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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ghostop14/sparrow-wifi | 4b8289773ea4304872062f65a6ffc9352612b08e | sparrowdialogs.py | python | BluetoothDialog.showNTContextMenu | (self, pos) | [] | def showNTContextMenu(self, pos):
curRow = self.bluetoothTable.currentRow()
if curRow == -1:
return
self.ntRightClickMenu.exec_(self.bluetoothTable.mapToGlobal(pos)) | [
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hanskrupakar/COCO-Style-Dataset-Generator-GUI | 35c095a815a6ef97d2e820d175bf46e32e59f40b | coco_dataset_generator/gui/poly_editor.py | python | PolygonInteractor.get_ind_under_point | (self, event) | return ind | get the index of the vertex under point if within epsilon tolerance | get the index of the vertex under point if within epsilon tolerance | [
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] | def get_ind_under_point(self, event):
'get the index of the vertex under point if within epsilon tolerance'
# display coords
xy = np.asarray(self.poly.xy)
xyt = self.poly.get_transform().transform(xy)
xt, yt = xyt[:, 0], xyt[:, 1]
d = np.hypot(xt - event.x, yt - event.y)
indseq, = np.nonzero(d == d.min())
ind = indseq[0]
if d[ind] >= self.epsilon:
ind = None
return ind | [
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rwth-i6/returnn | f2d718a197a280b0d5f0fd91a7fcb8658560dddb | returnn/tf/util/data.py | python | Data.copy_template_set_ctx | (self, ctx) | return Data(**kwargs) | :param ControlFlowContext ctx:
:return: new Data instance
:rtype: Data | :param ControlFlowContext ctx:
:return: new Data instance
:rtype: Data | [
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] | def copy_template_set_ctx(self, ctx):
"""
:param ControlFlowContext ctx:
:return: new Data instance
:rtype: Data
"""
kwargs = self.get_kwargs()
kwargs["control_flow_ctx"] = ctx
return Data(**kwargs) | [
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travisgoodspeed/goodfet | 1750cc1e8588af5470385e52fa098ca7364c2863 | contrib/hoder/GoodFETMCPCAN_ted.py | python | GoodFETMCPCAN.poke8 | (self,adr,val) | return val | Poke a value into RAM. Untested | Poke a value into RAM. Untested | [
"Poke",
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"into",
"RAM",
".",
"Untested"
] | def poke8(self,adr,val):
"""Poke a value into RAM. Untested"""
self.SPItrans([0x02,adr&0xFF,val&0xFF]);
newval=self.peek8(adr);
if newval!=val:
print "Failed to poke %02x to %02x. Got %02x." % (adr,val,newval);
print "Are you not in idle mode?";
return val; | [
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AutodeskRoboticsLab/Mimic | 85447f0d346be66988303a6a054473d92f1ed6f4 | mimic/scripts/extern/pyqtgraph_0_11_0/pyqtgraph/flowchart/Flowchart.py | python | Flowchart.saveState | (self) | return state | Return a serializable data structure representing the current state of this flowchart. | Return a serializable data structure representing the current state of this flowchart. | [
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] | def saveState(self):
"""Return a serializable data structure representing the current state of this flowchart.
"""
state = Node.saveState(self)
state['nodes'] = []
state['connects'] = []
for name, node in self._nodes.items():
cls = type(node)
if hasattr(cls, 'nodeName'):
clsName = cls.nodeName
pos = node.graphicsItem().pos()
ns = {'class': clsName, 'name': name, 'pos': (pos.x(), pos.y()), 'state': node.saveState()}
state['nodes'].append(ns)
conn = self.listConnections()
for a, b in conn:
state['connects'].append((a.node().name(), a.name(), b.node().name(), b.name()))
state['inputNode'] = self.inputNode.saveState()
state['outputNode'] = self.outputNode.saveState()
return state | [
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aliyun/aliyun-oss-python-sdk | 5f2afa0928a58c7c1cc6317ac147f3637481f6fd | oss2/models.py | python | InventoryConfiguration.__init__ | (self,
inventory_id=None,
is_enabled=None,
included_object_versions=None,
inventory_filter=None,
inventory_destination=None,
inventory_schedule=None,
optional_fields=None) | [] | def __init__(self,
inventory_id=None,
is_enabled=None,
included_object_versions=None,
inventory_filter=None,
inventory_destination=None,
inventory_schedule=None,
optional_fields=None):
self.inventory_id = inventory_id
self.is_enabled = is_enabled
self.included_object_versions = included_object_versions
self.inventory_filter = inventory_filter
self.inventory_destination = inventory_destination
self.inventory_schedule = inventory_schedule
self.optional_fields = optional_fields or [] | [
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dropbox/dropbox-sdk-python | 015437429be224732990041164a21a0501235db1 | dropbox/team_log.py | python | AdminAlertGeneralStateEnum.is_dismissed | (self) | return self._tag == 'dismissed' | Check if the union tag is ``dismissed``.
:rtype: bool | Check if the union tag is ``dismissed``. | [
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] | def is_dismissed(self):
"""
Check if the union tag is ``dismissed``.
:rtype: bool
"""
return self._tag == 'dismissed' | [
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] | https://github.com/dropbox/dropbox-sdk-python/blob/015437429be224732990041164a21a0501235db1/dropbox/team_log.py#L1200-L1206 | |
regel/loudml | 0008baef02259a8ae81dd210d3f91a51ffc9ed9f | loudml/mongo.py | python | MongoBucket.insert_times_data | (
self,
ts,
data,
tags=None,
*args,
**kwargs
) | Insert data | Insert data | [
"Insert",
"data"
] | def insert_times_data(
self,
ts,
data,
tags=None,
*args,
**kwargs
):
"""
Insert data
"""
ts = make_ts(ts)
data = data.copy()
data[self.timestamp_field] = ts
self.insert_data(data, tags=tags) | [
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QCoDeS/Qcodes | 3cda2cef44812e2aa4672781f2423bf5f816f9f9 | qcodes/dataset/linked_datasets/links.py | python | links_to_str | (links: List[Link]) | return output | Convert a list of links to string. Note that this is the output that gets
stored in the DB file | Convert a list of links to string. Note that this is the output that gets
stored in the DB file | [
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"DB",
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] | def links_to_str(links: List[Link]) -> str:
"""
Convert a list of links to string. Note that this is the output that gets
stored in the DB file
"""
output = json.dumps([link_to_str(link) for link in links])
return output | [
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F8LEFT/DecLLVM | d38e45e3d0dd35634adae1d0cf7f96f3bd96e74c | python/idaapi.py | python | func_t.is_far | (self, *args) | return _idaapi.func_t_is_far(self, *args) | is_far(self) -> bool | is_far(self) -> bool | [
"is_far",
"(",
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] | def is_far(self, *args):
"""
is_far(self) -> bool
"""
return _idaapi.func_t_is_far(self, *args) | [
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chaoss/grimoirelab-perceval | ba19bfd5e40bffdd422ca8e68526326b47f97491 | perceval/backends/core/gitter.py | python | Gitter.fetch_items | (self, category, **kwargs) | Fetch the messages.
:param category: the category of items to fetch
:param kwargs: backend arguments
:returns: a generator of items | Fetch the messages. | [
"Fetch",
"the",
"messages",
"."
] | def fetch_items(self, category, **kwargs):
"""Fetch the messages.
:param category: the category of items to fetch
:param kwargs: backend arguments
:returns: a generator of items
"""
from_date = kwargs['from_date']
logger.debug("Get Gitter message paginated items of room: %s from date: %s", self.room, from_date)
from_date = str_to_datetime(from_date).timestamp()
fetching = True
before_id = None
num_msgs = 0
page = 0
room = urijoin(self.group, self.room)
self.room_id = self.client.get_room_id(room)
if not self.room_id:
msg = "Room id not found for room %s" % room
logger.error(msg)
raise BackendError(cause=msg)
logger.debug("Room id of room: %s is %s", self.room, self.room_id)
while fetching:
page += 1
logger.debug("Page: %i" % page)
message_group = self.client.message_page(self.room_id, before_id)
message_group = message_group.json()
if not message_group:
fetching = False
continue
for raw_message in message_group:
if str_to_datetime(raw_message['sent']).timestamp() > from_date:
num_msgs += 1
yield raw_message
else:
fetching = False
before_id = message_group[0]['id']
logger.debug("Fetch process completed: %s messages fetched", num_msgs) | [
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tensorflow/models | 6b8bb0cbeb3e10415c7a87448f08adc3c484c1d3 | official/vision/beta/serving/detection.py | python | DetectionModule.serve | (self, images: tf.Tensor) | return final_outputs | Cast image to float and run inference.
Args:
images: uint8 Tensor of shape [batch_size, None, None, 3]
Returns:
Tensor holding detection output logits. | Cast image to float and run inference. | [
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] | def serve(self, images: tf.Tensor):
"""Cast image to float and run inference.
Args:
images: uint8 Tensor of shape [batch_size, None, None, 3]
Returns:
Tensor holding detection output logits.
"""
# Skip image preprocessing when input_type is tflite so it is compatible
# with TFLite quantization.
if self._input_type != 'tflite':
images, anchor_boxes, image_info = self.preprocess(images)
else:
with tf.device('cpu:0'):
anchor_boxes = self._build_anchor_boxes()
# image_info is a 3D tensor of shape [batch_size, 4, 2]. It is in the
# format of [[original_height, original_width],
# [desired_height, desired_width], [y_scale, x_scale],
# [y_offset, x_offset]]. When input_type is tflite, input image is
# supposed to be preprocessed already.
image_info = tf.convert_to_tensor([[
self._input_image_size, self._input_image_size, [1.0, 1.0], [0, 0]
]],
dtype=tf.float32)
input_image_shape = image_info[:, 1, :]
# To overcome keras.Model extra limitation to save a model with layers that
# have multiple inputs, we use `model.call` here to trigger the forward
# path. Note that, this disables some keras magics happens in `__call__`.
detections = self.model.call(
images=images,
image_shape=input_image_shape,
anchor_boxes=anchor_boxes,
training=False)
if self.params.task.model.detection_generator.apply_nms:
# For RetinaNet model, apply export_config.
# TODO(huizhongc): Add export_config to fasterrcnn and maskrcnn as needed.
if isinstance(self.params.task.model, configs.retinanet.RetinaNet):
export_config = self.params.task.export_config
# Normalize detection box coordinates to [0, 1].
if export_config.output_normalized_coordinates:
detection_boxes = (
detections['detection_boxes'] /
tf.tile(image_info[:, 2:3, :], [1, 1, 2]))
detections['detection_boxes'] = box_ops.normalize_boxes(
detection_boxes, image_info[:, 0:1, :])
# Cast num_detections and detection_classes to float. This allows the
# model inference to work on chain (go/chain) as chain requires floating
# point outputs.
if export_config.cast_num_detections_to_float:
detections['num_detections'] = tf.cast(
detections['num_detections'], dtype=tf.float32)
if export_config.cast_detection_classes_to_float:
detections['detection_classes'] = tf.cast(
detections['detection_classes'], dtype=tf.float32)
final_outputs = {
'detection_boxes': detections['detection_boxes'],
'detection_scores': detections['detection_scores'],
'detection_classes': detections['detection_classes'],
'num_detections': detections['num_detections']
}
else:
final_outputs = {
'decoded_boxes': detections['decoded_boxes'],
'decoded_box_scores': detections['decoded_box_scores']
}
if 'detection_masks' in detections.keys():
final_outputs['detection_masks'] = detections['detection_masks']
final_outputs.update({'image_info': image_info})
return final_outputs | [
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prompt-toolkit/pyvim | 210816b4b1d2dc00606ec924dda29e49ac4cd87c | pyvim/editor.py | python | Editor.show_message | (self, message) | Set a warning message. The layout will render it as a "pop-up" at the
bottom. | Set a warning message. The layout will render it as a "pop-up" at the
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] | def show_message(self, message):
"""
Set a warning message. The layout will render it as a "pop-up" at the
bottom.
"""
self.message = message | [
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veegee/guv | d7bac2ca6a73cc2059969af08223b82f3e187922 | guv/greenthread.py | python | sleep | (seconds=0) | Yield control to the hub until at least `seconds` have elapsed
:param float seconds: time to sleep for | Yield control to the hub until at least `seconds` have elapsed | [
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] | def sleep(seconds=0):
"""Yield control to the hub until at least `seconds` have elapsed
:param float seconds: time to sleep for
"""
hub = hubs.get_hub()
current = greenlet.getcurrent()
assert hub is not current, 'do not call blocking functions from the hub'
timer = hub.schedule_call_global(seconds, current.switch)
try:
hub.switch()
finally:
timer.cancel() | [
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awslabs/aws-ec2rescue-linux | 8ecf40e7ea0d2563dac057235803fca2221029d2 | lib/requests/packages/urllib3/packages/ordered_dict.py | python | OrderedDict.__eq__ | (self, other) | return dict.__eq__(self, other) | od.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive
while comparison to a regular mapping is order-insensitive. | od.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive
while comparison to a regular mapping is order-insensitive. | [
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] | def __eq__(self, other):
'''od.__eq__(y) <==> od==y. Comparison to another OD is order-sensitive
while comparison to a regular mapping is order-insensitive.
'''
if isinstance(other, OrderedDict):
return len(self)==len(other) and self.items() == other.items()
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | apps/beeswax/gen-py/hive_metastore/ThriftHiveMetastore.py | python | Iface.get_role_grants_for_principal | (self, request) | Parameters:
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ifwe/digsby | f5fe00244744aa131e07f09348d10563f3d8fa99 | digsby/src/util/BeautifulSoup.py | python | PageElement.findPreviousSiblings | (self, name=None, attrs={}, text=None,
limit=None, **kwargs) | return self._findAll(name, attrs, text, limit,
self.previousSiblingGenerator, **kwargs) | Returns the siblings of this Tag that match the given
criteria and appear before this Tag in the document. | Returns the siblings of this Tag that match the given
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"""Returns the siblings of this Tag that match the given
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return self._findAll(name, attrs, text, limit,
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openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | lms/djangoapps/program_enrollments/api/writing.py | python | change_program_enrollment_status | (program_enrollment, new_status) | return program_enrollment.status | Update a program enrollment with a new status.
Arguments:
program_enrollment (ProgramEnrollment)
status (str): from ProgramCourseEnrollmentStatuses
Returns: str
String from ProgramOperationStatuses. | Update a program enrollment with a new status. | [
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] | def change_program_enrollment_status(program_enrollment, new_status):
"""
Update a program enrollment with a new status.
Arguments:
program_enrollment (ProgramEnrollment)
status (str): from ProgramCourseEnrollmentStatuses
Returns: str
String from ProgramOperationStatuses.
"""
if new_status not in ProgramEnrollmentStatuses.__ALL__:
return ProgramOpStatuses.INVALID_STATUS
program_enrollment.status = new_status
program_enrollment.save()
return program_enrollment.status | [
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OpenMDAO/OpenMDAO | f47eb5485a0bb5ea5d2ae5bd6da4b94dc6b296bd | openmdao/devtools/iprofile.py | python | _iter_raw_prof_file | (rawname) | Returns an iterator of (funcpath, count, elapsed_time)
from a raw profile data file. | Returns an iterator of (funcpath, count, elapsed_time)
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"""
Returns an iterator of (funcpath, count, elapsed_time)
from a raw profile data file.
"""
with open(rawname, 'r') as f:
for line in f:
path, count, elapsed = line.split()
yield path, int(count), float(elapsed) | [
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hezhangsprinter/DCPDN | 4f27d1940512dd7637a88aaba40d5d5f5fb3ff74 | models/dehaze22.py | python | D1.__init__ | (self, nc, ndf, hidden_size) | self.deconv1 = nn.Sequential(nn.Conv2d(ndf,nc,kernel_size=3,stride=1,padding=1),
nn.Tanh()) | self.deconv1 = nn.Sequential(nn.Conv2d(ndf,nc,kernel_size=3,stride=1,padding=1),
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super(D1, self).__init__()
# 256
self.conv1 = nn.Sequential(nn.Conv2d(nc,ndf,kernel_size=3,stride=1,padding=1),
nn.ELU(True))
# 256
self.conv2 = conv_block(ndf,ndf)
# 128
self.conv3 = conv_block(ndf, ndf*2)
# 64
self.conv4 = conv_block(ndf*2, ndf*3)
# 32
self.encode = nn.Conv2d(ndf*3, hidden_size, kernel_size=1,stride=1,padding=0)
self.decode = nn.Conv2d(hidden_size, ndf, kernel_size=1,stride=1,padding=0)
# 32
self.deconv4 = deconv_block(ndf, ndf)
# 64
self.deconv3 = deconv_block(ndf, ndf)
# 128
self.deconv2 = deconv_block(ndf, ndf)
# 256
self.deconv1 = nn.Sequential(nn.Conv2d(ndf,ndf,kernel_size=3,stride=1,padding=1),
nn.ELU(True),
nn.Conv2d(ndf,ndf,kernel_size=3,stride=1,padding=1),
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"""
self.deconv1 = nn.Sequential(nn.Conv2d(ndf,nc,kernel_size=3,stride=1,padding=1),
nn.Tanh())
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demisto/content | 5c664a65b992ac8ca90ac3f11b1b2cdf11ee9b07 | Packs/PassiveTotal/Integrations/PassiveTotal_v2/PassiveTotal_v2.py | python | get_host_attribute_context_data | (records: List[Dict[str, Any]]) | return standard_results, custom_ec | Prepares context data for get components and get trackers command
:param records: API response
:return: standard entry command results list and custom entry context | Prepares context data for get components and get trackers command | [
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] | def get_host_attribute_context_data(records: List[Dict[str, Any]]) -> Tuple[list, list]:
"""
Prepares context data for get components and get trackers command
:param records: API response
:return: standard entry command results list and custom entry context
"""
custom_ec = createContext(data=records, removeNull=True)
standard_results: List[CommandResults] = []
for record in records:
if record.get('hostname'):
hostname = record.get('hostname')
dbot_score = Common.DBotScore(indicator=hostname, indicator_type=DBotScoreType.DOMAIN,
integration_name=INTEGRATION_NAME, score=Common.DBotScore.NONE)
if auto_detect_indicator_type(hostname) == FeedIndicatorType.Domain:
domain_ioc = Common.Domain(domain=hostname, dbot_score=dbot_score)
# add standard output with standard readable output
standard_results.append(CommandResults(
indicator=domain_ioc,
readable_output=tableToMarkdown('', domain_ioc.to_context().get(Common.Domain.CONTEXT_PATH))
))
elif record.get('address'):
address = record.get('address')
dbot_score = Common.DBotScore(indicator=address, indicator_type=DBotScoreType.IP,
integration_name=INTEGRATION_NAME, score=Common.DBotScore.NONE)
if auto_detect_indicator_type(address) == FeedIndicatorType.IP:
ip_ioc = Common.IP(ip=address, dbot_score=dbot_score)
# add standard output with standard readable output
standard_results.append(CommandResults(
indicator=ip_ioc,
readable_output=tableToMarkdown('', ip_ioc.to_context().get(Common.IP.CONTEXT_PATH))
))
return standard_results, custom_ec | [
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xmunoz/sodapy | 8a815a7ac3f4d955f0ac7f9b525c8755584179b4 | sodapy/socrata.py | python | Socrata._perform_update | (self, method, resource, payload) | return response | Execute the update task. | Execute the update task. | [
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] | def _perform_update(self, method, resource, payload):
"""
Execute the update task.
"""
if isinstance(payload, (dict, list)):
response = self._perform_request(method, resource, data=json.dumps(payload))
elif isinstance(payload, IOBase):
headers = {
"content-type": "text/csv",
}
response = self._perform_request(
method, resource, data=payload, headers=headers
)
else:
raise Exception(
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kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python3-alpha/python-libs/gdata/docs/service.py | python | DocumentQuery.ToUri | (self) | return new_feed | Generates a URI from the query parameters set in the object.
Returns:
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"""Generates a URI from the query parameters set in the object.
Returns:
A string containing the URI used to retrieve entries from the Document
List feed.
"""
old_feed = self.feed
self.feed = '/'.join([old_feed, self.visibility, self.projection])
new_feed = gdata.service.Query.ToUri(self)
self.feed = old_feed
return new_feed | [
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dimagi/commcare-hq | d67ff1d3b4c51fa050c19e60c3253a79d3452a39 | corehq/form_processor/migrations/0036_cleanup_models.py | python | _alter_to_uuid_sql_forawd | (model, field) | return 'ALTER TABLE "form_processor_{model}" ALTER COLUMN "{field}" TYPE uuid USING {field}::uuid'.format(
model=model, field=field
) | [] | def _alter_to_uuid_sql_forawd(model, field):
return 'ALTER TABLE "form_processor_{model}" ALTER COLUMN "{field}" TYPE uuid USING {field}::uuid'.format(
model=model, field=field
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plkmo/BERT-Relation-Extraction | 06075620fccb044785f5fd319e8d06df9af15b50 | src/model/ALBERT/tokenization_albert.py | python | AlbertTokenizer.save_vocabulary | (self, save_directory) | return (out_vocab_file,) | Save the sentencepiece vocabulary (copy original file) and special tokens file
to a directory. | Save the sentencepiece vocabulary (copy original file) and special tokens file
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""" Save the sentencepiece vocabulary (copy original file) and special tokens file
to a directory.
"""
if not os.path.isdir(save_directory):
logger.error("Vocabulary path ({}) should be a directory".format(save_directory))
return
out_vocab_file = os.path.join(save_directory, VOCAB_FILES_NAMES["vocab_file"])
if os.path.abspath(self.vocab_file) != os.path.abspath(out_vocab_file):
copyfile(self.vocab_file, out_vocab_file)
return (out_vocab_file,) | [
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NaturalHistoryMuseum/inselect | 196a3ae2a0ed4e2c7cb667aaba9a6be1bcd90ca6 | inselect/gui/views/metadata.py | python | FormContainer._create_field_control | (self, field, template) | Returns a QWidget for editing field, validated using template | Returns a QWidget for editing field, validated using template | [
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"""
if 'countryCode' == field.name:
return CountryComboBox(template)
elif 'language' == field.name:
return LanguageComboBox(template)
elif field.fixed_value:
return FixedValueControl(field.fixed_value)
elif field.choices:
combo = ChoicesFieldComboBox(field.name, template,
labels=field.choices)
return combo
elif field.choices_with_data:
choices = field.choices_with_data
combo = ChoicesWithDataFieldComboBox(field.name, template,
labels=iter(choices.keys()),
values=iter(choices.values()))
return combo
else:
# Not using Qt's very restrictive QValidator scheme
edit = FieldEdit(field.name, template)
return edit | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/pysaml2-4.9.0/src/saml2/sigver.py | python | _make_vals | (val, klass, seccont, klass_inst=None, prop=None, part=False,
base64encode=False, elements_to_sign=None) | Creates a class instance with a specified value, the specified
class instance may be a value on a property in a defined class instance.
:param val: The value
:param klass: The value class
:param klass_inst: The class instance which has a property on which
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:param prop: The property which the value should be assigned to.
:param part: If the value is one of a possible list of values it should be
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:return: Value class instance | Creates a class instance with a specified value, the specified
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"""
Creates a class instance with a specified value, the specified
class instance may be a value on a property in a defined class instance.
:param val: The value
:param klass: The value class
:param klass_inst: The class instance which has a property on which
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:param prop: The property which the value should be assigned to.
:param part: If the value is one of a possible list of values it should be
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:return: Value class instance
"""
cinst = None
if isinstance(val, dict):
cinst = _instance(klass, val, seccont, base64encode=base64encode,
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else:
try:
cinst = klass().set_text(val)
except ValueError:
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cis = [
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setattr(klass_inst, prop, cis)
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raise
if part:
return cinst
else:
if cinst:
cis = [cinst]
setattr(klass_inst, prop, cis) | [
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/Xenotix Python Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/poplib.py | python | POP3.list | (self, which=None) | return self._longcmd('LIST') | Request listing, return result.
Result without a message number argument is in form
['response', ['mesg_num octets', ...], octets].
Result when a message number argument is given is a
single response: the "scan listing" for that message. | Request listing, return result. | [
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"""Request listing, return result.
Result without a message number argument is in form
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Result when a message number argument is given is a
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if which is not None:
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deeptools/deepTools | ac42d29c298c026aa0c53c9db2553087ebc86b97 | deeptools/multiBamSummary.py | python | main | (args=None) | 1. get read counts at different positions either
all of same length or from genomic regions from the BED file
2. save data for further plotting | 1. get read counts at different positions either
all of same length or from genomic regions from the BED file | [
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"""
1. get read counts at different positions either
all of same length or from genomic regions from the BED file
2. save data for further plotting
"""
args = process_args(args)
if 'BED' in args:
bed_regions = args.BED
else:
bed_regions = None
if len(args.bamfiles) == 1 and not (args.outRawCounts or args.scalingFactors):
sys.stderr.write("You've input a single BAM file and not specified "
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stepsize = args.binSize + args.distanceBetweenBins
c = countR.CountReadsPerBin(
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numberOfSamples=None,
genomeChunkSize=args.genomeChunkSize,
numberOfProcessors=args.numberOfProcessors,
verbose=args.verbose,
region=args.region,
bedFile=bed_regions,
blackListFileName=args.blackListFileName,
extendReads=args.extendReads,
minMappingQuality=args.minMappingQuality,
ignoreDuplicates=args.ignoreDuplicates,
center_read=args.centerReads,
samFlag_include=args.samFlagInclude,
samFlag_exclude=args.samFlagExclude,
minFragmentLength=args.minFragmentLength,
maxFragmentLength=args.maxFragmentLength,
stepSize=stepsize,
zerosToNans=False,
out_file_for_raw_data=args.outRawCounts)
num_reads_per_bin = c.run(allArgs=args)
sys.stderr.write("Number of bins "
"found: {}\n".format(num_reads_per_bin.shape[0]))
if num_reads_per_bin.shape[0] < 2:
exit("ERROR: too few non zero bins found.\n"
"If using --region please check that this "
"region is covered by reads.\n")
# numpy will append .npz to the file name if we don't do this...
if args.outFileName:
f = open(args.outFileName, "wb")
np.savez_compressed(f,
matrix=num_reads_per_bin,
labels=args.labels)
f.close()
if args.scalingFactors:
f = open(args.scalingFactors, 'w')
f.write("sample\tscalingFactor\n")
scalingFactors = countR.estimateSizeFactors(num_reads_per_bin)
for sample, scalingFactor in zip(args.labels, scalingFactors):
f.write("{}\t{:6.4f}\n".format(sample, scalingFactor))
f.close()
if args.outRawCounts:
# append to the generated file the
# labels
header = "#'chr'\t'start'\t'end'\t"
header += "'" + "'\t'".join(args.labels) + "'\n"
f = open(args.outRawCounts, 'r+')
content = f.read()
f.seek(0, 0)
f.write(header + content)
f.close() | [
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/nad/media_player.py | python | NAD.update | (self) | Retrieve latest state. | Retrieve latest state. | [
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ceph/ceph-ansible | 583e60af84180f0414d67ee52c3ec7cd64ddb4dd | library/radosgw_realm.py | python | pre_generate_radosgw_cmd | (container_image=None) | return cmd | Generate radosgw-admin prefix comaand | Generate radosgw-admin prefix comaand | [
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Generate radosgw-admin prefix comaand
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openai/imitation | 8a2ed905e2ac54bda0f71e5ee364e90568e6d031 | policyopt/thutil.py | python | categorical_kl | (logprobs1_B_A, logprobs2_B_A, name=None) | return kl_B | KL divergence between categorical distributions, specified as log probabilities | KL divergence between categorical distributions, specified as log probabilities | [
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'''KL divergence between categorical distributions, specified as log probabilities'''
kl_B = (tensor.exp(logprobs1_B_A) * (logprobs1_B_A - logprobs2_B_A)).sum(axis=1)
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hzy46/Deep-Learning-21-Examples | 15c2d9edccad090cd67b033f24a43c544e5cba3e | chapter_5/research/object_detection/utils/np_box_list.py | python | BoxList._is_valid_boxes | (self, data) | return True | Check whether data fullfills the format of N*[ymin, xmin, ymax, xmin].
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data: a numpy array of shape [N, 4] representing box coordinates
Returns:
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Args:
data: a numpy array of shape [N, 4] representing box coordinates
Returns:
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return True | [
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lxdock/lxdock | f71006d130bc8b53603eea36a546003495437493 | lxdock/logging.py | python | _AtleastErrorFilter.filter | (self, record) | return record.levelno >= logging.ERROR | [] | def filter(self, record):
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ajinabraham/OWASP-Xenotix-XSS-Exploit-Framework | cb692f527e4e819b6c228187c5702d990a180043 | external/Scripting Engine/packages/IronPython.StdLib.2.7.4/content/Lib/distutils/file_util.py | python | _copy_file_contents | (src, dst, buffer_size=16*1024) | Copy the file 'src' to 'dst'.
Both must be filenames. Any error opening either file, reading from
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"""Copy the file 'src' to 'dst'.
Both must be filenames. Any error opening either file, reading from
'src', or writing to 'dst', raises DistutilsFileError. Data is
read/written in chunks of 'buffer_size' bytes (default 16k). No attempt
is made to handle anything apart from regular files.
"""
# Stolen from shutil module in the standard library, but with
# custom error-handling added.
fsrc = None
fdst = None
try:
try:
fsrc = open(src, 'rb')
except os.error, (errno, errstr):
raise DistutilsFileError("could not open '%s': %s" % (src, errstr))
if os.path.exists(dst):
try:
os.unlink(dst)
except os.error, (errno, errstr):
raise DistutilsFileError(
"could not delete '%s': %s" % (dst, errstr))
try:
fdst = open(dst, 'wb')
except os.error, (errno, errstr):
raise DistutilsFileError(
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while 1:
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except os.error, (errno, errstr):
raise DistutilsFileError(
"could not write to '%s': %s" % (dst, errstr))
finally:
if fdst:
fdst.close()
if fsrc:
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snapcore/snapcraft | b81550376df7f2d0dfe65f7bfb006a3107252450 | snapcraft/cli/snapcraftctl/_runner.py | python | build | () | Run the 'build' step of the calling part's lifecycle | Run the 'build' step of the calling part's lifecycle | [
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VLSIDA/OpenRAM | f66aac3264598eeae31225c62b6a4af52412d407 | compiler/base/hierarchy_spice.py | python | spice.analytical_delay | (self, corner, slew, load=0.0) | return delay_data(corner_delay, corner_slew) | Inform users undefined delay module while building new modules | Inform users undefined delay module while building new modules | [
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] | def analytical_delay(self, corner, slew, load=0.0):
"""Inform users undefined delay module while building new modules"""
# FIXME: Slew is not used in the model right now.
# Can be added heuristically as linear factor
relative_cap = logical_effort.convert_farad_to_relative_c(load)
stage_effort = self.get_stage_effort(relative_cap)
# If it fails, then keep running with a valid object.
if not stage_effort:
return delay_data(0.0, 0.0)
abs_delay = stage_effort.get_absolute_delay()
corner_delay = self.apply_corners_analytically(abs_delay, corner)
SLEW_APPROXIMATION = 0.1
corner_slew = SLEW_APPROXIMATION * corner_delay
return delay_data(corner_delay, corner_slew) | [
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emcconville/wand | 03682680c351645f16c3b8ea23bde79fbb270305 | wand/image.py | python | BaseImage.histogram | (self) | return HistogramDict(self) | (:class:`HistogramDict`) The mapping that represents the histogram.
Keys are :class:`~wand.color.Color` objects, and values are
the number of pixels.
.. tip::
True-color photos can have millions of color values. If performance
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with Image(filename='hd_photo.jpg') as img:
img.quantize(255, 'RGB', 0, False, False)
hist = img.histogram
.. versionadded:: 0.3.0 | (:class:`HistogramDict`) The mapping that represents the histogram.
Keys are :class:`~wand.color.Color` objects, and values are
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/lib/django-1.2/django/db/models/sql/compiler.py | python | SQLCompiler.quote_name_unless_alias | (self, name) | return r | A wrapper around connection.ops.quote_name that doesn't quote aliases
for table names. This avoids problems with some SQL dialects that treat
quoted strings specially (e.g. PostgreSQL). | A wrapper around connection.ops.quote_name that doesn't quote aliases
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espnet/espnet | ea411f3f627b8f101c211e107d0ff7053344ac80 | espnet/nets/e2e_asr_common.py | python | ErrorCalculator.__call__ | (self, ys_hat, ys_pad, is_ctc=False) | return cer, wer | Calculate sentence-level WER/CER score.
:param torch.Tensor ys_hat: prediction (batch, seqlen)
:param torch.Tensor ys_pad: reference (batch, seqlen)
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:param torch.Tensor ys_pad: reference (batch, seqlen)
:param bool is_ctc: calculate CER score for CTC
:return: sentence-level WER score
:rtype float
:return: sentence-level CER score
:rtype float
"""
cer, wer = None, None
if is_ctc:
return self.calculate_cer_ctc(ys_hat, ys_pad)
elif not self.report_cer and not self.report_wer:
return cer, wer
seqs_hat, seqs_true = self.convert_to_char(ys_hat, ys_pad)
if self.report_cer:
cer = self.calculate_cer(seqs_hat, seqs_true)
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/proxy/v1/service/__init__.py | python | ServiceInstance.date_updated | (self) | return self._properties['date_updated'] | :returns: The ISO 8601 date and time in GMT when the resource was last updated
:rtype: datetime | :returns: The ISO 8601 date and time in GMT when the resource was last updated
:rtype: datetime | [
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/layout/geo/_lataxis.py | python | Lataxis.gridwidth | (self) | return self["gridwidth"] | Sets the graticule's stroke width (in px).
The 'gridwidth' property is a number and may be specified as:
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The 'gridwidth' property is a number and may be specified as:
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/flask/cli.py | python | find_app_by_string | (script_info, module, app_name) | Checks if the given string is a variable name or a function. If it is a
function, it checks for specified arguments and whether it takes a
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arguments. | Checks if the given string is a variable name or a function. If it is a
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raise
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/schemes/hyperelliptic_curves/hyperelliptic_finite_field.py | python | HyperellipticCurve_finite_field.Cartier_matrix | (self) | return M | r"""
INPUT:
- ``E`` : Hyperelliptic Curve of the form `y^2 = f(x)` over a finite field, `\GF{q}`
OUTPUT:
- ``M``: The matrix `M = (c_{pi-j})`, where `c_i` are the coefficients of `f(x)^{(p-1)/2} = \sum c_i x^i`
REFERENCES:
N. Yui. On the Jacobian varieties of hyperelliptic curves over fields of characteristic `p > 2`.
EXAMPLES::
sage: K.<x>=GF(9,'x')[]
sage: C=HyperellipticCurve(x^7-1,0)
sage: C.Cartier_matrix()
[0 0 2]
[0 0 0]
[0 1 0]
sage: K.<x>=GF(49,'x')[]
sage: C=HyperellipticCurve(x^5+1,0)
sage: C.Cartier_matrix()
[0 3]
[0 0]
sage: P.<x>=GF(9,'a')[]
sage: E=HyperellipticCurve(x^29+1,0)
sage: E.Cartier_matrix()
[0 0 1 0 0 0 0 0 0 0 0 0 0 0]
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[0 0 0 0 0 0 0 0 0 0 0 1 0 0]
[0 0 0 0 0 0 0 0 0 0 0 0 0 0]
[0 0 0 0 0 0 0 0 0 0 0 0 0 0]
[0 0 0 0 0 0 0 0 0 0 0 0 0 0]
[0 0 0 0 0 0 0 0 0 0 0 0 0 0]
[0 0 0 0 0 0 0 0 0 0 0 0 0 0]
[1 0 0 0 0 0 0 0 0 0 0 0 0 0]
[0 0 0 1 0 0 0 0 0 0 0 0 0 0]
[0 0 0 0 0 0 1 0 0 0 0 0 0 0]
[0 0 0 0 0 0 0 0 0 1 0 0 0 0]
[0 0 0 0 0 0 0 0 0 0 0 0 1 0]
TESTS::
sage: K.<x>=GF(2,'x')[]
sage: C=HyperellipticCurve(x^7-1,x)
sage: C.Cartier_matrix()
Traceback (most recent call last):
...
ValueError: p must be odd
sage: K.<x>=GF(5,'x')[]
sage: C=HyperellipticCurve(x^7-1,4)
sage: C.Cartier_matrix()
Traceback (most recent call last):
...
ValueError: E must be of the form y^2 = f(x)
sage: K.<x>=GF(5,'x')[]
sage: C=HyperellipticCurve(x^8-1,0)
sage: C.Cartier_matrix()
Traceback (most recent call last):
...
ValueError: In this implementation the degree of f must be odd
sage: K.<x>=GF(5,'x')[]
sage: C=HyperellipticCurve(x^5+1,0,check_squarefree=False)
sage: C.Cartier_matrix()
Traceback (most recent call last):
...
ValueError: curve is not smooth | r"""
INPUT: | [
"r",
"INPUT",
":"
] | def Cartier_matrix(self):
r"""
INPUT:
- ``E`` : Hyperelliptic Curve of the form `y^2 = f(x)` over a finite field, `\GF{q}`
OUTPUT:
- ``M``: The matrix `M = (c_{pi-j})`, where `c_i` are the coefficients of `f(x)^{(p-1)/2} = \sum c_i x^i`
REFERENCES:
N. Yui. On the Jacobian varieties of hyperelliptic curves over fields of characteristic `p > 2`.
EXAMPLES::
sage: K.<x>=GF(9,'x')[]
sage: C=HyperellipticCurve(x^7-1,0)
sage: C.Cartier_matrix()
[0 0 2]
[0 0 0]
[0 1 0]
sage: K.<x>=GF(49,'x')[]
sage: C=HyperellipticCurve(x^5+1,0)
sage: C.Cartier_matrix()
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sage: P.<x>=GF(9,'a')[]
sage: E=HyperellipticCurve(x^29+1,0)
sage: E.Cartier_matrix()
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TESTS::
sage: K.<x>=GF(2,'x')[]
sage: C=HyperellipticCurve(x^7-1,x)
sage: C.Cartier_matrix()
Traceback (most recent call last):
...
ValueError: p must be odd
sage: K.<x>=GF(5,'x')[]
sage: C=HyperellipticCurve(x^7-1,4)
sage: C.Cartier_matrix()
Traceback (most recent call last):
...
ValueError: E must be of the form y^2 = f(x)
sage: K.<x>=GF(5,'x')[]
sage: C=HyperellipticCurve(x^8-1,0)
sage: C.Cartier_matrix()
Traceback (most recent call last):
...
ValueError: In this implementation the degree of f must be odd
sage: K.<x>=GF(5,'x')[]
sage: C=HyperellipticCurve(x^5+1,0,check_squarefree=False)
sage: C.Cartier_matrix()
Traceback (most recent call last):
...
ValueError: curve is not smooth
"""
#checking first that Cartier matrix is not already cached. Since
#it can be called by either Hasse_Witt or a_number.
#This way it does not matter which function is called first
#in the code.
# Trac Ticket #11115: Why shall we waste time by studying
# the cache manually? We only need to check whether the cached
# data belong to self.
M, Coeffs,g, Fq, p, E= self._Cartier_matrix_cached()
if E!=self:
self._Cartier_matrix_cached.clear_cache()
M, Coeffs,g, Fq, p, E= self._Cartier_matrix_cached()
return M | [
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mtianyan/VueDjangoAntdProBookShop | fd8fa2151c81edde2f8b8e6df8e1ddd799f940c2 | third_party/social_core/storage.py | python | UserMixin.user_exists | (cls, *args, **kwargs) | Return True/False if a User instance exists with the given arguments.
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benedekrozemberczki/littleballoffur | dbfec92c0ead8c5da134c9aead7987c7a36234b4 | littleballoffur/edge_sampling/randomedgesamplerwithpartialinduction.py | python | RandomEdgeSamplerWithPartialInduction.sample | (self, graph: Union[NXGraph, NKGraph]) | return new_graph | Sampling edges randomly with partial induction.
Arg types:
* **graph** *(NetworkX or NetworKit graph)* - The graph to be sampled from.
Return types:
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"""
Sampling edges randomly with partial induction.
Arg types:
* **graph** *(NetworkX or NetworKit graph)* - The graph to be sampled from.
Return types:
* **new_graph** *(NetworkX or NetworKit graph)* - The graph of sampled edges.
"""
self._deploy_backend(graph)
self._create_initial_set(graph)
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m-rtijn/mpu6050 | 0626053a5e1182f4951b78b8326691a9223a5f7d | mpu6050/mpu6050.py | python | mpu6050.set_filter_range | (self, filter_range=FILTER_BW_256) | return self.bus.write_byte_data(self.address, self.MPU_CONFIG, EXT_SYNC_SET | filter_range) | Sets the low-pass bandpass filter frequency | Sets the low-pass bandpass filter frequency | [
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moloch--/RootTheBox | 097272332b9f9b7e2df31ca0823ed10c7b66ac81 | models/WallOfSheep.py | python | WallOfSheep.by_victim_id | (cls, _id) | return dbsession.query(cls).filter_by(victim_id=_id).all() | Returns all entries for a _id | Returns all entries for a _id | [
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marcua/tweeql | eb8c61fb001e0b9755929f3b19be9fa16358187e | old/redis/client.py | python | Redis.sunion | (self, keys, *args) | return self.format_inline('SUNION', *keys) | Return the union of sets specifiued by ``keys`` | Return the union of sets specifiued by ``keys`` | [
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axnsan12/drf-yasg | d9700dbf8cc80d725a7db485c2d4446c19c29840 | src/drf_yasg/codecs.py | python | _OpenAPICodec.generate_swagger_object | (self, swagger) | return swagger.as_odict() | Generates the root Swagger object.
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google/coursebuilder-core | 08f809db3226d9269e30d5edd0edd33bd22041f4 | coursebuilder/models/models.py | python | StudentPreferencesDTO.show_hooks | (self) | return self.dict.get('show_hooks', True) | Show controls to permit editing of HTML inclusions (hook points).
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openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/Django/django/utils/dateformat.py | python | DateFormat.Y | (self) | return self.data.year | Year, 4 digits; e.g. '1999 | Year, 4 digits; e.g. '1999 | [
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BerkeleyAutomation/meshrender | 25b6fb711ef7a7871a5908459e6be5c76a04b631 | meshrender/viewer.py | python | SceneViewer._load_shaders | (self, vertex_shader, fragment_shader) | return shader | Load and compile shaders from strings. | Load and compile shaders from strings. | [
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"""
shader = shaders.compileProgram(
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deepinsight/insightface | c0b25f998a649f662c7136eb389abcacd7900e9d | python-package/insightface/thirdparty/face3d/morphable_model/morphabel_model.py | python | MorphabelModel.fit | (self, x, X_ind, max_iter = 4, isShow = False) | return fitted_sp, fitted_ep, s, angles, t | fit 3dmm & pose parameters
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x: (n, 2) image points
X_ind: (n,) corresponding Model vertex indices
max_iter: iteration
isShow: whether to reserve middle results for show
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fitted_sp: (n_sp, 1). shape parameters
fitted_ep: (n_ep, 1). exp parameters
s, angles, t | fit 3dmm & pose parameters
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x: (n, 2) image points
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max_iter: iteration
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graphql-python/graphql-core | 9ea9c3705d6826322027d9bb539d37c5b25f7af9 | src/graphql/language/parser.py | python | Parser.parse_argument_defs | (self) | return self.optional_many(
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KDD-OpenSource/DeepADoTS | 88c38320141a1062301cc9255f3e0fc111f55e80 | src/evaluation/evaluator.py | python | Evaluator.threshold | (self, score) | return np.nanmean(score) + 2 * np.nanstd(score) | [] | def threshold(self, score):
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Tautulli/Tautulli | 2410eb33805aaac4bd1c5dad0f71e4f15afaf742 | lib/dns/rdtypes/dsbase.py | python | DSBase.to_text | (self, origin=None, relativize=True, **kw) | return '%d %d %d %s' % (self.key_tag, self.algorithm,
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iclavera/learning_to_adapt | bd7d99ba402521c96631e7d09714128f549db0f1 | learning_to_adapt/envs/mujoco_env.py | python | MujocoEnv.get_current_obs | (self) | return self._get_full_obs() | [] | def get_current_obs(self):
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CedricGuillemet/Imogen | ee417b42747ed5b46cb11b02ef0c3630000085b3 | bin/Lib/lib2to3/btm_utils.py | python | get_characteristic_subpattern | (subpatterns) | return max(subpatterns, key=len) | Picks the most characteristic from a list of linear patterns
Current order used is:
names > common_names > common_chars | Picks the most characteristic from a list of linear patterns
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"""
if not isinstance(subpatterns, list):
return subpatterns
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subpatterns_with_names = []
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common_names = ['in', 'for', 'if' , 'not', 'None']
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subpatterns = subpatterns_with_common_names
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subpatterns = subpatterns_with_common_chars
# of the remaining subpatterns pick out the longest one
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javayhu/Gank-Alfred-Workflow | aca39bd0c7bc0c494eee204e10bca61dab760ab7 | source/workflow/workflow.py | python | Workflow._call_security | (self, action, service, account, *args) | return output | Call the ``security`` CLI app that provides access to keychains.
May raise `PasswordNotFound`, `PasswordExists` or `KeychainError`
exceptions (the first two are subclasses of `KeychainError`).
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"""Call the ``security`` CLI app that provides access to keychains.
May raise `PasswordNotFound`, `PasswordExists` or `KeychainError`
exceptions (the first two are subclasses of `KeychainError`).
:param action: The ``security`` action to call, e.g.
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:type action: ``unicode``
:param service: Name of the service.
:type service: ``unicode``
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:type account: ``unicode``
:param password: the password to secure
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cmd = ['security', action, '-s', service, '-a', account] + list(args)
p = subprocess.Popen(cmd, stdout=subprocess.PIPE,
stderr=subprocess.STDOUT)
retcode, output = p.wait(), p.stdout.read().strip().decode('utf-8')
if retcode == 44: # password does not exist
raise PasswordNotFound()
elif retcode == 45: # password already exists
raise PasswordExists()
elif retcode > 0:
err = KeychainError('Unknown Keychain error : %s' % output)
err.retcode = retcode
raise err
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keon/algorithms | 23d4e85a506eaeaff315e855be12f8dbe47a7ec3 | algorithms/map/hashtable.py | python | ResizableHashTable.__init__ | (self) | [] | def __init__(self):
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kubernetes-client/python | 47b9da9de2d02b2b7a34fbe05afb44afd130d73a | kubernetes/client/api/core_api.py | python | CoreApi.get_api_versions_with_http_info | (self, **kwargs) | return self.api_client.call_api(
'/api/', 'GET',
path_params,
query_params,
header_params,
body=body_params,
post_params=form_params,
files=local_var_files,
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collection_formats=collection_formats) | get_api_versions # noqa: E501
get available API versions # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_api_versions_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
:return: tuple(V1APIVersions, status_code(int), headers(HTTPHeaderDict))
If the method is called asynchronously,
returns the request thread. | get_api_versions # noqa: E501 | [
"get_api_versions",
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":",
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] | def get_api_versions_with_http_info(self, **kwargs): # noqa: E501
"""get_api_versions # noqa: E501
get available API versions # noqa: E501
This method makes a synchronous HTTP request by default. To make an
asynchronous HTTP request, please pass async_req=True
>>> thread = api.get_api_versions_with_http_info(async_req=True)
>>> result = thread.get()
:param async_req bool: execute request asynchronously
:param _return_http_data_only: response data without head status code
and headers
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
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:return: tuple(V1APIVersions, status_code(int), headers(HTTPHeaderDict))
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returns the request thread.
"""
local_var_params = locals()
all_params = [
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all_params.extend(
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for key, val in six.iteritems(local_var_params['kwargs']):
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)
local_var_params[key] = val
del local_var_params['kwargs']
collection_formats = {}
path_params = {}
query_params = []
header_params = {}
form_params = []
local_var_files = {}
body_params = None
# HTTP header `Accept`
header_params['Accept'] = self.api_client.select_header_accept(
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# Authentication setting
auth_settings = ['BearerToken'] # noqa: E501
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Source-Python-Dev-Team/Source.Python | d0ffd8ccbd1e9923c9bc44936f20613c1c76b7fb | addons/source-python/Python3/_pydecimal.py | python | Decimal.__rfloordiv__ | (self, other, context=None) | return other.__floordiv__(self, context=context) | Swaps self/other and returns __floordiv__. | Swaps self/other and returns __floordiv__. | [
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other = _convert_other(other)
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microsoft/debugpy | be8dd607f6837244e0b565345e497aff7a0c08bf | src/debugpy/_vendored/pydevd/_pydevd_bundle/pydevd_api.py | python | PyDevdAPI.reapply_breakpoints | (self, py_db) | Reapplies all the received breakpoints as they were received by the API (so, new
translations are applied). | Reapplies all the received breakpoints as they were received by the API (so, new
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Reapplies all the received breakpoints as they were received by the API (so, new
translations are applied).
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pydev_log.debug('Reapplying breakpoints.')
items = dict_items(py_db.api_received_breakpoints) # Create a copy with items to reapply.
self.remove_all_breakpoints(py_db, '*')
for _key, val in items:
_new_filename, api_add_breakpoint_params = val
self.add_breakpoint(py_db, *api_add_breakpoint_params) | [
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angeladai/ScanComplete | 7ab7b48e5688b3b71c99bdb64b3424e06b064312 | src/reader.py | python | ReadSceneBlocksLevel | (data_filepattern,
train_samples,
dim_block,
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is_base_level,
hierarchy_level,
num_quant_levels,
params,
quantize=False,
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num_epochs=None) | return (input_blocks, target_blocks, target_sem_blocks, target_lo_blocks,
target_sem_lo_blocks) | Reads a batch of block examples from the SSTable files.
Args:
data_filepattern: String matching input files.
train_samples: Train on previous model predictions.
dim_block: x/z dimension of train block.
height_block: y dimension of train block.
stored_dim_block: Stored data x/z dimension (high-resolution).
stored_height_block: Stored data y dimension (high-resolution).
is_base_level: Whether there are no previous hierarchy levels.
hierarchy_level: hierarchy level (1 is finest).
num_quant_levels: Number of quantization bins (if used).
params: Parameter dictionary.
quantize: Whether to quantize data.
shuffle: Whether to shuffle.
num_epochs: Number of times to go over the input.
Returns:
5-D tensor input batches of shape
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tf.float32.
5-D tensor target batches of shape
[batch_size, dim_target, height_target, dim_target, 2], dtype
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5-D tensor target semantics batches of shape
[batch_size, dim_target, height_target, dim_target], dtype tf.uint8.
(optionally) 5-D tensor low-resolution target batches of shape
[batch_size, dim_target//2, height_target//2, dim_target//2, 2], dtype
tf.float32.
(optionally) 5-D tensor low-resolution target semantics batches of shape
[batch_size, dim_target//2, height_target//2, dim_target//2], dtype
tf.uint8. | Reads a batch of block examples from the SSTable files. | [
"Reads",
"a",
"batch",
"of",
"block",
"examples",
"from",
"the",
"SSTable",
"files",
"."
] | def ReadSceneBlocksLevel(data_filepattern,
train_samples,
dim_block,
height_block,
stored_dim_block,
stored_height_block,
is_base_level,
hierarchy_level,
num_quant_levels,
params,
quantize=False,
shuffle=True,
num_epochs=None):
"""Reads a batch of block examples from the SSTable files.
Args:
data_filepattern: String matching input files.
train_samples: Train on previous model predictions.
dim_block: x/z dimension of train block.
height_block: y dimension of train block.
stored_dim_block: Stored data x/z dimension (high-resolution).
stored_height_block: Stored data y dimension (high-resolution).
is_base_level: Whether there are no previous hierarchy levels.
hierarchy_level: hierarchy level (1 is finest).
num_quant_levels: Number of quantization bins (if used).
params: Parameter dictionary.
quantize: Whether to quantize data.
shuffle: Whether to shuffle.
num_epochs: Number of times to go over the input.
Returns:
5-D tensor input batches of shape
[batch_size, dim_input, height_input, dim_input, 2], dtype
tf.float32.
5-D tensor target batches of shape
[batch_size, dim_target, height_target, dim_target, 2], dtype
tf.float32.
5-D tensor target semantics batches of shape
[batch_size, dim_target, height_target, dim_target], dtype tf.uint8.
(optionally) 5-D tensor low-resolution target batches of shape
[batch_size, dim_target//2, height_target//2, dim_target//2, 2], dtype
tf.float32.
(optionally) 5-D tensor low-resolution target semantics batches of shape
[batch_size, dim_target//2, height_target//2, dim_target//2], dtype
tf.uint8.
"""
assert (stored_dim_block >= dim_block and
stored_height_block >= height_block)
read_target_lo = not is_base_level
_, examples, samples_lo, samples_sem_lo = _ReadBlockExample(
data_filepattern,
train_samples=train_samples,
hierarchy_level=hierarchy_level,
is_base_level=is_base_level,
shuffle=shuffle,
num_epochs=num_epochs,
stored_dim_block=stored_dim_block,
stored_height_block=stored_height_block)
# jitter height (must be even)
jitter = (np.random.random_integers(
low=0, high=_HEIGHT_JITTER[hierarchy_level - 1]) // 2) * 2
# extract relevant portion of data block as per input/target dim
key_input = _RESOLUTIONS[hierarchy_level - 1] + '_' + _INPUT_FEATURE
key_target = _RESOLUTIONS[hierarchy_level - 1] + '_' + _TARGET_FEATURE
key_target_sem = _RESOLUTIONS[hierarchy_level - 1] + '_' + _TARGET_SEM_FEATURE
#key_input = 'input_sdf'
#key_target = 'target_df'
#key_target_sem = 'target_sem'
input_sdf_blocks = examples[key_input]
input_sdf_blocks = preprocessor.extract_block(
input_sdf_blocks, dim_block, height_block, dim_block, 1, jitter)
input_blocks = preprocessor.preprocess_sdf(input_sdf_blocks,
constants.TRUNCATION)
target_df_blocks = examples[key_target]
target_df_blocks = preprocessor.extract_block(
target_df_blocks, dim_block, height_block, dim_block, 1, jitter)
target_blocks = preprocessor.preprocess_target_sdf(
target_df_blocks, num_quant_levels, constants.TRUNCATION, quantize)
if read_target_lo:
if train_samples:
target_lo_blocks = samples_lo
else:
key_target_lo = _RESOLUTIONS[hierarchy_level] + '_' + _TARGET_FEATURE
target_lo_blocks = examples[key_target_lo]
target_lo_blocks = preprocessor.extract_block(
target_lo_blocks, dim_block // 2, height_block // 2, dim_block // 2, 1,
jitter // 2)
target_lo_blocks = preprocessor.preprocess_target_sdf(
target_lo_blocks, num_quant_levels, constants.TRUNCATION, quantize)
target_sem_blocks = tf.decode_raw(examples[key_target_sem], tf.uint8)
target_sem_blocks = tf.reshape(
target_sem_blocks,
[stored_dim_block, stored_height_block, stored_dim_block])
target_sem_blocks = preprocessor.extract_block(
target_sem_blocks, dim_block, height_block, dim_block, 1, jitter)
target_sem_blocks = preprocessor.preprocess_target_sem(target_sem_blocks)
if read_target_lo:
if train_samples:
target_sem_lo_blocks = tf.decode_raw(samples_sem_lo, tf.uint8)
else:
key_target_sem_lo = (
_RESOLUTIONS[hierarchy_level] + '_' + _TARGET_SEM_FEATURE)
target_sem_lo_blocks = tf.decode_raw(examples[key_target_sem_lo],
tf.uint8)
target_sem_lo_blocks = tf.reshape(target_sem_lo_blocks, [
stored_dim_block // 2, stored_height_block // 2, stored_dim_block // 2
])
target_sem_lo_blocks = preprocessor.extract_block(
target_sem_lo_blocks, dim_block // 2, height_block // 2, dim_block // 2,
1, jitter // 2)
if not train_samples:
target_sem_lo_blocks = preprocessor.preprocess_target_sem(
target_sem_lo_blocks)
blocks = [input_blocks, target_blocks, target_sem_blocks]
if read_target_lo:
blocks.append(target_lo_blocks)
blocks.append(target_sem_lo_blocks)
if shuffle:
batched = tf.train.shuffle_batch(
blocks,
batch_size=params['batch_size'],
num_threads=64,
capacity=params['batch_size'] * 100,
min_after_dequeue=params['batch_size'] * 4)
else:
batched = tf.train.batch(
blocks,
batch_size=params['batch_size'],
num_threads=16,
capacity=params['batch_size'])
input_blocks = batched[0]
target_blocks = batched[1]
target_sem_blocks = batched[2]
target_lo_blocks = None
target_sem_lo_blocks = None
if read_target_lo:
target_lo_blocks = batched[3]
target_sem_lo_blocks = batched[4]
return (input_blocks, target_blocks, target_sem_blocks, target_lo_blocks,
target_sem_lo_blocks) | [
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wistbean/learn_python3_spider | 73c873f4845f4385f097e5057407d03dd37a117b | stackoverflow/venv/lib/python3.6/site-packages/lxml/html/html5parser.py | python | fromstring | (html, guess_charset=None, parser=None) | return body | Parse the html, returning a single element/document.
This tries to minimally parse the chunk of text, without knowing if it
is a fragment or a document.
'base_url' will set the document's base_url attribute (and the tree's
docinfo.URL)
If `guess_charset` is true, or if the input is not Unicode but a
byte string, the `chardet` library will perform charset guessing
on the string. | Parse the html, returning a single element/document. | [
"Parse",
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"single",
"element",
"/",
"document",
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] | def fromstring(html, guess_charset=None, parser=None):
"""Parse the html, returning a single element/document.
This tries to minimally parse the chunk of text, without knowing if it
is a fragment or a document.
'base_url' will set the document's base_url attribute (and the tree's
docinfo.URL)
If `guess_charset` is true, or if the input is not Unicode but a
byte string, the `chardet` library will perform charset guessing
on the string.
"""
if not isinstance(html, _strings):
raise TypeError('string required')
doc = document_fromstring(html, parser=parser,
guess_charset=guess_charset)
# document starts with doctype or <html>, full document!
start = html[:50]
if isinstance(start, bytes):
# Allow text comparison in python3.
# Decode as ascii, that also covers latin-1 and utf-8 for the
# characters we need.
start = start.decode('ascii', 'replace')
start = start.lstrip().lower()
if start.startswith('<html') or start.startswith('<!doctype'):
return doc
head = _find_tag(doc, 'head')
# if the head is not empty we have a full document
if len(head):
return doc
body = _find_tag(doc, 'body')
# The body has just one element, so it was probably a single
# element passed in
if (len(body) == 1 and (not body.text or not body.text.strip())
and (not body[-1].tail or not body[-1].tail.strip())):
return body[0]
# Now we have a body which represents a bunch of tags which have the
# content that was passed in. We will create a fake container, which
# is the body tag, except <body> implies too much structure.
if _contains_block_level_tag(body):
body.tag = 'div'
else:
body.tag = 'span'
return body | [
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ijkguo/mx-rcnn | e556bb4e0209c2ce55386be8f701115538c3f010 | symimdb/coco.py | python | coco._write_coco_results | (self, _coco, detections) | example results
[{"image_id": 42,
"category_id": 18,
"bbox": [258.15,41.29,348.26,243.78],
"score": 0.236}, ...] | example results
[{"image_id": 42,
"category_id": 18,
"bbox": [258.15,41.29,348.26,243.78],
"score": 0.236}, ...] | [
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"]",
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"0",
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"}",
"...",
"]"
] | def _write_coco_results(self, _coco, detections):
""" example results
[{"image_id": 42,
"category_id": 18,
"bbox": [258.15,41.29,348.26,243.78],
"score": 0.236}, ...]
"""
cats = [cat['name'] for cat in _coco.loadCats(_coco.getCatIds())]
class_to_coco_ind = dict(zip(cats, _coco.getCatIds()))
results = []
for cls_ind, cls in enumerate(self.classes):
if cls == '__background__':
continue
logger.info('collecting %s results (%d/%d)' % (cls, cls_ind, self.num_classes - 1))
coco_cat_id = class_to_coco_ind[cls]
results.extend(self._coco_results_one_category(detections[cls_ind], coco_cat_id))
logger.info('writing results json to %s' % self._result_file)
with open(self._result_file, 'w') as f:
json.dump(results, f, sort_keys=True, indent=4) | [
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garethdmm/gryphon | 73e19fa2d0b64c3fc7dac9e0036fc92e25e5b694 | gryphon/lib/assets.py | python | transaction_position_query | (db, amount_field, currency_field, transaction_type=None, start_time=None, end_time=None, include_pending=False, exchange_ids=[]) | return query_result_to_position(result) | This sums up a transaction Money field which can have multiple currencies.
Takes an optional transaction_type to filter on deposits or withdrawals
Returns a multi-currency Position object | This sums up a transaction Money field which can have multiple currencies. | [
"This",
"sums",
"up",
"a",
"transaction",
"Money",
"field",
"which",
"can",
"have",
"multiple",
"currencies",
"."
] | def transaction_position_query(db, amount_field, currency_field, transaction_type=None, start_time=None, end_time=None, include_pending=False, exchange_ids=[]):
"""
This sums up a transaction Money field which can have multiple currencies.
Takes an optional transaction_type to filter on deposits or withdrawals
Returns a multi-currency Position object
"""
# See comment on trade_position_query above
query = db.query(currency_field, func.sum(amount_field))
if include_pending:
query = query.filter(or_(
Transaction.transaction_status == Transaction.COMPLETED,
Transaction.transaction_status == Transaction.IN_TRANSIT,
))
else:
query = query.filter(Transaction.transaction_status == Transaction.COMPLETED)
if transaction_type:
query = query.filter(Transaction.transaction_type == transaction_type)
if start_time:
# when include_pending is True we treat all transactions as being completed
# on their creation time (i.e. instantly)
if include_pending:
query = query.filter(Transaction.time_created > start_time)
else:
query = query.filter(or_(
and_(
Transaction.time_completed != None,
Transaction.time_completed > start_time,
),
and_(
Transaction.time_completed == None,
Transaction.time_created > start_time,
),
))
if end_time:
if include_pending:
query = query.filter(Transaction.time_created <= end_time)
else:
# We include transactions in the ledger based on when they were completed,
# not created. This is an issue because we only started recording
# time_completed on 2015-10-08. So for these pre-time_completed
# transactions we use their time_created instead.
query = query.filter(or_(
and_(
Transaction.time_completed != None,
Transaction.time_completed <= end_time,
),
and_(
Transaction.time_completed == None,
Transaction.time_created <= end_time,
),
))
if exchange_ids:
query = query.filter(Transaction.exchange_id.in_(exchange_ids))
query = query.group_by(currency_field)
result = query.all()
return query_result_to_position(result) | [
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... | https://github.com/garethdmm/gryphon/blob/73e19fa2d0b64c3fc7dac9e0036fc92e25e5b694/gryphon/lib/assets.py#L325-L390 | |
tenpy/tenpy | bbdd3dbbdb511948eb0e6ba7ff619ac6ca657fff | tenpy/networks/site.py | python | Site.multiply_operators | (self, operators) | return op | Multiply local operators (possibly given by their names) together.
Parameters
----------
operators : list of {str | :class:`~tenpy.linalg.np_conserved.Array`}
List of valid operator names (to be translated with :meth:`get_op`) or
directly on-site operators in the form of npc arrays with ``'p', 'p*'`` label.
The operators are multiplied left-to-right.
Returns
-------
combined_operator : :class:`~tenpy.linalg.np_conserved.Array`
The product of the given `operators` in a left-to-right multiplication following the
usual mathematical convention. For example, if ``operators=['Sz', 'Sp', 'Sx']``,
the final operator is equivalent to ``site.get_op('Sz Sp Sx')``, with the ``'Sx'``
operator acting first on any physical state. | Multiply local operators (possibly given by their names) together. | [
"Multiply",
"local",
"operators",
"(",
"possibly",
"given",
"by",
"their",
"names",
")",
"together",
"."
] | def multiply_operators(self, operators):
"""Multiply local operators (possibly given by their names) together.
Parameters
----------
operators : list of {str | :class:`~tenpy.linalg.np_conserved.Array`}
List of valid operator names (to be translated with :meth:`get_op`) or
directly on-site operators in the form of npc arrays with ``'p', 'p*'`` label.
The operators are multiplied left-to-right.
Returns
-------
combined_operator : :class:`~tenpy.linalg.np_conserved.Array`
The product of the given `operators` in a left-to-right multiplication following the
usual mathematical convention. For example, if ``operators=['Sz', 'Sp', 'Sx']``,
the final operator is equivalent to ``site.get_op('Sz Sp Sx')``, with the ``'Sx'``
operator acting first on any physical state.
"""
if len(operators) == 0:
return self.Id
op = operators[0]
if isinstance(op, str):
op = self.get_op(op)
for next_op in operators[1:]:
if isinstance(next_op, str):
next_op = self.get_op(next_op)
op = npc.tensordot(op, next_op, axes=['p*', 'p'])
return op | [
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jython/jython3 | def4f8ec47cb7a9c799ea4c745f12badf92c5769 | lib-python/3.5.1/http/client.py | python | HTTPMessage.getallmatchingheaders | (self, name) | return lst | Find all header lines matching a given header name.
Look through the list of headers and find all lines matching a given
header name (and their continuation lines). A list of the lines is
returned, without interpretation. If the header does not occur, an
empty list is returned. If the header occurs multiple times, all
occurrences are returned. Case is not important in the header name. | Find all header lines matching a given header name. | [
"Find",
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] | def getallmatchingheaders(self, name):
"""Find all header lines matching a given header name.
Look through the list of headers and find all lines matching a given
header name (and their continuation lines). A list of the lines is
returned, without interpretation. If the header does not occur, an
empty list is returned. If the header occurs multiple times, all
occurrences are returned. Case is not important in the header name.
"""
name = name.lower() + ':'
n = len(name)
lst = []
hit = 0
for line in self.keys():
if line[:n].lower() == name:
hit = 1
elif not line[:1].isspace():
hit = 0
if hit:
lst.append(line)
return lst | [
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aws/sagemaker-python-sdk | 9d259b316f7f43838c16f35c10e98a110b56735b | src/sagemaker/tensorflow/model.py | python | TensorFlowPredictor.regress | (self, data) | return self._classify_or_regress(data, "regress") | Placeholder docstring. | Placeholder docstring. | [
"Placeholder",
"docstring",
"."
] | def regress(self, data):
"""Placeholder docstring."""
return self._classify_or_regress(data, "regress") | [
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scikit-video/scikit-video | 87c7113a84b50679d9853ba81ba34b557f516b05 | skvideo/utils/xmltodict.py | python | parse | (xml_input, encoding=None, expat=expat, process_namespaces=False,
namespace_separator=':', **kwargs) | return handler.item | Parse the given XML input and convert it into a dictionary.
`xml_input` can either be a `string` or a file-like object.
If `xml_attribs` is `True`, element attributes are put in the dictionary
among regular child elements, using `@` as a prefix to avoid collisions. If
set to `False`, they are just ignored.
Simple example::
>>> import xmltodict
>>> doc = xmltodict.parse(\"\"\"
... <a prop="x">
... <b>1</b>
... <b>2</b>
... </a>
... \"\"\")
>>> doc['a']['@prop']
u'x'
>>> doc['a']['b']
[u'1', u'2']
If `item_depth` is `0`, the function returns a dictionary for the root
element (default behavior). Otherwise, it calls `item_callback` every time
an item at the specified depth is found and returns `None` in the end
(streaming mode).
The callback function receives two parameters: the `path` from the document
root to the item (name-attribs pairs), and the `item` (dict). If the
callback's return value is false-ish, parsing will be stopped with the
:class:`ParsingInterrupted` exception.
Streaming example::
>>> def handle(path, item):
... print 'path:%s item:%s' % (path, item)
... return True
...
>>> xmltodict.parse(\"\"\"
... <a prop="x">
... <b>1</b>
... <b>2</b>
... </a>\"\"\", item_depth=2, item_callback=handle)
path:[(u'a', {u'prop': u'x'}), (u'b', None)] item:1
path:[(u'a', {u'prop': u'x'}), (u'b', None)] item:2
The optional argument `postprocessor` is a function that takes `path`,
`key` and `value` as positional arguments and returns a new `(key, value)`
pair where both `key` and `value` may have changed. Usage example::
>>> def postprocessor(path, key, value):
... try:
... return key + ':int', int(value)
... except (ValueError, TypeError):
... return key, value
>>> xmltodict.parse('<a><b>1</b><b>2</b><b>x</b></a>',
... postprocessor=postprocessor)
OrderedDict([(u'a', OrderedDict([(u'b:int', [1, 2]), (u'b', u'x')]))])
You can pass an alternate version of `expat` (such as `defusedexpat`) by
using the `expat` parameter. E.g:
>>> import defusedexpat
>>> xmltodict.parse('<a>hello</a>', expat=defusedexpat.pyexpat)
OrderedDict([(u'a', u'hello')])
You can use the force_list argument to force lists to be created even
when there is only a single child of a given level of hierarchy. The
force_list argument is a tuple of keys. If the key for a given level
of hierarchy is in the force_list argument, that level of hierarchy
will have a list as a child (even if there is only one sub-element).
The index_keys operation takes precendence over this. This is applied
after any user-supplied postprocessor has already run.
For example, given this input:
<servers>
<server>
<name>host1</name>
<os>Linux</os>
<interfaces>
<interface>
<name>em0</name>
<ip_address>10.0.0.1</ip_address>
</interface>
</interfaces>
</server>
</servers>
If called with force_list=('interface',), it will produce
this dictionary:
{'servers':
{'server':
{'name': 'host1',
'os': 'Linux'},
'interfaces':
{'interface':
[ {'name': 'em0', 'ip_address': '10.0.0.1' } ] } } } | Parse the given XML input and convert it into a dictionary. | [
"Parse",
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"given",
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"and",
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"it",
"into",
"a",
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] | def parse(xml_input, encoding=None, expat=expat, process_namespaces=False,
namespace_separator=':', **kwargs):
"""Parse the given XML input and convert it into a dictionary.
`xml_input` can either be a `string` or a file-like object.
If `xml_attribs` is `True`, element attributes are put in the dictionary
among regular child elements, using `@` as a prefix to avoid collisions. If
set to `False`, they are just ignored.
Simple example::
>>> import xmltodict
>>> doc = xmltodict.parse(\"\"\"
... <a prop="x">
... <b>1</b>
... <b>2</b>
... </a>
... \"\"\")
>>> doc['a']['@prop']
u'x'
>>> doc['a']['b']
[u'1', u'2']
If `item_depth` is `0`, the function returns a dictionary for the root
element (default behavior). Otherwise, it calls `item_callback` every time
an item at the specified depth is found and returns `None` in the end
(streaming mode).
The callback function receives two parameters: the `path` from the document
root to the item (name-attribs pairs), and the `item` (dict). If the
callback's return value is false-ish, parsing will be stopped with the
:class:`ParsingInterrupted` exception.
Streaming example::
>>> def handle(path, item):
... print 'path:%s item:%s' % (path, item)
... return True
...
>>> xmltodict.parse(\"\"\"
... <a prop="x">
... <b>1</b>
... <b>2</b>
... </a>\"\"\", item_depth=2, item_callback=handle)
path:[(u'a', {u'prop': u'x'}), (u'b', None)] item:1
path:[(u'a', {u'prop': u'x'}), (u'b', None)] item:2
The optional argument `postprocessor` is a function that takes `path`,
`key` and `value` as positional arguments and returns a new `(key, value)`
pair where both `key` and `value` may have changed. Usage example::
>>> def postprocessor(path, key, value):
... try:
... return key + ':int', int(value)
... except (ValueError, TypeError):
... return key, value
>>> xmltodict.parse('<a><b>1</b><b>2</b><b>x</b></a>',
... postprocessor=postprocessor)
OrderedDict([(u'a', OrderedDict([(u'b:int', [1, 2]), (u'b', u'x')]))])
You can pass an alternate version of `expat` (such as `defusedexpat`) by
using the `expat` parameter. E.g:
>>> import defusedexpat
>>> xmltodict.parse('<a>hello</a>', expat=defusedexpat.pyexpat)
OrderedDict([(u'a', u'hello')])
You can use the force_list argument to force lists to be created even
when there is only a single child of a given level of hierarchy. The
force_list argument is a tuple of keys. If the key for a given level
of hierarchy is in the force_list argument, that level of hierarchy
will have a list as a child (even if there is only one sub-element).
The index_keys operation takes precendence over this. This is applied
after any user-supplied postprocessor has already run.
For example, given this input:
<servers>
<server>
<name>host1</name>
<os>Linux</os>
<interfaces>
<interface>
<name>em0</name>
<ip_address>10.0.0.1</ip_address>
</interface>
</interfaces>
</server>
</servers>
If called with force_list=('interface',), it will produce
this dictionary:
{'servers':
{'server':
{'name': 'host1',
'os': 'Linux'},
'interfaces':
{'interface':
[ {'name': 'em0', 'ip_address': '10.0.0.1' } ] } } }
"""
handler = _DictSAXHandler(namespace_separator=namespace_separator,
**kwargs)
if isinstance(xml_input, _unicode):
if not encoding:
encoding = 'utf-8'
xml_input = xml_input.encode(encoding)
if not process_namespaces:
namespace_separator = None
parser = expat.ParserCreate(
encoding,
namespace_separator
)
try:
parser.ordered_attributes = True
except AttributeError:
# Jython's expat does not support ordered_attributes
pass
parser.StartElementHandler = handler.startElement
parser.EndElementHandler = handler.endElement
parser.CharacterDataHandler = handler.characters
parser.buffer_text = True
try:
parser.ParseFile(xml_input)
except (TypeError, AttributeError):
parser.Parse(xml_input, True)
return handler.item | [
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rucio/rucio | 6d0d358e04f5431f0b9a98ae40f31af0ddff4833 | lib/rucio/client/dq2client.py | python | DQ2Client.getDatasetSize | (self, dsn, scope) | return size | Used to get the dataset size
@param dsn: is the dataset name.
@param scope: is the dataset scope.
B{Exceptions:}
- DataIdentifierNotFound is raised in case the dataset name doesn't exist.
@return: Size as integer | Used to get the dataset size | [
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"""
Used to get the dataset size
@param dsn: is the dataset name.
@param scope: is the dataset scope.
B{Exceptions:}
- DataIdentifierNotFound is raised in case the dataset name doesn't exist.
@return: Size as integer
"""
size = 0
for f in self.client.list_files(scope=scope, name=dsn):
size += f['bytes']
return size | [
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oracle/oci-python-sdk | 3c1604e4e212008fb6718e2f68cdb5ef71fd5793 | src/oci/mysql/db_system_client_composite_operations.py | python | DbSystemClientCompositeOperations.delete_analytics_cluster_and_wait_for_state | (self, db_system_id, wait_for_states=[], operation_kwargs={}, waiter_kwargs={}) | Calls :py:func:`~oci.mysql.DbSystemClient.delete_analytics_cluster` and waits for the :py:class:`~oci.mysql.models.WorkRequest`
to enter the given state(s).
:param str db_system_id: (required)
The DB System `OCID`__.
__ https://docs.cloud.oracle.com/Content/General/Concepts/identifiers.htm
:param list[str] wait_for_states:
An array of states to wait on. These should be valid values for :py:attr:`~oci.mysql.models.WorkRequest.status`
:param dict operation_kwargs:
A dictionary of keyword arguments to pass to :py:func:`~oci.mysql.DbSystemClient.delete_analytics_cluster`
:param dict waiter_kwargs:
A dictionary of keyword arguments to pass to the :py:func:`oci.wait_until` function. For example, you could pass ``max_interval_seconds`` or ``max_interval_seconds``
as dictionary keys to modify how long the waiter function will wait between retries and the maximum amount of time it will wait | Calls :py:func:`~oci.mysql.DbSystemClient.delete_analytics_cluster` and waits for the :py:class:`~oci.mysql.models.WorkRequest`
to enter the given state(s). | [
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"to",
"enter",
"the",... | def delete_analytics_cluster_and_wait_for_state(self, db_system_id, wait_for_states=[], operation_kwargs={}, waiter_kwargs={}):
"""
Calls :py:func:`~oci.mysql.DbSystemClient.delete_analytics_cluster` and waits for the :py:class:`~oci.mysql.models.WorkRequest`
to enter the given state(s).
:param str db_system_id: (required)
The DB System `OCID`__.
__ https://docs.cloud.oracle.com/Content/General/Concepts/identifiers.htm
:param list[str] wait_for_states:
An array of states to wait on. These should be valid values for :py:attr:`~oci.mysql.models.WorkRequest.status`
:param dict operation_kwargs:
A dictionary of keyword arguments to pass to :py:func:`~oci.mysql.DbSystemClient.delete_analytics_cluster`
:param dict waiter_kwargs:
A dictionary of keyword arguments to pass to the :py:func:`oci.wait_until` function. For example, you could pass ``max_interval_seconds`` or ``max_interval_seconds``
as dictionary keys to modify how long the waiter function will wait between retries and the maximum amount of time it will wait
"""
operation_result = None
try:
operation_result = self.client.delete_analytics_cluster(db_system_id, **operation_kwargs)
except oci.exceptions.ServiceError as e:
if e.status == 404:
return WAIT_RESOURCE_NOT_FOUND
else:
raise e
if not wait_for_states:
return operation_result
lowered_wait_for_states = [w.lower() for w in wait_for_states]
wait_for_resource_id = operation_result.headers['opc-work-request-id']
try:
waiter_result = oci.wait_until(
self.client,
self.client.get_work_request(wait_for_resource_id),
evaluate_response=lambda r: getattr(r.data, 'status') and getattr(r.data, 'status').lower() in lowered_wait_for_states,
**waiter_kwargs
)
result_to_return = waiter_result
return result_to_return
except Exception as e:
raise oci.exceptions.CompositeOperationError(partial_results=[operation_result], cause=e) | [
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facebookresearch/ParlAI | e4d59c30eef44f1f67105961b82a83fd28d7d78b | parlai/agents/rag/modules.py | python | RagModel.seq2seq_forward_pass | (
self, xs: torch.LongTensor, ys: torch.LongTensor
) | return logits, preds, encoder_states | Simulate a standard seq2seq encoder/decoder forward pass.
Used in thorough decoding.
:param xs:
input tokens
:param ys:
teacher forced decoder outputs
:return (logits, preds, encoder_states):
logits: token output distribution
preds: max probability token at each output position
encoder_states: output states from the encoder | Simulate a standard seq2seq encoder/decoder forward pass. | [
"Simulate",
"a",
"standard",
"seq2seq",
"encoder",
"/",
"decoder",
"forward",
"pass",
"."
] | def seq2seq_forward_pass(
self, xs: torch.LongTensor, ys: torch.LongTensor
) -> Tuple[torch.Tensor, torch.Tensor, Tuple[Any, ...]]:
"""
Simulate a standard seq2seq encoder/decoder forward pass.
Used in thorough decoding.
:param xs:
input tokens
:param ys:
teacher forced decoder outputs
:return (logits, preds, encoder_states):
logits: token output distribution
preds: max probability token at each output position
encoder_states: output states from the encoder
"""
encoder_states = self.seq2seq_encoder(xs) # type: ignore
bsz = ys.size(0)
seqlen = ys.size(1)
inputs = ys.narrow(1, 0, seqlen - 1)
dec_inputs = self._rag_model_interface.get_initial_forced_decoder_input(
bsz,
inputs,
n_docs=1,
start_idx=self.START_IDX,
end_idx=self.END_IDX,
input_turns_cnt=None,
)
latent, _ = self.seq2seq_decoder(
dec_inputs, encoder_states, None
) # type: ignore
logits = self.decoder_output(latent)
_, preds = logits.max(dim=-1)
return logits, preds, encoder_states | [
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xmengli/H-DenseUNet | 06cc436a43196310fe933d114a353839907cc176 | Keras-2.0.8/keras/backend/theano_backend.py | python | batch_flatten | (x) | return y | Turn a n-D tensor into a 2D tensor where
the first dimension is conserved. | Turn a n-D tensor into a 2D tensor where
the first dimension is conserved. | [
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] | def batch_flatten(x):
"""Turn a n-D tensor into a 2D tensor where
the first dimension is conserved.
"""
y = T.reshape(x, (x.shape[0], T.prod(x.shape[1:])))
if hasattr(x, '_keras_shape'):
if None in x._keras_shape[1:]:
y._keras_shape = (x._keras_shape[0], None)
else:
y._keras_shape = (x._keras_shape[0], np.prod(x._keras_shape[1:]))
return y | [
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googleads/google-ads-python | 2a1d6062221f6aad1992a6bcca0e7e4a93d2db86 | google/ads/googleads/v7/services/services/campaign_experiment_service/transports/grpc.py | python | CampaignExperimentServiceGrpcTransport.__init__ | (
self,
*,
host: str = "googleads.googleapis.com",
credentials: credentials.Credentials = None,
credentials_file: str = None,
scopes: Sequence[str] = None,
channel: grpc.Channel = None,
api_mtls_endpoint: str = None,
client_cert_source: Callable[[], Tuple[bytes, bytes]] = None,
ssl_channel_credentials: grpc.ChannelCredentials = None,
quota_project_id: Optional[str] = None,
client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
) | Instantiate the transport.
Args:
host (Optional[str]):
The hostname to connect to.
credentials (Optional[google.auth.credentials.Credentials]): The
authorization credentials to attach to requests. These
credentials identify the application to the service; if none
are specified, the client will attempt to ascertain the
credentials from the environment.
This argument is ignored if ``channel`` is provided.
credentials_file (Optional[str]): A file with credentials that can
be loaded with :func:`google.auth.load_credentials_from_file`.
This argument is ignored if ``channel`` is provided.
scopes (Optional(Sequence[str])): A list of scopes. This argument is
ignored if ``channel`` is provided.
channel (Optional[grpc.Channel]): A ``Channel`` instance through
which to make calls.
api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint.
If provided, it overrides the ``host`` argument and tries to create
a mutual TLS channel with client SSL credentials from
``client_cert_source`` or applicatin default SSL credentials.
client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]):
Deprecated. A callback to provide client SSL certificate bytes and
private key bytes, both in PEM format. It is ignored if
``api_mtls_endpoint`` is None.
ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials
for grpc channel. It is ignored if ``channel`` is provided.
quota_project_id (Optional[str]): An optional project to use for billing
and quota.
client_info (google.api_core.gapic_v1.client_info.ClientInfo):
The client info used to send a user-agent string along with
API requests. If ``None``, then default info will be used.
Generally, you only need to set this if you're developing
your own client library.
Raises:
google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
creation failed for any reason. | Instantiate the transport. | [
"Instantiate",
"the",
"transport",
"."
] | def __init__(
self,
*,
host: str = "googleads.googleapis.com",
credentials: credentials.Credentials = None,
credentials_file: str = None,
scopes: Sequence[str] = None,
channel: grpc.Channel = None,
api_mtls_endpoint: str = None,
client_cert_source: Callable[[], Tuple[bytes, bytes]] = None,
ssl_channel_credentials: grpc.ChannelCredentials = None,
quota_project_id: Optional[str] = None,
client_info: gapic_v1.client_info.ClientInfo = DEFAULT_CLIENT_INFO,
) -> None:
"""Instantiate the transport.
Args:
host (Optional[str]):
The hostname to connect to.
credentials (Optional[google.auth.credentials.Credentials]): The
authorization credentials to attach to requests. These
credentials identify the application to the service; if none
are specified, the client will attempt to ascertain the
credentials from the environment.
This argument is ignored if ``channel`` is provided.
credentials_file (Optional[str]): A file with credentials that can
be loaded with :func:`google.auth.load_credentials_from_file`.
This argument is ignored if ``channel`` is provided.
scopes (Optional(Sequence[str])): A list of scopes. This argument is
ignored if ``channel`` is provided.
channel (Optional[grpc.Channel]): A ``Channel`` instance through
which to make calls.
api_mtls_endpoint (Optional[str]): Deprecated. The mutual TLS endpoint.
If provided, it overrides the ``host`` argument and tries to create
a mutual TLS channel with client SSL credentials from
``client_cert_source`` or applicatin default SSL credentials.
client_cert_source (Optional[Callable[[], Tuple[bytes, bytes]]]):
Deprecated. A callback to provide client SSL certificate bytes and
private key bytes, both in PEM format. It is ignored if
``api_mtls_endpoint`` is None.
ssl_channel_credentials (grpc.ChannelCredentials): SSL credentials
for grpc channel. It is ignored if ``channel`` is provided.
quota_project_id (Optional[str]): An optional project to use for billing
and quota.
client_info (google.api_core.gapic_v1.client_info.ClientInfo):
The client info used to send a user-agent string along with
API requests. If ``None``, then default info will be used.
Generally, you only need to set this if you're developing
your own client library.
Raises:
google.auth.exceptions.MutualTLSChannelError: If mutual TLS transport
creation failed for any reason.
"""
self._ssl_channel_credentials = ssl_channel_credentials
if channel:
# Sanity check: Ensure that channel and credentials are not both
# provided.
credentials = False
# If a channel was explicitly provided, set it.
self._grpc_channel = channel
self._ssl_channel_credentials = None
elif api_mtls_endpoint:
warnings.warn(
"api_mtls_endpoint and client_cert_source are deprecated",
DeprecationWarning,
)
host = (
api_mtls_endpoint
if ":" in api_mtls_endpoint
else api_mtls_endpoint + ":443"
)
if credentials is None:
credentials, _ = auth.default(
scopes=self.AUTH_SCOPES, quota_project_id=quota_project_id
)
# Create SSL credentials with client_cert_source or application
# default SSL credentials.
if client_cert_source:
cert, key = client_cert_source()
ssl_credentials = grpc.ssl_channel_credentials(
certificate_chain=cert, private_key=key
)
else:
ssl_credentials = SslCredentials().ssl_credentials
# create a new channel. The provided one is ignored.
self._grpc_channel = type(self).create_channel(
host,
credentials=credentials,
credentials_file=credentials_file,
ssl_credentials=ssl_credentials,
scopes=scopes or self.AUTH_SCOPES,
quota_project_id=quota_project_id,
options=[
("grpc.max_send_message_length", -1),
("grpc.max_receive_message_length", -1),
],
)
self._ssl_channel_credentials = ssl_credentials
else:
host = host if ":" in host else host + ":443"
if credentials is None:
credentials, _ = auth.default(scopes=self.AUTH_SCOPES)
# create a new channel. The provided one is ignored.
self._grpc_channel = type(self).create_channel(
host,
credentials=credentials,
ssl_credentials=ssl_channel_credentials,
scopes=self.AUTH_SCOPES,
options=[
("grpc.max_send_message_length", -1),
("grpc.max_receive_message_length", -1),
],
)
self._stubs = {} # type: Dict[str, Callable]
# Run the base constructor.
super().__init__(
host=host, credentials=credentials, client_info=client_info,
) | [
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biolab/orange2 | db40a9449cb45b507d63dcd5739b223f9cffb8e6 | Orange/OrangeCanvas/scheme/scheme.py | python | Scheme.annotations | (self) | return list(self.__annotations) | A list of all annotations (:class:`.BaseSchemeAnnotation`) in the
scheme. | A list of all annotations (:class:`.BaseSchemeAnnotation`) in the
scheme. | [
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"""
A list of all annotations (:class:`.BaseSchemeAnnotation`) in the
scheme.
"""
return list(self.__annotations) | [
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/nova/nova/compute/manager.py | python | ComputeManager.host_maintenance_mode | (self, context, host, mode) | return self.driver.host_maintenance_mode(host, mode) | Start/Stop host maintenance window. On start, it triggers
guest VMs evacuation. | Start/Stop host maintenance window. On start, it triggers
guest VMs evacuation. | [
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"""Start/Stop host maintenance window. On start, it triggers
guest VMs evacuation."""
return self.driver.host_maintenance_mode(host, mode) | [
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haiwen/seahub | e92fcd44e3e46260597d8faa9347cb8222b8b10d | scripts/build/build-pro.py | python | check_targz_src_no_version | (proj, srcdir) | [] | def check_targz_src_no_version(proj, srcdir):
src_tarball = os.path.join(srcdir, '%s.tar.gz' % proj)
if not os.path.exists(src_tarball):
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pwnieexpress/pwn_plug_sources | 1a23324f5dc2c3de20f9c810269b6a29b2758cad | src/set/src/core/scapy.py | python | Dot1Q.default_payload_class | (self, pay) | return Raw | [] | def default_payload_class(self, pay):
if self.type <= 1500:
return LLC
return Raw | [
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cloudera/impyla | 0c736af4cad2bade9b8e313badc08ec50e81c948 | impala/_thrift_gen/hive_metastore/ThriftHiveMetastore.py | python | rename_partition_result.__repr__ | (self) | return '%s(%s)' % (self.__class__.__name__, ', '.join(L)) | [] | def __repr__(self):
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psychopy/psychopy | 01b674094f38d0e0bd51c45a6f66f671d7041696 | psychopy/hardware/crs/bits.py | python | DisplayPlusPlusTouch.getTouchEvent | (self, N=0, distance=None, t=None, type=None) | return value | Scans the touch log to return the Nth touch event.
You need to run getTouchLog before you run this function.
Returns as list of Dict like structures with members
time, x, y, and dir
time is the time stamp of the event.
x and y are the x and y locations of the event.
direction is the type of event: 'touched', 'released'
These values can be read as a structure:
res=getTouchResponses(3)
res[0].dir, res[0].x, res[0].time
or dictionary
res[0]['dir'], res[0]['x'], res[0]['time']
Example:
bits.startTouchLog()
while not event:
#do some processing
continue
bits.stopTouchLog()
bits.getTouchLog()
res=bits.getTouchEvent(N=10, distance=20, time=0.001, type='touched')
print(res.time)
Will extract the 10th touch events (ingnoreing releases) that are 20 pixels and 1 ms apart. | Scans the touch log to return the Nth touch event.
You need to run getTouchLog before you run this function.
Returns as list of Dict like structures with members
time, x, y, and dir
time is the time stamp of the event.
x and y are the x and y locations of the event.
direction is the type of event: 'touched', 'released'
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res[0].dir, res[0].x, res[0].time
or dictionary
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Example:
bits.startTouchLog()
while not event:
#do some processing
continue
bits.stopTouchLog()
bits.getTouchLog()
res=bits.getTouchEvent(N=10, distance=20, time=0.001, type='touched')
print(res.time)
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You need to run getTouchLog before you run this function.
Returns as list of Dict like structures with members
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time is the time stamp of the event.
x and y are the x and y locations of the event.
direction is the type of event: 'touched', 'released'
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bits.startTouchLog()
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continue
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bits.getTouchLog()
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print(res.time)
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"""
values = self.getTouchEvents(distance, t, type)
value = values[N]
return value | [
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JaniceWuo/MovieRecommend | 4c86db64ca45598917d304f535413df3bc9fea65 | movierecommend/venv1/Lib/site-packages/django/core/management/base.py | python | AppCommand.add_arguments | (self, parser) | [] | def add_arguments(self, parser):
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aws/aws-sam-cli | 2aa7bf01b2e0b0864ef63b1898a8b30577443acc | samcli/lib/bootstrap/companion_stack/data_types.py | python | CompanionStack.escaped_parent_stack_name | (self) | return self._escaped_parent_stack_name | Parent stack name with only alphanumeric characters | Parent stack name with only alphanumeric characters | [
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] | def escaped_parent_stack_name(self) -> str:
"""
Parent stack name with only alphanumeric characters
"""
return self._escaped_parent_stack_name | [
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mongodb/mongo-python-driver | c760f900f2e4109a247c2ffc8ad3549362007772 | pymongo/pool.py | python | SocketInfo.add_server_api | (self, command) | Add server_api parameters. | Add server_api parameters. | [
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] | def add_server_api(self, command):
"""Add server_api parameters."""
if self.opts.server_api:
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zaxlct/imooc-django | daf1ced745d3d21989e8191b658c293a511b37fd | extra_apps/xadmin/views/dashboard.py | python | ModelChoiceField.__deepcopy__ | (self, memo) | return result | [] | def __deepcopy__(self, memo):
result = forms.Field.__deepcopy__(self, memo)
return result | [
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Azure/azure-linux-extensions | a42ef718c746abab2b3c6a21da87b29e76364558 | VMEncryption/main/ResourceDiskUtil.py | python | ResourceDiskUtil._configure_fstab | (self) | return True | remove resource disk from /etc/fstab if present | remove resource disk from /etc/fstab if present | [
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cmd = "sed -i.bak '/azure_resource-part1/d' /etc/fstab"
if self.executor.ExecuteInBash(cmd) != CommonVariables.process_success:
self.logger.log(msg="Failed to configure resource disk entry of /etc/fstab", level=CommonVariables.WarningLevel)
return False
return True | [
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chipmuenk/pyfda | 665310b8548a940a575c0e5ff4bba94608d9ac26 | pyfda/libs/tree_builder.py | python | Tree_Builder.build_fil_tree | (self, fc, rt_dict, fil_tree=None) | return fil_tree | Read attributes (ft, rt, rt:fo) from filter class fc)
Attributes are stored in
the design method classes in the format (example from ``common.py``)
.. code-block:: python
self.ft = 'IIR'
self.rt_dict = {
'LP': {'man':{'fo': ('a','N'),
'msg': ('a', r"<br /><b>Note:</b> Read this!"),
'fspecs': ('a','F_C'),
'tspecs': ('u', {'frq':('u','F_PB','F_SB'),
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}
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}
}
}
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rt (e.g. 'LP') ft (e.g. 'IIR') fc (e.g. 'cheby1') fo ('min' or 'man')
All attributes found for fc are arranged in a dict, e.g.
for ``cheby1.LPman`` and ``cheby1.LPmin``, listing the parameters to be
displayed and whether they are active, unused, disabled or invisible for
each subwidget:
.. code-block:: python
'LP':{
'IIR':{
'Cheby1':{
'man':{'fo': ('a','N'),
'msg': ('a', r"<br /><b>Note:</b> Read this!"),
'fspecs': ('a','F_C'),
'tspecs': ('u', {'frq':('u','F_PB','F_SB'),
'amp':('u','A_PB','A_SB')})
},
'min':{'fo': ('d','N'),
'fspecs': ('d','F_C'),
'tspecs': ('a', {'frq':('a','F_PB','F_SB'),
'amp':('a','A_PB','A_SB')})
}
}
}
}, ...
Finally, the whole structure is frozen recursively to avoid inadvertedly
changing the filter tree.
For a full example, see the default filter tree ``fb.fil_tree`` defined
in ``filterbroker.py``.
Parameters
----------
None
Returns
-------
dict
filter tree | Read attributes (ft, rt, rt:fo) from filter class fc)
Attributes are stored in
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Attributes are stored in
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self.ft = 'IIR'
self.rt_dict = {
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'tspecs': ('a', {'frq':('a','F_SB','F_PB'),
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}
}
}
Build a dictionary of all filter combinations with the following hierarchy:
response types -> filter types -> filter classes -> filter order
rt (e.g. 'LP') ft (e.g. 'IIR') fc (e.g. 'cheby1') fo ('min' or 'man')
All attributes found for fc are arranged in a dict, e.g.
for ``cheby1.LPman`` and ``cheby1.LPmin``, listing the parameters to be
displayed and whether they are active, unused, disabled or invisible for
each subwidget:
.. code-block:: python
'LP':{
'IIR':{
'Cheby1':{
'man':{'fo': ('a','N'),
'msg': ('a', r"<br /><b>Note:</b> Read this!"),
'fspecs': ('a','F_C'),
'tspecs': ('u', {'frq':('u','F_PB','F_SB'),
'amp':('u','A_PB','A_SB')})
},
'min':{'fo': ('d','N'),
'fspecs': ('d','F_C'),
'tspecs': ('a', {'frq':('a','F_PB','F_SB'),
'amp':('a','A_PB','A_SB')})
}
}
}
}, ...
Finally, the whole structure is frozen recursively to avoid inadvertedly
changing the filter tree.
For a full example, see the default filter tree ``fb.fil_tree`` defined
in ``filterbroker.py``.
Parameters
----------
None
Returns
-------
dict
filter tree
"""
if not fil_tree:
fil_tree = {}
ft = ff.fil_inst.ft # get filter type (e.g. 'FIR')
for rt in rt_dict: # iterate over all response types
if rt == 'COM': # handle common info later
continue
if rt not in fil_tree: # is response type already in dict?
fil_tree.update({rt: {}}) # no, create it
if ft not in fil_tree[rt]: # filter type already in dict[rt]?
fil_tree[rt].update({ft: {}}) # no, create it
if fc not in fil_tree[rt][ft]: # filter class already in dict[rt][ft]?
fil_tree[rt][ft].update({fc: {}}) # no, create it
# now append all the individual 'min' / 'man' subwidget infos to fc:
fil_tree[rt][ft][fc].update(rt_dict[rt])
if 'COM' in rt_dict: # Now handle common info
for fo in rt_dict[rt]: # iterate over 'min' / 'max'
if fo in rt_dict['COM']: # and add common info first
merge_dicts(fil_tree[rt][ft][fc][fo],
rt_dict['COM'][fo], mode='add2')
return fil_tree | [
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openstack/nova | b49b7663e1c3073917d5844b81d38db8e86d05c4 | nova/virt/libvirt/volume/fibrechannel.py | python | LibvirtFibreChannelVolumeDriver.disconnect_volume | (self, connection_info, instance) | Detach the volume from instance_name. | Detach the volume from instance_name. | [
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"""Detach the volume from instance_name."""
LOG.debug("calling os-brick to detach FC Volume", instance=instance)
# TODO(walter-boring) eliminated the need for preserving
# multipath_id. Use scsi_id instead of multipath -ll
# This will then eliminate the need to pass anything in
# the 2nd param of disconnect_volume and be consistent
# with the rest of the connectors.
self.connector.disconnect_volume(connection_info['data'],
connection_info['data'])
LOG.debug("Disconnected FC Volume", instance=instance)
super(LibvirtFibreChannelVolumeDriver,
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littlecodersh/ItChat | d5ce5db32ca15cef8eefa548a438a9fcc4502a6d | itchat/components/login.py | python | web_init | (self) | return dic | [] | def web_init(self):
url = '%s/webwxinit' % self.loginInfo['url']
params = {
'r': int(-time.time() / 1579),
'pass_ticket': self.loginInfo['pass_ticket'], }
data = { 'BaseRequest': self.loginInfo['BaseRequest'], }
headers = {
'ContentType': 'application/json; charset=UTF-8',
'User-Agent' : config.USER_AGENT, }
r = self.s.post(url, params=params, data=json.dumps(data), headers=headers)
dic = json.loads(r.content.decode('utf-8', 'replace'))
# deal with login info
utils.emoji_formatter(dic['User'], 'NickName')
self.loginInfo['InviteStartCount'] = int(dic['InviteStartCount'])
self.loginInfo['User'] = wrap_user_dict(utils.struct_friend_info(dic['User']))
self.memberList.append(self.loginInfo['User'])
self.loginInfo['SyncKey'] = dic['SyncKey']
self.loginInfo['synckey'] = '|'.join(['%s_%s' % (item['Key'], item['Val'])
for item in dic['SyncKey']['List']])
self.storageClass.userName = dic['User']['UserName']
self.storageClass.nickName = dic['User']['NickName']
# deal with contact list returned when init
contactList = dic.get('ContactList', [])
chatroomList, otherList = [], []
for m in contactList:
if m['Sex'] != 0:
otherList.append(m)
elif '@@' in m['UserName']:
m['MemberList'] = [] # don't let dirty info pollute the list
chatroomList.append(m)
elif '@' in m['UserName']:
# mp will be dealt in update_local_friends as well
otherList.append(m)
if chatroomList:
update_local_chatrooms(self, chatroomList)
if otherList:
update_local_friends(self, otherList)
return dic | [
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... | https://github.com/littlecodersh/ItChat/blob/d5ce5db32ca15cef8eefa548a438a9fcc4502a6d/itchat/components/login.py#L188-L225 | |||
kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python-build/python-libs/gdata/src/gdata/tlslite/Session.py | python | Session.valid | (self) | return self.resumable or self.sharedKey | If this session can be used for session resumption.
@rtype: bool
@return: If this session can be used for session resumption. | If this session can be used for session resumption. | [
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"""If this session can be used for session resumption.
@rtype: bool
@return: If this session can be used for session resumption.
"""
return self.resumable or self.sharedKey | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/quadratic_forms/quadratic_form__automorphisms.py | python | _compute_automorphisms | (self) | Call PARI to compute the automorphism group of the quadratic form.
This uses :pari:`qfauto`.
OUTPUT: None, this just caches the result.
TESTS::
sage: DiagonalQuadraticForm(ZZ, [-1,1,1])._compute_automorphisms()
Traceback (most recent call last):
...
ValueError: not a definite form in QuadraticForm.automorphisms()
sage: DiagonalQuadraticForm(GF(5), [1,1,1])._compute_automorphisms()
Traceback (most recent call last):
...
NotImplementedError: computing the automorphism group of a quadratic form is only supported over ZZ | Call PARI to compute the automorphism group of the quadratic form. | [
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"""
Call PARI to compute the automorphism group of the quadratic form.
This uses :pari:`qfauto`.
OUTPUT: None, this just caches the result.
TESTS::
sage: DiagonalQuadraticForm(ZZ, [-1,1,1])._compute_automorphisms()
Traceback (most recent call last):
...
ValueError: not a definite form in QuadraticForm.automorphisms()
sage: DiagonalQuadraticForm(GF(5), [1,1,1])._compute_automorphisms()
Traceback (most recent call last):
...
NotImplementedError: computing the automorphism group of a quadratic form is only supported over ZZ
"""
if self.base_ring() is not ZZ:
raise NotImplementedError("computing the automorphism group of a quadratic form is only supported over ZZ")
if not self.is_definite():
raise ValueError("not a definite form in QuadraticForm.automorphisms()")
if hasattr(self, "__automorphisms_pari"):
return
A = self.__pari__().qfauto()
self.__number_of_automorphisms = A[0]
self.__automorphisms_pari = A[1] | [
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inducer/pudb | 82a0017982f20917c17989a0cb2b71c54ee90ba7 | pudb/debugger.py | python | Debugger.user_return | (self, frame, return_value) | This function is called when a return trap is set here. | This function is called when a return trap is set here. | [
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"""This function is called when a return trap is set here."""
if frame.f_code.co_name != "<module>":
frame.f_locals["__return__"] = return_value
if self._wait_for_mainpyfile:
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return
self._wait_for_mainpyfile = False
self.bottom_frame = frame
if "__exc_tuple__" not in frame.f_locals:
self.interaction(frame) | [
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CvvT/dumpDex | 92ab3b7e996194a06bf1dd5538a4954e8a5ee9c1 | python/idaapi.py | python | varloc_t._consume_scattered | (self, *args) | return _idaapi.varloc_t__consume_scattered(self, *args) | _consume_scattered(self, p) -> bool | _consume_scattered(self, p) -> bool | [
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return _idaapi.varloc_t__consume_scattered(self, *args) | [
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noxrepo/pox | 5f82461e01f8822bd7336603b361bff4ffbd2380 | pox/datapaths/switch.py | python | SoftwareSwitchBase._rx_packet_out | (self, packet_out, connection) | Handles packet_outs | Handles packet_outs | [
"Handles",
"packet_outs"
] | def _rx_packet_out (self, packet_out, connection):
"""
Handles packet_outs
"""
self.log.debug("Packet out details: %s", packet_out.show())
if packet_out.data:
self._process_actions_for_packet(packet_out.actions, packet_out.data,
packet_out.in_port, packet_out)
elif packet_out.buffer_id is not None:
self._process_actions_for_packet_from_buffer(packet_out.actions,
packet_out.buffer_id,
packet_out)
else:
self.log.warn("packet_out: No data and no buffer_id -- "
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/rings/valuation/trivial_valuation.py | python | TrivialValuationFactory.create_key | (self, domain) | return domain, | r"""
Create a key that identifies this valuation.
EXAMPLES::
sage: valuations.TrivialValuation(QQ) is valuations.TrivialValuation(QQ) # indirect doctest
True | r"""
Create a key that identifies this valuation. | [
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] | def create_key(self, domain):
r"""
Create a key that identifies this valuation.
EXAMPLES::
sage: valuations.TrivialValuation(QQ) is valuations.TrivialValuation(QQ) # indirect doctest
True
"""
return domain, | [
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | citrix_hypervisor/datadog_checks/citrix_hypervisor/config_models/shared.py | python | SharedConfig._initial_validation | (cls, values) | return validation.core.initialize_config(getattr(validators, 'initialize_shared', identity)(values)) | [] | def _initial_validation(cls, values):
return validation.core.initialize_config(getattr(validators, 'initialize_shared', identity)(values)) | [
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1012598167/flask_mongodb_game | 60c7e0351586656ec38f851592886338e50b4110 | python_flask/venv/Lib/site-packages/werkzeug/debug/tbtools.py | python | Frame.get_annotated_lines | (self) | return lines | Helper function that returns lines with extra information. | Helper function that returns lines with extra information. | [
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lines = [Line(idx + 1, x) for idx, x in enumerate(self.sourcelines)]
# find function definition and mark lines
if hasattr(self.code, "co_firstlineno"):
lineno = self.code.co_firstlineno - 1
while lineno > 0:
if _funcdef_re.match(lines[lineno].code):
break
lineno -= 1
try:
offset = len(inspect.getblock([x.code + "\n" for x in lines[lineno:]]))
except TokenError:
offset = 0
for line in lines[lineno : lineno + offset]:
line.in_frame = True
# mark current line
try:
lines[self.lineno - 1].current = True
except IndexError:
pass
return lines | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site-packages/sqlalchemy/sql/naming.py | python | ConventionDict._key_referred_table_name | (self) | return reftable | [] | def _key_referred_table_name(self):
fk = self.const.elements[0]
refs = fk.target_fullname.split(".")
if len(refs) == 3:
refschema, reftable, refcol = refs
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return reftable | [
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