nwo stringlengths 5 106 | sha stringlengths 40 40 | path stringlengths 4 174 | language stringclasses 1
value | identifier stringlengths 1 140 | parameters stringlengths 0 87.7k | argument_list stringclasses 1
value | return_statement stringlengths 0 426k | docstring stringlengths 0 64.3k | docstring_summary stringlengths 0 26.3k | docstring_tokens list | function stringlengths 18 4.83M | function_tokens list | url stringlengths 83 304 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
graphcore/examples | 46d2b7687b829778369fc6328170a7b14761e5c6 | applications/tensorflow/detection/yolov3/core/utils.py | python | postprocess_boxes | (pred_bbox, org_img_shape, input_size, score_threshold) | return np.concatenate([coors, scores[:, np.newaxis], classes[:, np.newaxis]], axis=-1) | Turn predicted boxes to image relative coordinate and remove invalid parts
Args:
pred_bbox: tensor of predicted boxes
org_image_shape: original image shape (h,w)
input_size: network input size, one integer, network input is a square image
score_threshold: box score threshold, boxes below this threshold will be discarded | Turn predicted boxes to image relative coordinate and remove invalid parts
Args:
pred_bbox: tensor of predicted boxes
org_image_shape: original image shape (h,w)
input_size: network input size, one integer, network input is a square image
score_threshold: box score threshold, boxes below this threshold will be discarded | [
"Turn",
"predicted",
"boxes",
"to",
"image",
"relative",
"coordinate",
"and",
"remove",
"invalid",
"parts",
"Args",
":",
"pred_bbox",
":",
"tensor",
"of",
"predicted",
"boxes",
"org_image_shape",
":",
"original",
"image",
"shape",
"(",
"h",
"w",
")",
"input_si... | def postprocess_boxes(pred_bbox, org_img_shape, input_size, score_threshold):
"""Turn predicted boxes to image relative coordinate and remove invalid parts
Args:
pred_bbox: tensor of predicted boxes
org_image_shape: original image shape (h,w)
input_size: network input size, one integer, network input is a square image
score_threshold: box score threshold, boxes below this threshold will be discarded
"""
valid_scale = [0, np.inf]
pred_bbox = np.array(pred_bbox)
pred_xywh = pred_bbox[:, 0:4]
pred_conf = pred_bbox[:, 4]
pred_prob = pred_bbox[:, 5:]
# # (1) (x, y, w, h) --> (xmin, ymin, xmax, ymax)
pred_coor = np.concatenate([pred_xywh[:, :2] - pred_xywh[:, 2:] * 0.5,
pred_xywh[:, :2] + pred_xywh[:, 2:] * 0.5], axis=-1)
# # (2) (xmin, ymin, xmax, ymax) -> (xmin_org, ymin_org, xmax_org, ymax_org)
org_h, org_w = org_img_shape
resize_ratio = min(input_size / org_w, input_size / org_h)
dw = (input_size - resize_ratio * org_w) / 2
dh = (input_size - resize_ratio * org_h) / 2
pred_coor[:, 0::2] = 1.0 * (pred_coor[:, 0::2] - dw) / resize_ratio
pred_coor[:, 1::2] = 1.0 * (pred_coor[:, 1::2] - dh) / resize_ratio
# # (3) clip some boxes those are out of range
pred_coor = np.concatenate([np.maximum(pred_coor[:, :2], [0, 0]),
np.minimum(pred_coor[:, 2:], [org_w - 1, org_h - 1])], axis=-1)
invalid_mask = np.logical_or(
(pred_coor[:, 0] > pred_coor[:, 2]), (pred_coor[:, 1] > pred_coor[:, 3]))
pred_coor[invalid_mask] = 0
# # (4) discard some invalid boxes
bboxes_scale = np.sqrt(np.multiply.reduce(
pred_coor[:, 2:4] - pred_coor[:, 0:2], axis=-1))
scale_mask = np.logical_and(
(valid_scale[0] < bboxes_scale), (bboxes_scale < valid_scale[1]))
# # (5) discard some boxes with low scores
classes = np.argmax(pred_prob, axis=-1)
scores = pred_conf * pred_prob[np.arange(len(pred_coor)), classes]
score_mask = scores > score_threshold
mask = np.logical_and(scale_mask, score_mask)
coors, scores, classes = pred_coor[mask], scores[mask], classes[mask]
return np.concatenate([coors, scores[:, np.newaxis], classes[:, np.newaxis]], axis=-1) | [
"def",
"postprocess_boxes",
"(",
"pred_bbox",
",",
"org_img_shape",
",",
"input_size",
",",
"score_threshold",
")",
":",
"valid_scale",
"=",
"[",
"0",
",",
"np",
".",
"inf",
"]",
"pred_bbox",
"=",
"np",
".",
"array",
"(",
"pred_bbox",
")",
"pred_xywh",
"="... | https://github.com/graphcore/examples/blob/46d2b7687b829778369fc6328170a7b14761e5c6/applications/tensorflow/detection/yolov3/core/utils.py#L164-L213 | |
XX-net/XX-Net | a9898cfcf0084195fb7e69b6bc834e59aecdf14f | code/default/lib/noarch/hyper/packages/rfc3986/uri.py | python | URIReference.scheme_is_valid | (self, require=False) | return self._is_valid(self.scheme, SCHEME_MATCHER, require) | Determines if the scheme component is valid.
:param str require: Set to ``True`` to require the presence of this
component.
:returns: ``True`` if the scheme is valid. ``False`` otherwise.
:rtype: bool | Determines if the scheme component is valid. | [
"Determines",
"if",
"the",
"scheme",
"component",
"is",
"valid",
"."
] | def scheme_is_valid(self, require=False):
"""Determines if the scheme component is valid.
:param str require: Set to ``True`` to require the presence of this
component.
:returns: ``True`` if the scheme is valid. ``False`` otherwise.
:rtype: bool
"""
return self._is_valid(self.scheme, SCHEME_MATCHER, require) | [
"def",
"scheme_is_valid",
"(",
"self",
",",
"require",
"=",
"False",
")",
":",
"return",
"self",
".",
"_is_valid",
"(",
"self",
".",
"scheme",
",",
"SCHEME_MATCHER",
",",
"require",
")"
] | https://github.com/XX-net/XX-Net/blob/a9898cfcf0084195fb7e69b6bc834e59aecdf14f/code/default/lib/noarch/hyper/packages/rfc3986/uri.py#L212-L220 | |
nadineproject/nadine | c41c8ef7ffe18f1853029c97eecc329039b4af6c | doors/core.py | python | TestDoorController.test_connection | (self) | return True | [] | def test_connection(self):
return True | [
"def",
"test_connection",
"(",
"self",
")",
":",
"return",
"True"
] | https://github.com/nadineproject/nadine/blob/c41c8ef7ffe18f1853029c97eecc329039b4af6c/doors/core.py#L331-L332 | |||
21dotco/two1-python | 4e833300fd5a58363e3104ed4c097631e5d296d3 | two1/bitcoin/coinbase.py | python | CoinbaseTransactionBuilder.build | (self, enonce1, enonce2, bitshare=True) | return tx_type(Transaction.DEFAULT_TRANSACTION_VERSION,
[cb_input],
self.outputs,
self.lock_time) | Builds a coinbase txn and returns it. If bitshare == True,
padding is added to the coinbase input script to align the
length of the txn without the last output & locktime to a
512-bit boundary.
Args:
enonce1 (bytes): byte stream to place in the coinbase input script. Must be
enonce1_len bytes long.
enonce2 (bytes): byte stream to place in the coinbase input script. Must be
enonce2_len bytes long.
bitshare (bool): True if this will be used for a 21 Bitshare device, False
otherwise. | Builds a coinbase txn and returns it. If bitshare == True,
padding is added to the coinbase input script to align the
length of the txn without the last output & locktime to a
512-bit boundary. | [
"Builds",
"a",
"coinbase",
"txn",
"and",
"returns",
"it",
".",
"If",
"bitshare",
"==",
"True",
"padding",
"is",
"added",
"to",
"the",
"coinbase",
"input",
"script",
"to",
"align",
"the",
"length",
"of",
"the",
"txn",
"without",
"the",
"last",
"output",
"... | def build(self, enonce1, enonce2, bitshare=True):
""" Builds a coinbase txn and returns it. If bitshare == True,
padding is added to the coinbase input script to align the
length of the txn without the last output & locktime to a
512-bit boundary.
Args:
enonce1 (bytes): byte stream to place in the coinbase input script. Must be
enonce1_len bytes long.
enonce2 (bytes): byte stream to place in the coinbase input script. Must be
enonce2_len bytes long.
bitshare (bool): True if this will be used for a 21 Bitshare device, False
otherwise.
"""
if len(enonce1) != self.enonce1_len:
raise ValueError("len(enonce1) does not match enonce1_len")
if len(enonce2) != self.enonce2_len:
raise ValueError("len(enonce2) does not match enonce2_len")
padding = self.bitshare_padding if bitshare else None
cb_input = self.build_input(enonce1, enonce2, padding)
tx_type = BitshareCoinbaseTransaction if bitshare else Transaction
return tx_type(Transaction.DEFAULT_TRANSACTION_VERSION,
[cb_input],
self.outputs,
self.lock_time) | [
"def",
"build",
"(",
"self",
",",
"enonce1",
",",
"enonce2",
",",
"bitshare",
"=",
"True",
")",
":",
"if",
"len",
"(",
"enonce1",
")",
"!=",
"self",
".",
"enonce1_len",
":",
"raise",
"ValueError",
"(",
"\"len(enonce1) does not match enonce1_len\"",
")",
"if"... | https://github.com/21dotco/two1-python/blob/4e833300fd5a58363e3104ed4c097631e5d296d3/two1/bitcoin/coinbase.py#L151-L178 | |
open-cogsci/OpenSesame | c4a3641b097a80a76937edbd8c365f036bcc9705 | opensesame_extensions/help/help.py | python | help.populate_help_menu | (self) | desc:
Is collected when the sitemap is done loading, and populates the
menu. | desc:
Is collected when the sitemap is done loading, and populates the
menu. | [
"desc",
":",
"Is",
"collected",
"when",
"the",
"sitemap",
"is",
"done",
"loading",
"and",
"populates",
"the",
"menu",
"."
] | def populate_help_menu(self):
"""
desc:
Is collected when the sitemap is done loading, and populates the
menu.
"""
if self._get_sitemap_thread.sitemap is None:
return
try:
_dict = safe_yaml_load(self._get_sitemap_thread.sitemap)
except yaml.scanner.ScannerError:
# If the sitemap was loaded but was not a valid yaml string. This
# can happen for example when a captive portal returns something
# invalid
return
if not isinstance(_dict, dict):
return
self.menu.clear()
menu = self.build_menu(
self.menu,
cfg.online_help_base_url,
_(u'Online help'),
_dict,
sub_menu=cfg.online_help_psychopy
)
if menu is not None:
self.action_online_help = self.menu.addMenu(menu)
if cfg.online_help_psychopy:
menu = self.psychopy_help_menu()
if menu is not None:
self.action_psychopy_help = self.menu.addMenu(menu)
self.menu.addSeparator() | [
"def",
"populate_help_menu",
"(",
"self",
")",
":",
"if",
"self",
".",
"_get_sitemap_thread",
".",
"sitemap",
"is",
"None",
":",
"return",
"try",
":",
"_dict",
"=",
"safe_yaml_load",
"(",
"self",
".",
"_get_sitemap_thread",
".",
"sitemap",
")",
"except",
"ya... | https://github.com/open-cogsci/OpenSesame/blob/c4a3641b097a80a76937edbd8c365f036bcc9705/opensesame_extensions/help/help.py#L139-L172 | ||
adonno/Home-AssistantConfig | 8038c0143c6a990e409951202bb1bda149fcbaf7 | custom_components/hacs/hacsbase/__init__.py | python | Hacs.register_repository | (self, full_name, category, check=True) | Register a repository. | Register a repository. | [
"Register",
"a",
"repository",
"."
] | async def register_repository(self, full_name, category, check=True):
"""Register a repository."""
from ..repositories.repository import RERPOSITORY_CLASSES
if full_name in self.common.skip:
self.logger.debug(f"Skipping {full_name}")
return
if category not in RERPOSITORY_CLASSES:
self.logger.error(f"{category} is not a valid repository category.")
return False
repository = RERPOSITORY_CLASSES[category](full_name)
if check:
try:
await repository.registration()
if repository.validate.errors:
self.common.skip.append(repository.information.full_name)
if not self.system.status.startup:
self.logger.error(f"Validation for {full_name} failed.")
return repository.validate.errors
repository.logger.info("Registration complete")
except AIOGitHubException as exception:
self.logger.debug(self.github.ratelimits.remaining)
self.logger.debug(self.github.ratelimits.reset_utc)
self.common.skip.append(repository.information.full_name)
if not self.system.status.startup:
self.logger.error(
f"Validation for {full_name} failed with {exception}."
)
return
self.repositories.append(repository) | [
"async",
"def",
"register_repository",
"(",
"self",
",",
"full_name",
",",
"category",
",",
"check",
"=",
"True",
")",
":",
"from",
".",
".",
"repositories",
".",
"repository",
"import",
"RERPOSITORY_CLASSES",
"if",
"full_name",
"in",
"self",
".",
"common",
... | https://github.com/adonno/Home-AssistantConfig/blob/8038c0143c6a990e409951202bb1bda149fcbaf7/custom_components/hacs/hacsbase/__init__.py#L116-L147 | ||
PhoenixDL/rising | 6de193375dcaac35605163c35cec259c9a2116d1 | rising/utils/affine.py | python | matrix_to_homogeneous | (batch: torch.Tensor) | return torch.cat([batch, missing], dim=-2) | Transforms a given transformation matrix to a homogeneous
transformation matrix.
Args:
batch: the batch of matrices to convert [N, dim, dim]
Returns:
torch.Tensor: the converted batch of matrices | Transforms a given transformation matrix to a homogeneous
transformation matrix. | [
"Transforms",
"a",
"given",
"transformation",
"matrix",
"to",
"a",
"homogeneous",
"transformation",
"matrix",
"."
] | def matrix_to_homogeneous(batch: torch.Tensor) -> torch.Tensor:
"""
Transforms a given transformation matrix to a homogeneous
transformation matrix.
Args:
batch: the batch of matrices to convert [N, dim, dim]
Returns:
torch.Tensor: the converted batch of matrices
"""
if batch.size(-1) == batch.size(-2):
missing = batch.new_zeros(size=(*batch.shape[:-1], 1))
batch = torch.cat([batch, missing], dim=-1)
missing = torch.zeros(
(batch.size(0), *[1 for tmp in batch.shape[1:-1]], batch.size(-1)), device=batch.device, dtype=batch.dtype
)
missing[..., -1] = 1
return torch.cat([batch, missing], dim=-2) | [
"def",
"matrix_to_homogeneous",
"(",
"batch",
":",
"torch",
".",
"Tensor",
")",
"->",
"torch",
".",
"Tensor",
":",
"if",
"batch",
".",
"size",
"(",
"-",
"1",
")",
"==",
"batch",
".",
"size",
"(",
"-",
"2",
")",
":",
"missing",
"=",
"batch",
".",
... | https://github.com/PhoenixDL/rising/blob/6de193375dcaac35605163c35cec259c9a2116d1/rising/utils/affine.py#L23-L45 | |
gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/plugins/db/dbapi/dbapi.py | python | DBAPI._txn_commit | (self) | Lowlevel interface to the backend transaction.
Executes a db END; | Lowlevel interface to the backend transaction.
Executes a db END; | [
"Lowlevel",
"interface",
"to",
"the",
"backend",
"transaction",
".",
"Executes",
"a",
"db",
"END",
";"
] | def _txn_commit(self):
"""
Lowlevel interface to the backend transaction.
Executes a db END;
"""
if self.transaction == None:
_LOG.debug(" DBAPI %s transaction commit", hex(id(self)))
self.dbapi.commit() | [
"def",
"_txn_commit",
"(",
"self",
")",
":",
"if",
"self",
".",
"transaction",
"==",
"None",
":",
"_LOG",
".",
"debug",
"(",
"\" DBAPI %s transaction commit\"",
",",
"hex",
"(",
"id",
"(",
"self",
")",
")",
")",
"self",
".",
"dbapi",
".",
"commit",
... | https://github.com/gramps-project/gramps/blob/04d4651a43eb210192f40a9f8c2bad8ee8fa3753/gramps/plugins/db/dbapi/dbapi.py#L211-L218 | ||
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/geometry/hyperplane_arrangement/hyperplane.py | python | Hyperplane.dimension | (self) | return self.linear_part().dimension() | r"""
The dimension of the hyperplane.
OUTPUT:
An integer.
EXAMPLES::
sage: H.<x,y,z> = HyperplaneArrangements(QQ)
sage: h = x + y + z - 1
sage: h.dimension()
2 | r"""
The dimension of the hyperplane. | [
"r",
"The",
"dimension",
"of",
"the",
"hyperplane",
"."
] | def dimension(self):
r"""
The dimension of the hyperplane.
OUTPUT:
An integer.
EXAMPLES::
sage: H.<x,y,z> = HyperplaneArrangements(QQ)
sage: h = x + y + z - 1
sage: h.dimension()
2
"""
return self.linear_part().dimension() | [
"def",
"dimension",
"(",
"self",
")",
":",
"return",
"self",
".",
"linear_part",
"(",
")",
".",
"dimension",
"(",
")"
] | https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/geometry/hyperplane_arrangement/hyperplane.py#L422-L437 | |
edfungus/Crouton | ada98b3930192938a48909072b45cb84b945f875 | clients/esp8266_clients/venv/lib/python2.7/site-packages/setuptools/dist.py | python | Distribution.handle_display_options | (self, option_order) | If there were any non-global "display-only" options
(--help-commands or the metadata display options) on the command
line, display the requested info and return true; else return
false. | If there were any non-global "display-only" options
(--help-commands or the metadata display options) on the command
line, display the requested info and return true; else return
false. | [
"If",
"there",
"were",
"any",
"non",
"-",
"global",
"display",
"-",
"only",
"options",
"(",
"--",
"help",
"-",
"commands",
"or",
"the",
"metadata",
"display",
"options",
")",
"on",
"the",
"command",
"line",
"display",
"the",
"requested",
"info",
"and",
"... | def handle_display_options(self, option_order):
"""If there were any non-global "display-only" options
(--help-commands or the metadata display options) on the command
line, display the requested info and return true; else return
false.
"""
import sys
if PY2 or self.help_commands:
return _Distribution.handle_display_options(self, option_order)
# Stdout may be StringIO (e.g. in tests)
import io
if not isinstance(sys.stdout, io.TextIOWrapper):
return _Distribution.handle_display_options(self, option_order)
# Don't wrap stdout if utf-8 is already the encoding. Provides
# workaround for #334.
if sys.stdout.encoding.lower() in ('utf-8', 'utf8'):
return _Distribution.handle_display_options(self, option_order)
# Print metadata in UTF-8 no matter the platform
encoding = sys.stdout.encoding
errors = sys.stdout.errors
newline = sys.platform != 'win32' and '\n' or None
line_buffering = sys.stdout.line_buffering
sys.stdout = io.TextIOWrapper(
sys.stdout.detach(), 'utf-8', errors, newline, line_buffering)
try:
return _Distribution.handle_display_options(self, option_order)
finally:
sys.stdout = io.TextIOWrapper(
sys.stdout.detach(), encoding, errors, newline, line_buffering) | [
"def",
"handle_display_options",
"(",
"self",
",",
"option_order",
")",
":",
"import",
"sys",
"if",
"PY2",
"or",
"self",
".",
"help_commands",
":",
"return",
"_Distribution",
".",
"handle_display_options",
"(",
"self",
",",
"option_order",
")",
"# Stdout may be St... | https://github.com/edfungus/Crouton/blob/ada98b3930192938a48909072b45cb84b945f875/clients/esp8266_clients/venv/lib/python2.7/site-packages/setuptools/dist.py#L670-L703 | ||
apache/libcloud | 90971e17bfd7b6bb97b2489986472c531cc8e140 | libcloud/compute/drivers/kamatera.py | python | KamateraNodeDriver.ex_get_node | (
self,
id=None,
name=None,
state=NodeState.UNKNOWN,
public_ips=None,
private_ips=None,
size=None,
image=None,
created_at=None,
location=None,
dailybackup=None,
managed=None,
billingcycle=None,
generated_password=None,
create_command_id=None,
poweronaftercreate=None,
) | return Node(
id=id,
name=name,
state=state,
public_ips=public_ips,
private_ips=private_ips,
driver=self,
size=size,
image=image,
created_at=created_at,
extra=extra,
) | Get a Kamatera node object.
:param id: Node ID (optional)
:type id: ``str``
:param name: Node name (optional)
:type name: ``str``
:param state: Node state (optional)
:type state: :class:`libcloud.compute.types.NodeState`
:param public_ips: Node public IPS. (optional)
:type public_ips: ``list`` of :str:
:param private_ips: Node private IPS. (optional)
:type private_ips: ``list`` of :str:
:param size: node size. (optional)
:type size: :class:`.NodeSize`
:param image: Node OS Image. (optional)
:type image: :class:`.NodeImage`
:param created_at: Node creation time. (optional)
:type created_at: ``datetime.datetime``
:param location: Node datacenter. (optional)
:type location: :class:`.NodeLocation`
:param dailybackup: create daily backups for the node (optional)
:type dailybackup: ``bool``
:param managed: provide managed support for the node (optional)
:type managed: ``bool``
:param billingcycle: billing cycle (hourly / monthly) (optional)
:type billingcycle: ``str``
:param generated_password: server generated password (optional)
:type generated_password: ``str``
:param create_command_id: creation task command ID (optional)
:type create_command_id: ``int``
:param poweronaftercreate: power on the node after create (optional)
:type poweronaftercreate: ``bool``
:return: The node.
:rtype: :class:`.Node` | Get a Kamatera node object. | [
"Get",
"a",
"Kamatera",
"node",
"object",
"."
] | def ex_get_node(
self,
id=None,
name=None,
state=NodeState.UNKNOWN,
public_ips=None,
private_ips=None,
size=None,
image=None,
created_at=None,
location=None,
dailybackup=None,
managed=None,
billingcycle=None,
generated_password=None,
create_command_id=None,
poweronaftercreate=None,
):
"""
Get a Kamatera node object.
:param id: Node ID (optional)
:type id: ``str``
:param name: Node name (optional)
:type name: ``str``
:param state: Node state (optional)
:type state: :class:`libcloud.compute.types.NodeState`
:param public_ips: Node public IPS. (optional)
:type public_ips: ``list`` of :str:
:param private_ips: Node private IPS. (optional)
:type private_ips: ``list`` of :str:
:param size: node size. (optional)
:type size: :class:`.NodeSize`
:param image: Node OS Image. (optional)
:type image: :class:`.NodeImage`
:param created_at: Node creation time. (optional)
:type created_at: ``datetime.datetime``
:param location: Node datacenter. (optional)
:type location: :class:`.NodeLocation`
:param dailybackup: create daily backups for the node (optional)
:type dailybackup: ``bool``
:param managed: provide managed support for the node (optional)
:type managed: ``bool``
:param billingcycle: billing cycle (hourly / monthly) (optional)
:type billingcycle: ``str``
:param generated_password: server generated password (optional)
:type generated_password: ``str``
:param create_command_id: creation task command ID (optional)
:type create_command_id: ``int``
:param poweronaftercreate: power on the node after create (optional)
:type poweronaftercreate: ``bool``
:return: The node.
:rtype: :class:`.Node`
"""
extra = {}
if location:
extra["location"] = location
if dailybackup is not None:
extra["dailybackup"] = dailybackup
if managed is not None:
extra["managed"] = managed
if billingcycle is not None:
extra["billingcycle"] = billingcycle
if generated_password is not None:
extra["generated_password"] = generated_password
if create_command_id is not None:
extra["create_command_id"] = create_command_id
if poweronaftercreate is not None:
extra["poweronaftercreate"] = poweronaftercreate
return Node(
id=id,
name=name,
state=state,
public_ips=public_ips,
private_ips=private_ips,
driver=self,
size=size,
image=image,
created_at=created_at,
extra=extra,
) | [
"def",
"ex_get_node",
"(",
"self",
",",
"id",
"=",
"None",
",",
"name",
"=",
"None",
",",
"state",
"=",
"NodeState",
".",
"UNKNOWN",
",",
"public_ips",
"=",
"None",
",",
"private_ips",
"=",
"None",
",",
"size",
"=",
"None",
",",
"image",
"=",
"None",... | https://github.com/apache/libcloud/blob/90971e17bfd7b6bb97b2489986472c531cc8e140/libcloud/compute/drivers/kamatera.py#L576-L671 | |
voxelmorph/voxelmorph | 92641b4808aefd3762bb2680d2b2aa8a491298ac | voxelmorph/py/utils.py | python | vol_to_sdt | (X_label, sdt=True, sdt_vol_resize=1) | return X_dt | Computes the signed distance transform from a volume. | Computes the signed distance transform from a volume. | [
"Computes",
"the",
"signed",
"distance",
"transform",
"from",
"a",
"volume",
"."
] | def vol_to_sdt(X_label, sdt=True, sdt_vol_resize=1):
"""
Computes the signed distance transform from a volume.
"""
X_dt = signed_dist_trf(X_label)
if not (sdt_vol_resize == 1):
if not isinstance(sdt_vol_resize, (list, tuple)):
sdt_vol_resize = [sdt_vol_resize] * X_dt.ndim
if any([f != 1 for f in sdt_vol_resize]):
X_dt = scipy.ndimage.interpolation.zoom(X_dt, sdt_vol_resize, order=1, mode='reflect')
if not sdt:
X_dt = np.abs(X_dt)
return X_dt | [
"def",
"vol_to_sdt",
"(",
"X_label",
",",
"sdt",
"=",
"True",
",",
"sdt_vol_resize",
"=",
"1",
")",
":",
"X_dt",
"=",
"signed_dist_trf",
"(",
"X_label",
")",
"if",
"not",
"(",
"sdt_vol_resize",
"==",
"1",
")",
":",
"if",
"not",
"isinstance",
"(",
"sdt_... | https://github.com/voxelmorph/voxelmorph/blob/92641b4808aefd3762bb2680d2b2aa8a491298ac/voxelmorph/py/utils.py#L385-L401 | |
SanPen/GridCal | d3f4566d2d72c11c7e910c9d162538ef0e60df31 | src/GridCal/Gui/GridEditorWidget/transformer2w_graphics.py | python | TransformerGraphicItem.setEndPos | (self, endpos) | Set the starting position
@param endpos:
@return: | Set the starting position | [
"Set",
"the",
"starting",
"position"
] | def setEndPos(self, endpos):
"""
Set the starting position
@param endpos:
@return:
"""
self.pos2 = endpos
self.redraw() | [
"def",
"setEndPos",
"(",
"self",
",",
"endpos",
")",
":",
"self",
".",
"pos2",
"=",
"endpos",
"self",
".",
"redraw",
"(",
")"
] | https://github.com/SanPen/GridCal/blob/d3f4566d2d72c11c7e910c9d162538ef0e60df31/src/GridCal/Gui/GridEditorWidget/transformer2w_graphics.py#L701-L708 | ||
JulianEberius/SublimePythonIDE | d70e40abc0c9f347af3204c7b910e0d6bfd6e459 | server/lib/python2/rope/contrib/generate.py | python | create_generate | (kind, project, resource, offset) | return generate(project, resource, offset) | A factory for creating `Generate` objects
`kind` can be 'variable', 'function', 'class', 'module' or
'package'. | A factory for creating `Generate` objects | [
"A",
"factory",
"for",
"creating",
"Generate",
"objects"
] | def create_generate(kind, project, resource, offset):
"""A factory for creating `Generate` objects
`kind` can be 'variable', 'function', 'class', 'module' or
'package'.
"""
generate = eval('Generate' + kind.title())
return generate(project, resource, offset) | [
"def",
"create_generate",
"(",
"kind",
",",
"project",
",",
"resource",
",",
"offset",
")",
":",
"generate",
"=",
"eval",
"(",
"'Generate'",
"+",
"kind",
".",
"title",
"(",
")",
")",
"return",
"generate",
"(",
"project",
",",
"resource",
",",
"offset",
... | https://github.com/JulianEberius/SublimePythonIDE/blob/d70e40abc0c9f347af3204c7b910e0d6bfd6e459/server/lib/python2/rope/contrib/generate.py#L6-L14 | |
mesonbuild/meson | a22d0f9a0a787df70ce79b05d0c45de90a970048 | mesonbuild/build.py | python | Executable.get_import_filename | (self) | return self.import_filename | The name of the import library that will be outputted by the compiler
Returns None if there is no import library required for this platform | The name of the import library that will be outputted by the compiler | [
"The",
"name",
"of",
"the",
"import",
"library",
"that",
"will",
"be",
"outputted",
"by",
"the",
"compiler"
] | def get_import_filename(self) -> T.Optional[str]:
"""
The name of the import library that will be outputted by the compiler
Returns None if there is no import library required for this platform
"""
return self.import_filename | [
"def",
"get_import_filename",
"(",
"self",
")",
"->",
"T",
".",
"Optional",
"[",
"str",
"]",
":",
"return",
"self",
".",
"import_filename"
] | https://github.com/mesonbuild/meson/blob/a22d0f9a0a787df70ce79b05d0c45de90a970048/mesonbuild/build.py#L1854-L1860 | |
grow/grow | 97fc21730b6a674d5d33948d94968e79447ce433 | grow/documents/document_fields.py | python | DocumentFields.__getitem__ | (self, key) | return self._data[key] | [] | def __getitem__(self, key):
return self._data[key] | [
"def",
"__getitem__",
"(",
"self",
",",
"key",
")",
":",
"return",
"self",
".",
"_data",
"[",
"key",
"]"
] | https://github.com/grow/grow/blob/97fc21730b6a674d5d33948d94968e79447ce433/grow/documents/document_fields.py#L15-L16 | |||
googleads/google-ads-python | 2a1d6062221f6aad1992a6bcca0e7e4a93d2db86 | google/ads/googleads/v9/services/services/topic_constant_service/client.py | python | TopicConstantServiceClient.topic_constant_path | (topic_id: str,) | return "topicConstants/{topic_id}".format(topic_id=topic_id,) | Return a fully-qualified topic_constant string. | Return a fully-qualified topic_constant string. | [
"Return",
"a",
"fully",
"-",
"qualified",
"topic_constant",
"string",
"."
] | def topic_constant_path(topic_id: str,) -> str:
"""Return a fully-qualified topic_constant string."""
return "topicConstants/{topic_id}".format(topic_id=topic_id,) | [
"def",
"topic_constant_path",
"(",
"topic_id",
":",
"str",
",",
")",
"->",
"str",
":",
"return",
"\"topicConstants/{topic_id}\"",
".",
"format",
"(",
"topic_id",
"=",
"topic_id",
",",
")"
] | https://github.com/googleads/google-ads-python/blob/2a1d6062221f6aad1992a6bcca0e7e4a93d2db86/google/ads/googleads/v9/services/services/topic_constant_service/client.py#L175-L177 | |
frenetic-lang/pyretic | 30462692f3e9675158862755955b44f3a37ea21c | pyretic/core/netkat.py | python | netkat_backend.generate_classifier | (cls, pol, switch_cnt, multistage, print_json=False,
return_json=False, server_port=NETKAT_PORT) | Generate JSON or classifier output from compiling an input policy. | Generate JSON or classifier output from compiling an input policy. | [
"Generate",
"JSON",
"or",
"classifier",
"output",
"from",
"compiling",
"an",
"input",
"policy",
"."
] | def generate_classifier(cls, pol, switch_cnt, multistage, print_json=False,
return_json=False, server_port=NETKAT_PORT):
""" Generate JSON or classifier output from compiling an input policy. """
def use_explicit_switches(pol):
""" Ensure every switch in the network gets reflected in the policy
sent to netkat. This is because netkat generates a separate copy of
the policy per switch, and it is necessary for it to know that a switch
appears in the policy through the policy itself."""
from pyretic.core.language import match, identity
pred_policy = None
used_cnt = switch_cnt if switch_cnt else 0
for i in range(1, used_cnt + 1):
if pred_policy is None:
pred_policy = match(switch = i)
else:
pred_policy |= match(switch = i)
if pred_policy is None:
pred_policy = identity
return pred_policy >> pol
def curl_channel_compilation(pol):
""" Communicate with the netKAT compile server through curl. """
import subprocess
f = open('/tmp/in.json', 'w')
if print_json:
cls.log().error("The policy being compiled to netkat is:")
cls.log().error(str(pol))
f.write(compile_to_netkat(pol))
f.close()
try:
output = subprocess.check_output(['curl', '-X', 'POST',
'localhost:%d/compile' %
server_port, '--data-binary',
'@/tmp/in.json', '-D',
'/tmp/header.txt'])
f = open('/tmp/out.json', 'w')
f.write(output)
f.close()
except subprocess.CalledProcessError:
print "error in calling frenetic"
if print_json:
cls.log().error("This is the json output:")
cls.log().error(str(output))
f = open('/tmp/header.txt')
time = 0
for line in f.readlines():
if line.startswith('x-compile-time:'):
time = float(line[line.index(":") + 1:-1])
break
return (output, time)
def httplib_channel_compilation(pol):
json_input = compile_to_netkat(pol)
write_to_file(json_input, TEMP_INPUT)
if print_json:
cls.log().error("This is the JSON input:")
cls.log().error(str(json_input))
headers = {"Content-Type": "application/x-www-form-urlencoded",
"Accept": "*/*"}
ctime = '0'
try:
# TODO: make the connection persist across compilations
conn = httplib.HTTPConnection("localhost", server_port)
conn.request("POST", NETKAT_DOM, json_input, headers)
resp = conn.getresponse()
ctime = resp.getheader(NETKAT_TIME_HDR, "-1")
netkat_out = resp.read()
write_to_file(ctime, TEMP_HEADERS)
write_to_file(netkat_out, TEMP_OUTPUT)
if print_json:
cls.log().error("This is the JSON output:")
cls.log().error(netkat_out)
conn.close()
except Exception as e:
cls.log().error(("Compiling with the netkat compilation" +
" server failed. (%s, port %d") % (
str(e), server_port))
sys.exit(0)
return (netkat_out, ctime)
pol = use_explicit_switches(pol)
qdict = {str(id(b)) : b for b in get_buckets_list(pol)}
vlan_offset_nbits = vlan_preprocess(pol)
# return curl_channel_compilation(pol)
(cls_json, ctime) = httplib_channel_compilation(pol)
if not return_json:
classifier = json_to_classifier(cls_json, qdict, multistage, vlan_offset_nbits)
return (classifier, ctime)
else:
return (cls_json, ctime) | [
"def",
"generate_classifier",
"(",
"cls",
",",
"pol",
",",
"switch_cnt",
",",
"multistage",
",",
"print_json",
"=",
"False",
",",
"return_json",
"=",
"False",
",",
"server_port",
"=",
"NETKAT_PORT",
")",
":",
"def",
"use_explicit_switches",
"(",
"pol",
")",
... | https://github.com/frenetic-lang/pyretic/blob/30462692f3e9675158862755955b44f3a37ea21c/pyretic/core/netkat.py#L70-L163 | ||
Raytone-D/puppet | 6212d4306d520c60f5f168aec3b79ee56071ee6b | puppet/util.py | python | go_to_top | (h_root: int, timeout: float = 1.0, interval: float = 0.01) | 窗口置顶 | 窗口置顶 | [
"窗口置顶"
] | def go_to_top(h_root: int, timeout: float = 1.0, interval: float = 0.01):
"""窗口置顶"""
keyboard.send('alt') # ! enables calls to SwitchToThisWindow
if user32.SwitchToThisWindow(h_root, True) != 0:
stop = int(timeout/interval)
for _ in range(stop):
if user32.GetForegroundWindow() == h_root:
return True
time.sleep(0.5 if user32.IsIconic(h_root) else interval) | [
"def",
"go_to_top",
"(",
"h_root",
":",
"int",
",",
"timeout",
":",
"float",
"=",
"1.0",
",",
"interval",
":",
"float",
"=",
"0.01",
")",
":",
"keyboard",
".",
"send",
"(",
"'alt'",
")",
"# ! enables calls to SwitchToThisWindow",
"if",
"user32",
".",
"Swit... | https://github.com/Raytone-D/puppet/blob/6212d4306d520c60f5f168aec3b79ee56071ee6b/puppet/util.py#L250-L259 | ||
mysql/mysql-connector-python | c5460bcbb0dff8e4e48bf4af7a971c89bf486d85 | lib/mysqlx/statement.py | python | Statement.exec_counter | (self) | return self._exec_counter | int: The number of times this statement was executed. | int: The number of times this statement was executed. | [
"int",
":",
"The",
"number",
"of",
"times",
"this",
"statement",
"was",
"executed",
"."
] | def exec_counter(self):
"""int: The number of times this statement was executed."""
return self._exec_counter | [
"def",
"exec_counter",
"(",
"self",
")",
":",
"return",
"self",
".",
"_exec_counter"
] | https://github.com/mysql/mysql-connector-python/blob/c5460bcbb0dff8e4e48bf4af7a971c89bf486d85/lib/mysqlx/statement.py#L167-L169 | |
boto/boto | b2a6f08122b2f1b89888d2848e730893595cd001 | boto/sts/__init__.py | python | regions | () | return get_regions('sts', connection_cls=STSConnection) | Get all available regions for the STS service.
:rtype: list
:return: A list of :class:`boto.regioninfo.RegionInfo` instances | Get all available regions for the STS service. | [
"Get",
"all",
"available",
"regions",
"for",
"the",
"STS",
"service",
"."
] | def regions():
"""
Get all available regions for the STS service.
:rtype: list
:return: A list of :class:`boto.regioninfo.RegionInfo` instances
"""
return get_regions('sts', connection_cls=STSConnection) | [
"def",
"regions",
"(",
")",
":",
"return",
"get_regions",
"(",
"'sts'",
",",
"connection_cls",
"=",
"STSConnection",
")"
] | https://github.com/boto/boto/blob/b2a6f08122b2f1b89888d2848e730893595cd001/boto/sts/__init__.py#L28-L35 | |
heynemann/pyvows | 5b0e2a202603c1fc00d1fa0c6134c92c15b7e2b7 | pyvows/reporting/coverage.py | python | VowsCoverageReporter.format_class_coverage | (self, cover_character, klass, space1, progress, coverage, space2, lines, cover_threshold) | return ' {0} {klass}{space1}\t{progress}{coverage}{space2} {lines}'.format(
# TODO:
# * remove manual spacing, use .format() alignment
cover_character,
klass=klass,
space1=space1,
progress=dim('•' * progress),
coverage=coverage,
space2=space2,
lines=lines
) | Accepts coverage data for a class and returns a formatted string (intended for
humans). | Accepts coverage data for a class and returns a formatted string (intended for
humans). | [
"Accepts",
"coverage",
"data",
"for",
"a",
"class",
"and",
"returns",
"a",
"formatted",
"string",
"(",
"intended",
"for",
"humans",
")",
"."
] | def format_class_coverage(self, cover_character, klass, space1, progress, coverage, space2, lines, cover_threshold):
'''Accepts coverage data for a class and returns a formatted string (intended for
humans).
'''
# FIXME:
# Doesn't this *actually* print coverage for a module, and not a class?
# preprocess raw data...
klass = klass.lstrip('.')
klass = blue(klass)
MET_THRESHOLD = coverage >= cover_threshold
coverage = '{prefix}{coverage:.1%}'.format(
prefix=' ' if (coverage > 0.000) else '',
coverage=coverage
)
if MET_THRESHOLD:
coverage = bold(coverage)
coverage = white(coverage)
# ...then format
return ' {0} {klass}{space1}\t{progress}{coverage}{space2} {lines}'.format(
# TODO:
# * remove manual spacing, use .format() alignment
cover_character,
klass=klass,
space1=space1,
progress=dim('•' * progress),
coverage=coverage,
space2=space2,
lines=lines
) | [
"def",
"format_class_coverage",
"(",
"self",
",",
"cover_character",
",",
"klass",
",",
"space1",
",",
"progress",
",",
"coverage",
",",
"space2",
",",
"lines",
",",
"cover_threshold",
")",
":",
"# FIXME:",
"# Doesn't this *actually* print coverage for a module,... | https://github.com/heynemann/pyvows/blob/5b0e2a202603c1fc00d1fa0c6134c92c15b7e2b7/pyvows/reporting/coverage.py#L134-L168 | |
frappe/frappe | b64cab6867dfd860f10ccaf41a4ec04bc890b583 | frappe/client.py | python | insert_many | (docs=None) | return out | Insert multiple documents
:param docs: JSON or list of dict objects to be inserted in one request | Insert multiple documents | [
"Insert",
"multiple",
"documents"
] | def insert_many(docs=None):
'''Insert multiple documents
:param docs: JSON or list of dict objects to be inserted in one request'''
if isinstance(docs, str):
docs = json.loads(docs)
out = []
if len(docs) > 200:
frappe.throw(_('Only 200 inserts allowed in one request'))
for doc in docs:
if doc.get("parent") and doc.get("parenttype"):
# inserting a child record
parent = frappe.get_doc(doc.get("parenttype"), doc.get("parent"))
parent.append(doc.get("parentfield"), doc)
parent.save()
out.append(parent.name)
else:
doc = frappe.get_doc(doc).insert()
out.append(doc.name)
return out | [
"def",
"insert_many",
"(",
"docs",
"=",
"None",
")",
":",
"if",
"isinstance",
"(",
"docs",
",",
"str",
")",
":",
"docs",
"=",
"json",
".",
"loads",
"(",
"docs",
")",
"out",
"=",
"[",
"]",
"if",
"len",
"(",
"docs",
")",
">",
"200",
":",
"frappe"... | https://github.com/frappe/frappe/blob/b64cab6867dfd860f10ccaf41a4ec04bc890b583/frappe/client.py#L177-L200 | |
PaddlePaddle/PGL | e48545f2814523c777b8a9a9188bf5a7f00d6e52 | apps/Graph4KG/dataset/trigraph.py | python | TriGraph.ents | (self) | return np.arange(0, self._num_ents) | All entity ids from 0 to :code:`num_ents - 1` (np.ndarray). | All entity ids from 0 to :code:`num_ents - 1` (np.ndarray). | [
"All",
"entity",
"ids",
"from",
"0",
"to",
":",
"code",
":",
"num_ents",
"-",
"1",
"(",
"np",
".",
"ndarray",
")",
"."
] | def ents(self):
"""All entity ids from 0 to :code:`num_ents - 1` (np.ndarray).
"""
return np.arange(0, self._num_ents) | [
"def",
"ents",
"(",
"self",
")",
":",
"return",
"np",
".",
"arange",
"(",
"0",
",",
"self",
".",
"_num_ents",
")"
] | https://github.com/PaddlePaddle/PGL/blob/e48545f2814523c777b8a9a9188bf5a7f00d6e52/apps/Graph4KG/dataset/trigraph.py#L320-L323 | |
uqfoundation/mystic | 154e6302d1f2f94e8f13e88ecc5f24241cc28ac7 | mystic/math/discrete.py | python | product_measure.flatten | (self) | return params | convert a product measure to a single list of parameters
Args:
None
Returns:
a list of parameters
Notes:
Given ``product_measure.pts = (M, N, ...)``, then the returned list is
``params = [wx1, ..., wxM, x1, ..., xM, wy1, ..., wyN, y1, ..., yN, ...]``.
Thus, *params* will have ``M`` weights and ``M`` corresponding positions,
followed by ``N`` weights and ``N`` corresponding positions, with this
pattern followed for each new dimension of the desired product measure. | convert a product measure to a single list of parameters | [
"convert",
"a",
"product",
"measure",
"to",
"a",
"single",
"list",
"of",
"parameters"
] | def flatten(self):
"""convert a product measure to a single list of parameters
Args:
None
Returns:
a list of parameters
Notes:
Given ``product_measure.pts = (M, N, ...)``, then the returned list is
``params = [wx1, ..., wxM, x1, ..., xM, wy1, ..., wyN, y1, ..., yN, ...]``.
Thus, *params* will have ``M`` weights and ``M`` corresponding positions,
followed by ``N`` weights and ``N`` corresponding positions, with this
pattern followed for each new dimension of the desired product measure.
"""
params = flatten(self)
return params | [
"def",
"flatten",
"(",
"self",
")",
":",
"params",
"=",
"flatten",
"(",
"self",
")",
"return",
"params"
] | https://github.com/uqfoundation/mystic/blob/154e6302d1f2f94e8f13e88ecc5f24241cc28ac7/mystic/math/discrete.py#L944-L961 | |
DSE-MSU/DeepRobust | 2bcde200a5969dae32cddece66206a52c87c43e8 | deeprobust/graph/utils.py | python | tensor2onehot | (labels) | return onehot_mx.to(labels.device) | Convert label tensor to label onehot tensor.
Parameters
----------
labels : torch.LongTensor
node labels
Returns
-------
torch.LongTensor
onehot labels tensor | Convert label tensor to label onehot tensor. | [
"Convert",
"label",
"tensor",
"to",
"label",
"onehot",
"tensor",
"."
] | def tensor2onehot(labels):
"""Convert label tensor to label onehot tensor.
Parameters
----------
labels : torch.LongTensor
node labels
Returns
-------
torch.LongTensor
onehot labels tensor
"""
eye = torch.eye(labels.max() + 1)
onehot_mx = eye[labels]
return onehot_mx.to(labels.device) | [
"def",
"tensor2onehot",
"(",
"labels",
")",
":",
"eye",
"=",
"torch",
".",
"eye",
"(",
"labels",
".",
"max",
"(",
")",
"+",
"1",
")",
"onehot_mx",
"=",
"eye",
"[",
"labels",
"]",
"return",
"onehot_mx",
".",
"to",
"(",
"labels",
".",
"device",
")"
] | https://github.com/DSE-MSU/DeepRobust/blob/2bcde200a5969dae32cddece66206a52c87c43e8/deeprobust/graph/utils.py#L26-L43 | |
Dozed12/df-style-worldgen | 937455d54f4b02df9c4b10ae6418f4c932fd97bf | libtcodpy.py | python | console_put_char | (con, x, y, c, flag=BKGND_DEFAULT) | [] | def console_put_char(con, x, y, c, flag=BKGND_DEFAULT):
if type(c) == str or type(c) == bytes:
_lib.TCOD_console_put_char(con, x, y, ord(c), flag)
else:
_lib.TCOD_console_put_char(con, x, y, c, flag) | [
"def",
"console_put_char",
"(",
"con",
",",
"x",
",",
"y",
",",
"c",
",",
"flag",
"=",
"BKGND_DEFAULT",
")",
":",
"if",
"type",
"(",
"c",
")",
"==",
"str",
"or",
"type",
"(",
"c",
")",
"==",
"bytes",
":",
"_lib",
".",
"TCOD_console_put_char",
"(",
... | https://github.com/Dozed12/df-style-worldgen/blob/937455d54f4b02df9c4b10ae6418f4c932fd97bf/libtcodpy.py#L763-L767 | ||||
sethmlarson/virtualbox-python | 984a6e2cb0e8996f4df40f4444c1528849f1c70d | virtualbox/library.py | python | ISystemProperties.max_guest_vram | (self) | return ret | Get int value for 'maxGuestVRAM'
Maximum guest video memory in Megabytes. | Get int value for 'maxGuestVRAM'
Maximum guest video memory in Megabytes. | [
"Get",
"int",
"value",
"for",
"maxGuestVRAM",
"Maximum",
"guest",
"video",
"memory",
"in",
"Megabytes",
"."
] | def max_guest_vram(self):
"""Get int value for 'maxGuestVRAM'
Maximum guest video memory in Megabytes.
"""
ret = self._get_attr("maxGuestVRAM")
return ret | [
"def",
"max_guest_vram",
"(",
"self",
")",
":",
"ret",
"=",
"self",
".",
"_get_attr",
"(",
"\"maxGuestVRAM\"",
")",
"return",
"ret"
] | https://github.com/sethmlarson/virtualbox-python/blob/984a6e2cb0e8996f4df40f4444c1528849f1c70d/virtualbox/library.py#L20137-L20142 | |
akamai-threat-research/mqtt-pwn | 40368e531660339fca1562a6c609c35f7ae4f989 | mqtt_pwn/connection/brute_forcer.py | python | ConnectionResult.set_return_code | (self, return_code) | Sets the return code field | Sets the return code field | [
"Sets",
"the",
"return",
"code",
"field"
] | def set_return_code(self, return_code):
"""Sets the return code field"""
self._return_code = return_code | [
"def",
"set_return_code",
"(",
"self",
",",
"return_code",
")",
":",
"self",
".",
"_return_code",
"=",
"return_code"
] | https://github.com/akamai-threat-research/mqtt-pwn/blob/40368e531660339fca1562a6c609c35f7ae4f989/mqtt_pwn/connection/brute_forcer.py#L17-L19 | ||
hatRiot/zarp | 2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad | src/lib/scapy/layers/sctp.py | python | _SCTPChunkGuessPayload.default_payload_class | (self,p) | [] | def default_payload_class(self,p):
if len(p) < 4:
return conf.padding_layer
else:
t = ord(p[0])
return globals().get(sctpchunktypescls.get(t, "Raw"), conf.raw_layer) | [
"def",
"default_payload_class",
"(",
"self",
",",
"p",
")",
":",
"if",
"len",
"(",
"p",
")",
"<",
"4",
":",
"return",
"conf",
".",
"padding_layer",
"else",
":",
"t",
"=",
"ord",
"(",
"p",
"[",
"0",
"]",
")",
"return",
"globals",
"(",
")",
".",
... | https://github.com/hatRiot/zarp/blob/2e772350a01c2aeed3f4da9685cd0cc5d6b3ecad/src/lib/scapy/layers/sctp.py#L179-L184 | ||||
LinkedInAttic/naarad | 261e2c0760fd6a6b0ee59064180bd8e3674311fe | src/naarad/metrics/metric.py | python | Metric.calc_key_stats | (self, metric_store) | Calculate stats such as percentile and mean
:param dict metric_store: The metric store used to store all the parsed log data
:return: None | Calculate stats such as percentile and mean | [
"Calculate",
"stats",
"such",
"as",
"percentile",
"and",
"mean"
] | def calc_key_stats(self, metric_store):
"""
Calculate stats such as percentile and mean
:param dict metric_store: The metric store used to store all the parsed log data
:return: None
"""
stats_to_calculate = ['mean', 'std', 'min', 'max'] # TODO: get input from user
percentiles_to_calculate = range(0, 100, 1) # TODO: get input from user
for column, groups_store in metric_store.items():
for group, time_store in groups_store.items():
data = metric_store[column][group].values()
if self.groupby:
column_name = group + '.' + column
else:
column_name = column
if column.startswith('qps'):
self.calculated_stats[column_name], self.calculated_percentiles[column_name] = naarad.utils.calculate_stats(data, stats_to_calculate, percentiles_to_calculate)
else:
self.calculated_stats[column_name], self.calculated_percentiles[column_name] = naarad.utils.calculate_stats(list(heapq.merge(*data)), stats_to_calculate,
percentiles_to_calculate)
self.update_summary_stats(column_name) | [
"def",
"calc_key_stats",
"(",
"self",
",",
"metric_store",
")",
":",
"stats_to_calculate",
"=",
"[",
"'mean'",
",",
"'std'",
",",
"'min'",
",",
"'max'",
"]",
"# TODO: get input from user",
"percentiles_to_calculate",
"=",
"range",
"(",
"0",
",",
"100",
",",
"1... | https://github.com/LinkedInAttic/naarad/blob/261e2c0760fd6a6b0ee59064180bd8e3674311fe/src/naarad/metrics/metric.py#L322-L343 | ||
enthought/mayavi | 2103a273568b8f0bd62328801aafbd6252543ae8 | mayavi/sources/array_source.py | python | ArraySource.remove_attribute | (self, name, category='point') | Remove an attribute by its name and optional category (point and
cell). Returns the removed array. | Remove an attribute by its name and optional category (point and
cell). Returns the removed array. | [
"Remove",
"an",
"attribute",
"by",
"its",
"name",
"and",
"optional",
"category",
"(",
"point",
"and",
"cell",
")",
".",
"Returns",
"the",
"removed",
"array",
"."
] | def remove_attribute(self, name, category='point'):
"""Remove an attribute by its name and optional category (point and
cell). Returns the removed array.
"""
data = getattr(self.image_data, '%s_data' % category)
data.remove_array(name) | [
"def",
"remove_attribute",
"(",
"self",
",",
"name",
",",
"category",
"=",
"'point'",
")",
":",
"data",
"=",
"getattr",
"(",
"self",
".",
"image_data",
",",
"'%s_data'",
"%",
"category",
")",
"data",
".",
"remove_array",
"(",
"name",
")"
] | https://github.com/enthought/mayavi/blob/2103a273568b8f0bd62328801aafbd6252543ae8/mayavi/sources/array_source.py#L215-L220 | ||
home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/alexa/capabilities.py | python | AlexaPowerController.properties_proactively_reported | (self) | return True | Return True if properties asynchronously reported. | Return True if properties asynchronously reported. | [
"Return",
"True",
"if",
"properties",
"asynchronously",
"reported",
"."
] | def properties_proactively_reported(self):
"""Return True if properties asynchronously reported."""
return True | [
"def",
"properties_proactively_reported",
"(",
"self",
")",
":",
"return",
"True"
] | https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/alexa/capabilities.py#L380-L382 | |
GoogleCloudPlatform/professional-services | 0c707aa97437f3d154035ef8548109b7882f71da | examples/vertex_pipeline/components/component_base/src/preprocess.py | python | executor_main | () | Main executor. | Main executor. | [
"Main",
"executor",
"."
] | def executor_main():
"""Main executor."""
parser = argparse.ArgumentParser()
parser.add_argument('--executor_input', type=str)
parser.add_argument('--function_to_execute', type=str)
args, _ = parser.parse_known_args()
executor_input = json.loads(args.executor_input)
function_to_execute = globals()[args.function_to_execute]
executor.Executor(
executor_input=executor_input,
function_to_execute=function_to_execute).execute() | [
"def",
"executor_main",
"(",
")",
":",
"parser",
"=",
"argparse",
".",
"ArgumentParser",
"(",
")",
"parser",
".",
"add_argument",
"(",
"'--executor_input'",
",",
"type",
"=",
"str",
")",
"parser",
".",
"add_argument",
"(",
"'--function_to_execute'",
",",
"type... | https://github.com/GoogleCloudPlatform/professional-services/blob/0c707aa97437f3d154035ef8548109b7882f71da/examples/vertex_pipeline/components/component_base/src/preprocess.py#L95-L108 | ||
kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python-modules/twisted/twisted/internet/selectreactor.py | python | SelectReactor.addReader | (self, reader) | Add a FileDescriptor for notification of data available to read. | Add a FileDescriptor for notification of data available to read. | [
"Add",
"a",
"FileDescriptor",
"for",
"notification",
"of",
"data",
"available",
"to",
"read",
"."
] | def addReader(self, reader):
"""
Add a FileDescriptor for notification of data available to read.
"""
self._reads[reader] = 1 | [
"def",
"addReader",
"(",
"self",
",",
"reader",
")",
":",
"self",
".",
"_reads",
"[",
"reader",
"]",
"=",
"1"
] | https://github.com/kuri65536/python-for-android/blob/26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891/python-modules/twisted/twisted/internet/selectreactor.py#L158-L162 | ||
fuzzbunch/fuzzbunch | 4b60a6c7cf9f84cf389d3fcdb9281de84ffb5802 | fuzzbunch/plugin.py | python | Plugin.execute | (self, session, mode) | Execute the plugin | Execute the plugin | [
"Execute",
"the",
"plugin"
] | def execute(self, session, mode):
"""Execute the plugin"""
pass | [
"def",
"execute",
"(",
"self",
",",
"session",
",",
"mode",
")",
":",
"pass"
] | https://github.com/fuzzbunch/fuzzbunch/blob/4b60a6c7cf9f84cf389d3fcdb9281de84ffb5802/fuzzbunch/plugin.py#L308-L310 | ||
SebKuzminsky/pycam | 55e3129f518e470040e79bb00515b4bfcf36c172 | pycam/Plugins/ParallelProcessing.py | python | ParallelProcessing.setup | (self) | return True | [] | def setup(self):
if self.gui and self._gtk:
box = self.gui.get_object("MultiprocessingFrame")
box.unparent()
self.core.register_ui("preferences", "Parallel processing", box, 60)
# "process pool" window
self.process_pool_window = self.gui.get_object("ProcessPoolWindow")
self.process_pool_window.set_default_size(500, 400)
self._gtk_handlers = []
self._gtk_handlers.extend((
(self.process_pool_window, "delete-event", self.toggle_process_pool_window, False),
(self.process_pool_window, "destroy", self.toggle_process_pool_window, False)))
self._gtk_handlers.append((
self.gui.get_object("ProcessPoolWindowClose"), "clicked",
self.toggle_process_pool_window, False))
self.gui.get_object("ProcessPoolRefreshInterval").set_value(3)
self.process_pool_model = self.gui.get_object("ProcessPoolStatisticsModel")
# show/hide controls
self.enable_parallel_processes = self.gui.get_object("EnableParallelProcesses")
if pycam.Utils.threading.is_multiprocessing_available():
self.gui.get_object("ParallelProcessingDisabledLabel").hide()
if pycam.Utils.threading.is_server_mode_available():
self.gui.get_object("ServerModeDisabledLabel").hide()
else:
self.gui.get_object("ServerModeSettingsFrame").hide()
else:
self.gui.get_object("ParallelProcessSettingsBox").hide()
self.gui.get_object("EnableParallelProcesses").hide()
self._gtk_handlers.append((self.enable_parallel_processes,
"toggled", self.handle_parallel_processes_settings))
self.number_of_processes = self.gui.get_object("NumberOfProcesses")
self.number_of_processes.set_value(pycam.Utils.threading.get_number_of_processes())
self.server_port_local_obj = self.gui.get_object("ServerPortLocal")
self.server_port_remote_obj = self.gui.get_object("RemoteServerPort")
self.auth_key_obj = self.gui.get_object("ServerPassword")
self._gtk_handlers.extend((
(self.number_of_processes, "value-changed",
self.handle_parallel_processes_settings),
(self.gui.get_object("EnableServerMode"), "toggled",
self.initialize_multiprocessing),
(self.gui.get_object("ServerPasswordGenerate"), "clicked",
self.generate_random_server_password),
(self.gui.get_object("ServerPasswordShow"), "toggled",
self.update_parallel_processes_settings)))
cpu_cores = pycam.Utils.threading.get_number_of_cores()
if cpu_cores is None:
cpu_cores = "unknown"
self.gui.get_object("AvailableCores").set_label(str(cpu_cores))
toggle_button = self.gui.get_object("ToggleProcessPoolWindow")
self._gtk_handlers.append((toggle_button, "toggled", self.toggle_process_pool_window))
self.register_gtk_accelerator("processes", toggle_button, None,
"ToggleProcessPoolWindow")
self.core.register_ui("view_menu", "ToggleProcessPoolWindow", toggle_button, 40)
self.register_gtk_handlers(self._gtk_handlers)
self.enable_parallel_processes.set_active(
pycam.Utils.threading.is_multiprocessing_enabled())
self.update_parallel_processes_settings()
return True | [
"def",
"setup",
"(",
"self",
")",
":",
"if",
"self",
".",
"gui",
"and",
"self",
".",
"_gtk",
":",
"box",
"=",
"self",
".",
"gui",
".",
"get_object",
"(",
"\"MultiprocessingFrame\"",
")",
"box",
".",
"unparent",
"(",
")",
"self",
".",
"core",
".",
"... | https://github.com/SebKuzminsky/pycam/blob/55e3129f518e470040e79bb00515b4bfcf36c172/pycam/Plugins/ParallelProcessing.py#L35-L92 | |||
pyg-team/pytorch_geometric | b920e9a3a64e22c8356be55301c88444ff051cae | benchmark/citation/gat.py | python | Net.forward | (self, data) | return F.log_softmax(x, dim=1) | [] | def forward(self, data):
x, edge_index = data.x, data.edge_index
x = F.dropout(x, p=args.dropout, training=self.training)
x = F.elu(self.conv1(x, edge_index))
x = F.dropout(x, p=args.dropout, training=self.training)
x = self.conv2(x, edge_index)
return F.log_softmax(x, dim=1) | [
"def",
"forward",
"(",
"self",
",",
"data",
")",
":",
"x",
",",
"edge_index",
"=",
"data",
".",
"x",
",",
"data",
".",
"edge_index",
"x",
"=",
"F",
".",
"dropout",
"(",
"x",
",",
"p",
"=",
"args",
".",
"dropout",
",",
"training",
"=",
"self",
"... | https://github.com/pyg-team/pytorch_geometric/blob/b920e9a3a64e22c8356be55301c88444ff051cae/benchmark/citation/gat.py#L37-L43 | |||
tjweir/liftbook | e977a7face13ade1a4558e1909a6951d2f8928dd | elyxer.py | python | FormulaFactory.clearany | (self, pos) | return None | Cleary any ignored type. | Cleary any ignored type. | [
"Cleary",
"any",
"ignored",
"type",
"."
] | def clearany(self, pos):
"Cleary any ignored type."
for type in self.ignoredtypes:
if self.instance(type).detect(pos):
return self.parsetype(type, pos)
return None | [
"def",
"clearany",
"(",
"self",
",",
"pos",
")",
":",
"for",
"type",
"in",
"self",
".",
"ignoredtypes",
":",
"if",
"self",
".",
"instance",
"(",
"type",
")",
".",
"detect",
"(",
"pos",
")",
":",
"return",
"self",
".",
"parsetype",
"(",
"type",
",",... | https://github.com/tjweir/liftbook/blob/e977a7face13ade1a4558e1909a6951d2f8928dd/elyxer.py#L4389-L4394 | |
Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/Python3/configparser.py | python | RawConfigParser._unify_values | (self, section, vars) | return _ChainMap(vardict, sectiondict, self._defaults) | Create a sequence of lookups with 'vars' taking priority over
the 'section' which takes priority over the DEFAULTSECT. | Create a sequence of lookups with 'vars' taking priority over
the 'section' which takes priority over the DEFAULTSECT. | [
"Create",
"a",
"sequence",
"of",
"lookups",
"with",
"vars",
"taking",
"priority",
"over",
"the",
"section",
"which",
"takes",
"priority",
"over",
"the",
"DEFAULTSECT",
"."
] | def _unify_values(self, section, vars):
"""Create a sequence of lookups with 'vars' taking priority over
the 'section' which takes priority over the DEFAULTSECT.
"""
sectiondict = {}
try:
sectiondict = self._sections[section]
except KeyError:
if section != self.default_section:
raise NoSectionError(section)
# Update with the entry specific variables
vardict = {}
if vars:
for key, value in vars.items():
if value is not None:
value = str(value)
vardict[self.optionxform(key)] = value
return _ChainMap(vardict, sectiondict, self._defaults) | [
"def",
"_unify_values",
"(",
"self",
",",
"section",
",",
"vars",
")",
":",
"sectiondict",
"=",
"{",
"}",
"try",
":",
"sectiondict",
"=",
"self",
".",
"_sections",
"[",
"section",
"]",
"except",
"KeyError",
":",
"if",
"section",
"!=",
"self",
".",
"def... | https://github.com/Source-Python-Dev-Team/Source.Python/blob/d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb/addons/source-python/Python3/configparser.py#L1131-L1149 | |
openstack/tempest | fe0ac89a5a1c43fa908a76759cd99eea3b1f9853 | tempest/lib/common/rest_client.py | python | RestClient.put | (self, url, body, headers=None, extra_headers=False, chunked=False) | return self.request('PUT', url, extra_headers, headers, body, chunked) | Send a HTTP PUT request using keystone service catalog and auth
:param str url: the relative url to send the put request to
:param dict body: the request body
:param dict headers: The headers to use for the request
:param bool extra_headers: Boolean value than indicates if the headers
returned by the get_headers() method are to
be used but additional headers are needed in
the request pass them in as a dict.
:param bool chunked: sends the body with chunked encoding
:return: a tuple with the first entry containing the response headers
and the second the response body
:rtype: tuple | Send a HTTP PUT request using keystone service catalog and auth | [
"Send",
"a",
"HTTP",
"PUT",
"request",
"using",
"keystone",
"service",
"catalog",
"and",
"auth"
] | def put(self, url, body, headers=None, extra_headers=False, chunked=False):
"""Send a HTTP PUT request using keystone service catalog and auth
:param str url: the relative url to send the put request to
:param dict body: the request body
:param dict headers: The headers to use for the request
:param bool extra_headers: Boolean value than indicates if the headers
returned by the get_headers() method are to
be used but additional headers are needed in
the request pass them in as a dict.
:param bool chunked: sends the body with chunked encoding
:return: a tuple with the first entry containing the response headers
and the second the response body
:rtype: tuple
"""
return self.request('PUT', url, extra_headers, headers, body, chunked) | [
"def",
"put",
"(",
"self",
",",
"url",
",",
"body",
",",
"headers",
"=",
"None",
",",
"extra_headers",
"=",
"False",
",",
"chunked",
"=",
"False",
")",
":",
"return",
"self",
".",
"request",
"(",
"'PUT'",
",",
"url",
",",
"extra_headers",
",",
"heade... | https://github.com/openstack/tempest/blob/fe0ac89a5a1c43fa908a76759cd99eea3b1f9853/tempest/lib/common/rest_client.py#L348-L363 | |
InvestmentSystems/static-frame | 0b19d6969bf6c17fb0599871aca79eb3b52cf2ed | static_frame/core/bus.py | python | Bus.to_series | (self) | return Series(self.values,
index=self._index,
own_index=True,
name=self._name,
) | Return a :obj:`Series` with the :obj:`Frame` contained in this :obj:`Bus`. If the :obj:`Bus` is associated with a :obj:`Store`, all :obj:`Frame` will be loaded into memory and the returned :obj:`Bus` will no longer be associated with the :obj:`Store`. | Return a :obj:`Series` with the :obj:`Frame` contained in this :obj:`Bus`. If the :obj:`Bus` is associated with a :obj:`Store`, all :obj:`Frame` will be loaded into memory and the returned :obj:`Bus` will no longer be associated with the :obj:`Store`. | [
"Return",
"a",
":",
"obj",
":",
"Series",
"with",
"the",
":",
"obj",
":",
"Frame",
"contained",
"in",
"this",
":",
"obj",
":",
"Bus",
".",
"If",
"the",
":",
"obj",
":",
"Bus",
"is",
"associated",
"with",
"a",
":",
"obj",
":",
"Store",
"all",
":",... | def to_series(self) -> Series:
'''Return a :obj:`Series` with the :obj:`Frame` contained in this :obj:`Bus`. If the :obj:`Bus` is associated with a :obj:`Store`, all :obj:`Frame` will be loaded into memory and the returned :obj:`Bus` will no longer be associated with the :obj:`Store`.
'''
# values returns an immutable array and will fully realize from Store
return Series(self.values,
index=self._index,
own_index=True,
name=self._name,
) | [
"def",
"to_series",
"(",
"self",
")",
"->",
"Series",
":",
"# values returns an immutable array and will fully realize from Store",
"return",
"Series",
"(",
"self",
".",
"values",
",",
"index",
"=",
"self",
".",
"_index",
",",
"own_index",
"=",
"True",
",",
"name"... | https://github.com/InvestmentSystems/static-frame/blob/0b19d6969bf6c17fb0599871aca79eb3b52cf2ed/static_frame/core/bus.py#L1323-L1331 | |
pret/pokemon-reverse-engineering-tools | 5e0715f2579adcfeb683448c9a7826cfd3afa57d | pokemontools/map_editor.py | python | MapRenderer.__init__ | (self, config=config, **kwargs) | [] | def __init__(self, config=config, **kwargs):
self.config = config
self.__dict__.update(kwargs)
self.map = Map(**kwargs) | [
"def",
"__init__",
"(",
"self",
",",
"config",
"=",
"config",
",",
"*",
"*",
"kwargs",
")",
":",
"self",
".",
"config",
"=",
"config",
"self",
".",
"__dict__",
".",
"update",
"(",
"kwargs",
")",
"self",
".",
"map",
"=",
"Map",
"(",
"*",
"*",
"kwa... | https://github.com/pret/pokemon-reverse-engineering-tools/blob/5e0715f2579adcfeb683448c9a7826cfd3afa57d/pokemontools/map_editor.py#L398-L401 | ||||
rucio/rucio | 6d0d358e04f5431f0b9a98ae40f31af0ddff4833 | lib/rucio/db/sqla/migrate_repo/versions/2af3291ec4c_added_replicas_history_table.py | python | upgrade | () | Upgrade the database to this revision | Upgrade the database to this revision | [
"Upgrade",
"the",
"database",
"to",
"this",
"revision"
] | def upgrade():
'''
Upgrade the database to this revision
'''
if context.get_context().dialect.name in ['oracle', 'mysql', 'postgresql']:
create_table('replicas_history',
sa.Column('rse_id', GUID()),
sa.Column('scope', sa.String(25)),
sa.Column('name', sa.String(255)),
sa.Column('bytes', sa.BigInteger))
create_primary_key('REPLICAS_HIST_PK', 'replicas_history', ['rse_id', 'scope', 'name'])
create_foreign_key('REPLICAS_HIST_RSE_ID_FK', 'replicas_history', 'rses', ['rse_id'], ['id'])
create_check_constraint('REPLICAS_HIST_SIZE_NN', 'replicas_history', 'bytes IS NOT NULL') | [
"def",
"upgrade",
"(",
")",
":",
"if",
"context",
".",
"get_context",
"(",
")",
".",
"dialect",
".",
"name",
"in",
"[",
"'oracle'",
",",
"'mysql'",
",",
"'postgresql'",
"]",
":",
"create_table",
"(",
"'replicas_history'",
",",
"sa",
".",
"Column",
"(",
... | https://github.com/rucio/rucio/blob/6d0d358e04f5431f0b9a98ae40f31af0ddff4833/lib/rucio/db/sqla/migrate_repo/versions/2af3291ec4c_added_replicas_history_table.py#L35-L49 | ||
LGE-ARC-AdvancedAI/auptimizer | 50f6e3b4e0cb9146ca90fd74b9b24ca97ae22617 | src/aup/Proposer/hyperopt/mongoexp.py | python | MongoJobs.set_attachment | (self, doc, blob, name, collection=None) | Attach potentially large data string `blob` to `doc` by name `name`
blob must be a string
doc must have been saved in some collection (must have an _id), but not
necessarily the jobs collection.
name must be a string
Returns None | Attach potentially large data string `blob` to `doc` by name `name` | [
"Attach",
"potentially",
"large",
"data",
"string",
"blob",
"to",
"doc",
"by",
"name",
"name"
] | def set_attachment(self, doc, blob, name, collection=None):
"""Attach potentially large data string `blob` to `doc` by name `name`
blob must be a string
doc must have been saved in some collection (must have an _id), but not
necessarily the jobs collection.
name must be a string
Returns None
"""
# If there is already a file with the given name for this doc, then we will delete it
# after writing the new file
attachments = doc.get('_attachments', [])
name_matches = [a for a in attachments if a[0] == name]
# the filename is set to something so that fs.list() will display the file
new_file_id = self.gfs.put(blob, filename='%s_%s' % (doc['_id'], name))
logger.info('stored blob of %i bytes with id=%s and filename %s_%s' % (
len(blob), str(new_file_id), doc['_id'], name))
new_attachments = ([a for a in attachments if a[0] != name] +
[(name, new_file_id)])
try:
ii = 0
doc = self.update(doc, {'_attachments': new_attachments},
collection=collection)
# there is a database leak until we actually delete the files that
# are no longer pointed to by new_attachments
while ii < len(name_matches):
self.gfs.delete(name_matches[ii][1])
ii += 1
except:
while ii < len(name_matches):
logger.warning("Leak during set_attachment: old_file_id=%s" % (
name_matches[ii][1]))
ii += 1
raise
assert len([n for n in self.attachment_names(doc) if n == name]) == 1 | [
"def",
"set_attachment",
"(",
"self",
",",
"doc",
",",
"blob",
",",
"name",
",",
"collection",
"=",
"None",
")",
":",
"# If there is already a file with the given name for this doc, then we will delete it",
"# after writing the new file",
"attachments",
"=",
"doc",
".",
"... | https://github.com/LGE-ARC-AdvancedAI/auptimizer/blob/50f6e3b4e0cb9146ca90fd74b9b24ca97ae22617/src/aup/Proposer/hyperopt/mongoexp.py#L570-L611 | ||
exercism/python | f79d44ef6c9cf68d8c76cb94017a590f04391635 | exercises/practice/run-length-encoding/.meta/example.py | python | encode | (string) | return ''.join(single_helper(key, group) for key, group in groupby(string)) | [] | def encode(string):
def single_helper(key, group):
size = len(list(group))
return key if size == 1 else str(size) + key
return ''.join(single_helper(key, group) for key, group in groupby(string)) | [
"def",
"encode",
"(",
"string",
")",
":",
"def",
"single_helper",
"(",
"key",
",",
"group",
")",
":",
"size",
"=",
"len",
"(",
"list",
"(",
"group",
")",
")",
"return",
"key",
"if",
"size",
"==",
"1",
"else",
"str",
"(",
"size",
")",
"+",
"key",
... | https://github.com/exercism/python/blob/f79d44ef6c9cf68d8c76cb94017a590f04391635/exercises/practice/run-length-encoding/.meta/example.py#L9-L13 | |||
replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | cpython/Lib/plat-mac/lib-scriptpackages/StdSuites/AppleScript_Suite.py | python | AppleScript_Suite_Events.ends_with | (self, _object, _attributes={}, **_arguments) | ends with: Ends with
Required argument: an AE object reference
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: anything | ends with: Ends with
Required argument: an AE object reference
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: anything | [
"ends",
"with",
":",
"Ends",
"with",
"Required",
"argument",
":",
"an",
"AE",
"object",
"reference",
"Keyword",
"argument",
"_attributes",
":",
"AppleEvent",
"attribute",
"dictionary",
"Returns",
":",
"anything"
] | def ends_with(self, _object, _attributes={}, **_arguments):
"""ends with: Ends with
Required argument: an AE object reference
Keyword argument _attributes: AppleEvent attribute dictionary
Returns: anything
"""
_code = 'ascr'
_subcode = 'ends'
if _arguments: raise TypeError, 'No optional args expected'
_arguments['----'] = _object
_reply, _arguments, _attributes = self.send(_code, _subcode,
_arguments, _attributes)
if _arguments.get('errn', 0):
raise aetools.Error, aetools.decodeerror(_arguments)
# XXXX Optionally decode result
if _arguments.has_key('----'):
return _arguments['----'] | [
"def",
"ends_with",
"(",
"self",
",",
"_object",
",",
"_attributes",
"=",
"{",
"}",
",",
"*",
"*",
"_arguments",
")",
":",
"_code",
"=",
"'ascr'",
"_subcode",
"=",
"'ends'",
"if",
"_arguments",
":",
"raise",
"TypeError",
",",
"'No optional args expected'",
... | https://github.com/replit-archive/empythoned/blob/977ec10ced29a3541a4973dc2b59910805695752/cpython/Lib/plat-mac/lib-scriptpackages/StdSuites/AppleScript_Suite.py#L385-L404 | ||
danecjensen/subscribely | 4d6ac60358b5fe26f0c01be68f1ba063df3b1ea0 | src/flask/app.py | python | Flask.try_trigger_before_first_request_functions | (self) | Called before each request and will ensure that it triggers
the :attr:`before_first_request_funcs` and only exactly once per
application instance (which means process usually).
:internal: | Called before each request and will ensure that it triggers
the :attr:`before_first_request_funcs` and only exactly once per
application instance (which means process usually). | [
"Called",
"before",
"each",
"request",
"and",
"will",
"ensure",
"that",
"it",
"triggers",
"the",
":",
"attr",
":",
"before_first_request_funcs",
"and",
"only",
"exactly",
"once",
"per",
"application",
"instance",
"(",
"which",
"means",
"process",
"usually",
")",... | def try_trigger_before_first_request_functions(self):
"""Called before each request and will ensure that it triggers
the :attr:`before_first_request_funcs` and only exactly once per
application instance (which means process usually).
:internal:
"""
if self._got_first_request:
return
with self._before_request_lock:
if self._got_first_request:
return
self._got_first_request = True
for func in self.before_first_request_funcs:
func() | [
"def",
"try_trigger_before_first_request_functions",
"(",
"self",
")",
":",
"if",
"self",
".",
"_got_first_request",
":",
"return",
"with",
"self",
".",
"_before_request_lock",
":",
"if",
"self",
".",
"_got_first_request",
":",
"return",
"self",
".",
"_got_first_req... | https://github.com/danecjensen/subscribely/blob/4d6ac60358b5fe26f0c01be68f1ba063df3b1ea0/src/flask/app.py#L1270-L1284 | ||
cooelf/SemBERT | f849452f864b5dd47f94e2911cffc15e9f6a5a2a | run_classifier.py | python | QnliProcessor.get_train_examples | (self, data_dir) | return self._create_examples(
self._read_tsv(os.path.join(data_dir, "train.tsv_tag")), "train") | See base class. | See base class. | [
"See",
"base",
"class",
"."
] | def get_train_examples(self, data_dir):
"""See base class."""
return self._create_examples(
self._read_tsv(os.path.join(data_dir, "train.tsv_tag")), "train") | [
"def",
"get_train_examples",
"(",
"self",
",",
"data_dir",
")",
":",
"return",
"self",
".",
"_create_examples",
"(",
"self",
".",
"_read_tsv",
"(",
"os",
".",
"path",
".",
"join",
"(",
"data_dir",
",",
"\"train.tsv_tag\"",
")",
")",
",",
"\"train\"",
")"
] | https://github.com/cooelf/SemBERT/blob/f849452f864b5dd47f94e2911cffc15e9f6a5a2a/run_classifier.py#L321-L324 | |
Cadene/tensorflow-model-zoo.torch | 990b10ffc22d4c8eacb2a502f20415b4f70c74c2 | models/research/cognitive_mapping_and_planning/tfcode/tf_utils.py | python | add_value_to_summary | (metric_summary, tag, val, log=True, tag_str=None) | Adds a scalar summary to the summary object. Optionally also logs to
logging. | Adds a scalar summary to the summary object. Optionally also logs to
logging. | [
"Adds",
"a",
"scalar",
"summary",
"to",
"the",
"summary",
"object",
".",
"Optionally",
"also",
"logs",
"to",
"logging",
"."
] | def add_value_to_summary(metric_summary, tag, val, log=True, tag_str=None):
"""Adds a scalar summary to the summary object. Optionally also logs to
logging."""
new_value = metric_summary.value.add();
new_value.tag = tag
new_value.simple_value = val
if log:
if tag_str is None:
tag_str = tag + '%f'
logging.info(tag_str, val) | [
"def",
"add_value_to_summary",
"(",
"metric_summary",
",",
"tag",
",",
"val",
",",
"log",
"=",
"True",
",",
"tag_str",
"=",
"None",
")",
":",
"new_value",
"=",
"metric_summary",
".",
"value",
".",
"add",
"(",
")",
"new_value",
".",
"tag",
"=",
"tag",
"... | https://github.com/Cadene/tensorflow-model-zoo.torch/blob/990b10ffc22d4c8eacb2a502f20415b4f70c74c2/models/research/cognitive_mapping_and_planning/tfcode/tf_utils.py#L688-L697 | ||
pypa/flit | a4524758604107bde8c77b5816612edb76a604aa | flit_core/flit_core/vendor/tomli/_re.py | python | match_to_datetime | (match: "re.Match") | return datetime(year, month, day, hour, minute, sec, micros, tzinfo=tz) | Convert a `RE_DATETIME` match to `datetime.datetime` or `datetime.date`.
Raises ValueError if the match does not correspond to a valid date
or datetime. | Convert a `RE_DATETIME` match to `datetime.datetime` or `datetime.date`. | [
"Convert",
"a",
"RE_DATETIME",
"match",
"to",
"datetime",
".",
"datetime",
"or",
"datetime",
".",
"date",
"."
] | def match_to_datetime(match: "re.Match") -> Union[datetime, date]:
"""Convert a `RE_DATETIME` match to `datetime.datetime` or `datetime.date`.
Raises ValueError if the match does not correspond to a valid date
or datetime.
"""
(
year_str,
month_str,
day_str,
hour_str,
minute_str,
sec_str,
micros_str,
zulu_time,
offset_sign_str,
offset_hour_str,
offset_minute_str,
) = match.groups()
year, month, day = int(year_str), int(month_str), int(day_str)
if hour_str is None:
return date(year, month, day)
hour, minute, sec = int(hour_str), int(minute_str), int(sec_str)
micros = int(micros_str.ljust(6, "0")) if micros_str else 0
if offset_sign_str:
tz: Optional[tzinfo] = cached_tz(
offset_hour_str, offset_minute_str, offset_sign_str
)
elif zulu_time:
tz = timezone.utc
else: # local date-time
tz = None
return datetime(year, month, day, hour, minute, sec, micros, tzinfo=tz) | [
"def",
"match_to_datetime",
"(",
"match",
":",
"\"re.Match\"",
")",
"->",
"Union",
"[",
"datetime",
",",
"date",
"]",
":",
"(",
"year_str",
",",
"month_str",
",",
"day_str",
",",
"hour_str",
",",
"minute_str",
",",
"sec_str",
",",
"micros_str",
",",
"zulu_... | https://github.com/pypa/flit/blob/a4524758604107bde8c77b5816612edb76a604aa/flit_core/flit_core/vendor/tomli/_re.py#L46-L78 | |
fake-name/ChromeController | 6c70d855e33e06463516b263bf9e6f34c48e29e8 | ChromeController/Generator/Generated.py | python | ChromeRemoteDebugInterface.Database_disable | (self) | return subdom_funcs | Function path: Database.disable
Domain: Database
Method name: disable
No return value.
Description: Disables database tracking, prevents database events from being sent to the client. | Function path: Database.disable
Domain: Database
Method name: disable
No return value.
Description: Disables database tracking, prevents database events from being sent to the client. | [
"Function",
"path",
":",
"Database",
".",
"disable",
"Domain",
":",
"Database",
"Method",
"name",
":",
"disable",
"No",
"return",
"value",
".",
"Description",
":",
"Disables",
"database",
"tracking",
"prevents",
"database",
"events",
"from",
"being",
"sent",
"... | def Database_disable(self):
"""
Function path: Database.disable
Domain: Database
Method name: disable
No return value.
Description: Disables database tracking, prevents database events from being sent to the client.
"""
subdom_funcs = self.synchronous_command('Database.disable')
return subdom_funcs | [
"def",
"Database_disable",
"(",
"self",
")",
":",
"subdom_funcs",
"=",
"self",
".",
"synchronous_command",
"(",
"'Database.disable'",
")",
"return",
"subdom_funcs"
] | https://github.com/fake-name/ChromeController/blob/6c70d855e33e06463516b263bf9e6f34c48e29e8/ChromeController/Generator/Generated.py#L3333-L3344 | |
aliyun/aliyun-odps-python-sdk | 20b391c8d6eb1a689eedf950c2fc702be5f057c9 | odps/lib/six.py | python | _SixMetaPathImporter.get_code | (self, fullname) | return None | Return None
Required, if is_package is implemented | Return None | [
"Return",
"None"
] | def get_code(self, fullname):
"""Return None
Required, if is_package is implemented"""
self.__get_module(fullname) # eventually raises ImportError
return None | [
"def",
"get_code",
"(",
"self",
",",
"fullname",
")",
":",
"self",
".",
"__get_module",
"(",
"fullname",
")",
"# eventually raises ImportError",
"return",
"None"
] | https://github.com/aliyun/aliyun-odps-python-sdk/blob/20b391c8d6eb1a689eedf950c2fc702be5f057c9/odps/lib/six.py#L233-L238 | |
alshedivat/keras-gp | 742019c428948673920284215058a0c284491b80 | kgp/backend/gpml.py | python | GPML.get_dlik_dx | (self, which_set, verbose=0) | return dlik_dx | Get derivative of the log marginal likelihood w.r.t. the kernel. | Get derivative of the log marginal likelihood w.r.t. the kernel. | [
"Get",
"derivative",
"of",
"the",
"log",
"marginal",
"likelihood",
"w",
".",
"r",
".",
"t",
".",
"the",
"kernel",
"."
] | def get_dlik_dx(self, which_set, verbose=0):
"""Get derivative of the log marginal likelihood w.r.t. the kernel.
"""
assert which_set in {'tr', 'tst', 'val', 'tmp'}
X_name, y_name = 'X_' + which_set, 'y_' + which_set
self.config.update({'X': X_name, 'y': y_name})
self.eng.eval(_gp_dlik.format(**self.config), verbose=verbose)
dlik_dx = self.eng.pull('dlik_dx')
return dlik_dx | [
"def",
"get_dlik_dx",
"(",
"self",
",",
"which_set",
",",
"verbose",
"=",
"0",
")",
":",
"assert",
"which_set",
"in",
"{",
"'tr'",
",",
"'tst'",
",",
"'val'",
",",
"'tmp'",
"}",
"X_name",
",",
"y_name",
"=",
"'X_'",
"+",
"which_set",
",",
"'y_'",
"+"... | https://github.com/alshedivat/keras-gp/blob/742019c428948673920284215058a0c284491b80/kgp/backend/gpml.py#L207-L215 | |
openelections/openelections-core | 3c516d8c4cf1166b1868b738a248d48f3378c525 | openelex/us/wa/transform/__init__.py | python | CreateResultsTransform._parse_winner | (self, raw_result) | Converts raw winner value into boolean | Converts raw winner value into boolean | [
"Converts",
"raw",
"winner",
"value",
"into",
"boolean"
] | def _parse_winner(self, raw_result):
"""
Converts raw winner value into boolean
"""
if raw_result.winner == 'Y':
# Winner in post-2002 contest
return True
elif raw_result.winner == 1:
# Winner in 2002 contest
return True
else:
return False | [
"def",
"_parse_winner",
"(",
"self",
",",
"raw_result",
")",
":",
"if",
"raw_result",
".",
"winner",
"==",
"'Y'",
":",
"# Winner in post-2002 contest",
"return",
"True",
"elif",
"raw_result",
".",
"winner",
"==",
"1",
":",
"# Winner in 2002 contest",
"return",
"... | https://github.com/openelections/openelections-core/blob/3c516d8c4cf1166b1868b738a248d48f3378c525/openelex/us/wa/transform/__init__.py#L491-L502 | ||
williballenthin/INDXParse | 454d70645b2d01f75ac4346bc2410fbe047d090c | INDXParse.py | python | NTATTR_STANDARD_INDEX_HEADER.deleted_entries | (self) | A generator that yields INDX entries found in the slack space
associated with this header. | A generator that yields INDX entries found in the slack space
associated with this header. | [
"A",
"generator",
"that",
"yields",
"INDX",
"entries",
"found",
"in",
"the",
"slack",
"space",
"associated",
"with",
"this",
"header",
"."
] | def deleted_entries(self):
"""
A generator that yields INDX entries found in the slack space
associated with this header.
"""
off = self.offset() + self.entry_size()
# NTATTR_STANDARD_INDEX_ENTRY is at least 0x52 bytes
# long, so don't overrun
# but if we do, then we're done
try:
while off < self.offset() + self.entry_allocated_size() - 0x52:
try:
g_logger.debug("Trying to find slack entry at %x.", off)
e = NTATTR_DIRECTORY_INDEX_SLACK_ENTRY(self._buf,
off, self)
if e.is_valid():
g_logger.debug("Slack entry is valid.")
off = e.end_offset()
yield e
else:
g_logger.debug("Slack entry is invalid.")
raise ParseException("Not a deleted entry")
except ParseException:
g_logger.debug("Scanning one byte forward.")
off += 1
except struct.error:
g_logger.debug("Slack entry parsing overran buffer.")
pass | [
"def",
"deleted_entries",
"(",
"self",
")",
":",
"off",
"=",
"self",
".",
"offset",
"(",
")",
"+",
"self",
".",
"entry_size",
"(",
")",
"# NTATTR_STANDARD_INDEX_ENTRY is at least 0x52 bytes",
"# long, so don't overrun",
"# but if we do, then we're done",
"try",
":",
"... | https://github.com/williballenthin/INDXParse/blob/454d70645b2d01f75ac4346bc2410fbe047d090c/INDXParse.py#L403-L431 | ||
bowenbaker/metaqnn | a25847f635e9545455f83405453e740646038f7a | libs/input_modules/get_datasets.py | python | get_mnist | (save_dir=None, root_path=None) | return Xtr, Ytr, Xte, Yte | If root_path is None, we download the data set from internet.
Either save path or root path must not be None and not both.
Returns Xtr, Ytr, Xte, Yte as numpy arrays | If root_path is None, we download the data set from internet. | [
"If",
"root_path",
"is",
"None",
"we",
"download",
"the",
"data",
"set",
"from",
"internet",
"."
] | def get_mnist(save_dir=None, root_path=None):
''' If root_path is None, we download the data set from internet.
Either save path or root path must not be None and not both.
Returns Xtr, Ytr, Xte, Yte as numpy arrays
'''
assert((save_dir is not None and root_path is None) or (save_dir is None and root_path is not None))
mnist_files = ['train-images-idx3-ubyte', 'train-labels-idx1-ubyte',
't10k-images-idx3-ubyte','t10k-labels-idx1-ubyte']
out_mnist_files = []
if root_path is None:
print 'Downloading MNIST dataset...'
for fname in mnist_files:
out_file = os.path.join(save_dir, "%s" % fname)
tar_path = os.path.join(save_dir, "%s.gz" % fname)
out_mnist_files.append(out_file)
url = urllib.URLopener()
url.retrieve("http://yann.lecun.com/exdb/mnist/%s.gz" % fname, tar_path)
print 'Download Done, Extracting... [%s]' % tar_path
os.system('gunzip -f %s' % tar_path)
Xtr, Ytr = load_mnist(out_mnist_files[0], out_mnist_files[1])
print 'Xtrain shape', Xtr.shape
print 'Ytrain shape', Ytr.shape
# Testing data
Xte, Yte = load_mnist(out_mnist_files[2], out_mnist_files[3])
print 'Xtest shape', Xte.shape
print 'Ytest shape', Yte.shape
return Xtr, Ytr, Xte, Yte | [
"def",
"get_mnist",
"(",
"save_dir",
"=",
"None",
",",
"root_path",
"=",
"None",
")",
":",
"assert",
"(",
"(",
"save_dir",
"is",
"not",
"None",
"and",
"root_path",
"is",
"None",
")",
"or",
"(",
"save_dir",
"is",
"None",
"and",
"root_path",
"is",
"not",... | https://github.com/bowenbaker/metaqnn/blob/a25847f635e9545455f83405453e740646038f7a/libs/input_modules/get_datasets.py#L345-L379 | |
cisco-sas/kitty | cb0760989dcdfe079e43ac574d872d0b18953a32 | kitty/model/low_level/aliases.py | python | BitMaskNotSet | (field, comp_value) | return Compare(field, '&=0', comp_value) | Condition applies if the given bitmask is equal to 0 in the value of the field
:rtype: :class:`~kitty.model.low_level.condition.Compare` | Condition applies if the given bitmask is equal to 0 in the value of the field | [
"Condition",
"applies",
"if",
"the",
"given",
"bitmask",
"is",
"equal",
"to",
"0",
"in",
"the",
"value",
"of",
"the",
"field"
] | def BitMaskNotSet(field, comp_value):
'''
Condition applies if the given bitmask is equal to 0 in the value of the field
:rtype: :class:`~kitty.model.low_level.condition.Compare`
'''
return Compare(field, '&=0', comp_value) | [
"def",
"BitMaskNotSet",
"(",
"field",
",",
"comp_value",
")",
":",
"return",
"Compare",
"(",
"field",
",",
"'&=0'",
",",
"comp_value",
")"
] | https://github.com/cisco-sas/kitty/blob/cb0760989dcdfe079e43ac574d872d0b18953a32/kitty/model/low_level/aliases.py#L327-L333 | |
ambakick/Person-Detection-and-Tracking | f925394ac29b5cf321f1ce89a71b193381519a0b | utils/np_box_mask_list_ops.py | python | iou | (box_mask_list1, box_mask_list2) | return np_mask_ops.iou(box_mask_list1.get_masks(),
box_mask_list2.get_masks()) | Computes pairwise intersection-over-union between box and mask collections.
Args:
box_mask_list1: BoxMaskList holding N boxes and masks
box_mask_list2: BoxMaskList holding M boxes and masks
Returns:
a numpy array with shape [N, M] representing pairwise iou scores. | Computes pairwise intersection-over-union between box and mask collections. | [
"Computes",
"pairwise",
"intersection",
"-",
"over",
"-",
"union",
"between",
"box",
"and",
"mask",
"collections",
"."
] | def iou(box_mask_list1, box_mask_list2):
"""Computes pairwise intersection-over-union between box and mask collections.
Args:
box_mask_list1: BoxMaskList holding N boxes and masks
box_mask_list2: BoxMaskList holding M boxes and masks
Returns:
a numpy array with shape [N, M] representing pairwise iou scores.
"""
return np_mask_ops.iou(box_mask_list1.get_masks(),
box_mask_list2.get_masks()) | [
"def",
"iou",
"(",
"box_mask_list1",
",",
"box_mask_list2",
")",
":",
"return",
"np_mask_ops",
".",
"iou",
"(",
"box_mask_list1",
".",
"get_masks",
"(",
")",
",",
"box_mask_list2",
".",
"get_masks",
"(",
")",
")"
] | https://github.com/ambakick/Person-Detection-and-Tracking/blob/f925394ac29b5cf321f1ce89a71b193381519a0b/utils/np_box_mask_list_ops.py#L79-L90 | |
horazont/aioxmpp | c701e6399c90a6bb9bec0349018a03bd7b644cde | aioxmpp/security_layer.py | python | make | (
password_provider,
*,
pin_store=None,
pin_type=PinType.PUBLIC_KEY,
post_handshake_deferred_failure=None,
anonymous=False,
ssl_context_factory=default_ssl_context,
no_verify=False) | return SecurityLayer(
ssl_context_factory,
certificate_verifier_factory,
True,
tuple(sasl_providers),
) | Construct a :class:`SecurityLayer`. Depending on the arguments passed,
different features are enabled or disabled.
.. warning::
When using any argument except `password_provider`, be sure to read
its documentation below the following overview **carefully**. Many
arguments can be used to shoot yourself in the foot easily, while
violating all security expectations.
Args:
password_provider (:class:`str` or coroutine function):
Password source to authenticate with.
Keyword Args:
pin_store (:class:`dict` or :class:`AbstractPinStore`):
Enable use of certificate/public key pinning. `pin_type` controls
the type of store used when a dict is passed instead of a pin store
object.
pin_type (:class:`~aioxmpp.security_layer.PinType`):
Type of pin store to create when `pin_store` is a dict.
post_handshake_deferred_failure (coroutine function):
Coroutine callback to invoke when using certificate pinning and the
verification of the certificate was not possible using either PKIX
or the pin store.
anonymous (:class:`str`, :data:`None` or :data:`False`):
trace token for SASL ANONYMOUS (:rfc:`4505`); passing a
non-:data:`False` value enables ANONYMOUS authentication.
ssl_context_factory (function): Factory function to create the SSL
context used to establish transport layer security. Defaults to
:func:`aioxmpp.security_layer.default_ssl_context`.
no_verify (:class:`bool`): *Disable* all certificate verification.
Usage is **strongly discouraged** outside controlled test
environments. See below for alternatives.
Raises:
RuntimeError: if `anonymous` is not :data:`False` and the version of
:mod:`aiosasl` does not support ANONYMOUS authentication.
Returns:
:class:`SecurityLayer`: object holding the entire security layer
configuration
`password_provider` must either be a coroutine function or a :class:`str`.
As a coroutine function, it is called during authentication with the JID we
are trying to authenticate against as the first, and the sequence number of
the authentication attempt as second argument. The sequence number starts
at 0. The coroutine is expected to return :data:`None` or a password. See
:class:`PasswordSASLProvider` for details. If `password_provider` is a
:class:`str`, a coroutine which returns the string on the first and
:data:`None` on subsequent attempts is created and used.
If `pin_store` is not :data:`None`, :class:`PinningPKIXCertificateVerifier`
is used instead of the default :class:`PKIXCertificateVerifier`. The
`pin_store` argument determines the pinned certificates: if it is a
dictionary, a :class:`AbstractPinStore` according to the :class:`PinType`
passed as `pin_type` argument is created and initialised with the data from
the dictionary using its :meth:`~AbstractPinStore.import_from_json` method.
Otherwise, `pin_store` must be a :class:`AbstractPinStore` instance which
is passed to the verifier.
`post_handshake_deferred_callback` is used only if `pin_store` is not
:data:`None`. It is passed to the equally-named argument of
:class:`PinningPKIXCertificateVerifier`, see the documentation there for
details on the semantics. If `post_handshake_deferred_callback` is
:data:`None` while `pin_store` is not, a coroutine which returns
:data:`False` is substituted.
`ssl_context_factory` can be a callable taking no arguments and returning
a :class:`OpenSSL.SSL.Context` object. If given, the factory will be used
to obtain an SSL context when the stream negotiates transport layer
security via TLS. By default,
:func:`aioxmpp.security_layer.default_ssl_context` is used, which should be
fine for most applications.
.. warning::
The :func:`~.default_ssl_context` implementation sets important
defaults. It is **strongly recommended** to use the context returned
by :func:`~.default_ssl_context` and modify it, instead of creating
a new context from scratch when implementing your own factory.
If `no_verify` is true, none of the above regarding certificate verifiers
matters. The internal null verifier is used, which **disables certificate
verification completely**.
.. warning::
Disabling certificate verification makes your application vulnerable to
trivial Man-in-the-Middle attacks. Do **not** use this outside
controlled test environments or when you know **exactly** what you’re
doing!
If you need to handle certificates which cannot be verified using the
public key infrastructure, consider making use of the `pin_store`
argument instead.
`anonymous` may be a string or :data:`False`. If it is not :data:`False`,
:class:`AnonymousSASLProvider` is used before password based authentication
is attempted. In addition, it is allowed to set `password_provider` to
:data:`None`. `anonymous` is the trace token to use, and SHOULD be the
empty string (as specified by :xep:`175`). This requires :mod:`aiosasl` 0.3
or newer.
.. note::
:data:`False` and ``""`` are treated differently for the `anonymous`
argument, despite both being false-y values!
.. note::
If `anonymous` is not :data:`False` and `password_provider` is not
:data:`None`, both authentication types are attempted. Anonymous
authentication is, in that case, preferred over password-based
authentication.
If you need to reverse the order, you have to construct your own
:class:`SecurityLayer` object.
.. warning::
Take the security and privacy considerations from :rfc:`4505` (which
specifies the ANONYMOUS SASL mechanism) and :xep:`175` (which discusses
the ANONYMOUS SASL mechanism in the XMPP context) into account before
using `anonymous`.
The versatility and simplicity of use of this function make (pun intended)
it the preferred way to construct :class:`SecurityLayer` instances.
.. versionadded:: 0.8
Support for SASL ANONYMOUS was added.
.. versionadded:: 0.11
Support for `ssl_context_factory`. | Construct a :class:`SecurityLayer`. Depending on the arguments passed,
different features are enabled or disabled. | [
"Construct",
"a",
":",
"class",
":",
"SecurityLayer",
".",
"Depending",
"on",
"the",
"arguments",
"passed",
"different",
"features",
"are",
"enabled",
"or",
"disabled",
"."
] | def make(
password_provider,
*,
pin_store=None,
pin_type=PinType.PUBLIC_KEY,
post_handshake_deferred_failure=None,
anonymous=False,
ssl_context_factory=default_ssl_context,
no_verify=False):
"""
Construct a :class:`SecurityLayer`. Depending on the arguments passed,
different features are enabled or disabled.
.. warning::
When using any argument except `password_provider`, be sure to read
its documentation below the following overview **carefully**. Many
arguments can be used to shoot yourself in the foot easily, while
violating all security expectations.
Args:
password_provider (:class:`str` or coroutine function):
Password source to authenticate with.
Keyword Args:
pin_store (:class:`dict` or :class:`AbstractPinStore`):
Enable use of certificate/public key pinning. `pin_type` controls
the type of store used when a dict is passed instead of a pin store
object.
pin_type (:class:`~aioxmpp.security_layer.PinType`):
Type of pin store to create when `pin_store` is a dict.
post_handshake_deferred_failure (coroutine function):
Coroutine callback to invoke when using certificate pinning and the
verification of the certificate was not possible using either PKIX
or the pin store.
anonymous (:class:`str`, :data:`None` or :data:`False`):
trace token for SASL ANONYMOUS (:rfc:`4505`); passing a
non-:data:`False` value enables ANONYMOUS authentication.
ssl_context_factory (function): Factory function to create the SSL
context used to establish transport layer security. Defaults to
:func:`aioxmpp.security_layer.default_ssl_context`.
no_verify (:class:`bool`): *Disable* all certificate verification.
Usage is **strongly discouraged** outside controlled test
environments. See below for alternatives.
Raises:
RuntimeError: if `anonymous` is not :data:`False` and the version of
:mod:`aiosasl` does not support ANONYMOUS authentication.
Returns:
:class:`SecurityLayer`: object holding the entire security layer
configuration
`password_provider` must either be a coroutine function or a :class:`str`.
As a coroutine function, it is called during authentication with the JID we
are trying to authenticate against as the first, and the sequence number of
the authentication attempt as second argument. The sequence number starts
at 0. The coroutine is expected to return :data:`None` or a password. See
:class:`PasswordSASLProvider` for details. If `password_provider` is a
:class:`str`, a coroutine which returns the string on the first and
:data:`None` on subsequent attempts is created and used.
If `pin_store` is not :data:`None`, :class:`PinningPKIXCertificateVerifier`
is used instead of the default :class:`PKIXCertificateVerifier`. The
`pin_store` argument determines the pinned certificates: if it is a
dictionary, a :class:`AbstractPinStore` according to the :class:`PinType`
passed as `pin_type` argument is created and initialised with the data from
the dictionary using its :meth:`~AbstractPinStore.import_from_json` method.
Otherwise, `pin_store` must be a :class:`AbstractPinStore` instance which
is passed to the verifier.
`post_handshake_deferred_callback` is used only if `pin_store` is not
:data:`None`. It is passed to the equally-named argument of
:class:`PinningPKIXCertificateVerifier`, see the documentation there for
details on the semantics. If `post_handshake_deferred_callback` is
:data:`None` while `pin_store` is not, a coroutine which returns
:data:`False` is substituted.
`ssl_context_factory` can be a callable taking no arguments and returning
a :class:`OpenSSL.SSL.Context` object. If given, the factory will be used
to obtain an SSL context when the stream negotiates transport layer
security via TLS. By default,
:func:`aioxmpp.security_layer.default_ssl_context` is used, which should be
fine for most applications.
.. warning::
The :func:`~.default_ssl_context` implementation sets important
defaults. It is **strongly recommended** to use the context returned
by :func:`~.default_ssl_context` and modify it, instead of creating
a new context from scratch when implementing your own factory.
If `no_verify` is true, none of the above regarding certificate verifiers
matters. The internal null verifier is used, which **disables certificate
verification completely**.
.. warning::
Disabling certificate verification makes your application vulnerable to
trivial Man-in-the-Middle attacks. Do **not** use this outside
controlled test environments or when you know **exactly** what you’re
doing!
If you need to handle certificates which cannot be verified using the
public key infrastructure, consider making use of the `pin_store`
argument instead.
`anonymous` may be a string or :data:`False`. If it is not :data:`False`,
:class:`AnonymousSASLProvider` is used before password based authentication
is attempted. In addition, it is allowed to set `password_provider` to
:data:`None`. `anonymous` is the trace token to use, and SHOULD be the
empty string (as specified by :xep:`175`). This requires :mod:`aiosasl` 0.3
or newer.
.. note::
:data:`False` and ``""`` are treated differently for the `anonymous`
argument, despite both being false-y values!
.. note::
If `anonymous` is not :data:`False` and `password_provider` is not
:data:`None`, both authentication types are attempted. Anonymous
authentication is, in that case, preferred over password-based
authentication.
If you need to reverse the order, you have to construct your own
:class:`SecurityLayer` object.
.. warning::
Take the security and privacy considerations from :rfc:`4505` (which
specifies the ANONYMOUS SASL mechanism) and :xep:`175` (which discusses
the ANONYMOUS SASL mechanism in the XMPP context) into account before
using `anonymous`.
The versatility and simplicity of use of this function make (pun intended)
it the preferred way to construct :class:`SecurityLayer` instances.
.. versionadded:: 0.8
Support for SASL ANONYMOUS was added.
.. versionadded:: 0.11
Support for `ssl_context_factory`.
"""
if isinstance(password_provider, str):
static_password = password_provider
async def password_provider(jid, nattempt):
if nattempt == 0:
return static_password
return None
if pin_store is not None:
if post_handshake_deferred_failure is None:
async def post_handshake_deferred_failure(verifier):
return False
if not isinstance(pin_store, AbstractPinStore):
pin_data = pin_store
if pin_type == PinType.PUBLIC_KEY:
logger.debug("using PublicKeyPinStore")
pin_store = PublicKeyPinStore()
else:
logger.debug("using CertificatePinStore")
pin_store = CertificatePinStore()
pin_store.import_from_json(pin_data)
def certificate_verifier_factory():
return PinningPKIXCertificateVerifier(
pin_store.query,
post_handshake_deferred_failure,
)
elif no_verify:
certificate_verifier_factory = _NullVerifier
else:
certificate_verifier_factory = PKIXCertificateVerifier
sasl_providers = []
if anonymous is not False:
if AnonymousSASLProvider is None:
raise RuntimeError(
"aiosasl does not support ANONYMOUS, please upgrade"
)
sasl_providers.append(
AnonymousSASLProvider(anonymous)
)
if password_provider is not None:
sasl_providers.append(
PasswordSASLProvider(
password_provider,
),
)
return SecurityLayer(
ssl_context_factory,
certificate_verifier_factory,
True,
tuple(sasl_providers),
) | [
"def",
"make",
"(",
"password_provider",
",",
"*",
",",
"pin_store",
"=",
"None",
",",
"pin_type",
"=",
"PinType",
".",
"PUBLIC_KEY",
",",
"post_handshake_deferred_failure",
"=",
"None",
",",
"anonymous",
"=",
"False",
",",
"ssl_context_factory",
"=",
"default_s... | https://github.com/horazont/aioxmpp/blob/c701e6399c90a6bb9bec0349018a03bd7b644cde/aioxmpp/security_layer.py#L1292-L1497 | |
MozillaSecurity/grizzly | 1c41478e32f323189a2c322ec041c3e0902a158a | grizzly/replay/crash.py | python | modify_args | (args, crash, bucket) | return args | Arguments:
args (argparse.Namespace): Result from `ReplayArgs.parse_args`.
Returns:
args (argparse.Namespace): Modified arguments. | [] | def modify_args(args, crash, bucket):
"""
Arguments:
args (argparse.Namespace): Result from `ReplayArgs.parse_args`.
Returns:
args (argparse.Namespace): Modified arguments.
"""
args.original_crash_id = args.input
args.input = str(crash.testcase_path())
if args.tool is None:
LOG.info("Setting default --tool=%s from CrashEntry", crash.tool)
args.tool = crash.tool
# load signature if needed
if bucket is not None:
args.sig = str(bucket.signature_path())
return args | [
"def",
"modify_args",
"(",
"args",
",",
"crash",
",",
"bucket",
")",
":",
"args",
".",
"original_crash_id",
"=",
"args",
".",
"input",
"args",
".",
"input",
"=",
"str",
"(",
"crash",
".",
"testcase_path",
"(",
")",
")",
"if",
"args",
".",
"tool",
"is... | https://github.com/MozillaSecurity/grizzly/blob/1c41478e32f323189a2c322ec041c3e0902a158a/grizzly/replay/crash.py#L32-L53 | ||
mandarjoshi90/coref | bd04f2e19b9dcc0b8bba848a335e4af3be50741c | bert/modeling.py | python | reshape_to_matrix | (input_tensor) | return output_tensor | Reshapes a >= rank 2 tensor to a rank 2 tensor (i.e., a matrix). | Reshapes a >= rank 2 tensor to a rank 2 tensor (i.e., a matrix). | [
"Reshapes",
"a",
">",
"=",
"rank",
"2",
"tensor",
"to",
"a",
"rank",
"2",
"tensor",
"(",
"i",
".",
"e",
".",
"a",
"matrix",
")",
"."
] | def reshape_to_matrix(input_tensor):
"""Reshapes a >= rank 2 tensor to a rank 2 tensor (i.e., a matrix)."""
ndims = input_tensor.shape.ndims
if ndims < 2:
raise ValueError("Input tensor must have at least rank 2. Shape = %s" %
(input_tensor.shape))
if ndims == 2:
return input_tensor
width = input_tensor.shape[-1]
output_tensor = tf.reshape(input_tensor, [-1, width])
return output_tensor | [
"def",
"reshape_to_matrix",
"(",
"input_tensor",
")",
":",
"ndims",
"=",
"input_tensor",
".",
"shape",
".",
"ndims",
"if",
"ndims",
"<",
"2",
":",
"raise",
"ValueError",
"(",
"\"Input tensor must have at least rank 2. Shape = %s\"",
"%",
"(",
"input_tensor",
".",
... | https://github.com/mandarjoshi90/coref/blob/bd04f2e19b9dcc0b8bba848a335e4af3be50741c/bert/modeling.py#L937-L948 | |
replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | dist/lib/python2.7/imaplib.py | python | Time2Internaldate | (date_time) | return '"' + dt + " %+03d%02d" % divmod(zone//60, 60) + '"' | Convert date_time to IMAP4 INTERNALDATE representation.
Return string in form: '"DD-Mmm-YYYY HH:MM:SS +HHMM"'. The
date_time argument can be a number (int or float) representing
seconds since epoch (as returned by time.time()), a 9-tuple
representing local time (as returned by time.localtime()), or a
double-quoted string. In the last case, it is assumed to already
be in the correct format. | Convert date_time to IMAP4 INTERNALDATE representation. | [
"Convert",
"date_time",
"to",
"IMAP4",
"INTERNALDATE",
"representation",
"."
] | def Time2Internaldate(date_time):
"""Convert date_time to IMAP4 INTERNALDATE representation.
Return string in form: '"DD-Mmm-YYYY HH:MM:SS +HHMM"'. The
date_time argument can be a number (int or float) representing
seconds since epoch (as returned by time.time()), a 9-tuple
representing local time (as returned by time.localtime()), or a
double-quoted string. In the last case, it is assumed to already
be in the correct format.
"""
if isinstance(date_time, (int, float)):
tt = time.localtime(date_time)
elif isinstance(date_time, (tuple, time.struct_time)):
tt = date_time
elif isinstance(date_time, str) and (date_time[0],date_time[-1]) == ('"','"'):
return date_time # Assume in correct format
else:
raise ValueError("date_time not of a known type")
dt = time.strftime("%d-%b-%Y %H:%M:%S", tt)
if dt[0] == '0':
dt = ' ' + dt[1:]
if time.daylight and tt[-1]:
zone = -time.altzone
else:
zone = -time.timezone
return '"' + dt + " %+03d%02d" % divmod(zone//60, 60) + '"' | [
"def",
"Time2Internaldate",
"(",
"date_time",
")",
":",
"if",
"isinstance",
"(",
"date_time",
",",
"(",
"int",
",",
"float",
")",
")",
":",
"tt",
"=",
"time",
".",
"localtime",
"(",
"date_time",
")",
"elif",
"isinstance",
"(",
"date_time",
",",
"(",
"t... | https://github.com/replit-archive/empythoned/blob/977ec10ced29a3541a4973dc2b59910805695752/dist/lib/python2.7/imaplib.py#L1382-L1410 | |
tdamdouni/Pythonista | 3e082d53b6b9b501a3c8cf3251a8ad4c8be9c2ad | stash/autopep8.py | python | standard_deviation | (numbers) | return (sum((n - mean) ** 2 for n in numbers) /
len(numbers)) ** .5 | Return standard devation. | Return standard devation. | [
"Return",
"standard",
"devation",
"."
] | def standard_deviation(numbers):
"""Return standard devation."""
numbers = list(numbers)
if not numbers:
return 0
mean = sum(numbers) / len(numbers)
return (sum((n - mean) ** 2 for n in numbers) /
len(numbers)) ** .5 | [
"def",
"standard_deviation",
"(",
"numbers",
")",
":",
"numbers",
"=",
"list",
"(",
"numbers",
")",
"if",
"not",
"numbers",
":",
"return",
"0",
"mean",
"=",
"sum",
"(",
"numbers",
")",
"/",
"len",
"(",
"numbers",
")",
"return",
"(",
"sum",
"(",
"(",
... | https://github.com/tdamdouni/Pythonista/blob/3e082d53b6b9b501a3c8cf3251a8ad4c8be9c2ad/stash/autopep8.py#L3445-L3452 | |
google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/server/grr_response_server/gui/api_call_router_with_approval_checks.py | python | ApiCallRouterWithApprovalChecks.GetFleetspeakPendingMessageCount | (
self,
args: api_client.ApiGetFleetspeakPendingMessageCountArgs,
context: Optional[api_call_context.ApiCallContext] = None
) | return self.delegate.GetFleetspeakPendingMessageCount(args, context=context) | [] | def GetFleetspeakPendingMessageCount(
self,
args: api_client.ApiGetFleetspeakPendingMessageCountArgs,
context: Optional[api_call_context.ApiCallContext] = None
) -> api_client.ApiGetFleetspeakPendingMessageCountHandler:
self.access_checker.CheckClientAccess(context, args.client_id)
return self.delegate.GetFleetspeakPendingMessageCount(args, context=context) | [
"def",
"GetFleetspeakPendingMessageCount",
"(",
"self",
",",
"args",
":",
"api_client",
".",
"ApiGetFleetspeakPendingMessageCountArgs",
",",
"context",
":",
"Optional",
"[",
"api_call_context",
".",
"ApiCallContext",
"]",
"=",
"None",
")",
"->",
"api_client",
".",
"... | https://github.com/google/grr/blob/8ad8a4d2c5a93c92729206b7771af19d92d4f915/grr/server/grr_response_server/gui/api_call_router_with_approval_checks.py#L253-L259 | |||
awslabs/deeplearning-benchmark | 3e9a906422b402869537f91056ae771b66487a8e | word_language_model/lstm_bucketing.py | python | tokenize_text | (fname, vocab=None, invalid_label=-1, start_label=0) | return sentences, vocab | [] | def tokenize_text(fname, vocab=None, invalid_label=-1, start_label=0):
try:
assert os.path.exists(fname)
except AssertionError:
subprocess.call(['{}/get_ptb_data.sh'.format(os.path.dirname(__file__))])
assert os.path.exists(fname)
lines = open(fname).readlines()
lines = [filter(None, i.split(' ')) for i in lines]
sentences, vocab = mx.rnn.encode_sentences(lines, vocab=vocab, invalid_label=invalid_label,
start_label=start_label)
return sentences, vocab | [
"def",
"tokenize_text",
"(",
"fname",
",",
"vocab",
"=",
"None",
",",
"invalid_label",
"=",
"-",
"1",
",",
"start_label",
"=",
"0",
")",
":",
"try",
":",
"assert",
"os",
".",
"path",
".",
"exists",
"(",
"fname",
")",
"except",
"AssertionError",
":",
... | https://github.com/awslabs/deeplearning-benchmark/blob/3e9a906422b402869537f91056ae771b66487a8e/word_language_model/lstm_bucketing.py#L51-L61 | |||
scipy/scipy | e0a749f01e79046642ccfdc419edbf9e7ca141ad | scipy/_lib/_uarray/_backend.py | python | generate_multimethod | (
argument_extractor: ArgumentExtractorType,
argument_replacer: ArgumentReplacerType,
domain: str,
default: typing.Optional[typing.Callable] = None,
) | return functools.update_wrapper(ua_func, argument_extractor) | Generates a multimethod.
Parameters
----------
argument_extractor : ArgumentExtractorType
A callable which extracts the dispatchable arguments. Extracted arguments
should be marked by the :obj:`Dispatchable` class. It has the same signature
as the desired multimethod.
argument_replacer : ArgumentReplacerType
A callable with the signature (args, kwargs, dispatchables), which should also
return an (args, kwargs) pair with the dispatchables replaced inside the args/kwargs.
domain : str
A string value indicating the domain of this multimethod.
default : Optional[Callable], optional
The default implementation of this multimethod, where ``None`` (the default) specifies
there is no default implementation.
Examples
--------
In this example, ``a`` is to be dispatched over, so we return it, while marking it as an ``int``.
The trailing comma is needed because the args have to be returned as an iterable.
>>> def override_me(a, b):
... return Dispatchable(a, int),
Next, we define the argument replacer that replaces the dispatchables inside args/kwargs with the
supplied ones.
>>> def override_replacer(args, kwargs, dispatchables):
... return (dispatchables[0], args[1]), {}
Next, we define the multimethod.
>>> overridden_me = generate_multimethod(
... override_me, override_replacer, "ua_examples"
... )
Notice that there's no default implementation, unless you supply one.
>>> overridden_me(1, "a")
Traceback (most recent call last):
...
uarray.BackendNotImplementedError: ...
>>> overridden_me2 = generate_multimethod(
... override_me, override_replacer, "ua_examples", default=lambda x, y: (x, y)
... )
>>> overridden_me2(1, "a")
(1, 'a')
See Also
--------
uarray :
See the module documentation for how to override the method by creating backends. | Generates a multimethod. | [
"Generates",
"a",
"multimethod",
"."
] | def generate_multimethod(
argument_extractor: ArgumentExtractorType,
argument_replacer: ArgumentReplacerType,
domain: str,
default: typing.Optional[typing.Callable] = None,
):
"""
Generates a multimethod.
Parameters
----------
argument_extractor : ArgumentExtractorType
A callable which extracts the dispatchable arguments. Extracted arguments
should be marked by the :obj:`Dispatchable` class. It has the same signature
as the desired multimethod.
argument_replacer : ArgumentReplacerType
A callable with the signature (args, kwargs, dispatchables), which should also
return an (args, kwargs) pair with the dispatchables replaced inside the args/kwargs.
domain : str
A string value indicating the domain of this multimethod.
default : Optional[Callable], optional
The default implementation of this multimethod, where ``None`` (the default) specifies
there is no default implementation.
Examples
--------
In this example, ``a`` is to be dispatched over, so we return it, while marking it as an ``int``.
The trailing comma is needed because the args have to be returned as an iterable.
>>> def override_me(a, b):
... return Dispatchable(a, int),
Next, we define the argument replacer that replaces the dispatchables inside args/kwargs with the
supplied ones.
>>> def override_replacer(args, kwargs, dispatchables):
... return (dispatchables[0], args[1]), {}
Next, we define the multimethod.
>>> overridden_me = generate_multimethod(
... override_me, override_replacer, "ua_examples"
... )
Notice that there's no default implementation, unless you supply one.
>>> overridden_me(1, "a")
Traceback (most recent call last):
...
uarray.BackendNotImplementedError: ...
>>> overridden_me2 = generate_multimethod(
... override_me, override_replacer, "ua_examples", default=lambda x, y: (x, y)
... )
>>> overridden_me2(1, "a")
(1, 'a')
See Also
--------
uarray :
See the module documentation for how to override the method by creating backends.
"""
kw_defaults, arg_defaults, opts = get_defaults(argument_extractor)
ua_func = _Function(
argument_extractor,
argument_replacer,
domain,
arg_defaults,
kw_defaults,
default,
)
return functools.update_wrapper(ua_func, argument_extractor) | [
"def",
"generate_multimethod",
"(",
"argument_extractor",
":",
"ArgumentExtractorType",
",",
"argument_replacer",
":",
"ArgumentReplacerType",
",",
"domain",
":",
"str",
",",
"default",
":",
"typing",
".",
"Optional",
"[",
"typing",
".",
"Callable",
"]",
"=",
"Non... | https://github.com/scipy/scipy/blob/e0a749f01e79046642ccfdc419edbf9e7ca141ad/scipy/_lib/_uarray/_backend.py#L169-L241 | |
akfamily/akshare | 590e50eece9ec067da3538c7059fd660b71f1339 | akshare/futures/cons.py | python | get_json_path | (name, module_file) | return module_json_path | 获取 JSON 配置文件的路径(从模块所在目录查找)
:param name: 文件名
:param module_file: filename
:return: str json_file_path | 获取 JSON 配置文件的路径(从模块所在目录查找)
:param name: 文件名
:param module_file: filename
:return: str json_file_path | [
"获取",
"JSON",
"配置文件的路径",
"(",
"从模块所在目录查找",
")",
":",
"param",
"name",
":",
"文件名",
":",
"param",
"module_file",
":",
"filename",
":",
"return",
":",
"str",
"json_file_path"
] | def get_json_path(name, module_file):
"""
获取 JSON 配置文件的路径(从模块所在目录查找)
:param name: 文件名
:param module_file: filename
:return: str json_file_path
"""
module_folder = os.path.abspath(os.path.dirname(os.path.dirname(module_file)))
module_json_path = os.path.join(module_folder, "file_fold", name)
return module_json_path | [
"def",
"get_json_path",
"(",
"name",
",",
"module_file",
")",
":",
"module_folder",
"=",
"os",
".",
"path",
".",
"abspath",
"(",
"os",
".",
"path",
".",
"dirname",
"(",
"os",
".",
"path",
".",
"dirname",
"(",
"module_file",
")",
")",
")",
"module_json_... | https://github.com/akfamily/akshare/blob/590e50eece9ec067da3538c7059fd660b71f1339/akshare/futures/cons.py#L436-L445 | |
YichenGong/Densely-Interactive-Inference-Network | cb2c23bc1aca7cafb523104b0db07df2332a877a | python/my/tensorflow/rnn_cell.py | python | TreeRNNCell.__call__ | (self, inputs, state, scope=None) | :param inputs: [N*B, I + B]
:param state: [N*B, d]
:param scope:
:return: [N*B, d] | :param inputs: [N*B, I + B]
:param state: [N*B, d]
:param scope:
:return: [N*B, d] | [
":",
"param",
"inputs",
":",
"[",
"N",
"*",
"B",
"I",
"+",
"B",
"]",
":",
"param",
"state",
":",
"[",
"N",
"*",
"B",
"d",
"]",
":",
"param",
"scope",
":",
":",
"return",
":",
"[",
"N",
"*",
"B",
"d",
"]"
] | def __call__(self, inputs, state, scope=None):
"""
:param inputs: [N*B, I + B]
:param state: [N*B, d]
:param scope:
:return: [N*B, d]
"""
with tf.variable_scope(scope or self.__class__.__name__):
d = self.state_size
x = tf.slice(inputs, [0, 0], [-1, self._input_size]) # [N*B, I]
mask = tf.slice(inputs, [0, self._input_size], [-1, -1]) # [N*B, B]
B = tf.shape(mask)[1]
prev_state = tf.expand_dims(tf.reshape(state, [-1, B, d]), 1) # [N, B, d] -> [N, 1, B, d]
mask = tf.tile(tf.expand_dims(tf.reshape(mask, [-1, B, B]), -1), [1, 1, 1, d]) # [N, B, B, d]
# prev_state = self._reduce_func(tf.tile(prev_state, [1, B, 1, 1]), 2)
prev_state = self._reduce_func(exp_mask(prev_state, mask), 2) # [N, B, d]
prev_state = tf.reshape(prev_state, [-1, d]) # [N*B, d]
return self._cell(x, prev_state) | [
"def",
"__call__",
"(",
"self",
",",
"inputs",
",",
"state",
",",
"scope",
"=",
"None",
")",
":",
"with",
"tf",
".",
"variable_scope",
"(",
"scope",
"or",
"self",
".",
"__class__",
".",
"__name__",
")",
":",
"d",
"=",
"self",
".",
"state_size",
"x",
... | https://github.com/YichenGong/Densely-Interactive-Inference-Network/blob/cb2c23bc1aca7cafb523104b0db07df2332a877a/python/my/tensorflow/rnn_cell.py#L34-L51 | ||
numenta/nupic | b9ebedaf54f49a33de22d8d44dff7c765cdb5548 | external/linux32/lib/python2.6/site-packages/matplotlib/axes.py | python | Axes.__pick | (self, x, y, trans=None, among=None) | return ds[0][1] | Return the artist under point that is closest to the *x*, *y*.
If *trans* is *None*, *x*, and *y* are in window coords,
(0,0 = lower left). Otherwise, *trans* is a
:class:`~matplotlib.transforms.Transform` that specifies the
coordinate system of *x*, *y*.
The selection of artists from amongst which the pick function
finds an artist can be narrowed using the optional keyword
argument *among*. If provided, this should be either a sequence
of permitted artists or a function taking an artist as its
argument and returning a true value if and only if that artist
can be selected.
Note this algorithm calculates distance to the vertices of the
polygon, so if you want to pick a patch, click on the edge! | Return the artist under point that is closest to the *x*, *y*.
If *trans* is *None*, *x*, and *y* are in window coords,
(0,0 = lower left). Otherwise, *trans* is a
:class:`~matplotlib.transforms.Transform` that specifies the
coordinate system of *x*, *y*. | [
"Return",
"the",
"artist",
"under",
"point",
"that",
"is",
"closest",
"to",
"the",
"*",
"x",
"*",
"*",
"y",
"*",
".",
"If",
"*",
"trans",
"*",
"is",
"*",
"None",
"*",
"*",
"x",
"*",
"and",
"*",
"y",
"*",
"are",
"in",
"window",
"coords",
"(",
... | def __pick(self, x, y, trans=None, among=None):
"""
Return the artist under point that is closest to the *x*, *y*.
If *trans* is *None*, *x*, and *y* are in window coords,
(0,0 = lower left). Otherwise, *trans* is a
:class:`~matplotlib.transforms.Transform` that specifies the
coordinate system of *x*, *y*.
The selection of artists from amongst which the pick function
finds an artist can be narrowed using the optional keyword
argument *among*. If provided, this should be either a sequence
of permitted artists or a function taking an artist as its
argument and returning a true value if and only if that artist
can be selected.
Note this algorithm calculates distance to the vertices of the
polygon, so if you want to pick a patch, click on the edge!
"""
# MGDTODO: Needs updating
if trans is not None:
xywin = trans.transform_point((x,y))
else:
xywin = x,y
def dist_points(p1, p2):
'return the distance between two points'
x1, y1 = p1
x2, y2 = p2
return math.sqrt((x1-x2)**2+(y1-y2)**2)
def dist_x_y(p1, x, y):
'*x* and *y* are arrays; return the distance to the closest point'
x1, y1 = p1
return min(np.sqrt((x-x1)**2+(y-y1)**2))
def dist(a):
if isinstance(a, Text):
bbox = a.get_window_extent()
l,b,w,h = bbox.bounds
verts = (l,b), (l,b+h), (l+w,b+h), (l+w, b)
xt, yt = zip(*verts)
elif isinstance(a, Patch):
path = a.get_path()
tverts = a.get_transform().transform_path(path)
xt, yt = zip(*tverts)
elif isinstance(a, mlines.Line2D):
xdata = a.get_xdata(orig=False)
ydata = a.get_ydata(orig=False)
xt, yt = a.get_transform().numerix_x_y(xdata, ydata)
return dist_x_y(xywin, np.asarray(xt), np.asarray(yt))
artists = self.lines + self.patches + self.texts
if callable(among):
artists = filter(test, artists)
elif iterable(among):
amongd = dict([(k,1) for k in among])
artists = [a for a in artists if a in amongd]
elif among is None:
pass
else:
raise ValueError('among must be callable or iterable')
if not len(artists): return None
ds = [ (dist(a),a) for a in artists]
ds.sort()
return ds[0][1] | [
"def",
"__pick",
"(",
"self",
",",
"x",
",",
"y",
",",
"trans",
"=",
"None",
",",
"among",
"=",
"None",
")",
":",
"# MGDTODO: Needs updating",
"if",
"trans",
"is",
"not",
"None",
":",
"xywin",
"=",
"trans",
".",
"transform_point",
"(",
"(",
"x",
",",... | https://github.com/numenta/nupic/blob/b9ebedaf54f49a33de22d8d44dff7c765cdb5548/external/linux32/lib/python2.6/site-packages/matplotlib/axes.py#L2487-L2552 | |
deluge-torrent/deluge | 2316088f5c0dd6cb044d9d4832fa7d56dcc79cdc | deluge/maketorrent.py | python | TorrentMetadata.set_pad_files | (self, pad) | Enable padding files for the torrent.
Args:
private (bool): True adds padding files to align files on piece boundaries. | Enable padding files for the torrent. | [
"Enable",
"padding",
"files",
"for",
"the",
"torrent",
"."
] | def set_pad_files(self, pad):
"""Enable padding files for the torrent.
Args:
private (bool): True adds padding files to align files on piece boundaries.
"""
self.__pad_files = pad | [
"def",
"set_pad_files",
"(",
"self",
",",
"pad",
")",
":",
"self",
".",
"__pad_files",
"=",
"pad"
] | https://github.com/deluge-torrent/deluge/blob/2316088f5c0dd6cb044d9d4832fa7d56dcc79cdc/deluge/maketorrent.py#L361-L368 | ||
shunyaoshih/TPA-LSTM | 598cfc90f778856084f0ca80b463894e7ea26481 | lib/data_generator.py | python | DataGenerator._float_list_feature | (self, value) | return tf.train.Feature(float_list=tf.train.FloatList(value=value)) | [] | def _float_list_feature(self, value):
return tf.train.Feature(float_list=tf.train.FloatList(value=value)) | [
"def",
"_float_list_feature",
"(",
"self",
",",
"value",
")",
":",
"return",
"tf",
".",
"train",
".",
"Feature",
"(",
"float_list",
"=",
"tf",
".",
"train",
".",
"FloatList",
"(",
"value",
"=",
"value",
")",
")"
] | https://github.com/shunyaoshih/TPA-LSTM/blob/598cfc90f778856084f0ca80b463894e7ea26481/lib/data_generator.py#L89-L90 | |||
IntelPython/sdc | 1ebf55c00ef38dfbd401a70b3945e352a5a38b87 | sdc/utilities/utils.py | python | gen_getitem | (out_var, in_var, ind, calltypes, nodes) | [] | def gen_getitem(out_var, in_var, ind, calltypes, nodes):
loc = out_var.loc
getitem = ir.Expr.static_getitem(in_var, ind, None, loc)
calltypes[getitem] = None
nodes.append(ir.Assign(getitem, out_var, loc)) | [
"def",
"gen_getitem",
"(",
"out_var",
",",
"in_var",
",",
"ind",
",",
"calltypes",
",",
"nodes",
")",
":",
"loc",
"=",
"out_var",
".",
"loc",
"getitem",
"=",
"ir",
".",
"Expr",
".",
"static_getitem",
"(",
"in_var",
",",
"ind",
",",
"None",
",",
"loc"... | https://github.com/IntelPython/sdc/blob/1ebf55c00ef38dfbd401a70b3945e352a5a38b87/sdc/utilities/utils.py#L525-L529 | ||||
dowjones/hammer | 674028a067cad91ce1a84577d30afe7b895f2a6a | hammer/reporting-remediation/reporting/create_s3bucket_acl_issue_tickets.py | python | CreateS3BucketsTickets.create_tickets_s3buckets | (self) | Class method to create jira tickets | Class method to create jira tickets | [
"Class",
"method",
"to",
"create",
"jira",
"tickets"
] | def create_tickets_s3buckets(self):
""" Class method to create jira tickets """
table_name = self.config.s3acl.ddb_table_name
main_account = Account(region=self.config.aws.region)
ddb_table = main_account.resource("dynamodb").Table(table_name)
jira = JiraReporting(self.config)
slack = SlackNotification(self.config)
for account_id, account_name in self.config.s3acl.accounts.items():
logging.debug(f"Checking '{account_name} / {account_id}'")
issues = IssueOperations.get_account_not_closed_issues(ddb_table, account_id, S3AclIssue)
for issue in issues:
bucket_name = issue.issue_id
tags = issue.issue_details.tags
# issue has been already reported
if issue.timestamps.reported is not None:
owner = issue.issue_details.owner
bu = issue.jira_details.business_unit
product = issue.jira_details.product
if issue.status in [IssueStatus.Resolved, IssueStatus.Whitelisted]:
logging.debug(f"Closing {issue.status.value} S3 bucket '{bucket_name}' public ACL issue")
comment = (f"Closing {issue.status.value} S3 bucket '{bucket_name}' public ACL issue "
f"in '{account_name} / {account_id}' account")
if issue.status == IssueStatus.Whitelisted:
# Adding label with "whitelisted" to jira ticket.
jira.add_label(
ticket_id=issue.jira_details.ticket,
label=IssueStatus.Whitelisted.value
)
jira.close_issue(
ticket_id=issue.jira_details.ticket,
comment=comment
)
slack.report_issue(
msg=f"{comment}"
f"{' (' + jira.ticket_url(issue.jira_details.ticket) + ')' if issue.jira_details.ticket else ''}",
owner=owner,
account_id=account_id,
bu=bu, product=product,
)
IssueOperations.set_status_closed(ddb_table, issue)
# issue.status != IssueStatus.Closed (should be IssueStatus.Open)
elif issue.timestamps.updated > issue.timestamps.reported:
logging.debug(f"Updating S3 bucket '{bucket_name}' public ACL issue")
comment = "Issue details are changed, please check again.\n"
comment += self.build_permissions_table(issue.issue_details.public_acls)
comment += JiraOperations.build_tags_table(tags)
jira.update_issue(
ticket_id=issue.jira_details.ticket,
comment=comment
)
slack.report_issue(
msg=f"S3 bucket '{bucket_name}' pubic ACL issue is changed "
f"in '{account_name} / {account_id}' account"
f"{' (' + jira.ticket_url(issue.jira_details.ticket) + ')' if issue.jira_details.ticket else ''}",
owner=owner,
account_id=account_id,
bu=bu, product=product,
)
IssueOperations.set_status_updated(ddb_table, issue)
else:
logging.debug(f"No changes for '{bucket_name}'")
# issue has not been reported yet
else:
logging.debug(f"Reporting S3 bucket '{bucket_name}' public ACL issue")
owner = tags.get("owner", None)
bu = tags.get("bu", None)
product = tags.get("product", None)
if bu is None:
bu = self.config.get_bu_by_name(bucket_name)
issue_summary = (f"S3 bucket '{bucket_name}' with public acl "
f"in '{account_name} / {account_id}' account{' [' + bu + ']' if bu else ''}")
issue_description = (
f"Bucket ACL allows unrestricted public access.\n\n"
f"*Threat*: "
f"This creates potential security vulnerabilities by allowing anyone to add, modify, or remove items in a bucket.\n\n"
f"*Risk*: High\n\n"
f"*Account Name*: {account_name}\n"
f"*Account ID*: {account_id}\n"
f"*S3 Bucket name*: {bucket_name}\n"
f"*Bucket Owner*: {owner}\n"
f"\n")
auto_remediation_date = (self.config.now + self.config.s3acl.issue_retention_date).date()
issue_description += f"\n{{color:red}}*Auto-Remediation Date*: {auto_remediation_date}{{color}}\n\n"
issue_description += JiraOperations.build_tags_table(tags)
issue_description += self.build_permissions_table(issue.issue_details.public_acls)
issue_description += f"\n"
issue_description += (
f"*Recommendation*: "
f"Update bucket permissions to restrict access to the owner or specific users "
f"or grant CloudFront OAI applicable permissions on each object that CloudFront distribution serves. "
)
if self.config.whitelisting_procedure_url:
issue_description += (f"For any other exceptions, please follow the [whitelisting procedure|{self.config.whitelisting_procedure_url}] "
f"and provide a strong business reasoning. ")
try:
response = jira.add_issue(
issue_summary=issue_summary, issue_description=issue_description,
priority="Major", labels=["publics3"],
owner=owner,
account_id=account_id,
bu=bu, product=product,
)
except Exception:
logging.exception("Failed to create jira ticket")
continue
if response is not None:
issue.jira_details.ticket = response.ticket_id
issue.jira_details.ticket_assignee_id = response.ticket_assignee_id
issue.jira_details.owner = owner
issue.jira_details.business_unit = bu
issue.jira_details.product = product
slack.report_issue(
msg=f"Discovered {issue_summary}"
f"{' (' + jira.ticket_url(issue.jira_details.ticket) + ')' if issue.jira_details.ticket else ''}",
owner=owner,
account_id=account_id,
bu=bu, product=product,
)
IssueOperations.set_status_reported(ddb_table, issue) | [
"def",
"create_tickets_s3buckets",
"(",
"self",
")",
":",
"table_name",
"=",
"self",
".",
"config",
".",
"s3acl",
".",
"ddb_table_name",
"main_account",
"=",
"Account",
"(",
"region",
"=",
"self",
".",
"config",
".",
"aws",
".",
"region",
")",
"ddb_table",
... | https://github.com/dowjones/hammer/blob/674028a067cad91ce1a84577d30afe7b895f2a6a/hammer/reporting-remediation/reporting/create_s3bucket_acl_issue_tickets.py#L30-L167 | ||
mdiazcl/fuzzbunch-debian | 2b76c2249ade83a389ae3badb12a1bd09901fd2c | windows/Resources/Python/Core/Lib/email/feedparser.py | python | FeedParser.__init__ | (self, _factory=message.Message) | return | _factory is called with no arguments to create a new message obj | _factory is called with no arguments to create a new message obj | [
"_factory",
"is",
"called",
"with",
"no",
"arguments",
"to",
"create",
"a",
"new",
"message",
"obj"
] | def __init__(self, _factory=message.Message):
"""_factory is called with no arguments to create a new message obj"""
self._factory = _factory
self._input = BufferedSubFile()
self._msgstack = []
self._parse = self._parsegen().next
self._cur = None
self._last = None
self._headersonly = False
return | [
"def",
"__init__",
"(",
"self",
",",
"_factory",
"=",
"message",
".",
"Message",
")",
":",
"self",
".",
"_factory",
"=",
"_factory",
"self",
".",
"_input",
"=",
"BufferedSubFile",
"(",
")",
"self",
".",
"_msgstack",
"=",
"[",
"]",
"self",
".",
"_parse"... | https://github.com/mdiazcl/fuzzbunch-debian/blob/2b76c2249ade83a389ae3badb12a1bd09901fd2c/windows/Resources/Python/Core/Lib/email/feedparser.py#L110-L119 | |
suavecode/SUAVE | 4f83c467c5662b6cc611ce2ab6c0bdd25fd5c0a5 | trunk/SUAVE/Plots/Performance/Mission_Plots.py | python | plot_battery_pack_conditions | (results, line_color = 'bo-', line_color2 = 'rs--', save_figure = False, save_filename = "Battery_Pack_Conditions", file_type = ".png") | return | This plots the battery pack conditions of the network
Assumptions:
None
Source:
None
Inputs:
results.segments.conditions.propulsion
battery_power_draw
battery_energy
battery_voltage_under_load
battery_voltage_open_circuit
current
Outputs:
Plots
Properties Used:
N/A | This plots the battery pack conditions of the network | [
"This",
"plots",
"the",
"battery",
"pack",
"conditions",
"of",
"the",
"network"
] | def plot_battery_pack_conditions(results, line_color = 'bo-', line_color2 = 'rs--', save_figure = False, save_filename = "Battery_Pack_Conditions", file_type = ".png"):
"""This plots the battery pack conditions of the network
Assumptions:
None
Source:
None
Inputs:
results.segments.conditions.propulsion
battery_power_draw
battery_energy
battery_voltage_under_load
battery_voltage_open_circuit
current
Outputs:
Plots
Properties Used:
N/A
"""
axis_font = {'size':'14'}
fig = plt.figure(save_filename)
fig.set_size_inches(12, 10)
fig.suptitle('Battery Pack Conditions')
for i in range(len(results.segments)):
time = results.segments[i].conditions.frames.inertial.time[:,0] / Units.min
pack_power = results.segments[i].conditions.propulsion.battery_power_draw[:,0]
pack_energy = results.segments[i].conditions.propulsion.battery_energy[:,0]
pack_volts = results.segments[i].conditions.propulsion.battery_voltage_under_load[:,0]
pack_volts_oc = results.segments[i].conditions.propulsion.battery_voltage_open_circuit[:,0]
pack_current = results.segments[i].conditions.propulsion.battery_current[:,0]
pack_SOC = results.segments[i].conditions.propulsion.battery_state_of_charge[:,0]
pack_current = results.segments[i].conditions.propulsion.battery_current[:,0]
pack_battery_amp_hr = (pack_energy/ Units.Wh )/pack_volts
pack_C_instant = pack_current/pack_battery_amp_hr
pack_C_nominal = pack_current/np.max(pack_battery_amp_hr)
axes = plt.subplot(3,3,1)
axes.plot(time, pack_SOC , line_color)
axes.set_ylabel('SOC',axis_font)
set_axes(axes)
axes = plt.subplot(3,3,2)
axes.plot(time, (pack_energy/Units.Wh)/1000, line_color)
axes.set_ylabel('Energy (kW-hr)',axis_font)
set_axes(axes)
axes = plt.subplot(3,3,3)
axes.plot(time, -pack_power/1000, line_color)
axes.set_ylabel('Power (kW)',axis_font)
set_axes(axes)
axes = plt.subplot(3,3,4)
axes.set_ylabel('Voltage (V)',axis_font)
set_axes(axes)
if i == 0:
axes.plot(time, pack_volts, line_color,label='Under Load')
axes.plot(time,pack_volts_oc, line_color2,label='Open Circuit')
else:
axes.plot(time, pack_volts, line_color)
axes.plot(time,pack_volts_oc,line_color2)
axes.legend(loc='upper right')
axes = plt.subplot(3,3,5)
axes.set_xlabel('Time (mins)',axis_font)
axes.set_ylabel('C-Rate (C)',axis_font)
set_axes(axes)
if i == 0:
axes.plot(time, pack_C_instant, line_color,label='Instantaneous')
axes.plot(time, pack_C_nominal, line_color2,label='Nominal')
else:
axes.plot(time, pack_C_instant, line_color)
axes.plot(time, pack_C_nominal, line_color2)
axes.legend(loc='upper right')
axes = plt.subplot(3,3,6)
axes.plot(time, pack_current, line_color)
axes.set_xlabel('Time (mins)',axis_font)
axes.set_ylabel('Current (A)',axis_font)
set_axes(axes)
# Set limits
for i in range(1,7):
ax = plt.subplot(3,3,i)
y_lo, y_hi = ax.get_ylim()
if y_lo>0: y_lo = 0
y_hi = y_hi*1.1
ax.set_ylim(y_lo,y_hi)
plt.tight_layout()
if save_figure:
fig.savefig(save_filename + file_type)
return | [
"def",
"plot_battery_pack_conditions",
"(",
"results",
",",
"line_color",
"=",
"'bo-'",
",",
"line_color2",
"=",
"'rs--'",
",",
"save_figure",
"=",
"False",
",",
"save_filename",
"=",
"\"Battery_Pack_Conditions\"",
",",
"file_type",
"=",
"\".png\"",
")",
":",
"axi... | https://github.com/suavecode/SUAVE/blob/4f83c467c5662b6cc611ce2ab6c0bdd25fd5c0a5/trunk/SUAVE/Plots/Performance/Mission_Plots.py#L383-L485 | |
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/jinja2/environment.py | python | TemplateExpression.__init__ | (self, template, undefined_to_none) | [] | def __init__(self, template, undefined_to_none):
self._template = template
self._undefined_to_none = undefined_to_none | [
"def",
"__init__",
"(",
"self",
",",
"template",
",",
"undefined_to_none",
")",
":",
"self",
".",
"_template",
"=",
"template",
"self",
".",
"_undefined_to_none",
"=",
"undefined_to_none"
] | https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/jinja2/environment.py#L1177-L1179 | ||||
tobegit3hub/deep_image_model | 8a53edecd9e00678b278bb10f6fb4bdb1e4ee25e | java_predict_client/src/main/proto/tensorflow/python/ops/rnn.py | python | _reverse_seq | (input_seq, lengths) | return results | Reverse a list of Tensors up to specified lengths.
Args:
input_seq: Sequence of seq_len tensors of dimension (batch_size, n_features)
or nested tuples of tensors.
lengths: A `Tensor` of dimension batch_size, containing lengths for each
sequence in the batch. If "None" is specified, simply reverses
the list.
Returns:
time-reversed sequence | Reverse a list of Tensors up to specified lengths. | [
"Reverse",
"a",
"list",
"of",
"Tensors",
"up",
"to",
"specified",
"lengths",
"."
] | def _reverse_seq(input_seq, lengths):
"""Reverse a list of Tensors up to specified lengths.
Args:
input_seq: Sequence of seq_len tensors of dimension (batch_size, n_features)
or nested tuples of tensors.
lengths: A `Tensor` of dimension batch_size, containing lengths for each
sequence in the batch. If "None" is specified, simply reverses
the list.
Returns:
time-reversed sequence
"""
if lengths is None:
return list(reversed(input_seq))
flat_input_seq = tuple(nest.flatten(input_) for input_ in input_seq)
flat_results = [[] for _ in range(len(input_seq))]
for sequence in zip(*flat_input_seq):
input_shape = tensor_shape.unknown_shape(
ndims=sequence[0].get_shape().ndims)
for input_ in sequence:
input_shape.merge_with(input_.get_shape())
input_.set_shape(input_shape)
# Join into (time, batch_size, depth)
s_joined = array_ops.pack(sequence)
# TODO(schuster, ebrevdo): Remove cast when reverse_sequence takes int32
if lengths is not None:
lengths = math_ops.to_int64(lengths)
# Reverse along dimension 0
s_reversed = array_ops.reverse_sequence(s_joined, lengths, 0, 1)
# Split again into list
result = array_ops.unpack(s_reversed)
for r, flat_result in zip(result, flat_results):
r.set_shape(input_shape)
flat_result.append(r)
results = [nest.pack_sequence_as(structure=input_, flat_sequence=flat_result)
for input_, flat_result in zip(input_seq, flat_results)]
return results | [
"def",
"_reverse_seq",
"(",
"input_seq",
",",
"lengths",
")",
":",
"if",
"lengths",
"is",
"None",
":",
"return",
"list",
"(",
"reversed",
"(",
"input_seq",
")",
")",
"flat_input_seq",
"=",
"tuple",
"(",
"nest",
".",
"flatten",
"(",
"input_",
")",
"for",
... | https://github.com/tobegit3hub/deep_image_model/blob/8a53edecd9e00678b278bb10f6fb4bdb1e4ee25e/java_predict_client/src/main/proto/tensorflow/python/ops/rnn.py#L435-L478 | |
IronLanguages/ironpython3 | 7a7bb2a872eeab0d1009fc8a6e24dca43f65b693 | Src/StdLib/Lib/encodings/charmap.py | python | StreamWriter.__init__ | (self,stream,errors='strict',mapping=None) | [] | def __init__(self,stream,errors='strict',mapping=None):
codecs.StreamWriter.__init__(self,stream,errors)
self.mapping = mapping | [
"def",
"__init__",
"(",
"self",
",",
"stream",
",",
"errors",
"=",
"'strict'",
",",
"mapping",
"=",
"None",
")",
":",
"codecs",
".",
"StreamWriter",
".",
"__init__",
"(",
"self",
",",
"stream",
",",
"errors",
")",
"self",
".",
"mapping",
"=",
"mapping"... | https://github.com/IronLanguages/ironpython3/blob/7a7bb2a872eeab0d1009fc8a6e24dca43f65b693/Src/StdLib/Lib/encodings/charmap.py#L42-L44 | ||||
GMvandeVen/continual-learning | a02db26d3b10754abdc4a549bdcde6af488c94e0 | callbacks.py | python | _sample_cb | (log, config, visdom=None, test_datasets=None, sample_size=64, iters_per_task=None) | return sample_cb if (visdom is not None) else None | Initiates function for evaluating samples of generative model.
[test_datasets] None or <list> of <Datasets> (if provided, also reconstructions are shown) | Initiates function for evaluating samples of generative model. | [
"Initiates",
"function",
"for",
"evaluating",
"samples",
"of",
"generative",
"model",
"."
] | def _sample_cb(log, config, visdom=None, test_datasets=None, sample_size=64, iters_per_task=None):
'''Initiates function for evaluating samples of generative model.
[test_datasets] None or <list> of <Datasets> (if provided, also reconstructions are shown)'''
def sample_cb(generator, batch, task=1):
'''Callback-function, to evaluate sample (and reconstruction) ability of the model.'''
iteration = batch if task==1 else (task-1)*iters_per_task + batch
if iteration % log == 0:
# Evaluate reconstruction-ability of model on [test_dataset]
if test_datasets is not None:
# Reconstruct samples from current task
evaluate.show_reconstruction(generator, test_datasets[task-1], config, size=int(sample_size/2),
visdom=visdom, task=task)
# Generate samples
evaluate.show_samples(generator, config, visdom=visdom, size=sample_size,
title="Generated images after {} iters in task {}".format(batch, task))
# Return the callback-function (except if neither visdom or pdf is selected!)
return sample_cb if (visdom is not None) else None | [
"def",
"_sample_cb",
"(",
"log",
",",
"config",
",",
"visdom",
"=",
"None",
",",
"test_datasets",
"=",
"None",
",",
"sample_size",
"=",
"64",
",",
"iters_per_task",
"=",
"None",
")",
":",
"def",
"sample_cb",
"(",
"generator",
",",
"batch",
",",
"task",
... | https://github.com/GMvandeVen/continual-learning/blob/a02db26d3b10754abdc4a549bdcde6af488c94e0/callbacks.py#L9-L32 | |
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/combinat/root_system/type_relabel.py | python | CartanType.ascii_art | (self, label=lambda i: i, node=None) | return self._type.ascii_art(lambda i: label(self._relabelling[i]), node) | Return an ascii art representation of this Cartan type.
EXAMPLES::
sage: print(CartanType(["G", 2]).relabel({1:2,2:1}).ascii_art())
3
O=<=O
2 1
sage: print(CartanType(["B", 3, 1]).relabel([1,3,2,0]).ascii_art())
O 1
|
|
O---O=>=O
3 2 0
sage: print(CartanType(["F", 4, 1]).relabel(lambda n: 4-n).ascii_art())
O---O---O=>=O---O
4 3 2 1 0 | Return an ascii art representation of this Cartan type. | [
"Return",
"an",
"ascii",
"art",
"representation",
"of",
"this",
"Cartan",
"type",
"."
] | def ascii_art(self, label=lambda i: i, node=None):
"""
Return an ascii art representation of this Cartan type.
EXAMPLES::
sage: print(CartanType(["G", 2]).relabel({1:2,2:1}).ascii_art())
3
O=<=O
2 1
sage: print(CartanType(["B", 3, 1]).relabel([1,3,2,0]).ascii_art())
O 1
|
|
O---O=>=O
3 2 0
sage: print(CartanType(["F", 4, 1]).relabel(lambda n: 4-n).ascii_art())
O---O---O=>=O---O
4 3 2 1 0
"""
if node is None:
node = self._ascii_art_node
return self._type.ascii_art(lambda i: label(self._relabelling[i]), node) | [
"def",
"ascii_art",
"(",
"self",
",",
"label",
"=",
"lambda",
"i",
":",
"i",
",",
"node",
"=",
"None",
")",
":",
"if",
"node",
"is",
"None",
":",
"node",
"=",
"self",
".",
"_ascii_art_node",
"return",
"self",
".",
"_type",
".",
"ascii_art",
"(",
"l... | https://github.com/sagemath/sage/blob/f9b2db94f675ff16963ccdefba4f1a3393b3fe0d/src/sage/combinat/root_system/type_relabel.py#L289-L311 | |
hyperledger/aries-cloudagent-python | 2f36776e99f6053ae92eed8123b5b1b2e891c02a | aries_cloudagent/utils/classloader.py | python | ClassLoader.load_subclass_of | (cls, base_class: Type, mod_path: str, package: str = None) | return imported_class | Resolve an implementation of a base path within a module.
Args:
base_class: the base class being implemented
mod_path: the absolute module path
package: the parent package to search for the module
Returns:
The resolved class
Raises:
ClassNotFoundError: If the module or class implementation could not be found
ModuleLoadError: If there was an error loading the module | Resolve an implementation of a base path within a module. | [
"Resolve",
"an",
"implementation",
"of",
"a",
"base",
"path",
"within",
"a",
"module",
"."
] | def load_subclass_of(cls, base_class: Type, mod_path: str, package: str = None):
"""
Resolve an implementation of a base path within a module.
Args:
base_class: the base class being implemented
mod_path: the absolute module path
package: the parent package to search for the module
Returns:
The resolved class
Raises:
ClassNotFoundError: If the module or class implementation could not be found
ModuleLoadError: If there was an error loading the module
"""
mod = cls.load_module(mod_path, package)
if not mod:
raise ClassNotFoundError(f"Module '{mod_path}' not found")
# Find an the first declared class that inherits from
try:
imported_class = next(
obj
for name, obj in inspect.getmembers(mod, inspect.isclass)
if issubclass(obj, base_class) and obj is not base_class
)
except StopIteration:
raise ClassNotFoundError(
f"Could not resolve a class that inherits from {base_class}"
) from None
return imported_class | [
"def",
"load_subclass_of",
"(",
"cls",
",",
"base_class",
":",
"Type",
",",
"mod_path",
":",
"str",
",",
"package",
":",
"str",
"=",
"None",
")",
":",
"mod",
"=",
"cls",
".",
"load_module",
"(",
"mod_path",
",",
"package",
")",
"if",
"not",
"mod",
":... | https://github.com/hyperledger/aries-cloudagent-python/blob/2f36776e99f6053ae92eed8123b5b1b2e891c02a/aries_cloudagent/utils/classloader.py#L123-L156 | |
zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/dateutil/tz/win.py | python | tzwin.__repr__ | (self) | return "tzwin(%s)" % repr(self._name) | [] | def __repr__(self):
return "tzwin(%s)" % repr(self._name) | [
"def",
"__repr__",
"(",
"self",
")",
":",
"return",
"\"tzwin(%s)\"",
"%",
"repr",
"(",
"self",
".",
"_name",
")"
] | https://github.com/zhl2008/awd-platform/blob/0416b31abea29743387b10b3914581fbe8e7da5e/web_flaskbb/lib/python2.7/site-packages/dateutil/tz/win.py#L229-L230 | |||
andabi/music-source-separation | ba9aa531ccca08437f1efe5dec1871faebf5c840 | mir_eval/hierarchy.py | python | _hierarchy_bounds | (intervals_hier) | return min(boundaries), max(boundaries) | Compute the covered time range of a hierarchical segmentation.
Parameters
----------
intervals_hier : list of ndarray
A hierarchical segmentation, encoded as a list of arrays of segment
intervals.
Returns
-------
t_min : float
t_max : float
The minimum and maximum times spanned by the annotation | Compute the covered time range of a hierarchical segmentation. | [
"Compute",
"the",
"covered",
"time",
"range",
"of",
"a",
"hierarchical",
"segmentation",
"."
] | def _hierarchy_bounds(intervals_hier):
'''Compute the covered time range of a hierarchical segmentation.
Parameters
----------
intervals_hier : list of ndarray
A hierarchical segmentation, encoded as a list of arrays of segment
intervals.
Returns
-------
t_min : float
t_max : float
The minimum and maximum times spanned by the annotation
'''
boundaries = list(itertools.chain(*list(itertools.chain(*intervals_hier))))
return min(boundaries), max(boundaries) | [
"def",
"_hierarchy_bounds",
"(",
"intervals_hier",
")",
":",
"boundaries",
"=",
"list",
"(",
"itertools",
".",
"chain",
"(",
"*",
"list",
"(",
"itertools",
".",
"chain",
"(",
"*",
"intervals_hier",
")",
")",
")",
")",
"return",
"min",
"(",
"boundaries",
... | https://github.com/andabi/music-source-separation/blob/ba9aa531ccca08437f1efe5dec1871faebf5c840/mir_eval/hierarchy.py#L81-L98 | |
PySimpleGUI/PySimpleGUI | 6c0d1fb54f493d45e90180b322fbbe70f7a5af3c | PySimpleGUIQt/PySimpleGUIQt.py | python | Output.write | (self, m) | MUST be called write. Don't mess with. It's called by Python itself because of reroute
:param m:
:return: | MUST be called write. Don't mess with. It's called by Python itself because of reroute
:param m:
:return: | [
"MUST",
"be",
"called",
"write",
".",
"Don",
"t",
"mess",
"with",
".",
"It",
"s",
"called",
"by",
"Python",
"itself",
"because",
"of",
"reroute",
":",
"param",
"m",
":",
":",
"return",
":"
] | def write(self, m):
"""
MUST be called write. Don't mess with. It's called by Python itself because of reroute
:param m:
:return:
"""
self.QT_TextBrowser.moveCursor(QtGui.QTextCursor.End)
self.QT_TextBrowser.insertPlainText( str(m)) | [
"def",
"write",
"(",
"self",
",",
"m",
")",
":",
"self",
".",
"QT_TextBrowser",
".",
"moveCursor",
"(",
"QtGui",
".",
"QTextCursor",
".",
"End",
")",
"self",
".",
"QT_TextBrowser",
".",
"insertPlainText",
"(",
"str",
"(",
"m",
")",
")"
] | https://github.com/PySimpleGUI/PySimpleGUI/blob/6c0d1fb54f493d45e90180b322fbbe70f7a5af3c/PySimpleGUIQt/PySimpleGUIQt.py#L1694-L1701 | ||
linxid/Machine_Learning_Study_Path | 558e82d13237114bbb8152483977806fc0c222af | Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/_dummy_thread.py | python | LockType.__init__ | (self) | [] | def __init__(self):
self.locked_status = False | [
"def",
"__init__",
"(",
"self",
")",
":",
"self",
".",
"locked_status",
"=",
"False"
] | https://github.com/linxid/Machine_Learning_Study_Path/blob/558e82d13237114bbb8152483977806fc0c222af/Machine Learning In Action/Chapter5-LogisticRegression/venv/Lib/_dummy_thread.py#L99-L100 | ||||
IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/IronPython/repackage/pip/pip/_vendor/requests/utils.py | python | default_user_agent | (name="python-requests") | return '%s/%s' % (name, __version__) | Return a string representing the default user agent. | Return a string representing the default user agent. | [
"Return",
"a",
"string",
"representing",
"the",
"default",
"user",
"agent",
"."
] | def default_user_agent(name="python-requests"):
"""Return a string representing the default user agent."""
return '%s/%s' % (name, __version__) | [
"def",
"default_user_agent",
"(",
"name",
"=",
"\"python-requests\"",
")",
":",
"return",
"'%s/%s'",
"%",
"(",
"name",
",",
"__version__",
")"
] | https://github.com/IronLanguages/main/blob/a949455434b1fda8c783289e897e78a9a0caabb5/External.LCA_RESTRICTED/Languages/IronPython/repackage/pip/pip/_vendor/requests/utils.py#L580-L582 | |
enthought/comtypes | 8f3abc93c213fccdf9cae54aa88bfc1dfc17b8e9 | comtypes/client/dynamic.py | python | _Dispatch.QueryInterface | (self, *args) | return self._comobj.QueryInterface(*args) | QueryInterface is forwarded to the real com object. | QueryInterface is forwarded to the real com object. | [
"QueryInterface",
"is",
"forwarded",
"to",
"the",
"real",
"com",
"object",
"."
] | def QueryInterface(self, *args):
"QueryInterface is forwarded to the real com object."
return self._comobj.QueryInterface(*args) | [
"def",
"QueryInterface",
"(",
"self",
",",
"*",
"args",
")",
":",
"return",
"self",
".",
"_comobj",
".",
"QueryInterface",
"(",
"*",
"args",
")"
] | https://github.com/enthought/comtypes/blob/8f3abc93c213fccdf9cae54aa88bfc1dfc17b8e9/comtypes/client/dynamic.py#L85-L87 | |
home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/panasonic_viera/media_player.py | python | PanasonicVieraTVEntity.device_class | (self) | return MediaPlayerDeviceClass.TV | Return the device class of the device. | Return the device class of the device. | [
"Return",
"the",
"device",
"class",
"of",
"the",
"device",
"."
] | def device_class(self):
"""Return the device class of the device."""
return MediaPlayerDeviceClass.TV | [
"def",
"device_class",
"(",
"self",
")",
":",
"return",
"MediaPlayerDeviceClass",
".",
"TV"
] | https://github.com/home-assistant/core/blob/265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1/homeassistant/components/panasonic_viera/media_player.py#L106-L108 | |
tebelorg/RPA-Python | 9e8b2b417777a0780a0d19c9f880a9bb8ac2e976 | tagui.py | python | _tagui_output | () | return tagui_output_text | function to wait for tagui output file to read and delete it | function to wait for tagui output file to read and delete it | [
"function",
"to",
"wait",
"for",
"tagui",
"output",
"file",
"to",
"read",
"and",
"delete",
"it"
] | def _tagui_output():
"""function to wait for tagui output file to read and delete it"""
global _tagui_delay, _tagui_init_directory
# to handle user changing current directory after init() is called
init_directory_output_file = os.path.join(_tagui_init_directory, 'rpa_python.txt')
# sleep to not splurge cpu cycles in while loop
while not os.path.isfile('rpa_python.txt'):
if os.path.isfile(init_directory_output_file): break
time.sleep(_tagui_delay)
# roundabout implementation to ensure backward compatibility
if os.path.isfile('rpa_python.txt'):
tagui_output_file = _py23_open('rpa_python.txt', 'r')
tagui_output_text = _py23_read(tagui_output_file.read())
tagui_output_file.close()
os.remove('rpa_python.txt')
else:
tagui_output_file = _py23_open(init_directory_output_file, 'r')
tagui_output_text = _py23_read(tagui_output_file.read())
tagui_output_file.close()
os.remove(init_directory_output_file)
return tagui_output_text | [
"def",
"_tagui_output",
"(",
")",
":",
"global",
"_tagui_delay",
",",
"_tagui_init_directory",
"# to handle user changing current directory after init() is called",
"init_directory_output_file",
"=",
"os",
".",
"path",
".",
"join",
"(",
"_tagui_init_directory",
",",
"'rpa_pyt... | https://github.com/tebelorg/RPA-Python/blob/9e8b2b417777a0780a0d19c9f880a9bb8ac2e976/tagui.py#L134-L158 | |
upyun/python-sdk | dabff535df78d5beba4c989a6b8a046977079cdc | examples/upload.py | python | rest_upload | () | rest文件上传 | rest文件上传 | [
"rest文件上传"
] | def rest_upload():
"""
rest文件上传
"""
with open(local_file, "rb") as f:
# headers 可选，见rest上传参数
headers = None
up.put(remote_file, f, headers=headers) | [
"def",
"rest_upload",
"(",
")",
":",
"with",
"open",
"(",
"local_file",
",",
"\"rb\"",
")",
"as",
"f",
":",
"# headers 可选，见rest上传参数",
"headers",
"=",
"None",
"up",
".",
"put",
"(",
"remote_file",
",",
"f",
",",
"headers",
"=",
"headers",
")"
] | https://github.com/upyun/python-sdk/blob/dabff535df78d5beba4c989a6b8a046977079cdc/examples/upload.py#L19-L26 | ||
evennia/evennia | fa79110ba6b219932f22297838e8ac72ebc0be0e | evennia/comms/comms.py | python | DefaultChannel.at_channel_creation | (self) | Called once, when the channel is first created. | Called once, when the channel is first created. | [
"Called",
"once",
"when",
"the",
"channel",
"is",
"first",
"created",
"."
] | def at_channel_creation(self):
"""
Called once, when the channel is first created.
"""
pass | [
"def",
"at_channel_creation",
"(",
"self",
")",
":",
"pass"
] | https://github.com/evennia/evennia/blob/fa79110ba6b219932f22297838e8ac72ebc0be0e/evennia/comms/comms.py#L67-L72 | ||
edisonlz/fastor | 342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3 | base/site-packages/debug_toolbar/views.py | python | sql_profile | (request) | Returns the output of running the SQL and getting the profiling statistics.
Expected GET variables:
sql: urlencoded sql with positional arguments
params: JSON encoded parameter values
duration: time for SQL to execute passed in from toolbar just for redisplay
hash: the hash of (secret + sql + params) for tamper checking | Returns the output of running the SQL and getting the profiling statistics. | [
"Returns",
"the",
"output",
"of",
"running",
"the",
"SQL",
"and",
"getting",
"the",
"profiling",
"statistics",
"."
] | def sql_profile(request):
"""
Returns the output of running the SQL and getting the profiling statistics.
Expected GET variables:
sql: urlencoded sql with positional arguments
params: JSON encoded parameter values
duration: time for SQL to execute passed in from toolbar just for redisplay
hash: the hash of (secret + sql + params) for tamper checking
"""
from debug_toolbar.panels.sql import reformat_sql
sql = request.GET.get('sql', '')
params = request.GET.get('params', '')
alias = request.GET.get('alias', 'default')
hash = sha_constructor(settings.SECRET_KEY + sql + params).hexdigest()
if hash != request.GET.get('hash', ''):
return HttpResponseBadRequest('Tamper alert') # SQL Tampering alert
if sql.lower().strip().startswith('select'):
params = simplejson.loads(params)
cursor = connections[alias].cursor()
result = None
headers = None
result_error = None
try:
cursor.execute("SET PROFILING=1") # Enable profiling
cursor.execute(sql, params) # Execute SELECT
cursor.execute("SET PROFILING=0") # Disable profiling
# The Query ID should always be 1 here but I'll subselect to get the last one just in case...
cursor.execute("SELECT * FROM information_schema.profiling WHERE query_id=(SELECT query_id FROM information_schema.profiling ORDER BY query_id DESC LIMIT 1)")
headers = [d[0] for d in cursor.description]
result = cursor.fetchall()
except:
result_error = "Profiling is either not available or not supported by your database."
cursor.close()
context = {
'result': result,
'result_error': result_error,
'sql': reformat_sql(cursor.db.ops.last_executed_query(cursor, sql, params)),
'duration': request.GET.get('duration', 0.0),
'headers': headers,
'alias': alias,
}
return render_to_response('debug_toolbar/panels/sql_profile.html', context)
raise InvalidSQLError("Only 'select' queries are allowed.") | [
"def",
"sql_profile",
"(",
"request",
")",
":",
"from",
"debug_toolbar",
".",
"panels",
".",
"sql",
"import",
"reformat_sql",
"sql",
"=",
"request",
".",
"GET",
".",
"get",
"(",
"'sql'",
",",
"''",
")",
"params",
"=",
"request",
".",
"GET",
".",
"get",... | https://github.com/edisonlz/fastor/blob/342078a18363ac41d3c6b1ab29dbdd44fdb0b7b3/base/site-packages/debug_toolbar/views.py#L115-L158 | ||
mrlesmithjr/Ansible | d44f0dc0d942bdf3bf7334b307e6048f0ee16e36 | roles/ansible-vsphere-management/scripts/pdns/lib/python2.7/site-packages/pip/download.py | python | get_file_content | (url, comes_from=None, session=None) | return url, content | Gets the content of a file; it may be a filename, file: URL, or
http: URL. Returns (location, content). Content is unicode. | Gets the content of a file; it may be a filename, file: URL, or
http: URL. Returns (location, content). Content is unicode. | [
"Gets",
"the",
"content",
"of",
"a",
"file",
";",
"it",
"may",
"be",
"a",
"filename",
"file",
":",
"URL",
"or",
"http",
":",
"URL",
".",
"Returns",
"(",
"location",
"content",
")",
".",
"Content",
"is",
"unicode",
"."
] | def get_file_content(url, comes_from=None, session=None):
"""Gets the content of a file; it may be a filename, file: URL, or
http: URL. Returns (location, content). Content is unicode."""
if session is None:
raise TypeError(
"get_file_content() missing 1 required keyword argument: 'session'"
)
match = _scheme_re.search(url)
if match:
scheme = match.group(1).lower()
if (scheme == 'file' and comes_from and
comes_from.startswith('http')):
raise InstallationError(
'Requirements file %s references URL %s, which is local'
% (comes_from, url))
if scheme == 'file':
path = url.split(':', 1)[1]
path = path.replace('\\', '/')
match = _url_slash_drive_re.match(path)
if match:
path = match.group(1) + ':' + path.split('|', 1)[1]
path = urllib_parse.unquote(path)
if path.startswith('/'):
path = '/' + path.lstrip('/')
url = path
else:
# FIXME: catch some errors
resp = session.get(url)
resp.raise_for_status()
return resp.url, resp.text
try:
with open(url, 'rb') as f:
content = auto_decode(f.read())
except IOError as exc:
raise InstallationError(
'Could not open requirements file: %s' % str(exc)
)
return url, content | [
"def",
"get_file_content",
"(",
"url",
",",
"comes_from",
"=",
"None",
",",
"session",
"=",
"None",
")",
":",
"if",
"session",
"is",
"None",
":",
"raise",
"TypeError",
"(",
"\"get_file_content() missing 1 required keyword argument: 'session'\"",
")",
"match",
"=",
... | https://github.com/mrlesmithjr/Ansible/blob/d44f0dc0d942bdf3bf7334b307e6048f0ee16e36/roles/ansible-vsphere-management/scripts/pdns/lib/python2.7/site-packages/pip/download.py#L389-L427 | |
cgat-developers/ruffus | fc8fa8dcf7b5f4b877e5bb712146e87abd26d046 | ruffus/task.py | python | Pipeline.set_tail_tasks | (self, tail_tasks) | Specifies tasks at the tail of the pipeline,
i.e. with only descendants/dependants | Specifies tasks at the tail of the pipeline,
i.e. with only descendants/dependants | [
"Specifies",
"tasks",
"at",
"the",
"tail",
"of",
"the",
"pipeline",
"i",
".",
"e",
".",
"with",
"only",
"descendants",
"/",
"dependants"
] | def set_tail_tasks(self, tail_tasks):
"""
Specifies tasks at the tail of the pipeline,
i.e. with only descendants/dependants
"""
self.tail_tasks = tail_tasks | [
"def",
"set_tail_tasks",
"(",
"self",
",",
"tail_tasks",
")",
":",
"self",
".",
"tail_tasks",
"=",
"tail_tasks"
] | https://github.com/cgat-developers/ruffus/blob/fc8fa8dcf7b5f4b877e5bb712146e87abd26d046/ruffus/task.py#L992-L997 | ||
fabtools/fabtools | 5fdc7174c3fae5e93a16d677d0466f41dc2be175 | fabtools/python.py | python | is_installed | (package, python_cmd='python', pip_cmd='pip') | return (package.lower() in packages) | Check if a Python package is installed (using pip).
Package names are case insensitive.
Example::
from fabtools.python import virtualenv
import fabtools
with virtualenv('/path/to/venv'):
fabtools.python.install('Flask')
assert fabtools.python.is_installed('flask')
.. _pip: http://www.pip-installer.org/ | Check if a Python package is installed (using pip). | [
"Check",
"if",
"a",
"Python",
"package",
"is",
"installed",
"(",
"using",
"pip",
")",
"."
] | def is_installed(package, python_cmd='python', pip_cmd='pip'):
"""
Check if a Python package is installed (using pip).
Package names are case insensitive.
Example::
from fabtools.python import virtualenv
import fabtools
with virtualenv('/path/to/venv'):
fabtools.python.install('Flask')
assert fabtools.python.is_installed('flask')
.. _pip: http://www.pip-installer.org/
"""
with settings(
hide('running', 'stdout', 'stderr', 'warnings'), warn_only=True):
res = run('%(python_cmd)s -m %(pip_cmd)s freeze' % locals())
packages = [line.split('==')[0].lower() for line in res.splitlines()]
return (package.lower() in packages) | [
"def",
"is_installed",
"(",
"package",
",",
"python_cmd",
"=",
"'python'",
",",
"pip_cmd",
"=",
"'pip'",
")",
":",
"with",
"settings",
"(",
"hide",
"(",
"'running'",
",",
"'stdout'",
",",
"'stderr'",
",",
"'warnings'",
")",
",",
"warn_only",
"=",
"True",
... | https://github.com/fabtools/fabtools/blob/5fdc7174c3fae5e93a16d677d0466f41dc2be175/fabtools/python.py#L89-L110 | |
awslabs/aws-data-wrangler | 548f5197bacd91bd50ebc66a0173eff9c56f69b1 | awswrangler/_config.py | python | _Config.concurrent_partitioning | (self) | return cast(bool, self["concurrent_partitioning"]) | Property concurrent_partitioning. | Property concurrent_partitioning. | [
"Property",
"concurrent_partitioning",
"."
] | def concurrent_partitioning(self) -> bool:
"""Property concurrent_partitioning."""
return cast(bool, self["concurrent_partitioning"]) | [
"def",
"concurrent_partitioning",
"(",
"self",
")",
"->",
"bool",
":",
"return",
"cast",
"(",
"bool",
",",
"self",
"[",
"\"concurrent_partitioning\"",
"]",
")"
] | https://github.com/awslabs/aws-data-wrangler/blob/548f5197bacd91bd50ebc66a0173eff9c56f69b1/awswrangler/_config.py#L198-L200 | |
andresriancho/w3af | cd22e5252243a87aaa6d0ddea47cf58dacfe00a9 | w3af/plugins/attack/db/sqlmap/lib/core/option.py | python | _adjustLoggingFormatter | () | Solves problem of line deletition caused by overlapping logging messages
and retrieved data info in inference mode | Solves problem of line deletition caused by overlapping logging messages
and retrieved data info in inference mode | [
"Solves",
"problem",
"of",
"line",
"deletition",
"caused",
"by",
"overlapping",
"logging",
"messages",
"and",
"retrieved",
"data",
"info",
"in",
"inference",
"mode"
] | def _adjustLoggingFormatter():
"""
Solves problem of line deletition caused by overlapping logging messages
and retrieved data info in inference mode
"""
if hasattr(FORMATTER, '_format'):
return
def format(record):
message = FORMATTER._format(record)
message = boldifyMessage(message)
if kb.get("prependFlag"):
message = "\n%s" % message
kb.prependFlag = False
return message
FORMATTER._format = FORMATTER.format
FORMATTER.format = format | [
"def",
"_adjustLoggingFormatter",
"(",
")",
":",
"if",
"hasattr",
"(",
"FORMATTER",
",",
"'_format'",
")",
":",
"return",
"def",
"format",
"(",
"record",
")",
":",
"message",
"=",
"FORMATTER",
".",
"_format",
"(",
"record",
")",
"message",
"=",
"boldifyMes... | https://github.com/andresriancho/w3af/blob/cd22e5252243a87aaa6d0ddea47cf58dacfe00a9/w3af/plugins/attack/db/sqlmap/lib/core/option.py#L455-L473 | ||
llSourcell/AI_Artist | 3038c06c2e389b9c919c881c9a169efe2fd7810e | lib/python2.7/site-packages/pip/_vendor/pkg_resources/__init__.py | python | _SetuptoolsVersionMixin.__getitem__ | (self, key) | return tuple(self)[key] | [] | def __getitem__(self, key):
return tuple(self)[key] | [
"def",
"__getitem__",
"(",
"self",
",",
"key",
")",
":",
"return",
"tuple",
"(",
"self",
")",
"[",
"key",
"]"
] | https://github.com/llSourcell/AI_Artist/blob/3038c06c2e389b9c919c881c9a169efe2fd7810e/lib/python2.7/site-packages/pip/_vendor/pkg_resources/__init__.py#L136-L137 | |||
tensorflow/tensor2tensor | 2a33b152d7835af66a6d20afe7961751047e28dd | tensor2tensor/utils/metrics.py | python | padded_sequence_accuracy | (predictions,
labels,
weights_fn=common_layers.weights_nonzero) | Percentage of times that predictions matches labels everywhere (non-0). | Percentage of times that predictions matches labels everywhere (non-0). | [
"Percentage",
"of",
"times",
"that",
"predictions",
"matches",
"labels",
"everywhere",
"(",
"non",
"-",
"0",
")",
"."
] | def padded_sequence_accuracy(predictions,
labels,
weights_fn=common_layers.weights_nonzero):
"""Percentage of times that predictions matches labels everywhere (non-0)."""
# If the last dimension is 1 then we're using L1/L2 loss.
if common_layers.shape_list(predictions)[-1] == 1:
return rounding_sequence_accuracy(
predictions, labels, weights_fn=weights_fn)
with tf.variable_scope(
"padded_sequence_accuracy", values=[predictions, labels]):
padded_predictions, padded_labels = common_layers.pad_with_zeros(
predictions, labels)
weights = weights_fn(padded_labels)
# Flatten, keeping batch dim (and num_classes dim for predictions)
# TPU argmax can only deal with a limited number of dimensions
predictions_shape = common_layers.shape_list(padded_predictions)
batch_size = predictions_shape[0]
num_classes = predictions_shape[-1]
flat_size = common_layers.list_product(
common_layers.shape_list(padded_labels)[1:])
padded_predictions = tf.reshape(
padded_predictions,
[batch_size, common_layers.list_product(predictions_shape[1:-1]),
num_classes])
padded_labels = tf.reshape(padded_labels, [batch_size, flat_size])
weights = tf.reshape(weights, [batch_size, flat_size])
outputs = tf.to_int32(tf.argmax(padded_predictions, axis=-1))
padded_labels = tf.to_int32(padded_labels)
not_correct = tf.to_float(tf.not_equal(outputs, padded_labels)) * weights
axis = list(range(1, len(outputs.get_shape())))
correct_seq = 1.0 - tf.minimum(1.0, tf.reduce_sum(not_correct, axis=axis))
return correct_seq, tf.constant(1.0) | [
"def",
"padded_sequence_accuracy",
"(",
"predictions",
",",
"labels",
",",
"weights_fn",
"=",
"common_layers",
".",
"weights_nonzero",
")",
":",
"# If the last dimension is 1 then we're using L1/L2 loss.",
"if",
"common_layers",
".",
"shape_list",
"(",
"predictions",
")",
... | https://github.com/tensorflow/tensor2tensor/blob/2a33b152d7835af66a6d20afe7961751047e28dd/tensor2tensor/utils/metrics.py#L212-L245 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.