xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

d8a2261fc5bc901a922af4a7c07416495077fb4d

92

py

Python

coingate/apps.py

glitzybunny/coingate_sandbox_payment

f5686964cdd6b7d65f9f37957da4b2cda6a02f63

[ "MIT" ]

2

2020-08-31T17:53:06.000Z

2020-08-31T18:33:05.000Z

coingate/apps.py

glitzybunny/coingate_sandbox_payment

f5686964cdd6b7d65f9f37957da4b2cda6a02f63

[ "MIT" ]

5

2021-03-30T12:48:17.000Z

2021-09-22T18:32:14.000Z

coingate/apps.py

glitzybunny/coingate_sandbox_payment

f5686964cdd6b7d65f9f37957da4b2cda6a02f63

[ "MIT" ]

1

2020-11-04T04:42:58.000Z

from django.apps import AppConfig class CoingateConfig(AppConfig): name = 'coingate'

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py

Python

aulaClasses/ex001.py

lalapapauhuh/Python

1454263b46d66a0b19b7a2fd1b465800fe95a2c8

[ "MIT" ]

null

aulaClasses/ex001.py

lalapapauhuh/Python

1454263b46d66a0b19b7a2fd1b465800fe95a2c8

[ "MIT" ]

null

aulaClasses/ex001.py

lalapapauhuh/Python

1454263b46d66a0b19b7a2fd1b465800fe95a2c8

[ "MIT" ]

null

'''Classe Bola: Crie uma classe que modele uma bola: Atributos: Cor, marca, material Métodos: trocaCor e mostraCor''' class Bola: def __init__(self, cor, marca, material): self.cor = cor self.marca = marca self.material = material def getCor(self): return self.cor def getMarca(self): return self.marca def getMaterial(self): return self.material def __str__(self): return 'Cor: '+ str(self.cor) + ', Marca: '+ str(self.marca) + ', Material: ' + str(self.material) def trocaCor(self, nova_cor): self.cor = nova_cor return self.cor bola1 = Bola('Vermelha', 'Adidas', 'Couro') bola2 = Bola('Verde', 'Brinquedo', 'Plastico') bola3 = Bola('Branca', 'Penalty', 'Couro') print(bola1) bola1.trocaCor('Azul') print(bola1)

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2b1ec4fe936e79d22b87038b7792343c6480748e

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py

Python

source/application/helper/extensions.py

wangkexiong/flask4gae

dcefb49dce51be6b716352c1d3021fe8e501e5ff

[ "MIT", "CC-BY-3.0", "BSD-2-Clause", "BSD-3-Clause" ]

1

2016-08-17T04:35:45.000Z

source/application/helper/extensions.py

wangkexiong/flask4gae

dcefb49dce51be6b716352c1d3021fe8e501e5ff

[ "MIT", "CC-BY-3.0", "BSD-2-Clause", "BSD-3-Clause" ]

null

source/application/helper/extensions.py

wangkexiong/flask4gae

dcefb49dce51be6b716352c1d3021fe8e501e5ff

[ "MIT", "CC-BY-3.0", "BSD-2-Clause", "BSD-3-Clause" ]

null

# -*- coding=utf-8 -*- from flask.ext.cache import Cache cache = Cache()

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py

Python

orbitdbviewer/__init__.py

phillmac/py-orbit-db-viewer

2532bd56771fad68e0e8752b5ce9163562fe71a1

[ "MIT" ]

null

orbitdbviewer/__init__.py

phillmac/py-orbit-db-viewer

2532bd56771fad68e0e8752b5ce9163562fe71a1

[ "MIT" ]

null

orbitdbviewer/__init__.py

phillmac/py-orbit-db-viewer

2532bd56771fad68e0e8752b5ce9163562fe71a1

[ "MIT" ]

null

from .version import version, version_info __version__ = version

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2b69d80c3f09732b89cb04fb5f73469f08029fe8

312

py

Python

ibug/face_pose_augmentation/face_pose_augmentor.py

ibug-group/face_pose_augmentation

96df817c194854bba261893703d26502feec1c22

[ "MIT" ]

3

2021-03-22T11:58:18.000Z

2022-03-11T20:29:22.000Z

ibug/face_pose_augmentation/face_pose_augmentor.py

ibug-group/face_pose_augmentation

96df817c194854bba261893703d26502feec1c22

[ "MIT" ]

null

ibug/face_pose_augmentation/face_pose_augmentor.py

ibug-group/face_pose_augmentation

96df817c194854bba261893703d26502feec1c22

[ "MIT" ]

1

2022-03-11T20:28:45.000Z

from scipy.interpolate import interp1d from .fpa import generate_profile_faces, retrieve_contour_landmark_aug __all__ = ['FacePoseAugmentor'] class FacePoseAugmentor(object): def __init__(self) -> None: pass def __call__(self, image, tddfa_result, delta_poses, landmarks=None): pass

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py

Python

penkins/controller/projects.py

penkins/penkins_ci

668606b505d02eed7fbe65604655e140ab60d6dd

[ "Apache-2.0" ]

2

2015-04-03T19:12:46.000Z

2016-04-06T09:49:17.000Z

penkins/controller/projects.py

penkins/penkins_ci

668606b505d02eed7fbe65604655e140ab60d6dd

[ "Apache-2.0" ]

5

2015-02-25T19:22:47.000Z

2019-02-09T08:48:00.000Z

penkins/controller/projects.py

penkins/penkins_ci

668606b505d02eed7fbe65604655e140ab60d6dd

[ "Apache-2.0" ]

1

2016-04-06T09:49:19.000Z

import re from penkins.db import db, Query class Projects(object): def get_all(self): return db.all() def is_exists(self, name): return False if len(db.search(Query().name == name)) == 0 else True def get(self): pass def validate_name(self, name): pattern = re.compile(r'^[a-zA-Z0-9]{1,32}$') return True if pattern.match(name) else False

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9947098e5b5b9a6705f3ff0b4c444a9931f4bb6d

351

py

Python

mria_py/__init__.py

ElcoK/MRIA

ce4fc1665004506c43320f968b1f1c435af5bc59

[ "MIT" ]

null

mria_py/__init__.py

ElcoK/MRIA

ce4fc1665004506c43320f968b1f1c435af5bc59

[ "MIT" ]

null

mria_py/__init__.py

ElcoK/MRIA

ce4fc1665004506c43320f968b1f1c435af5bc59

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Sun Nov 5 14:43:30 2017 @author: elcok """ __all__ = ['model','table','gams','visualize','uncertainty','basics'] from mria_py.core import model from mria_py.core import table from mria_py.core import gams from mria_py.core import visualize from mria_py.core import basics from mria_py.core import uncertainty

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9956967ddd7e2bf343479e00871e234e9e816671

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py

Python

tests/__init__.py

swingerman/ha-dual-thermostat

fccd85d56b62d652b3ebbd9fb3c54d58a72fdb00

[ "Apache-2.0", "MIT" ]

1

2020-09-15T15:32:12.000Z

tests/__init__.py

swingerman/ha-dual-climate

3e863eb1ad57021ba4d93decc3720d9cae91f607

[ "Apache-2.0", "MIT" ]

null

tests/__init__.py

swingerman/ha-dual-climate

3e863eb1ad57021ba4d93decc3720d9cae91f607

[ "Apache-2.0", "MIT" ]

null

"""dual_smart_thermostat tests."""

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9978affaf72b1fe78897d2f4fa6d6c3b01da42e0

149

py

Python

FeatureFileProcessor/exceptions/no_data_file_exception.py

JoaoGFarias/CucumberWithDataSauce

36b55c485fae8a4e2b9e0b84351eab87785cebd8

[ "MIT" ]

null

FeatureFileProcessor/exceptions/no_data_file_exception.py

JoaoGFarias/CucumberWithDataSauce

36b55c485fae8a4e2b9e0b84351eab87785cebd8

[ "MIT" ]

33

2018-02-04T02:03:03.000Z

2018-03-27T01:58:30.000Z

FeatureFileProcessor/exceptions/no_data_file_exception.py

JoaoGFarias/CucumberWithDataSauce

36b55c485fae8a4e2b9e0b84351eab87785cebd8

[ "MIT" ]

1

2019-04-22T14:25:54.000Z

class NoDataFileException(Exception): def __init__(self, message="No data file", errors=[]): super().__init__(message, errors) pass

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py

Python

week11/lab/counter.py

taoyichen/CS110-Assignments-Python

f2e4e485c820b835981e2e4b8bd0a26cc31cfe73

[ "MIT" ]

null

week11/lab/counter.py

taoyichen/CS110-Assignments-Python

f2e4e485c820b835981e2e4b8bd0a26cc31cfe73

[ "MIT" ]

null

week11/lab/counter.py

taoyichen/CS110-Assignments-Python

f2e4e485c820b835981e2e4b8bd0a26cc31cfe73

[ "MIT" ]

1

2020-06-06T08:21:18.000Z

''' Models simple up/down counter that maintains a single count Methods: get_count() incrememt() decrement() set() reset() 'to_string' ''' ## Start your class with the keyword 'class' and the name of the class: class Counter: #---------------------------------------------------------------------------- # Constructor ## This method creates the object in a valid state def __init__(self): ## Initialize the instance variable that represents the count self.__count = 0 #---------------------------------------------------------------------------- # Accessors ## return the information about the state of the object # return current value of count def get_count(self): ## Your code here return self.__count #---------------------------------------------------------------------------- # Mutators def increment(self): ## Your code here self.__count +=1 # Does NOT stop at 0 def decrement(self): ## Your code here self.__count -=1 def set_count(self, value): ## Your code here self.__count = value def reset(self): ## Your code here self.__count = 0 #---------------------------------------------------------------------------- # 'toString' # String representation of object's current state def __str__(self): return "Count = %d" % (self.__count)

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sdk/monitor/azure-mgmt-monitor/azure/mgmt/monitor/v2016_09_01/models/_models_py3.py

vincenttran-msft/azure-sdk-for-python

348b56f9f03eeb3f7b502eed51daf494ffff874d

[ "MIT" ]

1

2022-02-01T18:50:12.000Z

sdk/monitor/azure-mgmt-monitor/azure/mgmt/monitor/v2016_09_01/models/_models_py3.py

vincenttran-msft/azure-sdk-for-python

348b56f9f03eeb3f7b502eed51daf494ffff874d

[ "MIT" ]

null

sdk/monitor/azure-mgmt-monitor/azure/mgmt/monitor/v2016_09_01/models/_models_py3.py

vincenttran-msft/azure-sdk-for-python

348b56f9f03eeb3f7b502eed51daf494ffff874d

[ "MIT" ]

null

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- import datetime from typing import Dict, List, Optional, Union from azure.core.exceptions import HttpResponseError import msrest.serialization from ._monitor_management_client_enums import * class ErrorResponse(msrest.serialization.Model): """Describes the format of Error response. :ivar code: Error code. :vartype code: str :ivar message: Error message indicating why the operation failed. :vartype message: str """ _attribute_map = { 'code': {'key': 'code', 'type': 'str'}, 'message': {'key': 'message', 'type': 'str'}, } def __init__( self, *, code: Optional[str] = None, message: Optional[str] = None, **kwargs ): """ :keyword code: Error code. :paramtype code: str :keyword message: Error message indicating why the operation failed. :paramtype message: str """ super(ErrorResponse, self).__init__(**kwargs) self.code = code self.message = message class LocalizableString(msrest.serialization.Model): """The localizable string class. All required parameters must be populated in order to send to Azure. :ivar value: Required. the invariant value. :vartype value: str :ivar localized_value: the locale specific value. :vartype localized_value: str """ _validation = { 'value': {'required': True}, } _attribute_map = { 'value': {'key': 'value', 'type': 'str'}, 'localized_value': {'key': 'localizedValue', 'type': 'str'}, } def __init__( self, *, value: str, localized_value: Optional[str] = None, **kwargs ): """ :keyword value: Required. the invariant value. :paramtype value: str :keyword localized_value: the locale specific value. :paramtype localized_value: str """ super(LocalizableString, self).__init__(**kwargs) self.value = value self.localized_value = localized_value class LogSettings(msrest.serialization.Model): """Part of MultiTenantDiagnosticSettings. Specifies the settings for a particular log. All required parameters must be populated in order to send to Azure. :ivar category: Name of a Diagnostic Log category for a resource type this setting is applied to. To obtain the list of Diagnostic Log categories for a resource, first perform a GET diagnostic settings operation. :vartype category: str :ivar enabled: Required. a value indicating whether this log is enabled. :vartype enabled: bool :ivar retention_policy: the retention policy for this log. :vartype retention_policy: ~$(python-base-namespace).v2016_09_01.models.RetentionPolicy """ _validation = { 'enabled': {'required': True}, } _attribute_map = { 'category': {'key': 'category', 'type': 'str'}, 'enabled': {'key': 'enabled', 'type': 'bool'}, 'retention_policy': {'key': 'retentionPolicy', 'type': 'RetentionPolicy'}, } def __init__( self, *, enabled: bool, category: Optional[str] = None, retention_policy: Optional["RetentionPolicy"] = None, **kwargs ): """ :keyword category: Name of a Diagnostic Log category for a resource type this setting is applied to. To obtain the list of Diagnostic Log categories for a resource, first perform a GET diagnostic settings operation. :paramtype category: str :keyword enabled: Required. a value indicating whether this log is enabled. :paramtype enabled: bool :keyword retention_policy: the retention policy for this log. :paramtype retention_policy: ~$(python-base-namespace).v2016_09_01.models.RetentionPolicy """ super(LogSettings, self).__init__(**kwargs) self.category = category self.enabled = enabled self.retention_policy = retention_policy class Metric(msrest.serialization.Model): """A set of metric values in a time range. All required parameters must be populated in order to send to Azure. :ivar id: the id, resourceId, of the metric. :vartype id: str :ivar type: the resource type of the metric resource. :vartype type: str :ivar name: Required. the name and the display name of the metric, i.e. it is localizable string. :vartype name: ~$(python-base-namespace).v2016_09_01.models.LocalizableString :ivar unit: Required. the unit of the metric. Possible values include: "Count", "Bytes", "Seconds", "CountPerSecond", "BytesPerSecond", "Percent", "MilliSeconds", "ByteSeconds", "Unspecified", "Cores", "MilliCores", "NanoCores", "BitsPerSecond". :vartype unit: str or ~$(python-base-namespace).v2016_09_01.models.Unit :ivar data: Required. Array of data points representing the metric values. :vartype data: list[~$(python-base-namespace).v2016_09_01.models.MetricValue] """ _validation = { 'name': {'required': True}, 'unit': {'required': True}, 'data': {'required': True}, } _attribute_map = { 'id': {'key': 'id', 'type': 'str'}, 'type': {'key': 'type', 'type': 'str'}, 'name': {'key': 'name', 'type': 'LocalizableString'}, 'unit': {'key': 'unit', 'type': 'str'}, 'data': {'key': 'data', 'type': '[MetricValue]'}, } def __init__( self, *, name: "LocalizableString", unit: Union[str, "Unit"], data: List["MetricValue"], id: Optional[str] = None, type: Optional[str] = None, **kwargs ): """ :keyword id: the id, resourceId, of the metric. :paramtype id: str :keyword type: the resource type of the metric resource. :paramtype type: str :keyword name: Required. the name and the display name of the metric, i.e. it is localizable string. :paramtype name: ~$(python-base-namespace).v2016_09_01.models.LocalizableString :keyword unit: Required. the unit of the metric. Possible values include: "Count", "Bytes", "Seconds", "CountPerSecond", "BytesPerSecond", "Percent", "MilliSeconds", "ByteSeconds", "Unspecified", "Cores", "MilliCores", "NanoCores", "BitsPerSecond". :paramtype unit: str or ~$(python-base-namespace).v2016_09_01.models.Unit :keyword data: Required. Array of data points representing the metric values. :paramtype data: list[~$(python-base-namespace).v2016_09_01.models.MetricValue] """ super(Metric, self).__init__(**kwargs) self.id = id self.type = type self.name = name self.unit = unit self.data = data class MetricCollection(msrest.serialization.Model): """The collection of metric value sets. All required parameters must be populated in order to send to Azure. :ivar value: Required. the value of the collection. :vartype value: list[~$(python-base-namespace).v2016_09_01.models.Metric] """ _validation = { 'value': {'required': True}, } _attribute_map = { 'value': {'key': 'value', 'type': '[Metric]'}, } def __init__( self, *, value: List["Metric"], **kwargs ): """ :keyword value: Required. the value of the collection. :paramtype value: list[~$(python-base-namespace).v2016_09_01.models.Metric] """ super(MetricCollection, self).__init__(**kwargs) self.value = value class MetricSettings(msrest.serialization.Model): """Part of MultiTenantDiagnosticSettings. Specifies the settings for a particular metric. All required parameters must be populated in order to send to Azure. :ivar time_grain: Required. the timegrain of the metric in ISO8601 format. :vartype time_grain: ~datetime.timedelta :ivar enabled: Required. a value indicating whether this timegrain is enabled. :vartype enabled: bool :ivar retention_policy: the retention policy for this timegrain. :vartype retention_policy: ~$(python-base-namespace).v2016_09_01.models.RetentionPolicy """ _validation = { 'time_grain': {'required': True}, 'enabled': {'required': True}, } _attribute_map = { 'time_grain': {'key': 'timeGrain', 'type': 'duration'}, 'enabled': {'key': 'enabled', 'type': 'bool'}, 'retention_policy': {'key': 'retentionPolicy', 'type': 'RetentionPolicy'}, } def __init__( self, *, time_grain: datetime.timedelta, enabled: bool, retention_policy: Optional["RetentionPolicy"] = None, **kwargs ): """ :keyword time_grain: Required. the timegrain of the metric in ISO8601 format. :paramtype time_grain: ~datetime.timedelta :keyword enabled: Required. a value indicating whether this timegrain is enabled. :paramtype enabled: bool :keyword retention_policy: the retention policy for this timegrain. :paramtype retention_policy: ~$(python-base-namespace).v2016_09_01.models.RetentionPolicy """ super(MetricSettings, self).__init__(**kwargs) self.time_grain = time_grain self.enabled = enabled self.retention_policy = retention_policy class MetricValue(msrest.serialization.Model): """Represents a metric value. All required parameters must be populated in order to send to Azure. :ivar time_stamp: Required. the timestamp for the metric value in ISO 8601 format. :vartype time_stamp: ~datetime.datetime :ivar average: the average value in the time range. :vartype average: float :ivar minimum: the least value in the time range. :vartype minimum: float :ivar maximum: the greatest value in the time range. :vartype maximum: float :ivar total: the sum of all of the values in the time range. :vartype total: float :ivar count: the number of samples in the time range. Can be used to determine the number of values that contributed to the average value. :vartype count: long """ _validation = { 'time_stamp': {'required': True}, } _attribute_map = { 'time_stamp': {'key': 'timeStamp', 'type': 'iso-8601'}, 'average': {'key': 'average', 'type': 'float'}, 'minimum': {'key': 'minimum', 'type': 'float'}, 'maximum': {'key': 'maximum', 'type': 'float'}, 'total': {'key': 'total', 'type': 'float'}, 'count': {'key': 'count', 'type': 'long'}, } def __init__( self, *, time_stamp: datetime.datetime, average: Optional[float] = None, minimum: Optional[float] = None, maximum: Optional[float] = None, total: Optional[float] = None, count: Optional[int] = None, **kwargs ): """ :keyword time_stamp: Required. the timestamp for the metric value in ISO 8601 format. :paramtype time_stamp: ~datetime.datetime :keyword average: the average value in the time range. :paramtype average: float :keyword minimum: the least value in the time range. :paramtype minimum: float :keyword maximum: the greatest value in the time range. :paramtype maximum: float :keyword total: the sum of all of the values in the time range. :paramtype total: float :keyword count: the number of samples in the time range. Can be used to determine the number of values that contributed to the average value. :paramtype count: long """ super(MetricValue, self).__init__(**kwargs) self.time_stamp = time_stamp self.average = average self.minimum = minimum self.maximum = maximum self.total = total self.count = count class Resource(msrest.serialization.Model): """An azure resource object. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :ivar id: Azure resource Id. :vartype id: str :ivar name: Azure resource name. :vartype name: str :ivar type: Azure resource type. :vartype type: str :ivar location: Required. Resource location. :vartype location: str :ivar tags: A set of tags. Resource tags. :vartype tags: dict[str, str] """ _validation = { 'id': {'readonly': True}, 'name': {'readonly': True}, 'type': {'readonly': True}, 'location': {'required': True}, } _attribute_map = { 'id': {'key': 'id', 'type': 'str'}, 'name': {'key': 'name', 'type': 'str'}, 'type': {'key': 'type', 'type': 'str'}, 'location': {'key': 'location', 'type': 'str'}, 'tags': {'key': 'tags', 'type': '{str}'}, } def __init__( self, *, location: str, tags: Optional[Dict[str, str]] = None, **kwargs ): """ :keyword location: Required. Resource location. :paramtype location: str :keyword tags: A set of tags. Resource tags. :paramtype tags: dict[str, str] """ super(Resource, self).__init__(**kwargs) self.id = None self.name = None self.type = None self.location = location self.tags = tags class RetentionPolicy(msrest.serialization.Model): """Specifies the retention policy for the log. All required parameters must be populated in order to send to Azure. :ivar enabled: Required. a value indicating whether the retention policy is enabled. :vartype enabled: bool :ivar days: Required. the number of days for the retention in days. A value of 0 will retain the events indefinitely. :vartype days: int """ _validation = { 'enabled': {'required': True}, 'days': {'required': True, 'minimum': 0}, } _attribute_map = { 'enabled': {'key': 'enabled', 'type': 'bool'}, 'days': {'key': 'days', 'type': 'int'}, } def __init__( self, *, enabled: bool, days: int, **kwargs ): """ :keyword enabled: Required. a value indicating whether the retention policy is enabled. :paramtype enabled: bool :keyword days: Required. the number of days for the retention in days. A value of 0 will retain the events indefinitely. :paramtype days: int """ super(RetentionPolicy, self).__init__(**kwargs) self.enabled = enabled self.days = days class ServiceDiagnosticSettingsResource(Resource): """Description of a service diagnostic setting. Variables are only populated by the server, and will be ignored when sending a request. All required parameters must be populated in order to send to Azure. :ivar id: Azure resource Id. :vartype id: str :ivar name: Azure resource name. :vartype name: str :ivar type: Azure resource type. :vartype type: str :ivar location: Required. Resource location. :vartype location: str :ivar tags: A set of tags. Resource tags. :vartype tags: dict[str, str] :ivar storage_account_id: The resource ID of the storage account to which you would like to send Diagnostic Logs. :vartype storage_account_id: str :ivar service_bus_rule_id: The service bus rule ID of the service bus namespace in which you would like to have Event Hubs created for streaming Diagnostic Logs. The rule ID is of the format: '{service bus resource ID}/authorizationrules/{key name}'. :vartype service_bus_rule_id: str :ivar event_hub_authorization_rule_id: The resource Id for the event hub namespace authorization rule. :vartype event_hub_authorization_rule_id: str :ivar metrics: the list of metric settings. :vartype metrics: list[~$(python-base-namespace).v2016_09_01.models.MetricSettings] :ivar logs: the list of logs settings. :vartype logs: list[~$(python-base-namespace).v2016_09_01.models.LogSettings] :ivar workspace_id: The workspace ID (resource ID of a Log Analytics workspace) for a Log Analytics workspace to which you would like to send Diagnostic Logs. Example: /subscriptions/4b9e8510-67ab-4e9a-95a9-e2f1e570ea9c/resourceGroups/insights-integration/providers/Microsoft.OperationalInsights/workspaces/viruela2. :vartype workspace_id: str """ _validation = { 'id': {'readonly': True}, 'name': {'readonly': True}, 'type': {'readonly': True}, 'location': {'required': True}, } _attribute_map = { 'id': {'key': 'id', 'type': 'str'}, 'name': {'key': 'name', 'type': 'str'}, 'type': {'key': 'type', 'type': 'str'}, 'location': {'key': 'location', 'type': 'str'}, 'tags': {'key': 'tags', 'type': '{str}'}, 'storage_account_id': {'key': 'properties.storageAccountId', 'type': 'str'}, 'service_bus_rule_id': {'key': 'properties.serviceBusRuleId', 'type': 'str'}, 'event_hub_authorization_rule_id': {'key': 'properties.eventHubAuthorizationRuleId', 'type': 'str'}, 'metrics': {'key': 'properties.metrics', 'type': '[MetricSettings]'}, 'logs': {'key': 'properties.logs', 'type': '[LogSettings]'}, 'workspace_id': {'key': 'properties.workspaceId', 'type': 'str'}, } def __init__( self, *, location: str, tags: Optional[Dict[str, str]] = None, storage_account_id: Optional[str] = None, service_bus_rule_id: Optional[str] = None, event_hub_authorization_rule_id: Optional[str] = None, metrics: Optional[List["MetricSettings"]] = None, logs: Optional[List["LogSettings"]] = None, workspace_id: Optional[str] = None, **kwargs ): """ :keyword location: Required. Resource location. :paramtype location: str :keyword tags: A set of tags. Resource tags. :paramtype tags: dict[str, str] :keyword storage_account_id: The resource ID of the storage account to which you would like to send Diagnostic Logs. :paramtype storage_account_id: str :keyword service_bus_rule_id: The service bus rule ID of the service bus namespace in which you would like to have Event Hubs created for streaming Diagnostic Logs. The rule ID is of the format: '{service bus resource ID}/authorizationrules/{key name}'. :paramtype service_bus_rule_id: str :keyword event_hub_authorization_rule_id: The resource Id for the event hub namespace authorization rule. :paramtype event_hub_authorization_rule_id: str :keyword metrics: the list of metric settings. :paramtype metrics: list[~$(python-base-namespace).v2016_09_01.models.MetricSettings] :keyword logs: the list of logs settings. :paramtype logs: list[~$(python-base-namespace).v2016_09_01.models.LogSettings] :keyword workspace_id: The workspace ID (resource ID of a Log Analytics workspace) for a Log Analytics workspace to which you would like to send Diagnostic Logs. Example: /subscriptions/4b9e8510-67ab-4e9a-95a9-e2f1e570ea9c/resourceGroups/insights-integration/providers/Microsoft.OperationalInsights/workspaces/viruela2. :paramtype workspace_id: str """ super(ServiceDiagnosticSettingsResource, self).__init__(location=location, tags=tags, **kwargs) self.storage_account_id = storage_account_id self.service_bus_rule_id = service_bus_rule_id self.event_hub_authorization_rule_id = event_hub_authorization_rule_id self.metrics = metrics self.logs = logs self.workspace_id = workspace_id class ServiceDiagnosticSettingsResourcePatch(msrest.serialization.Model): """Service diagnostic setting resource for patch operations. :ivar tags: A set of tags. Resource tags. :vartype tags: dict[str, str] :ivar storage_account_id: The resource ID of the storage account to which you would like to send Diagnostic Logs. :vartype storage_account_id: str :ivar service_bus_rule_id: The service bus rule ID of the service bus namespace in which you would like to have Event Hubs created for streaming Diagnostic Logs. The rule ID is of the format: '{service bus resource ID}/authorizationrules/{key name}'. :vartype service_bus_rule_id: str :ivar event_hub_authorization_rule_id: The resource Id for the event hub namespace authorization rule. :vartype event_hub_authorization_rule_id: str :ivar metrics: the list of metric settings. :vartype metrics: list[~$(python-base-namespace).v2016_09_01.models.MetricSettings] :ivar logs: the list of logs settings. :vartype logs: list[~$(python-base-namespace).v2016_09_01.models.LogSettings] :ivar workspace_id: The workspace ID (resource ID of a Log Analytics workspace) for a Log Analytics workspace to which you would like to send Diagnostic Logs. Example: /subscriptions/4b9e8510-67ab-4e9a-95a9-e2f1e570ea9c/resourceGroups/insights-integration/providers/Microsoft.OperationalInsights/workspaces/viruela2. :vartype workspace_id: str """ _attribute_map = { 'tags': {'key': 'tags', 'type': '{str}'}, 'storage_account_id': {'key': 'properties.storageAccountId', 'type': 'str'}, 'service_bus_rule_id': {'key': 'properties.serviceBusRuleId', 'type': 'str'}, 'event_hub_authorization_rule_id': {'key': 'properties.eventHubAuthorizationRuleId', 'type': 'str'}, 'metrics': {'key': 'properties.metrics', 'type': '[MetricSettings]'}, 'logs': {'key': 'properties.logs', 'type': '[LogSettings]'}, 'workspace_id': {'key': 'properties.workspaceId', 'type': 'str'}, } def __init__( self, *, tags: Optional[Dict[str, str]] = None, storage_account_id: Optional[str] = None, service_bus_rule_id: Optional[str] = None, event_hub_authorization_rule_id: Optional[str] = None, metrics: Optional[List["MetricSettings"]] = None, logs: Optional[List["LogSettings"]] = None, workspace_id: Optional[str] = None, **kwargs ): """ :keyword tags: A set of tags. Resource tags. :paramtype tags: dict[str, str] :keyword storage_account_id: The resource ID of the storage account to which you would like to send Diagnostic Logs. :paramtype storage_account_id: str :keyword service_bus_rule_id: The service bus rule ID of the service bus namespace in which you would like to have Event Hubs created for streaming Diagnostic Logs. The rule ID is of the format: '{service bus resource ID}/authorizationrules/{key name}'. :paramtype service_bus_rule_id: str :keyword event_hub_authorization_rule_id: The resource Id for the event hub namespace authorization rule. :paramtype event_hub_authorization_rule_id: str :keyword metrics: the list of metric settings. :paramtype metrics: list[~$(python-base-namespace).v2016_09_01.models.MetricSettings] :keyword logs: the list of logs settings. :paramtype logs: list[~$(python-base-namespace).v2016_09_01.models.LogSettings] :keyword workspace_id: The workspace ID (resource ID of a Log Analytics workspace) for a Log Analytics workspace to which you would like to send Diagnostic Logs. Example: /subscriptions/4b9e8510-67ab-4e9a-95a9-e2f1e570ea9c/resourceGroups/insights-integration/providers/Microsoft.OperationalInsights/workspaces/viruela2. :paramtype workspace_id: str """ super(ServiceDiagnosticSettingsResourcePatch, self).__init__(**kwargs) self.tags = tags self.storage_account_id = storage_account_id self.service_bus_rule_id = service_bus_rule_id self.event_hub_authorization_rule_id = event_hub_authorization_rule_id self.metrics = metrics self.logs = logs self.workspace_id = workspace_id

39.579872

157

0.645155

2,888

24,777

5.408587

0.091413

0.015365

0.024328

0.03073

0.778873

0.751408

0.736044

0.720359

0.692446

0.675672

0

0.014024

0.240223

24,777

625

158

39.6432

0.815724

0.543205

0

0.594096

0

0.193588

0.029799

0

1

0.04059

false

0

0.01845

0

0.173432

0

null

0

1

0

1

0

null

0

4

41e312a8435442439bf68456922fd53bb3587946

199

py

Python

users/urls.py

Joabsonlg/ddm-rest-api

27d72f5e7dcb061f56b7fd504c76bc7746ecabe2

[ "MIT" ]

null

users/urls.py

Joabsonlg/ddm-rest-api

27d72f5e7dcb061f56b7fd504c76bc7746ecabe2

[ "MIT" ]

null

users/urls.py

Joabsonlg/ddm-rest-api

27d72f5e7dcb061f56b7fd504c76bc7746ecabe2

[ "MIT" ]

null

from django.conf.urls import url from users.views import PasswordResetView urlpatterns = [ url(r'^password/reset/confirm/(?P<uid>[\w-]+)/(?P<token>[\w-]+)/$', PasswordResetView.as_view(), ), ]

24.875

103

0.678392

26

199

5.153846

0.769231

0

0.105528

199

7

104

28.428571

0.752809

0

0.296482

0

1

0

false

0.4

0

0.4

0

1

0

null

0

1

0

null

0

1

0

4

41f145de90d8db0951e6947d894f25270bd87df6

347

py

Python

refined/predicates/__init__.py

espetro/refined

c2f38418268e8d89634ede1265d869d8d54dc9d4

[ "MIT" ]

4

2021-10-04T19:53:04.000Z

2021-12-17T07:08:42.000Z

refined/predicates/__init__.py

espetro/refined

c2f38418268e8d89634ede1265d869d8d54dc9d4

[ "MIT" ]

null

refined/predicates/__init__.py

espetro/refined

c2f38418268e8d89634ede1265d869d8d54dc9d4

[ "MIT" ]

null

from .base import RefinementPredicate, RefinementTypeException from .numeric import PositivePredicate, NegativePredicate from .collection import EmptyPredicate, NonEmptyPredicate from .string import ( ValidIntPredicate, ValidFloatPredicate, XmlPredicate, CsvPredicate, IPv4Predicate, IPv6Predicate, TrimmedPredicate, )

26.692308

62

0.795389

25

347

11.04

0.76

0

0.006849

0.158501

347

12

63

28.916667

0.938356

0

1

0

true

0

0.333333

0

0.333333

0

1

0

1

null

0

null

0

1

0

1

0

4

51060dd531668e89afc214b032d7874e7d4d14a8

83

py

Python

packages/jsii-rosetta/test/translations/imports/selective_import.py

NGL321/jsii

a31ebf5ef676391d97f2286edc21e5859c38c96c

[ "Apache-2.0" ]

1,639

2019-07-05T07:21:00.000Z

2022-03-31T09:55:01.000Z

packages/jsii-rosetta/test/translations/imports/selective_import.py

NGL321/jsii

a31ebf5ef676391d97f2286edc21e5859c38c96c

[ "Apache-2.0" ]

2,704

2019-07-01T23:10:28.000Z

2022-03-31T23:40:12.000Z

packages/jsii-rosetta/test/translations/imports/selective_import.py

NGL321/jsii

a31ebf5ef676391d97f2286edc21e5859c38c96c

[ "Apache-2.0" ]

146

2019-07-02T14:36:25.000Z

2022-03-26T00:21:27.000Z

from scope.some_module import one, Two, some_three, four as renamed Two() renamed()

27.666667

67

0.783133

14

83

4.5

0.785714

0

0.120482

83

3

68

27.666667

0.863014

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

0

1

0

null

0

1

0

1

0

4

511431191016a23f97c536d51308273c8e87f098

7,592

py

Python

legislativeinfo/models.py

nhieckqo/lei

f461d8dcbc8f9e037c661abb18b226aa6fa7acae

[ "MIT" ]

null

legislativeinfo/models.py

nhieckqo/lei

f461d8dcbc8f9e037c661abb18b226aa6fa7acae

[ "MIT" ]

null

legislativeinfo/models.py

nhieckqo/lei

f461d8dcbc8f9e037c661abb18b226aa6fa7acae

[ "MIT" ]

null

# This is an auto-generated Django model module. # You'll have to do the following manually to clean this up: # * Rearrange models' order # * Make sure each model has one field with primary_key=True # * Make sure each ForeignKey and OneToOneField has `on_delete` set to the desired behavior # * Remove `managed = False` lines if you wish to allow Django to create, modify, and delete the table # Feel free to rename the models, but don't rename db_table values or field names. from django.db import models class CfgApprovingOfficers(models.Model): li_ao_id = models.AutoField(primary_key=True) name = models.TextField(blank=True, null=True) designation = models.TextField(blank=True, null=True) class Meta: managed = False db_table = 'lei"."cfg_approving_officers' def __str__(self): return str(self.name) class CfgAttestingOfficers(models.Model): li_ao_id = models.AutoField(primary_key=True) name = models.TextField(blank=True, null=True) designation = models.TextField(blank=True, null=True) class Meta: managed = False db_table = 'lei"."cfg_attesting_officers' def __str__(self): return str(self.name) class CfgCertifyingOfficers(models.Model): li_co_id = models.AutoField(primary_key=True) name = models.TextField(blank=True, null=True) designation = models.TextField(blank=True, null=True) co_code = models.CharField(max_length=100, unique=True) class Meta: managed = False db_table = 'lei"."cfg_certifying_officers' def __str__(self): return str(self.name) + " - " + str(self.designation) class CfgGlobal(models.Model): li_cg_id = models.AutoField(primary_key=True) attribute_name = models.CharField(max_length=200, blank=True, null=True) val_text = models.TextField(blank=True, null=True) val_num = models.DecimalField(max_digits=65535, decimal_places=65535, blank=True, null=True) val_date = models.DateField(blank=True, null=True) class Meta: managed = False db_table = 'lei"."cfg_global' def __str__(self): return str(self.attribute_name) class CfgOfficials(models.Model): li_o_id = models.AutoField(primary_key=True) name = models.TextField(blank=True, null=True) designation = models.TextField(blank=True, null=True) class Meta: managed = False db_table = 'lei"."cfg_officials' def __str__(self): return str(self.name) class CfgPresidingOfficers(models.Model): li_po_id = models.AutoField(primary_key=True) name = models.TextField(blank=True, null=True) designation = models.TextField(blank=True, null=True) class Meta: managed = False db_table = 'lei"."cfg_presiding_officers' def __str__(self): return str(self.name) + " - " + str(self.designation) class LegApprovedBy(models.Model): li_lab_id = models.AutoField(primary_key=True) approved_by_name = models.TextField(blank=True, null=True) approved_by_designation = models.TextField(blank=True, null=True) approved_by_remarks = models.TextField(blank=True, null=True) li_li = models.ForeignKey('LegislativeInfo', models.DO_NOTHING, blank=True, null=True) class Meta: managed = False db_table = 'lei"."leg_approved_by' def __str__(self): return str(self.approved_by_name) class LegAttendees(models.Model): li_la_id = models.AutoField(primary_key=True) name = models.TextField(blank=True, null=True) designation = models.TextField(blank=True, null=True) is_present = models.BooleanField(blank=True, null=True) remarks = models.TextField(blank=True, null=True) li_li = models.ForeignKey('LegislativeInfo', models.DO_NOTHING, blank=True, null=True) li_li_o = models.ForeignKey('CfgOfficials', models.DO_NOTHING, blank=True, null=True) class Meta: managed = False db_table = 'lei"."leg_attendees' def __str__(self): return str(self.name) class LegAttestedBy(models.Model): li_lab_id = models.AutoField(primary_key=True) attested_by_name = models.TextField(blank=True, null=True) attested_by_designation = models.TextField(blank=True, null=True) attested_by_remarks = models.TextField(blank=True, null=True) li_li = models.ForeignKey('LegislativeInfo', models.DO_NOTHING, blank=True, null=True) class Meta: managed = False db_table = 'lei"."leg_attested_by' def __str__(self): return str(self.attested_by_name) class LegCertifiedBy(models.Model): li_lcb_id = models.AutoField(primary_key=True) certified_by_name = models.TextField(blank=True, null=True) certified_by_designation = models.TextField(blank=True, null=True) certified_by_remarks = models.TextField(blank=True, null=True) li_li = models.ForeignKey('LegislativeInfo', models.DO_NOTHING, blank=True, null=True) # co_code = models.ForeignKey('CfgCertifyingOfficers', models.DO_NOTHING, blank=True, null=True, to_field="co_code") li_li_co = models.ForeignKey('CfgCertifyingOfficers', models.DO_NOTHING, blank=True, null=True) class Meta: managed = False db_table = 'lei"."leg_certified_by' def __str__(self): return str(self.li_li) + " / " +str(self.certified_by_name) class LegPresidedOverBy(models.Model): li_lpob_id = models.AutoField(primary_key=True) presided_over_by_name = models.CharField(blank=True, null=True, max_length=500) presided_over_by_designation = models.CharField(blank=True, null=True, max_length=500) presided_over_by_remarks = models.CharField(blank=True, null=True, max_length=500) li_li = models.ForeignKey('LegislativeInfo', models.DO_NOTHING, blank=True, null=True) li_li_po = models.ForeignKey('CfgPresidingOfficers', models.DO_NOTHING, blank=True, null=True) class Meta: managed = False db_table = 'lei"."leg_presided_over_by' def __str__(self): return str(self.li_li) + " / " +str(self.presided_over_by_name) class LegislativeInfo(models.Model): li_id = models.AutoField(primary_key=True) record_no = models.CharField(max_length=100, blank=True, null=True) series = models.CharField(max_length=100, blank=True, null=True) approved_date = models.DateField(blank=True, null=True) summary = models.TextField(blank=True, null=True) body_text = models.TextField(blank=True, null=True) created_by_username = models.CharField(max_length=100, blank=True, null=True) created_date = models.DateTimeField(blank=True, null=True) edited_date = models.DateTimeField(blank=True, null=True) edited_by_username = models.CharField(max_length=100, blank=True, null=True) whole_text = models.TextField(blank=True, null=True) title = models.TextField(blank=True, null=True) scanned = models.BooleanField(blank=True, null=True) class Meta: managed = False db_table = 'lei"."legislative_info' def __str__(self): return str(self.record_no)+" - "+str(self.series) class OverviewLi(models.Model): li_id = models.IntegerField(blank=False, null=False, primary_key=True) res_no_full = models.TextField(blank=True, null=True) approved_date = models.DateField(blank=True, null=True) title = models.TextField(blank=True, null=True) summary = models.TextField(blank=True, null=True) scanned = models.BooleanField(blank=True, null=True) class Meta: managed = False # Created from a view. Don't remove. db_table = 'lei"."overview__li'

36.854369

120

0.712724

1,017

7,592

5.107178

0.154376

0.097035

0.140162

0.183288

0.747978

0.726415

0.686946

0.649788

0.562187

0.517328

0

0.005921

0.176897

7,592

205

121

37.034146

0.825252

0.081665

0

0.5

1

0

0.0632

0.035335

0

1

0.082192

false

0

0.006849

0.082192

0.821918

0

null

0

1

0

1

0

1

0

null

0

1

0

4

513d958aebd657d8e7a78672d2fc67b1944313aa

261

py

Python

src/sample/atm/bank_account_main.py

acc-cosc-1336/cosc-1336-spring-2018-artgonzalezacc

c5dcc0ad7c47345c274d61c7e94f6c3b0ed42245

[ "MIT" ]

null

src/sample/atm/bank_account_main.py

acc-cosc-1336/cosc-1336-spring-2018-artgonzalezacc

c5dcc0ad7c47345c274d61c7e94f6c3b0ed42245

[ "MIT" ]

null

src/sample/atm/bank_account_main.py

acc-cosc-1336/cosc-1336-spring-2018-artgonzalezacc

c5dcc0ad7c47345c274d61c7e94f6c3b0ed42245

[ "MIT" ]

null

from bank_account import BankAccount joes_account = BankAccount(500) print(joes_account.get_balance()) print() joes_account.deposit(500) print(joes_account.get_balance()) print() joes_account.withdraw(100) print(joes_account.get_balance())

16.3125

37

0.758621

34

261

5.529412

0.382353

0.351064

0.425532

0.303191

0.617021

0.478723

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0.039823

0.1341

261

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null

1

0

null

0

1

0

4

514615cd481fcb31980577d3ebc782c644b02aca

8,020

py

Python

sdk/python/pulumi_vault/jwt/_inputs.py

pulumi/pulumi-vault

1682875f4a5d7d508f36e166529ad2b8aec34090

[ "ECL-2.0", "Apache-2.0" ]

10

2019-10-07T17:44:18.000Z

2022-03-30T20:46:33.000Z

sdk/python/pulumi_vault/jwt/_inputs.py

pulumi/pulumi-vault

1682875f4a5d7d508f36e166529ad2b8aec34090

[ "ECL-2.0", "Apache-2.0" ]

79

2019-10-11T18:13:07.000Z

2022-03-31T21:09:41.000Z

sdk/python/pulumi_vault/jwt/_inputs.py

pulumi/pulumi-vault

1682875f4a5d7d508f36e166529ad2b8aec34090

[ "ECL-2.0", "Apache-2.0" ]

2

2019-10-28T10:08:40.000Z

2020-03-17T14:20:55.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities __all__ = [ 'AuthBackendTuneArgs', ] @pulumi.input_type class AuthBackendTuneArgs: def __init__(__self__, *, allowed_response_headers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, audit_non_hmac_request_keys: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, audit_non_hmac_response_keys: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, default_lease_ttl: Optional[pulumi.Input[str]] = None, listing_visibility: Optional[pulumi.Input[str]] = None, max_lease_ttl: Optional[pulumi.Input[str]] = None, passthrough_request_headers: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]] = None, token_type: Optional[pulumi.Input[str]] = None): """ :param pulumi.Input[Sequence[pulumi.Input[str]]] allowed_response_headers: List of headers to whitelist and allowing a plugin to include them in the response. :param pulumi.Input[Sequence[pulumi.Input[str]]] audit_non_hmac_request_keys: Specifies the list of keys that will not be HMAC'd by audit devices in the request data object. :param pulumi.Input[Sequence[pulumi.Input[str]]] audit_non_hmac_response_keys: Specifies the list of keys that will not be HMAC'd by audit devices in the response data object. :param pulumi.Input[str] default_lease_ttl: Specifies the default time-to-live. If set, this overrides the global default. Must be a valid [duration string](https://golang.org/pkg/time/#ParseDuration) :param pulumi.Input[str] listing_visibility: Specifies whether to show this mount in the UI-specific listing endpoint. Valid values are "unauth" or "hidden". :param pulumi.Input[str] max_lease_ttl: Specifies the maximum time-to-live. If set, this overrides the global default. Must be a valid [duration string](https://golang.org/pkg/time/#ParseDuration) :param pulumi.Input[Sequence[pulumi.Input[str]]] passthrough_request_headers: List of headers to whitelist and pass from the request to the backend. :param pulumi.Input[str] token_type: Specifies the type of tokens that should be returned by the mount. Valid values are "default-service", "default-batch", "service", "batch". """ if allowed_response_headers is not None: pulumi.set(__self__, "allowed_response_headers", allowed_response_headers) if audit_non_hmac_request_keys is not None: pulumi.set(__self__, "audit_non_hmac_request_keys", audit_non_hmac_request_keys) if audit_non_hmac_response_keys is not None: pulumi.set(__self__, "audit_non_hmac_response_keys", audit_non_hmac_response_keys) if default_lease_ttl is not None: pulumi.set(__self__, "default_lease_ttl", default_lease_ttl) if listing_visibility is not None: pulumi.set(__self__, "listing_visibility", listing_visibility) if max_lease_ttl is not None: pulumi.set(__self__, "max_lease_ttl", max_lease_ttl) if passthrough_request_headers is not None: pulumi.set(__self__, "passthrough_request_headers", passthrough_request_headers) if token_type is not None: pulumi.set(__self__, "token_type", token_type) @property @pulumi.getter(name="allowedResponseHeaders") def allowed_response_headers(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ List of headers to whitelist and allowing a plugin to include them in the response. """ return pulumi.get(self, "allowed_response_headers") @allowed_response_headers.setter def allowed_response_headers(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "allowed_response_headers", value) @property @pulumi.getter(name="auditNonHmacRequestKeys") def audit_non_hmac_request_keys(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Specifies the list of keys that will not be HMAC'd by audit devices in the request data object. """ return pulumi.get(self, "audit_non_hmac_request_keys") @audit_non_hmac_request_keys.setter def audit_non_hmac_request_keys(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "audit_non_hmac_request_keys", value) @property @pulumi.getter(name="auditNonHmacResponseKeys") def audit_non_hmac_response_keys(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ Specifies the list of keys that will not be HMAC'd by audit devices in the response data object. """ return pulumi.get(self, "audit_non_hmac_response_keys") @audit_non_hmac_response_keys.setter def audit_non_hmac_response_keys(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "audit_non_hmac_response_keys", value) @property @pulumi.getter(name="defaultLeaseTtl") def default_lease_ttl(self) -> Optional[pulumi.Input[str]]: """ Specifies the default time-to-live. If set, this overrides the global default. Must be a valid [duration string](https://golang.org/pkg/time/#ParseDuration) """ return pulumi.get(self, "default_lease_ttl") @default_lease_ttl.setter def default_lease_ttl(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "default_lease_ttl", value) @property @pulumi.getter(name="listingVisibility") def listing_visibility(self) -> Optional[pulumi.Input[str]]: """ Specifies whether to show this mount in the UI-specific listing endpoint. Valid values are "unauth" or "hidden". """ return pulumi.get(self, "listing_visibility") @listing_visibility.setter def listing_visibility(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "listing_visibility", value) @property @pulumi.getter(name="maxLeaseTtl") def max_lease_ttl(self) -> Optional[pulumi.Input[str]]: """ Specifies the maximum time-to-live. If set, this overrides the global default. Must be a valid [duration string](https://golang.org/pkg/time/#ParseDuration) """ return pulumi.get(self, "max_lease_ttl") @max_lease_ttl.setter def max_lease_ttl(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "max_lease_ttl", value) @property @pulumi.getter(name="passthroughRequestHeaders") def passthrough_request_headers(self) -> Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]: """ List of headers to whitelist and pass from the request to the backend. """ return pulumi.get(self, "passthrough_request_headers") @passthrough_request_headers.setter def passthrough_request_headers(self, value: Optional[pulumi.Input[Sequence[pulumi.Input[str]]]]): pulumi.set(self, "passthrough_request_headers", value) @property @pulumi.getter(name="tokenType") def token_type(self) -> Optional[pulumi.Input[str]]: """ Specifies the type of tokens that should be returned by the mount. Valid values are "default-service", "default-batch", "service", "batch". """ return pulumi.get(self, "token_type") @token_type.setter def token_type(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "token_type", value)

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1

0

1

0

null

0

1

0

4

5147f21139dd6c9dc6a43a9b47e7cc9528a3b408

1,057

py

Python

bek.py

ReyBek/lb2

57e933d3137cd1f72c6651668c7e78a3223ed4d9

[ "MIT" ]

null

bek.py

ReyBek/lb2

57e933d3137cd1f72c6651668c7e78a3223ed4d9

[ "MIT" ]

null

bek.py

ReyBek/lb2

57e933d3137cd1f72c6651668c7e78a3223ed4d9

[ "MIT" ]

null

print("что-то на бизарном\n\n") print("Меня зовут Кира Йошикаге.") print("Мне 33 года.") print("Мой дом находится в северо-восточной части Морио, где расположены все виллы.") print("Я не женат. Я работаю в универмаге Kame Yu и прихожу домой не позднее 8 вечера.") print("Я не курю, но иногда выпиваю.") print("Я ложусь спать в 11 вечера, и убеждаюсь, что я получаю ровно восемь часов сна, несмотря ни на что.") print("Выпив стакан теплого молока и потянувшись минут двадцать перед сном, я обычно без проблем сплю до утра.") print("Словно ребёнок я просыпаюсь утром без всякой усталости и стресса.") print("На моём последнем осмотре мне сказали, что у меня нет никаких проблем со здоровьем.") print("Я пытаюсь донести, что я обычный человек, который хочет жить спокойной жизнью.") print("Я забочусь о том, чтобы не утруждать себя какими-либо врагами – победами и поражениями, которые могли бы потревожить мой сон.") print("Вот как я отношусь к обществу, и я знаю, что это приносит мне счастье. Хотя, если бы мне пришлось сражаться, я бы никому не проиграл.")

81.307692

142

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178

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1,057

13

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81.307692

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0

1

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true

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null

0

1

0

null

0

1

0

1

0

4

5a98f69942b7ddee1c03b742b19eb1329ef1cfb4

9,728

py

Python

software/test/test.py

acmmmsys/2018-HTTP-Adaptive-Streaming-QoE-Estimation-With-P.1203

b73270267ce063532fb6280764a91910d18dba14

[ "zlib-acknowledgement" ]

4

2018-10-28T08:52:06.000Z

2021-09-06T12:26:34.000Z

software/test/test.py

acmmmsys/2018-HTTP-Adaptive-Streaming-QoE-Estimation-With-P.1203

b73270267ce063532fb6280764a91910d18dba14

[ "zlib-acknowledgement" ]

null

software/test/test.py

acmmmsys/2018-HTTP-Adaptive-Streaming-QoE-Estimation-With-P.1203

b73270267ce063532fb6280764a91910d18dba14

[ "zlib-acknowledgement" ]

1

2020-11-19T08:28:59.000Z

#!/usr/bin/env python3 import os import sys import unittest sys.path.insert(0, os.path.dirname(os.path.realpath(__file__)) + '/../') from itu_p1203 import __version__ from itu_p1203 import P1203Standalone from itu_p1203 import P1203Pv import itu_p1203.utils as utils class TestP1203Parts(unittest.TestCase): def test_parsing(self): """ Perform a small in-built test using example files """ print("Testing model version {}".format(__version__)) basedir = os.path.dirname(os.path.realpath(__file__)) + '/../' if not os.path.isdir(basedir + "examples"): print("Examples folder is missing.") sys.exit(1) test_files = [ basedir + "examples/mode0.json", basedir + "examples/mode0_no_stalling.json", basedir + "examples/mode0_with_representation_ids.json", basedir + "examples/mode1.json", basedir + "examples/mode1_without_audio_without_stalling.json", basedir + "examples/mode3.json", basedir + "examples/mode3_without_audio_without_stalling.json" ] for test_file in sorted(test_files): test_case = os.path.splitext(os.path.basename(test_file))[0] test_data = utils.read_json_without_comments(test_file) print("Checking {}".format(test_case)) test_model = P1203Standalone(test_data) test_model.calculate_complete() def test_model_functions(self): """ Run a series of tests against models """ print("Testing model version {}".format(__version__)) failed = 0 avg_qp_per_frame = [26.605956612329944, 30.17195734771418, 32.89184549356223, 34.06182531894014, 33.44129901960784, 29.722637578134574, 32.251378845446744, 33.26394507784725, 33.490804315841096, 29.593455080279448, 32.308805494235955, 33.448791855758614, 33.38045610593428, 29.569117647058825, 32.68492647058824, 33.27613678146832, 34.02036310107949, 29.60178943497978, 32.25796568627451, 33.3860294117647, 33.087388160313765, 29.707807329329576, 31.710413344781063, 33.097842079450714, 32.612452506434614, 29.593577644319158, 32.02500306410099, 32.81556372549019, 32.641666666666666, 34.54432863274065, 27.31764705882353, 30.356171099399436, 33.393111056631525, 34.91981363413438, 34.78062538320049, 30.418014705882353, 32.86985294117647, 34.362009803921566, 34.08370098039216, 30.840299056256896, 33.34681372549019, 33.40818828144153, 33.68730839975475, 31.09020713322711, 32.777178575805856, 33.80122549019608, 34.54001715896556, 31.11925481063856, 33.01911999019487, 34.29921549399363, 33.37153714145624, 31.462434121828654, 33.70106630714548, 34.37690044139284, 33.96542422756253, 31.5828431372549, 33.469607843137254, 34.24031862745098, 34.18799019607843, 35.191053921568624, 27.845833333333335, 31.17526657678637, 33.77561274509804, 34.446829387955354, 34.78239548853745, 31.00147076847653, 33.45030028189729, 34.64620098039216, 34.44056372549019, 31.30935163622993, 33.18163990685133, 34.2268660375046, 34.10626302242922, 31.07683823529412, 33.406004901960785, 34.60110294117647, 34.0031862745098, 31.03382767496017, 33.43982843137255, 34.810661764705884, 34.432598039215684, 30.966299019607842, 33.298811128814805, 34.02242921926707, 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34.48664215686274, 34.92313350496506, 31.46421568627451, 33.62046568627451, 34.84985905135433, 34.138007108714305, 31.483210784313727, 33.344485294117646, 34.30889924000981, 34.443804387792625, 35.37708333333333, 28.170976835396495, 31.956004901960785, 33.93345588235294, 35.29450711132908, 35.08335376317725, 31.724230910650814, 33.79671407552722, 35.314950980392155, 34.797916666666666, 31.761367814683172, 33.743718592964825, 34.753553921568624, 34.71997549019608, 31.56482843137255, 33.61691176470588, 34.767373452629, 34.947781318950724, 31.78208113739429, 33.56209390707368, 34.615686274509805, 34.90281862745098, 31.91469542836132, 33.58034072803039, 34.52120098039216, 34.77561274509804, 31.781468317195735, 33.27228147603285, 34.23664215686274, 34.34931338891614, 35.006624141315015, 28.3569064836377] tests = { "mode0": [ { "mos": 4.311, "args": (1920*1080, 1920*1080, 2801.27587623, 30) }, { "mos": 2.664, "args": (852*480, 1920*1080, 629.203792838, 30) }, { "mos": 1.085, "args": (426*240, 1920*1080, 224.771246112, 30) } ], "mode1": [ { "mos": 4.061, "args": (1920*1080, 1920*1080, 2409.39329393, 30, [], 10.9551545708) }, { "mos": 3.76, "args": (1920*1080, 1920*1080, 2805.94165942, 30, [], 7.4658972759) }, { "mos": 2.551, "args": (852*480, 1920*1080, 529.580495805, 30, [], 11.7097170972) }, { "mos": 1.118, "args": (426*240, 1920*1080, 132.874928749, 30, [], 22.5031055901) } ], "mode3": [ { "mos": 3.665, "args": (1920*1080, 1920*1080, 30, [], 0.6537627021) }, { "mos": 1.05, "args": (102240, 1920*1080, 30, [], 0.7688713219) }, { "mos": 3.671, "args": (1920*1080, 1920*1080, 30, [], None, avg_qp_per_frame)} ] } for mode, mode_tests in tests.items(): for test_data in mode_tests: fun = getattr(P1203Pv, "video_model_function_" + mode) ret = round(fun(*test_data["args"]), 3) mos = test_data["mos"] if abs(ret - mos) > 0.01: print("{mode} test failed, expected {mos}, got {ret}".format(**locals())) failed += 1 else: print("{mode} test passed".format(mode=mode)) self.assertTrue(failed == 0) if __name__ == '__main__': unittest.main()

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0

0.054006

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0

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false

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0

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0

null

0

1

0

1

0

null

0

4

5aae56eeb62afa137ba175a6b816eb92f861722b

293

py

Python

blog/post/tests.py

znf896/Django-React-

44bfbffc8f6a6fa13e001f3fc4b42005afa426bc

[ "MIT" ]

1

2021-05-10T15:29:00.000Z

blog/post/tests.py

znf896/Django-React-

44bfbffc8f6a6fa13e001f3fc4b42005afa426bc

[ "MIT" ]

7

2020-09-07T12:44:21.000Z

2022-02-26T18:35:20.000Z

blog/post/tests.py

znf896/Django-React-

44bfbffc8f6a6fa13e001f3fc4b42005afa426bc

[ "MIT" ]

null

from django.test import TestCase from datetime import datetime, timedelta, timezone # from .models import Post # Create your tests here. # print(datetime.now(timezone(timedelta(hours=8)))) # post = Post.objects.order_by('-id') # post2 = Post.objects.get(pk=3) # print(type(post), type(post2))

32.555556

51

0.744027

43

293

5.046512

0.627907

0.101382

0

0.015385

0.112628

293

8

52

36.625

0.819231

0.668942

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

4

85133c6a80f52c8b906f714fba534711cefe9107

311

py

Python

config/profile.py

tenstone/xiaoyun-smart-speaker-server

6afcdedd1a2485269afffb425803aff71b6cbd51

[ "MIT" ]

1

2020-05-18T06:58:25.000Z

config/profile.py

tenstone/xiaoyun-smart-speaker-server

6afcdedd1a2485269afffb425803aff71b6cbd51

[ "MIT" ]

1

2022-02-10T12:45:45.000Z

config/profile.py

tenstone/xiaoyun-smart-speaker-server

6afcdedd1a2485269afffb425803aff71b6cbd51

[ "MIT" ]

null

import config yaml_settings = config.load_yaml_settings() aliyun_ak_id = yaml_settings['aliyun']['ak_id'] aliyun_ak_secret = yaml_settings['aliyun']['ak_secret'] aliyun_iot_device_name = yaml_settings['aliyun']['iothub']['device_name'] aliyun_iot_product_key = yaml_settings['aliyun']['iothub']['product_key']

38.875

73

0.787781

44

311

5.090909

0.340909

0.321429

0.401786

0.267857

0.196429

0

0.057878

311

8

74

38.875

0.764505

0

0.230769

0

1

0

false

0

0.166667

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0.166667

0

null

1

0

1

0

null

0

4

51b38e61a90d7e467d243db43dea9b72fe3e2798

175

py

Python

backend/coreApi/coreApi/asgi.py

rochdikhalid/kopra-v1

1899e6f695ff8b3041aa7b4e24f99cb6f585085c

[ "MIT" ]

3

2021-12-14T12:31:18.000Z

2021-12-15T08:12:45.000Z

backend/coreApi/coreApi/asgi.py

rochdikhalid/kopra-v1

1899e6f695ff8b3041aa7b4e24f99cb6f585085c

[ "MIT" ]

null

backend/coreApi/coreApi/asgi.py

rochdikhalid/kopra-v1

1899e6f695ff8b3041aa7b4e24f99cb6f585085c

[ "MIT" ]

1

2022-01-06T14:41:27.000Z

import os from django.core.asgi import get_asgi_application os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'coreApi.settings') application = get_asgi_application()

21.875

68

0.794286

22

175

6.045455

0.590909

0.105263

0.270677

0

0.12

175

7

69

25

0.863636

0

0.22619

0.130952

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

4

51b85f9aa926f312768679de92c005addddd5a55

431

py

Python

pyfuncs/anonymous_functions/lambdas/open_closed/open_closed_tests.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

3

2017-05-02T10:28:13.000Z

2019-02-06T09:10:11.000Z

pyfuncs/anonymous_functions/lambdas/open_closed/open_closed_tests.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

2

2017-06-21T20:39:14.000Z

2020-02-25T10:28:57.000Z

pyfuncs/anonymous_functions/lambdas/open_closed/open_closed_tests.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

2

2016-07-29T04:35:22.000Z

2017-01-18T17:05:36.000Z

import unittest from Lambdas.OpenClosed.open_closed import greet, spoken, shouted, whispered class MyTestCase(unittest.TestCase): def test_1(self): self.assertEqual(greet(spoken, "Hello"), "Hello.") def test_2(self): self.assertEqual(greet(shouted, "Hello"), "HELLO!") def test_3(self): self.assertEqual(greet(whispered, "Hello"), "hello.") if __name__ == '__main__': unittest.main()

22.684211

76

0.675174

51

431

5.470588

0.490196

0.075269

0.204301

0.258065

0

0.008499

0.180974

431

18

77

23.944444

0.78187

0

0.095128

0

0.272727

1

0.272727

false

0

0.181818

0

0.545455

0

null

0

1

0

null

0

1

0

1

0

4

51f468130ef3c4010cdc5ac019207df588255d42

195

py

Python

samsa/kafka/exceptions.py

tombasche/samsa

c7e55f9cbc2f87df310a3ed8246b4c5784937984

[ "MIT" ]

null

samsa/kafka/exceptions.py

tombasche/samsa

c7e55f9cbc2f87df310a3ed8246b4c5784937984

[ "MIT" ]

null

samsa/kafka/exceptions.py

tombasche/samsa

c7e55f9cbc2f87df310a3ed8246b4c5784937984

[ "MIT" ]

1

2019-07-01T12:03:51.000Z

class KafkaTimeoutError(Exception): """ Error raised when the poll from Kafka returns nothing and therefore there is nothing to read. """ pass # pylint:disable=unnecessary-pass

27.857143

97

0.717949

24

195

5.833333

0.916667

0

0.210256

195

6

98

32.5

0.909091

0.646154

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

4

51fff6f063f69c8613fba172d3267c69077fa417

156

py

Python

src/cbopensource/connectors/taxii/__init__.py

jjfallete/cb-taxii-connector

31b42c8ea46d14f2af63788a8ffada0c998bdb46

[ "MIT" ]

16

2015-09-21T18:22:00.000Z

2021-11-04T11:16:12.000Z

src/cbopensource/connectors/taxii/__init__.py

jjfallete/cb-taxii-connector

31b42c8ea46d14f2af63788a8ffada0c998bdb46

[ "MIT" ]

20

2016-02-09T20:44:35.000Z

2022-03-28T20:48:09.000Z

src/cbopensource/connectors/taxii/__init__.py

jjfallete/cb-taxii-connector

31b42c8ea46d14f2af63788a8ffada0c998bdb46

[ "MIT" ]

9

2015-09-28T08:12:23.000Z

2022-03-28T20:09:12.000Z

31.2

80

0.339744

12

156

4.5

1

0

0.06338

0.089744

156

4

81

39

0.309859

0.442308

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

cfbb01ef6985d34bcf988ce915307a2f0349dba2

237

py

Python

PY/test.py

digitalrobertlima/BrCrypto

a49a0020266bf89e76db7b1f57792727eab3470f

[ "MIT" ]

null

PY/test.py

digitalrobertlima/BrCrypto

a49a0020266bf89e76db7b1f57792727eab3470f

[ "MIT" ]

null

PY/test.py

digitalrobertlima/BrCrypto

a49a0020266bf89e76db7b1f57792727eab3470f

[ "MIT" ]

null

import unittest from Block import * from Transaction import * from ecdsa import SigningKey, NIST384p class UnitTest(unittest.TestCase): def hash(self): self.assertEqual(calculateHash(0, "", 1465154705, [], 0, 0), "")

29.625

76

0.691983

27

237

6.074074

0.62963

0.121951

0

0.08377

0.194093

237

8

76

29.625

0.774869

0

0.142857

1

0.142857

false

0

0.571429

0

0.857143

0

1

0

null

0

1

0

null

0

1

0

1

0

4

32150a316f825044e34a51fba264b73b769087ea

152

py

Python

seiretsu/matrix/scoring_matrix.py

ja-b/seiretsu

665804d48043696b34cbca5a0e2de0d1ab27b84d

[ "MIT" ]

null

seiretsu/matrix/scoring_matrix.py

ja-b/seiretsu

665804d48043696b34cbca5a0e2de0d1ab27b84d

[ "MIT" ]

null

seiretsu/matrix/scoring_matrix.py

ja-b/seiretsu

665804d48043696b34cbca5a0e2de0d1ab27b84d

[ "MIT" ]

null

class ScoringMatrix(object): """ Defines a scoring-matrix between Kanji """ def get(self, **kwargs): raise NotImplementedError

19

42

0.638158

15

152

6.466667

1

0

0.256579

152

7

43

21.714286

0.858407

0.25

0

1

0.333333

false

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

5c63c79ad48961ad6e3375402609c9aeabf1b3d9

200

py

Python

api/crud_projects/router.py

pypeclub/openpype4-backend

a0abe2ed66887c6529b01bbb9cb00278bbff41e4

[ "Apache-2.0" ]

2

2022-03-09T08:02:52.000Z

2022-03-15T00:34:01.000Z

api/crud_projects/router.py

pypeclub/openpype4-backend

a0abe2ed66887c6529b01bbb9cb00278bbff41e4

[ "Apache-2.0" ]

1

2022-03-08T16:22:34.000Z

api/crud_projects/router.py

pypeclub/openpype4-backend

a0abe2ed66887c6529b01bbb9cb00278bbff41e4

[ "Apache-2.0" ]

null

from fastapi import APIRouter from openpype.api import ResponseFactory router = APIRouter( tags=["Projects"], responses={401: ResponseFactory.error(401), 403: ResponseFactory.error(403)}, )

22.222222

81

0.75

22

200

6.818182

0.636364

0.266667

0

0.069364

0.135

200

8

82

25

0.797688

0

0.04

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

4

5c736cbbc8168d23b68a2c4e75adab29b85191a6

1,206

py

Python

setup.py

dikkechill/LightMatchingEngine

112ea6c386aa33cb6d3dc024d9f5a1ec6c70aec4

[ "MIT" ]

251

2017-02-08T00:18:15.000Z

2022-03-31T03:36:03.000Z

setup.py

dikkechill/LightMatchingEngine

112ea6c386aa33cb6d3dc024d9f5a1ec6c70aec4

[ "MIT" ]

9

2017-02-08T02:20:49.000Z

2022-01-13T20:17:22.000Z

setup.py

dikkechill/LightMatchingEngine

112ea6c386aa33cb6d3dc024d9f5a1ec6c70aec4

[ "MIT" ]

80

2017-06-06T15:58:08.000Z

2022-03-05T07:32:42.000Z

from setuptools import setup, find_packages, Extension setup( name="lightmatchingengine", url="https://github.com/gavincyi/LightMatchingEngine", license='MIT', author="Gavin Chan", author_email="gavincyi@gmail.com", description="A light matching engine", packages=find_packages(exclude=('tests',)), use_scm_version=True, install_requires=[], setup_requires=['setuptools_scm', 'cython'], ext_modules=[Extension( 'lightmatchingengine.lightmatchingengine', ['lightmatchingengine/lightmatchingengine.pyx'])], tests_require=[ 'pytest' ], extras_require={ 'performance': ['pandas', 'docopt', 'tabulate', 'tqdm'] }, classifiers=[ 'Development Status :: 2 - Pre-Alpha', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', 'Programming Language :: Python :: 3.7', ], )

28.714286

63

0.621061

112

1,206

6.589286

0.553571

0.205962

0.271003

0.176152

0

0.013994

0.229685

1,206

41

64

29.414634

0.780409

0

0.058824

0

0.519071

0.067993

0

1

0

true

0

0.029412

0

0.029412

0

null

1

0

null

0

1

0

4

5cbac6b3ac6d45387f075b5224ec67897c10f280

68

py

Python

flaskserver.py

listenzcc/HTML_backend_scripts

3441ee643461219d1d90212a7f5f072c294b2c6a

[ "MIT" ]

null

flaskserver.py

listenzcc/HTML_backend_scripts

3441ee643461219d1d90212a7f5f072c294b2c6a

[ "MIT" ]

null

flaskserver.py

listenzcc/HTML_backend_scripts

3441ee643461219d1d90212a7f5f072c294b2c6a

[ "MIT" ]

null

from FlaskServer.server import Server app = Server() app.run()

13.6

38

0.705882

9

68

5.333333

0.666667

0.375

0

0.191176

68

4

39

17

0.872727

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

4

5cbc5c4d39d797d14a96ee7e3cf1b420bebb4090

77

py

Python

protexam/protexam_output.py

caufieldjh/protexam

425b62ed33fe6c747bc82d28c20ab5da96b17357

[ "MIT" ]

null

protexam/protexam_output.py

caufieldjh/protexam

425b62ed33fe6c747bc82d28c20ab5da96b17357

[ "MIT" ]

1

2021-09-29T18:47:42.000Z

2021-09-29T23:48:51.000Z

protexam/protexam_output.py

caufieldjh/protexam

425b62ed33fe6c747bc82d28c20ab5da96b17357

[ "MIT" ]

null

#!/usr/bin/python #protexam_output.py ''' Output functions for ProtExAM. '''

12.833333

30

0.714286

10

77

5.4

0.8

0

0.103896

77

5

31

15.4

0.782609

0.844156

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

5cd6116771f87fe8a6b99f8ba3cbb8f6acd5b7a9

480

py

Python

manage.py

robcharlwood/you-judge

16c15c8ac725f364fdfe0c48b7485d747d38c4d3

[ "MIT" ]

5

2018-11-05T14:51:08.000Z

2020-11-29T10:32:20.000Z

manage.py

robcharlwood/you-judge

16c15c8ac725f364fdfe0c48b7485d747d38c4d3

[ "MIT" ]

41

2018-07-30T19:49:30.000Z

2021-12-13T19:49:06.000Z

manage.py

robcharlwood/you-judge

16c15c8ac725f364fdfe0c48b7485d747d38c4d3

[ "MIT" ]

1

2021-03-01T09:24:59.000Z

#!/usr/bin/env python import os import sys from core.boot import fix_path fix_path(include_dev_libs=True) if __name__ == '__main__': os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'core.settings.local') from djangae.core.management import execute_from_command_line from djangae.core.management import test_execute_from_command_line if 'test' in sys.argv: test_execute_from_command_line(sys.argv) else: execute_from_command_line(sys.argv)

25.263158

74

0.764583

70

480

4.842857

0.485714

0.129794

0.212389

0.259587

0.442478

0.171091

0

0.152083

480

18

75

26.666667

0.832924

0.041667

0

0.115468

0.04793

0

1

0

true

0

0.416667

0

0.416667

0

null

0

1

0

null

0

1

0

1

0

4

7a298f862f68bd7b75a12e7274f9edf27416d649

99

py

Python

examples/myqueryset/simplerelate/apps.py

zhengtong0898/django-decode

69680853a4a5b07f6a9c4b65c7d86b2d401a92b1

[ "MIT" ]

5

2020-07-14T07:48:10.000Z

2021-12-20T21:20:10.000Z

examples/myqueryset/simplerelate/apps.py

zhengtong0898/django-decode

69680853a4a5b07f6a9c4b65c7d86b2d401a92b1

[ "MIT" ]

7

2021-03-26T03:13:38.000Z

2022-03-12T00:42:03.000Z

examples/myqueryset/simplerelate/apps.py

zhengtong0898/django-decode

69680853a4a5b07f6a9c4b65c7d86b2d401a92b1

[ "MIT" ]

1

2021-02-16T07:04:25.000Z

from django.apps import AppConfig class SimplerelateConfig(AppConfig): name = 'simplerelate'

16.5

36

0.777778

10

99

7.7

0.9

0

0.151515

99

5

37

19.8

0.916667

0

0.121212

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

7a2a336cd8c3364d0b4afa7365f32b55232c3c12

122

py

Python

djangobench/benchmarks/default_middleware/settings.py

Bouke/djangobench

94fc28d99f95c65d26d0fad8af44e46c49282220

[ "BSD-3-Clause" ]

3

2016-11-27T22:25:34.000Z

2018-12-12T20:06:40.000Z

djangobench/benchmarks/default_middleware/settings.py

Bouke/djangobench

94fc28d99f95c65d26d0fad8af44e46c49282220

[ "BSD-3-Clause" ]

null

djangobench/benchmarks/default_middleware/settings.py

Bouke/djangobench

94fc28d99f95c65d26d0fad8af44e46c49282220

[ "BSD-3-Clause" ]

null

from djangobench.base_settings import * INSTALLED_APPS = ['default_middleware'] ROOT_URLCONF = 'default_middleware.urls'

24.4

40

0.819672

14

122

6.785714

0.857143

0.357895

0

0.090164

122

4

41

30.5

0.855856

0

0.336066

0.188525

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

4

7a5dfdae8b762b229fea9c103d0e380405ed8de1

34

py

Python

check.py

skaidmd/Study_Bandits

02471926b5a5a3b568c8028a6234af9f85f99d37

[ "MIT" ]

null

check.py

skaidmd/Study_Bandits

02471926b5a5a3b568c8028a6234af9f85f99d37

[ "MIT" ]

null

check.py

skaidmd/Study_Bandits

02471926b5a5a3b568c8028a6234af9f85f99d37

[ "MIT" ]

null

for i in xrange(10000): print(i)

17

23

0.676471

7

34

3.285714

0.857143

0

0.178571

0.176471

34

2

24

17

0.642857

0

1

0

false

0

0.5

1

0

null

0

1

0

null

0

1

0

4

7a5f26a92d21e57f2287f5f6947b70d4a761e6bd

193

py

Python

.github/noep-pkg/setup.py

DropD/sparkplug

be817103ef32cbc908de004659b538993d14eeb4

[ "MIT" ]

5

2017-11-28T14:57:53.000Z

2019-01-16T08:48:10.000Z

.github/noep-pkg/setup.py

DropD/sparkplug

be817103ef32cbc908de004659b538993d14eeb4

[ "MIT" ]

49

2017-04-11T11:18:58.000Z

2021-02-10T23:06:20.000Z

.github/noep-pkg/setup.py

DropD/sparkplug

be817103ef32cbc908de004659b538993d14eeb4

[ "MIT" ]

8

2017-06-16T17:01:33.000Z

2021-02-09T10:28:03.000Z

# pylint: disable=missing-docstring from setuptools import setup, find_packages if __name__ == '__main__': setup(name='reentry-test-noep', packages=find_packages(), reentry_register=True)

32.166667

84

0.777202

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193

5.791667

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0.172662

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0.103627

193

5

85

38.6

0.803468

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0.158228

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null

0

1

0

null

0

1

0

1

0

4

7a847cce09fc81526b2881206804678f14b67f3b

412

py

Python

Ex017 - Catetos e Hipotenusa.py

MarcusMendes81/Python

4af6653da324604930d24542a84a530348029d39

[ "Apache-2.0" ]

null

Ex017 - Catetos e Hipotenusa.py

MarcusMendes81/Python

4af6653da324604930d24542a84a530348029d39

[ "Apache-2.0" ]

null

Ex017 - Catetos e Hipotenusa.py

MarcusMendes81/Python

4af6653da324604930d24542a84a530348029d39

[ "Apache-2.0" ]

null

'''cat1 = int(input('Digite o valor do primeiro cateto: ')) cat2 = int(input('Digite o valor do segundo cateto: ')) hip = ((cat1 ** 2) + (cat2 ** 2))**(1/2) print('O valor da hipotenusa é: {:.2f} '.format(hip))''' from math import hypot co = int(input('Digite o valor do primeiro cateto:')) ca = int(input('Digite o valor do segundo cateto:')) hip = hypot(co, ca) print('O valor da hipotenusa é:', hip)

41.2

60

0.635922

67

412

3.910448

0.38806

0.137405

0.21374

0.229008

0.748092

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0.026549

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412

9

61

45.777778

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1

0

1

0

1

0

null

0

4

7aa64f9e6b0f3b48c9091946c0172bf03f6957d0

635

py

Python

django_thermostat/admin.py

jpardobl/django-thermostat

184e398134f289eb0337ec2af33c650f9ee26a13

[ "BSD-3-Clause" ]

null

django_thermostat/admin.py

jpardobl/django-thermostat

184e398134f289eb0337ec2af33c650f9ee26a13

[ "BSD-3-Clause" ]

null

django_thermostat/admin.py

jpardobl/django-thermostat

184e398134f289eb0337ec2af33c650f9ee26a13

[ "BSD-3-Clause" ]

null

from django.contrib import admin from models import * class ThermometerAdmin(admin.ModelAdmin): pass admin.site.register(Thermometer, ThermometerAdmin) class RuleAdmin(admin.ModelAdmin): pass admin.site.register(Rule, RuleAdmin) class ConditionalAdmin(admin.ModelAdmin): pass admin.site.register(Conditional, ConditionalAdmin) class DayAdmin(admin.ModelAdmin): pass admin.site.register(Day, DayAdmin) class TimeRangeAdmin(admin.ModelAdmin): pass admin.site.register(TimeRange, TimeRangeAdmin) class ThermometerDataAdmin(admin.ModelAdmin): pass admin.site.register(ThermometerData, ThermometerDataAdmin)

21.896552

58

0.801575

68

635

7.485294

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0.176817

0.223969

0.282908

0.424361

0

0.110236

635

28

59

22.678571

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0.3

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null

0

1

0

null

0

1

0

4

7aacbb554973828c71b01733b077936fea952b6e

935

py

Python

nas4candle/nasapi/__init__.py

scrlnas2019/nas4candle

318959424cc66819c816054a87bd1cb5d426e2e7

[ "BSD-3-Clause" ]

1

2021-01-22T04:03:00.000Z

nas4candle/nasapi/__init__.py

scrlnas2019/nas4candle

318959424cc66819c816054a87bd1cb5d426e2e7

[ "BSD-3-Clause" ]

1

2021-01-23T00:14:17.000Z

nas4candle/nasapi/__init__.py

scrlnas2019/nas4candle

318959424cc66819c816054a87bd1cb5d426e2e7

[ "BSD-3-Clause" ]

2

2019-11-27T04:42:00.000Z

2021-01-22T04:06:59.000Z

""" nas4candle.nasapi is a Python package which provides a common interface for the implementation and study of scalable hyperparameter and neural architecture search methods. In this package we provide to the user different modules: - ``benchmark``: a set of problems for hyperparameter or neural architecture search which the user can use to compare our different search algorithms or as examples to build their own problems. - ``evaluator``: a set of objects which help to run search on different systems and for different cases such as quick and light experiments or long and heavy runs. - ``search``: a set of algorithms for hyperparameter and neural architecture search. You will also find a modular way to define new search algorithms and specific sub modules for hyperparameter or neural architecture search. """ from nas4candle.nasapi.__version__ import __version__ name = 'nas4candle.nasapi' version = __version__

103.888889

229

0.79893

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935

5.404412

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935

9

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103.888889

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1

0

1

0

1

0

null

0

1

0

4

7abfbae47feb06ca012a74702e0b9b6405a037c8

206

py

Python

app/indexView.py

HenrikRyborg/flask-auth

e652d06b1ccc033b39511573ac0cc06d3e79882c

[ "MIT" ]

1

2021-03-01T10:02:44.000Z

app/indexView.py

HenrikRyborg/flask-auth

e652d06b1ccc033b39511573ac0cc06d3e79882c

[ "MIT" ]

null

app/indexView.py

HenrikRyborg/flask-auth

e652d06b1ccc033b39511573ac0cc06d3e79882c

[ "MIT" ]

null

from flask import render_template, Blueprint indexBP = Blueprint('indexBP', __name__) # indexView @indexBP.route('/', methods=['GET','POST']) def indexView(): return render_template('index.html')

22.888889

44

0.713592

23

206

6.130435

0.73913

0.198582

0

0.131068

206

9

45

22.888889

0.78771

0.043689

0

0.127551

0

1

0.2

false

0

0.2

0.6

0.4

1

0

null

0

1

0

null

0

1

0

4

8fab65035aa835cebe9b59323b637d4a07f3dcab

263

py

Python

gizmo/__init__.py

davebshow/gizmo

d1679da0ec12e72e0fb1b4dd3e7d9a60ddb6b34a

[ "MIT" ]

2

2015-04-15T20:20:50.000Z

2015-04-27T17:25:12.000Z

gizmo/__init__.py

davebshow/gizmo

d1679da0ec12e72e0fb1b4dd3e7d9a60ddb6b34a

[ "MIT" ]

null

gizmo/__init__.py

davebshow/gizmo

d1679da0ec12e72e0fb1b4dd3e7d9a60ddb6b34a

[ "MIT" ]

null

from .connection import ConnectionManager, aiohttp_factory, websockets_factory from .client import AsyncGremlinClient from .exceptions import RequestError, GremlinServerError, SocketClientError from .tasks import async, group, chain, chord __version__ = "0.1.12"

43.833333

78

0.840304

29

263

7.413793

0.758621

0

0.016878

0.098859

263

5

79

52.6

0.890295

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0.022814

0

null

0

0.8

null

0

1

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null

0

1

0

null

0

1

0

1

0

4

8fccfa9e6bf33b4e1a6a7344dc07da92a9b53fc2

82

py

Python

events/moderation/__init__.py

DangVietH/DangVietBot

e59092c57d990339d6a4f0cd412e5f243df2d6ed

[ "MIT" ]

2

2022-03-24T09:03:40.000Z

2022-03-25T18:31:42.000Z

events/moderation/__init__.py

DangVietH/DangVietBot

e59092c57d990339d6a4f0cd412e5f243df2d6ed

[ "MIT" ]

null

events/moderation/__init__.py

DangVietH/DangVietBot

e59092c57d990339d6a4f0cd412e5f243df2d6ed

[ "MIT" ]

null

from .log import ModLog async def setup(bot): await bot.add_cog(ModLog(bot))

16.4

34

0.719512

14

82

4.142857

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0.170732

82

5

34

16.4

0.852941

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0

true

0

0.333333

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0.333333

0

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null

0

1

0

null

0

1

0

1

0

4

8fd38b8dd9d252340d0aabfb1b4d87bf0813cafe

194

py

Python

models.py

Dingrongdeer/x-village-todo

0a82f32e14c2340af9986034381700e405b0f9f9

[ "MIT" ]

null

models.py

Dingrongdeer/x-village-todo

0a82f32e14c2340af9986034381700e405b0f9f9

[ "MIT" ]

null

models.py

Dingrongdeer/x-village-todo

0a82f32e14c2340af9986034381700e405b0f9f9

[ "MIT" ]

null

from app import db class Record(db.Model): id = db.Column(db.Integer, primary_key=True) name = db.Column(db.String(120), nullable=True) cost = db.Column(db.Integer, nullable=True)

24.25

51

0.695876

31

194

4.322581

0.580645

0.179104

0.223881

0.253731

0

0.018519

0.164948

194

7

52

27.714286

0.808642

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1

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0.2

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1

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null

0

1

0

1

0

null

0

1

0

4

8ffbbc36f3f396fce6ccb9602bbbd4d2cb8602c2

142

py

Python

AlgoExpert/array/isValidSubsequence/data.py

Muzque/Leetcode

d06365792c9ef48e0a290da00ba5e71f212554d5

[ "MIT" ]

1

2021-05-11T09:52:38.000Z

AlgoExpert/array/isValidSubsequence/data.py

Muzque/Leetcode

d06365792c9ef48e0a290da00ba5e71f212554d5

[ "MIT" ]

null

AlgoExpert/array/isValidSubsequence/data.py

Muzque/Leetcode

d06365792c9ef48e0a290da00ba5e71f212554d5

[ "MIT" ]

1

2021-05-05T04:13:17.000Z

samples = [ { "input": { "array": [5, 1, 22, 25, 6, -1, 8, 10], }, "output": [1, 6, -1, 10], }, ]

15.777778

50

0.274648

16

142

2.4375

0.6875

0.102564

0

0.213333

0.471831

142

8

51

17.75

0.306667

0

0.112676

0

1

0

false

0

1

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null

0

1

0

1

0

1

0

null

0

4

8912fe2a35bf42f22d7c8914fa4f1894e330542c

155

py

Python

polyReorder/scripts/polyReorder/tools.py

rusn07/polyReorder

13da436761d5650707daf7d2660d19a27af4d949

[ "MIT" ]

20

2017-04-21T11:57:40.000Z

2022-03-12T07:00:51.000Z

polyReorder/scripts/polyReorder/tools.py

kamilisa/polyReorder

13da436761d5650707daf7d2660d19a27af4d949

[ "MIT" ]

1

2019-12-16T08:49:40.000Z

2019-12-23T14:15:50.000Z

polyReorder/scripts/polyReorder/tools.py

kamilisa/polyReorder

13da436761d5650707daf7d2660d19a27af4d949

[ "MIT" ]

9

2017-04-18T18:28:26.000Z

2021-09-26T05:45:48.000Z

""" polyReorder Support script for polyReorder plugin. """ from maya import cmds def polyReorderTool(*args): cmds.setToolTo(cmds.polyReorderCtx())

15.5

41

0.741935

17

155

6.764706

0.823529

0

0.148387

155

10

41

15.5

0.871212

0.335484

0

1

0.333333

true

0

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1

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null

0

null

0

1

0

1

0

4

8919ef8fea7fd7bcf98aa3474e10fa0054399229

607

py

Python

tests/kyu_8_tests/test_sum_mixed_array.py

the-zebulan/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

40

2016-03-09T12:26:20.000Z

2022-03-23T08:44:51.000Z

tests/kyu_8_tests/test_sum_mixed_array.py

akalynych/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

null

tests/kyu_8_tests/test_sum_mixed_array.py

akalynych/CodeWars

1eafd1247d60955a5dfb63e4882e8ce86019f43a

[ "MIT" ]

36

2016-11-07T19:59:58.000Z

2022-03-31T11:18:27.000Z

import unittest from katas.kyu_8.sum_mixed_array import sum_mix class SumMixTestCase(unittest.TestCase): def test_equal_1(self): self.assertEqual(sum_mix([9, 3, '7', '3']), 22) def test_equal_2(self): self.assertEqual(sum_mix(['5', '0', 9, 3, 2, 1, '9', 6, 7]), 42) def test_equal_3(self): self.assertEqual(sum_mix(['3', 6, 6, 0, '5', 8, 5, '6', 2, '0']), 41) def test_equal_4(self): self.assertEqual(sum_mix(['1', '5', '8', 8, 9, 9, 2, '3']), 45) def test_equal_5(self): self.assertEqual(sum_mix([8, 0, 0, 8, 5, 7, 2, 3, 7, 8, 6, 7]), 61)

28.904762

77

0.574959

109

607

3.027523

0.293578

0.109091

0.181818

0.333333

0.378788

0

0.124473

0.21911

607

20

78

30.35

0.57173

0

0.021417

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0.384615

false

0

0.153846

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null

0

1

0

null

0

1

0

1

0

4

64e713e31288c7168c26200e6daa2055d03e6268

149

py

Python

deui/html/view/footer_element.py

urushiyama/DeUI

14530d2dae7d96a3dee30759f85e02239fb433c5

[ "MIT" ]

1

2021-10-17T01:54:18.000Z

deui/html/view/footer_element.py

urushiyama/DeUI

14530d2dae7d96a3dee30759f85e02239fb433c5

[ "MIT" ]

null

deui/html/view/footer_element.py

urushiyama/DeUI

14530d2dae7d96a3dee30759f85e02239fb433c5

[ "MIT" ]

null

from .element import Element class Footer(Element): """ Represents content footer. """ def __str__(self): return "footer"

13.545455

30

0.610738

15

149

5.8

0.733333

0

0.281879

149

10

31

14.9

0.813084

0.174497

0

0.056075

0

1

0.25

false

0

0.25

1

0

1

0

null

0

null

0

1

0

1

0

4

8f1178a64b796f6489e0144feddc7b10d494f607

258

py

Python

quake/client/base/plan.py

It4innovations/quake

a57f37e5c871e0c7c00b84aef638b925ef96690a

[ "MIT" ]

1

2021-03-26T14:23:44.000Z

quake/client/base/plan.py

It4innovations/quake

a57f37e5c871e0c7c00b84aef638b925ef96690a

[ "MIT" ]

null

quake/client/base/plan.py

It4innovations/quake

a57f37e5c871e0c7c00b84aef638b925ef96690a

[ "MIT" ]

null

class Plan: def __init__(self): self.tasks = [] def add_task(self, task): assert task.task_id is None self.tasks.append(task) def take_tasks(self): tasks = self.tasks self.tasks = [] return tasks

19.846154

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4.181818

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0

0.337209

258

12

36

21.5

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0

0.2

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0.1

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0.3

false

0

0.5

0

null

1

0

null

0

1

0

4

8f24965a1803dfe08e2c010f3f7432a7a795a728

218

py

Python

site/app/api_1_0/__init__.py

aijaz/qrCodeSigninServer

255289374f3e9ed0ce2a8bcb41281ff467eba902

[ "MIT" ]

2

2020-07-07T20:53:06.000Z

2020-07-26T22:00:27.000Z

site/app/api_1_0/__init__.py

aijaz/qrCodeSigninServer

255289374f3e9ed0ce2a8bcb41281ff467eba902

[ "MIT" ]

4

2021-04-30T21:22:23.000Z

2022-01-13T02:57:52.000Z

site/app/api_1_0/__init__.py

aijaz/qrCodeSigninServer

255289374f3e9ed0ce2a8bcb41281ff467eba902

[ "MIT" ]

null

from flask import Blueprint, g import psycopg2.extras api = Blueprint('api', __name__) def get_cursor(): return g.conn.cursor(cursor_factory=psycopg2.extras.RealDictCursor) from . import authentication, covid

18.166667

71

0.775229

28

218

5.821429

0.642857

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0.133028

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11

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1

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null

0

null

0

1

0

4

8f26f3271116dd21429a47d3b5c489f2df7de06a

369

py

Python

backend/tests/models/test_labeler.py

druzhynin-oleksii/model_garden

3599f5d0c81bc79139ceabed5dd647c29ccadc31

[ "MIT" ]

8

2020-09-10T18:28:19.000Z

2022-02-22T03:41:14.000Z

backend/tests/models/test_labeler.py

druzhynin-oleksii/model_garden

3599f5d0c81bc79139ceabed5dd647c29ccadc31

[ "MIT" ]

1

2020-09-15T21:20:29.000Z

backend/tests/models/test_labeler.py

druzhynin-oleksii/model_garden

3599f5d0c81bc79139ceabed5dd647c29ccadc31

[ "MIT" ]

8

2020-09-10T16:29:35.000Z

2022-01-25T15:05:03.000Z

from tests import BaseTestCase class TestLabeler(BaseTestCase): def test_create(self): labeler = self.test_factory.create_labeler(labeler_id=3) self.assertEqual(labeler.labeler_id, 3) def test_str(self): labeler = self.test_factory.create_labeler(labeler_id=3) self.assertEqual(str(labeler), "Labeler(labeler_id=3, username='test_labeler_3')")

26.357143

86

0.764228

51

369

5.294118

0.333333

0.259259

0.237037

0.251852

0.474074

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369

13

87

28.384615

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1

0

null

0

1

0

4

8f2f7ef6d5e7c1330d56e51fa54fe548064c6788

239

py

Python

PyInquirer/separator.py

kevindurston21/PyInquirer

48ecba84d62c6232a625d44e7f8cc6084f25b858

[ "MIT" ]

1,587

2018-06-14T03:05:42.000Z

2022-03-31T17:51:51.000Z

PyInquirer/separator.py

kevindurston21/PyInquirer

48ecba84d62c6232a625d44e7f8cc6084f25b858

[ "MIT" ]

131

2018-06-27T12:38:34.000Z

2022-03-09T16:26:27.000Z

PyInquirer/separator.py

kevindurston21/PyInquirer

48ecba84d62c6232a625d44e7f8cc6084f25b858

[ "MIT" ]

257

2018-07-03T13:47:08.000Z

2022-03-24T19:49:46.000Z

# -*- coding: utf-8 -*- """ Used to space/separate choices group """ class Separator: line = '-' * 15 def __init__(self, line=None): if line: self.line = line def __str__(self): return self.line

14.9375

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0.313808

239

15

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0.72561

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null

0

null

0

1

0

1

0

4

8f48ef7abe7245cfabea527642f841bb241003e5

90

py

Python

__init__.py

FelixTheC/electronic_memory

20f7d89983a8751894ea61caf5f643c8d387e4a2

[ "MIT" ]

null

__init__.py

FelixTheC/electronic_memory

20f7d89983a8751894ea61caf5f643c8d387e4a2

[ "MIT" ]

null

__init__.py

FelixTheC/electronic_memory

20f7d89983a8751894ea61caf5f643c8d387e4a2

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ @created: 11.01.21 @author: felix """

11.25

23

0.555556

13

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3.846154

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0.105263

0.155556

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7

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8f58e408ac4f709aa15d3bc6ca6f6868290b6766

919

py

Python

flexbe_core/src/flexbe_core/core/__init__.py

duwke/flexbe_behavior_engine

8e2ca45fbdb68818599944d2d155f9367b607c5c

[ "BSD-3-Clause" ]

119

2015-07-14T20:24:17.000Z

2022-03-09T02:07:50.000Z

flexbe_core/src/flexbe_core/core/__init__.py

duwke/flexbe_behavior_engine

8e2ca45fbdb68818599944d2d155f9367b607c5c

[ "BSD-3-Clause" ]

139

2015-11-05T15:11:00.000Z

2022-03-24T13:46:47.000Z

flexbe_core/src/flexbe_core/core/__init__.py

duwke/flexbe_behavior_engine

8e2ca45fbdb68818599944d2d155f9367b607c5c

[ "BSD-3-Clause" ]

68

2015-11-24T01:50:24.000Z

2022-03-30T10:13:28.000Z

from .preemptable_state_machine import PreemptableStateMachine # noqa: F401 from .operatable_state_machine import OperatableStateMachine # noqa: F401 from .lockable_state_machine import LockableStateMachine # noqa: F401 from .ros_state_machine import RosStateMachine # noqa: F401 from .state_machine import StateMachine # noqa: F401 from .concurrency_container import ConcurrencyContainer # noqa: F401 from .priority_container import PriorityContainer # noqa: F401 from .state import State # noqa: F401 from .ros_state import RosState # noqa: F401 from .manually_transitionable_state import ManuallyTransitionableState # noqa: F401 from .lockable_state import LockableState # noqa: F401 from .preemptable_state import PreemptableState # noqa: F401 from .operatable_state import OperatableState # noqa: F401 from .event_state import EventState # noqa: F401 from .user_data import UserData # noqa: F401

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1

0

4

8f67bb0d4edbe00c03299656c39bb0b60432dbd9

90

py

Python

Python_Basics/Lists_and_Strings/lists.py

samyumobi/A-Complete-Python-Guide-For-Beginners

6ee3d73ebb481dbb5788cb0e615efdaf09079a18

[ "MIT" ]

7

2019-06-04T13:44:27.000Z

2021-01-05T22:42:15.000Z

Python_Basics/Lists_and_Strings/lists.py

samyumobi/A-Complete-Python-Guide-For-Beginners

6ee3d73ebb481dbb5788cb0e615efdaf09079a18

[ "MIT" ]

null

Python_Basics/Lists_and_Strings/lists.py

samyumobi/A-Complete-Python-Guide-For-Beginners

6ee3d73ebb481dbb5788cb0e615efdaf09079a18

[ "MIT" ]

5

2019-09-14T11:37:47.000Z

2021-07-26T19:49:24.000Z

my_list = ["one", 2, "three"] print(my_list) print(type(my_list)) l = [] # an empty list

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8f7ba01a226f0d23dcdcf6f1f962ca6dc8e5bbca

259

py

Python

avilla/core/utilles/__init__.py

GraiaProject/Avilla

3642bc8ff6d6e53f96b16270571582c948caa73a

[ "MIT" ]

55

2021-08-29T13:28:30.000Z

2022-03-13T14:11:51.000Z

avilla/core/utilles/__init__.py

GraiaProject/Avilla

3642bc8ff6d6e53f96b16270571582c948caa73a

[ "MIT" ]

40

2021-09-03T13:21:50.000Z

2022-03-26T13:31:24.000Z

avilla/core/utilles/__init__.py

GraiaProject/Avilla

3642bc8ff6d6e53f96b16270571582c948caa73a

[ "MIT" ]

13

2021-09-04T15:26:56.000Z

2022-02-12T12:38:04.000Z

import random import string def random_string(k: int = 12): return "".join(random.choices(string.ascii_letters + string.digits, k=k)) def as_async(func): async def wrapper(*args, **kwargs): return func(*args, **kwargs) return wrapper

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56a988b97f0d4c8117bce034498b320d152c8573

66

py

Python

sneakers/channels/googleDocs.py

michalkoczwara/sneaky-creeper

b398af8701d51b8b3a4baf37cdaa16de3d3649d1

[ "MIT" ]

1

2018-01-25T01:49:05.000Z

sneakers/channels/googleDocs.py

michalkoczwara/sneaky-creeper

b398af8701d51b8b3a4baf37cdaa16de3d3649d1

[ "MIT" ]

null

sneakers/channels/googleDocs.py

michalkoczwara/sneaky-creeper

b398af8701d51b8b3a4baf37cdaa16de3d3649d1

[ "MIT" ]

null

# see: https://github.com/themson/MurDocK/blob/master/docBuffer.py

66

0.787879

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66

5.2

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0.030303

66

1

66

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0.969697

0

null

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null

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0

1

0

1

0

null

0

1

0

4

853950f342973bf6ba49138ab3ecebb7f2a056c1

471

py

Python

examples/blatt_02.py

mazenbesher/simplex

5cc3013f20f87891658fe64bf73c7c4cc2843240

[ "MIT" ]

null

examples/blatt_02.py

mazenbesher/simplex

5cc3013f20f87891658fe64bf73c7c4cc2843240

[ "MIT" ]

null

examples/blatt_02.py

mazenbesher/simplex

5cc3013f20f87891658fe64bf73c7c4cc2843240

[ "MIT" ]

null

import numpy as np from simplex.main import LP, simplex """1""" # aufgabe1 = LP( # np.matrix('2 0 6; -2 8 4; 3 6 5'), # np.matrix('10; 12; 20'), # np.matrix('2; 1; 3; 0; 0; 0'), # [4, 5, 6]) # print(simplex(aufgabe1, True)[1]) """2""" # def aufgabe2(a, b, c): # print(simplex(LP( # np.matrix('{} {} 1 0; -1 {} 0 1'.format(a, b, c)), # np.matrix('8; 4'), # np.matrix('1; 1; 0; 0'), # [3, 4]))) # # aufgabe2(-8, 0, 0)

21.409091

60

0.456476

81

471

2.654321

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0.093023

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0.138643

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21

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4

853a41bcaffda102fd47f7876038e46f5f77cc91

76

py

Python

imfp/core/model_helpers.py

akoskaaa/imfp

bb02cf259311352f8f33d1001f2f202345ee00c9

[ "MIT" ]

null

imfp/core/model_helpers.py

akoskaaa/imfp

bb02cf259311352f8f33d1001f2f202345ee00c9

[ "MIT" ]

null

imfp/core/model_helpers.py

akoskaaa/imfp

bb02cf259311352f8f33d1001f2f202345ee00c9

[ "MIT" ]

null

def get_or_none(model, id): return model.objects.filter(id=id).first()

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0

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null

0

1

0

null

0

1

0

1

0

4

85667e737fa24576cb6e3459b3def50f9b408313

86

py

Python

strings/Exercises/slicing.py

WebucatorTraining/classfiles-actionable-python

930c154a6dbfa6c54768557a998b4dbafb43df38

[ "MIT" ]

2

2022-01-04T22:25:01.000Z

2022-01-16T16:50:23.000Z

strings/Exercises/slicing.py

WebucatorTraining/classfiles-actionable-python

930c154a6dbfa6c54768557a998b4dbafb43df38

[ "MIT" ]

null

strings/Exercises/slicing.py

WebucatorTraining/classfiles-actionable-python

930c154a6dbfa6c54768557a998b4dbafb43df38

[ "MIT" ]

null

def main(): phrase = input("Choose a phrase: ") # Write your code here main()

17.2

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1

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0

1

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1

0

4

856a19971c1f323aa725f82a64def3f9d01ef730

2,258

py

Python

tests/grammpy_test/rule_tests/computing_tests/FromRuleComputeRulesTest.py

PatrikValkovic/grammpy

8308a1fd349bf9ea0d267360cc9a4ab20d1629e8

[ "MIT" ]

1

2021-02-04T12:41:08.000Z

tests/grammpy_test/rule_tests/computing_tests/FromRuleComputeRulesTest.py

PatrikValkovic/grammpy

8308a1fd349bf9ea0d267360cc9a4ab20d1629e8

[ "MIT" ]

3

2017-07-08T16:28:52.000Z

2020-04-23T18:06:24.000Z

tests/grammpy_test/rule_tests/computing_tests/FromRuleComputeRulesTest.py

PatrikValkovic/grammpy

8308a1fd349bf9ea0d267360cc9a4ab20d1629e8

[ "MIT" ]

1

2021-02-04T12:41:10.000Z

#!/usr/bin/env python """ :Author Patrik Valkovic :Created 02.08.2017 10:04 :Licence MIT Part of grammpy """ from unittest import main, TestCase from grammpy import Rule class Single(Rule): rule = ([0], [1]) class TwoRight(Rule): rule = ([0], [1, 2]) class ThreeLeft(Rule): rule = ([0, 1, 'a'], [2]) class Multiple(Rule): rule = ([0, 1, 2], [3, 4]) class FromRuleComputeRulesTest(TestCase): def test_rules_single(self): r = Single.rules self.assertIsInstance(r, list) self.assertEqual(len(r), 1) self.assertEqual(r[0], Single.rule) self.assertIsInstance(r[0], tuple) self.assertEqual(r[0][0], [0]) self.assertEqual(r[0][1], [1]) self.assertEqual(r[0][0][0], 0) self.assertEqual(r[0][1][0], 1) def test_rules_twoRight(self): r = TwoRight.rules self.assertIsInstance(r, list) self.assertEqual(len(r), 1) self.assertEqual(r[0], TwoRight.rule) self.assertIsInstance(r[0], tuple) self.assertEqual(r[0][0], [0]) self.assertEqual(r[0][1], [1, 2]) self.assertEqual(r[0][0][0], 0) self.assertEqual(r[0][1][0], 1) self.assertEqual(r[0][1][1], 2) def test_rules_threeLeft(self): r = ThreeLeft.rules self.assertIsInstance(r, list) self.assertEqual(len(r), 1) self.assertEqual(r[0], ThreeLeft.rule) self.assertIsInstance(r[0], tuple) self.assertEqual(r[0][0], [0, 1, 'a']) self.assertEqual(r[0][1], [2]) self.assertEqual(r[0][0][0], 0) self.assertEqual(r[0][0][1], 1) self.assertEqual(r[0][0][2], 'a') self.assertEqual(r[0][1][0], 2) def test_rules_multiple(self): r = Multiple.rules self.assertIsInstance(r, list) self.assertEqual(len(r), 1) self.assertEqual(r[0], Multiple.rule) self.assertIsInstance(r[0], tuple) self.assertEqual(r[0][0], [0, 1, 2]) self.assertEqual(r[0][1], [3, 4]) self.assertEqual(r[0][0][0], 0) self.assertEqual(r[0][0][1], 1) self.assertEqual(r[0][0][2], 2) self.assertEqual(r[0][1][0], 3) self.assertEqual(r[0][1][1], 4) if __name__ == '__main__': main()

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null

1

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null

0

1

0

4

857808fe45808e4184ed3399b41b3db2017e224f

162

py

Python

vizdoomaze/envs/vizdoomazethree6.py

fanyuzeng/Vizdoomaze

5b444f2d861c908c4d96ae374bcce660d364f22e

[ "MIT" ]

3

2020-09-25T16:00:49.000Z

2020-10-29T10:32:30.000Z

vizdoomaze/envs/vizdoomazethree6.py

fanyuzeng/Vizdoomaze

5b444f2d861c908c4d96ae374bcce660d364f22e

[ "MIT" ]

null

vizdoomaze/envs/vizdoomazethree6.py

fanyuzeng/Vizdoomaze

5b444f2d861c908c4d96ae374bcce660d364f22e

[ "MIT" ]

1

2021-12-17T07:50:47.000Z

from vizdoomaze.envs.vizdoomenv import VizdoomEnv class vizdoomazeThree6(VizdoomEnv): def __init__(self): super(vizdoomazeThree6, self).__init__(59)

27

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0

0.028777

0.141975

162

6

50

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0.81295

0

1

0.25

false

0

0.25

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null

0

1

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null

0

1

0

1

0

4

85c0614dbef5b628377280ca297cebaf7d202b13

285

py

Python

src/gitsweep/entrypoints.py

soehlert/git-sweep

2599b74c56bfcc6116e5ef983970cdc7f81b8350

[ "MIT" ]

1,746

2015-01-04T17:56:24.000Z

2022-03-29T22:34:09.000Z

src/gitsweep/entrypoints.py

soehlert/git-sweep

2599b74c56bfcc6116e5ef983970cdc7f81b8350

[ "MIT" ]

30

2015-01-03T14:36:08.000Z

2021-10-06T20:02:32.000Z

src/gitsweep/entrypoints.py

soehlert/git-sweep

2599b74c56bfcc6116e5ef983970cdc7f81b8350

[ "MIT" ]

117

2015-01-03T14:13:58.000Z

2022-02-18T08:49:08.000Z

def main(): """ Command-line interface. """ import sys from gitsweep.cli import CommandLine CommandLine(sys.argv).run() def test(): """ Run git-sweep's test suite. """ import nose import sys nose.main(argv=['nose'] + sys.argv[1:])

13.571429

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285

20

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null

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1

0

1

0

1

0

4

a42281bcdeb80900603d7537e2c88a3e04bbe921

151

py

Python

src/send_test.py

pankdm/icfpc-2020

6cac8e1b2dfaa65d80db90cb82bdb642738fb423

[ "MIT" ]

null

src/send_test.py

pankdm/icfpc-2020

6cac8e1b2dfaa65d80db90cb82bdb642738fb423

[ "MIT" ]

null

src/send_test.py

pankdm/icfpc-2020

6cac8e1b2dfaa65d80db90cb82bdb642738fb423

[ "MIT" ]

null

import unittest from .send import do_send class SendTest(unittest.TestCase): def test_0(self): self.assertEqual("1101000", do_send("0"))

18.875

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151

7

50

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0

0.4

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0.8

0

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null

0

1

0

null

0

1

0

1

0

4

a424caa01efd996e5163da2f7703756084dd4954

219

py

Python

DjangoAPI/models.py

qbdq/MLAPI_DJREST

eb8e716014fba0ef70f6c9d71f05557f268aefee

[ "MIT" ]

null

DjangoAPI/models.py

qbdq/MLAPI_DJREST

eb8e716014fba0ef70f6c9d71f05557f268aefee

[ "MIT" ]

null

DjangoAPI/models.py

qbdq/MLAPI_DJREST

eb8e716014fba0ef70f6c9d71f05557f268aefee

[ "MIT" ]

null

from django.db import models # Create your models here. class house(models.Model): Size = models.IntegerField() Bedrooms = models.IntegerField() def __str__(self): return self.Size , self.Bedrooms

21.9

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10

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1

0

null

1

0

null

0

1

0

4

a4361a6487b62b5b6c8706a2d07ae5a4867fc25c

141

py

Python

courses/context_processors.py

TareqMonwer/Enstructor

1eb32cf89e762233d3dfbc2a34ec1ad6e63ac2ef

[ "bzip2-1.0.6" ]

3

2020-07-13T14:02:55.000Z

2020-10-31T10:00:16.000Z

courses/context_processors.py

TareqMonwer/Enstructor

1eb32cf89e762233d3dfbc2a34ec1ad6e63ac2ef

[ "bzip2-1.0.6" ]

4

2020-06-06T04:27:09.000Z

2022-03-12T00:34:03.000Z

courses/context_processors.py

TareqMonwer/Enstructor

1eb32cf89e762233d3dfbc2a34ec1ad6e63ac2ef

[ "bzip2-1.0.6" ]

null

from .models import Subject def active_categories(request): return { 'all_categories': Subject.ordered_active_subjects() }

17.625

59

0.70922

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141

6.4

0.8

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141

7

60

20.142857

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1

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0

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0.6

0

1

0

null

0

1

0

null

0

1

0

4

a437a954f816373df2f4e353e5d5016e5ad90509

260

py

Python

scapy_funcs/scapyget_tcp.py

SecTraversl/Toolbox_Python_3.8

0ad1d92d3a12225ea60e4eef3f263aecfffd1b65

[ "MIT" ]

null

scapy_funcs/scapyget_tcp.py

SecTraversl/Toolbox_Python_3.8

0ad1d92d3a12225ea60e4eef3f263aecfffd1b65

[ "MIT" ]

null

scapy_funcs/scapyget_tcp.py

SecTraversl/Toolbox_Python_3.8

0ad1d92d3a12225ea60e4eef3f263aecfffd1b65

[ "MIT" ]

null

# %% ####################################### # THIS IS NOT THE SAME AS: my_pcap.getlayer(TCP) def scapyget_tcp(packet_list: scapy.plist.PacketList): result_list = [ pckt for pckt in packet_list if pckt.haslayer('TCP')] return PacketList(result_list)

32.5

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7

74

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0

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0

1

0

1

0

null

0

1

0

1

0

4

a450bfedc9467bc49637fe7829ee85ada78750da

59

py

Python

000test.py

qq453388937/TornadoManager_Git

2512312461be5b6347d6da8bb30fb66c99c5e953

[ "MIT" ]

null

000test.py

qq453388937/TornadoManager_Git

2512312461be5b6347d6da8bb30fb66c99c5e953

[ "MIT" ]

null

000test.py

qq453388937/TornadoManager_Git

2512312461be5b6347d6da8bb30fb66c99c5e953

[ "MIT" ]

null

# -*- coding:utf-8 -*- a = {"name":"pxd"} print(a["name"])

14.75

22

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9

59

3.111111

0.777778

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0.019608

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59

4

23

14.75

0.529412

0.338983

0

0.289474

0

1

0

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0

0.5

1

0

null

1

0

1

0

null

0

1

0

4

a45f0514f8fc0e0b21b254b7160b361bd3063340

225

py

Python

froide/foirequest/media_urls.py

rufuspollock/froide

8ef4dbdd54a74f8c986d59e90348dfdbd85c5da4

[ "MIT" ]

1

2015-10-25T22:51:28.000Z

froide/foirequest/media_urls.py

okfse/froide

5ed80cf6550fb4cbc757029b2c860b53e784eb93

[ "MIT" ]

null

froide/foirequest/media_urls.py

okfse/froide

5ed80cf6550fb4cbc757029b2c860b53e784eb93

[ "MIT" ]

null

from django.conf.urls import patterns urlpatterns = patterns("froide.foirequest.views", (r'^(?P<message_id>\d+)/(?P<attachment_name>.+)$', 'auth_message_attachment', {}, 'foirequest-auth_message_attachment'), )

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23,925

py

Python

equideepdmri/layers/layer_builders.py

philip-mueller/equivariant-deep-dmri

4391de51eacea045783742bfd2ca2f1e2f7e964e

[ "MIT" ]

13

2021-02-19T06:08:53.000Z

2022-02-21T10:30:05.000Z

equideepdmri/layers/layer_builders.py

philip-mueller/equivariant-deep-dmri

4391de51eacea045783742bfd2ca2f1e2f7e964e

[ "MIT" ]

3

2021-03-25T14:18:40.000Z

2021-11-05T12:32:57.000Z

equideepdmri/layers/layer_builders.py

philip-mueller/equivariant-deep-dmri

4391de51eacea045783742bfd2ca2f1e2f7e964e

[ "MIT" ]

5

2021-04-23T12:59:00.000Z

2021-12-26T21:09:37.000Z

from collections import OrderedDict from functools import partial from typing import Union, List import torch from torch import nn from e3nn.non_linearities.rescaled_act import sigmoid from e3nn.non_linearities.gated_block import GatedBlock from equideepdmri.layers.EquivariantPQLayer import EquivariantPQLayer from equideepdmri.layers.BatchNormalization import BatchNorm from equideepdmri.layers.QLengthWeightedPool import QLengthWeightedAvgPool from equideepdmri.utils.q_space import Q_SamplingSchema from equideepdmri.utils.spherical_tensor import SphericalTensorType from equideepdmri.layers.filter.utils import get_scalar_non_linearity def build_pq_layer(type_in: Union[SphericalTensorType, List[int]], type_out: Union[SphericalTensorType, List[int]], p_kernel_size: int, kernel: str, q_sampling_schema_in: Union[Q_SamplingSchema, torch.Tensor, List, None], q_sampling_schema_out: Union[Q_SamplingSchema, torch.Tensor, List, None], non_linearity_config=None, use_non_linearity=True, batch_norm_config=None, use_batch_norm=True, transposed=False, auto_recompute=True, **kernel_kwargs) -> nn.Module: """ Builds a pq-layer consisting of an EquivariantPQLayer followed by a nonlinearity (e.g. gated nonlinearity). :param type_in: The spherical tensor type of the input feature map. This defines how many channels of each tensor order the input feature map has. It can either be given as SphericalTensorType object or as List[int]] the element at index i of the list defines the number of order-i channels, e.g. the first element defines the number of order-0 (scalar) channels and the second the number of order-1 (vector) channels and so on. For all orders corresponding to out-of-range indices the number of channels is 0. :param type_out: The spherical tensor type of the output feature map (after non-linearity). This defines how many channels of each tensor order the output feature map has. It can either be given as SphericalTensorType object or as List[int]] the element at index i of the list defines the number of order-i channels, e.g. the first element defines the number of order-0 (scalar) channels and the second the number of order-1 (vector) channels and so on. For all orders corresponding to out-of-range indices the number of channels is 0. :param p_kernel_size: Size of the kernel in p-space. Note that the kernel always covers the whole q-space (as it is not translationally equivariant), so there is no q_kernel_size. :param kernel: Which filter basis to use in the EquivariantPQLayer layer. Valid options are: - "p_space": to use the p-space filter basis using only p-space coordinate offsets in the angular and radial part. - "q_space": to use the q-space filter basis using only q-space coordinate offsets in the angular part and q-space coordinates from input and output in the radial part. - "pq_diff": to use the pq-diff filter basis using difference between p- and q-space coordinate offsets in the angular part and p-space coordinate offsets, q-space coordinates from input and output in the radial part. - "pq_TP": to use the TP (tensor product) filter basis using the tensor product of the p- and q-space filters in the angular part and p-space coordinate offsets, q-space coordinates from input and output in the radial part. - "sum(<filters>)": where <filters> is a ";"-separated list (without spaces) of valid options for kernel_definition, e.g. "sum(pq_diff;p_space)" or "sum(pq_diff;q_space)". This uses the sum of the named basis filters. - "concat(<filters>)" where <filters> is a ";"-separated list (without spaces) of strings "<output_channels>:<filter_type>" where <output_channels> lists the channels of each order where the named filter is to be used (e.g. "[3, 4]" to use it for 3 scalar and 4 vector output channelw) and <filter_type> names a valid kernel_definition to use for these output channels. The number of all concatenated channels needs to math type_out. Example: "concat([3,4]:pq_diff,[5,2,1]:p_space)" which would require type_out = [8,6,1] :param q_sampling_schema_in: The q-sampling schema of input feature map. The q-sampling schema may either be given as a Q_SamplingSchema object, a Tensor of size (Q_in, 3) or a list of length Q_in (one element for each vector) of lists of size 3 of floats. Note that Q_in is not explicitly given but derived form the length of this parameter. If this is None (default) then the input does not have q-space but only p-space. :param q_sampling_schema_out: The q-sampling schema of output feature map. The q-sampling schema may either be given as a Q_SamplingSchema object, a Tensor of size (Q_out, 3) or a list of length Q_out (one element for each vector) of lists of size 3 of floats. Note that Q_out is not explicitly given but derived form the length of this parameter. If this is None (default) then the output does not have q-space but only p-space. :param non_linearity_config: Dict with the following optional keys: - tensor_non_lin: The nonlinearity to use for channels with l>0 (non-scalar channels). Default (and currently only option) is "gated". - scalar_non_lin: The nonlinearity to use for channles with l=0 (scalar channels). Valid options are "swish" and "relu". Default is "swish". :param use_non_linearity: Whether to use a nonlinearity. :param batch_norm_config: Dict with the following optional keys: - eps: avoid division by zero when we normalize by the variance - momentum: momentum of the running average - affine: do we have weight and bias parameters - reduce: method to contract over the spacial dimensions :param use_batch_norm: Whether to use a batch normalization :param transposed: Whether to perform a transposed convolution using the equivariant kernel :param auto_recompute: Whether to automatically recompute the kernel in each forward pass. By default it is recomputed each time. If this parameter is set to false, it is not recomputed and the method recompute() needs to be called explicitly after parameters of this nn.Module have been updated. :param kernel_selection_rule: Rule defining which angular filter orders (l_filter) to use for a paths form input orders l_in to output orders l_out. Defaults to using all possible filter orders, i.e. all l_filter with \|l_in - l_out\| <= l_filter <= l_in + l_out. Options are: - dict with key "lmax" and int value which additionally defines a maximum l_filter. - dict with int-pairs as keys and list of ints as values that defines for each pair of l_in and l_out the list of l_filter to use. E.g. {(0,0): [0], (1,1): [0,1], (0,1): [1]} :param p_radial_basis_type: The radial basis function type used for p-space. Valid options are "gaussian" (default), "cosine", "bessel". Note that this parameter is ignored if there is no basis filter using p-space. :param p_radial_basis_params: A (optional) dict of additional parameters for the radial basis function used for p-space. Valid keys in this dict are: - num_layers: Number of layers in the FC applied to the radial basis function. If num_layers = 0 (default) then no FC is applied to the radial basis function. - num_units: Number of units (neurons) in each of the layer in the FC applied to the radial basis function. No default, this parameter is required and must be >0 if num_layers > 0. - activation_function: activation function used in the FC applied to the radial basis function, valid are "relu" (default) or "swish" Note that this parameter is ignored if there is no basis filter using p-space. :param q_radial_basis_type: The radial basis function type used for q-space (q-in and q-out). Valid options are "gaussian" (default), "cosine", "bessel". Note that this parameter is ignored if there is no basis filter using q-space. :param q_out_radial_basis_type: The radial basis function type used for q-out (q-space of output feature map). See q_radial_basis_type but only for q-out. Defaults to q_radial_basis_type. :param q_in_radial_basis_type: The radial basis function type used for q-in (q-space of input feature map). See q_radial_basis_type but only for q-in. Defaults to q_radial_basis_type. :param q_radial_basis_params: A (optional) dict of additional parameters for the radial basis function used for q-space. Valid keys in this dict are: - num_layers: Number of layers in the FC applied to the radial basis function. If num_layers = 0 (default) then no FC is applied to the radial basis function. - num_units: Number of units (neurons) in each of the layer in the FC applied to the radial basis function. No default, this parameter is required and must be >0 if num_layers > 0. - activation_function: activation function used in the FC applied to the radial basis function, valid are "relu" (default) or "swish" Note that this parameter is ignored if there is no basis filter using q-space. :param q_out_radial_basis_params: A dict of additional parameters for the radial basis function used for q-out (q-space of output feature map). See q_radial_basis_params but only for q-out. Defaults to q_radial_basis_params. :param q_in_radial_basis_params: A dict of additional parameters for the radial basis function used for q-in (q-space of input feature map). See q_radial_basis_params but only for q-in. Defaults to q_radial_basis_params. :param sub_kernel_selection_rule: Rule defining for the TP filter which pairs of l_p and l_q to use for each l_filter. Defaults to "TP\pm 1". Options are: - dict with string keys: defines some constraints which combinations to use. The following constraint always holds: \|l_p - l_q\| <= l_filter <= l_p + l_q Additionally constraints can be defined by the following keys in the dict: - "l_diff_to_out_max": Maximum difference between l_p and l_filter as well as l_q and l_filter. Default to 1 (as in "TP\pm 1") - "l_max" (optional): Maximum value for l_p and l_q. - "l_in_diff_max" (optional): Maximum difference between l_p and l_q. - dict with ints as keys and list of int-pairs as values that defines for each l_filter the used pairs of l_p and l_q. E.g. {0: [(0, 0), (1, 1)], 1: [(0, 1), (1, 0), (1, 1)]} Note that this parameter is ignored if no TP-filter basis is used. For additional parameters see EquivariantPQLayer. """ type_in = SphericalTensorType.from_multiplicities_or_type(type_in) type_out = SphericalTensorType.from_multiplicities_or_type(type_out) if batch_norm_config is None: batch_norm_config = {} if non_linearity_config is None: non_linearity_config = {} if use_non_linearity: type_non_lin_in, non_linearity = build_non_linearity(type_out, **non_linearity_config) conv = EquivariantPQLayer(type_in, type_non_lin_in, kernel_definition=kernel, p_kernel_size=p_kernel_size, q_sampling_schema_in=q_sampling_schema_in, q_sampling_schema_out=q_sampling_schema_out, transposed=transposed, auto_recompute_kernel=auto_recompute, **kernel_kwargs) if use_batch_norm: batch_norm = BatchNorm(type_non_lin_in.Rs, **batch_norm_config) return nn.Sequential( OrderedDict([('conv', conv), ('batch_norm', batch_norm), ('non_linearity', non_linearity)])) else: return nn.Sequential(OrderedDict([('conv', conv), ('non_linearity', non_linearity)])) else: conv = EquivariantPQLayer(type_in, type_out, kernel_definition=kernel, p_kernel_size=p_kernel_size, q_sampling_schema_in=q_sampling_schema_in, q_sampling_schema_out=q_sampling_schema_out, transposed=transposed, auto_recompute_kernel=auto_recompute, **kernel_kwargs) if use_batch_norm: batch_norm = BatchNorm(type_out.Rs, **batch_norm_config) return nn.Sequential(OrderedDict([('conv', conv), ('batch_norm', batch_norm)])) else: return conv def build_p_layer(type_in: Union[SphericalTensorType, List[int]], type_out: Union[SphericalTensorType, List[int]], kernel_size: int, non_linearity_config=None, use_non_linearity=True, batch_norm_config=None, use_batch_norm=True, transposed=False, auto_recompute=True, **kernel_kwargs): """ Builds a p-layer consisting of an EquivariantPLayer followed by a nonlinearity (e.g. gated nonlinearity). :param type_in: The spherical tensor type of the input feature map. This defines how many channels of each tensor order the input feature map has. It can either be given as SphericalTensorType object or as List[int]] the element at index i of the list defines the number of order-i channels, e.g. the first element defines the number of order-0 (scalar) channels and the second the number of order-1 (vector) channels and so on. For all orders corresponding to out-of-range indices the number of channels is 0. :param type_out: The spherical tensor type of the output feature map (after non-linearity). This defines how many channels of each tensor order the output feature map has. It can either be given as SphericalTensorType object or as List[int]] the element at index i of the list defines the number of order-i channels, e.g. the first element defines the number of order-0 (scalar) channels and the second the number of order-1 (vector) channels and so on. For all orders corresponding to out-of-range indices the number of channels is 0. :param p_kernel_size: Size of the kernel in p-space. Note that the kernel always covers the whole q-space (as it is not translationally equivariant), so there is no q_kernel_size. :param non_linearity_config: Dict with the following optional keys: - tensor_non_lin: The nonlinearity to use for channels with l>0 (non-scalar channels). Default (and currently only option) is "gated". - scalar_non_lin: The nonlinearity to use for channles with l=0 (scalar channels). Valid options are "swish" and "relu". Default is "swish". :param use_non_linearity: Whether to use a nonlinearity. :param batch_norm_config: Dict with the following optional keys: - eps: avoid division by zero when we normalize by the variance - momentum: momentum of the running average - affine: do we have weight and bias parameters - reduce: method to contract over the spacial dimensions :param use_batch_norm: Whether to use a batch normalization :param transposed: Whether to perform a transposed convolution using the equivariant kernel :param auto_recompute: Whether to automatically recompute the kernel in each forward pass. By default it is recomputed each time. If this parameter is set to false, it is not recomputed and the method recompute() needs to be called explicitly after parameters of this nn.Module have been updated. :param kernel_selection_rule: Rule defining which angular filter orders (l_filter) to use for a paths form input orders l_in to output orders l_out. Defaults to using all possible filter orders, i.e. all l_filter with \|l_in - l_out\| <= l_filter <= l_in + l_out. Options are: - dict with key "lmax" and int value which additionally defines a maximum l_filter. - dict with int-pairs as keys and list of ints as values that defines for each pair of l_in and l_out the list of l_filter to use. E.g. {(0,0): [0], (1,1): [0,1], (0,1): [1]} :param p_radial_basis_type: The radial basis function type used for p-space. Valid options are "gaussian" (default), "cosine", "bessel". Note that this parameter is ignored if there is no basis filter using p-space. :param p_radial_basis_params: A (optional) dict of additional parameters for the radial basis function used for p-space. Valid keys in this dict are: - num_layers: Number of layers in the FC applied to the radial basis function. If num_layers = 0 (default) then no FC is applied to the radial basis function. - num_units: Number of units (neurons) in each of the layer in the FC applied to the radial basis function. No default, this parameter is required and must be >0 if num_layers > 0. - activation_function: activation function used in the FC applied to the radial basis function, valid are "relu" (default) or "swish" Note that this parameter is ignored if there is no basis filter using p-space. For additional parameters see EquivariantPLayer. """ return build_pq_layer(type_in, type_out, kernel_size, kernel='p_space', q_sampling_schema_in=None, q_sampling_schema_out=None, non_linearity_config=non_linearity_config, use_non_linearity=use_non_linearity, batch_norm_config=batch_norm_config, use_batch_norm=use_batch_norm, transposed=transposed, auto_recompute=auto_recompute, **kernel_kwargs) def build_q_reduction_layer(type_in: Union[SphericalTensorType, List[int]], q_sampling_schema_in: Q_SamplingSchema, reduction='length_weighted_average', auto_recompute=True, **kwargs): """ Builds a q-reduction layer to globally reduce q-space leaving only p-space. :param type_in: The spherical tensor type of the input feature map. This defines how many channels of each tensor order the input feature map has. It can either be given as SphericalTensorType object or as List[int]] the element at index i of the list defines the number of order-i channels, e.g. the first element defines the number of order-0 (scalar) channels and the second the number of order-1 (vector) channels and so on. For all orders corresponding to out-of-range indices the number of channels is 0. :param q_sampling_schema_in: The q-sampling schema of input feature map. The q-sampling schema may either be given as a Q_SamplingSchema object, a Tensor of size (Q_in, 3) or a list of length Q_in (one element for each vector) of lists of size 3 of floats. Note that Q_in is not explicitly given but derived form the length of this parameter. If this is None (default) then the input does not have q-space but only p-space. :param reduction: The type of reduction to use. Valid options are: - length_weighted_average: To use QLengthWeightedAvgPool (global length-weighted avg-pooling over q-space) For additional parameters in param kwargs see QLengthWeightedAvgPool. - mean: To use global avg-pooling over q-space. - conv: To use an EquivariantPQLayer (and gated nonlinearity) without output q-space. For additional parameters in param kwargs see build_pq_layer (except the params type_out, q_sampling_schema_out). :param auto_recompute: Whether to automatically recompute the kernels in each forward pass. :return (reduction_layer, type_out): - reduction_layer: The created q-reduction layer (nn.Module) - type_out: The spherical tensor type of the output feature map. """ type_in = SphericalTensorType.from_multiplicities_or_type(type_in) if reduction == 'length_weighted_average': return QLengthWeightedAvgPool(type_in, q_sampling_schema_in, auto_recompute=auto_recompute, **kwargs), type_in elif reduction == 'mean': return partial(torch.mean, dim=2), type_in elif reduction == 'conv': type_out = SphericalTensorType.from_multiplicities_or_type(kwargs.pop('type_out', type_in)) return build_pq_layer(type_in, type_out, q_sampling_schema_in=q_sampling_schema_in, q_sampling_schema_out=None, **kwargs), type_out else: raise ValueError(f'q-reduction "{reduction}" not supported.') def build_non_linearity(type_out: SphericalTensorType, tensor_non_lin='gated', scalar_non_lin='swish') -> ( SphericalTensorType, nn.Module): """ Builds a nonlinearity for spherical tensor feature maps. Currently only the gated nonlinearity is supported. :param type_out: The spherical tensor type of the output feature map (after non-linearity). This defines how many channels of each tensor order the output feature map has. It can either be given as SphericalTensorType object or as List[int]] the element at index i of the list defines the number of order-i channels, e.g. the first element defines the number of order-0 (scalar) channels and the second the number of order-1 (vector) channels and so on. For all orders corresponding to out-of-range indices the number of channels is 0. :param tensor_non_lin: The nonlinearity to use for channels with l>0 (non-scalar channels). Default (and currently only option) is "gated". :param scalar_non_lin: The nonlinearity to use for channles with l=0 (scalar channels). Valid options are "swish" and "relu". Default is "swish". :return (type_in, nonlinearity): - type_in: The expected spherical tensor type of the input feature map. - nonlinearity: the nonlinearity (as nn.Module) which accepts the input feature map. """ type_out = SphericalTensorType.from_multiplicities_or_type(type_out) if tensor_non_lin == 'gated': scalar_non_lin = get_scalar_non_linearity(scalar_non_lin) non_lin = GatedBlockNonLin(type_out.Rs, scalar_non_lin, sigmoid) return SphericalTensorType.from_Rs(non_lin.Rs_in), non_lin else: raise ValueError(f'Tensor Non-linearity "{tensor_non_lin}" not supported.') class GatedBlockNonLin(GatedBlock): def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) def forward(self, x): x = super(GatedBlockNonLin, self).forward(x, dim=1) return x

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a48aa9fe8f0221dbec4ecf446df70abcc9722dce

163

py

Python

vizdoommaze/envs/vizdoommazeone20.py

Brodong/vizdoommaze

1b7531f59f6eb5e94d22193d95febaf52ff6a874

[ "MIT" ]

null

vizdoommaze/envs/vizdoommazeone20.py

Brodong/vizdoommaze

1b7531f59f6eb5e94d22193d95febaf52ff6a874

[ "MIT" ]

null

vizdoommaze/envs/vizdoommazeone20.py

Brodong/vizdoommaze

1b7531f59f6eb5e94d22193d95febaf52ff6a874

[ "MIT" ]

1

2021-01-14T08:58:28.000Z

from vizdoommaze.envs.vizdoomenv import VizdoomEnv class VizdoomMazeOne20(VizdoomEnv): def __init__(self): super(VizdoomMazeOne20, self).__init__(33)

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a49d4b0e5ced335c5e40468014e18c6108f2d9e4

415

py

Python

tests/app/schema/allocation.py

abhan00/fastana

46f90832d8e24185619292f76cbd1b3ce73f2dae

[ "Apache-2.0" ]

1

2021-05-01T13:44:44.000Z

tests/app/schema/allocation.py

abhan00/fastana

46f90832d8e24185619292f76cbd1b3ce73f2dae

[ "Apache-2.0" ]

9

2021-04-17T03:22:56.000Z

2021-05-12T16:40:53.000Z

tests/app/schema/allocation.py

abhan00/fastana

46f90832d8e24185619292f76cbd1b3ce73f2dae

[ "Apache-2.0" ]

null

from datetime import datetime from typing import Optional from fastmsa.schema import BaseModel class BatchAddSchema(BaseModel): eta: Optional[datetime] ref: str sku: str qty: int class BatchDelete(BaseModel): eta: Optional[datetime] refs: list[str] sku: str qty: int class BatchAllocateSchema(BaseModel): eta: Optional[datetime] orderid: str sku: str qty: int

15.961538

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null

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4

f165f20daf8c2a9c1625ca9db17f8316e1d65a57

178

py

Python

config.py

josecahe/sd-midterm2

0c78e4c2b576ecc346e46e004617c455ff503680

[ "MIT" ]

null

config.py

josecahe/sd-midterm2

0c78e4c2b576ecc346e46e004617c455ff503680

[ "MIT" ]

null

config.py

josecahe/sd-midterm2

0c78e4c2b576ecc346e46e004617c455ff503680

[ "MIT" ]

null

from pymongo import MongoClient client = MongoClient("mongodb+srv://prueba:prueba123@cluster0-vba48.mongodb.net/test?retryWrites=true&w=majority") db = client.test DEBUG = True

29.666667

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1

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null

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4

f1791163c78209966040601a27272016205ccac3

53

py

Python

zoom/_assets/standard_apps/register/app.py

zodman/ZoomFoundry

87a69f519a2ab6b63aeec0a564ce41259e64f88d

[ "MIT" ]

8

2017-04-10T09:53:15.000Z

2020-08-16T09:53:14.000Z

zoom/_assets/standard_apps/register/app.py

zodman/ZoomFoundry

87a69f519a2ab6b63aeec0a564ce41259e64f88d

[ "MIT" ]

49

2017-04-13T22:51:48.000Z

2019-08-15T22:53:25.000Z

zoom/_assets/standard_apps/register/app.py

zodman/ZoomFoundry

87a69f519a2ab6b63aeec0a564ce41259e64f88d

[ "MIT" ]

12

2017-04-11T04:16:47.000Z

2019-08-10T21:41:54.000Z

""" basic app """ import zoom app = zoom.App()

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74c95efbfbb8ad8e3e41ded40fc76e86cf3528d3

219

py

Python

justredis/sync/environment.py

illuminatedwax/justredis

8e692d0983de5809964d4e4e361447c5fa400e88

[ "MIT" ]

45

2020-02-28T17:43:10.000Z

2022-03-08T09:20:34.000Z

justredis/sync/environment.py

illuminatedwax/justredis

8e692d0983de5809964d4e4e361447c5fa400e88

[ "MIT" ]

4

2020-02-29T00:05:04.000Z

2022-01-24T20:39:51.000Z

justredis/sync/environment.py

illuminatedwax/justredis

8e692d0983de5809964d4e4e361447c5fa400e88

[ "MIT" ]

4

2020-06-08T19:50:48.000Z

2022-02-23T16:33:09.000Z

from .environments.threaded import ThreadedEnvironment def get_environment(environment=ThreadedEnvironment, **kargs): if environment == "threaded": environment = ThreadedEnvironment return environment

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74dd0489b316374331edf6e3a3e46fe92af004a4

61

py

Python

atividade1.py

Laura32855/logicaprogramacao

a295b4a34b0dc866dd1801bca36400181db1092c

[ "MIT" ]

null

atividade1.py

Laura32855/logicaprogramacao

a295b4a34b0dc866dd1801bca36400181db1092c

[ "MIT" ]

null

atividade1.py

Laura32855/logicaprogramacao

a295b4a34b0dc866dd1801bca36400181db1092c

[ "MIT" ]

null

def atividade(): print( "Olá professor" ) atividade()

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null

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1

0

null

0

1

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4

74dffe7b0562f3dbafee43522b694c412630ad19

600

py

Python

Chapter-04/Character Picture Grid.py

Carkzis/Automate-the-Boring-Stuff

093106c787f9f2cf297f33d72d9cd73872c3d748

[ "BSD-3-Clause" ]

null

Chapter-04/Character Picture Grid.py

Carkzis/Automate-the-Boring-Stuff

093106c787f9f2cf297f33d72d9cd73872c3d748

[ "BSD-3-Clause" ]

null

Chapter-04/Character Picture Grid.py

Carkzis/Automate-the-Boring-Stuff

093106c787f9f2cf297f33d72d9cd73872c3d748

[ "BSD-3-Clause" ]

null

""" Character Picture Grid. Makes a heart. """ grid = [['.', '.', '.', '.', '.', '.'], ['.', 'O', 'O', '.', '.', '.'], ['O', 'O', 'O', 'O', '.', '.'], ['O', 'O', 'O', 'O', 'O', '.'], ['.', 'O', 'O', 'O', 'O', 'O'], ['O', 'O', 'O', 'O', 'O', '.'], ['O', 'O', 'O', 'O', '.', '.'], ['.', 'O', 'O', '.', '.', '.'], ['.', '.', '.', '.', '.', '.']] for y in range(6): for x in range(9): # Loop within loop to switch x and y. print(grid[x][y], end='') # Print the # or space. print() # Print a newline at the end of the row.

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600

19

61

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null

1

0

1

0

null

0

4

74ee146f7526b198ba84d68b77b4948be52f3ce2

659

gyp

Python

binding.gyp

godsflaw/node-opendkim

704e9b698ff7f216aa6871694cce5cd7175d2471

[ "MIT" ]

1

2017-11-12T20:40:57.000Z

binding.gyp

godsflaw/node-opendkim

704e9b698ff7f216aa6871694cce5cd7175d2471

[ "MIT" ]

36

2017-05-12T17:26:57.000Z

2018-11-05T17:04:16.000Z

binding.gyp

godsflaw/node-opendkim

704e9b698ff7f216aa6871694cce5cd7175d2471

[ "MIT" ]

5

2017-10-25T01:14:19.000Z

2018-10-12T10:07:09.000Z

{ "targets": [{ "target_name": "opendkim", "sources": [ "src/opendkim_body_async.cc", "src/opendkim_chunk_async.cc", "src/opendkim_chunk_end_async.cc", "src/opendkim_eoh_async.cc", "src/opendkim_eom_async.cc", "src/opendkim_flush_cache_async.cc", "src/opendkim_header_async.cc", "src/opendkim_sign_async.cc", "src/opendkim_verify_async.cc", "src/opendkim.cc", ], "include_dirs": [ "<!(node -e \"require('nan')\")" ], "libraries": [ "-lopendkim" ] }] }

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true

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null

1

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null

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4

74f18beff942059c5e8be0eb0dc1227f9a45d244

66

py

Python

proxySTAR_V3/certbot/venv.1509389747.bak/lib/python2.7/site-packages/pylint/test/input/func_import_syntax_error.py

mami-project/lurk

98c293251e9b1e9c9a4b02789486c5ddaf46ba3c

[ "Apache-2.0" ]

2

2017-07-05T09:57:33.000Z

2017-11-14T23:05:53.000Z

Libraries/Python/pylint/v1.4.4/pylint/test/input/func_import_syntax_error.py

davidbrownell/Common_Environment

4015872aeac8d5da30a6aa7940e1035a6aa6a75d

[ "BSL-1.0" ]

1

2019-01-17T14:26:22.000Z

2019-01-17T22:56:26.000Z

Libraries/Python/pylint/v1.4.4/pylint/test/input/func_import_syntax_error.py

davidbrownell/Common_Environment

4015872aeac8d5da30a6aa7940e1035a6aa6a75d

[ "BSL-1.0" ]

1

2017-08-31T14:33:03.000Z

# pylint: disable=no-absolute-import from . import syntax_error

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9

66

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0.136364

66

2

38

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0

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true

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null

0

1

0

1

0

4

74f9bc3ffd9a8a4f388f6f8f6a8233e86e4cf843

102

py

Python

app/email_delivery/apps.py

Younlab/Search-all-library-books-in-Ansan

d2050a455ca4d8acaf5e4d18a6e5cc4e99eaf85c

[ "MIT" ]

null

app/email_delivery/apps.py

Younlab/Search-all-library-books-in-Ansan

d2050a455ca4d8acaf5e4d18a6e5cc4e99eaf85c

[ "MIT" ]

null

app/email_delivery/apps.py

Younlab/Search-all-library-books-in-Ansan

d2050a455ca4d8acaf5e4d18a6e5cc4e99eaf85c

[ "MIT" ]

null

from django.apps import AppConfig class EmailDeliveryConfig(AppConfig): name = 'email_delivery'

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11

102

7.181818

0.909091

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0.147059

102

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38

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false

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0.333333

0

1

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null

0

1

0

null

0

1

0

1

0

4

2d00503ef20f9f86d2955031e531a4324ede2f50

341

py

Python

mysite/mobile/models.py

PUNITKUMARGAUTAM/mydjango

5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc

[ "MIT" ]

null

mysite/mobile/models.py

PUNITKUMARGAUTAM/mydjango

5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc

[ "MIT" ]

null

mysite/mobile/models.py

PUNITKUMARGAUTAM/mydjango

5dd86a99bc0fae0cad712412d2de9c0c6cee6dcc

[ "MIT" ]

null

from django.db import models # Create your models here. class MobileBrand(models.Model): mobilesplus = models.CharField(max_length = 300) mobilesrealme = models.CharField(max_length = 50) mobilesredmi = models.CharField(max_length = 50) mobilesapple = models.CharField(max_length = 50) class Meta: db_table = "Mobiles"

28.416667

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341

5.880952

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0.242915

0.291498

0.388664

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341

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1

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null

1

0

null

0

1

0

4

2d3ce5fb54a04454906060ab7c897b20d1daa49d

147

py

Python

dt_jax/test_with_cpu.py

yun-kwak/decision-transformer-jax

6b5cc8bd62a5d3f41c533b167b5d5f7e158f0df1

[ "MIT" ]

1

2022-02-12T11:51:12.000Z

dt_jax/test_with_cpu.py

yun-kwak/decision-transformer-jax

6b5cc8bd62a5d3f41c533b167b5d5f7e158f0df1

[ "MIT" ]

null

dt_jax/test_with_cpu.py

yun-kwak/decision-transformer-jax

6b5cc8bd62a5d3f41c533b167b5d5f7e158f0df1

[ "MIT" ]

null

import os os.environ["CUDA_VISIBLE_DEVICES"] = "-1" os.environ["JAX_PLATFORM_NAME"] = "cpu" os.environ["XLA_PYTHON_CLIENT_PREALLOCATE"] = "false"

24.5

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74224fd183ec77d5348bfd9efc83616155da1428

450

py

Python

tests/test_mixin_data.py

superzarzar/fixtures-mongoengine

da7f8ad73db498055b279d2e66ced0c81fe8a834

[ "MIT" ]

6

2017-05-04T14:14:13.000Z

2020-02-04T08:05:49.000Z

tests/test_mixin_data.py

superzarzar/fixtures-mongoengine

da7f8ad73db498055b279d2e66ced0c81fe8a834

[ "MIT" ]

8

2016-08-24T18:39:25.000Z

2020-02-03T13:37:45.000Z

tests/test_mixin_data.py

superzarzar/fixtures-mongoengine

da7f8ad73db498055b279d2e66ced0c81fe8a834

[ "MIT" ]

5

2017-08-23T23:58:20.000Z

2020-02-03T13:12:57.000Z

# -*- coding: utf-8 -*- from tests.test_case import MongoFixturesTestCase # class BaseMixinDataFixtureTestCase(MongoFixturesTestCase): # # def __init__(self, methodName='runTest'): # super(BaseMixinDataFixtureTestCase, self).__init__(methodName) # FixtureMixin.__init__(self) # # def setUp(self): # super(BaseMixinDataFixtureTestCase, self).setUp() # # self.unload_fixtures() # self.load_fixtures()

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true

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0

null

0

1

0

1

0

4

744e0589d958e920488ee77fa2e5547e25a9703a

122

py

Python

run.py

admariner/social-media-profiler

2001167201fc9602fef3070ee9d31f005978bfe8

[ "MIT" ]

34

2020-12-14T15:48:26.000Z

2022-02-27T14:24:29.000Z

run.py

pandrey2003/social-media-profiler

4160e318997d161d63b8233511a65669542da026

[ "MIT" ]

1

2021-12-15T02:37:32.000Z

run.py

admariner/social-media-profiler

2001167201fc9602fef3070ee9d31f005978bfe8

[ "MIT" ]

6

2021-02-11T16:29:04.000Z

2022-03-23T11:42:32.000Z

# -*- coding: utf-8 -*- """The run file of the project.""" from app.app import run if __name__ == '__main__': run()

15.25

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7

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true

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0

1

0

1

0

4

74571e7132346f3d854dde82b59e1f5d4d7c6437

19,733

py

Python

Blackjack.py

samalawadi/beginner-blackjack-python

c9503dbf58b839c93870eebc8d2049abf5214ee0

[ "MIT" ]

null

Blackjack.py

samalawadi/beginner-blackjack-python

c9503dbf58b839c93870eebc8d2049abf5214ee0

[ "MIT" ]

null

Blackjack.py

samalawadi/beginner-blackjack-python

c9503dbf58b839c93870eebc8d2049abf5214ee0

[ "MIT" ]

null

import random from turtle import * hideturtle() speed(0) def hit_stand_dd_cmd(x,y,card_num): global hit_stand_dd global deposit global round global double_down if double_down == True: hit_stand_dd = raw_input("What do you want to do? (hit, stand, double down): ") else: hit_stand_dd = raw_input("What do you want to do? (hit, stand): ") if hit_stand_dd == 'hit': double_down = False if card_num == player_five_num or card_num == player_six_num: begin_fill() color('white') card_outline(x,y) end_fill() color('black') player_card(x,y,card_num) else: player_card(x,y,card_num) elif hit_stand_dd == 'stand': dealer_ai() elif hit_stand_dd == 'double down': if double_down == True: if round > deposit: print "Insufficient funds" print 'Your balance: $' + str(deposit) hit_stand_dd_cmd(x,y,card_num) elif card_num == player_five_num or card_num == player_six_num: begin_fill() color('white') card_outline(x,y) end_fill() color('black') player_card(x,y,card_num) deposit = deposit - round round = round*2 dealer_ai() else: player_card(x,y,card_num) deposit = deposit - round round = round*2 dealer_ai() else: print 'invalid command' hit_stand_dd_cmd(x,y,card_num) else: print 'invalid command' hit_stand_dd_cmd(x,y,card_num) def card_outline(x,y): penup() setposition(x,y) pendown() for i in range (2): forward(75) left(90) forward(100) left(90) #empty first dealer card def card_empty(x,y): card_outline(x,y) left(53.13) forward(125) left(126.87) forward(75) left(126.87) forward(125) left(53.13) penup() #moves turtle out of the view def tclear(): penup() setposition(-200,-200) def clear_table(): color('white') begin_fill() for i in range(4): forward(400) left(90) end_fill() color('black') def two(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() for i in range(2): forward(10) right(90) for i in range(2): forward(10) left(90) forward(10) def three(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() for i in range(2): forward(10) right(90) forward(10) backward(10) left(90) forward(10) right(90) forward(10) right(180) def four(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() right(90) forward(10) left(90) forward(10) backward(5) left(90) forward(10) backward(20) right(90) def five(x,y): card_outline(x,y) penup() setposition(x+20,y+90) pendown() left(180) for i in range(2): forward(10) left(90) for i in range(2): forward(10) right(90) forward(10) right(180) def six(x,y): card_outline(x,y) penup() setposition(x+20,y+90) pendown() left(180) forward(10) left(90) forward(20) for i in range(3): left(90) forward(10) right(180) def seven(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() forward(10) right(90) forward(20) left(90) def eight(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() for i in range(6): forward(10) right(90) left(90) for i in range(3): forward(10) right(90) def nine(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() for i in range(5): forward(10) right(90) forward(20) left(90) def ten(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() right(90) forward(20) penup() setposition(x+15,y+90) pendown() left(180) for i in range(2): right(90) forward(10) right(90) forward(20) right(90) def jack(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() forward(15) backward(5) right(90) forward(20) right(90) forward(10) right(90) forward(10) right(90) def queen(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() for i in range(3): forward(10) right(90) forward(20) right(90) forward(5) left(90) backward(5) forward(5) for i in range(2): forward(5) left(90) right(90) def king(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() right(90) forward(20) backward(10) left(135) forward(14.14) backward(14.14) right(90) forward(14.14) backward(14.14) left(45) def ace(x,y): card_outline(x,y) penup() setposition(x+10,y+90) pendown() right(90) forward(20) backward(20) left(90) for i in range(5): forward(10) right(90) forward(20) left(90) def club(x,y): penup() setposition(x+32.5,y+30) pendown() begin_fill() forward(10) left(90) forward(10) right(135) for i in range(2): circle(7.5,320) right(255) circle(7.5,320) right(135) forward(5) end_fill() left(90) def diamond(x,y): penup() setposition(x+37.5,y+30) pendown() color("red") begin_fill() left(62.5) forward(20) left(55) forward(20) left(125) forward(20) end_fill() left(117.5) color("black") def heart(x,y): penup() setposition(x+37.5,y+30) pendown() color("red") begin_fill() left(45) forward(22.5) left(45) circle(7.5,180) left(180) circle(7.5,180) end_fill() left(90) color("black") def spade(x,y): penup() setposition(x+32.5,y+30) pendown() begin_fill() forward(10) left(90) forward(10) right(135) circle(5,180) forward(20) left(90) forward(20) circle(5,180) right(135) forward(10.15) left(90) forward(5) end_fill() suits = [club,diamond,heart,spade] cards_num = ("2","3","4","5","6","7","8","9","10","10","10","10","11") ten_card = [ten, jack, queen, king] #draws player card and adds to player total def player_card(x,y,card_num): global player_total if card_num == '2': two(x,y) player_total = player_total + 2 elif card_num == '3': three(x,y) player_total = player_total + 3 elif card_num == '4': four(x,y) player_total = player_total + 4 elif card_num == '5': five(x,y) player_total = player_total + 5 elif card_num == '6': six(x,y) player_total = player_total + 6 elif card_num == '7': seven(x,y) player_total = player_total + 7 elif card_num == '8': eight(x,y) player_total = player_total + 8 elif card_num == '9': nine(x,y) player_total = player_total + 9 elif card_num == '10': ten_card_rand(x,y) player_total = player_total + 10 elif card_num == '11': ace(x,y) player_total = player_total + 11 random.choice(suits)(x,y) def dealer_one_empty(): card_empty(-150,50) def dealer_one_clear(): for i in range(8): color("white") card_empty(-150,50) color("black") #draws dealer card and adds to dealer's total def dealer_card(x,y,card_num): global dealer_total if card_num == '2': two(x,y) dealer_total = dealer_total + 2 elif card_num == '3': three(x,y) dealer_total = dealer_total + 3 elif card_num == '4': four(x,y) dealer_total = dealer_total + 4 elif card_num == '5': five(x,y) dealer_total = dealer_total + 5 elif card_num == '6': six(x,y) dealer_total = dealer_total + 6 elif card_num == '7': seven(x,y) dealer_total = dealer_total + 7 elif card_num == '8': eight(x,y) dealer_total = dealer_total + 8 elif card_num == '9': nine(x,y) dealer_total = dealer_total + 9 elif card_num == '10': ten_card_rand(x,y) dealer_total = dealer_total + 10 elif card_num == '11': ace(x,y) dealer_total = dealer_total + 11 random.choice(suits)(x,y) deposit = float(raw_input('How much money do you want to deposit? ')) def dealer_check(): global deposit global dealer_total global player_total global dealer_soft tclear() print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) if dealer_total > 21: print 'You win' deposit = deposit + round*2 print 'Your balance: $' + str(deposit) elif player_total > 21: print "Bust! You lose" print 'Your balance: $' + str(deposit) elif dealer_total == player_total: print 'Its a draw!' deposit = deposit + round print 'Your balance: $' + str(deposit) elif dealer_total == 21: print 'You lose' print 'Your balance: $' + str(deposit) elif dealer_total < 21 and dealer_total > player_total: print 'You lose' print 'Your balance: $' + str(deposit) elif dealer_total < 21 and dealer_total < player_total: print 'You win' deposit = deposit + round*2 print 'Your balance: $' + str(deposit) def dealer_ai(): global deposit global dealer_total global player_total global dealer_soft dealer_one_clear() dealer_card(-150,50,dealer_one_num) if dealer_one_num == '11': dealer_soft = True if dealer_total >= 17: if dealer_soft == True and dealer_total > 21: dealer_total = dealer_total - 20 dealer_soft = False dealer_card(10,50,dealer_three_num) else: dealer_check() return else: dealer_card(10,50,dealer_three_num) if dealer_three_num == '11': dealer_soft = True if dealer_total >= 17: if dealer_total > 21 and dealer_soft == True: dealer_total = dealer_total - 10 dealer_soft = False if dealer_total <= 17: dealer_card(90,50,dealer_four_num) else: dealer_check() return else: dealer_card(90,50,dealer_four_num) if dealer_four_num == '11': dealer_soft = True if dealer_total >= 17: if dealer_total > 21 and dealer_soft == True: dealer_total = dealer_total - 10 dealer_soft = False if dealer_total <= 17: color('white') begin_fill() card_outline(-125,13) end_fill() color('black') dealer_card(-125,13,dealer_five_num) if dealer_five_num == '11': dealer_soft = True else: dealer_check() return else: color('white') begin_fill() card_outline(-125,13) end_fill() color('black') dealer_card(-125,13,dealer_five_num) if dealer_five_num == '11': dealer_soft = True if dealer_total >= 17: if dealer_total > 21 and dealer_soft == True: dealer_total = dealer_total - 10 dealer_soft = False if dealer_total <= 17: color('white') begin_fill() card_outline(-45,13) end_fill() color('black') dealer_card(-45,13,dealer_six_num) if dealer_six_num == '11': dealer_soft = True else: dealer_check() return else: color('white') begin_fill() card_outline(-45,13) end_fill() color('black') dealer_card(-45,13,dealer_six_num) if dealer_six_num == '11': dealer_soft = True if dealer_total >= 17: if dealer_total > 21 and dealer_soft == True: dealer_total = dealer_total - 10 dealer_soft = False dealer_check() return else: dealer_check() return while True: player_total = 0 dealer_total = 0 soft = False dealer_soft = False double_down = True ten_card_rand = random.choice(ten_card) player_one_num = random.choice(cards_num) player_two_num = random.choice(cards_num) player_three_num = random.choice(cards_num) player_four_num = random.choice(cards_num) player_five_num = random.choice(cards_num) player_six_num = random.choice(cards_num) dealer_one_num = random.choice(cards_num) dealer_two_num = random.choice(cards_num) dealer_three_num = random.choice(cards_num) dealer_four_num = random.choice(cards_num) dealer_five_num = random.choice(cards_num) dealer_six_num = random.choice(cards_num) if deposit == 0: print 'You are bankrupt. Please run the game again.' break round = float(raw_input('How much do you want to bet? ')) if round > deposit: print "Insufficient funds" print 'Your balance: $' + str(deposit) continue tclear() clear_table() deposit = deposit - round print 'Your balance: $' + str(deposit) #first two dealer cards (1 empty, 1 not) dealer_one_empty() dealer_card(-70,50,dealer_two_num) if dealer_two_num == '11': dealer_soft = True #first two player cards when game starts player_card(-150,-150,player_one_num) player_card(-70,-150,player_two_num) if player_one_num == '11' or player_two_num == '11': soft = True if soft == True and player_total > 21: player_total = player_total - 20 soft = False if dealer_soft == True: print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) + ' soft' else: print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) elif dealer_soft == True: print "Your Total: " + str(player_total) + ' soft,' + " Dealer's Total: " + str(dealer_total) + ' soft' else: print "Your Total: " + str(player_total) + ' soft,' + " Dealer's Total: " + str(dealer_total) elif dealer_soft == True: print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) + ' soft' else: print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) tclear() if player_total == 21: print "Blackjack, You Win!" deposit = deposit + round*1.5 print 'Your balance: $' + str(deposit) continue #card 3 player else: hit_stand_dd_cmd(10,-150,player_three_num) if hit_stand_dd == 'stand' or hit_stand_dd == 'double down': continue else: tclear() if player_three_num == '11': soft = True if soft == True and player_total > 21: player_total = player_total - 10 soft = False print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) elif soft == True and player_total < 21: print "Your Total: " + str(player_total) + ' soft,' + " Dealer's Total: " + str(dealer_total) else: print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) if player_total == 21: print "You win!" deposit = deposit + round*2 print 'Your balance: $' + str(deposit) continue elif player_total > 21: print "Bust! You lose" print 'Your balance: $' + str(deposit) continue else: hit_stand_dd_cmd(90,-150,player_four_num) if hit_stand_dd == 'stand': continue else: tclear() if player_four_num == '11': soft = True if soft == True and player_total > 21: player_total = player_total - 10 soft = False print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) elif soft == True and player_total < 21: print "Your Total: " + str(player_total) + ' soft,' + " Dealer's Total: " + str(dealer_total) else: print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) if player_total == 21: print "You win!" deposit = deposit + round*2 print 'Your balance: $' + str(deposit) continue elif player_total > 21: print "Bust! You lose" print 'Your balance: $' + str(deposit) continue else: hit_stand_dd_cmd(-125,-187,player_five_num) if hit_stand_dd == 'stand' or hit_stand_dd == 'double down': continue else: tclear() if player_five_num == '11': soft = True if soft == True and player_total > 21: player_total = player_total - 10 soft = False print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) elif soft == True and player_total < 21: print "Your Total: " + str(player_total) + ' soft,' + " Dealer's Total: " + str(dealer_total) else: print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) if player_total == 21: print "You win!" deposit = deposit + round*2 print 'Your balance: $' + str(deposit) continue elif player_total > 21: print "Bust! You lose" print 'Your balance: $' + str(deposit) continue else: hit_stand_dd_cmd(-45,-187,player_six_num) if hit_stand_dd == 'stand' or hit_stand_dd == 'double down': continue else: tclear() if player_six_num == '11': soft = True if soft == True and player_total > 21: player_total = player_total - 10 soft = False print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) elif soft == True and player_total < 21: print "Your Total: " + str(player_total) + ' soft,' + " Dealer's Total: " + str(dealer_total) else: print "Your Total: " + str(player_total) + " Dealer's Total: " + str(dealer_total) if player_total == 21: print "You win!" deposit = deposit + round*2 print 'Your balance: $' + str(deposit) continue elif player_total < 21: print "You win!" deposit = deposit + round*2 print 'Your balance: $' + str(deposit) continue elif player_total > 21: print "Bust! You lose" print 'Your balance: $' + str(deposit) continue print 'Gameover'

26.7023

116

0.543303

2,573

19,733

3.986397

0.066848

0.082578

0.014039

0.035195

0.814371

0.78132

0.680706

0.656332

0.626499

0.568587

0

0.057848

0.342979

19,733

738

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0.733282

0.011554

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0

1

0

1

0

null

0

1

0

4

745bdcbec58f959ab95b87adc2635a5c089650f4

5,238

py

Python

data/dataset_nocyclone.py

cfld/MultitaskAIS

d9b95b8f2f94e5f1fd241108a4f5d14b505de0db

[ "MIT" ]

62

2018-12-08T13:20:06.000Z

2022-03-30T11:04:31.000Z

data/dataset_nocyclone.py

cfld/MultitaskAIS

d9b95b8f2f94e5f1fd241108a4f5d14b505de0db

[ "MIT" ]

21

2019-03-07T11:24:54.000Z

2020-12-24T04:05:08.000Z

data/dataset_nocyclone.py

cfld/MultitaskAIS

d9b95b8f2f94e5f1fd241108a4f5d14b505de0db

[ "MIT" ]

35

2019-02-14T14:44:36.000Z

2022-02-27T14:32:21.000Z

#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Fri Apr 20 09:50:23 2018 @author: vnguye04 """ import numpy as np import matplotlib.pyplot as plt import pickle LAT, LON, SOG, COG, HEADING, ROT, NAV_STT, TIMESTAMP, MMSI = list(range(9)) ## Training set no cyclone ############################################################################### with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/dataset5/dataset5_train.pkl","rb") as f: Vs_train = pickle.load(f) Vs = Vs_train for key in list(Vs.keys()): tmp = Vs[key] plt.plot(tmp[:,1],tmp[:,0]) plt.xlim([0,1]) plt.ylim([0,1]) for key in list(Vs.keys()): tmp = Vs[key] lat_max = np.max(tmp[:,LAT]) lon_max = np.max(tmp[:,LON]) lat_min = np.min(tmp[:,LAT]) lon_min = np.min(tmp[:,LON]) if (lat_max < 0.24) and (lat_min > 0.155) and (lon_max<0.53) and (lon_min>0.485): Vs.pop(key,None) with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/dataset5/dataset5_train_nocyclone.pkl","wb") as f: pickle.dump(Vs,f) ## Test set moved cyclone ############################################################################### with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/MarineC_Jan2014_norm/MarineC_Jan2014_norm_train.pkl","rb") as f: Vs_test = pickle.load(f) Vs = Vs_test for key in list(Vs.keys()): tmp = Vs[key] lat_max = np.max(tmp[:,LAT]) lon_max = np.max(tmp[:,LON]) lat_min = np.min(tmp[:,LAT]) lon_min = np.min(tmp[:,LON]) if (lat_max < 0.24) and (lat_min > 0.155) and (lon_max<0.53) and (lon_min>0.485): print(("key: ", key, "mmsi: ", tmp[0,MMSI])) Vs[key][:,LON] += 3.8/10.5 Vs[key][:,LAT] += 0.5/3.5 else: Vs.pop(key,None) for key in list(Vs.keys()): tmp = Vs[key] plt.plot(tmp[:,1],tmp[:,0]) plt.xlim([0,1]) plt.ylim([0,1]) plt.show() with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/MarineC_Jan2014_norm/MarineC_Jan2014_norm_test_movedcyclones.pkl","wb") as f: pickle.dump(Vs,f) ## Test set only cyclone ############################################################################### with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/MarineC_Jan2014_norm/MarineC_Jan2014_norm_train.pkl","rb") as f: Vs_test = pickle.load(f) Vs = Vs_test for key in list(Vs.keys()): tmp = Vs[key] lat_max = np.max(tmp[:,LAT]) lon_max = np.max(tmp[:,LON]) lat_min = np.min(tmp[:,LAT]) lon_min = np.min(tmp[:,LON]) if (lat_max < 0.24) and (lat_min > 0.155) and (lon_max<0.53) and (lon_min>0.485): print(("key: ", key, "mmsi: ", tmp[0,MMSI])) else: Vs.pop(key,None) with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/MarineC_Jan2014_norm/MarineC_Jan2014_norm_test_onlycyclones.pkl","wb") as f: pickle.dump(Vs,f) # Step 10: Route Divergence ############################################################################### with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/MarineC_Jan2014_norm/MarineC_Jan2014_norm_train.pkl","rb") as f: Vs_train = pickle.load(f) with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/MarineC_Jan2014_norm/MarineC_Jan2014_norm_test.pkl","rb") as f: Vs_test = pickle.load(f) #for key in Vs.keys(): # tmp = Vs[key] # lat_begin = tmp[0,LAT] # lat_end = tmp[-1,LAT] # lon_begin = tmp[0,LON] # lon_end = tmp[-1,LON] # if (lat_begin < 0.38) and (lat_begin > 0.35) and (lon_begin <0.43) and (lon_begin >0.36): # print("key: ", key, "mmsi: ", tmp[0,MMSI]) # elif (lat_end < 0.38) and (lat_end > 0.35) and (lon_end <0.43) and (lon_end >0.36): # print("key: ", key, "mmsi: ", tmp[0,MMSI]) # else: # Vs.pop(key,None) #for key in Vs.keys(): # tmp = Vs[key] # print(tmp[0,MMSI], len(tmp)/2) # plt.figure() # plt.plot(tmp[:,1],tmp[:,0]) # plt.title(str(tmp[0,MMSI])) # plt.xlim([0,1]) # plt.ylim([0,1]) FIG_DPI = 150 plt.figure(figsize=(1920/FIG_DPI, 640/FIG_DPI), dpi=FIG_DPI) cmap = plt.cm.get_cmap('Blues') Vs = Vs_test d_i = 0 N = len(Vs) l_v_true = [] for key in list(Vs.keys()): tmp = Vs[key] c = cmap(float(d_i)/(N-1)) d_i+=1 lat_begin = tmp[0,LAT] lat_end = tmp[-1,LAT] lon_begin = tmp[0,LON] lon_end = tmp[-1,LON] if (lat_end < 0.38) and (lat_end > 0.35) and (lon_end <0.43) and (lon_end >0.36): if int(tmp[0,MMSI]) == 538200309: # if True: plt.plot(tmp[:,1],tmp[:,0],color='g',linewidth=2) v_true = np.copy(tmp) l_v_true.append(v_true) else: plt.plot(tmp[:,1],tmp[:,0],color=c,linewidth=0.3) plt.xlim([0,1]) plt.ylim([0,1]) Vs_divergence = dict() for e in range(-5,6): Vs_divergence[e] = np.copy(v_true) Vs_divergence[e][:,LAT] += e*0.01 # Vs_divergence[e][:,LON] += 0.5 # divergences 2 only for key in list(Vs_divergence.keys()): tmp = Vs_divergence[key] plt.plot(tmp[:,1],tmp[:,0],linewidth=0.8) plt.xlim([0,1]) plt.ylim([0,1]) plt.show() with open("/homes/vnguye04/Bureau/Sanssauvegarde/Datasets/MarineC/MarineC_Jan2014_norm/MarineC_Jan2014_norm_test_divergences.pkl","wb") as f: pickle.dump(Vs_divergence,f)

31.365269

143

0.590683

852

5,238

3.494131

0.161972

0.022842

0.084649

0.063487

0.750084

0.744038

0.71179

0.672489

0.644273

0

0.061478

0.170867

5,238

166

144

31.554217

0.623993

0.174112

0

0.61

0

0.251134

0.239547

0

1

0

false

0

0.03

0

0.03

0.02

0

null

0

1

0

1

0

null

0

4

746ca4f2b408cb97359d82dde3cfc18070cca29c

115

py

Python

detention_data_dashboard/__init__.py

detentiondatadashboard/detention-data-dashboard

445ce560a463a415fd78e9a7a96eeec4bad885c7

[ "MIT" ]

1

2021-12-16T02:02:36.000Z

detention_data_dashboard/__init__.py

detentiondatadashboard/detention-data-dashboard

445ce560a463a415fd78e9a7a96eeec4bad885c7

[ "MIT" ]

null

detention_data_dashboard/__init__.py

detentiondatadashboard/detention-data-dashboard

445ce560a463a415fd78e9a7a96eeec4bad885c7

[ "MIT" ]

null

""" importing all the functions from the app python script """ from .data_download import * from .figure import *

16.428571

54

0.73913

16

115

5.25

0.75

0

0.173913

115

6

55

19.166667

0.884211

0.469565

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

747ca7acf4499de7f3aabcfe1abe252911ceee6d

766

py

Python

main.py

LuisAlbuquerque/smart_gallery

46dcb15906c479b15dfdd364a81dc33735611e23

[ "MIT" ]

null

main.py

LuisAlbuquerque/smart_gallery

46dcb15906c479b15dfdd364a81dc33735611e23

[ "MIT" ]

null

main.py

LuisAlbuquerque/smart_gallery

46dcb15906c479b15dfdd364a81dc33735611e23

[ "MIT" ]

null

import os import shutil def find_people(name,gallery): if not os.path.exists(f'/label_photos/{ name }'): return None else: #photos = os.listdir(f'/label_photos/{ name }') photos_w_person = os.popen(f'face-recognition /label_photos/{ name } { gallery }').read() def add_photo2find(name,photo): # test if exist folder with NAME name else create if not os.path.exists(f'/label_photos/{ name }'): os.makedirs(f'/label_photos/{ name }') # mv photo to this folder photos = os.listdir(f'/label_photos/{ name }') shutil.move(photo,f'/label_photos/{ name }/{ name }[{ len(photos) }]{ photo.split(".")[-1] }') def all_photos(path): return os.listdir(f'/label_photos/{ name }') def main(): pass main()

29.461538

98

0.63577

110

766

4.309091

0.4

0.185654

0.253165

0.236287

0.322785

0.270042

0.139241

0

0.003263

0.199739

766

25

99

30.64

0.769984

0.154047

0

0.117647

0

0.36124

0

1

0.235294

false

0.058824

0.117647

0.058824

0.470588

0

null

0

1

0

null

0

1

0

1

0

4

778cc4275fb56d8c322c352e55edea2a57d981aa

135

py

Python

desafios/desafio 006.py

juaoantonio/curso_video_python

7520223d8647929530a1cd96f7c7d8c8f264ba1e

[ "MIT" ]

null

desafios/desafio 006.py

juaoantonio/curso_video_python

7520223d8647929530a1cd96f7c7d8c8f264ba1e

[ "MIT" ]

null

desafios/desafio 006.py

juaoantonio/curso_video_python

7520223d8647929530a1cd96f7c7d8c8f264ba1e

[ "MIT" ]

null

n = int(input('Digite um número inteiro: ')) print(f'O dobro de {n} é {n*2}, o seu triplo é {n*3}, sua raiz quadrada é {n**(1/2):.1f}')

67.5

90

0.607407

30

135

2.733333

0.733333

0.073171

0

0.044248

0.162963

135

2

90

67.5

0.681416

0

0.5

0.779412

0

1

0

false

0

0.5

0

null

0

1

0

1

0

null

0

1

0

4

77d01a9c16dca1699b702fe2c54c114cf8921c43

102

py

Python

grading_system/apps.py

joshuariveramnltech/projectIE

9f707f6f1a30ca728580ba738877c77785155ae5

[ "MIT" ]

null

grading_system/apps.py

joshuariveramnltech/projectIE

9f707f6f1a30ca728580ba738877c77785155ae5

[ "MIT" ]

5

2021-02-08T20:32:43.000Z

2021-09-08T01:13:03.000Z

grading_system/apps.py

joshuariveramnltech/projectIE

9f707f6f1a30ca728580ba738877c77785155ae5

[ "MIT" ]

null

from django.apps import AppConfig class GradingSystemConfig(AppConfig): name = 'grading_system'

17

37

0.784314

11

102

7.181818

0.909091

0

0.147059

102

5

38

20.4

0.908046

0

0.137255

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

77d1c2b0f66e2f75e113aef918eec9c976156c58

51

py

Python

extra/dynamic/integer_partition.py

lsbardel/mathfun

98e7c210409c2b5777e91059c3651cef4f3045dd

[ "BSD-3-Clause" ]

null

extra/dynamic/integer_partition.py

lsbardel/mathfun

98e7c210409c2b5777e91059c3651cef4f3045dd

[ "BSD-3-Clause" ]

null

extra/dynamic/integer_partition.py

lsbardel/mathfun

98e7c210409c2b5777e91059c3651cef4f3045dd

[ "BSD-3-Clause" ]

null

def integert_partition(S: Sequence[int]): pass

17

41

0.72549

7

51

5.142857

1

0

0.156863

51

2

42

25.5

0.837209

0

1

0.5

false

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

4

77d70bde701d743048a08e51ae1350712adbdfa7

355

py

Python

iotd/index/admin.py

boilerplate-limdongjin/boilerplate_drf_elasticbeanstalk

21acc7c5ba031caef35002f9655b4f829de7e319

[ "MIT" ]

2

2018-03-14T08:13:12.000Z

2018-03-14T08:17:54.000Z

iotd/index/admin.py

boilerplate-limdongjin/boilerplate_drf_elasticbeanstalk

21acc7c5ba031caef35002f9655b4f829de7e319

[ "MIT" ]

null

iotd/index/admin.py

boilerplate-limdongjin/boilerplate_drf_elasticbeanstalk

21acc7c5ba031caef35002f9655b4f829de7e319

[ "MIT" ]

null

from django.contrib import admin import index.models as models # Register your models here. admin.site.register(models.Bills) admin.site.register(models.Newkeywords) admin.site.register(models.People) admin.site.register(models.Analyses) admin.site.register(models.Attends) admin.site.register(models.Post) admin.site.register(models.Simdata)

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77ec8126c3fb9597356b15f72698c6193987d100

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py

Python

data_preprocessing/uav123_annotation_to_video_converter.py

Hoclor/CoSADUV-Contextual-Saliency-for-Detecting-Anomalies-in-UAV-Video

674b72af15ba8833317b8daa9d1e614ea63151c1

[ "MIT" ]

4

2019-07-01T14:55:33.000Z

2021-01-18T02:34:38.000Z

data_preprocessing/uav123_annotation_to_video_converter.py

Hoclor/CoSADUV-Contextual-Saliency-for-Detecting-Anomalies-in-UAV-Video

674b72af15ba8833317b8daa9d1e614ea63151c1

[ "MIT" ]

null

data_preprocessing/uav123_annotation_to_video_converter.py

Hoclor/CoSADUV-Contextual-Saliency-for-Detecting-Anomalies-in-UAV-Video

674b72af15ba8833317b8daa9d1e614ea63151c1

[ "MIT" ]

null

"""A tool to convert annotations for UAV123 datset into Ground-Truth or Bounding-Box images. Based off the same code as `cvat_annotation_converter.py' (https://gist.github.com/cheind/9850e35bb08cfe12500942fb8b55531f). Created for use with NVVL, which was subsequently abandoned. Included for archival purposes (not used). """ import os import random import time import numpy as np from tqdm import tqdm import cv2 def draw_annotations( dataset_folder, sequence_name, target_folder=None, display=False, settings={} ): tqdm.write(sequence_name) # Get the sequnce folder and annotations folder sequence_folder = os.path.join(dataset_folder, "data_seq", "UAV123", sequence_name) annotation_file = os.path.join( dataset_folder, "anno", "UAV123", sequence_name + ".txt" ) # Get the default target folder if none is given if target_folder == None: target_folder = os.path.join( dataset_folder, "ground_truth", "UAV123", sequence_name ) # Check if the target_folder exists if not os.path.exists(target_folder): # Create the target_folder os.makedirs(target_folder) # Get a list of frames in sequence_folder if os.name == "posix": # Unix frames = os.listdir(sequence_folder) else: # Windows (os.name == 'nt') with os.scandir(sequence_folder) as file_iterator: frames = [file_object.name for file_object in list(file_iterator)] # Extract the annotations from the annotation_file try: with open(annotation_file, "r") as f: annotations = f.readlines() except FileNotFoundError: # Skip this sequence as it doesn't have a single annotation file # (simplifies processing, but loses out on some data) return 0 # Convert each line from a string to a list with 4 numbers def process_line(line): ret = line.strip().split(",") ret = list(map(lambda n: int(n) if n != "NaN" else -1, ret)) return ret annotations = list(map(process_line, annotations)) # Define the codec and create VideoWriter object fourcc = cv2.VideoWriter_fourcc(*"DIVX") framerate = 30 (width, height) = (1280, 720) out = cv2.VideoWriter( os.path.join(target_folder, sequence_name + ".avi"), fourcc, framerate, (width, height), 1, ) last_time = time.time() for frame_count, annotation in enumerate(tqdm(annotations)): # Get the corresponding frame name frame_name = frames[frame_count] # Read this frame frame = cv2.imread(os.path.join(sequence_folder, frame_name)) # Only draw an annotiation if it exists - i.e. annotation is not -1 if all(a != -1 for a in annotation): # Draw the rectangle as a red bounding box x_tl = annotation[0] y_tl = annotation[1] x_br = x_tl + annotation[2] y_br = y_tl + annotation[3] cv2.rectangle(frame, (x_tl, y_tl), (x_br, y_br), [0, 0, 255], 2, -1) # Write the frame with boxes out.write(frame) # Also save the frame individually cv2.imwrite(os.path.join(target_folder, frame_name[:-4] + ".png"), frame) # Display the resulting frame if display: # Force the function to run at the framerate of the video while time.time() - last_time < ((1 / framerate) / 1.025): # Enforce time passed as slightly less than 1/framerate, # as displaying the output takes some time as well pass last_time = time.time() cv2.imshow("frame", frame) if cv2.waitKey(1) & 0xFF == ord("q"): break # Release everything out.release() cv2.destroyAllWindows() def draw_groundtruth( dataset_folder, sequence_name, target_folder=None, display=False, settings={} ): tqdm.write(sequence_name) # Get the sequnce folder and annotations folder sequence_folder = os.path.join(dataset_folder, "data_seq", "UAV123", sequence_name) annotation_file = os.path.join( dataset_folder, "anno", "UAV123", sequence_name + ".txt" ) # Get the default target folder if none is given if target_folder == None: target_folder = os.path.join( dataset_folder, "ground_truth", "UAV123", sequence_name ) # Check if the target_folder exists if not os.path.exists(target_folder): # Create the target_folder os.makedirs(target_folder) # Get a list of frames in sequence_folder if os.name == "posix": # Unix frames = os.listdir(sequence_folder) else: # Windows (os.name == 'nt') with os.scandir(sequence_folder) as file_iterator: frames = [file_object.name for file_object in list(file_iterator)] # Extract the annotations from the annotation_file try: with open(annotation_file, "r") as f: annotations = f.readlines() except FileNotFoundError: # Skip this sequence as it doesn't have a single annotation file # (simplifies processing, but loses out on some data) return 0 # Convert each line from a string to a list with 4 numbers def process_line(line): ret = line.strip().split(",") ret = list(map(lambda n: int(n) if n != "NaN" else -1, ret)) return ret annotations = list(map(process_line, annotations)) # Define the codec and create VideoWriter object fourcc = cv2.VideoWriter_fourcc(*"DIVX") framerate = 30 (width, height) = (1280, 720) out = cv2.VideoWriter( os.path.join(target_folder, sequence_name + ".avi"), fourcc, framerate, (width, height), 0, ) blank_frame = np.zeros((height, width), dtype=np.uint8) last_time = time.time() for frame_count, annotation in enumerate(tqdm(annotations)): # Copy a new blank frame frame = np.copy(blank_frame) # Get the corresponding frame name frame_name = frames[frame_count] # Only draw an annotiation if it exists - i.e. annotation is not -1 if all(a != -1 for a in annotation): # Draw the rectangle as a filled in white box x_tl = annotation[0] y_tl = annotation[1] x_br = x_tl + annotation[2] y_br = y_tl + annotation[3] cv2.rectangle(frame, (x_tl, y_tl), (x_br, y_br), 255, cv2.FILLED) # Write the frame with boxes out.write(frame) # Also save the frame individually cv2.imwrite(os.path.join(target_folder, frame_name[:-4] + ".png"), frame) # Display the resulting frame if display: # Force the function to run at the framerate of the video while time.time() - last_time < ((1 / framerate) / 1.025): # Enforce time passed as slightly less than 1/framerate, # as displaying the output takes some time as well pass last_time = time.time() cv2.imshow("frame", frame) if cv2.waitKey(1) & 0xFF == ord("q"): break # Release everything out.release() cv2.destroyAllWindows() def prepare_for_nvvl( dataset_folder, sequence_name, target_folder=None, display=False, settings={} ): """ Creates a video of the original sequence, and a separate video of the ground truth data, stored in target_folder and target_folder/targets respectively. """ # Read in optional settings try: random_start = settings["random_start"] except KeyError: # random_start not given, use default value random_start = False try: duration = settings["duration"] except KeyError: # random_start not given, use default value duration = -1 # Get the sequnce folder and annotations folder sequence_folder = os.path.join(dataset_folder, "data_seq", "UAV123", sequence_name) annotation_file = os.path.join( dataset_folder, "anno", "UAV123", sequence_name + ".txt" ) # Get the default target folder if none is given if target_folder == None: target_folder = os.path.join( dataset_folder, "ground_truth", "UAV123", sequence_name ) # Check if the target_folder exists if not os.path.exists(target_folder): # Create the target_folder os.makedirs(target_folder) # Get a list of frames in sequence_folder if os.name == "posix": # Unix frames = os.listdir(sequence_folder) else: # Windows (os.name == 'nt') with os.scandir(sequence_folder) as file_iterator: frames = [file_object.name for file_object in list(file_iterator)] # Extract the annotations from the annotation_file try: with open(annotation_file, "r") as f: annotations = f.readlines() except FileNotFoundError: # Skip this sequence as it doesn't have a single annotation file # (simplifies processing, but loses out on some data) return 0 # If random_start is True, randomly generate a starting frame # (that is at least 'duration' frames before the end of the video) if random_start: try: start_time = random.randrange(0, len(annotations) - duration) except ValueError: # The sequence is too short for the requested duration, so skip it return else: start_time = 0 # Print out the sequence name, start frame, end frame tqdm.write(sequence_name + " " + str(start_time) + "-" + str(start_time + duration)) # Convert each line from a string to a list with 4 numbers def process_line(line): ret = line.strip().split(",") ret = list(map(lambda n: int(n) if n != "NaN" else -1, ret)) return ret annotations = list(map(process_line, annotations)) # Define the codec and create VideoWriter objects fourcc = cv2.VideoWriter_fourcc(*"DIVX") framerate = 30 (width, height) = (1280, 720) out_data = cv2.VideoWriter( os.path.join(target_folder, sequence_name + ".avi"), fourcc, framerate, (width, height), 1, ) out_target = cv2.VideoWriter( os.path.join(target_folder, "targets", sequence_name + ".avi"), fourcc, framerate, (width, height), 0, ) blank_frame = np.zeros((height, width), dtype=np.uint8) last_time = time.time() for frame_count, annotation in enumerate( tqdm(annotations[start_time : start_time + duration]) ): # Copy a new blank frame frame = np.copy(blank_frame) # Get the corresponding frame name frame_name = frames[frame_count] # Read the input data frame input_frame = cv2.imread(os.path.join(sequence_folder, frame_name)) # Only draw an annotiation if it exists - i.e. annotation is not -1 if all(a != -1 for a in annotation): # Draw the rectangle as a filled in white box x_tl = annotation[0] y_tl = annotation[1] x_br = x_tl + annotation[2] y_br = y_tl + annotation[3] cv2.rectangle(frame, (x_tl, y_tl), (x_br, y_br), 255, cv2.FILLED) # Write the frame with boxes out_target.write(frame) # Write the original input frame out_data.write(input_frame) # Display the resulting frame if display: # Force the function to run at the framerate of the video while time.time() - last_time < ((1 / framerate) / 1.025): # Enforce time passed as slightly less than 1/framerate, # as displaying the output takes some time as well pass last_time = time.time() cv2.imshow("input frame", input_frame) if cv2.waitKey(1) & 0xFF == ord("q"): break # Release everything out_target.release() out_data.release() cv2.destroyAllWindows() if __name__ == "__main__": import argparse parser = argparse.ArgumentParser( description="Draw annotations, either on original videos or as ground-truth saliency maps" ) parser.add_argument( "--dataset", "-d", dest="dataset", help="Folder containing the UAV123 dataset", required=False, default="C:\\Users\\simon\\Downloads\\Project Datasets\\UAV123\\UAV123", ) parser.add_argument( "--sequence", "-s", dest="name", help="Name of sequence to be processed", required=False, ) parser.add_argument( "--target", "-t", dest="target_folder", help="Name of folder to write results to", required=False, ) parser.add_argument( "--function", "-f", dest="drawing_function", help="Function to use: 'bounding_boxes', 'groundtruth', or 'nvvl'", required=True, ) parser.add_argument("--verbose", "-v", dest="verbose", action="store_true") args = parser.parse_args() if args.drawing_function == "bounding_boxes": drawing_function = draw_annotations elif args.drawing_function == "groundtruth": drawing_function = draw_groundtruth elif args.drawing_function == "nvvl": drawing_function = prepare_for_nvvl try: duration = int(input("Duration (in frames at 30fps, -1 for full video): ")) except ValueError: duration = -1 # int not given, use -1 (default value) rand_start = input("Choose a random starting frame? (y/n): ").lower() rand_start = True if rand_start in "yes" and rand_start != "" else False settings = {"random_start": rand_start, "duration": duration} if args.name == None: # Read all files in the folder and call the appropriate function on each # video/annotation pair found. # Get a list of frames in sequence_folder if os.name == "posix": # Unix sequences = os.listdir(os.path.join(args.dataset, "data_seq", "UAV123")) else: # Windows (os.name == 'nt') with os.scandir( os.path.join(args.dataset, "data_seq", "UAV123") ) as folder_iterator: sequences = [ folder_object.name for folder_object in list(folder_iterator) ] # Call the drawing function with each sequence name in sequences for seq_name in tqdm(sequences): drawing_function( args.dataset, seq_name, target_folder=args.target_folder, display=args.verbose, settings=settings, ) elif len(args.name.strip().split(",")) > 1: for seq_name in tqdm(args.name.strip().split(",")): drawing_function( args.dataset, seq_name.strip(), target_folder=args.target_folder, display=args.verbose, settings=settings, ) else: # Draw bounding boxes on the original video or ground-truth saliency maps, # depending on if -bb was specified drawing_function( args.dataset, args.name, target_folder=args.target_folder, display=args.verbose, settings=settings, )

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7ac4bdad94ae806f6f720e45259f6e5b4067675a

224

py

Python

namespaced/context_processors.py

ferrix/namespaced

56ac0b30fa0873f9b2cd0ea116b744337509d312

[ "MIT" ]

null

namespaced/context_processors.py

ferrix/namespaced

56ac0b30fa0873f9b2cd0ea116b744337509d312

[ "MIT" ]

null

namespaced/context_processors.py

ferrix/namespaced

56ac0b30fa0873f9b2cd0ea116b744337509d312

[ "MIT" ]

null

''' Automatically set `current_app` into context based on URL namespace. ''' def namespaced(request): ''' Set `current_app` to url namespace ''' request.current_app = request.resolver_match.namespace return {}

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7ae4f9789b88d0fdd254efdb7bce254578daecd8

198

py

Python

duel/utils.py

yupeng0921/duel

0bc29db597c6816c08673250ea5c5c8dc5e76e0e

[ "MIT" ]

null

duel/utils.py

yupeng0921/duel

0bc29db597c6816c08673250ea5c5c8dc5e76e0e

[ "MIT" ]

null

duel/utils.py

yupeng0921/duel

0bc29db597c6816c08673250ea5c5c8dc5e76e0e

[ "MIT" ]

null

#!/usr/bin/env python class AssembleError(Exception): def __init__(self, line_no, reason): message = '%d: %s' % (line_no, reason) super(AssembleError, self).__init__(message)

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null

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7af2c29059ce2ab6fd52661596a3831e6052d1a4

313

py

Python

tests/test_utils.py

MapleCCC/LZW-Compressor

df770b557abaa096817a0f158d3eabc515e21d0e

[ "WTFPL" ]

2

2020-04-04T14:20:28.000Z

2020-05-05T11:39:07.000Z

tests/test_utils.py

MapleCCC/LZW-Compressor

df770b557abaa096817a0f158d3eabc515e21d0e

[ "WTFPL" ]

null

tests/test_utils.py

MapleCCC/LZW-Compressor

df770b557abaa096817a0f158d3eabc515e21d0e

[ "WTFPL" ]

null

import functools from LZW.utils import undecorate def test_undecorate(): def get_two(func): return functools.wraps(func)(lambda: 2) def get_one(func): return functools.wraps(func)(lambda: 1) @get_two @get_one def raw(): return 0 assert undecorate(raw)() == 0

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7af5b566656aa5710fa5311e12698ad3150933fa

56

py

Python

cli.py

Overboard/httpfind

2c372daa66dcc7158e8bb179b29d8001d473bc4a

[ "MIT" ]

2

2018-03-18T17:08:24.000Z

2018-12-24T01:07:53.000Z

cli.py

Overboard/httpfind

2c372daa66dcc7158e8bb179b29d8001d473bc4a

[ "MIT" ]

null

cli.py

Overboard/httpfind

2c372daa66dcc7158e8bb179b29d8001d473bc4a

[ "MIT" ]

null

""" Demo file of use """ from httpfind import cli cli()

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bb096e4e81fe8b2338a4a66bf7742d79e9a56fd6

88

py

Python

2020/examples-in-class-2020-11-26/example_list_comprehensions2.py

ati-ozgur/course-python

38237d120043c07230658b56dc3aeb01c3364933

[ "Apache-2.0" ]

1

2021-02-04T16:59:11.000Z

2020/examples-in-class-2020-11-26/example_list_comprehensions2.py

ati-ozgur/course-python

38237d120043c07230658b56dc3aeb01c3364933

[ "Apache-2.0" ]

null

2020/examples-in-class-2020-11-26/example_list_comprehensions2.py

ati-ozgur/course-python

38237d120043c07230658b56dc3aeb01c3364933

[ "Apache-2.0" ]

1

2019-10-30T14:37:48.000Z

l1 = list(range(10)) new_list = [x*x + 2*x + 1 for x in l1] print(l1) print(new_list)

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bb1ec43e6b7238a88c39cfe89a1589ba6d14a0b9

252

py

Python

video/serializers.py

chandojo/climbbeta

17b393535413d035d6cf831cab700c5fd2dc703c

[ "MIT" ]

1

2019-01-25T03:57:54.000Z

video/serializers.py

chandojo/climbbeta

17b393535413d035d6cf831cab700c5fd2dc703c

[ "MIT" ]

39

2019-03-29T17:13:06.000Z

2022-02-10T08:26:46.000Z

video/serializers.py

chandojo/climbbeta

17b393535413d035d6cf831cab700c5fd2dc703c

[ "MIT" ]

1

2019-12-10T18:19:59.000Z

from rest_framework import serializers from .models import * class VideoSerializer(serializers.ModelSerializer): class Meta: model = Videos fields = ('uri', 'created', 'name', 'city', 'author', 'thumbnail', 'description', 'slug')

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bb507315111c663857f3e274f8871f3624fe9ca5

190

py

Python

funcionario/forms.py

apolloalves/DCMNIT

161920dabacab79a81fc3c61216f5be46e2094d7

[ "MIT" ]

1

2020-04-25T19:06:41.000Z

funcionario/forms.py

apolloalves/DCMNIT

161920dabacab79a81fc3c61216f5be46e2094d7

[ "MIT" ]

null

funcionario/forms.py

apolloalves/DCMNIT

161920dabacab79a81fc3c61216f5be46e2094d7

[ "MIT" ]

null

from django import forms from funcionario.models import Funcionario class FuncionarioForm(forms.ModelForm): class Meta: model = Funcionario fields = "__all__"

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bb5aa15ab50925a3780c37cbf39d77e2498f8e25

123

py

Python

test/conftest.py

nervecell23/position-sizing

1934ac6265660d7262ca3cc528237dfdfa152b0c

[ "MIT" ]

null

test/conftest.py

nervecell23/position-sizing

1934ac6265660d7262ca3cc528237dfdfa152b0c

[ "MIT" ]

null

test/conftest.py

nervecell23/position-sizing

1934ac6265660d7262ca3cc528237dfdfa152b0c

[ "MIT" ]

null

import pytest import os @pytest.fixture(autouse=True) def set_env(monkeypatch): monkeypatch.setenv("TESTING", "TRUE")

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