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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/Python-2.7.9/Mac/Modules/res/resscan.py | python | ResourcesScanner.makeblacklisttypes | (self) | return [
] | [] | def makeblacklisttypes(self):
return [
] | [
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aws-solutions/aws-instance-scheduler | d9208ddc4528536f20e14127ea0f49f8c52ea811 | source/lambda/configuration/config_admin.py | python | ConfigAdmin.get_period | (self, name, exception_if_not_exists=True) | return {"period": ConfigAdmin._for_output(period)} | Gets a specific period
:param name: name of the period
:param exception_if_not_exists: set to True to raise an exception if it does not exist
:return: | Gets a specific period
:param name: name of the period
:param exception_if_not_exists: set to True to raise an exception if it does not exist
:return: | [
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"""
Gets a specific period
:param name: name of the period
:param exception_if_not_exists: set to True to raise an exception if it does not exist
:return:
"""
if name is None or len(name) == 0:
raise ValueError(ERR_GET_EMPTY_PERIOD_NAME)
period = self._get_period(name)
if period is None:
if exception_if_not_exists:
raise ValueError(ERR_GET_PERIOD_NOT_FOUND.format(name))
return None
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AliLozano/django-messages-extends | d231b6535e95c31fe26ae33148615961ec07454b | messages_extends/storages.py | python | FallbackStorage._store | (self, messages, response, *args, **kwargs) | return messages | Stores the messages, returning any unstored messages after trying all
backends.
For each storage backend, any messages not stored are passed on to the
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"""
Stores the messages, returning any unstored messages after trying all
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For each storage backend, any messages not stored are passed on to the
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"""
for storage in self.storages:
if messages:
messages = storage._store(messages, response,
remove_oldest=False)
# Even if there are no more messages, continue iterating to ensure
# storages which contained messages are flushed.
elif storage in self._used_storages:
storage._store([], response)
self._used_storages.remove(storage)
return messages | [
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qgriffith-zz/OpenEats | 9373ce65f838f19fead6f73c9491d2211e770769 | list/models.py | python | GroceryList.__unicode__ | (self) | return self.title | [] | def __unicode__(self):
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crossbario/autobahn-python | fa9f2da0c5005574e63456a3a04f00e405744014 | autobahn/asyncio/component.py | python | Component._is_ssl_error | (self, e) | return isinstance(e, ssl.SSLError) | Internal helper. | Internal helper. | [
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"""
Internal helper.
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web2py/web2py | 095905c4e010a1426c729483d912e270a51b7ba8 | gluon/html.py | python | ASSIGNJS | (**kargs) | return XML(s) | Example:
ASSIGNJS(var1='1', var2='2') will return the following javascript variables assignations :
var var1 = "1";
var var2 = "2";
Args:
**kargs: Any keywords arguments and assigned values.
Returns:
Javascript vars assignations for the key/value passed. | Example:
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"""
Example:
ASSIGNJS(var1='1', var2='2') will return the following javascript variables assignations :
var var1 = "1";
var var2 = "2";
Args:
**kargs: Any keywords arguments and assigned values.
Returns:
Javascript vars assignations for the key/value passed.
"""
from gluon.serializers import json
s = ""
for key, value in kargs.items():
s += 'var %s = %s;\n' % (key, json(value))
return XML(s) | [
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mozman/ezdxf | 59d0fc2ea63f5cf82293428f5931da7e9f9718e9 | src/ezdxf/math/ellipse.py | python | ConstructionEllipse.vertices | (self, params: Iterable[float]) | Yields vertices on ellipse for iterable `params` in WCS.
Args:
params: param values in the range from [0, 2π) in radians,
param goes counter clockwise around the extrusion vector,
major_axis = local x-axis = 0 rad. | Yields vertices on ellipse for iterable `params` in WCS. | [
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] | def vertices(self, params: Iterable[float]) -> Iterable[Vec3]:
"""Yields vertices on ellipse for iterable `params` in WCS.
Args:
params: param values in the range from [0, 2π) in radians,
param goes counter clockwise around the extrusion vector,
major_axis = local x-axis = 0 rad.
"""
center = self.center
ratio = self.ratio
x_axis = self.major_axis.normalize()
y_axis = self.minor_axis.normalize()
radius_x = self.major_axis.magnitude
radius_y = radius_x * ratio
for param in params:
x = math.cos(param) * radius_x * x_axis
y = math.sin(param) * radius_y * y_axis
yield center + x + y | [
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Dash-Industry-Forum/dash-live-source-simulator | 23cb15c35656a731d9f6d78a30f2713eff2ec20d | dashlivesim/cc_inserter/mpdprocessor.py | python | Period.parse | (self) | Parse the node and its children. | Parse the node and its children. | [
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AlvarBer/Persimmon | da08ed854dd0305d7e4684e97ee828acffd76b4d | persimmon/backend/backend.py | python | Backend._exec_graph_parallel | (self) | Execution algorithm, introduces all blocks on a set, when a block
is executed it is taken out of the set until the set is empty. | Execution algorithm, introduces all blocks on a set, when a block
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unseen = set(self.ir.blocks.keys()) # All blocks are unseen at start
# All output pins along their respectives values
seen = {} # type: Dict[int, Any]
while unseen:
unseen, seen = self._exec_block(unseen.pop(), unseen, seen)
logger.info('Execution done')
self.emit('graph_executed') | [
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val-iisc/deligan | 68451c8923650b9239a87efb3b88f04b6969e54b | src/cifar/params.py | python | read_model_data | (model, filename) | Unpickles and loads parameters into a Lasagne model. | Unpickles and loads parameters into a Lasagne model. | [
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filename = os.path.join('./', '%s.%s' % (filename, PARAM_EXTENSION))
with open(filename, 'r') as f:
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ninja-ide/ninja-ide | 87d91131bd19fdc3dcfd91eb97ad1e41c49c60c0 | ninja_ide/core/plugin_manager.py | python | __get_all_plugin_descriptors | () | return [pf for pf in os.listdir(resources.PLUGINS)
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'''
Returns all the .plugin files
'''
global PLUGIN_EXTENSION
return [pf for pf in os.listdir(resources.PLUGINS)
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/sankey/node/_hoverlabel.py | python | Hoverlabel.bordercolor | (self) | return self["bordercolor"] | Sets the border color of the hover labels for this trace.
The 'bordercolor' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
ivory, khaki, lavender, lavenderblush, lawngreen,
lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
linen, magenta, maroon, mediumaquamarine,
mediumblue, mediumorchid, mediumpurple,
mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
mintcream, mistyrose, moccasin, navajowhite, navy,
oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
plum, powderblue, purple, red, rosybrown,
royalblue, rebeccapurple, saddlebrown, salmon,
sandybrown, seagreen, seashell, sienna, silver,
skyblue, slateblue, slategray, slategrey, snow,
springgreen, steelblue, tan, teal, thistle, tomato,
turquoise, violet, wheat, white, whitesmoke,
yellow, yellowgreen
- A list or array of any of the above
Returns
-------
str|numpy.ndarray | Sets the border color of the hover labels for this trace.
The 'bordercolor' property is a color and may be specified as:
- A hex string (e.g. '#ff0000')
- An rgb/rgba string (e.g. 'rgb(255,0,0)')
- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
- An hsv/hsva string (e.g. 'hsv(0,100%,100%)')
- A named CSS color:
aliceblue, antiquewhite, aqua, aquamarine, azure,
beige, bisque, black, blanchedalmond, blue,
blueviolet, brown, burlywood, cadetblue,
chartreuse, chocolate, coral, cornflowerblue,
cornsilk, crimson, cyan, darkblue, darkcyan,
darkgoldenrod, darkgray, darkgrey, darkgreen,
darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
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lightskyblue, lightslategray, lightslategrey,
lightsteelblue, lightyellow, lime, limegreen,
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- An hsl/hsla string (e.g. 'hsl(0,100%,50%)')
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beige, bisque, black, blanchedalmond, blue,
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chartreuse, chocolate, coral, cornflowerblue,
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darkkhaki, darkmagenta, darkolivegreen, darkorange,
darkorchid, darkred, darksalmon, darkseagreen,
darkslateblue, darkslategray, darkslategrey,
darkturquoise, darkviolet, deeppink, deepskyblue,
dimgray, dimgrey, dodgerblue, firebrick,
floralwhite, forestgreen, fuchsia, gainsboro,
ghostwhite, gold, goldenrod, gray, grey, green,
greenyellow, honeydew, hotpink, indianred, indigo,
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lemonchiffon, lightblue, lightcoral, lightcyan,
lightgoldenrodyellow, lightgray, lightgrey,
lightgreen, lightpink, lightsalmon, lightseagreen,
lightskyblue, lightslategray, lightslategrey,
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mediumseagreen, mediumslateblue, mediumspringgreen,
mediumturquoise, mediumvioletred, midnightblue,
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oldlace, olive, olivedrab, orange, orangered,
orchid, palegoldenrod, palegreen, paleturquoise,
palevioletred, papayawhip, peachpuff, peru, pink,
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royalblue, rebeccapurple, saddlebrown, salmon,
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getdock/whitelist | 704bb41552f71d1a91ecf35e373d8f0b7434f144 | app/user/verifications.py | python | verify_ids | (upload: IDUpload) | [] | def verify_ids(upload: IDUpload) -> str:
user = upload.user
state = user.transition(ID_PENDING_VERIFICATION)
# Make sure that state didn't changed after we reached pending verification state
if state != ID_PENDING_VERIFICATION:
return state
image1 = upload.upload1.to_base64()
image2 = upload.upload2.to_base64()
try:
response = verify(
user=user,
kyc=False,
image1=image1,
image2=image2,
doc_type=upload.doc_type,
doc_state=upload.doc_state,
doc_country=upload.doc_country,
)
if response.user:
apply_response(user, response, False)
except IDMError as err:
return user.transition(ID_FAILED, details=err.text) | [
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GoogleCloudPlatform/PerfKitBenchmarker | 6e3412d7d5e414b8ca30ed5eaf970cef1d919a67 | perfkitbenchmarker/linux_benchmarks/cloudsuite_web_search_benchmark.py | python | Run | (benchmark_spec) | return results | Run the Web Search benchmark.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
Returns:
A list of sample.Sample objects. | Run the Web Search benchmark. | [
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] | def Run(benchmark_spec):
"""Run the Web Search benchmark.
Args:
benchmark_spec: The benchmark specification. Contains all data that is
required to run the benchmark.
Returns:
A list of sample.Sample objects.
"""
clients = benchmark_spec.vm_groups['clients'][0]
servers = benchmark_spec.vm_groups['servers'][0]
benchmark_cmd = ('sudo docker run --rm --net host --name client '
'cloudsuite/web-search:client %s %d %d %d %d ' %
(servers.internal_ip,
FLAGS.cloudsuite_web_search_scale,
FLAGS.cloudsuite_web_search_ramp_up,
FLAGS.cloudsuite_web_search_steady_state,
FLAGS.cloudsuite_web_search_ramp_down))
stdout, _ = clients.RemoteCommand(benchmark_cmd, should_log=True)
ops_per_sec = re.findall(r'\<metric unit="ops/sec"\>(\d+\.?\d*)', stdout)
num_ops_per_sec = float(ops_per_sec[0])
p90 = re.findall(r'\<p90th\>(\d+\.?\d*)', stdout)
num_p90 = float(p90[0])
p99 = re.findall(r'\<p99th\>(\d+\.?\d*)', stdout)
num_p99 = float(p99[0])
results = []
results.append(sample.Sample('Operations per second', num_ops_per_sec,
'ops/s'))
results.append(sample.Sample('90th percentile latency', num_p90, 's'))
results.append(sample.Sample('99th percentile latency', num_p99, 's'))
return results | [
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serge-sans-paille/pythran | f9f73aa5a965adc4ebcb91a439784dbe9ef911fa | pythran/analyses/ast_matcher.py | python | Placeholder.__init__ | (self, identifier, type=None) | Placehorder are identified using an identifier. | Placehorder are identified using an identifier. | [
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""" Placehorder are identified using an identifier. """
self.id = identifier
self.type = type
super(Placeholder, self).__init__() | [
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Abjad/abjad | d0646dfbe83db3dc5ab268f76a0950712b87b7fd | abjad/string.py | python | String.to_accent_free_snake_case | (self) | return type(self)(string_) | Changes string to accent-free snake case.
.. container:: example
>>> abjad.String('Déja vu').to_accent_free_snake_case()
'deja_vu' | Changes string to accent-free snake case. | [
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] | def to_accent_free_snake_case(self) -> "String":
"""
Changes string to accent-free snake case.
.. container:: example
>>> abjad.String('Déja vu').to_accent_free_snake_case()
'deja_vu'
"""
string = self.strip_diacritics()
string_ = string.replace(" ", "_")
string_ = string_.replace("'", "_")
string_ = string_.lower()
return type(self)(string_) | [
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robotlearn/pyrobolearn | 9cd7c060723fda7d2779fa255ac998c2c82b8436 | pyrobolearn/algos/evaluator.py | python | Evaluator.__call__ | (self, verbose=False) | Evaluate the trajectories performed by the policy.
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Evaluate the trajectories performed by the policy.
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verbose (bool): If true, print information on the standard output.
"""
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hacs/integration | 8ad321da6de4bf5ffa06bdaff1802e25edae5705 | custom_components/hacs/tasks/load_hacs_repository.py | python | async_setup_task | (hacs: HacsBase, hass: HomeAssistant) | return Task(hacs=hacs, hass=hass) | Set up this task. | Set up this task. | [
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respeaker/respeaker_python_library | 905a5334ccdc2d474ad973caf6a23d05c65bbb25 | respeaker/gpio.py | python | Gpio._sysfs_gpio_value_path | (self) | return SYSFS_GPIO_VALUE_PATH % self.number | Get the file that represent the value of this pin.
@rtype: str
@return: the path to sysfs value file | Get the file that represent the value of this pin. | [
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] | def _sysfs_gpio_value_path(self):
"""
Get the file that represent the value of this pin.
@rtype: str
@return: the path to sysfs value file
"""
return SYSFS_GPIO_VALUE_PATH % self.number | [
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miyosuda/unreal | 31d4886149412fa248f6efa490ab65bd2f425cde | train/experience.py | python | Experience.sample_rp_sequence | (self) | return sampled_frames | Sample 4 successive frames for reward prediction. | Sample 4 successive frames for reward prediction. | [
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] | def sample_rp_sequence(self):
"""
Sample 4 successive frames for reward prediction.
"""
if np.random.randint(2) == 0:
from_zero = True
else:
from_zero = False
if len(self._zero_reward_indices) == 0:
# zero rewards container was empty
from_zero = False
elif len(self._non_zero_reward_indices) == 0:
# non zero rewards container was empty
from_zero = True
if from_zero:
index = np.random.randint(len(self._zero_reward_indices))
end_frame_index = self._zero_reward_indices[index]
else:
index = np.random.randint(len(self._non_zero_reward_indices))
end_frame_index = self._non_zero_reward_indices[index]
start_frame_index = end_frame_index-3
raw_start_frame_index = start_frame_index - self._top_frame_index
sampled_frames = []
for i in range(4):
frame = self._frames[raw_start_frame_index+i]
sampled_frames.append(frame)
return sampled_frames | [
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alephsecurity/abootool | 4117b82d07e6b3a80eeab560d2140ae2dcfe2463 | log.py | python | E | (msg, *kargs, **kwargs) | [] | def E(msg, *kargs, **kwargs):
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phil-bergmann/tracking_wo_bnw | 72ee403de01c472f6eb5cde60b56b86aa6a617c8 | src/tracktor/datasets/mot_wrapper.py | python | MOT17PrivateWrapper.__init__ | (self, split, dataloader, data_dir) | Initliazes all subset of the dataset.
Keyword arguments:
split -- the split of the dataset to use
dataloader -- args for the MOT_Sequence dataloader | Initliazes all subset of the dataset. | [
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] | def __init__(self, split, dataloader, data_dir):
"""Initliazes all subset of the dataset.
Keyword arguments:
split -- the split of the dataset to use
dataloader -- args for the MOT_Sequence dataloader
"""
train_sequences = ['MOT17-02', 'MOT17-04', 'MOT17-05', 'MOT17-09', 'MOT17-10', 'MOT17-11', 'MOT17-13']
test_sequences = ['MOT17-01', 'MOT17-03', 'MOT17-06', 'MOT17-07', 'MOT17-08', 'MOT17-12', 'MOT17-14']
if "train" == split:
sequences = train_sequences
elif "test" == split:
sequences = test_sequences
elif "all" == split:
sequences = train_sequences + test_sequences
elif f"MOT17-{split}" in train_sequences + test_sequences:
sequences = [f"MOT17-{split}"]
else:
raise NotImplementedError("MOT17 split not available.")
self._data = []
for s in sequences:
self._data.append(MOTSequence(s, data_dir, **dataloader)) | [
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mongodb/pymodm | be1c7b079df4954ef7e79e46f1b4a9ac9510766c | pymodm/queryset.py | python | QuerySet.bulk_create | (self, object_or_objects, retrieve=False, full_clean=False) | return ids | Save Model instances in bulk.
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:returns: A list of ids for the documents saved, or of the
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example::
>>> vacation_ids = Vacation.objects.bulk_create([
... Vacation(destination='TOKYO', travel_method='PLANE'),
... Vacation(destination='ALGIERS', travel_method='PLANE')])
>>> print(vacation_ids)
[ObjectId('578926716e32ab1d6a8dc718'),
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] | def bulk_create(self, object_or_objects, retrieve=False, full_clean=False):
"""Save Model instances in bulk.
:parameters:
- `object_or_objects`: A list of MongoModel instances or a single
instance.
- `retrieve`: Whether to return the saved MongoModel
instances. If ``False`` (the default), only the ids will be
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- `full_clean`: Whether to validate each object by calling
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This isn't done by default.
:returns: A list of ids for the documents saved, or of the
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example::
>>> vacation_ids = Vacation.objects.bulk_create([
... Vacation(destination='TOKYO', travel_method='PLANE'),
... Vacation(destination='ALGIERS', travel_method='PLANE')])
>>> print(vacation_ids)
[ObjectId('578926716e32ab1d6a8dc718'),
ObjectId('578926716e32ab1d6a8dc719')]
"""
retrieve = validate_boolean('retrieve', retrieve)
full_clean = validate_boolean('full_clean', full_clean)
TopLevelMongoModel = _import('pymodm.base.models.TopLevelMongoModel')
if isinstance(object_or_objects, TopLevelMongoModel):
object_or_objects = [object_or_objects]
object_or_objects = validate_list_or_tuple(
'object_or_objects', object_or_objects)
if full_clean:
for object in object_or_objects:
object.full_clean()
docs = (obj.to_son() for obj in object_or_objects)
ids = self._collection.insert_many(docs).inserted_ids
if retrieve:
return list(self.raw({'_id': {'$in': ids}}))
return ids | [
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/core/ext-py/kombu-4.3.0/kombu/pools.py | python | reset | (*args, **kwargs) | Reset all pools by closing open resources. | Reset all pools by closing open resources. | [
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] | def reset(*args, **kwargs):
"""Reset all pools by closing open resources."""
for pool in _all_pools():
try:
pool.force_close_all()
except Exception:
pass
for group in _groups:
group.clear() | [
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prody/ProDy | b24bbf58aa8fffe463c8548ae50e3955910e5b7f | prody/atomic/atom.py | python | Atom.setFlag | (self, label, value) | Update flag associated with *label*.
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openedx/edx-platform | 68dd185a0ab45862a2a61e0f803d7e03d2be71b5 | common/lib/sandbox-packages/verifiers/draganddrop.py | python | flat_user_answer | (user_answer) | return result | Convert nested `user_answer` to flat format.
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Convert nested `user_answer` to flat format.
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"""
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complex_value_list = []
v_value = value
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v_key = list(v_value.keys())[0]
v_value = list(v_value.values())[0]
complex_value_list.append(v_key)
complex_value = '{0}'.format(v_value)
for i in reversed(complex_value_list):
complex_value = '{0}[{1}]'.format(complex_value, i)
res = {key: complex_value}
return res
else:
return answer
result = []
for answer in user_answer:
parse_answer = parse_user_answer(answer)
result.append(parse_answer)
return result | [
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isnowfy/pydown | 71ecc891868cd2a34b7e5fe662c99474f2d0fd7f | pygments/formatters/terminal256.py | python | EscapeSequence.__init__ | (self, fg=None, bg=None, bold=False, underline=False) | [] | def __init__(self, fg=None, bg=None, bold=False, underline=False):
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... | https://github.com/isnowfy/pydown/blob/71ecc891868cd2a34b7e5fe662c99474f2d0fd7f/pygments/formatters/terminal256.py#L36-L40 | ||||
jquast/x84 | 11f445bb82e6e895d7cce57d4c6d8572d1981162 | x84/sftp.py | python | X84SFTPServer._dummy_dir_stat | (self) | return attr | Stat on our dummy __flagged__ directory. | Stat on our dummy __flagged__ directory. | [
"Stat",
"on",
"our",
"dummy",
"__flagged__",
"directory",
"."
] | def _dummy_dir_stat(self):
""" Stat on our dummy __flagged__ directory. """
self.log.debug('_dummy_dir_stat')
attr = SFTPAttributes.from_stat(
os.stat(self.root))
attr.filename = flagged_dirname
return attr | [
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awslabs/aws-servicebroker | c301912e7df3a2f09a9c34d3ae7ffe67c55aa3a0 | sample-apps/rds/sample-app/src/pymysql/cursors.py | python | SSCursor.fetchall | (self) | return list(self.fetchall_unbuffered()) | Fetch all, as per MySQLdb. Pretty useless for large queries, as
it is buffered. See fetchall_unbuffered(), if you want an unbuffered
generator version of this method. | Fetch all, as per MySQLdb. Pretty useless for large queries, as
it is buffered. See fetchall_unbuffered(), if you want an unbuffered
generator version of this method. | [
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"""
Fetch all, as per MySQLdb. Pretty useless for large queries, as
it is buffered. See fetchall_unbuffered(), if you want an unbuffered
generator version of this method.
"""
return list(self.fetchall_unbuffered()) | [
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mwaskom/seaborn | 77e3b6b03763d24cc99a8134ee9a6f43b32b8e7b | seaborn/_decorators.py | python | _deprecate_positional_args | (f) | return inner_f | Decorator for methods that issues warnings for positional arguments.
Using the keyword-only argument syntax in pep 3102, arguments after the
* will issue a warning when passed as a positional argument.
Parameters
----------
f : function
function to check arguments on | Decorator for methods that issues warnings for positional arguments. | [
"Decorator",
"for",
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"that",
"issues",
"warnings",
"for",
"positional",
"arguments",
"."
] | def _deprecate_positional_args(f):
"""Decorator for methods that issues warnings for positional arguments.
Using the keyword-only argument syntax in pep 3102, arguments after the
* will issue a warning when passed as a positional argument.
Parameters
----------
f : function
function to check arguments on
"""
sig = signature(f)
kwonly_args = []
all_args = []
for name, param in sig.parameters.items():
if param.kind == Parameter.POSITIONAL_OR_KEYWORD:
all_args.append(name)
elif param.kind == Parameter.KEYWORD_ONLY:
kwonly_args.append(name)
@wraps(f)
def inner_f(*args, **kwargs):
extra_args = len(args) - len(all_args)
if extra_args > 0:
plural = "s" if extra_args > 1 else ""
article = "" if plural else "a "
warnings.warn(
"Pass the following variable{} as {}keyword arg{}: {}. "
"From version 0.12, the only valid positional argument "
"will be `data`, and passing other arguments without an "
"explicit keyword will result in an error or misinterpretation."
.format(plural, article, plural,
", ".join(kwonly_args[:extra_args])),
FutureWarning
)
kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})
return f(**kwargs)
return inner_f | [
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rcorcs/NatI | fdf014f4292afdc95250add7b6658468043228e1 | en/parser/nltk_lite/contrib/paradigm.py | python | Domain.getHorizontalHTML | (self,p_parentSpan=1) | return "<tr>" + ret_string*p_parentSpan + "</tr>" | Return a horizontal html table | Return a horizontal html table | [
"Return",
"a",
"horizontal",
"html",
"table"
] | def getHorizontalHTML(self,p_parentSpan=1):
"""
Return a horizontal html table
"""
ret_string = ""
for item in self.getList():
ret_string += "<td>" + item + "</td>"
return "<tr>" + ret_string*p_parentSpan + "</tr>" | [
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vita-epfl/monoloco | f5e82c48e8ee5af352f2c9b1690050f4e02fc1b6 | monoloco/utils/iou.py | python | reorder_matches | (matches, boxes, mode='left_rigth') | return [matches[matches_left.index(idx_boxes)] for idx_boxes in ordered_boxes if idx_boxes in matches_left] | Reorder a list of (idx, idx_gt) matches based on position of the detections in the image
ordered_boxes = (5, 6, 7, 0, 1, 4, 2, 4)
matches = [(0, x), (2,x), (4,x), (3,x), (5,x)]
Output --> [(5, x), (0, x), (3, x), (2, x), (5, x)] | Reorder a list of (idx, idx_gt) matches based on position of the detections in the image
ordered_boxes = (5, 6, 7, 0, 1, 4, 2, 4)
matches = [(0, x), (2,x), (4,x), (3,x), (5,x)]
Output --> [(5, x), (0, x), (3, x), (2, x), (5, x)] | [
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"""
Reorder a list of (idx, idx_gt) matches based on position of the detections in the image
ordered_boxes = (5, 6, 7, 0, 1, 4, 2, 4)
matches = [(0, x), (2,x), (4,x), (3,x), (5,x)]
Output --> [(5, x), (0, x), (3, x), (2, x), (5, x)]
"""
assert mode == 'left_right'
# Order the boxes based on the left-right position in the image and
ordered_boxes = np.argsort([box[0] for box in boxes]) # indices of boxes ordered from left to right
matches_left = [int(idx) for (idx, _) in matches]
return [matches[matches_left.index(idx_boxes)] for idx_boxes in ordered_boxes if idx_boxes in matches_left] | [
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bsolomon1124/pyfinance | c6fd88ba4fb5c9f083ebc3ff60960a1b4df76c55 | pyfinance/returns.py | python | TSeries.rsq_adj | (self, benchmark, **kwargs) | return self.CAPM(benchmark, **kwargs).rsq_adj | Adjusted R-squared.
Formula: 1. - ((1. - `self._rsq`) * (n - 1.) / (n - k - 1.))
Parameters
----------
benchmark : {pd.Series, TSeries, pd.DataFrame, np.ndarray}
The benchmark securitie(s) to which `self` is compared.
**kwargs
Passed to pyfinance.ols.OLS().
Returns
-------
float | Adjusted R-squared. | [
"Adjusted",
"R",
"-",
"squared",
"."
] | def rsq_adj(self, benchmark, **kwargs):
"""Adjusted R-squared.
Formula: 1. - ((1. - `self._rsq`) * (n - 1.) / (n - k - 1.))
Parameters
----------
benchmark : {pd.Series, TSeries, pd.DataFrame, np.ndarray}
The benchmark securitie(s) to which `self` is compared.
**kwargs
Passed to pyfinance.ols.OLS().
Returns
-------
float
"""
return self.CAPM(benchmark, **kwargs).rsq_adj | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/combinat/dyck_word.py | python | DyckWord.number_of_double_rises | (self) | return len(self.positions_of_double_rises()) | r"""
Return a the number of positions in ``self`` where there are two
consecutive `1`'s.
EXAMPLES::
sage: DyckWord([1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0]).number_of_double_rises()
2
sage: DyckWord([1, 1, 0, 0]).number_of_double_rises()
1
sage: DyckWord([1, 0, 1, 0]).number_of_double_rises()
0 | r"""
Return a the number of positions in ``self`` where there are two
consecutive `1`'s. | [
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] | def number_of_double_rises(self) -> int:
r"""
Return a the number of positions in ``self`` where there are two
consecutive `1`'s.
EXAMPLES::
sage: DyckWord([1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 0, 1, 0]).number_of_double_rises()
2
sage: DyckWord([1, 1, 0, 0]).number_of_double_rises()
1
sage: DyckWord([1, 0, 1, 0]).number_of_double_rises()
0
"""
return len(self.positions_of_double_rises()) | [
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marinho/geraldo | 868ebdce67176d9b6205cddc92476f642c783fff | site/newsite/django_1_0/django/utils/_decimal.py | python | Decimal.sqrt | (self, context=None) | return ans._fix(context) | Return the square root of self.
Uses a converging algorithm (Xn+1 = 0.5*(Xn + self / Xn))
Should quadratically approach the right answer. | Return the square root of self. | [
"Return",
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"of",
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"."
] | def sqrt(self, context=None):
"""Return the square root of self.
Uses a converging algorithm (Xn+1 = 0.5*(Xn + self / Xn))
Should quadratically approach the right answer.
"""
if self._is_special:
ans = self._check_nans(context=context)
if ans:
return ans
if self._isinfinity() and self._sign == 0:
return Decimal(self)
if not self:
#exponent = self._exp / 2, using round_down.
#if self._exp < 0:
# exp = (self._exp+1) // 2
#else:
exp = (self._exp) // 2
if self._sign == 1:
#sqrt(-0) = -0
return Decimal( (1, (0,), exp))
else:
return Decimal( (0, (0,), exp))
if context is None:
context = getcontext()
if self._sign == 1:
return context._raise_error(InvalidOperation, 'sqrt(-x), x > 0')
tmp = Decimal(self)
expadd = tmp._exp // 2
if tmp._exp & 1:
tmp._int += (0,)
tmp._exp = 0
else:
tmp._exp = 0
context = context._shallow_copy()
flags = context._ignore_all_flags()
firstprec = context.prec
context.prec = 3
if tmp.adjusted() & 1 == 0:
ans = Decimal( (0, (8,1,9), tmp.adjusted() - 2) )
ans = ans.__add__(tmp.__mul__(Decimal((0, (2,5,9), -2)),
context=context), context=context)
ans._exp -= 1 + tmp.adjusted() // 2
else:
ans = Decimal( (0, (2,5,9), tmp._exp + len(tmp._int)- 3) )
ans = ans.__add__(tmp.__mul__(Decimal((0, (8,1,9), -3)),
context=context), context=context)
ans._exp -= 1 + tmp.adjusted() // 2
#ans is now a linear approximation.
Emax, Emin = context.Emax, context.Emin
context.Emax, context.Emin = DefaultContext.Emax, DefaultContext.Emin
half = Decimal('0.5')
maxp = firstprec + 2
rounding = context._set_rounding(ROUND_HALF_EVEN)
while 1:
context.prec = min(2*context.prec - 2, maxp)
ans = half.__mul__(ans.__add__(tmp.__div__(ans, context=context),
context=context), context=context)
if context.prec == maxp:
break
#round to the answer's precision-- the only error can be 1 ulp.
context.prec = firstprec
prevexp = ans.adjusted()
ans = ans._round(context=context)
#Now, check if the other last digits are better.
context.prec = firstprec + 1
# In case we rounded up another digit and we should actually go lower.
if prevexp != ans.adjusted():
ans._int += (0,)
ans._exp -= 1
lower = ans.__sub__(Decimal((0, (5,), ans._exp-1)), context=context)
context._set_rounding(ROUND_UP)
if lower.__mul__(lower, context=context) > (tmp):
ans = ans.__sub__(Decimal((0, (1,), ans._exp)), context=context)
else:
upper = ans.__add__(Decimal((0, (5,), ans._exp-1)),context=context)
context._set_rounding(ROUND_DOWN)
if upper.__mul__(upper, context=context) < tmp:
ans = ans.__add__(Decimal((0, (1,), ans._exp)),context=context)
ans._exp += expadd
context.prec = firstprec
context.rounding = rounding
ans = ans._fix(context)
rounding = context._set_rounding_decision(NEVER_ROUND)
if not ans.__mul__(ans, context=context) == self:
# Only rounded/inexact if here.
context._regard_flags(flags)
context._raise_error(Rounded)
context._raise_error(Inexact)
else:
#Exact answer, so let's set the exponent right.
#if self._exp < 0:
# exp = (self._exp +1)// 2
#else:
exp = self._exp // 2
context.prec += ans._exp - exp
ans = ans._rescale(exp, context=context)
context.prec = firstprec
context._regard_flags(flags)
context.Emax, context.Emin = Emax, Emin
return ans._fix(context) | [
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wit-ai/pywit | 365b33ac25d503285442e37201dff7bc10dd6ff0 | wit/wit.py | python | Wit.create_app_version | (self, app_id, tag_name, headers=None, verbose=None) | return resp | Create a new version of your app.
:param app_id: ID of existing app
:param tag_name: name of tag | Create a new version of your app.
:param app_id: ID of existing app
:param tag_name: name of tag | [
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"""
Create a new version of your app.
:param app_id: ID of existing app
:param tag_name: name of tag
"""
params = {}
headers = headers or {}
data = {"tag":tag_name}
endpoint = '/apps/' + app_id + "/tags/"
if verbose:
params['verbose'] = verbose
resp = req(self.logger, self.access_token, 'POST', endpoint, params, json=data , headers=headers)
return resp | [
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zynga/jasy | 8a2ec2c2ca3f6c0f73cba4306e581c89b30f1b18 | jasy/js/optimize/BlockReducer.py | python | cleanParens | (node) | Automatically tries to remove superfluous parens which are sometimes added for more clearance
and readability but which are not required for parsing and just produce overhead. | Automatically tries to remove superfluous parens which are sometimes added for more clearance
and readability but which are not required for parsing and just produce overhead. | [
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] | def cleanParens(node):
"""
Automatically tries to remove superfluous parens which are sometimes added for more clearance
and readability but which are not required for parsing and just produce overhead.
"""
parent = node.parent
if node.type == "function":
# Ignore for direct execution functions. This is required
# for parsing e.g. (function(){})(); which does not work
# without parens around the function instance other than
# priorities might suggest. It only works this way when being
# part of assignment/declaration.
if parent.type == "call" and parent.parent.type in ("declaration", "assign"):
node.parenthesized = False
# Need to make sure to not modify in cases where we use a "dot" operator e.g.
# var x = (function(){ return 1; }).hide();
elif node.type == "assign" and parent.type == "hook":
node.parenthesized = node.rel == "condition"
elif getattr(node, "rel", None) == "condition":
# inside a condition e.g. while(condition) or for(;condition;) we do not need
# parens aroudn an expression
node.parenthesized = False
elif node.type in jasy.js.parse.Lang.expressions and parent.type == "return":
# Returns never need parens around the expression
node.parenthesized = False
elif node.type in jasy.js.parse.Lang.expressions and parent.type == "list" and parent.parent.type == "call":
# Parameters don't need to be wrapped in parans
node.parenthesized = False
elif node.type in ("new", "string", "number", "boolean") and parent.type == "dot":
# Constructs like (new foo.bar.Object).doSomething()
# "new" is defined with higher priority than "dot" but in
# this case it does not work without parens. Interestingly
# the same works without issues when having "new_with_args"
# instead like: new foo.bar.Object("param").doSomething()
pass
elif node.type == "unary_plus" or node.type == "unary_minus":
# Prevent unary operators from getting joined with parent
# x+(+x) => x++x => FAIL
pass
elif node.type in jasy.js.parse.Lang.expressions and parent.type in jasy.js.parse.Lang.expressions:
prio = jasy.js.parse.Lang.expressionOrder[node.type]
parentPrio = jasy.js.parse.Lang.expressionOrder[node.parent.type]
# Only higher priorities are optimized. Others are just to complex e.g.
# "hello" + (3+4) + "world" is not allowed to be translated to
# "hello" + 3+4 + "world"
if prio > parentPrio:
node.parenthesized = False
elif prio == parentPrio:
if node.type == "hook":
node.parenthesized = False | [
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PySimpleGUI/PySimpleGUI | 6c0d1fb54f493d45e90180b322fbbe70f7a5af3c | DemoPrograms/Demo_Desktop_Widget_Drive_Usage.py | python | update_window | (window) | [] | def update_window(window):
particians = psutil.disk_partitions()
for count, part in enumerate(particians):
mount = part[0]
try:
usage = psutil.disk_usage(mount)
window[('-NAME-', mount)].update(mount)
window[('-PROG-', mount)].update_bar(int(usage.percent))
window[('-%-', mount)].update(f'{usage.percent}%')
window[('-STATS-', mount)].update(f'{human_size(usage.used)} / {human_size(usage.total)} = {human_size(usage.free)} free')
except:
pass | [
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holoviz/holoviews | cc6b27f01710402fdfee2aeef1507425ca78c91f | holoviews/core/dimension.py | python | ViewableTree.dimension_values | (self, dimension, expanded=True, flat=True) | Return the values along the requested dimension.
Concatenates values on all nodes with requested dimension.
Args:
dimension: The dimension to return values for
expanded (bool, optional): Whether to expand values
Whether to return the expanded values, behavior depends
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"""Return the values along the requested dimension.
Concatenates values on all nodes with requested dimension.
Args:
dimension: The dimension to return values for
expanded (bool, optional): Whether to expand values
Whether to return the expanded values, behavior depends
on the type of data:
* Columnar: If false returns unique values
* Geometry: If false returns scalar values per geometry
* Gridded: If false returns 1D coordinates
flat (bool, optional): Whether to flatten array
Returns:
NumPy array of values along the requested dimension
"""
dimension = self.get_dimension(dimension, strict=True).name
all_dims = self.traverse(lambda x: [d.name for d in x.dimensions()])
if dimension in chain.from_iterable(all_dims):
values = [el.dimension_values(dimension) for el in self
if dimension in el.dimensions(label=True)]
vals = np.concatenate(values)
return vals if expanded else util.unique_array(vals)
else:
return super().dimension_values(
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windelbouwman/ppci | 915c069e0667042c085ec42c78e9e3c9a5295324 | ppci/lang/c/codegenerator.py | python | CCodeGenerator.create_function_internal | (self, function) | Create the function and put it into the var_map | Create the function and put it into the var_map | [
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""" Create the function and put it into the var_map """
if function.storage_class == "static":
binding = ir.Binding.LOCAL
else:
binding = ir.Binding.GLOBAL
# Create ir function:
if function.typ.return_type.is_void:
ir_function = self.builder.new_procedure(function.name, binding)
elif function.typ.return_type.is_struct:
# Pass implicit first argument to function when complex type
# is returned.
ir_function = self.builder.new_procedure(function.name, binding)
return_value_address = ir.Parameter("return_value_address", ir.ptr)
ir_function.add_parameter(return_value_address)
else:
return_type = self.get_ir_type(function.typ.return_type)
ir_function = self.builder.new_function(
function.name, binding, return_type
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self.ir_var_map[function] = ir_function | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/combinat/root_system/cartan_type.py | python | CartanTypeFactory._samples | (self) | return finite_crystallographic + \
[CartanType(t) for t in [["I", 5], ["H", 3], ["H", 4]]] + \
[t.affine() for t in finite_crystallographic if t.is_irreducible()] + \
[CartanType(t) for t in [["BC", 1, 2], ["BC", 5, 2]]] + \
[CartanType(t).dual() for t in [["B", 5, 1], ["C", 4, 1], ["F", 4, 1], ["G", 2, 1],["BC", 1, 2], ["BC", 5, 2]]] | Return a sample of all implemented Cartan types.
.. NOTE:: This is intended to be used through :meth:`samples`.
EXAMPLES::
sage: CartanType._samples()
[['A', 1], ['A', 5], ['B', 1], ['B', 5], ['C', 1], ['C', 5], ['D', 2], ['D', 3], ['D', 5],
['E', 6], ['E', 7], ['E', 8], ['F', 4], ['G', 2], ['I', 5], ['H', 3], ['H', 4],
['A', 1, 1], ['A', 5, 1], ['B', 1, 1], ['B', 5, 1],
['C', 1, 1], ['C', 5, 1], ['D', 3, 1], ['D', 5, 1],
['E', 6, 1], ['E', 7, 1], ['E', 8, 1], ['F', 4, 1], ['G', 2, 1], ['BC', 1, 2], ['BC', 5, 2],
['B', 5, 1]^*, ['C', 4, 1]^*, ['F', 4, 1]^*, ['G', 2, 1]^*, ['BC', 1, 2]^*, ['BC', 5, 2]^*] | Return a sample of all implemented Cartan types. | [
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] | def _samples(self):
"""
Return a sample of all implemented Cartan types.
.. NOTE:: This is intended to be used through :meth:`samples`.
EXAMPLES::
sage: CartanType._samples()
[['A', 1], ['A', 5], ['B', 1], ['B', 5], ['C', 1], ['C', 5], ['D', 2], ['D', 3], ['D', 5],
['E', 6], ['E', 7], ['E', 8], ['F', 4], ['G', 2], ['I', 5], ['H', 3], ['H', 4],
['A', 1, 1], ['A', 5, 1], ['B', 1, 1], ['B', 5, 1],
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['B', 5, 1]^*, ['C', 4, 1]^*, ['F', 4, 1]^*, ['G', 2, 1]^*, ['BC', 1, 2]^*, ['BC', 5, 2]^*]
"""
finite_crystallographic = \
[CartanType (t) for t in [['A', 1], ['A', 5], ['B', 1], ['B', 5],
['C', 1], ['C', 5], ['D', 2], ['D', 3], ['D', 5],
["E", 6], ["E", 7], ["E", 8],
["F", 4],
["G", 2]]]
# Support for hand constructed Dynkin diagrams as Cartan types is not yet ready enough for including an example here.
# from sage.combinat.root_system.dynkin_diagram import DynkinDiagram_class
# g = DynkinDiagram_class.an_instance()
return finite_crystallographic + \
[CartanType(t) for t in [["I", 5], ["H", 3], ["H", 4]]] + \
[t.affine() for t in finite_crystallographic if t.is_irreducible()] + \
[CartanType(t) for t in [["BC", 1, 2], ["BC", 5, 2]]] + \
[CartanType(t).dual() for t in [["B", 5, 1], ["C", 4, 1], ["F", 4, 1], ["G", 2, 1],["BC", 1, 2], ["BC", 5, 2]]] | [
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ghostop14/sparrow-wifi | 4b8289773ea4304872062f65a6ffc9352612b08e | wirelessengine.py | python | WirelessNetwork.getChannelString | (self) | return retVal | [] | def getChannelString(self):
if self.bandwidth == 40 and self.secondaryChannel > 0:
retVal = str(self.channel) + '+' + str(self.secondaryChannel)
else:
retVal = str(self.channel)
return retVal | [
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WikiTeam/wikiteam | 7f1f9985f667c417501f0dc872ab4fe416b6acda | wikiteam/wikiteam.py | python | getNamespaces | (config={}) | return namespacenames | Returns list of namespaces for this wiki | Returns list of namespaces for this wiki | [
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""" Returns list of namespaces for this wiki """
namespaces = []
namespacenames = []
if config['wikiengine'] == 'mediawiki':
import mediawiki
namespaces, namespacenames = mediawiki.mwGetNamespaces(config=config)
return namespacenames | [
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wenwei202/terngrad | ec4f75e9a3a1e1c4b2e6494d830fbdfdd2e03ddc | terngrad/inception/slim/ops.py | python | dropout | (inputs, keep_prob=0.5, is_training=True, scope=None) | Returns a dropout layer applied to the input.
Args:
inputs: the tensor to pass to the Dropout layer.
keep_prob: the probability of keeping each input unit.
is_training: whether or not the model is in training mode. If so, dropout is
applied and values scaled. Otherwise, inputs is returned.
scope: Optional scope for name_scope.
Returns:
a tensor representing the output of the operation. | Returns a dropout layer applied to the input. | [
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] | def dropout(inputs, keep_prob=0.5, is_training=True, scope=None):
"""Returns a dropout layer applied to the input.
Args:
inputs: the tensor to pass to the Dropout layer.
keep_prob: the probability of keeping each input unit.
is_training: whether or not the model is in training mode. If so, dropout is
applied and values scaled. Otherwise, inputs is returned.
scope: Optional scope for name_scope.
Returns:
a tensor representing the output of the operation.
"""
if is_training and keep_prob > 0:
with tf.name_scope(scope, 'Dropout', [inputs]):
return tf.nn.dropout(inputs, keep_prob)
else:
return inputs | [
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gleeda/memtriage | c24f4859995cccb9d88ccc0118d90693019cc1d5 | volatility/volatility/plugins/malware/servicediff.py | python | ServiceDiff.services_from_registry | (addr_space) | return services | Enumerate services from the cached registry hive | Enumerate services from the cached registry hive | [
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] | def services_from_registry(addr_space):
"""Enumerate services from the cached registry hive"""
services = {}
plugin = hivelist.HiveList(addr_space.get_config())
for hive in plugin.calculate():
## find the SYSTEM hive
name = hive.get_name()
if not name.lower().endswith("system"):
continue
## get the root key
hive_space = hive.address_space()
root = rawreg.get_root(hive_space)
if not root:
break
## open the services key
key = rawreg.open_key(root, ["ControlSet001", "Services"])
if not key:
break
## build a dictionary of the key names
for subkey in rawreg.subkeys(key):
services[(str(subkey.Name).lower())] = subkey
## we don't need to keep trying
break
return services | [
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Gallopsled/pwntools-write-ups | b7160403288a2d5273e89f115545a4f7fecf32af | 2014/defcon-quals/bbgp/doit.py | python | send_pkt | (cmd, payload) | Send a BGP packet | Send a BGP packet | [
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"""Send a BGP packet"""
r.send(flat(
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sidewalklabs/s2sphere | d1d067e8c06e5fbaf0cc0158bade947b4a03a438 | s2sphere/sphere.py | python | SphereInterval.get_complement_center | (self) | [] | def get_complement_center(self):
if self.lo() != self.hi():
return self.complement().get_center()
else:
if self.hi() <= 0:
return self.hi() + math.pi
else:
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oilshell/oil | 94388e7d44a9ad879b12615f6203b38596b5a2d3 | Python-2.7.13/Tools/webchecker/webchecker.py | python | MyStringIO.__init__ | (self, url, info) | [] | def __init__(self, url, info):
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self.__info = info
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hzlzh/AlfredWorkflow.com | 7055f14f6922c80ea5943839eb0caff11ae57255 | Sources/Workflows/Rotten-Tomatoes/PyAl/Request/requests/packages/oauthlib/oauth2/draft25/__init__.py | python | Client._add_mac_token | (self, uri, http_method=u'GET', body=None,
headers=None, token_placement=AUTH_HEADER) | return uri, headers, body | Add a MAC token to the request authorization header. | Add a MAC token to the request authorization header. | [
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] | def _add_mac_token(self, uri, http_method=u'GET', body=None,
headers=None, token_placement=AUTH_HEADER):
"""Add a MAC token to the request authorization header."""
headers = prepare_mac_header(self.token, uri, self.key, http_method,
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hash_algorithm=self.hash_algorithm)
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panpanpandas/ultrafinance | ce3594dbfef747cba0c39f059316df7c208aac40 | ultrafinance/dam/hbaseLib.py | python | HBaseLib.deleteTable | (self, tName) | delete table name | delete table name | [
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] | def deleteTable(self, tName):
''' delete table name '''
if self.__client.isTableEnabled(tName):
self.__client.disableTable(tName)
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getnikola/nikola | 2da876e9322e42a93f8295f950e336465c6a4ee5 | nikola/post.py | python | Post._load_data | (self) | Load data field from metadata. | Load data field from metadata. | [
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"""Load data field from metadata."""
self.data = Functionary(lambda: None, self.default_lang)
for lang in self.translations:
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openstack/barbican | a9d2b133c8dc3307974f119f9a2b23a4ba82e8ce | barbican/common/policy.py | python | reset | () | [] | def reset():
global ENFORCER
if ENFORCER:
ENFORCER.clear()
ENFORCER = None | [
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awkman/pywifi | 719baf73d8d32c623dbaf5e9de5d973face152a4 | pywifi/_wifiutil_linux.py | python | WifiUtil.scan_results | (self, obj) | return bsses | Get the AP list after scanning. | Get the AP list after scanning. | [
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"""Get the AP list after scanning."""
bsses = []
bsses_summary = self._send_cmd_to_wpas(obj['name'], 'SCAN_RESULTS', True)
bsses_summary = bsses_summary[:-1].split('\n')
if len(bsses_summary) == 1:
return bsses
for l in bsses_summary[1:]:
values = l.split('\t')
bss = Profile()
bss.bssid = values[0]
bss.freq = int(values[1])
bss.signal = int(values[2])
bss.ssid = values[4]
bss.akm = []
if 'WPA-PSK' in values[3]:
bss.akm.append(AKM_TYPE_WPAPSK)
if 'WPA2-PSK' in values[3]:
bss.akm.append(AKM_TYPE_WPA2PSK)
if 'WPA-EAP' in values[3]:
bss.akm.append(AKM_TYPE_WPA)
if 'WPA2-EAP' in values[3]:
bss.akm.append(AKM_TYPE_WPA2)
bss.auth = AUTH_ALG_OPEN
bsses.append(bss)
return bsses | [
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davidcomfort/dash_sample_dashboard | ee0c991142ac33df9945a70205017466a5b3754d | components/printButton.py | python | print_button | () | return printButton | [] | def print_button():
printButton = html.A(['Print PDF'],className="button no-print print",style={'position': "absolute", 'top': '-40', 'right': '0'})
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Kronuz/esprima-python | 809cb6e257b1d3d5b0d23f2bca7976e21f02fc3d | esprima/visitor.py | python | Visitor.generic_visit | (self, obj) | return self.visit(self.visit_Object(obj)) | [] | def generic_visit(self, obj):
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llSourcell/AI_in_Medicine_Clinical_Imaging_Classification | fee82c34a83917b47db2e57a90bdb7f9bb4d81e9 | src/rotate_images.py | python | mirror_images | (file_path, mirror_direction, lst_imgs) | Mirrors image left or right, based on criteria specified.
INPUT
file_path: file path to the folder containing images.
mirror_direction: criteria for mirroring left or right.
lst_imgs: list of image strings.
OUTPUT
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'''
Mirrors image left or right, based on criteria specified.
INPUT
file_path: file path to the folder containing images.
mirror_direction: criteria for mirroring left or right.
lst_imgs: list of image strings.
OUTPUT
Images mirrored left or right.
'''
for l in lst_imgs:
img = cv2.imread(file_path + str(l) + '.jpeg')
img = cv2.flip(img, 1)
cv2.imwrite(file_path + str(l) + '_mir' + '.jpeg', img) | [
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travisgoodspeed/goodfet | 1750cc1e8588af5470385e52fa098ca7364c2863 | client/GoodFETConsole.py | python | GoodFETConsole.CMDdump | (self,args) | [] | def CMDdump(self,args):
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vhf/confusable_homoglyphs | 14f43ddd74099520ddcda29fac557c27a28190e6 | confusable_homoglyphs/categories.py | python | category | (chr) | return a | Retrieves the unicode category for a unicode character.
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>>> categories.category('τ')
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>>> categories.category('-')
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"""Retrieves the unicode category for a unicode character.
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'L'
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>>> categories.category('-')
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:param chr: A unicode character
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_, a = aliases_categories(chr)
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donnemartin/gitsome | d7c57abc7cb66e9c910a844f15d4536866da3310 | xonsh/ply/example/BASIC/basparse.py | python | p_dimitem_single | (p) | dimitem : ID LPAREN INTEGER RPAREN | dimitem : ID LPAREN INTEGER RPAREN | [
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'''dimitem : ID LPAREN INTEGER RPAREN'''
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GoogleCloudPlatform/appengine-mapreduce | 2045eb3605b6ecb40c83d11dd5442a89fe5c5dd6 | python/src/mapreduce/input_readers.py | python | _OldAbstractDatastoreInputReader.__str__ | (self) | Returns the string representation of this InputReader. | Returns the string representation of this InputReader. | [
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"""Returns the string representation of this InputReader."""
if self._ns_range is None:
return repr(self._key_ranges)
else:
return repr(self._ns_range) | [
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ywangd/stash | 773d15b8fb3853a65c15fe160bf5584c99437170 | bin/mc.py | python | McCmd.help_usage | (self, *args) | prints help about the usage. | prints help about the usage. | [
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"""prints help about the usage."""
help = """USAGE
===============
This guide describes how to use mc.
1.) using filesystem
First, you need to connect to a filesystem.
Use the 'connect'-command for this.
Usage:
connect <id> <fsi-name> [args [args ...]]
'id' is a number used to identify the connection in commands.
The ID 0 should not be used, as it is used internally.
'fsi-name' is the name of the FSI you want to use (e.g. 'local').
'args' is passed to the FSI and may contain server, username...
Example:
connect 1 local
>opens the local filesystem.
>you can later use this filesystem by passing 1 to commands.
connect 2 ftp ftp.example.org 21 YourName YourPswd -s
>connects to FTP-server ftp.example.org on port 21
>switch over to SFTP
>login as YourName with YourPswd
>you can later use this filesystem by passing 2 to commands.
If you want to get a list of connected filesystems, use 'connected'.
If you want to disconnect, use disconnect <id>.
If you want to get a list of aviable FSIs, use help fsis.
If you want to see help on a FSI, use help fsi_<name>
2.) Using commands
After you are connected, you can use any aviable command.
To get a list of aviable commands, type '?' or 'help'.
To see the Usage of a command, use 'help <command>'.
3.) Quitting
To quit, use the 'exit' command.
4.) Tips
You can run shell commands while using mc:
!echo test
shell python
5.) Additional Info
-mc does not transfer file deletions when running a command on the remote fs
-mc may behave weird in subdirs
"""
self.stdout.write(help + "\n") | [
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semontesdeoca/MNPR | 8acf9862e38b709eba63a978d35cc658754ec9e9 | scripts/coopLib.py | python | getTransforms | (objects, fullPath=False) | return transforms | Get transform nodes of objects
Args:
objects (list): List of objects
fullPath (bool): If full path or not
Returns:
List of transform nodes | Get transform nodes of objects
Args:
objects (list): List of objects
fullPath (bool): If full path or not
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List of transform nodes | [
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"""
Get transform nodes of objects
Args:
objects (list): List of objects
fullPath (bool): If full path or not
Returns:
List of transform nodes
"""
transforms = []
for node in objects:
transforms.append(getTransform(node, fullPath))
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YaoZeyuan/ZhihuHelp_archived | a0e4a7acd4512452022ce088fff2adc6f8d30195 | src/lib/oauth/zhihu_oauth/zhcls/me.py | python | Me.whispers | (self) | return None | 私信列表 | 私信列表 | [
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私信列表
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insarlab/MintPy | 4357b8c726dec8a3f936770e3f3dda92882685b7 | mintpy/image_stitch.py | python | get_corners | (atr) | return S, N, W, E, width, length | Get corners coordinate. | Get corners coordinate. | [
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] | def get_corners(atr):
"""Get corners coordinate."""
length = int(atr['LENGTH'])
width = int(atr['WIDTH'])
W = float(atr['X_FIRST'])
N = float(atr['Y_FIRST'])
lon_step = float(atr['X_STEP'])
lat_step = float(atr['Y_STEP'])
S = N + lat_step * length
E = W + lon_step * width
return S, N, W, E, width, length | [
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flyingpot/pytorch_deephash | fbd94a2cfe1c20ef833eca8cfb1dc7010ae22805 | net.py | python | AlexNetPlusLatent.forward | (self, x) | return features, result | [] | def forward(self, x):
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home-assistant/core | 265ebd17a3f17ed8dc1e9bdede03ac8e323f1ab1 | homeassistant/components/xbee/switch.py | python | setup_platform | (
hass: HomeAssistant,
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discovery_info: DiscoveryInfoType | None = None,
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google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/server/grr_response_server/gui/api_plugins/user.py | python | _GetAllUsernames | () | return sorted(user.username for user in data_store.REL_DB.ReadGRRUsers()) | [] | def _GetAllUsernames():
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jupyter/enterprise_gateway | 1a529b13f3d9ab94411e4751d4bd35bafd6bbc2e | enterprise_gateway/services/kernels/remotemanager.py | python | RemoteKernelManager._link_dependent_props | (self) | Ensure that RemoteKernelManager, when used as part of an EnterpriseGatewayApp,
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simondlevy/AirSimTensorFlow | 998fec23f3d717d8aa5d407bfc41c4ad05e2c208 | tf_softmax_layer.py | python | inference | (x, xsize, ysize, W_vals=0, b_vals=0) | return output | This is a general-purpose softmax inference layer implementation. | This is a general-purpose softmax inference layer implementation. | [
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This is a general-purpose softmax inference layer implementation.
'''
W_init = tf.constant_initializer(value=W_vals)
b_init = tf.constant_initializer(value=b_vals)
W = tf.get_variable('W', [xsize, ysize], initializer=W_init)
b = tf.get_variable('b', [ysize], initializer=b_init)
output = tf.nn.softmax(tf.matmul(x, W) + b)
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... | https://github.com/simondlevy/AirSimTensorFlow/blob/998fec23f3d717d8aa5d407bfc41c4ad05e2c208/tf_softmax_layer.py#L18-L28 | |
JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | chap19/monitor/monitor/monitor/openstack/common/timeutils.py | python | isotime | (at=None, subsecond=False) | return st | Stringify time in ISO 8601 format | Stringify time in ISO 8601 format | [
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] | def isotime(at=None, subsecond=False):
"""Stringify time in ISO 8601 format"""
if not at:
at = utcnow()
st = at.strftime(_ISO8601_TIME_FORMAT
if not subsecond
else _ISO8601_TIME_FORMAT_SUBSECOND)
tz = at.tzinfo.tzname(None) if at.tzinfo else 'UTC'
st += ('Z' if tz == 'UTC' else tz)
return st | [
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DataDog/integrations-core | 934674b29d94b70ccc008f76ea172d0cdae05e1e | istio/datadog_checks/istio/config_models/defaults.py | python | instance_skip_proxy | (field, value) | return False | [] | def instance_skip_proxy(field, value):
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cuthbertLab/music21 | bd30d4663e52955ed922c10fdf541419d8c67671 | music21/braille/noteGrouping.py | python | NoteGroupingTranscriber.showClefSigns | (self) | Generally, in Braille, clef signs are not used. However, they
can be shown for pedagogical purposes or to make a facsimile
transcription of the sighted text.
If not set but self.brailleElementGrouping.showClefSigns
is set, uses that instead.
>>> ngt = braille.noteGrouping.NoteGroupingTranscriber()
>>> ngt.showClefSigns
False
>>> beg = braille.segment.BrailleElementGrouping()
>>> ngt.brailleElementGrouping = beg
>>> ngt.showClefSigns
False
>>> beg.showClefSigns = True
>>> ngt.showClefSigns
True
>>> ngt.showClefSigns = False
>>> ngt.showClefSigns
False | Generally, in Braille, clef signs are not used. However, they
can be shown for pedagogical purposes or to make a facsimile
transcription of the sighted text. | [
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'''
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transcription of the sighted text.
If not set but self.brailleElementGrouping.showClefSigns
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>>> ngt.showClefSigns
False
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>>> ngt.brailleElementGrouping = beg
>>> ngt.showClefSigns
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>>> beg.showClefSigns = True
>>> ngt.showClefSigns
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>>> ngt.showClefSigns = False
>>> ngt.showClefSigns
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'''
if self._showClefSigns is not None:
return self._showClefSigns
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qiime2/qiime2 | 3906f67c70a1321e99e7fc59e79550c2432a8cee | qiime2/core/type/signature.py | python | PipelineSignature.__init__ | (self, callable, inputs, parameters, outputs,
input_descriptions=None, parameter_descriptions=None,
output_descriptions=None) | Parameters
----------
callable : callable
Callable with view type annotations on parameters and return.
inputs : dict
Parameter name to semantic type.
parameters : dict
Parameter name to primitive type.
outputs : list of tuple
Each tuple contains the name of the output (str) and its QIIME
type.
input_descriptions : dict, optional
Input name to description string.
parameter_descriptions : dict, optional
Parameter name to description string.
output_descriptions : dict, optional
Output name to description string. | [] | def __init__(self, callable, inputs, parameters, outputs,
input_descriptions=None, parameter_descriptions=None,
output_descriptions=None):
"""
Parameters
----------
callable : callable
Callable with view type annotations on parameters and return.
inputs : dict
Parameter name to semantic type.
parameters : dict
Parameter name to primitive type.
outputs : list of tuple
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input_descriptions : dict, optional
Input name to description string.
parameter_descriptions : dict, optional
Parameter name to description string.
output_descriptions : dict, optional
Output name to description string.
"""
inputs, parameters, outputs, signature_order = \
self._parse_signature(callable, inputs, parameters, outputs,
input_descriptions, parameter_descriptions,
output_descriptions)
self._assert_valid_inputs(inputs)
self._assert_valid_parameters(parameters)
self._assert_valid_outputs(outputs)
self._assert_valid_views(inputs, parameters, outputs)
self.inputs = inputs
self.parameters = parameters
self.outputs = outputs
self.signature_order = signature_order | [
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richardaecn/class-balanced-loss | 1d7857208a2abc03d84e35a9d5383af8225d4b4d | tpu/models/experimental/distribution_strategy/resnet_preprocessing.py | python | _decode_and_center_crop | (image_bytes, image_size) | return image | Crops to center of image with padding then scales image_size. | Crops to center of image with padding then scales image_size. | [
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"""Crops to center of image with padding then scales image_size."""
shape = tf.image.extract_jpeg_shape(image_bytes)
image_height = shape[0]
image_width = shape[1]
padded_center_crop_size = tf.cast(
((image_size / (image_size + CROP_PADDING)) *
tf.cast(tf.minimum(image_height, image_width), tf.float32)),
tf.int32)
offset_height = ((image_height - padded_center_crop_size) + 1) // 2
offset_width = ((image_width - padded_center_crop_size) + 1) // 2
crop_window = tf.stack([offset_height, offset_width,
padded_center_crop_size, padded_center_crop_size])
image = tf.image.decode_and_crop_jpeg(image_bytes, crop_window, channels=3)
image = tf.image.resize_bicubic([image], [image_size, image_size])[0]
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bspaans/python-mingus | 6558cacffeaab4f084a3eedda12b0e86fd24c430 | mingus/core/value.py | python | subtract | (value1, value2) | return 1 / (1.0 / value1 - 1.0 / value2) | Return the note value for value1 minus value2.
There are no exceptions for producing negative values, which can be
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Example:
>>> subtract(quarter, eighth)
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"""Return the note value for value1 minus value2.
There are no exceptions for producing negative values, which can be
useful for taking differences.
Example:
>>> subtract(quarter, eighth)
8.0
"""
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xiaolonw/TimeCycle | 16d33ac0fb0a08105a9ca781c7b1b36898e3b601 | utils/torch_util.py | python | BatchTensorToVars.__call__ | (self, batch) | return batch_var | [] | def __call__(self, batch):
batch_var = {}
for key,value in batch.items():
if isinstance(value,torch.Tensor) and not self.use_cuda:
batch_var[key] = Variable(value,requires_grad=False)
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twilio/twilio-python | 6e1e811ea57a1edfadd5161ace87397c563f6915 | twilio/rest/taskrouter/v1/workspace/task_queue/__init__.py | python | TaskQueueInstance.links | (self) | return self._properties['links'] | :returns: The URLs of related resources
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"""
:returns: The URLs of related resources
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JacquesLucke/animation_nodes | b1e3ace8dcb0a771fd882fc3ac4e490b009fa0d1 | animation_nodes/base_types/nodes/base_node.py | python | AnimationNode.iterInputSocketsWithTemplate | (self) | [] | def iterInputSocketsWithTemplate(self):
inputsInfo = infoByNode[self.identifier].inputs
for socket in self.inputs:
yield (socket, inputsInfo[socket.identifier].template) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_flaskbb/lib/python2.7/site.py | python | fixclasspath | () | Adjust the special classpath sys.path entries for Jython. These
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"""Adjust the special classpath sys.path entries for Jython. These
entries should follow the base virtualenv lib directories.
"""
paths = []
classpaths = []
for path in sys.path:
if path == '__classpath__' or path.startswith('__pyclasspath__'):
classpaths.append(path)
else:
paths.append(path)
sys.path = paths
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PaulSonOfLars/tgbot | 0ece72778b7772725ab214fe0929daaa2fc7d2d1 | tg_bot/modules/warns.py | python | warns | (bot: Bot, update: Update, args: List[str]) | [] | def warns(bot: Bot, update: Update, args: List[str]):
message = update.effective_message # type: Optional[Message]
chat = update.effective_chat # type: Optional[Chat]
user_id = extract_user(message, args) or update.effective_user.id
result = sql.get_warns(user_id, chat.id)
if result and result[0] != 0:
num_warns, reasons = result
limit, soft_warn = sql.get_warn_setting(chat.id)
if reasons:
text = "This user has {}/{} warnings, for the following reasons:".format(num_warns, limit)
for reason in reasons:
text += "\n - {}".format(reason)
msgs = split_message(text)
for msg in msgs:
update.effective_message.reply_text(msg)
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update.effective_message.reply_text(
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update.effective_message.reply_text("This user hasn't got any warnings!") | [
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JulianEberius/SublimePythonIDE | d70e40abc0c9f347af3204c7b910e0d6bfd6e459 | server/lib/python2/rope/base/project.py | python | _Project.remove_observer | (self, observer) | Remove a registered `ResourceObserver` | Remove a registered `ResourceObserver` | [
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sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/groups/abelian_gps/dual_abelian_group.py | python | DualAbelianGroup_class.__str__ | (self) | return s | Print method.
EXAMPLES::
sage: F = AbelianGroup(3,[5,64,729], names=list("abc"))
sage: Fd = F.dual_group(base_ring=CC)
sage: print(Fd)
DualAbelianGroup( AbelianGroup ( 3, (5, 64, 729) ) ) | Print method. | [
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"""
Print method.
EXAMPLES::
sage: F = AbelianGroup(3,[5,64,729], names=list("abc"))
sage: Fd = F.dual_group(base_ring=CC)
sage: print(Fd)
DualAbelianGroup( AbelianGroup ( 3, (5, 64, 729) ) )
"""
s = "DualAbelianGroup( AbelianGroup ( %s, %s ) )"%(self.ngens(), self.gens_orders())
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openhatch/oh-mainline | ce29352a034e1223141dcc2f317030bbc3359a51 | vendor/packages/south/south/modelsinspector.py | python | add_ignored_fields | (patterns) | Allows you to add some ignore field patterns. | Allows you to add some ignore field patterns. | [
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assert isinstance(patterns, (list, tuple))
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lixinsu/RCZoo | 37fcb7962fbd4c751c561d4a0c84173881ea8339 | scripts/reader/extract_eval_results.py | python | compare_result | (files) | [] | def compare_result(files):
results = {}
for ifile in files:
print(ifile.split('/')[-1])
save_name = ifile.split('/')[-1].split('.')[0]
res = extract_file(ifile)
results['%s-EM' % save_name] = [float(ires[1]) for ires in res]
results['%s-F1' % save_name] = [float(ires[2]) for ires in res]
pd.DataFrame.from_dict(results).to_csv('compare.csv', sep=',') | [
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marcoeilers/nagini | a2a19df7d833e67841e03c9885869c3dddef3327 | src/nagini_translation/translators/obligation/obligation_info.py | python | PythonLoopObligationInfo.get_prepend_body | (self) | return self._prepend_body | Return statements to be prepended to the loop body. | Return statements to be prepended to the loop body. | [
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feisuzhu/thbattle | ac0dee1b2d86de7664289cf432b157ef25427ba1 | tools/THB.app/Contents/Resources/pycparser.egg/pycparser/c_parser.py | python | CParser.p_expression | (self, p) | expression : assignment_expression
| expression COMMA assignment_expression | expression : assignment_expression
| expression COMMA assignment_expression | [
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""" expression : assignment_expression
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p[0] = p[1]
else:
if not isinstance(p[1], c_ast.ExprList):
p[1] = c_ast.ExprList([p[1]], p[1].coord)
p[1].exprs.append(p[3])
p[0] = p[1] | [
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IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/CPython/27/Lib/idlelib/EditorWindow.py | python | EditorWindow._filename_to_unicode | (self, filename) | convert filename to unicode in order to display it in Tk | convert filename to unicode in order to display it in Tk | [
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] | def _filename_to_unicode(self, filename):
"""convert filename to unicode in order to display it in Tk"""
if isinstance(filename, unicode) or not filename:
return filename
else:
try:
return filename.decode(self.filesystemencoding)
except UnicodeDecodeError:
# XXX
try:
return filename.decode(self.encoding)
except UnicodeDecodeError:
# byte-to-byte conversion
return filename.decode('iso8859-1') | [
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cbfinn/maml_rl | 9c8e2ebd741cb0c7b8bf2d040c4caeeb8e06cc95 | rllab/regressors/categorical_mlp_regressor.py | python | CategoricalMLPRegressor.__init__ | (
self,
input_shape,
output_dim,
prob_network=None,
hidden_sizes=(32, 32),
hidden_nonlinearity=NL.rectify,
optimizer=None,
use_trust_region=True,
step_size=0.01,
normalize_inputs=True,
name=None,
) | :param input_shape: Shape of the input data.
:param output_dim: Dimension of output.
:param hidden_sizes: Number of hidden units of each layer of the mean network.
:param hidden_nonlinearity: Non-linearity used for each layer of the mean network.
:param optimizer: Optimizer for minimizing the negative log-likelihood.
:param use_trust_region: Whether to use trust region constraint.
:param step_size: KL divergence constraint for each iteration | :param input_shape: Shape of the input data.
:param output_dim: Dimension of output.
:param hidden_sizes: Number of hidden units of each layer of the mean network.
:param hidden_nonlinearity: Non-linearity used for each layer of the mean network.
:param optimizer: Optimizer for minimizing the negative log-likelihood.
:param use_trust_region: Whether to use trust region constraint.
:param step_size: KL divergence constraint for each iteration | [
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self,
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prob_network=None,
hidden_sizes=(32, 32),
hidden_nonlinearity=NL.rectify,
optimizer=None,
use_trust_region=True,
step_size=0.01,
normalize_inputs=True,
name=None,
):
"""
:param input_shape: Shape of the input data.
:param output_dim: Dimension of output.
:param hidden_sizes: Number of hidden units of each layer of the mean network.
:param hidden_nonlinearity: Non-linearity used for each layer of the mean network.
:param optimizer: Optimizer for minimizing the negative log-likelihood.
:param use_trust_region: Whether to use trust region constraint.
:param step_size: KL divergence constraint for each iteration
"""
Serializable.quick_init(self, locals())
if optimizer is None:
if use_trust_region:
optimizer = PenaltyLbfgsOptimizer()
else:
optimizer = LbfgsOptimizer()
self.output_dim = output_dim
self._optimizer = optimizer
if prob_network is None:
prob_network = MLP(
input_shape=input_shape,
output_dim=output_dim,
hidden_sizes=hidden_sizes,
hidden_nonlinearity=hidden_nonlinearity,
output_nonlinearity=NL.softmax,
)
l_prob = prob_network.output_layer
LasagnePowered.__init__(self, [l_prob])
xs_var = prob_network.input_layer.input_var
ys_var = TT.imatrix("ys")
old_prob_var = TT.matrix("old_prob")
x_mean_var = theano.shared(
np.zeros((1,) + input_shape),
name="x_mean",
broadcastable=(True,) + (False,) * len(input_shape)
)
x_std_var = theano.shared(
np.ones((1,) + input_shape),
name="x_std",
broadcastable=(True,) + (False,) * len(input_shape)
)
normalized_xs_var = (xs_var - x_mean_var) / x_std_var
prob_var = L.get_output(l_prob, {prob_network.input_layer: normalized_xs_var})
old_info_vars = dict(prob=old_prob_var)
info_vars = dict(prob=prob_var)
dist = self._dist = Categorical(output_dim)
mean_kl = TT.mean(dist.kl_sym(old_info_vars, info_vars))
loss = - TT.mean(dist.log_likelihood_sym(ys_var, info_vars))
predicted = special.to_onehot_sym(TT.argmax(prob_var, axis=1), output_dim)
self._f_predict = ext.compile_function([xs_var], predicted)
self._f_prob = ext.compile_function([xs_var], prob_var)
self._prob_network = prob_network
self._l_prob = l_prob
optimizer_args = dict(
loss=loss,
target=self,
network_outputs=[prob_var],
)
if use_trust_region:
optimizer_args["leq_constraint"] = (mean_kl, step_size)
optimizer_args["inputs"] = [xs_var, ys_var, old_prob_var]
else:
optimizer_args["inputs"] = [xs_var, ys_var]
self._optimizer.update_opt(**optimizer_args)
self._use_trust_region = use_trust_region
self._name = name
self._normalize_inputs = normalize_inputs
self._x_mean_var = x_mean_var
self._x_std_var = x_std_var | [
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scrapinghub/frontera | 84f9e1034d2868447db88e865596c0fbb32e70f6 | frontera/contrib/messagebus/zeromq/socket_config.py | python | SocketConfig.db_in | (self) | return 'tcp://%s:%d' % (self.ip_addr, self.base_port + 4) | TCP socket for incoming messages | TCP socket for incoming messages | [
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"""
TCP socket for incoming messages
"""
return 'tcp://%s:%d' % (self.ip_addr, self.base_port + 4) | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/wagtail_bak/contrib/modeladmin/views.py | python | InspectView.get_field_label | (self, field_name, field=None) | return label | Return a label to display for a field | Return a label to display for a field | [
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] | def get_field_label(self, field_name, field=None):
""" Return a label to display for a field """
label = None
if field is not None:
label = getattr(field, 'verbose_name', None)
if label is None:
label = getattr(field, 'name', None)
if label is None:
label = field_name
return label | [
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benknight/hue-alfred-workflow | 4447ba61116caf4a448b50c4bfb866565d66d81e | logic/packages/requests/models.py | python | RequestEncodingMixin.path_url | (self) | return ''.join(url) | Build the path URL to use. | Build the path URL to use. | [
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"""Build the path URL to use."""
url = []
p = urlsplit(self.url)
path = p.path
if not path:
path = '/'
url.append(path)
query = p.query
if query:
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url.append(query)
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IBM/lale | b4d6829c143a4735b06083a0e6c70d2cca244162 | lale/lib/sklearn/stacking_regressor.py | python | _StackingRegressorImpl._concatenate_predictions | (self, X, predictions) | return _concatenate_predictions_pandas(self, X, predictions) | [] | def _concatenate_predictions(self, X, predictions):
if not isinstance(X, pd.DataFrame):
return super()._concatenate_predictions(X, predictions)
return _concatenate_predictions_pandas(self, X, predictions) | [
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rossant/galry | 6201fa32fb5c9ef3cea700cc22caf52fb69ebe31 | experimental/gallery.py | python | anim | (fig, (t,)) | [] | def anim(fig, (t,)):
global CURRENT_IMAGE
image_last_loaded = pw.current()
# Skip if current image in memory is None.
if image_last_loaded is None or np.array_equal(image_last_loaded, pw.EMPTY):
return
# Update only if current displayed image is empty, and current image in
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if (CURRENT_IMAGE is None or np.array_equal(CURRENT_IMAGE, pw.EMPTY)):
print "update"
CURRENT_IMAGE = pw.current()
show_image(fig, CURRENT_IMAGE) | [
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spack/spack | 675210bd8bd1c5d32ad1cc83d898fb43b569ed74 | lib/spack/external/attr/_funcs.py | python | asdict | (
inst,
recurse=True,
filter=None,
dict_factory=dict,
retain_collection_types=False,
value_serializer=None,
) | return rv | Return the ``attrs`` attribute values of *inst* as a dict.
Optionally recurse into other ``attrs``-decorated classes.
:param inst: Instance of an ``attrs``-decorated class.
:param bool recurse: Recurse into classes that are also
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:param callable filter: A callable whose return code determines whether an
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:param callable dict_factory: A callable to produce dictionaries from. For
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dictionaries, pass in ``collections.OrderedDict``.
:param bool retain_collection_types: Do not convert to ``list`` when
encountering an attribute whose type is ``tuple`` or ``set``. Only
meaningful if ``recurse`` is ``True``.
:param Optional[callable] value_serializer: A hook that is called for every
attribute or dict key/value. It receives the current instance, field
and value and must return the (updated) value. The hook is run *after*
the optional *filter* has been applied.
:rtype: return type of *dict_factory*
:raise attr.exceptions.NotAnAttrsClassError: If *cls* is not an ``attrs``
class.
.. versionadded:: 16.0.0 *dict_factory*
.. versionadded:: 16.1.0 *retain_collection_types*
.. versionadded:: 20.3.0 *value_serializer* | Return the ``attrs`` attribute values of *inst* as a dict. | [
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inst,
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retain_collection_types=False,
value_serializer=None,
):
"""
Return the ``attrs`` attribute values of *inst* as a dict.
Optionally recurse into other ``attrs``-decorated classes.
:param inst: Instance of an ``attrs``-decorated class.
:param bool recurse: Recurse into classes that are also
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:param Optional[callable] value_serializer: A hook that is called for every
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and value and must return the (updated) value. The hook is run *after*
the optional *filter* has been applied.
:rtype: return type of *dict_factory*
:raise attr.exceptions.NotAnAttrsClassError: If *cls* is not an ``attrs``
class.
.. versionadded:: 16.0.0 *dict_factory*
.. versionadded:: 16.1.0 *retain_collection_types*
.. versionadded:: 20.3.0 *value_serializer*
"""
attrs = fields(inst.__class__)
rv = dict_factory()
for a in attrs:
v = getattr(inst, a.name)
if filter is not None and not filter(a, v):
continue
if value_serializer is not None:
v = value_serializer(inst, a, v)
if recurse is True:
if has(v.__class__):
rv[a.name] = asdict(
v,
True,
filter,
dict_factory,
retain_collection_types,
value_serializer,
)
elif isinstance(v, (tuple, list, set, frozenset)):
cf = v.__class__ if retain_collection_types is True else list
rv[a.name] = cf(
[
_asdict_anything(
i,
filter,
dict_factory,
retain_collection_types,
value_serializer,
)
for i in v
]
)
elif isinstance(v, dict):
df = dict_factory
rv[a.name] = df(
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kk,
filter,
df,
retain_collection_types,
value_serializer,
),
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vv,
filter,
df,
retain_collection_types,
value_serializer,
),
)
for kk, vv in iteritems(v)
)
else:
rv[a.name] = v
else:
rv[a.name] = v
return rv | [
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open-telemetry/opentelemetry-python | f5d872050204685b5ef831d02ec593956820ebe6 | opentelemetry-api/src/opentelemetry/trace/__init__.py | python | get_tracer | (
instrumenting_module_name: str,
instrumenting_library_version: typing.Optional[str] = None,
tracer_provider: Optional[TracerProvider] = None,
schema_url: typing.Optional[str] = None,
) | return tracer_provider.get_tracer(
instrumenting_module_name, instrumenting_library_version, schema_url
) | Returns a `Tracer` for use by the given instrumentation library.
This function is a convenience wrapper for
opentelemetry.trace.TracerProvider.get_tracer.
If tracer_provider is omitted the current configured one is used. | Returns a `Tracer` for use by the given instrumentation library. | [
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] | def get_tracer(
instrumenting_module_name: str,
instrumenting_library_version: typing.Optional[str] = None,
tracer_provider: Optional[TracerProvider] = None,
schema_url: typing.Optional[str] = None,
) -> "Tracer":
"""Returns a `Tracer` for use by the given instrumentation library.
This function is a convenience wrapper for
opentelemetry.trace.TracerProvider.get_tracer.
If tracer_provider is omitted the current configured one is used.
"""
if tracer_provider is None:
tracer_provider = get_tracer_provider()
return tracer_provider.get_tracer(
instrumenting_module_name, instrumenting_library_version, schema_url
) | [
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python-mechanize/mechanize | 3cd4d19ee701d9aa458fa23b7515c268d3f1cef0 | mechanize/_http.py | python | parse_head | (fileobj) | return p() | Return a list of key, value pairs. | Return a list of key, value pairs. | [
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] | def parse_head(fileobj):
"""Return a list of key, value pairs."""
p = HTTPEquivParser(fileobj.read(4096))
return p() | [
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buke/GreenOdoo | 3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df | source/addons/im_chat/im_chat.py | python | im_chat_session.add_user | (self, cr, uid, uuid, user_id, context=None) | add the given user to the given session | add the given user to the given session | [
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] | def add_user(self, cr, uid, uuid, user_id, context=None):
""" add the given user to the given session """
sids = self.search(cr, uid, [('uuid', '=', uuid)], context=context, limit=1)
for session in self.browse(cr, uid, sids, context=context):
if user_id not in [u.id for u in session.user_ids]:
self.write(cr, uid, [session.id], {'user_ids': [(4, user_id)]}, context=context)
# notify the all the channel users and anonymous channel
notifications = []
for channel_user_id in session.user_ids:
info = self.session_info(cr, channel_user_id.id, [session.id], context=context)
notifications.append([(cr.dbname, 'im_chat.session', channel_user_id.id), info])
# Anonymous are not notified when a new user is added : cannot exec session_info as uid = None
info = self.session_info(cr, openerp.SUPERUSER_ID, [session.id], context=context)
notifications.append([session.uuid, info])
self.pool['bus.bus'].sendmany(cr, uid, notifications)
# send a message to the conversation
user = self.pool['res.users'].read(cr, uid, user_id, ['name'], context=context)
self.pool["im_chat.message"].post(cr, uid, uid, session.uuid, "meta", user['name'] + " joined the conversation.", context=context) | [
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... | https://github.com/buke/GreenOdoo/blob/3d8c55d426fb41fdb3f2f5a1533cfe05983ba1df/source/addons/im_chat/im_chat.py#L117-L134 | ||
bslatkin/effectivepython | 4ae6f3141291ea137eb29a245bf889dbc8091713 | example_code/item_20.py | python | careful_divide | (a: float, b: float) | Divides a by b.
Raises:
ValueError: When the inputs cannot be divided. | Divides a by b. | [
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"by",
"b",
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] | def careful_divide(a: float, b: float) -> float:
"""Divides a by b.
Raises:
ValueError: When the inputs cannot be divided.
"""
try:
return a / b
except ZeroDivisionError as e:
raise ValueError('Invalid inputs') | [
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angr/angr | 4b04d56ace135018083d36d9083805be8146688b | angr/storage/memory_mixins/paged_memory/pages/list_page.py | python | ListPage._resolve_range | (mo: SimMemoryObject, page_addr: int, page_size) | return start, end | [] | def _resolve_range(mo: SimMemoryObject, page_addr: int, page_size) -> Tuple[int,int]:
start = max(mo.base, page_addr)
end = min(mo.last_addr + 1, page_addr + page_size)
if end <= start:
l.warning("Nothing left of the memory object to store in SimPage.")
return start, end | [
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AppScale/gts | 46f909cf5dc5ba81faf9d81dc9af598dcf8a82a9 | AppServer/google/appengine/ext/mapreduce/output_writers.py | python | OutputWriter.finalize | (self, ctx, shard_state) | Finalize writer shard-level state.
This should only be called when shard_state.result_status shows success.
After finalizing the outputs, it should save per-shard output file info
into shard_state.writer_state so that other operations can find the
outputs.
Args:
ctx: an instance of context.Context.
shard_state: shard state. ShardState.writer_state can be modified. | Finalize writer shard-level state. | [
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] | def finalize(self, ctx, shard_state):
"""Finalize writer shard-level state.
This should only be called when shard_state.result_status shows success.
After finalizing the outputs, it should save per-shard output file info
into shard_state.writer_state so that other operations can find the
outputs.
Args:
ctx: an instance of context.Context.
shard_state: shard state. ShardState.writer_state can be modified.
"""
raise NotImplementedError("finalize() not implemented in %s" %
self.__class__) | [
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