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llSourcell/AI_Artist | 3038c06c2e389b9c919c881c9a169efe2fd7810e | lib/python2.7/site-packages/pip/_vendor/requests/models.py | python | PreparedRequest.prepare_auth | (self, auth, url='') | Prepares the given HTTP auth data. | Prepares the given HTTP auth data. | [
"Prepares",
"the",
"given",
"HTTP",
"auth",
"data",
"."
] | def prepare_auth(self, auth, url=''):
"""Prepares the given HTTP auth data."""
# If no Auth is explicitly provided, extract it from the URL first.
if auth is None:
url_auth = get_auth_from_url(self.url)
auth = url_auth if any(url_auth) else None
if auth:
if isinstance(auth, tuple) and len(auth) == 2:
# special-case basic HTTP auth
auth = HTTPBasicAuth(*auth)
# Allow auth to make its changes.
r = auth(self)
# Update self to reflect the auth changes.
self.__dict__.update(r.__dict__)
# Recompute Content-Length
self.prepare_content_length(self.body) | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/lyric/config_flow.py | python | OAuth2FlowHandler.async_step_reauth_confirm | (self, user_input=None) | return await self.async_step_user() | Dialog that informs the user that reauth is required. | Dialog that informs the user that reauth is required. | [
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] | async def async_step_reauth_confirm(self, user_input=None):
"""Dialog that informs the user that reauth is required."""
if user_input is None:
return self.async_show_form(
step_id="reauth_confirm",
data_schema=vol.Schema({}),
)
return await self.async_step_user() | [
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linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/site-packages/pip/_vendor/cachecontrol/serialize.py | python | Serializer.loads | (self, request, data) | [] | def loads(self, request, data):
# Short circuit if we've been given an empty set of data
if not data:
return
# Determine what version of the serializer the data was serialized
# with
try:
ver, data = data.split(b",", 1)
except ValueError:
ver = b"cc=0"
# Make sure that our "ver" is actually a version and isn't a false
# positive from a , being in the data stream.
if ver[:3] != b"cc=":
data = ver + data
ver = b"cc=0"
# Get the version number out of the cc=N
ver = ver.split(b"=", 1)[-1].decode("ascii")
# Dispatch to the actual load method for the given version
try:
return getattr(self, "_loads_v{0}".format(ver))(request, data)
except AttributeError:
# This is a version we don't have a loads function for, so we'll
# just treat it as a miss and return None
return | [
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TuSimple/simpledet | 97413463f0bc3116f684eaf7031fd3dd6ded3149 | core/detection_module.py | python | DetModule.forward | (self, data_batch, is_train=None) | Forward computation. It supports data batches with different shapes, such as
different batch sizes or different image sizes.
If reshaping of data batch relates to modification of symbol or module, such as
changing image layout ordering or switching from training to predicting, module
rebinding is required.
See Also
----------
:meth:`BaseModule.forward`.
Parameters
----------
data_batch : DataBatch
Could be anything with similar API implemented.
is_train : bool
Default is ``None``, which means ``is_train`` takes the value of ``self.for_training``. | Forward computation. It supports data batches with different shapes, such as
different batch sizes or different image sizes.
If reshaping of data batch relates to modification of symbol or module, such as
changing image layout ordering or switching from training to predicting, module
rebinding is required. | [
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"""Forward computation. It supports data batches with different shapes, such as
different batch sizes or different image sizes.
If reshaping of data batch relates to modification of symbol or module, such as
changing image layout ordering or switching from training to predicting, module
rebinding is required.
See Also
----------
:meth:`BaseModule.forward`.
Parameters
----------
data_batch : DataBatch
Could be anything with similar API implemented.
is_train : bool
Default is ``None``, which means ``is_train`` takes the value of ``self.for_training``.
"""
assert self.binded and self.params_initialized
curr_data_shapes = tuple(i.shape for i in self._data_shapes)
if isinstance(data_batch, list):
assert data_batch is not None, "Encountered empty data batch"
new_data_shapes = []
for i in range(len(data_batch[0].data)):
shape = data_batch[0].data[i].shape
for db in data_batch:
assert shape == db.data[i].shape, \
"All data batches in a list need to have the same shape"
new_batch_size = len(data_batch) * shape[0]
new_data_shapes.append((new_batch_size,) + shape[1:])
new_data_shapes = tuple(new_data_shapes)
else:
new_data_shapes = tuple(i.shape for i in data_batch.data)
if curr_data_shapes != new_data_shapes:
if hasattr(data_batch, "provide_data") and data_batch.provide_data:
new_dshape = data_batch.provide_data
else:
new_dshape = [DataDesc(i.name, shape, i.dtype, i.layout) \
for i, shape in zip(self._data_shapes, new_data_shapes)]
if hasattr(data_batch, "provide_label") and data_batch.provide_label:
new_lshape = data_batch.provide_label
elif hasattr(data_batch, "label") and data_batch.label:
new_lshape = [DataDesc(i.name, j.shape, i.dtype, i.layout) \
for i, j in zip(self._label_shapes, data_batch.label)]
else:
new_lshape = None
self.reshape(new_dshape, new_lshape)
self._exec_group.forward(data_batch, is_train) | [
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... | https://github.com/TuSimple/simpledet/blob/97413463f0bc3116f684eaf7031fd3dd6ded3149/core/detection_module.py#L592-L644 | ||
dabeaz/ply | 559a7a1feabb0853be79d4f4dd9e9e9e5ea0d08c | example/yply/ylex.py | python | t_code_ignore_char | (t) | r'\'([^\\\n]|(\\.))*?\ | r'\'([^\\\n]|(\\.))*?\ | [
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r'\'([^\\\n]|(\\.))*?\'' | [
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] | https://github.com/dabeaz/ply/blob/559a7a1feabb0853be79d4f4dd9e9e9e5ea0d08c/example/yply/ylex.py#L75-L76 | ||
TheAlgorithms/Python | 9af2eef9b3761bf51580dedfb6fa7136ca0c5c2c | project_euler/problem_064/sol1.py | python | solution | (n: int = 10000) | return count_odd_periods | Returns the count of numbers <= 10000 with odd periods.
This function calls continuous_fraction_period for numbers which are
not perfect squares.
This is checked in if sr - floor(sr) != 0 statement.
If an odd period is returned by continuous_fraction_period,
count_odd_periods is increased by 1.
>>> solution(2)
1
>>> solution(5)
2
>>> solution(7)
2
>>> solution(11)
3
>>> solution(13)
4 | Returns the count of numbers <= 10000 with odd periods.
This function calls continuous_fraction_period for numbers which are
not perfect squares.
This is checked in if sr - floor(sr) != 0 statement.
If an odd period is returned by continuous_fraction_period,
count_odd_periods is increased by 1. | [
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"""
Returns the count of numbers <= 10000 with odd periods.
This function calls continuous_fraction_period for numbers which are
not perfect squares.
This is checked in if sr - floor(sr) != 0 statement.
If an odd period is returned by continuous_fraction_period,
count_odd_periods is increased by 1.
>>> solution(2)
1
>>> solution(5)
2
>>> solution(7)
2
>>> solution(11)
3
>>> solution(13)
4
"""
count_odd_periods = 0
for i in range(2, n + 1):
sr = sqrt(i)
if sr - floor(sr) != 0:
if continuous_fraction_period(i) % 2 == 1:
count_odd_periods += 1
return count_odd_periods | [
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FederatedAI/FATE | 32540492623568ecd1afcb367360133616e02fa3 | python/federatedml/transfer_learning/hetero_ftl/ftl_base.py | python | FTL.learning_rate_decay | (self, learning_rate, epoch) | return learning_rate * 1 / np.sqrt(epoch + 1) | learning_rate decay | learning_rate decay | [
"learning_rate",
"decay"
] | def learning_rate_decay(self, learning_rate, epoch):
"""
learning_rate decay
"""
return learning_rate * 1 / np.sqrt(epoch + 1) | [
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huawei-noah/CV-Backbones | 03e8cdfe92494a55ddfb11cc875ff2e1c33f91da | versatile_filters/vcnn.py | python | vgg11 | (pretrained=False, **kwargs) | return model | VGG 11-layer model (configuration "A")
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet | VGG 11-layer model (configuration "A") | [
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] | def vgg11(pretrained=False, **kwargs):
"""VGG 11-layer model (configuration "A")
Args:
pretrained (bool): If True, returns a model pre-trained on ImageNet
"""
if pretrained:
kwargs['init_weights'] = False
model = VGG(make_layers(cfg['A']), **kwargs)
if pretrained:
model.load_state_dict(model_zoo.load_url(model_urls['vgg11']))
return model | [
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marcosfede/algorithms | 1ee7c815f9d556c9cef4d4b0d21ee3a409d21629 | dp/matrix_chain_order.py | python | main | () | [] | def main():
array = [30, 35, 15, 5, 10, 20, 25]
n = len(array)
# Size of matrix created from above array will be
# 30*35 35*15 15*5 5*10 10*20 20*25
matrix, optimal_solution = matrix_chain_order(array)
print("No. of Operation required: " + str((matrix[1][n - 1])))
print_optimal_solution(optimal_solution, 1, n - 1) | [
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nucleic/enaml | 65c2a2a2d765e88f2e1103046680571894bb41ed | enaml/qt/qt_scintilla.py | python | QtScintilla.set_autocomplete | (self, mode) | Set the autocompletion mode | Set the autocompletion mode | [
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] | def set_autocomplete(self, mode):
""" Set the autocompletion mode
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self.widget.setAutoCompletionSource(AUTOCOMPLETION_SOURCE[mode]) | [
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bruderstein/PythonScript | df9f7071ddf3a079e3a301b9b53a6dc78cf1208f | PythonLib/full/_pyio.py | python | TextIOWrapper.fileno | (self) | return self.buffer.fileno() | [] | def fileno(self):
return self.buffer.fileno() | [
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gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/gen/git_revision.py | python | get_git_revision | (path="") | Return the short commit hash of the latest commit. | Return the short commit hash of the latest commit. | [
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] | def get_git_revision(path=""):
"""
Return the short commit hash of the latest commit.
"""
stdout = ""
command = ['git', 'log', '-1', '--format=%h', path]
try:
proc = subprocess.Popen(command,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE)
(stdout, stderr) = proc.communicate()
except OSError:
return "" # subprocess failed
# subprocess worked
if stdout and len(stdout) > 0: # has output
try:
stdout = stdout.decode("utf-8", errors='replace')
except UnicodeDecodeError:
pass
return "-" + stdout if stdout else ""
else: # no output from git log
return "" | [
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i-pan/kaggle-rsna18 | 2db498fe99615d935aa676f04847d0c562fd8e46 | models/DeformableConvNets/lib/dataset/coco.py | python | coco._load_coco_annotation | (self, index) | return roi_rec | coco ann: [u'segmentation', u'area', u'iscrowd', u'image_id', u'bbox', u'category_id', u'id']
iscrowd:
crowd instances are handled by marking their overlaps with all categories to -1
and later excluded in training
bbox:
[x1, y1, w, h]
:param index: coco image id
:return: roidb entry | coco ann: [u'segmentation', u'area', u'iscrowd', u'image_id', u'bbox', u'category_id', u'id']
iscrowd:
crowd instances are handled by marking their overlaps with all categories to -1
and later excluded in training
bbox:
[x1, y1, w, h]
:param index: coco image id
:return: roidb entry | [
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"""
coco ann: [u'segmentation', u'area', u'iscrowd', u'image_id', u'bbox', u'category_id', u'id']
iscrowd:
crowd instances are handled by marking their overlaps with all categories to -1
and later excluded in training
bbox:
[x1, y1, w, h]
:param index: coco image id
:return: roidb entry
"""
im_ann = self.coco.loadImgs(index)[0]
width = im_ann['width']
height = im_ann['height']
annIds = self.coco.getAnnIds(imgIds=index, iscrowd=False)
objs = self.coco.loadAnns(annIds)
# sanitize bboxes
valid_objs = []
for obj in objs:
x, y, w, h = obj['bbox']
x1 = np.max((0, x))
y1 = np.max((0, y))
x2 = np.min((width - 1, x1 + np.max((0, w - 1))))
y2 = np.min((height - 1, y1 + np.max((0, h - 1))))
if obj['area'] > 0 and x2 >= x1 and y2 >= y1:
obj['clean_bbox'] = [x1, y1, x2, y2]
valid_objs.append(obj)
objs = valid_objs
num_objs = len(objs)
boxes = np.zeros((num_objs, 4), dtype=np.uint16)
gt_classes = np.zeros((num_objs), dtype=np.int32)
overlaps = np.zeros((num_objs, self.num_classes), dtype=np.float32)
for ix, obj in enumerate(objs):
cls = self._coco_ind_to_class_ind[obj['category_id']]
boxes[ix, :] = obj['clean_bbox']
gt_classes[ix] = cls
if obj['iscrowd']:
overlaps[ix, :] = -1.0
else:
overlaps[ix, cls] = 1.0
roi_rec = {'image': self.image_path_from_index(index),
'height': height,
'width': width,
'boxes': boxes,
'gt_classes': gt_classes,
'gt_overlaps': overlaps,
'max_classes': overlaps.argmax(axis=1),
'max_overlaps': overlaps.max(axis=1),
'flipped': False}
return roi_rec | [
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wbond/oscrypto | d40c62577706682a0f6da5616ad09964f1c9137d | oscrypto/_openssl/symmetric.py | python | aes_cbc_pkcs7_decrypt | (key, data, iv) | return _decrypt(cipher, key, data, iv, True) | Decrypts AES ciphertext in CBC mode using a 128, 192 or 256 bit key
:param key:
The encryption key - a byte string either 16, 24 or 32 bytes long
:param data:
The ciphertext - a byte string
:param iv:
The initialization vector - a byte string 16-bytes long
:raises:
ValueError - when any of the parameters contain an invalid value
TypeError - when any of the parameters are of the wrong type
OSError - when an error is returned by OpenSSL
:return:
A byte string of the plaintext | Decrypts AES ciphertext in CBC mode using a 128, 192 or 256 bit key | [
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] | def aes_cbc_pkcs7_decrypt(key, data, iv):
"""
Decrypts AES ciphertext in CBC mode using a 128, 192 or 256 bit key
:param key:
The encryption key - a byte string either 16, 24 or 32 bytes long
:param data:
The ciphertext - a byte string
:param iv:
The initialization vector - a byte string 16-bytes long
:raises:
ValueError - when any of the parameters contain an invalid value
TypeError - when any of the parameters are of the wrong type
OSError - when an error is returned by OpenSSL
:return:
A byte string of the plaintext
"""
cipher = _calculate_aes_cipher(key)
if len(iv) != 16:
raise ValueError(pretty_message(
'''
iv must be 16 bytes long - is %s
''',
len(iv)
))
return _decrypt(cipher, key, data, iv, True) | [
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edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/gdata/codesearch/service.py | python | CodesearchService.__init__ | (self, email=None, password=None, source=None,
server='www.google.com', additional_headers=None, **kwargs) | Creates a client for the Google codesearch service.
Args:
email: string (optional) The user's email address, used for
authentication.
password: string (optional) The user's password.
source: string (optional) The name of the user's application.
server: string (optional) The name of the server to which a connection
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**kwargs: The other parameters to pass to gdata.service.GDataService
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server='www.google.com', additional_headers=None, **kwargs):
"""Creates a client for the Google codesearch service.
Args:
email: string (optional) The user's email address, used for
authentication.
password: string (optional) The user's password.
source: string (optional) The name of the user's application.
server: string (optional) The name of the server to which a connection
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**kwargs: The other parameters to pass to gdata.service.GDataService
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"""
gdata.service.GDataService.__init__(
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source=source, server=server, additional_headers=additional_headers,
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Fizzadar/pyinfra | ff0913d6a172966760b63fe59e55dff9ea852e0d | pyinfra/facts/server.py | python | KernelModules.process | (output) | return modules | [] | def process(output):
modules = {}
for line in output:
name, size, instances, depends, state, _ = line.split(' ', 5)
instances = int(instances)
module = {
'size': size,
'instances': instances,
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modules[name] = module
return modules | [
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qtile/qtile | 803dc06fc1f8b121a1d8fe047f26a43812cd427f | libqtile/backend/x11/window.py | python | Window.cmd_static | (
self,
screen: Optional[int] = None,
x: Optional[int] = None,
y: Optional[int] = None,
width: Optional[int] = None,
height: Optional[int] = None,
) | Makes this window a static window, attached to a Screen
If any of the arguments are left unspecified, the values given by the
window itself are used instead. So, for a window that's aware of its
appropriate size and location (like dzen), you don't have to specify
anything. | Makes this window a static window, attached to a Screen | [
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] | def cmd_static(
self,
screen: Optional[int] = None,
x: Optional[int] = None,
y: Optional[int] = None,
width: Optional[int] = None,
height: Optional[int] = None,
) -> None:
"""Makes this window a static window, attached to a Screen
If any of the arguments are left unspecified, the values given by the
window itself are used instead. So, for a window that's aware of its
appropriate size and location (like dzen), you don't have to specify
anything.
"""
self.defunct = True
if screen is None:
screen = self.qtile.current_screen
else:
screen = self.qtile.screens[screen]
if self.group:
self.group.remove(self)
s = Static(self.window, self.qtile, screen, x, y, width, height)
self.qtile.windows_map[self.window.wid] = s
self.qtile.core.update_client_list(self.qtile.windows_map)
hook.fire("client_managed", s) | [
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pywavefront/PyWavefront | 7ae734c3317e2af59b93f3e24b68e5a57a2088ab | pywavefront/texture.py | python | Texture.path | (self) | return str(self._path) | str: search_path + name | str: search_path + name | [
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"""str: search_path + name"""
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SamSchott/maestral | a32653bac7b5a76cb326d4fd5a4fb2c11f19a2fc | src/maestral/sync.py | python | SyncEngine.excluded_items | (self) | return self._excluded_items | List of all files and folders excluded from sync. Changes are saved to the
config file. If a parent folder is excluded, its children will automatically be
removed from the list. If only children are given but not the parent folder, any
new items added to the parent will be synced. Change this property *before*
downloading newly included items or deleting excluded items. | List of all files and folders excluded from sync. Changes are saved to the
config file. If a parent folder is excluded, its children will automatically be
removed from the list. If only children are given but not the parent folder, any
new items added to the parent will be synced. Change this property *before*
downloading newly included items or deleting excluded items. | [
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"""List of all files and folders excluded from sync. Changes are saved to the
config file. If a parent folder is excluded, its children will automatically be
removed from the list. If only children are given but not the parent folder, any
new items added to the parent will be synced. Change this property *before*
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ConvLab/ConvLab | a04582a77537c1a706fbf64715baa9ad0be1301a | convlab/modules/policy/user/multiwoz/policy_agenda_multiwoz.py | python | Goal.task_complete | (self) | return True | Check that all requests have been met
Returns:
(boolean): True to accomplish. | Check that all requests have been met
Returns:
(boolean): True to accomplish. | [
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"""
Check that all requests have been met
Returns:
(boolean): True to accomplish.
"""
for domain in self.domains:
if 'reqt' in self.domain_goals[domain]:
reqt_vals = self.domain_goals[domain]['reqt'].values()
for val in reqt_vals:
if val in NOT_SURE_VALS:
return False
if 'booked' in self.domain_goals[domain]:
if self.domain_goals[domain]['booked'] in NOT_SURE_VALS:
return False
return True | [
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wagtail/wagtail | ba8207a5d82c8a1de8f5f9693a7cd07421762999 | wagtail/core/models/__init__.py | python | PageViewRestriction.save | (self, user=None, **kwargs) | Custom save handler to include logging.
:param user: the user add/updating the view restriction
:param specific_instance: the specific model instance the restriction applies to | Custom save handler to include logging.
:param user: the user add/updating the view restriction
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"""
Custom save handler to include logging.
:param user: the user add/updating the view restriction
:param specific_instance: the specific model instance the restriction applies to
"""
specific_instance = self.page.specific
is_new = self.id is None
super().save(**kwargs)
if specific_instance:
log(
instance=specific_instance,
action='wagtail.view_restriction.create' if is_new else 'wagtail.view_restriction.edit',
user=user,
data={
'restriction': {
'type': self.restriction_type,
'title': force_str(dict(self.RESTRICTION_CHOICES).get(self.restriction_type))
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googlefonts/gftools | 8ad55dd4d7e38729524329c79f236476f1576e67 | Lib/gftools/utils.py | python | download_file | (url, dst_path=None) | Download a file from a url. If no dst_path is specified, store the file
as a BytesIO object | Download a file from a url. If no dst_path is specified, store the file
as a BytesIO object | [
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] | def download_file(url, dst_path=None):
"""Download a file from a url. If no dst_path is specified, store the file
as a BytesIO object"""
request = requests.get(url, stream=True)
if not dst_path:
return BytesIO(request.content)
with open(dst_path, 'wb') as downloaded_file:
downloaded_file.write(request.content) | [
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smart-mobile-software/gitstack | d9fee8f414f202143eb6e620529e8e5539a2af56 | python/Lib/zipfile.py | python | ZipFile.close | (self) | Close the file, and for mode "w" and "a" write the ending
records. | Close the file, and for mode "w" and "a" write the ending
records. | [
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] | def close(self):
"""Close the file, and for mode "w" and "a" write the ending
records."""
if self.fp is None:
return
if self.mode in ("w", "a") and self._didModify: # write ending records
count = 0
pos1 = self.fp.tell()
for zinfo in self.filelist: # write central directory
count = count + 1
dt = zinfo.date_time
dosdate = (dt[0] - 1980) << 9 | dt[1] << 5 | dt[2]
dostime = dt[3] << 11 | dt[4] << 5 | (dt[5] // 2)
extra = []
if zinfo.file_size > ZIP64_LIMIT \
or zinfo.compress_size > ZIP64_LIMIT:
extra.append(zinfo.file_size)
extra.append(zinfo.compress_size)
file_size = 0xffffffff
compress_size = 0xffffffff
else:
file_size = zinfo.file_size
compress_size = zinfo.compress_size
if zinfo.header_offset > ZIP64_LIMIT:
extra.append(zinfo.header_offset)
header_offset = 0xffffffffL
else:
header_offset = zinfo.header_offset
extra_data = zinfo.extra
if extra:
# Append a ZIP64 field to the extra's
extra_data = struct.pack(
'<HH' + 'Q'*len(extra),
1, 8*len(extra), *extra) + extra_data
extract_version = max(45, zinfo.extract_version)
create_version = max(45, zinfo.create_version)
else:
extract_version = zinfo.extract_version
create_version = zinfo.create_version
try:
filename, flag_bits = zinfo._encodeFilenameFlags()
centdir = struct.pack(structCentralDir,
stringCentralDir, create_version,
zinfo.create_system, extract_version, zinfo.reserved,
flag_bits, zinfo.compress_type, dostime, dosdate,
zinfo.CRC, compress_size, file_size,
len(filename), len(extra_data), len(zinfo.comment),
0, zinfo.internal_attr, zinfo.external_attr,
header_offset)
except DeprecationWarning:
print >>sys.stderr, (structCentralDir,
stringCentralDir, create_version,
zinfo.create_system, extract_version, zinfo.reserved,
zinfo.flag_bits, zinfo.compress_type, dostime, dosdate,
zinfo.CRC, compress_size, file_size,
len(zinfo.filename), len(extra_data), len(zinfo.comment),
0, zinfo.internal_attr, zinfo.external_attr,
header_offset)
raise
self.fp.write(centdir)
self.fp.write(filename)
self.fp.write(extra_data)
self.fp.write(zinfo.comment)
pos2 = self.fp.tell()
# Write end-of-zip-archive record
centDirCount = count
centDirSize = pos2 - pos1
centDirOffset = pos1
if (centDirCount >= ZIP_FILECOUNT_LIMIT or
centDirOffset > ZIP64_LIMIT or
centDirSize > ZIP64_LIMIT):
# Need to write the ZIP64 end-of-archive records
zip64endrec = struct.pack(
structEndArchive64, stringEndArchive64,
44, 45, 45, 0, 0, centDirCount, centDirCount,
centDirSize, centDirOffset)
self.fp.write(zip64endrec)
zip64locrec = struct.pack(
structEndArchive64Locator,
stringEndArchive64Locator, 0, pos2, 1)
self.fp.write(zip64locrec)
centDirCount = min(centDirCount, 0xFFFF)
centDirSize = min(centDirSize, 0xFFFFFFFF)
centDirOffset = min(centDirOffset, 0xFFFFFFFF)
# check for valid comment length
if len(self.comment) >= ZIP_MAX_COMMENT:
if self.debug > 0:
msg = 'Archive comment is too long; truncating to %d bytes' \
% ZIP_MAX_COMMENT
self.comment = self.comment[:ZIP_MAX_COMMENT]
endrec = struct.pack(structEndArchive, stringEndArchive,
0, 0, centDirCount, centDirCount,
centDirSize, centDirOffset, len(self.comment))
self.fp.write(endrec)
self.fp.write(self.comment)
self.fp.flush()
if not self._filePassed:
self.fp.close()
self.fp = None | [
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jd/tenacity | 005ef22015ec4fda8646bf9dce7aaa1a4fa121d2 | tenacity/wait.py | python | wait_base.__radd__ | (self, other: "wait_base") | return self.__add__(other) | [] | def __radd__(self, other: "wait_base") -> typing.Union["wait_combine", "wait_base"]:
# make it possible to use multiple waits with the built-in sum function
if other == 0:
return self
return self.__add__(other) | [
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albertz/music-player | d23586f5bf657cbaea8147223be7814d117ae73d | mac/pyobjc-core/Examples/NonFunctional/RemotePyInterpreter/netrepr.py | python | ObjectPool.referenceForObject | (self, obj) | return rval | [] | def referenceForObject(self, obj):
obj_id = id(obj)
rval = self.obj_ids.get(obj_id)
if rval is None:
ident = self._identfactory.next()
rval = ObjectReference(self, ident, type_string(obj), obj, obj_id)
rval = rval.alloc().autorelease()
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Pext/Pext | f13e455e8003e7719e583dcff1fdb2826b6e10e0 | pext/__main__.py | python | ModuleManager.unload | (self, index: int, for_reload=False, window=None) | Unload a module by tab index. | Unload a module by tab index. | [
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Core.remove_module(index)
if window:
window.remove_module(index, for_reload) | [
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k2kobayashi/sprocket | e16d9c8c49ef8aa15a5dec89bfb0049a9baf845e | example/download_speech_corpus.py | python | ExtensionList.itemize_in_directory | (self, directory, recurse=False) | Search for audio files with the designated extensions in the directory.
Parameters
----------
directory : Path
The path of the directory where audio files are searched for.
recurse : bool
`True` if audio files in subdirectories must be searched.
Returns
-------
Generator[Path, None, None]
paths of audio files. | Search for audio files with the designated extensions in the directory. | [
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"""
Search for audio files with the designated extensions in the directory.
Parameters
----------
directory : Path
The path of the directory where audio files are searched for.
recurse : bool
`True` if audio files in subdirectories must be searched.
Returns
-------
Generator[Path, None, None]
paths of audio files.
"""
query_prefix = ("**/" if recurse else "") + "*."
for extension in self.extensions:
yield from directory.glob(query_prefix + extension) | [
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davidteather/TikTok-Api | a356324ab3171d473619fdf3e1dd71e5996cfc29 | TikTokApi/tiktok.py | python | TikTokApi.get_music_object_full_by_api | (self, id, **kwargs) | return res["musicInfo"] | Returns a music object for a specific sound id, but using the API rather than HTML requests.
##### Parameters
* id: The sound id to get the object for
This can be found by using other methods. | Returns a music object for a specific sound id, but using the API rather than HTML requests. | [
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"""Returns a music object for a specific sound id, but using the API rather than HTML requests.
##### Parameters
* id: The sound id to get the object for
This can be found by using other methods.
"""
(
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maxCount,
device_id,
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kwargs["custom_device_id"] = device_id
api_url = "{}node/share/music/-{}?{}".format(
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res = self.get_data(url=api_url, **kwargs)
if res.get("statusCode", 200) == 10203:
raise TikTokNotFoundError()
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ales-tsurko/cells | 4cf7e395cd433762bea70cdc863a346f3a6fe1d0 | packaging/macos/python/lib/python3.7/tkinter/tix.py | python | Tree.close | (self, entrypath) | Close the entry given by entryPath if its mode is close. | Close the entry given by entryPath if its mode is close. | [
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omz/PythonistaAppTemplate | f560f93f8876d82a21d108977f90583df08d55af | PythonistaAppTemplate/PythonistaKit.framework/pylib/site-packages/reportlab/platypus/figures.py | python | FlexFigure._scale | (self,availWidth,availHeight) | Rescale to fit according to the rules, but only once | Rescale to fit according to the rules, but only once | [
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"Rescale to fit according to the rules, but only once"
if self._scaleFactor is None or self.width>availWidth or self.height>availHeight:
w, h = Figure.wrap(self, availWidth, availHeight)
captionHeight = h - self.figureHeight
if self.scaleFactor is None:
#scale factor None means auto
self._scaleFactor = min(availWidth/self.width,(availHeight-captionHeight)/self.figureHeight)
else: #they provided a factor
self._scaleFactor = self.scaleFactor
if self._scaleFactor<1 and self.shrinkToFit:
self.width = self.width * self._scaleFactor - 0.0001
self.figureHeight = self.figureHeight * self._scaleFactor
elif self._scaleFactor>1 and self.growToFit:
self.width = self.width*self._scaleFactor - 0.0001
self.figureHeight = self.figureHeight * self._scaleFactor | [
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pypa/setuptools | 9f37366aab9cd8f6baa23e6a77cfdb8daf97757e | setuptools/_distutils/msvccompiler.py | python | MSVCCompiler.link | (self,
target_desc,
objects,
output_filename,
output_dir=None,
libraries=None,
library_dirs=None,
runtime_library_dirs=None,
export_symbols=None,
debug=0,
extra_preargs=None,
extra_postargs=None,
build_temp=None,
target_lang=None) | [] | def link(self,
target_desc,
objects,
output_filename,
output_dir=None,
libraries=None,
library_dirs=None,
runtime_library_dirs=None,
export_symbols=None,
debug=0,
extra_preargs=None,
extra_postargs=None,
build_temp=None,
target_lang=None):
if not self.initialized:
self.initialize()
(objects, output_dir) = self._fix_object_args(objects, output_dir)
fixed_args = self._fix_lib_args(libraries, library_dirs,
runtime_library_dirs)
(libraries, library_dirs, runtime_library_dirs) = fixed_args
if runtime_library_dirs:
self.warn ("I don't know what to do with 'runtime_library_dirs': "
+ str (runtime_library_dirs))
lib_opts = gen_lib_options(self,
library_dirs, runtime_library_dirs,
libraries)
if output_dir is not None:
output_filename = os.path.join(output_dir, output_filename)
if self._need_link(objects, output_filename):
if target_desc == CCompiler.EXECUTABLE:
if debug:
ldflags = self.ldflags_shared_debug[1:]
else:
ldflags = self.ldflags_shared[1:]
else:
if debug:
ldflags = self.ldflags_shared_debug
else:
ldflags = self.ldflags_shared
export_opts = []
for sym in (export_symbols or []):
export_opts.append("/EXPORT:" + sym)
ld_args = (ldflags + lib_opts + export_opts +
objects + ['/OUT:' + output_filename])
# The MSVC linker generates .lib and .exp files, which cannot be
# suppressed by any linker switches. The .lib files may even be
# needed! Make sure they are generated in the temporary build
# directory. Since they have different names for debug and release
# builds, they can go into the same directory.
if export_symbols is not None:
(dll_name, dll_ext) = os.path.splitext(
os.path.basename(output_filename))
implib_file = os.path.join(
os.path.dirname(objects[0]),
self.library_filename(dll_name))
ld_args.append ('/IMPLIB:' + implib_file)
if extra_preargs:
ld_args[:0] = extra_preargs
if extra_postargs:
ld_args.extend(extra_postargs)
self.mkpath(os.path.dirname(output_filename))
try:
self.spawn([self.linker] + ld_args)
except DistutilsExecError as msg:
raise LinkError(msg)
else:
log.debug("skipping %s (up-to-date)", output_filename) | [
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IOActive/XDiFF | 552d3394e119ca4ced8115f9fd2d7e26760e40b1 | classes/db.py | python | Db.get_software | (self) | return self.restrict_software | Get the current software ids restriction | Get the current software ids restriction | [
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tdryer/hangups | f0b37be1d46e71b30337227d7c46192cc726dcb4 | examples/common.py | python | run_example | (example_coroutine, *extra_args) | Run a hangups example coroutine.
Args:
example_coroutine (coroutine): Coroutine to run with a connected
hangups client and arguments namespace as arguments.
extra_args (str): Any extra command line arguments required by the
example. | Run a hangups example coroutine. | [
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] | def run_example(example_coroutine, *extra_args):
"""Run a hangups example coroutine.
Args:
example_coroutine (coroutine): Coroutine to run with a connected
hangups client and arguments namespace as arguments.
extra_args (str): Any extra command line arguments required by the
example.
"""
args = _get_parser(extra_args).parse_args()
logging.basicConfig(level=logging.DEBUG if args.debug else logging.WARNING)
# Obtain hangups authentication cookies, prompting for credentials from
# standard input if necessary.
cookies = hangups.auth.get_auth_stdin(args.token_path)
client = hangups.Client(cookies)
loop = asyncio.get_event_loop()
task = asyncio.ensure_future(_async_main(example_coroutine, client, args),
loop=loop)
try:
loop.run_until_complete(task)
except KeyboardInterrupt:
task.cancel()
loop.run_until_complete(task)
finally:
loop.close() | [
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nschloe/quadpy | c4c076d8ddfa968486a2443a95e2fb3780dcde0f | src/quadpy/e2r2/_helpers.py | python | E2r2Scheme.plot | (self, show_axes=False) | [] | def plot(self, show_axes=False):
from matplotlib import pyplot as plt
ax = plt.gca()
plt.axis("equal")
if not show_axes:
ax.set_axis_off()
I0 = 2 * math.pi
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dbsr/vimfox | 4a0145937226843b4b8b5681136ab9a45fb5d066 | vimfox/server/server.py | python | send_vimfox_file | (filename) | [] | def send_vimfox_file(filename):
app.logger.info(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'assets', filename))
try:
return send_file(os.path.join(os.path.dirname(os.path.abspath(__file__)), 'assets', filename))
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/taskrouter/v1/workspace/worker/worker_channel.py | python | WorkerChannelList.__repr__ | (self) | return '<Twilio.Taskrouter.V1.WorkerChannelList>' | Provide a friendly representation
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:rtype: str | Provide a friendly representation | [
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"""
Provide a friendly representation
:returns: Machine friendly representation
:rtype: str
"""
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stoq/stoq | c26991644d1affcf96bc2e0a0434796cabdf8448 | stoqlib/domain/workorder.py | python | WorkOrder.finish | (self, current_branch: Branch, user: LoginUser) | Finishes this work order's task
The :obj:`.execution_responsible` has finished working on
this order's task. It's possible now to give the equipment
back to the |client| and create a |sale| so we are able
to :meth:`deliver <.deliver>` this order. | Finishes this work order's task | [
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] | def finish(self, current_branch: Branch, user: LoginUser):
"""Finishes this work order's task
The :obj:`.execution_responsible` has finished working on
this order's task. It's possible now to give the equipment
back to the |client| and create a |sale| so we are able
to :meth:`deliver <.deliver>` this order.
"""
assert self.can_finish(current_branch)
self.finish_date = localnow()
# Make sure we are not overwriting this value, since we can reopen the
# order and finish again
if not self.execution_branch:
self.execution_branch = current_branch
self._change_status(self.STATUS_WORK_FINISHED, user) | [
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collinsctk/PyQYT | 7af3673955f94ff1b2df2f94220cd2dab2e252af | ExtentionPackages/tornado/auth.py | python | OpenIdMixin.get_authenticated_user | (self, callback, http_client=None) | Fetches the authenticated user data upon redirect.
This method should be called by the handler that receives the
redirect from the `authenticate_redirect()` method (which is
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redirect from the `authenticate_redirect()` method (which is
often the same as the one that calls it; in that case you would
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The result of this method will generally be used to set a cookie.
"""
# Verify the OpenID response via direct request to the OP
args = dict((k, v[-1]) for k, v in self.request.arguments.items())
args["openid.mode"] = u("check_authentication")
url = self._OPENID_ENDPOINT
if http_client is None:
http_client = self.get_auth_http_client()
http_client.fetch(url, functools.partial(
self._on_authentication_verified, callback),
method="POST", body=urllib_parse.urlencode(args)) | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/categories/category_with_axiom.py | python | CategoryWithAxiom.extra_super_categories | (self) | return [] | Return the extra super categories of a category with axiom.
Default implementation which returns ``[]``.
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sage: FiniteSets().extra_super_categories()
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Default implementation which returns ``[]``.
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sage: FiniteSets().extra_super_categories()
[]
"""
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cuthbertLab/music21 | bd30d4663e52955ed922c10fdf541419d8c67671 | music21/text.py | python | Trigram.makeWords | (self, count) | return ''.join(text) | returns a string of made-up words based on the known text. | returns a string of made-up words based on the known text. | [
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'''
returns a string of made-up words based on the known text.
'''
text = []
k = ' '
while count:
n = self.likely(k)
text.append(n)
k = k[1] + n
if n in ' \t':
count -= 1
return ''.join(text) | [
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phimpme/phimpme-generator | ba6d11190b9016238f27672e1ad55e6a875b74a0 | Phimpme/site-packages/coverage/files.py | python | FnmatchMatcher.match | (self, fpath) | return False | Does `fpath` match one of our filename patterns? | Does `fpath` match one of our filename patterns? | [
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] | https://github.com/phimpme/phimpme-generator/blob/ba6d11190b9016238f27672e1ad55e6a875b74a0/Phimpme/site-packages/coverage/files.py#L188-L193 | |
O365/python-o365 | 7f77005c3cee8177d0141e79b8eda8a7b60c5124 | O365/calendar.py | python | Event.organizer | (self) | return self.__organizer | Organizer of the meeting event
:rtype: Recipient | Organizer of the meeting event | [
"Organizer",
"of",
"the",
"meeting",
"event"
] | def organizer(self):
""" Organizer of the meeting event
:rtype: Recipient
"""
return self.__organizer | [
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gorakhargosh/watchdog | 77e1f4668bc42b4a8706b181d882fd68c05ab8b9 | src/watchdog/utils/patterns.py | python | match_any_paths | (paths, included_patterns=None, excluded_patterns=None, case_sensitive=True) | return False | Matches from a set of paths based on acceptable patterns and
ignorable patterns.
:param pathnames:
A list of path names that will be filtered based on matching and
ignored patterns.
:param included_patterns:
Allow filenames matching wildcard patterns specified in this list.
If no pattern list is specified, ["*"] is used as the default pattern,
which matches all files.
:param excluded_patterns:
Ignores filenames matching wildcard patterns specified in this list.
If no pattern list is specified, no files are ignored.
:param case_sensitive:
``True`` if matching should be case-sensitive; ``False`` otherwise.
:returns:
``True`` if any of the paths matches; ``False`` otherwise. | Matches from a set of paths based on acceptable patterns and
ignorable patterns.
:param pathnames:
A list of path names that will be filtered based on matching and
ignored patterns.
:param included_patterns:
Allow filenames matching wildcard patterns specified in this list.
If no pattern list is specified, ["*"] is used as the default pattern,
which matches all files.
:param excluded_patterns:
Ignores filenames matching wildcard patterns specified in this list.
If no pattern list is specified, no files are ignored.
:param case_sensitive:
``True`` if matching should be case-sensitive; ``False`` otherwise.
:returns:
``True`` if any of the paths matches; ``False`` otherwise. | [
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"""
Matches from a set of paths based on acceptable patterns and
ignorable patterns.
:param pathnames:
A list of path names that will be filtered based on matching and
ignored patterns.
:param included_patterns:
Allow filenames matching wildcard patterns specified in this list.
If no pattern list is specified, ["*"] is used as the default pattern,
which matches all files.
:param excluded_patterns:
Ignores filenames matching wildcard patterns specified in this list.
If no pattern list is specified, no files are ignored.
:param case_sensitive:
``True`` if matching should be case-sensitive; ``False`` otherwise.
:returns:
``True`` if any of the paths matches; ``False`` otherwise.
"""
included = ["*"] if included_patterns is None else included_patterns
excluded = [] if excluded_patterns is None else excluded_patterns
for path in paths:
if _match_path(path, set(included), set(excluded), case_sensitive):
return True
return False | [
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google-research/albert | 932b41f0319fbef7efd069d5ff545e3358574e19 | tokenization.py | python | encode_pieces | (sp_model, text, return_unicode=True, sample=False) | return new_pieces | turn sentences into word pieces. | turn sentences into word pieces. | [
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] | def encode_pieces(sp_model, text, return_unicode=True, sample=False):
"""turn sentences into word pieces."""
if six.PY2 and isinstance(text, six.text_type):
text = six.ensure_binary(text, "utf-8")
if not sample:
pieces = sp_model.EncodeAsPieces(text)
else:
pieces = sp_model.SampleEncodeAsPieces(text, 64, 0.1)
new_pieces = []
for piece in pieces:
piece = printable_text(piece)
if len(piece) > 1 and piece[-1] == "," and piece[-2].isdigit():
cur_pieces = sp_model.EncodeAsPieces(
six.ensure_binary(piece[:-1]).replace(SPIECE_UNDERLINE, b""))
if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
if len(cur_pieces[0]) == 1:
cur_pieces = cur_pieces[1:]
else:
cur_pieces[0] = cur_pieces[0][1:]
cur_pieces.append(piece[-1])
new_pieces.extend(cur_pieces)
else:
new_pieces.append(piece)
# note(zhiliny): convert back to unicode for py2
if six.PY2 and return_unicode:
ret_pieces = []
for piece in new_pieces:
if isinstance(piece, str):
piece = six.ensure_text(piece, "utf-8")
ret_pieces.append(piece)
new_pieces = ret_pieces
return new_pieces | [
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caktus/django-timepiece | 52515dec027664890efbc535429e1ba1ee152f40 | timepiece/reports/forms.py | python | BillableHoursReportForm.__init__ | (self, *args, **kwargs) | If the 'select_all' argument is given, any data values for users,
activities, and project_types are overwritten with all available
choices. | If the 'select_all' argument is given, any data values for users,
activities, and project_types are overwritten with all available
choices. | [
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"""
If the 'select_all' argument is given, any data values for users,
activities, and project_types are overwritten with all available
choices.
"""
select_all = kwargs.pop('select_all', False)
super(BillableHoursReportForm, self).__init__(*args, **kwargs)
self.fields['from_date'].required = True
self.fields['to_date'].required = True
user_ids = Entry.no_join.values_list('user', flat=True)
users = User.objects.filter(id__in=user_ids)
activities = Activity.objects.all()
project_types = Attribute.objects.all()
self.fields['users'].queryset = users
self.fields['activities'].queryset = activities
self.fields['project_types'].queryset = project_types
if select_all:
self.data['users'] = list(users.values_list('id', flat=True))
self.data['activities'] = list(activities.values_list('id',
flat=True))
self.data['project_types'] = list(project_types.values_list('id',
flat=True)) | [
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sham00n/buster | 131437e6128b6ad85fa2a9f17ad51311c885b8c2 | buster/lib/modules/github.py | python | email2github | (email,response) | [] | def email2github(email,response):
try:
if response.status_code==200:
data=response.json()
if data['items'] != []:
return data['items'][0]['html_url']
else:
return ""
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print("[=]Warning:Something went wrong while attempting to scrap github.com")
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scrapinghub/splash | 802d8391984bae049ef95a3fe1a74feaee95a233 | splash/har_builder.py | python | HarBuilder.store_reply_finished | (self, req_id, reply, content) | Store information about a finished reply. | Store information about a finished reply. | [
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] | def store_reply_finished(self, req_id, reply, content):
"""
Store information about a finished reply.
"""
if not self.log.has_entry(req_id):
return
entry = self.log.get_mutable_entry(req_id)
entry["_splash_processing_state"] = self.REQUEST_FINISHED
# update timings
now = datetime.utcnow()
start_time = entry['_tmp']['start_time']
response_start_time = entry['_tmp']['response_start_time']
receive_time = get_duration(response_start_time, now)
total_time = get_duration(start_time, now)
entry["timings"]["receive"] = receive_time
entry["time"] = total_time
if not entry["timings"]["send"]:
wait_time = entry["timings"]["wait"]
entry["timings"]["send"] = total_time - receive_time - wait_time
if entry["timings"]["send"] < 1e-6:
entry["timings"]["send"] = 0
# update other reply information
entry["response"].update(reply2har(reply, content=content)) | [
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unknown-horizons/unknown-horizons | 7397fb333006d26c3d9fe796c7bd9cb8c3b43a49 | horizons/scenario/conditions.py | python | _get_player_settlements | (session) | return session.world.player.settlements | Helper generator, returns settlements of local player. | Helper generator, returns settlements of local player. | [
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] | def _get_player_settlements(session):
"""Helper generator, returns settlements of local player."""
return session.world.player.settlements | [
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EducationalTestingService/skll | 1502fe8455cbb2c76cfc819db66f02f8ae11d321 | skll/experiments/utils.py | python | _get_stat_float | (label_result_dict, stat) | A helper function to get output for the precision, recall, and f-score
columns in the confusion matrix.
Parameters
----------
label_result_dict : dict
Dictionary containing the stat we'd like
to retrieve for a particular label.
stat : str
The statistic we're looking for in the dictionary.
Returns
-------
stat_float : float
The value of the stat if it's in the dictionary, and NaN
otherwise. | A helper function to get output for the precision, recall, and f-score
columns in the confusion matrix. | [
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] | def _get_stat_float(label_result_dict, stat):
"""
A helper function to get output for the precision, recall, and f-score
columns in the confusion matrix.
Parameters
----------
label_result_dict : dict
Dictionary containing the stat we'd like
to retrieve for a particular label.
stat : str
The statistic we're looking for in the dictionary.
Returns
-------
stat_float : float
The value of the stat if it's in the dictionary, and NaN
otherwise.
"""
if stat in label_result_dict and label_result_dict[stat] is not None:
return label_result_dict[stat]
else:
return float('nan') | [
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IntelPython/sdc | 1ebf55c00ef38dfbd401a70b3945e352a5a38b87 | sdc/timsort.py | python | sort | (key_arrs, lo, hi, data) | [] | def sort(key_arrs, lo, hi, data): # pragma: no cover
nRemaining = hi - lo
if nRemaining < 2:
return # Arrays of size 0 and 1 are always sorted
# If array is small, do a "mini-TimSort" with no merges
if nRemaining < MIN_MERGE:
initRunLen = countRunAndMakeAscending(key_arrs, lo, hi, data)
binarySort(key_arrs, lo, hi, lo + initRunLen, data)
return
# March over the array once, left to right, finding natural runs,
# extending short natural runs to minRun elements, and merging runs
# to maintain stack invariant.
(stackSize, runBase, runLen, tmpLength, tmp, tmp_data,
minGallop) = init_sort_start(key_arrs, data)
minRun = minRunLength(nRemaining)
while True: # emulating do-while
# Identify next run
run_len = countRunAndMakeAscending(key_arrs, lo, hi, data)
# If run is short, extend to min(minRun, nRemaining)
if run_len < minRun:
force = nRemaining if nRemaining <= minRun else minRun
binarySort(key_arrs, lo, lo + force, lo + run_len, data)
run_len = force
# Push run onto pending-run stack, and maybe merge
stackSize = pushRun(stackSize, runBase, runLen, lo, run_len)
stackSize, tmpLength, tmp, tmp_data, minGallop = mergeCollapse(
stackSize, runBase, runLen, key_arrs, data, tmpLength, tmp,
tmp_data, minGallop)
# Advance to find next run
lo += run_len
nRemaining -= run_len
if nRemaining == 0:
break
# Merge all remaining runs to complete sort
assert lo == hi
stackSize, tmpLength, tmp, tmp_data, minGallop = mergeForceCollapse(
stackSize, runBase, runLen, key_arrs, data, tmpLength, tmp,
tmp_data, minGallop)
assert stackSize == 1 | [
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Parsely/pykafka | e7665bf36bfe521050fdcb017c68e92365bd89ed | pykafka/handlers.py | python | ResponseFuture.get | (self, response_cls=None, timeout=None, **response_kwargs) | Block until data is ready and return.
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] | def get(self, response_cls=None, timeout=None, **response_kwargs):
"""Block until data is ready and return.
Raises an exception if there was an error.
"""
self._ready.wait(timeout)
if self.error:
raise self.error
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return response_cls(self.response, **response_kwargs)
else:
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ukBaz/python-bluezero | e6b4e96342de6c66571a6660d711c018f8c6b470 | bluezero/adapter.py | python | Adapter.discoverabletimeout | (self) | return self.adapter_props.Get(constants.ADAPTER_INTERFACE,
'DiscoverableTimeout') | Discoverable timeout of the Adapter. | Discoverable timeout of the Adapter. | [
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] | def discoverabletimeout(self):
"""Discoverable timeout of the Adapter."""
return self.adapter_props.Get(constants.ADAPTER_INTERFACE,
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scikit-hep/awkward-0.x | dd885bef15814f588b58944d2505296df4aaae0e | awkward0/array/base.py | python | AwkwardArray.count | (self) | return self._reduce(None, 0, None) | [] | def count(self):
return self._reduce(None, 0, None) | [
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theatlantic/django-nested-admin | 2554f51f6d05489dd2d81b24c60b59781fda4e8a | nested_admin/__init__.py | python | module.__dir__ | (self) | return result | Just show what we want to show. | Just show what we want to show. | [
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] | def __dir__(self):
"""Just show what we want to show."""
result = list(new_module.__all__)
result.extend(('__file__', '__path__', '__doc__', '__all__',
'__docformat__', '__name__', '__path__',
'__package__', '__version__'))
return result | [
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dabeaz/python-cookbook | 6e46b78e5644b3e5bf7426d900e2203b7cc630da | src/2/writing_a_simple_recursive_descent_parser/example.py | python | ExpressionEvaluator._expect | (self,toktype) | Consume next token if it matches toktype or raise SyntaxError | Consume next token if it matches toktype or raise SyntaxError | [
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] | def _expect(self,toktype):
'Consume next token if it matches toktype or raise SyntaxError'
if not self._accept(toktype):
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google/tf-quant-finance | 8fd723689ebf27ff4bb2bd2acb5f6091c5e07309 | tf_quant_finance/experimental/pricing_platform/framework/core/processed_market_data.py | python | ProcessedMarketData.yield_curve | (self, curve_type: curve_types.CurveType) | The yield curve object. | The yield curve object. | [
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] | def yield_curve(self, curve_type: curve_types.CurveType) -> RateCurve:
"""The yield curve object."""
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edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/django/contrib/staticfiles/handlers.py | python | StaticFilesHandler._should_handle | (self, path) | return path.startswith(self.base_url[2]) and not self.base_url[1] | Checks if the path should be handled. Ignores the path if:
* the host is provided as part of the base_url
* the request's path isn't under the media path (or equal) | Checks if the path should be handled. Ignores the path if: | [
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"""
Checks if the path should be handled. Ignores the path if:
* the host is provided as part of the base_url
* the request's path isn't under the media path (or equal)
"""
return path.startswith(self.base_url[2]) and not self.base_url[1] | [
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holoviz/datashader | 25578abde75c7fa28c6633b33cb8d8a1e433da67 | datashader/glyphs/line.py | python | LinesAxis1.compute_x_bounds | (self, df) | return self.maybe_expand_bounds((min(mins), max(maxes))) | [] | def compute_x_bounds(self, df):
xs = tuple(df[xlabel] for xlabel in self.x)
bounds_list = [self._compute_bounds(xcol) for xcol in xs]
mins, maxes = zip(*bounds_list)
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PokemonGoF/PokemonGo-Bot-Desktop | 4bfa94f0183406c6a86f93645eff7abd3ad4ced8 | build/pywin/Lib/wsgiref/handlers.py | python | BaseHandler.handle_error | (self) | Log current error, and send error output to client if possible | Log current error, and send error output to client if possible | [
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self.result = self.error_output(self.environ, self.start_response)
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tobegit3hub/deep_image_model | 8a53edecd9e00678b278bb10f6fb4bdb1e4ee25e | java_predict_client/src/main/proto/tensorflow/python/training/moving_averages.py | python | _zero_debias | (unbiased_var, value, decay) | Compute the delta required for a debiased Variable.
All exponential moving averages initialized with Tensors are initialized to 0,
and therefore are biased to 0. Variables initialized to 0 and used as EMAs are
similarly biased. This function creates the debias updated amount according to
a scale factor, as in https://arxiv.org/abs/1412.6980.
To demonstrate the bias the results from 0-initialization, take an EMA that
was initialized to `0` with decay `b`. After `t` timesteps of seeing the
constant `c`, the variable have the following value:
```
EMA = 0*b^(t) + c*(1 - b)*b^(t-1) + c*(1 - b)*b^(t-2) + ...
= c*(1 - b^t)
```
To have the true value `c`, we would divide by the scale factor `1 - b^t`.
In order to perform debiasing, we use two shadow variables. One keeps track of
the biased estimate, and the other keeps track of the number of updates that
have occurred.
Args:
unbiased_var: A Variable representing the current value of the unbiased EMA.
value: A Tensor representing the most recent value.
decay: A Tensor representing `1-decay` for the EMA.
Returns:
The amount that the unbiased variable should be updated. Computing this
tensor will also update the shadow variables appropriately. | Compute the delta required for a debiased Variable. | [
"Compute",
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"Variable",
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] | def _zero_debias(unbiased_var, value, decay):
"""Compute the delta required for a debiased Variable.
All exponential moving averages initialized with Tensors are initialized to 0,
and therefore are biased to 0. Variables initialized to 0 and used as EMAs are
similarly biased. This function creates the debias updated amount according to
a scale factor, as in https://arxiv.org/abs/1412.6980.
To demonstrate the bias the results from 0-initialization, take an EMA that
was initialized to `0` with decay `b`. After `t` timesteps of seeing the
constant `c`, the variable have the following value:
```
EMA = 0*b^(t) + c*(1 - b)*b^(t-1) + c*(1 - b)*b^(t-2) + ...
= c*(1 - b^t)
```
To have the true value `c`, we would divide by the scale factor `1 - b^t`.
In order to perform debiasing, we use two shadow variables. One keeps track of
the biased estimate, and the other keeps track of the number of updates that
have occurred.
Args:
unbiased_var: A Variable representing the current value of the unbiased EMA.
value: A Tensor representing the most recent value.
decay: A Tensor representing `1-decay` for the EMA.
Returns:
The amount that the unbiased variable should be updated. Computing this
tensor will also update the shadow variables appropriately.
"""
with variable_scope.variable_scope(
"ZeroDebias", values=[unbiased_var, value, decay]) as scope:
with ops.colocate_with(unbiased_var):
biased_var = variable_scope.get_variable(
unbiased_var.op.name + "_biased",
initializer=init_ops.zeros_initializer(
unbiased_var.get_shape(), dtype=unbiased_var.dtype),
trainable=False)
# Initializing the local_step to `0` would cause problems with the
# debiasing equation, so we instead initialize to `1`.
local_step = variable_scope.get_variable(
unbiased_var.op.name + "_local_step",
initializer=init_ops.ones_initializer([], dtype=unbiased_var.dtype),
trainable=False)
# Get an update ops for both shadow variables.
update_biased = state_ops.assign_sub(biased_var,
(biased_var - value) * decay,
name=scope.name)
update_local_step = local_step.assign_add(1)
# Compute the value of the delta to update the unbiased EMA. Make sure to
# use the new values of the biased variable and the local step.
with ops.control_dependencies([update_biased, update_local_step]):
# This function gets `1 - decay`, so use `1.0 - decay` in the exponent.
unbiased_ema_delta = (unbiased_var - biased_var.ref() /
(1 - math_ops.pow(1.0 - decay, local_step.ref())))
return unbiased_ema_delta | [
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danirus/django-comments-xtd | c2ec50226d219d98fe0faeae4e66e8a676b47e5b | django_comments_xtd/api/serializers.py | python | WriteCommentSerializer.validate_reply_to | (self, value) | return value | [] | def validate_reply_to(self, value):
if value != 0:
try:
parent = get_model().objects.get(pk=value)
except get_model().DoesNotExist:
raise serializers.ValidationError(
"reply_to comment does not exist")
else:
max = max_thread_level_for_content_type(parent.content_type)
if parent.level == max:
raise serializers.ValidationError(
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spotify/luigi | c3b66f4a5fa7eaa52f9a72eb6704b1049035c789 | luigi/configuration/core.py | python | _check_parser | (parser_class, parser) | [] | def _check_parser(parser_class, parser):
if not parser_class.enabled:
msg = (
"Parser not installed yet. "
"Please, install luigi with required parser:\n"
"pip install luigi[{parser}]"
)
raise ImportError(msg.format(parser=parser)) | [
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inkandswitch/livebook | 93c8d467734787366ad084fc3566bf5cbe249c51 | public/pypyjs/modules/datetime.py | python | date.ctime | (self) | return "%s %s %2d 00:00:00 %04d" % (
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apache/libcloud | 90971e17bfd7b6bb97b2489986472c531cc8e140 | libcloud/compute/drivers/ec2.py | python | BaseEC2NodeDriver.ex_delete_subnet | (self, subnet) | return self._get_boolean(res) | Deletes a VPC subnet.
:param subnet: The subnet to delete
:type subnet: :class:`.EC2NetworkSubnet`
:rtype: ``bool`` | Deletes a VPC subnet. | [
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"""
Deletes a VPC subnet.
:param subnet: The subnet to delete
:type subnet: :class:`.EC2NetworkSubnet`
:rtype: ``bool``
"""
params = {"Action": "DeleteSubnet", "SubnetId": subnet.id}
res = self.connection.request(self.path, params=params).object
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/setuptools/__init__.py | python | Command.reinitialize_command | (self, command, reinit_subcommands=0, **kw) | return cmd | [] | def reinitialize_command(self, command, reinit_subcommands=0, **kw):
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OpenAgricultureFoundation/openag-device-software | a51d2de399c0a6781ae51d0dcfaae1583d75f346 | device/utilities/communication/i2c/main.py | python | I2C.read | (
self, num_bytes: int, retry: bool = True, disable_mux: bool = False
) | Reads num bytes from device. Returns byte array. | Reads num bytes from device. Returns byte array. | [
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self, num_bytes: int, retry: bool = True, disable_mux: bool = False
) -> bytes:
"""Reads num bytes from device. Returns byte array."""
with self.i2c_lock:
self.manage_mux("read bytes", disable_mux)
#self.logger.debug("Reading {} bytes".format(num_bytes))
bytes_ = bytes(self.io.read(self.address, num_bytes))
#self.logger.debug("Read bytes: {}".format(byte_str(bytes_)))
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dipy/dipy | be956a529465b28085f8fc435a756947ddee1c89 | dipy/reconst/shore.py | python | shore_matrix_pdf | (radial_order, zeta, rtab) | return psi | r"""Compute the SHORE propagator matrix [1]_"
Parameters
----------
radial_order : unsigned int,
an even integer that represent the order of the basis
zeta : unsigned int,
scale factor
rtab : array, shape (N,3)
real space points in which calculates the pdf
References
----------
.. [1] Merlet S. et al., "Continuous diffusion signal, EAP and
ODF estimation via Compressive Sensing in diffusion MRI", Medical
Image Analysis, 2013. | r"""Compute the SHORE propagator matrix [1]_" | [
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r"""Compute the SHORE propagator matrix [1]_"
Parameters
----------
radial_order : unsigned int,
an even integer that represent the order of the basis
zeta : unsigned int,
scale factor
rtab : array, shape (N,3)
real space points in which calculates the pdf
References
----------
.. [1] Merlet S. et al., "Continuous diffusion signal, EAP and
ODF estimation via Compressive Sensing in diffusion MRI", Medical
Image Analysis, 2013.
"""
r, theta, phi = cart2sphere(rtab[:, 0], rtab[:, 1], rtab[:, 2])
theta[np.isnan(theta)] = 0
F = radial_order / 2
n_c = int(np.round(1 / 6.0 * (F + 1) * (F + 2) * (4 * F + 3)))
psi = np.zeros((r.shape[0], n_c))
counter = 0
for l in range(0, radial_order + 1, 2):
for n in range(l, int((radial_order + l) / 2) + 1):
for m in range(-l, l + 1):
psi[:, counter] = real_sh_descoteaux_from_index(
m, l, theta, phi) * \
genlaguerre(n - l, l + 0.5)(4 * np.pi ** 2 *
zeta * r ** 2) *\
np.exp(-2 * np.pi ** 2 * zeta * r ** 2) *\
_kappa_pdf(zeta, n, l) *\
(4 * np.pi ** 2 * zeta * r ** 2) ** (l / 2) * \
(-1) ** (n - l / 2)
counter += 1
return psi | [
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hatRiot/zarp | 2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad | src/lib/scapy/modules/nmap.py | python | NmapKnowledgeBase.lazy_init | (self) | [] | def lazy_init(self):
try:
f=open(self.filename)
except IOError:
return
self.base = []
name = None
try:
for l in f:
l = l.strip()
if not l or l[0] == "#":
continue
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self.base.append((name,sig))
name = l[12:].strip()
sig={}
p = self.base
continue
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op = l.find("(")
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s = map(lambda x: x.split("="), l[op+1:cl].split("%"))
si = {}
for n,v in s:
si[n] = v
sig[test]=si
if name is not None:
self.base.append((name,sig))
except:
self.base = None
warning("Can't read nmap database [%s](new nmap version ?)" % self.filename)
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yuanxiaosc/Multiple-Relations-Extraction-Only-Look-Once | 3d1fc216c6aedc0494e52f2ff142af856dcb673f | experimental_loss_function/run_multiple_relations_extraction_balanced_loss.py | python | DataProcessor.get_labels | (self) | Gets the list of labels for this data set. | Gets the list of labels for this data set. | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/vpc/v20170312/vpc_client.py | python | VpcClient.CreateLocalGateway | (self, request) | 该接口用于创建用于CDC的本地网关。
:param request: Request instance for CreateLocalGateway.
:type request: :class:`tencentcloud.vpc.v20170312.models.CreateLocalGatewayRequest`
:rtype: :class:`tencentcloud.vpc.v20170312.models.CreateLocalGatewayResponse` | 该接口用于创建用于CDC的本地网关。 | [
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] | def CreateLocalGateway(self, request):
"""该接口用于创建用于CDC的本地网关。
:param request: Request instance for CreateLocalGateway.
:type request: :class:`tencentcloud.vpc.v20170312.models.CreateLocalGatewayRequest`
:rtype: :class:`tencentcloud.vpc.v20170312.models.CreateLocalGatewayResponse`
"""
try:
params = request._serialize()
body = self.call("CreateLocalGateway", params)
response = json.loads(body)
if "Error" not in response["Response"]:
model = models.CreateLocalGatewayResponse()
model._deserialize(response["Response"])
return model
else:
code = response["Response"]["Error"]["Code"]
message = response["Response"]["Error"]["Message"]
reqid = response["Response"]["RequestId"]
raise TencentCloudSDKException(code, message, reqid)
except Exception as e:
if isinstance(e, TencentCloudSDKException):
raise
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raise TencentCloudSDKException(e.message, e.message) | [
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smartbgp/yabgp | f073633a813899cd9b413bc28ea2f7737deee141 | yabgp/core/timer.py | python | BGPTimer.reset | (self, seconds_fromnow) | Resets an already running timer, or starts it if it wasn't running.
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angr/angr | 4b04d56ace135018083d36d9083805be8146688b | angr/state_plugins/trace_additions.py | python | FormatInfoDontConstrain.__init__ | (self, addr, func_name, check_symbolic_arg) | [] | def __init__(self, addr, func_name, check_symbolic_arg):
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JBakamovic/cxxd | 142c19649b036bd6f6bdcd4684de735ea11a6c94 | parser/cxxd_config_parser.py | python | CxxdConfigParser._extract_clang_format_binary_path | (self, config) | return None | [] | def _extract_clang_format_binary_path(self, config):
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tp4a/teleport | 1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad | server/www/packages/packages-darwin/x64/tornado/template.py | python | _ChunkList.__init__ | (self, chunks) | [] | def __init__(self, chunks):
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/layout/updatemenu/_pad.py | python | Pad.r | (self) | return self["r"] | The amount of padding (in px) on the right side of the
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microsoft/azure-devops-python-api | 451cade4c475482792cbe9e522c1fee32393139e | azure-devops/azure/devops/v5_1/feature_availability/feature_availability_client.py | python | FeatureAvailabilityClient.get_feature_flag_by_name_and_user_id | (self, name, user_id, check_feature_exists=None) | return self._deserialize('FeatureFlag', response) | GetFeatureFlagByNameAndUserId.
[Preview API] Retrieve information on a single feature flag and its current states for a user
:param str name: The name of the feature to retrieve
:param str user_id: The id of the user to check
:param bool check_feature_exists: Check if feature exists
:rtype: :class:`<FeatureFlag> <azure.devops.v5_1.feature_availability.models.FeatureFlag>` | GetFeatureFlagByNameAndUserId.
[Preview API] Retrieve information on a single feature flag and its current states for a user
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:param str user_id: The id of the user to check
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panpanpandas/ultrafinance | ce3594dbfef747cba0c39f059316df7c208aac40 | ultrafinance/dam/excelLib.py | python | ExcelLib.readRow | (self, row, startCol=0, endCol=-1) | return self.__operation.readRow(row, startCol, endCol) | read row | read row | [
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skelsec/pypykatz | dd129ff36e00593d1340776b517f7e749ad8d314 | pypykatz/commons/winapi/local/function_defs/kernel32.py | python | MemoryBasicInformation.is_free | (self) | return self.State == MEM_FREE | @rtype: bool
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"""
@rtype: bool
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openshift/openshift-tools | 1188778e728a6e4781acf728123e5b356380fe6f | openshift/installer/vendored/openshift-ansible-3.10.0-0.29.0/roles/lib_vendored_deps/library/oc_adm_ca_server_cert.py | python | Utils.get_resource_file | (sfile, sfile_type='yaml') | return contents | return the service file | return the service file | [
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''' return the service file '''
contents = None
with open(sfile) as sfd:
contents = sfd.read()
if sfile_type == 'yaml':
# AUDIT:no-member makes sense here due to ruamel.YAML/PyYAML usage
# pylint: disable=no-member
if hasattr(yaml, 'RoundTripLoader'):
contents = yaml.load(contents, yaml.RoundTripLoader)
else:
contents = yaml.safe_load(contents)
elif sfile_type == 'json':
contents = json.loads(contents)
return contents | [
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albertz/PyCParser | 080a7b0472444fd366006c44fc15e388122989bd | sortedcontainers/sortedlist.py | python | SortedListWithKey.__repr__ | (self) | return temp.format(
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leapcode/bitmask_client | d2fe20df24fc6eaf146fa5ce1e847de6ab515688 | src/leap/bitmask/gui/eip_status.py | python | EIPStatusWidget.set_eip_status_menu | (self, eip_status_menu) | Sets the eip_status_menu to use.
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:type eip_status_menu: QtGui.QMenu
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leap_assert_type(eip_status_menu, QtGui.QMenu)
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FSecureLABS/Jandroid | e31d0dab58a2bfd6ed8e0a387172b8bd7c893436 | libs/platform-tools/platform-tools_linux/systrace/catapult/devil/devil/utils/lsusb.py | python | lsusb | () | return devices | Call lsusb and return the parsed output. | Call lsusb and return the parsed output. | [
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"""Call lsusb and return the parsed output."""
_, lsusb_list_output = cmd_helper.GetCmdStatusAndOutputWithTimeout(
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devices = []
for line in lsusb_list_output.splitlines():
m = _LSUSB_BUS_DEVICE_RE.match(line)
if m:
bus_num = m.group(1)
dev_num = m.group(2)
try:
devices.append(_lsusbv_on_device(bus_num, dev_num))
except cmd_helper.TimeoutError:
# Will be blacklisted if it is in expected device file, but times out.
logger.info('lsusb -v %s:%s timed out.', bus_num, dev_num)
return devices | [
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quartiq/rayopt | 3890c72b8f56253bdce309b0fe42beda91c6d3e0 | rayopt/transformations.py | python | quaternion_slerp | (quat0, quat1, fraction, spin=0, shortestpath=True) | return q0 | Return spherical linear interpolation between two quaternions.
>>> q0 = random_quaternion()
>>> q1 = random_quaternion()
>>> q = quaternion_slerp(q0, q1, 0)
>>> numpy.allclose(q, q0)
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>>> numpy.allclose(q, q1)
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>>> numpy.allclose(2, math.acos(numpy.dot(q0, q1)) / angle) or \
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"""Return spherical linear interpolation between two quaternions.
>>> q0 = random_quaternion()
>>> q1 = random_quaternion()
>>> q = quaternion_slerp(q0, q1, 0)
>>> numpy.allclose(q, q0)
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>>> numpy.allclose(q, q1)
True
>>> q = quaternion_slerp(q0, q1, 0.5)
>>> angle = math.acos(numpy.dot(q0, q))
>>> numpy.allclose(2, math.acos(numpy.dot(q0, q1)) / angle) or \
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"""
q0 = unit_vector(quat0[:4])
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if abs(abs(d) - 1.0) < _EPS:
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# invert rotation
d = -d
numpy.negative(q1, q1)
angle = math.acos(d) + spin * math.pi
if abs(angle) < _EPS:
return q0
isin = 1.0 / math.sin(angle)
q0 *= math.sin((1.0 - fraction) * angle) * isin
q1 *= math.sin(fraction * angle) * isin
q0 += q1
return q0 | [
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emesene/emesene | 4548a4098310e21b16437bb36223a7f632a4f7bc | emesene/gui/gtkui/AdiumTextBox.py | python | OutputText.__init__ | (self, config, handler) | constructor | constructor | [
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gtk.ScrolledWindow.__init__(self)
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openstack/swift | b8d7c3dcb817504dcc0959ba52cc4ed2cf66c100 | swift/obj/diskfile.py | python | DiskFileManager._update_suffix_hashes | (self, hashes, ondisk_info) | Applies policy specific updates to the given dict of md5 hashes for
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saltstack/salt | fae5bc757ad0f1716483ce7ae180b451545c2058 | salt/utils/jinja.py | python | lst_avg | (lst) | return float(lst) | Returns the average value of a list.
.. code-block:: jinja
{% my_list = [1,2,3,4] -%}
{{ set my_list | avg }}
will be rendered as:
.. code-block:: yaml
2.5 | Returns the average value of a list. | [
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"""
Returns the average value of a list.
.. code-block:: jinja
{% my_list = [1,2,3,4] -%}
{{ set my_list | avg }}
will be rendered as:
.. code-block:: yaml
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"""
if not isinstance(lst, Hashable):
return float(sum(lst) / len(lst))
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yuanxiaosc/Multiple-Relations-Extraction-Only-Look-Once | 3d1fc216c6aedc0494e52f2ff142af856dcb673f | bert/run_classifier.py | python | file_based_input_fn_builder | (input_file, seq_length, is_training,
drop_remainder) | return input_fn | Creates an `input_fn` closure to be passed to TPUEstimator. | Creates an `input_fn` closure to be passed to TPUEstimator. | [
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drop_remainder):
"""Creates an `input_fn` closure to be passed to TPUEstimator."""
name_to_features = {
"input_ids": tf.FixedLenFeature([seq_length], tf.int64),
"input_mask": tf.FixedLenFeature([seq_length], tf.int64),
"segment_ids": tf.FixedLenFeature([seq_length], tf.int64),
"label_ids": tf.FixedLenFeature([], tf.int64),
"is_real_example": tf.FixedLenFeature([], tf.int64),
}
def _decode_record(record, name_to_features):
"""Decodes a record to a TensorFlow example."""
example = tf.parse_single_example(record, name_to_features)
# tf.Example only supports tf.int64, but the TPU only supports tf.int32.
# So cast all int64 to int32.
for name in list(example.keys()):
t = example[name]
if t.dtype == tf.int64:
t = tf.to_int32(t)
example[name] = t
return example
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"""The actual input function."""
batch_size = params["batch_size"]
# For training, we want a lot of parallel reading and shuffling.
# For eval, we want no shuffling and parallel reading doesn't matter.
d = tf.data.TFRecordDataset(input_file)
if is_training:
d = d.repeat()
d = d.shuffle(buffer_size=100)
d = d.apply(
tf.contrib.data.map_and_batch(
lambda record: _decode_record(record, name_to_features),
batch_size=batch_size,
drop_remainder=drop_remainder))
return d
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/layout/ternary/caxis/_tickformatstop.py | python | Tickformatstop.__init__ | (
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arg=None,
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enabled=None,
name=None,
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value=None,
**kwargs
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arg
dict of properties compatible with this constructor or
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range [*min*, *max*], where "min", "max" - dtick values
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string - dtickformat for described zoom level, the same
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Tickformatstop | Construct a new Tickformatstop object
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dict of properties compatible with this constructor or
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Determines whether or not this stop is used. If
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modifications (including `visible: false` or `enabled:
false` to hide it). If there is no template or no
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value
string - dtickformat for described zoom level, the same
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super(Tickformatstop, self).__init__("tickformatstops")
if "_parent" in kwargs:
self._parent = kwargs["_parent"]
return
# Validate arg
# ------------
if arg is None:
arg = {}
elif isinstance(arg, self.__class__):
arg = arg.to_plotly_json()
elif isinstance(arg, dict):
arg = _copy.copy(arg)
else:
raise ValueError(
"""\
The first argument to the plotly.graph_objs.layout.ternary.caxis.Tickformatstop
constructor must be a dict or
an instance of :class:`plotly.graph_objs.layout.ternary.caxis.Tickformatstop`"""
)
# Handle skip_invalid
# -------------------
self._skip_invalid = kwargs.pop("skip_invalid", False)
self._validate = kwargs.pop("_validate", True)
# Populate data dict with properties
# ----------------------------------
_v = arg.pop("dtickrange", None)
_v = dtickrange if dtickrange is not None else _v
if _v is not None:
self["dtickrange"] = _v
_v = arg.pop("enabled", None)
_v = enabled if enabled is not None else _v
if _v is not None:
self["enabled"] = _v
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_v = name if name is not None else _v
if _v is not None:
self["name"] = _v
_v = arg.pop("templateitemname", None)
_v = templateitemname if templateitemname is not None else _v
if _v is not None:
self["templateitemname"] = _v
_v = arg.pop("value", None)
_v = value if value is not None else _v
if _v is not None:
self["value"] = _v
# Process unknown kwargs
# ----------------------
self._process_kwargs(**dict(arg, **kwargs))
# Reset skip_invalid
# ------------------
self._skip_invalid = False | [
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digidotcom/xbee-python | 0757f4be0017530c205175fbee8f9f61be9614d1 | digi/xbee/filesystem.py | python | FileSystemManager.read_file | (self, file, offset=0, progress_cb=None) | return _ReadFileProcess(self, file, offset, self.DEFAULT_TIMEOUT,
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Args:
file (:class:`.FileSystemElement` or String): File to read or its
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Raises:
FileSystemException: If there is any error performing the operation
and `progress_cb` is `None`.
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return _ReadFileProcess(self, file, offset, self.DEFAULT_TIMEOUT,
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krintoxi/NoobSec-Toolkit | 38738541cbc03cedb9a3b3ed13b629f781ad64f6 | NoobSecToolkit /tools/inject/thirdparty/gprof2dot/gprof2dot.py | python | DotWriter.begin_graph | (self) | [] | def begin_graph(self):
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asyml/texar | a23f021dae289a3d768dc099b220952111da04fd | texar/tf/modules/decoders/rnn_decoder_base.py | python | RNNDecoderBase.vocab_size | (self) | return self._vocab_size | The vocab size. | The vocab size. | [
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google/coursebuilder-core | 08f809db3226d9269e30d5edd0edd33bd22041f4 | coursebuilder/modules/courses/triggers.py | python | ContentTrigger.type | (self) | return None if self.content is None else self.content.type | Returns associated course content type if one exists, or None. | Returns associated course content type if one exists, or None. | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/libs/azure/src/azure/abfs/abfs.py | python | ABFS._local_copy_file | (self, local_src, remote_dst, chunk_size=UPLOAD_CHUCK_SIZE) | A wraper function for copying local Files | A wraper function for copying local Files | [
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offset = 0
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hequan2017/autoops | 5e717a2d86dd37cd2cfaf6db3d9613a0c41c49ae | script/connections.py | python | Connection._send_autocommit_mode | (self) | Set whether or not to commit after every execute() | Set whether or not to commit after every execute() | [
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AstusRush/AMaDiA | e2ad87318d9dd30bc24428e05c29cb32a29c83aa | External_Libraries/python_control_master/control/frdata.py | python | FrequencyResponseData.eval | (self, omega) | return self._evalfr(omega) | Evaluate a transfer function at a single angular frequency.
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sqlmapproject/sqlmap | 3b07b70864624dff4c29dcaa8a61c78e7f9189f7 | thirdparty/pydes/pyDes.py | python | _baseDes.getMode | (self) | return self._mode | getMode() -> pyDes.ECB or pyDes.CBC | getMode() -> pyDes.ECB or pyDes.CBC | [
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tosher/Mediawiker | 81bf97cace59bedcb1668e7830b85c36e014428e | lib/Crypto.win.x64/Crypto/Hash/keccak.py | python | Keccak_Hash.update | (self, data) | return self | Continue hashing of a message by consuming the next chunk of data.
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"_raw_kecca... | https://github.com/tosher/Mediawiker/blob/81bf97cace59bedcb1668e7830b85c36e014428e/lib/Crypto.win.x64/Crypto/Hash/keccak.py#L81-L96 | |
CedricGuillemet/Imogen | ee417b42747ed5b46cb11b02ef0c3630000085b3 | bin/Lib/functools.py | python | _le_from_lt | (self, other, NotImplemented=NotImplemented) | return op_result or self == other | Return a <= b. Computed by @total_ordering from (a < b) or (a == b). | Return a <= b. Computed by | [
"Return",
"a",
"<",
"=",
"b",
".",
"Computed",
"by"
] | def _le_from_lt(self, other, NotImplemented=NotImplemented):
'Return a <= b. Computed by @total_ordering from (a < b) or (a == b).'
op_result = self.__lt__(other)
return op_result or self == other | [
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nathanlopez/Stitch | 8e22e91c94237959c02d521aab58dc7e3d994cea | Application/stitch_osxshell.py | python | st_osxshell.help_location | (self) | [] | def help_location(self): st_help_location() | [
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] | https://github.com/nathanlopez/Stitch/blob/8e22e91c94237959c02d521aab58dc7e3d994cea/Application/stitch_osxshell.py#L249-L249 | ||||
wrye-bash/wrye-bash | d495c47cfdb44475befa523438a40c4419cb386f | Mopy/bash/patcher/patchers/preservers.py | python | ImportCellsPatcher.buildPatch | (self, log, progress, __attrgetters=attrgetter_cache) | Adds merged lists to patchfile. | Adds merged lists to patchfile. | [
"Adds",
"merged",
"lists",
"to",
"patchfile",
"."
] | def buildPatch(self, log, progress, __attrgetters=attrgetter_cache):
"""Adds merged lists to patchfile."""
def handlePatchCellBlock(patchCellBlock):
"""This function checks if an attribute or flag in CellData has
a value which is different to the corresponding value in the
bash patch file.
The Patch file will contain the last corresponding record
found when it is created regardless of tags.
If the CellData value is different, then the value is copied
to the bash patch, and the cell is flagged as modified.
Modified cell Blocks are kept, the other are discarded."""
modified = False
patch_cell = patchCellBlock.cell
patch_cell_fid = patch_cell.fid
for attr,value in cellData[patch_cell_fid].items():
curr_value = __attrgetters[attr](patch_cell)
##: If we made MelSorted sort on load too, we could drop this -
# but that might be too expensive? Maybe add a parameter to
# MelSorted to sort on load only for specific subrecords?
if attr == u'regions':
if set(value).difference(set(curr_value)):
setattr_deep(patch_cell, attr, value)
modified = True
else:
if value != curr_value:
setattr_deep(patch_cell, attr, value)
modified = True
if modified:
patch_cell.setChanged()
keep(patch_cell_fid)
return modified
if not self.isActive: return
keep = self.patchFile.getKeeper()
cellData, count = self.cellData, Counter()
for cellBlock in self.patchFile.tops[b'CELL'].cellBlocks:
cell_fid = cellBlock.cell.fid
if cell_fid in cellData and handlePatchCellBlock(cellBlock):
count[cell_fid[0]] += 1
for worldBlock in self.patchFile.tops[b'WRLD'].worldBlocks:
keepWorld = False
for cellBlock in worldBlock.cellBlocks:
cell_fid = cellBlock.cell.fid
if cell_fid in cellData and handlePatchCellBlock(cellBlock):
count[cell_fid[0]] += 1
keepWorld = True
if worldBlock.worldCellBlock:
cell_fid = worldBlock.worldCellBlock.cell.fid
if cell_fid in cellData and handlePatchCellBlock(
worldBlock.worldCellBlock):
count[cell_fid[0]] += 1
keepWorld = True
if keepWorld:
keep(worldBlock.world.fid)
self.cellData.clear()
self._patchLog(log, count) | [
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