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marcharper/python-ternary
|
a95361820073c1ace36f9cf31f3e4650c404920b
|
ternary/helpers.py
|
python
|
unzip
|
(l)
|
return list(zip(*l))
|
[(a1, b1), ..., (an, bn)] ----> ([a1, ..., an], [b1, ..., bn])
|
[(a1, b1), ..., (an, bn)] ----> ([a1, ..., an], [b1, ..., bn])
|
[
"[",
"(",
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"a1",
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"an",
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"[",
"b1",
"...",
"bn",
"]",
")"
] |
def unzip(l):
"""[(a1, b1), ..., (an, bn)] ----> ([a1, ..., an], [b1, ..., bn])"""
return list(zip(*l))
|
[
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"(",
"l",
")",
":",
"return",
"list",
"(",
"zip",
"(",
"*",
"l",
")",
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https://github.com/marcharper/python-ternary/blob/a95361820073c1ace36f9cf31f3e4650c404920b/ternary/helpers.py#L16-L18
|
|
jssimporter/JSSImporter
|
4f82f4c22aa6be99edfec55acb16d0b52cc03182
|
JSSImporter.py
|
python
|
JSSImporter.add_or_update_static_group
|
(self, group)
|
return computer_group
|
Either add a new group or update existing group.
|
Either add a new group or update existing group.
|
[
"Either",
"add",
"a",
"new",
"group",
"or",
"update",
"existing",
"group",
"."
] |
def add_or_update_static_group(self, group):
"""Either add a new group or update existing group."""
# Check for pre-existing group first
try:
computer_group = self.jss.ComputerGroup(group["name"])
self.output(
"Static Computer Group: {} already exists.".format(computer_group.name)
)
except jss.GetError:
computer_group = jss.ComputerGroup(self.jss, group["name"])
computer_group.save()
self.output(
"Static Computer Group '{}' created.".format(computer_group.name)
)
self.env["jss_changed_objects"]["jss_group_added"].append(
computer_group.name
)
return computer_group
|
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https://github.com/jssimporter/JSSImporter/blob/4f82f4c22aa6be99edfec55acb16d0b52cc03182/JSSImporter.py#L1160-L1178
|
|
TencentCloud/tencentcloud-sdk-python
|
3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2
|
tencentcloud/vod/v20180717/models.py
|
python
|
DomainDetailInfo.__init__
|
(self)
|
r"""
:param Domain: 域名名称。
:type Domain: str
:param AccelerateAreaInfos: 加速地区信息。
注意：此字段可能返回 null，表示取不到有效值。
:type AccelerateAreaInfos: list of AccelerateAreaInfo
:param DeployStatus: 部署状态，取值有：
<li>Online：上线；</li>
<li>Deploying：部署中；</li>
<li>Locked: 锁定中，出现该状态时，无法对该域名进行部署变更。</li>
:type DeployStatus: str
:param HTTPSConfig: HTTPS 配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type HTTPSConfig: :class:`tencentcloud.vod.v20180717.models.DomainHTTPSConfig`
:param UrlSignatureAuthPolicy: [Key 防盗链](https://cloud.tencent.com/document/product/266/14047)配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type UrlSignatureAuthPolicy: :class:`tencentcloud.vod.v20180717.models.UrlSignatureAuthPolicy`
:param RefererAuthPolicy: [Referer 防盗链](https://cloud.tencent.com/document/product/266/14046)配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type RefererAuthPolicy: :class:`tencentcloud.vod.v20180717.models.RefererAuthPolicy`
:param CreateTime: 域名添加到腾讯云点播系统中的时间。
<li>格式按照 ISO 8601标准表示，详见 [ISO 日期格式说明](https://cloud.tencent.com/document/product/266/11732#iso-.E6.97.A5.E6.9C.9F.E6.A0.BC.E5.BC.8F)。</li>
:type CreateTime: str
|
r"""
:param Domain: 域名名称。
:type Domain: str
:param AccelerateAreaInfos: 加速地区信息。
注意：此字段可能返回 null，表示取不到有效值。
:type AccelerateAreaInfos: list of AccelerateAreaInfo
:param DeployStatus: 部署状态，取值有：
<li>Online：上线；</li>
<li>Deploying：部署中；</li>
<li>Locked: 锁定中，出现该状态时，无法对该域名进行部署变更。</li>
:type DeployStatus: str
:param HTTPSConfig: HTTPS 配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type HTTPSConfig: :class:`tencentcloud.vod.v20180717.models.DomainHTTPSConfig`
:param UrlSignatureAuthPolicy: [Key 防盗链](https://cloud.tencent.com/document/product/266/14047)配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type UrlSignatureAuthPolicy: :class:`tencentcloud.vod.v20180717.models.UrlSignatureAuthPolicy`
:param RefererAuthPolicy: [Referer 防盗链](https://cloud.tencent.com/document/product/266/14046)配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type RefererAuthPolicy: :class:`tencentcloud.vod.v20180717.models.RefererAuthPolicy`
:param CreateTime: 域名添加到腾讯云点播系统中的时间。
<li>格式按照 ISO 8601标准表示，详见 [ISO 日期格式说明](https://cloud.tencent.com/document/product/266/11732#iso-.E6.97.A5.E6.9C.9F.E6.A0.BC.E5.BC.8F)。</li>
:type CreateTime: str
|
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":",
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def __init__(self):
r"""
:param Domain: 域名名称。
:type Domain: str
:param AccelerateAreaInfos: 加速地区信息。
注意：此字段可能返回 null，表示取不到有效值。
:type AccelerateAreaInfos: list of AccelerateAreaInfo
:param DeployStatus: 部署状态，取值有：
<li>Online：上线；</li>
<li>Deploying：部署中；</li>
<li>Locked: 锁定中，出现该状态时，无法对该域名进行部署变更。</li>
:type DeployStatus: str
:param HTTPSConfig: HTTPS 配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type HTTPSConfig: :class:`tencentcloud.vod.v20180717.models.DomainHTTPSConfig`
:param UrlSignatureAuthPolicy: [Key 防盗链](https://cloud.tencent.com/document/product/266/14047)配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type UrlSignatureAuthPolicy: :class:`tencentcloud.vod.v20180717.models.UrlSignatureAuthPolicy`
:param RefererAuthPolicy: [Referer 防盗链](https://cloud.tencent.com/document/product/266/14046)配置信息。
注意：此字段可能返回 null，表示取不到有效值。
:type RefererAuthPolicy: :class:`tencentcloud.vod.v20180717.models.RefererAuthPolicy`
:param CreateTime: 域名添加到腾讯云点播系统中的时间。
<li>格式按照 ISO 8601标准表示，详见 [ISO 日期格式说明](https://cloud.tencent.com/document/product/266/11732#iso-.E6.97.A5.E6.9C.9F.E6.A0.BC.E5.BC.8F)。</li>
:type CreateTime: str
"""
self.Domain = None
self.AccelerateAreaInfos = None
self.DeployStatus = None
self.HTTPSConfig = None
self.UrlSignatureAuthPolicy = None
self.RefererAuthPolicy = None
self.CreateTime = None
|
[
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] |
https://github.com/TencentCloud/tencentcloud-sdk-python/blob/3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2/tencentcloud/vod/v20180717/models.py#L10855-L10886
|
||
Teradata/stacki
|
a8085dce179dbe903f65f136f4b63bcc076cc057
|
common/src/stack/command/stack/argument_processors/firmware.py
|
python
|
FirmwareArgProcessor.ensure_unique_models
|
(self, make, models)
|
Ensures that none of the given model names already exist in the database for the given make.
If an empty iterable is provided, a CommandError is raised.
If any model name is blank, a CommandError is raised.
|
Ensures that none of the given model names already exist in the database for the given make.
|
[
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"the",
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"model",
"names",
"already",
"exist",
"in",
"the",
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"for",
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"given",
"make",
"."
] |
def ensure_unique_models(self, make, models):
"""Ensures that none of the given model names already exist in the database for the given make.
If an empty iterable is provided, a CommandError is raised.
If any model name is blank, a CommandError is raised.
"""
# We don't require that the make exists because a set of models for a non-existent make would be
# entirely new in that they are going to be added under a make that doesn't already exist.
models = tuple(models)
if not models:
raise CommandError(cmd = self, msg = "Models are required.")
# No empty strings allowed.
if not all(models):
raise CommandError(cmd = self, msg = "A model cannot be an empty string.")
# ensure the model name doesn't already exist for the given make
existing_makes_models = [
(make, model)
for make, model, exists in (
(make, model, self.model_exists(make, model)) for model in models
)
if exists
]
if existing_makes_models:
raise CommandError(cmd = self, msg = f"The following make and model combinations already exist {existing_makes_models}.")
|
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https://github.com/Teradata/stacki/blob/a8085dce179dbe903f65f136f4b63bcc076cc057/common/src/stack/command/stack/argument_processors/firmware.py#L136-L162
|
||
PlasmaPy/PlasmaPy
|
78d63e341216475ce3318e1409296480407c9019
|
plasmapy/particles/ionization_state.py
|
python
|
IonizationState.ionic_symbols
|
(self)
|
return self.to_list().symbols
|
The ionic symbols for all charge states.
|
The ionic symbols for all charge states.
|
[
"The",
"ionic",
"symbols",
"for",
"all",
"charge",
"states",
"."
] |
def ionic_symbols(self) -> List[str]:
"""The ionic symbols for all charge states."""
return self.to_list().symbols
|
[
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"]",
":",
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"(",
")",
".",
"symbols"
] |
https://github.com/PlasmaPy/PlasmaPy/blob/78d63e341216475ce3318e1409296480407c9019/plasmapy/particles/ionization_state.py#L730-L732
|
|
benedekrozemberczki/GEMSEC
|
c023122bdafe88278cdbd24b7fcf9dafe8e95b34
|
src/calculation_helper.py
|
python
|
alias_setup
|
(probs)
|
return J, q
|
Compute utility lists for non-uniform sampling from discrete distributions.
Refer to https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/
for details
|
Compute utility lists for non-uniform sampling from discrete distributions.
Refer to https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/
for details
|
[
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"discrete",
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"-",
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"/",
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def alias_setup(probs):
"""
Compute utility lists for non-uniform sampling from discrete distributions.
Refer to https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/
for details
"""
K = len(probs)
q = np.zeros(K)
J = np.zeros(K, dtype=np.int)
smaller = []
larger = []
for kk, prob in enumerate(probs):
q[kk] = K*prob
if q[kk] < 1.0:
smaller.append(kk)
else:
larger.append(kk)
while len(smaller) > 0 and len(larger) > 0:
small = smaller.pop()
large = larger.pop()
J[small] = large
q[large] = q[large] + q[small] - 1.0
if q[large] < 1.0:
smaller.append(large)
else:
larger.append(large)
return J, q
|
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")",
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":",
"larger",
".",
"append",
"(",
"large",
")",
"return",
"J",
",",
"q"
] |
https://github.com/benedekrozemberczki/GEMSEC/blob/c023122bdafe88278cdbd24b7fcf9dafe8e95b34/src/calculation_helper.py#L300-L330
|
|
mlflow/mlflow
|
364aca7daf0fcee3ec407ae0b1b16d9cb3085081
|
mlflow/store/tracking/dbmodels/models.py
|
python
|
SqlTag.to_mlflow_entity
|
(self)
|
return RunTag(key=self.key, value=self.value)
|
Convert DB model to corresponding MLflow entity.
:return: :py:class:`mlflow.entities.RunTag`.
|
Convert DB model to corresponding MLflow entity.
|
[
"Convert",
"DB",
"model",
"to",
"corresponding",
"MLflow",
"entity",
"."
] |
def to_mlflow_entity(self):
"""
Convert DB model to corresponding MLflow entity.
:return: :py:class:`mlflow.entities.RunTag`.
"""
return RunTag(key=self.key, value=self.value)
|
[
"def",
"to_mlflow_entity",
"(",
"self",
")",
":",
"return",
"RunTag",
"(",
"key",
"=",
"self",
".",
"key",
",",
"value",
"=",
"self",
".",
"value",
")"
] |
https://github.com/mlflow/mlflow/blob/364aca7daf0fcee3ec407ae0b1b16d9cb3085081/mlflow/store/tracking/dbmodels/models.py#L282-L288
|
|
BlackLight/platypush
|
a6b552504e2ac327c94f3a28b607061b6b60cf36
|
platypush/plugins/music/spotify/__init__.py
|
python
|
MusicSpotifyPlugin.get_albums
|
(self, limit: int = 50, offset: int = 0)
|
return SpotifyAlbumSchema().dump(
self._spotify_paginate_results(
'/v1/me/albums',
limit=limit,
offset=offset,
), many=True
)
|
Get the list of albums saved by the user.
:param limit: Maximum number of results (default: 50).
:param offset: Return results starting from this index (default: 0).
:return: .. schema:: spotify.SpotifyAlbumSchema(many=True)
|
Get the list of albums saved by the user.
|
[
"Get",
"the",
"list",
"of",
"albums",
"saved",
"by",
"the",
"user",
"."
] |
def get_albums(self, limit: int = 50, offset: int = 0) -> List[dict]:
"""
Get the list of albums saved by the user.
:param limit: Maximum number of results (default: 50).
:param offset: Return results starting from this index (default: 0).
:return: .. schema:: spotify.SpotifyAlbumSchema(many=True)
"""
return SpotifyAlbumSchema().dump(
self._spotify_paginate_results(
'/v1/me/albums',
limit=limit,
offset=offset,
), many=True
)
|
[
"def",
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"limit",
",",
"offset",
"=",
"offset",
",",
")",
",",
"many",
"=",
"True",
")"
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https://github.com/BlackLight/platypush/blob/a6b552504e2ac327c94f3a28b607061b6b60cf36/platypush/plugins/music/spotify/__init__.py#L801-L815
|
|
ITCoders/Human-detection-and-Tracking
|
0f132b9d809be8f84859a21fd6c310026089db52
|
create_face_model.py
|
python
|
get_images_and_labels
|
(path)
|
return images, labels
|
convert images to matrices
assign label to every image according to person
Using test data to make the machine learn this data
Args:
path: path to images directory
Returns:
matrix of images, labels
|
convert images to matrices
assign label to every image according to person
Using test data to make the machine learn this data
Args:
path: path to images directory
|
[
"convert",
"images",
"to",
"matrices",
"assign",
"label",
"to",
"every",
"image",
"according",
"to",
"person",
"Using",
"test",
"data",
"to",
"make",
"the",
"machine",
"learn",
"this",
"data",
"Args",
":",
"path",
":",
"path",
"to",
"images",
"directory"
] |
def get_images_and_labels(path):
"""
convert images to matrices
assign label to every image according to person
Using test data to make the machine learn this data
Args:
path: path to images directory
Returns:
matrix of images, labels
"""
i = 0
image_paths = [os.path.join(path, f)
for f in os.listdir(path) if not f.endswith('.sad')]
images = []
labels = []
for image_path in image_paths:
image_pil = Image.open(image_path).convert('L')
image = np.array(image_pil, 'uint8')
image = imutils.resize(image, width=min(500, image.shape[1]))
nbr = int(os.path.split(image_path)[1].split(
".")[0].replace("subject", ""))
faces = faceCascade.detectMultiScale(image)
for (x, y, w, h) in faces:
images.append(image[y: y + h, x: x + w])
# cv2.imwrite("subject02."+str(i)+".jpg",image[y: y + h, x: x + w])
# i=i+1
labels.append(nbr)
cv2.imshow("Adding faces to traning set",
image[y: y + h, x: x + w])
cv2.imshow('win', image[y: y + h, x: x + w])
cv2.waitKey(50)
return images, labels
|
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"waitKey",
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")",
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"images",
",",
"labels"
] |
https://github.com/ITCoders/Human-detection-and-Tracking/blob/0f132b9d809be8f84859a21fd6c310026089db52/create_face_model.py#L15-L47
|
|
nucleic/enaml
|
65c2a2a2d765e88f2e1103046680571894bb41ed
|
enaml/qt/qt_image_view.py
|
python
|
QImageView.allowUpscaling
|
(self)
|
return self._allow_upscaling
|
Returns whether or not the image can be scaled greater than
its natural size.
|
Returns whether or not the image can be scaled greater than
its natural size.
|
[
"Returns",
"whether",
"or",
"not",
"the",
"image",
"can",
"be",
"scaled",
"greater",
"than",
"its",
"natural",
"size",
"."
] |
def allowUpscaling(self):
""" Returns whether or not the image can be scaled greater than
its natural size.
"""
return self._allow_upscaling
|
[
"def",
"allowUpscaling",
"(",
"self",
")",
":",
"return",
"self",
".",
"_allow_upscaling"
] |
https://github.com/nucleic/enaml/blob/65c2a2a2d765e88f2e1103046680571894bb41ed/enaml/qt/qt_image_view.py#L160-L165
|
|
skylander86/lambda-text-extractor
|
6da52d077a2fc571e38bfe29c33ae68f6443cd5a
|
lib-linux_x64/requests/adapters.py
|
python
|
HTTPAdapter.init_poolmanager
|
(self, connections, maxsize, block=DEFAULT_POOLBLOCK, **pool_kwargs)
|
Initializes a urllib3 PoolManager.
This method should not be called from user code, and is only
exposed for use when subclassing the
:class:`HTTPAdapter <requests.adapters.HTTPAdapter>`.
:param connections: The number of urllib3 connection pools to cache.
:param maxsize: The maximum number of connections to save in the pool.
:param block: Block when no free connections are available.
:param pool_kwargs: Extra keyword arguments used to initialize the Pool Manager.
|
Initializes a urllib3 PoolManager.
|
[
"Initializes",
"a",
"urllib3",
"PoolManager",
"."
] |
def init_poolmanager(self, connections, maxsize, block=DEFAULT_POOLBLOCK, **pool_kwargs):
"""Initializes a urllib3 PoolManager.
This method should not be called from user code, and is only
exposed for use when subclassing the
:class:`HTTPAdapter <requests.adapters.HTTPAdapter>`.
:param connections: The number of urllib3 connection pools to cache.
:param maxsize: The maximum number of connections to save in the pool.
:param block: Block when no free connections are available.
:param pool_kwargs: Extra keyword arguments used to initialize the Pool Manager.
"""
# save these values for pickling
self._pool_connections = connections
self._pool_maxsize = maxsize
self._pool_block = block
self.poolmanager = PoolManager(num_pools=connections, maxsize=maxsize,
block=block, strict=True, **pool_kwargs)
|
[
"def",
"init_poolmanager",
"(",
"self",
",",
"connections",
",",
"maxsize",
",",
"block",
"=",
"DEFAULT_POOLBLOCK",
",",
"*",
"*",
"pool_kwargs",
")",
":",
"# save these values for pickling",
"self",
".",
"_pool_connections",
"=",
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"self",
".",
"_pool_maxsize",
"=",
"maxsize",
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"_pool_block",
"=",
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"poolmanager",
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"PoolManager",
"(",
"num_pools",
"=",
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"block",
"=",
"block",
",",
"strict",
"=",
"True",
",",
"*",
"*",
"pool_kwargs",
")"
] |
https://github.com/skylander86/lambda-text-extractor/blob/6da52d077a2fc571e38bfe29c33ae68f6443cd5a/lib-linux_x64/requests/adapters.py#L144-L162
|
||
ljvmiranda921/seagull
|
26828319066b53301170345ba28ae27cb795d1fd
|
seagull/board.py
|
python
|
Board.add
|
(self, lifeform: Lifeform, loc: Tuple[int, int])
|
Add a lifeform to the board
Parameters
----------
lifeform: :obj:`seagull.lifeforms.base.Lifeform`
A lifeform that can evolve in the board
loc : array_like of size 2
Initial location of the lifeform on the board
|
Add a lifeform to the board
|
[
"Add",
"a",
"lifeform",
"to",
"the",
"board"
] |
def add(self, lifeform: Lifeform, loc: Tuple[int, int]):
"""Add a lifeform to the board
Parameters
----------
lifeform: :obj:`seagull.lifeforms.base.Lifeform`
A lifeform that can evolve in the board
loc : array_like of size 2
Initial location of the lifeform on the board
"""
try:
row, col = loc
height, width = lifeform.size
self.state[row : row + height, col : col + width] = lifeform.layout
except ValueError:
logger.error("Lifeform is out-of-bounds!")
raise
|
[
"def",
"add",
"(",
"self",
",",
"lifeform",
":",
"Lifeform",
",",
"loc",
":",
"Tuple",
"[",
"int",
",",
"int",
"]",
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":",
"try",
":",
"row",
",",
"col",
"=",
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"height",
",",
"width",
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"size",
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"[",
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"ValueError",
":",
"logger",
".",
"error",
"(",
"\"Lifeform is out-of-bounds!\"",
")",
"raise"
] |
https://github.com/ljvmiranda921/seagull/blob/26828319066b53301170345ba28ae27cb795d1fd/seagull/board.py#L59-L75
|
||
HIPS/Spearmint
|
990d27d4477bbc9b0d5cfb2c950fc387decf6ea2
|
spearmint/resources/resource.py
|
python
|
Resource.acceptingJobs
|
(self, jobs)
|
return True
|
Is this resource currently accepting new jobs?
|
Is this resource currently accepting new jobs?
|
[
"Is",
"this",
"resource",
"currently",
"accepting",
"new",
"jobs?"
] |
def acceptingJobs(self, jobs):
"""Is this resource currently accepting new jobs?"""
if self.numPending(jobs) >= self.max_concurrent:
return False
if self.numComplete(jobs) >= self.max_finished_jobs:
return False
return True
|
[
"def",
"acceptingJobs",
"(",
"self",
",",
"jobs",
")",
":",
"if",
"self",
".",
"numPending",
"(",
"jobs",
")",
">=",
"self",
".",
"max_concurrent",
":",
"return",
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"self",
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"jobs",
")",
">=",
"self",
".",
"max_finished_jobs",
":",
"return",
"False",
"return",
"True"
] |
https://github.com/HIPS/Spearmint/blob/990d27d4477bbc9b0d5cfb2c950fc387decf6ea2/spearmint/resources/resource.py#L320-L328
|
|
jgagneastro/coffeegrindsize
|
22661ebd21831dba4cf32bfc6ba59fe3d49f879c
|
App/venv/lib/python3.7/site-packages/pip/_internal/vcs/__init__.py
|
python
|
VersionControl.switch
|
(self, dest, url, rev_options)
|
Switch the repo at ``dest`` to point to ``URL``.
Args:
rev_options: a RevOptions object.
|
Switch the repo at ``dest`` to point to ``URL``.
|
[
"Switch",
"the",
"repo",
"at",
"dest",
"to",
"point",
"to",
"URL",
"."
] |
def switch(self, dest, url, rev_options):
"""
Switch the repo at ``dest`` to point to ``URL``.
Args:
rev_options: a RevOptions object.
"""
raise NotImplementedError
|
[
"def",
"switch",
"(",
"self",
",",
"dest",
",",
"url",
",",
"rev_options",
")",
":",
"raise",
"NotImplementedError"
] |
https://github.com/jgagneastro/coffeegrindsize/blob/22661ebd21831dba4cf32bfc6ba59fe3d49f879c/App/venv/lib/python3.7/site-packages/pip/_internal/vcs/__init__.py#L396-L403
|
||
tlsfuzzer/tlslite-ng
|
8720db53067ba4f7bb7b5a32d682033d8b5446f9
|
tlslite/extensions.py
|
python
|
ALPNExtension.__repr__
|
(self)
|
return "ALPNExtension(protocol_names={0!r})"\
.format(self.protocol_names)
|
Create programmer-readable representation of object
:rtype: str
|
Create programmer-readable representation of object
|
[
"Create",
"programmer",
"-",
"readable",
"representation",
"of",
"object"
] |
def __repr__(self):
"""
Create programmer-readable representation of object
:rtype: str
"""
return "ALPNExtension(protocol_names={0!r})"\
.format(self.protocol_names)
|
[
"def",
"__repr__",
"(",
"self",
")",
":",
"return",
"\"ALPNExtension(protocol_names={0!r})\"",
".",
"format",
"(",
"self",
".",
"protocol_names",
")"
] |
https://github.com/tlsfuzzer/tlslite-ng/blob/8720db53067ba4f7bb7b5a32d682033d8b5446f9/tlslite/extensions.py#L1544-L1551
|
|
OkunaOrg/okuna-api
|
f87d8e80d2f182c01dbce68155ded0078ee707e4
|
openbook_communities/queries.py
|
python
|
make_search_communities_query_for_user
|
(query, user, excluded_from_profile_posts=True)
|
return search_communities_query
|
:param query:
:param user:
:param excluded_from_profile_posts: Whether to include the communities that were excluded from profile posts
:return:
|
:param query:
:param user:
:param excluded_from_profile_posts: Whether to include the communities that were excluded from profile posts
:return:
|
[
":",
"param",
"query",
":",
":",
"param",
"user",
":",
":",
"param",
"excluded_from_profile_posts",
":",
"Whether",
"to",
"include",
"the",
"communities",
"that",
"were",
"excluded",
"from",
"profile",
"posts",
":",
"return",
":"
] |
def make_search_communities_query_for_user(query, user, excluded_from_profile_posts=True):
"""
:param query:
:param user:
:param excluded_from_profile_posts: Whether to include the communities that were excluded from profile posts
:return:
"""
search_communities_query = make_search_communities_query(query=query)
if not excluded_from_profile_posts:
search_communities_query.add(make_exclude_excluded_communities_from_profile_posts_query_for_user(user=user),
Q.AND)
return search_communities_query
|
[
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"(",
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"=",
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"Q",
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"AND",
")",
"return",
"search_communities_query"
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https://github.com/OkunaOrg/okuna-api/blob/f87d8e80d2f182c01dbce68155ded0078ee707e4/openbook_communities/queries.py#L27-L40
|
|
blurstudio/cross3d
|
277968d1227de740fc87ef61005c75034420eadf
|
cross3d/abstract/abstractuserprops.py
|
python
|
AbstractUserProps.unescapeValue
|
(string)
|
return string
|
Replaces any html codes with their associated unstorable characters
|
Replaces any html codes with their associated unstorable characters
|
[
"Replaces",
"any",
"html",
"codes",
"with",
"their",
"associated",
"unstorable",
"characters"
] |
def unescapeValue(string):
"""
Replaces any html codes with their associated unstorable characters
"""
string = unicode(string)
try:
return json.loads( string )
except ValueError:
pass
string, typ = AbstractUserProps._decodeString(string)
if typ == float:
return float(string)
elif typ == int:
return int(string)
elif typ in (list, dict, tuple, bool, OrderedDict):
return eval(string)
return string
|
[
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"AbstractUserProps",
".",
"_decodeString",
"(",
"string",
")",
"if",
"typ",
"==",
"float",
":",
"return",
"float",
"(",
"string",
")",
"elif",
"typ",
"==",
"int",
":",
"return",
"int",
"(",
"string",
")",
"elif",
"typ",
"in",
"(",
"list",
",",
"dict",
",",
"tuple",
",",
"bool",
",",
"OrderedDict",
")",
":",
"return",
"eval",
"(",
"string",
")",
"return",
"string"
] |
https://github.com/blurstudio/cross3d/blob/277968d1227de740fc87ef61005c75034420eadf/cross3d/abstract/abstractuserprops.py#L199-L216
|
|
uber/petastorm
|
3579e68b86d17b57339efd0da1e8a56033d121d1
|
petastorm/codecs.py
|
python
|
CompressedImageCodec.__init__
|
(self, image_codec='png', quality=80)
|
CompressedImageCodec would compress/encompress images.
:param image_codec: any format string supported by opencv. e.g. ``png``, ``jpeg``
:param quality: used when using ``jpeg`` lossy compression
|
CompressedImageCodec would compress/encompress images.
|
[
"CompressedImageCodec",
"would",
"compress",
"/",
"encompress",
"images",
"."
] |
def __init__(self, image_codec='png', quality=80):
"""CompressedImageCodec would compress/encompress images.
:param image_codec: any format string supported by opencv. e.g. ``png``, ``jpeg``
:param quality: used when using ``jpeg`` lossy compression
"""
assert OPENCV_AVAILABLE, "{} requires opencv-python to be installed".format(type(self).__name__)
self._image_codec = '.' + image_codec
self._quality = quality
|
[
"def",
"__init__",
"(",
"self",
",",
"image_codec",
"=",
"'png'",
",",
"quality",
"=",
"80",
")",
":",
"assert",
"OPENCV_AVAILABLE",
",",
"\"{} requires opencv-python to be installed\"",
".",
"format",
"(",
"type",
"(",
"self",
")",
".",
"__name__",
")",
"self",
".",
"_image_codec",
"=",
"'.'",
"+",
"image_codec",
"self",
".",
"_quality",
"=",
"quality"
] |
https://github.com/uber/petastorm/blob/3579e68b86d17b57339efd0da1e8a56033d121d1/petastorm/codecs.py#L59-L68
|
||
dmeranda/demjson
|
5bc65974e7141746acc88c581f5d2dfb8ea14064
|
demjson.py
|
python
|
JSON.__sanity_check_start
|
(self, state)
|
return is_sane
|
Check that the document seems sane by looking at the first couple characters.
Check that the decoding seems sane. Per RFC 4627 section 3:
"Since the first two characters of a JSON text will
always be ASCII characters [RFC0020], ..."
[WAS removed from RFC 7158, but still valid via the grammar.]
This check is probably not necessary, but it allows us to
raise a suitably descriptive error rather than an obscure
syntax error later on.
Note that the RFC requirements of two ASCII characters seems
to be an incorrect statement as a JSON string literal may have
as it's first character any unicode character. Thus the first
two characters will always be ASCII, unless the first
character is a quotation mark. And in non-strict mode we can
also have a few other characters too.
|
Check that the document seems sane by looking at the first couple characters.
|
[
"Check",
"that",
"the",
"document",
"seems",
"sane",
"by",
"looking",
"at",
"the",
"first",
"couple",
"characters",
"."
] |
def __sanity_check_start(self, state):
"""Check that the document seems sane by looking at the first couple characters.
Check that the decoding seems sane. Per RFC 4627 section 3:
"Since the first two characters of a JSON text will
always be ASCII characters [RFC0020], ..."
[WAS removed from RFC 7158, but still valid via the grammar.]
This check is probably not necessary, but it allows us to
raise a suitably descriptive error rather than an obscure
syntax error later on.
Note that the RFC requirements of two ASCII characters seems
to be an incorrect statement as a JSON string literal may have
as it's first character any unicode character. Thus the first
two characters will always be ASCII, unless the first
character is a quotation mark. And in non-strict mode we can
also have a few other characters too.
"""
is_sane = True
unitxt = state.buf.peekstr(2)
if len(unitxt) >= 2:
first, second = unitxt[:2]
if first in self._string_quotes:
pass # second can be anything inside string literal
else:
if ((ord(first) < 0x20 or ord(first) > 0x7f) or \
(ord(second) < 0x20 or ord(second) > 0x7f)) and \
(not self.isws(first) and not self.isws(second)):
# Found non-printable ascii, must check unicode
# categories to see if the character is legal.
# Only whitespace, line and paragraph separators,
# and format control chars are legal here.
import unicodedata
catfirst = unicodedata.category(unicode(first))
catsecond = unicodedata.category(unicode(second))
if catfirst not in ('Zs','Zl','Zp','Cf') or \
catsecond not in ('Zs','Zl','Zp','Cf'):
state.push_fatal( 'The input is gibberish, is the Unicode encoding correct?' )
return is_sane
|
[
"def",
"__sanity_check_start",
"(",
"self",
",",
"state",
")",
":",
"is_sane",
"=",
"True",
"unitxt",
"=",
"state",
".",
"buf",
".",
"peekstr",
"(",
"2",
")",
"if",
"len",
"(",
"unitxt",
")",
">=",
"2",
":",
"first",
",",
"second",
"=",
"unitxt",
"[",
":",
"2",
"]",
"if",
"first",
"in",
"self",
".",
"_string_quotes",
":",
"pass",
"# second can be anything inside string literal",
"else",
":",
"if",
"(",
"(",
"ord",
"(",
"first",
")",
"<",
"0x20",
"or",
"ord",
"(",
"first",
")",
">",
"0x7f",
")",
"or",
"(",
"ord",
"(",
"second",
")",
"<",
"0x20",
"or",
"ord",
"(",
"second",
")",
">",
"0x7f",
")",
")",
"and",
"(",
"not",
"self",
".",
"isws",
"(",
"first",
")",
"and",
"not",
"self",
".",
"isws",
"(",
"second",
")",
")",
":",
"# Found non-printable ascii, must check unicode",
"# categories to see if the character is legal.",
"# Only whitespace, line and paragraph separators,",
"# and format control chars are legal here.",
"import",
"unicodedata",
"catfirst",
"=",
"unicodedata",
".",
"category",
"(",
"unicode",
"(",
"first",
")",
")",
"catsecond",
"=",
"unicodedata",
".",
"category",
"(",
"unicode",
"(",
"second",
")",
")",
"if",
"catfirst",
"not",
"in",
"(",
"'Zs'",
",",
"'Zl'",
",",
"'Zp'",
",",
"'Cf'",
")",
"or",
"catsecond",
"not",
"in",
"(",
"'Zs'",
",",
"'Zl'",
",",
"'Zp'",
",",
"'Cf'",
")",
":",
"state",
".",
"push_fatal",
"(",
"'The input is gibberish, is the Unicode encoding correct?'",
")",
"return",
"is_sane"
] |
https://github.com/dmeranda/demjson/blob/5bc65974e7141746acc88c581f5d2dfb8ea14064/demjson.py#L4923-L4963
|
|
microsoft/unilm
|
65f15af2a307ebb64cfb25adf54375b002e6fe8d
|
xtune/src/transformers/data/processors/glue.py
|
python
|
RteProcessor.get_example_from_tensor_dict
|
(self, tensor_dict)
|
return InputExample(
tensor_dict["idx"].numpy(),
tensor_dict["sentence1"].numpy().decode("utf-8"),
tensor_dict["sentence2"].numpy().decode("utf-8"),
str(tensor_dict["label"].numpy()),
)
|
See base class.
|
See base class.
|
[
"See",
"base",
"class",
"."
] |
def get_example_from_tensor_dict(self, tensor_dict):
"""See base class."""
return InputExample(
tensor_dict["idx"].numpy(),
tensor_dict["sentence1"].numpy().decode("utf-8"),
tensor_dict["sentence2"].numpy().decode("utf-8"),
str(tensor_dict["label"].numpy()),
)
|
[
"def",
"get_example_from_tensor_dict",
"(",
"self",
",",
"tensor_dict",
")",
":",
"return",
"InputExample",
"(",
"tensor_dict",
"[",
"\"idx\"",
"]",
".",
"numpy",
"(",
")",
",",
"tensor_dict",
"[",
"\"sentence1\"",
"]",
".",
"numpy",
"(",
")",
".",
"decode",
"(",
"\"utf-8\"",
")",
",",
"tensor_dict",
"[",
"\"sentence2\"",
"]",
".",
"numpy",
"(",
")",
".",
"decode",
"(",
"\"utf-8\"",
")",
",",
"str",
"(",
"tensor_dict",
"[",
"\"label\"",
"]",
".",
"numpy",
"(",
")",
")",
",",
")"
] |
https://github.com/microsoft/unilm/blob/65f15af2a307ebb64cfb25adf54375b002e6fe8d/xtune/src/transformers/data/processors/glue.py#L446-L453
|
|
bugy/script-server
|
9a57ce15903c81bcb537b872f1330ee55ba31563
|
src/react/observable.py
|
python
|
Observable.__init__
|
(self)
|
[] |
def __init__(self):
super().__init__()
|
[
"def",
"__init__",
"(",
"self",
")",
":",
"super",
"(",
")",
".",
"__init__",
"(",
")"
] |
https://github.com/bugy/script-server/blob/9a57ce15903c81bcb537b872f1330ee55ba31563/src/react/observable.py#L104-L105
|
||||
scikit-learn/scikit-learn
|
1d1aadd0711b87d2a11c80aad15df6f8cf156712
|
examples/applications/plot_model_complexity_influence.py
|
python
|
benchmark_influence
|
(conf)
|
return prediction_powers, prediction_times, complexities
|
Benchmark influence of `changing_param` on both MSE and latency.
|
Benchmark influence of `changing_param` on both MSE and latency.
|
[
"Benchmark",
"influence",
"of",
"changing_param",
"on",
"both",
"MSE",
"and",
"latency",
"."
] |
def benchmark_influence(conf):
"""
Benchmark influence of `changing_param` on both MSE and latency.
"""
prediction_times = []
prediction_powers = []
complexities = []
for param_value in conf["changing_param_values"]:
conf["tuned_params"][conf["changing_param"]] = param_value
estimator = conf["estimator"](**conf["tuned_params"])
print("Benchmarking %s" % estimator)
estimator.fit(conf["data"]["X_train"], conf["data"]["y_train"])
conf["postfit_hook"](estimator)
complexity = conf["complexity_computer"](estimator)
complexities.append(complexity)
start_time = time.time()
for _ in range(conf["n_samples"]):
y_pred = estimator.predict(conf["data"]["X_test"])
elapsed_time = (time.time() - start_time) / float(conf["n_samples"])
prediction_times.append(elapsed_time)
pred_score = conf["prediction_performance_computer"](
conf["data"]["y_test"], y_pred
)
prediction_powers.append(pred_score)
print(
"Complexity: %d | %s: %.4f | Pred. Time: %fs\n"
% (
complexity,
conf["prediction_performance_label"],
pred_score,
elapsed_time,
)
)
return prediction_powers, prediction_times, complexities
|
[
"def",
"benchmark_influence",
"(",
"conf",
")",
":",
"prediction_times",
"=",
"[",
"]",
"prediction_powers",
"=",
"[",
"]",
"complexities",
"=",
"[",
"]",
"for",
"param_value",
"in",
"conf",
"[",
"\"changing_param_values\"",
"]",
":",
"conf",
"[",
"\"tuned_params\"",
"]",
"[",
"conf",
"[",
"\"changing_param\"",
"]",
"]",
"=",
"param_value",
"estimator",
"=",
"conf",
"[",
"\"estimator\"",
"]",
"(",
"*",
"*",
"conf",
"[",
"\"tuned_params\"",
"]",
")",
"print",
"(",
"\"Benchmarking %s\"",
"%",
"estimator",
")",
"estimator",
".",
"fit",
"(",
"conf",
"[",
"\"data\"",
"]",
"[",
"\"X_train\"",
"]",
",",
"conf",
"[",
"\"data\"",
"]",
"[",
"\"y_train\"",
"]",
")",
"conf",
"[",
"\"postfit_hook\"",
"]",
"(",
"estimator",
")",
"complexity",
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"conf",
"[",
"\"complexity_computer\"",
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"(",
"estimator",
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"complexities",
".",
"append",
"(",
"complexity",
")",
"start_time",
"=",
"time",
".",
"time",
"(",
")",
"for",
"_",
"in",
"range",
"(",
"conf",
"[",
"\"n_samples\"",
"]",
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"y_pred",
"=",
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".",
"predict",
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"\"data\"",
"]",
"[",
"\"X_test\"",
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")",
"elapsed_time",
"=",
"(",
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".",
"time",
"(",
")",
"-",
"start_time",
")",
"/",
"float",
"(",
"conf",
"[",
"\"n_samples\"",
"]",
")",
"prediction_times",
".",
"append",
"(",
"elapsed_time",
")",
"pred_score",
"=",
"conf",
"[",
"\"prediction_performance_computer\"",
"]",
"(",
"conf",
"[",
"\"data\"",
"]",
"[",
"\"y_test\"",
"]",
",",
"y_pred",
")",
"prediction_powers",
".",
"append",
"(",
"pred_score",
")",
"print",
"(",
"\"Complexity: %d | %s: %.4f | Pred. Time: %fs\\n\"",
"%",
"(",
"complexity",
",",
"conf",
"[",
"\"prediction_performance_label\"",
"]",
",",
"pred_score",
",",
"elapsed_time",
",",
")",
")",
"return",
"prediction_powers",
",",
"prediction_times",
",",
"complexities"
] |
https://github.com/scikit-learn/scikit-learn/blob/1d1aadd0711b87d2a11c80aad15df6f8cf156712/examples/applications/plot_model_complexity_influence.py#L103-L137
|
|
gleeda/memtriage
|
c24f4859995cccb9d88ccc0118d90693019cc1d5
|
volatility/volatility/plugins/overlays/windows/kpcr_vtypes.py
|
python
|
_KPCROnx86.get_kdbg
|
(self)
|
return DebuggerDataList.dereference().dereference_as("_KDDEBUGGER_DATA64")
|
Find this CPUs KDBG.
Please note the KdVersionBlock pointer is NULL on
all KPCR structures except the one for the first CPU.
In some cases on x64, even the first CPU has a NULL
KdVersionBlock, so this is really a hit-or-miss.
|
Find this CPUs KDBG.
|
[
"Find",
"this",
"CPUs",
"KDBG",
"."
] |
def get_kdbg(self):
"""Find this CPUs KDBG.
Please note the KdVersionBlock pointer is NULL on
all KPCR structures except the one for the first CPU.
In some cases on x64, even the first CPU has a NULL
KdVersionBlock, so this is really a hit-or-miss.
"""
DebuggerDataList = self.KdVersionBlock.dereference_as("_DBGKD_GET_VERSION64").DebuggerDataList
# DebuggerDataList is a pointer to unsigned long on x86
# and a pointer to unsigned long long on x64. The first
# dereference() dereferences the pointer, and the second
# dereference() dereferences the unsigned long or long long
# as the actual KDBG address.
return DebuggerDataList.dereference().dereference_as("_KDDEBUGGER_DATA64")
|
[
"def",
"get_kdbg",
"(",
"self",
")",
":",
"DebuggerDataList",
"=",
"self",
".",
"KdVersionBlock",
".",
"dereference_as",
"(",
"\"_DBGKD_GET_VERSION64\"",
")",
".",
"DebuggerDataList",
"# DebuggerDataList is a pointer to unsigned long on x86 ",
"# and a pointer to unsigned long long on x64. The first ",
"# dereference() dereferences the pointer, and the second ",
"# dereference() dereferences the unsigned long or long long",
"# as the actual KDBG address. ",
"return",
"DebuggerDataList",
".",
"dereference",
"(",
")",
".",
"dereference_as",
"(",
"\"_KDDEBUGGER_DATA64\"",
")"
] |
https://github.com/gleeda/memtriage/blob/c24f4859995cccb9d88ccc0118d90693019cc1d5/volatility/volatility/plugins/overlays/windows/kpcr_vtypes.py#L34-L49
|
|
holzschu/Carnets
|
44effb10ddfc6aa5c8b0687582a724ba82c6b547
|
Library/lib/python3.7/site-packages/docutils/nodes.py
|
python
|
Node.walk
|
(self, visitor)
|
return stop
|
Traverse a tree of `Node` objects, calling the
`dispatch_visit()` method of `visitor` when entering each
node. (The `walkabout()` method is similar, except it also
calls the `dispatch_departure()` method before exiting each
node.)
This tree traversal supports limited in-place tree
modifications. Replacing one node with one or more nodes is
OK, as is removing an element. However, if the node removed
or replaced occurs after the current node, the old node will
still be traversed, and any new nodes will not.
Within ``visit`` methods (and ``depart`` methods for
`walkabout()`), `TreePruningException` subclasses may be raised
(`SkipChildren`, `SkipSiblings`, `SkipNode`, `SkipDeparture`).
Parameter `visitor`: A `NodeVisitor` object, containing a
``visit`` implementation for each `Node` subclass encountered.
Return true if we should stop the traversal.
|
Traverse a tree of `Node` objects, calling the
`dispatch_visit()` method of `visitor` when entering each
node. (The `walkabout()` method is similar, except it also
calls the `dispatch_departure()` method before exiting each
node.)
|
[
"Traverse",
"a",
"tree",
"of",
"Node",
"objects",
"calling",
"the",
"dispatch_visit",
"()",
"method",
"of",
"visitor",
"when",
"entering",
"each",
"node",
".",
"(",
"The",
"walkabout",
"()",
"method",
"is",
"similar",
"except",
"it",
"also",
"calls",
"the",
"dispatch_departure",
"()",
"method",
"before",
"exiting",
"each",
"node",
".",
")"
] |
def walk(self, visitor):
"""
Traverse a tree of `Node` objects, calling the
`dispatch_visit()` method of `visitor` when entering each
node. (The `walkabout()` method is similar, except it also
calls the `dispatch_departure()` method before exiting each
node.)
This tree traversal supports limited in-place tree
modifications. Replacing one node with one or more nodes is
OK, as is removing an element. However, if the node removed
or replaced occurs after the current node, the old node will
still be traversed, and any new nodes will not.
Within ``visit`` methods (and ``depart`` methods for
`walkabout()`), `TreePruningException` subclasses may be raised
(`SkipChildren`, `SkipSiblings`, `SkipNode`, `SkipDeparture`).
Parameter `visitor`: A `NodeVisitor` object, containing a
``visit`` implementation for each `Node` subclass encountered.
Return true if we should stop the traversal.
"""
stop = False
visitor.document.reporter.debug(
'docutils.nodes.Node.walk calling dispatch_visit for %s'
% self.__class__.__name__)
try:
try:
visitor.dispatch_visit(self)
except (SkipChildren, SkipNode):
return stop
except SkipDeparture: # not applicable; ignore
pass
children = self.children
try:
for child in children[:]:
if child.walk(visitor):
stop = True
break
except SkipSiblings:
pass
except StopTraversal:
stop = True
return stop
|
[
"def",
"walk",
"(",
"self",
",",
"visitor",
")",
":",
"stop",
"=",
"False",
"visitor",
".",
"document",
".",
"reporter",
".",
"debug",
"(",
"'docutils.nodes.Node.walk calling dispatch_visit for %s'",
"%",
"self",
".",
"__class__",
".",
"__name__",
")",
"try",
":",
"try",
":",
"visitor",
".",
"dispatch_visit",
"(",
"self",
")",
"except",
"(",
"SkipChildren",
",",
"SkipNode",
")",
":",
"return",
"stop",
"except",
"SkipDeparture",
":",
"# not applicable; ignore",
"pass",
"children",
"=",
"self",
".",
"children",
"try",
":",
"for",
"child",
"in",
"children",
"[",
":",
"]",
":",
"if",
"child",
".",
"walk",
"(",
"visitor",
")",
":",
"stop",
"=",
"True",
"break",
"except",
"SkipSiblings",
":",
"pass",
"except",
"StopTraversal",
":",
"stop",
"=",
"True",
"return",
"stop"
] |
https://github.com/holzschu/Carnets/blob/44effb10ddfc6aa5c8b0687582a724ba82c6b547/Library/lib/python3.7/site-packages/docutils/nodes.py#L101-L145
|
|
khanhnamle1994/natural-language-processing
|
01d450d5ac002b0156ef4cf93a07cb508c1bcdc5
|
assignment1/.env/lib/python2.7/site-packages/pip/_vendor/distlib/_backport/tarfile.py
|
python
|
TarFile.open
|
(cls, name=None, mode="r", fileobj=None, bufsize=RECORDSIZE, **kwargs)
|
Open a tar archive for reading, writing or appending. Return
an appropriate TarFile class.
mode:
'r' or 'r:*' open for reading with transparent compression
'r:' open for reading exclusively uncompressed
'r:gz' open for reading with gzip compression
'r:bz2' open for reading with bzip2 compression
'a' or 'a:' open for appending, creating the file if necessary
'w' or 'w:' open for writing without compression
'w:gz' open for writing with gzip compression
'w:bz2' open for writing with bzip2 compression
'r|*' open a stream of tar blocks with transparent compression
'r|' open an uncompressed stream of tar blocks for reading
'r|gz' open a gzip compressed stream of tar blocks
'r|bz2' open a bzip2 compressed stream of tar blocks
'w|' open an uncompressed stream for writing
'w|gz' open a gzip compressed stream for writing
'w|bz2' open a bzip2 compressed stream for writing
|
Open a tar archive for reading, writing or appending. Return
an appropriate TarFile class.
|
[
"Open",
"a",
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"for",
"reading",
"writing",
"or",
"appending",
".",
"Return",
"an",
"appropriate",
"TarFile",
"class",
"."
] |
def open(cls, name=None, mode="r", fileobj=None, bufsize=RECORDSIZE, **kwargs):
"""Open a tar archive for reading, writing or appending. Return
an appropriate TarFile class.
mode:
'r' or 'r:*' open for reading with transparent compression
'r:' open for reading exclusively uncompressed
'r:gz' open for reading with gzip compression
'r:bz2' open for reading with bzip2 compression
'a' or 'a:' open for appending, creating the file if necessary
'w' or 'w:' open for writing without compression
'w:gz' open for writing with gzip compression
'w:bz2' open for writing with bzip2 compression
'r|*' open a stream of tar blocks with transparent compression
'r|' open an uncompressed stream of tar blocks for reading
'r|gz' open a gzip compressed stream of tar blocks
'r|bz2' open a bzip2 compressed stream of tar blocks
'w|' open an uncompressed stream for writing
'w|gz' open a gzip compressed stream for writing
'w|bz2' open a bzip2 compressed stream for writing
"""
if not name and not fileobj:
raise ValueError("nothing to open")
if mode in ("r", "r:*"):
# Find out which *open() is appropriate for opening the file.
for comptype in cls.OPEN_METH:
func = getattr(cls, cls.OPEN_METH[comptype])
if fileobj is not None:
saved_pos = fileobj.tell()
try:
return func(name, "r", fileobj, **kwargs)
except (ReadError, CompressionError) as e:
if fileobj is not None:
fileobj.seek(saved_pos)
continue
raise ReadError("file could not be opened successfully")
elif ":" in mode:
filemode, comptype = mode.split(":", 1)
filemode = filemode or "r"
comptype = comptype or "tar"
# Select the *open() function according to
# given compression.
if comptype in cls.OPEN_METH:
func = getattr(cls, cls.OPEN_METH[comptype])
else:
raise CompressionError("unknown compression type %r" % comptype)
return func(name, filemode, fileobj, **kwargs)
elif "|" in mode:
filemode, comptype = mode.split("|", 1)
filemode = filemode or "r"
comptype = comptype or "tar"
if filemode not in "rw":
raise ValueError("mode must be 'r' or 'w'")
stream = _Stream(name, filemode, comptype, fileobj, bufsize)
try:
t = cls(name, filemode, stream, **kwargs)
except:
stream.close()
raise
t._extfileobj = False
return t
elif mode in "aw":
return cls.taropen(name, mode, fileobj, **kwargs)
raise ValueError("undiscernible mode")
|
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] |
https://github.com/khanhnamle1994/natural-language-processing/blob/01d450d5ac002b0156ef4cf93a07cb508c1bcdc5/assignment1/.env/lib/python2.7/site-packages/pip/_vendor/distlib/_backport/tarfile.py#L1714-L1787
|
||
mandarjoshi90/coref
|
bd04f2e19b9dcc0b8bba848a335e4af3be50741c
|
conll-2012/v3/scripts/conll2name.py
|
python
|
load_config
|
(cfg_name=None, config_append=[])
|
return config
|
Load a configuration file to memory.
The given configuration file name can be a full path, in which
case we simply read that configuration file. Otherwise, if you
give 'myconfig' or something similar, we look in the current
directory and the home directory. We also look to see if files
with this name and extension '.conf' exist. So for 'myconfig' we
would look in the following places:
* ./myconfig
* ./myconfig.conf
* [home]/.myconfig
* [home]/.myconfig.conf
Once we find the configuration, we load it. We also extend
ConfigParser to support ``[]`` notation. So you could look up key
``k`` in section ``s`` with ``config[s,k]``. See
:func:`FancyConfigParser` .
If config_append is set we use :func:`parse_cfg_args` and add any
values it creates to the config object. These values override any
previous ones.
|
Load a configuration file to memory.
|
[
"Load",
"a",
"configuration",
"file",
"to",
"memory",
"."
] |
def load_config(cfg_name=None, config_append=[]):
""" Load a configuration file to memory.
The given configuration file name can be a full path, in which
case we simply read that configuration file. Otherwise, if you
give 'myconfig' or something similar, we look in the current
directory and the home directory. We also look to see if files
with this name and extension '.conf' exist. So for 'myconfig' we
would look in the following places:
* ./myconfig
* ./myconfig.conf
* [home]/.myconfig
* [home]/.myconfig.conf
Once we find the configuration, we load it. We also extend
ConfigParser to support ``[]`` notation. So you could look up key
``k`` in section ``s`` with ``config[s,k]``. See
:func:`FancyConfigParser` .
If config_append is set we use :func:`parse_cfg_args` and add any
values it creates to the config object. These values override any
previous ones.
"""
config = FancyConfigParser()
if cfg_name:
config_locs = [cfg_name + '.conf',
os.path.expanduser('~/.' + cfg_name + '.conf'),
cfg_name,
os.path.expanduser('~/.' + cfg_name)]
l = config.read(config_locs)
if not l:
raise Exception("Couldn't find config file. Looked in:" +
"".join(["\n - " + c for c in config_locs]) +
"\nto no avail.")
for (section, key_name), value in parse_cfg_args(config_append).iteritems():
if not config.has_section(section):
config.add_section(section)
config.set(section, key_name, value)
problems = []
for section in config.sections():
if not is_config_section_registered(section):
on.common.log.status("Ignoring unknown configuration section", section)
continue
for option in config.options(section):
if not is_config_registered(section, option):
problems.append("Unknown configuration variable %s.%s" % (section, option))
continue
value = config.get(section, option)
allowed = allowed_config_values(section, option)
multiple = allow_multiple_config_values(section, option)
values = value.split() if multiple else [value]
for value in values:
if allowed and not value in allowed:
problems.append("Illegal value '%s' for configuration variable %s.%s. Permitted values are: %s" %
(value, section, option, ", ".join(["'%s'" % x for x in allowed])))
for option in required_config_options(section):
if not config.has_option(section, option):
problems.append("Required configuration variable %s.%s is absent" % (section, option))
for section in required_config_sections():
if not config.has_section(section):
problems.append("Required configuration section %s is absent" % section)
if problems:
print_config_docs()
on.common.log.status("Configuration Problems:")
for problem in problems:
on.common.log.status(" " + problem)
sys.exit(-1)
return config
|
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"(",
"-",
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")",
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] |
https://github.com/mandarjoshi90/coref/blob/bd04f2e19b9dcc0b8bba848a335e4af3be50741c/conll-2012/v3/scripts/conll2name.py#L257-L339
|
|
plaid/plaid-python
|
8c60fca608e426f3ff30da8857775946d29e122c
|
plaid/model/income_verification_status_webhook.py
|
python
|
IncomeVerificationStatusWebhook.openapi_types
|
()
|
return {
'webhook_type': (str,), # noqa: E501
'webhook_code': (str,), # noqa: E501
'income_verification_id': (str,), # noqa: E501
'item_id': (str,), # noqa: E501
'verification_status': (str,), # noqa: E501
}
|
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type.
|
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
|
[
"This",
"must",
"be",
"a",
"method",
"because",
"a",
"model",
"may",
"have",
"properties",
"that",
"are",
"of",
"type",
"self",
"this",
"must",
"run",
"after",
"the",
"class",
"is",
"loaded"
] |
def openapi_types():
"""
This must be a method because a model may have properties that are
of type self, this must run after the class is loaded
Returns
openapi_types (dict): The key is attribute name
and the value is attribute type.
"""
return {
'webhook_type': (str,), # noqa: E501
'webhook_code': (str,), # noqa: E501
'income_verification_id': (str,), # noqa: E501
'item_id': (str,), # noqa: E501
'verification_status': (str,), # noqa: E501
}
|
[
"def",
"openapi_types",
"(",
")",
":",
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"{",
"'webhook_type'",
":",
"(",
"str",
",",
")",
",",
"# noqa: E501",
"'webhook_code'",
":",
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",",
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",",
"# noqa: E501",
"'income_verification_id'",
":",
"(",
"str",
",",
")",
",",
"# noqa: E501",
"'item_id'",
":",
"(",
"str",
",",
")",
",",
"# noqa: E501",
"'verification_status'",
":",
"(",
"str",
",",
")",
",",
"# noqa: E501",
"}"
] |
https://github.com/plaid/plaid-python/blob/8c60fca608e426f3ff30da8857775946d29e122c/plaid/model/income_verification_status_webhook.py#L69-L84
|
|
python-cmd2/cmd2
|
c1f6114d52161a3b8a32d3cee1c495d79052e1fb
|
cmd2/py_bridge.py
|
python
|
PyBridge.__dir__
|
(self)
|
return attributes
|
Return a custom set of attribute names
|
Return a custom set of attribute names
|
[
"Return",
"a",
"custom",
"set",
"of",
"attribute",
"names"
] |
def __dir__(self) -> List[str]:
"""Return a custom set of attribute names"""
attributes: List[str] = []
attributes.insert(0, 'cmd_echo')
return attributes
|
[
"def",
"__dir__",
"(",
"self",
")",
"->",
"List",
"[",
"str",
"]",
":",
"attributes",
":",
"List",
"[",
"str",
"]",
"=",
"[",
"]",
"attributes",
".",
"insert",
"(",
"0",
",",
"'cmd_echo'",
")",
"return",
"attributes"
] |
https://github.com/python-cmd2/cmd2/blob/c1f6114d52161a3b8a32d3cee1c495d79052e1fb/cmd2/py_bridge.py#L95-L99
|
|
nucleic/enaml
|
65c2a2a2d765e88f2e1103046680571894bb41ed
|
enaml/layout/geometry.py
|
python
|
BaseBox.right
|
(self)
|
return self[1]
|
The 'right' component of the box.
|
The 'right' component of the box.
|
[
"The",
"right",
"component",
"of",
"the",
"box",
"."
] |
def right(self):
""" The 'right' component of the box.
"""
return self[1]
|
[
"def",
"right",
"(",
"self",
")",
":",
"return",
"self",
"[",
"1",
"]"
] |
https://github.com/nucleic/enaml/blob/65c2a2a2d765e88f2e1103046680571894bb41ed/enaml/layout/geometry.py#L193-L197
|
|
jorgebastida/django-dajaxice
|
bf41c7623804856326b09f0724b4cb7d14440d7e
|
dajaxice/core/Dajaxice.py
|
python
|
Dajaxice.clean_method
|
(self, method)
|
return method
|
Clean the http method.
|
Clean the http method.
|
[
"Clean",
"the",
"http",
"method",
"."
] |
def clean_method(self, method):
""" Clean the http method. """
method = method.upper()
if method not in ['GET', 'POST']:
method = 'POST'
return method
|
[
"def",
"clean_method",
"(",
"self",
",",
"method",
")",
":",
"method",
"=",
"method",
".",
"upper",
"(",
")",
"if",
"method",
"not",
"in",
"[",
"'GET'",
",",
"'POST'",
"]",
":",
"method",
"=",
"'POST'",
"return",
"method"
] |
https://github.com/jorgebastida/django-dajaxice/blob/bf41c7623804856326b09f0724b4cb7d14440d7e/dajaxice/core/Dajaxice.py#L86-L91
|
|
Alexey-T/CudaText
|
6a8b9a974c5d5029c6c273bde83198c83b3a5fb9
|
app/py/sys/urllib3/poolmanager.py
|
python
|
ProxyManager.urlopen
|
(self, method, url, redirect=True, **kw)
|
return super(ProxyManager, self).urlopen(method, url, redirect=redirect, **kw)
|
Same as HTTP(S)ConnectionPool.urlopen, ``url`` must be absolute.
|
Same as HTTP(S)ConnectionPool.urlopen, ``url`` must be absolute.
|
[
"Same",
"as",
"HTTP",
"(",
"S",
")",
"ConnectionPool",
".",
"urlopen",
"url",
"must",
"be",
"absolute",
"."
] |
def urlopen(self, method, url, redirect=True, **kw):
"Same as HTTP(S)ConnectionPool.urlopen, ``url`` must be absolute."
u = parse_url(url)
if not connection_requires_http_tunnel(self.proxy, self.proxy_config, u.scheme):
# For connections using HTTP CONNECT, httplib sets the necessary
# headers on the CONNECT to the proxy. If we're not using CONNECT,
# we'll definitely need to set 'Host' at the very least.
headers = kw.get("headers", self.headers)
kw["headers"] = self._set_proxy_headers(url, headers)
return super(ProxyManager, self).urlopen(method, url, redirect=redirect, **kw)
|
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https://github.com/Alexey-T/CudaText/blob/6a8b9a974c5d5029c6c273bde83198c83b3a5fb9/app/py/sys/urllib3/poolmanager.py#L522-L532
|
|
dask/dask
|
c2b962fec1ba45440fe928869dc64cfe9cc36506
|
dask/dataframe/io/io.py
|
python
|
from_bcolz
|
(x, chunksize=None, categorize=True, index=None, lock=lock, **kwargs)
|
Read BColz CTable into a Dask Dataframe
BColz is a fast on-disk compressed column store with careful attention
given to compression. https://bcolz.readthedocs.io/en/latest/
Parameters
----------
x : bcolz.ctable
chunksize : int, optional
The size(rows) of blocks to pull out from ctable.
categorize : bool, defaults to True
Automatically categorize all string dtypes
index : string, optional
Column to make the index
lock: bool or Lock
Lock to use when reading or False for no lock (not-thread-safe)
See Also
--------
from_array: more generic function not optimized for bcolz
|
Read BColz CTable into a Dask Dataframe
|
[
"Read",
"BColz",
"CTable",
"into",
"a",
"Dask",
"Dataframe"
] |
def from_bcolz(x, chunksize=None, categorize=True, index=None, lock=lock, **kwargs):
"""Read BColz CTable into a Dask Dataframe
BColz is a fast on-disk compressed column store with careful attention
given to compression. https://bcolz.readthedocs.io/en/latest/
Parameters
----------
x : bcolz.ctable
chunksize : int, optional
The size(rows) of blocks to pull out from ctable.
categorize : bool, defaults to True
Automatically categorize all string dtypes
index : string, optional
Column to make the index
lock: bool or Lock
Lock to use when reading or False for no lock (not-thread-safe)
See Also
--------
from_array: more generic function not optimized for bcolz
"""
if lock is True:
lock = Lock()
import bcolz
import dask.array as da
if isinstance(x, str):
x = bcolz.ctable(rootdir=x)
bc_chunklen = max(x[name].chunklen for name in x.names)
if chunksize is None and bc_chunklen > 10000:
chunksize = bc_chunklen
categories = dict()
if categorize:
for name in x.names:
if (
np.issubdtype(x.dtype[name], np.string_)
or np.issubdtype(x.dtype[name], np.unicode_)
or np.issubdtype(x.dtype[name], np.object_)
):
a = da.from_array(x[name], chunks=(chunksize * len(x.names),))
categories[name] = da.unique(a).compute()
columns = tuple(x.dtype.names)
divisions = tuple(range(0, len(x), chunksize))
divisions = divisions + (len(x) - 1,)
if x.rootdir:
token = tokenize(
(x.rootdir, os.path.getmtime(x.rootdir)),
chunksize,
categorize,
index,
kwargs,
)
else:
token = tokenize(
(id(x), x.shape, x.dtype), chunksize, categorize, index, kwargs
)
new_name = "from_bcolz-" + token
dsk = {
(new_name, i): (
dataframe_from_ctable,
x,
(slice(i * chunksize, (i + 1) * chunksize),),
columns,
categories,
lock,
)
for i in range(0, int(ceil(len(x) / chunksize)))
}
meta = dataframe_from_ctable(x, slice(0, 0), columns, categories, lock)
result = DataFrame(dsk, new_name, meta, divisions)
if index:
assert index in x.names
a = da.from_array(x[index], chunks=(chunksize * len(x.names),))
q = np.linspace(0, 100, len(x) // chunksize + 2)
divisions = tuple(da.percentile(a, q).compute())
return set_partition(result, index, divisions, **kwargs)
else:
return result
|
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https://github.com/dask/dask/blob/c2b962fec1ba45440fe928869dc64cfe9cc36506/dask/dataframe/io/io.py#L235-L320
|
||
1040003585/WebScrapingWithPython
|
a770fa5b03894076c8c9539b1ffff34424ffc016
|
portia_examle/lib/python2.7/site-packages/pip/_vendor/html5lib/_inputstream.py
|
python
|
HTMLUnicodeInputStream.char
|
(self)
|
return char
|
Read one character from the stream or queue if available. Return
EOF when EOF is reached.
|
Read one character from the stream or queue if available. Return
EOF when EOF is reached.
|
[
"Read",
"one",
"character",
"from",
"the",
"stream",
"or",
"queue",
"if",
"available",
".",
"Return",
"EOF",
"when",
"EOF",
"is",
"reached",
"."
] |
def char(self):
""" Read one character from the stream or queue if available. Return
EOF when EOF is reached.
"""
# Read a new chunk from the input stream if necessary
if self.chunkOffset >= self.chunkSize:
if not self.readChunk():
return EOF
chunkOffset = self.chunkOffset
char = self.chunk[chunkOffset]
self.chunkOffset = chunkOffset + 1
return char
|
[
"def",
"char",
"(",
"self",
")",
":",
"# Read a new chunk from the input stream if necessary",
"if",
"self",
".",
"chunkOffset",
">=",
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"+",
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] |
https://github.com/1040003585/WebScrapingWithPython/blob/a770fa5b03894076c8c9539b1ffff34424ffc016/portia_examle/lib/python2.7/site-packages/pip/_vendor/html5lib/_inputstream.py#L240-L253
|
|
dimagi/commcare-hq
|
d67ff1d3b4c51fa050c19e60c3253a79d3452a39
|
corehq/apps/app_manager/suite_xml/features/mobile_ucr.py
|
python
|
ReportModuleSuiteHelper.__init__
|
(self, report_module)
|
[] |
def __init__(self, report_module):
assert isinstance(report_module, ReportModule)
self.report_module = report_module
self.domain = self.app.domain
self._loaded = None
|
[
"def",
"__init__",
"(",
"self",
",",
"report_module",
")",
":",
"assert",
"isinstance",
"(",
"report_module",
",",
"ReportModule",
")",
"self",
".",
"report_module",
"=",
"report_module",
"self",
".",
"domain",
"=",
"self",
".",
"app",
".",
"domain",
"self",
".",
"_loaded",
"=",
"None"
] |
https://github.com/dimagi/commcare-hq/blob/d67ff1d3b4c51fa050c19e60c3253a79d3452a39/corehq/apps/app_manager/suite_xml/features/mobile_ucr.py#L77-L81
|
||||
jliljebl/flowblade
|
995313a509b80e99eb1ad550d945bdda5995093b
|
flowblade-trunk/Flowblade/tools/titler.py
|
python
|
Titler._keep_layers_toggled
|
(self, widget)
|
[] |
def _keep_layers_toggled(self, widget):
global _keep_titler_data
_keep_titler_data = widget.get_active()
|
[
"def",
"_keep_layers_toggled",
"(",
"self",
",",
"widget",
")",
":",
"global",
"_keep_titler_data",
"_keep_titler_data",
"=",
"widget",
".",
"get_active",
"(",
")"
] |
https://github.com/jliljebl/flowblade/blob/995313a509b80e99eb1ad550d945bdda5995093b/flowblade-trunk/Flowblade/tools/titler.py#L762-L764
|
||||
learningequality/kolibri
|
d056dbc477aaf651ab843caa141a6a1e0a491046
|
kolibri/core/content/api.py
|
python
|
RemoteChannelViewSet._studio_response_to_kolibri_response
|
(cls, studioresp)
|
return resp
|
This modifies the JSON response returned by Kolibri Studio,
and then transforms its keys that are more in line with the keys
we return with /api/channels.
|
This modifies the JSON response returned by Kolibri Studio,
and then transforms its keys that are more in line with the keys
we return with /api/channels.
|
[
"This",
"modifies",
"the",
"JSON",
"response",
"returned",
"by",
"Kolibri",
"Studio",
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"line",
"with",
"the",
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"we",
"return",
"with",
"/",
"api",
"/",
"channels",
"."
] |
def _studio_response_to_kolibri_response(cls, studioresp):
"""
This modifies the JSON response returned by Kolibri Studio,
and then transforms its keys that are more in line with the keys
we return with /api/channels.
"""
# See the spec at:
# https://docs.google.com/document/d/1FGR4XBEu7IbfoaEy-8xbhQx2PvIyxp0VugoPrMfo4R4/edit#
# Go through the channel's included_languages and add in the native name
# for each language
included_languages = {}
for code in studioresp.get("included_languages", []):
included_languages[code] = cls._get_lang_native_name(code)
channel_lang_name = cls._get_lang_native_name(studioresp.get("language"))
resp = {
"id": studioresp["id"],
"description": studioresp.get("description"),
"tagline": studioresp.get("tagline", None),
"name": studioresp["name"],
"lang_code": studioresp.get("language"),
"lang_name": channel_lang_name,
"thumbnail": studioresp.get("icon_encoding"),
"public": studioresp.get("public", True),
"total_resources": studioresp.get("total_resource_count", 0),
"total_file_size": studioresp.get("published_size"),
"version": studioresp.get("version", 0),
"included_languages": included_languages,
"last_updated": studioresp.get("last_published"),
"version_notes": studioresp.get("version_notes"),
}
return resp
|
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":",
"# See the spec at:",
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https://github.com/learningequality/kolibri/blob/d056dbc477aaf651ab843caa141a6a1e0a491046/kolibri/core/content/api.py#L1488-L1523
|
|
nicodv/kmodes
|
db8616692b617659e350dc8e0cd52de376a7ce07
|
kmodes/kmodes.py
|
python
|
k_modes
|
(X, n_clusters, max_iter, dissim, init, n_init, verbose, random_state, n_jobs)
|
return all_centroids[best], enc_map, all_labels[best], \
all_costs[best], all_n_iters[best], all_epoch_costs[best]
|
k-modes algorithm
|
k-modes algorithm
|
[
"k",
"-",
"modes",
"algorithm"
] |
def k_modes(X, n_clusters, max_iter, dissim, init, n_init, verbose, random_state, n_jobs):
"""k-modes algorithm"""
random_state = check_random_state(random_state)
if sparse.issparse(X):
raise TypeError("k-modes does not support sparse data.")
X = check_array(X, dtype=None)
# Convert the categorical values in X to integers for speed.
# Based on the unique values in X, we can make a mapping to achieve this.
X, enc_map = encode_features(X)
n_points, n_attrs = X.shape
assert n_clusters <= n_points, "Cannot have more clusters ({}) " \
"than data points ({}).".format(n_clusters, n_points)
# Are there more n_clusters than unique rows? Then set the unique
# rows as initial values and skip iteration.
unique = get_unique_rows(X)
n_unique = unique.shape[0]
if n_unique <= n_clusters:
max_iter = 0
n_init = 1
n_clusters = n_unique
init = unique
results = []
seeds = random_state.randint(np.iinfo(np.int32).max, size=n_init)
if n_jobs == 1:
for init_no in range(n_init):
results.append(_k_modes_single(X, n_clusters, n_points, n_attrs, max_iter,
dissim, init, init_no, verbose, seeds[init_no]))
else:
results = Parallel(n_jobs=n_jobs, verbose=0)(
delayed(_k_modes_single)(X, n_clusters, n_points, n_attrs, max_iter,
dissim, init, init_no, verbose, seed)
for init_no, seed in enumerate(seeds))
all_centroids, all_labels, all_costs, all_n_iters, all_epoch_costs = zip(*results)
best = np.argmin(all_costs)
if n_init > 1 and verbose:
print("Best run was number {}".format(best + 1))
return all_centroids[best], enc_map, all_labels[best], \
all_costs[best], all_n_iters[best], all_epoch_costs[best]
|
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] |
https://github.com/nicodv/kmodes/blob/db8616692b617659e350dc8e0cd52de376a7ce07/kmodes/kmodes.py#L202-L246
|
|
bytefish/facerec
|
4071e1e79a50dbf1d1f2e061d24448576e5ac37d
|
py/facerec/validation.py
|
python
|
ValidationStrategy.print_results
|
(self)
|
[] |
def print_results(self):
print(self.model)
for validation_result in self.validation_results:
print(validation_result)
|
[
"def",
"print_results",
"(",
"self",
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"print",
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"model",
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"for",
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"in",
"self",
".",
"validation_results",
":",
"print",
"(",
"validation_result",
")"
] |
https://github.com/bytefish/facerec/blob/4071e1e79a50dbf1d1f2e061d24448576e5ac37d/py/facerec/validation.py#L135-L138
|
||||
demisto/content
|
5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07
|
Packs/F5/Integrations/F5_ASM/F5_ASM.py
|
python
|
f5_update_policy_file_type_command
|
(client: Client, policy_md5: str, file_type_id: str,
file_type_name: str,
query_string_length: int, check_post_data_length: bool,
response_check: bool, check_request_length: bool,
post_data_length: int,
perform_staging: bool)
|
return command_results
|
Update a given file type from a certain policy.
Args:
client (Client): f5 client.
policy_md5 (str): MD5 hash of the policy.
file_type_id (str): ID of the file type.
file_type_name (str): The new file type to add.
query_string_length (int): Query string length. default is 100.
check_post_data_length (bool): indicates if the user wishes check the length of
data in post method. default is True.
response_check (bool): Indicates if the user wishes to check the response.
check_request_length (bool): Indicates if the user wishes to check the request length.
post_data_length (int): post data length.
perform_staging (bool): Indicates if the user wishes the new file type to be at staging.
|
Update a given file type from a certain policy.
|
[
"Update",
"a",
"given",
"file",
"type",
"from",
"a",
"certain",
"policy",
"."
] |
def f5_update_policy_file_type_command(client: Client, policy_md5: str, file_type_id: str,
file_type_name: str,
query_string_length: int, check_post_data_length: bool,
response_check: bool, check_request_length: bool,
post_data_length: int,
perform_staging: bool) -> CommandResults:
"""
Update a given file type from a certain policy.
Args:
client (Client): f5 client.
policy_md5 (str): MD5 hash of the policy.
file_type_id (str): ID of the file type.
file_type_name (str): The new file type to add.
query_string_length (int): Query string length. default is 100.
check_post_data_length (bool): indicates if the user wishes check the length of
data in post method. default is True.
response_check (bool): Indicates if the user wishes to check the response.
check_request_length (bool): Indicates if the user wishes to check the request length.
post_data_length (int): post data length.
perform_staging (bool): Indicates if the user wishes the new file type to be at staging.
"""
result = client.update_policy_file_type(policy_md5, file_type_id, file_type_name,
query_string_length, check_post_data_length,
response_check, check_request_length, post_data_length,
perform_staging)
outputs, headers = build_output(OBJECT_FIELDS, result)
readable_output = tableToMarkdown('f5 data for updating policy methods:', outputs, headers,
removeNull=True)
command_results = CommandResults(
outputs_prefix='f5.FileType',
outputs_key_field='id',
readable_output=readable_output,
outputs=remove_empty_elements(outputs),
raw_response=result
)
return command_results
|
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] |
https://github.com/demisto/content/blob/5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07/Packs/F5/Integrations/F5_ASM/F5_ASM.py#L985-L1021
|
|
Azure/azure-devops-cli-extension
|
11334cd55806bef0b99c3bee5a438eed71e44037
|
azure-devops/azext_devops/devops_sdk/v5_1/build/build_client.py
|
python
|
BuildClient.get_definitions
|
(self, project, name=None, repository_id=None, repository_type=None, query_order=None, top=None, continuation_token=None, min_metrics_time=None, definition_ids=None, path=None, built_after=None, not_built_after=None, include_all_properties=None, include_latest_builds=None, task_id_filter=None, process_type=None, yaml_filename=None)
|
return self.GetDefinitionsResponseValue(response_value, continuation_token)
|
GetDefinitions.
Gets a list of definitions.
:param str project: Project ID or project name
:param str name: If specified, filters to definitions whose names match this pattern.
:param str repository_id: A repository ID. If specified, filters to definitions that use this repository.
:param str repository_type: If specified, filters to definitions that have a repository of this type.
:param str query_order: Indicates the order in which definitions should be returned.
:param int top: The maximum number of definitions to return.
:param str continuation_token: A continuation token, returned by a previous call to this method, that can be used to return the next set of definitions.
:param datetime min_metrics_time: If specified, indicates the date from which metrics should be included.
:param [int] definition_ids: A comma-delimited list that specifies the IDs of definitions to retrieve.
:param str path: If specified, filters to definitions under this folder.
:param datetime built_after: If specified, filters to definitions that have builds after this date.
:param datetime not_built_after: If specified, filters to definitions that do not have builds after this date.
:param bool include_all_properties: Indicates whether the full definitions should be returned. By default, shallow representations of the definitions are returned.
:param bool include_latest_builds: Indicates whether to return the latest and latest completed builds for this definition.
:param str task_id_filter: If specified, filters to definitions that use the specified task.
:param int process_type: If specified, filters to definitions with the given process type.
:param str yaml_filename: If specified, filters to YAML definitions that match the given filename.
:rtype: :class:`<GetDefinitionsResponseValue>`
|
GetDefinitions.
Gets a list of definitions.
:param str project: Project ID or project name
:param str name: If specified, filters to definitions whose names match this pattern.
:param str repository_id: A repository ID. If specified, filters to definitions that use this repository.
:param str repository_type: If specified, filters to definitions that have a repository of this type.
:param str query_order: Indicates the order in which definitions should be returned.
:param int top: The maximum number of definitions to return.
:param str continuation_token: A continuation token, returned by a previous call to this method, that can be used to return the next set of definitions.
:param datetime min_metrics_time: If specified, indicates the date from which metrics should be included.
:param [int] definition_ids: A comma-delimited list that specifies the IDs of definitions to retrieve.
:param str path: If specified, filters to definitions under this folder.
:param datetime built_after: If specified, filters to definitions that have builds after this date.
:param datetime not_built_after: If specified, filters to definitions that do not have builds after this date.
:param bool include_all_properties: Indicates whether the full definitions should be returned. By default, shallow representations of the definitions are returned.
:param bool include_latest_builds: Indicates whether to return the latest and latest completed builds for this definition.
:param str task_id_filter: If specified, filters to definitions that use the specified task.
:param int process_type: If specified, filters to definitions with the given process type.
:param str yaml_filename: If specified, filters to YAML definitions that match the given filename.
:rtype: :class:`<GetDefinitionsResponseValue>`
|
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] |
def get_definitions(self, project, name=None, repository_id=None, repository_type=None, query_order=None, top=None, continuation_token=None, min_metrics_time=None, definition_ids=None, path=None, built_after=None, not_built_after=None, include_all_properties=None, include_latest_builds=None, task_id_filter=None, process_type=None, yaml_filename=None):
"""GetDefinitions.
Gets a list of definitions.
:param str project: Project ID or project name
:param str name: If specified, filters to definitions whose names match this pattern.
:param str repository_id: A repository ID. If specified, filters to definitions that use this repository.
:param str repository_type: If specified, filters to definitions that have a repository of this type.
:param str query_order: Indicates the order in which definitions should be returned.
:param int top: The maximum number of definitions to return.
:param str continuation_token: A continuation token, returned by a previous call to this method, that can be used to return the next set of definitions.
:param datetime min_metrics_time: If specified, indicates the date from which metrics should be included.
:param [int] definition_ids: A comma-delimited list that specifies the IDs of definitions to retrieve.
:param str path: If specified, filters to definitions under this folder.
:param datetime built_after: If specified, filters to definitions that have builds after this date.
:param datetime not_built_after: If specified, filters to definitions that do not have builds after this date.
:param bool include_all_properties: Indicates whether the full definitions should be returned. By default, shallow representations of the definitions are returned.
:param bool include_latest_builds: Indicates whether to return the latest and latest completed builds for this definition.
:param str task_id_filter: If specified, filters to definitions that use the specified task.
:param int process_type: If specified, filters to definitions with the given process type.
:param str yaml_filename: If specified, filters to YAML definitions that match the given filename.
:rtype: :class:`<GetDefinitionsResponseValue>`
"""
route_values = {}
if project is not None:
route_values['project'] = self._serialize.url('project', project, 'str')
query_parameters = {}
if name is not None:
query_parameters['name'] = self._serialize.query('name', name, 'str')
if repository_id is not None:
query_parameters['repositoryId'] = self._serialize.query('repository_id', repository_id, 'str')
if repository_type is not None:
query_parameters['repositoryType'] = self._serialize.query('repository_type', repository_type, 'str')
if query_order is not None:
query_parameters['queryOrder'] = self._serialize.query('query_order', query_order, 'str')
if top is not None:
query_parameters['$top'] = self._serialize.query('top', top, 'int')
if continuation_token is not None:
query_parameters['continuationToken'] = self._serialize.query('continuation_token', continuation_token, 'str')
if min_metrics_time is not None:
query_parameters['minMetricsTime'] = self._serialize.query('min_metrics_time', min_metrics_time, 'iso-8601')
if definition_ids is not None:
definition_ids = ",".join(map(str, definition_ids))
query_parameters['definitionIds'] = self._serialize.query('definition_ids', definition_ids, 'str')
if path is not None:
query_parameters['path'] = self._serialize.query('path', path, 'str')
if built_after is not None:
query_parameters['builtAfter'] = self._serialize.query('built_after', built_after, 'iso-8601')
if not_built_after is not None:
query_parameters['notBuiltAfter'] = self._serialize.query('not_built_after', not_built_after, 'iso-8601')
if include_all_properties is not None:
query_parameters['includeAllProperties'] = self._serialize.query('include_all_properties', include_all_properties, 'bool')
if include_latest_builds is not None:
query_parameters['includeLatestBuilds'] = self._serialize.query('include_latest_builds', include_latest_builds, 'bool')
if task_id_filter is not None:
query_parameters['taskIdFilter'] = self._serialize.query('task_id_filter', task_id_filter, 'str')
if process_type is not None:
query_parameters['processType'] = self._serialize.query('process_type', process_type, 'int')
if yaml_filename is not None:
query_parameters['yamlFilename'] = self._serialize.query('yaml_filename', yaml_filename, 'str')
response = self._send(http_method='GET',
location_id='dbeaf647-6167-421a-bda9-c9327b25e2e6',
version='5.1',
route_values=route_values,
query_parameters=query_parameters)
response_value = self._deserialize('[BuildDefinitionReference]', self._unwrap_collection(response))
continuation_token = self._get_continuation_token(response)
return self.GetDefinitionsResponseValue(response_value, continuation_token)
|
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https://github.com/Azure/azure-devops-cli-extension/blob/11334cd55806bef0b99c3bee5a438eed71e44037/azure-devops/azext_devops/devops_sdk/v5_1/build/build_client.py#L714-L780
|
|
pokealarm/pokealarm
|
2edc3a978b7435a453d1917fbf436891fad1e18f
|
PokeAlarm/Filters/RaidFilter.py
|
python
|
RaidFilter.__init__
|
(self, mgr, name, data)
|
Initializes base parameters for a filter.
|
Initializes base parameters for a filter.
|
[
"Initializes",
"base",
"parameters",
"for",
"a",
"filter",
"."
] |
def __init__(self, mgr, name, data):
""" Initializes base parameters for a filter. """
super(RaidFilter, self).__init__(mgr, 'egg', name)
# Monster ID - f.mon_ids in r.mon_id
self.mon_ids = self.evaluate_attribute( #
event_attribute='mon_id', eval_func=operator.contains,
limit=BaseFilter.parse_as_set(
MonUtils.get_monster_id, 'monsters', data))
# Exclude Monster ID - f.monster_ids not contains r.ex_mon_id
self.exclude_mon_ids = self.evaluate_attribute( #
event_attribute='mon_id',
eval_func=lambda d, v: not operator.contains(d, v),
limit=BaseFilter.parse_as_set(
MonUtils.get_monster_id, 'monsters_exclude', data))
# Distance
self.min_dist = self.evaluate_attribute( # f.min_dist <= r.distance
event_attribute='distance', eval_func=operator.le,
limit=BaseFilter.parse_as_type(float, 'min_dist', data))
self.max_dist = self.evaluate_attribute( # f.max_dist <= r.distance
event_attribute='distance', eval_func=operator.ge,
limit=BaseFilter.parse_as_type(float, 'max_dist', data))
# Time Left
self.min_time_left = self.evaluate_attribute(
# f.min_time_left <= r.time_left
event_attribute='time_left', eval_func=operator.le,
limit=BaseFilter.parse_as_type(int, 'min_time_left', data))
self.max_time_left = self.evaluate_attribute(
# f.max_time_left >= r.time_left
event_attribute='time_left', eval_func=operator.ge,
limit=BaseFilter.parse_as_type(int, 'max_time_left', data))
# Monster Info
self.min_lvl = self.evaluate_attribute( # f.min_lvl <= r.mon_lvl
event_attribute='raid_lvl', eval_func=operator.le,
limit=BaseFilter.parse_as_type(int, 'min_raid_lvl', data))
self.max_lvl = self.evaluate_attribute( # f.max_lvl >= r.mon_lvl
event_attribute='raid_lvl', eval_func=operator.ge,
limit=BaseFilter.parse_as_type(int, 'max_raid_lvl', data))
# Monster Forms
self.forms = self.evaluate_attribute( # f.forms in r.form_id
event_attribute='form_id', eval_func=operator.contains,
limit=BaseFilter.parse_as_set(int, 'form_ids', data))
# Exclude Forms - f.forms_ids not contains m.ex_form_id
self.exclude_form_ids = self.evaluate_attribute( #
event_attribute='form_id',
eval_func=lambda d, v: not operator.contains(d, v),
limit=BaseFilter.parse_as_set(int, 'exclude_forms', data))
# Monster Costumes
self.costumes = self.evaluate_attribute( # f.costumes in m.costume_id
event_attribute='costume_id', eval_func=operator.contains,
limit=BaseFilter.parse_as_set(int, 'costume_ids', data))
# Exclude Costumes - f.costumes_ids not contains m.ex_costume_id
self.exclude_costume_ids = self.evaluate_attribute( #
event_attribute='costume_id',
eval_func=lambda d, v: not operator.contains(d, v),
limit=BaseFilter.parse_as_set(int, 'exclude_costumes', data))
# Gender
self.genders = self.evaluate_attribute( # f.genders contains m.gender
event_attribute='gender', eval_func=operator.contains,
limit=BaseFilter.parse_as_set(
MonUtils.get_gender_sym, 'genders', data))
# CP
self.min_cp = self.evaluate_attribute( # f.min_cp <= r.cp
event_attribute='cp', eval_func=operator.le,
limit=BaseFilter.parse_as_type(int, 'min_cp', data))
self.max_cp = self.evaluate_attribute( # f.max_cp >= r.cp
event_attribute='cp', eval_func=operator.ge,
limit=BaseFilter.parse_as_type(int, 'max_cp', data))
# Quick Move
self.quick_moves = self.evaluate_attribute( # f.q_ms contains r.q_m
event_attribute='quick_id', eval_func=operator.contains,
limit=BaseFilter.parse_as_set(
MonUtils.get_move_id, 'quick_moves', data))
# Charge Move
self.charge_moves = self.evaluate_attribute( # f.c_ms contains r.c_m
event_attribute='charge_id', eval_func=operator.contains,
limit=BaseFilter.parse_as_set(
MonUtils.get_move_id, 'charge_moves', data))
# Gym name
self.gym_name_contains = self.evaluate_attribute( # f.gn matches e.gn
event_attribute='gym_name', eval_func=GymUtils.match_regex_dict,
limit=BaseFilter.parse_as_set(
GymUtils.create_regex, 'gym_name_contains', data))
self.gym_name_excludes = self.evaluate_attribute( # f.gn no-match e.gn
event_attribute='gym_name',
eval_func=GymUtils.not_match_regex_dict,
limit=BaseFilter.parse_as_set(
GymUtils.create_regex, 'gym_name_excludes', data))
# Gym sponsor
self.sponsored = self.evaluate_attribute( #
event_attribute='sponsor_id', eval_func=lambda y, x: (x > 0) == y,
limit=BaseFilter.parse_as_type(bool, 'sponsored', data))
# Gym park
self.park_contains = self.evaluate_attribute( # f.gp matches e.gp
event_attribute='park', eval_func=GymUtils.match_regex_dict,
limit=BaseFilter.parse_as_set(
GymUtils.create_regex, 'park_contains', data))
self.is_ex_eligible = self.evaluate_attribute(
event_attribute='ex_eligible',
eval_func=operator.eq,
limit=BaseFilter.parse_as_type(bool, 'is_ex_eligible', data)
)
# Team Info
self.old_team = self.evaluate_attribute( # f.ctis contains m.cti
event_attribute='current_team_id', eval_func=operator.contains,
limit=BaseFilter.parse_as_set(
GymUtils.get_team_id, 'current_teams', data))
# Weather
self.weather_ids = self.evaluate_attribute( # f.w_ids contains m.w_id
event_attribute='weather_id', eval_func=operator.contains,
limit=BaseFilter.parse_as_set(get_weather_id, 'weather', data))
# Geofences
self.geofences = BaseFilter.parse_as_list(str, 'geofences', data)
# Custom DTS
self.custom_dts = BaseFilter.parse_as_dict(
str, str, 'custom_dts', data)
# Missing Info
self.is_missing_info = BaseFilter.parse_as_type(
bool, 'is_missing_info', data)
# Reject leftover parameters
for key in data:
raise ValueError("'{}' is not a recognized parameter for"
" Raid filters".format(key))
|
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")"
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https://github.com/pokealarm/pokealarm/blob/2edc3a978b7435a453d1917fbf436891fad1e18f/PokeAlarm/Filters/RaidFilter.py#L14-L156
|
||
lazylibrarian/LazyLibrarian
|
ae3c14e9db9328ce81765e094ab2a14ed7155624
|
lib/pythontwitter/__init__.py
|
python
|
Status.__init__
|
(self,
created_at=None,
favorited=None,
favorite_count=None,
id=None,
text=None,
location=None,
user=None,
in_reply_to_screen_name=None,
in_reply_to_user_id=None,
in_reply_to_status_id=None,
truncated=None,
source=None,
now=None,
urls=None,
user_mentions=None,
hashtags=None,
media=None,
geo=None,
place=None,
coordinates=None,
contributors=None,
retweeted=None,
retweeted_status=None,
current_user_retweet=None,
retweet_count=None,
possibly_sensitive=None,
scopes=None,
withheld_copyright=None,
withheld_in_countries=None,
withheld_scope=None)
|
An object to hold a Twitter status message.
This class is normally instantiated by the twitter.Api class and
returned in a sequence.
Note: Dates are posted in the form "Sat Jan 27 04:17:38 +0000 2007"
Args:
created_at:
The time this status message was posted. [Optional]
favorited:
Whether this is a favorite of the authenticated user. [Optional]
favorite_count:
Number of times this status message has been favorited. [Optional]
id:
The unique id of this status message. [Optional]
text:
The text of this status message. [Optional]
location:
the geolocation string associated with this message. [Optional]
relative_created_at:
A human readable string representing the posting time. [Optional]
user:
A twitter.User instance representing the person posting the
message. [Optional]
now:
The current time, if the client chooses to set it.
Defaults to the wall clock time. [Optional]
urls:
user_mentions:
hashtags:
geo:
place:
coordinates:
contributors:
retweeted:
retweeted_status:
current_user_retweet:
retweet_count:
possibly_sensitive:
scopes:
withheld_copyright:
withheld_in_countries:
withheld_scope:
|
An object to hold a Twitter status message.
|
[
"An",
"object",
"to",
"hold",
"a",
"Twitter",
"status",
"message",
"."
] |
def __init__(self,
created_at=None,
favorited=None,
favorite_count=None,
id=None,
text=None,
location=None,
user=None,
in_reply_to_screen_name=None,
in_reply_to_user_id=None,
in_reply_to_status_id=None,
truncated=None,
source=None,
now=None,
urls=None,
user_mentions=None,
hashtags=None,
media=None,
geo=None,
place=None,
coordinates=None,
contributors=None,
retweeted=None,
retweeted_status=None,
current_user_retweet=None,
retweet_count=None,
possibly_sensitive=None,
scopes=None,
withheld_copyright=None,
withheld_in_countries=None,
withheld_scope=None):
'''An object to hold a Twitter status message.
This class is normally instantiated by the twitter.Api class and
returned in a sequence.
Note: Dates are posted in the form "Sat Jan 27 04:17:38 +0000 2007"
Args:
created_at:
The time this status message was posted. [Optional]
favorited:
Whether this is a favorite of the authenticated user. [Optional]
favorite_count:
Number of times this status message has been favorited. [Optional]
id:
The unique id of this status message. [Optional]
text:
The text of this status message. [Optional]
location:
the geolocation string associated with this message. [Optional]
relative_created_at:
A human readable string representing the posting time. [Optional]
user:
A twitter.User instance representing the person posting the
message. [Optional]
now:
The current time, if the client chooses to set it.
Defaults to the wall clock time. [Optional]
urls:
user_mentions:
hashtags:
geo:
place:
coordinates:
contributors:
retweeted:
retweeted_status:
current_user_retweet:
retweet_count:
possibly_sensitive:
scopes:
withheld_copyright:
withheld_in_countries:
withheld_scope:
'''
self.created_at = created_at
self.favorited = favorited
self.favorite_count = favorite_count
self.id = id
self.text = text
self.location = location
self.user = user
self.now = now
self.in_reply_to_screen_name = in_reply_to_screen_name
self.in_reply_to_user_id = in_reply_to_user_id
self.in_reply_to_status_id = in_reply_to_status_id
self.truncated = truncated
self.retweeted = retweeted
self.source = source
self.urls = urls
self.user_mentions = user_mentions
self.hashtags = hashtags
self.media = media
self.geo = geo
self.place = place
self.coordinates = coordinates
self.contributors = contributors
self.retweeted_status = retweeted_status
self.current_user_retweet = current_user_retweet
self.retweet_count = retweet_count
self.possibly_sensitive = possibly_sensitive
self.scopes = scopes
self.withheld_copyright = withheld_copyright
self.withheld_in_countries = withheld_in_countries
self.withheld_scope = withheld_scope
|
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"=",
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] |
https://github.com/lazylibrarian/LazyLibrarian/blob/ae3c14e9db9328ce81765e094ab2a14ed7155624/lib/pythontwitter/__init__.py#L137-L242
|
||
demisto/content
|
5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07
|
Packs/Smokescreen_IllusionBLACK/Integrations/Smokescreen_IllusionBLACK/Smokescreen_IllusionBLACK.py
|
python
|
Client.is_subdomain_decoy
|
(self, subdomain)
|
Checks if the subdomain is an IllusionBLACK TI decoy
Args:
subdomain: The subdomain to check. For example: experience.illusionblack.com
Returns: True if subdomain is a decoy else False
|
Checks if the subdomain is an IllusionBLACK TI decoy
Args:
subdomain: The subdomain to check. For example: experience.illusionblack.com
Returns: True if subdomain is a decoy else False
|
[
"Checks",
"if",
"the",
"subdomain",
"is",
"an",
"IllusionBLACK",
"TI",
"decoy",
"Args",
":",
"subdomain",
":",
"The",
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"to",
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".",
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":",
"experience",
".",
"illusionblack",
".",
"com",
"Returns",
":",
"True",
"if",
"subdomain",
"is",
"a",
"decoy",
"else",
"False"
] |
def is_subdomain_decoy(self, subdomain):
"""
Checks if the subdomain is an IllusionBLACK TI decoy
Args:
subdomain: The subdomain to check. For example: experience.illusionblack.com
Returns: True if subdomain is a decoy else False
"""
response = self._http_request(
method="GET",
url_suffix="/decoy/recon",
ok_codes=(200,)
)
ti_decoys: List = response["items"]
for ti_decoy in ti_decoys:
if subdomain == ti_decoy["name"]:
return "True", {"IllusionBlack.IsSubdomainDecoy": {"Subdomain": subdomain, "Value": True}}
return "False", {"IllusionBlack.IsSubdomainDecoy": {"Subdomain": subdomain, "Value": False}}
|
[
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"{",
"\"Subdomain\"",
":",
"subdomain",
",",
"\"Value\"",
":",
"False",
"}",
"}"
] |
https://github.com/demisto/content/blob/5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07/Packs/Smokescreen_IllusionBLACK/Integrations/Smokescreen_IllusionBLACK/Smokescreen_IllusionBLACK.py#L141-L157
|
||
tslearn-team/tslearn
|
6c93071b385a89112b82799ae5870daeca1ab88b
|
tslearn/bases/bases.py
|
python
|
BaseModelPackage._to_dict
|
(self, output=None, hyper_parameters_only=False)
|
return d
|
Get model hyper-parameters and model-parameters
as a dict that can be saved to disk.
Returns
-------
params : dict
dict with relevant attributes sufficient to describe the model.
|
Get model hyper-parameters and model-parameters
as a dict that can be saved to disk.
|
[
"Get",
"model",
"hyper",
"-",
"parameters",
"and",
"model",
"-",
"parameters",
"as",
"a",
"dict",
"that",
"can",
"be",
"saved",
"to",
"disk",
"."
] |
def _to_dict(self, output=None, hyper_parameters_only=False):
"""
Get model hyper-parameters and model-parameters
as a dict that can be saved to disk.
Returns
-------
params : dict
dict with relevant attributes sufficient to describe the model.
"""
if not self._is_fitted():
raise NotFittedError("Model must be fit before it can be packaged")
d = {'hyper_params': self.get_params(),
'model_params': self._get_model_params()}
# This is just for json support to convert numpy arrays to lists
if output == 'json':
d['model_params'] = BaseModelPackage._listify(d['model_params'])
d['hyper_params'] = BaseModelPackage._listify(d['hyper_params'])
elif output == 'hdf5':
d['hyper_params'] = \
BaseModelPackage._none_to_str(d['hyper_params'])
if hyper_parameters_only:
del d["model_params"]
return d
|
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"[",
"\"model_params\"",
"]",
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] |
https://github.com/tslearn-team/tslearn/blob/6c93071b385a89112b82799ae5870daeca1ab88b/tslearn/bases/bases.py#L63-L92
|
|
deepfakes/faceswap
|
09c7d8aca3c608d1afad941ea78e9fd9b64d9219
|
tools/manual/faceviewer/viewport.py
|
python
|
TKFace.photo
|
(self)
|
return self._photo
|
:class:`tkinter.PhotoImage`: The face in a format that can be placed on the
:class:`~tools.manual.faceviewer.frame.FacesViewer` canvas.
|
:class:`tkinter.PhotoImage`: The face in a format that can be placed on the
:class:`~tools.manual.faceviewer.frame.FacesViewer` canvas.
|
[
":",
"class",
":",
"tkinter",
".",
"PhotoImage",
":",
"The",
"face",
"in",
"a",
"format",
"that",
"can",
"be",
"placed",
"on",
"the",
":",
"class",
":",
"~tools",
".",
"manual",
".",
"faceviewer",
".",
"frame",
".",
"FacesViewer",
"canvas",
"."
] |
def photo(self):
""" :class:`tkinter.PhotoImage`: The face in a format that can be placed on the
:class:`~tools.manual.faceviewer.frame.FacesViewer` canvas. """
return self._photo
|
[
"def",
"photo",
"(",
"self",
")",
":",
"return",
"self",
".",
"_photo"
] |
https://github.com/deepfakes/faceswap/blob/09c7d8aca3c608d1afad941ea78e9fd9b64d9219/tools/manual/faceviewer/viewport.py#L1033-L1036
|
|
AppScale/gts
|
46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9
|
AppServer/lib/grizzled/grizzled/db/base.py
|
python
|
DB.rollback
|
(self)
|
Roll the current transaction back.
:raise Warning: Non-fatal warning
:raise Error: Error
|
Roll the current transaction back.
|
[
"Roll",
"the",
"current",
"transaction",
"back",
"."
] |
def rollback(self):
"""
Roll the current transaction back.
:raise Warning: Non-fatal warning
:raise Error: Error
"""
dbi = self.__driver.get_import()
try:
self.__db.rollback()
except dbi.Warning, val:
raise Warning(val)
except dbi.Error, val:
raise Error(val)
|
[
"def",
"rollback",
"(",
"self",
")",
":",
"dbi",
"=",
"self",
".",
"__driver",
".",
"get_import",
"(",
")",
"try",
":",
"self",
".",
"__db",
".",
"rollback",
"(",
")",
"except",
"dbi",
".",
"Warning",
",",
"val",
":",
"raise",
"Warning",
"(",
"val",
")",
"except",
"dbi",
".",
"Error",
",",
"val",
":",
"raise",
"Error",
"(",
"val",
")"
] |
https://github.com/AppScale/gts/blob/46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9/AppServer/lib/grizzled/grizzled/db/base.py#L631-L644
|
||
Tautulli/Tautulli
|
2410eb33805aaac4bd1c5dad0f71e4f15afaf742
|
lib/paho/mqtt/client.py
|
python
|
Client.on_connect_fail
|
(self, func)
|
Define the connection failure callback implementation
Expected signature is:
on_connect_fail(client, userdata)
client: the client instance for this callback
userdata: the private user data as set in Client() or userdata_set()
Decorator: @client.connect_fail_callback() (```client``` is the name of the
instance which this callback is being attached to)
|
Define the connection failure callback implementation
|
[
"Define",
"the",
"connection",
"failure",
"callback",
"implementation"
] |
def on_connect_fail(self, func):
""" Define the connection failure callback implementation
Expected signature is:
on_connect_fail(client, userdata)
client: the client instance for this callback
userdata: the private user data as set in Client() or userdata_set()
Decorator: @client.connect_fail_callback() (```client``` is the name of the
instance which this callback is being attached to)
"""
with self._callback_mutex:
self._on_connect_fail = func
|
[
"def",
"on_connect_fail",
"(",
"self",
",",
"func",
")",
":",
"with",
"self",
".",
"_callback_mutex",
":",
"self",
".",
"_on_connect_fail",
"=",
"func"
] |
https://github.com/Tautulli/Tautulli/blob/2410eb33805aaac4bd1c5dad0f71e4f15afaf742/lib/paho/mqtt/client.py#L1910-L1924
|
||
vaab/colour
|
11f138eb7841d2045160b378a2eec0c2321144c0
|
colour.py
|
python
|
hsl2rgb
|
(hsl)
|
return r, g, b
|
Convert HSL representation towards RGB
:param h: Hue, position around the chromatic circle (h=1 equiv h=0)
:param s: Saturation, color saturation (0=full gray, 1=full color)
:param l: Ligthness, Overhaul lightness (0=full black, 1=full white)
:rtype: 3-uple for RGB values in float between 0 and 1
Hue, Saturation, Range from Lightness is a float between 0 and 1
Note that Hue can be set to any value but as it is a rotation
around the chromatic circle, any value above 1 or below 0 can
be expressed by a value between 0 and 1 (Note that h=0 is equiv
to h=1).
This algorithm came from:
http://www.easyrgb.com/index.php?X=MATH&H=19#text19
Here are some quick notion of HSL to RGB conversion:
>>> from colour import hsl2rgb
With a lightness put at 0, RGB is always rgbblack
>>> hsl2rgb((0.0, 0.0, 0.0))
(0.0, 0.0, 0.0)
>>> hsl2rgb((0.5, 0.0, 0.0))
(0.0, 0.0, 0.0)
>>> hsl2rgb((0.5, 0.5, 0.0))
(0.0, 0.0, 0.0)
Same for lightness put at 1, RGB is always rgbwhite
>>> hsl2rgb((0.0, 0.0, 1.0))
(1.0, 1.0, 1.0)
>>> hsl2rgb((0.5, 0.0, 1.0))
(1.0, 1.0, 1.0)
>>> hsl2rgb((0.5, 0.5, 1.0))
(1.0, 1.0, 1.0)
With saturation put at 0, the RGB should be equal to Lightness:
>>> hsl2rgb((0.0, 0.0, 0.25))
(0.25, 0.25, 0.25)
>>> hsl2rgb((0.5, 0.0, 0.5))
(0.5, 0.5, 0.5)
>>> hsl2rgb((0.5, 0.0, 0.75))
(0.75, 0.75, 0.75)
With saturation put at 1, and lightness put to 0.5, we can find
normal full red, green, blue colors:
>>> hsl2rgb((0 , 1.0, 0.5))
(1.0, 0.0, 0.0)
>>> hsl2rgb((1 , 1.0, 0.5))
(1.0, 0.0, 0.0)
>>> hsl2rgb((1.0/3 , 1.0, 0.5))
(0.0, 1.0, 0.0)
>>> hsl2rgb((2.0/3 , 1.0, 0.5))
(0.0, 0.0, 1.0)
Of course:
>>> hsl2rgb((0.0, 2.0, 0.5)) # doctest: +ELLIPSIS
Traceback (most recent call last):
...
ValueError: Saturation must be between 0 and 1.
And:
>>> hsl2rgb((0.0, 0.0, 1.5)) # doctest: +ELLIPSIS
Traceback (most recent call last):
...
ValueError: Lightness must be between 0 and 1.
|
Convert HSL representation towards RGB
|
[
"Convert",
"HSL",
"representation",
"towards",
"RGB"
] |
def hsl2rgb(hsl):
"""Convert HSL representation towards RGB
:param h: Hue, position around the chromatic circle (h=1 equiv h=0)
:param s: Saturation, color saturation (0=full gray, 1=full color)
:param l: Ligthness, Overhaul lightness (0=full black, 1=full white)
:rtype: 3-uple for RGB values in float between 0 and 1
Hue, Saturation, Range from Lightness is a float between 0 and 1
Note that Hue can be set to any value but as it is a rotation
around the chromatic circle, any value above 1 or below 0 can
be expressed by a value between 0 and 1 (Note that h=0 is equiv
to h=1).
This algorithm came from:
http://www.easyrgb.com/index.php?X=MATH&H=19#text19
Here are some quick notion of HSL to RGB conversion:
>>> from colour import hsl2rgb
With a lightness put at 0, RGB is always rgbblack
>>> hsl2rgb((0.0, 0.0, 0.0))
(0.0, 0.0, 0.0)
>>> hsl2rgb((0.5, 0.0, 0.0))
(0.0, 0.0, 0.0)
>>> hsl2rgb((0.5, 0.5, 0.0))
(0.0, 0.0, 0.0)
Same for lightness put at 1, RGB is always rgbwhite
>>> hsl2rgb((0.0, 0.0, 1.0))
(1.0, 1.0, 1.0)
>>> hsl2rgb((0.5, 0.0, 1.0))
(1.0, 1.0, 1.0)
>>> hsl2rgb((0.5, 0.5, 1.0))
(1.0, 1.0, 1.0)
With saturation put at 0, the RGB should be equal to Lightness:
>>> hsl2rgb((0.0, 0.0, 0.25))
(0.25, 0.25, 0.25)
>>> hsl2rgb((0.5, 0.0, 0.5))
(0.5, 0.5, 0.5)
>>> hsl2rgb((0.5, 0.0, 0.75))
(0.75, 0.75, 0.75)
With saturation put at 1, and lightness put to 0.5, we can find
normal full red, green, blue colors:
>>> hsl2rgb((0 , 1.0, 0.5))
(1.0, 0.0, 0.0)
>>> hsl2rgb((1 , 1.0, 0.5))
(1.0, 0.0, 0.0)
>>> hsl2rgb((1.0/3 , 1.0, 0.5))
(0.0, 1.0, 0.0)
>>> hsl2rgb((2.0/3 , 1.0, 0.5))
(0.0, 0.0, 1.0)
Of course:
>>> hsl2rgb((0.0, 2.0, 0.5)) # doctest: +ELLIPSIS
Traceback (most recent call last):
...
ValueError: Saturation must be between 0 and 1.
And:
>>> hsl2rgb((0.0, 0.0, 1.5)) # doctest: +ELLIPSIS
Traceback (most recent call last):
...
ValueError: Lightness must be between 0 and 1.
"""
h, s, l = [float(v) for v in hsl]
if not (0.0 - FLOAT_ERROR <= s <= 1.0 + FLOAT_ERROR):
raise ValueError("Saturation must be between 0 and 1.")
if not (0.0 - FLOAT_ERROR <= l <= 1.0 + FLOAT_ERROR):
raise ValueError("Lightness must be between 0 and 1.")
if s == 0:
return l, l, l
if l < 0.5:
v2 = l * (1.0 + s)
else:
v2 = (l + s) - (s * l)
v1 = 2.0 * l - v2
r = _hue2rgb(v1, v2, h + (1.0 / 3))
g = _hue2rgb(v1, v2, h)
b = _hue2rgb(v1, v2, h - (1.0 / 3))
return r, g, b
|
[
"def",
"hsl2rgb",
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"hsl",
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":",
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",",
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",",
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"0.0",
"-",
"FLOAT_ERROR",
"<=",
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")",
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"\"Saturation must be between 0 and 1.\"",
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"/",
"3",
")",
")",
"return",
"r",
",",
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",",
"b"
] |
https://github.com/vaab/colour/blob/11f138eb7841d2045160b378a2eec0c2321144c0/colour.py#L272-L367
|
|
mattupstate/flask-principal
|
0b5cd06b464ae8b60939857784bda86c03dda1eb
|
flask_principal.py
|
python
|
Principal.identity_loader
|
(self, f)
|
return f
|
Decorator to define a function as an identity loader.
An identity loader function is called before request to find any
provided identities. The first found identity is used to load from.
For example::
app = Flask(__name__)
principals = Principal(app)
@principals.identity_loader
def load_identity_from_weird_usecase():
return Identity('ali')
|
Decorator to define a function as an identity loader.
|
[
"Decorator",
"to",
"define",
"a",
"function",
"as",
"an",
"identity",
"loader",
"."
] |
def identity_loader(self, f):
"""Decorator to define a function as an identity loader.
An identity loader function is called before request to find any
provided identities. The first found identity is used to load from.
For example::
app = Flask(__name__)
principals = Principal(app)
@principals.identity_loader
def load_identity_from_weird_usecase():
return Identity('ali')
"""
self.identity_loaders.appendleft(f)
return f
|
[
"def",
"identity_loader",
"(",
"self",
",",
"f",
")",
":",
"self",
".",
"identity_loaders",
".",
"appendleft",
"(",
"f",
")",
"return",
"f"
] |
https://github.com/mattupstate/flask-principal/blob/0b5cd06b464ae8b60939857784bda86c03dda1eb/flask_principal.py#L422-L439
|
|
charlesq34/pointnet2
|
42926632a3c33461aebfbee2d829098b30a23aaa
|
utils/tf_util.py
|
python
|
conv2d
|
(inputs,
num_output_channels,
kernel_size,
scope,
stride=[1, 1],
padding='SAME',
data_format='NHWC',
use_xavier=True,
stddev=1e-3,
weight_decay=None,
activation_fn=tf.nn.relu,
bn=False,
bn_decay=None,
is_training=None)
|
2D convolution with non-linear operation.
Args:
inputs: 4-D tensor variable BxHxWxC
num_output_channels: int
kernel_size: a list of 2 ints
scope: string
stride: a list of 2 ints
padding: 'SAME' or 'VALID'
data_format: 'NHWC' or 'NCHW'
use_xavier: bool, use xavier_initializer if true
stddev: float, stddev for truncated_normal init
weight_decay: float
activation_fn: function
bn: bool, whether to use batch norm
bn_decay: float or float tensor variable in [0,1]
is_training: bool Tensor variable
Returns:
Variable tensor
|
2D convolution with non-linear operation.
|
[
"2D",
"convolution",
"with",
"non",
"-",
"linear",
"operation",
"."
] |
def conv2d(inputs,
num_output_channels,
kernel_size,
scope,
stride=[1, 1],
padding='SAME',
data_format='NHWC',
use_xavier=True,
stddev=1e-3,
weight_decay=None,
activation_fn=tf.nn.relu,
bn=False,
bn_decay=None,
is_training=None):
""" 2D convolution with non-linear operation.
Args:
inputs: 4-D tensor variable BxHxWxC
num_output_channels: int
kernel_size: a list of 2 ints
scope: string
stride: a list of 2 ints
padding: 'SAME' or 'VALID'
data_format: 'NHWC' or 'NCHW'
use_xavier: bool, use xavier_initializer if true
stddev: float, stddev for truncated_normal init
weight_decay: float
activation_fn: function
bn: bool, whether to use batch norm
bn_decay: float or float tensor variable in [0,1]
is_training: bool Tensor variable
Returns:
Variable tensor
"""
with tf.variable_scope(scope) as sc:
kernel_h, kernel_w = kernel_size
assert(data_format=='NHWC' or data_format=='NCHW')
if data_format == 'NHWC':
num_in_channels = inputs.get_shape()[-1].value
elif data_format=='NCHW':
num_in_channels = inputs.get_shape()[1].value
kernel_shape = [kernel_h, kernel_w,
num_in_channels, num_output_channels]
kernel = _variable_with_weight_decay('weights',
shape=kernel_shape,
use_xavier=use_xavier,
stddev=stddev,
wd=weight_decay)
stride_h, stride_w = stride
outputs = tf.nn.conv2d(inputs, kernel,
[1, stride_h, stride_w, 1],
padding=padding,
data_format=data_format)
biases = _variable_on_cpu('biases', [num_output_channels],
tf.constant_initializer(0.0))
outputs = tf.nn.bias_add(outputs, biases, data_format=data_format)
if bn:
outputs = batch_norm_for_conv2d(outputs, is_training,
bn_decay=bn_decay, scope='bn',
data_format=data_format)
if activation_fn is not None:
outputs = activation_fn(outputs)
return outputs
|
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] |
https://github.com/charlesq34/pointnet2/blob/42926632a3c33461aebfbee2d829098b30a23aaa/utils/tf_util.py#L120-L185
|
||
clovaai/assembled-cnn
|
9cdc29761d828ecd3708ea13e5acc44c696ec30f
|
datasets/build_ethz_food101.py
|
python
|
_process_image_files_batch
|
(thread_index, offsets, output_filenames, filenames, labels)
|
하나의 스레드 단위에서 이미지 리스트를 읽어 TRRecord 타입으로 변환하는 함수
:param thread_index: 현재 작업중인 thread 번호.
:param offsets: offset list. 이미지 목록 중 현재 스레드에서 처리해야 할 offset 값으로 shard 갯수만큼 리스트로 제공
:param output_filenames: 출력 파일 이름으로 shard 갯수만큼 리스트로 제공.
:param filenames: 처리해야 할 전체 이미지 파일 리스트
:param labels: 처리해야 할 전체 이미지 레이블 리스트
|
하나의 스레드 단위에서 이미지 리스트를 읽어 TRRecord 타입으로 변환하는 함수
:param thread_index: 현재 작업중인 thread 번호.
:param offsets: offset list. 이미지 목록 중 현재 스레드에서 처리해야 할 offset 값으로 shard 갯수만큼 리스트로 제공
:param output_filenames: 출력 파일 이름으로 shard 갯수만큼 리스트로 제공.
:param filenames: 처리해야 할 전체 이미지 파일 리스트
:param labels: 처리해야 할 전체 이미지 레이블 리스트
|
[
"하나의",
"스레드",
"단위에서",
"이미지",
"리스트를",
"읽어",
"TRRecord",
"타입으로",
"변환하는",
"함수",
":",
"param",
"thread_index",
":",
"현재",
"작업중인",
"thread",
"번호",
".",
":",
"param",
"offsets",
":",
"offset",
"list",
".",
"이미지",
"목록",
"중",
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"스레드에서",
"처리해야",
"할",
"offset",
"값으로",
"shard",
"갯수만큼",
"리스트로",
"제공",
":",
"param",
"output_filenames",
":",
"출력",
"파일",
"이름으로",
"shard",
"갯수만큼",
"리스트로",
"제공",
".",
":",
"param",
"filenames",
":",
"처리해야",
"할",
"전체",
"이미지",
"파일",
"리스트",
":",
"param",
"labels",
":",
"처리해야",
"할",
"전체",
"이미지",
"레이블",
"리스트"
] |
def _process_image_files_batch(thread_index, offsets, output_filenames, filenames, labels):
"""
하나의 스레드 단위에서 이미지 리스트를 읽어 TRRecord 타입으로 변환하는 함수
:param thread_index: 현재 작업중인 thread 번호.
:param offsets: offset list. 이미지 목록 중 현재 스레드에서 처리해야 할 offset 값으로 shard 갯수만큼 리스트로 제공
:param output_filenames: 출력 파일 이름으로 shard 갯수만큼 리스트로 제공.
:param filenames: 처리해야 할 전체 이미지 파일 리스트
:param labels: 처리해야 할 전체 이미지 레이블 리스트
"""
assert len(offsets) == len(output_filenames)
assert len(filenames) == len(labels)
num_files_in_thread = offsets[-1][1] - offsets[0][0]
counter = 0
# 하나의 thread 에는 여러 개의 shard 가 할당될 수 있다.
for offset, output_filename in zip(offsets, output_filenames):
output_file = os.path.join(FLAGS.output_dir, output_filename)
writer = tf.python_io.TFRecordWriter(output_file)
# offset 에는 현재 shard 에 대한 (start, end) offset이 저장되어 있음.
files_in_shard = np.arange(offset[0], offset[1], dtype=int)
shard_counter = 0
for i in files_in_shard:
filename = filenames[i]
label = labels[i]
try:
image_data, height, width = _process_image(filename)
except ValueError:
dataset_utils.log('[thread %2d]: Invalid image found. %s - [skip].' % (thread_index, filename))
continue
example = data_util.convert_to_example_without_bbox(image_data, 'jpg', label, height, width)
writer.write(example.SerializeToString())
counter += 1
shard_counter += 1
if not counter % 1000:
dataset_utils.log('%s [thread %2d]: Processed %d of %d images in thread batch.' %
(datetime.now(), thread_index, counter, num_files_in_thread))
writer.close()
dataset_utils.log('%s [thread %2d]: Wrote %d images to %s' %
(datetime.now(), thread_index, shard_counter, output_file))
|
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] |
https://github.com/clovaai/assembled-cnn/blob/9cdc29761d828ecd3708ea13e5acc44c696ec30f/datasets/build_ethz_food101.py#L56-L99
|
||
securesystemslab/zippy
|
ff0e84ac99442c2c55fe1d285332cfd4e185e089
|
zippy/lib-python/3/imaplib.py
|
python
|
IMAP4.subscribe
|
(self, mailbox)
|
return self._simple_command('SUBSCRIBE', mailbox)
|
Subscribe to new mailbox.
(typ, [data]) = <instance>.subscribe(mailbox)
|
Subscribe to new mailbox.
|
[
"Subscribe",
"to",
"new",
"mailbox",
"."
] |
def subscribe(self, mailbox):
"""Subscribe to new mailbox.
(typ, [data]) = <instance>.subscribe(mailbox)
"""
return self._simple_command('SUBSCRIBE', mailbox)
|
[
"def",
"subscribe",
"(",
"self",
",",
"mailbox",
")",
":",
"return",
"self",
".",
"_simple_command",
"(",
"'SUBSCRIBE'",
",",
"mailbox",
")"
] |
https://github.com/securesystemslab/zippy/blob/ff0e84ac99442c2c55fe1d285332cfd4e185e089/zippy/lib-python/3/imaplib.py#L774-L779
|
|
ucsb-seclab/karonte
|
427ac313e596f723e40768b95d13bd7a9fc92fd8
|
eval/multi_bin/network-facing/run_utils.py
|
python
|
get_reg_used
|
(p, cfg, addr, idx, s_addr)
|
return None
|
Finds whether and which register is used to store a string address.
:param addr: basic block address
:param idx: statement idx of the statement referencing a string
:param s: string referenced in the statement pointed by idx
:return: the register name the string is assigned to
|
Finds whether and which register is used to store a string address.
|
[
"Finds",
"whether",
"and",
"which",
"register",
"is",
"used",
"to",
"store",
"a",
"string",
"address",
"."
] |
def get_reg_used(p, cfg, addr, idx, s_addr):
"""
Finds whether and which register is used to store a string address.
:param addr: basic block address
:param idx: statement idx of the statement referencing a string
:param s: string referenced in the statement pointed by idx
:return: the register name the string is assigned to
"""
if not are_parameters_in_registers(p):
raise Exception("Parameters are not in registers")
block = p.factory.block(addr)
stmt = block.vex.statements[idx]
no = cfg.get_any_node(addr)
# sometimes strings are reference indirectly through an address contained in the
# text section
endianess = '<I' if 'LE' in p.arch.memory_endness else '>I'
s_addr_2 = None
try:
s_addr_2 = struct.unpack(endianess, ''.join(p.loader.memory.read_bytes(s_addr, p.arch.bytes)))[0]
except:
pass
if hasattr(stmt, 'offset'):
return p.arch.register_names[stmt.offset]
# damn! The string is not assigned directly to a register, but to a tmp.
# It means we have to find out what register is used to pass the string
# to the function call
# save the function manager, CFGAccurate will change it
fm = p.kb.functions
cfga = p.analyses.CFGAccurate(starts=(no.function_address,), keep_state=True, call_depth=0)
no = cfga.get_any_node(addr)
if not no:
cfga = p.analyses.CFGAccurate(starts=(addr,), keep_state=True, call_depth=0)
no = cfga.get_any_node(addr)
if not no:
return None
args = get_args_call(p, no)
# restore the old function manager
p.kb.functions = fm
for _, vals in args.iteritems():
for o, v in vals:
if v in (s_addr, s_addr_2):
return p.arch.register_names[o]
return None
|
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"[",
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"]",
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] |
https://github.com/ucsb-seclab/karonte/blob/427ac313e596f723e40768b95d13bd7a9fc92fd8/eval/multi_bin/network-facing/run_utils.py#L272-L324
|
|
digidotcom/xbee-python
|
0757f4be0017530c205175fbee8f9f61be9614d1
|
digi/xbee/packets/socket.py
|
python
|
SocketCreatePacket.create_packet
|
(raw, operating_mode)
|
return SocketCreatePacket(raw[4], IPProtocol.get(raw[5]), op_mode=operating_mode)
|
Override method.
Returns:
:class:`.SocketCreatePacket`.
Raises:
InvalidPacketException: if the bytearray length is less than 7.
(start delim. + length (2 bytes) + frame type + frame id
+ protocol + checksum = 7 bytes).
InvalidPacketException: if the length field of 'raw' is different
from its real length. (length field: bytes 2 and 3)
InvalidPacketException: if the first byte of 'raw' is not the
header byte. See :class:`.SpecialByte`.
InvalidPacketException: if the calculated checksum is different
from the checksum field value (last byte).
InvalidPacketException: if the frame type is not
:attr:`.ApiFrameType.SOCKET_CREATE`.
InvalidOperatingModeException: if `operating_mode` is not supported.
.. seealso::
| :meth:`.XBeePacket.create_packet`
| :meth:`.XBeeAPIPacket._check_api_packet`
|
Override method.
|
[
"Override",
"method",
"."
] |
def create_packet(raw, operating_mode):
"""
Override method.
Returns:
:class:`.SocketCreatePacket`.
Raises:
InvalidPacketException: if the bytearray length is less than 7.
(start delim. + length (2 bytes) + frame type + frame id
+ protocol + checksum = 7 bytes).
InvalidPacketException: if the length field of 'raw' is different
from its real length. (length field: bytes 2 and 3)
InvalidPacketException: if the first byte of 'raw' is not the
header byte. See :class:`.SpecialByte`.
InvalidPacketException: if the calculated checksum is different
from the checksum field value (last byte).
InvalidPacketException: if the frame type is not
:attr:`.ApiFrameType.SOCKET_CREATE`.
InvalidOperatingModeException: if `operating_mode` is not supported.
.. seealso::
| :meth:`.XBeePacket.create_packet`
| :meth:`.XBeeAPIPacket._check_api_packet`
"""
if operating_mode not in (OperatingMode.ESCAPED_API_MODE,
OperatingMode.API_MODE):
raise InvalidOperatingModeException(op_mode=operating_mode)
XBeeAPIPacket._check_api_packet(
raw, min_length=SocketCreatePacket.__MIN_PACKET_LENGTH)
if raw[3] != ApiFrameType.SOCKET_CREATE.code:
raise InvalidPacketException(
message="This packet is not a Socket Create packet.")
return SocketCreatePacket(raw[4], IPProtocol.get(raw[5]), op_mode=operating_mode)
|
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"[",
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] |
https://github.com/digidotcom/xbee-python/blob/0757f4be0017530c205175fbee8f9f61be9614d1/digi/xbee/packets/socket.py#L68-L104
|
|
apache/tvm
|
6eb4ed813ebcdcd9558f0906a1870db8302ff1e0
|
python/tvm/topi/x86/tensor_intrin.py
|
python
|
dot_16x1x16_uint8_int8_int32_skylake
|
()
|
return te.decl_tensor_intrin(
C.op,
_intrin_func,
binds={data: a_buffer, kernel: b_buffer},
default_buffer_params=buffer_params,
)
|
Int8 dot product by every 4 elements using AVX512 Skylake instructions.
This function takes two arrays of uint8 and int8 datatype -- data[4] and
kernel[16][4] -- and computes a dot product of data[4] with every
4 elements of kernels, resulting in output[16] of int32 datatype.
The pseudo code is as follows.
.. code-block:: c
void dot_16x1x16_uint8_int8_int32(uint8 data[4], int8 kernel[16][4],
int32 output[16]){
for (int i = 0; i < 16; i++){
output[i] = 0;
for (int k = 0; k < 4; k++){
output[i] += data[k] * kernel[i][k]
}
}
}
Physically, the kernel array sits in an AVX512 vector register and
the data[4] is broadcasted to another AVX512 vector register. This
function returns a TensorIntrin that can be used to tensorize
a schedule.
Returns
-------
intrin : TensorIntrin
The Skylake int8 TensorIntrin that can be used in tensorizing schedule
|
Int8 dot product by every 4 elements using AVX512 Skylake instructions.
This function takes two arrays of uint8 and int8 datatype -- data[4] and
kernel[16][4] -- and computes a dot product of data[4] with every
4 elements of kernels, resulting in output[16] of int32 datatype.
The pseudo code is as follows.
.. code-block:: c
void dot_16x1x16_uint8_int8_int32(uint8 data[4], int8 kernel[16][4],
int32 output[16]){
for (int i = 0; i < 16; i++){
output[i] = 0;
for (int k = 0; k < 4; k++){
output[i] += data[k] * kernel[i][k]
}
}
}
|
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def dot_16x1x16_uint8_int8_int32_skylake():
"""
Int8 dot product by every 4 elements using AVX512 Skylake instructions.
This function takes two arrays of uint8 and int8 datatype -- data[4] and
kernel[16][4] -- and computes a dot product of data[4] with every
4 elements of kernels, resulting in output[16] of int32 datatype.
The pseudo code is as follows.
.. code-block:: c
void dot_16x1x16_uint8_int8_int32(uint8 data[4], int8 kernel[16][4],
int32 output[16]){
for (int i = 0; i < 16; i++){
output[i] = 0;
for (int k = 0; k < 4; k++){
output[i] += data[k] * kernel[i][k]
}
}
}
Physically, the kernel array sits in an AVX512 vector register and
the data[4] is broadcasted to another AVX512 vector register. This
function returns a TensorIntrin that can be used to tensorize
a schedule.
Returns
-------
intrin : TensorIntrin
The Skylake int8 TensorIntrin that can be used in tensorizing schedule
"""
int32_lanes = get_simd_32bit_lanes()
num_int8_elements = 4 # 4 int8 elements in int32
data = te.placeholder((num_int8_elements,), dtype="uint8", name="data")
kernel = te.placeholder((int32_lanes, num_int8_elements), dtype="int8", name="kernel")
k = te.reduce_axis((0, num_int8_elements), name="k")
C = te.compute(
(int32_lanes,),
lambda i: te.sum(data[k].astype("int32") * kernel[i, k].astype("int32"), axis=k),
name="C",
)
a_buffer = tvm.tir.decl_buffer(
data.shape, dtype="uint8", name="a_buffer", offset_factor=1, strides=[1]
)
b_buffer = tvm.tir.decl_buffer(
kernel.shape, dtype="int8", name="b_buffer", offset_factor=1, strides=[te.var("ldw"), 1]
)
def _intrin_func(ins, outs):
def _instr(index):
# int_lx32 - output datatype after pmaddubs - 16 bits to number of lanes
# int_8xl - input datatype to pmaddubs - 8 bits to number of lanes
# int_32xl - output datatype after pmaddw - 32 bits per number of lanes
if int32_lanes == 4:
int_lx32 = "int16x8"
int_8xl = "int8x16"
int_32xl = "int32x4"
pmaddubs = "llvm.x86.ssse3.pmadd.ub.sw.128"
pmaddw = "llvm.x86.sse2.pmadd.wd"
elif int32_lanes == 8:
int_lx32 = "int16x16"
int_8xl = "int8x32"
int_32xl = "int32x8"
pmaddubs = "llvm.x86.avx2.pmadd.ub.sw"
pmaddw = "llvm.x86.avx2.pmadd.wd"
elif int32_lanes == 16:
int_lx32 = "int16x32"
int_8xl = "int8x64"
int_32xl = "int32x16"
pmaddubs = "llvm.x86.avx512.pmaddubs.w.512"
pmaddw = "llvm.x86.avx512.pmaddw.d.512"
ib = tvm.tir.ir_builder.create()
if index == 1:
ib.emit(outs[0].vstore(0, tvm.tir.const(0, int_32xl)))
return ib.get()
a_int8 = ins[0].vload([0], "uint8x4")
re_int32 = tvm.tir.call_intrin("int32", "tir.reinterpret", a_int8)
vec_ai32 = re_int32.astype(int_32xl)
vec_a = tvm.tir.call_intrin(int_8xl, "tir.reinterpret", vec_ai32)
vec_b = ins[1].vload([0, 0], int_8xl)
vec_one = tvm.tir.const(1, int_lx32)
pair_reduction = tvm.tir.call_llvm_pure_intrin(
int_lx32,
pmaddubs,
tvm.tir.const(0, "uint32"),
vec_a,
vec_b,
)
quad_reduction = tvm.tir.call_llvm_pure_intrin(
int_32xl,
pmaddw,
tvm.tir.const(0, "uint32"),
pair_reduction,
vec_one,
)
if index == 0:
ib.emit(outs[0].vstore(0, quad_reduction))
else:
ib.emit(outs[0].vstore(0, quad_reduction + outs[0].vload([0], int_32xl)))
return ib.get()
# body, reset, update
return _instr(0), _instr(1), _instr(2)
buffer_params = {"offset_factor": 1}
return te.decl_tensor_intrin(
C.op,
_intrin_func,
binds={data: a_buffer, kernel: b_buffer},
default_buffer_params=buffer_params,
)
|
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https://github.com/apache/tvm/blob/6eb4ed813ebcdcd9558f0906a1870db8302ff1e0/python/tvm/topi/x86/tensor_intrin.py#L37-L149
|
|
viniciuschiele/flask-apscheduler
|
5f878c41417824a4f37b353cb4b22973a81746f2
|
flask_apscheduler/scheduler.py
|
python
|
APScheduler.add_job
|
(self, id, func, **kwargs)
|
return self._scheduler.add_job(**job_def)
|
Add the given job to the job list and wakes up the scheduler if it's already running.
:param str id: explicit identifier for the job (for modifying it later)
:param func: callable (or a textual reference to one) to run at the given time
|
Add the given job to the job list and wakes up the scheduler if it's already running.
|
[
"Add",
"the",
"given",
"job",
"to",
"the",
"job",
"list",
"and",
"wakes",
"up",
"the",
"scheduler",
"if",
"it",
"s",
"already",
"running",
"."
] |
def add_job(self, id, func, **kwargs):
"""
Add the given job to the job list and wakes up the scheduler if it's already running.
:param str id: explicit identifier for the job (for modifying it later)
:param func: callable (or a textual reference to one) to run at the given time
"""
job_def = dict(kwargs)
job_def['id'] = id
job_def['func'] = func
job_def['name'] = job_def.get('name') or id
fix_job_def(job_def)
return self._scheduler.add_job(**job_def)
|
[
"def",
"add_job",
"(",
"self",
",",
"id",
",",
"func",
",",
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"*",
"kwargs",
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"self",
".",
"_scheduler",
".",
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"(",
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"*",
"job_def",
")"
] |
https://github.com/viniciuschiele/flask-apscheduler/blob/5f878c41417824a4f37b353cb4b22973a81746f2/flask_apscheduler/scheduler.py#L153-L168
|
|
Tencent/bk-bcs-saas
|
2b437bf2f5fd5ce2078f7787c3a12df609f7679d
|
bcs-app/backend/container_service/clusters/base/utils.py
|
python
|
get_cluster_coes
|
(access_token, project_id, cluster_id)
|
return cluster["type"]
|
获取集群类型，因为集群创建后，集群类型不允许修改
TODO: 为减少调用接口耗时，是否需要缓存？
|
获取集群类型，因为集群创建后，集群类型不允许修改
TODO: 为减少调用接口耗时，是否需要缓存？
|
[
"获取集群类型，因为集群创建后，集群类型不允许修改",
"TODO",
":",
"为减少调用接口耗时，是否需要缓存？"
] |
def get_cluster_coes(access_token, project_id, cluster_id):
"""获取集群类型，因为集群创建后，集群类型不允许修改
TODO: 为减少调用接口耗时，是否需要缓存？
"""
cluster = get_cluster(access_token, project_id, cluster_id)
return cluster["type"]
|
[
"def",
"get_cluster_coes",
"(",
"access_token",
",",
"project_id",
",",
"cluster_id",
")",
":",
"cluster",
"=",
"get_cluster",
"(",
"access_token",
",",
"project_id",
",",
"cluster_id",
")",
"return",
"cluster",
"[",
"\"type\"",
"]"
] |
https://github.com/Tencent/bk-bcs-saas/blob/2b437bf2f5fd5ce2078f7787c3a12df609f7679d/bcs-app/backend/container_service/clusters/base/utils.py#L102-L107
|
|
jgagneastro/coffeegrindsize
|
22661ebd21831dba4cf32bfc6ba59fe3d49f879c
|
App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/scipy/signal/signaltools.py
|
python
|
correlate
|
(in1, in2, mode='full', method='auto')
|
r"""
Cross-correlate two N-dimensional arrays.
Cross-correlate `in1` and `in2`, with the output size determined by the
`mode` argument.
Parameters
----------
in1 : array_like
First input.
in2 : array_like
Second input. Should have the same number of dimensions as `in1`.
mode : str {'full', 'valid', 'same'}, optional
A string indicating the size of the output:
``full``
The output is the full discrete linear cross-correlation
of the inputs. (Default)
``valid``
The output consists only of those elements that do not
rely on the zero-padding. In 'valid' mode, either `in1` or `in2`
must be at least as large as the other in every dimension.
``same``
The output is the same size as `in1`, centered
with respect to the 'full' output.
method : str {'auto', 'direct', 'fft'}, optional
A string indicating which method to use to calculate the correlation.
``direct``
The correlation is determined directly from sums, the definition of
correlation.
``fft``
The Fast Fourier Transform is used to perform the correlation more
quickly (only available for numerical arrays.)
``auto``
Automatically chooses direct or Fourier method based on an estimate
of which is faster (default). See `convolve` Notes for more detail.
.. versionadded:: 0.19.0
Returns
-------
correlate : array
An N-dimensional array containing a subset of the discrete linear
cross-correlation of `in1` with `in2`.
See Also
--------
choose_conv_method : contains more documentation on `method`.
Notes
-----
The correlation z of two d-dimensional arrays x and y is defined as::
z[...,k,...] = sum[..., i_l, ...] x[..., i_l,...] * conj(y[..., i_l - k,...])
This way, if x and y are 1-D arrays and ``z = correlate(x, y, 'full')``
then
.. math::
z[k] = (x * y)(k - N + 1)
= \sum_{l=0}^{||x||-1}x_l y_{l-k+N-1}^{*}
for :math:`k = 0, 1, ..., ||x|| + ||y|| - 2`
where :math:`||x||` is the length of ``x``, :math:`N = \max(||x||,||y||)`,
and :math:`y_m` is 0 when m is outside the range of y.
``method='fft'`` only works for numerical arrays as it relies on
`fftconvolve`. In certain cases (i.e., arrays of objects or when
rounding integers can lose precision), ``method='direct'`` is always used.
Examples
--------
Implement a matched filter using cross-correlation, to recover a signal
that has passed through a noisy channel.
>>> from scipy import signal
>>> sig = np.repeat([0., 1., 1., 0., 1., 0., 0., 1.], 128)
>>> sig_noise = sig + np.random.randn(len(sig))
>>> corr = signal.correlate(sig_noise, np.ones(128), mode='same') / 128
>>> import matplotlib.pyplot as plt
>>> clock = np.arange(64, len(sig), 128)
>>> fig, (ax_orig, ax_noise, ax_corr) = plt.subplots(3, 1, sharex=True)
>>> ax_orig.plot(sig)
>>> ax_orig.plot(clock, sig[clock], 'ro')
>>> ax_orig.set_title('Original signal')
>>> ax_noise.plot(sig_noise)
>>> ax_noise.set_title('Signal with noise')
>>> ax_corr.plot(corr)
>>> ax_corr.plot(clock, corr[clock], 'ro')
>>> ax_corr.axhline(0.5, ls=':')
>>> ax_corr.set_title('Cross-correlated with rectangular pulse')
>>> ax_orig.margins(0, 0.1)
>>> fig.tight_layout()
>>> fig.show()
|
r"""
Cross-correlate two N-dimensional arrays.
|
[
"r",
"Cross",
"-",
"correlate",
"two",
"N",
"-",
"dimensional",
"arrays",
"."
] |
def correlate(in1, in2, mode='full', method='auto'):
r"""
Cross-correlate two N-dimensional arrays.
Cross-correlate `in1` and `in2`, with the output size determined by the
`mode` argument.
Parameters
----------
in1 : array_like
First input.
in2 : array_like
Second input. Should have the same number of dimensions as `in1`.
mode : str {'full', 'valid', 'same'}, optional
A string indicating the size of the output:
``full``
The output is the full discrete linear cross-correlation
of the inputs. (Default)
``valid``
The output consists only of those elements that do not
rely on the zero-padding. In 'valid' mode, either `in1` or `in2`
must be at least as large as the other in every dimension.
``same``
The output is the same size as `in1`, centered
with respect to the 'full' output.
method : str {'auto', 'direct', 'fft'}, optional
A string indicating which method to use to calculate the correlation.
``direct``
The correlation is determined directly from sums, the definition of
correlation.
``fft``
The Fast Fourier Transform is used to perform the correlation more
quickly (only available for numerical arrays.)
``auto``
Automatically chooses direct or Fourier method based on an estimate
of which is faster (default). See `convolve` Notes for more detail.
.. versionadded:: 0.19.0
Returns
-------
correlate : array
An N-dimensional array containing a subset of the discrete linear
cross-correlation of `in1` with `in2`.
See Also
--------
choose_conv_method : contains more documentation on `method`.
Notes
-----
The correlation z of two d-dimensional arrays x and y is defined as::
z[...,k,...] = sum[..., i_l, ...] x[..., i_l,...] * conj(y[..., i_l - k,...])
This way, if x and y are 1-D arrays and ``z = correlate(x, y, 'full')``
then
.. math::
z[k] = (x * y)(k - N + 1)
= \sum_{l=0}^{||x||-1}x_l y_{l-k+N-1}^{*}
for :math:`k = 0, 1, ..., ||x|| + ||y|| - 2`
where :math:`||x||` is the length of ``x``, :math:`N = \max(||x||,||y||)`,
and :math:`y_m` is 0 when m is outside the range of y.
``method='fft'`` only works for numerical arrays as it relies on
`fftconvolve`. In certain cases (i.e., arrays of objects or when
rounding integers can lose precision), ``method='direct'`` is always used.
Examples
--------
Implement a matched filter using cross-correlation, to recover a signal
that has passed through a noisy channel.
>>> from scipy import signal
>>> sig = np.repeat([0., 1., 1., 0., 1., 0., 0., 1.], 128)
>>> sig_noise = sig + np.random.randn(len(sig))
>>> corr = signal.correlate(sig_noise, np.ones(128), mode='same') / 128
>>> import matplotlib.pyplot as plt
>>> clock = np.arange(64, len(sig), 128)
>>> fig, (ax_orig, ax_noise, ax_corr) = plt.subplots(3, 1, sharex=True)
>>> ax_orig.plot(sig)
>>> ax_orig.plot(clock, sig[clock], 'ro')
>>> ax_orig.set_title('Original signal')
>>> ax_noise.plot(sig_noise)
>>> ax_noise.set_title('Signal with noise')
>>> ax_corr.plot(corr)
>>> ax_corr.plot(clock, corr[clock], 'ro')
>>> ax_corr.axhline(0.5, ls=':')
>>> ax_corr.set_title('Cross-correlated with rectangular pulse')
>>> ax_orig.margins(0, 0.1)
>>> fig.tight_layout()
>>> fig.show()
"""
in1 = asarray(in1)
in2 = asarray(in2)
if in1.ndim == in2.ndim == 0:
return in1 * in2.conj()
elif in1.ndim != in2.ndim:
raise ValueError("in1 and in2 should have the same dimensionality")
# Don't use _valfrommode, since correlate should not accept numeric modes
try:
val = _modedict[mode]
except KeyError:
raise ValueError("Acceptable mode flags are 'valid',"
" 'same', or 'full'.")
# this either calls fftconvolve or this function with method=='direct'
if method in ('fft', 'auto'):
return convolve(in1, _reverse_and_conj(in2), mode, method)
elif method == 'direct':
# fastpath to faster numpy.correlate for 1d inputs when possible
if _np_conv_ok(in1, in2, mode):
return np.correlate(in1, in2, mode)
# _correlateND is far slower when in2.size > in1.size, so swap them
# and then undo the effect afterward if mode == 'full'. Also, it fails
# with 'valid' mode if in2 is larger than in1, so swap those, too.
# Don't swap inputs for 'same' mode, since shape of in1 matters.
swapped_inputs = ((mode == 'full') and (in2.size > in1.size) or
_inputs_swap_needed(mode, in1.shape, in2.shape))
if swapped_inputs:
in1, in2 = in2, in1
if mode == 'valid':
ps = [i - j + 1 for i, j in zip(in1.shape, in2.shape)]
out = np.empty(ps, in1.dtype)
z = sigtools._correlateND(in1, in2, out, val)
else:
ps = [i + j - 1 for i, j in zip(in1.shape, in2.shape)]
# zero pad input
in1zpadded = np.zeros(ps, in1.dtype)
sc = tuple(slice(0, i) for i in in1.shape)
in1zpadded[sc] = in1.copy()
if mode == 'full':
out = np.empty(ps, in1.dtype)
elif mode == 'same':
out = np.empty(in1.shape, in1.dtype)
z = sigtools._correlateND(in1zpadded, in2, out, val)
if swapped_inputs:
# Reverse and conjugate to undo the effect of swapping inputs
z = _reverse_and_conj(z)
return z
else:
raise ValueError("Acceptable method flags are 'auto',"
" 'direct', or 'fft'.")
|
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")"
] |
https://github.com/jgagneastro/coffeegrindsize/blob/22661ebd21831dba4cf32bfc6ba59fe3d49f879c/App/dist/coffeegrindsize.app/Contents/Resources/lib/python3.7/scipy/signal/signaltools.py#L105-L269
|
||
TheAlgorithms/Python
|
9af2eef9b3761bf51580dedfb6fa7136ca0c5c2c
|
ciphers/porta_cipher.py
|
python
|
generate_table
|
(key: str)
|
return [alphabet[char] for char in key.upper()]
|
>>> generate_table('marvin') # doctest: +NORMALIZE_WHITESPACE
[('ABCDEFGHIJKLM', 'UVWXYZNOPQRST'), ('ABCDEFGHIJKLM', 'NOPQRSTUVWXYZ'),
('ABCDEFGHIJKLM', 'STUVWXYZNOPQR'), ('ABCDEFGHIJKLM', 'QRSTUVWXYZNOP'),
('ABCDEFGHIJKLM', 'WXYZNOPQRSTUV'), ('ABCDEFGHIJKLM', 'UVWXYZNOPQRST')]
|
>>> generate_table('marvin') # doctest: +NORMALIZE_WHITESPACE
[('ABCDEFGHIJKLM', 'UVWXYZNOPQRST'), ('ABCDEFGHIJKLM', 'NOPQRSTUVWXYZ'),
('ABCDEFGHIJKLM', 'STUVWXYZNOPQR'), ('ABCDEFGHIJKLM', 'QRSTUVWXYZNOP'),
('ABCDEFGHIJKLM', 'WXYZNOPQRSTUV'), ('ABCDEFGHIJKLM', 'UVWXYZNOPQRST')]
|
[
">>>",
"generate_table",
"(",
"marvin",
")",
"#",
"doctest",
":",
"+",
"NORMALIZE_WHITESPACE",
"[",
"(",
"ABCDEFGHIJKLM",
"UVWXYZNOPQRST",
")",
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"ABCDEFGHIJKLM",
"NOPQRSTUVWXYZ",
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"ABCDEFGHIJKLM",
"STUVWXYZNOPQR",
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"QRSTUVWXYZNOP",
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"ABCDEFGHIJKLM",
"WXYZNOPQRSTUV",
")",
"(",
"ABCDEFGHIJKLM",
"UVWXYZNOPQRST",
")",
"]"
] |
def generate_table(key: str) -> list[tuple[str, str]]:
"""
>>> generate_table('marvin') # doctest: +NORMALIZE_WHITESPACE
[('ABCDEFGHIJKLM', 'UVWXYZNOPQRST'), ('ABCDEFGHIJKLM', 'NOPQRSTUVWXYZ'),
('ABCDEFGHIJKLM', 'STUVWXYZNOPQR'), ('ABCDEFGHIJKLM', 'QRSTUVWXYZNOP'),
('ABCDEFGHIJKLM', 'WXYZNOPQRSTUV'), ('ABCDEFGHIJKLM', 'UVWXYZNOPQRST')]
"""
return [alphabet[char] for char in key.upper()]
|
[
"def",
"generate_table",
"(",
"key",
":",
"str",
")",
"->",
"list",
"[",
"tuple",
"[",
"str",
",",
"str",
"]",
"]",
":",
"return",
"[",
"alphabet",
"[",
"char",
"]",
"for",
"char",
"in",
"key",
".",
"upper",
"(",
")",
"]"
] |
https://github.com/TheAlgorithms/Python/blob/9af2eef9b3761bf51580dedfb6fa7136ca0c5c2c/ciphers/porta_cipher.py#L31-L38
|
|
saltstack/salt
|
fae5bc757ad0f1716483ce7ae180b451545c2058
|
salt/sdb/cache.py
|
python
|
set_
|
(key, value, service=None, profile=None)
|
return get(key, service, profile)
|
Set a key/value pair in the cache service
|
Set a key/value pair in the cache service
|
[
"Set",
"a",
"key",
"/",
"value",
"pair",
"in",
"the",
"cache",
"service"
] |
def set_(key, value, service=None, profile=None): # pylint: disable=W0613
"""
Set a key/value pair in the cache service
"""
key, profile = _parse_key(key, profile)
cache = salt.cache.Cache(__opts__)
cache.store(profile["bank"], key, value)
return get(key, service, profile)
|
[
"def",
"set_",
"(",
"key",
",",
"value",
",",
"service",
"=",
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",",
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] |
https://github.com/saltstack/salt/blob/fae5bc757ad0f1716483ce7ae180b451545c2058/salt/sdb/cache.py#L62-L69
|
|
oilshell/oil
|
94388e7d44a9ad879b12615f6203b38596b5a2d3
|
Python-2.7.13/Lib/plat-mac/Carbon/Menus.py
|
python
|
FOUR_CHAR_CODE
|
(x)
|
return x
|
[] |
def FOUR_CHAR_CODE(x): return x
|
[
"def",
"FOUR_CHAR_CODE",
"(",
"x",
")",
":",
"return",
"x"
] |
https://github.com/oilshell/oil/blob/94388e7d44a9ad879b12615f6203b38596b5a2d3/Python-2.7.13/Lib/plat-mac/Carbon/Menus.py#L3-L3
|
|||
garydoranjr/misvm
|
b2118fe04d98c00436bdf8a0e4bbfb6082c5751c
|
misvm/misssvm.py
|
python
|
MissSVM.fit
|
(self, bags, y)
|
@param bags : a sequence of n bags; each bag is an m-by-k array-like
object containing m instances with k features
@param y : an array-like object of length n containing -1/+1 labels
|
[] |
def fit(self, bags, y):
"""
@param bags : a sequence of n bags; each bag is an m-by-k array-like
object containing m instances with k features
@param y : an array-like object of length n containing -1/+1 labels
"""
self._bags = list(map(np.asmatrix, bags))
bs = BagSplitter(self._bags,
np.asmatrix(y).reshape((-1, 1)))
self._X = np.vstack([bs.pos_instances,
bs.pos_instances,
bs.pos_instances,
bs.neg_instances])
self._y = np.vstack([np.matrix(np.ones((bs.X_p + bs.L_p, 1))),
-np.matrix(np.ones((bs.L_p + bs.L_n, 1)))])
if self.scale_C:
C = self.C / float(len(self._bags))
else:
C = self.C
# Setup SVM and adjust constraints
_, _, f, A, b, lb, ub = self._setup_svm(self._y, self._y, C)
ub[:bs.X_p] *= (float(bs.L_n) / float(bs.X_p))
ub[bs.X_p: bs.X_p + 2 * bs.L_p] *= (float(bs.L_n) / float(bs.L_p))
K = kernel_by_name(self.kernel, gamma=self.gamma, p=self.p)(self._X, self._X)
D = spdiag(self._y)
ub0 = np.matrix(ub)
ub0[bs.X_p: bs.X_p + 2 * bs.L_p] *= 0.5
def get_V(pos_classifications):
eye_n = bs.L_n + 2 * bs.L_p
top = np.zeros((bs.X_p, bs.L_p))
for row, (i, j) in enumerate(slices(bs.pos_groups)):
top[row, i:j] = _grad_softmin(-pos_classifications[i:j], self.alpha).flat
return sp.bmat([[sp.coo_matrix(top), None],
[None, sp.eye(eye_n, eye_n)]])
V0 = get_V(np.matrix(np.zeros((bs.L_p, 1))))
qp = IterativeQP(D * V0 * K * V0.T * D, f, A, b, lb, ub0)
best_obj = float('inf')
best_svm = None
for rr in range(self.restarts + 1):
if rr == 0:
if self.verbose:
print('Non-random start...')
# Train on instances
alphas, obj = qp.solve(self.verbose)
else:
if self.verbose:
print('Random restart %d of %d...' % (rr, self.restarts))
alphas = np.matrix([uniform(0.0, 1.0) for i in range(len(lb))]).T
obj = Objective(0.0, 0.0)
svm = MICA(kernel=self.kernel, gamma=self.gamma, p=self.p,
verbose=self.verbose, sv_cutoff=self.sv_cutoff)
svm._X = self._X
svm._y = self._y
svm._V = V0
svm._alphas = alphas
svm._objective = obj
svm._compute_separator(K)
svm._K = K
class missCCCP(CCCP):
def bailout(cself, svm, obj_val):
return svm
def iterate(cself, svm, obj_val):
cself.mention('Linearizing constraints...')
classifications = svm._predictions[bs.X_p: bs.X_p + bs.L_p]
V = get_V(classifications)
cself.mention('Computing slacks...')
# Difference is [1 - y_i*(w*phi(x_i) + b)]
pos_differences = 1.0 - classifications
neg_differences = 1.0 + classifications
# Slacks are positive differences only
pos_slacks = np.multiply(pos_differences > 0, pos_differences)
neg_slacks = np.multiply(neg_differences > 0, neg_differences)
all_slacks = np.hstack([pos_slacks, neg_slacks])
cself.mention('Linearizing...')
# Compute gradient across pairs
slack_grads = np.vstack([_grad_softmin(pair, self.alpha)
for pair in all_slacks])
# Stack results into one column
slack_grads = np.vstack([np.ones((bs.X_p, 1)),
slack_grads[:, 0],
slack_grads[:, 1],
np.ones((bs.L_n, 1))])
# Update QP
qp.update_H(D * V * K * V.T * D)
qp.update_ub(np.multiply(ub, slack_grads))
# Re-solve
cself.mention('Solving QP...')
alphas, obj = qp.solve(self.verbose)
new_svm = MICA(kernel=self.kernel, gamma=self.gamma, p=self.p,
verbose=self.verbose, sv_cutoff=self.sv_cutoff)
new_svm._X = self._X
new_svm._y = self._y
new_svm._V = V
new_svm._alphas = alphas
new_svm._objective = obj
new_svm._compute_separator(K)
new_svm._K = K
if cself.check_tolerance(obj_val, obj):
return None, new_svm
return {'svm': new_svm, 'obj_val': obj}, None
cccp = missCCCP(verbose=self.verbose, svm=svm, obj_val=None,
max_iters=self.max_iters)
svm = cccp.solve()
if svm is not None:
obj = float(svm._objective)
if obj < best_obj:
best_svm = svm
best_obj = obj
if best_svm is not None:
self._V = best_svm._V
self._alphas = best_svm._alphas
self._objective = best_svm._objective
self._compute_separator(best_svm._K)
self._bag_predictions = self.predict(self._bags)
|
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https://github.com/garydoranjr/misvm/blob/b2118fe04d98c00436bdf8a0e4bbfb6082c5751c/misvm/misssvm.py#L45-L173
|
|||
HymanLiuTS/flaskTs
|
286648286976e85d9b9a5873632331efcafe0b21
|
flasky/lib/python2.7/site-packages/sqlalchemy/dialects/mssql/base.py
|
python
|
MSSQLCompiler.visit_binary
|
(self, binary, **kwargs)
|
return super(MSSQLCompiler, self).visit_binary(binary, **kwargs)
|
Move bind parameters to the right-hand side of an operator, where
possible.
|
Move bind parameters to the right-hand side of an operator, where
possible.
|
[
"Move",
"bind",
"parameters",
"to",
"the",
"right",
"-",
"hand",
"side",
"of",
"an",
"operator",
"where",
"possible",
"."
] |
def visit_binary(self, binary, **kwargs):
"""Move bind parameters to the right-hand side of an operator, where
possible.
"""
if (
isinstance(binary.left, expression.BindParameter)
and binary.operator == operator.eq
and not isinstance(binary.right, expression.BindParameter)
):
return self.process(
expression.BinaryExpression(binary.right,
binary.left,
binary.operator),
**kwargs)
return super(MSSQLCompiler, self).visit_binary(binary, **kwargs)
|
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https://github.com/HymanLiuTS/flaskTs/blob/286648286976e85d9b9a5873632331efcafe0b21/flasky/lib/python2.7/site-packages/sqlalchemy/dialects/mssql/base.py#L1287-L1302
|
|
pyparallel/pyparallel
|
11e8c6072d48c8f13641925d17b147bf36ee0ba3
|
Lib/site-packages/pygments-2.0.2-py3.3.egg/pygments/scanner.py
|
python
|
Scanner.test
|
(self, pattern)
|
return self.check(pattern) is not None
|
Apply a pattern on the current position and check
if it patches. Doesn't touch pos.
|
Apply a pattern on the current position and check
if it patches. Doesn't touch pos.
|
[
"Apply",
"a",
"pattern",
"on",
"the",
"current",
"position",
"and",
"check",
"if",
"it",
"patches",
".",
"Doesn",
"t",
"touch",
"pos",
"."
] |
def test(self, pattern):
"""Apply a pattern on the current position and check
if it patches. Doesn't touch pos."""
return self.check(pattern) is not None
|
[
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"is",
"not",
"None"
] |
https://github.com/pyparallel/pyparallel/blob/11e8c6072d48c8f13641925d17b147bf36ee0ba3/Lib/site-packages/pygments-2.0.2-py3.3.egg/pygments/scanner.py#L67-L70
|
|
ilius/pyglossary
|
d599b3beda3ae17642af5debd83bb991148e6425
|
pyglossary/plugin_lib/py38/gzip_no_crc.py
|
python
|
GzipFile.filename
|
(self)
|
return self.name
|
[] |
def filename(self):
import warnings
warnings.warn("use the name attribute", DeprecationWarning, 2)
if self.mode == WRITE and self.name[-3:] != ".gz":
return self.name + ".gz"
return self.name
|
[
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"self",
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"name",
"+",
"\".gz\"",
"return",
"self",
".",
"name"
] |
https://github.com/ilius/pyglossary/blob/d599b3beda3ae17642af5debd83bb991148e6425/pyglossary/plugin_lib/py38/gzip_no_crc.py#L200-L205
|
|||
GothicAi/Instaboost
|
b6f80405b8706adad4aca1c1bdbb650b9c1c71e5
|
mmdetection/mmdet/core/bbox/samplers/random_sampler.py
|
python
|
RandomSampler._sample_pos
|
(self, assign_result, num_expected, **kwargs)
|
Randomly sample some positive samples.
|
Randomly sample some positive samples.
|
[
"Randomly",
"sample",
"some",
"positive",
"samples",
"."
] |
def _sample_pos(self, assign_result, num_expected, **kwargs):
"""Randomly sample some positive samples."""
pos_inds = torch.nonzero(assign_result.gt_inds > 0)
if pos_inds.numel() != 0:
pos_inds = pos_inds.squeeze(1)
if pos_inds.numel() <= num_expected:
return pos_inds
else:
return self.random_choice(pos_inds, num_expected)
|
[
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",",
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".",
"random_choice",
"(",
"pos_inds",
",",
"num_expected",
")"
] |
https://github.com/GothicAi/Instaboost/blob/b6f80405b8706adad4aca1c1bdbb650b9c1c71e5/mmdetection/mmdet/core/bbox/samplers/random_sampler.py#L35-L43
|
||
out0fmemory/GoAgent-Always-Available
|
c4254984fea633ce3d1893fe5901debd9f22c2a9
|
server/lib/google/appengine/_internal/antlr3/streams.py
|
python
|
TokenRewriteStream.rollback
|
(self, *args)
|
Rollback the instruction stream for a program so that
the indicated instruction (via instructionIndex) is no
longer in the stream. UNTESTED!
|
Rollback the instruction stream for a program so that
the indicated instruction (via instructionIndex) is no
longer in the stream. UNTESTED!
|
[
"Rollback",
"the",
"instruction",
"stream",
"for",
"a",
"program",
"so",
"that",
"the",
"indicated",
"instruction",
"(",
"via",
"instructionIndex",
")",
"is",
"no",
"longer",
"in",
"the",
"stream",
".",
"UNTESTED!"
] |
def rollback(self, *args):
"""
Rollback the instruction stream for a program so that
the indicated instruction (via instructionIndex) is no
longer in the stream. UNTESTED!
"""
if len(args) == 2:
programName = args[0]
instructionIndex = args[1]
elif len(args) == 1:
programName = self.DEFAULT_PROGRAM_NAME
instructionIndex = args[0]
else:
raise TypeError("Invalid arguments")
p = self.programs.get(programName, None)
if p is not None:
self.programs[programName] = (
p[self.MIN_TOKEN_INDEX:instructionIndex])
|
[
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] |
https://github.com/out0fmemory/GoAgent-Always-Available/blob/c4254984fea633ce3d1893fe5901debd9f22c2a9/server/lib/google/appengine/_internal/antlr3/streams.py#L1066-L1085
|
||
buke/GreenOdoo
|
3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df
|
runtime/common/lib/python2.7/site-packages/libxml2.py
|
python
|
relaxNGInitTypes
|
()
|
return ret
|
Initilize the default type libraries.
|
Initilize the default type libraries.
|
[
"Initilize",
"the",
"default",
"type",
"libraries",
"."
] |
def relaxNGInitTypes():
"""Initilize the default type libraries. """
ret = libxml2mod.xmlRelaxNGInitTypes()
return ret
|
[
"def",
"relaxNGInitTypes",
"(",
")",
":",
"ret",
"=",
"libxml2mod",
".",
"xmlRelaxNGInitTypes",
"(",
")",
"return",
"ret"
] |
https://github.com/buke/GreenOdoo/blob/3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df/runtime/common/lib/python2.7/site-packages/libxml2.py#L1574-L1577
|
|
sagemath/sage
|
f9b2db94f675ff16963ccdefba4f1a3393b3fe0d
|
src/sage/combinat/root_system/type_dual.py
|
python
|
CartanType.dual
|
(self)
|
return self._type
|
EXAMPLES::
sage: ct = CartanType(['F', 4, 1]).dual()
sage: ct.dual()
['F', 4, 1]
|
EXAMPLES::
|
[
"EXAMPLES",
"::"
] |
def dual(self):
"""
EXAMPLES::
sage: ct = CartanType(['F', 4, 1]).dual()
sage: ct.dual()
['F', 4, 1]
"""
return self._type
|
[
"def",
"dual",
"(",
"self",
")",
":",
"return",
"self",
".",
"_type"
] |
https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/combinat/root_system/type_dual.py#L324-L332
|
|
numenta/nupic
|
b9ebedaf54f49a33de22d8d44dff7c765cdb5548
|
external/linux32/lib/python2.6/site-packages/matplotlib/pyplot.py
|
python
|
jet
|
()
|
set the default colormap to jet and apply to current image if any.
See help(colormaps) for more information
|
set the default colormap to jet and apply to current image if any.
See help(colormaps) for more information
|
[
"set",
"the",
"default",
"colormap",
"to",
"jet",
"and",
"apply",
"to",
"current",
"image",
"if",
"any",
".",
"See",
"help",
"(",
"colormaps",
")",
"for",
"more",
"information"
] |
def jet():
'''
set the default colormap to jet and apply to current image if any.
See help(colormaps) for more information
'''
rc('image', cmap='jet')
im = gci()
if im is not None:
im.set_cmap(cm.jet)
draw_if_interactive()
|
[
"def",
"jet",
"(",
")",
":",
"rc",
"(",
"'image'",
",",
"cmap",
"=",
"'jet'",
")",
"im",
"=",
"gci",
"(",
")",
"if",
"im",
"is",
"not",
"None",
":",
"im",
".",
"set_cmap",
"(",
"cm",
".",
"jet",
")",
"draw_if_interactive",
"(",
")"
] |
https://github.com/numenta/nupic/blob/b9ebedaf54f49a33de22d8d44dff7c765cdb5548/external/linux32/lib/python2.6/site-packages/matplotlib/pyplot.py#L2599-L2609
|
||
thomasvs/morituri
|
135b2f7bf27721177e3aeb1d26403f1b29116599
|
morituri/extern/task/task.py
|
python
|
ITaskListener.progressed
|
(self, task, value)
|
Implement me to be informed about progress.
@type value: float
@param value: progress, from 0.0 to 1.0
|
Implement me to be informed about progress.
|
[
"Implement",
"me",
"to",
"be",
"informed",
"about",
"progress",
"."
] |
def progressed(self, task, value):
"""
Implement me to be informed about progress.
@type value: float
@param value: progress, from 0.0 to 1.0
"""
|
[
"def",
"progressed",
"(",
"self",
",",
"task",
",",
"value",
")",
":"
] |
https://github.com/thomasvs/morituri/blob/135b2f7bf27721177e3aeb1d26403f1b29116599/morituri/extern/task/task.py#L247-L253
|
||
bnpy/bnpy
|
d5b311e8f58ccd98477f4a0c8a4d4982e3fca424
|
bnpy/allocmodel/hmm/HDPHMM.py
|
python
|
HDPHMM.get_init_prob_vector
|
(self)
|
return expELogPi0[0:self.K]
|
Get vector of initial probabilities for all K active states
|
Get vector of initial probabilities for all K active states
|
[
"Get",
"vector",
"of",
"initial",
"probabilities",
"for",
"all",
"K",
"active",
"states"
] |
def get_init_prob_vector(self):
''' Get vector of initial probabilities for all K active states
'''
expELogPi0 = digamma(
self.startTheta) - digamma(np.sum(self.startTheta))
np.exp(expELogPi0, out=expELogPi0)
return expELogPi0[0:self.K]
|
[
"def",
"get_init_prob_vector",
"(",
"self",
")",
":",
"expELogPi0",
"=",
"digamma",
"(",
"self",
".",
"startTheta",
")",
"-",
"digamma",
"(",
"np",
".",
"sum",
"(",
"self",
".",
"startTheta",
")",
")",
"np",
".",
"exp",
"(",
"expELogPi0",
",",
"out",
"=",
"expELogPi0",
")",
"return",
"expELogPi0",
"[",
"0",
":",
"self",
".",
"K",
"]"
] |
https://github.com/bnpy/bnpy/blob/d5b311e8f58ccd98477f4a0c8a4d4982e3fca424/bnpy/allocmodel/hmm/HDPHMM.py#L81-L87
|
|
itailang/SampleNet
|
442459abc54f9e14f0966a169a094a98febd32eb
|
classification/utils/plyfile.py
|
python
|
PlyProperty.name
|
(self)
|
return self._name
|
[] |
def name(self):
return self._name
|
[
"def",
"name",
"(",
"self",
")",
":",
"return",
"self",
".",
"_name"
] |
https://github.com/itailang/SampleNet/blob/442459abc54f9e14f0966a169a094a98febd32eb/classification/utils/plyfile.py#L730-L731
|
|||
oilshell/oil
|
94388e7d44a9ad879b12615f6203b38596b5a2d3
|
Python-2.7.13/Lib/decimal.py
|
python
|
Context.remainder_near
|
(self, a, b)
|
return a.remainder_near(b, context=self)
|
Returns to be "a - b * n", where n is the integer nearest the exact
value of "x / b" (if two integers are equally near then the even one
is chosen). If the result is equal to 0 then its sign will be the
sign of a.
This operation will fail under the same conditions as integer division
(that is, if integer division on the same two operands would fail, the
remainder cannot be calculated).
>>> ExtendedContext.remainder_near(Decimal('2.1'), Decimal('3'))
Decimal('-0.9')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('6'))
Decimal('-2')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('3'))
Decimal('1')
>>> ExtendedContext.remainder_near(Decimal('-10'), Decimal('3'))
Decimal('-1')
>>> ExtendedContext.remainder_near(Decimal('10.2'), Decimal('1'))
Decimal('0.2')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('0.3'))
Decimal('0.1')
>>> ExtendedContext.remainder_near(Decimal('3.6'), Decimal('1.3'))
Decimal('-0.3')
>>> ExtendedContext.remainder_near(3, 11)
Decimal('3')
>>> ExtendedContext.remainder_near(Decimal(3), 11)
Decimal('3')
>>> ExtendedContext.remainder_near(3, Decimal(11))
Decimal('3')
|
Returns to be "a - b * n", where n is the integer nearest the exact
value of "x / b" (if two integers are equally near then the even one
is chosen). If the result is equal to 0 then its sign will be the
sign of a.
|
[
"Returns",
"to",
"be",
"a",
"-",
"b",
"*",
"n",
"where",
"n",
"is",
"the",
"integer",
"nearest",
"the",
"exact",
"value",
"of",
"x",
"/",
"b",
"(",
"if",
"two",
"integers",
"are",
"equally",
"near",
"then",
"the",
"even",
"one",
"is",
"chosen",
")",
".",
"If",
"the",
"result",
"is",
"equal",
"to",
"0",
"then",
"its",
"sign",
"will",
"be",
"the",
"sign",
"of",
"a",
"."
] |
def remainder_near(self, a, b):
"""Returns to be "a - b * n", where n is the integer nearest the exact
value of "x / b" (if two integers are equally near then the even one
is chosen). If the result is equal to 0 then its sign will be the
sign of a.
This operation will fail under the same conditions as integer division
(that is, if integer division on the same two operands would fail, the
remainder cannot be calculated).
>>> ExtendedContext.remainder_near(Decimal('2.1'), Decimal('3'))
Decimal('-0.9')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('6'))
Decimal('-2')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('3'))
Decimal('1')
>>> ExtendedContext.remainder_near(Decimal('-10'), Decimal('3'))
Decimal('-1')
>>> ExtendedContext.remainder_near(Decimal('10.2'), Decimal('1'))
Decimal('0.2')
>>> ExtendedContext.remainder_near(Decimal('10'), Decimal('0.3'))
Decimal('0.1')
>>> ExtendedContext.remainder_near(Decimal('3.6'), Decimal('1.3'))
Decimal('-0.3')
>>> ExtendedContext.remainder_near(3, 11)
Decimal('3')
>>> ExtendedContext.remainder_near(Decimal(3), 11)
Decimal('3')
>>> ExtendedContext.remainder_near(3, Decimal(11))
Decimal('3')
"""
a = _convert_other(a, raiseit=True)
return a.remainder_near(b, context=self)
|
[
"def",
"remainder_near",
"(",
"self",
",",
"a",
",",
"b",
")",
":",
"a",
"=",
"_convert_other",
"(",
"a",
",",
"raiseit",
"=",
"True",
")",
"return",
"a",
".",
"remainder_near",
"(",
"b",
",",
"context",
"=",
"self",
")"
] |
https://github.com/oilshell/oil/blob/94388e7d44a9ad879b12615f6203b38596b5a2d3/Python-2.7.13/Lib/decimal.py#L5149-L5181
|
|
entropy1337/infernal-twin
|
10995cd03312e39a48ade0f114ebb0ae3a711bb8
|
Modules/build/pip/pip/utils/appdirs.py
|
python
|
site_config_dirs
|
(appname)
|
return pathlist
|
Return a list of potential user-shared config dirs for this application.
"appname" is the name of application.
Typical user config directories are:
Mac OS X: /Library/Application Support/<AppName>/
Unix: /etc or $XDG_CONFIG_DIRS[i]/<AppName>/ for each value in
$XDG_CONFIG_DIRS
Win XP: C:\Documents and Settings\All Users\Application ...
...Data\<AppName>\
Vista: (Fail! "C:\ProgramData" is a hidden *system* directory
on Vista.)
Win 7: Hidden, but writeable on Win 7:
C:\ProgramData\<AppName>\
|
Return a list of potential user-shared config dirs for this application.
|
[
"Return",
"a",
"list",
"of",
"potential",
"user",
"-",
"shared",
"config",
"dirs",
"for",
"this",
"application",
"."
] |
def site_config_dirs(appname):
"""Return a list of potential user-shared config dirs for this application.
"appname" is the name of application.
Typical user config directories are:
Mac OS X: /Library/Application Support/<AppName>/
Unix: /etc or $XDG_CONFIG_DIRS[i]/<AppName>/ for each value in
$XDG_CONFIG_DIRS
Win XP: C:\Documents and Settings\All Users\Application ...
...Data\<AppName>\
Vista: (Fail! "C:\ProgramData" is a hidden *system* directory
on Vista.)
Win 7: Hidden, but writeable on Win 7:
C:\ProgramData\<AppName>\
"""
if WINDOWS:
path = os.path.normpath(_get_win_folder("CSIDL_COMMON_APPDATA"))
pathlist = [os.path.join(path, appname)]
elif sys.platform == 'darwin':
pathlist = [os.path.join('/Library/Application Support', appname)]
else:
# try looking in $XDG_CONFIG_DIRS
xdg_config_dirs = os.getenv('XDG_CONFIG_DIRS', '/etc/xdg')
if xdg_config_dirs:
pathlist = [
os.sep.join([os.path.expanduser(x), appname])
for x in xdg_config_dirs.split(os.pathsep)
]
else:
pathlist = []
# always look in /etc directly as well
pathlist.append('/etc')
return pathlist
|
[
"def",
"site_config_dirs",
"(",
"appname",
")",
":",
"if",
"WINDOWS",
":",
"path",
"=",
"os",
".",
"path",
".",
"normpath",
"(",
"_get_win_folder",
"(",
"\"CSIDL_COMMON_APPDATA\"",
")",
")",
"pathlist",
"=",
"[",
"os",
".",
"path",
".",
"join",
"(",
"path",
",",
"appname",
")",
"]",
"elif",
"sys",
".",
"platform",
"==",
"'darwin'",
":",
"pathlist",
"=",
"[",
"os",
".",
"path",
".",
"join",
"(",
"'/Library/Application Support'",
",",
"appname",
")",
"]",
"else",
":",
"# try looking in $XDG_CONFIG_DIRS",
"xdg_config_dirs",
"=",
"os",
".",
"getenv",
"(",
"'XDG_CONFIG_DIRS'",
",",
"'/etc/xdg'",
")",
"if",
"xdg_config_dirs",
":",
"pathlist",
"=",
"[",
"os",
".",
"sep",
".",
"join",
"(",
"[",
"os",
".",
"path",
".",
"expanduser",
"(",
"x",
")",
",",
"appname",
"]",
")",
"for",
"x",
"in",
"xdg_config_dirs",
".",
"split",
"(",
"os",
".",
"pathsep",
")",
"]",
"else",
":",
"pathlist",
"=",
"[",
"]",
"# always look in /etc directly as well",
"pathlist",
".",
"append",
"(",
"'/etc'",
")",
"return",
"pathlist"
] |
https://github.com/entropy1337/infernal-twin/blob/10995cd03312e39a48ade0f114ebb0ae3a711bb8/Modules/build/pip/pip/utils/appdirs.py#L165-L200
|
|
CedricGuillemet/Imogen
|
ee417b42747ed5b46cb11b02ef0c3630000085b3
|
bin/Lib/selectors.py
|
python
|
BaseSelector.register
|
(self, fileobj, events, data=None)
|
Register a file object.
Parameters:
fileobj -- file object or file descriptor
events -- events to monitor (bitwise mask of EVENT_READ|EVENT_WRITE)
data -- attached data
Returns:
SelectorKey instance
Raises:
ValueError if events is invalid
KeyError if fileobj is already registered
OSError if fileobj is closed or otherwise is unacceptable to
the underlying system call (if a system call is made)
Note:
OSError may or may not be raised
|
Register a file object.
|
[
"Register",
"a",
"file",
"object",
"."
] |
def register(self, fileobj, events, data=None):
"""Register a file object.
Parameters:
fileobj -- file object or file descriptor
events -- events to monitor (bitwise mask of EVENT_READ|EVENT_WRITE)
data -- attached data
Returns:
SelectorKey instance
Raises:
ValueError if events is invalid
KeyError if fileobj is already registered
OSError if fileobj is closed or otherwise is unacceptable to
the underlying system call (if a system call is made)
Note:
OSError may or may not be raised
"""
raise NotImplementedError
|
[
"def",
"register",
"(",
"self",
",",
"fileobj",
",",
"events",
",",
"data",
"=",
"None",
")",
":",
"raise",
"NotImplementedError"
] |
https://github.com/CedricGuillemet/Imogen/blob/ee417b42747ed5b46cb11b02ef0c3630000085b3/bin/Lib/selectors.py#L96-L116
|
||
trailofbits/manticore
|
b050fdf0939f6c63f503cdf87ec0ab159dd41159
|
manticore/core/smtlib/solver.py
|
python
|
PortfolioSolver._reset
|
(self, constraints: Optional[str] = None)
|
Auxiliary method to reset the smtlib external solver to initial defaults
|
Auxiliary method to reset the smtlib external solver to initial defaults
|
[
"Auxiliary",
"method",
"to",
"reset",
"the",
"smtlib",
"external",
"solver",
"to",
"initial",
"defaults"
] |
def _reset(self, constraints: Optional[str] = None) -> None:
"""Auxiliary method to reset the smtlib external solver to initial defaults"""
if self._support_reset:
self._smtlib.start() # does not do anything if already started
self._smtlib.send("(reset)")
else:
self._smtlib.stop() # does not do anything if already stopped
self._smtlib.start()
self._smtlib.init()
if constraints is not None:
self._smtlib.send(constraints)
|
[
"def",
"_reset",
"(",
"self",
",",
"constraints",
":",
"Optional",
"[",
"str",
"]",
"=",
"None",
")",
"->",
"None",
":",
"if",
"self",
".",
"_support_reset",
":",
"self",
".",
"_smtlib",
".",
"start",
"(",
")",
"# does not do anything if already started",
"self",
".",
"_smtlib",
".",
"send",
"(",
"\"(reset)\"",
")",
"else",
":",
"self",
".",
"_smtlib",
".",
"stop",
"(",
")",
"# does not do anything if already stopped",
"self",
".",
"_smtlib",
".",
"start",
"(",
")",
"self",
".",
"_smtlib",
".",
"init",
"(",
")",
"if",
"constraints",
"is",
"not",
"None",
":",
"self",
".",
"_smtlib",
".",
"send",
"(",
"constraints",
")"
] |
https://github.com/trailofbits/manticore/blob/b050fdf0939f6c63f503cdf87ec0ab159dd41159/manticore/core/smtlib/solver.py#L1066-L1078
|
||
wxWidgets/Phoenix
|
b2199e299a6ca6d866aa6f3d0888499136ead9d6
|
wx/lib/graphics.py
|
python
|
GraphicsBitmap.__init__
|
(self, width=-1, height=-1, format=FORMAT_ARGB32)
|
Create either a NULL GraphicsBitmap or an empty one if a size is given
|
Create either a NULL GraphicsBitmap or an empty one if a size is given
|
[
"Create",
"either",
"a",
"NULL",
"GraphicsBitmap",
"or",
"an",
"empty",
"one",
"if",
"a",
"size",
"is",
"given"
] |
def __init__(self, width=-1, height=-1, format=FORMAT_ARGB32):
"""Create either a NULL GraphicsBitmap or an empty one if a size is given"""
self._surface = None
if width > 0 and height > 0:
self._surface = cairo.ImageSurface(format, width, height)
|
[
"def",
"__init__",
"(",
"self",
",",
"width",
"=",
"-",
"1",
",",
"height",
"=",
"-",
"1",
",",
"format",
"=",
"FORMAT_ARGB32",
")",
":",
"self",
".",
"_surface",
"=",
"None",
"if",
"width",
">",
"0",
"and",
"height",
">",
"0",
":",
"self",
".",
"_surface",
"=",
"cairo",
".",
"ImageSurface",
"(",
"format",
",",
"width",
",",
"height",
")"
] |
https://github.com/wxWidgets/Phoenix/blob/b2199e299a6ca6d866aa6f3d0888499136ead9d6/wx/lib/graphics.py#L611-L615
|
||
IJDykeman/wangTiles
|
7c1ee2095ebdf7f72bce07d94c6484915d5cae8b
|
experimental_code/tiles_3d/venv_mac_py3/lib/python2.7/site-packages/pip/_vendor/distlib/locators.py
|
python
|
SimpleScrapingLocator.get_page
|
(self, url)
|
return result
|
Get the HTML for an URL, possibly from an in-memory cache.
XXX TODO Note: this cache is never actually cleared. It's assumed that
the data won't get stale over the lifetime of a locator instance (not
necessarily true for the default_locator).
|
Get the HTML for an URL, possibly from an in-memory cache.
|
[
"Get",
"the",
"HTML",
"for",
"an",
"URL",
"possibly",
"from",
"an",
"in",
"-",
"memory",
"cache",
"."
] |
def get_page(self, url):
"""
Get the HTML for an URL, possibly from an in-memory cache.
XXX TODO Note: this cache is never actually cleared. It's assumed that
the data won't get stale over the lifetime of a locator instance (not
necessarily true for the default_locator).
"""
# http://peak.telecommunity.com/DevCenter/EasyInstall#package-index-api
scheme, netloc, path, _, _, _ = urlparse(url)
if scheme == 'file' and os.path.isdir(url2pathname(path)):
url = urljoin(ensure_slash(url), 'index.html')
if url in self._page_cache:
result = self._page_cache[url]
logger.debug('Returning %s from cache: %s', url, result)
else:
host = netloc.split(':', 1)[0]
result = None
if host in self._bad_hosts:
logger.debug('Skipping %s due to bad host %s', url, host)
else:
req = Request(url, headers={'Accept-encoding': 'identity'})
try:
logger.debug('Fetching %s', url)
resp = self.opener.open(req, timeout=self.timeout)
logger.debug('Fetched %s', url)
headers = resp.info()
content_type = headers.get('Content-Type', '')
if HTML_CONTENT_TYPE.match(content_type):
final_url = resp.geturl()
data = resp.read()
encoding = headers.get('Content-Encoding')
if encoding:
decoder = self.decoders[encoding] # fail if not found
data = decoder(data)
encoding = 'utf-8'
m = CHARSET.search(content_type)
if m:
encoding = m.group(1)
try:
data = data.decode(encoding)
except UnicodeError: # pragma: no cover
data = data.decode('latin-1') # fallback
result = Page(data, final_url)
self._page_cache[final_url] = result
except HTTPError as e:
if e.code != 404:
logger.exception('Fetch failed: %s: %s', url, e)
except URLError as e: # pragma: no cover
logger.exception('Fetch failed: %s: %s', url, e)
with self._lock:
self._bad_hosts.add(host)
except Exception as e: # pragma: no cover
logger.exception('Fetch failed: %s: %s', url, e)
finally:
self._page_cache[url] = result # even if None (failure)
return result
|
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"'Fetch failed: %s: %s'",
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",",
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":",
"self",
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"_page_cache",
"[",
"url",
"]",
"=",
"result",
"# even if None (failure)",
"return",
"result"
] |
https://github.com/IJDykeman/wangTiles/blob/7c1ee2095ebdf7f72bce07d94c6484915d5cae8b/experimental_code/tiles_3d/venv_mac_py3/lib/python2.7/site-packages/pip/_vendor/distlib/locators.py#L752-L809
|
|
SheffieldML/GPy
|
bb1bc5088671f9316bc92a46d356734e34c2d5c0
|
GPy/util/mocap.py
|
python
|
vertex.__init__
|
(self, name, id, parents=[], children=[], meta = {})
|
[] |
def __init__(self, name, id, parents=[], children=[], meta = {}):
self.name = name
self.id = id
self.parents = parents
self.children = children
self.meta = meta
|
[
"def",
"__init__",
"(",
"self",
",",
"name",
",",
"id",
",",
"parents",
"=",
"[",
"]",
",",
"children",
"=",
"[",
"]",
",",
"meta",
"=",
"{",
"}",
")",
":",
"self",
".",
"name",
"=",
"name",
"self",
".",
"id",
"=",
"id",
"self",
".",
"parents",
"=",
"parents",
"self",
".",
"children",
"=",
"children",
"self",
".",
"meta",
"=",
"meta"
] |
https://github.com/SheffieldML/GPy/blob/bb1bc5088671f9316bc92a46d356734e34c2d5c0/GPy/util/mocap.py#L7-L12
|
||||
openhatch/oh-mainline
|
ce29352a034e1223141dcc2f317030bbc3359a51
|
vendor/packages/twill/twill/commands.py
|
python
|
find
|
(what, flags='')
|
>> find <regexp> [<flags>]
Succeed if the regular expression is on the page. Sets the local
variable __match__ to the matching text.
Flags is a string consisting of the following characters:
* i: ignorecase
* m: multiline
* s: dotall
For explanations of these, please see the Python re module
documentation.
|
>> find <regexp> [<flags>]
Succeed if the regular expression is on the page. Sets the local
variable __match__ to the matching text.
|
[
">>",
"find",
"<regexp",
">",
"[",
"<flags",
">",
"]",
"Succeed",
"if",
"the",
"regular",
"expression",
"is",
"on",
"the",
"page",
".",
"Sets",
"the",
"local",
"variable",
"__match__",
"to",
"the",
"matching",
"text",
"."
] |
def find(what, flags=''):
"""
>> find <regexp> [<flags>]
Succeed if the regular expression is on the page. Sets the local
variable __match__ to the matching text.
Flags is a string consisting of the following characters:
* i: ignorecase
* m: multiline
* s: dotall
For explanations of these, please see the Python re module
documentation.
"""
regexp = re.compile(what, _parseFindFlags(flags))
page = browser.get_html()
m = regexp.search(page)
if not m:
raise TwillAssertionError("no match to '%s'" % (what,))
if m.groups():
match_str = m.group(1)
else:
match_str = m.group(0)
_, local_dict = get_twill_glocals()
local_dict['__match__'] = match_str
|
[
"def",
"find",
"(",
"what",
",",
"flags",
"=",
"''",
")",
":",
"regexp",
"=",
"re",
".",
"compile",
"(",
"what",
",",
"_parseFindFlags",
"(",
"flags",
")",
")",
"page",
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"get_html",
"(",
")",
"m",
"=",
"regexp",
".",
"search",
"(",
"page",
")",
"if",
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"m",
":",
"raise",
"TwillAssertionError",
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"\"no match to '%s'\"",
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"0",
")",
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",",
"local_dict",
"=",
"get_twill_glocals",
"(",
")",
"local_dict",
"[",
"'__match__'",
"]",
"=",
"match_str"
] |
https://github.com/openhatch/oh-mainline/blob/ce29352a034e1223141dcc2f317030bbc3359a51/vendor/packages/twill/twill/commands.py#L218-L247
|
||
1040003585/WebScrapingWithPython
|
a770fa5b03894076c8c9539b1ffff34424ffc016
|
portia_examle/lib/python2.7/site-packages/pip/_vendor/requests/models.py
|
python
|
Response.iter_lines
|
(self, chunk_size=ITER_CHUNK_SIZE, decode_unicode=None, delimiter=None)
|
Iterates over the response data, one line at a time. When
stream=True is set on the request, this avoids reading the
content at once into memory for large responses.
.. note:: This method is not reentrant safe.
|
Iterates over the response data, one line at a time. When
stream=True is set on the request, this avoids reading the
content at once into memory for large responses.
|
[
"Iterates",
"over",
"the",
"response",
"data",
"one",
"line",
"at",
"a",
"time",
".",
"When",
"stream",
"=",
"True",
"is",
"set",
"on",
"the",
"request",
"this",
"avoids",
"reading",
"the",
"content",
"at",
"once",
"into",
"memory",
"for",
"large",
"responses",
"."
] |
def iter_lines(self, chunk_size=ITER_CHUNK_SIZE, decode_unicode=None, delimiter=None):
"""Iterates over the response data, one line at a time. When
stream=True is set on the request, this avoids reading the
content at once into memory for large responses.
.. note:: This method is not reentrant safe.
"""
pending = None
for chunk in self.iter_content(chunk_size=chunk_size, decode_unicode=decode_unicode):
if pending is not None:
chunk = pending + chunk
if delimiter:
lines = chunk.split(delimiter)
else:
lines = chunk.splitlines()
if lines and lines[-1] and chunk and lines[-1][-1] == chunk[-1]:
pending = lines.pop()
else:
pending = None
for line in lines:
yield line
if pending is not None:
yield pending
|
[
"def",
"iter_lines",
"(",
"self",
",",
"chunk_size",
"=",
"ITER_CHUNK_SIZE",
",",
"decode_unicode",
"=",
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"splitlines",
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"[",
"-",
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"-",
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"lines",
":",
"yield",
"line",
"if",
"pending",
"is",
"not",
"None",
":",
"yield",
"pending"
] |
https://github.com/1040003585/WebScrapingWithPython/blob/a770fa5b03894076c8c9539b1ffff34424ffc016/portia_examle/lib/python2.7/site-packages/pip/_vendor/requests/models.py#L710-L739
|
||
codelv/enaml-native
|
04c3a015bcd649f374c5ecd98fcddba5e4fbdbdc
|
src/enamlnative/ios/app.py
|
python
|
IPhoneApplication.load_plugin_factories
|
(self)
|
Add any plugin toolkit widgets to the ANDROID_FACTORIES
|
Add any plugin toolkit widgets to the ANDROID_FACTORIES
|
[
"Add",
"any",
"plugin",
"toolkit",
"widgets",
"to",
"the",
"ANDROID_FACTORIES"
] |
def load_plugin_factories(self):
""" Add any plugin toolkit widgets to the ANDROID_FACTORIES """
for plugin in self.get_plugins(group='enaml_native_ios_factories'):
get_factories = plugin.load()
PLUGIN_FACTORIES = get_factories()
factories.IOS_FACTORIES.update(PLUGIN_FACTORIES)
|
[
"def",
"load_plugin_factories",
"(",
"self",
")",
":",
"for",
"plugin",
"in",
"self",
".",
"get_plugins",
"(",
"group",
"=",
"'enaml_native_ios_factories'",
")",
":",
"get_factories",
"=",
"plugin",
".",
"load",
"(",
")",
"PLUGIN_FACTORIES",
"=",
"get_factories",
"(",
")",
"factories",
".",
"IOS_FACTORIES",
".",
"update",
"(",
"PLUGIN_FACTORIES",
")"
] |
https://github.com/codelv/enaml-native/blob/04c3a015bcd649f374c5ecd98fcddba5e4fbdbdc/src/enamlnative/ios/app.py#L172-L177
|
||
playframework/play1
|
0ecac3bc2421ae2dbec27a368bf671eda1c9cba5
|
python/Lib/warnings.py
|
python
|
_show_warning
|
(message, category, filename, lineno, file=None, line=None)
|
Hook to write a warning to a file; replace if you like.
|
Hook to write a warning to a file; replace if you like.
|
[
"Hook",
"to",
"write",
"a",
"warning",
"to",
"a",
"file",
";",
"replace",
"if",
"you",
"like",
"."
] |
def _show_warning(message, category, filename, lineno, file=None, line=None):
"""Hook to write a warning to a file; replace if you like."""
if file is None:
file = sys.stderr
if file is None:
# sys.stderr is None - warnings get lost
return
try:
file.write(formatwarning(message, category, filename, lineno, line))
except (IOError, UnicodeError):
pass # the file (probably stderr) is invalid - this warning gets lost.
|
[
"def",
"_show_warning",
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"category",
",",
"filename",
",",
"lineno",
",",
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"=",
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"(",
"IOError",
",",
"UnicodeError",
")",
":",
"pass",
"# the file (probably stderr) is invalid - this warning gets lost."
] |
https://github.com/playframework/play1/blob/0ecac3bc2421ae2dbec27a368bf671eda1c9cba5/python/Lib/warnings.py#L25-L35
|
||
fnl/segtok
|
ad7ff3b31b40787e8f3ca983db887684ab335fcf
|
count_continuations.py
|
python
|
abbreviation_pattern
|
(continuation)
|
return re.compile(pattern.format(continuation))
|
[] |
def abbreviation_pattern(continuation):
pattern = r'\.\s+{}\b'
return re.compile(pattern.format(continuation))
|
[
"def",
"abbreviation_pattern",
"(",
"continuation",
")",
":",
"pattern",
"=",
"r'\\.\\s+{}\\b'",
"return",
"re",
".",
"compile",
"(",
"pattern",
".",
"format",
"(",
"continuation",
")",
")"
] |
https://github.com/fnl/segtok/blob/ad7ff3b31b40787e8f3ca983db887684ab335fcf/count_continuations.py#L82-L84
|
|||
hsokooti/RegNet
|
28a8b6132677bb58e9fc811c0dd15d78913c7e86
|
functions/setting/setting_utils.py
|
python
|
dsmoothlist_by_deform_exp
|
(deform_exp, ag_mode)
|
return dsmoothlist_training, dsmoothlist_validation
|
Automatically extract the selected artificial generations for training and validation set:
'Resp': ['respiratory_motion', 'single_frequency', 'mixed_frequency', 'zero'],
'NoResp': ['single_frequency', 'mixed_frequency', 'zero'],
'SingleOnly': ['single_frequency'],
'MixedOnly': ['mixed_frequency'],
'SingleResp': ['single_frequency', 'respiratory_motion', 'zero'],
please note that for validation set we do not need to select all of them
:param deform_exp:
:param ag_mode: artificial generation mode: 'Resp', 'NoResp', 'SingleOnly', 'MixedOnly', 'SingleResp', 'Visualization'
:return:
|
Automatically extract the selected artificial generations for training and validation set:
'Resp': ['respiratory_motion', 'single_frequency', 'mixed_frequency', 'zero'],
'NoResp': ['single_frequency', 'mixed_frequency', 'zero'],
'SingleOnly': ['single_frequency'],
'MixedOnly': ['mixed_frequency'],
'SingleResp': ['single_frequency', 'respiratory_motion', 'zero'],
please note that for validation set we do not need to select all of them
:param deform_exp:
:param ag_mode: artificial generation mode: 'Resp', 'NoResp', 'SingleOnly', 'MixedOnly', 'SingleResp', 'Visualization'
:return:
|
[
"Automatically",
"extract",
"the",
"selected",
"artificial",
"generations",
"for",
"training",
"and",
"validation",
"set",
":",
"Resp",
":",
"[",
"respiratory_motion",
"single_frequency",
"mixed_frequency",
"zero",
"]",
"NoResp",
":",
"[",
"single_frequency",
"mixed_frequency",
"zero",
"]",
"SingleOnly",
":",
"[",
"single_frequency",
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"MixedOnly",
":",
"[",
"mixed_frequency",
"]",
"SingleResp",
":",
"[",
"single_frequency",
"respiratory_motion",
"zero",
"]",
"please",
"note",
"that",
"for",
"validation",
"set",
"we",
"do",
"not",
"need",
"to",
"select",
"all",
"of",
"them",
":",
"param",
"deform_exp",
":",
":",
"param",
"ag_mode",
":",
"artificial",
"generation",
"mode",
":",
"Resp",
"NoResp",
"SingleOnly",
"MixedOnly",
"SingleResp",
"Visualization",
":",
"return",
":"
] |
def dsmoothlist_by_deform_exp(deform_exp, ag_mode):
"""
Automatically extract the selected artificial generations for training and validation set:
'Resp': ['respiratory_motion', 'single_frequency', 'mixed_frequency', 'zero'],
'NoResp': ['single_frequency', 'mixed_frequency', 'zero'],
'SingleOnly': ['single_frequency'],
'MixedOnly': ['mixed_frequency'],
'SingleResp': ['single_frequency', 'respiratory_motion', 'zero'],
please note that for validation set we do not need to select all of them
:param deform_exp:
:param ag_mode: artificial generation mode: 'Resp', 'NoResp', 'SingleOnly', 'MixedOnly', 'SingleResp', 'Visualization'
:return:
"""
if ag_mode not in ['Resp', 'NoResp', 'SingleOnly', 'MixedOnly', 'SingleResp', 'Visualization']:
raise ValueError("exp_mode should be in ['Resp', 'NoResp', 'SingleOnly', 'MixedOnly', 'SingleResp', 'Visualization']")
dsmoothlist_training = []
dsmoothlist_validation = []
deform_exp_setting = load_deform_exp_setting(deform_exp)
all_deform_methods = deform_exp_setting['DeformMethods']
comp_dict = {'Resp': ['respiratory_motion', 'single_frequency', 'mixed_frequency', 'zero'],
'NoResp': ['single_frequency', 'mixed_frequency', 'zero'],
'SingleOnly': ['single_frequency'],
'MixedOnly': ['mixed_frequency'],
'SingleResp': ['single_frequency', 'respiratory_motion', 'zero'],
'Visualization': []
}
for i, deform_method in enumerate(all_deform_methods):
if deform_method in comp_dict[ag_mode]:
dsmoothlist_training.append(i)
if deform_exp in ['3D_max7_D14_K', '3D_max15_D14_K', '3D_max20_D14_K', '3D_max15_SingleFrequency_Visualization']:
if ag_mode == 'Resp':
dsmoothlist_validation = [0, 5, 10]
elif ag_mode == 'NoResp':
dsmoothlist_validation = [5, 8, 10]
elif ag_mode == 'SingleResp':
dsmoothlist_validation = [4, 8, 10]
elif ag_mode == 'SingleOnly':
dsmoothlist_validation = [5, 6, 8]
elif ag_mode == 'MixedOnly':
dsmoothlist_validation = [9, 10, 12]
else:
raise ValueError('dsmoothlist_validation not found for deform_exp='+deform_exp+', please add it manually')
return dsmoothlist_training, dsmoothlist_validation
|
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] |
https://github.com/hsokooti/RegNet/blob/28a8b6132677bb58e9fc811c0dd15d78913c7e86/functions/setting/setting_utils.py#L710-L754
|
|
hakril/PythonForWindows
|
61e027a678d5b87aa64fcf8a37a6661a86236589
|
windows/winproxy/apis/kernel32.py
|
python
|
lstrcmpA
|
(lpString1, lpString2)
|
return lstrcmpA.ctypes_function(lpString1, lpString2)
|
[] |
def lstrcmpA(lpString1, lpString2):
return lstrcmpA.ctypes_function(lpString1, lpString2)
|
[
"def",
"lstrcmpA",
"(",
"lpString1",
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")",
":",
"return",
"lstrcmpA",
".",
"ctypes_function",
"(",
"lpString1",
",",
"lpString2",
")"
] |
https://github.com/hakril/PythonForWindows/blob/61e027a678d5b87aa64fcf8a37a6661a86236589/windows/winproxy/apis/kernel32.py#L395-L396
|
|||
IronLanguages/main
|
a949455434b1fda8c783289e897e78a9a0caabb5
|
External.LCA_RESTRICTED/Languages/IronPython/27/Lib/distutils/ccompiler.py
|
python
|
CCompiler._fix_object_args
|
(self, objects, output_dir)
|
return (objects, output_dir)
|
Typecheck and fix up some arguments supplied to various methods.
Specifically: ensure that 'objects' is a list; if output_dir is
None, replace with self.output_dir. Return fixed versions of
'objects' and 'output_dir'.
|
Typecheck and fix up some arguments supplied to various methods.
Specifically: ensure that 'objects' is a list; if output_dir is
None, replace with self.output_dir. Return fixed versions of
'objects' and 'output_dir'.
|
[
"Typecheck",
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"output_dir",
".",
"Return",
"fixed",
"versions",
"of",
"objects",
"and",
"output_dir",
"."
] |
def _fix_object_args(self, objects, output_dir):
"""Typecheck and fix up some arguments supplied to various methods.
Specifically: ensure that 'objects' is a list; if output_dir is
None, replace with self.output_dir. Return fixed versions of
'objects' and 'output_dir'.
"""
if not isinstance(objects, (list, tuple)):
raise TypeError, \
"'objects' must be a list or tuple of strings"
objects = list (objects)
if output_dir is None:
output_dir = self.output_dir
elif not isinstance(output_dir, str):
raise TypeError, "'output_dir' must be a string or None"
return (objects, output_dir)
|
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https://github.com/IronLanguages/main/blob/a949455434b1fda8c783289e897e78a9a0caabb5/External.LCA_RESTRICTED/Languages/IronPython/27/Lib/distutils/ccompiler.py#L408-L424
|
|
skylander86/lambda-text-extractor
|
6da52d077a2fc571e38bfe29c33ae68f6443cd5a
|
lib-linux_x64/requests/utils.py
|
python
|
add_dict_to_cookiejar
|
(cj, cookie_dict)
|
return cookiejar_from_dict(cookie_dict, cj)
|
Returns a CookieJar from a key/value dictionary.
:param cj: CookieJar to insert cookies into.
:param cookie_dict: Dict of key/values to insert into CookieJar.
:rtype: CookieJar
|
Returns a CookieJar from a key/value dictionary.
|
[
"Returns",
"a",
"CookieJar",
"from",
"a",
"key",
"/",
"value",
"dictionary",
"."
] |
def add_dict_to_cookiejar(cj, cookie_dict):
"""Returns a CookieJar from a key/value dictionary.
:param cj: CookieJar to insert cookies into.
:param cookie_dict: Dict of key/values to insert into CookieJar.
:rtype: CookieJar
"""
return cookiejar_from_dict(cookie_dict, cj)
|
[
"def",
"add_dict_to_cookiejar",
"(",
"cj",
",",
"cookie_dict",
")",
":",
"return",
"cookiejar_from_dict",
"(",
"cookie_dict",
",",
"cj",
")"
] |
https://github.com/skylander86/lambda-text-extractor/blob/6da52d077a2fc571e38bfe29c33ae68f6443cd5a/lib-linux_x64/requests/utils.py#L379-L387
|
|
erevus-cn/pocscan
|
5fef32b1abe22a9f666ad3aacfd1f99d784cb72d
|
pocscan/plugins/pocsuite/packages/requests/packages/urllib3/packages/ordered_dict.py
|
python
|
OrderedDict.viewitems
|
(self)
|
return ItemsView(self)
|
od.viewitems() -> a set-like object providing a view on od's items
|
od.viewitems() -> a set-like object providing a view on od's items
|
[
"od",
".",
"viewitems",
"()",
"-",
">",
"a",
"set",
"-",
"like",
"object",
"providing",
"a",
"view",
"on",
"od",
"s",
"items"
] |
def viewitems(self):
"od.viewitems() -> a set-like object providing a view on od's items"
return ItemsView(self)
|
[
"def",
"viewitems",
"(",
"self",
")",
":",
"return",
"ItemsView",
"(",
"self",
")"
] |
https://github.com/erevus-cn/pocscan/blob/5fef32b1abe22a9f666ad3aacfd1f99d784cb72d/pocscan/plugins/pocsuite/packages/requests/packages/urllib3/packages/ordered_dict.py#L258-L260
|
|
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_flaskbb/Python-2.7.9/Tools/webchecker/webchecker.py
|
python
|
Checker.openpage
|
(self, url_pair)
|
[] |
def openpage(self, url_pair):
url, fragment = url_pair
try:
return self.urlopener.open(url)
except (OSError, IOError), msg:
msg = self.sanitize(msg)
self.note(0, "Error %s", msg)
if self.verbose > 0:
self.show(" HREF ", url, " from", self.todo[url_pair])
self.setbad(url_pair, msg)
return None
|
[
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"url_pair",
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":",
"url",
",",
"fragment",
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"(",
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",",
"msg",
")",
"return",
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] |
https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/Python-2.7.9/Tools/webchecker/webchecker.py#L540-L550
|
||||
blinktrade/bitex
|
a4896e7faef9c4aa0ca5325f18b77db67003764e
|
libs/ws4py/manager.py
|
python
|
WebSocketManager.stop
|
(self)
|
Mark the manager as terminated and
releases its resources.
|
Mark the manager as terminated and
releases its resources.
|
[
"Mark",
"the",
"manager",
"as",
"terminated",
"and",
"releases",
"its",
"resources",
"."
] |
def stop(self):
"""
Mark the manager as terminated and
releases its resources.
"""
self.running = False
with self.lock:
self.websockets.clear()
self.poller.release()
|
[
"def",
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"False",
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"websockets",
".",
"clear",
"(",
")",
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")"
] |
https://github.com/blinktrade/bitex/blob/a4896e7faef9c4aa0ca5325f18b77db67003764e/libs/ws4py/manager.py#L216-L224
|
||
Tautulli/Tautulli
|
2410eb33805aaac4bd1c5dad0f71e4f15afaf742
|
lib/cloudinary/cache/storage/key_value_storage.py
|
python
|
KeyValueStorage.clear
|
(self)
|
Clears all entries
:return: bool True on success or False on failure
|
Clears all entries
|
[
"Clears",
"all",
"entries"
] |
def clear(self):
"""
Clears all entries
:return: bool True on success or False on failure
"""
raise NotImplementedError
|
[
"def",
"clear",
"(",
"self",
")",
":",
"raise",
"NotImplementedError"
] |
https://github.com/Tautulli/Tautulli/blob/2410eb33805aaac4bd1c5dad0f71e4f15afaf742/lib/cloudinary/cache/storage/key_value_storage.py#L45-L51
|
||
openshift/openshift-tools
|
1188778e728a6e4781acf728123e5b356380fe6f
|
ansible/roles/lib_openshift_3.2/library/oadm_policy_user.py
|
python
|
OpenShiftCLI._process
|
(self, template_name, create=False, params=None, template_data=None)
|
return self.openshift_cmd(['-n', self.namespace, 'create', '-f', fname])
|
return all pods
|
return all pods
|
[
"return",
"all",
"pods"
] |
def _process(self, template_name, create=False, params=None, template_data=None):
'''return all pods '''
cmd = ['process', '-n', self.namespace]
if template_data:
cmd.extend(['-f', '-'])
else:
cmd.append(template_name)
if params:
param_str = ["%s=%s" % (key, value) for key, value in params.items()]
cmd.append('-v')
cmd.extend(param_str)
results = self.openshift_cmd(cmd, output=True, input_data=template_data)
if results['returncode'] != 0 or not create:
return results
fname = '/tmp/%s' % template_name
yed = Yedit(fname, results['results'])
yed.write()
atexit.register(Utils.cleanup, [fname])
return self.openshift_cmd(['-n', self.namespace, 'create', '-f', fname])
|
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"'create'",
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https://github.com/openshift/openshift-tools/blob/1188778e728a6e4781acf728123e5b356380fe6f/ansible/roles/lib_openshift_3.2/library/oadm_policy_user.py#L100-L123
|
|
TencentCloud/tencentcloud-sdk-python
|
3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2
|
tencentcloud/apigateway/v20180808/models.py
|
python
|
UpdateApiAppKeyRequest.__init__
|
(self)
|
r"""
:param ApiAppId: 应用唯一 ID。
:type ApiAppId: str
:param ApiAppKey: 应用的Key。
:type ApiAppKey: str
:param ApiAppSecret: 应用的Secret。
:type ApiAppSecret: str
|
r"""
:param ApiAppId: 应用唯一 ID。
:type ApiAppId: str
:param ApiAppKey: 应用的Key。
:type ApiAppKey: str
:param ApiAppSecret: 应用的Secret。
:type ApiAppSecret: str
|
[
"r",
":",
"param",
"ApiAppId",
":",
"应用唯一",
"ID。",
":",
"type",
"ApiAppId",
":",
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":",
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":",
"str",
":",
"param",
"ApiAppSecret",
":",
"应用的Secret。",
":",
"type",
"ApiAppSecret",
":",
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] |
def __init__(self):
r"""
:param ApiAppId: 应用唯一 ID。
:type ApiAppId: str
:param ApiAppKey: 应用的Key。
:type ApiAppKey: str
:param ApiAppSecret: 应用的Secret。
:type ApiAppSecret: str
"""
self.ApiAppId = None
self.ApiAppKey = None
self.ApiAppSecret = None
|
[
"def",
"__init__",
"(",
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":",
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".",
"ApiAppId",
"=",
"None",
"self",
".",
"ApiAppKey",
"=",
"None",
"self",
".",
"ApiAppSecret",
"=",
"None"
] |
https://github.com/TencentCloud/tencentcloud-sdk-python/blob/3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2/tencentcloud/apigateway/v20180808/models.py#L9094-L9105
|
||
plizonczyk/noiseprotocol
|
73375448c55af85df0230841af868b7f31942f0a
|
noise/state.py
|
python
|
SymmetricState.encrypt_and_hash
|
(self, plaintext: bytes)
|
return ciphertext
|
Sets ciphertext = EncryptWithAd(h, plaintext), calls MixHash(ciphertext), and returns ciphertext. Note that if
k is empty, the EncryptWithAd() call will set ciphertext equal to plaintext.
:param plaintext: bytes sequence
:return: ciphertext bytes sequence
|
Sets ciphertext = EncryptWithAd(h, plaintext), calls MixHash(ciphertext), and returns ciphertext. Note that if
k is empty, the EncryptWithAd() call will set ciphertext equal to plaintext.
|
[
"Sets",
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"EncryptWithAd",
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"MixHash",
"(",
"ciphertext",
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"the",
"EncryptWithAd",
"()",
"call",
"will",
"set",
"ciphertext",
"equal",
"to",
"plaintext",
"."
] |
def encrypt_and_hash(self, plaintext: bytes) -> bytes:
"""
Sets ciphertext = EncryptWithAd(h, plaintext), calls MixHash(ciphertext), and returns ciphertext. Note that if
k is empty, the EncryptWithAd() call will set ciphertext equal to plaintext.
:param plaintext: bytes sequence
:return: ciphertext bytes sequence
"""
ciphertext = self.cipher_state.encrypt_with_ad(self.h, plaintext)
self.mix_hash(ciphertext)
return ciphertext
|
[
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":",
"bytes",
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"->",
"bytes",
":",
"ciphertext",
"=",
"self",
".",
"cipher_state",
".",
"encrypt_with_ad",
"(",
"self",
".",
"h",
",",
"plaintext",
")",
"self",
".",
"mix_hash",
"(",
"ciphertext",
")",
"return",
"ciphertext"
] |
https://github.com/plizonczyk/noiseprotocol/blob/73375448c55af85df0230841af868b7f31942f0a/noise/state.py#L164-L174
|
|
aiidateam/aiida-core
|
c743a335480f8bb3a5e4ebd2463a31f9f3b9f9b2
|
aiida/backends/sqlalchemy/migrations/versions/375c2db70663_dblog_uuid_uniqueness_constraint.py
|
python
|
upgrade
|
()
|
Add unique key constraint to the UUID column.
|
Add unique key constraint to the UUID column.
|
[
"Add",
"unique",
"key",
"constraint",
"to",
"the",
"UUID",
"column",
"."
] |
def upgrade():
"""Add unique key constraint to the UUID column."""
op.create_unique_constraint('db_dblog_uuid_key', 'db_dblog', ['uuid'])
|
[
"def",
"upgrade",
"(",
")",
":",
"op",
".",
"create_unique_constraint",
"(",
"'db_dblog_uuid_key'",
",",
"'db_dblog'",
",",
"[",
"'uuid'",
"]",
")"
] |
https://github.com/aiidateam/aiida-core/blob/c743a335480f8bb3a5e4ebd2463a31f9f3b9f9b2/aiida/backends/sqlalchemy/migrations/versions/375c2db70663_dblog_uuid_uniqueness_constraint.py#L29-L31
|
||
b1naryth1ef/disco
|
7a2e86a2a3dc58e207d2c6e9a686a3296d652864
|
disco/types/message.py
|
python
|
Message.guild
|
(self)
|
return self.channel.guild
|
Returns
-------
`Guild`
The guild (if applicable) this message was created in.
|
Returns
-------
`Guild`
The guild (if applicable) this message was created in.
|
[
"Returns",
"-------",
"Guild",
"The",
"guild",
"(",
"if",
"applicable",
")",
"this",
"message",
"was",
"created",
"in",
"."
] |
def guild(self):
"""
Returns
-------
`Guild`
The guild (if applicable) this message was created in.
"""
return self.channel.guild
|
[
"def",
"guild",
"(",
"self",
")",
":",
"return",
"self",
".",
"channel",
".",
"guild"
] |
https://github.com/b1naryth1ef/disco/blob/7a2e86a2a3dc58e207d2c6e9a686a3296d652864/disco/types/message.py#L376-L383
|
|
openstack/heat
|
ea6633c35b04bb49c4a2858edc9df0a82d039478
|
heat/engine/resource.py
|
python
|
Resource.handle_delete
|
(self)
|
return None
|
Default implementation; should be overridden by resources.
|
Default implementation; should be overridden by resources.
|
[
"Default",
"implementation",
";",
"should",
"be",
"overridden",
"by",
"resources",
"."
] |
def handle_delete(self):
"""Default implementation; should be overridden by resources."""
if self.entity and self.resource_id is not None:
with self._default_client_plugin().ignore_not_found:
obj = getattr(self.client(), self.entity)
obj.delete(self.resource_id)
return self.resource_id
return None
|
[
"def",
"handle_delete",
"(",
"self",
")",
":",
"if",
"self",
".",
"entity",
"and",
"self",
".",
"resource_id",
"is",
"not",
"None",
":",
"with",
"self",
".",
"_default_client_plugin",
"(",
")",
".",
"ignore_not_found",
":",
"obj",
"=",
"getattr",
"(",
"self",
".",
"client",
"(",
")",
",",
"self",
".",
"entity",
")",
"obj",
".",
"delete",
"(",
"self",
".",
"resource_id",
")",
"return",
"self",
".",
"resource_id",
"return",
"None"
] |
https://github.com/openstack/heat/blob/ea6633c35b04bb49c4a2858edc9df0a82d039478/heat/engine/resource.py#L1965-L1972
|
|
zhl2008/awd-platform
|
0416b31abea29743387b10b3914581fbe8e7da5e
|
web_flaskbb/lib/python2.7/site-packages/six.py
|
python
|
MovedAttribute.__init__
|
(self, name, old_mod, new_mod, old_attr=None, new_attr=None)
|
[] |
def __init__(self, name, old_mod, new_mod, old_attr=None, new_attr=None):
super(MovedAttribute, self).__init__(name)
if PY3:
if new_mod is None:
new_mod = name
self.mod = new_mod
if new_attr is None:
if old_attr is None:
new_attr = name
else:
new_attr = old_attr
self.attr = new_attr
else:
self.mod = old_mod
if old_attr is None:
old_attr = name
self.attr = old_attr
|
[
"def",
"__init__",
"(",
"self",
",",
"name",
",",
"old_mod",
",",
"new_mod",
",",
"old_attr",
"=",
"None",
",",
"new_attr",
"=",
"None",
")",
":",
"super",
"(",
"MovedAttribute",
",",
"self",
")",
".",
"__init__",
"(",
"name",
")",
"if",
"PY3",
":",
"if",
"new_mod",
"is",
"None",
":",
"new_mod",
"=",
"name",
"self",
".",
"mod",
"=",
"new_mod",
"if",
"new_attr",
"is",
"None",
":",
"if",
"old_attr",
"is",
"None",
":",
"new_attr",
"=",
"name",
"else",
":",
"new_attr",
"=",
"old_attr",
"self",
".",
"attr",
"=",
"new_attr",
"else",
":",
"self",
".",
"mod",
"=",
"old_mod",
"if",
"old_attr",
"is",
"None",
":",
"old_attr",
"=",
"name",
"self",
".",
"attr",
"=",
"old_attr"
] |
https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/six.py#L141-L157
|
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