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tomguluson92/PRNet_PyTorch | 2d30e244855a043eec071baf78e8edbab9c11c78 | face3d/morphable_model/load.py | python | load_pncc_code | (path = 'pncc_code.mat') | return pncc_code | load pncc code of BFM
PNCC code: Defined in 'Face Alignment Across Large Poses: A 3D Solution Xiangyu'
download at http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm.
Args:
path: path to data.
Returns:
pncc_code: [nver, 3] | load pncc code of BFM
PNCC code: Defined in 'Face Alignment Across Large Poses: A 3D Solution Xiangyu'
download at http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm.
Args:
path: path to data.
Returns:
pncc_code: [nver, 3] | [
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''' load pncc code of BFM
PNCC code: Defined in 'Face Alignment Across Large Poses: A 3D Solution Xiangyu'
download at http://www.cbsr.ia.ac.cn/users/xiangyuzhu/projects/3DDFA/main.htm.
Args:
path: path to data.
Returns:
pncc_code: [nver, 3]
'''
C = sio.loadmat(path)
pncc_code = C['vertex_code'].T
return pncc_code | [
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nucleic/enaml | 65c2a2a2d765e88f2e1103046680571894bb41ed | enaml/qt/qt_window.py | python | finalize_close | (d) | Finalize the closing of the declaration object.
This is performed as a deferred call so that the window may fully
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""" Finalize the closing of the declaration object.
This is performed as a deferred call so that the window may fully
close before the declaration is potentially destroyed.
"""
d.visible = False
d.closed()
if d.destroy_on_close:
d.destroy() | [
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tribe29/checkmk | 6260f2512e159e311f426e16b84b19d0b8e9ad0c | buildscripts/infrastructure/build-nodes/aws/inventory/ec2.py | python | Ec2Inventory.to_safe | (self, word) | return re.sub(regex + "]", "_", word) | Converts 'bad' characters in a string to underscores so they can be used as Ansible groups | Converts 'bad' characters in a string to underscores so they can be used as Ansible groups | [
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''' Converts 'bad' characters in a string to underscores so they can be used as Ansible groups '''
regex = r"[^A-Za-z0-9\_"
if not self.replace_dash_in_groups:
regex += r"\-"
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Tools/scripts/findnocoding.py | python | get_declaration | (line) | return b'' | [] | def get_declaration(line):
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dropbox/hydra | 101b274e5ac89e1fa196ff6aeb4e1cfc66717341 | copy_state_db.py | python | _mongo_dict_to_str | (d) | return "%s:%d/%s/%s" % (d['host'], d['port'], d['db'], d['collection']) | [] | def _mongo_dict_to_str(d):
if 'id_source' in d:
return d['id_source']['shard_name']
return "%s:%d/%s/%s" % (d['host'], d['port'], d['db'], d['collection']) | [
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apple/coremltools | 141a83af482fcbdd5179807c9eaff9a7999c2c49 | coremltools/converters/onnx/_operators_nd.py | python | _convert_randomuniform | (builder, node, graph, err) | convert to CoreML Random Uniform Static Layer:
https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L4526 | convert to CoreML Random Uniform Static Layer:
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"""
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https://github.com/apple/coremltools/blob/655b3be5cc0d42c3c4fa49f0f0e4a93a26b3e492/mlmodel/format/NeuralNetwork.proto#L4526
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haiwen/seahub | e92fcd44e3e46260597d8faa9347cb8222b8b10d | seahub/two_factor/middleware.py | python | IsVerified.__init__ | (self, user) | [] | def __init__(self, user):
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googlearchive/simian | fb9c43946ff7ba29be417068d6447cfc0adfe9ef | src/simian/mac/munki/handlers/__init__.py | python | StrHeaderDateToDatetime | (str_header_dt) | Converts a string header date to a datetime object.
Args:
str_header_dt: str date from header, i.e. If-Modified-Since.
Returns:
datetime.datetime object, or None if there's a parsing error. | Converts a string header date to a datetime object. | [
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"""Converts a string header date to a datetime object.
Args:
str_header_dt: str date from header, i.e. If-Modified-Since.
Returns:
datetime.datetime object, or None if there's a parsing error.
"""
if not str_header_dt:
return
try:
# NOTE(user): strptime is a py2.5+ feature.
return datetime.datetime.strptime(str_header_dt, HEADER_DATE_FORMAT)
except ValueError:
logging.exception(
'Error parsing If-Modified-Since date: %s', str_header_dt) | [
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opencobra/cobrapy | 0b9ea70cb0ffe78568d445ce3361ad10ec6b02a2 | src/cobra/io/sbml.py | python | _sbase_notes_dict | (sbase, notes) | Set SBase notes based on dictionary.
Parameters
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sbase : libsbml.SBase
SBML object to set notes on
notes : notes object
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"""Set SBase notes based on dictionary.
Parameters
----------
sbase : libsbml.SBase
SBML object to set notes on
notes : notes object
notes information from cobra object
"""
if notes and len(notes) > 0:
tokens = (
['<html xmlns = "http://www.w3.org/1999/xhtml" >']
+ ["<p>{}: {}</p>".format(k, v) for (k, v) in notes.items()]
+ ["</html>"]
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_check(
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eoyilmaz/stalker | a35c041b79d953d00dc2a09cf8206956ca269bef | stalker/models/task.py | python | Task._validate_children | (self, key, child) | return child | validates the given child | validates the given child | [
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"""validates the given child
"""
# just empty the resources list
# do it without a flush
from stalker.db.session import DBSession
with DBSession.no_autoflush:
self.resources = []
# if this is the first ever child we receive
# set total_scheduled_seconds to child's total_logged_seconds
# and set schedule_seconds to child's schedule_seconds
if self.is_leaf:
# remove info from parent
old_schedule_seconds = self.schedule_seconds
self._total_logged_seconds = child.total_logged_seconds
self._schedule_seconds = child.schedule_seconds
# got a parent ?
if self.parent:
# update schedule_seconds
self.parent._schedule_seconds -= old_schedule_seconds
self.parent._schedule_seconds += child.schedule_seconds
# it was a leaf but now a parent, so set the start to max and
# end to min
import pytz
self._start = datetime.datetime.max.replace(tzinfo=pytz.utc)
self._end = datetime.datetime.min.replace(tzinfo=pytz.utc)
# extend start and end dates
self._expand_dates(self, child.start, child.end)
return child | [
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memray/seq2seq-keyphrase | 9145c63ebdc4c3bc431f8091dc52547a46804012 | emolga/dataset/build_dataset.py | python | filter_unk | (X, min_freq=5) | return word2idx, id2word | [] | def filter_unk(X, min_freq=5):
voc = dict()
for l in X:
for w in l:
if w not in voc:
voc[w] = 1
else:
voc[w] += 1
word2idx = dict()
word2idx['<eol>'] = 0
id2word = dict()
id2word[0] = '<eol>'
at = 1
for w in voc:
if voc[w] > min_freq:
word2idx[w] = at
id2word[at] = w
at += 1
word2idx['<unk>'] = at
id2word[at] = '<unk>'
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CedricGuillemet/Imogen | ee417b42747ed5b46cb11b02ef0c3630000085b3 | bin/Lib/calendar.py | python | Calendar.monthdatescalendar | (self, year, month) | return [ dates[i:i+7] for i in range(0, len(dates), 7) ] | Return a matrix (list of lists) representing a month's calendar.
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dates = list(self.itermonthdates(year, month))
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/algebras/free_algebra_element.py | python | FreeAlgebraElement.to_pbw_basis | (self) | return self.parent().pbw_element(self) | Return ``self`` in the Poincaré-Birkhoff-Witt (PBW) basis.
EXAMPLES::
sage: F.<x,y,z> = FreeAlgebra(ZZ, 3)
sage: p = x^2*y + 3*y*x + 2
sage: p.to_pbw_basis()
2*PBW[1] + 3*PBW[y]*PBW[x] + PBW[x^2*y]
+ 2*PBW[x*y]*PBW[x] + PBW[y]*PBW[x]^2 | Return ``self`` in the Poincaré-Birkhoff-Witt (PBW) basis. | [
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Return ``self`` in the Poincaré-Birkhoff-Witt (PBW) basis.
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sage: p = x^2*y + 3*y*x + 2
sage: p.to_pbw_basis()
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leancloud/satori | 701caccbd4fe45765001ca60435c0cb499477c03 | satori-rules/alarm/backends/onealert.py | python | OneAlertBackend.send | (self, ev) | [] | def send(self, ev):
api_key = self.conf.get('api_key')
if not api_key:
return
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}),
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if not resp.ok:
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apache/tvm | 6eb4ed813ebcdcd9558f0906a1870db8302ff1e0 | python/tvm/contrib/mps.py | python | matmul | (lhs, rhs, transa=False, transb=False) | return te.extern(
(m, n),
[lhs, rhs],
lambda ins, outs: tvm.tir.call_packed(
"tvm.contrib.mps.matmul", ins[0], ins[1], outs[0], transa, transb
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name="C",
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This function serves as an example on how to calle external libraries.
Parameters
----------
lhs : Tensor
The left matrix operand
rhs : Tensor
The right matrix operand
transa : bool
Whether transpose lhs
transb : bool
Whether transpose rhs
Returns
-------
C : Tensor
The result tensor. | Create an extern op that compute matrix mult of A and rhs with CrhsLAS | [
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"""Create an extern op that compute matrix mult of A and rhs with CrhsLAS
This function serves as an example on how to calle external libraries.
Parameters
----------
lhs : Tensor
The left matrix operand
rhs : Tensor
The right matrix operand
transa : bool
Whether transpose lhs
transb : bool
Whether transpose rhs
Returns
-------
C : Tensor
The result tensor.
"""
m = lhs.shape[0] if transa is False else lhs.shape[1]
n = rhs.shape[1] if transb is False else rhs.shape[0]
if transa:
m = b
if transb:
n = c
return te.extern(
(m, n),
[lhs, rhs],
lambda ins, outs: tvm.tir.call_packed(
"tvm.contrib.mps.matmul", ins[0], ins[1], outs[0], transa, transb
),
name="C",
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IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/logging/handlers.py | python | RotatingFileHandler.__init__ | (self, filename, mode='a', maxBytes=0, backupCount=0, encoding=None, delay=False) | Open the specified file and use it as the stream for logging.
By default, the file grows indefinitely. You can specify particular
values of maxBytes and backupCount to allow the file to rollover at
a predetermined size.
Rollover occurs whenever the current log file is nearly maxBytes in
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"app.log.1", "app.log.2", ... through to "app.log.5". The file being
written to is always "app.log" - when it gets filled up, it is closed
and renamed to "app.log.1", and if files "app.log.1", "app.log.2" etc.
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Open the specified file and use it as the stream for logging.
By default, the file grows indefinitely. You can specify particular
values of maxBytes and backupCount to allow the file to rollover at
a predetermined size.
Rollover occurs whenever the current log file is nearly maxBytes in
length. If backupCount is >= 1, the system will successively create
new files with the same pathname as the base file, but with extensions
".1", ".2" etc. appended to it. For example, with a backupCount of 5
and a base file name of "app.log", you would get "app.log",
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respectively.
If maxBytes is zero, rollover never occurs.
"""
# If rotation/rollover is wanted, it doesn't make sense to use another
# mode. If for example 'w' were specified, then if there were multiple
# runs of the calling application, the logs from previous runs would be
# lost if the 'w' is respected, because the log file would be truncated
# on each run.
if maxBytes > 0:
mode = 'a'
BaseRotatingHandler.__init__(self, filename, mode, encoding, delay)
self.maxBytes = maxBytes
self.backupCount = backupCount | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/site-packages/pip/_vendor/distlib/manifest.py | python | Manifest.sorted | (self, wantdirs=False) | return [os.path.join(*path_tuple) for path_tuple in
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assert parent not in ('', '/')
add_dir(dirs, parent)
result = set(self.files) # make a copy!
if wantdirs:
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for f in result:
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kindredresearch/SenseAct | e7acbeb7918d0069ea82f0bab09ecb99807fdc9b | senseact/devices/camera/camera_communicator.py | python | CameraCommunicator._actuator_handler | (self) | There's no actuator available for cameras. | There's no actuator available for cameras. | [
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glitchdotcom/WebPutty | 4f5da5eb2b4668cbf3c15cf002feacd1d95d2ef7 | ziplibs/werkzeug/urls.py | python | _safe_urlsplit | (s) | return rv | the urllib.urlsplit cache breaks if it contains unicode and
we cannot control that. So we force type cast that thing back
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"""
rv = urlparse.urlsplit(s)
if type(rv[1]) is not type(s):
try:
return tuple(map(type(s), rv))
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# oh well, we most likely will break later again, but
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CJWorkbench/cjworkbench | e0b878d8ff819817fa049a4126efcbfcec0b50e6 | cjwstate/rendercache/io.py | python | clear_cached_render_result_for_step | (step: Step) | Delete a CachedRenderResult, if it exists.
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This deletes the Parquet file from disk, _then_ empties relevant
database fields and saves them (and only them).
"""
delete_parquet_files_for_step(step.workflow_id, step.id)
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step.cached_render_result_json = b"null"
step.cached_render_result_status = None
step.cached_render_result_columns = None
step.cached_render_result_nrows = None
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awslabs/autogluon | 7309118f2ab1c9519f25acf61a283a95af95842b | core/src/autogluon/core/scheduler/seq_scheduler.py | python | LocalSequentialScheduler.get_best_reward | (self) | return self.searcher.get_best_reward() | Get the best reward from the finished jobs. | Get the best reward from the finished jobs. | [
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sbraz/pymediainfo | 2e5891b457632dc6fcb71f422906c5a6beb175e7 | pymediainfo/__init__.py | python | MediaInfo.menu_tracks | (self) | return self._tracks("Menu") | :return: All :class:`Track`\\s of type ``Menu``.
:rtype: list of :class:`Track`\\s | :return: All :class:`Track`\\s of type ``Menu``.
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albertz/music-player | d23586f5bf657cbaea8147223be7814d117ae73d | mac/pyobjc-framework-Cocoa/Examples/AppKit/WebServicesTool/WSTConnectionWindowControllerClass.py | python | WSTConnectionWindowController.createToolbarItems | (self) | Creates all of the toolbar items that can be made available in
the toolbar. The actual set of available toolbar items is
determined by other mechanisms (user defaults, for example). | Creates all of the toolbar items that can be made available in
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addToolbarItem(self, kWSTReloadContentsToolbarItemIdentifier,
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self._toolbarAllowedItemIdentifiers = [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/helpers/config_entry_oauth2_flow.py | python | AbstractOAuth2Implementation.name | (self) | Name of the implementation. | Name of the implementation. | [
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nosmokingbandit/Watcher3 | 0217e75158b563bdefc8e01c3be7620008cf3977 | lib/sqlalchemy/interfaces.py | python | ConnectionProxy.execute | (self, conn, execute, clauseelement, *multiparams, **params) | return execute(clauseelement, *multiparams, **params) | Intercept high level execute() events. | Intercept high level execute() events. | [
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] | def execute(self, conn, execute, clauseelement, *multiparams, **params):
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amimo/dcc | 114326ab5a082a42c7728a375726489e4709ca29 | androguard/gui/sourcewindow.py | python | SourceWindow.keyPressEvent | (self, event) | Keyboard shortcuts | Keyboard shortcuts | [
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] | def keyPressEvent(self, event):
"""Keyboard shortcuts"""
key = event.key()
if key == QtCore.Qt.Key_X:
self.actionXref()
elif key == QtCore.Qt.Key_G:
self.actionGoto()
elif key == QtCore.Qt.Key_X:
self.actionXref()
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self.actionInfo()
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edfungus/Crouton | ada98b3930192938a48909072b45cb84b945f875 | clients/python_clients/cf_demo_client/cf_env/lib/python2.7/site-packages/werkzeug/wrappers.py | python | ResponseStreamMixin.stream | (self) | return ResponseStream(self) | The response iterable as write-only stream. | The response iterable as write-only stream. | [
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crossbario/crossbar | ed350b7ba1c8421f3640b9c2e94a21ed4cfdff64 | crossbar/common/checkconfig.py | python | check_transport_auth_tls | (config) | Check a WAMP-TLS configuration item. | Check a WAMP-TLS configuration item. | [
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] | def check_transport_auth_tls(config):
"""
Check a WAMP-TLS configuration item.
"""
if 'type' not in config:
raise InvalidConfigException("missing mandatory attribute 'type' in WAMP-TLS configuration")
if config['type'] not in ['static', 'dynamic', 'function']:
raise InvalidConfigException(
"invalid type '{}' in WAMP-TLS configuration - must be one of 'static', 'dynamic', 'function'".format(
config['type']))
if config['type'] == 'static':
# FIXME
pass
elif config['type'] == 'dynamic':
if 'authenticator' not in config:
raise InvalidConfigException(
"missing mandatory attribute 'authenticator' in dynamic WAMP-TLS configuration")
check_or_raise_uri(
config['authenticator'],
"invalid authenticator URI '{}' in dynamic WAMP-TLS configuration".format(config['authenticator']))
elif config['type'] == 'function':
if 'create' not in config:
raise InvalidConfigException("missing mandatory attribute 'create' in function WAMP-TLS configuration")
else:
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playframework/play1 | 0ecac3bc2421ae2dbec27a368bf671eda1c9cba5 | python/Lib/logging/handlers.py | python | BufferingHandler.shouldFlush | (self, record) | return (len(self.buffer) >= self.capacity) | Should the handler flush its buffer?
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aneisch/home-assistant-config | 86e381fde9609cb8871c439c433c12989e4e225d | custom_components/alexa_media/alexa_entity.py | python | get_entity_data | (
login_obj: AlexaLogin, entity_ids: List[Text]
) | return entities | Get and process the entity data into a more usable format. | Get and process the entity data into a more usable format. | [
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) -> AlexaEntityData:
"""Get and process the entity data into a more usable format."""
entities = {}
if entity_ids:
raw = await AlexaAPI.get_entity_state(login_obj, entity_ids=entity_ids)
device_states = raw.get("deviceStates", []) if isinstance(raw, dict) else None
if device_states:
for device_state in device_states:
entity_id = device_state.get("entity", {}).get("entityId")
if entity_id:
entities[entity_id] = []
cap_states = device_state.get("capabilityStates", [])
for cap_state in cap_states:
entities[entity_id].append(json.loads(cap_state))
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tanghaibao/goatools | 647e9dd833695f688cd16c2f9ea18f1692e5c6bc | goatools/go_enrichment.py | python | GOEnrichmentRecord.get_pvalue | (self) | return getattr(self, "p_uncorrected") | Returns pval for 1st method, if it exists. Else returns uncorrected pval. | Returns pval for 1st method, if it exists. Else returns uncorrected pval. | [
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IJDykeman/wangTiles | 7c1ee2095ebdf7f72bce07d94c6484915d5cae8b | experimental_code/tiles_3d/venv_mac_py3/lib/python2.7/site-packages/pip/_internal/req/req_install.py | python | InstallRequirement.populate_link | (self, finder, upgrade, require_hashes) | Ensure that if a link can be found for this, that it is found.
Note that self.link may still be None - if Upgrade is False and the
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Note that self.link may still be None - if Upgrade is False and the
requirement is already installed.
If require_hashes is True, don't use the wheel cache, because cached
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"""
if self.link is None:
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old_link = self.link
self.link = self._wheel_cache.get(self.link, self.name)
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radlab/sparrow | afb8efadeb88524f1394d1abe4ea66c6fd2ac744 | deploy/third_party/boto-2.1.1/boto/storage_uri.py | python | BucketStorageUri.clone_replace_name | (self, new_name) | return BucketStorageUri(self.scheme, self.bucket_name, new_name,
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@param new_name: new object name
"""
if not self.bucket_name:
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missionpinball/mpf | 8e6b74cff4ba06d2fec9445742559c1068b88582 | mpf/platforms/rpi/rpi.py | python | RaspberryPiHardwarePlatform.configure_switch | (self, number: str, config: SwitchConfig, platform_config: dict) | return RpiSwitch(config, number, self) | Configure a switch with pull up. | Configure a switch with pull up. | [
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] | def configure_switch(self, number: str, config: SwitchConfig, platform_config: dict) -> "SwitchPlatformInterface":
"""Configure a switch with pull up."""
# set input
self.send_command(self.pi.set_mode(int(number), apigpio.INPUT))
# configure pull up
self.send_command(self.pi.set_pull_up_down(int(number), apigpio.PUD_UP))
if config.debounce:
# configure debounce to 2ms
self.send_command(self.pi.set_glitch_filter(int(number), 2000))
else:
# configure debounce to 100us
self.send_command(self.pi.set_glitch_filter(int(number), 100))
# add callback
self.send_command(self.pi.add_callback(int(number), apigpio.EITHER_EDGE, self._switch_changed))
return RpiSwitch(config, number, self) | [
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wiseman/mavelous | eef41c096cc282bb3acd33a747146a88d2bd1eee | modules/kml.py | python | mavlink_packet | (m) | handle an incoming mavlink packet | handle an incoming mavlink packet | [
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state = g_module_context.mmap_state | [
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inasafe/inasafe | 355eb2ce63f516b9c26af0c86a24f99e53f63f87 | safe/gui/tools/wizard/step_fc05_functions2.py | python | StepFcFunctions2.on_tblFunctions2_itemSelectionChanged | (self) | Choose selected hazard x exposure constraints combination.
.. note:: This is an automatic Qt slot
executed when the category selection changes. | Choose selected hazard x exposure constraints combination. | [
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] | def on_tblFunctions2_itemSelectionChanged(self):
"""Choose selected hazard x exposure constraints combination.
.. note:: This is an automatic Qt slot
executed when the category selection changes.
"""
functions = self.selected_functions_2()
if not functions:
self.lblAvailableFunctions2.clear()
else:
text = self.tr('Available functions:') + ' ' + ', '.join(
[f['name'] for f in functions])
self.lblAvailableFunctions2.setText(text)
self.parent.pbnNext.setEnabled(True)
# Put a dot to the selected cell - note there is no way
# to center an icon without using a custom ItemDelegate
selection = self.tblFunctions2.selectedItems()
selItem = (len(selection) == 1) and selection[0] or None
for row in range(self.tblFunctions2.rowCount()):
for column in range(self.tblFunctions2.columnCount()):
item = self.tblFunctions2.item(row, column)
item.setText((item == selItem) and '•' or '') | [
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polychromatic/polychromatic | 106bc3fdfda650a732341bf45e0d20fd281cc521 | pylib/controller/editor.py | python | VisualEffectEditor._show_file_error | (self) | Alias to the _show_file_error() function from the Effects tab. | Alias to the _show_file_error() function from the Effects tab. | [
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"""
Alias to the _show_file_error() function from the Effects tab.
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self.appdata.tab_effects._show_file_error()
self.closeEvent() | [
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wanggrun/Adaptively-Connected-Neural-Networks | e27066ef52301bdafa5932f43af8feeb23647edb | tensorpack-installed/build/lib/tensorpack/dataflow/base.py | python | RNGDataFlow.reset_state | (self) | Reset the RNG | Reset the RNG | [
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] | def reset_state(self):
""" Reset the RNG """
self.rng = get_rng(self) | [
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unode/firefox_decrypt | a3daadc09603a6cf8c4b7e49a59776340bc885e7 | firefox_decrypt.py | python | ask_section | (sections: ConfigParser) | return final_choice | Prompt the user which profile should be used for decryption | Prompt the user which profile should be used for decryption | [
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"""
Prompt the user which profile should be used for decryption
"""
# Do not ask for choice if user already gave one
choice = "ASK"
while choice not in sections:
sys.stderr.write("Select the Mozilla profile you wish to decrypt\n")
print_sections(sections)
try:
choice = input()
except EOFError:
LOG.error("Could not read Choice, got EOF")
raise Exit(Exit.READ_GOT_EOF)
try:
final_choice = sections[choice]
except KeyError:
LOG.error("Profile No. %s does not exist!", choice)
raise Exit(Exit.NO_SUCH_PROFILE)
LOG.debug("Profile selection matched %s", final_choice)
return final_choice | [
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tensorlayer/tensorlayer | cb4eb896dd063e650ef22533ed6fa6056a71cad5 | examples/reinforcement_learning/tutorial_wrappers.py | python | FireResetEnv.__init__ | (self, env) | Take action on reset for environments that are fixed until firing. | Take action on reset for environments that are fixed until firing. | [
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"""Take action on reset for environments that are fixed until firing."""
super(FireResetEnv, self).__init__(env)
assert env.unwrapped.get_action_meanings()[1] == 'FIRE'
assert len(env.unwrapped.get_action_meanings()) >= 3 | [
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TensorVision/TensorVision | d971ed2b7d8fe1c0caf407eb7bdaebc0838e5801 | tensorvision/utils.py | python | cfg | () | return None | General configuration values. | General configuration values. | [
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openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/scrapy/scrapy/xlib/pydispatch/saferef.py | python | BoundMethodWeakref.calculateKey | ( cls, target ) | return (id(target.im_self),id(target.im_func)) | Calculate the reference key for this reference
Currently this is a two-tuple of the id()'s of the
target object and the target function respectively. | Calculate the reference key for this reference | [
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"""Calculate the reference key for this reference
Currently this is a two-tuple of the id()'s of the
target object and the target function respectively.
"""
return (id(target.im_self),id(target.im_func)) | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/appengine/ext/mapreduce/input_readers.py | python | _GoogleCloudStorageInputReader.split_input | (cls, mapper_spec) | return readers | Returns a list of input readers.
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"""Returns a list of input readers.
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are fewer files than shards, fewer than the requested number of shards will
be used. Input files are currently never split (although for some formats
could be and may be split in a future implementation).
Args:
mapper_spec: an instance of model.MapperSpec.
Returns:
A list of InputReaders. None when no input data can be found.
"""
reader_spec = cls.get_params(mapper_spec, allow_old=False)
bucket = reader_spec[cls.BUCKET_NAME_PARAM]
filenames = reader_spec[cls.OBJECT_NAMES_PARAM]
delimiter = reader_spec.get(cls.DELIMITER_PARAM)
account_id = reader_spec.get(cls._ACCOUNT_ID_PARAM)
buffer_size = reader_spec.get(cls.BUFFER_SIZE_PARAM)
fail_on_missing_input = reader_spec.get(cls.FAIL_ON_MISSING_INPUT)
all_filenames = []
for filename in filenames:
if filename.endswith("*"):
all_filenames.extend(
[file_stat.filename for file_stat in cloudstorage.listbucket(
"/" + bucket + "/" + filename[:-1], delimiter=delimiter,
_account_id=account_id)])
else:
all_filenames.append("/%s/%s" % (bucket, filename))
readers = []
for shard in range(0, mapper_spec.shard_count):
shard_filenames = all_filenames[shard::mapper_spec.shard_count]
if shard_filenames:
reader = cls(
shard_filenames, buffer_size=buffer_size, _account_id=account_id,
delimiter=delimiter)
reader._fail_on_missing_input = fail_on_missing_input
readers.append(reader)
return readers | [
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dmlc/dgl | 8d14a739bc9e446d6c92ef83eafe5782398118de | python/dgl/_deprecate/runtime/ir/program.py | python | set_current_prog | (program) | Set the current program. | Set the current program. | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter4-NaiveBayes/venv/Lib/site-packages/pip/cmdoptions.py | python | _merge_hash | (option, opt_str, value, parser) | Given a value spelled "algo:digest", append the digest to a list
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"""Given a value spelled "algo:digest", append the digest to a list
pointed to in a dict by the algo name."""
if not parser.values.hashes:
parser.values.hashes = {}
try:
algo, digest = value.split(':', 1)
except ValueError:
parser.error('Arguments to %s must be a hash name '
'followed by a value, like --hash=sha256:abcde...' %
opt_str)
if algo not in STRONG_HASHES:
parser.error('Allowed hash algorithms for %s are %s.' %
(opt_str, ', '.join(STRONG_HASHES)))
parser.values.hashes.setdefault(algo, []).append(digest) | [
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golemhq/golem | 84f51478b169cdeab73fc7e2a22a64d0a2a29263 | golem/execution_runner/execution_runner.py | python | ExecutionRunner._select_environments | (self, project_envs) | return envs | Define the environments to use for the test.
The test can have a list of environments set from 2 places:
- using the -e|--environments CLI argument
- suite `environments` variable
If both of these are empty try using the first env if there
are any envs defined for the project. Otherwise just return ['']
meaning: no envs will be used. | Define the environments to use for the test. | [
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"""Define the environments to use for the test.
The test can have a list of environments set from 2 places:
- using the -e|--environments CLI argument
- suite `environments` variable
If both of these are empty try using the first env if there
are any envs defined for the project. Otherwise just return ['']
meaning: no envs will be used.
"""
if self.cli_args.envs:
# use the environments passed through command line
envs = self.cli_args.envs
elif self.suite.envs:
# use the environments defined in the suite
envs = self.suite.envs
elif project_envs:
# if there are available envs, use the first by default
envs = [sorted(project_envs)[0]]
else:
envs = []
return envs | [
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/template/context.py | python | RequestContext.new | (self, values=None) | return new_context | [] | def new(self, values=None):
new_context = super(RequestContext, self).new(values)
# This is for backwards-compatibility: RequestContexts created via
# Context.new don't include values from context processors.
if hasattr(new_context, '_processors_index'):
del new_context._processors_index
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/homematic/cover.py | python | setup_platform | (
hass: HomeAssistant,
config: ConfigType,
add_entities: AddEntitiesCallback,
discovery_info: DiscoveryInfoType | None = None,
) | Set up the platform. | Set up the platform. | [
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] | def setup_platform(
hass: HomeAssistant,
config: ConfigType,
add_entities: AddEntitiesCallback,
discovery_info: DiscoveryInfoType | None = None,
) -> None:
"""Set up the platform."""
if discovery_info is None:
return
devices: list[HMCover] = []
for conf in discovery_info[ATTR_DISCOVER_DEVICES]:
if conf[ATTR_DEVICE_TYPE] in HM_GARAGE:
devices.append(HMGarage(conf))
else:
devices.append(HMCover(conf))
add_entities(devices, True) | [
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | ansible/roles/lib_oa_openshift/library/oc_volume.py | python | Utils.create_tmp_file_from_contents | (rname, data, ftype='yaml') | return tmp | create a file in tmp with name and contents | create a file in tmp with name and contents | [
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''' create a file in tmp with name and contents'''
tmp = Utils.create_tmpfile(prefix=rname)
if ftype == 'yaml':
# AUDIT:no-member makes sense here due to ruamel.YAML/PyYAML usage
# pylint: disable=no-member
if hasattr(yaml, 'RoundTripDumper'):
Utils._write(tmp, yaml.dump(data, Dumper=yaml.RoundTripDumper))
else:
Utils._write(tmp, yaml.safe_dump(data, default_flow_style=False))
elif ftype == 'json':
Utils._write(tmp, json.dumps(data))
else:
Utils._write(tmp, data)
# Register cleanup when module is done
atexit.register(Utils.cleanup, [tmp])
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tomplus/kubernetes_asyncio | f028cc793e3a2c519be6a52a49fb77ff0b014c9b | kubernetes_asyncio/client/models/v1_component_status.py | python | V1ComponentStatus.kind | (self) | return self._kind | Gets the kind of this V1ComponentStatus. # noqa: E501
Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds # noqa: E501
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Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds # noqa: E501
:return: The kind of this V1ComponentStatus. # noqa: E501
:rtype: str
"""
return self._kind | [
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jgagneastro/coffeegrindsize | 22661ebd21831dba4cf32bfc6ba59fe3d49f879c | App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/pandas/core/resample.py | python | Resampler.interpolate | (self, method='linear', axis=0, limit=None, inplace=False,
limit_direction='forward', limit_area=None,
downcast=None, **kwargs) | return result.interpolate(method=method, axis=axis, limit=limit,
inplace=inplace,
limit_direction=limit_direction,
limit_area=limit_area,
downcast=downcast, **kwargs) | Interpolate values according to different methods.
.. versionadded:: 0.18.1 | Interpolate values according to different methods. | [
"Interpolate",
"values",
"according",
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"different",
"methods",
"."
] | def interpolate(self, method='linear', axis=0, limit=None, inplace=False,
limit_direction='forward', limit_area=None,
downcast=None, **kwargs):
"""
Interpolate values according to different methods.
.. versionadded:: 0.18.1
"""
result = self._upsample(None)
return result.interpolate(method=method, axis=axis, limit=limit,
inplace=inplace,
limit_direction=limit_direction,
limit_area=limit_area,
downcast=downcast, **kwargs) | [
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viewflow/viewflow | 2389bd379a2ab22cc277585df7c09514e273541d | viewflow/nodes/switch.py | python | Switch.Default | (self, node) | return result | Last node to activate if no one other succeed. | Last node to activate if no one other succeed. | [
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"""Last node to activate if no one other succeed."""
result = copy(self)
result._activate_next.append((node, None))
return result | [
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NVIDIA/DeepLearningExamples | 589604d49e016cd9ef4525f7abcc9c7b826cfc5e | TensorFlow/Detection/SSD/models/research/object_detection/exporter.py | python | profile_inference_graph | (graph) | Profiles the inference graph.
Prints model parameters and computation FLOPs given an inference graph.
BatchNorms are excluded from the parameter count due to the fact that
BatchNorms are usually folded. BatchNorm, Initializer, Regularizer
and BiasAdd are not considered in FLOP count.
Args:
graph: the inference graph. | Profiles the inference graph. | [
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] | def profile_inference_graph(graph):
"""Profiles the inference graph.
Prints model parameters and computation FLOPs given an inference graph.
BatchNorms are excluded from the parameter count due to the fact that
BatchNorms are usually folded. BatchNorm, Initializer, Regularizer
and BiasAdd are not considered in FLOP count.
Args:
graph: the inference graph.
"""
tfprof_vars_option = (
tf.contrib.tfprof.model_analyzer.TRAINABLE_VARS_PARAMS_STAT_OPTIONS)
tfprof_flops_option = tf.contrib.tfprof.model_analyzer.FLOAT_OPS_OPTIONS
# Batchnorm is usually folded during inference.
tfprof_vars_option['trim_name_regexes'] = ['.*BatchNorm.*']
# Initializer and Regularizer are only used in training.
tfprof_flops_option['trim_name_regexes'] = [
'.*BatchNorm.*', '.*Initializer.*', '.*Regularizer.*', '.*BiasAdd.*'
]
tf.contrib.tfprof.model_analyzer.print_model_analysis(
graph,
tfprof_options=tfprof_vars_option)
tf.contrib.tfprof.model_analyzer.print_model_analysis(
graph,
tfprof_options=tfprof_flops_option) | [
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hhatto/autopep8 | 577774fa57619ea87682c0999d9e91cd1cdb7425 | autopep8.py | python | _get_indentword | (source) | return indent_word | Return indentation type. | Return indentation type. | [
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"""Return indentation type."""
indent_word = ' ' # Default in case source has no indentation
try:
for t in generate_tokens(source):
if t[0] == token.INDENT:
indent_word = t[1]
break
except (SyntaxError, tokenize.TokenError):
pass
return indent_word | [
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gem/oq-engine | 1bdb88f3914e390abcbd285600bfd39477aae47c | openquake/commonlib/hazard_writers.py | python | gen_gmfs | (gmf_set) | Generate GMF nodes from a gmf_set
:param gmf_set: a sequence of GMF objects with attributes
imt, sa_period, sa_damping, event_id and containing a list
of GMF nodes with attributes gmv and location. The nodes
are sorted by lon/lat. | Generate GMF nodes from a gmf_set
:param gmf_set: a sequence of GMF objects with attributes
imt, sa_period, sa_damping, event_id and containing a list
of GMF nodes with attributes gmv and location. The nodes
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Generate GMF nodes from a gmf_set
:param gmf_set: a sequence of GMF objects with attributes
imt, sa_period, sa_damping, event_id and containing a list
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are sorted by lon/lat.
"""
for gmf in gmf_set:
gmf_node = Node('gmf')
gmf_node['IMT'] = gmf.imt
if gmf.imt == 'SA':
gmf_node['saPeriod'] = str(gmf.sa_period)
gmf_node['saDamping'] = str(gmf.sa_damping)
gmf_node['ruptureId'] = gmf.event_id
sorted_nodes = sorted(gmf)
gmf_node.nodes = (
Node('node', dict(gmv=n.gmv, lon=n.location.x, lat=n.location.y))
for n in sorted_nodes)
yield gmf_node | [
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Digital-Sapphire/PyUpdater | d408f54a38ab63ab5f4bcf6471ac1a546357b29f | pyupdater/core/package_handler/__init__.py | python | PackageHandler.process_packages | (self, report_errors=False) | Gets a list of updates to process. Adds the name of an
update to the version file if not already present. Processes
all packages. Updates the version file meta-data. Then writes
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all packages. Updates the version file meta-data. Then writes
version file back to disk.
"""
if self.patch_support:
log.info("Patch support enabled")
else:
log.info("Patch support disabled")
# Getting a list of meta data from all packages in the
# pyu-data/new directory. Also create a patch manifest
# to create patches.
pkg_manifest, patch_manifest = self._get_package_list(report_errors)
patches = PackageHandler._make_patches(patch_manifest)
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self._write_config_to_file(self.config)
self._move_packages(pkg_manifest) | [
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clinton-hall/nzbToMedia | 27669389216902d1085660167e7bda0bd8527ecf | libs/common/mutagen/apev2.py | python | _APEValue._validate | (self, value) | Returns validated value or raises TypeError/ValueErrr | Returns validated value or raises TypeError/ValueErrr | [
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scikit-learn/scikit-learn | 1d1aadd0711b87d2a11c80aad15df6f8cf156712 | sklearn/covariance/_shrunk_covariance.py | python | ledoit_wolf | (X, *, assume_centered=False, block_size=1000) | return shrunk_cov, shrinkage | Estimates the shrunk Ledoit-Wolf covariance matrix.
Read more in the :ref:`User Guide <shrunk_covariance>`.
Parameters
----------
X : array-like of shape (n_samples, n_features)
Data from which to compute the covariance estimate
assume_centered : bool, default=False
If True, data will not be centered before computation.
Useful to work with data whose mean is significantly equal to
zero but is not exactly zero.
If False, data will be centered before computation.
block_size : int, default=1000
Size of blocks into which the covariance matrix will be split.
This is purely a memory optimization and does not affect results.
Returns
-------
shrunk_cov : ndarray of shape (n_features, n_features)
Shrunk covariance.
shrinkage : float
Coefficient in the convex combination used for the computation
of the shrunk estimate.
Notes
-----
The regularized (shrunk) covariance is:
(1 - shrinkage) * cov + shrinkage * mu * np.identity(n_features)
where mu = trace(cov) / n_features | Estimates the shrunk Ledoit-Wolf covariance matrix. | [
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"""Estimates the shrunk Ledoit-Wolf covariance matrix.
Read more in the :ref:`User Guide <shrunk_covariance>`.
Parameters
----------
X : array-like of shape (n_samples, n_features)
Data from which to compute the covariance estimate
assume_centered : bool, default=False
If True, data will not be centered before computation.
Useful to work with data whose mean is significantly equal to
zero but is not exactly zero.
If False, data will be centered before computation.
block_size : int, default=1000
Size of blocks into which the covariance matrix will be split.
This is purely a memory optimization and does not affect results.
Returns
-------
shrunk_cov : ndarray of shape (n_features, n_features)
Shrunk covariance.
shrinkage : float
Coefficient in the convex combination used for the computation
of the shrunk estimate.
Notes
-----
The regularized (shrunk) covariance is:
(1 - shrinkage) * cov + shrinkage * mu * np.identity(n_features)
where mu = trace(cov) / n_features
"""
X = check_array(X)
# for only one feature, the result is the same whatever the shrinkage
if len(X.shape) == 2 and X.shape[1] == 1:
if not assume_centered:
X = X - X.mean()
return np.atleast_2d((X ** 2).mean()), 0.0
if X.ndim == 1:
X = np.reshape(X, (1, -1))
warnings.warn(
"Only one sample available. You may want to reshape your data array"
)
n_features = X.size
else:
_, n_features = X.shape
# get Ledoit-Wolf shrinkage
shrinkage = ledoit_wolf_shrinkage(
X, assume_centered=assume_centered, block_size=block_size
)
emp_cov = empirical_covariance(X, assume_centered=assume_centered)
mu = np.sum(np.trace(emp_cov)) / n_features
shrunk_cov = (1.0 - shrinkage) * emp_cov
shrunk_cov.flat[:: n_features + 1] += shrinkage * mu
return shrunk_cov, shrinkage | [
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boostorg/build | aaa95bba19a7acb07badb1929737c67583b14ba0 | src/build/feature.py | python | free_features | () | return __free_features | Returns all free features. | Returns all free features. | [
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gkrizek/bash-lambda-layer | 703b0ade8174022d44779d823172ab7ac33a5505 | bin/botocore/config.py | python | Config.merge | (self, other_config) | return Config(**config_options) | Merges the config object with another config object
This will merge in all non-default values from the provided config
and return a new config object
:type other_config: botocore.config.Config
:param other config: Another config object to merge with. The values
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:type other_config: botocore.config.Config
:param other config: Another config object to merge with. The values
in the provided config object will take precedence in the merging
:returns: A config object built from the merged values of both
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"""
# Make a copy of the current attributes in the config object.
config_options = copy.copy(self._user_provided_options)
# Merge in the user provided options from the other config
config_options.update(other_config._user_provided_options)
# Return a new config object with the merged properties.
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mesalock-linux/mesapy | ed546d59a21b36feb93e2309d5c6b75aa0ad95c9 | lib-python/2.7/lib2to3/fixer_base.py | python | BaseFix.warning | (self, node, reason) | Used for warning the user about possible uncertainty in the
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criteo/biggraphite | 1f647ada6b3f2b2f3fb4e59d326f73a2c891fc30 | biggraphite/glob_utils.py | python | CharNotIn.__init__ | (self, values) | Initializes the CharNotIn. | Initializes the CharNotIn. | [
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morganstanley/treadmill | f18267c665baf6def4374d21170198f63ff1cde4 | lib/python/treadmill/cli/admin/master.py | python | monitor_group | (parent) | App monitor CLI group | App monitor CLI group | [
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"""App monitor CLI group"""
formatter = cli.make_formatter('app-monitor')
@parent.group()
def monitor():
"""Manage app monitors configuration.
"""
@monitor.command()
@click.option('-n', '--count', type=int, help='Instance count')
@click.option('-p', '--policy', type=click.Choice(['fifo', 'lifo']),
help='Instance scale policy: fifo (remove oldest first), '
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@click.argument('app')
@cli.admin.ON_EXCEPTIONS
def configure(app, count, policy):
"""Create, get or modify an app monitor configuration"""
zkclient = context.GLOBAL.zk.conn
options = {}
if count is not None:
options['count'] = count
if policy is not None:
options['policy'] = policy
existing = masterapi.get_appmonitor(zkclient, app)
# reconfigure if any of the parameters is specified
if options:
if count is None and existing is not None:
count = existing.get('count')
if policy is None and existing is not None:
policy = existing.get('policy')
data = masterapi.update_appmonitor(zkclient, app, count, policy)
else:
data = existing
cli.out(formatter(data))
@monitor.command()
@click.argument('app')
@cli.admin.ON_EXCEPTIONS
def delete(app):
"""Deletes app monitor"""
masterapi.delete_appmonitor(context.GLOBAL.zk.conn, app)
@monitor.command(name='list')
def _list():
"""List all configured monitors"""
zkclient = context.GLOBAL.zk.conn
suspended_monitors = masterapi.get_suspended_appmonitors(zkclient)
monitors = [
masterapi.get_appmonitor(
zkclient, app,
suspended_monitors=suspended_monitors,
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for app in masterapi.appmonitors(zkclient)
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cli.out(formatter(monitors))
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clinton-hall/nzbToMedia | 27669389216902d1085660167e7bda0bd8527ecf | libs/common/chardet/charsetprober.py | python | CharSetProber.filter_international_words | (buf) | return filtered | We define three types of bytes:
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international: international characters [\x80-\xFF]
marker: everything else [^a-zA-Z\x80-\xFF]
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words = re.findall(b'[a-zA-Z]*[\x80-\xFF]+[a-zA-Z]*[^a-zA-Z\x80-\xFF]?',
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for word in words:
filtered.extend(word[:-1])
# If the last character in the word is a marker, replace it with a
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last_char = word[-1:]
if not last_char.isalpha() and last_char < b'\x80':
last_char = b' '
filtered.extend(last_char)
return filtered | [
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Kozea/cairocffi | 2473d1bb82a52ca781edec595a95951509db2969 | cairocffi/context.py | python | Context.get_dash | (self) | return list(dashes), offset[0] | Return the current dash pattern.
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dashes = ffi.new('double[]', cairo.cairo_get_dash_count(self._pointer))
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cairo.cairo_get_dash(self._pointer, dashes, offset)
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Unidata/MetPy | 1153590f397ae23adfea66c4adb0a206872fa0ad | examples/gridding/Natural_Neighbor_Verification.py | python | draw_polygon_with_info | (ax, polygon, off_x=0, off_y=0) | Draw one of the natural neighbor polygons with some information. | Draw one of the natural neighbor polygons with some information. | [
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pts = np.array(polygon)[ConvexHull(polygon).vertices]
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avex, avey = np.mean(pts, axis=0)
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oracle/graalpython | 577e02da9755d916056184ec441c26e00b70145c | graalpython/lib-python/3/importlib/metadata.py | python | PackagePath.locate | (self) | return self.dist.locate_file(self) | Return a path-like object for this path | Return a path-like object for this path | [
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giantbranch/python-hacker-code | addbc8c73e7e6fb9e4fcadcec022fa1d3da4b96d | 我手敲的代码(中文注释)/chapter11/volatility/conf.py | python | ConfObject.__init__ | (self) | This is a singleton object kept in the class | This is a singleton object kept in the class | [
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UCL-INGI/INGInious | 60f10cb4c375ce207471043e76bd813220b95399 | inginious/frontend/user_manager.py | python | UserManager.session_api_key | (self) | return self.get_user_api_key(self.session_username()) | Returns the API key for the current user. Created on first demand. | Returns the API key for the current user. Created on first demand. | [
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wechatpy/wechatpy | 5f693a7e90156786c2540ad3c941d12cdf6d88ef | wechatpy/client/api/merchant/express.py | python | MerchantExpress.update | (self, template_id, delivery_template) | return self._post(
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ncoudray/DeepPATH | 62bf7e7f74a80889f1e07890b8fe814f076f780d | DeepPATH_code/01_training/xClasses/inception/data/build_imagenet_data.py | python | _process_dataset | (name, directory, num_shards, synset_to_human,
image_to_bboxes) | Process a complete data set and save it as a TFRecord.
Args:
name: string, unique identifier specifying the data set.
directory: string, root path to the data set.
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synset_to_human: dict of synset to human labels, e.g.,
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Args:
name: string, unique identifier specifying the data set.
directory: string, root path to the data set.
num_shards: integer number of shards for this data set.
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"""
filenames, synsets, labels = _find_image_files(directory, FLAGS.labels_file)
humans = _find_human_readable_labels(synsets, synset_to_human)
bboxes = _find_image_bounding_boxes(filenames, image_to_bboxes)
_process_image_files(name, filenames, synsets, labels,
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biolab/orange3 | 41685e1c7b1d1babe680113685a2d44bcc9fec0b | Orange/widgets/evaluate/owrocanalysis.py | python | roc_curve_threshold_average | (curves, thresh_samples) | return ((fpr_samples.mean(axis=0), fpr_samples.std(axis=0)),
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raise ValueError("No curves")
fpr_samples, tpr_samples = [], []
for fpr, tpr, thresh in curves:
ind = np.searchsorted(thresh[::-1], thresh_samples, side="left")
ind = ind[::-1]
ind = np.clip(ind, 0, len(thresh) - 1)
fpr_samples.append(fpr[ind])
tpr_samples.append(tpr[ind])
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/taskrouter/v1/workspace/task_queue/task_queue_cumulative_statistics.py | python | TaskQueueCumulativeStatisticsInstance.tasks_deleted | (self) | return self._properties['tasks_deleted'] | :returns: The total number of Tasks deleted in the TaskQueue
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cantools/cantools | 8d86d61bc010f328cf414150331fecfd4b6f4dc3 | cantools/database/can/signal.py | python | NamedSignalValue.value | (self) | return self._value | The integer value that gets mapped | The integer value that gets mapped | [
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"""The integer value that gets mapped
"""
return self._value | [
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eth-brownie/brownie | 754bda9f0a294b2beb86453d5eca4ff769a877c8 | brownie/utils/docopt.py | python | BranchPattern.fix_repeating_arguments | (self) | return self | Fix elements that should accumulate/increment values. | Fix elements that should accumulate/increment values. | [
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] | def fix_repeating_arguments(self) -> "BranchPattern":
"""Fix elements that should accumulate/increment values."""
either = [list(child.children) for child in transform(self).children]
for case in either:
for e in [child for child in case if case.count(child) > 1]:
if type(e) is Argument or type(e) is Option and e.argcount:
if e.value is None:
e.value = []
elif type(e.value) is not list:
e.value = e.value.split()
if type(e) is Command or type(e) is Option and e.argcount == 0:
e.value = 0
return self | [
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beeware/ouroboros | a29123c6fab6a807caffbb7587cf548e0c370296 | ouroboros/_strptime.py | python | _strptime | (data_string, format="%a %b %d %H:%M:%S %Y") | return (year, month, day,
hour, minute, second,
weekday, julian, tz, tzname, gmtoff), fraction | Return a 2-tuple consisting of a time struct and an int containing
the number of microseconds based on the input string and the
format string. | Return a 2-tuple consisting of a time struct and an int containing
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"""Return a 2-tuple consisting of a time struct and an int containing
the number of microseconds based on the input string and the
format string."""
for index, arg in enumerate([data_string, format]):
if not isinstance(arg, str):
msg = "strptime() argument {} must be str, not {}"
raise TypeError(msg.format(index, type(arg)))
global _TimeRE_cache, _regex_cache
with _cache_lock:
locale_time = _TimeRE_cache.locale_time
if (_getlang() != locale_time.lang or
time.tzname != locale_time.tzname or
time.daylight != locale_time.daylight):
_TimeRE_cache = TimeRE()
_regex_cache.clear()
locale_time = _TimeRE_cache.locale_time
if len(_regex_cache) > _CACHE_MAX_SIZE:
_regex_cache.clear()
format_regex = _regex_cache.get(format)
if not format_regex:
try:
format_regex = _TimeRE_cache.compile(format)
# KeyError raised when a bad format is found; can be specified as
# \\, in which case it was a stray % but with a space after it
except KeyError as err:
bad_directive = err.args[0]
if bad_directive == "\\":
bad_directive = "%"
del err
raise ValueError("'%s' is a bad directive in format '%s'" %
(bad_directive, format)) from None
# IndexError only occurs when the format string is "%"
except IndexError:
raise ValueError("stray %% in format '%s'" % format) from None
_regex_cache[format] = format_regex
found = format_regex.match(data_string)
if not found:
raise ValueError("time data %r does not match format %r" %
(data_string, format))
if len(data_string) != found.end():
raise ValueError("unconverted data remains: %s" %
data_string[found.end():])
year = None
month = day = 1
hour = minute = second = fraction = 0
tz = -1
tzoffset = None
# Default to -1 to signify that values not known; not critical to have,
# though
week_of_year = -1
week_of_year_start = -1
# weekday and julian defaulted to None so as to signal need to calculate
# values
weekday = julian = None
found_dict = found.groupdict()
for group_key in found_dict.keys():
# Directives not explicitly handled below:
# c, x, X
# handled by making out of other directives
# U, W
# worthless without day of the week
if group_key == 'y':
year = int(found_dict['y'])
# Open Group specification for strptime() states that a %y
#value in the range of [00, 68] is in the century 2000, while
#[69,99] is in the century 1900
if year <= 68:
year += 2000
else:
year += 1900
elif group_key == 'Y':
year = int(found_dict['Y'])
elif group_key == 'm':
month = int(found_dict['m'])
elif group_key == 'B':
month = locale_time.f_month.index(found_dict['B'].lower())
elif group_key == 'b':
month = locale_time.a_month.index(found_dict['b'].lower())
elif group_key == 'd':
day = int(found_dict['d'])
elif group_key == 'H':
hour = int(found_dict['H'])
elif group_key == 'I':
hour = int(found_dict['I'])
ampm = found_dict.get('p', '').lower()
# If there was no AM/PM indicator, we'll treat this like AM
if ampm in ('', locale_time.am_pm[0]):
# We're in AM so the hour is correct unless we're
# looking at 12 midnight.
# 12 midnight == 12 AM == hour 0
if hour == 12:
hour = 0
elif ampm == locale_time.am_pm[1]:
# We're in PM so we need to add 12 to the hour unless
# we're looking at 12 noon.
# 12 noon == 12 PM == hour 12
if hour != 12:
hour += 12
elif group_key == 'M':
minute = int(found_dict['M'])
elif group_key == 'S':
second = int(found_dict['S'])
elif group_key == 'f':
s = found_dict['f']
# Pad to always return microseconds.
s += "0" * (6 - len(s))
fraction = int(s)
elif group_key == 'A':
weekday = locale_time.f_weekday.index(found_dict['A'].lower())
elif group_key == 'a':
weekday = locale_time.a_weekday.index(found_dict['a'].lower())
elif group_key == 'w':
weekday = int(found_dict['w'])
if weekday == 0:
weekday = 6
else:
weekday -= 1
elif group_key == 'j':
julian = int(found_dict['j'])
elif group_key in ('U', 'W'):
week_of_year = int(found_dict[group_key])
if group_key == 'U':
# U starts week on Sunday.
week_of_year_start = 6
else:
# W starts week on Monday.
week_of_year_start = 0
elif group_key == 'z':
z = found_dict['z']
tzoffset = int(z[1:3]) * 60 + int(z[3:5])
if z.startswith("-"):
tzoffset = -tzoffset
elif group_key == 'Z':
# Since -1 is default value only need to worry about setting tz if
# it can be something other than -1.
found_zone = found_dict['Z'].lower()
for value, tz_values in enumerate(locale_time.timezone):
if found_zone in tz_values:
# Deal with bad locale setup where timezone names are the
# same and yet time.daylight is true; too ambiguous to
# be able to tell what timezone has daylight savings
if (time.tzname[0] == time.tzname[1] and
time.daylight and found_zone not in ("utc", "gmt")):
break
else:
tz = value
break
leap_year_fix = False
if year is None and month == 2 and day == 29:
year = 1904 # 1904 is first leap year of 20th century
leap_year_fix = True
elif year is None:
year = 1900
# If we know the week of the year and what day of that week, we can figure
# out the Julian day of the year.
if julian is None and week_of_year != -1 and weekday is not None:
week_starts_Mon = True if week_of_year_start == 0 else False
julian = _calc_julian_from_U_or_W(year, week_of_year, weekday,
week_starts_Mon)
# Cannot pre-calculate datetime_date() since can change in Julian
# calculation and thus could have different value for the day of the week
# calculation.
if julian is None:
# Need to add 1 to result since first day of the year is 1, not 0.
julian = datetime_date(year, month, day).toordinal() - \
datetime_date(year, 1, 1).toordinal() + 1
else: # Assume that if they bothered to include Julian day it will
# be accurate.
datetime_result = datetime_date.fromordinal((julian - 1) + datetime_date(year, 1, 1).toordinal())
year = datetime_result.year
month = datetime_result.month
day = datetime_result.day
if weekday is None:
weekday = datetime_date(year, month, day).weekday()
# Add timezone info
tzname = found_dict.get("Z")
if tzoffset is not None:
gmtoff = tzoffset * 60
else:
gmtoff = None
if leap_year_fix:
# the caller didn't supply a year but asked for Feb 29th. We couldn't
# use the default of 1900 for computations. We set it back to ensure
# that February 29th is smaller than March 1st.
year = 1900
return (year, month, day,
hour, minute, second,
weekday, julian, tz, tzname, gmtoff), fraction | [
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vyos/vyos-1x | 6e8a8934a7d4e1b21d7c828e372303683b499b56 | python/vyos/migrator.py | python | Migrator.save_json_record | (self, component_versions: dict) | Write component versions to a json file | Write component versions to a json file | [
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"""
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"""
mask = os.umask(0o113)
version_file = vyos.defaults.component_version_json
try:
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p4-team/ctf | 05ab90cd04ea26f0fca860579939617f57961a1a | 2017-02-25-bkp/sponge/hash.py | python | Hasher.hash | (self, s) | return self.squeeze() + self.squeeze() | Hash an input of any length of bytes. Return a 160-bit digest. | Hash an input of any length of bytes. Return a 160-bit digest. | [
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"""Hash an input of any length of bytes. Return a 160-bit digest."""
self.reset()
blocks = len(s) // 10
for i in range(blocks):
self.ingest(s[10*i:10*(i+1)])
self.final_ingest(s[blocks*10:])
return self.squeeze() + self.squeeze() | [
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runawayhorse001/LearningApacheSpark | 67f3879dce17553195f094f5728b94a01badcf24 | pyspark/sql/functions.py | python | unix_timestamp | (timestamp=None, format='yyyy-MM-dd HH:mm:ss') | return Column(sc._jvm.functions.unix_timestamp(_to_java_column(timestamp), format)) | Convert time string with given pattern ('yyyy-MM-dd HH:mm:ss', by default)
to Unix time stamp (in seconds), using the default timezone and the default
locale, return null if fail.
if `timestamp` is None, then it returns current timestamp.
>>> spark.conf.set("spark.sql.session.timeZone", "America/Los_Angeles")
>>> time_df = spark.createDataFrame([('2015-04-08',)], ['dt'])
>>> time_df.select(unix_timestamp('dt', 'yyyy-MM-dd').alias('unix_time')).collect()
[Row(unix_time=1428476400)]
>>> spark.conf.unset("spark.sql.session.timeZone") | Convert time string with given pattern ('yyyy-MM-dd HH:mm:ss', by default)
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Convert time string with given pattern ('yyyy-MM-dd HH:mm:ss', by default)
to Unix time stamp (in seconds), using the default timezone and the default
locale, return null if fail.
if `timestamp` is None, then it returns current timestamp.
>>> spark.conf.set("spark.sql.session.timeZone", "America/Los_Angeles")
>>> time_df = spark.createDataFrame([('2015-04-08',)], ['dt'])
>>> time_df.select(unix_timestamp('dt', 'yyyy-MM-dd').alias('unix_time')).collect()
[Row(unix_time=1428476400)]
>>> spark.conf.unset("spark.sql.session.timeZone")
"""
sc = SparkContext._active_spark_context
if timestamp is None:
return Column(sc._jvm.functions.unix_timestamp())
return Column(sc._jvm.functions.unix_timestamp(_to_java_column(timestamp), format)) | [
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saymedia/remoteobjects | d250e9a0e53c53744cb16c5fb2dc136df3785c1f | examples/twitter.py | python | Status.get_status | (cls, id, http=None) | return cls.get(urljoin(Twitter.endpoint, "/statuses/show/%d.json" % int(id)), http=http) | [] | def get_status(cls, id, http=None):
return cls.get(urljoin(Twitter.endpoint, "/statuses/show/%d.json" % int(id)), http=http) | [
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Lib/distutils/text_file.py | python | TextFile.open | (self, filename) | Open a new file named 'filename'. This overrides both the
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"""Open a new file named 'filename'. This overrides both the
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self.filename = filename
self.file = open (self.filename, 'r')
self.current_line = 0 | [
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neubig/nn4nlp-code | 970d91a51664b3d91a9822b61cd76abea20218cb | 14-semparsing/ucca/ucca/core.py | python | Passage.layer | (self, ID) | return self._layers[ID] | Returns the :class:Layer object whose ID is given.
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:raise KeyError: if no Layer with this ID is present | Returns the :class:Layer object whose ID is given. | [
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return self._layers[ID] | [
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InQuest/ThreatIngestor | 28d41bc991aad994d3bb8218d6f79779b889ab4d | threatingestor/sources/__init__.py | python | Source.__init__ | (self, name, *args, **kwargs) | Override this constructor in child classes.
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emedvedev/attention-ocr | 2ef51cba4770b86fccd34bae4e77d8f3eda3e797 | aocr/model/cnn.py | python | tf_create_attention_map | (incoming) | return tf.reshape(incoming, (-1, np.prod(shape[1:3]), shape[3])) | flatten hight and width into one dimention of size attn_length
:param incoming: 3D Tensor [batch_size x cur_h x cur_w x num_channels]
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bethesirius/ChosunTruck | 889644385ce57f971ec2921f006fbb0a167e6f1e | linux/tensorbox/pymouse/x11.py | python | PyMouseEvent.run | (self) | [] | def run(self):
try:
if self.capture and self.capture_move:
capturing = X.ButtonPressMask | X.ButtonReleaseMask | X.PointerMotionMask
elif self.capture:
capturing = X.ButtonPressMask | X.ButtonReleaseMask
elif self.capture_move:
capturing = X.PointerMotionMask
else:
capturing = False
if capturing:
self.display2.screen().root.grab_pointer(True,
capturing,
X.GrabModeAsync,
X.GrabModeAsync,
0, 0, X.CurrentTime)
self.display.screen().root.grab_pointer(True,
capturing,
X.GrabModeAsync,
X.GrabModeAsync,
0, 0, X.CurrentTime)
self.display2.record_enable_context(self.ctx, self.handler)
self.display2.record_free_context(self.ctx)
except KeyboardInterrupt:
self.stop() | [
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zzzeek/sqlalchemy | fc5c54fcd4d868c2a4c7ac19668d72f506fe821e | lib/sqlalchemy/orm/attributes.py | python | CollectionAttributeImpl.set_committed_value | (self, state, dict_, value) | return user_data | Set an attribute value on the given instance and 'commit' it. | Set an attribute value on the given instance and 'commit' it. | [
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"""Set an attribute value on the given instance and 'commit' it."""
collection, user_data = self._initialize_collection(state)
if value:
collection.append_multiple_without_event(value)
state.dict[self.key] = user_data
state._commit(dict_, [self.key])
if self.key in state._pending_mutations:
# pending items exist. issue a modified event,
# add/remove new items.
state._modified_event(dict_, self, user_data, True)
pending = state._pending_mutations.pop(self.key)
added = pending.added_items
removed = pending.deleted_items
for item in added:
collection.append_without_event(item)
for item in removed:
collection.remove_without_event(item)
return user_data | [
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tensorflow/tensor2tensor | 2a33b152d7835af66a6d20afe7961751047e28dd | tensor2tensor/models/research/transformer_vae_flow_prior_ops.py | python | generic_loss | (top_out, targets, model_hparams, vocab_size, weights_fn) | return common_layers.padded_cross_entropy(
logits,
targets,
model_hparams.label_smoothing,
cutoff=cutoff,
weights_fn=weights_fn,
reduce_sum=False) | Compute loss numerator and denominator for one shard of output. | Compute loss numerator and denominator for one shard of output. | [
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] | def generic_loss(top_out, targets, model_hparams, vocab_size, weights_fn):
"""Compute loss numerator and denominator for one shard of output."""
del vocab_size # unused arg
logits = top_out
logits = common_attention.maybe_upcast(logits, hparams=model_hparams)
cutoff = getattr(model_hparams, "video_modality_loss_cutoff", 0.0)
return common_layers.padded_cross_entropy(
logits,
targets,
model_hparams.label_smoothing,
cutoff=cutoff,
weights_fn=weights_fn,
reduce_sum=False) | [
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openstack/tempest | fe0ac89a5a1c43fa908a76759cd99eea3b1f9853 | tempest/lib/services/compute/keypairs_client.py | python | KeyPairsClient.list_keypairs | (self, **params) | return rest_client.ResponseBody(resp, body) | Lists keypairs that are associated with the account.
For a full list of available parameters, please refer to the official
API reference:
https://docs.openstack.org/api-ref/compute/#list-keypairs | Lists keypairs that are associated with the account. | [
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"""Lists keypairs that are associated with the account.
For a full list of available parameters, please refer to the official
API reference:
https://docs.openstack.org/api-ref/compute/#list-keypairs
"""
url = 'os-keypairs'
if params:
url += '?%s' % urllib.urlencode(params)
resp, body = self.get(url)
body = json.loads(body)
schema = self.get_schema(self.schema_versions_info)
self.validate_response(schema.list_keypairs, resp, body)
return rest_client.ResponseBody(resp, body) | [
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selfteaching/selfteaching-python-camp | 9982ee964b984595e7d664b07c389cddaf158f1e | exercises/1901050024/d09/mymodule/stats_word.py | python | stats_text_en | (en,count1) | 1. 英文词频统计：使用正则表达式过滤英文字符，使用Counter统计并排序。
2. 参数类型检查，不为字符串抛出异常。 | 1. 英文词频统计：使用正则表达式过滤英文字符，使用Counter统计并排序。
2. 参数类型检查，不为字符串抛出异常。 | [
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"2",
".",
"参数类型检查，不为字符串抛出异常。"
] | def stats_text_en(en,count1):
''' 1. 英文词频统计：使用正则表达式过滤英文字符，使用Counter统计并排序。
2. 参数类型检查，不为字符串抛出异常。
'''
if type(en) == str :
text_en = re.sub("[^A-Za-z]", " ", en.strip())
enList = text_en.split( )
count1 = int(input('请输入获取的英文单词数量：'))
return collections.Counter(enList).most_common(count1)
else:
raise ValueError ('type of argumengt is not str') | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/asyncio/futures.py | python | Future.done | (self) | return self._state != _PENDING | Return True if the future is done.
Done means either that a result / exception are available, or that the
future was cancelled. | Return True if the future is done. | [
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] | def done(self):
"""Return True if the future is done.
Done means either that a result / exception are available, or that the
future was cancelled.
"""
return self._state != _PENDING | [
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angr/angr | 4b04d56ace135018083d36d9083805be8146688b | angr/analyses/decompiler/utils.py | python | insert_node | (parent, insert_idx, node, node_idx, label=None, insert_location=None) | [] | def insert_node(parent, insert_idx, node, node_idx, label=None, insert_location=None):
if isinstance(parent, SequenceNode):
parent.nodes.insert(insert_idx, node)
elif isinstance(parent, CodeNode):
# Make a new sequence node
seq = SequenceNode(parent.addr, nodes=[parent.node, node])
parent.node = seq
elif isinstance(parent, MultiNode):
parent.nodes.insert(insert_idx, node)
elif isinstance(parent, ConditionNode):
if node_idx == 0:
# true node
if not isinstance(parent.true_node, (SequenceNode, MultiNode)):
parent.true_node = SequenceNode(parent.true_node.addr, nodes=[parent.true_node])
insert_node(parent.true_node, insert_idx - node_idx, node, 0)
else:
# false node
if not isinstance(parent.false_node, (SequenceNode, MultiNode)):
parent.false_node = SequenceNode(parent.false_node.addr, nodes=[parent.false_node])
insert_node(parent.false_node, insert_idx - node_idx, node, 0)
elif isinstance(parent, CascadingConditionNode):
cond, child_node = parent.condition_and_nodes[node_idx]
if not isinstance(child_node, SequenceNode):
child_node = SequenceNode(child_node.addr, nodes=[child_node])
parent.condition_and_nodes[node_idx] = (cond, child_node)
insert_node(child_node, insert_idx - node_idx, node, 0)
elif isinstance(parent, SwitchCaseNode):
# note that this case will be hit only when the parent node is not a container, such as SequenceNode or
# MultiNode. we always need to create a new SequenceNode and replace the original node in place.
if label == 'switch_expr':
raise TypeError("You cannot insert a node after an expression.")
if label == 'case':
# node_idx is the case number
if insert_location == 'after':
new_nodes = [ parent.cases[node_idx], node ]
elif insert_location == 'before':
new_nodes = [ node, parent.cases[node_idx] ]
else:
raise TypeError("Unsupported 'insert_location' value %r." % insert_location)
seq = SequenceNode(new_nodes[0].addr, nodes=new_nodes)
parent.cases[node_idx] = seq
elif label == 'default':
if insert_location == 'after':
new_nodes = [ parent.default_node, node ]
elif insert_location == 'before':
new_nodes = [ node, parent.default_node ]
else:
raise TypeError("Unsupported 'insert_location' value %r." % insert_location)
seq = SequenceNode(new_nodes[0].addr, nodes=new_nodes)
parent.default_node = seq
else:
raise NotImplementedError() | [
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andresriancho/w3af | cd22e5252243a87aaa6d0ddea47cf58dacfe00a9 | w3af/core/data/kb/vuln_templates/base_template.py | python | BaseTemplate.get_options | (self) | return ol | In this case we provide a sample implementation since most
vulnerabilities will have this template. If the specific vulnerability
needs other params then it should override this implementation. | In this case we provide a sample implementation since most
vulnerabilities will have this template. If the specific vulnerability
needs other params then it should override this implementation. | [
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"""
In this case we provide a sample implementation since most
vulnerabilities will have this template. If the specific vulnerability
needs other params then it should override this implementation.
"""
ol = OptionList()
d = 'Vulnerability name (eg. SQL Injection)'
o = opt_factory('name', self.name, d, 'string')
ol.add(o)
d = 'URL (without query string parameters)'
o = opt_factory('url', self.url, d, 'url')
ol.add(o)
d = 'Query string or postdata parameters in url-encoded form'
h = 'If the HTTP method is GET, the data will be sent in the ' \
'query-string otherwise it will be sent using the HTTP request\'s' \
' body. If the vulnerability requires the request to be sent using'\
' multipart-forms, the exploit will convert this url-encoded data' \
' into that format.\n\n'\
'Enter the original parameter value, not the one which triggers'\
' the vulnerability. Correct input looks like "id=2" not like'\
' "id=2;cat /etc/passwd".'
o = opt_factory('data', self.data, d, 'string', help=h)
ol.add(o)
d = 'HTTP method'
o = opt_factory('method', self.method, d, 'string')
ol.add(o)
d = 'Vulnerable parameter (needs to be one of the entered in the data'\
' field).'
o = opt_factory('vulnerable_parameter', self.vulnerable_parameter, d,
'string')
ol.add(o)
return ol | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/appengine/api/images/__init__.py | python | Image.crop | (self, left_x, top_y, right_x, bottom_y) | Crop the image.
The four arguments are the scaling numbers to describe the bounding box
which will crop the image. The upper left point of the bounding box will
be at (left_x*image_width, top_y*image_height) the lower right point will
be at (right_x*image_width, bottom_y*image_height).
Args:
left_x: float value between 0.0 and 1.0 (inclusive).
top_y: float value between 0.0 and 1.0 (inclusive).
right_x: float value between 0.0 and 1.0 (inclusive).
bottom_y: float value between 0.0 and 1.0 (inclusive).
Raises:
TypeError if the args are not of type 'float'.
BadRequestError when there is something wrong with the given bounding box
or if MAX_TRANSFORMS_PER_REQUEST transforms have already been requested
for this image. | Crop the image. | [
"Crop",
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"."
] | def crop(self, left_x, top_y, right_x, bottom_y):
"""Crop the image.
The four arguments are the scaling numbers to describe the bounding box
which will crop the image. The upper left point of the bounding box will
be at (left_x*image_width, top_y*image_height) the lower right point will
be at (right_x*image_width, bottom_y*image_height).
Args:
left_x: float value between 0.0 and 1.0 (inclusive).
top_y: float value between 0.0 and 1.0 (inclusive).
right_x: float value between 0.0 and 1.0 (inclusive).
bottom_y: float value between 0.0 and 1.0 (inclusive).
Raises:
TypeError if the args are not of type 'float'.
BadRequestError when there is something wrong with the given bounding box
or if MAX_TRANSFORMS_PER_REQUEST transforms have already been requested
for this image.
"""
self._validate_crop_arg(left_x, "left_x")
self._validate_crop_arg(top_y, "top_y")
self._validate_crop_arg(right_x, "right_x")
self._validate_crop_arg(bottom_y, "bottom_y")
if left_x >= right_x:
raise BadRequestError("left_x must be less than right_x")
if top_y >= bottom_y:
raise BadRequestError("top_y must be less than bottom_y")
self._check_transform_limits()
transform = images_service_pb.Transform()
transform.set_crop_left_x(left_x)
transform.set_crop_top_y(top_y)
transform.set_crop_right_x(right_x)
transform.set_crop_bottom_y(bottom_y)
self._transforms.append(transform) | [
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IronLanguages/ironpython2 | 51fdedeeda15727717fb8268a805f71b06c0b9f1 | Src/StdLib/Lib/imputil.py | python | ImportManager._reload_hook | (self, module) | Python calls this hook to reload a module. | Python calls this hook to reload a module. | [
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"Python calls this hook to reload a module."
# reloading of a module may or may not be possible (depending on the
# importer), but at least we can validate that it's ours to reload
importer = module.__dict__.get('__importer__')
if not importer:
### oops. now what...
pass
# okay. it is using the imputil system, and we must delegate it, but
# we don't know what to do (yet)
### we should blast the module dict and do another get_code(). need to
### flesh this out and add proper docco...
raise SystemError, "reload not yet implemented" | [
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phonopy/phonopy | 816586d0ba8177482ecf40e52f20cbdee2260d51 | phonopy/api_qha.py | python | PhonopyQHA.get_bulk_modulus_temperature | (self) | return self.bulk_modulus_temperature | Return bulk moduli at temperatures. | Return bulk moduli at temperatures. | [
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] | def get_bulk_modulus_temperature(self):
"""Return bulk moduli at temperatures."""
warnings.warn(
"PhonopyQHA.get_bulk_modulus_temperature() is deprecated."
"Use bulk_modulus_temperature attribute.",
DeprecationWarning,
)
return self.bulk_modulus_temperature | [
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simons-public/protonfixes | 24ecb378bc4e99bfe698090661d255dcbb5b677f | protonfixes/gamefixes/390710.py | python | main | () | Installs d3dxof | Installs d3dxof | [
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""" Installs d3dxof
"""
# https://github.com/ValveSoftware/Proton/issues/970#issuecomment-420421289
util.protontricks('d3dxof') | [
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Pymol-Scripts/Pymol-script-repo | bcd7bb7812dc6db1595953dfa4471fa15fb68c77 | modules/pdb2pqr/contrib/numpy-1.1.0/numpy/ma/core.py | python | _minimum_operation.__init__ | (self) | minimum(a, b) or minimum(a)
In one argument case, returns the scalar minimum. | minimum(a, b) or minimum(a)
In one argument case, returns the scalar minimum. | [
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"""minimum(a, b) or minimum(a)
In one argument case, returns the scalar minimum.
"""
self.ufunc = umath.minimum
self.afunc = amin
self.compare = less
self.fill_value_func = minimum_fill_value | [
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] | https://github.com/Pymol-Scripts/Pymol-script-repo/blob/bcd7bb7812dc6db1595953dfa4471fa15fb68c77/modules/pdb2pqr/contrib/numpy-1.1.0/numpy/ma/core.py#L2745-L2752 | ||
AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.3/django/middleware/transaction.py | python | TransactionMiddleware.process_response | (self, request, response) | return response | Commits and leaves transaction management. | Commits and leaves transaction management. | [
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"management",
"."
] | def process_response(self, request, response):
"""Commits and leaves transaction management."""
if transaction.is_managed():
if transaction.is_dirty():
transaction.commit()
transaction.leave_transaction_management()
return response | [
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/packages/site-packages/sqlalchemy/orm/util.py | python | AliasedInsp.class_ | (self) | return self.mapper.class_ | Return the mapped class ultimately represented by this
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] | def class_(self):
"""Return the mapped class ultimately represented by this
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/net/proto2/python/internal/wire_format.py | python | _VarUInt64ByteSizeNoTag | (uint64) | return 10 | Returns the number of bytes required to serialize a single varint
using boundary value comparisons. (unrolled loop optimization -WPierce)
uint64 must be unsigned. | Returns the number of bytes required to serialize a single varint
using boundary value comparisons. (unrolled loop optimization -WPierce)
uint64 must be unsigned. | [
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] | def _VarUInt64ByteSizeNoTag(uint64):
"""Returns the number of bytes required to serialize a single varint
using boundary value comparisons. (unrolled loop optimization -WPierce)
uint64 must be unsigned.
"""
if uint64 <= 0x7f: return 1
if uint64 <= 0x3fff: return 2
if uint64 <= 0x1fffff: return 3
if uint64 <= 0xfffffff: return 4
if uint64 <= 0x7ffffffff: return 5
if uint64 <= 0x3ffffffffff: return 6
if uint64 <= 0x1ffffffffffff: return 7
if uint64 <= 0xffffffffffffff: return 8
if uint64 <= 0x7fffffffffffffff: return 9
if uint64 > UINT64_MAX:
raise message.EncodeError('Value out of range: %d' % uint64)
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