xszheng2020/the_stack_dedup_python_hits_2 · Datasets at Hugging Face

993ea445eb7f4a47f6f9aa018ee57cbb229cee13

652

py

Python

src/splits_creation.py

ValentinMastro/av1_split_encode

27fcec1cfc92701c3fa37b6d6470f18422f2819c

[ "MIT" ]

null

src/splits_creation.py

ValentinMastro/av1_split_encode

27fcec1cfc92701c3fa37b6d6470f18422f2819c

[ "MIT" ]

1

2022-01-21T06:35:49.000Z

2022-01-25T12:29:37.000Z

src/splits_creation.py

ValentinMastro/av1_split_encode

27fcec1cfc92701c3fa37b6d6470f18422f2819c

[ "MIT" ]

null

#!/usr/bin/env python3 from src.splits import Trim_split, Vapoursynth_split def select_split_class(parameters, index, begin, end): if (parameters.splitting_method == "ffmpeg_trim"): return Trim_split(parameters, index, begin, end) elif (parameters.splitting_method == "Vapoursynth"): return Vapoursynth_split(parameters, index, begin, end) elif (parameters.splitting_method == "MagicYUV"): pass def create_splits_from_keyframes(parameters, keyframes): splits = [] for index in range(len(keyframes)-1): begin, end = keyframes[index], keyframes[index+1] splits.append(select_split_class(parameters, index, begin, end)) return splits

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652

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null

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0

null

0

1

0

2

9940a116a01f4e47312e5f4cf38763ccdc7a21a7

974

py

Python

python/binary_search.py

Hamng/python-sources

0cc5a5d9e576440d95f496edcfd921ae37fcd05a

[ "Unlicense" ]

null

python/binary_search.py

Hamng/python-sources

0cc5a5d9e576440d95f496edcfd921ae37fcd05a

[ "Unlicense" ]

1

2019-02-23T18:30:51.000Z

python/binary_search.py

Hamng/python-sources

0cc5a5d9e576440d95f496edcfd921ae37fcd05a

[ "Unlicense" ]

null

# -*- coding: utf-8 -*- """ Created on Mon Dec 14 13:29:10 2020 @author: Ham """ def locate(ar, target): lft = 0 rgt = len(ar) - 1 while lft <= rgt: mid = (lft + rgt) // 2 if ar[mid] == target: return mid if target < ar[mid]: rgt = mid - 1 else: lft = mid + 1 return -1 #for i,e in enumerate(ar): # if e == target: # return i return -1 ar = range(11, 34) print('locate([],', 20, 'found at', locate(ar, 20)) print('locate([],', 10, 'found at', locate(ar, 10)) print('locate([],', 50, 'found at', locate(ar, 50)) print('locate([],', 11, 'found at', locate(ar, 11)) print('locate([],', 33, 'found at', locate(ar, 33)) print('locate([],', 21, 'found at', locate(ar, 21)) print('locate([],', 22, 'found at', locate(ar, 22)) print('locate([],', 23, 'found at', locate(ar, 23)) print('locate([],', 24, 'found at', locate(ar, 24))

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0.391304

0

null

0

1

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null

0

2

99411b0cfc335f939ca03f747656b817d94aefbb

784

py

Python

tests/dispatchers/handlers/test_dispatchers_email.py

bitcaster-io/bitcaster

9f1bad96e00e3bc78a22451731e231d30662b166

[ "BSD-3-Clause" ]

4

2018-03-01T10:22:30.000Z

2020-04-04T16:31:11.000Z

tests/dispatchers/handlers/test_dispatchers_email.py

bitcaster-io/bitcaster

9f1bad96e00e3bc78a22451731e231d30662b166

[ "BSD-3-Clause" ]

60

2018-05-20T04:42:32.000Z

2022-02-10T17:03:37.000Z

tests/dispatchers/handlers/test_dispatchers_email.py

bitcaster-io/bitcaster

9f1bad96e00e3bc78a22451731e231d30662b166

[ "BSD-3-Clause" ]

1

2018-08-04T05:06:45.000Z

import os import pytest from bitcaster.dispatchers import Email from bitcaster.utils.tests.dispatcher_testcase import DispatcherBaseTest pytestmark = pytest.mark.django_db @pytest.mark.plugin @pytest.mark.skipif_missing('TEST_EMAIL_USER', 'TEST_EMAIL_PASSWORD', 'TEST_EMAIL_RECIPIENT') class TestDispatcherEmail(DispatcherBaseTest): TARGET = Email CONFIG = {'username': os.environ.get('TEST_EMAIL_USER'), 'password': os.environ.get('TEST_EMAIL_PASSWORD'), 'server': os.environ.get('TEST_EMAIL_HOST', 'smtp.gmail.com'), 'port': os.environ.get('TEST_EMAIL_PORT', '587'), 'tls': os.environ.get('TEST_EMAIL_TLS', '1'), 'sender': 'sender@sender.com'} RECIPIENT = os.environ.get('TEST_EMAIL_RECIPIENT')

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null

0

1

0

null

0

1

0

2

995612c96395164f8373540180613aa3fca1c524

320

py

Python

override.py

Sp-X/PCAP

f34cf9415262178bd6dfd7941512ff695876d3da

[ "MIT" ]

null

override.py

Sp-X/PCAP

f34cf9415262178bd6dfd7941512ff695876d3da

[ "MIT" ]

null

override.py

Sp-X/PCAP

f34cf9415262178bd6dfd7941512ff695876d3da

[ "MIT" ]

null

class Mouse: def __init__(self, name): self.name = name def __str__(self): return "My name is " + self.name class AncientMouse(Mouse): def __str__(self): return "Meum nomen est " + self.name mus = AncientMouse("Caesar") # Prints "Meum nomen est Caesar" print(mus)

21.333333

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0.176796

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null

0

1

0

null

0

1

0

2

995ae27b97de25734e48f7daab78eff604dc8d6f

2,812

py

Python

sandbox/globalsettings/models.py

Bastilla123/shop2

b2a7ded5b39d0228fadfdb1c9e1fbd3ab0e4cfba

[ "BSD-3-Clause" ]

null

sandbox/globalsettings/models.py

Bastilla123/shop2

b2a7ded5b39d0228fadfdb1c9e1fbd3ab0e4cfba

[ "BSD-3-Clause" ]

12

2021-12-01T11:05:47.000Z

2022-03-01T11:06:09.000Z

sandbox/globalsettings/models.py

Bastilla123/shop2

b2a7ded5b39d0228fadfdb1c9e1fbd3ab0e4cfba

[ "BSD-3-Clause" ]

null

from django.db import models from django.db.models.signals import post_save from django.dispatch import receiver from django.contrib.auth.models import User #from photo.models import Photo class Paymentmethod(models.Model): code = models.CharField(max_length=10, null=True, blank=True, default="") method = models.CharField(max_length=100, null=True, blank=True, default="") is_active = models.BooleanField(default=False) class Globalsettings(models.Model): client_companyname = models.CharField(max_length=240, null=True, blank=True, default="") client_city = models.CharField(max_length=240, null=True, blank=True, default="") client_street = models.CharField(max_length=240, null=True, blank=True, default="") client_zip = models.IntegerField(null=True, blank=True, default=0) client_country = models.PositiveSmallIntegerField(null=True, blank=True, default=0) bank = models.CharField(max_length=240, null=True, blank=True, default="") steuernr = models.CharField(max_length=13, null=True, blank=True, default="") bic_swift = models.PositiveSmallIntegerField(null=True, blank=True, default=0) iban = models.PositiveIntegerField(null=True, blank=True, default=0) phone = models.CharField(max_length=240, null=True, blank=True, default="") email = models.CharField(max_length=240, null=True, blank=True, default="") impressum = models.TextField(blank=True, default="", null=True) kleingewerbe = models.BooleanField(default=False) cashondelivery = models.ManyToManyField(Paymentmethod, blank=True, null=True, default=None, related_name="Globalsettings_cashondelivery") class UserSettings(models.Model): user_link = models.OneToOneField( User, on_delete=models.CASCADE, related_name="usersettings_user_link", primary_key=True, ) street = models.CharField(max_length=120, default="", blank=True, null=True) zip = models.DecimalField(max_digits=7, decimal_places=0, blank=True, null=True) city = models.CharField(max_length=120, default="", blank=True, null=True) birthdate = models.DateField(default=None, blank=True, null=True) company_position = models.CharField(max_length=240, default="", blank=True, null=True) description = models.TextField(blank=True, default="", null=True) #image = models.OneToOneField(Photo, null=True, blank=True, on_delete=models.CASCADE) #Social Media facebook_url = models.CharField(max_length=240, default="", blank=True, null=True) instagram_url = models.CharField(max_length=240, default="", blank=True, null=True) @receiver(post_save, sender=User) def create_user_profile(sender, instance, created, **kwargs): if created: UserSettings.objects.create(user_link=instance)

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2,812

53

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false

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0

null

0

1

0

null

0

1

0

2

9971f366ce29441f55363040d84d470174381052

108

py

Python

main.py

Colk-tech/discoplug

76ae4a71d78d6709e8e393958f3f444cb501759c

[ "MIT" ]

null

main.py

Colk-tech/discoplug

76ae4a71d78d6709e8e393958f3f444cb501759c

[ "MIT" ]

1

2022-03-24T08:30:10.000Z

2022-03-24T09:15:11.000Z

main.py

Colk-tech/discoplug

76ae4a71d78d6709e8e393958f3f444cb501759c

[ "MIT" ]

null

from src.discord.bot import DiscordBOT if __name__ == "__main__": bot = DiscordBOT() bot.launch()

15.428571

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0.675926

13

108

5

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108

6

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0

1

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false

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1

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null

0

1

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null

0

2

99892cea2230bd84c374e64c27308a34778a34c4

1,260

py

Python

fluentogram/src/impl/runner.py

Arustinal/fluentogram

c3d7b307b40d520ef1db5e2a0945f3d7fe269b78

[ "MIT" ]

null

fluentogram/src/impl/runner.py

Arustinal/fluentogram

c3d7b307b40d520ef1db5e2a0945f3d7fe269b78

[ "MIT" ]

null

fluentogram/src/impl/runner.py

Arustinal/fluentogram

c3d7b307b40d520ef1db5e2a0945f3d7fe269b78

[ "MIT" ]

null

# coding=utf-8 """ A translator runner by itself """ from typing import TypeVar, List from fluentogram.src.impl import AttribTracer, FluentTranslator TTranslatorRunner = TypeVar("TTranslatorRunner", bound="TranslatorRunner") class TranslatorRunner(AttribTracer): """This is one-shot per Telegram event translator with attrib tracer access way.""" def __init__(self, translators: List[FluentTranslator]) -> None: super().__init__() self.translators = translators self.request_line = "" def get(self, key: str, **kwargs) -> str: """Faster, direct way to use translator, without sugar-like typing supported attribute access way""" return self._get_translation(key, **kwargs) def _get_translation(self, key, **kwargs): for translator in self.translators: try: return translator.get(key, **kwargs) except KeyError: continue def __call__(self, **kwargs) -> str: text = self._get_translation(self.request_line[:-1], **kwargs) self.request_line = "" return text def __getattr__(self, item: str) -> TTranslatorRunner: self.request_line += f"{item}{self.translators[0].separator}" return self

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false

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0

null

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null

0

1

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1

0

2

41dcfb43014cc728eb2e70b8bf45de511d7c1657

2,379

py

Python

tests/formatters/chrome_preferences.py

pyllyukko/plaso

7533db2d1035ca71d264d6281ebd5db2d073c587

[ "Apache-2.0" ]

1,253

2015-01-02T13:58:02.000Z

2022-03-31T08:43:39.000Z

tests/formatters/chrome_preferences.py

pyllyukko/plaso

7533db2d1035ca71d264d6281ebd5db2d073c587

[ "Apache-2.0" ]

3,388

2015-01-02T11:17:58.000Z

2022-03-30T10:21:45.000Z

tests/formatters/chrome_preferences.py

pyllyukko/plaso

7533db2d1035ca71d264d6281ebd5db2d073c587

[ "Apache-2.0" ]

376

2015-01-20T07:04:54.000Z

2022-03-04T23:53:00.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """Tests for the Google Chrome Preferences file event formatter.""" import unittest from plaso.formatters import chrome_preferences from tests.formatters import test_lib class ChromePreferencesPrimaryURLFormatterHelperTest( test_lib.EventFormatterTestCase): """Tests for the Google Chrome preferences primary URL formatter helper.""" def testFormatEventValues(self): """Tests the FormatEventValues function.""" formatter_helper = ( chrome_preferences.ChromePreferencesPrimaryURLFormatterHelper()) event_values = {'primary_url': 'https://example.com'} formatter_helper.FormatEventValues(event_values) self.assertEqual(event_values['primary_url'], 'https://example.com') event_values = {'primary_url': ''} formatter_helper.FormatEventValues(event_values) self.assertEqual(event_values['primary_url'], 'local file') event_values = {'primary_url': None} formatter_helper.FormatEventValues(event_values) self.assertIsNone(event_values['primary_url']) class ChromePreferencesSecondaryURLFormatterHelperTest( test_lib.EventFormatterTestCase): """Tests for the Google Chrome preferences secondary URL formatter helper.""" def testFormatEventValues(self): """Tests the FormatEventValues function.""" formatter_helper = ( chrome_preferences.ChromePreferencesSecondaryURLFormatterHelper()) event_values = { 'primary_url': 'https://example.com', 'secondary_url': 'https://anotherexample.com'} formatter_helper.FormatEventValues(event_values) self.assertEqual( event_values['secondary_url'], 'https://anotherexample.com') event_values = { 'primary_url': 'https://example.com', 'secondary_url': 'https://example.com'} formatter_helper.FormatEventValues(event_values) self.assertIsNone(event_values['secondary_url']) event_values = { 'primary_url': 'https://example.com', 'secondary_url': ''} formatter_helper.FormatEventValues(event_values) self.assertEqual(event_values['secondary_url'], 'local file') event_values = { 'primary_url': 'https://example.com', 'secondary_url': None} formatter_helper.FormatEventValues(event_values) self.assertIsNone(event_values['secondary_url']) if __name__ == '__main__': unittest.main()

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null

0

2

41e9d47a070d901a1509bec90ba3b4cd92478800

2,023

py

Python

devo/common/dates/dateoperations.py

felixpelaez/python-sdk

13409db8a436d0a7f833242fd289328353373265

[ "MIT" ]

null

devo/common/dates/dateoperations.py

felixpelaez/python-sdk

13409db8a436d0a7f833242fd289328353373265

[ "MIT" ]

null

devo/common/dates/dateoperations.py

felixpelaez/python-sdk

13409db8a436d0a7f833242fd289328353373265

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Utils for date operations.""" from datetime import datetime as dt, timedelta from .dateutils import DateUtils class DateOperations(object): """ This class is a collection of allowed operations on date parsing """ @staticmethod def month(): """ Return millis for a month :return: 30 * 24 * 60 * 60 * 1000 """ return 2592000000 @staticmethod def week(): """ Return millis for a week :return: 7 * 24 * 60 * 60 * 1000 """ return 604800000 @staticmethod def day(): """ Return millis for a day :return: 24 * 60 * 60 * 1000 """ return 86400000 @staticmethod def hour(): """ Return millis for an hour :return: Return 60 * 60 * 1000 """ return 3600000 @staticmethod def minute(): """ Return millis for a minute :return: 60 * 1000 """ return 60000 @staticmethod def second(): """ Return millis for a second :return: 1000 """ return 1000 @staticmethod def now(): """ Return current millis in UTC :return: Millis """ return DateUtils.to_millis(dt.utcnow()) @staticmethod def now_without_ms(): """ Return current millis in UTC :return: Millis """ return DateUtils.to_millis(DateUtils.trunc_time_minute(dt.utcnow())) @staticmethod def today(): """ Return current millis with the time truncated to 00:00:00 :return: Millis """ return DateUtils.to_millis(DateUtils.trunc_time(dt.utcnow())) @staticmethod def yesterday(): """ Return millis from yesterday with time truncated to 00:00:00 :return: Millis """ date = DateUtils.trunc_time(dt.utcnow()) - timedelta(days=1) return DateUtils.to_millis(date)

21.98913

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2,023

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null

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null

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1

0

2

510e62cbba52bcc8b070eefec8577dd8334f7a8f

245

py

Python

pylings/ex_for_beginner/reverse_integer.py

magiskboy/pylings

6639107925b3cb8710403c4381027be894a043c2

[ "MIT" ]

null

pylings/ex_for_beginner/reverse_integer.py

magiskboy/pylings

6639107925b3cb8710403c4381027be894a043c2

[ "MIT" ]

null

pylings/ex_for_beginner/reverse_integer.py

magiskboy/pylings

6639107925b3cb8710403c4381027be894a043c2

[ "MIT" ]

null

""" DESCRIPTION: Write a code to extract each digit from an integer, in the reverse order EXAMPLE Input: n = 1234 Output: "4 3 2 1" """ def main(n: int) -> str: ret_val: str = "" # Enter the code below return ret_val

11.136364

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0.333333

false

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null

0

null

0

1

0

1

0

2

512231868289dfe82b8fbe5a8453ba5fa10be0bc

248

py

Python

baekjoon/rust/effective_hacking_input_gen.py

yskang/AlgorithmPracticeWithPython

f7129bd1924a7961489198f0ee052d2cd1e9cf40

[ "MIT" ]

null

baekjoon/rust/effective_hacking_input_gen.py

yskang/AlgorithmPracticeWithPython

f7129bd1924a7961489198f0ee052d2cd1e9cf40

[ "MIT" ]

1

2019-11-04T06:44:04.000Z

2019-11-04T06:46:55.000Z

baekjoon/rust/effective_hacking_input_gen.py

yskang/AlgorithmPractice

31b76e38b4c2f1e3e29fb029587662a745437912

[ "MIT" ]

null

from random import randint n = randint(1, 10) m = randint(1, 10) print(f'{n} {m}') for _ in range(m): while True: a = randint(1, n) b = randint(1, n) if a != b: print(f'{a} {b}') break

16.533333

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0.447581

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248

2.894737

0.5

0.290909

0.181818

0

0.053333

0.395161

248

15

30

16.533333

0.68

0

0.056225

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1

0

false

0

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0.181818

0

null

1

0

null

0

2

512f5e2f4a0a78538eba5d3573c70d5097d57776

6,252

py

Python

Cats vs Dogs Classification/cats_vs_dogs.py

DhruvAwasthi/ModelsCollection

80ab3ada2d5cb23cce7a3db23be1ec1dc14d8733

[ "Apache-2.0" ]

2

2020-10-22T16:52:56.000Z

2021-10-03T15:57:14.000Z

Cats vs Dogs Classification/cats_vs_dogs.py

DhruvAwasthi/ModelsCollection

80ab3ada2d5cb23cce7a3db23be1ec1dc14d8733

[ "Apache-2.0" ]

null

Cats vs Dogs Classification/cats_vs_dogs.py

DhruvAwasthi/ModelsCollection

80ab3ada2d5cb23cce7a3db23be1ec1dc14d8733

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """Untitled0.ipynb Automatically generated by Colaboratory. Original file is located at https://colab.research.google.com/drive/13osyIHB9WZp5yZL8td8zLGJ7vGZNqywq """ import os import zipfile import random import tensorflow as tf from tensorflow.keras.optimizers import RMSprop from tensorflow.keras.preprocessing.image import ImageDataGenerator from shutil import copyfile !wget --no-check-certificate \ "https://download.microsoft.com/download/3/E/1/3E1C3F21-ECDB-4869-8368-6DEBA77B919F/kagglecatsanddogs_3367a.zip" \ -O "/tmp/cats-and-dogs.zip" local_zip = '/tmp/cats-and-dogs.zip' zip_ref = zipfile.ZipFile(local_zip, 'r') zip_ref.extractall('/tmp') zip_ref.close() print(len(os.listdir('/tmp/PetImages/Cat/'))) print(len(os.listdir('/tmp/PetImages/Dog/'))) try: os.mkdir('/tmp/cats-v-dogs') os.mkdir('/tmp/cats-v-dogs/training') os.mkdir('/tmp/cats-v-dogs/testing') os.mkdir('/tmp/cats-v-dogs/training/cats') os.mkdir('/tmp/cats-v-dogs/training/dogs') os.mkdir('/tmp/cats-v-dogs/testing/cats') os.mkdir('/tmp/cats-v-dogs/testing/dogs') except OSError: pass def split_data(SOURCE, TRAINING, TESTING, SPLIT_SIZE): files = [] for filename in os.listdir(SOURCE): file = SOURCE + filename if os.path.getsize(file) > 0: files.append(filename) else: print(filename + " is zero length, so ignoring.") training_length = int(len(files) * SPLIT_SIZE) testing_length = int(len(files) - training_length) shuffled_set = random.sample(files, len(files)) training_set = shuffled_set[0:training_length] testing_set = shuffled_set[:testing_length] for filename in training_set: this_file = SOURCE + filename destination = TRAINING + filename copyfile(this_file, destination) for filename in testing_set: this_file = SOURCE + filename destination = TESTING + filename copyfile(this_file, destination) CAT_SOURCE_DIR = "/tmp/PetImages/Cat/" TRAINING_CATS_DIR = "/tmp/cats-v-dogs/training/cats/" TESTING_CATS_DIR = "/tmp/cats-v-dogs/testing/cats/" DOG_SOURCE_DIR = "/tmp/PetImages/Dog/" TRAINING_DOGS_DIR = "/tmp/cats-v-dogs/training/dogs/" TESTING_DOGS_DIR = "/tmp/cats-v-dogs/testing/dogs/" split_size = .9 split_data(CAT_SOURCE_DIR, TRAINING_CATS_DIR, TESTING_CATS_DIR, split_size) split_data(DOG_SOURCE_DIR, TRAINING_DOGS_DIR, TESTING_DOGS_DIR, split_size) print(len(os.listdir('/tmp/cats-v-dogs/training/cats/'))) print(len(os.listdir('/tmp/cats-v-dogs/training/dogs/'))) print(len(os.listdir('/tmp/cats-v-dogs/testing/cats/'))) print(len(os.listdir('/tmp/cats-v-dogs/testing/dogs/'))) model = tf.keras.models.Sequential([ tf.keras.layers.Conv2D(16, (3, 3), activation='relu', input_shape=(150, 150, 3)), tf.keras.layers.MaxPooling2D(2, 2), tf.keras.layers.Conv2D(32, (3, 3), activation='relu'), tf.keras.layers.MaxPooling2D(2, 2), tf.keras.layers.Conv2D(64, (3, 3), activation='relu'), tf.keras.layers.MaxPooling2D(2, 2), tf.keras.layers.Flatten(), tf.keras.layers.Dense(512, activation='relu'), tf.keras.layers.Dense(1, activation='sigmoid') ]) model.compile(optimizer=RMSprop(lr=0.001), loss='binary_crossentropy', metrics=['accuracy']) TRAINING_DIR = "/tmp/cats-v-dogs/training/" train_datagen = ImageDataGenerator(rescale=1./255, rotation_range=40, width_shift_range=0.2, height_shift_range=0.2, shear_range=0.2, zoom_range=0.2, horizontal_flip=True, fill_mode='nearest') train_generator = train_datagen.flow_from_directory(TRAINING_DIR, batch_size=100, class_mode='binary', target_size=(150, 150)) VALIDATION_DIR = "/tmp/cats-v-dogs/testing/" validation_datagen = ImageDataGenerator(rescale=1./255, rotation_range=40, width_shift_range=0.2, height_shift_range=0.2, shear_range=0.2, zoom_range=0.2, horizontal_flip=True, fill_mode='nearest') validation_generator = validation_datagen.flow_from_directory(VALIDATION_DIR, batch_size=100, class_mode='binary', target_size=(150, 150)) history = model.fit(train_generator, epochs=15, verbose=1, validation_data=validation_generator) # Commented out IPython magic to ensure Python compatibility. # %matplotlib inline import matplotlib.image as mpimg import matplotlib.pyplot as plt #----------------------------------------------------------- # Retrieve a list of list results on training and test data # sets for each training epoch #----------------------------------------------------------- acc=history.history['accuracy'] val_acc=history.history['val_accuracy'] loss=history.history['loss'] val_loss=history.history['val_loss'] epochs=range(len(acc)) # Get number of epochs #------------------------------------------------ # Plot training and validation accuracy per epoch #------------------------------------------------ plt.plot(epochs, acc, 'r', "Training Accuracy") plt.plot(epochs, val_acc, 'b', "Validation Accuracy") plt.title('Training and validation accuracy') plt.figure() #------------------------------------------------ # Plot training and validation loss per epoch #------------------------------------------------ plt.plot(epochs, loss, 'r', "Training Loss") plt.plot(epochs, val_loss, 'b', "Validation Loss") plt.figure() import numpy as np from google.colab import files from keras.preprocessing import image uploaded = files.upload() for fn in uploaded.keys(): # predicting images path = '/content/' + fn img = image.load_img(path, target_size=(150, 150)) x = image.img_to_array(img) x = np.expand_dims(x, axis=0) images = np.vstack([x]) classes = model.predict(images, batch_size=10) print(classes[0]) if classes[0]>0.5: print(fn + " is a dog") else: print(fn + " is a cat")

34.351648

118

0.630678

796

6,252

4.816583

0.272613

0.03469

0.035472

0.053208

0.356286

0.311163

0.226656

0.181012

0.140845

0

0.027376

0.193698

6,252

182

119

34.351648

0.733188

0.100448

0

0.234848

1

0.007576

0.179662

0.093049

0

null

0.007576

0.090909

null

0.075758

0

null

0

1

0

null

0

1

0

2

5137b889372eb98218355aa6e747192f6fb5c0b2

111

py

Python

iotest.py

erichmatt/pyboard

f5cbda2bd5036c643afe60bd72332958c3a4b387

[ "MIT" ]

null

iotest.py

erichmatt/pyboard

f5cbda2bd5036c643afe60bd72332958c3a4b387

[ "MIT" ]

null

iotest.py

erichmatt/pyboard

f5cbda2bd5036c643afe60bd72332958c3a4b387

[ "MIT" ]

null

import time f = open('testlist.csv','w') for x in range(100): f.write(str(time.clock())) f.write("\n")

18.5

30

0.594595

20

111

3.3

0.8

0.181818

0

0.032609

0.171171

111

5

31

22.2

0.684783

0

0.135135

0

1

0

false

0

0.2

0

0.2

0

1

0

null

0

1

0

null

0

2

513e466953e9624c26fa627e365787c9d6c87190

465

py

Python

projects/balancer.py

donuk/pyboard-robotics

c8cb816bc0a3f0bb30977b184cee97e3e85b1c3f

[ "Apache-2.0" ]

null

projects/balancer.py

donuk/pyboard-robotics

c8cb816bc0a3f0bb30977b184cee97e3e85b1c3f

[ "Apache-2.0" ]

1

2019-12-27T15:49:23.000Z

projects/balancer.py

donuk/pyboard-robotics

c8cb816bc0a3f0bb30977b184cee97e3e85b1c3f

[ "Apache-2.0" ]

null

# main.py -- put your code here! from lib.servo import servo1, stop_servos_before_finishing from lib.accelerometer import accelerometer turn_left = True # This will stop the servos if anything goes wrong with stop_servos_before_finishing(): # Loop forever while True: x = accelerometer.x() if x < -5: servo1.forward() elif x > 5: servo1.backward() else: servo1.stop()

24.473684

59

0.608602

57

465

4.842105

0.631579

0.050725

0.115942

0.181159

0

0.018927

0.31828

465

18

60

25.833333

0.851735

0.197849

0

0.055556

0

1

0

false

0

0.166667

0

0.166667

0

null

0

1

0

null

0

1

0

2

513f7a9c349e22fc27386406afdcb4c854e324d9

1,217

py

Python

testing/tests/001-main/003-self/200-json/003-repositories.py

fekblom/critic

a6b60c9053e13d4c878d50531860d7389568626d

[ "Apache-2.0" ]

null

testing/tests/001-main/003-self/200-json/003-repositories.py

fekblom/critic

a6b60c9053e13d4c878d50531860d7389568626d

[ "Apache-2.0" ]

null

testing/tests/001-main/003-self/200-json/003-repositories.py

fekblom/critic

a6b60c9053e13d4c878d50531860d7389568626d

[ "Apache-2.0" ]

null

# @dependency 001-main/002-createrepository.py frontend.json( "repositories", expect={ "repositories": [critic_json] }) frontend.json( "repositories/1", expect=critic_json) frontend.json( "repositories", params={ "name": "critic" }, expect=critic_json) frontend.json( "repositories/4711", expect={ "error": { "title": "No such resource", "message": "Resource not found: Invalid repository id: 4711" }}, expected_http_status=404) frontend.json( "repositories/critic", expect={ "error": { "title": "Invalid API request", "message": "Invalid numeric id: 'critic'" }}, expected_http_status=400) frontend.json( "repositories", params={ "name": "nosuchrepository" }, expect={ "error": { "title": "No such resource", "message": "Resource not found: Invalid repository name: 'nosuchrepository'" }}, expected_http_status=404) frontend.json( "repositories", params={ "filter": "interesting" }, expect={ "error": { "title": "Invalid API request", "message": "Invalid repository filter parameter: 'interesting'" }}, expected_http_status=400)

29.682927

104

0.614626

116

1,217

6.353448

0.327586

0.113976

0.227951

0.089552

0.654003

0.548168

0.43962

0.317503

0.189959

0

0.02897

0.234182

1,217

40

105

30.425

0.761803

0.036154

0

0.65625

0

0.412468

0

1

0

true

0

null

0

1

0

null

0

1

0

2

515992ed5a7c31c979b341f8c384d04b01621296

129

py

Python

src/beginner/1151.py

henrikhorbovyi/URI

6df34d87bb7bbbf760ab774e01da87ad669acae9

[ "Apache-2.0" ]

1

2018-07-04T01:53:29.000Z

src/beginner/1151.py

henrikhorbovyi/URI

6df34d87bb7bbbf760ab774e01da87ad669acae9

[ "Apache-2.0" ]

null

src/beginner/1151.py

henrikhorbovyi/URI

6df34d87bb7bbbf760ab774e01da87ad669acae9

[ "Apache-2.0" ]

null

N = int(input()) a,b = 1,1 print(0,end=' ') for i in range(1,N-1): if i != N: print(a,end=' ') a,b = b,a+b print(a,end='\n')

16.125

22

0.496124

32

129

2

0.4375

0.09375

0.28125

0

0.048544

0.20155

129

8

23

16.125

0.572816

0

0.030769

0

1

0

false

0

0.375

0

null

0

1

0

1

0

null

0

2

515cd796f7e34f68f9a7c813d0344e52bda689a0

826

py

Python

playground/optimization/ott2butKAMA2-serenity/custom_indicators/ewo.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

38

2021-09-18T15:33:28.000Z

2022-02-21T17:29:08.000Z

fractional/custom_indicators/ewo.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

4

2022-01-02T14:46:12.000Z

2022-02-16T18:39:41.000Z

fractional/custom_indicators/ewo.py

ysdede/jesse_strategies

ade9f4ba42cec11207c766d267b9d8feb8bce648

[ "CC0-1.0" ]

11

2021-10-19T06:21:43.000Z

2022-02-21T17:29:10.000Z

import numpy as np import talib from typing import Union from jesse.helpers import get_candle_source, slice_candles def ewo(candles: np.ndarray, short_period: int = 5, long_period: int = 35, source_type="close", sequential=False) -> \ Union[float, np.ndarray]: """ Elliott Wave Oscillator :param candles: np.ndarray :param short_period: int - default: 5 :param long_period: int - default: 34 :param source_type: str - default: close :param sequential: bool - default: False :return: Union[float, np.ndarray] """ candles = slice_candles(candles, sequential) src = get_candle_source(candles, source_type) ewo = np.subtract(talib.EMA(src, timeperiod=short_period), talib.EMA(src, timeperiod=long_period)) if sequential: return ewo else: return ewo[-1]

29.5

118

0.697337

111

826

5.054054

0.405405

0.064171

0.053476

0.067736

0

0.01059

0.199758

826

28

119

29.5

0.838124

0.292978

0

0.009174

0

1

0.076923

false

0

0.307692

0

0.538462

0

null

0

null

0

1

0

1

0

2

51638f725fbcd2002829a1c5d2ecadbde1f14bc4

588

py

Python

class and objects/abstract calss inherit from another abstract class.py

ZephyrAveryl777/Python-Programs

26de85c31af28382d406d27d54186b966a7b1bfc

[ "MIT" ]

6

2020-08-13T11:49:29.000Z

2021-03-07T05:46:17.000Z

class and objects/abstract calss inherit from another abstract class.py

ZephyrAveryl777/Python-Programs

26de85c31af28382d406d27d54186b966a7b1bfc

[ "MIT" ]

null

class and objects/abstract calss inherit from another abstract class.py

ZephyrAveryl777/Python-Programs

26de85c31af28382d406d27d54186b966a7b1bfc

[ "MIT" ]

1

2021-04-24T06:12:48.000Z

''' A class that is derived from an abstract class cannot be instantiated unless all of its abstract methods are overridden. ''' from abc import ABC,abstractmethod print(__doc__,end="") print('\n'+'-'*25+'Abstract class inherit from another abstract class'+'-'*35) class A(ABC): def __init__(self,username): self.username=username super().__init__() @abstractmethod def name(self): pass class B(A): @abstractmethod def age(self): pass class C(B): def name(self): print(self.username) def age(self): return c=C('Testing-123456') c.name()

20.275862

79

0.678571

83

588

4.662651

0.506024

0.100775

0.056848

0

0.020964

0.188776

588

29

80

20.275862

0.790356

0.205782

0

0.380952

0

0.157407

0

1

0.238095

false

0.095238

0.047619

0.47619

0.142857

0

null

0

null

0

1

0

1

0

2

516646dce18d825a2d1a4a1379f922eb2f8854f9

369

py

Python

scripts/8-pacotes-modulos-python/ex107/teste.py

dev-alissonalves/python-codes

376a5e52cebcf9e5102f55c6aa44745aaef50add

[ "MIT" ]

1

2021-07-05T10:46:25.000Z

scripts/8-pacotes-modulos-python/ex107/teste.py

dev-alissonalves/python-codes

376a5e52cebcf9e5102f55c6aa44745aaef50add

[ "MIT" ]

null

scripts/8-pacotes-modulos-python/ex107/teste.py

dev-alissonalves/python-codes

376a5e52cebcf9e5102f55c6aa44745aaef50add

[ "MIT" ]

1

2021-07-05T15:41:08.000Z

import moeda p = float(input("Informe um valor qualquer: ")) print("\n") print("-=-=-=-=- INÍCIO =-=-=-=") print(f"A metade do valor {p:.2f} é: {moeda.metade(p)}") print(f"O dobro do valor {p:.2f} é: {moeda.dobro(p)}") print(f"Aumentando 10%, temos: {moeda.aumentar(p, 10)}") print(f"Diminuindo 10%, temos: {moeda.diminuir(p, 10)}") print("-=-=-=-=- FIM =-=-=-=")

24.6

56

0.588076

57

369

3.807018

0.473684

0.110599

0.073733

0.092166

0.147465

0

0.030864

0.121951

369

14

57

26.357143

0.638889

0

0.695652

0

1

0

false

0

0.111111

0

0.111111

0.777778

0

null

0

1

0

null

0

1

0

2

5a9d312c9847bdaf1084e0b7133c41b344493da3

5,568

py

Python

mvp/djfulcrum/filters/run_filters.py

venicegeo/fulcrum_demo

0f160655ac1eede1c5d537f688b00d7fe1d08fa9

[ "Apache-2.0" ]

null

mvp/djfulcrum/filters/run_filters.py

venicegeo/fulcrum_demo

0f160655ac1eede1c5d537f688b00d7fe1d08fa9

[ "Apache-2.0" ]

null

mvp/djfulcrum/filters/run_filters.py

venicegeo/fulcrum_demo

0f160655ac1eede1c5d537f688b00d7fe1d08fa9

[ "Apache-2.0" ]

null

from __future__ import absolute_import import os from importlib import import_module def filter_features(features, filter_name=None, run_once=False): """ Args: features: A geojson Feature Collection filter_name: The name of a filter to use if None all active filters are used (default:None) run_once: Run the filter one time without being active. Returns: Geojson Feature Collection that passed any filters in the in filter package If no features passed None is returned """ from ..models import Filter from ..djfulcrum import delete_feature workspace = os.path.dirname(os.path.abspath(__file__)) files = os.listdir(workspace) if features.get('features'): filtered_feature_count = len(features.get('features')) filtered_results = None if filter_name: filter_models = Filter.objects.filter(filter_name__iexact=filter_name) else: filter_models = Filter.objects.all() if filter_models: un_needed = [] for filter_model in filter_models: if filter_model.filter_name in files: if filter_model.filter_active or run_once: if not features: break try: module_name = 'djfulcrum.filters.' + str(filter_model.filter_name.rstrip('.py')) mod = import_module(module_name) print "Running: {}".format(filter_model.filter_name) filtered_results = mod.filter_features(features) except ImportError: print "Could not filter features - ImportError" except TypeError as te: print te print "Could not filter features - TypeError" except Exception as e: "Unknown error occurred, could not filter features" print repr(e) if filtered_results: if filtered_results.get('failed').get('features'): for feature in filtered_results.get('failed').get('features'): if run_once: delete_feature(feature.get('properties').get('fulcrum_id')) print "{} features failed the filter".format( len(filtered_results.get('failed').get('features'))) if filtered_results.get('passed').get('features'): print "{} features passed the filter".format( len(filtered_results.get('passed').get('features'))) features = filtered_results.get('passed') filtered_feature_count = len(filtered_results.get('passed').get('features')) else: features = None filtered_feature_count = 0 else: print "Failure to get filtered results" else: un_needed.append(filter_model) if un_needed: for filter_model in un_needed: print("The filter {} was found in the database but the module is " "missing.".format(filter_model.filter_name)) print("It will be disabled. If the module is installed later, reenable the filter " "in the admin console.") filter_model.filter_active = False else: features = None filtered_feature_count = 0 return features, filtered_feature_count def check_filters(): """ Returns: True if checking the filters was successful. Finds '.py' files used for filtering and adds to db model for use in admin console. Sets cache value so function will not running fully every time it is called by tasks.py """ from ..models import Filter from ..tasks import get_lock_id from django.db import IntegrityError from importlib import import_module from django.core.cache import cache workspace = os.path.dirname(os.path.abspath(__file__)) files = os.listdir(workspace) if files: lock_id = get_lock_id('list-filters-success') if cache.get(lock_id): return True for filter_file in files: if filter_file.endswith('.py'): if filter_file == 'run_filters.py' or filter_file == '__init__.py': continue try: filter_names = Filter.objects.filter(filter_name__iexact=filter_file) if not filter_names.exists(): filter_model = Filter.objects.create(filter_name=filter_file) print ("Created filter {}".format(filter_model.filter_name)) except IntegrityError: return False try: mod = import_module('djfulcrum.filters.' + str(filter_file.rstrip('.py'))) if 'setup_filter_model' in dir(mod): mod.setup_filter_model() except ImportError: return False cache.set(lock_id, True, 20) return True

46.016529

108

0.541128

576

5,568

5.038194

0.255208

0.049276

0.046864

0.036182

0.287388

0.201585

0.160924

0.044108

0

0.001174

0.38829

5,568

120

109

46.4

0.850851

0

0.270833

0

0.129378

0

null

0.052083

0.15625

null

0.114583

0

null

0

null

0

1

0

1

0

2

5aa4948852536ca4f40cb2992519749d10b4cc3f

18,304

py

Python

src/intensio_obfuscator/core/obfuscation/intensio_delete.py

bbhunter/Intensio-Obfuscator

f66a22b50c19793edac673cfd7dc319405205c39

[ "MIT" ]

553

2019-06-08T17:47:41.000Z

2022-03-29T03:12:11.000Z

src/intensio_obfuscator/core/obfuscation/intensio_delete.py

bbhunter/Intensio-Obfuscator

f66a22b50c19793edac673cfd7dc319405205c39

[ "MIT" ]

69

2019-06-08T13:25:47.000Z

2022-02-15T08:34:07.000Z

src/intensio_obfuscator/core/obfuscation/intensio_delete.py

bbhunter/Intensio-Obfuscator

f66a22b50c19793edac673cfd7dc319405205c39

[ "MIT" ]

130

2019-06-08T18:44:13.000Z

2022-03-27T01:00:52.000Z

# -*- coding: utf-8 -*- # https://github.com/Hnfull/Intensio-Obfuscator #---------------------------------------------------------- [Lib] -----------------------------------------------------------# import re import fileinput import os import sys from progress.bar import Bar try: from intensio_obfuscator.core.utils.intensio_utils import Utils, Reg except ModuleNotFoundError: from core.utils.intensio_utils import Utils, Reg #------------------------------------------------- [Function(s)/Class(es)] --------------------------------------------------# class Delete: def __init__(self): self.utils = Utils() def LinesSpaces(self, outputArg, verboseArg): checkLinesSpace = {} checkEmptyLineOutput = 0 checkEmptyLineInput = 0 countRecursFiles = 0 numberLine = 0 recursFiles = self.utils.CheckFileDir( output=outputArg, detectFiles="py", blockDir="__pycache__", blockFile=False, dirOnly=False ) for file in recursFiles: countRecursFiles += 1 # -- Delete all empty lines -- # with Bar("Obfuscation ", fill="=", max=countRecursFiles, suffix="%(percent)d%%") as bar: for file in recursFiles: with fileinput.FileInput(file, inplace=True) as inputFile: for eachLine in inputFile: if re.match(Reg.detectLineEmpty, eachLine): checkEmptyLineInput += 1 pass else: sys.stdout.write(eachLine) bar.next(1) bar.finish() with Bar("Check ", fill="=", max=countRecursFiles, suffix="%(percent)d%%") as bar: for file in recursFiles: numberLine = 0 with open(file, "r") as readFile: readF = readFile.readlines() for eachLine in readF: numberLine += 1 if re.match(Reg.detectLineEmpty, eachLine): checkLinesSpace[numberLine] = file checkEmptyLineOutput += 1 bar.next(1) bar.finish() if checkEmptyLineOutput == 0: return 1 else: if verboseArg: print("\n[!] Empty line that not been deleted... :\n") for key, value in checkLinesSpace.items(): print("\n-> File : {}".format(value)) print("-> Line : {}".format(key)) else: print("\n[*] Empty line that deleted : {}\n".format(checkEmptyLineInput)) return 0 def Comments(self, outputArg, verboseArg): getIndexList = [] filesConcerned = [] eachLineListCheckIndex = [] countLineCommentOutput = 0 countLineCommentInput = 0 multipleLinesComments = 0 countRecursFiles = 0 noCommentsQuotes = 0 getIndex = 0 detectIntoSimpleQuotes = None eachLineCheckIndex = "" recursFiles = self.utils.CheckFileDir( output=outputArg, detectFiles="py", blockDir="__pycache__", blockFile=False, dirOnly=False ) for i in recursFiles: countRecursFiles += 1 # -- Delete comments and count comments will be deleted -- # print("\n[+] Running delete comments in {} file(s)...\n".format(countRecursFiles)) with Bar("Obfuscation ", fill="=", max=countRecursFiles, suffix="%(percent)d%%") as bar: for file in recursFiles: with fileinput.input(file, inplace=True) as inputFile: for eachLine in inputFile: if re.match(Reg.pythonFileHeader, eachLine): sys.stdout.write(eachLine) else: if multipleLinesComments == 1: if re.match(Reg.quotesCommentsEndMultipleLines, eachLine): if self.utils.VerifyMultipleLinesComments(eachLine) == True: if multipleLinesComments == 1: countLineCommentInput += 1 multipleLinesComments = 0 else: countLineCommentInput += 1 else: countLineCommentInput += 1 elif noCommentsQuotes == 1: if re.match(Reg.checkIfEndVarStdoutMultipleQuotes, eachLine): sys.stdout.write(eachLine) noCommentsQuotes = 0 else: sys.stdout.write(eachLine) else: if re.match(Reg.quotesCommentsOneLine, eachLine): countLineCommentInput += 1 else: if re.match(Reg.quotesCommentsMultipleLines, eachLine): if self.utils.VerifyMultipleLinesComments(eachLine) == True: countLineCommentInput += 1 multipleLinesComments = 1 else: sys.stdout.write(eachLine) else: if re.match(Reg.checkIfStdoutMultipleQuotes, eachLine) \ or re.match(Reg.checkIfVarMultipleQuotes, eachLine): sys.stdout.write(eachLine) noCommentsQuotes = 1 elif re.match(Reg.checkIfRegexMultipleQuotes, eachLine): sys.stdout.write(eachLine) else: sys.stdout.write(eachLine) with fileinput.input(file, inplace=True) as inputFile: for eachLine in inputFile: if re.match(Reg.pythonFileHeader, eachLine): sys.stdout.write(eachLine) else: if re.match(Reg.hashCommentsBeginLine, eachLine): countLineCommentInput += 1 elif re.match(Reg.hashCommentsAfterLine, eachLine): eachLineList = list(eachLine) getIndexList = [] for i, v in enumerate(eachLineList): if v == "#": getIndexList.append(i) for i in getIndexList: if self.utils.DetectIntoSimpleQuotes(eachLine, maxIndexLine=i) == False: countLineCommentInput += 1 detectIntoSimpleQuotes = False break else: continue if detectIntoSimpleQuotes == False: for i in getIndexList: eachLineListCheckIndex = eachLineList[:i] eachLineListCheckIndex.append("\n") eachLineCheckIndex = "".join(eachLineListCheckIndex) if self.utils.DetectIntoSimpleQuotes(eachLineCheckIndex, maxIndexLine=i) == False: getIndex = i break else: continue eachLineList = eachLineList[:getIndex] eachLineList.append("\n") eachLine = "".join(eachLineList) sys.stdout.write(eachLine) detectIntoSimpleQuotes = None countLineCommentInput += 1 else: sys.stdout.write(eachLine) else: sys.stdout.write(eachLine) bar.next(1) bar.finish() # -- Check if all comments are deleted -- # with Bar("Check ", fill="=", max=countRecursFiles, suffix="%(percent)d%%") as bar: for file in recursFiles: with open(file, "r") as readFile: readF = readFile.readlines() for eachLine in readF: if re.match(Reg.pythonFileHeader, eachLine): continue else: if multipleLinesComments == 1: if re.match(Reg.quotesCommentsEndMultipleLines, eachLine): if self.utils.VerifyMultipleLinesComments(eachLine) == True: if multipleLinesComments == 1: countLineCommentOutput += 1 multipleLinesComments = 0 filesConcerned.append(file) else: countLineCommentOutput += 1 filesConcerned.append(file) else: countLineCommentOutput += 1 filesConcerned.append(file) elif noCommentsQuotes == 1: if re.match(Reg.checkIfEndVarStdoutMultipleQuotes, eachLine): noCommentsQuotes = 0 else: continue else: if re.match(Reg.quotesCommentsOneLine, eachLine): countLineCommentOutput += 1 filesConcerned.append(file) else: if re.match(Reg.quotesCommentsMultipleLines, eachLine): if self.utils.VerifyMultipleLinesComments(eachLine) == True: countLineCommentOutput += 1 multipleLinesComments = 1 filesConcerned.append(file) else: continue else: if re.match(Reg.checkIfStdoutMultipleQuotes, eachLine) \ or re.match(Reg.checkIfVarMultipleQuotes, eachLine): noCommentsQuotes = 1 elif re.match(Reg.checkIfRegexMultipleQuotes, eachLine): continue else: continue with open(file, "r") as readFile: readF = readFile.readlines() for eachLine in readF: if re.match(Reg.pythonFileHeader, eachLine): continue else: if re.match(Reg.hashCommentsBeginLine, eachLine): countLineCommentOutput += 1 filesConcerned.append(file) elif re.match(Reg.hashCommentsAfterLine, eachLine): eachLineList = list(eachLine) getIndexList = [] for i, v in enumerate(eachLineList): if v == "#": getIndexList.append(i) for i in getIndexList: if self.utils.DetectIntoSimpleQuotes(eachLine, maxIndexLine=i) == False: countLineCommentOutput += 1 detectIntoSimpleQuotes = False filesConcerned.append(file) break else: continue if detectIntoSimpleQuotes == False: for i in getIndexList: eachLineListCheckIndex = eachLineList[:i] eachLineListCheckIndex.append("\n") eachLineCheckIndex = "".join(eachLineListCheckIndex) if self.utils.DetectIntoSimpleQuotes(eachLineCheckIndex, maxIndexLine=i) == False: getIndex = i break else: continue eachLineList = eachLineList[:getIndex] eachLineList.append("\n") eachLine = "".join(eachLineList) countLineCommentOutput += 1 detectIntoSimpleQuotes = None else: continue else: continue bar.next(1) bar.finish() if countLineCommentOutput == 0: print("\n-> {} lines of comments deleted\n".format(countLineCommentInput)) return 1 else: if verboseArg: filesConcerned = self.utils.RemoveDuplicatesValuesInList(filesConcerned) print("\nFiles concerned of comments no deleted :\n") for f in filesConcerned: print("-> {}".format(f)) print("\n-> {} lines of comments no deleted\n".format(countLineCommentOutput)) return 0 def TrashFiles(self, outputArg, verboseArg): countRecursFiles = 0 deleteFiles = 0 checkPycFile = [] currentPosition = os.getcwd() recursFiles = self.utils.CheckFileDir( output=outputArg, detectFiles="pyc", blockDir="__pycache__", blockFile=False, dirOnly=False ) for number in recursFiles: countRecursFiles += 1 if countRecursFiles == 0: print("[!] No .pyc file(s) found in {}".format(outputArg)) return 1 print("\n[+] Running delete {} .pyc file(s)...\n".format(countRecursFiles)) # -- Check if .pyc file(s) exists and delete it -- # with Bar("Setting up ", fill="=", max=countRecursFiles, suffix="%(percent)d%%") as bar: for file in recursFiles: if re.match(Reg.detectPycFiles, file): deleteFiles += 1 checkPycFile.append(file) bar.next(1) bar.finish() # -- Delete pyc file(s) -- # with Bar("Correction ", fill="=", max=countRecursFiles, suffix="%(percent)d%%") as bar: for file in recursFiles: if re.match(Reg.detectPycFiles, file): extractPycFiles = re.search(r".*\.pyc$", file) moveFolder = re.sub(r".*\.pyc$", "", file) os.chdir(moveFolder) os.remove(extractPycFiles.group(0)) os.chdir(currentPosition) bar.next(1) bar.finish() checkRecursFiles = self.utils.CheckFileDir( output=outputArg, detectFiles="pyc", blockDir="__pycache__", blockFile=False, dirOnly=False ) if checkRecursFiles != []: if verboseArg: for pycFile in checkRecursFiles: print("-> .pyc file no deleted : {}".format(pycFile)) return 0 else: if verboseArg: for pycFile in checkPycFile: print("-> .pyc file deleted : {}".format(pycFile)) print("\n-> {} .pyc file(s) deleted".format(deleteFiles)) return 1

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0.036146

0.033366

0.670513

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null

0

1

0

1

0

null

0

2

5ab3d12f2d0c6dadc8b931d7354407aa96d8ba44

793

py

Python

test_pascals_triangle.py

jaebradley/leetcode.py

64634cc7d0e975ddd163f35acb18cc92960b8eb5

[ "MIT" ]

null

test_pascals_triangle.py

jaebradley/leetcode.py

64634cc7d0e975ddd163f35acb18cc92960b8eb5

[ "MIT" ]

2

2019-11-13T19:55:49.000Z

2019-11-13T19:55:57.000Z

test_pascals_triangle.py

jaebradley/leetcode.py

64634cc7d0e975ddd163f35acb18cc92960b8eb5

[ "MIT" ]

null

from unittest import TestCase from pascals_triangle import Solution class TestSolution(TestCase): def setUp(self) -> None: self.solution = Solution() def test_generate(self): self.assertListEqual( [[1]], self.solution.generate(1) ) self.assertListEqual( [[1], [1, 1]], self.solution.generate(2) ) self.assertListEqual( [[1], [1, 1], [1, 2, 1]], self.solution.generate(3) ) self.assertListEqual( [[1], [1, 1], [1, 2, 1], [1, 3, 3, 1]], self.solution.generate(4) ) self.assertListEqual( [[1], [1, 1], [1, 2, 1], [1, 3, 3, 1], [1, 4, 6, 4, 1]], self.solution.generate(5) )

23.323529

68

0.474149

88

793

4.25

0.25

0.074866

0.05615

0.280749

0.221925

0.15508

0

0.07984

0.368222

793

33

69

24.030303

0.666667

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0

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null

0

1

0

1

0

null

0

2

5abe0804e10d04a719d8730679fd30f1b996a4d5

289

py

Python

app/__init__.py

tirgei/stack-overflow-lite-api

34a3ca2a63b2acdfa5bdbeda556417ae7ccc5b28

[ "MIT" ]

1

2018-12-17T08:35:02.000Z

app/__init__.py

tirgei/stack-overflow-lite-api

34a3ca2a63b2acdfa5bdbeda556417ae7ccc5b28

[ "MIT" ]

1

2018-12-19T15:44:18.000Z

app/__init__.py

tirgei/stack-overflow-lite-api

34a3ca2a63b2acdfa5bdbeda556417ae7ccc5b28

[ "MIT" ]

null

import os from flask import Flask from instance.config import app_config from app.api.v1.views.user_views import v1 as users_v1 def create_app(config_name): app = Flask(__name__) app.config.from_object(app_config[config_name]) app.register_blueprint(users_v1) return app

24.083333

54

0.782007

47

289

4.510638

0.425532

0.169811

0.122642

0

0.01626

0.148789

289

12

55

24.083333

0.845528

0

1

0.111111

false

0

0.444444

0

0.666667

0.111111

0

null

0

null

0

1

0

1

0

2

5abe73158155f231abe8be65125222d9b38f4f5b

72

py

Python

ashd/pipelinev2/global_vals.py

johnnygreco/asas-sn-hd

1baf7ff6c0cb7c65caf7b2e07ed67b13049c92d9

[ "MIT" ]

null

ashd/pipelinev2/global_vals.py

johnnygreco/asas-sn-hd

1baf7ff6c0cb7c65caf7b2e07ed67b13049c92d9

[ "MIT" ]

null

ashd/pipelinev2/global_vals.py

johnnygreco/asas-sn-hd

1baf7ff6c0cb7c65caf7b2e07ed67b13049c92d9

[ "MIT" ]

null

# note that these are default variables MAX_TRIES = 10 MAX_FINDINGS = 3

18

39

0.777778

12

72

4.5

0.916667

0

0.050847

0.180556

72

4

40

18

0.864407

0.513889

0

1

0

false

0

1

0

null

0

1

0

null

0

2

5acbcb9e5fd66f410d8f88ab087aa7d19eba06e5

881

py

Python

setup.py

williamfzc/devcube

71bc293161d489ca47a8c3deebfdc52e8933f82f

[ "MIT" ]

4

2020-08-07T07:52:10.000Z

2020-08-07T16:32:03.000Z

setup.py

williamfzc/devcube

71bc293161d489ca47a8c3deebfdc52e8933f82f

[ "MIT" ]

null

setup.py

williamfzc/devcube

71bc293161d489ca47a8c3deebfdc52e8933f82f

[ "MIT" ]

null

from setuptools import setup, find_packages from devcube import ( __AUTHOR__, __AUTHOR_EMAIL__, __VERSION__, __PROJECT_NAME__, ) with open("requirements.txt", encoding="utf-8") as f: requirements = [ each.strip() for each in f.readlines() if not each.startswith("git+") ] setup( name=__PROJECT_NAME__, version=__VERSION__, author=__AUTHOR__, author_email=__AUTHOR_EMAIL__, packages=find_packages(), include_package_data=True, classifiers=[ "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", ], python_requires=">=3.6", install_requires=requirements, entry_points={"console_scripts": ["devcube = devcube.cli:main"]}, )

27.53125

77

0.653802

94

881

5.648936

0.521277

0.178908

0.235405

0.195857

0

0.014535

0.219069

881

31

78

28.419355

0.757267

0

0.280363

0

1

0

false

0

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0

0.068966

0

null

0

1

0

null

0

2

5ae221e0b2b897840f866c40878a6fd9835def7f

3,150

py

Python

asyncapi_schema_pydantic/v2_3_0/message_bindings.py

albertnadal/asyncapi-schema-pydantic

83966bdc11f2d465a10b52cec5ff79d18fa6f5fe

[ "MIT" ]

null

asyncapi_schema_pydantic/v2_3_0/message_bindings.py

albertnadal/asyncapi-schema-pydantic

83966bdc11f2d465a10b52cec5ff79d18fa6f5fe

[ "MIT" ]

null

asyncapi_schema_pydantic/v2_3_0/message_bindings.py

albertnadal/asyncapi-schema-pydantic

83966bdc11f2d465a10b52cec5ff79d18fa6f5fe

[ "MIT" ]

null

from typing import Optional from pydantic import BaseModel, Extra from .http_bindings import HttpMessageBinding from .web_sockets_bindings import WebSocketsMessageBinding from .kafka_bindings import KafkaMessageBinding from .anypoint_mq_bindings import AnypointMqMessageBinding from .amqp_bindings import AmqpMessageBinding from .amqp1_bindings import Amqp1MessageBinding from .mqtt_bindings import MqttMessageBinding from .mqtt5_bindings import Mqtt5MessageBinding from .nats_bindings import NatsMessageBinding from .jms_bindings import JmsMessageBinding from .sns_bindings import SnsMessageBinding from .solace_bindings import SolaceMessageBinding from .sqs_bindings import SqsMessageBinding from .stomp_bindings import StompMessageBinding from .redis_bindings import RedisMessageBinding from .mercure_bindings import MercureMessageBinding from .ibm_mq_bindings import IbmMqMessageBinding class MessageBindings(BaseModel): """ Map describing protocol-specific definitions for a message. """ http: Optional[HttpMessageBinding] = None """ Protocol-specific information for an HTTP message, i.e., a request or a response. """ ws: Optional[WebSocketsMessageBinding] = None """ Protocol-specific information for a WebSockets message. """ kafka: Optional[KafkaMessageBinding] = None """ Protocol-specific information for a Kafka message. """ anypointmq: Optional[AnypointMqMessageBinding] = None """ Protocol-specific information for an Anypoint MQ message. """ amqp: Optional[AmqpMessageBinding] = None """ Protocol-specific information for an AMQP 0-9-1 message. """ amqp1: Optional[Amqp1MessageBinding] = None """ Protocol-specific information for an AMQP 1.0 message. """ mqtt: Optional[MqttMessageBinding] = None """ Protocol-specific information for an MQTT message. """ mqtt5: Optional[Mqtt5MessageBinding] = None """ Protocol-specific information for an MQTT 5 message. """ nats: Optional[NatsMessageBinding] = None """ Protocol-specific information for a NATS message. """ jms: Optional[JmsMessageBinding] = None """ Protocol-specific information for a JMS message. """ sns: Optional[SnsMessageBinding] = None """ Protocol-specific information for an SNS message. """ solace: Optional[SolaceMessageBinding] = None """ Protocol-specific information for a Solace message. """ sqs: Optional[SqsMessageBinding] = None """ Protocol-specific information for an SQS message. """ stomp: Optional[StompMessageBinding] = None """ Protocol-specific information for a STOMP message. """ redis: Optional[RedisMessageBinding] = None """ Protocol-specific information for a Redis message. """ mercure: Optional[MercureMessageBinding] = None """ Protocol-specific information for a Mercure message. """ ibmmq: Optional[IbmMqMessageBinding] = None """ Protocol-specific information for an IBM MQ message. """ class Config: extra = Extra.forbid

27.155172

85

0.724127

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3,150

7.177778

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0

null

0

1

0

null

0

1

0

2

5aefdc6a6208c608443af8d9fd5961f34de89ce8

796

py

Python

dltb/tool/tests/test_detector.py

CogSciUOS/DeepLearningToolbox

bf07578b9486d8c48e25df357bc4b9963b513b46

[ "MIT" ]

2

2019-09-01T01:38:59.000Z

2020-02-13T19:25:51.000Z

dltb/tool/tests/test_detector.py

CogSciUOS/DeepLearningToolbox

bf07578b9486d8c48e25df357bc4b9963b513b46

[ "MIT" ]

null

dltb/tool/tests/test_detector.py

CogSciUOS/DeepLearningToolbox

bf07578b9486d8c48e25df357bc4b9963b513b46

[ "MIT" ]

null

from unittest import TestCase from dltb.tool import Tool from dltb.tool.detector import Detections from dltb.base.image import Image class TestDetector(TestCase): def setUp(self): self.detector = Tool['haar'] self.detector.prepare() # self.image = imread('examples/reservoir-dogs.jpg') self.image = Image.as_data('examples/reservoir-dogs.jpg') def test_detect1(self): detections = self.detector.detect(self.image) self.assertTrue(isinstance(detections, Detections)) # self.datasource.unprepare() # self.assertFalse(self.datasource.prepared) self.assertEqual(len(detections), 6) def test_detect2(self): pass # self.datasource.prepare() # self.assertEqual(len(self.datasource), 2330)

29.481481

65

0.679648

92

796

5.847826

0.423913

0.104089

0.04461

0.089219

0

0.011111

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796

26

66

30.615385

0.842857

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0

null

0

null

0

1

0

1

0

2

5af814eaaf5e5ef51807162ca3f9fb884b962ee7

813

py

Python

cpp/src/examples/pbe_keyset.py

nawien-sharma/keyczar

c55563bbd70f4b6fefc7444e296aab9894475f9a

[ "Apache-2.0" ]

null

cpp/src/examples/pbe_keyset.py

nawien-sharma/keyczar

c55563bbd70f4b6fefc7444e296aab9894475f9a

[ "Apache-2.0" ]

null

cpp/src/examples/pbe_keyset.py

nawien-sharma/keyczar

c55563bbd70f4b6fefc7444e296aab9894475f9a

[ "Apache-2.0" ]

1

2021-04-13T05:05:30.000Z

# Encrypts and decrypts a short message from a PBE encrypted JSON key set. # # Example: python pbe_keyset.py ~/my-pbe-json-aes-encrypted password # import os import sys import keyczar def Encrypt(crypted_path, password): if not os.path.exists(crypted_path): return input = 'Secret message' reader = keyczar.KeysetPBEJSONFileReader(crypted_path, password) crypter = keyczar.Crypter.Read(reader) ciphertext = crypter.Encrypt(input) print 'plaintext:', input print 'ciphertext:', ciphertext decrypted = crypter.Decrypt(ciphertext) assert decrypted == input if __name__ == '__main__': if (len(sys.argv) != 3): print >> sys.stderr, "Provide a valid JSON key set path and a password as arguments." sys.exit(1) Encrypt(sys.argv[1], sys.argv[2])

26.225806

93

0.694957

107

813

5.168224

0.523364

0.059675

0.036166

0

0.006154

0.200492

813

30

94

27.1

0.844615

0.170972

0

0.156951

0

0.052632

0

null

0.157895

null

0.157895

0

null

0

null

0

1

0

1

0

2

5afa767a6c14464cc2c5b0783f37229c88180e39

298

py

Python

events/views.py

austinprog/hsvdotbeer

2979a2b0b105b85d0865c6771bfcb7debb98b3e8

[ "Apache-2.0" ]

null

events/views.py

austinprog/hsvdotbeer

2979a2b0b105b85d0865c6771bfcb7debb98b3e8

[ "Apache-2.0" ]

6

2020-08-03T09:50:01.000Z

2021-06-10T18:17:28.000Z

events/views.py

austinprog/hsvdotbeer

2979a2b0b105b85d0865c6771bfcb7debb98b3e8

[ "Apache-2.0" ]

null

from rest_framework.viewsets import ModelViewSet from . import models from . import serializers class EventViewSet(ModelViewSet): serializer_class = serializers.EventSerializer queryset = models.Event.objects.select_related('venue').order_by( 'start_time', 'venue__name', )

22.923077

69

0.758389

32

298

6.84375

0.71875

0.091324

0

0.157718

298

12

70

24.833333

0.87251

0

0.087248

0

1

0

false

0

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0

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0

null

0

null

0

1

0

1

0

2

850c52ae07fd7b9cb26557ccb87770e03a7ec740

1,079

py

Python

src/modules/dropout.py

HuicheolMoon/P4_ModelOptimization

63a1615068de16e75514be0af4a317ab44ab9eb3

[ "MIT" ]

null

src/modules/dropout.py

HuicheolMoon/P4_ModelOptimization

63a1615068de16e75514be0af4a317ab44ab9eb3

[ "MIT" ]

null

src/modules/dropout.py

HuicheolMoon/P4_ModelOptimization

63a1615068de16e75514be0af4a317ab44ab9eb3

[ "MIT" ]

null

# Dropout Module import torch from torch import nn as nn from src.modules.base_generator import GeneratorAbstract class Dropout(nn.Module): """Dropout module.""" def __init__(self, prob: int =0.5): """ Args: prob: dropout probability """ super().__init__() self.dropout = nn.Dropout(prob) def forward(self, x: torch.Tensor) -> torch.Tensor: """Forward.""" return self.dropout(x) class DropoutGenerator(GeneratorAbstract): """Dropout module generator for parsing.""" def __init__(self, *args, **kwargs): """Initailize.""" super().__init__(*args, **kwargs) @property def out_channel(self) -> int: """Get out channel size.""" return self.in_channel def __call__(self, repeat: int = 1): p = self.args[0] if repeat > 1: module = [] for i in range(repeat): module.append(Dropout(prob=p)) else: module = Dropout(prob=p) return self._get_module(module)

23.977778

56

0.567192

120

1,079

4.891667

0.391667

0.06644

0.037479

0

0.006667

0.304912

1,079

44

57

24.522727

0.776

0.137164

0

1

0.208333

false

0

0.125

0

0.541667

0

null

0

null

0

1

0

1

0

2

8511df590273fd306cf7ac94104ea0f8adb88c19

410

py

Python

tutorial/list.py

Dannyps/fpai-datamining

98d18aa697f7a13ba790423eba6e6c6b71a32a56

[ "Unlicense" ]

null

tutorial/list.py

Dannyps/fpai-datamining

98d18aa697f7a13ba790423eba6e6c6b71a32a56

[ "Unlicense" ]

null

tutorial/list.py

Dannyps/fpai-datamining

98d18aa697f7a13ba790423eba6e6c6b71a32a56

[ "Unlicense" ]

null

test = [11.0, "Alice has a cat", 12, 4, "5"] print("len(test) = " + str(len(test))) print("test[1] = " + str(test[1])) print("test[3:6] = " + str(test[3:6])) print("test[1:6:2] = " + str(test[1:6:2])) print("test[:6] = " + str(test[:6])) print("test[-2] = " + str(test[-2])) test.append(121) test2 = test + [1, 2, 3] print("len(test2) = " + str(len(test2))) test2[0] = "Lodz" test2[6] = 77 print(test2)

19.52381

44

0.531707

74

410

2.945946

0.297297

0.206422

0.091743

0.06422

0

0.113703

0.163415

410

20

45

20.5

0.521866

0

0.25122

0

1

0

false

0

0.615385

0

null

1

0

null

0

1

0

2

851427682ec24633568e4a0bcaca14c5a15c7093

7,023

py

Python

tests/test.py

YegorDB/CTHPoker

3e49e85ca00c47589f7ccc8b47d68caa4c1ce649

[ "Apache-2.0" ]

null

tests/test.py

YegorDB/CTHPoker

3e49e85ca00c47589f7ccc8b47d68caa4c1ce649

[ "Apache-2.0" ]

null

tests/test.py

YegorDB/CTHPoker

3e49e85ca00c47589f7ccc8b47d68caa4c1ce649

[ "Apache-2.0" ]

null

# Copyright 2019 Yegor Bitensky # 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 pytest from cthpoker import findCombo, findRatioCombo def get_parameters(func): def wrap(self, values): return func(self, **values) return wrap class TestFindCombo: variants = [ {'cards': [144, 134, 124, 114, 104], 'value': [9, 14]}, {'cards': [134, 122, 124, 114, 104, 94], 'value': [9, 13]}, {'cards': [124, 114, 101, 104, 94, 84, 21], 'value': [9, 12]}, {'cards': [123, 114, 104, 94, 84, 73, 74], 'value': [9, 11]}, {'cards': [141, 104, 94, 84, 74, 64, 52], 'value': [9, 10]}, {'cards': [94, 84, 74, 73, 64, 52, 54], 'value': [9, 9]}, {'cards': [121, 84, 74, 64, 54, 44, 23], 'value': [9, 8]}, {'cards': [143, 74, 64, 54, 44, 34, 23], 'value': [9, 7]}, {'cards': [114, 104, 64, 54, 44, 34, 24], 'value': [9, 6]}, {'cards': [141, 144, 62, 54, 44, 34, 24], 'value': [9, 5]}, {'cards': [144, 142, 143, 141], 'value': [8, 14]}, {'cards': [134, 144, 132, 133, 131], 'value': [8, 13, 14]}, {'cards': [124, 134, 144, 122, 123, 121], 'value': [8, 12, 14]}, {'cards': [114, 134, 112, 133, 113, 111], 'value': [8, 11, 13]}, {'cards': [104, 144, 53, 102, 103, 101], 'value': [8, 10, 14]}, {'cards': [144, 142, 143, 131, 133], 'value': [7, 14, 13]}, {'cards': [144, 131, 133, 124, 123, 122], 'value': [7, 12, 13]}, {'cards': [131, 114, 113, 133, 112, 134, 53], 'value': [7, 13, 11]}, {'cards': [101, 114, 113, 103, 83, 104, 82], 'value': [7, 10, 11]}, {'cards': [114, 51, 112, 92, 113, 54, 52], 'value': [7, 11, 5]}, {'cards': [144, 134, 124, 114, 94], 'value': [6, 14, 13, 12, 11, 9]}, {'cards': [143, 134, 104, 94, 54, 24], 'value': [6, 13, 10, 9, 5, 2]}, {'cards': [132, 104, 94, 73, 74, 54, 24], 'value': [6, 10, 9, 7, 5, 2]}, {'cards': [94, 84, 74, 54, 44, 34, 24], 'value': [6, 9, 8, 7, 5, 4]}, {'cards': [123, 74, 54, 44, 34, 24, 21], 'value': [6, 7, 5, 4, 3, 2]}, {'cards': [144, 133, 121, 112, 103], 'value': [5, 14]}, {'cards': [121, 113, 104, 103, 94, 81], 'value': [5, 12]}, {'cards': [104, 94, 81, 72, 64, 54, 23], 'value': [5, 10]}, {'cards': [81, 72, 63, 54, 41, 32, 23], 'value': [5, 8]}, {'cards': [114, 113, 64, 51, 42, 31, 23], 'value': [5, 6]}, {'cards': [141, 51, 42, 31, 23], 'value': [5, 5]}, {'cards': [144, 143, 141], 'value': [4, 14]}, {'cards': [134, 133, 131, 42], 'value': [4, 13, 4]}, {'cards': [142, 124, 123, 121, 72], 'value': [4, 12, 14, 7]}, {'cards': [132, 122, 114, 113, 111, 92], 'value': [4, 11, 13, 12]}, {'cards': [74, 52, 42, 34, 33, 31, 22], 'value': [4, 3, 7, 5]}, {'cards': [144, 143, 131, 133], 'value': [3, 14, 13]}, {'cards': [142, 131, 133, 123, 122], 'value': [3, 13, 12, 14]}, {'cards': [132, 111, 113, 101, 93, 92], 'value': [3, 11, 9, 13]}, {'cards': [101, 104, 93, 92, 74, 51, 53], 'value': [3, 10, 9, 7]}, {'cards': [51, 53, 43, 42, 31, 34, 24], 'value': [3, 5, 4, 3]}, {'cards': [144, 143], 'value': [2, 14]}, {'cards': [144, 132, 133], 'value': [2, 13, 14]}, {'cards': [134, 122, 123, 112], 'value': [2, 12, 13, 11]}, {'cards': [134, 122, 113, 112, 104], 'value': [2, 11, 13, 12, 10]}, {'cards': [143, 113, 104, 83, 81, 63], 'value': [2, 8, 14, 11, 10]}, {'cards': [131, 122, 113, 104, 63, 51, 53], 'value': [2, 5, 13, 12, 11]}, {'cards': [44], 'value': [1, 4]}, {'cards': [141, 72], 'value': [1, 14, 7]}, {'cards': [122, 53, 32], 'value': [1, 12, 5, 3]}, {'cards': [112, 103, 91, 84], 'value': [1, 11, 10, 9, 8]}, {'cards': [134, 102, 83, 63, 21], 'value': [1, 13, 10, 8, 6, 2]}, {'cards': [104, 93, 72, 54, 43, 31], 'value': [1, 10, 9, 7, 5, 4]}, {'cards': [134, 122, 94, 73, 52, 41, 23], 'value': [1, 13, 12, 9, 7, 5]}, ] @pytest.mark.parametrize("values", variants) @get_parameters def test_all_values(self, cards, value): assert findCombo(cards) == value class TestFindRatioCombo: variants = [ {'cards': [114, 104, 94, 84, 21, 1124, 1101], 'value': [9, 12], 'kind': 2}, {'cards': [104, 94, 84, 74, 64, 1141, 1051], 'value': [9, 10], 'kind': 0}, {'cards': [143, 21, 31, 41, 51, 1141, 1082], 'value': [9, 5], 'kind': 2}, {'cards': [141, 21, 31, 41, 51, 1142, 1134], 'value': [9, 5], 'kind': 0}, {'cards': [134, 132, 133, 131, 74, 1144, 1022], 'value': [8, 13, 14], 'kind': 0}, {'cards': [134, 144, 123, 121, 22, 1124, 1122], 'value': [8, 12, 14], 'kind': 2}, {'cards': [112, 132, 113, 134, 52, 1131, 1114], 'value': [7, 13, 11], 'kind': 2}, {'cards': [114, 112, 102, 104, 82, 1101, 1083], 'value': [7, 10, 11], 'kind': 1}, {'cards': [114, 51, 112, 54, 52, 1092, 1134], 'value': [7, 5, 11], 'kind': 0}, {'cards': [74, 54, 44, 34, 24, 1094, 1084], 'value': [6, 9, 8, 7, 5, 4], 'kind': 2}, {'cards': [74, 54, 44, 34, 24, 1123, 1021], 'value': [6, 7, 5, 4, 3, 2], 'kind': 0}, {'cards': [63, 54, 41, 32, 23, 1081, 1072], 'value': [5, 8], 'kind': 2}, {'cards': [64, 51, 42, 31, 23, 1114, 1113], 'value': [5, 6], 'kind': 0}, {'cards': [142, 24, 31, 41, 53, 1144, 1101], 'value': [5, 5], 'kind': 2}, {'cards': [142, 24, 31, 41, 53, 1104, 1101], 'value': [5, 5], 'kind': 0}, {'cards': [122, 113, 111, 92, 52, 1132, 1114], 'value': [4, 11, 13, 12], 'kind': 2}, {'cards': [42, 34, 33, 31, 22, 1074, 1052], 'value': [4, 3, 7, 5], 'kind': 0}, {'cards': [113, 132, 101, 92, 34, 1111, 1093], 'value': [3, 11, 9, 13], 'kind': 2}, {'cards': [104, 93, 92, 74, 53, 1101, 1051], 'value': [3, 10, 9, 7], 'kind': 1}, {'cards': [51, 53, 43, 42, 31, 1034, 1024], 'value': [3, 5, 4, 3], 'kind': 0}, {'cards': [143, 112, 104, 63, 43, 1083, 1081], 'value': [2, 8, 14, 11, 10], 'kind': 2}, {'cards': [112, 104, 63, 51, 53, 1131, 1123], 'value': [2, 5, 13, 12, 11], 'kind': 0}, {'cards': [134, 122, 94, 73, 23, 1052, 1041], 'value': [1, 13, 12, 9, 7, 5], 'kind': 2}, {'cards': [141, 104, 93, 72, 54, 1043, 1031], 'value': [1, 14, 10, 9, 7, 5], 'kind': 0}, ] @pytest.mark.parametrize("values", variants) @get_parameters def test_all_values(self, cards, value, kind): assert findRatioCombo(cards) == [value, kind]

57.097561

96

0.477431

1,099

7,023

3.044586

0.166515

0.026898

0.032875

0.014345

0.222056

0.127316

0.067543

0.046623

0

0.314176

0.256728

7,023

122

97

57.565574

0.32682

0.078457

0

0.061224

0

0.13744

0

0.020408

1

0.040816

false

0

0.020408

0.010204

0.122449

0

null

0

1

0

1

0

null

0

2

851639da53c56a4337a1ff09a45417f2f39ee42c

61

py

Python

cbbuild-manifest/version.py

ceejatec/python-couchbase-commons

ad74fc3de98eeaadf0ea38da86639d07f92b0945

[ "Apache-2.0" ]

null

cbbuild-manifest/version.py

ceejatec/python-couchbase-commons

ad74fc3de98eeaadf0ea38da86639d07f92b0945

[ "Apache-2.0" ]

null

cbbuild-manifest/version.py

ceejatec/python-couchbase-commons

ad74fc3de98eeaadf0ea38da86639d07f92b0945

[ "Apache-2.0" ]

1

2020-02-18T08:10:51.000Z

# Update this file for version changes __version__ = '0.5.3'

20.333333

38

0.737705

10

61

4.1

0.9

0

0.058824

0.163934

61

2

39

30.5

0.745098

0.590164

0

0.217391

0

1

0

false

0

1

0

null

0

1

0

null

0

2

851e3aedc187910bb5e2a11f8eaab604baa8b396

634

py

Python

dimensigon/network/auth.py

dimensigon/dimensigon

079d7c91a66e10f13510d89844fbadb27e005b40

[ "Apache-2.0" ]

2

2020-11-20T10:27:14.000Z

2021-02-21T13:57:56.000Z

dimensigon/network/auth.py

dimensigon/dimensigon

079d7c91a66e10f13510d89844fbadb27e005b40

[ "Apache-2.0" ]

null

dimensigon/network/auth.py

dimensigon/dimensigon

079d7c91a66e10f13510d89844fbadb27e005b40

[ "Apache-2.0" ]

null

from requests.auth import AuthBase class HTTPBearerAuth(AuthBase): def __init__(self, token): self.token = token def __eq__(self, other): return self.token == getattr(other, 'token', None) def __ne__(self, other): return not self == other def __call__(self, r): if hasattr(r, 'headers'): r.headers.update(self.header) else: r['headers'].update(self.header) r.pop('auth', None) return r @property def header(self): return {'Authorization': str(self)} def __str__(self): return 'Bearer ' + self.token

22.642857

58

0.578864

74

634

4.689189

0.418919

0.103746

0.086455

0.103746

0.138329

0

0.299685

634

27

59

23.481481

0.781532

0

0.067823

0

1

0.3

false

0

0.05

0.2

0.65

0

null

0

null

0

1

0

1

0

2

85246a13fd70ce31f59ef368d91ed8a4a6677db5

236

py

Python

pygame/song with pygame.py

vitorhugo1207/SomethingsInPython

505a7e906cd391a9c6f820900c8ac8b7f456a5dc

[ "MIT" ]

null

pygame/song with pygame.py

vitorhugo1207/SomethingsInPython

505a7e906cd391a9c6f820900c8ac8b7f456a5dc

[ "MIT" ]

null

pygame/song with pygame.py

vitorhugo1207/SomethingsInPython

505a7e906cd391a9c6f820900c8ac8b7f456a5dc

[ "MIT" ]

null

import pygame text = input('Nome da musica: ') pygame.init() pygame.mixer.music.load(text) pygame.mixer.music.play() print('S para parar.') text2 = input('-> ') if text2 == 'S': pygame.mixer.stop() else: pygame.event.wait()

14.75

32

0.652542

34

236

4.529412

0.647059

0.214286

0.207792

0

0.01005

0.15678

236

15

33

15.733333

0.763819

0

0.139831

0

1

0

false

0

0.090909

0

0.090909

0

null

1

0

null

0

2

8529f954b36e705a8589749f2d20932ba107fc8d

1,351

py

Python

pfrf_example/pfrf_example/controller/person_controller.py

problemfighter/pfms-example

97e1ea951a3ae34b4df88da791e00857b5c433e9

[ "Apache-2.0" ]

2

2021-07-16T21:34:26.000Z

2021-07-16T21:35:11.000Z

pfrf_example/pfrf_example/controller/person_controller.py

problemfighter/pfms-example

97e1ea951a3ae34b4df88da791e00857b5c433e9

[ "Apache-2.0" ]

null

pfrf_example/pfrf_example/controller/person_controller.py

problemfighter/pfms-example

97e1ea951a3ae34b4df88da791e00857b5c433e9

[ "Apache-2.0" ]

null

from flask import Blueprint from pfms.swagger.pfms_swagger_decorator import pfms_create, pfms_details, pfms_pagination_sort_search_list, pfms_restore, pfms_delete from pfrf_example.dto.person_dto import PersonCreateDto, PersonDetailsDto, PersonUpdateDto from pfrf_example.service.person_service import PersonService person_controller = Blueprint("person_controller", __name__, url_prefix="/api/v1/person") person_service = PersonService() @person_controller.route("/create", methods=['POST']) @pfms_create(request_body=PersonCreateDto) def create(): return person_service.create() @person_controller.route("/details/<int:id>", methods=['GET']) @pfms_details(response_obj=PersonDetailsDto) def details(id: int): return person_service.details(id) @person_controller.route("/update", methods=['POST']) @pfms_create(request_body=PersonUpdateDto) def update(): return person_service.update() @person_controller.route("/delete/<int:id>", methods=['DELETE']) @pfms_delete() def delete(id: int): return person_service.delete(id) @person_controller.route("/restore/<int:id>", methods=['GET']) @pfms_restore() def restore(id: int): return person_service.restore(id) @person_controller.route("/list", methods=['GET']) @pfms_pagination_sort_search_list(response_obj=PersonDetailsDto) def list(): return person_service.list()

30.022222

134

0.783864

170

1,351

5.952941

0.252941

0.102767

0.124506

0.050395

0.227273

0.063241

0

0.000808

0.083642

1,351

44

135

30.704545

0.81664

0

0.091044

0

1

0.2

false

0

0.133333

0.2

0.533333

0.066667

0

null

0

null

0

1

0

2

51b0a533b3ef7b0274f3b039ee56940b42536735

506

py

Python

tests/test_oscillator.py

borismarin/org.geppetto.model.apigen

ed099ac64301de11570779e5e294b7a210a0e0b2

[ "MIT" ]

null

tests/test_oscillator.py

borismarin/org.geppetto.model.apigen

ed099ac64301de11570779e5e294b7a210a0e0b2

[ "MIT" ]

null

tests/test_oscillator.py

borismarin/org.geppetto.model.apigen

ed099ac64301de11570779e5e294b7a210a0e0b2

[ "MIT" ]

null

from gpt_oscillator import oscillator_lib as lib def test_dynamic_types(): assert(type(lib.oscillator) is type) osc = lib.oscillator("o_id", "o_name") assert(osc.id == 'o_id') def test_default_ids(): o2 = lib.oscillator() o3 = lib.oscillator() assert(o2.id == 'oscillator_0') assert(o3.id == 'oscillator_1') def test_type_inheritance(): so = lib.aSpecialOcillator() assert(isinstance(so, lib.aSpecialOcillator)) # d'uh! assert(isinstance(so, lib.oscillator))

24.095238

58

0.681818

69

506

4.811594

0.42029

0.195783

0.13253

0.126506

0

0.014423

0.177866

506

20

59

25.3

0.783654

0.009881

0

0.076152

0

0.428571

1

0.214286

false

0

0.071429

0

0.285714

0

null

0

null

0

1

0

1

0

2

51b652b8422d3f9d57c3800b5be4e37b3c91f691

2,992

py

Python

src/web_encoder/exceptions.py

cesarmerjan/web_encoder

7a1bbde6a1c1aceede433e105175f20d17629313

[ "MIT" ]

null

src/web_encoder/exceptions.py

cesarmerjan/web_encoder

7a1bbde6a1c1aceede433e105175f20d17629313

[ "MIT" ]

null

src/web_encoder/exceptions.py

cesarmerjan/web_encoder

7a1bbde6a1c1aceede433e105175f20d17629313

[ "MIT" ]

null

class WebEncoderException(Exception): pass class InvalidEncodingErrors(WebEncoderException): """Exception raised for errors in the input value of encoding_errors attribute of WebEncoder class. Args: message: explanation of the error """ def __init__(self, message=None): self.message = ( message or "Invalid encoding_errors value. It should be 'strict', 'ignore', 'replace' or 'xmlcharrefreplace'." ) super().__init__(self.message) class InvalidStringType(WebEncoderException): """Exception raised for errors in the input value of _string into _string_to_bytes method of WebEncoder class. Args: message: explanation of the error """ def __init__(self, message=None): self.message = message or "The _string need to be str type." super().__init__(self.message) class InvalidBytesType(WebEncoderException): """Exception raised for errors in the input value of _bytes into methods of WebEncoder class. Args: message: explanation of the error """ def __init__(self, message=None): self.message = message or "The _bytes need to be bytes type." super().__init__(self.message) class InvalidDataType(WebEncoderException): """Exception raised for errors in the input value of data into encode method of WebEncoder class. Args: message: explanation of the error """ def __init__(self, message=None): self.message = message or "The data need to be str type." super().__init__(self.message) class InvalidEncodedDataType(WebEncoderException): """Exception raised for errors in the input value of encoded_data into decode method of WebEncoder class. Args: message: explanation of the error """ def __init__(self, message=None): self.message = message or "The encoded_data need to be str type." super().__init__(self.message) class DataDecodeError(WebEncoderException): """Exception raised for data decoding error in _bytes_to_string of WebEncoder class. Args: message: explanation of the error """ def __init__(self, message=None): self.message = message or "Could not decode the message." super().__init__(self.message) class CannotBeCompressed(WebEncoderException): """Exception raised for errors in the _compress_data method of WebEncoder class. Args: message: explanation of the error """ def __init__(self, message=None): self.message = message or "The data cannot be compressed." super().__init__(self.message) class CannotBeDecompressed(WebEncoderException): """Exception raised for errors in the _decompress_data method of WebEncoder class. Args: message: explanation of the error """ def __init__(self, message=None): self.message = message or "The data cannot be decompressed." super().__init__(self.message)

29.333333

114

0.688168

354

2,992

5.584746

0.175141

0.133536

0.121396

0.149722

0.726353

0.688417

0.673748

0.62519

0

0.231618

2,992

101

115

29.623762

0.859939

0.365307

0

0.432432

0

0.18187

0

1

0.216216

false

0.027027

0

0.459459

0

null

0

1

0

null

0

1

0

2

51be679d682fbf8eb496c5c3820e7d6843d898a5

380

py

Python

apps/reputation/serializers.py

macdaliot/exist

65244f79c602c5a00c3ea6a7eef512ce9c21e60a

[ "MIT" ]

159

2019-03-15T10:46:19.000Z

2022-03-12T09:19:31.000Z

apps/reputation/serializers.py

macdaliot/exist

65244f79c602c5a00c3ea6a7eef512ce9c21e60a

[ "MIT" ]

6

2019-03-16T12:51:24.000Z

2020-07-09T02:25:42.000Z

apps/reputation/serializers.py

macdaliot/exist

65244f79c602c5a00c3ea6a7eef512ce9c21e60a

[ "MIT" ]

36

2019-03-16T10:37:14.000Z

2021-11-14T21:04:18.000Z

from rest_framework import serializers from .models import blacklist class blSerializer(serializers.ModelSerializer): source = serializers.CharField(source='get_source_display') class Meta: model = blacklist fields = ('__all__') class sourceSerializer(serializers.ModelSerializer): class Meta: model = blacklist fields = ('SOURCES',)

27.142857

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0.715789

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380

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0.196226

0.10566

0.173585

0.218868

0

0.202632

380

13

64

29.230769

0.874587

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0.363636

0

0.084211

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1

0

false

0

0.181818

0

0.636364

0

null

0

1

0

null

0

1

0

2

51bf679a93edad177bbce42cdd412836a80f29c2

2,042

py

Python

run.py

ShawnHXH/GNN-CCA

598d5bb13e445b864e728cc2c9e1af38783a2319

[ "MIT" ]

null

run.py

ShawnHXH/GNN-CCA

598d5bb13e445b864e728cc2c9e1af38783a2319

[ "MIT" ]

null

run.py

ShawnHXH/GNN-CCA

598d5bb13e445b864e728cc2c9e1af38783a2319

[ "MIT" ]

null

import argparse from tools.trainer import Trainer def make_parser(): parser = argparse.ArgumentParser() # training config parser.add_argument("--train", default=False, action="store_true") parser.add_argument("--epochs", type=int, default=100, help="training epochs") parser.add_argument("--batch-size", type=int, default=16, help="batch size for training") parser.add_argument("--eval-batch-size", type=int, default=64, help="batch size for validating") parser.add_argument("-s", "--max-passing-steps", type=int, default=4, help="maximum message passing steps in GNN for MPN") # testing config parser.add_argument("--test", default=False, action="store_true") parser.add_argument("--ckpt", type=str, help="path to test model") parser.add_argument("--visualize", default=False, action="store_true", help="visualize the testing results") # common config parser.add_argument("--device", type=str, default="cuda", help="device for training") parser.add_argument("--output", type=str, default="./ckpt", help="output dir for training") # reid feature extractor parser.add_argument("--reid-name", type=str, default="osnet_ain_x1_0", help="the name of feature extractor model") parser.add_argument("--reid-path", type=str, default="ckpt/osnet_ain_ms_d_c.pth.tar", help="the path to feature extractor model") # dataset parser.add_argument("--epfl", default=False, action="store_true", help="using EPFL dataset for training") parser.add_argument("--seq-name", type=str, nargs="+", help="using specific sequences in dataset, 'all' means using all of them") return parser if __name__ == '__main__': args = make_parser().parse_args() main = Trainer(args) if args.train: main.train() elif args.test: main.test() else: raise ValueError("Please assign a state in (train, test)")

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0.648384

261

2,042

4.934866

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0.097826

0.184783

0.071429

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0.11646

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0

0.006219

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2,042

45

101

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0

null

0

1

0

null

0

1

0

2

51c8ccc28d7cc3aedfe256bc301ddc9a177e5fc2

376

py

Python

src/901_1000/0922_sort-array-by-parity-ii/sort-array-by-parity-ii.py

himichael/LeetCode

d54f48e785af3d47a2a67a95fd3343d2b23f8ae5

[ "Apache-2.0" ]

1

2019-12-18T06:08:47.000Z

src/901_1000/0922_sort-array-by-parity-ii/sort-array-by-parity-ii.py

himichael/LeetCode

d54f48e785af3d47a2a67a95fd3343d2b23f8ae5

[ "Apache-2.0" ]

1

2019-05-18T09:35:22.000Z

src/901_1000/0922_sort-array-by-parity-ii/sort-array-by-parity-ii.py

himichael/LeetCode

d54f48e785af3d47a2a67a95fd3343d2b23f8ae5

[ "Apache-2.0" ]

null

class Solution(object): def sortArrayByParityII(self, A): if not A: return [] n = len(A) res = [0] * n i = 0 for x in A: if x%2==0: res[i] = x i += 2 i = 1 for x in A: if x%2==1: res[i] = x i += 2 return res

22.117647

37

0.316489

50

376

2.4

0.42

0.075

0.1

0.116667

0.3

0.183333

0

0.056604

0.577128

376

17

38

22.117647

0.691824

0

0.352941

0

null

0

null

0

null

0

1

0

null

0

1

0

2

51cb3b7c3ae579225f507efca28cc4220ea99cfb

681

py

Python

corshinesubd.py

Corshine-Official/Eztools

9278ef4916172505895071c4fc82ee68f4b92e18

[ "MIT" ]

1

2020-05-02T17:14:46.000Z

corshinesubd.py

Corshine-Official/Eztools

9278ef4916172505895071c4fc82ee68f4b92e18

[ "MIT" ]

null

corshinesubd.py

Corshine-Official/Eztools

9278ef4916172505895071c4fc82ee68f4b92e18

[ "MIT" ]

null

################################################## ## / ___/ _ \| _ \/ ___|| | | |_ _| \ | | ____|## ##| | | | | | |_) \___ \| |_| || || \| | _| ## ##| |__| |_| | _ < ___) | _ || || |\ | |___ ## ## \____\___/|_| \_\____/|_| |_|___|_| \_|_____|## ################################################## #Usage: python3 corshinesubd.py (domain) import requests import sys sub_list = open("wordlistsubd.txt").read() subs = sub_list.splitlines() for sub in subs: url_to_check = f"http://{sub}.{sys.argv[1]}" try: requests.get(url_to_check) except requests.ConnectionError: pass else: print("Valid domain: ",url_to_check)

25.222222

50

0.433186

49

681

4.714286

0.673469

0.064935

0.12987

0

0.003788

0.22467

681

26

51

26.192308

0.433712

0.325991

0

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0.166667

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0.166667

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0

null

0

1

0

null

0

1

0

2

51d84e96d0312983385d2c010401ad3d5ca51c3c

390

py

Python

osmaxx/job_progress/views.py

tyrasd/osmaxx

da4454083d17b2ef8b0623cad62e39992b6bd52a

[ "MIT" ]

27

2015-03-30T14:17:26.000Z

2022-02-19T17:30:44.000Z

osmaxx/job_progress/views.py

tyrasd/osmaxx

da4454083d17b2ef8b0623cad62e39992b6bd52a

[ "MIT" ]

483

2015-03-09T16:58:03.000Z

2022-03-14T09:29:06.000Z

osmaxx/job_progress/views.py

tyrasd/osmaxx

da4454083d17b2ef8b0623cad62e39992b6bd52a

[ "MIT" ]

6

2015-04-07T07:38:30.000Z

2020-04-01T12:45:53.000Z

from django.http import HttpResponse from django.shortcuts import get_object_or_404 from osmaxx.excerptexport.models import Export def tracker(request, export_id): export = get_object_or_404(Export, pk=export_id) export.set_and_handle_new_status(request.GET['status'], incoming_request=request) response = HttpResponse('') response.status_code = 200 return response

27.857143

85

0.787179

53

390

5.528302

0.54717

0.068259

0.075085

0.095563

0

0.026706

0.135897

390

13

86

30

0.84273

0

0.015385

0

1

0.111111

false

0

0.333333

0

0.555556

0

null

0

null

0

1

0

1

0

2

51e43ed69446545aaa1166e7327dd9ff90d24b54

191

py

Python

okta/models/app/AppUserProfile.py

xmercury-qb/okta-sdk-python

a668a963b13fc61177b36c5438c6ec5fa6f17c4e

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

1

2020-06-19T18:54:00.000Z

okta/models/app/AppUserProfile.py

xmercury-qb/okta-sdk-python

a668a963b13fc61177b36c5438c6ec5fa6f17c4e

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

3

2018-10-09T22:14:33.000Z

2018-10-09T23:10:40.000Z

okta/models/app/AppUserProfile.py

xmercury-qb/okta-sdk-python

a668a963b13fc61177b36c5438c6ec5fa6f17c4e

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

2

2018-11-08T19:32:46.000Z

2021-03-30T06:35:48.000Z

class AppUserProfile: types = { 'username': str, 'password': str } def __init__(self): self.username = None # str self.password = None # str

14.692308

35

0.518325

18

191

5.277778

0.555556

0.147368

0

0.376963

191

12

36

15.916667

0.798319

0.036649

0

0.088398

0

1

0.125

false

0.25

0

0.375

0

1

0

null

0

null

0

1

0

2

51e6e07b849141bd9def2d517b1954741683241d

122

py

Python

hydra/__init__.py

Hydraverse/hypy

7f276975747ba86296044526acc090e540ee77cc

[ "Apache-2.0" ]

3

2021-11-18T19:04:10.000Z

2022-01-26T04:53:51.000Z

hydra/__init__.py

Hydraverse/hypy

7f276975747ba86296044526acc090e540ee77cc

[ "Apache-2.0" ]

null

hydra/__init__.py

Hydraverse/hypy

7f276975747ba86296044526acc090e540ee77cc

[ "Apache-2.0" ]

null

"""Hydra Library Tools & Applications. """ __all__ = ( "app", "hy", "log", "rpc", "test", "util" ) VERSION = "2.6.5"

15.25

45

0.532787

15

122

4.066667

1

0

0.030612

0.196721

122

7

46

17.428571

0.591837

0.286885

0

0.3

0

1

0

false

0

1

0

null

0

1

0

null

0

2

51ea02eff58b5c67bd9880c1554ad4af45dd3227

569

py

Python

test/SpeedTest.py

prajwal309/TierraCrossSection

4b8896540616ec3f46322ea4c40df9f2b4774a44

[ "MIT" ]

null

test/SpeedTest.py

prajwal309/TierraCrossSection

4b8896540616ec3f46322ea4c40df9f2b4774a44

[ "MIT" ]

null

test/SpeedTest.py

prajwal309/TierraCrossSection

4b8896540616ec3f46322ea4c40df9f2b4774a44

[ "MIT" ]

null

#author:Prajwal Niraula #insitution: MIT import matplotlib.pyplot as plt import time import numpy as np try: from HAPILite import CalcCrossSection except: from ..HAPILite import CalcCrossSection WaveNumber = np.arange(0,10000,0.001) StartTime = time.time() CrossSection = CalcCrossSection("CO2",Temp=1000.0,WN_Grid=WaveNumber, Profile="Doppler", NCORES=-1) StopTime = time.time() print("The time take to calculate the cross-section is %4.3f" %(StopTime - StartTime)) plt.figure() plt.plot(WaveNumber, CrossSection, "k-") plt.title("L-HAPI") plt.show()

21.074074

100

0.745167

79

569

5.35443

0.658228

0.056738

0.085106

0.160757

0

0.038306

0.128295

569

26

101

21.884615

0.814516

0.065026

0

0.133962

0

1

0

false

0

0.3125

0

0.3125

0.0625

0

null

0

1

0

null

0

1

0

2

51f6dd3ff8f3aa50fc8c26af38852974d4425e94

666

py

Python

app/user/schemas.py

joeseggie/resourceidea

aae6120e3ec84f3fc7e1ab1bc833ce37bd06685f

[ "MIT" ]

null

app/user/schemas.py

joeseggie/resourceidea

aae6120e3ec84f3fc7e1ab1bc833ce37bd06685f

[ "MIT" ]

21

2019-01-26T20:39:34.000Z

2019-06-20T10:09:57.000Z

app/user/schemas.py

joeseggie/resourceidea

aae6120e3ec84f3fc7e1ab1bc833ce37bd06685f

[ "MIT" ]

null

from marshmallow import fields from marshmallow import Schema from marshmallow.validate import OneOf class UsersListFilterSchema(Schema): sort_key = fields.String( OneOf(choices=['username', 'email', 'phone_number']), missing='username') sort_order = fields.String(missing='asc') class UsersListSchema(Schema): username = fields.String() email = fields.String() phone_number = fields.String() class UserInputSchema(Schema): username = fields.String() password = fields.String() confirm_password = fields.String() email = fields.String() confirm_email = fields.String() phone_number = fields.String()

25.615385

61

0.707207

71

666

6.535211

0.338028

0.284483

0.109914

0.112069

0.260776

0.172414

0

0.181682

666

25

62

26.64

0.851376

0

0.315789

0

0.054054

0

1

0

false

0.105263

0.157895

0

0.894737

0

null

1

0

null

0

1

0

2

51fc23caa27319c9a7c6759a461e51d312c4b89e

3,335

py

Python

testcases/DPO.py

vaibhav92/op-test-framework

792fa18d3f09fd8c28073074815ff96d373ab96d

[ "Apache-2.0" ]

null

testcases/DPO.py

vaibhav92/op-test-framework

792fa18d3f09fd8c28073074815ff96d373ab96d

[ "Apache-2.0" ]

null

testcases/DPO.py

vaibhav92/op-test-framework

792fa18d3f09fd8c28073074815ff96d373ab96d

[ "Apache-2.0" ]

null

#!/usr/bin/env python2 # IBM_PROLOG_BEGIN_TAG # This is an automatically generated prolog. # # $Source: op-test-framework/testcases/OpTestDPO.py $ # # OpenPOWER Automated Test Project # # Contributors Listed Below - COPYRIGHT 2017 # [+] International Business Machines Corp. # # # 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. # # IBM_PROLOG_END_TAG # @package DPO.py # Delayed Power off testcase is to test OS graceful shutdown request # to be notified from OPAL and OS should process the request. # We will use "ipmitool power soft" command to issue DPO. from common.OpTestConstants import OpTestConstants as BMC_CONST from common.OpTestError import OpTestError import unittest import pexpect import OpTestConfiguration from common.OpTestSystem import OpSystemState class Base(unittest.TestCase): def setUp(self): conf = OpTestConfiguration.conf self.cv_IPMI = conf.ipmi() self.cv_SYSTEM = conf.system() self.cv_HOST = conf.host() self.bmc_type = conf.args.bmc_type self.util = self.cv_SYSTEM.util class DPOSkiroot(Base): def setup_test(self): self.cv_SYSTEM.goto_state(OpSystemState.PETITBOOT_SHELL) self.c = self.cv_SYSTEM.sys_get_ipmi_console() self.cv_SYSTEM.host_console_unique_prompt() self.host = "Skiroot" ## # @brief This will test DPO feature in skiroot and Host # # @return BMC_CONST.FW_SUCCESS or raise OpTestError # def runTest(self): self.setup_test() self.c.run_command("uname -a") if self.host == "Host": self.cv_SYSTEM.load_ipmi_drivers(True) self.c.sol.sendline("ipmitool power soft") try: rc = self.c.sol.expect_exact(["reboot: Power down", "Chassis Power Control: Soft", "Power down", "Invalid command", "Unspecified error", "Could not open device at" ], timeout=120) self.assertIn(rc, [0, 1, 2], "Failed to power down") except pexpect.TIMEOUT: raise OpTestError("Soft power off not happening") rc = self.cv_SYSTEM.sys_wait_for_standby_state() print rc self.cv_SYSTEM.set_state(OpSystemState.OFF) self.cv_SYSTEM.goto_state(OpSystemState.OS) class DPOHost(DPOSkiroot): def setup_test(self): self.host = "Host" self.cv_SYSTEM.goto_state(OpSystemState.OS) self.util.PingFunc(self.cv_HOST.ip, BMC_CONST.PING_RETRY_POWERCYCLE) self.c = self.cv_SYSTEM.sys_get_ipmi_console() self.cv_SYSTEM.host_console_login() self.cv_SYSTEM.host_console_unique_prompt()

35.860215

76

0.651274

426

3,335

4.957746

0.453052

0.045455

0.073864

0.022727

0.158617

0.143466

0.110322

0.053977

0

0.00613

0.266267

3,335

92

77

36.25

0.856968

0.335232

0

0.163265

1

0

0.092117

0

0.020408

0

null

0

0.122449

null

0.020408

0

null

0

1

0

null

0

1

0

2

a40837dd0431a46c20a1dc405b0aa97db458697f

777

py

Python

nsc.py

Lord-Vlad/numeral-system-converter

38bdf11fc8a0816fc57d5f5e6c893fef5707de2c

[ "MIT" ]

null

nsc.py

Lord-Vlad/numeral-system-converter

38bdf11fc8a0816fc57d5f5e6c893fef5707de2c

[ "MIT" ]

null

nsc.py

Lord-Vlad/numeral-system-converter

38bdf11fc8a0816fc57d5f5e6c893fef5707de2c

[ "MIT" ]

null

# Numeral System Converter """ TODO 1. Convert from any system to decimal """ def binary_to_decimal(bin_string:str) -> int: bin_string = str(bin_string).strip() if not bin_string: raise ValueError("Empty string was passed to the function") is_negative = bin_string[0] == "-" if is_negative: bin_string = bin_string[1:] if not all(char in "01" for char in bin_string): raise ValueError("Non-binary value was passed to the function") decimal_number = 0 for char in bin_string: decimal_number = 2 * decimal_number + int(char) return -decimal_number if is_negative else decimal_number def to_dec(num:int) -> int: pass def main(): print(binary_to_decimal(2)) pass if __name__ == "__main__": main()

25.9

71

0.674389

115

777

4.295652

0.4

0.163968

0.060729

0.097166

0.161943

0

0.013333

0.227799

777

30

72

25.9

0.81

0.087516

0

0.1

0

0.132479

0

0.033333

0

1

0.15

false

0.2

0

0.2

0.05

0

null

0

null

0

1

0

1

0

2

cfb6d7eb0802680ca32ee8d7f0c2b6622c37bbe6

135

py

Python

python/problem7.py

jreese/euler

0e2a809620cb02367120c0fbfbf9b419edd42c6e

[ "MIT" ]

1

2015-12-19T09:59:39.000Z

python/problem7.py

jreese/euler

0e2a809620cb02367120c0fbfbf9b419edd42c6e

[ "MIT" ]

null

python/problem7.py

jreese/euler

0e2a809620cb02367120c0fbfbf9b419edd42c6e

[ "MIT" ]

null

from primes import sieve target = 10001 primes = sieve() n = 1 while n <= target: prime = primes.next() n += 1 print prime

10.384615

25

0.622222

20

135

4.2

0.6

0.047619

0

0.071429

0.274074

135

12

26

11.25

0.785714

0

null

0

0.125

null

0.125

1

0

null

0

null

0

1

0

2

cfbad6b4d8d4be1f6071c7e4b841238f41f1f4b7

976

py

Python

env/lib/python3.7/site-packages/indicoio/text/organizations.py

Novandev/gn_api

08b071ae3916bb7a183d61843a2cd09e9fe15c7b

[ "MIT" ]

4

2015-08-20T22:42:19.000Z

2016-03-14T01:28:45.000Z

indicoio/text/organizations.py

mikesperry/IndicoIo-python

caa155b8b31b76df3f86f559ce5324f061a03e40

[ "MIT" ]

null

indicoio/text/organizations.py

mikesperry/IndicoIo-python

caa155b8b31b76df3f86f559ce5324f061a03e40

[ "MIT" ]

null

from ..utils.api import api_handler from ..utils.decorators import detect_batch_decorator @detect_batch_decorator def organizations(text, cloud=None, batch=None, api_key=None, version=2, **kwargs): """ Given input text, returns references to specific organizations found in the text Example usage: .. code-block:: python >>> text = "London Underground's boss Mike Brown warned that the strike ..." >>> entities = indicoio.organizations(text) [ { u'text': "London Underground", u'confidence': 0.8643872141838074, u'position': [0, 18] } ] :param text: The text to be analyzed. :type text: str or unicode :rtype: Dictionary of language probability pairs """ url_params = {"batch": batch, "api_key": api_key, "version": version} return api_handler(text, cloud=cloud, api="organizations", url_params=url_params, **kwargs)

33.655172

96

0.630123

114

976

5.289474

0.570175

0.029851

0.066335

0

0.029126

0.26127

976

28

97

34.857143

0.807212

0.514344

0

0.085562

0

1

0.166667

false

0

0.333333

0

0.666667

0

null

0

null

0

1

0

1

0

2

cfbd2f1a8cd10091dcf8bd4bc792ebe73cbb6d06

1,832

py

Python

indico/migrations/versions/20190118_1213_7ec3949a21c7_use_enum_for_resv_occurrence_state.py

salevajo/indico

6f9cbabc20d1641caea907099388ae2b04965cf8

[ "MIT" ]

1

2018-11-12T21:29:26.000Z

indico/migrations/versions/20190118_1213_7ec3949a21c7_use_enum_for_resv_occurrence_state.py

salevajo/indico

6f9cbabc20d1641caea907099388ae2b04965cf8

[ "MIT" ]

9

2020-09-08T09:25:57.000Z

2022-01-13T02:59:05.000Z

indico/migrations/versions/20190118_1213_7ec3949a21c7_use_enum_for_resv_occurrence_state.py

salevajo/indico

6f9cbabc20d1641caea907099388ae2b04965cf8

[ "MIT" ]

3

2020-07-20T09:09:44.000Z

2020-10-19T00:29:49.000Z

"""Use enum for resv occurrence state Revision ID: 7ec3949a21c7 Revises: 579a36843848 Create Date: 2019-01-18 12:13:42.042274 """ import sqlalchemy as sa from alembic import op from indico.core.db.sqlalchemy import PyIntEnum from indico.modules.rb.models.reservation_occurrences import ReservationOccurrenceState # revision identifiers, used by Alembic. revision = '7ec3949a21c7' down_revision = '579a36843848' branch_labels = None depends_on = None def upgrade(): op.add_column('reservation_occurrences', sa.Column('state', PyIntEnum(ReservationOccurrenceState), nullable=True), schema='roombooking') op.execute(''' UPDATE roombooking.reservation_occurrences SET state = CASE WHEN is_rejected THEN 4 WHEN is_cancelled THEN 3 ELSE 2 END ''') op.alter_column('reservation_occurrences', 'state', nullable=False, schema='roombooking') op.drop_column('reservation_occurrences', 'is_cancelled', schema='roombooking') op.drop_column('reservation_occurrences', 'is_rejected', schema='roombooking') def downgrade(): op.add_column('reservation_occurrences', sa.Column('is_rejected', sa.Boolean(), nullable=True), schema='roombooking') op.add_column('reservation_occurrences', sa.Column('is_cancelled', sa.Boolean(), nullable=True), schema='roombooking') op.execute(''' UPDATE roombooking.reservation_occurrences SET is_cancelled = (state = 3), is_rejected = (state = 4) ''') op.alter_column('reservation_occurrences', 'is_rejected', nullable=False, schema='roombooking') op.alter_column('reservation_occurrences', 'is_cancelled', nullable=False, schema='roombooking') op.drop_column('reservation_occurrences', 'state', schema='roombooking')

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null

1

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null

0

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cfc57d3e1135b16bab03c2bf1964e838746c06d7

11,582

py

Python

doubtlab/reason.py

avvorstenbosch/doubtlab

5691ceb29a615c998f23f989ccae9dd37872031a

[ "MIT" ]

null

doubtlab/reason.py

avvorstenbosch/doubtlab

5691ceb29a615c998f23f989ccae9dd37872031a

[ "MIT" ]

null

doubtlab/reason.py

avvorstenbosch/doubtlab

5691ceb29a615c998f23f989ccae9dd37872031a

[ "MIT" ]

null

import numpy as np from cleanlab.pruning import get_noise_indices class ProbaReason: """ Assign doubt based on low proba-confidence values from a scikit-learn model. Arguments: model: scikit-learn classifier max_proba: maximum probability threshold for doubt assignment Usage: ```python from sklearn.datasets import load_iris from sklearn.linear_model import LogisticRegression from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import ProbaReason X, y = load_iris(return_X_y=True) model = LogisticRegression(max_iter=1_000) model.fit(X, y) doubt = DoubtEnsemble(reason = ProbaReason(model, max_proba=0.55)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model, max_proba=0.55): self.model = model self.max_proba = max_proba def __call__(self, X, y=None): result = self.model.predict_proba(X).max(axis=1) <= self.max_proba return result.astype(np.float16) class RandomReason: """ Assign doubt based on a random value. Arguments: probability: probability of assigning a doubt random_seed: seed for random number generator Usage: ```python from sklearn.datasets import load_iris from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import RandomReason X, y = load_iris(return_X_y=True) doubt = DoubtEnsemble(reason = RandomReason(probability=0.05, random_seed=42)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, probability=0.01, random_seed=42): self.probability = probability self.random_seed = random_seed def __call__(self, X, y=None): np.random.seed(self.random_seed) rvals = np.random.random(size=len(X)) return np.where(rvals < self.probability, rvals, 0) class WrongPredictionReason: """ Assign doubt when the model prediction doesn't match the label. Arguments: model: scikit-learn classifier Usage: ```python from sklearn.datasets import load_iris from sklearn.linear_model import LogisticRegression from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import WrongPredictionReason X, y = load_iris(return_X_y=True) model = LogisticRegression(max_iter=1_000) model.fit(X, y) doubt = DoubtEnsemble(reason = WrongPredictionReason(model=model)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model): self.model = model def __call__(self, X, y): return (self.model.predict(X) != y).astype(np.float16) class LongConfidenceReason: """ Assign doubt when a wrong class gains too much confidence. Arguments: model: scikit-learn classifier threshold: confidence threshold for doubt assignment Usage: ```python from sklearn.datasets import load_iris from sklearn.linear_model import LogisticRegression from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import LongConfidenceReason X, y = load_iris(return_X_y=True) model = LogisticRegression(max_iter=1_000) model.fit(X, y) doubt = DoubtEnsemble(reason = LongConfidenceReason(model=model)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model, threshold=0.2): self.model = model self.threshold = threshold def _max_bad_class_confidence(self, X, y): probas = self.model.predict_proba(X) values = [] for i, proba in enumerate(probas): proba_dict = { self.model.classes_[j]: v for j, v in enumerate(proba) if j != y[i] } values.append(max(proba_dict.values())) return np.array(values) def __call__(self, X, y): confidences = self._max_bad_class_confidence(X, y) return np.where(confidences > self.threshold, confidences, 0) class MarginConfidenceReason: """ Assign doubt when a the difference between the top two most confident classes is too large. Throws an error when there are only two classes. Arguments: model: scikit-learn classifier threshold: confidence threshold for doubt assignment Usage: ```python from sklearn.datasets import load_iris from sklearn.linear_model import LogisticRegression from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import MarginConfidenceReason X, y = load_iris(return_X_y=True) model = LogisticRegression(max_iter=1_000) model.fit(X, y) doubt = DoubtEnsemble(reason = MarginConfidenceReason(model=model)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model, threshold=0.2): self.model = model self.threshold = threshold def _calc_margin(self, probas): sorted = np.sort(probas, axis=1) return sorted[:, -1] - sorted[:, -2] def __call__(self, X, y): probas = self.model.predict_proba(X) margin = self._calc_margin(probas) return np.where(margin > self.threshold, margin, 0) class ShortConfidenceReason: """ Assign doubt when the correct class gains too little confidence. Arguments: model: scikit-learn classifier threshold: confidence threshold for doubt assignment Usage: ```python from sklearn.datasets import load_iris from sklearn.linear_model import LogisticRegression from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import ShortConfidenceReason X, y = load_iris(return_X_y=True) model = LogisticRegression(max_iter=1_000) model.fit(X, y) doubt = DoubtEnsemble(reason = ShortConfidenceReason(model=model)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model, threshold=0.2): self.model = model self.threshold = threshold def _correct_class_confidence(self, X, y): """ Gives the predicted confidence (or proba) associated with the correct label `y` from a given model. """ probas = self.model.predict_proba(X) values = [] for i, proba in enumerate(probas): proba_dict = {self.model.classes_[j]: v for j, v in enumerate(proba)} values.append(proba_dict[y[i]]) return np.array(values) def __call__(self, X, y): confidences = self._correct_class_confidence(X, y) return np.where(confidences < self.threshold, 1 - confidences, 0) class DisagreeReason: """ Assign doubt when two scikit-learn models disagree on a prediction. Arguments: model1: scikit-learn classifier model2: a different scikit-learn classifier Usage: ```python from sklearn.datasets import load_iris from sklearn.linear_model import LogisticRegression from sklearn.neighbors import KNeighborsClassifier from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import DisagreeReason X, y = load_iris(return_X_y=True) model1 = LogisticRegression(max_iter=1_000) model2 = KNeighborsClassifier() model1.fit(X, y) model2.fit(X, y) doubt = DoubtEnsemble(reason = DisagreeReason(model1, model2)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model1, model2): self.model1 = model1 self.model2 = model2 def __call__(self, X, y): result = self.model1.predict(X) != self.model2.predict(X) return result.astype(np.float16) class OutlierReason: """ Assign doubt when a scikit-learn outlier model detects an outlier. Arguments: model: scikit-learn outlier model Usage: ```python from sklearn.datasets import load_iris from sklearn.ensemble import IsolationForest from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import OutlierReason X, y = load_iris(return_X_y=True) model = IsolationForest() model.fit(X) doubt = DoubtEnsemble(reason = OutlierReason(model)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model): self.model = model def __call__(self, X, y): return (self.model.predict(X) == -1).astype(np.float16) class AbsoluteDifferenceReason: """ Assign doubt when the absolute difference between label and regression is too large. Arguments: model: scikit-learn outlier model threshold: cutoff for doubt assignment Usage: ```python from sklearn.datasets import load_diabetes from sklearn.linear_model import LinearRegression from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import AbsoluteDifferenceReason X, y = load_diabetes(return_X_y=True) model = LinearRegression() model.fit(X, y) doubt = DoubtEnsemble(reason = AbsoluteDifferenceReason(model, threshold=100)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model, threshold): self.model = model self.threshold = threshold def __call__(self, X, y): difference = np.abs(self.model.predict(X) - y) return (difference >= self.threshold).astype(np.float16) class RelativeDifferenceReason: """ Assign doubt when the relative difference between label and regression is too large. Arguments: model: scikit-learn outlier model threshold: cutoff for doubt assignment Usage: ```python from sklearn.datasets import load_diabetes from sklearn.linear_model import LinearRegression from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import RelativeDifferenceReason X, y = load_diabetes(return_X_y=True) model = LinearRegression() model.fit(X, y) doubt = DoubtEnsemble(reason = RelativeDifferenceReason(model, threshold=0.5)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model, threshold): self.model = model self.threshold = threshold def __call__(self, X, y): difference = np.abs(self.model.predict(X) - y) / y return (difference >= self.threshold).astype(np.float16) class CleanlabReason: """ Assign doubt when using the cleanlab heuristic. Arguments: model: scikit-learn outlier model sorted_index_method: method used by cleanlab for sorting indices min_doubt: the minimum doubt output value used for sorting by the ensemble Usage: ```python from sklearn.datasets import load_iris from sklearn.linear_model import LogisticRegression from sklearn.neighbors import KNeighborsClassifier from doubtlab.ensemble import DoubtEnsemble from doubtlab.reason import CleanlabReason X, y = load_iris(return_X_y=True) model = LogisticRegression() model.fit(X, y) doubt = DoubtEnsemble(reason = CleanlabReason(model)) indices = doubt.get_indices(X, y) ``` """ def __init__(self, model, sorted_index_method="normalized_margin", min_doubt=0.5): self.model = model self.sorted_index_method = sorted_index_method self.min_doubt = min_doubt def __call__(self, X, y): probas = self.model.predict_proba(X) ordered_label_errors = get_noise_indices(y, probas, self.sorted_index_method) result = np.zeros_like(y) conf_arr = np.linspace(1, self.min_doubt, result.shape[0]) for idx, conf in zip(ordered_label_errors, conf_arr): result[idx] = conf return result

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null

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null

0

1

0

1

0

2

cfec891329d44a43054514a9a4545d735ea4e91e

2,577

py

Python

api/api/models.py

shmulik323/project-manager-course

ab74c7b474b0bb459b4886e3b9cbb6fc4c37df92

[ "MIT" ]

null

api/api/models.py

shmulik323/project-manager-course

ab74c7b474b0bb459b4886e3b9cbb6fc4c37df92

[ "MIT" ]

6

2020-03-24T17:00:59.000Z

2021-12-13T19:59:12.000Z

api/api/models.py

shmulik323/project-manager-course

ab74c7b474b0bb459b4886e3b9cbb6fc4c37df92

[ "MIT" ]

1

2019-11-23T16:10:59.000Z

from datetime import datetime from flask_sqlalchemy import SQLAlchemy from flask_login import UserMixin from werkzeug.security import generate_password_hash, check_password_hash db = SQLAlchemy() class User(db.Model, UserMixin): __tablename__ = 'user' id = db.Column(db.Integer, primary_key=True) name = db.Column(db.String(50)) last = db.Column(db.String(50)) username = db.Column(db.String(50), unique=True, nullable=False) email = db.Column(db.String(150), unique=True, nullable=False) image_file = db.Column( db.String(150), nullable=False, default="default.jpg") password = db.Column(db.String(256)) admin = db.Column(db.Boolean, default=False) premium = db.Column(db.Boolean, default=False) def __init__(self, email, password, name, last, username, image_file="default.jpg"): self.email = email self.password = generate_password_hash(password, method='sha256') self.username = username self.name = name self.last = last self.image_file = image_file if image_file else "default.jpg" def change(self): self.premium = True if self.premium == False else False def promote(self): self.admin = True @classmethod def authenticate(cls, **kwargs): email = kwargs.get('email') password = kwargs.get('password') username = kwargs.get('username') if not email or not password: if not username: return None user = cls.query.filter_by(email=email).first() if not user: user = cls.query.filter_by(username=username).first() if not user or not check_password_hash(user.password, password): return None return user def to_dict(self): return dict(id=self.id, email=self.email, username=self.username, name=self.name, last=self.last, admin=self.admin, premium=self.premium, image_file=self.image_file) class Pdf(db.Model): __tablename__ = "pdf" id = db.Column(db.Integer, primary_key=True) name = db.Column(db.String(50), unique=True) data = db.Column(db.String()) user_id = db.Column(db.Integer) def __init__(self, name, data, user_id): self.name = name self.data = data self.user_id = user_id def __repr__(self): return super().__repr__() def to_dict(self): return dict(id=self.id, name=self.name, data=self.data, user_id=self.user_id) class PremiumUser(User): __tablename__ = 'premium' credit_card = db.Column(db.String(50))

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0.114754

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0.622951

0

null

0

1

0

null

0

1

0

2

cff262684fe94d016ad16523903cb2cd8bae4d2f

1,166

py

Python

src/wai/common/meta/_import_code.py

waikato-datamining/wai-common

bf3d7ae6e01bcb7ffe9f5c2b5d10a05908a68c34

[ "MIT" ]

null

src/wai/common/meta/_import_code.py

waikato-datamining/wai-common

bf3d7ae6e01bcb7ffe9f5c2b5d10a05908a68c34

[ "MIT" ]

8

2020-07-01T02:11:31.000Z

2020-12-17T01:57:17.000Z

src/wai/common/meta/_import_code.py

waikato-datamining/wai-common

bf3d7ae6e01bcb7ffe9f5c2b5d10a05908a68c34

[ "MIT" ]

null

from typing import Type, Union def get_import_code(cls: Type, indent: Union[int, str] = "", alias_inner_class: bool = True) -> str: """ Gets the code to use to import a class. :param cls: The class. :param indent: The indentation of the code. :param alias_inner_class: Whether to add code to alias inner classes as outer classes. :return: The code. """ # Can't get import code for closure classes if "<locals>" in cls.__qualname__: raise ValueError(f"Can't get import code for closure class '{cls.__qualname__}'") # Get the outer-most class to import outer_class = cls.__qualname__[:cls.__qualname__.index(".")] if "." in cls.__qualname__ else cls.__qualname__ # Format the indentation string if isinstance(indent, int): indent = " " * indent # Get the code for importing the outer-most class code = f"{indent}from {cls.__module__} import {outer_class}" # If it's an inner class, alias it if cls.__name__ != outer_class and alias_inner_class: code += f"\n{indent}{cls.__name__} = {cls.__qualname__}" return code

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null

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null

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0

1

0

2

cff5c9bc1794fa2471b86b8045d56eef733f0820

210

py

Python

python_caltrain/__init__.py

wwong/python-caltrain

09a19549b7cecde8558d67a9c07fb622fba0106b

[ "MIT" ]

2

2017-03-01T04:55:16.000Z

2017-05-15T02:07:06.000Z

python_caltrain/__init__.py

wwong/python-caltrain

09a19549b7cecde8558d67a9c07fb622fba0106b

[ "MIT" ]

3

2019-08-20T00:37:41.000Z

2020-02-15T17:36:27.000Z

python_caltrain/__init__.py

wwong/python-caltrain

09a19549b7cecde8558d67a9c07fb622fba0106b

[ "MIT" ]

1

2020-02-14T04:42:14.000Z

from .caltrain import ( Caltrain, Train, Trip, TransitType, Station, Stop, Direction, UnknownStationError, UnexpectedGTFSLayoutError, ) from .__version__ import __version__

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cff879c3a2664236747d343dcb3c0091efc4d764

5,311

py

Python

tests/unit/pypyr/steps/fileread_test.py

FranklinHarry/pypyr

fcabdbeabc67dc11aca5585bb90c9dfa0088e946

[ "Apache-2.0" ]

1

2021-12-30T20:47:18.000Z

tests/unit/pypyr/steps/fileread_test.py

FranklinHarry/pypyr

fcabdbeabc67dc11aca5585bb90c9dfa0088e946

[ "Apache-2.0" ]

null

tests/unit/pypyr/steps/fileread_test.py

FranklinHarry/pypyr

fcabdbeabc67dc11aca5585bb90c9dfa0088e946

[ "Apache-2.0" ]

null

"""fileread.py unit tests.""" from unittest.mock import mock_open, patch import pytest from pypyr.context import Context from pypyr.errors import KeyInContextHasNoValueError, KeyNotInContextError import pypyr.steps.fileread as fileread def test_fileread_no_input_raises(): """No input.""" context = Context({ 'k1': 'v1'}) with pytest.raises(KeyNotInContextError) as err_info: fileread.run_step(context) assert str(err_info.value) == ("context['fileRead'] " "doesn't exist. It must exist for " "pypyr.steps.fileread.") def test_fileread_none_raises(): """Input exists but is None.""" context = Context({ 'k1': 'v1', 'fileRead': None}) with pytest.raises(KeyInContextHasNoValueError) as err_info: fileread.run_step(context) assert str(err_info.value) == ("context['fileRead'] must have a " "value for pypyr.steps.fileread.") def test_fileread_none_path_raises(): """None path raises.""" context = Context({ 'fileRead': { 'path': None}}) with pytest.raises(KeyInContextHasNoValueError) as err_info: fileread.run_step(context) assert str(err_info.value) == ("context['fileRead']['path'] must have a " "value for pypyr.steps.fileread.") def test_fileread_empty_path_raises(): """Empty path raises.""" context = Context({ 'fileRead': { 'path': ''}}) with pytest.raises(KeyInContextHasNoValueError) as err_info: fileread.run_step(context) assert str(err_info.value) == ("context['fileRead']['path'] must have a " "value for pypyr.steps.fileread.") def test_fileread_no_key_raises(): """No key raises.""" context = Context({ 'fileRead': { 'path': '/arb'}}) with pytest.raises(KeyNotInContextError) as err_info: fileread.run_step(context) assert str(err_info.value) == ("context['fileRead']['key'] " "doesn't exist. It must exist for " "pypyr.steps.fileread.") def test_fileread_none_key_raises(): """None key raises.""" context = Context({ 'fileRead': { 'path': '/arb', 'key': None}}) with pytest.raises(KeyInContextHasNoValueError) as err_info: fileread.run_step(context) assert str(err_info.value) == ("context['fileRead']['key'] must have a " "value for pypyr.steps.fileread.") def test_fileread_empty_key_raises(): """Empty key raises.""" context = Context({ 'fileRead': { 'path': '/arb', 'key': ''}}) with pytest.raises(KeyInContextHasNoValueError) as err_info: fileread.run_step(context) assert str(err_info.value) == ("context['fileRead']['key'] must have a " "value for pypyr.steps.fileread.") # endregion validation # region text mode def test_fileread_defaults(): """Read file with minimal defaults.""" context = Context({ 'fileRead': { 'path': '/arb', 'key': 'out'}}) with patch('pypyr.steps.fileread.open', mock_open(read_data='one\ntwo\nthree')) as mocked_open: fileread.run_step(context) assert context['out'] == 'one\ntwo\nthree' mocked_open.assert_called_once_with('/arb', 'r') # endregion text mode # region binary mode def test_fileread_binary_true(): """Read file with binary true.""" context = Context({ 'fileRead': { 'path': '/arb', 'key': 'out', 'binary': True}}) with patch('pypyr.steps.fileread.open', mock_open(read_data=b'12345')) as mocked_open: fileread.run_step(context) assert context['out'] == b'12345' mocked_open.assert_called_once_with('/arb', 'rb') def test_fileread_binary_explicit_false(): """Read file with binary explicit false.""" context = Context({ 'fileRead': { 'path': '/arb', 'key': 'out', 'binary': False}}) with patch('pypyr.steps.fileread.open', mock_open(read_data='one\ntwo\nthree')) as mocked_open: fileread.run_step(context) assert context['out'] == 'one\ntwo\nthree' mocked_open.assert_called_once_with('/arb', 'r') # endregion binary mode # region substitutions def test_fileread_substitutions(): """Read file with substitutions.""" context = Context({ 'p': '/arb', 'k': 'out', 'b': False, 'fileRead': { 'path': '{p}', 'key': '{k}', 'binary': '{b}'}}) with patch('pypyr.steps.fileread.open', mock_open(read_data='one\ntwo\nthree')) as mocked_open: fileread.run_step(context) assert context['out'] == 'one\ntwo\nthree' assert context == { 'p': '/arb', 'k': 'out', 'b': False, 'out': 'one\ntwo\nthree', 'fileRead': { 'path': '{p}', 'key': '{k}', 'binary': '{b}'}} mocked_open.assert_called_once_with('/arb', 'r') # endregion substitutions

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doc/userGuide/tutorial/introductory.py

lbl-srg/MPCPy

3e7bc83b1aa80e16474e77d2574c7bbaba080976

[ "BSD-3-Clause-LBNL" ]

96

2017-03-31T09:59:44.000Z

2022-03-23T18:39:37.000Z

doc/userGuide/tutorial/introductory.py

kuzha/MPCPy

9f78aa68236f87d39a50de54978c5064f9cc13c6

[ "BSD-3-Clause-LBNL" ]

150

2017-03-03T17:28:34.000Z

2021-02-24T20:03:24.000Z

doc/userGuide/tutorial/introductory.py

kuzha/MPCPy

9f78aa68236f87d39a50de54978c5064f9cc13c6

[ "BSD-3-Clause-LBNL" ]

32

2017-04-24T18:22:40.000Z

2022-03-29T17:51:20.000Z

# -*- coding: utf-8 -*- """ This tutorial will introduce the basic concepts and workflow of mpcpy. By the end, we will train a simple model based on emulated data, and use the model to optimize the control signal of the system. All required data files for this tutorial are located in doc/userGuide/tutorial. The model is a simple RC model of zone thermal response to ambient temperature and a singal heat input. It is written in Modelica: .. code-block:: modelica model RC "A simple RC network for example purposes" Modelica.Blocks.Interfaces.RealInput weaTDryBul(unit="K") "Ambient temperature"; Modelica.Blocks.Interfaces.RealInput Qflow(unit="W") "Heat input"; Modelica.Blocks.Interfaces.RealOutput Tzone(unit="K") "Zone temperature"; Modelica.Thermal.HeatTransfer.Components.HeatCapacitor heatCapacitor(C=1e5) "Thermal capacitance of zone"; Modelica.Thermal.HeatTransfer.Components.ThermalResistor thermalResistor(R=0.01) "Thermal resistance of zone"; Modelica.Thermal.HeatTransfer.Sources.PrescribedTemperature preTemp; Modelica.Thermal.HeatTransfer.Sensors.TemperatureSensor senTemp; Modelica.Thermal.HeatTransfer.Sources.PrescribedHeatFlow preHeat; equation connect(senTemp.T, Tzone) connect(preHeat.Q_flow, Qflow) connect(heatCapacitor.port, senTemp.port) connect(heatCapacitor.port, preHeat.port) connect(preTemp.port, thermalResistor.port_a) connect(thermalResistor.port_b, heatCapacitor.port) connect(preTemp.T, weaTDryBul) end RC; Variables and Units ------------------- First, lets get familiar with variables and units, the basic building blocks of MPCPy. >>> from mpcpy import variables >>> from mpcpy import units Static variables contain data that is not a timeseries: >>> setpoint = variables.Static('setpoint', 20, units.degC) >>> print(setpoint) # doctest: +NORMALIZE_WHITESPACE Name: setpoint Variability: Static Quantity: Temperature Display Unit: degC The unit assigned to the variable is the display unit. However, each display unit quantity has a base unit that is used to store the data in memory. This makes it easy to convert between units when necessary. For example, the degC display unit has a quantity temperature, which has base unit in Kelvin. >>> # Get the data in display units >>> setpoint.display_data() 20.0 >>> # Get the data in base units >>> setpoint.get_base_data() 293.15 >>> # Convert the display unit to degF >>> setpoint.set_display_unit(units.degF) >>> setpoint.display_data() # doctest: +NORMALIZE_WHITESPACE 68.0 Timeseries variables contain data in the form of a ``pandas`` Series with a datetime index: >>> # Create pandas Series object >>> import pandas as pd >>> data = [0, 5, 10, 15, 20] >>> index = pd.date_range(start='1/1/2017', periods=len(data), freq='H') >>> ts = pd.Series(data=data, index=index, name='power_data') Now we can do the same thing with the timeseries variable as we did with the static variable: >>> # Create mpcpy variable >>> power_data = variables.Timeseries('power_data', ts, units.Btuh) >>> print(power_data) # doctest: +NORMALIZE_WHITESPACE Name: power_data Variability: Timeseries Quantity: Power Display Unit: Btuh >>> # Get the data in display units >>> power_data.display_data() 2017-01-01 00:00:00+00:00 0.0 2017-01-01 01:00:00+00:00 5.0 2017-01-01 02:00:00+00:00 10.0 2017-01-01 03:00:00+00:00 15.0 2017-01-01 04:00:00+00:00 20.0 Freq: H, Name: power_data, dtype: float64 >>> # Get the data in base units >>> power_data.get_base_data() 2017-01-01 00:00:00+00:00 0.000000 2017-01-01 01:00:00+00:00 1.465355 2017-01-01 02:00:00+00:00 2.930711 2017-01-01 03:00:00+00:00 4.396066 2017-01-01 04:00:00+00:00 5.861421 Freq: H, Name: power_data, dtype: float64 >>> # Convert the display unit to kW >>> power_data.set_display_unit(units.kW) >>> power_data.display_data() 2017-01-01 00:00:00+00:00 0.000000 2017-01-01 01:00:00+00:00 0.001465 2017-01-01 02:00:00+00:00 0.002931 2017-01-01 03:00:00+00:00 0.004396 2017-01-01 04:00:00+00:00 0.005861 Freq: H, Name: power_data, dtype: float64 There is additional functionality with the units that may be useful, such as setting new data and getting the units. Consult the documentation on these classes for more information. Collect model weather and control signal data --------------------------------------------- Now, we would like to collect the weather data and control signal inputs for our model. We do this using exodata objects: >>> from mpcpy import exodata Let's take our weather data from an EPW file. We instantiate the weather exodata object by supplying the path to the EPW file: >>> weather = exodata.WeatherFromEPW('USA_IL_Chicago-OHare.Intl.AP.725300_TMY3.epw') Note that using the weather exodata object assumes that weather inputs to our model are named a certain way. Consult the documentation on the weather exodata class for more information. In this case, the ambient dry bulb temperature input in our model is named weaTDryBul. Let's take our control input signal from a CSV file. The CSV file looks like: :: Time,Qflow_csv 01/01/17 12:00 AM,3000 01/01/17 01:00 AM,3000 01/01/17 02:00 AM,3000 ... 01/02/17 10:00 PM,3000 01/02/17 11:00 PM,3000 01/03/17 12:00 AM,3000 We instantiate the control exodata object by supplying the path to the CSV file as well as a map of the names of the columns to the input of our model. We also assume that the data in the CSV file is given in the local time of the weather file, and so we supply this optional parameter, tz_name, upon instantiation as well. If no time zone is supplied, it is assumed to be UTC. >>> variable_map = {'Qflow_csv' : ('Qflow', units.W)} >>> control = exodata.ControlFromCSV('ControlSignal.csv', ... variable_map, ... tz_name = weather.tz_name) Now we are ready to collect the exogenous data from our data sources for a given time period. >>> start_time = '1/1/2017' >>> final_time = '1/3/2017' >>> weather.collect_data(start_time, final_time) # doctest: +ELLIPSIS -etc- >>> control.collect_data(start_time, final_time) Use the ``display_data()`` and ``get_base_data()`` functions for the weather and control objects to get the data in the form of a pandas dataframe. Note that the data is given in UTC time. >>> control.display_data() # doctest: +ELLIPSIS Qflow Time 2017-01-01 06:00:00+00:00 3000.0 2017-01-01 07:00:00+00:00 3000.0 2017-01-01 08:00:00+00:00 3000.0 -etc- Simulate as Emulated System --------------------------- The model has parameters for the resistance and capacitance set in the modelica code. For the purposes of this tutorial, we will assume that the model with these parameter values represents the actual system. We now wish to collect measurements from this 'actual system.' For this, we use the systems module of mpcpy. >>> from mpcpy import systems First, we instantiate our system model by supplying a measurement dictionary, information about where the model resides, and information about model exodata. The measurement dictionary holds information about and data from the variables being measured. We start with defining the variables we are interested in measuring and their sample rate. In this case, we have two, the output of the model, called 'Tzone' and the control input called 'Qflow'. Note that 'heatCapacitor.T' would also be valid instead of 'Tzone'. >>> measurements = {'Tzone' : {}, 'Qflow' : {}} >>> measurements['Tzone']['Sample'] = variables.Static('sample_rate_Tzone', ... 3600, ... units.s) >>> measurements['Qflow']['Sample'] = variables.Static('sample_rate_Qflow', ... 3600, ... units.s) The model information is given by a tuple containing the path to the Modelica (.mo) file, the path of the model within the .mo file, and a list of paths of any required libraries other than the Modelica Standard. For this example, there are no additional libraries. >>> moinfo = ('Tutorial.mo', 'Tutorial.RC', {}) Ultimately, the modelica model is compiled into an FMU. If the emulation model is already an FMU, than an fmupath can be specified instead of the modelica information tuple. For more information, see the documentation on the systmems class. We can now instantiate the system emulation object with our measurement dictionary, model information, collected exogenous data, and time zone: >>> emulation = systems.EmulationFromFMU(measurements, ... moinfo = moinfo, ... weather_data = weather.data, ... control_data = control.data, ... tz_name = weather.tz_name) Finally, we can collect the measurements from our emulation over a specified time period and display the results as a pandas dataframe. The ``collect_measurements()`` function updates the measurement dictionary with timeseries data in the ``'Measured'`` field for each variable. >>> # Collect the data >>> emulation.collect_measurements('1/1/2017', '1/2/2017') # doctest: +ELLIPSIS -etc- >>> # Display the results >>> emulation.display_measurements('Measured').applymap('{:.2f}'.format) # doctest: +ELLIPSIS Qflow Tzone Time 2017-01-01 06:00:00+00:00 3000.00 293.15 2017-01-01 07:00:00+00:00 3000.00 291.01 2017-01-01 08:00:00+00:00 3000.00 291.32 -etc- Estimate Parameters ------------------- Now assume that we do not know the parameters of the model. Or, that we have measurements from a real or emulated system, and would like to estimate parameters of our model to fit the measurements. For this, we use the models module from mpcpy. >>> from mpcpy import models In this case, we have a Modelica model with two parameters that we would like to train based on the measured data from our system; the resistance and capacitance. We first need to collect some information about our parameters and do so using a parameters exodata object. The parameter information is stored in a CSV file that looks like: :: Name,Free,Value,Minimum,Maximum,Covariance,Unit heatCapacitor.C,True,40000,1.00E+04,1.00E+06,1000,J/K thermalResistor.R,True,0.002,0.001,0.1,0.0001,K/W The name is the name of the parameter in the model. The Free field indicates if the parameter is free to be changed during the estimation method or not. The Value is the current value of the parameter. If the parameter is to be estimated, this would be an initial guess. If the parameter's Free field is set to False, then the value is set to the parameter upon simulation. The Minimum and Maximum fields set the minimum and maximum value allowed by the parameter during estimation. The Covariance field sets the covariance of the parameter, and is only used for unscented kalman filtering. Finally, the Unit field specifies the unit of the parameter using the name string of MPCPy unit classes. >>> parameters = exodata.ParameterFromCSV('Parameters.csv') >>> parameters.collect_data() >>> parameters.display_data() # doctest: +NORMALIZE_WHITESPACE Covariance Free Maximum Minimum Unit Value Name heatCapacitor.C 1000 True 1e+06 10000 J/K 40000 thermalResistor.R 0.0001 True 0.1 0.001 K/W 0.002 Now, we can instantiate the model object by defining the estimation method, validation method, measurement dictionary, model information, parameter data, and exogenous data. In this case, we use JModelica optimization to perform the parameter estimation and will validate the parameter estimation by calculating the root mean square error (RMSE) between measurements from the model and emulation. >>> model = models.Modelica(models.JModelicaParameter, ... models.RMSE, ... emulation.measurements, ... moinfo = moinfo, ... parameter_data = parameters.data, ... weather_data = weather.data, ... control_data = control.data, ... tz_name = weather.tz_name) Let's simulate the model to see how far off we are with our initial parameter guesses. The ``simulate()`` function updates the measurement dictionary with timeseries data in the ``'Simulated'`` field for each variable. >>> # Simulate the model >>> model.simulate('1/1/2017', '1/2/2017') # doctest: +ELLIPSIS -etc- >>> # Display the results >>> model.display_measurements('Simulated').applymap('{:.2f}'.format) # doctest: +ELLIPSIS Qflow Tzone Time 2017-01-01 06:00:00+00:00 3000.00 293.15 2017-01-01 07:00:00+00:00 3000.00 266.95 2017-01-01 08:00:00+00:00 3000.00 267.44 -etc- Now, we are ready to estimate the parameters to better fit the emulated measurements. In addtion to a training period, we must supply a list of measurement variables for which to minimize the error between the simulated and measured data. In this case, we only have one, ``'Tzone'``. The ``estimate()`` function updates the Value field for the parameter data in the model. >>> model.parameter_estimate('1/1/2017', '1/2/2017', ['Tzone']) # doctest: +ELLIPSIS -etc- Let's validate the estimation on the training period. The ``validate()`` method will simulate the model over the specified time period, calculate the RMSE between the simulated and measured data, and generate a plot in the working directory that shows the simulated and measured data for each measurement variable. >>> # Perform validation >>> model.validate('1/1/2017', '1/2/2017', 'validate_tra', plot=1) # doctest: +ELLIPSIS -etc- >>> # Get RMSE >>> print("%.3f" % model.RMSE['Tzone'].display_data()) # doctest: +NORMALIZE_WHITESPACE 0.041 Now let's validate on a different period of exogenous data: >>> # Define validation period >>> start_time_val = '1/2/2017' >>> final_time_val = '1/3/2017' >>> # Collect new measurements >>> emulation.collect_measurements(start_time_val, final_time_val) # doctest: +ELLIPSIS -etc- >>> # Assign new measurements to model >>> model.measurements = emulation.measurements >>> # Perform validation >>> model.validate(start_time_val, final_time_val, 'validate_val', plot=1) # doctest: +ELLIPSIS -etc- >>> # Get RMSE >>> print("%.3f" % model.RMSE['Tzone'].display_data()) # doctest: +NORMALIZE_WHITESPACE 0.047 Finally, let's view the estimated parameter values: >>> for key in model.parameter_data.keys(): ... print(key, "%.2f" % model.parameter_data[key]['Value'].display_data()) ('heatCapacitor.C', '119828.30') ('thermalResistor.R', '0.01') Optimize Control ---------------- We are now ready to optimize control of our system heater using our calibrated MPC model. Specificlaly, we would like to maintain a comfortable temperature in our zone with the minimum amount of heater energy. We can do this by using the optimization module of MPCPy. >>> from mpcpy import optimization First, we need to collect some constraint data to add to our optimization problem. In this case, we will constrain the heating input to between 0 and 4000 W, and the temperature to a comfortable range, between 20 and 25 degC. We collect contraint data from a CSV using a constraint exodata data object. The constraint CSV looks like: :: Time,Qflow_min,Qflow_max,T_min,T_max 01/01/17 12:00 AM,0,4000,20,25 01/01/17 01:00 AM,0,4000,20,25 01/01/17 02:00 AM,0,4000,20,25 ... 01/02/17 10:00 PM,0,4000,20,25 01/02/17 11:00 PM,0,4000,20,25 01/03/17 12:00 AM,0,4000,20,25 The constraint exodata object is used to determine which column of data matches with which model variable and whether it is a less-than-or-equal-to (LTE) or greater-than-or-equal-to (GTE) constraint: >>> # Define variable map >>> variable_map = {'Qflow_min' : ('Qflow', 'GTE', units.W), ... 'Qflow_max' : ('Qflow', 'LTE', units.W), ... 'T_min' : ('Tzone', 'GTE', units.degC), ... 'T_max' : ('Tzone', 'LTE', units.degC)} >>> # Instantiate constraint exodata object >>> constraints = exodata.ConstraintFromCSV('Constraints.csv', ... variable_map, ... tz_name = weather.tz_name) >>> # Collect data >>> constraints.collect_data('1/1/2017', '1/3/2017') >>> # Get data >>> constraints.display_data() # doctest: +ELLIPSIS Qflow_GTE Qflow_LTE Tzone_GTE Tzone_LTE Time 2017-01-01 06:00:00+00:00 0.0 4000.0 20.0 25.0 2017-01-01 07:00:00+00:00 0.0 4000.0 20.0 25.0 2017-01-01 08:00:00+00:00 0.0 4000.0 20.0 25.0 -etc- We can now instantiate an optimization object using our calibrated MPC model, selecting an optimization problem type and solver package, and specifying which of the variables in the model to treat as the objective variable. In this case, we choose an energy minimization problem (integral of variable over time horizon) to be solved using JModelica, and Qflow to be the variable we wish to minimize the integral of over the time horizon. >>> opt_problem = optimization.Optimization(model, ... optimization.EnergyMin, ... optimization.JModelica, ... 'Qflow', ... constraint_data = constraints.data) The information provided is used to automatically generate a .mop (optimization model file for JModelica) and transfer the optimization problem using JModelica. Using the ``optimize()`` function optimizes the variables defined in the control data of the model object and updates their timeseries data with the optimal solution for the time period specified. Note that other than the constraints, the exogenous data within the model object is used, and the control interval is assumed to be the same as the measurement sampling rate of the model. Use the ``get_optimization_options()`` and ``set_optimization_options()`` to see and change the options for the optimization solver; for instance number of control points, maximum iteration number, tolerance, or maximum CPU time. See the documentation for these functions for more information. >>> opt_problem.optimize('1/2/2017', '1/3/2017') # doctest: +ELLIPSIS -etc- We can get the optimization solver statistics in the form of (return message, # of iterations, objective value, solution time in seconds): >>> opt_problem.get_optimization_statistics() # doctest: +ELLIPSIS ('Solve_Succeeded', 12, -etc-) We can retrieve the optimal control solution and verify that the constraints were satisfied. The intermediate points are a result of the direct collocation method used by JModelica. >>> opt_problem.display_measurements('Simulated').applymap('{:.2f}'.format) # doctest: +ELLIPSIS Qflow Tzone Time 2017-01-02 06:00:00+00:00 669.93 298.15 2017-01-02 06:09:18.183693+00:00 1512.95 293.15 2017-01-02 06:38:41.816307+00:00 2599.01 293.15 2017-01-02 07:00:00+00:00 1888.28 293.15 -etc- Finally, we can simulate the model using the optimized control trajectory. Note that the ``model.control_data`` dictionary is updated by the ``opt_problem.optimize()`` function. >>> model.control_data['Qflow'].display_data().loc[pd.to_datetime('1/2/2017 06:00:00'):pd.to_datetime('1/3/2017 06:00:00')].map('{:.2f}'.format) # doctest: +ELLIPSIS 2017-01-02 06:00:00+00:00 669.93 2017-01-02 06:09:18.183693+00:00 1512.95 2017-01-02 06:38:41.816307+00:00 2599.01 2017-01-02 07:00:00+00:00 1888.28 -etc- >>> model.simulate('1/2/2017', '1/3/2017') # doctest: +ELLIPSIS -etc- >>> model.display_measurements('Simulated').applymap('{:.2f}'.format) # doctest: +ELLIPSIS Qflow Tzone Time 2017-01-02 06:00:00+00:00 669.93 293.15 2017-01-02 07:00:00+00:00 1888.28 291.41 2017-01-02 08:00:00+00:00 2277.67 293.03 -etc- Note there is some mismatch between the simulated model output temperature and the raw optimal control solution model output temperature output. This is due to the interpolation of control input results during simulation not aligning with the collocation polynomials and timestep determined by the optimization solver. We can solve the optimization problem again, this time updating the ``model.control_data`` with a greater time resolution of 1 second. Some mismatch will still occur due to the optimization solution using collocation being an approximation of the true dynamic model. >>> opt_problem.optimize('1/2/2017', '1/3/2017', res_control_step=1.0) # doctest: +ELLIPSIS -etc- >>> model.control_data['Qflow'].display_data().loc[pd.to_datetime('1/2/2017 06:00:00'):pd.to_datetime('1/3/2017 06:00:00')].map('{:.2f}'.format) # doctest: +ELLIPSIS 2017-01-02 06:00:00+00:00 669.93 2017-01-02 06:00:01+00:00 671.66 2017-01-02 06:00:02+00:00 673.38 -etc- >>> model.simulate('1/2/2017', '1/3/2017') # doctest: +ELLIPSIS -etc- >>> model.display_measurements('Simulated').applymap('{:.2f}'.format) # doctest: +ELLIPSIS Qflow Tzone Time 2017-01-02 06:00:00+00:00 669.93 293.15 2017-01-02 07:00:00+00:00 1888.28 292.67 2017-01-02 08:00:00+00:00 2277.67 293.13 -etc- """ if __name__ == "__main__": import doctest doctest.ELLIPSIS_MARKER = '-etc-' (n_fails, n_tests) = doctest.testmod() if n_fails: print('\nTutorial finished with {0} fails.'.format(n_fails)); else: print('\nTutorial finished OK.')

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codigo_das_aulas/aula_05/aula_05_01.py

VeirichR/curso-python-selenium

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codigo_das_aulas/aula_05/aula_05_01.py

VeirichR/curso-python-selenium

9b9107a64adb4e6bcf10c76287e0b4cc7d024321

[ "CC0-1.0" ]

8

2020-04-20T11:20:43.000Z

2021-08-18T16:41:15.000Z

codigo_das_aulas/aula_05/aula_05_01.py

VeirichR/curso-python-selenium

9b9107a64adb4e6bcf10c76287e0b4cc7d024321

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from selenium.webdriver import Firefox url = 'http://selenium.dunossauro.live/aula_05_a.html' firefox = Firefox() firefox.get(url) div_py = firefox.find_element_by_id('python') div_hk = firefox.find_element_by_id('haskell') print(div_hk.text) firefox.quit()

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Python

case_05.py

AlexRogalskiy/Python

78a38746de51688dc118ba921da08b920fe4caf2

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case_05.py

AlexRogalskiy/Python

78a38746de51688dc118ba921da08b920fe4caf2

[ "MIT" ]

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case_05.py

AlexRogalskiy/Python

78a38746de51688dc118ba921da08b920fe4caf2

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import pandas as pd print pd.__version__ #Load data #------------------------------------------ df = pd.read_csv("Data.csv") df.to_csv("Data_copy.csv") df = pd.read_excel("Data.xlsx", "Sheet1") df.to_excel("Data_copy.xlsx", sheet_name="Sheet1") #Dataframe preview #------------------------------------------ df.head(5) df.tail(5) df.columns() #Rename columns #------------------------------------------ df2 = df.rename(columns={'ID':'EMPID'}) df2 = df.rename(columns={'ID':'EMPID'}, inplace=True) #Select columns/rows #------------------------------------------ df[['ID', "Gender"]] df[df['Sales'] > 10 & df['BMI'] > 1000] #Handle missing values #------------------------------------------ df.dropna() df.fillna(value=5) mean = df['Sales'].mean() df['Sales'].fillna(mean) #Creat column #------------------------------------------ df['Sales_Rate'] = df['Sales'] * 40; #Aggregate data #------------------------------------------ df.groupby('Gender').sum() pd.pivot_table(df, values='Sales', index=['Income', 'Product'], columns=['Gender']) pd.pivot_table(df, values='Sales', index=['Income', 'Product'], columns=['Gender'], aggfunc=len) pd.crosstab(df['Gender'], df['Income']) #Merge dataframes #------------------------------------------ pd.concat([df1, df2]) pd.merge(df1, df2, on='ID', how='inner') #Apply function #------------------------------------------ df['Income'].map(lambda x: 10 + x) df[['Sales','Income']].apply(sum) func = lambda x: x + '' df.applymap(func) #Identify unique values #------------------------------------------ df['ID'].unique() #Basic stattistics #------------------------------------------ df.describe() df.cov() df.corr()

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mayaside/ChangeRenderSetting.py

Kususumu/pythonServerWorkplace

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mayaside/ChangeRenderSetting.py

Kususumu/pythonServerWorkplace

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[ "MIT" ]

null

mayaside/ChangeRenderSetting.py

Kususumu/pythonServerWorkplace

d76080276b9616bbf5945413bcf4336779546ebc

[ "MIT" ]

null

#ChangeRenderSetting.py ##This only use in the maya software render , not in arnold #Three main Node of Maya Render: # ->defaultRenderGlobals, defaultRenderQuality and defaultResolution # ->those are separate nodes in maya ''' import maya.cmds as cmds #Function : getRenderGlobals() #Usage : get the Value of Render Globals and print it def getRenderGlobals() : render_glob = "defaultRenderGlobals" list_Attr = cmds.listAttr(render_glob,r = True,s = True) #loop the list print 'defaultRenderSetting As follows :' for attr in list_Attr: get_attr_name = "%s.%s"%(render_glob, attr) print "setAttr %s %s"%(get_attr_name, cmds.getAttr(get_attr_name)) #Function : getRenderResolution() #Usage : get the Value of Render Resolution and print it def getRenderResolution() : resolu_list = "defaultResolution" list_Attr = cmds.listAttr(resolu_list,r = True , s = True) print 'defaultResolution As follows :' for attr in list_Attr: get_attr_name = "%s.%s"%(resolu_list, attr) print "setAttr %s %s"%(get_attr_name, cmds.getAttr(get_attr_name)) #defaultRenderGlobals.startFrame = 2.0 #Function : startEndFrame #Usage : to change the Global value(startFrame,endFrame) of the Render #use for set the render startFrame,endFrame,byframe #Example : startEndFrame(3.0,7.0) def startEndFrame(startTime,endTime) : cmds.setAttr("defaultRenderGlobals.startFrame",startTime) cmds.setAttr("defaultRenderGlobals.endFrame",endTime) #Function : setWidthAndHeight #Usage : to change the Resolution value(width,height) of the Render #Example : setWidthAndHeight(960,540) def setWidthAndHeight(width,height) : cmds.setAttr("defaultResolution.width",width) cmds.setAttr("defaultResolution.height",height) '''

35.039216

74

0.734751

225

1,787

5.737778

0.324444

0.032533

0.051123

0.024787

0.176607

0.139427

0

0.008032

0.163962

1,787

51

75

35.039216

0.856091

0.988248

0

null

0

null

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1

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true

0

null

0

null

0

1

0

null

0

1

0

2

5c729e31ba9386c63c16a49f742b6865ce1e6073

8,745

py

Python

hxlm/ontologia/python/systema.py

EticaAI/HXL-Data-Science-file-formats

c7c5aa56c452ac1613242ee04cc9ae66f38ec24d

[ "Unlicense" ]

3

2021-01-25T20:44:10.000Z

2021-04-19T22:47:05.000Z

hxlm/ontologia/python/systema.py

fititnt/HXL-Data-Science-file-formats

f4fe9866e53280767f9cb4c8c488ef9c8b9d33cd

[ "Unlicense" ]

24

2021-01-26T00:36:39.000Z

2021-11-13T23:59:56.000Z

hxlm/ontologia/python/systema.py

fititnt/HXL-Data-Science-file-formats

f4fe9866e53280767f9cb4c8c488ef9c8b9d33cd

[ "Unlicense" ]

1

2021-09-05T03:43:37.000Z

"""hxlm.ontologia.python.systema This module, like hxlm.ontologia.python.commune, contains generic data classes when implementing HXLm in python. But one main difference is that on this module... the initial author have no idea good naming in Latin! But note that most of what is here was created on last 100 years, so we may need to keep as it is. Trivia: - "systēma" - https://en.wiktionary.org/wiki/systema#Latin - Latin, Etymology: From Ancient Greek σύστημα (sústēma, “organised whole, body”), from σύν (sún, “with, together”) + ἵστημι (hístēmi, “I stand”). - Noun, systēma n (genitive systēmatis); third declension, - 1. system - 2. harmony Author: 2021, Emerson Rocha (Etica.AI) <rocha@ieee.org> License: Public Domain / BSD Zero Clause License SPDX-License-Identifier: Unlicense OR 0BSD """ from dataclasses import InitVar, dataclass # from typing import NamedTuple, TypedDict from enum import Enum from typing import Any, Union __all__ = ['EntryPointType', 'FileType', 'RemoteType', 'ResourceWrapper', 'URNType'] class EntryPointType(Enum): """Typehints for entry points to resources (the 'pointer', not content)""" # TODO: webdav? # https://tools.ietf.org/html/rfc1738 (File protocol) FTP = 'ftp' """FTP/FTPS protocol https://tools.ietf.org/html/rfc959""" GIT = 'git://' """Git protocol (abstracton over SSH) See: - https://git-scm.com/book/en/v2/Git-on-the-Server-The-Protocols """ HTTP = "http" """Generic HTTP/HTTPS entrypoint, https://tools.ietf.org/html/rfc2616""" # https://english.stackexchange.com/questions/113606 # /difference-between-folder-and-directory LOCAL_DIR = "file://localhost/dir/" """Local directory""" LOCAL_FILE = "file://localhost/file" """Local file""" NETWORK_DIR = "file://remotehost/dir/" """Directory acessible via access to an non-localhost hostname""" NETWORK_FILE = "file://remotehost/file" """File acessible via access to an non-localhost hostname""" PYDICT = "PyDict" """Entrypoint already is Python Dict object""" PYLIST = "PyList" """Entrypoint already is Python List object""" # Note: hxlm.core, at least for entrypoint type, mostly use python list # and in some cases dict. So at the moment we will not implement # other internal types SSH = 'ssh://' """Secure Shell (SSH), https://tools.ietf.org/html/rfc4253""" # https://docs.python.org/3/library/asyncio-stream.html STREAM = "STREAM" """Data stream""" STRING = "STRING" """Generic raw string ready to be immediately parsed (see STREAM""" UNKNOW = "?" """Unknow entrypoint""" URN = "URN" """Uniform Resource Name, see https://tools.ietf.org/html/rfc8141""" @dataclass(repr=False) class Factum: """Encapsulate contextual messages for smarter L10N output (S-expressions!) The ideal usage og Factum is, with processing of some external function, convert terms like the 'vkg.attr.descriptionem' to what would have meaning to the user. Since Factum can also be used even for debug program (or or the Vocabulary Knowledge Graph may not be ready) is possible to do a raw print() of contents. Not ideal, but a fallback. >>> Factum("Testing") (vkg.attr.factum (vkg.attr.descriptionem "Testing")) >>> Factum("Testing", linguam="ENG") (vkg.attr.factum (vkg.attr.descriptionem (ENG "Testing"))) >>> Factum("Testing", datum=[1, 2]) (vkg.attr.factum (vkg.attr.descriptionem "Testing")(vkg.attr.datum "[1, 2]")) """ descriptionem: str """Textual information about the fact. Strongly recommended not omit""" fontem: Any = None """Source of the message to be presented to end user. Can be ommited. Try keep it short. Must be something that can be converted to string. """ datum: Any = None """Extra context about the message. Can be ommited.""" linguam: str = None """When descriptionem is an natural language, this can explicit this""" # TODO: implement type of Factum (like if is error, or informative message) def __repr__(self): """Export an string representation without user translation of terms Please consider using helpers instead of export objects directly. """ if self.linguam is None: desc = '"' + self.descriptionem + '"' else: desc = '(' + self.linguam + ' "' + self.descriptionem + '")' resultatum = "(vkg.attr.factum " resultatum += '(vkg.attr.descriptionem ' + desc + ')' if self.fontem is not None: resultatum += '(vkg.attr.fontem "' + str(self.fontem) + '")' if self.datum is not None: resultatum += '(vkg.attr.datum "' + str(self.datum) + '")' resultatum += ")" return resultatum class FileType(Enum): """File formats See: - https://en.wikipedia.org/wiki/File_format - https://en.wikipedia.org/wiki/Container_format_(computing) - https://en.wikipedia.org/wiki/Delimiter#Delimiter_collision """ CSV = '.csv?' """Generic CSV (allows non-strict), https://tools.ietf.org/html/rfc4180 Can be used when the content is likely to be CSV, but the file was not processed yet """ # TODO: zip # TODO: gz CSV_RFC4180 = '.csv' """An CSV strict compliant with https://tools.ietf.org/html/rfc4180""" JSON = '.json' """JSON JavaScript Object Notation, https://tools.ietf.org/html/rfc8259""" JSON5 = '.json5' """ JSON5 Data Interchange Format (JSON5), https://json5.org/""" TSV = '.tsv' # .tsv, .tab """Tab-separated values, a more strict CSV type (No RFC for this one) See: - https://en.wikipedia.org/wiki/Tab-separated_values """ YAML = '.yml' # .yml, .yaml """An YAML 'YAML Ain't Markup Language' container, https://yaml.org/""" # Class definition: Almost the same @dataclass class L10NContext: """Localization Context for current user, see hxlm.core.localization This dataclass is mostly an wrapper around the context of current user (so it will try to localize/translate based on users know languages) but can be also used when exporting or explicitly requiting an different localization. """ available: list """Available languages (lid) on loaded VKG""" user: list """Orderen know languages of the user""" def about(self, key: str = None): """Export values""" about = { 'available': self.available, 'user': self.user, } if key: if key in about: return about[key] return None return about class RemoteType(Enum): """Typehints for specialization of entrypoints""" # TODO: S3 # TODO: Google Spreadsheet # TODO: CKAN # TODO: HXL-Proxy # TODO: FTP strict / FTPS HTTP = "http://" """Generic HTTP without HTTPS""" HTTPS = "https://" """Generic HTTPS""" UNKNOW = "?" """Unknow entrypoint""" # Class definition: Almost the same @dataclass(init=True, eq=True) class ResourceWrapper: """An Resource Wrapper""" content: Union[dict, list, str] = None """If the entrypoint already is not an RAW string/object, the content""" entrypoint: InitVar[Any] = None entrypoint_t: InitVar[EntryPointType] = None log: InitVar[list] = [] """Log of messages. Can be used when failed = True or for verbose output""" failed: bool = False """If this resource tried to be loaded, bug failed""" remote_t: InitVar[RemoteType] = None # def about(self, key: str = None): # """Export values""" # about = { # 'failed': self.failed, # 'log': self.log, # 'entrypoint': self.entrypoint, # 'entrypoint_t': self.entrypoint_t, # 'remote_t': self.remote_t, # 'content': self.content, # } # if key: # if key in about: # return about[key] # return None # return about class URNType(Enum): """Uniform Resource Name, see https://tools.ietf.org/html/rfc8141 See also hxlm/core/htype/urn.py (not fully implemented yet with this) """ DATA = "urn:data" """URN Data See: - https://github.com/EticaAI/HXL-Data-Science-file-formats/tree/main /urn-data-specification """ HDP = "urn:hdp" """HDP Declarative Programming URN""" IETF = "urn:ietf" """IETF URN, see https://tools.ietf.org/html/rfc2648""" ISO = "urn:ietf" """..., see https://tools.ietf.org/html/rfc5141""" UNKNOW = "?" """Unknow URN type"""

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79

0.629503

1,097

8,745

4.996354

0.354603

0.015326

0.028097

0.034118

0.168217

0.140668

0.083197

0.068601

0.053275

0.039044

0

0.011896

0.240595

8,745

307

80

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0.813432

0.405031

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0.038462

0

0.135235

0.040385

0

0.013029

0

1

0.025641

false

0

0.038462

0

0.717949

0

null

0

null

0

1

0

1

0

2

5c7eef17cbb62508fcf15afbb4cca512d6b1522f

789

py

Python

acton_test_app.py

akshaybkiitb/HW_acton_spec

6872683633fc41d44947868d0e8534e5275b10db

[ "BSD-3-Clause" ]

2

2019-12-11T01:22:04.000Z

2022-03-30T13:44:52.000Z

acton_test_app.py

akshaybkiitb/HW_acton_spec

6872683633fc41d44947868d0e8534e5275b10db

[ "BSD-3-Clause" ]

null

acton_test_app.py

akshaybkiitb/HW_acton_spec

6872683633fc41d44947868d0e8534e5275b10db

[ "BSD-3-Clause" ]

2

2020-05-18T14:10:05.000Z

2020-07-31T11:24:53.000Z

from __future__ import division, print_function from ScopeFoundry import BaseMicroscopeApp #from ScopeFoundry.helper_funcs import sibling_path, load_qt_ui_file import logging logging.basicConfig(level=logging.DEBUG) class SpecTestApp(BaseMicroscopeApp): name = 'spec_test_app' def setup(self): # from ScopeFoundryHW.andor_camera import AndorCCDHW # self.add_hardware(AndorCCDHW(self)) from ScopeFoundryHW.acton_spec import ActonSpectrometerHW self.add_hardware(ActonSpectrometerHW) # from ScopeFoundryHW.andor_camera import AndorCCDReadoutMeasure # self.add_measurement(AndorCCDReadoutMeasure) # if __name__ == '__main__': import sys app = SpecTestApp(sys.argv) sys.exit(app.exec_())

28.178571

72

0.732573

82

789

6.719512

0.54878

0.098004

0.079855

0.105263

0.127042

0

0.201521

789

28

73

28.178571

0.874603

0.372624

0

0.043659

0

1

0.076923

false

0

0.384615

0

0.615385

0.076923

0

null

0

null

0

1

0

1

0

2

5c87620e45ca5473590bf908661872d3585bab69

1,017

py

Python

Problems/0005. Longest Palindromic Substring/SolutionPython3.py

SpacelandingCat/leetcode

761093513aed0d4779944ca152180e3356facc2f

[ "MIT" ]

null

Problems/0005. Longest Palindromic Substring/SolutionPython3.py

SpacelandingCat/leetcode

761093513aed0d4779944ca152180e3356facc2f

[ "MIT" ]

null

Problems/0005. Longest Palindromic Substring/SolutionPython3.py

SpacelandingCat/leetcode

761093513aed0d4779944ca152180e3356facc2f

[ "MIT" ]

null

class Solution: def longestPalindrome(self, s: str) -> str: result = '' pal_s = set(s) if len(pal_s) == 1: return s for ind_c in range(len(s)): pal = '' ind_l = ind_c ind_r = ind_c + 1 while ind_l > -1 and ind_r < len(s): if s[ind_l] == s[ind_r]: pal = s[ind_l] + pal + s[ind_r] ind_l -= 1 ind_r += 1 else: break if len(result) < len(pal): result = pal pal = s[ind_c] ind_l = ind_c - 1 ind_r = ind_c + 1 while ind_l > -1 and ind_r < len(s): if s[ind_l] == s[ind_r]: pal = s[ind_l] + pal + s[ind_r] ind_l -= 1 ind_r += 1 else: break if len(result) < len(pal): result = pal return result

31.78125

51

0.360865

131

1,017

2.587786

0.19084

0.117994

0.103245

0.047198

0.60767

0

0.021368

0.539823

1,017

32

52

31.78125

0.702991

0

0.625

0

1

0.03125

false

0

0.125

0

null

0

1

0

1

0

null

0

2

5c8ab1b3eddace8397226479e640c75020c3d5d9

147

py

Python

python/fib.py

Cinia/fibonacci

7ca6dd20e1faced2ce31c8349835dc4f6181a0d2

[ "MIT" ]

null

python/fib.py

Cinia/fibonacci

7ca6dd20e1faced2ce31c8349835dc4f6181a0d2

[ "MIT" ]

null

python/fib.py

Cinia/fibonacci

7ca6dd20e1faced2ce31c8349835dc4f6181a0d2

[ "MIT" ]

null

import sys def fib(i): if i < 2: return 1 return fib(i-1) + fib(i-2) if __name__ == "__main__": print(fib(int(sys.argv[1])))

14.7

32

0.544218

26

147

2.769231

0.538462

0.166667

0

0.04717

0.278912

147

9

33

16.333333

0.632075

0

0.054422

0

1

0.142857

false

0

0.142857

0

0.571429

0.142857

1

0

null

0

1

0

null

0

2

5c90dc090af95d86c043cbd504b3dcbe75aa4737

13,243

py

Python

tests/test_soda.py

Adam-Lechnos/SocrataPython

798e7abe160d3a7c1aa2b6c42708ad0b600b097e

[ "MIT" ]

null

tests/test_soda.py

Adam-Lechnos/SocrataPython

798e7abe160d3a7c1aa2b6c42708ad0b600b097e

[ "MIT" ]

null

tests/test_soda.py

Adam-Lechnos/SocrataPython

798e7abe160d3a7c1aa2b6c42708ad0b600b097e

[ "MIT" ]

null

from sodapy import Socrata from sodapy.constants import DEFAULT_API_PREFIX, OLD_API_PREFIX import requests import requests_mock import os.path import inspect import json PREFIX = "https://" DOMAIN = "fakedomain.com" DATASET_IDENTIFIER = "songs" APPTOKEN = "FakeAppToken" USERNAME = "fakeuser" PASSWORD = "fakepassword" TEST_DATA_PATH = os.path.join(os.path.dirname(os.path.abspath(inspect.getfile( inspect.currentframe()))), "test_data") def test_client(): client = Socrata(DOMAIN, APPTOKEN) assert isinstance(client, Socrata) client.close() def test_get(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, session_adapter=mock_adapter) response_data = "get_songs.txt" setup_mock(adapter, "GET", response_data, 200) response = client.get(DATASET_IDENTIFIER) assert isinstance(response, list) assert len(response) == 10 client.close() def test_get_unicode(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, session_adapter=mock_adapter) response_data = "get_songs_unicode.txt" setup_mock(adapter, "GET", response_data, 200) response = client.get(DATASET_IDENTIFIER) assert isinstance(response, list) assert len(response) == 10 client.close() def test_get_metadata_and_attachments(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, session_adapter=mock_adapter) response_data = "get_song_metadata.txt" setup_old_api_mock(adapter, "GET", response_data, 200) response = client.get_metadata(DATASET_IDENTIFIER) assert isinstance(response, dict) assert "newBackend" in response assert "attachments" in response["metadata"] response = client.download_attachments(DATASET_IDENTIFIER) assert isinstance(response, list) assert len(response) == 0 client.close() def test_update_metadata(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, session_adapter=mock_adapter) response_data = "update_song_metadata.txt" setup_old_api_mock(adapter, "PUT", response_data, 200) data = {"category": "Education", "attributionLink": "https://testing.updates"} response = client.update_metadata(DATASET_IDENTIFIER, data) assert isinstance(response, dict) assert response.get("category") == data["category"] assert response.get("attributionLink") == data["attributionLink"] client.close() def test_upsert_exception(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, session_adapter=mock_adapter) response_data = "403_response_json.txt" setup_mock(adapter, "POST", response_data, 403, reason="Forbidden") data = [{"theme": "Surfing", "artist": "Wavves", "title": "King of the Beach", "year": "2010"}] try: client.upsert(DATASET_IDENTIFIER, data) except Exception as e: assert isinstance(e, requests.exceptions.HTTPError) else: raise AssertionError("No exception raised for bad request.") def test_upsert(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, username=USERNAME, password=PASSWORD, session_adapter=mock_adapter) response_data = "upsert_songs.txt" data = [{"theme": "Surfing", "artist": "Wavves", "title": "King of the Beach", "year": "2010"}] setup_mock(adapter, "POST", response_data, 200) response = client.upsert(DATASET_IDENTIFIER, data) assert isinstance(response, dict) assert response.get("Rows Created") == 1 client.close() def test_replace(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, username=USERNAME, password=PASSWORD, session_adapter=mock_adapter) response_data = "replace_songs.txt" data = [ {"theme": "Surfing", "artist": "Wavves", "title": "King of the Beach", "year": "2010"}, {"theme": "History", "artist": "Best Friends Forever", "title": "Abe Lincoln", "year": "2008"}, ] setup_mock(adapter, "PUT", response_data, 200) response = client.replace(DATASET_IDENTIFIER, data) assert isinstance(response, dict) assert response.get("Rows Created") == 2 client.close() def test_delete(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, username=USERNAME, password=PASSWORD, session_adapter=mock_adapter) uri = "{0}{1}{2}/{3}.json".format(PREFIX, DOMAIN, OLD_API_PREFIX, DATASET_IDENTIFIER) adapter.register_uri("DELETE", uri, status_code=200) response = client.delete(DATASET_IDENTIFIER) assert response.status_code == 200 try: client.delete("foobar") except Exception as e: assert isinstance(e, requests_mock.exceptions.NoMockAddress) finally: client.close() def test_create(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, username=USERNAME, password=PASSWORD, session_adapter=mock_adapter) response_data = "create_foobar.txt" setup_mock(adapter, "POST", response_data, 200, dataset_identifier=None) columns = [ {"fieldName": "foo", "name": "Foo", "dataTypeName": "text"}, {"fieldName": "bar", "name": "Bar", "dataTypeName": "number"} ] tags = ["foo", "bar"] response = client.create("Foo Bar", description="test dataset", columns=columns, tags=tags, row_identifier="bar") request = adapter.request_history[0] request_payload = json.loads(request.text) # can't figure out how to use .json # Test request payload for dataset_key in ["name", "description", "columns", "tags"]: assert dataset_key in request_payload for column_key in ["fieldName", "name", "dataTypeName"]: assert column_key in request_payload["columns"][0] # Test response assert isinstance(response, dict) assert len(response.get("id")) == 9 client.close() def test_set_permission(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, username=USERNAME, password=PASSWORD, session_adapter=mock_adapter) response_data = "empty.txt" setup_old_api_mock(adapter, "PUT", response_data, 200) # Test response response = client.set_permission(DATASET_IDENTIFIER, "public") assert response.status_code == 200 # Test request request = adapter.request_history[0] query_string = request.url.split("?")[-1] params = query_string.split("&") assert len(params) == 2 assert "method=setPermission" in params assert "value=public.read" in params client.close() def test_publish(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, username=USERNAME, password=PASSWORD, session_adapter=mock_adapter) response_data = "create_foobar.txt" setup_publish_mock(adapter, "POST", response_data, 200) response = client.publish(DATASET_IDENTIFIER) assert isinstance(response, dict) assert len(response.get("id")) == 9 client.close() def test_import_non_data_file(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, username=USERNAME, password=PASSWORD, session_adapter=mock_adapter) response_data = "successblobres.txt" nondatasetfile_path = 'tests/test_data/nondatasetfile.zip' setup_import_non_data_file(adapter, "POST", response_data, 200) with open(nondatasetfile_path, 'rb') as f: files = ( {'file': ("nondatasetfile.zip", f)} ) response = client.create_non_data_file({}, files) assert isinstance(response, dict) assert response.get("blobFileSize") == 496 client.close() def test_replace_non_data_file(): mock_adapter = {} mock_adapter["prefix"] = PREFIX adapter = requests_mock.Adapter() mock_adapter["adapter"] = adapter client = Socrata(DOMAIN, APPTOKEN, username=USERNAME, password=PASSWORD, session_adapter=mock_adapter) response_data = "successblobres.txt" nondatasetfile_path = 'tests/test_data/nondatasetfile.zip' setup_replace_non_data_file(adapter, "POST", response_data, 200) with open(nondatasetfile_path, 'rb') as fin: file = ( {'file': ("nondatasetfile.zip", fin)} ) response = client.replace_non_data_file(DATASET_IDENTIFIER, {}, file) assert isinstance(response, dict) assert response.get("blobFileSize") == 496 client.close() def setup_publish_mock(adapter, method, response, response_code, reason="OK", dataset_identifier=DATASET_IDENTIFIER, content_type="json"): path = os.path.join(TEST_DATA_PATH, response) with open(path, "r") as response_body: body = json.load(response_body) uri = "{0}{1}{2}/{3}/publication.{4}".format(PREFIX, DOMAIN, OLD_API_PREFIX, dataset_identifier, content_type) headers = { "content-type": "application/json; charset=utf-8" } adapter.register_uri(method, uri, status_code=response_code, json=body, reason=reason, headers=headers) def setup_import_non_data_file(adapter, method, response, response_code, reason="OK", dataset_identifier=DATASET_IDENTIFIER, content_type="json"): path = os.path.join(TEST_DATA_PATH, response) with open(path, "r") as response_body: body = json.load(response_body) uri = "{0}{1}/api/imports2/?method=blob".format(PREFIX, DOMAIN) headers = { "content-type": "application/json; charset=utf-8" } adapter.register_uri(method, uri, status_code=response_code, json=body, reason=reason, headers=headers) def setup_replace_non_data_file(adapter, method, response, response_code, reason="OK", dataset_identifier=DATASET_IDENTIFIER, content_type="json"): path = os.path.join(TEST_DATA_PATH, response) with open(path, "r") as response_body: body = json.load(response_body) uri = "{0}{1}{2}/{3}.{4}?method=replaceBlob&id={3}".format(PREFIX, DOMAIN, OLD_API_PREFIX, dataset_identifier, "txt") headers = { "content-type": "text/plain; charset=utf-8" } adapter.register_uri(method, uri, status_code=response_code, json=body, reason=reason, headers=headers) def setup_old_api_mock(adapter, method, response, response_code, reason="OK", dataset_identifier=DATASET_IDENTIFIER, content_type="json"): path = os.path.join(TEST_DATA_PATH, response) with open(path, "r") as response_body: try: body = json.load(response_body) except ValueError: body = None uri = "{0}{1}{2}/{3}.{4}".format(PREFIX, DOMAIN, OLD_API_PREFIX, dataset_identifier, content_type) headers = { "content-type": "application/json; charset=utf-8" } adapter.register_uri(method, uri, status_code=response_code, json=body, reason=reason, headers=headers) def setup_mock(adapter, method, response, response_code, reason="OK", dataset_identifier=DATASET_IDENTIFIER, content_type="json"): path = os.path.join(TEST_DATA_PATH, response) with open(path, "r") as response_body: body = json.load(response_body) if dataset_identifier is None: # for create endpoint uri = "{0}{1}{2}.{3}".format(PREFIX, DOMAIN, OLD_API_PREFIX, "json") else: # most cases uri = "{0}{1}{2}{3}.{4}".format(PREFIX, DOMAIN, DEFAULT_API_PREFIX, dataset_identifier, content_type) headers = { "content-type": "application/json; charset=utf-8" } adapter.register_uri(method, uri, status_code=response_code, json=body, reason=reason, headers=headers)

32.538084

95

0.659896

1,511

13,243

5.577101

0.130377

0.101816

0.083304

0.067877

0.737866

0.70642

0.699775

0.679601

0.643289

0.626557

0

0.011701

0.219135

13,243

406

96

32.618227

0.803211

0.009514

0

0.575758

0

0.129072

0.019757

0

0.117845

1

0.063973

false

0.030303

0.037037

0

0.10101

0

null

0

1

0

1

0

null

0

2

5c9a4d3b8666bef59e42b987ae0767e462ac1a09

151

py

Python

COJ/1049Sum.py

Loptt/python-programs

798985a540e1b4de0d416867b5a4c6f6d75771a0

[ "MIT" ]

null

COJ/1049Sum.py

Loptt/python-programs

798985a540e1b4de0d416867b5a4c6f6d75771a0

[ "MIT" ]

null

COJ/1049Sum.py

Loptt/python-programs

798985a540e1b4de0d416867b5a4c6f6d75771a0

[ "MIT" ]

null

num = raw_input() num = int(num) suma = 0 if num >= 0: for x in range(0, num + 1): suma += x else: for x in range(num, 2): suma += x print suma

12.583333

28

0.569536

31

151

2.741935

0.483871

0.094118

0.141176

0.258824

0

0.045455

0.271523

151

12

29

12.583333

0.727273

0

0.2

0

null

0

null

0.1

0

null

0

1

0

null

0

1

0

2

5c9af6716995ec97062daa8eaf37fe3a39fc3c3f

909

py

Python

portcast/schemas.py

FyonnOh/PortCastAssignment

23cdc1ec22990a919ebd7131c2ddc07038c32d14

[ "MIT" ]

null

portcast/schemas.py

FyonnOh/PortCastAssignment

23cdc1ec22990a919ebd7131c2ddc07038c32d14

[ "MIT" ]

null

portcast/schemas.py

FyonnOh/PortCastAssignment

23cdc1ec22990a919ebd7131c2ddc07038c32d14

[ "MIT" ]

1

2022-01-11T07:56:21.000Z

from typing import List, Optional from pydantic import BaseModel class TransshipmentBase(BaseModel): is_loaded: bool is_discharged: bool discharge_date: str loaded_date: str discharge_location: str loaded_location: str vessel: str class TransshipmentCreate(TransshipmentBase): pass class Transshipment(TransshipmentBase): id: int container_id: str is_loaded: bool is_discharged: bool discharge_date: str loaded_date: str discharge_location: str loaded_location: str vessel: str class Config: orm_mode = True class ContainerBase(BaseModel): id: str final_pod: str final_pod_eta: str class ContainerCreate(ContainerBase): pass class Container(ContainerBase): id: str final_pod: str final_pod_eta: str transshipments: List[Transshipment] = [] class Config: orm_mode = True

17.150943

45

0.70187

105

909

5.87619

0.32381

0.045381

0.071313

0.045381

0.510535

0.447326

0.350081

0

0.242024

909

52

46

17.480769

0.895501

0

0.702703

0

1

0

false

0.054054

0

0.891892

0

null

0

1

0

null

0

1

0

2

5cb6b53628daa912f11e9c3ebd832c8dd8740466

271

py

Python

temas/tema2/codigo/t2e07.correos.py

GabJL/FP2021

9c2c80c3bd0b7e112f66475c48ecdcf20b611338

[ "MIT" ]

1

2021-11-29T12:12:48.000Z

temas/tema2/codigo/t2e07.correos.py

GabJL/FP2021

9c2c80c3bd0b7e112f66475c48ecdcf20b611338

[ "MIT" ]

null

temas/tema2/codigo/t2e07.correos.py

GabJL/FP2021

9c2c80c3bd0b7e112f66475c48ecdcf20b611338

[ "MIT" ]

null

nombre = input("Nombre: ") apellido = input("Apellido: ") edad_nac = input("Edad de nacimiento: ") correo1 = nombre[0] + "." + apellido + edad_nac[-2:] + "@uma.es" correo2 = nombre[:3] + apellido[:3] + edad_nac[-2:] + "@uma.es" print("Correos:", correo1, "y", correo2)

30.111111

64

0.616236

36

271

4.555556

0.472222

0.128049

0.182927

0.134146

0.158537

0

0.038961

0.147601

271

8

65

33.875

0.670996

0

0.228782

0

1

0

false

0

0.166667

0

null

0

1

0

1

0

null

0

2

5cbf10894183be7ac7e35be9617195b1566c8060

734

py

Python

settings/wrappers.py

xupei0610/PFPN

7ad049f84d1cc03200bb6cea383d5c00721f9ac4

[ "MIT" ]

9

2020-12-07T02:32:18.000Z

2022-02-07T02:38:54.000Z

settings/wrappers.py

xupei0610/PFPN

7ad049f84d1cc03200bb6cea383d5c00721f9ac4

[ "MIT" ]

null

settings/wrappers.py

xupei0610/PFPN

7ad049f84d1cc03200bb6cea383d5c00721f9ac4

[ "MIT" ]

1

2022-01-01T01:45:01.000Z

class DiscreteActionWrapper: def __init__(self, env, n): self.env = env self.action_cont = [ # [l + (_+0.5)*(h-l)/n for _ in range(n)] # [l + _*(h-l)/(n+1) for _ in range(n)] [l + _*(h-l)/(n-1) for _ in range(n)] for h, l in zip(self.env.action_space.high, self.env.action_space.low) ] self.env.action_space.shape = [n] * len(self.env.action_space.high) delattr(self.env.action_space, "low") delattr(self.env.action_space, "high") def step(self, a): action_cont = [_[i] for _, i in zip(self.action_cont, a)] return self.env.step(action_cont) def __getattr__(self, name): return getattr(self.env, name)

40.777778

82

0.565395

110

734

3.536364

0.272727

0.179949

0.200514

0.277635

0.424165

0.11054

0

0.007533

0.276567

734

17

83

43.176471

0.725047

0.104905

0

0.010703

0

1

0.2

false

0

0.066667

0.4

0

null

0

1

0

null

0

2

7a233abefcdd79a70599ef23710df83a02c92b84

1,408

py

Python

src/addresses/models.py

caesarorz/complete-ecommerce

35493812167c208c166df3048190a9988adf6bb0

[ "MIT" ]

null

src/addresses/models.py

caesarorz/complete-ecommerce

35493812167c208c166df3048190a9988adf6bb0

[ "MIT" ]

null

src/addresses/models.py

caesarorz/complete-ecommerce

35493812167c208c166df3048190a9988adf6bb0

[ "MIT" ]

null

from django.db import models # Create your models here. from billing.models import BillingProfile ADDRESS_TYPES = ( # ('billing', 'Facturacion'), # ('billing','Billing'), ('shipping', 'Envio'), # ('shipping','Shipping'), ) class Address(models.Model): billing_profile = models.ForeignKey(BillingProfile, on_delete=models.CASCADE) address_type = models.CharField(max_length=120, choices=ADDRESS_TYPES) direccion_linea_1 = models.CharField(max_length=120) direccion_linea_2 = models.CharField(max_length=120, null=True, blank=True) # pais = models.CharField(max_length=120, default='Costa Rica') provincia = models.CharField(max_length=120) canton = models.CharField(max_length=120) distrito = models.CharField(max_length=120, null=True, blank=True) def __str__(self): return str(self.billing_profile) def get_address(self): return "{linea1} {linea2}, {provincia}, {canton}, {distrito} ".format( # {postal} linea1 = self.direccion_linea_1, linea2 = self.direccion_linea_2 or "", # pais = self.pais, provincia = self.provincia, canton = self.canton, distrito = self.distrito, )

39.111111

91

0.584517

141

1,408

5.652482

0.368794

0.131744

0.158093

0.21079

0.279799

0.110414

0

0.029683

0.306108

1,408

35

92

40.228571

0.78608

0.153409

0

0.055743

0

1

0.086957

false

0

0.086957

0.608696

0

null

0

1

0

null

0

1

0

2

7a2d41f97cfb2016f65180d1790a374db4dad3de

1,286

py

Python

homework/if-elif-else.py

mcorley-gba/IntroCS21-22

a823e17f2cb618be0e67468cb15f48873ae85152

[ "MIT" ]

null

homework/if-elif-else.py

mcorley-gba/IntroCS21-22

a823e17f2cb618be0e67468cb15f48873ae85152

[ "MIT" ]

null

homework/if-elif-else.py

mcorley-gba/IntroCS21-22

a823e17f2cb618be0e67468cb15f48873ae85152

[ "MIT" ]

null

#Write an if-elif-else chain that determines a person's stage of life. #Set a value for the variable age, then: # If the person is less than 2, print a message that the person # is a baby. # # If the person is at least 2 years old, but less than 4, print # a message that the person is a toddler. # # If the person is at least 4 years old, but less than 13, print # a message that the person is a kid. # # If the person is at least 13 years old, but less than 20, print # a message that the person is a teenager. # # If the person is at least 20 years old, but less than 65, print # a message that the person is an adult. # # If the person is age 65 or older, print a message that the # the person is an elder. #Write your code below: #age = 1 #If time, come back and change to user input. age = eval(input("How old are you?\n")) #56 #if conditional_test: if age < 2: print("You are a baby!") elif age < 4: #elif = else if print("You are a toddler!") elif age < 13: print("You are a kid!") elif age < 20: print("You are a teenager!") elif age < 65: print("You are an adult!") else: #Else is a catch-all if every previous if test fails. print("You are an elder!") if sports = "y": print("You play sports!")

31.365854

71

0.654743

238

1,286

3.533613

0.302521

0.128419

0.156956

0.092747

0.380499

0.26635

0.171225

0.137931

0

0.028213

0.255832

1,286

41

72

31.365854

0.850575

0.687403

0

0.35809

0

null

0

null

0.466667

0

null

0

null

0

1

0

1

0

2

7a487e2a7618ec44c666e6aeb17a864f5b09aa19

241

py

Python

ABC/abc101-abc150/abc112/a.py

KATO-Hiro/AtCoder

cbbdb18e95110b604728a54aed83a6ed6b993fde

[ "CC0-1.0" ]

2

2020-06-12T09:54:23.000Z

2021-05-04T01:34:07.000Z

ABC/abc101-abc150/abc112/a.py

KATO-Hiro/AtCoder

cbbdb18e95110b604728a54aed83a6ed6b993fde

[ "CC0-1.0" ]

961

2020-06-23T07:26:22.000Z

2022-03-31T21:34:52.000Z

ABC/abc101-abc150/abc112/a.py

KATO-Hiro/AtCoder

cbbdb18e95110b604728a54aed83a6ed6b993fde

[ "CC0-1.0" ]

null

# -*- coding: utf-8 -*- def main(): n = int(input()) if n == 1: print("Hello World") else: a = int(input()) b = int(input()) print(a + b) if __name__ == '__main__': main()

14.176471

29

0.39834

28

241

3.142857

0.607143

0.272727

0

0.014184

0.414938

241

16

30

15.0625

0.609929

0.087137

0

0.094059

0

1

0.1

false

0

0.1

0.2

1

0

null

1

0

null

0

2

7a48add92c5fa309680f94449d41fc1a514c1384

752

py

Python

project/access/tests/fixtures/grants.py

jssmk/asylum

004b05939784b86ba559968a7cdcedf248edb01f

[ "MIT" ]

1

2017-04-08T21:31:37.000Z

project/access/tests/fixtures/grants.py

jssmk/asylum

004b05939784b86ba559968a7cdcedf248edb01f

[ "MIT" ]

9

2016-01-23T22:40:26.000Z

2021-09-13T17:44:11.000Z

project/access/tests/fixtures/grants.py

jssmk/asylum

004b05939784b86ba559968a7cdcedf248edb01f

[ "MIT" ]

1

2017-04-08T22:13:42.000Z

# -*- coding: utf-8 -*- import random import factory.django import factory.fuzzy from access.models import AccessType, TokenType from members.models import Member from members.tests.fixtures.memberlikes import MemberFactory from asylum.tests.utils import FuzzyLoremipsum class GrantFactory(factory.django.DjangoModelFactory): class Meta: model = 'access.Grant' django_get_or_create = ('atype', 'owner') atype = factory.fuzzy.FuzzyChoice(AccessType.objects.all()) owner = factory.fuzzy.FuzzyChoice(Member.objects.filter(access_tokens__ttype__in=TokenType.objects.all())) # It only makes sense to generate grants for members that have tokens #owner = factory.SubFactory(MemberFactory) #notes = FuzzyLoremipsum()

34.181818

181

0.765957

90

752

6.311111

0.577778

0.06338

0.080986

0

0.001548

0.140957

752

21

182

35.809524

0.877709

0.206117

0

0.037162

0

1

0

false

0

0.538462

0

0.846154

0

null

0

null

0

1

0

1

0

2

7a4b25e795260a82a448484fd77fd363f09417a7

8,117

py

Python

app/models.py

gacbas/Zumicrospectro

22f49158df193be0a3314806d1f42662b6a3f029

[ "MIT" ]

null

app/models.py

gacbas/Zumicrospectro

22f49158df193be0a3314806d1f42662b6a3f029

[ "MIT" ]

null

app/models.py

gacbas/Zumicrospectro

22f49158df193be0a3314806d1f42662b6a3f029

[ "MIT" ]

null

from datetime import datetime from hashlib import md5 from time import time from flask import current_app from flask_login import UserMixin from werkzeug.security import generate_password_hash, check_password_hash import jwt from app import db, login from app.search import add_to_index, remove_from_index, query_index import array arraytypecode = chr(ord('f')) class SearchableMixin(object): @classmethod def search(cls, expression, page, per_page): ids, total = query_index(cls.__tablename__, expression, page, per_page) if total == 0: return cls.query.filter_by(id=0), 0 when = [] for i in range(len(ids)): when.append((ids[i], i)) return cls.query.filter(cls.id.in_(ids)).order_by( db.case(when, value=cls.id)), total @classmethod def before_commit(cls, session): session._changes = { 'add': [obj for obj in session.new if isinstance(obj, cls)], 'update': [obj for obj in session.dirty if isinstance(obj, cls)], 'delete': [obj for obj in session.deleted if isinstance(obj, cls)] } @classmethod def after_commit(cls, session): for obj in session._changes['add']: add_to_index(cls.__tablename__, obj) for obj in session._changes['update']: add_to_index(cls.__tablename__, obj) for obj in session._changes['delete']: remove_from_index(cls.__tablename__, obj) session._changes = None @classmethod def reindex(cls): for obj in cls.query: add_to_index(cls.__tablename__, obj) followers = db.Table( 'followers', db.Column('follower_id', db.Integer, db.ForeignKey('user.id')), db.Column('followed_id', db.Integer, db.ForeignKey('user.id')) ) class User(UserMixin, db.Model): id = db.Column(db.Integer, primary_key=True) username = db.Column(db.String(64), index=True, unique=True) email = db.Column(db.String(120), index=True, unique=True) password_hash = db.Column(db.String(128)) posts = db.relationship('Post', backref='author', lazy='dynamic') about_me = db.Column(db.String(140)) last_seen = db.Column(db.DateTime, default=datetime.utcnow) followed = db.relationship( 'User', secondary=followers, primaryjoin=(followers.c.follower_id == id), secondaryjoin=(followers.c.followed_id == id), backref=db.backref('followers', lazy='dynamic'), lazy='dynamic') def __repr__(self): return '<User {}>'.format(self.username) def set_password(self, password): self.password_hash = generate_password_hash(password) def check_password(self, password): return check_password_hash(self.password_hash, password) def avatar(self, size): digest = md5(self.email.lower().encode('utf-8')).hexdigest() return 'https://www.gravatar.com/avatar/{}?d=identicon&s={}'.format( digest, size) def follow(self, user): if not self.is_following(user): self.followed.append(user) def unfollow(self, user): if self.is_following(user): self.followed.remove(user) def is_following(self, user): return self.followed.filter( followers.c.followed_id == user.id).count() > 0 def followed_posts(self): followed = Post.query.join( followers, (followers.c.followed_id == Post.user_id)).filter( followers.c.follower_id == self.id) own = Post.query.filter_by(user_id=self.id) return followed.union(own).order_by(Post.timestamp.desc()) def get_reset_password_token(self, expires_in=600): return jwt.encode( {'reset_password': self.id, 'exp': time() + expires_in}, current_app.config['SECRET_KEY'], algorithm='HS256').decode('utf-8') @staticmethod def verify_reset_password_token(token): try: id = jwt.decode(token, current_app.config['SECRET_KEY'], algorithms=['HS256'])['reset_password'] except: return return User.query.get(id) @login.user_loader def load_user(id): return User.query.get(int(id)) class Post(SearchableMixin, db.Model): __searchable__ = ['body'] id = db.Column(db.Integer, primary_key=True) body = db.Column(db.String(140)) timestamp = db.Column(db.DateTime, index=True, default=datetime.utcnow) user_id = db.Column(db.Integer, db.ForeignKey('user.id')) language = db.Column(db.String(5)) image = db.Column(db.LargeBinary) extension = db.Column(db.String(50)) def __repr__(self): return '<Post {}>'.format(self.body) db.event.listen(db.session, 'before_commit', Post.before_commit) db.event.listen(db.session, 'after_commit', Post.after_commit) class Samples(db.Model): sample_id = db.Column(db.Integer, primary_key=True, autoincrement=True) spectral_library = db.Column(db.String(256)) class_mineral = db.Column(db.String) name = db.Column(db.String) image = db.Column(db.LargeBinary) image_link = db.Column(db.String) wavelength_range = db.Column(db.String(128)) description = db.Column(db.TEXT) @staticmethod def get_classes(): try: clsses = Samples.query.with_entities(Samples.class_mineral).distinct().all() except: return [] return [cls[0] for cls in clsses] @staticmethod def get_names_by_class(cls): try: nms = Samples.query.filter(Samples.class_mineral == cls).with_entities(Samples.name).distinct().all() except: return [] return [nm[0] for nm in nms] @staticmethod def get_sample_id_by_name(name): try: lst0 = Samples.query.filter(Samples.name.contains(name)).with_entities(Samples.sample_id).distinct().all() lst1 = Samples.query.filter(Samples.name.contains(name.lower())).with_entities( Samples.sample_id).distinct().all() lst2 = Samples.query.filter(Samples.name.contains(name.title())).with_entities( Samples.sample_id).distinct().all() lst = list(set().union(lst0, lst1, lst2)) except: return [] return [l[0] for l in lst] @staticmethod def get_spectra_metatadata_by_sample_id(iid): try: qr = Samples.query.filter(Samples.sample_id == iid).first() txt = "Name: " + qr.name + "\n" + \ "Class: " + qr.class_mineral + "\n" + \ "Wavelength range: " + qr.wavelength_range + "\n" + \ "Description: " + qr.description except: txt = [] return txt @staticmethod def get_sample_image_from_id(iid): try: im = Samples.query.filter(Samples.sample_id == iid).with_entities(Samples.image).first() except: return None return im.image class Spectra(db.Model): spectrum_id = db.Column(db.Integer, primary_key=True, autoincrement=True) sample_id = db.Column(db.Integer, db.ForeignKey('samples.sample_id', ondelete='CASCADE')) instrument = db.Column(db.String(128)) measurement = db.Column(db.String(128)) x_unit = db.Column(db.String(128)) y_unit = db.Column(db.String(128)) min_wavelength = db.Column(db.Float) max_wavelength = db.Column(db.Float) num_values = db.Column(db.Integer) additional_information = db.Column(db.TEXT) x_data = db.Column(db.LargeBinary) y_data = db.Column(db.LargeBinary) sample = db.relationship("Samples", backref=db.backref("spectrum", passive_deletes=True, uselist=False)) @staticmethod def get_spectrum_by_id(iid): try: dt = Spectra.query.filter(Spectra.sample_id == iid).with_entities(Spectra.x_data, Spectra.y_data).first() x = array.array(arraytypecode) x.frombytes(dt.x_data) y = array.array(arraytypecode) y.frombytes(dt.y_data) except: return [] return [list(x), list(y)]

35.600877

118

0.63521

1,039

8,117

4.795958

0.218479

0.056191

0.066225

0.051375

0.274734

0.168573

0.13827

0.052177

0.038932

0

0.00982

0.234693

8,117

228

119

35.600877

0.792337

0

0.208333

1

0

0.047425

0

1

0.114583

false

0.057292

0.052083

0.03125

0.5

0

null

0

1

0

null

0

1

0

2

7a4fdc53b715ad463c963713fbdd91b3d75425ed

292

py

Python

_pysh/styles.py

etianen/py.sh

8172cc39508bd8ead68af20cdcfe96a6d2583fb5

[ "MIT" ]

3

2018-12-18T23:21:30.000Z

2021-12-24T05:37:18.000Z

_pysh/styles.py

etianen/py.sh

8172cc39508bd8ead68af20cdcfe96a6d2583fb5

[ "MIT" ]

35

2016-03-27T20:42:12.000Z

2017-10-17T10:57:27.000Z

_pysh/styles.py

etianen/py.sh

8172cc39508bd8ead68af20cdcfe96a6d2583fb5

[ "MIT" ]

6

2016-06-07T11:43:02.000Z

2021-12-24T05:37:24.000Z

class StyleMapping: def __init__(self, opts): self._opts = opts def __getitem__(self, key): return getattr(self._opts, "style_{}".format(key), "").encode().decode("unicode_escape") def apply_styles(opts, command): return command.format_map(StyleMapping(opts))

24.333333

96

0.678082

35

292

5.257143

0.571429

0.130435

0

0.178082

292

11

97

26.545455

0.766667

0

0.075342

0

1

0.428571

false

0

0.285714

0.857143

0

null

0

null

0

1

0

1

0

2

7a667e0205507dfaafc0fa2f690894e26f9139e1

1,368

py

Python

libs/sqlobject/tests/test_sqlbuilder_importproxy.py

scambra/HTPC-Manager

1a1440db84ae1b6e7a2610c7f3bd5b6adf0aab1d

[ "MIT" ]

422

2015-01-08T14:08:08.000Z

2022-02-07T11:47:37.000Z

libs/sqlobject/tests/test_sqlbuilder_importproxy.py

scambra/HTPC-Manager

1a1440db84ae1b6e7a2610c7f3bd5b6adf0aab1d

[ "MIT" ]

581

2015-01-01T08:07:16.000Z

2022-02-23T11:44:37.000Z

libs/sqlobject/tests/test_sqlbuilder_importproxy.py

scambra/HTPC-Manager

1a1440db84ae1b6e7a2610c7f3bd5b6adf0aab1d

[ "MIT" ]

162

2015-01-01T00:21:16.000Z

2022-02-23T02:36:04.000Z

from sqlobject import * from sqlobject.tests.dbtest import * from sqlobject.views import * from sqlobject.sqlbuilder import ImportProxy, Alias def testSimple(): nyi = ImportProxy('NotYetImported') x = nyi.q.name class NotYetImported(SQLObject): name = StringCol(dbName='a_name') y = nyi.q.name assert str(x) == 'not_yet_imported.a_name' assert str(y) == 'not_yet_imported.a_name' def testAddition(): nyi = ImportProxy('NotYetImported2') x = nyi.q.name+nyi.q.name class NotYetImported2(SQLObject): name = StringCol(dbName='a_name') assert str(x) == '((not_yet_imported2.a_name) + (not_yet_imported2.a_name))' def testOnView(): nyi = ImportProxy('NotYetImportedV') x = nyi.q.name class NotYetImported3(SQLObject): name = StringCol(dbName='a_name') class NotYetImportedV(ViewSQLObject): class sqlmeta: idName = NotYetImported3.q.id name = StringCol(dbName=NotYetImported3.q.name) assert str(x) == 'not_yet_imported_v.name' def testAlias(): nyi = ImportProxy('NotYetImported4') y = Alias(nyi, 'y') x = y.q.name class NotYetImported4(SQLObject): name = StringCol(dbName='a_name') assert str(y) == 'not_yet_imported4 y' assert tablesUsedSet(x, None) == set(['not_yet_imported4 y']) assert str(x) == 'y.a_name'

26.307692

80

0.666667

171

1,368

5.192982

0.251462

0.050676

0.045045

0.126126

0.400901

0.273649

0.191441

0.15991

0

0.010138

0.206871

1,368

51

81

26.823529

0.808295

0

0.162162

0

0.188596

0.089912

0

0.189189

1

0.108108

false

0

0.567568

0

0.972973

0

null

0

null

0

1

0

1

0

2

7a756102e6c5960c9b3b3d7df97056599e46634f

846

py

Python

nlu/components/classifiers/generic_classifier/generic_classifier.py

milyiyo/nlu

d209ed11c6a84639c268f08435552248391c5573

[ "Apache-2.0" ]

480

2020-08-24T02:36:40.000Z

2022-03-30T08:09:43.000Z

nlu/components/classifiers/generic_classifier/generic_classifier.py

milyiyo/nlu

d209ed11c6a84639c268f08435552248391c5573

[ "Apache-2.0" ]

28

2020-09-26T18:55:43.000Z

2022-03-26T01:05:45.000Z

nlu/components/classifiers/generic_classifier/generic_classifier.py

milyiyo/nlu

d209ed11c6a84639c268f08435552248391c5573

[ "Apache-2.0" ]

76

2020-09-25T22:55:12.000Z

2022-03-17T20:25:52.000Z

from sparknlp_jsl.annotator import GenericClassifierModel, GenericClassifierApproach from sparknlp_jsl.base import * class GenericClassifier: @staticmethod def get_default_model(): return GenericClassifierModel.pretrained() \ .setInputCols("feature_vector") \ .setOutputCol("generic_classification") \ @staticmethod def get_pretrained_model(name, language): return GenericClassifierModel.pretrained(name,language) \ .setInputCols("feature_vector") \ .setOutputCol("generic_classification") \ @staticmethod def get_default_trainable_model(): return GenericClassifierApproach() \ .setInputCols("feature_vector") \ .setOutputCol("generic_classification") \ .setLabelColumn("y") \ .setEpochsNumber(2)

33.84

85

0.682033

64

846

8.78125

0.46875

0.080071

0.096085

0.197509

0.373665

0.270463

0

0.001534

0.229314

846

24

86

35.25

0.860429

0

0.45

0

0.128842

0.078014

0

1

0.15

false

0

0.1

0.15

0.45

0

null

0

1

0

null

0

1

0

2

7a849b05642c39d1086f0df1b170473231c30737

98

py

Python

exp/exception_handling_dynamic_creation.py

nicolasessisbreton/fython

988f5a94cee8b16b0000501a22239195c73424a1

[ "Apache-2.0" ]

41

2016-01-21T05:14:45.000Z

2021-11-24T20:37:21.000Z

exp/exception_handling_dynamic_creation.py

nicolasessisbreton/fython

988f5a94cee8b16b0000501a22239195c73424a1

[ "Apache-2.0" ]

5

2016-01-21T05:36:37.000Z

2016-08-22T19:26:51.000Z

exp/exception_handling_dynamic_creation.py

nicolasessisbreton/fython

988f5a94cee8b16b0000501a22239195c73424a1

[ "Apache-2.0" ]

3

2016-01-23T04:03:44.000Z

2016-08-21T15:58:38.000Z

a = type('a_fyerr', (Exception,), {}) try: raise a('aa') except Exception as e: print(type(e))

14

37

0.612245

16

98

3.6875

0.6875

0

0.163265

98

7

38

14

0.719512

0

0.090909

0

1

0

false

0

0.2

1

0

null

0

1

0

null

0

2

7a8ac69d9312c897a80eef7fbe6316c24ba27db8

2,809

py

Python

wsu/tools/simx/simx/python/simx/base/extension.py

tinyos-io/tinyos-3.x-contrib

3aaf036722a2afc0c0aad588459a5c3e00bd3c01

[ "BSD-3-Clause", "MIT" ]

1

2020-02-28T20:35:09.000Z

wsu/tools/simx/simx/python/simx/base/extension.py

tinyos-io/tinyos-3.x-contrib

3aaf036722a2afc0c0aad588459a5c3e00bd3c01

[ "BSD-3-Clause", "MIT" ]

null

wsu/tools/simx/simx/python/simx/base/extension.py

tinyos-io/tinyos-3.x-contrib

3aaf036722a2afc0c0aad588459a5c3e00bd3c01

[ "BSD-3-Clause", "MIT" ]

null

import re class Extension(object): """ Base class and helper functions for TossimBase extensions. Extensions allow adding extra information and methods to L{TossimBase} and associated L{Node} objects. Some examples are advanced topology configuration (see L{simx.fluid}) and sensor readings (see L{simx.sensor}). """ def __init__(self, extension_name): """ Initializer. @type extension_name: string @param extension_name: name used when extension is registered; it should be unique per extension type """ self.extension_name = extension_name @staticmethod def mixin(target_class, source_class): """ Mixes the source_class into the target_class. More specifically, mixes in instance methods while ignoring class methods, static methods and other class attributes. If an instance method already exists in the target_class an exception is raised. @type target_class: class @param target_class: class to mixin methods @type source_class: class @param source_class: class with mixin methods @raise RuntimeError: if a name conflict occurs during mixin """ def instance_method(attr): return hasattr(attr, "im_func") and not attr.im_self for name in (name for name in dir(source_class) if not re.match("^__.*__$", name)): method = getattr(source_class, name) if instance_method(method): if hasattr(target_class, name): raise RuntimeError("duplicate method: %s" % name) else: setattr(target_class, name, method.im_func) def decorate_node_class(self, node_class): """ This called once; it can be used to decorate the node class. The order it is invoked relative to other extensions is the order the extension was registered. @type node_class: class, of L{Node} @param node_class: class to decorate """ pass def decorate_node(self, node): """ This is called once per node. The order it is invoked relative to other extensions is the order the extension was registered. @type node: L{Node} @param node: node to decorate """ pass def decorate_tossim_class(self, tossim_class): """ This called once; it can be used to decorate the tossim class. The order it is invoked relative to other extensions is the order the extension was registered. @type tossim_class: class, of TossimBase @param tossim_class: class to decorate """ pass

30.532609

70

0.620862

343

2,809

4.962099

0.306122

0.047004

0.021152

0.256757

0.207403

0

0.317195

2,809

91

71

30.868132

0.887383

0.551442

0

0.136364

0

0.038002

0

1

0.272727

false

0.136364

0.045455

0.409091

0

null

0

null

0

1

0

1

0

2

8f85163033775c570b74b9dc7062353045d4c52d

1,796

py

Python

src/genie/libs/parser/iosxe/tests/ShowIpNhrpNhsDetail/cli/equal/golden_output_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

src/genie/libs/parser/iosxe/tests/ShowIpNhrpNhsDetail/cli/equal/golden_output_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

src/genie/libs/parser/iosxe/tests/ShowIpNhrpNhsDetail/cli/equal/golden_output_expected.py

nielsvanhooy/genieparser

9a1955749697a6777ca614f0af4d5f3a2c254ccd

[ "Apache-2.0" ]

null

expected_output = { "Tunnel0": { "nhs_ip": { "111.0.0.100": { "nhs_state": "E", "nbma_address": "111.1.1.1", "priority": 0, "cluster": 0, "req_sent": 0, "req_failed": 0, "reply_recv": 0, "current_request_id": 94, "protection_socket_requested": "FALSE", } } }, "Tunnel100": { "nhs_ip": { "100.0.0.100": { "nhs_state": "RE", "nbma_address": "101.1.1.1", "priority": 0, "cluster": 0, "req_sent": 105434, "req_failed": 0, "reply_recv": 105434, "receive_time": "00:00:49", "current_request_id": 35915, "ack": 35914, "protection_socket_requested": "FALSE", } } }, "Tunnel111": { "nhs_ip": { "111.0.0.100": { "nhs_state": "E", "nbma_address": "111.1.1.1", "priority": 0, "cluster": 0, "req_sent": 184399, "req_failed": 0, "reply_recv": 0, "current_request_id": 35916, } } }, "pending_registration_requests": { "req_id": { "16248": { "ret": 64, "nhs_ip": "111.0.0.100", "nhs_state": "expired", "tunnel": "Tu111", }, "57": { "ret": 64, "nhs_ip": "172.16.0.1", "nhs_state": "expired", "tunnel": "Tu100", }, } }, }

27.630769

55

0.342428

149

1,796

3.879195

0.369128

0.020761

0.034602

0.055363

0.480969

0.425606

0.389273

0.217993

0

0.150731

0.505011

1,796

64

56

28.0625

0.499438

0

0.40625

0

0.320156

0.046214

0

1

0

false

0

null

0

1

0

1

0

null

0

2

8f8538f9d3c50e10e3bee464d57a3a8811ef1814

151

py

Python

emotion_detection/read_emotions.py

yaiestura/coursera_hse_research

510d2cc4e255346b9fefa0d386b566af1123be81

[ "MIT" ]

null

emotion_detection/read_emotions.py

yaiestura/coursera_hse_research

510d2cc4e255346b9fefa0d386b566af1123be81

[ "MIT" ]

null

emotion_detection/read_emotions.py

yaiestura/coursera_hse_research

510d2cc4e255346b9fefa0d386b566af1123be81

[ "MIT" ]

null

def main(): with open("emotions.txt", "r") as f: count = set(f.readlines()) print(count) print(len(count)) if __name__ == '__main__': main()

15.1

37

0.615894

22

151

3.863636

0.727273

0

0.178808

151

9

38

16.777778

0.685484

0

0.139073

0

1

0.142857

false

0

0.142857

0.285714

1

0

null

0

1

0

null

0

2

8fa5dd1f18048a804e383db31d6325e0de639243

287

py

Python

pyexcelerate/__init__.py

AlexHill/PyExcelerate

8944c1c30117d4a7e19d9eb15d05c00929d16989

[ "BSD-2-Clause" ]

null

pyexcelerate/__init__.py

AlexHill/PyExcelerate

8944c1c30117d4a7e19d9eb15d05c00929d16989

[ "BSD-2-Clause" ]

null

pyexcelerate/__init__.py

AlexHill/PyExcelerate

8944c1c30117d4a7e19d9eb15d05c00929d16989

[ "BSD-2-Clause" ]

null

from .Workbook import Workbook from .Style import Style from .Fill import Fill from .Font import Font from .Format import Format from .Alignment import Alignment try: import pkg_resources __version__ = pkg_resources.require('PyExcelerate')[0].version except: __version__ = 'unknown'

22.076923

63

0.797909

38

287

5.763158

0.447368

0.109589

0

0.004016

0.132404

287

12

64

23.916667

0.875502

0

0.066202

0

1

0

false

0

0.636364

0

0.636364

0

null

0

null

0

1

0

1

0

2

8fb0cc91f84bbc539459ee97c5ce225a96109b9f

315

py

Python

booth/gprInit.py

Fife/MSU-Robotics-Club

ba74df39020c6310324fa960c651a6f3d647ce1e

[ "MIT" ]

9

2021-11-30T20:05:49.000Z

2022-01-27T00:50:55.000Z

booth/gprInit.py

Fife/MSU-Robotics-Club

ba74df39020c6310324fa960c651a6f3d647ce1e

[ "MIT" ]

1

2022-01-30T00:34:42.000Z

booth/gprInit.py

Fife/MSU-Robotics-Club

ba74df39020c6310324fa960c651a6f3d647ce1e

[ "MIT" ]

1

2022-01-27T00:48:48.000Z

import getopt, sys from Extractor1 import * #Only argument is the path of the argos experiment file try: experiment_path = sys.argv[1] except IndexError: print("Erorr, Nothing was passed in as an argument.") else: experiment_path = sys.argv[1] root = getRoot(experiment_path) writeInit(root)

17.5

55

0.72381

45

315

5

0.688889

0.186667

0.151111

0.186667

0.195556

0

0.011858

0.196825

315

17

56

18.529412

0.87747

0.171429

0

0.2

0

0.169884

0

1

0

false

0.1

0.2

0

0.2

0.1

0

null

0

1

0

null

0

1

0

2

8fbf5ecc6ed3de785cd388008c750e0d8edb9542

1,777

py

Python

src/NodeGenerators/PeanoHilbertDistributeNodes.py

as1m0n/spheral

4d72822f56aca76d70724c543d389d15ff6ca48e

[ "BSD-Source-Code", "BSD-3-Clause-LBNL", "FSFAP" ]

19

2020-10-21T01:49:17.000Z

2022-03-15T12:29:17.000Z

src/NodeGenerators/PeanoHilbertDistributeNodes.py

markguozhiming/spheral

bbb982102e61edb8a1d00cf780bfa571835e1b61

[ "BSD-Source-Code", "BSD-3-Clause-LBNL", "FSFAP" ]

41

2020-09-28T23:14:27.000Z

2022-03-28T17:01:33.000Z

src/NodeGenerators/PeanoHilbertDistributeNodes.py

markguozhiming/spheral

bbb982102e61edb8a1d00cf780bfa571835e1b61

[ "BSD-Source-Code", "BSD-3-Clause-LBNL", "FSFAP" ]

5

2020-11-03T16:14:26.000Z

2022-01-03T19:07:24.000Z

import Spheral import distributeNodesGeneric #------------------------------------------------------------------------------- # Domain decompose using PeanoHilbert ordering (1d method). #------------------------------------------------------------------------------- def distributeNodes1d(*listOfNodeTuples): distributeNodesGeneric.distributeNodesGeneric(listOfNodeTuples, Spheral.DataBase1d, Spheral.globalNodeIDsAll1d, Spheral.PeanoHilbertOrderRedistributeNodes1d) #------------------------------------------------------------------------------- # Domain decompose using PeanoHilbert ordering (2d method). #------------------------------------------------------------------------------- def distributeNodes2d(*listOfNodeTuples): distributeNodesGeneric.distributeNodesGeneric(listOfNodeTuples, Spheral.DataBase2d, Spheral.globalNodeIDsAll2d, Spheral.PeanoHilbertOrderRedistributeNodes2d) #------------------------------------------------------------------------------- # Domain decompose using PeanoHilbert ordering (3d method). #------------------------------------------------------------------------------- def distributeNodes3d(*listOfNodeTuples): distributeNodesGeneric.distributeNodesGeneric(listOfNodeTuples, Spheral.DataBase3d, Spheral.globalNodeIDsAll3d, Spheral.PeanoHilbertOrderRedistributeNodes3d)

57.322581

95

0.409679

61

1,777

11.934426

0.42623

0.061813

0.082418

0.131868

0.506868

0

0.011914

0.291503

1,777

30

96

59.233333

0.566322

0.36466

0

0.176471

0

1

0.176471

true

0

0.117647

0

0.294118

0

1

null

0

null

0

1

0

2

8fc68c6f7d1c08754edd736345f131547afecca5

677

py

Python

dzTraficoBackend/dzTrafico/BusinessEntities/LCRecommendation.py

DZAymen/dz-Trafico

74ff9caf9e3845d8af977c46b04a2d3421a0661b

[ "MIT" ]

null

dzTraficoBackend/dzTrafico/BusinessEntities/LCRecommendation.py

DZAymen/dz-Trafico

74ff9caf9e3845d8af977c46b04a2d3421a0661b

[ "MIT" ]

null

dzTraficoBackend/dzTrafico/BusinessEntities/LCRecommendation.py

DZAymen/dz-Trafico

74ff9caf9e3845d8af977c46b04a2d3421a0661b

[ "MIT" ]

null

class LCRecommendation: TURN_LEFT = -1 TURN_RIGHT = 1 STRAIGHT_AHEAD = 0 CHANGE_TO_EITHER_WAY = 2 change_lane = True change_to_either_way = False recommendation = 0 def __init__(self, lane, recommendation): self.lane = lane self.recommendation = recommendation if recommendation == self.TURN_RIGHT: self.target_lane = lane - 1 elif recommendation == self.TURN_LEFT: self.target_lane = lane + 1 elif recommendation == self.CHANGE_TO_EITHER_WAY: self.change_to_either_way = True elif recommendation == self.STRAIGHT_AHEAD: self.change_lane = False

29.434783

57

0.645495

79

677

5.202532

0.303797

0.218978

0.136253

0.16545

0.291971

0.199513

0

0.014553

0.289513

677

23

58

29.434783

0.839917

0

1

0.052632

false

0

0.473684

0

null

1

0

1

0

null

0

2

8fdf0d6e3dcdf33d021bba7c08fb3cbf31721907

302

py

Python

python/CV_ex049.py

FaunoGuazina/X_very_old_algorithm_exercises

c9b9ec78e8b82f2e23ef85ba9a5e7fd6e0deaea6

[ "MIT" ]

null

python/CV_ex049.py

FaunoGuazina/X_very_old_algorithm_exercises

c9b9ec78e8b82f2e23ef85ba9a5e7fd6e0deaea6

[ "MIT" ]

null

python/CV_ex049.py

FaunoGuazina/X_very_old_algorithm_exercises

c9b9ec78e8b82f2e23ef85ba9a5e7fd6e0deaea6

[ "MIT" ]

null

print('=ˆ= ' * 8) print(' TAULA DE MULTIPLICACIÓ') print('=ˆ= ' * 8) num = int(input('introduïu un número per trobar\nla taula de multiplicació: ')) print(' ' * 7, '-' * 13) x = 1 for c in range(1, 11): print(' ' * 7, '{} x {:2} = {:3}'.format(num, x, num*x)) x += 1 print(' ' * 7, '-' * 13)

30.2

79

0.516556

48

302

3.25

0.5625

0.115385

0.089744

0.320513

0

0.06867

0.228477

302

10

80

30.2

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0.4

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false

0

0.6

0

null

0

1

0

null

0

1

0

2

8fe31103547372def2141cfd476d4dc83dfc8cfd

129

py

Python

src/keri/vdr/__init__.py

SmithSamuelM/keripy-wot

ec329f4e011026d655bf46d269792ac97f23276d

[ "Apache-2.0" ]

10

2021-06-09T16:15:32.000Z

2022-03-28T22:14:11.000Z

src/keri/vdr/__init__.py

SmithSamuelM/keripy-wot

ec329f4e011026d655bf46d269792ac97f23276d

[ "Apache-2.0" ]

47

2021-06-17T20:00:02.000Z

2022-03-31T20:20:44.000Z

src/keri/vdr/__init__.py

SmithSamuelM/keripy-wot

ec329f4e011026d655bf46d269792ac97f23276d

[ "Apache-2.0" ]

6

2021-06-10T11:24:25.000Z

2022-01-28T08:07:43.000Z

# -*- encoding: utf-8 -*- """ KERI keri.vdr Package """ __all__ = ["issuing", "eventing", "registering", "viring", "verifying"]

16.125

71

0.604651

13

129

5.692308

0.923077

0

0.009009

0.139535

129

7

72

18.428571

0.657658

0.356589

0

0.546667

0

1

0

false

0

1

0

null

0

1

0

null

0

2

8ff27d008364f8f98d08457e48951f175ea9e3e0

356

py

Python

app/app/tests.py

obetron/recipe-app-api

5dbdeb4eea13ca9388091b7c2fcc3461640a397c

[ "MIT" ]

null

app/app/tests.py

obetron/recipe-app-api

5dbdeb4eea13ca9388091b7c2fcc3461640a397c

[ "MIT" ]

null

app/app/tests.py

obetron/recipe-app-api

5dbdeb4eea13ca9388091b7c2fcc3461640a397c

[ "MIT" ]

null

from django.test import TestCase from app.calc import add, substract class MyTestCase(TestCase): def test_add(self): """Test that two numbers are added together""" self.assertEqual(add(11, 3), 14) def test_substract(self): """Test that values are substracted and returned""" self.assertEqual(substract(5, 11), 6)

27.384615

59

0.674157

48

356

4.958333

0.604167

0.058824

0.10084

0

0.032374

0.219101

356

12

60

29.666667

0.823741

0.241573

0

0.285714

1

0.285714

false

0

0.285714

0

0.714286

0

null

0

null

0

1

0

1

0

2

8ff6fb9297dead34c9e84a21e45d008aa46a7bf0

1,146

py

Python

entangle/http.py

radiantone/entangle

82ee5adaf5a3e40bca5b049e272736d3a8322568

[ "MIT" ]

102

2021-04-02T22:15:24.000Z

2022-02-02T10:13:48.000Z

entangle/http.py

radiantone/entangle

82ee5adaf5a3e40bca5b049e272736d3a8322568

[ "MIT" ]

null

entangle/http.py

radiantone/entangle

82ee5adaf5a3e40bca5b049e272736d3a8322568

[ "MIT" ]

7

2021-06-01T01:52:57.000Z

2021-07-12T22:58:27.000Z

""" http.py - Module that provides http oriented decorators """ from functools import partial import requests def request(function=None, timeout=None, url=None, method='GET', sleep=None): """ :param function: :param timeout: :param url: :param method: :param sleep: :return: """ def decorator(func): def wrapper(f_func): # Build http request function here, get result # call func with result def invoke_request(_func, **kwargs): def make_request(url, method, data): if method == 'GET': response = requests.get(url=url, params=data) return response.content return None response = make_request(url, method, kwargs) return _func(response) pfunc = partial(invoke_request, f_func) pfunc.__name__ = func.__name__ return pfunc return wrapper(func) if function is not None: return decorator(function) return decorator

22.92

69

0.541012

115

1,146

5.252174

0.382609

0.049669

0.046358

0.066225

0

0.378709

1,146

49

70

23.387755

0.848315

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0.208333

false

0

0.083333

0

0.583333

0

null

0

null

0

1

0

1

0

2

891463285334b75309673863ed31806da507dbd1

1,080

py

Python

SimGeneral/DataMixingModule/python/supplementary/ReconstructionLocalCosmics_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

852

2015-01-11T21:03:51.000Z

2022-03-25T21:14:00.000Z

SimGeneral/DataMixingModule/python/supplementary/ReconstructionLocalCosmics_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

30,371

2015-01-02T00:14:40.000Z

2022-03-31T23:26:05.000Z

SimGeneral/DataMixingModule/python/supplementary/ReconstructionLocalCosmics_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

3,240

2015-01-02T05:53:18.000Z

2022-03-31T17:24:21.000Z

import FWCore.ParameterSet.Config as cms # # tracker # from RecoLocalTracker.Configuration.RecoLocalTracker_Cosmics_cff import * from RecoTracker.Configuration.RecoTrackerP5_cff import * from RecoVertex.BeamSpotProducer.BeamSpot_cff import * from RecoTracker.Configuration.RecoTrackerBHM_cff import * from RecoTracker.DeDx.dedxEstimators_Cosmics_cff import * # # calorimeters # from RecoLocalCalo.Configuration.RecoLocalCalo_Cosmics_cff import * from RecoEcal.Configuration.RecoEcalCosmics_cff import * # # muons # from RecoLocalMuon.Configuration.RecoLocalMuonCosmics_cff import * from RecoMuon.Configuration.RecoMuonCosmics_cff import * # primary vertex #from RecoVertex.Configuration.RecoVertexCosmicTracks_cff import * # local reco trackerCosmics = cms.Sequence(offlineBeamSpot*trackerlocalreco) caloCosmics = cms.Sequence(calolocalreco) muonsLocalRecoCosmics = cms.Sequence(muonlocalreco+muonlocalrecoNoDrift) localReconstructionCosmics = cms.Sequence(trackerCosmics*caloCosmics*muonsLocalRecoCosmics) reconstructionCosmics = cms.Sequence(localReconstructionCosmics)

30

91

0.858333

100

1,080

9.14

0.45

0.098468

0.085339

0.078775

0.080963

0

0.001005

0.078704

1,080

35

92

30.857143

0.917588

0.108333

0

1

0

false

0

0.666667

0

0.666667

0

null

0

null

0

1

0

1

0

2

64df1cf1557766bd4bb7ac11c42f4c8045b38a1c

318

py

Python

roglick/mobs.py

Kromey/roglick

b76202af71df0c30be0bd5f06a3428c990476e0e

[ "MIT" ]

6

2015-05-05T21:28:35.000Z

2019-04-14T13:42:38.000Z

roglick/mobs.py

Kromey/roglick

b76202af71df0c30be0bd5f06a3428c990476e0e

[ "MIT" ]

null

roglick/mobs.py

Kromey/roglick

b76202af71df0c30be0bd5f06a3428c990476e0e

[ "MIT" ]

null

from roglick.engine import colors,file_obj class Mob(file_obj.MultiFileObj): def __init__(self): super().__init__('data/mobs/*.json') def _process_item(self, item): item['sprite']['color'] = getattr(colors, item['sprite']['color']) return super()._process_item(item) npcs = Mob()

21.2

74

0.650943

40

318

4.825

0.6

0.072539

0.15544

0

0.185535

318

14

75

22.714286

0.745174

0

0.119874

0

1

0.25

false

0

0.125

0

0.625

0

null

0

null

0

1

0

1

0

2

64ea6bc027cd362adcba9bdbbd869cf670b03e8e

779

py

Python

books/repositories/elastic.py

OurBooks-Team-Yuml/Books

58abbbcd761f4ec359c6ab62a36ee77da6348e43

[ "MIT" ]

null

books/repositories/elastic.py

OurBooks-Team-Yuml/Books

58abbbcd761f4ec359c6ab62a36ee77da6348e43

[ "MIT" ]

45

2019-12-16T11:10:27.000Z

2020-05-18T07:15:15.000Z

books/repositories/elastic.py

OurBooks-Team-Yuml/Books

58abbbcd761f4ec359c6ab62a36ee77da6348e43

[ "MIT" ]

null

from dataclasses import asdict import os from elasticsearch import Elasticsearch from books.entities import Author, Book from books.use_cases.repositories import BaseElasticRepository class ElasticRepository(BaseElasticRepository): def add_book(self, book: Book) -> None: es = self._get_elastic() es.index(index=os.environ['ES_BOOKS_INDEX'], id=book.id, body=asdict(book)) def add_author(self, author: Author) -> None: full_name = f"{author.first_name} {author.last_name}" body = {**asdict(author), "full_name": full_name} es = self._get_elastic() es.index(index=os.environ['ES_AUTHORS_INDEX'], id=author.id, body=body) def _get_elastic(self) -> Elasticsearch: return Elasticsearch(os.environ['ES_URL'])

32.458333

83

0.709884

102

779

5.235294

0.343137

0.05618

0.061798

0.059925

0.146067

0

0.173299

779

23

84

33.869565

0.829193

0

0.125

0

0.106547

0

1

0.1875

false

0

0.3125

0.0625

0.625

0

null

0

null

0

1

0

1

0

2

64ecc1a5cceb67533c436f6bebe184eefbb4042f

366

py

Python

adminlte/tests.py

ricardochaves/django-adminlte

7d47948119a04056bec4e7572c69f288ab307894

[ "BSD-3-Clause" ]

1

2017-07-25T01:31:31.000Z

adminlte/tests.py

ricardochaves/django-adminlte

7d47948119a04056bec4e7572c69f288ab307894

[ "BSD-3-Clause" ]

null

adminlte/tests.py

ricardochaves/django-adminlte

7d47948119a04056bec4e7572c69f288ab307894

[ "BSD-3-Clause" ]

5

2017-10-17T06:05:21.000Z

2020-12-10T03:04:28.000Z

from django.test import TestCase from django.forms.boundfield import BoundField from django.forms import Widget from .templatetags.extra_functions import add_class # Create your tests here. class ExtraFunciontionsTests(TestCase): def teste_add_class(self): field = Widget() add_class(field, "teste") self.assertEqual('', 'Ricardo')

21.529412

51

0.737705

44

366

6.022727

0.545455

0.113208

0

0.180328

366

16

52

22.875

0.883333

0.062842

0

0.035191

0

0.111111

1

0.111111

false

0

0.444444

0

0.666667

0

null

0

null

0

1

0

1

0

2

64f169dde7e95020d7483a3a6cfc83ba0f2c825e

2,306

py

Python

litterbox/fabric/dataset_record.py

rwightman/tensorflow-litterbox

ddeeb3a6c7de64e5391050ffbb5948feca65ad3c

[ "Apache-2.0" ]

49

2016-09-09T15:31:36.000Z

2022-03-09T09:43:52.000Z

litterbox/fabric/dataset_record.py

TangxinKevin/tensorflow-litterbox

ddeeb3a6c7de64e5391050ffbb5948feca65ad3c

[ "Apache-2.0" ]

1

2017-06-09T07:24:16.000Z

2017-06-09T15:28:11.000Z

litterbox/fabric/dataset_record.py

TangxinKevin/tensorflow-litterbox

ddeeb3a6c7de64e5391050ffbb5948feca65ad3c

[ "Apache-2.0" ]

29

2016-09-20T07:29:54.000Z

2021-09-28T08:03:49.000Z

# Copyright (C) 2016 Ross Wightman. 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 # ============================================================================== # Based on original Work Copyright 2016 Google Inc. 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. # ============================================================================== """ """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import os import tensorflow as tf from abc import ABCMeta from abc import abstractmethod from .dataset import Dataset from .dataset import FLAGS class DatasetRecord(Dataset): """A simple class for handling data sets.""" __metaclass__ = ABCMeta def __init__(self, name, subset): super(DatasetRecord, self).__init__(name, subset, is_record=True) def data_files(self): """Returns a python list of all (sharded) data subset files. Returns: python list of all (sharded) data set files. Raises: ValueError: if there are not data_files matching the subset. """ tf_record_pattern = os.path.join(FLAGS.data_dir, '%s-*' % self.subset) data_files = tf.gfile.Glob(tf_record_pattern) if not data_files: print('No files found for dataset %s/%s at %s' % (self.name, self.subset, FLAGS.data_dir)) exit(-1) return data_files def reader(self): """Return a reader for a single entry from the data set. See io_ops.py for details of Reader class. Returns: Reader object that reads the data set. """ return tf.TFRecordReader()

32.942857

80

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2,306

4.71875

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0.034437

0.042384

0.274172

0.239735

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0

null

0

null

0

1

0

1

0

2

64f6ae25e737cbba29b652bf6659a581666ab26e

1,574

py

Python

src/azure-cli/azure/cli/command_modules/serviceconnector/__init__.py

YuanyuanNi/azure-cli

63844964374858bfacd209bfe1b69eb456bd64ca

[ "MIT" ]

3,287

2016-07-26T17:34:33.000Z

2022-03-31T09:52:13.000Z

src/azure-cli/azure/cli/command_modules/serviceconnector/__init__.py

YuanyuanNi/azure-cli

63844964374858bfacd209bfe1b69eb456bd64ca

[ "MIT" ]

19,206

2016-07-26T07:04:42.000Z

2022-03-31T23:57:09.000Z

src/azure-cli/azure/cli/command_modules/serviceconnector/__init__.py

YuanyuanNi/azure-cli

63844964374858bfacd209bfe1b69eb456bd64ca

[ "MIT" ]

2,575

2016-07-26T06:44:40.000Z

2022-03-31T22:56:06.000Z

# -------------------------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # -------------------------------------------------------------------------------------------- from azure.cli.core import AzCommandsLoader from azure.cli.command_modules.serviceconnector._help import helps # pylint: disable=unused-import class MicrosoftServiceConnectorCommandsLoader(AzCommandsLoader): def __init__(self, cli_ctx=None): from azure.cli.core.commands import CliCommandType from azure.cli.command_modules.serviceconnector._client_factory import cf_connection_cl connection_custom = CliCommandType( operations_tmpl='azure.cli.command_modules.serviceconnector.custom#{}', client_factory=cf_connection_cl) parent = super(MicrosoftServiceConnectorCommandsLoader, self) parent.__init__(cli_ctx=cli_ctx, custom_command_type=connection_custom) def load_command_table(self, args): from azure.cli.command_modules.serviceconnector.commands import load_command_table as load_command_table_manual load_command_table_manual(self, args) return self.command_table def load_arguments(self, command): from azure.cli.command_modules.serviceconnector._params import load_arguments as load_arguments_manual load_arguments_manual(self, command) COMMAND_LOADER_CLS = MicrosoftServiceConnectorCommandsLoader

49.1875

119

0.693139

160

1,574

6.5125

0.39375

0.053743

0.069098

0.105566

0.197697

0.161228

0

0.135959

1,574

31

120

50.774194

0.766176

0.232529

0

0.043261

0

1

0.157895

false

0

0.315789

0

0.578947

0

null

0

null

0

1

0

1

0

2

64f8b4b24e32e694e7569255090ea2b01133abbc

2,991

py

Python

gui/interface.py

sgtdarkskull/passwordManager

e0570c4dd185bd66319338f682fc653108693aeb

[ "MIT" ]

null

gui/interface.py

sgtdarkskull/passwordManager

e0570c4dd185bd66319338f682fc653108693aeb

[ "MIT" ]

null

gui/interface.py

sgtdarkskull/passwordManager

e0570c4dd185bd66319338f682fc653108693aeb

[ "MIT" ]

null

# from kivy.app import App # from kivy.core.text import LabelBase # from kivy.uix.gridlayout import GridLayout # from kivy.uix.relativelayout import RelativeLayout # from kivy.uix.screenmanager import Screen, ScreenManager # from kivy.config import Config # from gui.components import * # # LabelBase.register(name='Macondo', fn_regular='assets/Macondo.ttf') # LabelBase.register(name='Kalam', fn_regular='assets/Kalam-Regular.ttf') # # Config.set('graphics', 'width', '480') # Config.set('graphics', 'height', '720') # Config.write() # # # class PScreenManager(ScreenManager): # pass # # # class MainScreen(Screen): # pass # # # class MainLayout(GridLayout): # pass # # # class MainInterface(RelativeLayout): # pass # # # class LoginScreen(Screen): # pass # # # class LoginLayout(GridLayout): # # def validate_login_request(self): # username = self.ids["username"].text # passwd = self.ids["passwd"].text # # if username == "user1" and passwd == "user1": # self.ids["login_label"].text = "Access Granted" # # # class Interface(App): # def build(self): # self.title = "Password Manager" # return MainInterface() # # # # <MainInterface>: # PScreenManager: # # <PScreenManager>: # id: "s_manager" # MainScreen: # #LoginScreen: # # # <MainScreen>: # name: "main_screen" # MainLayout: # # # <MainLayout>: # cols: 1 # rows: 2 # padding: (dp(20), 0, dp(20), dp(20)) # Label: # text: "Password Manager" # font_name: "Kalam" # font_size: dp(30) # GridLayout: # rows: 3 # padding: dp(40) # spacing: dp(20) # KvRoundButtonUi: # button_color: .6, .2, .2 # button_label_text: "Login" # on_release: # app.root.children[0].current = "login_screen" # root.parent.manager.transition.direction = "left" # KvRoundButtonUi: # button_color: .6, .2, .2 # button_label_text: "Signup" # KvRoundButtonUi: # button_color: .6, .2, .2 # button_label_text: "Check/Generate Password" # # <LoginScreen>: # name: "login_screen" # BoxLayout: # orientation: "vertical" # KvPreviousButtonUi: # on_release: # app.root.children[0].current = "main_screen" # root.manager.transition.direction = "right" # LoginLayout: # # # <LoginLayout>: # cols: 1 # rows: 2 # padding: (dp(20), 0, dp(20), dp(20)) # Label: # id: login_label # text: "Login Screen" # font_name: "Macondo" # font_size: dp(30) # GridLayout: # cols: 1 # rows: 3 # padding: dp(40) # spacing: dp(30) # GridLayout: # cols: 2 # padding: dp(10) # Label: # text: "USERNAME: " # KvTextFieldUi: # id: username # GridLayout: # cols: 2 # padding: dp(10) # Label: # text: "PASSWORD" # KvTextFieldUi: # id: passwd # password: True # #password_mask: "*" # GridLayout: # cols: 1 # KvRoundButtonUi: # id: "login_button" # button_color: .6, .2, .2 # button_label_text: "Login" # on_press: root.validate_login_request()

21.212766

73

0.624875

337

2,991

5.445104

0.299703

0.044142

0.021798

0.028338

0.256676

0.232698

0.171662

0.133515

0.077384

0

0.026372

0.213975

2,991

140

74

21.364286

0.754147

0.905383

0

null

0

null

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null

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null

0

1

0

null

0

1

0

2

8f1a04cc211ed87cb6f0af3e14b79fa038ff718d

1,354

py

Python

digitalocean/LoadBalancers.py

SuleAlOthman/digitalocean

005e18ebdc4c4d8175641d60af97640531b190a1

[ "MIT" ]

2

2021-02-12T16:09:06.000Z

2021-11-18T14:12:32.000Z

digitalocean/LoadBalancers.py

sulealothman/digitalocean

005e18ebdc4c4d8175641d60af97640531b190a1

[ "MIT" ]

null

digitalocean/LoadBalancers.py

sulealothman/digitalocean

005e18ebdc4c4d8175641d60af97640531b190a1

[ "MIT" ]

null

from .reqmethods import Req, Arrange class LoadBalancers(Req, Arrange): slug = 'load_balancers' def __init__(self, token): self.setToken(token) def getAllLoadBalancers(self): data = self.get(f'{self.slug}') if 'id' in data: return data return self.arrangeData(data) def getLoadBalancerById(self, lbId): data = self.get(f'{self.slug}/{lbId}') if 'id' in data: return data return self.arrangeData(data) def storeLoadBalancer(self, body): data = self.post(f'{self.slug}', body) return data def updateLoadBalancer(self, lbId, body): data = self.put(f'{self.slug}/{lbId}', body) return data def storeForwardingRulesLoadBalancer(self, lbId, body): data = self.post(f'{self.slug}/{lbId}/forwarding_rules', body) return data def deleteForwardingRulesLoadBalancer(self, lbId, body): data = self.delete(f'{self.slug}/{lbId}/forwarding_rules', body) return data def deleteLoadBalancer(self, lbId): data = self.delete(f'{self.slug}/{lbId}') return data def storeDropletsLoadBalancer(self, lbId, dropletsId): body = {'droplet_ids' : f'{dropletsId}'} data = self.post(f'{self.slug}/{firewallId}/droplets', body) return data def deleteDropletsLoadBalancer(self, lbId, dropletsId): body = {'droplet_ids' : f'{dropletsId}'} data = self.delete(f'{self.slug}/{lbId}/droplets', body) return data

26.038462

66

0.706795

176

1,354

5.386364

0.25

0.075949

0.085443

0.082278

0.508439

0.466245

0.410338

0.303797

0

0.145495

1,354

51

67

26.54902

0.81936

0

0.394737

0

0.199409

0.096012

0

1

0.263158

false

0

0.026316

0

0.631579

0

null

0

null

0

1

0

1

0

2

8f298f88db8450c1767bf13f5feb645e359ce31f

418

py

Python

analyzer/darwin/modules/packages/app.py

phdphuc/mac-a-mal-cuckoo

8bbec99de276e854a6f48bc9ff069b911d111af2

[ "MIT" ]

41

2018-03-23T07:51:17.000Z

2021-04-07T08:26:25.000Z

analyzer/darwin/modules/packages/app.py

phdphuc/mac-a-mal-cuckoo

8bbec99de276e854a6f48bc9ff069b911d111af2

[ "MIT" ]

7

2018-04-09T13:38:11.000Z

2020-10-17T08:04:59.000Z

analyzer/darwin/modules/packages/app.py

phdphuc/mac-a-mal-cuckoo

8bbec99de276e854a6f48bc9ff069b911d111af2

[ "MIT" ]

8

2018-03-22T20:07:33.000Z

2020-07-27T08:49:11.000Z

#!/usr/bin/env python # Copyright (C) 2018 phdphuc # This software may be modified and distributed under the terms # of the MIT license. See the LICENSE file for details. from os import system, path from lib.core.packages import Package from plistlib import readPlist class App(Package): """ OS X application analysis package. """ def prepare(self): system("/bin/chmod -R +x \"%s\"" % self.target)

26.125

63

0.708134

62

418

4.774194

0.774194

0

0.011799

0.188995

418

15

64

27.866667

0.861357

0.476077

0

0.086124

0

1

0.166667

false

0

0.5

0

0.833333

0

null

0

null

0

1

0

1

0

2

8f32fa49eadc4d964717c5da62ff74fed30dd0ac

519

py

Python

Projects/project07/insert-test.py

tonysulfaro/CSE-331

b4f743b1127ebe531ba8417420d043e9c149135a

[ "MIT" ]

2

2019-02-13T17:49:18.000Z

2020-09-30T04:51:53.000Z

Projects/project07/insert-test.py

tonysulfaro/CSE-331

b4f743b1127ebe531ba8417420d043e9c149135a

[ "MIT" ]

null

Projects/project07/insert-test.py

tonysulfaro/CSE-331

b4f743b1127ebe531ba8417420d043e9c149135a

[ "MIT" ]

null

from HashTable import HashTable def assertNode(node, key, value): if key is None: assert node is None else: assert node.key == key and node.value == value ht = HashTable() ht.insert("abc", 1) ht.insert("acb", 2) ht.insert("bac", 3) assertNode(ht.table[0], "bac", 3) assertNode(ht.table[1], None, None) assertNode(ht.table[2], "abc", 1) assertNode(ht.table[3], "acb", 2) ht.insert("abc", 10) # Reassignment assertNode(ht.table[2], "abc", 10) assert ht.size == 3 assert ht.capacity == 4

18.535714

54

0.643545

83

519

4.024096

0.349398

0.179641

0.254491

0.071856

0.251497

0

0.040094

0.183044

519

27

55

19.222222

0.747642

0.023121

0

0.047525

0

0.555556

1

0.055556

false

0

0.055556

0

0.111111

0

null

0

1

0

null

0

1

0

2