xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

1dcda00f06d484c429e78cd8348704164d75422d

507

py

Python

contesto/__init__.py

kaktaktoa/contesto

c31d10959abf1397182c24216880c487d29ac184

[ "MIT" ]

null

contesto/__init__.py

kaktaktoa/contesto

c31d10959abf1397182c24216880c487d29ac184

[ "MIT" ]

null

contesto/__init__.py

kaktaktoa/contesto

c31d10959abf1397182c24216880c487d29ac184

[ "MIT" ]

null

from contesto.config import config from contesto.basis.test_case import ContestoTestCase from contesto.basis.benchmark import BenchmarkBaseCase from contesto.basis.page import Page, WebPage, MobilePage from contesto.basis.component import Component, WebComponent, MobileComponent from contesto.core.locator import * from contesto.core.finder import find_element, find_elements from contesto.core.driver_mixin import * from contesto.globals import current_test from contesto.step import Step, step, is_step

42.25

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0.854043

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507

6.279412

0.411765

0.28103

0.159251

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0.094675

507

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null

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1

0

1

0

4

1df84d03d4dedda02e3d15a5a6f8e4d3b39b329c

245

py

Python

sales/serializers.py

joarkm/olmonopolet-api

5fb605f53d6fc87c441ae0f72360c524cb0d3fb7

[ "MIT" ]

2

2020-11-21T13:15:53.000Z

2021-05-18T19:17:41.000Z

sales/serializers.py

joarkm/olmonopolet-api

5fb605f53d6fc87c441ae0f72360c524cb0d3fb7

[ "MIT" ]

6

2021-03-21T19:24:26.000Z

2021-09-22T19:09:31.000Z

sales/serializers.py

joarkm/olmonopolet-api

5fb605f53d6fc87c441ae0f72360c524cb0d3fb7

[ "MIT" ]

1

2021-05-20T21:52:10.000Z

from rest_framework import serializers from .models import DailySale class DailySaleSerializer(serializers.ModelSerializer): class Meta: fields=('beer_id','store_id','sales_day','beers_sold','last_updated') model = DailySale

35

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0.755102

28

245

6.392857

0.785714

0

0.146939

245

7

78

35

0.856459

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false

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null

0

1

0

null

0

1

0

1

0

4

38078293d27ebd5374a29f80e1845de043a57dc2

150

py

Python

contests_atcoder/abc161/abc161_b.py

takelifetime/competitive-programming

e7cf8ef923ccefad39a1727ca94c610d650fcb76

[ "BSD-2-Clause" ]

null

contests_atcoder/abc161/abc161_b.py

takelifetime/competitive-programming

e7cf8ef923ccefad39a1727ca94c610d650fcb76

[ "BSD-2-Clause" ]

1

2021-01-02T06:36:51.000Z

contests_atcoder/abc161/abc161_b.py

takelifetime/competitive-programming

e7cf8ef923ccefad39a1727ca94c610d650fcb76

[ "BSD-2-Clause" ]

null

n, m = map(int, input().split()) a = list(map(int, input().split())) a.sort(reverse=True) if a[m-1] * 4 * m < sum(a): print("No") else: print("Yes")

21.428571

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0.566667

29

150

2.931034

0.655172

0.141176

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0.376471

0.4

0

0.015625

0.146667

150

7

40

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null

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1

0

null

0

4

381d918d4ccee3d8d356969cadd9803f3f8a5b54

212

py

Python

tests/fixtures/info2.py

Nitnelav/synpp

b2b2136a99701ce77fd4fea939f8efb521f67c21

[ "MIT" ]

6

2020-04-01T12:06:20.000Z

2021-11-02T19:10:27.000Z

tests/fixtures/info2.py

Nitnelav/synpp

b2b2136a99701ce77fd4fea939f8efb521f67c21

[ "MIT" ]

26

2019-12-08T12:25:39.000Z

2022-02-28T07:24:56.000Z

tests/fixtures/info2.py

Nitnelav/synpp

b2b2136a99701ce77fd4fea939f8efb521f67c21

[ "MIT" ]

8

2020-06-19T15:49:46.000Z

2021-07-06T10:15:37.000Z

def configure(context): context.stage("tests.fixtures.info1") def execute(context): context.set_info("abc", "123") context.set_info("concat", "123" + context.get_info("tests.fixtures.info1", "uvw"))

30.285714

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212

5.142857

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0.194444

0.25

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0.117925

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35.333333

0.727273

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null

0

1

0

1

0

null

0

1

0

4

3849f17833f0b2721a53c16b7e3526ee3bbdc1fc

86

py

Python

setup.py

Yeachan-Heo/HSC2021-AlphaSolar

e572fb2fc44922f454c19396e17537bb706d23c8

[ "MIT" ]

13

2021-06-11T06:17:23.000Z

2021-07-19T01:50:36.000Z

setup.py

Yeachan-Heo/HSC2021-AlphaSolar

e572fb2fc44922f454c19396e17537bb706d23c8

[ "MIT" ]

null

setup.py

Yeachan-Heo/HSC2021-AlphaSolar

e572fb2fc44922f454c19396e17537bb706d23c8

[ "MIT" ]

5

2021-06-11T06:32:24.000Z

2021-06-14T02:16:24.000Z

from setuptools import setup setup(packages=["alphasolar"], name="alphasolar") #asdf

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null

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1

0

1

0

4

69c0934faedd49900c35f0566f6f4e1dfba19135

3,473

py

Python

tests/test_AdresseParser.py

bmadjic/AdresseParser

b57d15078888056086b643b2b905b336c160bcad

[ "MIT" ]

null

tests/test_AdresseParser.py

bmadjic/AdresseParser

b57d15078888056086b643b2b905b336c160bcad

[ "MIT" ]

null

tests/test_AdresseParser.py

bmadjic/AdresseParser

b57d15078888056086b643b2b905b336c160bcad

[ "MIT" ]

null

from unittest import TestCase from AdresseParser import AdresseParser """Run python -m unittest discover tests""" class TestAdresseParser(TestCase): def setUp(self) -> None: self.adresse_parser = AdresseParser() self.adresse1 = self.adresse_parser.parse("88 rue de rivoli 75002 paris") self.adresse2 = self.adresse_parser.parse("75002 paris 88 rue de rivoli") self.adresse3 = self.adresse_parser.parse("88 rue de rivoli") self.adresse4 = self.adresse_parser.parse("rue de rivoli 75002 paris") self.adresse5 = self.adresse_parser.parse("75002 paris rue de rivoli") def test_succes_parse_numero(self): self.assertEqual(self.adresse1["numero"], str(88)) self.assertEqual(self.adresse2["numero"], str(88)) self.assertEqual(self.adresse3["numero"], str(88)) self.assertEqual(self.adresse4["numero"], str(-1)) self.assertEqual(self.adresse5["numero"], str(-1)) def test_succes_parse_rue(self): self.assertEqual(self.adresse1["rue"]["type"], "RUE") self.assertEqual(self.adresse1["rue"]["nom"], "RIVOLI") self.assertEqual(self.adresse2["rue"]["type"], "RUE") self.assertEqual(self.adresse2["rue"]["nom"], "RIVOLI") self.assertEqual(self.adresse3["rue"]["type"], "RUE") self.assertEqual(self.adresse3["rue"]["nom"], "RIVOLI") self.assertEqual(self.adresse4["rue"]["type"], "RUE") self.assertEqual(self.adresse4["rue"]["nom"], "RIVOLI") self.assertEqual(self.adresse5["rue"]["type"], "RUE") self.assertEqual(self.adresse5["rue"]["nom"], "RIVOLI") def test_succes_parse_ville(self): self.assertEqual(self.adresse1["ville"]["arrondissement"], 2) self.assertEqual(self.adresse1["ville"]["nom"], "PARIS") self.assertEqual(self.adresse2["ville"]["arrondissement"], 2) self.assertEqual(self.adresse2["ville"]["nom"], "PARIS") self.assertEqual(self.adresse3["ville"]["arrondissement"], 0) self.assertEqual(self.adresse3["ville"]["nom"], "") self.assertEqual(self.adresse4["ville"]["arrondissement"], 2) self.assertEqual(self.adresse4["ville"]["nom"], "PARIS") self.assertEqual(self.adresse5["ville"]["arrondissement"], 2) self.assertEqual(self.adresse5["ville"]["nom"], "PARIS") def test_succes_parse_departement(self): self.assertEqual(self.adresse1["departement"]["numero"], 75) self.assertEqual(self.adresse1["departement"]["nom"], "Paris") self.assertEqual(self.adresse2["departement"]["numero"], 75) self.assertEqual(self.adresse2["departement"]["nom"], "Paris") self.assertEqual(self.adresse3["departement"]["numero"], 75) self.assertEqual(self.adresse3["departement"]["nom"], "Paris") self.assertEqual(self.adresse4["departement"]["numero"], 75) self.assertEqual(self.adresse4["departement"]["nom"], "Paris") self.assertEqual(self.adresse5["departement"]["numero"], 75) self.assertEqual(self.adresse5["departement"]["nom"], "Paris") def test_succes_parse_region(self): self.assertEqual(self.adresse1["region"], "Île-de-France") self.assertEqual(self.adresse2["region"], "Île-de-France") self.assertEqual(self.adresse3["region"], "Île-de-France") self.assertEqual(self.adresse4["region"], "Île-de-France") self.assertEqual(self.adresse5["region"], "Île-de-France")

41.843373

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395

3,473

5.718987

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0.265604

0.336432

0.095618

0.80965

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0.032347

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3,473

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82

41.843373

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0

0.20169

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0.727273

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0.109091

false

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0

null

1

0

1

0

null

0

1

0

4

69da23616aa4ddd123da5974448feff50ac1f828

2,132

py

Python

_assignments/intermediate/regex/re_standards_a.py

sages-pl/2022-01-pythonsqlalchemy-aptiv

1d6d856608e9dbe25b139e8968c48b7f46753b84

[ "MIT" ]

null

_assignments/intermediate/regex/re_standards_a.py

sages-pl/2022-01-pythonsqlalchemy-aptiv

1d6d856608e9dbe25b139e8968c48b7f46753b84

[ "MIT" ]

null

_assignments/intermediate/regex/re_standards_a.py

sages-pl/2022-01-pythonsqlalchemy-aptiv

1d6d856608e9dbe25b139e8968c48b7f46753b84

[ "MIT" ]

null

""" * Assignment: RE Standards PESEL * Complexity: medium * Lines of code: 0 lines * Time: 5 min * Warning: Do no write any code - **discussion only** English: TODO: English Translation X. Run doctests - all must succeed Polish: 1. Napisz implementację `is_pesel_valid` a. Temat walidacji Pesel jest zbyt trudny dla Regex b. W tej funkcji użujemy prostego sprawdzenia r'^\d{11}$' c. Już tylko taki kawałek kodu pozwoli na uniknięcie 80% błędów 2. Napisz implementację `is_pesel_woman` a. Pesel należy do kobiety, jeżeli przed ostatnia cyfra jest parzysta a. Nie korzystaj z regex 3. Uruchom doctesty - wszystkie muszą się powieść Discuss: * nie pisz kodu, przeprowadź tylko dyskusję * Co to jest suma kontrolna? * Mając PESEL "69072101234" a. Jakie wyrażenie może być na pierwszym miejscu w PESEL? b. Jakie wyrażenie może być na drugim miejscu w PESEL? c. Jakie wyrażenie może być na trzecim miejscu w PESEL? d. Jakie wyrażenie może być na czwartym miejscu w PESEL? e. Jakie wyrażenie może być na piątym miejscu w PESEL? f. Jakie wyrażenie może być na szóstym miejscu w PESEL? * Mając PESEL "18220812345" a. Jakie wyrażenie może być na pierwszym miejscu w PESEL? b. Jakie wyrażenie może być na drugim miejscu w PESEL? c. Jakie wyrażenie może być na trzecim miejscu w PESEL? d. Jakie wyrażenie może być na czwartym miejscu w PESEL? e. Jakie wyrażenie może być na piątym miejscu w PESEL? f. Jakie wyrażenie może być na szóstym miejscu w PESEL? Tests: >>> import sys; sys.tracebacklimit = 0 >>> is_pesel_valid('69072101234') True >>> is_pesel_valid('18220812345') True >>> is_pesel_woman('69072101234') False >>> is_pesel_woman('18220812345') True """ import re PATTERN = r'^\d{11}$' def is_pesel_valid(pesel: str) -> bool: ... def is_pesel_woman(pesel: str) -> bool: """ Check whether PESEL is woman's. If the second to last number is even, then PESEL is woman's, in other case PESEL is man's. """ ...

30.028169

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null

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1

0

4

69dd7e2c77c7bfe28caa6cf3f8c0bfaaec8daa37

385

py

Python

python-serv/core/validator/rule.py

plvhx/efishery-backend-test

091a51534bc5259993debea2cb55a4f4548f3d07

[ "BSD-3-Clause" ]

null

python-serv/core/validator/rule.py

plvhx/efishery-backend-test

091a51534bc5259993debea2cb55a4f4548f3d07

[ "BSD-3-Clause" ]

null

python-serv/core/validator/rule.py

plvhx/efishery-backend-test

091a51534bc5259993debea2cb55a4f4548f3d07

[ "BSD-3-Clause" ]

null

from abc import ABC class AbstractRule(ABC): pass class Rule(AbstractRule): def __init__(self, name, data_type, required=True): self.name = name self.type = data_type self.required = required def get_name(self): return self.name def get_type(self): return self.type def is_required(self): return self.required

17.5

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0.633766

50

385

4.7

0.36

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385

21

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18.333333

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false

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1

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4

385d55f31e4d10f3124614234c4211c34607e24d

537

py

Python

jsub/manager/error.py

xianghuzhao/jsub

fda16e9a0983410d33e454d9f1c4a94134e49d41

[ "MIT" ]

2

2017-05-26T07:17:34.000Z

2019-04-08T05:53:35.000Z

jsub/manager/error.py

xianghuzhao/jsub

fda16e9a0983410d33e454d9f1c4a94134e49d41

[ "MIT" ]

null

jsub/manager/error.py

xianghuzhao/jsub

fda16e9a0983410d33e454d9f1c4a94134e49d41

[ "MIT" ]

1

2019-04-08T06:52:46.000Z

from jsub.error import JsubError class ExtensionNotFoundError(JsubError): pass class BadConfigError(JsubError): pass class ConfigNotSetupError(JsubError): pass class ExtensionNotSetupError(JsubError): pass class RepoNotSetupError(ExtensionNotSetupError): pass class ContentNotSetupError(ExtensionNotSetupError): pass class ScenarioNotSetupError(ExtensionNotSetupError): pass class JobvarListNotSetupError(ExtensionNotSetupError): pass class BackendNotSetupError(ExtensionNotSetupError): pass

16.78125

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0.141527

537

31

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0.473684

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true

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null

0

null

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1

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1

0

4

385dfe1c01c96f781d3e88f713c98961b99b4d9e

293

py

Python

GraduationDesign/SSFN_V6_02/Methods/WJ/wj_similarity.py

sivanWu0222/GraduationProject

3f98d078b763dd84a246999879040c34cfbc5efb

[ "MIT" ]

12

2019-04-27T11:17:16.000Z

2022-02-27T14:03:12.000Z

GraduationDesign/SSFN_V6_02/Methods/WJ/wj_similarity.py

sivanWu0222/GraduationProject

3f98d078b763dd84a246999879040c34cfbc5efb

[ "MIT" ]

1

2022-03-21T12:31:29.000Z

2022-03-26T03:01:14.000Z

GraduationDesign/SSFN_V6_02/Methods/WJ/wj_similarity.py

sivanWu0222/GraduationProject

3f98d078b763dd84a246999879040c34cfbc5efb

[ "MIT" ]

null

def wj_similarity(word2vec, sentence1words, sentence2words): """ 计算句子的WMD距离 :param word2vec: Word2Vec对象 :param sentence1words: 句子1词语列表 :param sentence2words: 句子2词语列表 :return: 两个句子的wj相似度 """ return word2vec.sentence_similarity(sentence1words, sentence2words)

29.3

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0.050633

0.191126

293

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null

0

1

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4

387784917102d793d93b964d695956b211aaa4e7

2,440

py

Python

tests/test_trio.py

thedjinn/pyee

94a6d54ccb878748be876e4118292b847bc4a143

[ "MIT" ]

null

tests/test_trio.py

thedjinn/pyee

94a6d54ccb878748be876e4118292b847bc4a143

[ "MIT" ]

null

tests/test_trio.py

thedjinn/pyee

94a6d54ccb878748be876e4118292b847bc4a143

[ "MIT" ]

null

# -*- coding: utf-8 -*- import pytest import pytest_trio.plugin # noqa import trio from pyee import TrioEventEmitter class PyeeTestError(Exception): pass @pytest.mark.trio async def test_trio_emit(): """Test that the trio event emitter can handle wrapping coroutines """ async with TrioEventEmitter() as ee: should_call = trio.Event() @ee.on("event") async def event_handler(): should_call.set() ee.emit("event") result = False with trio.move_on_after(0.1): await should_call.wait() result = True assert result @pytest.mark.trio async def test_trio_once_emit(): """Test that trio event emitters also wrap coroutines when using once """ async with TrioEventEmitter() as ee: should_call = trio.Event() @ee.once("event") async def event_handler(): should_call.set() ee.emit("event") result = False with trio.move_on_after(0.1): await should_call.wait() result = True assert result @pytest.mark.trio async def test_trio_error(): """Test that trio event emitters can handle errors when wrapping coroutines """ async with TrioEventEmitter() as ee: send, rcv = trio.open_memory_channel(1) @ee.on("event") async def event_handler(): raise PyeeTestError() @ee.on("error") async def handle_error(exc): async with send: await send.send(exc) ee.emit("event") result = None with trio.move_on_after(0.1): async with rcv: result = await rcv.__anext__() assert isinstance(result, PyeeTestError) @pytest.mark.trio async def test_sync_error(event_loop): """Test that regular functions have the same error handling as coroutines""" async with TrioEventEmitter() as ee: send, rcv = trio.open_memory_channel(1) @ee.on("event") def sync_handler(): raise PyeeTestError() @ee.on("error") async def handle_error(exc): async with send: await send.send(exc) ee.emit("event") result = None with trio.move_on_after(0.1): async with rcv: result = await rcv.__anext__() assert isinstance(result, PyeeTestError)

21.59292

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0.588115

293

2,440

4.750853

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2,440

112

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false

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null

0

1

0

1

0

1

0

null

0

4

3890794cc8ee794c45ba856f259aba682613ddd2

2,522

py

Python

utils.py

karianjahi/recommender_system

9484a6a779c6ac731046d1519f4dd7c2ae96901e

[ "MIT" ]

null

utils.py

karianjahi/recommender_system

9484a6a779c6ac731046d1519f4dd7c2ae96901e

[ "MIT" ]

null

utils.py

karianjahi/recommender_system

9484a6a779c6ac731046d1519f4dd7c2ae96901e

[ "MIT" ]

null

""" UTILS - Helper functions to use for your recommender funcions, etc - Data: import files/models here e.g. - movies: list of movie titles and assigned cluster - ratings - user_item_matrix - item-item matrix - Models: - nmf_model: trained sklearn NMF model """ import pandas as pd import numpy as np from fuzzywuzzy import process from sklearn.impute import SimpleImputer import pickle movies = pd.read_csv('data/movies_clusters_ratings.csv') ratings = pd.read_csv("data/ratings_clean.csv") user_item_matrix = pd.read_csv("data/my_user_item_matrix.csv", index_col=0) model = pickle.load(open("nmf_model.sav","rb")) def match_movie_title(input_title, movie_titles): """ Matches inputed movie title to existing one in the list with fuzzywuzzy """ matched_title = process.extractOne(input_title, movie_titles)[0] return matched_title def print_movie_titles(movie_titles): """ Prints list of movie titles in cli app """ pass def create_user_vector(user_rating, movies): """ Convert dict of user_ratings to a user_vector """ # generate the user vector print(user_rating) user_vector = None return user_vector def lookup_movieId(movieId): """ Convert output of recommendation to movie title """ assert isinstance(movieId, int) # match movieId to title movie_title = list(movies[movies["movieid"] == movieId]["title"])[0] return movie_title def create_user_item_matrix(): pass def printt(item): print("=======================================") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print(item) print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("") print("=======================================") if __name__ == "__main__": user_rating = { "four rooms": 5, "sudden death": 3, "othello": 4, "nixon": 3, "Golden eye": 1, "total eclipse": 5, "nadja": 3 } #print(create_user_vector(user_rating, movies)) print("====================") print("") print("") print("") print("") print("") print("") print("") print("") print("") print(user_item_matrix)

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py

Python

miapy/miapy/plotting/__init__.py

SCAN-NRAD/BrainRegressorCNN

7917c6a6c4e3728db17ec762c63f8253392e6c04

[ "BSD-3-Clause" ]

1

2022-02-11T18:49:34.000Z

miapy/miapy/plotting/__init__.py

SCAN-NRAD/BrainRegressorCNN

7917c6a6c4e3728db17ec762c63f8253392e6c04

[ "BSD-3-Clause" ]

null

miapy/miapy/plotting/__init__.py

SCAN-NRAD/BrainRegressorCNN

7917c6a6c4e3728db17ec762c63f8253392e6c04

[ "BSD-3-Clause" ]

null

""" ======================================== Image plotting (:mod:`plotting` package) ======================================== This package facilitates the plotting of images for presentation and documentation purposes. Plotting (:mod:`plotting.plotter`) ---------------------------------- .. automodule:: plotting.plotter :members: """

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38a2303a599c37b9e68ee26bd177ee9a459a29bc

665

py

Python

wagtailschemaorg/templates.py

fredvollmer/wagtail-schema.org

e3f702304b33b040b57e2f18090096c45cc163f8

[ "BSD-2-Clause" ]

null

wagtailschemaorg/templates.py

fredvollmer/wagtail-schema.org

e3f702304b33b040b57e2f18090096c45cc163f8

[ "BSD-2-Clause" ]

null

wagtailschemaorg/templates.py

fredvollmer/wagtail-schema.org

e3f702304b33b040b57e2f18090096c45cc163f8

[ "BSD-2-Clause" ]

null

import json from django.utils.html import conditional_escape from django.utils.safestring import mark_safe from .encoder import JSONLDEncoder from .registry import registry def nl(xs): return mark_safe('\n'.join(map(conditional_escape, xs))) def ld_for_site(site, request=None): return nl(map(ld_print_entity, registry.get_entities(site, request))) def ld_for_object(obj, request=None): return nl(map(ld_print_entity, obj.ld_entity_list(request))) def ld_print_entity(entity): json_out = json.dumps(entity, cls=JSONLDEncoder, sort_keys=True) return mark_safe('<script type="application/ld+json">{}</script>'.format( json_out))

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0

null

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0

1

0

4

38ba6b8c0d60a8ce7e19aa11744f570ea58f9efd

170

py

Python

backend/coreApi/trips/urls.py

rochdikhalid/kopra-v1

1899e6f695ff8b3041aa7b4e24f99cb6f585085c

[ "MIT" ]

3

2021-12-14T12:31:18.000Z

2021-12-15T08:12:45.000Z

backend/coreApi/trips/urls.py

rochdikhalid/kopra-v1

1899e6f695ff8b3041aa7b4e24f99cb6f585085c

[ "MIT" ]

null

backend/coreApi/trips/urls.py

rochdikhalid/kopra-v1

1899e6f695ff8b3041aa7b4e24f99cb6f585085c

[ "MIT" ]

1

2022-01-06T14:41:27.000Z

from django.urls import path from trips import views urlpatterns = [ path('api/trips/', views.tripApi), path('api/trips/<int:id>/', views.tripApi), ]

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null

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1

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4

38be1017e4cfbd80d2ca4337459d6841e9264ef4

158

py

Python

hjz/code_graph/code_tag.py

hantianjz/Code-Graph

1cfe9a8491ff91f0c1b5f7698365db4819848eeb

[ "MIT" ]

null

hjz/code_graph/code_tag.py

hantianjz/Code-Graph

1cfe9a8491ff91f0c1b5f7698365db4819848eeb

[ "MIT" ]

null

hjz/code_graph/code_tag.py

hantianjz/Code-Graph

1cfe9a8491ff91f0c1b5f7698365db4819848eeb

[ "MIT" ]

null

#!/usr/bin/python3 import subprocess def generate_code_tag(): """ """ def main(): generate_graph(nodes, edges) if __name__ == "__main__": main()

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1

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null

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1

0

4

38c1cd62cf086dc7f2571ab29b8751180e7c04e0

93

py

Python

app/apps.py

6Arin9/wulkanowy-web

a97778f4a3716ca2d3c4cf4d4dd83cfa76e1d050

[ "Apache-2.0" ]

16

2020-11-23T19:44:41.000Z

2021-09-29T20:21:07.000Z

app/apps.py

6Arin9/wulkanowy-web

a97778f4a3716ca2d3c4cf4d4dd83cfa76e1d050

[ "Apache-2.0" ]

28

2021-01-12T16:22:57.000Z

2022-02-28T06:04:55.000Z

app/apps.py

6Arin9/wulkanowy-web

a97778f4a3716ca2d3c4cf4d4dd83cfa76e1d050

[ "Apache-2.0" ]

9

2021-02-05T19:48:12.000Z

2021-10-02T18:11:26.000Z

from django.apps import AppConfig class WulkanowyConfig(AppConfig): name = 'Wulkanowy'

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38e29aa0999cbc8eb9a5ba124edbf32be3dc2661

330

py

Python

tests/test_regex_utils.py

fareszr/app

1f3bc693eccb307234e53653f6fa2cb25ddc0647

[ "MIT" ]

null

tests/test_regex_utils.py

fareszr/app

1f3bc693eccb307234e53653f6fa2cb25ddc0647

[ "MIT" ]

null

tests/test_regex_utils.py

fareszr/app

1f3bc693eccb307234e53653f6fa2cb25ddc0647

[ "MIT" ]

null

from app.regex_utils import regex_match def test_regex_match(flask_client): assert regex_match("prefix.*", "prefix-abcd") # this generates re2 error "Argument 'pattern' has incorrect type (expected bytes, got PythonRePattern)" # fallback to re assert not regex_match("(?!abcd)s(\\.|-)?([a-z0-9]{4,6})", "abcd")

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0.151515

330

9

109

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0.354545

0

1

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0.152381

0

0.5

1

0.25

false

0

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0

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1

0

null

0

1

0

1

0

4

38e9303e1bb9a36263e74f4eef9e66071efad3a8

58

py

Python

tests/loghandler/__init__.py

AISyLab/side-channel-attacks

83c93b1087c9f16423ece7191c3171d07ed1cdce

[ "MIT" ]

14

2020-04-20T16:22:00.000Z

2022-01-26T16:52:35.000Z

tests/loghandler/__init__.py

AISyLab/side-channel-attacks

83c93b1087c9f16423ece7191c3171d07ed1cdce

[ "MIT" ]

1

2021-09-02T13:53:05.000Z

2021-09-02T14:19:01.000Z

tests/loghandler/__init__.py

AISyLab/side-channel-attacks

83c93b1087c9f16423ece7191c3171d07ed1cdce

[ "MIT" ]

6

2020-07-02T16:24:18.000Z

2022-02-07T08:55:20.000Z

# This file is here so Python can always find our modules

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1

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1

0

null

0

1

0

4

c7f99039f0d47d00a336236fc3d23ee403808fac

11

py

Python

webrepl_cfg.py

hauchel/duco

875cb45bb6339642bcdc2f74e75c1c35aa59fb8b

[ "MIT" ]

5

2021-05-29T17:20:22.000Z

2021-07-10T09:38:43.000Z

webrepl_cfg.py

hauchel/duco

875cb45bb6339642bcdc2f74e75c1c35aa59fb8b

[ "MIT" ]

null

webrepl_cfg.py

hauchel/duco

875cb45bb6339642bcdc2f74e75c1c35aa59fb8b

[ "MIT" ]

1

2021-12-07T00:53:30.000Z

PASS = 'p'

5.5

10

0.454545

2

11

2.5

1

0

0.272727

11

1

11

0.625

0

0.090909

0

1

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false

1

0

1

0

null

0

1

0

null

0

1

0

4

c7ff6851a8c7cb3d545a1e5eec532dce1060b071

232

py

Python

one_fm/one_fm/doctype/training_evaluation_form/training_evaluation_form_dashboard.py

askmetoo/One-FM

c93ed63695a3e62ee8129bd9adf563116b749030

[ "MIT" ]

16

2021-06-14T23:56:47.000Z

2022-03-22T12:05:06.000Z

one_fm/one_fm/doctype/training_evaluation_form/training_evaluation_form_dashboard.py

askmetoo/One-FM

c93ed63695a3e62ee8129bd9adf563116b749030

[ "MIT" ]

119

2020-08-17T16:27:45.000Z

2022-03-28T12:42:56.000Z

one_fm/one_fm/doctype/training_evaluation_form/training_evaluation_form_dashboard.py

askmetoo/One-FM

c93ed63695a3e62ee8129bd9adf563116b749030

[ "MIT" ]

12

2021-05-16T13:35:40.000Z

2022-02-21T12:41:04.000Z

from __future__ import unicode_literals from frappe import _ def get_data(): return { 'fieldname': 'training_evaluation_form', 'transactions': [ { 'items': ['Training Evaluation Form Response'] }, ] }

17.846154

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232

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0

0.241379

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12

52

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0.801136

0

0.377273

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0

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0.090909

true

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0

1

0

null

1

0

null

0

1

0

4

2a261e7faa280fc9f859c3fda281f9cbf7e1c0ed

603

py

Python

hastyherald/agent/hhagent/meta.py

vesche/snippets

7a9d598df99c26c4e0c63669f9f95a94eeed0d08

[ "Unlicense" ]

7

2016-01-03T19:42:07.000Z

2018-10-23T14:03:12.000Z

hastyherald/agent/hhagent/meta.py

vesche/snippets

7a9d598df99c26c4e0c63669f9f95a94eeed0d08

[ "Unlicense" ]

null

hastyherald/agent/hhagent/meta.py

vesche/snippets

7a9d598df99c26c4e0c63669f9f95a94eeed0d08

[ "Unlicense" ]

1

2018-03-09T08:52:01.000Z

"""hhagent.meta""" BANNER = ''' __ __ ____ _____ ______ __ __ __ __ ___ ____ ____ _ ___ | | | / |/ ___/| || | || | | / _]| \ / || | | \\ | | || o ( \_ | || | || | | / [_ | D )| o || | | \\ | _ || |\__ ||_| |_|| ~ || _ || _]| / | || |___ | D | | | || _ |/ \ | | | |___, || | || [_ | \ | _ || || | | | || | |\ | | | | || | || || . \| | || || | |__|__||__|__| \___| |__| |____/ |__|__||_____||__|\_||__|__||_____||_____| ''' VERSION = '0.1.0'

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2a39bd04af16a77e9b458ec933e8d92049153f27

425

py

Python

pgquery/__init__.py

deknowny/pgquery

e8f9093f05fc0825886ba443cd648b5653040088

[ "MIT" ]

2

2021-10-01T21:14:23.000Z

2022-01-29T19:51:55.000Z

pgquery/__init__.py

deknowny/genorm

e8f9093f05fc0825886ba443cd648b5653040088

[ "MIT" ]

null

pgquery/__init__.py

deknowny/genorm

e8f9093f05fc0825886ba443cd648b5653040088

[ "MIT" ]

null

__version__ = "0.1.0a0" from pgquery.builder.actor import BuildingActor from pgquery.builder.clauses.column import ( Integer, References, Serial, Text, Varchar, ) from pgquery.builder.clauses.func import Func from pgquery.builder.clauses.literal import Literal from pgquery.builder.clauses.logical import And, Or from pgquery.builder.clauses.table import Table from pgquery.colorizer import colorize_sql

26.5625

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0.327273

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false

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0.5

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null

1

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null

0

1

0

4

2a3c678ca7b37c361fbb45baee31520af7704235

112

py

Python

modules/2.79/bpy/types/ObjectSolverConstraint.py

cmbasnett/fake-bpy-module

acb8b0f102751a9563e5b5e5c7cd69a4e8aa2a55

[ "MIT" ]

null

modules/2.79/bpy/types/ObjectSolverConstraint.py

cmbasnett/fake-bpy-module

acb8b0f102751a9563e5b5e5c7cd69a4e8aa2a55

[ "MIT" ]

null

modules/2.79/bpy/types/ObjectSolverConstraint.py

cmbasnett/fake-bpy-module

acb8b0f102751a9563e5b5e5c7cd69a4e8aa2a55

[ "MIT" ]

null

class ObjectSolverConstraint: camera = None clip = None object = None use_active_clip = None

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12

112

6

0.666667

0.222222

0

0.294643

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8

30

14

0.911392

0

1

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false

0

1

0

1

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null

1

0

1

0

null

0

1

0

4

2a434e550f7c12fd8bd84bdc8c4d4f5b021278c7

327

py

Python

pysteps/verification/__init__.py

leabeusch/pysteps

5f162d4b1155e4cfd894c9635eed3f0e823adedd

[ "BSD-3-Clause" ]

null

pysteps/verification/__init__.py

leabeusch/pysteps

5f162d4b1155e4cfd894c9635eed3f0e823adedd

[ "BSD-3-Clause" ]

null

pysteps/verification/__init__.py

leabeusch/pysteps

5f162d4b1155e4cfd894c9635eed3f0e823adedd

[ "BSD-3-Clause" ]

null

# -- coding: utf-8 -- """Methods for verification of deterministic, probabilistic and ensemble forecasts.""" from .interface import get_method from .detcatscores import * from .detcontscores import * from .ensscores import * from .plots import * from .probscores import * from .spatialscores import * from .salscores import *

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0.885714

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0

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true

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null

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0

1

0

1

0

1

0

4

2a6d9f61e73d8df3b9a745c4bdd586e3fe0af979

42

py

Python

sheets/python/yaml-dump-without-compact-mode.py

zgmarx/cheatsheet

b29e43a55c5c0fae8763a855025d77a8f46e1208

[ "MIT" ]

1

2020-03-31T11:26:05.000Z

sheets/python/yaml-dump-without-compact-mode.py

zgmarx/cheatsheet

b29e43a55c5c0fae8763a855025d77a8f46e1208

[ "MIT" ]

null

sheets/python/yaml-dump-without-compact-mode.py

zgmarx/cheatsheet

b29e43a55c5c0fae8763a855025d77a8f46e1208

[ "MIT" ]

null

yaml.dump(..., default_flow_style=False)

14

40

0.738095

6

42

4.833333

1

0

0.071429

42

2

41

21

0.74359

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

4

aa49d0989b7347cde26b17cb422ced47a86146e1

165

py

Python

app/models/phone_type.py

olivierpons/evalr

7c76474ad41769804965a11550501321d7b1889b

[ "MIT" ]

null

app/models/phone_type.py

olivierpons/evalr

7c76474ad41769804965a11550501321d7b1889b

[ "MIT" ]

null

app/models/phone_type.py

olivierpons/evalr

7c76474ad41769804965a11550501321d7b1889b

[ "MIT" ]

null

from django.db import models from app.models.base import BaseModel class PhoneType(BaseModel): name = models.CharField(max_length=200, blank=True, null=True)

20.625

66

0.775758

24

165

5.291667

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165

7

67

23.571429

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0

1

0

false

0

0.5

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

aa6b3b1f1f6bc588f92d463ed7d5c0cfdeb40a79

233

py

Python

CodeWars/8 Kyu/Generate user links.py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

CodeWars/8 Kyu/Generate user links.py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

CodeWars/8 Kyu/Generate user links.py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

def generate_link(user): user = ''.join(('%'+hex(ord(let)).upper()[-2:] if not (let.isalpha() or let.isdigit() or let == '_' or let == '.' or let == '/') else let) for let in user) return 'http://www.codewars.com/users/'+user

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aa85f29a4571ab733191e121620646482bf09e3a

96

py

Python

paintera_tools/curate/__init__.py

wolny/paintera_tools

e55b08b5154991873eaea7bf43448ce9da4ad6e7

[ "MIT" ]

1

2019-06-23T21:32:15.000Z

paintera_tools/curate/__init__.py

wolny/paintera_tools

e55b08b5154991873eaea7bf43448ce9da4ad6e7

[ "MIT" ]

null

paintera_tools/curate/__init__.py

wolny/paintera_tools

e55b08b5154991873eaea7bf43448ce9da4ad6e7

[ "MIT" ]

1

2019-08-08T11:36:47.000Z

from .splitter import interactive_splitter, batch_splitter from .postprocess import postprocess

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aa912151eb510ad9b366a0dc69e79ca67410b687

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py

Python

datary/requests/__init__.py

Datary/python-sdk

2790a50e1ad262cbe3210665dc34f497625e923d

[ "MIT" ]

null

datary/requests/__init__.py

Datary/python-sdk

2790a50e1ad262cbe3210665dc34f497625e923d

[ "MIT" ]

null

datary/requests/__init__.py

Datary/python-sdk

2790a50e1ad262cbe3210665dc34f497625e923d

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Datary Requests Module """ from .requests import DataryRequests

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2ab5d83e96ecc91c1450a7c3270cb6d6153ce97c

91

py

Python

hapic/ext/pyramid/__init__.py

raphj/hapic

b169ee901005bbe535e27ec878a051c2c1226e43

[ "MIT" ]

20

2017-10-13T11:23:33.000Z

2021-12-09T12:42:06.000Z

hapic/ext/pyramid/__init__.py

raphj/hapic

b169ee901005bbe535e27ec878a051c2c1226e43

[ "MIT" ]

130

2017-10-10T15:09:13.000Z

2021-12-30T10:36:08.000Z

hapic/ext/pyramid/__init__.py

raphj/hapic

b169ee901005bbe535e27ec878a051c2c1226e43

[ "MIT" ]

7

2017-10-17T07:24:42.000Z

2021-09-16T14:33:17.000Z

# -*- coding: utf-8 -*- from hapic.ext.pyramid.context import PyramidContext # noqa: F401

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2af97c5cd11784e18d857f8842a259dc728a3fb1

162

py

Python

web/servicecalls/siteservice_gets.py

vacoj/mbodjango

e9a6df563862c587e4cc2c2713ed7f8ea0a6e4e3

[ "MIT" ]

8

2015-10-27T12:38:54.000Z

2018-02-23T03:03:24.000Z

web/servicecalls/siteservice_gets.py

vacoj/mbodjango

e9a6df563862c587e4cc2c2713ed7f8ea0a6e4e3

[ "MIT" ]

3

2015-10-28T22:23:58.000Z

2016-01-13T04:05:04.000Z

web/servicecalls/siteservice_gets.py

vacoj/mbodjango

e9a6df563862c587e4cc2c2713ed7f8ea0a6e4e3

[ "MIT" ]

9

2015-09-28T17:32:17.000Z

2018-02-01T00:01:04.000Z

from helpers.mbosoap.SiteService import SiteServiceCalls def GetSessionTypes(): sessiontypes = SiteServiceCalls().GetSessionTypes() return sessiontypes

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2d6f1376c326e99de84c8d2757528c2becc04be7

850

py

Python

sourced/ml/core/extractors/__init__.py

r0mainK/ml-core

ac17828d58e817e771caf2b2c3de523d527874b8

[ "Apache-2.0" ]

13

2019-05-30T21:19:06.000Z

2021-12-22T18:27:55.000Z

sourced/ml/core/extractors/__init__.py

r0mainK/ml-core

ac17828d58e817e771caf2b2c3de523d527874b8

[ "Apache-2.0" ]

23

2019-04-16T11:45:06.000Z

2020-04-08T14:47:08.000Z

sourced/ml/core/extractors/__init__.py

r0mainK/ml-core

ac17828d58e817e771caf2b2c3de523d527874b8

[ "Apache-2.0" ]

16

2019-04-11T14:08:31.000Z

2021-02-03T19:57:14.000Z

# flake8: noqa from sourced.ml.core.extractors.helpers import __extractors__, get_names_from_kwargs, \ register_extractor, filter_kwargs, create_extractors_from_args from sourced.ml.core.extractors.bags_extractor import Extractor, BagsExtractor, RoleIdsExtractor from sourced.ml.core.extractors.identifiers import IdentifiersBagExtractor from sourced.ml.core.extractors.literals import LiteralsBagExtractor from sourced.ml.core.extractors.uast_random_walk import UastRandomWalkBagExtractor from sourced.ml.core.extractors.uast_seq import UastSeqBagExtractor from sourced.ml.core.extractors.children import ChildrenBagExtractor from sourced.ml.core.extractors.graphlets import GraphletBagExtractor from sourced.ml.core.extractors.identifier_distance import IdentifierDistance from sourced.ml.core.extractors.id_sequence import IdSequenceExtractor

65.384615

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2d77106bf97e6427fb58a99bd1f1430d0b47cccc

3,965

py

Python

test.py

MohammadForouhesh/Computational-Political-Science-Papers-Implementations

403bc6123b4e6f4c30667aa135a5d5a588638209

[ "MIT" ]

1

2022-02-19T09:52:47.000Z

test.py

Faethe79/tracking-policy-agendas

1bdc735f37d2d3bdce572fd719f1c7d307db008e

[ "MIT" ]

5

2022-03-12T13:50:30.000Z

2022-03-14T10:34:11.000Z

test.py

Faethe79/tracking-policy-agendas

1bdc735f37d2d3bdce572fd719f1c7d307db008e

[ "MIT" ]

1

2022-02-27T10:00:09.000Z

""" UnitTest Module .................................................................................................... MIT License Copyright (c) 2021-2023 AUT Iran, Mohammad H Forouhesh Copyright (c) 2021-2022 MetoData.ai, Mohammad H Forouhesh .................................................................................................... This module serves as unit testing for various functionalities in the code. """ import unittest from tracking_policy_agendas.api import downloader from tracking_policy_agendas.classifiers.pa_clf import PAClf from tracking_policy_agendas.classifiers.xgb_clf import XgbClf from tracking_policy_agendas.classifiers.naive_bayes_clf import GNBClf from tracking_policy_agendas.classifiers.lasso_clf import LassoClf class XgbTestCase(unittest.TestCase): def setUp(self) -> None: self.clf = XgbClf(text_array=None, labels=None, load_path='xgb_vaccine') def test_xgb_api(self) -> None: self.assertRaises(Exception, downloader, path='wrong-path') def test_xgb_soundness(self) -> None: self.assertEqual(self.clf['تزریق دوز سوم واکسن هم تصویب شد'], self.clf['کرونا با ماسک و واکسن هم از بین نمیرود']) self.assertNotEqual(self.clf['واکسیناسیون عمومی کزاز در ریشه کنی این بیماری بسیار مثمر ثمر بوده است'], self.clf['تزریق دوز سوم واکسن کرونا هم تصویب شد']) def test_xgb_completeness(self) -> None: self.assertEqual(self.clf.predict('دوز سوم واکسن کرونا'), 1) self.assertEqual(self.clf['رئيس‌جمهور جمهوری اسلامی'], 0) self.assertEqual(self.clf['بورس نماد اقتصاد بحران زده‌ی ایران'], 0) class PATestCase(unittest.TestCase): def setUp(self) -> None: self.clf = PAClf(text_array=None, labels=None, load_path='pa_vaccine') def test_pa_api(self) -> None: self.assertRaises(Exception, downloader, path='wrong-path') def test_pa_soundness(self) -> None: self.assertEqual(self.clf['تزریق دوز سوم واکسن هم تصویب شد'], self.clf['کرونا با ماسک و واکسن هم از بین نمیرود']) self.assertNotEqual(self.clf['واکسیناسیون عمومی کزاز در ریشه کنی این بیماری بسیار مثمر ثمر بوده است'], self.clf['تزریق دوز سوم واکسن کرونا هم تصویب شد']) def test_pa_completeness(self) -> None: self.assertEqual(self.clf.predict('دوز سوم واکسن کرونا'), 1) self.assertEqual(self.clf['بورس نماد اقتصاد بحران زده‌ی ایران'], 0) class LassoTestCase(unittest.TestCase): def setUp(self) -> None: self.clf = LassoClf(text_array=None, labels=None, load_path='lasso_vaccine') def test_lasso_api(self) -> None: self.assertRaises(Exception, downloader, path='wrong-path') def test_lasso_soundness(self) -> None: self.assertEqual(self.clf['تزریق دوز سوم واکسن هم تصویب شد'], self.clf['کرونا با ماسک و واکسن هم از بین نمیرود']) self.assertNotEqual(self.clf['واکسیناسیون عمومی کزاز در ریشه کنی این بیماری بسیار مثمر ثمر بوده است'], self.clf['تزریق دوز سوم واکسن کرونا هم تصویب شد']) def test_lasso_completeness(self) -> None: self.assertEqual(self.clf.predict('دوز سوم واکسن کرونا'), 1) class GNBTestCase(unittest.TestCase): def setUp(self) -> None: self.clf = GNBClf(text_array=None, labels=None, load_path='gnb_vaccine') def test_gnb_api(self) -> None: self.assertRaises(Exception, downloader, path='wrong-path') def test_gnb_soundness(self) -> None: self.assertEqual(self.clf['تزریق دوز سوم واکسن کرونا هم تصویب شد'], self.clf['کرونا با ماسک و واکسن هم از بین نمیرود']) def test_gnb_completeness(self) -> None: self.assertEqual(self.clf.predict('دوز سوم واکسن کرونا'), 1) self.assertEqual(self.clf['رئيس‌جمهور جمهوری اسلامی'], 0) self.assertEqual(self.clf['بورس نماد اقتصاد بحران زده‌ی ایران'], 0) if __name__ == '__main__': unittest.main()

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2da751bbaeb1ca599f3c49fa84fbf41ce22a3752

221

py

Python

python_actr/__init__.py

osaaso1/python_actr

f7cb03bcf78310f1a6b68e72d2cef28bd8f83aab

[ "MIT" ]

3

2021-12-11T02:51:51.000Z

2022-01-23T02:33:18.000Z

python_actr/__init__.py

osaaso1/python_actr

f7cb03bcf78310f1a6b68e72d2cef28bd8f83aab

[ "MIT" ]

8

2022-01-17T22:51:27.000Z

2022-03-15T00:44:20.000Z

python_actr/__init__.py

osaaso1/python_actr

f7cb03bcf78310f1a6b68e72d2cef28bd8f83aab

[ "MIT" ]

8

2021-12-06T20:16:35.000Z

2022-03-14T07:21:56.000Z

from .model import Model, log_everything from .production import ProductionSystem from .logger import log, finished from .runner import run, run_with from .display import display from .actr import * from . import version

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4

2da7ea1b35a9a5296e4f8e5e39ea1215a9abc18e

88

py

Python

pg_copy/apps.py

amalek215/django-pg-copy

cf910714dcf6a4fcb820074ebbd4b0f09425e388

[ "BSD-3-Clause" ]

16

2019-03-07T18:22:21.000Z

2022-02-18T11:15:05.000Z

pg_copy/apps.py

amalek215/django-pg-copy

cf910714dcf6a4fcb820074ebbd4b0f09425e388

[ "BSD-3-Clause" ]

2

2018-04-17T22:58:23.000Z

2020-06-26T12:01:14.000Z

pg_copy/apps.py

amalek215/django-pg-copy

cf910714dcf6a4fcb820074ebbd4b0f09425e388

[ "BSD-3-Clause" ]

6

2018-04-17T21:38:12.000Z

2022-01-23T21:30:57.000Z

from django.apps import AppConfig class PgCopyConfig(AppConfig): name = "pg_copy"

14.666667

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2dadd07d8916afa7e7e337da1b04cd245311ecf1

67

py

Python

tests/source/input/import_wordtok_alias.py

tomaarsen/module_dependencies

4b452bf9dcea28df4ed2e632f33eda627b2363f5

[ "MIT" ]

1

2022-01-22T17:11:20.000Z

tests/source/input/import_wordtok_alias.py

tomaarsen/module_dependencies

4b452bf9dcea28df4ed2e632f33eda627b2363f5

[ "MIT" ]

null

tests/source/input/import_wordtok_alias.py

tomaarsen/module_dependencies

4b452bf9dcea28df4ed2e632f33eda627b2363f5

[ "MIT" ]

null

from nltk import word_tokenize as word_tknr tokenizer = word_tknr

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null

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1

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4

2dc0518d3dff01ff0e6c49a1570148ab33823cca

63

py

Python

metaclass/Item.py

majianfei/practice

345f63c2f4118617f0165700e079cb70a32eb4f8

[ "MIT" ]

1

2019-08-13T15:14:12.000Z

metaclass/Item.py

majianfei/practice

345f63c2f4118617f0165700e079cb70a32eb4f8

[ "MIT" ]

null

metaclass/Item.py

majianfei/practice

345f63c2f4118617f0165700e079cb70a32eb4f8

[ "MIT" ]

null

class Item(): def func3(self): print("func3")

12.6

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null

0

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0

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4

2dc9c4e05cc218ee7203cc131f414cb8013e506c

2,614

py

Python

tests/unit/domain/test_event_publishing.py

ets-labs/newsfeed

9f59f94e1cd5f24d4b4121929050fc8b304173af

[ "BSD-3-Clause" ]

10

2019-11-07T15:04:02.000Z

2022-02-19T11:47:40.000Z

tests/unit/domain/test_event_publishing.py

ets-labs/newsfeed

9f59f94e1cd5f24d4b4121929050fc8b304173af

[ "BSD-3-Clause" ]

27

2019-10-31T16:31:27.000Z

2020-01-14T15:21:29.000Z

tests/unit/domain/test_event_publishing.py

ets-labs/newsfeed

9f59f94e1cd5f24d4b4121929050fc8b304173af

[ "BSD-3-Clause" ]

10

2019-11-07T15:08:43.000Z

2021-12-03T22:31:49.000Z

"""Event publishing tests.""" async def test_event_publishing(container): """Check event publishing.""" newsfeed_id = '123' event_dispatcher_service = container.event_dispatcher_service() event_processor_service = container.event_processor_service() await _process_event( event_dispatcher_service, event_processor_service, newsfeed_id=newsfeed_id, data={ 'event_data': 'some_data_1', }, ) await _process_event( event_dispatcher_service, event_processor_service, newsfeed_id=newsfeed_id, data={ 'event_data': 'some_data_2', }, ) event_repository = container.event_repository() events = await event_repository.get_by_newsfeed_id(newsfeed_id) assert events[0].data == { 'event_data': 'some_data_2', } assert events[1].data == { 'event_data': 'some_data_1', } async def test_event_publishing_to_subscriber(container): """Check event publishing.""" newsfeed_id = '123' subscriber_newsfeed_id = '124' subscription_service = container.subscription_service() await subscription_service.create_subscription( newsfeed_id=subscriber_newsfeed_id, to_newsfeed_id=newsfeed_id, ) event_dispatcher_service = container.event_dispatcher_service() event_processor_service = container.event_processor_service() await _process_event( event_dispatcher_service, event_processor_service, newsfeed_id=newsfeed_id, data={ 'event_data': 'some_data_1', }, ) await _process_event( event_dispatcher_service, event_processor_service, newsfeed_id=newsfeed_id, data={ 'event_data': 'some_data_2', }, ) event_repository = container.event_repository() events = await event_repository.get_by_newsfeed_id(newsfeed_id) assert events[0].data == { 'event_data': 'some_data_2', } assert events[1].data == { 'event_data': 'some_data_1', } subscriber_events = await event_repository.get_by_newsfeed_id(subscriber_newsfeed_id) assert subscriber_events[0].data == { 'event_data': 'some_data_2', } assert subscriber_events[1].data == { 'event_data': 'some_data_1', } async def _process_event(event_dispatcher_service, event_processor_service, newsfeed_id, data): await event_dispatcher_service.dispatch_new_event( newsfeed_id=newsfeed_id, data=data, ) await event_processor_service.process_event()

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9307bf35dd2fd7ee77bca328781097b1712f3450

23

py

Python

cantools/version.py

sfpetersen/cantools

e6437431914183161c585889097f067f578843d4

[ "MIT" ]

null

cantools/version.py

sfpetersen/cantools

e6437431914183161c585889097f067f578843d4

[ "MIT" ]

null

cantools/version.py

sfpetersen/cantools

e6437431914183161c585889097f067f578843d4

[ "MIT" ]

null

__version__ = '35.4.0'

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1

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null

0

4

930d5b47414d786e77b827dd3107e4cabd5aba96

207

py

Python

weborquesta/music/views.py

miguel-rojorev/weborquesta

d0c98e1acea1346d521deb2ec15ae76d9c855546

[ "MIT" ]

null

weborquesta/music/views.py

miguel-rojorev/weborquesta

d0c98e1acea1346d521deb2ec15ae76d9c855546

[ "MIT" ]

null

weborquesta/music/views.py

miguel-rojorev/weborquesta

d0c98e1acea1346d521deb2ec15ae76d9c855546

[ "MIT" ]

null

from django.shortcuts import render from .models import Music # Create your views here. def music(request): audios = Music.objects.all() return render(request, "music/music.html", {'audios':audios})

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9362b63dc77c88ff9a66bbb49db7f78d13980c7d

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py

Python

todo_api/serializers.py

Saknowman/django_setting_sample_project

3f11103a57628190ed4ab480cba39d4474847040

[ "MIT" ]

null

todo_api/serializers.py

Saknowman/django_setting_sample_project

3f11103a57628190ed4ab480cba39d4474847040

[ "MIT" ]

7

2020-06-06T00:28:14.000Z

2022-02-10T11:03:44.000Z

todo_api/serializers.py

Saknowman/django_setting_sample_project

3f11103a57628190ed4ab480cba39d4474847040

[ "MIT" ]

null

from rest_framework import serializers from .models import Task class TaskSerializer(serializers.ModelSerializer): class Meta: model = Task fields = ['title', 'status']

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fac0cfd49abb091ebc16d9f6ab886e7b920930b4

191

py

Python

third_party/phkit/phkit/chinese/pinyin.py

zh794390558/DeepSpeech

34178893327ad359cb816e55d7c66a10244fa08a

[ "Apache-2.0" ]

null

third_party/phkit/phkit/chinese/pinyin.py

zh794390558/DeepSpeech

34178893327ad359cb816e55d7c66a10244fa08a

[ "Apache-2.0" ]

null

third_party/phkit/phkit/chinese/pinyin.py

zh794390558/DeepSpeech

34178893327ad359cb816e55d7c66a10244fa08a

[ "Apache-2.0" ]

null

#!usr/bin/env python # -*- coding: utf-8 -*- # author: kuangdd # date: 2020/2/17 """ #### pinyin 转为拼音的方法，汉字转拼音，分离声调。拼音为字母+数字形式，例如pin1。 """ from ..pinyinkit import text2pinyin, split_pinyin

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faca5ef88bb7ecfa9f9dbf44a164934f02e900b4

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py

Python

opencolorio_config_aces/config/studio/generate/__init__.py

michdolan/OpenColorIO-Config-ACES

5216c2a184e03529557993b7dc670d351aadddc7

[ "BSD-3-Clause" ]

52

2020-05-19T05:05:11.000Z

2022-03-29T20:20:42.000Z

opencolorio_config_aces/config/studio/generate/__init__.py

michdolan/OpenColorIO-Config-ACES

5216c2a184e03529557993b7dc670d351aadddc7

[ "BSD-3-Clause" ]

41

2020-05-17T03:18:24.000Z

2022-03-31T12:02:35.000Z

opencolorio_config_aces/config/studio/generate/__init__.py

michdolan/OpenColorIO-Config-ACES

5216c2a184e03529557993b7dc670d351aadddc7

[ "BSD-3-Clause" ]

12

2020-05-18T18:21:57.000Z

2022-03-29T20:00:55.000Z

# SPDX-License-Identifier: BSD-3-Clause # Copyright Contributors to the OpenColorIO Project.

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faf1d9d0d06a202750017725065478e26d66dc7d

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py

Python

antlir/tests/test_unionfind.py

SaurabhAgarwala/antlir

d9513d35d3eaa9d28717a40057a14d099c6ec775

[ "MIT" ]

28

2020-08-11T16:22:46.000Z

2022-03-04T15:41:52.000Z

antlir/tests/test_unionfind.py

SaurabhAgarwala/antlir

d9513d35d3eaa9d28717a40057a14d099c6ec775

[ "MIT" ]

137

2020-08-11T16:07:49.000Z

2022-02-27T10:59:05.000Z

antlir/tests/test_unionfind.py

SaurabhAgarwala/antlir

d9513d35d3eaa9d28717a40057a14d099c6ec775

[ "MIT" ]

10

2020-09-10T00:01:28.000Z

2022-03-08T18:00:28.000Z

#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. import unittest from ..unionfind import UnionFind class TestUnionFind(unittest.TestCase): def setUp(self): self.union_find = UnionFind() def test_find(self): """Tests implementation details and find with path compression""" self.union_find.add(1) self.assertEqual(self.union_find._parent(1), 1) self.union_find.union(2, 1) self.assertEqual(self.union_find._parent(1), 1) self.assertEqual(self.union_find._parent(2), 1) self.assertEqual(self.union_find.find(3), 3) self.union_find.union(3, 2) self.assertEqual(self.union_find._parent(3), 1) def test_flatten(self): """Tests implementation of flatten(), which should do find on all keys""" self.union_find.add(1) self.union_find.union(3, 2) self.union_find.union(7, 5) self.union_find.union(2, 1) self.union_find.union(4, 2) self.union_find.union(5, 2) self.union_find.union(6, 5) self.union_find.add(14) self.union_find.union(14, 12) self.union_find.union(15, 13) self.union_find.union(16, 11) self.union_find.union(15, 14) self.union_find.union(16, 17) self.union_find.union(13, 11) self.assertEqual(self.union_find._representative_dict[1], 1) self.assertEqual(self.union_find._representative_dict[2], 1) self.assertEqual(self.union_find._representative_dict[3], 2) self.assertEqual(self.union_find._representative_dict[4], 1) self.assertEqual(self.union_find._representative_dict[5], 1) self.assertEqual(self.union_find._representative_dict[6], 1) self.assertEqual(self.union_find._representative_dict[7], 5) self.assertEqual(self.union_find._representative_dict[11], 17) self.assertEqual(self.union_find._representative_dict[12], 17) self.assertEqual(self.union_find._representative_dict[13], 12) self.assertEqual(self.union_find._representative_dict[14], 12) self.assertEqual(self.union_find._representative_dict[15], 13) self.assertEqual(self.union_find._representative_dict[16], 11) self.assertEqual(self.union_find._representative_dict[17], 17) self.union_find.flatten() self.assertEqual(self.union_find._representative_dict[1], 1) self.assertEqual(self.union_find._representative_dict[2], 1) self.assertEqual(self.union_find._representative_dict[3], 1) self.assertEqual(self.union_find._representative_dict[4], 1) self.assertEqual(self.union_find._representative_dict[5], 1) self.assertEqual(self.union_find._representative_dict[6], 1) self.assertEqual(self.union_find._representative_dict[7], 1) self.assertEqual(self.union_find._representative_dict[11], 17) self.assertEqual(self.union_find._representative_dict[12], 17) self.assertEqual(self.union_find._representative_dict[13], 17) self.assertEqual(self.union_find._representative_dict[14], 17) self.assertEqual(self.union_find._representative_dict[15], 17) self.assertEqual(self.union_find._representative_dict[16], 17) self.assertEqual(self.union_find._representative_dict[17], 17) def test_enumerate(self): union_find = UnionFind() union_find.add(1) union_find.union(2, 1) union_find.union(3, 2) count = 0 for _ in union_find: count += 1 self.assertEqual(count, 3) keys = list(union_find) self.assertEqual(keys[0], 1) def test_iteritems(self): union_find = UnionFind() union_find.add(1) union_find.union(2, 1) union_find.union(3, 2) count = 0 for key, val in union_find.items(): count += 1 self.assertEqual(union_find.find(key), val) self.assertEqual(count, 3) def test_persistence(self): """Makes sure that once two nodes are joined, they do not split""" union_find = UnionFind() union_find.add(1) union_find.union(1, 2) self.assertEqual(union_find.find(1), 2) self.assertEqual(union_find.find(2), 2) union_find.add(1) union_find.add(2) self.assertEqual(union_find.find(1), 2) self.assertEqual(union_find.find(2), 2) if __name__ == "__main__": unittest.main()

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87b209f3a6ca98164e4289ed16e73f9f7fcb2798

273

py

Python

classes/Internal_Rate_Return.py

Fixed-Income-OS/fixedincome-py

9dc1ef0faf2d26cfacc9d79eed0e2f12cdb5b1fa

[ "Apache-2.0" ]

4

2019-11-25T04:22:59.000Z

2021-05-18T04:57:16.000Z

classes/Internal_Rate_Return.py

Fixed-Income-OS/fixedincome-py

9dc1ef0faf2d26cfacc9d79eed0e2f12cdb5b1fa

[ "Apache-2.0" ]

5

2019-11-15T00:29:52.000Z

2021-06-02T00:37:37.000Z

classes/Internal_Rate_Return.py

Fixed-Income-OS/fixedincome-py

9dc1ef0faf2d26cfacc9d79eed0e2f12cdb5b1fa

[ "Apache-2.0" ]

4

2020-03-03T20:06:48.000Z

2022-02-19T02:01:56.000Z

import numpy as np class InternalRateReturn: def __init__(self, price, cash_flow): self.price = price self.cash_flow = cash_flow def calculate(self): self.cash_flow.insert(0, self.price) return round(np.irr(self.cash_flow) * 100)

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87cb51f6547fdf60661f8e9bb827a71aef585c0c

290

py

Python

src/models/composed_lstm.py

clin366/airpollutionnowcast

f9152583eebc4ad747c8d0510460334a5fb23ff9

[ "MIT" ]

null

src/models/composed_lstm.py

clin366/airpollutionnowcast

f9152583eebc4ad747c8d0510460334a5fb23ff9

[ "MIT" ]

9

2020-03-24T18:12:45.000Z

2022-02-10T00:36:57.000Z

src/models/composed_lstm.py

clin366/airpollutionnowcast

f9152583eebc4ad747c8d0510460334a5fb23ff9

[ "MIT" ]

null

''' Author: Chen Lin Email: chen.lin@emory.edu Date created: 2019/9/21 Python Version: 3.6 ''' import sys sys.path.append('.') from src.models.composed_model import ComposedModel from src.models.lstm import LSTMModel class ComposedLSTM(ComposedModel, LSTMModel): pass

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e21109bbcd13b1d8abce2d567e66e0bbf467be0d

115

py

Python

b8/paths.py

aliafshar/b8

81cdb5c687299e7ecd7b0c8f75e54a19b392d0f2

[ "Unlicense" ]

4

2020-11-01T22:55:14.000Z

2022-03-30T16:48:21.000Z

b8/paths.py

aliafshar/b8

81cdb5c687299e7ecd7b0c8f75e54a19b392d0f2

[ "Unlicense" ]

1

2020-11-01T22:49:32.000Z

2020-11-01T23:02:36.000Z

b8/paths.py

aliafshar/b8

81cdb5c687299e7ecd7b0c8f75e54a19b392d0f2

[ "Unlicense" ]

null

28.75

47

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115

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0

4

35534aa031751fe671ef7f7a6c91d73c584d08db

4,782

py

Python

core/admin/migrations/versions/546b04c886f0_.py

mboogert/Mailu

ebf6d84aabebe854824546df3ea64566107ed004

[ "MIT" ]

3,620

2016-10-30T14:13:46.000Z

2022-03-31T18:40:15.000Z

core/admin/migrations/versions/546b04c886f0_.py

mboogert/Mailu

ebf6d84aabebe854824546df3ea64566107ed004

[ "MIT" ]

2,113

2016-10-27T10:36:52.000Z

2022-03-31T16:38:26.000Z

core/admin/migrations/versions/546b04c886f0_.py

mboogert/Mailu

ebf6d84aabebe854824546df3ea64566107ed004

[ "MIT" ]

815

2016-10-29T12:02:00.000Z

2022-03-31T08:44:28.000Z

""" Fix constraint naming by addint a name to all constraints Revision ID: 546b04c886f0 Revises: 5aeb5811408e Create Date: 2018-12-08 16:33:37.757634 """ # revision identifiers, used by Alembic. revision = '546b04c886f0' down_revision = 'cd79ed46d9c2' from alembic import op, context import sqlalchemy as sa def upgrade(): # Only run this for somehow supported data types at the date we started naming constraints # Among others, these will probably fail on MySQL if context.get_bind().engine.name not in ('sqlite', 'postgresql'): return metadata = context.get_context().opts['target_metadata'] # Drop every constraint on every table with op.batch_alter_table('alias', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('alias_pkey', type_="primary") batch_op.drop_constraint('alias_domain_name_fkey', type_="foreignkey") with op.batch_alter_table('alternative', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('alternative_pkey', type_="primary") batch_op.drop_constraint('alternative_domain_name_fkey', type_="foreignkey") with op.batch_alter_table('manager', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('manager_domain_name_fkey', type_="foreignkey") batch_op.drop_constraint('manager_user_email_fkey', type_="foreignkey") with op.batch_alter_table('token', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('token_pkey', type_="primary") batch_op.drop_constraint('token_user_email_fkey', type_="foreignkey") with op.batch_alter_table('fetch', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('fetch_pkey', type_="primary") batch_op.drop_constraint('fetch_user_email_fkey', type_="foreignkey") with op.batch_alter_table('relay', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('relay_pkey', type_="primary") with op.batch_alter_table('config', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('config_pkey', type_="primary") with op.batch_alter_table('user', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('user_pkey', type_="primary") batch_op.drop_constraint('user_domain_name_fkey', type_="foreignkey") with op.batch_alter_table('domain', naming_convention=metadata.naming_convention) as batch_op: batch_op.drop_constraint('domain_pkey', type_="primary") # Recreate constraints with proper names with op.batch_alter_table('domain', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_primary_key('domain_pkey', ['name']) with op.batch_alter_table('alias', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_primary_key('alias_pkey', ['email']) batch_op.create_foreign_key('alias_domain_name_fkey', 'domain', ['domain_name'], ['name']) with op.batch_alter_table('user', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_primary_key('user_pkey', ['email']) batch_op.create_foreign_key('user_domain_name_fkey', 'domain', ['domain_name'], ['name']) with op.batch_alter_table('alternative', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_primary_key('alternative_pkey', ['name']) batch_op.create_foreign_key('alternative_domain_name_fkey', 'domain', ['domain_name'], ['name']) with op.batch_alter_table('manager', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_foreign_key('manager_domain_name_fkey', 'domain', ['domain_name'], ['name']) batch_op.create_foreign_key('manager_user_email_fkey', 'user', ['user_email'], ['email']) with op.batch_alter_table('token', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_primary_key('token_pkey', ['id']) batch_op.create_foreign_key('token_user_email_fkey', 'user', ['user_email'], ['email']) with op.batch_alter_table('fetch', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_primary_key('fetch_pkey', ['id']) batch_op.create_foreign_key('fetch_user_email_fkey', 'user', ['user_email'], ['email']) with op.batch_alter_table('relay', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_primary_key('relay_pkey', ['name']) with op.batch_alter_table('config', naming_convention=metadata.naming_convention) as batch_op: batch_op.create_primary_key('config_pkey', ['name']) def downgrade(): pass

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3566d74ed2d08a35c1f17560269150324ee95b0e

86

py

Python

binset/apps.py

wh8983298/GreaterWMS

487e819fcf21a0dca1c74f5b44bc7221353ea3e2

[ "Apache-2.0" ]

1,063

2020-11-15T12:55:15.000Z

2022-03-31T14:33:12.000Z

binset/apps.py

ashrafali46/GreaterWMS

1aed14a8c26c8ac4571db5e6b07ab7e4fa3c7c72

[ "Apache-2.0" ]

96

2020-11-18T00:06:05.000Z

2022-03-03T09:05:39.000Z

binset/apps.py

ashrafali46/GreaterWMS

1aed14a8c26c8ac4571db5e6b07ab7e4fa3c7c72

[ "Apache-2.0" ]

349

2020-11-15T13:15:30.000Z

2022-03-31T11:01:15.000Z

from django.apps import AppConfig class BinsetConfig(AppConfig): name = 'binset'

17.2

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358b15031a69d3752e5b10a1216da08bdf18876b

103

py

Python

src/audio_processor/__init__.py

Brian-Pho/RVST598_Speech_Emotion_Recognition

e31d2c948319f0f38515e509545b39f2e0ecac96

[ "MIT" ]

2

2019-10-25T14:59:16.000Z

2019-11-22T13:15:28.000Z

src/audio_processor/__init__.py

Brian-Pho/RVST598_Speech-Emotion-Recognition

e31d2c948319f0f38515e509545b39f2e0ecac96

[ "MIT" ]

null

src/audio_processor/__init__.py

Brian-Pho/RVST598_Speech-Emotion-Recognition

e31d2c948319f0f38515e509545b39f2e0ecac96

[ "MIT" ]

null

""" This package processes audio data into a more usable format for machine learning applications. """

20.6

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0

1

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1

0

null

0

1

0

4

35928f3a83f68b0623531c902c54c5cfd75d99eb

454

py

Python

choria_discovery/discovery.py

optiz0r/py-choria-discovery

3db3e017861479370d40904f0f8e8971faeba737

[ "Apache-2.0" ]

null

choria_discovery/discovery.py

optiz0r/py-choria-discovery

3db3e017861479370d40904f0f8e8971faeba737

[ "Apache-2.0" ]

null

choria_discovery/discovery.py

optiz0r/py-choria-discovery

3db3e017861479370d40904f0f8e8971faeba737

[ "Apache-2.0" ]

null

import logging from choria_external.base import ChoriaExternal # Ensure the protocol messages are loaded and registered import choria_discovery.protocol class Discovery(ChoriaExternal): """ Base class for External Discovery requests """ def discover(self): """ Implement the node discovery action This method should be overridden by subclasses """ pass def execute(self): self.discover()

21.619048

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35a24a27a7b9b6c0a4d8b126617353c093939585

62

py

Python

src/ralph/deployment/__init__.py

DoNnMyTh/ralph

97b91639fa68965ad3fd9d0d2652a6545a2a5b72

[ "Apache-2.0" ]

1,668

2015-01-01T12:51:20.000Z

2022-03-29T09:05:35.000Z

src/ralph/deployment/__init__.py

hq-git/ralph

e2448caf02d6e5abfd81da2cff92aefe0a534883

[ "Apache-2.0" ]

2,314

2015-01-02T13:26:26.000Z

2022-03-29T04:06:03.000Z

src/ralph/deployment/__init__.py

hq-git/ralph

e2448caf02d6e5abfd81da2cff92aefe0a534883

[ "Apache-2.0" ]

534

2015-01-05T12:40:28.000Z

2022-03-29T21:10:12.000Z

default_app_config = 'ralph.deployment.apps.DeploymentConfig'

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1

0

1

null

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35adeb92c268593776c6216a1b47db4dc988df5e

378

py

Python

src/libcask/error.py

ianpreston/cask

9e1d9c38b5a9b8827547ed963b0018003abbb047

[ "MIT" ]

6

2016-01-23T23:24:24.000Z

2022-03-06T04:19:01.000Z

src/libcask/error.py

ianpreston/cask

9e1d9c38b5a9b8827547ed963b0018003abbb047

[ "MIT" ]

null

src/libcask/error.py

ianpreston/cask

9e1d9c38b5a9b8827547ed963b0018003abbb047

[ "MIT" ]

null

class ContainerError(Exception): pass class AlreadyRunning(ContainerError): pass class NotRunning(ContainerError): pass class AlreadyExists(ContainerError): pass class AttributeInvalid(ContainerError): pass class NoSuchContainer(ContainerError): pass class NoSuchImage(ContainerError): pass class InvalidImage(ContainerError): pass

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null

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1

0

4

35b6e519ab315d0ee6a9b9185230ec479fb83e6b

1,504

py

Python

apps/homepage/serializers.py

ShAlireza/gamein-backend

cd7db7a06cacb4398fb89d291e7fc796702157a2

[ "MIT" ]

5

2020-05-26T12:50:29.000Z

2020-06-09T19:22:16.000Z

apps/homepage/serializers.py

ShAlireza/gamein-backend

cd7db7a06cacb4398fb89d291e7fc796702157a2

[ "MIT" ]

7

2021-03-30T13:28:52.000Z

2022-01-13T02:45:23.000Z

apps/homepage/serializers.py

ShAlireza/gamein-backend

cd7db7a06cacb4398fb89d291e7fc796702157a2

[ "MIT" ]

1

2020-05-29T14:08:05.000Z

from drf_yasg.utils import swagger_serializer_method from rest_framework import serializers from .models import * from rest_framework.serializers import ModelSerializer class AboutSerializer(ModelSerializer): class Meta: model = About fields = '__all__' class StatisticsSerializer(ModelSerializer): class Meta: model = Statistics fields = '__all__' class EventSerializer(ModelSerializer): class Meta: model = Event fields = '__all__' class WinnerSerializer(ModelSerializer): class Meta: model = Winner fields = '__all__' class StaffSerializer(ModelSerializer): class Meta: model = Staff fields = '__all__' class StaffTeamSerializer(ModelSerializer): class Meta: model = StaffTeam fields = '__all__' class SponsorSerializer(ModelSerializer): class Meta: model = Sponsor fields = '__all__' class QuoteSerializer(ModelSerializer): class Meta: model = Quote fields = '__all__' class SocialSerializer(ModelSerializer): class Meta: model = Social fields = '__all__' class VideoSerializer(ModelSerializer): class Meta: model = Video fields = '__all__' class FAQSerializer(ModelSerializer): class Meta: model = FAQ fields = '__all__' class HomepageSerializer(ModelSerializer): class Meta: model = Homepage fields = '__all__' depth = 3

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7.075758

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0

null

0

1

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35d18cab4f5990676a33217f63251faa5f3f2037

382

py

Python

Application/remove_from_blacklist.py

soheyldaliraan/instagram_sub_bot_remover

8ccf7134c79b8a9c9c09413321f526dd388c5609

[ "MIT" ]

27

2019-02-10T09:04:36.000Z

2022-03-07T21:44:26.000Z

Application/remove_from_blacklist.py

soheyldaliraan/instagram_sub_bot_remover

8ccf7134c79b8a9c9c09413321f526dd388c5609

[ "MIT" ]

1

2022-03-01T02:45:18.000Z

Application/remove_from_blacklist.py

soheyldaliraan/instagram_sub_bot_remover

8ccf7134c79b8a9c9c09413321f526dd388c5609

[ "MIT" ]

5

2019-12-27T07:43:33.000Z

2022-02-15T19:51:37.000Z

import os import pandas as pd import configuration def remove_from_blacklist(pk): if os.path.exists(configuration.blacklist_path): black_dataset = pd.read_csv(configuration.blacklist_path) black_dataset.drop(black_dataset[black_dataset['pk'] == pk].index, inplace=True) black_dataset.to_csv(configuration.blacklist_path, columns=['pk', 'username'])

27.285714

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0.5

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null

1

0

null

0

1

0

4

ea3923e81a3fa7afd6634fb00836d13902e8813d

171

py

Python

serious_shop/items/apps.py

ImustAdmit/django-serious-shop

e2145f2315b4afdfe1fc35fb2b6e02adc0df33c5

[ "MIT" ]

1

2020-09-17T13:40:42.000Z

serious_shop/items/apps.py

ImustAdmit/django-serious-shop

e2145f2315b4afdfe1fc35fb2b6e02adc0df33c5

[ "MIT" ]

null

serious_shop/items/apps.py

ImustAdmit/django-serious-shop

e2145f2315b4afdfe1fc35fb2b6e02adc0df33c5

[ "MIT" ]

null

from django.apps import AppConfig from django.utils.translation import ugettext_lazy as _ class ItemsConfig(AppConfig): name = "items" verbose_name = _("Items")

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null

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4

ea498d1934f7e64e034ea99a3852ff7fdab2b8dc

191

py

Python

docs/examples/compute/digitalocean/instantiate_api_v1.0.py

atsaki/libcloud

ae85479e835494e196e2f6e79aae9a475603d8ac

[ "Apache-2.0" ]

3

2016-06-03T03:40:18.000Z

2018-09-24T05:28:47.000Z

docs/examples/compute/digitalocean/instantiate_api_v1.0.py

atsaki/libcloud

ae85479e835494e196e2f6e79aae9a475603d8ac

[ "Apache-2.0" ]

1

2015-10-26T21:29:56.000Z

2015-10-27T17:29:20.000Z

docs/examples/compute/digitalocean/instantiate_api_v1.0.py

atsaki/libcloud

ae85479e835494e196e2f6e79aae9a475603d8ac

[ "Apache-2.0" ]

3

2016-02-08T23:38:18.000Z

2019-11-05T00:31:34.000Z

from libcloud.compute.types import Provider from libcloud.compute.providers import get_driver cls = get_driver(Provider.DIGITAL_OCEAN) driver = cls('client id', 'api key', api_version='v1')

31.833333

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0

1

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4

ea74e5fbf7a46a012c2919a0ff73451f60eaa6a2

562

py

Python

src/sage/rings/complex_field.py

UCD4IDS/sage

43474c96d533fd396fe29fe0782d44dc7f5164f7

[ "BSL-1.0" ]

1,742

2015-01-04T07:06:13.000Z

2022-03-30T11:32:52.000Z

src/sage/rings/complex_field.py

UCD4IDS/sage

43474c96d533fd396fe29fe0782d44dc7f5164f7

[ "BSL-1.0" ]

66

2015-03-19T19:17:24.000Z

2022-03-16T11:59:30.000Z

src/sage/rings/complex_field.py

UCD4IDS/sage

43474c96d533fd396fe29fe0782d44dc7f5164f7

[ "BSL-1.0" ]

495

2015-01-10T10:23:18.000Z

2022-03-24T22:06:11.000Z

r""" Deprecated in favor of :mod:`sage.rings.complex_mpfr` TESTS:: sage: from sage.rings.complex_field import ComplexField doctest:warning ... DeprecationWarning: the complex_field module is deprecated, please use sage.rings.complex_mpfr See http://trac.sagemath.org/24483 for details. sage: ComplexField() Complex Field with 53 bits of precision """ from sage.misc.superseded import deprecation from sage.rings.complex_mpfr import * deprecation(24483, "the complex_field module is deprecated, please use sage.rings.complex_mpfr")

31.222222

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0.106635

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0.293839

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1

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null

0

1

0

1

0

4

ea770b71bab0b926d4f77cb36e86c70b6b4b3dbc

214

py

Python

TargetNone.py

Bob-Z/RoRBot

d8b45e48bcebc3ed9905fa5ff05fd5e3509fd18f

[ "Apache-2.0" ]

null

TargetNone.py

Bob-Z/RoRBot

d8b45e48bcebc3ed9905fa5ff05fd5e3509fd18f

[ "Apache-2.0" ]

null

TargetNone.py

Bob-Z/RoRBot

d8b45e48bcebc3ed9905fa5ff05fd5e3509fd18f

[ "Apache-2.0" ]

null

class TargetNone: def __init__(self): pass def run(self, position, rotation, speed_ms, rot_diff, target_speed_ms, go_up): return 0.0, 0.0, 0.0 def reset(self): self.__init__()

21.4

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1

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1

0

4

ea7c1f7ee251dcd0d9748e2d0e10641305897adc

173

py

Python

tests/core/admin-module/test_admin_nodeInfo.py

happyuc-project/webu.py

5a01124fc84d74df09a33d9dabe88b704cd5b6c6

[ "MIT" ]

null

tests/core/admin-module/test_admin_nodeInfo.py

happyuc-project/webu.py

5a01124fc84d74df09a33d9dabe88b704cd5b6c6

[ "MIT" ]

null

tests/core/admin-module/test_admin_nodeInfo.py

happyuc-project/webu.py

5a01124fc84d74df09a33d9dabe88b704cd5b6c6

[ "MIT" ]

null

def test_admin_nodeInfo(webu, skip_if_testrpc): skip_if_testrpc(webu) node_info = webu.admin.nodeInfo assert 'enode' in node_info assert 'id' in node_info

21.625

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1

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1

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null

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4

ea8074848d6eefc73108f8591ed9efa5b23d5c40

17,682

py

Python

src/models/transformer_model.py

flowersteam/spatio-temporal-language-transformers

a33a9bc4748586ef08f9768de2aafd76de71823c

[ "MIT" ]

3

2021-11-26T18:04:53.000Z

2022-01-02T05:28:04.000Z

src/models/transformer_model.py

flowersteam/spatio-temporal-language-transformers

a33a9bc4748586ef08f9768de2aafd76de71823c

[ "MIT" ]

null

src/models/transformer_model.py

flowersteam/spatio-temporal-language-transformers

a33a9bc4748586ef08f9768de2aafd76de71823c

[ "MIT" ]

null

""" This module implements the models used for the experiments. """ import math import torch import torch.nn as nn from functools import reduce from src.models.shared import Feedforward ### Helper fns prod = lambda x, y: x * y prod_reduce = lambda l: reduce(prod, l, 1) ### Helper modules class PositionalEncoding(nn.Module): """ Positional encoding matrix based on sinusoids. From pytorch language modeling example here: https://pytorch.org/tutorials/beginner/transformer_tutorial.html """ def __init__(self, d_model, dropout=0.1, max_len=5000, device=torch.device('cpu')): super().__init__() self.dropout = nn.Dropout(p=dropout) pe = torch.zeros(max_len, d_model, device=device) position = torch.arange(0, max_len, dtype=torch.float, device=device).unsqueeze(1) div_term = torch.exp( torch.arange( 0, d_model, 2, device=device ).float() * (-math.log(10000.0) / d_model) ) pe[:, 0::2] = torch.sin(position * div_term) pe[:, 1::2] = torch.cos(position * div_term) pe = pe.unsqueeze(0).transpose(0, 1) self.register_buffer('pe', pe) def forward(self, x): # x is [T, B, (Nobj), H] if len(x.shape) == 4: # adaptation for tensors with 4 dimensions pe = self.pe.unsqueeze(1) else: pe = self.pe x = x + pe[:x.size(0)] return self.dropout(x) class TransformerModule(nn.Module): """ Wrapper around the TransformerEncoderLayer and TransformerEncoder. Also allows for easier processing of 4+ dimensional tensors; the first dimension in considered as the obj dim on which to perform self-attention; the middle dims (at least 1) are considered as batch dims and have no effect, the last dim is considered as the feature dim. """ def __init__(self, hidden_size, num_heads, num_layers, dropout=0.1): super().__init__() tfm_layer = nn.TransformerEncoderLayer( hidden_size, num_heads, hidden_size, dropout=dropout, ) layernorm = nn.LayerNorm(hidden_size) self.tfm = nn.TransformerEncoder( tfm_layer, num_layers, layernorm, ) def forward(self, x): if len(x.shape) == 3: return self.tfm(x) elif len(x.shape) > 3: shape = list(x.shape) mid_shape = shape[1:-1] mid_size = prod_reduce(mid_shape) x = x.reshape(shape[0], mid_size, shape[-1]) x = self.tfm(x) x = x.reshape(shape[:1] + mid_shape + shape[-1:]) return x else: raise ValueError('Invalid shape for input') class Transformer_UT(nn.Module): """ This model concatenates all the tokens corresponding to temporal traces of objects and words in the sentence, and performs num_layers of self-attention over all tokens. A learned query vector is used to query the transformed tensors. Parameters: - body_size: number of body features; - obj_size: number of object features; - voc_size: size of the vocabulary used in descriptions of the scene - seq_length: maximum size of a sentence; - hidden_size: size of: the output of the core and object encoding layers, the hidden layers of both Transformers; - num_heads: number of attention heads in both Transformers; - num_layers: number of layers in both Transformers; - dropout: dropout used in the Transformers, defaults to 0.1; - device: device on which to load the model; - word_aggreg: whether to use word_aggregation, if True the model becomes UT-WA """ def __init__(self, body_size, obj_size, voc_size, seq_length, hidden_size, num_heads, num_layers, dropout=0.1, device=torch.device('cpu'), word_aggreg=False, **kwargs): super().__init__() self.body_size = body_size self.obj_size = obj_size self.voc_size = voc_size self.seq_length = seq_length self.ff_size = hidden_size self.hidden_size = hidden_size self.num_heads = num_heads self.num_layers = num_layers self.dropout = dropout self.device = device self.word_aggreg = word_aggreg self.fc_cast_body = Feedforward(self.body_size, [self.ff_size, self.hidden_size]) self.fc_cast_obj = Feedforward(self.obj_size, [self.ff_size, self.hidden_size]) self.fc_cast_words = Feedforward(self.voc_size, [self.ff_size, self.hidden_size]) # init cls token self.query = nn.Parameter(torch.zeros(self.hidden_size)) # self.query_token = torch.zeros(self.hidden_size, device=device) self.sensory_oh = torch.tensor([1., 0.], device=device) self.linguistic_oh = torch.tensor([0., 1.], device=device) self.dim_adjust_proj = nn.Linear(self.hidden_size + 2, self.hidden_size) self.fc_out = Feedforward(self.hidden_size, [self.ff_size, 1]) self.transformer = TransformerModule( hidden_size=hidden_size, num_heads=num_heads, num_layers=num_layers, dropout=dropout, ) if self.word_aggreg: self.word_transformer = TransformerModule( hidden_size=hidden_size, num_heads=num_heads, num_layers=num_layers, dropout=dropout, ) self.pe = PositionalEncoding(self.hidden_size, device=device, dropout=dropout) self.device = device self.to(self.device) def forward(self, state_trace, body_trace, description): state_trace = self.fc_cast_obj(state_trace) # [B, T, Nobj, h] body_trace = self.fc_cast_body(body_trace) # [B, T, 1, h] words = self.fc_cast_words(description) # [B, Seq, h] query_token = self.query B, T, Nobj, h = state_trace.shape _, S, _ = words.shape state_trace = state_trace.permute(1, 2, 0, 3) # [T, Nobj, B, h] body_trace = body_trace.permute(1, 2, 0, 3) # [T, 1, B, h] words = words.transpose(0, 1) # [S, B, h] # positional encoding state_trace = self.pe(state_trace) body_trace = self.pe(body_trace) words = self.pe(words) state_trace = state_trace.reshape(T * Nobj, B, h) body_trace = body_trace.reshape(T, B, h) sensory_trace = torch.cat([state_trace, body_trace], 0) # add one hot identifiers and reproject to hidden dim sensory_trace = torch.cat([ sensory_trace, self.sensory_oh.expand(T * (Nobj + 1), B, 2) ], -1) words = torch.cat([ words, self.linguistic_oh.expand(S, B, 2) ], -1) sensory_trace = self.dim_adjust_proj(sensory_trace) words = self.dim_adjust_proj(words) if self.word_aggreg: words = torch.cat([words, query_token.expand(1, B, h)], 0) words = self.word_transformer(words)[-1:] tfm_input = torch.cat([ sensory_trace, words, query_token.expand(1, B, h) # query is last token ], dim=0) tfm_output = self.transformer(tfm_input) return torch.sigmoid(self.fc_out(tfm_output[-1])) class SpatialFirstTransformer(nn.Module): """ This model performs a first round of self-attention in individual frames/timesteps, using linguistic information, then performs self-attention over the temporal dimension. Parameters: - body_size: number of body features; - obj_size: number of object features; - voc_size: size of the vocabulary used in descriptions of the scene - seq_length: maximum size of a sentence; - hidden_size: size of: the output of the core and object encoding layers, the hidden layers of both Transformers; - num_heads: number of attention heads in both Transformers; - num_layers: number of layers in both Transformers; - dropout: dropout used in the Transformers, defaults to 0.1; - device: device on which to load the model; - word_aggreg: whether to use word_aggregation, if True the model becomes UT-WA """ def __init__(self, body_size, obj_size, voc_size, seq_length, hidden_size, num_heads, num_layers, dropout=0.1, device=torch.device('cpu'), word_aggreg=False, **kwargs): super().__init__() self.body_size = body_size self.obj_size = obj_size self.voc_size = voc_size self.seq_length = seq_length self.ff_size = hidden_size self.hidden_size = hidden_size self.num_heads = num_heads self.num_layers = num_layers self.dropout = dropout self.device = device self.word_aggreg = word_aggreg self.fc_cast_body = Feedforward(self.body_size, [self.ff_size, self.hidden_size]) self.fc_cast_obj = Feedforward(self.obj_size, [self.ff_size, self.hidden_size]) self.fc_cast_words = Feedforward(self.voc_size, [self.ff_size, self.hidden_size]) # init cls token self.query = nn.Parameter(torch.zeros(self.hidden_size)) # self.query_token = torch.zeros(self.hidden_size, device=device) self.sensory_oh = torch.tensor([1., 0.], device=device) self.linguistic_oh = torch.tensor([0., 1.], device=device) self.dim_adjust_proj = nn.Linear(self.hidden_size + 2, self.hidden_size) self.fc_out = Feedforward(self.hidden_size, [self.ff_size, 1]) self.spatial_transformer = TransformerModule( hidden_size=hidden_size, num_heads=num_heads, num_layers=num_layers, dropout=dropout, ) self.temporal_transformer = TransformerModule( hidden_size=hidden_size, num_heads=num_heads, num_layers=num_layers, dropout=dropout, ) if self.word_aggreg: self.word_transformer = TransformerModule( hidden_size=hidden_size, num_heads=num_heads, num_layers=num_layers, dropout=dropout, ) self.pe = PositionalEncoding(self.hidden_size, device=device, dropout=dropout) self.device = device self.to(self.device) def forward(self, state_trace, body_trace, description): state_trace = self.fc_cast_obj(state_trace) # [B, T, Nobj, h] body_trace = self.fc_cast_body(body_trace) # [B, T, 1, h] words = self.fc_cast_words(description) # [B, Seq, h] query_token = self.query B, T, Nobj, h = state_trace.shape _, S, _ = words.shape state_trace = state_trace.permute(1, 2, 0, 3) body_trace = body_trace.permute(1, 2, 0, 3) words = words.transpose(0, 1) # positional encoding state_trace = self.pe(state_trace) # [T, Nobj, B, h] body_trace = self.pe(body_trace) # [T, 1, B, h] words = self.pe(words) # [S, B, h] # add sensory and linguistic identifiers and reproject to dim state_trace = torch.cat([state_trace, self.sensory_oh.expand(T, Nobj, B, 2)], -1) state_trace = self.dim_adjust_proj(state_trace) body_trace = torch.cat([body_trace, self.sensory_oh.expand(T, 1, B, 2)], -1) body_trace = self.dim_adjust_proj(body_trace) words = torch.cat([words, self.linguistic_oh.expand(S, B, 2)], -1) words = self.dim_adjust_proj(words) # aggreg words if need be if self.word_aggreg: words = torch.cat([words, query_token.expand(1, B, h)], 0) words = self.word_transformer(words)[-1:] S = 1 # make spatial transformer input words = words.expand(T, S, B, h) query_token_spatial = query_token.expand(T, 1, B, h) spatial_tfm_input = torch.cat([ state_trace, body_trace, words, query_token_spatial ], 1) spatial_tfm_input.transpose(0, 1) # [Nobj + 1 + S + 1, T, B, h] # [T, B, h] temporal_tfm_input = self.spatial_transformer(spatial_tfm_input)[-1] query_token_temporal = query_token.expand([1, B, h]) temporal_tfm_input = torch.cat([temporal_tfm_input, query_token_temporal], 0) return torch.sigmoid(self.fc_out(self.temporal_transformer(temporal_tfm_input)[-1])) class TemporalFirstTransformer(nn.Module): """ This model performs a first round of self-attention over individual object traces using linguitic information, then performs self attention on the resulting object summaries. Parameters: - body_size: number of body features; - obj_size: number of object features; - voc_size: size of the vocabulary used in descriptions of the scene - seq_length: maximum size of a sentence; - hidden_size: size of: the output of the core and object encoding layers, the hidden layers of both Transformers; - num_heads: number of attention heads in both Transformers; - num_layers: number of layers in both Transformers; - dropout: dropout used in the Transformers, defaults to 0.1; - device: device on which to load the model; - word_aggreg: whether to use word_aggregation, if True the model becomes UT-WA """ def __init__(self, body_size, obj_size, voc_size, seq_length, hidden_size, num_heads, num_layers, dropout=0.1, device=torch.device('cpu'), word_aggreg=False, **kwargs): super().__init__() self.body_size = body_size self.obj_size = obj_size self.voc_size = voc_size self.seq_length = seq_length self.ff_size = hidden_size self.hidden_size = hidden_size self.num_heads = num_heads self.num_layers = num_layers self.dropout = dropout self.device = device self.word_aggreg = word_aggreg self.fc_cast_body = Feedforward(self.body_size, [self.ff_size, self.hidden_size]) self.fc_cast_obj = Feedforward(self.obj_size, [self.ff_size, self.hidden_size]) self.fc_cast_words = Feedforward(self.voc_size, [self.ff_size, self.hidden_size]) # init cls token self.query = nn.Parameter(torch.zeros(self.hidden_size)) # self.query_token = torch.zeros(self.hidden_size, device=device) self.sensory_oh = torch.tensor([1., 0.], device=device) self.linguistic_oh = torch.tensor([0., 1.], device=device) self.dim_adjust_proj = nn.Linear(self.hidden_size + 2, self.hidden_size) self.fc_out = Feedforward(self.hidden_size, [self.ff_size, 1]) self.spatial_transformer = TransformerModule( hidden_size=hidden_size, num_heads=num_heads, num_layers=num_layers, dropout=dropout, ) self.temporal_transformer = TransformerModule( hidden_size=hidden_size, num_heads=num_heads, num_layers=num_layers, dropout=dropout, ) if self.word_aggreg: self.word_transformer = TransformerModule( hidden_size=hidden_size, num_heads=num_heads, num_layers=num_layers, dropout=dropout, ) self.pe = PositionalEncoding(self.hidden_size, device=device, dropout=dropout) self.device = device self.to(self.device) def forward(self, state_trace, body_trace, description): state_trace = self.fc_cast_obj(state_trace) # [B, T, Nobj, h] body_trace = self.fc_cast_body(body_trace) # [B, T, 1, h] words = self.fc_cast_words(description) # [B, Seq, h] query_token = self.query B, T, Nobj, h = state_trace.shape _, S, _ = words.shape state_trace = state_trace.permute(1, 2, 0, 3) body_trace = body_trace.permute(1, 2, 0, 3) words = words.transpose(0, 1) # positional encoding state_trace = self.pe(state_trace) # [T, Nobj, B, h] body_trace = self.pe(body_trace) # [T, 1, B, h] sensory_trace = torch.cat([state_trace, body_trace], 1) # [T, Nobj+1, B, h] words = self.pe(words) # [S, B, h] # add sensory and linguistic identifiers and reproject to dim sensory_trace = torch.cat([sensory_trace, self.sensory_oh.expand(T, Nobj + 1, B, 2)], -1) sensory_trace = self.dim_adjust_proj(sensory_trace) words = torch.cat([words, self.linguistic_oh.expand(S, B, 2)], -1) words = self.dim_adjust_proj(words) # aggreg words if need be if self.word_aggreg: words = torch.cat([words, query_token.expand(1, B, h)], 0) words = self.word_transformer(words)[-1:] S = 1 words = words.expand(Nobj + 1, S, B, h).transpose(0, 1) query_token_temporal = query_token.expand(1, Nobj + 1, B, h) temporal_tfm_input = torch.cat([ sensory_trace, words, query_token_temporal ], 0) # out is [T, B, h] spatial_tfm_input = self.temporal_transformer(temporal_tfm_input)[-1] query_token_spatial = query_token.expand([1, B, h]) spatial_tfm_input = torch.cat([spatial_tfm_input, query_token_spatial], 0) return torch.sigmoid(self.fc_out(self.spatial_transformer(spatial_tfm_input)[-1]))

37.303797

97

0.621706

2,356

17,682

4.45034

0.098896

0.059132

0.041392

0.025751

0.767859

0.749452

0.731998

0.714258

0.685551

0.671149

0

0.012549

0.278928

17,682

474

98

37.303797

0.809804

0.233401

0

0.663265

0

0.002799

0

1

0.034014

false

0

0.017007

0

0.088435

0

null

0

1

0

1

0

null

0

4

ea82aa6e4246fdd22e64753ef51e6e4e18ee026c

279

py

Python

app/models/content.py

yogeshwaran01/Book-Store

7b4caa37b4132d8e969798eface3fd56c9721395

[ "MIT" ]

null

app/models/content.py

yogeshwaran01/Book-Store

7b4caa37b4132d8e969798eface3fd56c9721395

[ "MIT" ]

null

app/models/content.py

yogeshwaran01/Book-Store

7b4caa37b4132d8e969798eface3fd56c9721395

[ "MIT" ]

null

from app import database as db class Note(db.Model): # type: ignore id = db.Column(db.Integer, primary_key=True) title = db.Column(db.Text()) info = db.Column(db.Text()) link = db.Column(db.Text()) def __repr__(self) -> str: return f"{self.title}"

23.25

48

0.623656

43

279

3.930233

0.627907

0.189349

0.236686

0.248521

0

0.218638

279

11

49

25.363636

0.775229

0.043011

0

0.045283

0

1

0.125

false

0

0.125

1

0

null

0

1

0

null

0

1

0

4

578fad38630cb3dc8fb9e479454fd2f2a02a0ad5

51

py

Python

lr1 parser/test.py

arvin2079/java-lexer-with-python

6d4b163bea139b647c3f8d3d1539eaf706602cc7

[ "MIT" ]

null

lr1 parser/test.py

arvin2079/java-lexer-with-python

6d4b163bea139b647c3f8d3d1539eaf706602cc7

[ "MIT" ]

null

lr1 parser/test.py

arvin2079/java-lexer-with-python

6d4b163bea139b647c3f8d3d1539eaf706602cc7

[ "MIT" ]

null

l = ['a', '-', 'C', '----', 'S'] print(''.join(l))

17

32

0.27451

7

51

2

0.857143

0

0.156863

51

3

33

17

0.325581

0

0.153846

0

1

0

false

0

0.5

1

0

null

0

1

0

1

0

null

0

1

0

4

579e9f32e6aa0f8ffd97b4d9575834e3f78e74ec

174

py

Python

client/launcher.py

MatejKafka/guess-the-song

58bbefffd7a00b851932fac6c982128a1013c24d

[ "WTFPL" ]

null

client/launcher.py

MatejKafka/guess-the-song

58bbefffd7a00b851932fac6c982128a1013c24d

[ "WTFPL" ]

null

client/launcher.py

MatejKafka/guess-the-song

58bbefffd7a00b851932fac6c982128a1013c24d

[ "WTFPL" ]

null

# slight hack - pyinstaller does not allow main file # as module, this file allows me to use module namespace from src import __main__ if __name__ == "__main__": __main__()

34.8

57

0.758621

26

174

4.461538

0.807692

0

0.178161

174

5

58

34.8

0.811189

0.609195

0

0.121212

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

0

1

0

null

0

1

0

1

0

4

57b99a9e33d5ca32803983d019b3516cd30fdc79

2,167

py

Python

test_project/test_project/formtest/views.py

scott-w/view-helpers

389fe3599e5b4e5da35f490a33895b220025b2a5

[ "BSD-3-Clause" ]

1

2015-12-10T17:52:50.000Z

test_project/test_project/formtest/views.py

scott-w/view-helpers

389fe3599e5b4e5da35f490a33895b220025b2a5

[ "BSD-3-Clause" ]

null

test_project/test_project/formtest/views.py

scott-w/view-helpers

389fe3599e5b4e5da35f490a33895b220025b2a5

[ "BSD-3-Clause" ]

null

from django.views.generic import View from pebble_helpers.views.mixins.form import RedirectReverseMixin class SuccessUrlView(RedirectReverseMixin, View): """View that has a Success Url """ success_url = 'testproject-success-plain' class SuccessUrlArgView(RedirectReverseMixin, View): """View that has a Success Url that takes an arg. """ success_url = 'testproject-success-arg' def get_success_args(self): """ """ return 0, class SuccessUrlKwargView(RedirectReverseMixin, View): """View that has a Success Url that takes a kwarg. """ success_url = 'testproject-success-kwarg' def get_success_kwargs(self): """ """ return {'i': 0} class SuccessUrlArgKwargView(RedirectReverseMixin, View): """View that has both get_success_kwargs and get_success_args defined. """ success_url = 'testproject-success-argkwarg' def get_success_args(self): """ """ return 0, def get_success_kwargs(self): """ """ return {'i': 0} class FailureUrlView(RedirectReverseMixin, View): """View that has a Failure Url """ failure_url = 'testproject-failure-plain' class FailureUrlArgView(RedirectReverseMixin, View): """View that has a Failure Url that takes an Arg. """ failure_url = 'testproject-failure-arg' def get_failure_args(self): """ """ return 0, class FailureUrlKwargView(RedirectReverseMixin, View): """View that has a Failure Url that takes a kwarg. """ failure_url = 'testproject-failure-kwarg' def get_failure_kwargs(self): """ """ return {'i': 0} class FailureUrlArgKwargView(RedirectReverseMixin, View): """View that has both get_failure_kwargs and get_failure_args defined. """ failure_url = 'testproject-failure-argkwarg' def get_failure_args(self): """ """ return 0, def get_failure_kwargs(self): """ """ return {'i': 0} class NoUrlView(RedirectReverseMixin, View): """View that has neither a Success or Failure Url. """

22.340206

74

0.635441

235

2,167

5.719149

0.2

0.160714

0.1875

0.214286

0.53497

0.485119

0.339286

0.270833

0.16369

0

0.004954

0.25473

2,167

96

75

22.572917

0.827245

0.216428

0

0.457143

0

0.134905

0.132286

0

1

0.228571

false

0

0.057143

0

1

0

null

0

1

0

null

0

1

0

1

0

4

57ea3d03d3673d8433a77e85aa2a6d72179ed833

212

py

Python

backend/document/domain/exceptions.py

linearcombination/InterleavedResourcesGenerator

8c2f8ae30304eab5806e516c58158e6c3ddeaa2b

[ "MIT" ]

1

2022-01-10T21:03:26.000Z

backend/document/domain/exceptions.py

linearcombination/InterleavedResourcesGenerator

8c2f8ae30304eab5806e516c58158e6c3ddeaa2b

[ "MIT" ]

null

backend/document/domain/exceptions.py

linearcombination/InterleavedResourcesGenerator

8c2f8ae30304eab5806e516c58158e6c3ddeaa2b

[ "MIT" ]

1

2021-09-10T19:49:59.000Z

"""This module provides custom domain exceptions.""" from typing import final @final class InvalidDocumentRequestException(Exception): def __init__(self, message: str): self.message: str = message

21.2

52

0.740566

23

212

6.652174

0.782609

0.143791

0.183007

0

0.169811

212

9

53

23.555556

0.869318

0.216981

0

1

0.2

false

0

0.2

0

0.6

0

1

0

null

0

1

0

1

0

null

0

1

0

4

57fcecc2ce3e54b39114eb5ff7eef5166ecf89c3

43

py

Python

Scripts/rm_aspect.py

9bstudios/mecco_renderMonkey

6a88a65ec4f9bd76150927df07fad7c85e3a87f4

[ "MIT" ]

1

2021-04-19T23:43:56.000Z

Scripts/rm_aspect.py

adamohern/mecco_renderMonkey

6a88a65ec4f9bd76150927df07fad7c85e3a87f4

[ "MIT" ]

null

Scripts/rm_aspect.py

adamohern/mecco_renderMonkey

6a88a65ec4f9bd76150927df07fad7c85e3a87f4

[ "MIT" ]

2

2019-10-21T15:21:44.000Z

2021-09-23T15:59:43.000Z

# python args = lx.args() lx.out(args[0])

8.6

16

0.604651

8

43

3.25

0.625

0.461538

0

0.027778

0.162791

43

5

17

8.6

0.694444

0.139535

0

1

0

false

0

1

0

null

1

0

1

0

null

0

4

17c83c2e236a9921f97986d8951d93cf4e3e9ff1

779

py

Python

03-design-section/designable_web/designable_web/views.py

g2gcio/course-demo

b0d00a6ac7a6a6a17af963cee67cf13dc5941e95

[ "MIT" ]

276

2016-04-04T20:57:36.000Z

2022-03-12T02:42:46.000Z

03-design-section/designable_web/designable_web/views.py

g2gcio/course-demo

b0d00a6ac7a6a6a17af963cee67cf13dc5941e95

[ "MIT" ]

37

2016-10-13T12:04:27.000Z

2020-11-22T10:36:53.000Z

03-design-section/designable_web/designable_web/views.py

g2gcio/course-demo

b0d00a6ac7a6a6a17af963cee67cf13dc5941e95

[ "MIT" ]

163

2016-10-03T02:10:00.000Z

2022-03-25T03:43:01.000Z

from pyramid.view import view_config import designable_web.utils @view_config(route_name='index', renderer='templates/index.pt') def index(_): return extend_model({'project': 'designable_web'}) @view_config(route_name='box', renderer='templates/box_model.pt') def box_model(_): return extend_model({}) @view_config(route_name='selectors', renderer='templates/selectors.pt') def selectors(_): return extend_model({}) @view_config(route_name='layout', renderer='templates/layout.pt') def layout(_): return extend_model({}) @view_config(route_name='float', renderer='templates/float.pt') def float_(_): return extend_model({}) def extend_model(model_dict): model_dict['build_cache_id'] = designable_web.utils.build_cache_id return model_dict

23.606061

71

0.748395

104

779

5.269231

0.259615

0.109489

0.136861

0.173358

0.19708

0

0.107831

779

32

72

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17de6fa86f76256b240f0ebb381df43c9d3066fd

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py

Python

controller/LoadCraft/apps/utils_mq_listener/apps.py

antondmtvch/yah2j

3ed2e82a2c72b93ad1f11905ff37b79c386b0a58

[ "MIT" ]

4

2019-12-04T10:39:09.000Z

2020-02-18T06:57:05.000Z

controller/LoadCraft/apps/utils_mq_listener/apps.py

antondmtvch/yah2j

3ed2e82a2c72b93ad1f11905ff37b79c386b0a58

[ "MIT" ]

37

2019-12-18T13:12:50.000Z

2022-02-10T10:52:37.000Z

controller/LoadCraft/apps/utils_mq_listener/apps.py

antondmtvch/yah2j

3ed2e82a2c72b93ad1f11905ff37b79c386b0a58

[ "MIT" ]

5

2019-12-06T10:55:56.000Z

2020-06-01T19:32:32.000Z

from django.apps import AppConfig class UtilsMqListenerConfig(AppConfig): name = 'utils_mq_listener'

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py

Python

presalytics/lib/plugins/__init__.py

presalytics/python-client

5d80b78562126feeeb49af4738e2c1aed12dce3a

[ "MIT" ]

4

2020-02-21T16:30:46.000Z

2021-01-12T12:22:03.000Z

presalytics/lib/plugins/__init__.py

presalytics/python-client

5d80b78562126feeeb49af4738e2c1aed12dce3a

[ "MIT" ]

4

2019-12-28T19:30:08.000Z

2020-03-31T19:27:45.000Z

presalytics/lib/plugins/__init__.py

presalytics/python-client

5d80b78562126feeeb49af4738e2c1aed12dce3a

[ "MIT" ]

null

""" Library folder for plugins configured from `presalytics.story.outline.Plugin` class """

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4

aa02d1114f383df02d21751cb0b4236b1bd6765f

5,026

py

Python

scripts/us_bjs/nps/import_data.py

padma-g/data

b65e4e04a759ecc5b0b4df67e8cc290b0ddcadff

[ "Apache-2.0" ]

1

2021-01-01T05:27:56.000Z

scripts/us_bjs/nps/import_data.py

padma-g/data

b65e4e04a759ecc5b0b4df67e8cc290b0ddcadff

[ "Apache-2.0" ]

null

scripts/us_bjs/nps/import_data.py

padma-g/data

b65e4e04a759ecc5b0b4df67e8cc290b0ddcadff

[ "Apache-2.0" ]

1

2021-01-01T05:27:58.000Z

import pandas as pd from preprocess_data import preprocess_df from nps_statvar_writer import write_sv from absl import flags from absl import app FLAGS = flags.FLAGS flags.DEFINE_string('input_file', 'NPS_1978-2018_Data.tsv', 'file path to tsv file with import data', short_name='i') AGGREGATE_COLUMNS = [ "Count_Person_Incarcerated_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_WhiteAlone_MeasuredBasedOnJurisdiction", "Count_Person_BlackOrAfricanAmericanAlone_Incarcerated_MeasuredBasedOnJurisdiction", "Count_Person_HispanicOrLatino_Incarcerated_MeasuredBasedOnJurisdiction", "Count_Person_AmericanIndianOrAlaskaNativeAlone_Incarcerated_MeasuredBasedOnJurisdiction", "Count_Person_AsianAlone_Incarcerated_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_NativeHawaiianOrOtherPacificIslanderAlone_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_TwoOrMoreRaces_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_Incarcerated_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_Incarcerated_JudicialExecution_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_IllnessOrNaturalCause_Incarcerated_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_AIDS_Incarcerated_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_Incarcerated_IntentionalSelf-Harm(Suicide)_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_Accidents(UnintentionalInjuries)_Incarcerated_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_DeathDueToAnotherPerson_Incarcerated_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_Assault(Homicide)_Incarcerated_MeasuredBasedOnJurisdiction", "Count_MortalityEvent_Incarcerated_NPSOtherCauseOfDeath_MeasuredBasedOnJurisdiction", "Count_IncarcerationEvent_AdmittedToPrison_Incarcerated_MaxSentenceGreaterThan1Year_Sentenced_MeasuredBasedOnJurisdiction", "Count_IncarcerationEvent_Incarcerated_MaxSentenceGreaterThan1Year_ReleasedFromPrison_Sentenced_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_MaxSentenceGreaterThan1Year_Sentenced_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_MaxSentence1YearOrLess_Sentenced_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_Unsentenced_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_InState_PrivatelyOperated_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_OutOfState_PrivatelyOperated_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_Local_LocallyOperated_MeasuredBasedOnJurisdiction", "Count_Person_FederallyOperated_Incarcerated_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_OutOfState_StateOperated_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_NotAUSCitizen_StateOperated&FederallyOperated&PrivatelyOperated_MeasuredBasedOnCustody", "Count_Person_Incarcerated_MaxSentenceGreaterThan1Year_NotAUSCitizen_Sentenced_StateOperated&FederallyOperated&PrivatelyOperated_MeasuredBasedOnCustody", "Count_Person_Incarcerated_MaxSentence1YearOrLess_NotAUSCitizen_Sentenced_StateOperated&FederallyOperated&PrivatelyOperated_MeasuredBasedOnCustody", "Count_Person_Incarcerated_NotAUSCitizen_StateOperated&FederallyOperated&PrivatelyOperated_Unsentenced_MeasuredBasedOnCustody", "Count_Person_Female_Incarcerated_MeasuredBasedOnJurisdiction", "Count_Person_Incarcerated_Male_MeasuredBasedOnJurisdiction" ] FILENAME = 'national_prison_stats' def generate_tmcf(df): template = """ Node: E:{filename}->E{i} typeOf: dcs:StatVarObservation variableMeasured: dcs:{stat_var} measurementMethod: dcs:{mmethod} observationAbout: C:{filename}->GeoId observationDate: C:{filename}->YEAR value: C:{filename}->{stat_var} """ with open('national_prison_stats.tmcf', 'w') as tmcf_f: col_num = 0 for col in list(df.columns): if not col == "GeoId" and not col == "YEAR": if col in AGGREGATE_COLUMNS: tmcf_f.write( template.format_map({ 'i': col_num, 'stat_var': col, 'filename': FILENAME, 'mmethod': 'dcAggregate/NationalPrisonerStatistics' })) else: tmcf_f.write( template.format_map({ 'i': col_num, 'stat_var': col, 'filename': FILENAME, 'mmethod': 'NationalPrisonerStatistics' })) col_num += 1 def save_csv(df, filename): df.to_csv(filename + '.csv', index=False) def main(args): df = pd.read_csv(FLAGS.input_file, delimiter='\t') processed_df = preprocess_df(df) save_csv(processed_df, FILENAME) generate_tmcf(processed_df) f = open("nps_statvars.mcf", "w+") write_sv(f) if __name__ == '__main__': app.run(main)

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aa36a5cc8745de8f060a520ebe1650d3bd2afe80

580

py

Python

test_importing/taskflow_import_dag2.py

csprl-nowigence/airflow

f0c3b56ba13de95299ff8193b2d45275183ea575

[ "Apache-2.0" ]

null

test_importing/taskflow_import_dag2.py

csprl-nowigence/airflow

f0c3b56ba13de95299ff8193b2d45275183ea575

[ "Apache-2.0" ]

null

test_importing/taskflow_import_dag2.py

csprl-nowigence/airflow

f0c3b56ba13de95299ff8193b2d45275183ea575

[ "Apache-2.0" ]

null

import pendulum from airflow.decorators import dag, task import test_importing.mylib @dag( default_args={ 'owner': 'csprl', }, schedule_interval=None, start_date=pendulum.datetime(2022, 1, 1, tz='UTC'), catchup=False, tags=['debugging', 'learning', 'troubleshooting'], ) def import_with_package(): @task def main_task(): test_importing.mylib.func1() print(test_importing.mylib.func2()) print(test_importing.mylib.var1) print(test_importing.mylib.var2) main_task() this_dag = import_with_package()

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4

aa38ea99c20ca8b73b73e9d9e5b550e2a0eb6143

225

py

Python

binance_utils/connection.py

victorvalentee/python-binance-tick-data

5cd1c37ee7dbe93c398e3f9dc2eed2af198cc28e

[ "MIT" ]

null

binance_utils/connection.py

victorvalentee/python-binance-tick-data

5cd1c37ee7dbe93c398e3f9dc2eed2af198cc28e

[ "MIT" ]

null

binance_utils/connection.py

victorvalentee/python-binance-tick-data

5cd1c37ee7dbe93c398e3f9dc2eed2af198cc28e

[ "MIT" ]

null

import binance from config import BINANCE_API_KEY, BINANCE_API_SECRET async def connect(): binance_client = binance.Client(BINANCE_API_KEY, BINANCE_API_SECRET) await binance_client.load() return binance_client

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null

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350d2442f3be28cf555f5223b8b68675f3b34327

175

py

Python

rl2048player/__init__.py

aar015/rl-2048-player

91c67f5d9bf3e4e1ee7ef3c204ff356b449827d8

[ "MIT" ]

null

rl2048player/__init__.py

aar015/rl-2048-player

91c67f5d9bf3e4e1ee7ef3c204ff356b449827d8

[ "MIT" ]

null

rl2048player/__init__.py

aar015/rl-2048-player

91c67f5d9bf3e4e1ee7ef3c204ff356b449827d8

[ "MIT" ]

null

'''Package containing all code related to learning algorithms''' from .agents import QAgent, TD0Agent, SARSAAgent from .masks import Mask_rxcx4 from .examples import example1

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1

0

4

351b2d5a1a71bc6f162c992f89bc5da245a2c424

100

py

Python

mdm_inventory/users/serializers/__init__.py

TeamWalls/mdm-backend-django

4e23f9abc8531eb786d5e6cf958c9ffa8acd6b1d

[ "MIT" ]

null

mdm_inventory/users/serializers/__init__.py

TeamWalls/mdm-backend-django

4e23f9abc8531eb786d5e6cf958c9ffa8acd6b1d

[ "MIT" ]

null

mdm_inventory/users/serializers/__init__.py

TeamWalls/mdm-backend-django

4e23f9abc8531eb786d5e6cf958c9ffa8acd6b1d

[ "MIT" ]

null

from .users import ( UserCreateSerializer, UserUpdateSerializer, UserDisableSerializer )

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null

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4

351f8d0603b8ae7a9a7bb593a8f8d4e78d921ca4

22

py

Python

plaid/version.py

cwatsonplaid/plaid-python

118200484ca6f24d4dbed4cf00e46f5b4d20f914

[ "MIT" ]

null

plaid/version.py

cwatsonplaid/plaid-python

118200484ca6f24d4dbed4cf00e46f5b4d20f914

[ "MIT" ]

null

plaid/version.py

cwatsonplaid/plaid-python

118200484ca6f24d4dbed4cf00e46f5b4d20f914

[ "MIT" ]

null

__version__ = '7.3.0'

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1

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null

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3532d44591878b86460925f680f44872786b8aa6

61

py

Python

sequin/__init__.py

josefdlange/sequin

496099949444602e5ed988a8d9aed0bf3dc47dd2

[ "MIT" ]

null

sequin/__init__.py

josefdlange/sequin

496099949444602e5ed988a8d9aed0bf3dc47dd2

[ "MIT" ]

null

sequin/__init__.py

josefdlange/sequin

496099949444602e5ed988a8d9aed0bf3dc47dd2

[ "MIT" ]

null

from base import SequinEntity, SequinEvent, register_database

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1

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0

4

3533010fb748fc7b5f8658024873ea797cbeb4f1

20,819

py

Python

contest/weekly/229/max_score/py/greedy.py

phunc20/leetcode

4581f39be565593ad0f5718dd4b0e1c34c209bf3

[ "MIT" ]

null

contest/weekly/229/max_score/py/greedy.py

phunc20/leetcode

4581f39be565593ad0f5718dd4b0e1c34c209bf3

[ "MIT" ]

null

contest/weekly/229/max_score/py/greedy.py

phunc20/leetcode

4581f39be565593ad0f5718dd4b0e1c34c209bf3

[ "MIT" ]

null

#class Solution: # def maximumScore(self, nums: List[int], multipliers: List[int]) -> int: def maximumScore(nums, multipliers): """ Greedy cannot give the best solution. """ from random import randomint def random_pick(H, T): k = randomint(0,1) if k % 2: return H, 0 else: return T, -1 m = len(multipliers) n = len(nums) score = 0 for i in range(m): head = nums[0] tail = nums[-1] # randomly pick one if they are equal if head == tail: chosen, idx = random_pick(head, tail) score += multipliers[i] * chosen if idx == 0: nums = nums[1:] else: nums = nums[:-1] else: multipliers[i] if __name__ == "__main__": nums = [1,2,3] multipliers = [3,2,1] ans = maximumScore(nums, multipliers) expected = 14 #print(f"{'Correct' if ans == expected else 'Incorrect'}") print(f"{'Correct' if ans == expected else f'Incorrect: ans = {ans}, expected = {expected}'}") nums = [-5,-3,-3,-2,7,1] multipliers = [-10,-5,3,4,6] ans = maximumScore(nums, multipliers) expected = 102 print(f"{'Correct' if ans == expected else f'Incorrect: ans = {ans}, expected = {expected}'}") nums = 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multipliers = [-525,571,-905,-670,-892,-87,-697,-566,-606,-375,-749,-294,-312,-765,-714,-833,496,-990,-731,-228,-178,-564,-566,-495,-328,-319,-180,-895,-461,-453,-16,-938,-627,-8,-95,144,-60,-794,-663,-723,-492,-427,-719,-497,-506,-823,-974,-529,-427,-640,-274,-675,-741,899,-349,-283,-584,-521,-634,-346,-690,-868,-603,-409,-479,-895,-783,-532,-748,-611,126,-523,-995,-109,-225,-845,-470,-884,-125,-201,-24,-450,-516,-654,-285,-309,-41,-895,-306,-337,-827,-288,-99,-551,-518,-895,965,-568,-254,-166,-363,-77,-173,520,-649,-428,-684,-358,750,-401,-58,-747,-638,-3,-222,-986,-992,-826,-690,-290,-86,300,-984,532,-564,-231,-677,-160,-912,-740,-447,-172,-164,-269,-150,-28,-193,-419,-803,-838,632,-461,-483,-82,-804,-205,-629,-163,-449,-330,-987,-760,-783,-739,-525,-965,-661,-19,-842,-324,-81,770,-111,-613,-244,-689,-193,-367,-939,-107,-936,-840,-112,-700,-330,-396,-138,-156,-362,310,-437,-848,-5,-624,631,-388,-192,-66,-704,-916,-796,542,-37,-858,-68,-961,-533,-157,-306,-768,-688,-888,-987,-437,-465,244,-542,-976,-173,-23,-945,-378,-456,-564,-764,544,747,-389,-167,-388,-934,-178,-466,-361,-169,-610,-95,-836,-611,-387,-472,-396,-629,-33,-799,-691,-853,-328,-234,-264,-978,-189,-308,-510,-665,-719,-246,-220,-418,-732,982,-521,-708,-790,-683,-793,-169,-335,-584,-429,-421,-355,-295,-150,-888,-394,-431,-149,-243,-394,-56,-774,-170,-906,-811,-712,-456,-541,-757,-373,-40,-278,-132,-79,-774,263,-612,-811,-366,-813,-576,-8,676,-43,-983,-376,-153,-48,-906,-182,-335,-285,-419,-909,-433,-223,-487,60,-766,-356,-701,-623,-672,-872,-320,-782,-5,-747,-415,-385,-835,-393,-693,-22,-91,-638,-786,-133,-14,-218,-713,-560,-725,-200,-890,766,-979,-369,-481,-924,-500,-295,-940,-658,-528,-684,490,-690,-881,-781,-410,-141,-365,-598,-840,-440,-460,-787,-450,-326,-92,-596,-141,-65,-930,-691,-547,-765,-76,-328,-751,-653,-783,-552,-470,-478,-232,-829,-477,462,-831,-713,-851,-228,-254,135,-528,-784,-292,-472,-26,-890,-252,-684,-580,-791,-273,-623,-53,-289,-52,-165,-261,-395,-939,-477,-455,-138,-473,-289,-139,-63,-685,-11,-294,-152,-182,-907,-218,-233,-631,-809,-292,-703,-78,-527,-92,-778,-223,-636,-22,-122,-419,-440,-518,-310,-34,-93,-166,-584,-312,-627,-711,326,-513,-818,-350,-897,-676,-503,-664,-447,-653,-105,502,-678,-734,-614,-334,-170,-152,-409,-707,-410,-295,-78,961,-800,-152,-342,-342,-30,487,-692,-426,947,-111,-454,-184,-168,-105,-460,-994,-565,-944,492,-602,-353,-112,-224,-368,-849,-468,-866,-908,-577,-211,-905,-177,-829,-693,-912,-924,-280,-172,-467,-794,-470,-953,-919,-904,-174,-868,-865,-463,-976,-939,-225,-592,-235,-172,-308,-115,-605,-930,-698,-460,-344,-810,-467,-80,-610,-521,-877,-9,-202,-951,-496,-521,-569,-447,-815,-987,-661,-727,739,-744,-672,-635,-431,-233,-57,-704,-277,-8,-794,-127,-744,-251,-771,-617,-412,-925,-311,-611,-169,-756,-219,-627,-175,-149,-765,-32,-553,-576,-484,-698,-599,-84,-677,-117,636,-253,-950,-208,-893,-622,-8,-477,-4,-981,-581,-406,-59,-89,167,-222,758,-100,536,-688,-952,-57,-797,-649,-983,-442,-828,-544,-842,-473,-133,-548,-514,-889,-430,-119,-835,-863,-231,-754,-533,-134,-832,-785,-537,-205,-870,-729,-641,-71,-915,-789,-340,-501,-641,-483,-525,-146,-100,-645,-543,-780,-466,-231,-964,-315,-311,881,-864,-501,-661,-156,-213,-872,-823,-999,-87,-687,-892,-925,-196,-438,-606,-178,-841,-660,-981,-579,-640,-203,-430,-532,-670,-713,-329,-631,-297,-522,-679,-45,-18,-36,-930,-359,-18,-335,-791,-242,-106,-674,-152,847,-167,-366,-973,-95,-658,-18,-989,-422,-832,-331,-853,-969,-673,-13,-802,-86,-147,-82,-253,522,-403,-463,-964,-57,-344,-434,-976,-385,597,-522,-954,-711,-620,-554,-542,-392,-511,-440,-290,-749,-243,186,-312,-704,-275,-317,-525,-57,-228,-395,177,-916,-390,-57,-811,-555,445,-499,-90,-787,-718,-596,-250,-882,-875,-19,-627,-6,-830,-724,-716,-841,-133,-122,-839,-815,-360,486,-181,-599,-264,-579,-506,-375,-2,-465,-186,-88,-334,-362,-612,-494,-79,-9,-824,-191,-910,-382,-453,-670,-750,-664,-127,-749,-734,-132,-698,699,-563,-985,-399,-961,-602,-733,-495,-305,-375,-790,-367,-136,-314,-979,-303,-32,-109,-920,-677] ans = maximumScore(nums, multipliers) expected = "Unknown" print(f"{'Correct' if ans == expected else f'Incorrect: ans = {ans}, expected = {expected}'}")

408.215686

15,353

0.699073

4,941

20,819

2.943534

0.211091

0.005294

0.007426

0.004125

0.02324

0.015402

0.013339

0

0.676349

0.02272

20,819

50

15,354

416.38

0.038484

0.010615

0

0.230769

0

0.076923

0.012974

0

1

0.051282

false

0

0.025641

0

0.128205

0.076923

0

null

0

1

0

1

0

null

0

4

3538b3abe57630da9f9d1b056bf354c3392e9ba5

346

py

Python

pages/admin.py

connorpekovic/djangox

f3790abe3981a82ee6fd3ac134ce87338da4dd94

[ "MIT" ]

null

pages/admin.py

connorpekovic/djangox

f3790abe3981a82ee6fd3ac134ce87338da4dd94

[ "MIT" ]

5

2021-04-08T20:25:22.000Z

2021-10-03T21:19:50.000Z

pages/admin.py

connorpekovic/djangox

f3790abe3981a82ee6fd3ac134ce87338da4dd94

[ "MIT" ]

null

from django.contrib import admin from .models import Response # Description: Register your models here. If you want the model to appear in # the admin screens, you must include it here with these 2 lines of code. # # Improvements: Add inline detail. class ResponceAdmin(admin.ModelAdmin): pass admin.site.register(Response, ResponceAdmin)

28.833333

77

0.780347

50

346

5.4

0.76

0

0.003436

0.15896

346

12

78

28.833333

0.924399

0.520231

0

1

0

true

0.2

0.4

0

0.6

0

null

0

null

0

1

0

1

0

4

35425877797818acfc9446104f1f4fbff6407793

57

py

Python

gc-ai-notebook-tutorials/src/third_party/python-path-specification/setup.py

kalona/training-data-analyst

fd619ea2c63519463b759393e818078c5a60df15

[ "Apache-2.0" ]

11

2020-05-19T09:52:35.000Z

2022-02-25T10:39:56.000Z

gc-ai-notebook-tutorials/src/third_party/python-path-specification/setup.py

kalona/training-data-analyst

fd619ea2c63519463b759393e818078c5a60df15

[ "Apache-2.0" ]

null

gc-ai-notebook-tutorials/src/third_party/python-path-specification/setup.py

kalona/training-data-analyst

fd619ea2c63519463b759393e818078c5a60df15

[ "Apache-2.0" ]

1

2021-07-16T22:42:55.000Z

# encoding: utf-8 from setuptools import setup setup()

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354457b01115de740c4d7d5bab8b6817fa17ec98

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py

Python

src/heatspreader/shell/__init__.py

acticloud/heat-spreader

89d62f0ba4fe62309029258ff75a66ea6d803e39

[ "MIT" ]

null

src/heatspreader/shell/__init__.py

acticloud/heat-spreader

89d62f0ba4fe62309029258ff75a66ea6d803e39

[ "MIT" ]

null

src/heatspreader/shell/__init__.py

acticloud/heat-spreader

89d62f0ba4fe62309029258ff75a66ea6d803e39

[ "MIT" ]

null

from .shell import Shell __all__ = ["Shell"]

11.5

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null

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1

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3548cd4ec5cc76217fad382dce629c54f556fef2

110

py

Python

aviation/__init__.py

xsvStudios/xH-Cogs

ff207561c73e12631028a967786a1c5e68258996

[ "MIT" ]

1

2020-07-26T18:28:11.000Z

aviation/__init__.py

xsvStudios/xsvCogs

ff207561c73e12631028a967786a1c5e68258996

[ "MIT" ]

null

aviation/__init__.py

xsvStudios/xsvCogs

ff207561c73e12631028a967786a1c5e68258996

[ "MIT" ]

null

from .aviation import Aviation # Setup file to read in the cog def setup(bot): bot.add_cog(Aviation(bot))

22

31

0.736364

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110

4.210526

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0.172727

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0.333333

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null

0

1

0

null

0

1

0

1

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4

104be773bfee5b3beaa21261e832886eab88ebd2

1,337

py

Python

src/jk_argparsing/textmodel/TBlock.py

jkpubsrc/python-module-jk-argsparsing

9ef4b907c67fd1df5bd8c378df46ba527ebc2a83

[ "Apache-2.0" ]

null

src/jk_argparsing/textmodel/TBlock.py

jkpubsrc/python-module-jk-argsparsing

9ef4b907c67fd1df5bd8c378df46ba527ebc2a83

[ "Apache-2.0" ]

null

src/jk_argparsing/textmodel/TBlock.py

jkpubsrc/python-module-jk-argsparsing

9ef4b907c67fd1df5bd8c378df46ba527ebc2a83

[ "Apache-2.0" ]

null

class TBlock(object): ################################################################################################################################ ## Constructor ################################################################################################################################ # # Constructor method. # def __init__(self, text:str): assert isinstance(text, str) self.__text = text # ################################################################################################################################ ## Public Properties ################################################################################################################################ @property def text(self) -> str: return self.__text # ################################################################################################################################ ## Helper Methods ################################################################################################################################ ################################################################################################################################ ## Public Methods ################################################################################################################################ #

27.285714

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1,337

5.5

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130

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0.059088

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529cc9eb78ab2fd12455f4d5aba851c68761912e

330

py

Python

rex/exploit/__init__.py

tiedaoxiaotubie/rex

049bbce3ab2717cbb4d2f0fc10fe8c0433b39c1d

[ "BSD-2-Clause" ]

1

2021-01-22T11:25:40.000Z

rex/exploit/__init__.py

tiedaoxiaotubie/rex

049bbce3ab2717cbb4d2f0fc10fe8c0433b39c1d

[ "BSD-2-Clause" ]

null

rex/exploit/__init__.py

tiedaoxiaotubie/rex

049bbce3ab2717cbb4d2f0fc10fe8c0433b39c1d

[ "BSD-2-Clause" ]

1

2018-07-17T03:00:20.000Z

from .exceptions import CannotExploit, CannotExplore, NoSuchShellcode from .shellcodes import Shellcodes from .shellcode_factory import ShellcodeFactory from .exploit import Exploit, ExploitException from .exploit_factory import ExploitFactory from .cgc_exploit_factory import CGCExploitFactory from .techniques import Techniques

41.25

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null

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1

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1

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4

52f803bd080fe46af55734b645fdc85f40d74ecf

322

py

Python

v3/Libraries/builtin/statement/pass.py

TheShellLand/python

a35e9b32bec3a3ff03d6f0f4c2c2cc891180e516

[ "MIT" ]

null

v3/Libraries/builtin/statement/pass.py

TheShellLand/python

a35e9b32bec3a3ff03d6f0f4c2c2cc891180e516

[ "MIT" ]

1

2021-06-01T22:50:19.000Z

v3/Libraries/builtin/statement/pass.py

TheShellLand/python

a35e9b32bec3a3ff03d6f0f4c2c2cc891180e516

[ "MIT" ]

null

#!/usr/bin/python for letter in 'Python': if letter == 'h': pass print 'This is pass block' print 'Current Letter :', letter print "Good bye!" # Current Letter : P # Current Letter : y # Current Letter : t # This is pass block # Current Letter : h # Current Letter : o # Current Letter : n # Good bye!

17.888889

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0.63354

47

322

4.340426

0.446809

0.446078

0.098039

0.147059

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0.251553

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18

36

17.888889

0.846473

0.493789

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null

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1

0

1

0

1

0

4

5e21483b927b28fbab71b745198ed9ca86059d00

21

py

Python

vttformatter/__init__.py

georgiewellock/VTT_formatter

9d97fb313c0c7977c224c65551d154d893fed2d8

[ "MIT" ]

2

2019-07-10T22:42:02.000Z

2021-03-18T02:09:51.000Z

vttformatter/__init__.py

georgiewellock/VTT_formatter

9d97fb313c0c7977c224c65551d154d893fed2d8

[ "MIT" ]

null

vttformatter/__init__.py

georgiewellock/VTT_formatter

9d97fb313c0c7977c224c65551d154d893fed2d8

[ "MIT" ]

null

__version__ = '2.11'

10.5

20

0.666667

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3.333333

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0.142857

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1

21

0.388889

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false

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1

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null

0

1

0

1

0

null

0

4

5e220f2439c5fd361155faa613d1d4b2969404cf

225

py

Python

clubbi_utils/publisher.py

dev-clubbi/clubbi_utils

3a3622374daf0927e6b8aedb58266e8792426880

[ "MIT" ]

null

clubbi_utils/publisher.py

dev-clubbi/clubbi_utils

3a3622374daf0927e6b8aedb58266e8792426880

[ "MIT" ]

34

2021-11-23T14:10:52.000Z

2022-03-30T22:46:24.000Z

clubbi_utils/publisher.py

dev-clubbi/clubbi_utils

3a3622374daf0927e6b8aedb58266e8792426880

[ "MIT" ]

null

from asyncio import Protocol from typing import Any, Optional, Dict class Publisher(Protocol): async def publish(self, message: Any, attributes: Optional[Dict[str, str]] = None) -> None: """Protocol function"""

28.125

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0.706667

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225

5.678571

0.678571

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0.177778

225

7

96

32.142857

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true

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null

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null

0

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1

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4

eaabd7127a0ffec1afb345fb1cf84a14696e0d35

93

py

Python

apps/documento/apps.py

diegocostacmp/gestao_rh

5fc6333aa1937ecbd05528ca01f4b9cb5f5eb895

[ "Linux-OpenIB" ]

null

apps/documento/apps.py

diegocostacmp/gestao_rh

5fc6333aa1937ecbd05528ca01f4b9cb5f5eb895

[ "Linux-OpenIB" ]

6

2020-02-08T21:28:12.000Z

2022-03-12T00:15:11.000Z

apps/documento/apps.py

diegocostacmp/gestao_rh

5fc6333aa1937ecbd05528ca01f4b9cb5f5eb895

[ "Linux-OpenIB" ]

null

from django.apps import AppConfig class DocumentoConfig(AppConfig): name = "documento"

15.5

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0.763441

10

93

7.1

0.9

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0.16129

93

5

34

18.6

0.910256

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false

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0.333333

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null

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1

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4

eaaf9181ab5fdb6778c4f31963c93427b3e8ad32

350

py

Python

trident/loggers/__init__.py

cronin4392/trident

1c1eb01bcde861496ce83e265ff071fc9bcb9db2

[ "MIT" ]

68

2020-11-13T06:40:52.000Z

2022-03-28T12:40:59.000Z

trident/loggers/__init__.py

cronin4392/trident

1c1eb01bcde861496ce83e265ff071fc9bcb9db2

[ "MIT" ]

1

2021-08-15T17:06:35.000Z

2021-11-10T04:42:52.000Z

trident/loggers/__init__.py

cronin4392/trident

1c1eb01bcde861496ce83e265ff071fc9bcb9db2

[ "MIT" ]

11

2020-11-24T13:14:16.000Z

2021-12-26T07:41:29.000Z

"""trident models""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from trident.backend.common import get_backend if get_backend()=='pytorch': from . import pytorch_tensorboard as tensorboard elif get_backend()=='tensorflow': from . import tensorflow_tensorboard as tensorboard

31.818182

55

0.808571

43

350

6.139535

0.418605

0.113636

0.181818

0

0.122857

350

11

55

31.818182

0.859935

0.04

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true

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null

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null

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0

1

0

1

0

4

eaf799c893aca0561a899b7414d4f9b46d90a877

274

py

Python

savu/plugins/savers/base_saver_tools.py

elainehoml/Savu

e4772704606f71d6803d832084e10faa585e7358

[ "Apache-2.0" ]

39

2015-03-30T14:03:42.000Z

2022-03-16T16:50:33.000Z

savu/plugins/savers/base_saver_tools.py

elainehoml/Savu

e4772704606f71d6803d832084e10faa585e7358

[ "Apache-2.0" ]

670

2015-02-11T11:08:09.000Z

2022-03-21T09:27:57.000Z

savu/plugins/savers/base_saver_tools.py

elainehoml/Savu

e4772704606f71d6803d832084e10faa585e7358

[ "Apache-2.0" ]

54

2015-02-13T14:09:52.000Z

2022-01-24T13:57:09.000Z

from savu.plugins.plugin_tools import PluginTools class BaseSaverTools(PluginTools): """A base plugin from which all data saver plugins should inherit. """ def define_parameters(self): """ out_datasets: visibility: hidden """

27.4

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0.649635

29

274

6.034483

0.862069

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0.266423

274

10

71

27.4

0.870647

0.383212

0

1

0.333333

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0.333333

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null

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null

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1

0

1

0

1

0

4

d83591fa2aa33aa06919cd0f444fbfb320df4f49

34

py

Python

src/Wython.example/expressions/example4.py

JRasmusBm/metaborg-python

ffc47439744be53c3a8f3bf7bbd55fbfc3f9f193

[ "Apache-2.0" ]

2

2020-09-18T13:10:29.000Z

2021-09-23T21:04:46.000Z

src/Wython.example/expressions/example4.py

MetaBorgCube/metaborg-python

f16cbfd7840e1c762b947eb743cfad1cdd60c237

[ "Apache-2.0" ]

3

2018-05-04T21:01:59.000Z

2018-06-15T20:39:06.000Z

src/Wython.example/expressions/example4.py

JRasmusBm/metaborg-python

ffc47439744be53c3a8f3bf7bbd55fbfc3f9f193

[ "Apache-2.0" ]

2

2018-05-04T13:51:53.000Z

2019-03-11T08:09:37.000Z

a = lambda x,y=1+1, z=13: print(x)

34

0.588235

10

34

2

0.8

0

0.137931

0.147059

34

1

34

0.551724

0

1

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false

0

1

0

null

0

1

0

null

0

1

0

4

dc22ece2b9570973edfc3c4711b8e716b71b8e59

132

py

Python

rebrickable_latest_set_id.py

maczniak/brickstats

ac16a62242a374b15d46ccf4132db445dfa1fd76

[ "MIT" ]

1

2015-09-10T00:04:23.000Z

rebrickable_latest_set_id.py

maczniak/brickstats

ac16a62242a374b15d46ccf4132db445dfa1fd76

[ "MIT" ]

null

rebrickable_latest_set_id.py

maczniak/brickstats

ac16a62242a374b15d46ccf4132db445dfa1fd76

[ "MIT" ]

null

rebrickable_latest_set_id = { 620: '620-3', 630: '630-3', 6200: '6200-2', 6202: '6202-2', 6862: '6862-2', 70012: '70012-2', }

14.666667

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0.583333

22

132

3.363636

0.545455

0

0.472727

0.166667

132

8

30

16.5

0.2

0

0.265152

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

4

dc2be8649a2b4266ed87a484a715922e4a5e2bf2

22

py

Python

tarbell/__init__.py

write-this-way/flask-tarbell

0e23e8d90ba66fde1a961ea530c99d94357ff664

[ "BSD-3-Clause" ]

1

2016-03-12T21:16:46.000Z

tarbell/__init__.py

write-this-way/flask-tarbell

0e23e8d90ba66fde1a961ea530c99d94357ff664

[ "BSD-3-Clause" ]

null

tarbell/__init__.py

write-this-way/flask-tarbell

0e23e8d90ba66fde1a961ea530c99d94357ff664

[ "BSD-3-Clause" ]

null

__VERSION__ = '0.9b4'

11

21

0.681818

3

22

3.666667

1

0

0.157895

0.136364

22

1

22

0.421053

0

0.227273

0

1

0

false

0

1

0

null

0

1

0

1

0

null

0

4

dc3bca935497cfe32c4a6635c3656fd20b0c7b9c

87

py

Python

rlbox/core/__init__.py

ocraft/rl-sandbox

fba6571545cf040829998ba4cd9009a15ac1bbdd

[ "MIT" ]

2

2019-03-23T17:52:39.000Z

2019-03-29T17:29:52.000Z

rlbox/core/__init__.py

ocraft/rl-sandbox

fba6571545cf040829998ba4cd9009a15ac1bbdd

[ "MIT" ]

null

rlbox/core/__init__.py

ocraft/rl-sandbox

fba6571545cf040829998ba4cd9009a15ac1bbdd

[ "MIT" ]

2

2020-05-19T21:32:52.000Z

2020-09-30T09:28:45.000Z

from .core import AgentProgram, Agent, Environment, Run from .space import Space, Spec

29

55

0.793103

12

87

5.75

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0.137931

87

2

56

43.5

0.92

0

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true

0

1

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1

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1

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null

0

1

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1

0

4

dc50b7c77720dd7fbd8d9a149c2c78f80b685849

36

py

Python

jetbrains-academy/Tic-Tac-Toe/Problems/Poster artist/task.py

robinpatra/ML-Study-3

6f401706a8da4cac5e63304ce09ff6ff62756d0b

[ "MIT" ]

null

jetbrains-academy/Tic-Tac-Toe/Problems/Poster artist/task.py

robinpatra/ML-Study-3

6f401706a8da4cac5e63304ce09ff6ff62756d0b

[ "MIT" ]

null

jetbrains-academy/Tic-Tac-Toe/Problems/Poster artist/task.py

robinpatra/ML-Study-3

6f401706a8da4cac5e63304ce09ff6ff62756d0b

[ "MIT" ]

null

word = input() print(word.upper())

9

19

0.638889

5

36

4.6

0.8

0

0.138889

36

3

20

12

0.741935

0

1

0

false

0

0.5

1

0

null

0

1

0

null

0

1

0

4

dc5bc4ecb5cb7599cee61d33ccd218509963a01a

169

py

Python

server/server/__init__.py

LezendarySandwich/Generic-CSP-Solver

1f0577a92e4ebaabe60f1c7dcac4904872e704f4

[ "MIT" ]

1

2021-03-06T11:11:59.000Z

server/server/__init__.py

LezendarySandwich/Generic-CSP-Solver

1f0577a92e4ebaabe60f1c7dcac4904872e704f4

[ "MIT" ]

null

server/server/__init__.py

LezendarySandwich/Generic-CSP-Solver

1f0577a92e4ebaabe60f1c7dcac4904872e704f4

[ "MIT" ]

null

from flask import Flask def create_app(): app = Flask(__name__) from .api import api as api_blueprint app.register_blueprint(api_blueprint) return app

18.777778

41

0.727811

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169

4.791667

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0.208696

0

0.213018

169

8

42

21.125

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0.166667

false

0

0.333333

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0.333333

1

0

null

1

0

1

0

null

0

1

0

4

dca14782d592df99844a7fbfa2c8ba6e8268e3c9

139

py

Python

GCP/sample-notebooks/CrossValScore/CrossValScore/trainer/model.py

SAP-samples/dwc-fedml

39ea8cefc31741c4ec37eb6c0d70dd48e7c034ba

[ "Apache-2.0" ]

2

2021-11-24T14:58:56.000Z

2022-01-12T07:32:29.000Z

GCP/sample-notebooks/CrossValScore/CrossValScore/trainer/model.py

SAP-samples/dwc-fedml

39ea8cefc31741c4ec37eb6c0d70dd48e7c034ba

[ "Apache-2.0" ]

null

GCP/sample-notebooks/CrossValScore/CrossValScore/trainer/model.py

SAP-samples/dwc-fedml

39ea8cefc31741c4ec37eb6c0d70dd48e7c034ba

[ "Apache-2.0" ]

2

2021-12-16T15:18:15.000Z

2022-01-12T07:32:41.000Z

from sklearn.linear_model import LogisticRegression def get_estimator(flags): clf = LogisticRegression(max_iter=1000) return clf

19.857143

51

0.791367

17

139

6.294118

0.882353

0

0.033898

0.151079

139

6

52

23.166667

0.872881

0

1

0.25

false

0

0.25

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

4

f4d1bf83aad9bde1e4313739a5920db0de00038b

52

py

Python

mudaemod_module/__init__.py

alentoghostflame/StupidAlentoBot

c024bfb79a9ecb0d9fda5ddc4e361a0cb878baba

[ "MIT" ]

1

2021-12-12T02:50:20.000Z

mudaemod_module/__init__.py

alentoghostflame/StupidAlentoBot

c024bfb79a9ecb0d9fda5ddc4e361a0cb878baba

[ "MIT" ]

17

2020-02-07T23:40:36.000Z

2020-12-22T16:38:44.000Z

mudaemod_module/__init__.py

alentoghostflame/StupidAlentoBot

c024bfb79a9ecb0d9fda5ddc4e361a0cb878baba

[ "MIT" ]

null

from mudaemod_module.mudaemod import MudaeModModule

26

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7.666667

0.833333

0

0.076923

52

1

52

0.958333

0

1

0

true

0

1

0

1

0

1

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null

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1

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null

0

1

0

1

0

4

7625d7f650f5643c7d2dd0b07f1a6bb4fc6f314d

223

py

Python

optimade/server/models/util.py

dietherjohn20/optimade-python-tools

c0c2bbf5851b3c4033a536b978fe633bd84bdf95

[ "MIT" ]

null

optimade/server/models/util.py

dietherjohn20/optimade-python-tools

c0c2bbf5851b3c4033a536b978fe633bd84bdf95

[ "MIT" ]

null

optimade/server/models/util.py

dietherjohn20/optimade-python-tools

c0c2bbf5851b3c4033a536b978fe633bd84bdf95

[ "MIT" ]

null

from typing import cast, Any, Dict, Type from pydantic import ConstrainedInt, errors from pydantic.types import OptionalInt from pydantic.validators import list_validator class NonnegativeInt(ConstrainedInt): ge = 0

22.3

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223

6.428571

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0.005236

0.143498

223

9

47

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0.937173

0

1

0

false

0

0.666667

0

1

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1

0

null

0

1

0

null

0

1

0

1

0

4