a choice, type the option's key and press enter, or just press enter for the
default option. The '*' sign indicates the default option and brackets a selectable one.
""",
[
Option("1", "Install classifier (SVM Multiclass)", toggle=True),
Option("2", "Install models (TEES models for BioNLP'09-13 and DDI'11-13)", toggle=True),
Option("3", "Install corpora (BioNLP'09-13 and DDI'11-13)", toggle=True),
Option("4", "Install preprocessing tools (BANNER, BLLIP parser etc)", toggle=True),
Option("c", "Continue and install selected items", "Install Directory", isDefault=True),
Option("q", "Quit", handler=sys.exit),
])
Menu("Models", "Install TEES models\n", [
Option("1", "Redownload already downloaded files", toggle=False),
Option.SPACE,
Option("i", "Install", isDefault=True),
Option("s", "Skip")],
modelsMenuInitializer)
Menu("Corpora", "Install corpora\n", [
Option("1", "Redownload already downloaded files", toggle=False),
Option.SPACE,
Option("2", "Install BioNLP'09 (GENIA) corpus", toggle=False),
Option("3", "Install BioNLP'11 corpora", toggle=False),
Option("4", "Install BioNLP'13 corpora", toggle=False),
Option.SPACE,
Option("5", "Install DDI'11 (Drug-Drug Interactions) corpus", toggle=False),
Option("6", "Install DDI'13 (Drug-Drug Interactions) corpus", toggle=False),
Option.SPACE,
Option("7", "Install BioNLP evaluators", toggle=False),
Option.SPACE,
Option("i", "Install", isDefault=True),
Option("s", "Skip")],
corpusMenuInitializer)
Menu("Tools",
"""
The tools are required for processing unannotated text and can
be used as part of TEES, or independently through their wrappers. For
information and usage conditions, see https://github.com/jbjorne/TEES/wiki/Licenses.
Some of the tools need to be compiled from source, this will take a while.
The external tools used by TEES are:
The GENIA Sentence Splitter of Tokyo University (Tsuruoka Y. et. al.)
The BANNER named entity recognizer by Robert Leaman et. al.
The BLLIP parser of Brown University (Charniak E., Johnson M. et. al.)
The Stanford Parser of the Stanford Natural Language Processing Group
""",
[
Option("1", "Redownload already downloaded files", toggle=False),
Option.SPACE,
Option("2", "Install GENIA Sentence Splitter", toggle=False),
Option("3", "Install BANNER named entity recognizer", toggle=False),
Option("4", "Install BLLIP parser", toggle=False),
Option("5", "Install Stanford Parser", toggle=False),
Option.SPACE,
Option("i", "Install", isDefault=True),
Option("s", "Skip")],
toolsMenuInitializer)
return "Configure TEES" | [
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IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/CPython/27/Lib/lib-tk/ttk.py | python | Treeview.see | (self, item) | Ensure that item is visible.
Sets all of item's ancestors open option to True, and scrolls
the widget if necessary so that item is within the visible
portion of the tree. | Ensure that item is visible. | [
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] | def see(self, item):
"""Ensure that item is visible.
Sets all of item's ancestors open option to True, and scrolls
the widget if necessary so that item is within the visible
portion of the tree."""
self.tk.call(self._w, "see", item) | [
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triaquae/triaquae | bbabf736b3ba56a0c6498e7f04e16c13b8b8f2b9 | TriAquae/models/django_wsgiserver/wsgiserver/wsgiserver2.py | python | WSGIGateway_10.get_environ | (self) | return env | Return a new environ dict targeting the given wsgi.version | Return a new environ dict targeting the given wsgi.version | [
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"""Return a new environ dict targeting the given wsgi.version"""
req = self.req
env = {
# set a non-standard environ entry so the WSGI app can know what
# the *real* server protocol is (and what features to support).
# See http://www.faqs.org/rfcs/rfc2145.html.
'ACTUAL_SERVER_PROTOCOL': req.server.protocol,
'PATH_INFO': req.path,
'QUERY_STRING': req.qs,
'REMOTE_ADDR': req.conn.remote_addr or '',
'REMOTE_PORT': str(req.conn.remote_port or ''),
'REQUEST_METHOD': req.method,
'REQUEST_URI': req.uri,
'SCRIPT_NAME': '',
'SERVER_NAME': req.server.server_name,
# Bah. "SERVER_PROTOCOL" is actually the REQUEST protocol.
'SERVER_PROTOCOL': req.request_protocol,
'SERVER_SOFTWARE': req.server.software,
'wsgi.errors': sys.stderr,
'wsgi.input': req.rfile,
'wsgi.multiprocess': False,
'wsgi.multithread': True,
'wsgi.run_once': False,
'wsgi.url_scheme': req.scheme,
'wsgi.version': (1, 0),
}
if isinstance(req.server.bind_addr, basestring):
# AF_UNIX. This isn't really allowed by WSGI, which doesn't
# address unix domain sockets. But it's better than nothing.
env["SERVER_PORT"] = ""
else:
env["SERVER_PORT"] = str(req.server.bind_addr[1])
# Request headers
for k, v in req.inheaders.iteritems():
env["HTTP_" + k.upper().replace("-", "_")] = v
# CONTENT_TYPE/CONTENT_LENGTH
ct = env.pop("HTTP_CONTENT_TYPE", None)
if ct is not None:
env["CONTENT_TYPE"] = ct
cl = env.pop("HTTP_CONTENT_LENGTH", None)
if cl is not None:
env["CONTENT_LENGTH"] = cl
if req.conn.ssl_env:
env.update(req.conn.ssl_env)
return env | [
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XX-net/XX-Net | a9898cfcf0084195fb7e69b6bc834e59aecdf14f | python3.8.2/Lib/ssl.py | python | SSLObject.session | (self) | return self._sslobj.session | The SSLSession for client socket. | The SSLSession for client socket. | [
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pypa/pip | 7f8a6844037fb7255cfd0d34ff8e8cf44f2598d4 | src/pip/_vendor/distlib/_backport/tarfile.py | python | _Stream.write | (self, s) | Write string s to the stream. | Write string s to the stream. | [
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"""
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self.pos += len(s)
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inspurer/WorkAttendanceSystem | 1221e2d67bdf5bb15fe99517cc3ded58ccb066df | V2.0/venv/Lib/site-packages/pip-9.0.1-py3.5.egg/pip/_vendor/html5lib/_inputstream.py | python | EncodingBytes.skip | (self, chars=spaceCharactersBytes) | return None | Skip past a list of characters | Skip past a list of characters | [
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git-cola/git-cola | b48b8028e0c3baf47faf7b074b9773737358163d | cola/widgets/standard.py | python | WidgetMixin.__init__ | (self) | [] | def __init__(self):
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google/clusterfuzz | f358af24f414daa17a3649b143e71ea71871ef59 | src/clusterfuzz/_internal/config/db_config.py | python | get_value_for_job | (data, target_job_type) | return result | Parses a value for a particular job type. If job type is not found,
return the default value. | Parses a value for a particular job type. If job type is not found,
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CvvT/dumpDex | 92ab3b7e996194a06bf1dd5538a4954e8a5ee9c1 | python/idaapi.py | python | unregister_custom_data_format | (*args) | return _idaapi.unregister_custom_data_format(*args) | unregister_custom_data_format(dtid, dfid) -> bool
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@param dfid: data format id
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ganeti/ganeti | d340a9ddd12f501bef57da421b5f9b969a4ba905 | lib/cli_opts.py | python | _SplitKeyVal | (opt, data, parse_prefixes) | return kv_dict | Convert a KeyVal string into a dict.
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@rtype: dict
@return: {key=val, key=val}
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This function will convert a key=val[,...] string into a dict. Empty
values will be converted specially: keys which have the prefix 'no_'
will have the value=False and the prefix stripped, keys with the prefix
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@type opt: string
@param opt: a string holding the option name for which we process the
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@type data: string
@param data: a string of the format key=val,key=val,...
@type parse_prefixes: bool
@param parse_prefixes: whether to handle prefixes specially
@rtype: dict
@return: {key=val, key=val}
@raises errors.ParameterError: if there are duplicate keys
"""
kv_dict = {}
if data:
for elem in utils.UnescapeAndSplit(data, sep=","):
if "=" in elem:
key, val = elem.split("=", 1)
elif parse_prefixes:
if elem.startswith(NO_PREFIX):
key, val = elem[len(NO_PREFIX):], False
elif elem.startswith(UN_PREFIX):
key, val = elem[len(UN_PREFIX):], None
else:
key, val = elem, True
else:
raise errors.ParameterError("Missing value for key '%s' in option %s" %
(elem, opt))
if key in kv_dict:
raise errors.ParameterError("Duplicate key '%s' in option %s" %
(key, opt))
kv_dict[key] = val
return kv_dict | [
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keiffster/program-y | 8c99b56f8c32f01a7b9887b5daae9465619d0385 | src/programy/storage/stores/sql/store/lookups.py | python | SQLLookupsStore.process_line | (self, name, fields, verbose=False) | return False | [] | def process_line(self, name, fields, verbose=False):
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merkremont/LineVodka | c2fa74107cecf00dd17416b62e4eb579e2c7bbaf | LineAlpha/LineThrift/TalkService.py | python | Client.sendChatChecked | (self, seq, consumer, lastMessageId) | Parameters:
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uqfoundation/dill | 1094a28f685a330181e6894d0294509b1da08f3c | dill/source.py | python | _namespace | (obj) | return qual | _namespace(obj); return namespace hierarchy (as a list of names)
for the given object. For an instance, find the class hierarchy.
For example:
>>> from functools import partial
>>> p = partial(int, base=2)
>>> _namespace(p)
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>>> p = partial(int, base=2)
>>> _namespace(p)
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"""
# mostly for functions and modules and such
#FIXME: 'wrong' for decorators and curried functions
try: #XXX: needs some work and testing on different types
module = qual = str(getmodule(obj)).split()[1].strip('"').strip("'")
qual = qual.split('.')
if ismodule(obj):
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# get name of a lambda, function, etc
name = getname(obj) or obj.__name__ # failing, raise AttributeError
# check special cases (NoneType, ...)
if module in ['builtins','__builtin__']: # BuiltinFunctionType
if _intypes(name): return ['types'] + [name]
return qual + [name] #XXX: can be wrong for some aliased objects
except: pass
# special case: numpy.inf and numpy.nan (we don't want them as floats)
if str(obj) in ['inf','nan','Inf','NaN']: # is more, but are they needed?
return ['numpy'] + [str(obj)]
# mostly for classes and class instances and such
module = getattr(obj.__class__, '__module__', None)
qual = str(obj.__class__)
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except ValueError: pass # str(obj.__class__) made the 'try' unnecessary
qual = qual.split(".")
if module in ['builtins','__builtin__']:
# check special cases (NoneType, Ellipsis, ...)
if qual[-1] == 'ellipsis': qual[-1] = 'EllipsisType'
if _intypes(qual[-1]): module = 'types' #XXX: BuiltinFunctionType
qual = [module] + qual
return qual | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | ansible/roles/lib_openshift_3.2/library/oadm_router.py | python | Yedit.read | (self) | return contents | read from file | read from file | [
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oracle/oci-python-sdk | 3c1604e4e212008fb6718e2f68cdb5ef71fd5793 | src/oci/bds/bds_client.py | python | BdsClient.delete_bds_metastore_configuration | (self, bds_instance_id, metastore_config_id, **kwargs) | Delete the BDS metastore configuration represented by the provided ID.
:param str bds_instance_id: (required)
The OCID of the cluster.
:param str metastore_config_id: (required)
The metastore configuration ID
:param str opc_request_id: (optional)
The client request ID for tracing.
:param str if_match: (optional)
For optimistic concurrency control. In the PUT or DELETE call
for a resource, set the `if-match` parameter to the value of the
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The resource will be updated or deleted only if the etag you
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: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 None
:rtype: :class:`~oci.response.Response`
:example:
Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/bds/delete_bds_metastore_configuration.py.html>`__ to see an example of how to use delete_bds_metastore_configuration API. | Delete the BDS metastore configuration represented by the provided ID. | [
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"""
Delete the BDS metastore configuration represented by the provided ID.
:param str bds_instance_id: (required)
The OCID of the cluster.
:param str metastore_config_id: (required)
The metastore configuration ID
:param str opc_request_id: (optional)
The client request ID for tracing.
:param str if_match: (optional)
For optimistic concurrency control. In the PUT or DELETE call
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The resource will be updated or deleted only if the etag you
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A retry strategy to apply to this specific operation/call. This will override any retry strategy set at the client-level.
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The specifics of the default retry strategy are described `here <https://docs.oracle.com/en-us/iaas/tools/python/latest/sdk_behaviors/retries.html>`__.
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:return: A :class:`~oci.response.Response` object with data of type None
:rtype: :class:`~oci.response.Response`
:example:
Click `here <https://docs.cloud.oracle.com/en-us/iaas/tools/python-sdk-examples/latest/bds/delete_bds_metastore_configuration.py.html>`__ to see an example of how to use delete_bds_metastore_configuration API.
"""
resource_path = "/bdsInstances/{bdsInstanceId}/metastoreConfigs/{metastoreConfigId}"
method = "DELETE"
# Don't accept unknown kwargs
expected_kwargs = [
"retry_strategy",
"opc_request_id",
"if_match"
]
extra_kwargs = [_key for _key in six.iterkeys(kwargs) if _key not in expected_kwargs]
if extra_kwargs:
raise ValueError(
"delete_bds_metastore_configuration got unknown kwargs: {!r}".format(extra_kwargs))
path_params = {
"bdsInstanceId": bds_instance_id,
"metastoreConfigId": metastore_config_id
}
path_params = {k: v for (k, v) in six.iteritems(path_params) if v is not missing}
for (k, v) in six.iteritems(path_params):
if v is None or (isinstance(v, six.string_types) and len(v.strip()) == 0):
raise ValueError('Parameter {} cannot be None, whitespace or empty string'.format(k))
header_params = {
"accept": "application/json",
"content-type": "application/json",
"opc-request-id": kwargs.get("opc_request_id", missing),
"if-match": kwargs.get("if_match", 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_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,
path_params=path_params,
header_params=header_params)
else:
return self.base_client.call_api(
resource_path=resource_path,
method=method,
path_params=path_params,
header_params=header_params) | [
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theotherp/nzbhydra | 4b03d7f769384b97dfc60dade4806c0fc987514e | libs/cookielib.py | python | request_host | (request) | return host.lower() | Return request-host, as defined by RFC 2965.
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url = request.get_full_url()
host = urlparse.urlparse(url)[1]
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"get_header... | https://github.com/theotherp/nzbhydra/blob/4b03d7f769384b97dfc60dade4806c0fc987514e/libs/cookielib.py#L598-L612 | |
dmitry-k/yandex_smart_home | 9d068203d80891bc946618a4cc0a435ee9184d74 | custom_components/yandex_smart_home/capability_mode.py | python | ModeCapability.supported | (self) | return bool(self.supported_yandex_modes) | Test if capability is supported. | Test if capability is supported. | [
"Test",
"if",
"capability",
"is",
"supported",
"."
] | def supported(self) -> bool:
"""Test if capability is supported."""
return bool(self.supported_yandex_modes) | [
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graalvm/mx | 29c0debab406352df3af246be2f8973be5db69ae | mx.py | python | _tmpPomFile | (dist, versionGetter, validateMetadata='none') | return tmp.name | [] | def _tmpPomFile(dist, versionGetter, validateMetadata='none'):
tmp = tempfile.NamedTemporaryFile('w', suffix='.pom', delete=False)
tmp.write(_genPom(dist, versionGetter, validateMetadata))
tmp.close()
return tmp.name | [
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... | https://github.com/graalvm/mx/blob/29c0debab406352df3af246be2f8973be5db69ae/mx.py#L11138-L11142 | |||
PaddlePaddle/PaddleSpeech | 26524031d242876b7fdb71582b0b3a7ea45c7d9d | dataset/thchs30/thchs30.py | python | prepare_dataset | (url, md5sum, target_dir, manifest_path, subset) | Download, unpack and create manifest file. | Download, unpack and create manifest file. | [
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] | def prepare_dataset(url, md5sum, target_dir, manifest_path, subset):
"""Download, unpack and create manifest file."""
datadir = os.path.join(target_dir, subset)
if not os.path.exists(datadir):
filepath = download(url, md5sum, target_dir)
unpack(filepath, target_dir)
else:
print("Skip downloading and unpacking. Data already exists in %s." %
target_dir)
if subset == 'data_thchs30':
create_manifest(datadir, manifest_path) | [
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determined-ai/determined | f637264493acc14f12e66550cb51c520b5d27f6c | harness/determined/tensorboard/util.py | python | find_tb_files | (base_dir: pathlib.Path) | return [file for filetype in tb_file_types for file in base_dir.rglob(filetype)] | Recursively searches through base_dir and subdirectories to find files
needed by Tensorboard, currently matching by filenames and extensions.
This method is used to sync files generated during training to persistent storage.
:param base_dir: starting directory path
:return: list of filepaths within base_dir that are relevant Tensorboard files | Recursively searches through base_dir and subdirectories to find files
needed by Tensorboard, currently matching by filenames and extensions.
This method is used to sync files generated during training to persistent storage. | [
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"generated... | def find_tb_files(base_dir: pathlib.Path) -> List[pathlib.Path]:
"""
Recursively searches through base_dir and subdirectories to find files
needed by Tensorboard, currently matching by filenames and extensions.
This method is used to sync files generated during training to persistent storage.
:param base_dir: starting directory path
:return: list of filepaths within base_dir that are relevant Tensorboard files
"""
if not base_dir.exists():
logging.warning(f"{base_dir} directory does not exist.")
return []
return [file for filetype in tb_file_types for file in base_dir.rglob(filetype)] | [
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/chat/v2/service/user/user_binding.py | python | UserBindingInstance.fetch | (self) | return self._proxy.fetch() | Fetch the UserBindingInstance
:returns: The fetched UserBindingInstance
:rtype: twilio.rest.chat.v2.service.user.user_binding.UserBindingInstance | Fetch the UserBindingInstance | [
"Fetch",
"the",
"UserBindingInstance"
] | def fetch(self):
"""
Fetch the UserBindingInstance
:returns: The fetched UserBindingInstance
:rtype: twilio.rest.chat.v2.service.user.user_binding.UserBindingInstance
"""
return self._proxy.fetch() | [
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