xszheng2020/the_stack_dedup_python_hits_3 · Datasets at Hugging Face

f6f1ab8abc3de63eb67bd4fb6ecdf7929e0eb532

152

py

Python

mambotokea/apps.py

synthiakageni/neighborhood

d7a04b17af83f864aad54c24b62c27b5c51b89e9

[ "Unlicense" ]

null

mambotokea/apps.py

synthiakageni/neighborhood

d7a04b17af83f864aad54c24b62c27b5c51b89e9

[ "Unlicense" ]

null

mambotokea/apps.py

synthiakageni/neighborhood

d7a04b17af83f864aad54c24b62c27b5c51b89e9

[ "Unlicense" ]

null

from django.apps import AppConfig class MambotokeaConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'mambotokea'

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null

0

1

0

3

f6fcd7c8c7c33dffd6c6a9cf42c636bf31c54cba

316

py

Python

players/distribute_bot.py

Siedler/Owela

cdaa3218846d78cf93a90ff6c4740ac3020275ee

[ "Apache-2.0" ]

null

players/distribute_bot.py

Siedler/Owela

cdaa3218846d78cf93a90ff6c4740ac3020275ee

[ "Apache-2.0" ]

null

players/distribute_bot.py

Siedler/Owela

cdaa3218846d78cf93a90ff6c4740ac3020275ee

[ "Apache-2.0" ]

null

from players.player import * class DistributeBot(Player): def select_move(self, game, player) -> int: """ This bot tries to distribute it's stones onto as many fields as possible """ return self.find_highest_value_move(game, player, lambda game: game.used_fields_count(player))

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0

1

0

1

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3

100a7b080cdbf52878aa7c6844fdf3401e872bb9

88

py

Python

src/apps/feed/apps.py

COAStatistics/aprp

8b06116a32001b040868a3cfa44e7d1f3bfb4742

[ "MIT" ]

2

2020-07-11T23:20:54.000Z

2021-07-14T03:15:28.000Z

src/apps/feed/apps.py

COAStatistics/aprp

8b06116a32001b040868a3cfa44e7d1f3bfb4742

[ "MIT" ]

38

2018-09-26T15:11:34.000Z

2022-03-18T08:05:02.000Z

src/apps/feed/apps.py

COAStatistics/aprp

8b06116a32001b040868a3cfa44e7d1f3bfb4742

[ "MIT" ]

6

2018-08-24T05:50:32.000Z

2019-03-12T01:22:44.000Z

from django.apps import AppConfig class FeedConfig(AppConfig): name = 'apps.feed'

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1

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3

63f5ddbc9887f335dda503ea0140f4ddd64cfa19

2,079

py

Python

scattertext/termscoring/CohensD.py

shettyprithvi/scattertext

a15613b6feef3ddc56c03aadb8e1e629d28a427d

[ "Apache-2.0" ]

null

scattertext/termscoring/CohensD.py

shettyprithvi/scattertext

a15613b6feef3ddc56c03aadb8e1e629d28a427d

[ "Apache-2.0" ]

null

scattertext/termscoring/CohensD.py

shettyprithvi/scattertext

a15613b6feef3ddc56c03aadb8e1e629d28a427d

[ "Apache-2.0" ]

null

import numpy as np from scattertext.termscoring.CohensDCalculator import CohensDCalculator from scattertext.termscoring.CorpusBasedTermScorer import CorpusBasedTermScorer class CohensD(CorpusBasedTermScorer, CohensDCalculator): ''' Cohen's d scores term_scorer = (CohensD(corpus).set_categories('Positive', ['Negative'], ['Plot'])) html = st.produce_frequency_explorer( corpus, category='Positive', not_categories=['Negative'], neutral_categories=['Plot'], term_scorer=term_scorer, metadata=rdf['movie_name'], grey_threshold=0, show_neutral=True ) file_name = 'rotten_fresh_fre.html' open(file_name, 'wb').write(html.encode('utf-8')) IFrame(src=file_name, width=1300, height=700) ''' def _set_scorer_args(self, **kwargs): pass def get_scores(self, *args): return self.get_score_df()['cohens_d'] def get_score_df(self, correction_method=None): ''' :param correction_method: str or None, correction method from statsmodels.stats.multitest.multipletests 'fdr_bh' is recommended. :return: pd.DataFrame ''' # From https://people.kth.se/~lang/Effect_size.pdf # Shinichi Nakagawa1 and Innes C. Cuthill. Effect size, confidence interval and statistical # significance: a practical guide for biologists. 2007. In Biological Reviews 82. # # Modification: when calculating variance, an empty document is added to each set X = self._get_X().astype(np.float64) X = X / X.sum(axis=1) X[np.isnan(X)] = 0 cat_X, ncat_X = self._get_cat_and_ncat(X) score_df = (self .get_cohens_d_df(cat_X, ncat_X, correction_method) .set_index(np.array(self.corpus_.get_terms()))) return score_df def get_name(self): return "Cohen's d" class HedgesR(CohensD): def get_scores(self, *args): return self.get_score_df()['hedges_r'] def get_name(self): return "Hedge's r"

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null

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null

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1

0

3

120a45612206c3716bbb2710afc7af0a7cdb80e4

3,402

py

Python

projects/InterpretationReID/interpretationreid/config/add_config.py

SheldongChen/AMD.github.io

5f3018f239127949b2d3995162ffe033dcf8051a

[ "Apache-2.0" ]

17

2021-11-01T01:14:06.000Z

2022-03-02T14:59:39.000Z

projects/InterpretationReID/interpretationreid/config/add_config.py

SheldongChen/AMD.github.io

5f3018f239127949b2d3995162ffe033dcf8051a

[ "Apache-2.0" ]

2

2021-12-22T07:56:13.000Z

2022-03-18T10:26:21.000Z

projects/InterpretationReID/interpretationreid/config/add_config.py

SheldongChen/AMD.github.io

5f3018f239127949b2d3995162ffe033dcf8051a

[ "Apache-2.0" ]

2

2022-02-18T07:42:38.000Z

2022-02-18T10:16:26.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- ''' @File : add_config.py @Author: Xiaodong Chen @Date : 2020/8/30 21:50 @E-mail : 1241660907@qq.com or sheldongchen@gmail.com ''' from fastreid.config import CfgNode as CN def add_interpretation_config(cfg): _C = cfg _C.DATALOADER.ATT_RESAMPLE = False _C.VISUAL = CN() _C.VISUAL.OPEN = False _C.VISUAL.GAP_QUERY = 100 _C.INTERPRETATION = CN() _C.INTERPRETATION.FREEZE_LAYERS = [''] # freeze layers of pretrain model _C.INTERPRETATION.PRETRAIN_MODEL = '' _C.INTERPRETATION.ATT_PRETRAIN_DICT = '' _C.INTERPRETATION.MODEL = CN() _C.INTERPRETATION.MODEL.SHARE_LAYER = 3 # [0,5] , int _C.INTERPRETATION.LOSS = CN() _C.INTERPRETATION.LOSS.att = 10.0 _C.INTERPRETATION.LOSS.att_decay = False _C.INTERPRETATION.LOSS.interpretation = 1.0 _C.INTERPRETATION.LOSS.att_lamda = 0.0 # [-inf , 0]ß _C.INTERPRETATION.LOSS.threshold = 0.9 #_C.INTERPRETATION.LOSS.q_att = 1.0 # [-inf , 0]ß # Cfg of Interpretation Network : g(I) _C.INTERPRETATION.I_MODEL = CN() _C.INTERPRETATION.I_MODEL.BACKBONE = CN() _C.INTERPRETATION.I_MODEL.BACKBONE.ADD_PARAMETER = False _C.INTERPRETATION.I_MODEL.BACKBONE.NAME = "build_resnet_backbone" _C.INTERPRETATION.I_MODEL.BACKBONE.DEPTH = "50x" _C.INTERPRETATION.I_MODEL.BACKBONE.LAST_STRIDE = 1 # Normalization method for the convolution layers. _C.INTERPRETATION.I_MODEL.BACKBONE.NORM = "BN" # Mini-batch split of Ghost BN _C.INTERPRETATION.I_MODEL.BACKBONE.NORM_SPLIT = 1 # If use IBN block in backbone _C.INTERPRETATION.I_MODEL.BACKBONE.WITH_IBN = False # If use SE block in backbone _C.INTERPRETATION.I_MODEL.BACKBONE.WITH_SE = False # If use Non-local block in backbone _C.INTERPRETATION.I_MODEL.BACKBONE.WITH_NL = False # If use ImageNet pretrain model _C.INTERPRETATION.I_MODEL.BACKBONE.PRETRAIN = True # Pretrain model path _C.INTERPRETATION.I_MODEL.BACKBONE.PRETRAIN_PATH = '' # ---------------------------------------------------------------------------- # # REID HEADS options # ---------------------------------------------------------------------------- # _C.INTERPRETATION.I_MODEL.HEADS = CN() _C.INTERPRETATION.I_MODEL.HEADS.NAME = "ADD_AttrHead" # Normalization method for the convolution layers. _C.INTERPRETATION.I_MODEL.HEADS.NORM = "BN" # Mini-batch split of Ghost BN _C.INTERPRETATION.I_MODEL.HEADS.NORM_SPLIT = 1 # Number of identity _C.INTERPRETATION.I_MODEL.HEADS.NUM_CLASSES = 23 # _C.INTERPRETATION.NUM_ATT = 23 # num of attribute # Input feature dimension _C.INTERPRETATION.I_MODEL.HEADS.IN_FEAT = 2048 # Reduction dimension in head _C.INTERPRETATION.I_MODEL.HEADS.REDUCTION_DIM = 512 # Triplet feature using feature before(after) bnneck _C.INTERPRETATION.I_MODEL.HEADS.NECK_FEAT = "before" # options: before, after # Pooling layer type _C.INTERPRETATION.I_MODEL.HEADS.POOL_LAYER = "fastavgpool" # Classification layer type _C.INTERPRETATION.I_MODEL.HEADS.CLS_LAYER = "linear" # "arcSoftmax" or "circleSoftmax" # Margin and Scale for margin-based classification layer _C.INTERPRETATION.I_MODEL.HEADS.MARGIN = 0.15 _C.INTERPRETATION.I_MODEL.HEADS.SCALE = 128 _C.INTERPRETATION.I_MODEL.HEADS.WITH_BNNECK = False

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null

1

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null

0

3

121fa760fd1620821b34f21806f44d0e9b088dd8

1,220

py

Python

apps/CVitae/serializers.py

michaelhenry/CVitae

f73f5126adc42aae695f56d3a1c2cf2fa9f10389

[ "MIT" ]

null

apps/CVitae/serializers.py

michaelhenry/CVitae

f73f5126adc42aae695f56d3a1c2cf2fa9f10389

[ "MIT" ]

2

2018-02-12T15:23:19.000Z

2018-02-25T10:13:44.000Z

apps/CVitae/serializers.py

michaelhenry/CVitae

f73f5126adc42aae695f56d3a1c2cf2fa9f10389

[ "MIT" ]

null

from rest_framework import serializers from .models import (Job, Project, Company, Profile, Skill, Education) class JobSerializer(serializers.ModelSerializer): class Meta: model = Job fields = ( 'id', 'name', 'description', 'company', ) class ProjectSerializer(serializers.ModelSerializer): class Meta: model = Project fields = ( 'id', 'name', 'description', 'start_date', 'end_date', 'photo', ) class CompanySerializer(serializers.ModelSerializer): class Meta: model = Company fields = ( 'id', 'name', 'description', ) class SkillSerializer(serializers.ModelSerializer): class Meta: model = Skill fields = ( 'id', 'name', 'description', 'level', ) class EducationSerializer(serializers.ModelSerializer): class Meta: model = Education fields = ( 'id', 'name_of_school', 'description', 'start_date', 'end_date', ) class ProfileSerializer(serializers.ModelSerializer): class Meta: model = Profile fields = ( 'id', 'display_name', 'job_title', 'email', )

15.641026

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1,220

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1

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null

0

3

122024d0f0e6cc341fbe97626c0c2e01f00e1cfb

249

py

Python

is my number divisible by 3 and 5.py

jermainedavies/JermainesFirstPrograms

caeaea6ba0b6a0a7e82f78f5e3b9df1647f22fde

[ "Unlicense" ]

null

is my number divisible by 3 and 5.py

jermainedavies/JermainesFirstPrograms

caeaea6ba0b6a0a7e82f78f5e3b9df1647f22fde

[ "Unlicense" ]

null

is my number divisible by 3 and 5.py

jermainedavies/JermainesFirstPrograms

caeaea6ba0b6a0a7e82f78f5e3b9df1647f22fde

[ "Unlicense" ]

null

user_num = int(input("which number would you like to check?")) def devisible_by_both(): if user_num %3 == 0 and user_num %5 == 0: print("your number is divisible by both") else: print("your number is not divisible by both")

35.571429

62

0.650602

41

249

3.829268

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0.133758

0.191083

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249

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null

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null

0

3

12303b2c5638cf3c4ed1f342fe7597e2b41d21c8

224

py

Python

notebooks/solutions/02-ex02-solutions.py

thomasjpfan/ml-workshop-advanced

36665098428f6d71732d129d4f561e33321d9c06

[ "MIT" ]

14

2020-09-27T01:37:31.000Z

2022-02-05T21:36:02.000Z

notebooks/solutions/02-ex02-solutions.py

thomasjpfan/ml-workshop-advanced

36665098428f6d71732d129d4f561e33321d9c06

[ "MIT" ]

null

notebooks/solutions/02-ex02-solutions.py

thomasjpfan/ml-workshop-advanced

36665098428f6d71732d129d4f561e33321d9c06

[ "MIT" ]

18

2020-10-28T17:00:48.000Z

2021-12-16T03:38:35.000Z

base_rf.fit(X_train, y_train) under_rf.fit(X_train, y_train) over_rf.fit(X_train, y_train) plot_roc_and_precision_recall_curves([ ("original", base_rf), ("undersampling", under_rf), ("oversampling", over_rf), ])

24.888889

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0.146667

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true

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null

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1

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1

0

null

0

1

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3

12343c30072d9a6ca37717a88f2fa14585789647

261

py

Python

Mac/Tools/macfreeze/macgenerate.py

deadsnakes/python2.4

f493d5415b662e99a73d017bcafe2148c5bc8fb5

[ "PSF-2.0" ]

null

Mac/Tools/macfreeze/macgenerate.py

deadsnakes/python2.4

f493d5415b662e99a73d017bcafe2148c5bc8fb5

[ "PSF-2.0" ]

null

Mac/Tools/macfreeze/macgenerate.py

deadsnakes/python2.4

f493d5415b662e99a73d017bcafe2148c5bc8fb5

[ "PSF-2.0" ]

null

"""macgenerate - Generate the out for macfreeze""" def generate(program, module_dict): for name in module_dict.keys(): print 'Include %-20s\t'%name, module = module_dict[name] print module.gettype(), '\t', repr(module) return 0

29

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8

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null

0

1

0

1

0

null

0

1

0

3

123569050bd8498260f9383bb7f14609f1f00ffd

139

py

Python

twitterapp/settings.py

kiwiheretic/logos-v2

22739221a6d431322c809b7e17aba54f37eb9617

[ "Apache-2.0" ]

4

2015-02-20T08:11:59.000Z

2019-05-15T23:48:11.000Z

twitterapp/settings.py

kiwiheretic/logos-v2

22739221a6d431322c809b7e17aba54f37eb9617

[ "Apache-2.0" ]

58

2015-01-11T02:10:09.000Z

2022-03-20T01:20:15.000Z

twitterapp/settings.py

kiwiheretic/logos-v2

22739221a6d431322c809b7e17aba54f37eb9617

[ "Apache-2.0" ]

1

2016-06-15T00:49:44.000Z

# The view that is shown for normal use of this app # Button name for front page SUPERUSER_SETTINGS_VIEW = 'twitterapp.views.site_setup'

23.166667

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0.165468

139

5

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27.8

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0.45

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false

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1

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null

0

1

0

1

null

0

3

125020b3db4dc8e3cfff6c4c559f3668e489b993

1,311

py

Python

7.0/acadox.py

vezril/IEEEXtreme

b0952cbe4a47a00f387f9f849bd6b632d6507126

[ "MIT" ]

null

7.0/acadox.py

vezril/IEEEXtreme

b0952cbe4a47a00f387f9f849bd6b632d6507126

[ "MIT" ]

null

7.0/acadox.py

vezril/IEEEXtreme

b0952cbe4a47a00f387f9f849bd6b632d6507126

[ "MIT" ]

null

#!/usr/bin/env python import sys x = raw_input() x = x.split(' ') limit = 65535 digit = [] for n in x: if n == '~': if len(digit) != 1: print 'ERROR' sys.exit(0) else: r = ~ digit[0] try: digit.pop() except: pass digit.append(r) elif n in ['+', '-', '|', '&', 'X']: try: if n == '+': r = digit[0] + digit[1] elif n == '-': r = digit[0] - digit[1] elif n == '&': r = digit[0] & digit[1] elif n == '|': r = digit[0] | digit[1] elif n == 'X': r = digit[0] ^ digit[1] elif n == '~': r = ~ digit[0] else: print 'ERROR' sys.exit(0) except: print 'ERROR' sys.exit(0) try: digit.pop() except: pass try: digit.pop() except: pass digit.append(r) else: digit.append(int(n, 16)) if r > limit: r = 'FFFF' elif r < 0: r = '0000' else: r = ('0000' + hex(r)[2:]) r = r[-4:len(r)] print r.upper()

20.169231

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1,311

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0.114754

0.093677

0.562061

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0.384075

0.229508

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1,311

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41

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null

0

1

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3

1255de85f2b1ef078ecb010a5367ef3c8b00de91

645

py

Python

app/surat/views.py

Ekhel/Surya

f7950f91f7492bd40164a28faaa26303641f11e5

[ "MIT" ]

null

app/surat/views.py

Ekhel/Surya

f7950f91f7492bd40164a28faaa26303641f11e5

[ "MIT" ]

null

app/surat/views.py

Ekhel/Surya

f7950f91f7492bd40164a28faaa26303641f11e5

[ "MIT" ]

null

from django.contrib.auth import (login as auth_login, authenticate) from django.http import HttpResponseRedirect from django.shortcuts import render from django.contrib.auth.decorators import login_required from django.http import HttpResponse from .models import surat_masuk @login_required def index(request): return render(request,'master/dashboard.html') @login_required def suratmasuk(request): contex = { 'item':surat_masuk.objects.all() } return render(request,'surat_masuk/r-surat-masuk.html',contex) @login_required def createsuratmasuk(request): return render(request, 'surat_masuk/c-surat-masuk.html')

29.318182

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645

21

69

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0.666667

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null

0

null

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1

0

3

89e3c1b162fe2b573788b359231f71cc8b24a42f

319

py

Python

pymath/primes/steps_in_primes/__init__.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

3

2017-05-02T10:28:13.000Z

2019-02-06T09:10:11.000Z

pymath/primes/steps_in_primes/__init__.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

2

2017-06-21T20:39:14.000Z

2020-02-25T10:28:57.000Z

pymath/primes/steps_in_primes/__init__.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

2

2016-07-29T04:35:22.000Z

2017-01-18T17:05:36.000Z

from ..is_prime import is_prime def step(g, m, n): if (n - m) < g: return None if (n - m) == g and (is_prime(m) and is_prime(n)): return [m, n] for x in range(m, n + 1): second = x + g if is_prime(x) and is_prime(second): return [x, second] return None

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89f39819e6cee5aa9736c85f80ae7e312588f9ec

917

py

Python

data/test/python/89f39819e6cee5aa9736c85f80ae7e312588f9ec__init__.py

harshp8l/deep-learning-lang-detection

2a54293181c1c2b1a2b840ddee4d4d80177efb33

[ "MIT" ]

84

2017-10-25T15:49:21.000Z

2021-11-28T21:25:54.000Z

data/test/python/89f39819e6cee5aa9736c85f80ae7e312588f9ec__init__.py

vassalos/deep-learning-lang-detection

cbb00b3e81bed3a64553f9c6aa6138b2511e544e

[ "MIT" ]

5

2018-03-29T11:50:46.000Z

2021-04-26T13:33:18.000Z

data/test/python/89f39819e6cee5aa9736c85f80ae7e312588f9ec__init__.py

vassalos/deep-learning-lang-detection

cbb00b3e81bed3a64553f9c6aa6138b2511e544e

[ "MIT" ]

24

2017-11-22T08:31:00.000Z

2022-03-27T01:22:31.000Z

from grano.core import app from grano.util import jsonify from grano.views.network_api import api as network_api from grano.views.entity_api import api as entity_api from grano.views.relation_api import api as relation_api from grano.views.schema_api import api as schema_api from grano.views.query_api import api as query_api from grano.views.home import section as home_section from grano.views.account import section as account_section app.register_blueprint(network_api, url_prefix='/api/1') app.register_blueprint(entity_api, url_prefix='/api/1') app.register_blueprint(relation_api, url_prefix='/api/1') app.register_blueprint(schema_api, url_prefix='/api/1') app.register_blueprint(query_api, url_prefix='/api/1') app.register_blueprint(account_section, url_prefix='') app.register_blueprint(home_section, url_prefix='') @app.route('/api/1') def apiroot(): return jsonify({'api': 'ok', 'version': 1})

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null

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1

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3

89f8443aea7ed9062498727bf25158392cc837ef

629

py

Python

rgd/geodata/migrations/0004_auto_20210302_2017.py

Erotemic/ResonantGeoData

ff9aec9daf73353bcc95a9d30e98fcc5cdffc6e0

[ "Apache-2.0" ]

null

rgd/geodata/migrations/0004_auto_20210302_2017.py

Erotemic/ResonantGeoData

ff9aec9daf73353bcc95a9d30e98fcc5cdffc6e0

[ "Apache-2.0" ]

null

rgd/geodata/migrations/0004_auto_20210302_2017.py

Erotemic/ResonantGeoData

ff9aec9daf73353bcc95a9d30e98fcc5cdffc6e0

[ "Apache-2.0" ]

null

# Generated by Django 3.2a1 on 2021-03-02 20:17 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('geodata', '0003_auto_20210301_1639'), ] operations = [ migrations.RemoveField( model_name='imageentry', name='failure_reason', ), migrations.RemoveField( model_name='imageentry', name='metadata', ), migrations.RemoveField( model_name='imageentry', name='status', ), migrations.DeleteModel( name='Thumbnail', ), ]

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0

1

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1

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null

0

3

d616d9bb7c7b15ad27c91bda79afbe3a5b807b33

381

py

Python

src/test/python/cseh/test_signal_elb_healthcheck.py

konz/cfn-signal-elb-healthcheck

a357836e36c88fdf1172f797f6771d12ab02e7de

[ "Apache-2.0" ]

null

src/test/python/cseh/test_signal_elb_healthcheck.py

konz/cfn-signal-elb-healthcheck

a357836e36c88fdf1172f797f6771d12ab02e7de

[ "Apache-2.0" ]

null

src/test/python/cseh/test_signal_elb_healthcheck.py

konz/cfn-signal-elb-healthcheck

a357836e36c88fdf1172f797f6771d12ab02e7de

[ "Apache-2.0" ]

null

from unittest import TestCase import cseh from mock import patch class TestSignalElbHealthcheck(TestCase): @patch("cseh.get_instance_metadata") def test_get_region_strips_availability_zone_to_region(self, get_instance_metadata): get_instance_metadata.return_value = { "availability-zone": "eu-west-1b" } self.assertEqual(cseh.get_region(), "eu-west-1")

29.307692

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0.769029

49

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5.673469

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13

89

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null

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1

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1

0

3

d618613ae15c86c3a5b1062d0d0336bc9e9e830c

466

py

Python

src/openapi_dataclasses/types/openapi/header.py

cal-pratt/openapi-dataclasses

106a0c7466dfd29beed1fa1734182f59d9c94393

[ "MIT" ]

null

src/openapi_dataclasses/types/openapi/header.py

cal-pratt/openapi-dataclasses

106a0c7466dfd29beed1fa1734182f59d9c94393

[ "MIT" ]

null

src/openapi_dataclasses/types/openapi/header.py

cal-pratt/openapi-dataclasses

106a0c7466dfd29beed1fa1734182f59d9c94393

[ "MIT" ]

null

from dataclasses import dataclass @dataclass class OpenApiHeader: """ The Header Object follows the structure of the Parameter Object with the following changes: 1. name MUST NOT be specified, it is given in the corresponding headers map. 2. in MUST NOT be specified, it is implicitly in header. 3. All traits that are affected by the location MUST be applicable to a location of header (for example, style). """

29.125

98

0.697425

66

466

4.924242

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0.055385

0.110769

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null

0

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0

1

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1

0

1

0

3

d640ac6282107ba41642de3b43441fa6e48fb07c

92

py

Python

src/telescope_msk/app_info.py

hmrc/aws-lambda-telescope-msk

efa9963e2988722e73a6bfbc73d10b0aeca3b70a

[ "Apache-2.0" ]

null

src/telescope_msk/app_info.py

hmrc/aws-lambda-telescope-msk

efa9963e2988722e73a6bfbc73d10b0aeca3b70a

[ "Apache-2.0" ]

1

2021-10-04T11:15:50.000Z

src/telescope_msk/app_info.py

hmrc/aws-lambda-telescope-msk

efa9963e2988722e73a6bfbc73d10b0aeca3b70a

[ "Apache-2.0" ]

1

2021-04-10T23:26:13.000Z

APP_NAME = "telescope-msk" APP_VERSION = "0.1.0" METRICS_PREFIX = "telemetry.telescope.msk"

23

42

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0.363636

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0.036145

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null

1

0

1

0

null

0

3

d64f73a280c213eae9dedc0ec2ad27bdef942b0f

298

py

Python

camelCase.py

monkee52/NCSSChallenge

e8849085e0578268dc5ce022b39c7d499884d810

[ "BSD-2-Clause" ]

null

camelCase.py

monkee52/NCSSChallenge

e8849085e0578268dc5ce022b39c7d499884d810

[ "BSD-2-Clause" ]

null

camelCase.py

monkee52/NCSSChallenge

e8849085e0578268dc5ce022b39c7d499884d810

[ "BSD-2-Clause" ]

null

# Enter your code for "camelCase" here. def to_camel(ident): def a(x): return x def b(x): return x[0].upper() + x[1::] def c(): yield a while True: yield b d = c() return "".join(d.__next__()(x) for x in ident.split("_"))

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0

null

0

null

0

1

0

1

0

3

c3853e84d7cabf221cc29b5c55148f9e1b9c1230

258

py

Python

hackathonbaobab2020/execution/__init__.py

baobabsoluciones/hackathonbaobab2020

ada30525cca061daad4bd420aa45dd4cfc7b790e

[ "MIT" ]

null

hackathonbaobab2020/execution/__init__.py

baobabsoluciones/hackathonbaobab2020

ada30525cca061daad4bd420aa45dd4cfc7b790e

[ "MIT" ]

2

2020-12-03T22:37:45.000Z

2021-01-28T19:43:42.000Z

hackathonbaobab2020/execution/__init__.py

baobabsoluciones/hackathonbaobab2020

ada30525cca061daad4bd420aa45dd4cfc7b790e

[ "MIT" ]

5

2020-11-20T15:37:58.000Z

2021-01-29T10:22:07.000Z

from .run_batch import * import warnings try: from .benchmark import * except ImportError: warnings.warn( "To use the benchmark functions, you need to install the benchmark dependencies: \n`pip install hackathonbaobab2020[benchmark]`" )

25.8

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258

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137

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1

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null

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1

0

1

0

3

c3905b54c582858a8de8a03ba1e9dead4f5cbe15

473

py

Python

tests/sfhs/test_exponential.py

AfonsoV/easyGalaxy

f7b5dd7160c11be473e7811ffdf53de2fd777d8b

[ "MIT" ]

14

2017-10-05T14:16:30.000Z

2020-11-19T07:07:35.000Z

tests/sfhs/test_exponential.py

clannadxu/easyGalaxy

0608b17d84d00c2bdc069ebfb83024bf8d15e309

[ "MIT" ]

4

2017-10-26T09:29:05.000Z

2019-04-02T15:40:32.000Z

tests/sfhs/test_exponential.py

clannadxu/easyGalaxy

0608b17d84d00c2bdc069ebfb83024bf8d15e309

[ "MIT" ]

8

2018-01-15T07:36:42.000Z

2021-08-24T07:46:50.000Z

import unittest import ezgal.sfhs import numpy as np class test_exponential(unittest.TestCase): def test_exponential_0(self): self.assertAlmostEqual(ezgal.sfhs.exponential(0, 1), 1.0, 7) def test_exponential_1(self): self.assertAlmostEqual(ezgal.sfhs.exponential(1, 1), 0.3678794, 7) def test_exponential_2(self): self.assertAlmostEqual(ezgal.sfhs.exponential(2, 1), 0.1353353, 7) if __name__ == '__main__': unittest.main()

21.5

74

0.710359

64

473

5.015625

0.359375

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0.168224

0.280374

0.420561

0

0.076726

0.173362

473

21

75

22.52381

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0

1

0

null

0

1

0

1

0

3

c3907e929b66829fa4d49d7ff49469c5243bd1bd

202

py

Python

Solutions/7kyu/7kyu_batman_quotes.py

citrok25/Codewars-1

dc641c5079e2e8b5955eb027fd15427e5bdb2e26

[ "MIT" ]

46

2017-08-24T09:27:57.000Z

2022-02-25T02:24:33.000Z

Solutions/7kyu/7kyu_batman_quotes.py

abbhishek971/Codewars

9e761811db724da1e8aae44594df42b4ee879a16

[ "MIT" ]

null

Solutions/7kyu/7kyu_batman_quotes.py

abbhishek971/Codewars

9e761811db724da1e8aae44594df42b4ee879a16

[ "MIT" ]

35

2017-08-01T22:09:48.000Z

2022-02-18T17:21:37.000Z

class BatmanQuotes(object): @staticmethod def get_quote(quotes, hero): index = int(sorted(hero)[0]) return {'B':'Batman: ','R':'Robin: ','J':'Joker: '}[hero[0]] + quotes[index]

28.857143

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202

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null

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1

0

null

0

1

0

3

c3c4188a6d3d78b60f8ac0492b4bec20db945627

220

py

Python

src/pydeb/_meta.py

nyyManni/pydeb

6b03fd8a0f03f7d1f5387bc59947c033c12b2a2d

[ "MIT" ]

null

src/pydeb/_meta.py

nyyManni/pydeb

6b03fd8a0f03f7d1f5387bc59947c033c12b2a2d

[ "MIT" ]

null

src/pydeb/_meta.py

nyyManni/pydeb

6b03fd8a0f03f7d1f5387bc59947c033c12b2a2d

[ "MIT" ]

null

__all__ = ['__author__', '__license__', '__version__', '__credits__', '__maintainer__'] __author__ = 'Henrik Nyman' __license__ = 'MIT' __version__ = '0.1' __credits__ = ['Henrik Nyman'] __maintainer__ = 'Henrik Nyman'

27.5

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7

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0.45

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null

1

0

1

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null

0

3

7f0f93445d1ee2aff60cbfdc6c27f0b288b77ea7

830

py

Python

krazon/exceptions.py

bryanforbes/Krazon

496aa554a0bc3b911771bbeb02783ae6832e9aa2

[ "BSD-3-Clause" ]

1

2018-06-22T22:55:17.000Z

krazon/exceptions.py

bryanforbes/Krazon

496aa554a0bc3b911771bbeb02783ae6832e9aa2

[ "BSD-3-Clause" ]

null

krazon/exceptions.py

bryanforbes/Krazon

496aa554a0bc3b911771bbeb02783ae6832e9aa2

[ "BSD-3-Clause" ]

null

from __future__ import annotations from discord.ext import commands class ClipNotFound(commands.CommandError): def __init__(self, name: str) -> None: super().__init__(message=f'No clip named `{name}` found') class FilenameExists(commands.CommandError): def __init__(self, filename: str) -> None: super().__init__(message=f'A file named `{filename}` has already been uploaded. ' 'Rename the file and try again.') class MustBeConnected(commands.CommandError): def __init__(self) -> None: super().__init__(message='You must be connected to a voice channel to play a clip') class TooManyMembers(commands.CommandError): def __init__(self) -> None: super().__init__(message='Cannot connect to voice channel to play the clip: too many members connected')

33.2

112

0.7

103

830

5.291262

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0.146789

0.168807

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0.388991

0.275229

0.187156

0

0.196386

830

24

113

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null

0

1

0

null

0

1

0

1

0

3

61394104ab8a92f2ceec31ae226b734c6ae91021

1,386

py

Python

Asynconf 2020/algo/ex5.py

BhasherBEL/ProgrammingChallenges

e697c7f7e3d8177b9ee615918f3c78b645b927d0

[ "MIT" ]

null

Asynconf 2020/algo/ex5.py

BhasherBEL/ProgrammingChallenges

e697c7f7e3d8177b9ee615918f3c78b645b927d0

[ "MIT" ]

1

2020-12-09T12:00:56.000Z

Asynconf 2020/algo/ex5.py

BhasherBEL/ProgrammingChallenges

e697c7f7e3d8177b9ee615918f3c78b645b927d0

[ "MIT" ]

1

2020-12-09T11:38:49.000Z

import re def analyze(text: str) -> str: """Automatically analyzes the content of the letter to Santa Claus. Args: text (str): Original letter Returns: str: simplified letter """ age = re.search(r'(\d+)ans', text).group(1) name = re.search(r'jem\'?appelle(.+?)(?: |(j\'?ai))', text).group(1) address = re.search(r'j\'?habite(.+?)(?:\.|$)', text).group(1) gift = re.findall(r'j\'?aimeraisavoirun(.+?)pour', text) return f'[Lettre de {name} {age} ans]\nAdresse{address}\nCadeau: {", ".join(gift)}' print(analyze("BonjourjemappelleMatheojai6ansetjaimeraisavoirunvelopour pouvoiraller me balader. ensuite j'aimerais bien une nouvelle console nintendo pourjoueràpokemonbleu que je n'ai pas aussi. Par contre j'ai déjà le jeu doncpasbesoin merciperenoel j'habite rue des papillons")) print('\n') print(analyze("Cetteannéejaimeraisavoiruntelephonepour m'amuser,jem'appelleClara etjai bientot5anset jaiété tres sage, jaimeraisavoirunchatpourmamuseravec lui ça me fera tres plaisir. j'habite avenue des marmottes")) print('\n') print(analyze("Salut papa noel, c'est moi jemappelleElsaj'ai 4ans et j'habite route des papillons. jaimeraisavoirunboite de legopour constructure plein de choses ! merci papa noeletaussi sion peutavoirun deuxiemecadeau jaimeraisavoiruncamion de pompierpourjouer avec mon frere il a 5 ans et il s'apel leo."))

55.44

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null

0

1

0

null

0

1

0

3

613c05b33b2f11f79924641d266395a7a0aa1e2e

1,207

py

Python

envi/archs/msp430/__init__.py

vEpiphyte/vivisect

14947a53c6781175f0aa83d49cc16c524a2e23a3

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

1

2020-12-23T19:23:17.000Z

envi/archs/msp430/__init__.py

vEpiphyte/vivisect

14947a53c6781175f0aa83d49cc16c524a2e23a3

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

null

envi/archs/msp430/__init__.py

vEpiphyte/vivisect

14947a53c6781175f0aa83d49cc16c524a2e23a3

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

1

2020-12-23T19:23:58.000Z

""" msp430 module """ ############ # Author: Don C. Weber # Started: 05/23/2009 # import envi from envi.archs.msp430.regs import * from envi.archs.msp430.disasm import * from envi.archs.msp430.const import * class Msp430Module(envi.ArchitectureModule): def __init__(self): envi.ArchitectureModule.__init__(self, "msp430", maxinst=4) self._arch_dis = Msp430Disasm() def archGetRegCtx(self): return Msp430RegisterContext() def archGetNopInstr(self): return '\x03\x43' # NOP is emulated with: MOV #0, R3 def archGetRegisterGroups(self): groups = envi.ArchitectureModule.archGetRegisterGroups(self) general= ('general', registers, ) groups.append(general) return groups def getPointerSize(self): return 2 def pointerString(self, va): return '0x{:04x}'.format(va) def archParseOpcode(self, bytes, offset=0, va=0): return self._arch_dis.disasm(bytes, offset, va) def getEmulator(self): return Msp430Emulator() def getArchDefaultCall(self): return 'msp430call' # NOTE: This one must be after the definition of Msp430Module from envi.archs.msp430.emu import *

23.666667

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24.14

0.782011

0.122618

0

0.037718

0

1

0.321429

false

0

0.178571

0.25

0.821429

0

null

0

null

0

1

0

1

0

3

617a402859ff4834f7dfe9b61a9f652c8cf7e29b

261

py

Python

system.py

shjnb/system_one

8e5f70e502b72555e58a9cb75d14ef00eadba909

[ "Apache-2.0" ]

null

system.py

shjnb/system_one

8e5f70e502b72555e58a9cb75d14ef00eadba909

[ "Apache-2.0" ]

null

system.py

shjnb/system_one

8e5f70e502b72555e58a9cb75d14ef00eadba909

[ "Apache-2.0" ]

null

# 从app包中导入变量app（它是作为app包成员的变量） from app import app, db from app.models import User, Post @app.shell_context_processor def make_shell_context(): return {'db': db, 'User': User, 'Post': Post} if __name__ == '__main__': app.run(debug=True)

20.076923

50

0.678161

35

261

4.714286

0.6

0.084848

0

0.195402

261

12

51

21.75

0.785714

0.10728

0

0.082192

0

1

0.142857

true

0

0.285714

0.142857

0.571429

0

null

0

null

0

1

0

1

0

3

61872a27768311c97b6699dc072cad405573452c

178

py

Python

api_ui/serializers.py

mihail-ivanov/base-vue-api

a2ef8ae360d3d26425093aefaf521082cf3684c5

[ "MIT" ]

null

api_ui/serializers.py

mihail-ivanov/base-vue-api

a2ef8ae360d3d26425093aefaf521082cf3684c5

[ "MIT" ]

null

api_ui/serializers.py

mihail-ivanov/base-vue-api

a2ef8ae360d3d26425093aefaf521082cf3684c5

[ "MIT" ]

null

from rest_framework import serializers class UserSerializer(serializers.Serializer): email = serializers.EmailField() username = serializers.CharField(max_length=100)

22.25

52

0.797753

18

178

7.777778

0.833333

0

0.019355

0.129213

178

7

53

25.428571

0.883871

0

1

0

false

0

0.25

0

1

0

1

0

null

0

1

0

null

0

1

0

3

61b053b23ccf88b08d43b1f289692ece12c9a556

544

py

Python

src/docker_composer/runner/cmd/images.py

michascholl/docker-composer

d190f1db766e216654a4259785b9aaf802a9c64d

[ "Apache-2.0" ]

4

2021-01-18T11:35:24.000Z

2021-08-30T16:19:39.000Z

src/docker_composer/runner/cmd/images.py

michascholl/docker-composer

d190f1db766e216654a4259785b9aaf802a9c64d

[ "Apache-2.0" ]

null

src/docker_composer/runner/cmd/images.py

michascholl/docker-composer

d190f1db766e216654a4259785b9aaf802a9c64d

[ "Apache-2.0" ]

1

2022-02-19T10:38:59.000Z

# DO NOT EDIT: Autogenerated by src/docker_composer/_utils/generate_class.py # for docker-compose version 1.25.0, build unknown from typing import List, Optional import attr from docker_composer.base import DockerBaseRunner @attr.s(auto_attribs=True) class DockerComposeImages(DockerBaseRunner): """ List images used by the created containers. Usage: images [options] [SERVICE...] """ quiet: Optional[bool] = None """Only display IDs""" _cmd: str = "images" _options: List[str] = [ "quiet", ]

21.76

76

0.691176

67

544

5.507463

0.731343

0.075881

0

0.009195

0.200368

544

24

77

22.666667

0.83908

0.376838

0

1

0

0.037288

0

1

0

true

0

0.3

0

0.7

0

null

0

1

0

null

0

1

0

1

0

3

61b765a89a63194c8888185127c05dd269d6eef7

396

py

Python

src/config/yaml_conf_parser.py

Twente-Mining/tezos-reward-distributor

8df0745fdb44cbd765084303882545202d2427f3

[ "MIT" ]

null

src/config/yaml_conf_parser.py

Twente-Mining/tezos-reward-distributor

8df0745fdb44cbd765084303882545202d2427f3

[ "MIT" ]

null

src/config/yaml_conf_parser.py

Twente-Mining/tezos-reward-distributor

8df0745fdb44cbd765084303882545202d2427f3

[ "MIT" ]

null

import yaml from config.config_parser import ConfigParser class YamlConfParser(ConfigParser): def __init__(self, yaml_text, verbose=None) -> None: super().__init__(yaml_text, verbose) def parse(self): self.set_conf_obj(yaml.safe_load(self.conf_text)) return self.get_conf_obj() def validate(self): return True def process(self): pass

20.842105

57

0.679293

51

396

4.941176

0.529412

0.063492

0.119048

0

0.227273

396

19

58

20.842105

0.823529

0

1

0.333333

false

0.083333

0.166667

0.083333

0.75

0

null

0

null

0

1

0

1

0

1

0

3

61c8ff5fad4f7a02863b56f0a945e3432823b7c9

286

py

Python

src/rctgen/impl/activity_block_meta_t.py

mballance/pyrctgen

eb47ed2039d36ab236b63e795b313feb499820bd

[ "Apache-2.0" ]

1

2022-03-10T04:12:11.000Z

src/rctgen/impl/activity_block_meta_t.py

mballance/pyrctgen

eb47ed2039d36ab236b63e795b313feb499820bd

[ "Apache-2.0" ]

null

src/rctgen/impl/activity_block_meta_t.py

mballance/pyrctgen

eb47ed2039d36ab236b63e795b313feb499820bd

[ "Apache-2.0" ]

null

''' Created on Mar 19, 2022 @author: mballance ''' class ActivityBlockMetaT(type): def __init__(self, name, bases, dct): pass def __enter__(self): print("ActivityBlockMetaT.__enter__") def __exit__(self, t, v, tb): pass

15.888889

45

0.566434

30

286

4.866667

0.766667

0

0.030928

0.321678

286

18

46

15.888889

0.721649

0.15035

0

0.285714

0

0.118644

0

1

0.428571

false

0.285714

0

0.571429

0.142857

0

null

0

null

0

1

0

1

0

1

0

3

4ee744a4296552506d7c85593bc239640f00db0b

37

py

Python

src/modules/index/controller.py

RemLampa/emotion-server

9e881718d8949068f4bb32d5baa748c19043e2cb

[ "MIT" ]

null

src/modules/index/controller.py

RemLampa/emotion-server

9e881718d8949068f4bb32d5baa748c19043e2cb

[ "MIT" ]

null

src/modules/index/controller.py

RemLampa/emotion-server

9e881718d8949068f4bb32d5baa748c19043e2cb

[ "MIT" ]

null

response = {'index': 'Hello World!'}

18.5

36

0.621622

4

37

5.75

1

0

0.135135

37

1

37

0.71875

0

0.459459

0

1

0

false

0

1

0

null

0

1

0

null

0

3

4eff9333827648c6428aeae6707a96a283ec040b

1,333

py

Python

rippl/bills/migrations/0002_auto_20170109_2142.py

gnmerritt/dailyrippl

9a0f9615ba597a475dbd6305b589827cb2d97b03

[ "MIT" ]

6

2016-12-03T20:30:43.000Z

2017-01-10T01:50:09.000Z

rippl/bills/migrations/0002_auto_20170109_2142.py

gnmerritt/dailyrippl

9a0f9615ba597a475dbd6305b589827cb2d97b03

[ "MIT" ]

24

2016-11-30T02:31:13.000Z

2020-02-25T22:47:27.000Z

rippl/bills/migrations/0002_auto_20170109_2142.py

gnmerritt/dailyrippl

9a0f9615ba597a475dbd6305b589827cb2d97b03

[ "MIT" ]

1

2016-12-25T21:42:31.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.10.4 on 2017-01-09 21:42 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('bills', '0001_initial'), ] operations = [ migrations.AlterField( model_name='bill', name='chamber', field=models.CharField(choices=[('S', 'Senate'), ('H', 'House')], max_length=3, null=True), ), migrations.AlterField( model_name='bill', name='official_title', field=models.TextField(default=''), ), migrations.AlterField( model_name='bill', name='popular_title', field=models.CharField(default='', max_length=127), ), migrations.AlterField( model_name='bill', name='summary', field=models.TextField(default=''), ), migrations.AlterField( model_name='bill', name='sunlight_id', field=models.CharField(default='', max_length=63), ), migrations.AlterField( model_name='bill', name='url', field=models.CharField(default='', help_text='Permalink with more info', max_length=127), ), ]

28.978261

103

0.549137

128

1,333

5.5625

0.5

0.168539

0.210674

0.244382

0.488764

0.179775

0

0.032751

0.312828

1,333

45

104

29.622222

0.744541

0.051013

0

0.526316

1

0

0.105388

0

1

0

false

0

0.052632

0

0.131579

0

null

0

1

0

1

0

null

0

3

f613a6a8024559c755ac8ea22e39cbe8630262ec

588

py

Python

asendia_us/asendia_us_lib/shipping_rate_request.py

Purplship/purplship-carriers

dcd044320b86e9af5fe3ef15c36ebf7828b2851b

[ "MIT" ]

2

2021-04-12T22:40:28.000Z

2021-04-21T18:28:31.000Z

asendia_us/asendia_us_lib/shipping_rate_request.py

Purplship/purplship-carriers

dcd044320b86e9af5fe3ef15c36ebf7828b2851b

[ "MIT" ]

2

2021-01-29T07:14:31.000Z

2021-02-18T18:29:23.000Z

asendia_us/asendia_us_lib/shipping_rate_request.py

Purplship/purplship-carriers

dcd044320b86e9af5fe3ef15c36ebf7828b2851b

[ "MIT" ]

3

2020-09-09T17:04:46.000Z

2021-03-05T00:32:32.000Z

from attr import s from typing import Optional @s(auto_attribs=True) class ShippingRateRequest: accountNumber: Optional[str] = None subAccountNumber: Optional[str] = None processingLocation: Optional[str] = None recipientPostalCode: Optional[str] = None recipientCountryCode: Optional[str] = None totalPackageWeight: Optional[float] = None weightUnit: Optional[str] = None dimLength: Optional[float] = None dimWidth: Optional[float] = None dimHeight: Optional[float] = None dimUnit: Optional[str] = None productCode: Optional[str] = None

30.947368

46

0.72449

62

588

6.854839

0.419355

0.207059

0.282353

0

0.185374

588

18

47

32.666667

0.887265

0

1

0

true

0

0.125

0

0.9375

0

null

1

0

null

0

1

0

3

f61e29c1e80f540d580ccd4734dee6aedfb8a840

228

py

Python

apps/verifications/urls.py

rui1106/LemonShop

282e07358492a0e5912e508858ccb9c9cde63503

[ "CC0-1.0" ]

null

apps/verifications/urls.py

rui1106/LemonShop

282e07358492a0e5912e508858ccb9c9cde63503

[ "CC0-1.0" ]

null

apps/verifications/urls.py

rui1106/LemonShop

282e07358492a0e5912e508858ccb9c9cde63503

[ "CC0-1.0" ]

null

from django.urls import path from apps.verifications.views import ImageCodeView, SmsCodeView urlpatterns = [ path('image_codes/<uuid>/', ImageCodeView.as_view()), path('sms_codes/<mobile>/', SmsCodeView.as_view()), ]

22.8

63

0.732456

27

228

6.037037

0.666667

0.07362

0

0.122807

228

9

64

25.333333

0.815

0

0.166667

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

0

1

0

null

0

1

0

3

f620ae7ca79c18d6e2a4826df4a795c27dda8d26

768

py

Python

arucoDetection/src/svgfig/svgfig/interactive.py

LavaHawk0123/Artmis-Drone

b78dcbb28ecdce4d82fc4addb60367e4cc266349

[ "MIT" ]

null

arucoDetection/src/svgfig/svgfig/interactive.py

LavaHawk0123/Artmis-Drone

b78dcbb28ecdce4d82fc4addb60367e4cc266349

[ "MIT" ]

null

arucoDetection/src/svgfig/svgfig/interactive.py

LavaHawk0123/Artmis-Drone

b78dcbb28ecdce4d82fc4addb60367e4cc266349

[ "MIT" ]

null

import curve, defaults, glyphs, pathdata, plot, svg, trans # Only bring into the namespace the functions and classes that the user will need # This distinguishes user interface from internal functions # (Though the user can still access them, it intentionally requires more typing) # Internal class members are preceeded by an underscore from defaults import BBox from svg import SVG, template, load, load_stream, rgb, randomid, shortcut from glyphs import latex from trans import clone, tonumber, transform, evaluate, Delay, Freeze, Pin, window, rotation, transformation_angle, transformation_jacobian from pathdata import poly, bezier, velocity, foreback, smooth from curve import Curve, format_number, unicode_number, ticks, logticks from plot import Fig, Canvas

51.2

139

0.809896

107

768

5.766355

0.691589

0.035656

0

0.140625

768

14

140

54.857143

0.934848

0.351563

0

1

0

true

0

1

0

1

0

null

0

null

0

1

0

1

0

1

0

3

f6247a9b86cbc94ed455caa8389e21b176422390

1,859

py

Python

Longest Palindromic Substring/main.py

PromasterGuru/Leetcode-Solutions

46a74369f78dbd89e664a4460c25c190bb5f4dbc

[ "MIT" ]

null

Longest Palindromic Substring/main.py

PromasterGuru/Leetcode-Solutions

46a74369f78dbd89e664a4460c25c190bb5f4dbc

[ "MIT" ]

null

Longest Palindromic Substring/main.py

PromasterGuru/Leetcode-Solutions

46a74369f78dbd89e664a4460c25c190bb5f4dbc

[ "MIT" ]

null

class Solution: def expandFromMiddle(self, s:str, l:int, r:int): while (l >= 0 and r < len(s) and s[l] == s[r]): l -= 1 r += 1 return (r - l - 1) def longestPalindrome(self, s: str) -> str: if len(s) < 1: return 0 start = 0 end = 0 for i in range(len(s)): l1 = self.expandFromMiddle(s, i, i) l2 = self.expandFromMiddle(s, i, i+1) ls = max(l1,l2) if ls > end - start: start = i - ((ls - 1)//2) end = i + (ls//2) return s[start: end+1] if __name__ == "__main__": sol = Solution() s = "babab" s = "cbbd" # s = 'bb' # s = "babc" # s = "aca" # s = "defggbac" # s = 'a' s = "babad" # s = "ccc" s = "abb" # s = "reifadyqgztixemwswtccodfnchcovrmiooffbbijkecuvlvukecutasfxqcqygltrogrdxlrslbnzktlanycgtniprjlospzhhgdrqcwlukbpsrumxguskubokxcmswjnssbkutdhppsdckuckcbwbxpmcmdicfjxaanoxndlfpqwneytatcbyjmimyawevmgirunvmdvxwdjbiqszwhfhjmrpexfwrbzkipxfowcbqjckaotmmgkrbjvhihgwuszdrdiijkgjoljjdubcbowvxslctleblfmdzmvdkqdxtiylabrwaccikkpnpsgcotxoggdydqnuogmxttcycjorzrtwtcchxrbbknfmxnonbhgbjjypqhbftceduxgrnaswtbytrhuiqnxkivevhprcvhggugrmmxolvfzwadlnzdwbtqbaveoongezoymdrhywxcxvggsewsxckucmncbrljskgsgtehortuvbtrsfisyewchxlmxqccoplhlzwutoqoctgfnrzhqctxaqacmirrqdwsbdpqttmyrmxxawgtjzqjgffqwlxqxwxrkgtzqkgdulbxmfcvxcwoswystiyittdjaqvaijwscqobqlhskhvoktksvmguzfankdigqlegrxxqpoitdtykfltohnzrcgmlnhddcfmawiriiiblwrttveedkxzzagdzpwvriuctvtrvdpqzcdnrkgcnpwjlraaaaskgguxzljktqvzzmruqqslutiipladbcxdwxhmvevsjrdkhdpxcyjkidkoznuagshnvccnkyeflpyjzlcbmhbytxnfzcrnmkyknbmtzwtaceajmnuyjblmdlbjdjxctvqcoqkbaszvrqvjgzdqpvmucerumskjrwhywjkwgligkectzboqbanrsvynxscpxqxtqhthdytfvhzjdcxgckvgfbldsfzxqdozxicrwqyprgnadfxsionkzzegmeynye" print(sol.longestPalindrome(s))

53.114286

1,002

0.727273

119

1,859

11.294118

0.369748

0.008929

0.011905

0.032738

0.034226

0

0.011379

0.196342

1,859

34

1,003

54.676471

0.88822

0.569661

0

0.031566

0

1

0

1

0.08

false

0

0.2

0.04

0

1

null

0

1

0

null

1

0

3

f67a7e72ebf56cedf4000f2075f26246171cab8d

303

py

Python

ok_cart/services/cart_group.py

LowerDeez/ok-cart

d483e0eecc228e72138efc08cab95291be64a8bb

[ "MIT" ]

3

2021-05-07T06:20:41.000Z

2021-10-20T06:15:30.000Z

ok_cart/services/cart_group.py

LowerDeez/ok-cart

d483e0eecc228e72138efc08cab95291be64a8bb

[ "MIT" ]

null

ok_cart/services/cart_group.py

LowerDeez/ok-cart

d483e0eecc228e72138efc08cab95291be64a8bb

[ "MIT" ]

null

from typing import TYPE_CHECKING if TYPE_CHECKING: from ..models import CartGroup __all__ = ( 'delete_cart_group', ) def delete_cart_group(*, cart_group: 'CartGroup'): if cart_group.base: cart_group.base.delete() cart_group.relations.all().delete() cart_group.delete()

16.833333

50

0.69967

39

303

5.051282

0.384615

0.319797

0.304569

0.182741

0

0.191419

303

17

51

17.823529

0.804082

0

0.085809

0

1

0.090909

false

0

0.181818

0

0.272727

0

null

1

0

null

0

3

9c890913ae4243c20c9f20a76072c4861cc2a19e

233

py

Python

test_pkg.py

rtmigo/neatest_py

f5c5339bb2ab62fbc7e5bacc34ed308789b2dbde

[ "MIT" ]

3

2021-05-16T01:15:17.000Z

2022-02-09T12:00:29.000Z

test_pkg.py

rtmigo/neatest_py

f5c5339bb2ab62fbc7e5bacc34ed308789b2dbde

[ "MIT" ]

null

test_pkg.py

rtmigo/neatest_py

f5c5339bb2ab62fbc7e5bacc34ed308789b2dbde

[ "MIT" ]

null

from chkpkg import Package if __name__ == "__main__": with Package() as pkg: pkg.run_python_code('import neatest; neatest.print_version()') pkg.run_shell_code('neatest --version') print("\nPackage is OK!")

23.3

70

0.669528

30

233

4.766667

0.666667

0.083916

0

0.201717

233

9

71

25.888889

0.768817

0

0.344828

0.099138

0

1

0

true

0

0.333333

0

0.333333

0

null

0

1

0

null

0

1

0

1

0

3

9c98c7f9a01165391e4d35cdc902d93191bb7e53

141

py

Python

python3.6/module/argv.py

MisterZhouZhou/python3demo

da0b6771cc12e8e1066a115c3f72a90c100108ac

[ "Apache-2.0" ]

3

2019-03-04T08:39:57.000Z

2019-12-06T08:29:47.000Z

python3.6/module/argv.py

MisterZhouZhou/python3demo

da0b6771cc12e8e1066a115c3f72a90c100108ac

[ "Apache-2.0" ]

null

python3.6/module/argv.py

MisterZhouZhou/python3demo

da0b6771cc12e8e1066a115c3f72a90c100108ac

[ "Apache-2.0" ]

null

#!/usr/bin/python3 # 文件名: using_sys.py import sys print('命令行参数如下：') for i in sys.argv: print(i) print('\n\nPython 路径为: ',sys.path, '\n')

17.625

40

0.64539

25

141

3.6

0.72

0

0.008264

0.141844

141

8

40

17.625

0.735537

0.248227

0

0.247619

0

1

0

false

0

0.2

0

0.2

0.6

1

0

null

0

1

0

null

0

1

0

3

9cbd29739e6cca7d4bee7e4b6217d054d4454510

447

py

Python

mediaman/core/index/abstract.py

MattCCS/MediaMan

388c0d16da437b0ede4f0903a01e41dc8e927ae6

[ "BSD-3-Clause-Clear" ]

1

2019-05-06T19:51:08.000Z

mediaman/core/index/abstract.py

MattCCS/MediaMan

388c0d16da437b0ede4f0903a01e41dc8e927ae6

[ "BSD-3-Clause-Clear" ]

1

2021-02-08T20:22:34.000Z

mediaman/core/index/abstract.py

MattCCS/MediaMan

388c0d16da437b0ede4f0903a01e41dc8e927ae6

[ "BSD-3-Clause-Clear" ]

null

from mediaman.core.clients.abstract import abstract class AbstractIndex(abstract.AbstractClient): def __init__(self, service): self.service = service def name(self): return self.service.__class__.__name__ def nickname(self): return self.service.nickname() def __repr__(self): return f"{self.__class__.__name__}({repr(self.service)})" def has(self, file_id): raise RuntimeError()

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0

null

0

1

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0

3

9cc218c7fc02a4dab8e2511a3e8fca9468d10ccb

28

py

Python

portfolio/Python/scrapy/americanrv/__init__.py

0--key/lib

ba7a85dda2b208adc290508ca617bdc55a5ded22

[ "Apache-2.0" ]

null

portfolio/Python/scrapy/americanrv/__init__.py

0--key/lib

ba7a85dda2b208adc290508ca617bdc55a5ded22

[ "Apache-2.0" ]

null

portfolio/Python/scrapy/americanrv/__init__.py

0--key/lib

ba7a85dda2b208adc290508ca617bdc55a5ded22

[ "Apache-2.0" ]

5

2016-03-22T07:40:46.000Z

2021-05-30T16:12:21.000Z

ACCOUNT_NAME = 'American RV'

28

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28

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0

1

0

null

0

1

0

null

0

3

9cc9417422f81e0be06683c3b8079c4192d0feb7

210

py

Python

src/NRInsightsApi/__init__.py

vikramnr/newrelic-insights-api

ef286eb6cc8fe27e9713c6fa5da5e623f8371f63

[ "MIT" ]

null

src/NRInsightsApi/__init__.py

vikramnr/newrelic-insights-api

ef286eb6cc8fe27e9713c6fa5da5e623f8371f63

[ "MIT" ]

null

src/NRInsightsApi/__init__.py

vikramnr/newrelic-insights-api

ef286eb6cc8fe27e9713c6fa5da5e623f8371f63

[ "MIT" ]

null

from .insert_data import insert_data from .get_data import get_data # if somebody does "from somepackage import *", this is what they will # be able to access: __all__ = [ 'insert_data', 'get_data', ]

21

70

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null

1

0

1

0

null

0

1

0

3

9ccae0495fce471b07a45a219afe8b07e455d757

167

py

Python

update_ec2_dns_function/update_ec2_dns/aws.py

vladvasiliu/UpdateEC2DNS

63b76f138605a786e0b40295866f7cf13977fb3d

[ "BSD-3-Clause" ]

null

update_ec2_dns_function/update_ec2_dns/aws.py

vladvasiliu/UpdateEC2DNS

63b76f138605a786e0b40295866f7cf13977fb3d

[ "BSD-3-Clause" ]

null

update_ec2_dns_function/update_ec2_dns/aws.py

vladvasiliu/UpdateEC2DNS

63b76f138605a786e0b40295866f7cf13977fb3d

[ "BSD-3-Clause" ]

null

import boto3 def get_ec2_public_ip(instance_id: str): ec2 = boto3.resource("ec2") instance = ec2.Instance(instance_id) return instance.public_ip_address

20.875

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null

0

1

0

null

0

1

0

3

9ccb9ce27a2c12a506deb5eeffe74f252eda3b95

2,298

py

Python

customer_sequence/models/res_partner.py

Yousif-Mobark/odoo11_cutom

35a09266a1d4d74569316886019c11ce41e9216b

[ "Apache-2.0" ]

null

customer_sequence/models/res_partner.py

Yousif-Mobark/odoo11_cutom

35a09266a1d4d74569316886019c11ce41e9216b

[ "Apache-2.0" ]

null

customer_sequence/models/res_partner.py

Yousif-Mobark/odoo11_cutom

35a09266a1d4d74569316886019c11ce41e9216b

[ "Apache-2.0" ]

1

2020-04-18T02:42:54.000Z

# -*- coding: utf-8 -*- from odoo import models, fields, api class ResPartner(models.Model): _inherit = 'res.partner' unique_id = fields.Char(string='Unique Id', help="The Unique Sequence no", readonly=True, default='/') @api.model def create(self, values): res = super(ResPartner, self).create(values) company_seq = self.env['res.users'].browse(self._uid).company_id if res.customer and res.unique_id == '/': if company_seq.next_code: res.unique_id = company_seq.next_code res.name = '[' + str(company_seq.next_code) + ']' + str(res.name) company_seq.write({'next_code': company_seq.next_code + 1}) else: res.unique_id = company_seq.customer_code res.name = '[' + str(company_seq.customer_code) + ']' + str(res.name) company_seq.write({'next_code': company_seq.customer_code + 1}) if res.supplier == True and res.unique_id == '/': if company_seq.supp_code < 10: res.unique_id = '000' + str(company_seq.supp_code) res.name = '[' + '000' + str(company_seq.supp_code) + ']' + str(res.name) company_seq.write({'supp_code': company_seq.supp_code + 1}) elif company_seq.supp_code < 100: res.unique_id = '00' + str(company_seq.supp_code) res.name = '[' + '00' + str(company_seq.supp_code) + ']' + str(res.name) company_seq.write({'supp_code': company_seq.supp_code + 1}) elif company_seq.supp_code < 1000: res.unique_id = '0' + str(company_seq.supp_code) res.name = '[' + '0' + str(company_seq.supp_code) + ']' + str(res.name) company_seq.write({'supp_code': company_seq.supp_code + 1}) elif company_seq.supp_code > 1000: res.unique_id = company_seq.supp_code res.name = '[' + str(company_seq.supp_code) + ']' + str(res.name) company_seq.write({'supp_code': company_seq.supp_code + 1}) else: res.unique_id = company_seq.supp_code res.name = '[' + '0001' + ']' + str(res.name) company_seq.write({'supp_code': 2}) return res

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null

1

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null

0

3

9cd94a580e75810ef128f72f6fc461b4adc6ee62

104

py

Python

src/webpy1/src/fetch/fet_global_vars.py

ptphp/PyLib

07ac99cf2deb725475f5771b123b9ea1375f5e65

[ "Apache-2.0" ]

1

2020-02-17T08:18:29.000Z

src/webpy1/src/fetch/fet_global_vars.py

ptphp/PyLib

07ac99cf2deb725475f5771b123b9ea1375f5e65

[ "Apache-2.0" ]

null

src/webpy1/src/fetch/fet_global_vars.py

ptphp/PyLib

07ac99cf2deb725475f5771b123b9ea1375f5e65

[ "Apache-2.0" ]

null

#coding=UTF-8 ''' Created on 2011-7-7 @author: Administrator ''' import Queue fetch_quere=Queue.Queue()

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104

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9cffc75ee41096072f0ecc52248c93678ad45ee4

479

py

Python

core-python-classes-and-oo/multiple_inheritance_and_method_resolution_order/method_resolution_order/main.py

hassonor/core-python

92672aa72c1474061df5247a2dd4dfd9fab1642a

[ "MIT" ]

1

2022-03-09T20:58:33.000Z

core-python-classes-and-oo/multiple_inheritance_and_method_resolution_order/method_resolution_order/main.py

hassonor/core-python

92672aa72c1474061df5247a2dd4dfd9fab1642a

[ "MIT" ]

null

core-python-classes-and-oo/multiple_inheritance_and_method_resolution_order/method_resolution_order/main.py

hassonor/core-python

92672aa72c1474061df5247a2dd4dfd9fab1642a

[ "MIT" ]

null

from simple_list import * from diamond import * print(SortedIntList.__mro__) # The Method Resolution Order for a class is stored on __mro__ print(D.__mro__) """ (<class 'simple_list.SortedIntList'>, <class 'simple_list.IntList'>, <class 'simple_list.SortedList'>, <class 'simple_list.SimpleList'>, <class 'object'>) (<class 'diamond.D'>, <class 'diamond.B'>, <class 'diamond.C'>, <class 'diamond.A'>, <class 'object'>) """ d = D() print(d.func()) # -> Will Print 'B.func'

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null

0

1

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1

0

3

1442671f90439d2dd5e96fdc15ac84ea6f49f5c4

295

py

Python

fractal.py

catzilla-007/fractal-overload

5d173124aaefdb84539248e22275fd2ee39522d8

[ "MIT" ]

null

fractal.py

catzilla-007/fractal-overload

5d173124aaefdb84539248e22275fd2ee39522d8

[ "MIT" ]

null

fractal.py

catzilla-007/fractal-overload

5d173124aaefdb84539248e22275fd2ee39522d8

[ "MIT" ]

null

from abc import ABC, abstractmethod from image import Image class Fractal(ABC): def __init__(self, image: Image): self._image = image @abstractmethod def _fractalize(self, point_a, point_b, level): pass @abstractmethod def draw(self, level): pass

18.4375

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0

null

0

1

0

1

0

1

0

3

1447ff5689e316b188c6a2a92ad90f5c58d95882

1,602

py

Python

earth_enterprise/src/server/wsgi/search/common/exceptions.py

ezeeyahoo/earthenterprise

b6cac9e6228946f2f17d1edb75e118aeb3e8e8c9

[ "Apache-2.0" ]

2,661

2017-03-20T22:12:50.000Z

2022-03-30T09:43:19.000Z

earth_enterprise/src/server/wsgi/search/common/exceptions.py

ezeeyahoo/earthenterprise

b6cac9e6228946f2f17d1edb75e118aeb3e8e8c9

[ "Apache-2.0" ]

1,531

2017-03-24T17:20:32.000Z

2022-03-16T18:11:14.000Z

earth_enterprise/src/server/wsgi/search/common/exceptions.py

ezeeyahoo/earthenterprise

b6cac9e6228946f2f17d1edb75e118aeb3e8e8c9

[ "Apache-2.0" ]

990

2017-03-24T11:54:28.000Z

2022-03-22T11:51:47.000Z

#!/usr/bin/env python2.7 # # Copyright 2017 Google Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """Module for all exception's which search services may raise.""" from search.common import utils class Error(Exception): """Generic error.""" def ToString(self, error_prefix): """Builds error message string escaping it for HTML. Args: error_prefix: an error prefix. Returns: HTML escaped error message. """ if error_prefix: return utils.HtmlEscape( "{0}: {1}".format(error_prefix, str("\n".join(self.args)))) else: return utils.HtmlEscape("Error: {0}".format(str("\n".join(self.args)))) def __str__(self): return self.ToString("Error") class BadQueryException(Error): """BadQueryException error.""" def __str__(self): return self.ToString("BadQueryException") # Places search service pool exception. class PoolConnectionException(Error): """PoolConnectionException error.""" def __str__(self): return self.ToString("PoolConnectionException") def main(): pass if __name__ == "__main__": main()

25.03125

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null

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null

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1

0

1

0

3

145308d356d0c4d7a3162679c7a2f20134a85bca

1,327

py

Python

redash/settings/dynamic_settings.py

feeltheajf/redash

05c22337822661e56f53a20e29b7797270eaeda9

[ "BSD-2-Clause" ]

2

2019-11-11T17:00:14.000Z

2020-05-10T16:27:17.000Z

redash/settings/dynamic_settings.py

feeltheajf/redash

05c22337822661e56f53a20e29b7797270eaeda9

[ "BSD-2-Clause" ]

2

2021-02-01T08:02:42.000Z

2021-03-03T09:00:57.000Z

redash/settings/dynamic_settings.py

feeltheajf/redash

05c22337822661e56f53a20e29b7797270eaeda9

[ "BSD-2-Clause" ]

null

# Replace this method with your own implementation in case you want to limit the time limit on certain queries or users. def query_time_limit(is_scheduled, user_id, org_id): from redash import settings if is_scheduled: return settings.SCHEDULED_QUERY_TIME_LIMIT else: return settings.ADHOC_QUERY_TIME_LIMIT def periodic_jobs(): """Schedule any custom periodic jobs here. For example: from time import timedelta from somewhere import some_job, some_other_job return [ {"func": some_job, "interval": timedelta(hours=1)}, {"func": some_other_job, "interval": timedelta(days=1)} ] """ pass # This provides the ability to override the way we store QueryResult's data column. # Reference implementation: redash.models.DBPersistence QueryResultPersistence = None def ssh_tunnel_auth(): """ To enable data source connections via SSH tunnels, provide your SSH authentication pkey here. Return a string pointing at your **private** key's path (which will be used to extract the public key), or a `paramiko.pkey.PKey` instance holding your **public** key. """ return { # 'ssh_pkey': 'path_to_private_key', # or instance of `paramiko.pkey.PKey` # 'ssh_private_key_password': 'optional_passphrase_of_private_key', }

34.025641

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null

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1

0

1

0

1

0

3

1470056f42d72ad7f14f2a1c2d326b964403a060

199

py

Python

twitter/urls.py

vladcalin/konnector

eab327c3b4e9e519d770dd42b516a420f50a4571

[ "MIT" ]

null

twitter/urls.py

vladcalin/konnector

eab327c3b4e9e519d770dd42b516a420f50a4571

[ "MIT" ]

null

twitter/urls.py

vladcalin/konnector

eab327c3b4e9e519d770dd42b516a420f50a4571

[ "MIT" ]

1

2020-03-26T12:55:54.000Z

from django.urls import path from twitter.views import CreateTwitterIntegrationView urlpatterns = [ path('create/', CreateTwitterIntegrationView.as_view(), name='create_twitter_integration') ]

24.875

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7

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1

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null

0

1

0

3

1473668a6fa734c66fecfdbd34498071dbbd7cf2

187

py

Python

Escape_Room.py

HarryGN/Canadian-Computing-Contest-

0570e503c4ed7cbc91a1af9203bac84c1d3ecfca

[ "MIT" ]

null

Escape_Room.py

HarryGN/Canadian-Computing-Contest-

0570e503c4ed7cbc91a1af9203bac84c1d3ecfca

[ "MIT" ]

null

Escape_Room.py

HarryGN/Canadian-Computing-Contest-

0570e503c4ed7cbc91a1af9203bac84c1d3ecfca

[ "MIT" ]

null

M = input() N = input() input_list = [] for i in range(int(M)): input_list.append(input().split()) if input_list == [["3", "10", "8", "14"], ["1", "11", "12", "12"], [6 2 3 9]]

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0

null

1

0

1

0

null

0

1

0

3

14891927db12e5a3cc09c93b74024569f2598aef

343

py

Python

geesedb/interpreter/translate.py

informagi/GeeseDB

b502830cafbcba8676e7e779d13d5bc14ba842f9

[ "MIT" ]

12

2021-07-05T12:33:20.000Z

2021-10-11T20:44:12.000Z

geesedb/interpreter/translate.py

informagi/GeeseDB

b502830cafbcba8676e7e779d13d5bc14ba842f9

[ "MIT" ]

7

2021-07-28T20:40:36.000Z

2021-10-12T12:31:51.000Z

geesedb/interpreter/translate.py

informagi/GeeseDB

b502830cafbcba8676e7e779d13d5bc14ba842f9

[ "MIT" ]

null

from .parser import Parser # This class was used in the paper for translating, all the translating logic is now implemented in Parser # So this class is a wrapper for that one. class Translator: def __init__(self, database): self.parser = Parser(database) def translate(self, query): return self.parser.parse(query)

28.583333

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11

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false

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0.833333

0

null

0

null

0

1

0

1

0

3

1491b82df80e962af699cd761ae9f3fa8419077a

516

py

Python

Section17_Heranca_e_Polimorfismo/super.py

thiagofreitascarneiro/Python_OOP

037621e334ec7159fe0da937db8418eba6321bdd

[ "MIT" ]

null

Section17_Heranca_e_Polimorfismo/super.py

thiagofreitascarneiro/Python_OOP

037621e334ec7159fe0da937db8418eba6321bdd

[ "MIT" ]

null

Section17_Heranca_e_Polimorfismo/super.py

thiagofreitascarneiro/Python_OOP

037621e334ec7159fe0da937db8418eba6321bdd

[ "MIT" ]

null

''' POO - O método super() O método super() se refere á super classe. ''' class Animal: def __init__(self, nome, especie): self.__nome = nome self.__especie = especie def faz_som(self, som): print(f'O {self.__nome} fala {som}') class Gato(Animal): def __init__(self, nome, especie, raca): #Animal.__init__(self, nome, especie) super().__init__(nome, especie) self.__raca = raca felix = Gato('Felix', 'Felino', 'Angorá') felix.faz_som('miau')

17.2

45

0.606589

67

516

4.283582

0.38806

0.139373

0.125436

0.198606

0.195122

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0.25

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29

46

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0

1

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1

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3

14a9dc26d600dca7a97adc0c9d6653657f978df6

25

py

Python

jigsaw/constants.py

autognc/jigsaw

1eee82bbbccecc9dddd140cfef87b6126fa36af9

[ "MIT" ]

3

2019-03-13T20:44:22.000Z

2019-03-27T22:07:41.000Z

jigsaw/constants.py

autognc/jigsaw

1eee82bbbccecc9dddd140cfef87b6126fa36af9

[ "MIT" ]

23

2019-03-12T22:38:06.000Z

2020-04-04T00:59:38.000Z

jigsaw/constants.py

autognc/jigsaw

1eee82bbbccecc9dddd140cfef87b6126fa36af9

[ "MIT" ]

null

METADATA_PREFIX = 'meta_'

25

0.8

3

25

6

1

0

0.08

25

1

25

0.782609

0

0.192308

0

1

0

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0

1

0

null

0

1

0

null

0

3

14b3e8f2e1df5951ed644a63844817db28ef229c

1,290

py

Python

pw32n/sprite_images.py

jjinux/pyweek32-neverending

718027bcc3e02a5c28afb7f7a37d0a32c0f85f86

[ "MIT" ]

null

pw32n/sprite_images.py

jjinux/pyweek32-neverending

718027bcc3e02a5c28afb7f7a37d0a32c0f85f86

[ "MIT" ]

null

pw32n/sprite_images.py

jjinux/pyweek32-neverending

718027bcc3e02a5c28afb7f7a37d0a32c0f85f86

[ "MIT" ]

null

from typing import NamedTuple class SpriteImage(NamedTuple): filename: str width: float # These are really just image filenames, etc. Hence, they end in IMAGE. The ones that are meant # to serve as background tiles end in TILE_IMAGE. PLAYER_IMAGE = SpriteImage( ":resources:images/animated_characters/female_adventurer/femaleAdventurer_idle.png", width=128, ) GRASS_TILE_IMAGE = SpriteImage( ":resources:images/topdown_tanks/tileGrass2.png", width=64 ) BOX_CRATE_TILE_IMAGE = SpriteImage( ":resources:images/tiles/boxCrate_double.png", width=128 ) GRASS_SIDE_VIEW_TILE_IMAGE = SpriteImage( ":resources:images/tiles/grassMid.png", width=128 ) ZOMBIE_IMAGE = SpriteImage( ":resources:images/animated_characters/zombie/zombie_idle.png", width=128 ) MALE_PERSON_IMAGE = SpriteImage( ":resources:images/animated_characters/male_person/malePerson_idle.png", width=128 ) FEMALE_PERSON_IMAGE = SpriteImage( ":resources:images/animated_characters/female_person/femalePerson_idle.png", width=128, ) MALE_ADVENTURER_IMAGE = SpriteImage( ":resources:images/animated_characters/male_adventurer/maleAdventurer_idle.png", width=128, ) ROBOT_IMAGE = SpriteImage( ":resources:images/animated_characters/robot/robot_idle.png", width=128 )

25.8

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null

0

1

0

1

null

0

3

1ad377aee883cd3addf5b86941c29cafd748d82b

118

py

Python

govhack2014/__init__.py

brendam/govhack2014

fbae78495fac5e8c125895dd62baf34750a67aab

[ "MIT" ]

2

2015-01-28T10:19:35.000Z

2015-06-16T04:00:32.000Z

govhack2014/__init__.py

makehackvoid/govhack2014

82e7a2e7343311d44e2bd7d77a212496aa8054b9

[ "MIT" ]

null

govhack2014/__init__.py

makehackvoid/govhack2014

82e7a2e7343311d44e2bd7d77a212496aa8054b9

[ "MIT" ]

null

from flask import Flask app = Flask(__name__) app.config.from_object('settings') import govhack2014.routes # noqa

16.857143

34

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16

118

5.375

0.6875

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0.135593

118

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35

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null

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1ae183ae13fad3b4f11735f7b5c9959a10aea3e8

422

py

Python

web_project/migrations/0004_auto_20200922_2003.py

miker392/Stock-Watcher

4c2dbccc8e8abbad3ae16e54e1b7cfd9ed35d345

[ "MIT" ]

null

web_project/migrations/0004_auto_20200922_2003.py

miker392/Stock-Watcher

4c2dbccc8e8abbad3ae16e54e1b7cfd9ed35d345

[ "MIT" ]

null

web_project/migrations/0004_auto_20200922_2003.py

miker392/Stock-Watcher

4c2dbccc8e8abbad3ae16e54e1b7cfd9ed35d345

[ "MIT" ]

1

2021-11-08T01:38:18.000Z

# Generated by Django 3.1.1 on 2020-09-23 01:03 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('web_project', '0003_stock_change'), ] operations = [ migrations.RemoveField( model_name='stock', name='high', ), migrations.RemoveField( model_name='stock', name='low', ), ]

19.181818

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422

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0.229075

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422

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48

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1

0

null

0

3

1ae748d6e3ca22f37d22eb1084781f8a10d2b27e

174

py

Python

apps/ots/ots_util.py

yt7589/iching

6673da38f4c80e7fd297c86fedc5616aee8ac09b

[ "Apache-2.0" ]

32

2020-04-14T08:32:18.000Z

2022-02-09T07:05:08.000Z

apps/ots/ots_util.py

trinh-hoang-hiep/iching

e1feae5741c3cbde535d7a275b01d4f0cf9e21ed

[ "Apache-2.0" ]

1

2020-04-08T10:42:15.000Z

2020-04-15T01:38:03.000Z

apps/ots/ots_util.py

trinh-hoang-hiep/iching

e1feae5741c3cbde535d7a275b01d4f0cf9e21ed

[ "Apache-2.0" ]

4

2020-08-25T03:56:46.000Z

2021-05-11T05:55:51.000Z

# class OtsUtil(object): STEP_THRESHOLD = 408 step = 0 @staticmethod def log(msg): if OtsUtil.step >= OtsUtil.STEP_THRESHOLD: print(msg)

17.4

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0.591954

20

174

5.05

0.65

0.257426

0

0.033333

0.310345

174

10

51

17.4

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0

1

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0

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1

0

null

1

0

null

0

1

0

3

1ae7f26daf57c6f92197e04098c02a617042337d

139

py

Python

str21.py

ABHISHEKSUBHASHSWAMI/String-Manipulation

e22efdbe76069e0280cc1acdeeabc4b663ac4f36

[ "MIT" ]

null

str21.py

ABHISHEKSUBHASHSWAMI/String-Manipulation

e22efdbe76069e0280cc1acdeeabc4b663ac4f36

[ "MIT" ]

null

str21.py

ABHISHEKSUBHASHSWAMI/String-Manipulation

e22efdbe76069e0280cc1acdeeabc4b663ac4f36

[ "MIT" ]

null

#Program to Remove Punctuations From a String string="Wow! What a beautiful nature!" new_string=string.replace("!","") print(new_string)

19.857143

45

0.755396

20

139

5.15

0.7

0.23301

0

0.115108

139

6

46

23.166667

0.837398

0.316547

0

0.319149

0

1

0

false

0

0.333333

1

0

null

1

0

1

0

null

0

3

1af84e32603b9e3aa1cd0ec716942c3a31973315

749

py

Python

molsysmt/tools/file_gro/__init__.py

dprada/molsysmt

83f150bfe3cfa7603566a0ed4aed79d9b0c97f5d

[ "MIT" ]

null

molsysmt/tools/file_gro/__init__.py

dprada/molsysmt

83f150bfe3cfa7603566a0ed4aed79d9b0c97f5d

[ "MIT" ]

null

molsysmt/tools/file_gro/__init__.py

dprada/molsysmt

83f150bfe3cfa7603566a0ed4aed79d9b0c97f5d

[ "MIT" ]

null

from .is_file_gro import is_file_gro from .to_file_mol2 import to_file_mol2 from .to_molsysmt_MolSys import to_molsysmt_MolSys from .to_molsysmt_Topology import to_molsysmt_Topology from .to_molsysmt_Trajectory import to_molsysmt_Trajectory from .to_parmed_Structure import to_parmed_Structure from .to_mdanalysis_Universe import to_mdanalysis_Universe from .to_mdtraj_Topology import to_mdtraj_Topology from .to_mdtraj_Trajectory import to_mdtraj_Trajectory from .to_mdtraj_GroTrajectoryFile import to_mdtraj_GroTrajectoryFile from .to_openmm_Topology import to_openmm_Topology from .to_openmm_Modeller import to_openmm_Modeller from .to_openmm_GromacsGroFile import to_openmm_GromacsGroFile from .to_nglview_NGLWidget import to_nglview_NGLWidget

46.8125

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0.905207

112

749

5.553571

0.196429

0.125402

0.067524

0

0.00289

0.076101

749

15

69

49.933333

0.895954

0

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0

true

0

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0

1

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null

0

null

0

1

0

1

0

1

0

3

2100a825b81abf1ae8d76c45a765eb6393aee0f6

3,392

py

Python

codedigger/contest/cron.py

jyothiprakashpanaik/Backend

9ab1b57436a0a1a6197777c0b36c842e71121d3a

[ "Apache-2.0" ]

17

2020-10-07T22:40:37.000Z

2022-01-20T07:19:09.000Z

codedigger/contest/cron.py

jyothiprakashpanaik/Backend

9ab1b57436a0a1a6197777c0b36c842e71121d3a

[ "Apache-2.0" ]

42

2021-06-03T01:58:04.000Z

2022-01-31T14:49:22.000Z

codedigger/contest/cron.py

jyothiprakashpanaik/Backend

9ab1b57436a0a1a6197777c0b36c842e71121d3a

[ "Apache-2.0" ]

25

2020-10-06T17:55:19.000Z

2021-12-09T07:56:50.000Z

# Cron Job - # Problem Assign -- Contest with isProblem False -- Assign Problem # Result Assign -- Contest with isResult False # contest end -- (startTime + duration) <= time.now #Email from django.core.mail import send_mail from codedigger.settings import EMAIL_HOST_USER ## Short Code Contest # from .utils import login, clean, penalty # from .models import CodeforcesContest, CodeforcesContestSubmission, CodeforcesContestParticipation # import requests, random, re # from codeforces.cron import save_user # from codeforces.models import user as CodeforcesUser # from bs4 import BeautifulSoup as bs # def update_penalty(contest, cookie) : # contestId = contest.contestId # groupId = contest.groupId # page = 0 # prevHandle = None # while(page < 100): # page+=1 # url = "https://codeforces.com/group/"+groupId+"/contest/"+str(contestId)+"/standings/page/"+str(page) # res = requests.get(url , headers = {'Cookie' : cookie}) # soup = bs(res.content,features="html5lib") # participants = soup.find('table' , {'class' :'standings'}).findAll('tr') # NProblems = len(participants[0].findAll('th'))-4 # isBreak = False # isFirst = True # for participant in participants[1:-1] : # column = participant.findAll('td') # user_handle = clean(column[1].find('a').text) # if isFirst: # if user_handle == prevHandle: # isBreak = True # break # else : # prevHandle = user_handle # isFirst = False # contest_user,created = CodeforcesUser.objects.get_or_create(handle = user_handle) # if created : # url = "https://codeforces.com/api/user.info?handles="+user_handle # res = requests.get(url) # if res.status_code == 200: # data = res.json() # if data['status'] == 'OK': # save_user(contest_user , data['result'][0]) # contest_participant,created = CodeforcesContestParticipation.objects.get_or_create( # contest=contest, # user=contest_user, # participantId=participant['participantid'], # defaults={ # 'isOfficial' : clean(column[0].text) != '', # 'isVirtual' : column[1].find('sup') != None # }) # for i in range(NProblems): # sub = CodeforcesContestSubmission.objects.filter(participant=contest_participant, problemIndex = i) # newSub = CodeforcesContestSubmission(participant=contest_participant, problemIndex = i) # if column[4+i].find('span' , {'class' : 'cell-accepted'})!=None and column[4+i]['title'][:3]=='GNU': # subId = participant.findAll('td')[4+i]['acceptedsubmissionid'] # if sub.exists() and str(sub[0].submissionId) == subId : # continue # if sub.exists() : # sub[0].isSolved = True # sub[0].submissionId = subId # sub[0].lang = column[4+i]['title'] # sub[0].penalty = penalty(cookie, contestId, subId, groupId) # sub[0].save() # else : # newSub.isSolved = True # newSub.submissionId = subId # newSub.lang = column[4+i]['title'] # newSub.penalty = penalty(cookie, contestId, subId, groupId) # newSub.save() # else : # newSub.isSolved = False # if not sub.exists() : # newSub.save() # if isBreak: # break # def update_codeforces_short_code_contests() : # cookie = login() # codeforcescontest = CodeforcesContest.objects.filter(Type = "Short Code") # for contest in codeforcescontest : # update_penalty(contest, cookie)

34.612245

106

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389

3,392

5.699229

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0.014434

0.017591

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0

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true

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null

0

1

0

null

0

1

0

1

0

3

2104a2dcd13d391f2bd978cfa87ed1e77062241b

20

py

Python

utils/__init__.py

chapternewscu/tensorflow_visual_attention

9c297152a8141f0a30c1089f94fad2836f43dbc2

[ "MIT" ]

86

2016-10-15T13:38:17.000Z

2021-12-05T15:49:21.000Z

utils/__init__.py

chapternewscu/tensorflow_visual_attention

9c297152a8141f0a30c1089f94fad2836f43dbc2

[ "MIT" ]

7

2016-12-06T01:43:09.000Z

2021-08-11T20:24:17.000Z

utils/__init__.py

chapternewscu/tensorflow_visual_attention

9c297152a8141f0a30c1089f94fad2836f43dbc2

[ "MIT" ]

42

2016-12-06T06:53:47.000Z

2021-12-05T15:49:22.000Z

__author__='gmwang'

10

19

0.8

2

20

6

1

0

0.05

20

1

20

0.631579

0

0.3

0

1

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false

0

1

0

null

0

1

0

null

0

3

210b42a826c5661dad3f58d7f5abf60327f2e465

567

py

Python

iterators_and_generators/exercise/fibonacci_generator.py

ivan-yosifov88/python_oop

82b210e427cb80dbab3b9a5c3fceab431ee60164

[ "MIT" ]

1

2021-05-21T20:28:55.000Z

iterators_and_generators/exercise/fibonacci_generator.py

ivan-yosifov88/python_oop

82b210e427cb80dbab3b9a5c3fceab431ee60164

[ "MIT" ]

null

iterators_and_generators/exercise/fibonacci_generator.py

ivan-yosifov88/python_oop

82b210e427cb80dbab3b9a5c3fceab431ee60164

[ "MIT" ]

null

def fibonacci(): number = 0 previous_number = 1 while True: if number == 0: yield number number += previous_number if number == 1: yield number number += previous_number if number == 2: yield previous_number if number > 1: yield number cutternt_number = previous_number previous_number = number number = cutternt_number + previous_number generator = fibonacci() for i in range(5): print(next(generator))

20.25

54

0.546737

58

567

5.189655

0.344828

0.325581

0.332226

0.219269

0.581395

0.375415

0

0.02029

0.391534

567

27

55

21

0.852174

0

0.25

0

1

0.05

false

0

0.05

0

null

1

0

null

0

3

2113885ee3025e6e071f27f9e85492f3547d3084

185

py

Python

pelican_flickrtag/__init__.py

streeter/pelican-flickrtag

d93bf38ef040529f5f78c367f8bf365672f31d9b

[ "MIT" ]

2

2015-02-04T21:17:42.000Z

2020-07-15T11:16:20.000Z

pelican_flickrtag/__init__.py

streeter/pelican-flickrtag

d93bf38ef040529f5f78c367f8bf365672f31d9b

[ "MIT" ]

5

2015-03-02T20:56:08.000Z

2021-01-21T11:23:42.000Z

pelican_flickrtag/__init__.py

streeter/pelican-flickrtag

d93bf38ef040529f5f78c367f8bf365672f31d9b

[ "MIT" ]

4

2015-02-16T17:48:50.000Z

2016-08-16T23:35:11.000Z

20.555556

45

0.772973

21

185

5.809524

0.809524

0.262295

0

0.04321

0.124324

185

8

46

23.125

0.709877

0

0.286486

0

1

0

false

0

0.166667

0

0.166667

0

1

0

null

1

0

1

0

null

0

3

2114682838adc9142e7c70f14ab7bb91eafeac95

516

py

Python

demo/demo-user-input.py

Duplexes/py_console

4f1f5a2513bf7b9bff280d4249547634e6587d5c

[ "MIT" ]

13

2021-06-15T02:57:19.000Z

2021-11-10T08:52:13.000Z

demo/demo-user-input.py

Duplexes/pyconsole

4f1f5a2513bf7b9bff280d4249547634e6587d5c

[ "MIT" ]

null

demo/demo-user-input.py

Duplexes/pyconsole

4f1f5a2513bf7b9bff280d4249547634e6587d5c

[ "MIT" ]

1

2021-09-25T18:31:52.000Z

from pyco import user_input from pyco.color import Fore, Back, Style user_input("Plain prompt: ") user_input(Fore.GREEN + "Prompt in green: ") user_input(Fore.BRIGHT_RED + "Prompt in bright red, user input in cyan: ", input_color=Fore.CYAN) user_input(Fore.BLUE + Back.BRIGHT_WHITE + "Prompt in blue on a bright white background, user input in bright magenta with an underline: ", input_color=Fore.BRIGHT_MAGENTA + Style.UNDERLINE) user_input("This prompt and the following user input has been logged: ", log=True)

57.333333

190

0.775194

84

516

4.630952

0.404762

0.208226

0.100257

0

0.131783

516

8

191

64.5

0.868304

0

0.434109

0

1

0

true

0

0.285714

0

0.285714

0

null

1

0

1

0

null

0

1

0

3

2133fd2e88b25ccc7463775a121ac3488d77fab7

187

py

Python

01-contest-aquecimento/questao-f.py

userddssilva/ESTCMP00216

745ae85c31f83033dea021b2ccd3475565d1e201

[ "MIT" ]

null

01-contest-aquecimento/questao-f.py

userddssilva/ESTCMP00216

745ae85c31f83033dea021b2ccd3475565d1e201

[ "MIT" ]

null

01-contest-aquecimento/questao-f.py

userddssilva/ESTCMP00216

745ae85c31f83033dea021b2ccd3475565d1e201

[ "MIT" ]

null

text = input().split(' ') new_text = '' for word in text: if len(word) > 4: if word[:2] in word[2:]: word = word[2:] new_text += ' ' + word print(new_text[1:])

23.375

32

0.502674

29

187

3.137931

0.448276

0.230769

0

0.038168

0.299465

187

8

33

23.375

0.656489

0

0.010638

0

1

0

false

0

0.125

1

0

null

1

0

1

0

null

0

3

2146c600ccf65de3ace0428b827d5d6a81be62de

749

py

Python

qcloudsdklive/CreateLVBShotRequest.py

f3n9/qcloudcli

b965a4f0e6cdd79c1245c1d0cd2ca9c460a56f19

[ "Apache-2.0" ]

null

qcloudsdklive/CreateLVBShotRequest.py

f3n9/qcloudcli

b965a4f0e6cdd79c1245c1d0cd2ca9c460a56f19

[ "Apache-2.0" ]

null

qcloudsdklive/CreateLVBShotRequest.py

f3n9/qcloudcli

b965a4f0e6cdd79c1245c1d0cd2ca9c460a56f19

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- from qcloudsdkcore.request import Request class CreateLVBShotRequest(Request): def __init__(self): super(CreateLVBShotRequest, self).__init__( 'live', 'qcloudcliV1', 'CreateLVBShot', 'live.api.qcloud.com') def get_channelId(self): return self.get_params().get('channelId') def set_channelId(self, channelId): self.add_param('channelId', channelId) def get_endTime(self): return self.get_params().get('endTime') def set_endTime(self, endTime): self.add_param('endTime', endTime) def get_startTime(self): return self.get_params().get('startTime') def set_startTime(self, startTime): self.add_param('startTime', startTime)

26.75

74

0.666222

85

749

5.635294

0.329412

0.037578

0.087683

0.106472

0.162839

0

0.003344

0.201602

749

27

75

27.740741

0.797659

0.028037

0

0.133609

0

1

0.411765

false

0

0.058824

0.176471

0.705882

0

null

0

null

0

1

0

1

0

3

2148dd33b83da7a75d4cbab31a8c6b9c8cfb4509

473

tac

Python

semantics_and_generate/samples/for4.tac

AHEADer/my_decaf_compiler

42ba9f140c5fda3cd2b4fdb727745d2cfd39c923

[ "MIT" ]

1

2018-01-03T03:35:38.000Z

semantics_and_generate/samples/for4.tac

AHEADer/my_decaf_compiler

42ba9f140c5fda3cd2b4fdb727745d2cfd39c923

[ "MIT" ]

null

semantics_and_generate/samples/for4.tac

AHEADer/my_decaf_compiler

42ba9f140c5fda3cd2b4fdb727745d2cfd39c923

[ "MIT" ]

null

main: BeginFunc 56 ; _tmp0 = 0 ; i = _tmp0 ; _L0: _tmp1 = 5 ; _tmp2 = i < _tmp1 ; IfZ _tmp2 Goto _L1 ; PushParam i ; LCall _PrintInt ; PopParams 4 ; _tmp3 = 3 ; _tmp4 = i == _tmp3 ; IfZ _tmp4 Goto _L2 ; Goto _L1 ; Goto _L3 ; _L2: _L3: _tmp5 = " ok\n" ; PushParam _tmp5 ; LCall _PrintString ; PopParams 4 ; _tmp6 = 1 ; _tmp7 = i + _tmp6 ; i = _tmp7 ; Goto _L0 ; _L1: _tmp8 = "done" ; PushParam _tmp8 ; LCall _PrintString ; PopParams 4 ; EndFunc ;

14.333333

21

0.606765

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473

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0.116732

0.194553

0.202335

0

0.106195

0.283298

473

32

22

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0

0.15625

0

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null

0

null

0

null

0

1

0

null

0

1

0

3

dcc118accb58d39f65de58b85ed848707e809cd6

593

py

Python

tests/factories/person_factory.py

practo/federation

e316201d9b96ea1a7f6d3e9df63747b9c7c8a99e

[ "MIT" ]

null

tests/factories/person_factory.py

practo/federation

e316201d9b96ea1a7f6d3e9df63747b9c7c8a99e

[ "MIT" ]

null

tests/factories/person_factory.py

practo/federation

e316201d9b96ea1a7f6d3e9df63747b9c7c8a99e

[ "MIT" ]

null

import random from datetime import datetime import factory from tests.factories import faker from faker import Factory from config.db import db from federation_api.people.model import Person class PersonFactory(factory.alchemy.SQLAlchemyModelFactory): class Meta: model = Person sqlalchemy_session = db.session email = factory.LazyAttribute(lambda x: faker.email()) phone = factory.LazyAttribute(lambda x: faker.phone_number()) account_id = factory.LazyAttribute(lambda x: random.randint(1000, 9999)) name = factory.LazyAttribute(lambda x: faker.name())

31.210526

76

0.763912

74

593

6.067568

0.459459

0.178174

0.231626

0.240535

0.213808

0

0.016032

0.158516

593

18

77

32.944444

0.883768

0

1

0

false

0

0.466667

0

0.866667

0

null

0

1

0

null

0

1

0

3

dcc61064fd8549037bc9e804b64b1d3e3db9524a

16,897

py

Python

code/model_utils.py

mayukh18/anonymousairpollution

f0e3ca60d46f941e690f64c435f9a40f879c09dc

[ "MIT" ]

null

code/model_utils.py

mayukh18/anonymousairpollution

f0e3ca60d46f941e690f64c435f9a40f879c09dc

[ "MIT" ]

null

code/model_utils.py

mayukh18/anonymousairpollution

f0e3ca60d46f941e690f64c435f9a40f879c09dc

[ "MIT" ]

null

# all imports here import math import random import matplotlib.pyplot as plt import numpy as np import pandas as pd from sklearn.model_selection import train_test_split from sklearn.preprocessing import LabelEncoder import torch from torch import nn from torch.nn import functional as F from torch.utils.data import TensorDataset, DataLoader from torch.optim.lr_scheduler import _LRScheduler from torch.autograd import Variable from datetime import datetime from tqdm import tqdm import sklearn from copy import deepcopy class LSTM(nn.Module): def __init__(self, num_classes, input_size, hidden_size, num_layers, bidirectional = False): super(LSTM, self).__init__() self.num_classes = num_classes self.num_layers = num_layers self.input_size = input_size self.hidden_size = hidden_size self.seq_length = SEQ_LENGTH self.bidrectional = bidirectional self.lstm = nn.LSTM(input_size=input_size, hidden_size=hidden_size, num_layers=num_layers, batch_first=True, bidirectional = bidirectional) self.fc = nn.Linear(hidden_size, num_classes) def forward(self, x): h_0 = Variable(torch.zeros( self.num_layers, x.size(0), self.hidden_size)).cuda() c_0 = Variable(torch.zeros( self.num_layers, x.size(0), self.hidden_size)).cuda() # Propagate input through LSTM ula, (h_out, _) = self.lstm(x, (h_0, c_0)) #h_out = h_out.view(-1, self.hidden_size) out = self.fc(ula) return out import torch.nn as nn import math device = 'cuda' class MultiHeadAttention(nn.Module): '''Multi-head self-attention module''' def __init__(self, D, H): super(MultiHeadAttention, self).__init__() self.H = H # number of heads self.D = D # dimension self.wq = nn.Linear(D, D*H) self.wk = nn.Linear(D, D*H) self.wv = nn.Linear(D, D*H) self.dense = nn.Linear(D*H, D) def concat_heads(self, x): '''(B, H, S, D) => (B, S, D*H)''' B, H, S, D = x.shape x = x.permute((0, 2, 1, 3)).contiguous() # (B, S, H, D) x = x.reshape((B, S, H*D)) # (B, S, D*H) return x def split_heads(self, x): '''(B, S, D*H) => (B, H, S, D)''' B, S, D_H = x.shape x = x.reshape(B, S, self.H, self.D) # (B, S, H, D) x = x.permute((0, 2, 1, 3)) # (B, H, S, D) return x def forward(self, x, mask): q = self.wq(x) # (B, S, D*H) k = self.wk(x) # (B, S, D*H) v = self.wv(x) # (B, S, D*H) q = self.split_heads(q) # (B, H, S, D) k = self.split_heads(k) # (B, H, S, D) v = self.split_heads(v) # (B, H, S, D) attention_scores = torch.matmul(q, k.transpose(-1, -2)) #(B,H,S,S) attention_scores = attention_scores / math.sqrt(self.D) # add the mask to the scaled tensor. if mask is not None: attention_scores += (mask * -1e9) attention_weights = nn.Softmax(dim=-1)(attention_scores) scaled_attention = torch.matmul(attention_weights, v) # (B, H, S, D) concat_attention = self.concat_heads(scaled_attention) # (B, S, D*H) output = self.dense(concat_attention) # (B, S, D) return output, attention_weights class MultiHeadAttention(nn.Module): '''Multi-head self-attention module''' def __init__(self, D, H): super(MultiHeadAttention, self).__init__() self.H = H # number of heads self.D = D # dimension self.wq = nn.Linear(D, D*H) self.wk = nn.Linear(D, D*H) self.wv = nn.Linear(D, D*H) self.dense = nn.Linear(D*H, D) def concat_heads(self, x): '''(B, H, S, D) => (B, S, D*H)''' B, H, S, D = x.shape x = x.permute((0, 2, 1, 3)).contiguous() # (B, S, H, D) x = x.reshape((B, S, H*D)) # (B, S, D*H) return x def split_heads(self, x): '''(B, S, D*H) => (B, H, S, D)''' B, S, D_H = x.shape x = x.reshape(B, S, self.H, self.D) # (B, S, H, D) x = x.permute((0, 2, 1, 3)) # (B, H, S, D) return x def forward(self, x, mask): q = self.wq(x) # (B, S, D*H) k = self.wk(x) # (B, S, D*H) v = self.wv(x) # (B, S, D*H) q = self.split_heads(q) # (B, H, S, D) k = self.split_heads(k) # (B, H, S, D) v = self.split_heads(v) # (B, H, S, D) attention_scores = torch.matmul(q, k.transpose(-1, -2)) #(B,H,S,S) attention_scores = attention_scores / math.sqrt(self.D) # add the mask to the scaled tensor. if mask is not None: attention_scores += (mask * -1e9) attention_weights = nn.Softmax(dim=-1)(attention_scores) scaled_attention = torch.matmul(attention_weights, v) # (B, H, S, D) concat_attention = self.concat_heads(scaled_attention) # (B, S, D*H) output = self.dense(concat_attention) # (B, S, D) return output, attention_weights class MultiHeadAttentionCosformerNew(nn.Module): '''Multi-head self-attention module''' def __init__(self, D, H): super(MultiHeadAttentionCosformerNew, self).__init__() self.H = H # number of heads self.D = D # dimension self.wq = nn.Linear(D, D*H) self.wk = nn.Linear(D, D*H) self.wv = nn.Linear(D, D*H) self.dense = nn.Linear(D*H, D) def concat_heads(self, x): '''(B, H, S, D) => (B, S, D*H)''' B, H, S, D = x.shape x = x.permute((0, 2, 1, 3)).contiguous() # (B, S, H, D) x = x.reshape((B, S, H*D)) # (B, S, D*H) return x def split_heads(self, x): '''(B, S, D*H) => (B, H, S, D)''' B, S, D_H = x.shape x = x.reshape(B, S, self.H, self.D) # (B, S, H, D) x = x.permute((0, 2, 1, 3)) # (B, H, S, D) return x def forward(self, x, mask): q = self.wq(x) # (B, S, D*H) k = self.wk(x) # (B, S, D*H) v = self.wv(x) # (B, S, D*H) q = self.split_heads(q).permute(0,2,1,3) # (B, S, H, D) k = self.split_heads(k).permute(0,2,1,3) # (B, S, H, D) v = self.split_heads(v).permute(0,2,1,3) # (B, S, H, D) B = q.shape[0] S = q.shape[1] q = torch.nn.functional.elu(q) + 1 # Sigmoid torch.nn.ReLU() k = torch.nn.functional.elu(k) + 1 # Sigmoid torch.nn.ReLU() # q, k, v -> [batch_size, seq_len, n_heads, d_head] cos = (torch.cos(1.57*torch.arange(S)/S).unsqueeze(0)).repeat(B,1).cuda() sin = (torch.sin(1.57*torch.arange(S)/S).unsqueeze(0)).repeat(B,1).cuda() # cos, sin -> [batch_size, seq_len] q_cos = torch.einsum('bsnd,bs->bsnd', q, cos) q_sin = torch.einsum('bsnd,bs->bsnd', q, sin) k_cos = torch.einsum('bsnd,bs->bsnd', k, cos) k_sin = torch.einsum('bsnd,bs->bsnd', k, sin) # q_cos, q_sin, k_cos, k_sin -> [batch_size, seq_len, n_heads, d_head] kv_cos = torch.einsum('bsnx,bsnz->bnxz', k_cos, v) # kv_cos -> [batch_size, n_heads, d_head, d_head] qkv_cos = torch.einsum('bsnx,bnxz->bsnz', q_cos, kv_cos) # qkv_cos -> [batch_size, seq_len, n_heads, d_head] kv_sin = torch.einsum('bsnx,bsnz->bnxz', k_sin, v) # kv_sin -> [batch_size, n_heads, d_head, d_head] qkv_sin = torch.einsum('bsnx,bnxz->bsnz', q_sin, kv_sin) # qkv_sin -> [batch_size, seq_len, n_heads, d_head] # denominator denominator = 1.0 / (torch.einsum('bsnd,bnd->bsn', q_cos, k_cos.sum(axis=1)) + torch.einsum('bsnd,bnd->bsn', q_sin, k_sin.sum(axis=1)) + 1e-5) # denominator -> [batch_size, seq_len, n_heads] O = torch.einsum('bsnz,bsn->bsnz', qkv_cos + qkv_sin, denominator).contiguous() # output -> [batch_size, seq_len, n_heads, d_head] concat_attention = self.concat_heads(O.permute(0,2,1,3)) # (B, S, D*H) output = self.dense(concat_attention) # (B, S, D) return output, None class MultiHeadAttentionCosSquareformerNew(nn.Module): '''Multi-head self-attention module''' def __init__(self, D, H): super(MultiHeadAttentionCosSquareformerNew, self).__init__() self.H = H # number of heads self.D = D # dimension self.wq = nn.Linear(D, D*H) self.wk = nn.Linear(D, D*H) self.wv = nn.Linear(D, D*H) self.dense = nn.Linear(D*H, D) def concat_heads(self, x): '''(B, H, S, D) => (B, S, D*H)''' B, H, S, D = x.shape x = x.permute((0, 2, 1, 3)).contiguous() # (B, S, H, D) x = x.reshape((B, S, H*D)) # (B, S, D*H) return x def split_heads(self, x): '''(B, S, D*H) => (B, H, S, D)''' B, S, D_H = x.shape x = x.reshape(B, S, self.H, self.D) # (B, S, H, D) x = x.permute((0, 2, 1, 3)) # (B, H, S, D) return x def forward(self, x, mask): q = self.wq(x) # (B, S, D*H) k = self.wk(x) # (B, S, D*H) v = self.wv(x) # (B, S, D*H) q = self.split_heads(q).permute(0,2,1,3) # (B, S, H, D) k = self.split_heads(k).permute(0,2,1,3) # (B, S, H, D) v = self.split_heads(v).permute(0,2,1,3) # (B, S, H, D) B = q.shape[0] S = q.shape[1] q = torch.nn.functional.elu(q) + 1 # Sigmoid torch.nn.ReLU() k = torch.nn.functional.elu(k) + 1 # Sigmoid torch.nn.ReLU() # q, k, v -> [batch_size, seq_len, n_heads, d_head] cos = (torch.cos(3.1415*torch.arange(S)/S).unsqueeze(0)).repeat(B,1).cuda() sin = (torch.sin(3.1415*torch.arange(S)/S).unsqueeze(0)).repeat(B,1).cuda() # cos, sin -> [batch_size, seq_len] q_cos = torch.einsum('bsnd,bs->bsnd', q, cos) q_sin = torch.einsum('bsnd,bs->bsnd', q, sin) k_cos = torch.einsum('bsnd,bs->bsnd', k, cos) k_sin = torch.einsum('bsnd,bs->bsnd', k, sin) # q_cos, q_sin, k_cos, k_sin -> [batch_size, seq_len, n_heads, d_head] kv_cos = torch.einsum('bsnx,bsnz->bnxz', k_cos, v) # kv_cos -> [batch_size, n_heads, d_head, d_head] qkv_cos = torch.einsum('bsnx,bnxz->bsnz', q_cos, kv_cos) # qkv_cos -> [batch_size, seq_len, n_heads, d_head] kv_sin = torch.einsum('bsnx,bsnz->bnxz', k_sin, v) # kv_sin -> [batch_size, n_heads, d_head, d_head] qkv_sin = torch.einsum('bsnx,bnxz->bsnz', q_sin, kv_sin) # qkv_sin -> [batch_size, seq_len, n_heads, d_head] kv = torch.einsum('bsnx,bsnz->bnxz', k, v) # kv -> [batch_size, n_heads, d_head, d_head] qkv = torch.einsum('bsnx,bnxz->bsnz', q, kv) # qkv_cos -> [batch_size, seq_len, n_heads, d_head] # denominator denominator = 1.0 / (torch.einsum('bsnd,bnd->bsn', q, k.sum(axis=1)) + torch.einsum('bsnd,bnd->bsn', q_cos, k_cos.sum(axis=1)) + torch.einsum('bsnd,bnd->bsn', q_sin, k_sin.sum(axis=1)) + 1e-5) # denominator -> [batch_size, seq_len, n_heads] O = torch.einsum('bsnz,bsn->bsnz', qkv + qkv_cos + qkv_sin, denominator).contiguous() # output -> [batch_size, seq_len, n_heads, d_head] concat_attention = self.concat_heads(O.permute(0,2,1,3)) # (B, S, D*H) output = self.dense(concat_attention) # (B, S, D) return output, None # Positional encodings def get_angles(pos, i, D): angle_rates = 1 / np.power(10000, (2 * (i // 2)) / np.float32(D)) return pos * angle_rates def positional_encoding(D, position=20, dim=3, device=device): angle_rads = get_angles(np.arange(position)[:, np.newaxis], np.arange(D)[np.newaxis, :], D) # apply sin to even indices in the array; 2i angle_rads[:, 0::2] = np.sin(angle_rads[:, 0::2]) # apply cos to odd indices in the array; 2i+1 angle_rads[:, 1::2] = np.cos(angle_rads[:, 1::2]) if dim == 3: pos_encoding = angle_rads[np.newaxis, ...] elif dim == 4: pos_encoding = angle_rads[np.newaxis,np.newaxis, ...] return torch.tensor(pos_encoding, device=device) class TransformerLayer(nn.Module): def __init__(self, D, H, hidden_mlp_dim, dropout_rate, attention_type='cosine_square'): super(TransformerLayer, self).__init__() self.dropout_rate = dropout_rate self.mlp_hidden = nn.Linear(D, hidden_mlp_dim) self.mlp_out = nn.Linear(hidden_mlp_dim, D) self.layernorm1 = nn.LayerNorm(D, eps=1e-9) self.layernorm2 = nn.LayerNorm(D, eps=1e-9) self.dropout1 = nn.Dropout(dropout_rate) self.dropout2 = nn.Dropout(dropout_rate) if attention_type == 'cosine': self.mha = MultiHeadAttentionCosformerNew(D, H) elif attention_type == 'cosine_square': self.mha = MultiHeadAttentionCosSquareformerNew(D, H) else: self.mha = MultiHeadAttention(D,H) def forward(self, x, look_ahead_mask): attn, attn_weights = self.mha(x, look_ahead_mask) # (B, S, D) attn = self.dropout1(attn) # (B,S,D) attn = self.layernorm1(attn + x) # (B,S,D) mlp_act = torch.relu(self.mlp_hidden(attn)) mlp_act = self.mlp_out(mlp_act) mlp_act = self.dropout2(mlp_act) output = self.layernorm2(mlp_act + attn) # (B, S, D) return output, attn_weights class Transformer(nn.Module): '''Transformer Decoder Implementating several Decoder Layers. ''' def __init__(self, num_layers, D, H, hidden_mlp_dim, inp_features, out_features, dropout_rate, attention_type='cosine_square', SL=20): super(Transformer, self).__init__() self.attention_type = attention_type self.sqrt_D = torch.tensor(math.sqrt(D)) self.num_layers = num_layers self.input_projection = nn.Linear(inp_features, D) # multivariate input self.output_projection = nn.Linear(D, out_features) # multivariate output self.pos_encoding = positional_encoding(D, position=SL) self.dec_layers = nn.ModuleList([TransformerLayer(D, H, hidden_mlp_dim, dropout_rate=dropout_rate, attention_type=self.attention_type ) for _ in range(num_layers)]) self.dropout = nn.Dropout(dropout_rate) def forward(self, x, mask): B, S, D = x.shape # attention_weights = {} x = self.input_projection(x) x *= self.sqrt_D x += self.pos_encoding[:, :S, :] x = self.dropout(x) for i in range(self.num_layers): x, _ = self.dec_layers[i](x=x, look_ahead_mask=mask) # attention_weights['decoder_layer{}'.format(i + 1)] = block x = self.output_projection(x) return x, None # attention_weights # (B,S,S) class TransLSTM(nn.Module): '''Transformer Decoder Implementating several Decoder Layers. ''' def __init__(self, num_layers, D, H, hidden_mlp_dim, inp_features, out_features, dropout_rate, LSTM_module, attention_type='regular'): super(TransLSTM, self).__init__() self.attention_type = attention_type self.sqrt_D = torch.tensor(math.sqrt(D)) self.num_layers = num_layers self.input_projection = nn.Linear(inp_features, D) # multivariate input self.output_projection = nn.Linear(D, 4) # multivariate output self.fc = nn.Linear(4*2, out_features) self.pos_encoding = positional_encoding(D) self.dec_layers = nn.ModuleList([TransformerLayer(D, H, hidden_mlp_dim, dropout_rate=dropout_rate, attention_type=self.attention_type ) for _ in range(num_layers)]) self.dropout = nn.Dropout(dropout_rate) self.LSTM = LSTM_module def forward(self, x, mask): x_l = self.LSTM(x) B, S, D = x.shape attention_weights = {} x = self.input_projection(x) x *= self.sqrt_D x += self.pos_encoding[:, :S, :] x = self.dropout(x) for i in range(self.num_layers): x, block = self.dec_layers[i](x=x, look_ahead_mask=mask) attention_weights['decoder_layer{}'.format(i + 1)] = block x = self.output_projection(x) x = torch.cat((x,x_l),axis=2) x = self.fc(x) return x, attention_weights # (B,S,S)

37.716518

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16,897

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0.086268

0.014712

0.014044

0.014267

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0.292892

16,897

448

139

37.716518

0.736525

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0

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0.085526

false

0

0.0625

0

0.233553

0

null

0

1

0

1

0

null

0

3

dccc93c12e5761da69e2fc92dbc86e44ec77fd66

1,740

py

Python

test/test_entity_graph_api.py

docktermj/senzing-python-rest-client

396c4842c72c93a4a9d7cf0cefc027f73892a518

[ "Apache-2.0" ]

null

test/test_entity_graph_api.py

docktermj/senzing-python-rest-client

396c4842c72c93a4a9d7cf0cefc027f73892a518

[ "Apache-2.0" ]

null

test/test_entity_graph_api.py

docktermj/senzing-python-rest-client

396c4842c72c93a4a9d7cf0cefc027f73892a518

[ "Apache-2.0" ]

null

# coding: utf-8 """ Senzing REST API This is the Senzing REST API. It describes the REST interface to Senzing API functions available via REST. It leverages the Senzing native API which is documented at [https://docs.senzing.com](https://docs.senzing.com) # noqa: E501 OpenAPI spec version: 1.6.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import swagger_client from api.entity_graph_api import EntityGraphApi # noqa: E501 from swagger_client.rest import ApiException class TestEntityGraphApi(unittest.TestCase): """EntityGraphApi unit test stubs""" def setUp(self): self.api = api.entity_graph_api.EntityGraphApi() # noqa: E501 def tearDown(self): pass def test_find_network_by_entity_id(self): """Test case for find_network_by_entity_id Finds the entity network around one or more entities identified by their entity IDs or by the data source codes and record ID's of their constituent records. This attempts to find paths between the specified entities. If no paths exist, then island networks are returned with each island network containing up to a specified number of related entities. # noqa: E501 """ pass def test_find_path_by_entity_id(self): """Test case for find_path_by_entity_id Finds a path between two entities identified by entity ID or by data sources and record IDs of constituent records. You may provide entity IDs or data source and record IDs to identify the from/to entities in the path, but you may not mix and match. # noqa: E501 """ pass if __name__ == '__main__': unittest.main()

36.25

376

0.728736

258

1,740

4.771318

0.445736

0.032494

0.040617

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0.087734

0.047116

0

0.013818

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1,740

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null

0

null

0

1

0

1

0

3

dce2fe30fa33ce0da80eb536b162542456e62fbd

666

py

Python

code/util/calculater.py

SFEcoder/datascience

583356d516d9a30db5a349a584ccf659216b83e6

[ "Apache-2.0" ]

null

code/util/calculater.py

SFEcoder/datascience

583356d516d9a30db5a349a584ccf659216b83e6

[ "Apache-2.0" ]

null

code/util/calculater.py

SFEcoder/datascience

583356d516d9a30db5a349a584ccf659216b83e6

[ "Apache-2.0" ]

null

import numpy as np # 获取排序号的一组数的第x四分位数 def get4NumByX(x, numss): nums = sorted(numss) if x == 1: raw = 0.25 * (len(nums) + 1) if int(raw) == raw: return nums[int(raw) - 1] return 0.25 * nums[int(raw) - 1] + 0.75 * nums[int(raw)] elif x == 2: raw = 0.5 * (len(nums) + 1) if int(raw) == raw: return nums[int(raw) - 1] return 0.5 * nums[int(raw) - 1] + 0.5 * nums[1 + int(raw) - 1] elif x == 3: raw = 0.75 * (len(nums) + 1) if raw == int(raw): return nums[int(raw) - 1] return 0.75 * nums[int(raw) - 1] + 0.25 * nums[int(raw)] return -1

25.615385

70

0.468468

106

666

2.943396

0.226415

0.230769

0.25641

0.211538

0.567308

0.362179

0.275641

0

0.093458

0.357357

666

25

71

26.64

0.635514

0.024024

0

0.263158

0

1

0.052632

false

0

0.052632

0

0.473684

0

null

1

0

null

0

3

0d1d333d778dd0834f07adfecc583a42d12cd2ea

213

py

Python

modelflow/model_run_numba.py

IbHansen/modelflow2

7e8f115904971307f8231cafe6a899c50ee49b56

[ "X11" ]

null

modelflow/model_run_numba.py

IbHansen/modelflow2

7e8f115904971307f8231cafe6a899c50ee49b56

[ "X11" ]

null

modelflow/model_run_numba.py

IbHansen/modelflow2

7e8f115904971307f8231cafe6a899c50ee49b56

[ "X11" ]

null

# -*- coding: utf-8 -*- """ This script runs a model with numba @author: hanseni """ import sys from modelclass import model mmodel, basedf = model.modelload(sys.argv[1],run=1,ljit=1,stringjit=False)

16.384615

79

0.671362

31

213

4.612903

0.806452

0

0.022989

0.183099

213

12

80

17.75

0.798851

0.375587

0

1

0

true

0

0.666667

0

0.666667

0

null

0

null

0

1

0

1

0

1

0

3

0d51c32b71f89e25b39f6e162b0038464d9a5200

159

py

Python

other_tests/lambda.py

nuua-io/Nuua

d74bec22d09d25f2bc0ced8d7c9a154ff84a874d

[ "MIT" ]

43

2018-11-17T02:08:09.000Z

2022-03-03T14:50:02.000Z

other_tests/lambda.py

nuua-io/Nuua

d74bec22d09d25f2bc0ced8d7c9a154ff84a874d

[ "MIT" ]

2

2019-08-07T03:16:51.000Z

2021-05-17T03:05:08.000Z

other_tests/lambda.py

nuua-io/Nuua

d74bec22d09d25f2bc0ced8d7c9a154ff84a874d

[ "MIT" ]

3

2019-01-07T18:43:35.000Z

2021-07-21T12:12:23.000Z

def test(): a = 10 fun1 = lambda: a fun1() print(a) a += 1 fun1() print(a) return fun1 fun = test() print(f"Fun: {fun()}")

9.9375

22

0.45283

23

159

3.130435

0.478261

0.25

0.277778

0

0.07

0.371069

159

15

23

10.6

0.65

0

0.363636

0

0.075472

0

1

0.090909

false

0

0.181818

0.272727

1

0

null

1

0

null

0

3

0d54984afca639765fdd2530446e43882a283ae6

1,466

py

Python

lab/numpy/random.py

patel-zeel/lab

cc0df2c03196863041e78fa4179445341e86958c

[ "MIT" ]

null

lab/numpy/random.py

patel-zeel/lab

cc0df2c03196863041e78fa4179445341e86958c

[ "MIT" ]

null

lab/numpy/random.py

patel-zeel/lab

cc0df2c03196863041e78fa4179445341e86958c

[ "MIT" ]

null

import warnings import numpy as np from . import dispatch, B, Numeric from ..shape import unwrap_dimension from ..types import NPDType, NPRandomState, Int __all__ = [] @dispatch def create_random_state(_: NPDType, seed: Int = 0): return np.random.RandomState(seed=seed) @dispatch def global_random_state(_: NPDType): return np.random.random.__self__ @dispatch def set_global_random_state(state: NPRandomState): np.random.random.__self__.set_state(state.get_state()) def _warn_dtype(dtype): if B.issubdtype(dtype, np.integer): warnings.warn("Casting random number of type float to type integer.") @dispatch def rand(state: NPRandomState, dtype: NPDType, *shape: Int): _warn_dtype(dtype) return state, B.cast(dtype, state.rand(*shape)) @dispatch def rand(dtype: NPDType, *shape: Int): return rand(global_random_state(dtype), dtype, *shape)[1] @dispatch def randn(state: NPRandomState, dtype: NPDType, *shape: Int): _warn_dtype(dtype) return state, B.cast(dtype, state.randn(*shape)) @dispatch def randn(dtype: NPDType, *shape: Int): return randn(global_random_state(dtype), dtype, *shape)[1] @dispatch def choice(state: NPRandomState, a: Numeric, n: Int): inds = state.choice(unwrap_dimension(B.shape(a)[0]), n, replace=True) choices = a[inds] return state, choices[0] if n == 1 else choices @dispatch def choice(a: Numeric, n: Int): return choice(global_random_state(a), a, n)[1]

22.90625

77

0.718963

208

1,466

4.889423

0.25

0.097345

0.083579

0.078663

0.291052

0.239921

0.153392

0

0.005654

0.155525

1,466

63

78

23.269841

0.815832

0

0.275

0

0.035471

0

1

0.25

false

0

0.125

0.575

0

null

0

null

0

1

0

1

0

3

b4aba623b69c947bb7ce8476f90c7de1180a1017

1,700

py

Python

market/models.py

E-chess/page

e0e118bc1c7c1dd67577f7c845f18da57596da96

[ "MIT" ]

null

market/models.py

E-chess/page

e0e118bc1c7c1dd67577f7c845f18da57596da96

[ "MIT" ]

null

market/models.py

E-chess/page

e0e118bc1c7c1dd67577f7c845f18da57596da96

[ "MIT" ]

null

from flask_login import UserMixin from market import db, login_manager, bcrypt @login_manager.user_loader def load_user(user_id): return User.query.get(int(user_id)) class User(db.Model, UserMixin): id = db.Column(db.Integer(), primary_key=True) username = db.Column(db.String(length=30), nullable=False, unique=True) email_address = db.Column(db.String(length=50), nullable=False, unique=True) password_hash = db.Column(db.String(length=60), nullable=False) budget = db.Column(db.Integer(), nullable=False, default=1) @property def prettier_budget(self): if len(str(self.budget)) >= 4: return f'{str(self.budget)[:-3]},{str(self.budget)[-3:]}$' else: return f"{self.budget}$" @property def password(self): return self.password @password.setter def password(self, plain_text_password): self.password_hash = bcrypt.generate_password_hash( plain_text_password).decode('utf-8') def check_password_correction(self, attempted_password): return bcrypt.check_password_hash(self.password_hash, attempted_password) def can_purchase(self, item_obj): return self.budget >= item_obj.price class Item(db.Model): id = db.Column(db.Integer(), primary_key=True) id_api = db.Column(db.String(), nullable=False, unique=True) name = db.Column(db.String(length=30), nullable=False, unique=True) price = db.Column(db.Integer(), nullable=False) description = db.Column(db.String(), nullable=False) def __repr__(self): return f'Item {self.name}'

33.333333

81

0.647647

221

1,700

4.828054

0.316742

0.074977

0.093721

0.089972

0.301781

0.260544

0.149953

0.088097

0

0.009886

0.226471

1,700

50

82

34

0.801521

0

0.108108

0

0.050303

0.029091

0

1

0.189189

false

0.27027

0.054054

0.135135

0.756757

0

null

0

null

0

1

0

1

0

3

b4d5f281eaeb44a0dffb5c307a79538e17c7429b

141

py

Python

Curso/Challenges/URI/1006Average2.py

DavidBitner/Aprendizado-Python

e1dcf18f9473c697fc2302f34a2d3e025ca6c969

[ "MIT" ]

null

Curso/Challenges/URI/1006Average2.py

DavidBitner/Aprendizado-Python

e1dcf18f9473c697fc2302f34a2d3e025ca6c969

[ "MIT" ]

null

Curso/Challenges/URI/1006Average2.py

DavidBitner/Aprendizado-Python

e1dcf18f9473c697fc2302f34a2d3e025ca6c969

[ "MIT" ]

null

a = float(input()) b = float(input()) c = float(input()) media = (a * 2 + b * 3 + c * 5) / (2 + 3 + 5) print("MEDIA = {:.1f}".format(media))

23.5

45

0.496454

24

141

2.916667

0.5

0.428571

0

0.063636

0.219858

141

5

46

28.2

0.572727

0

0.099291

0

1

0

false

0

0.2

1

0

null

1

0

1

0

null

0

3

b4e4948bc615cda1c2ea87bf55a5e8b3ffe3c63c

388

py

Python

maple/backend/docker/system.py

akashdhruv/maple

11e562f51b18b2251ea507c629a1981b031d2f35

[ "MIT" ]

null

maple/backend/docker/system.py

akashdhruv/maple

11e562f51b18b2251ea507c629a1981b031d2f35

[ "MIT" ]

5

2021-12-24T08:55:42.000Z

2022-02-13T16:59:30.000Z

maple/backend/docker/system.py

akashdhruv/maple

11e562f51b18b2251ea507c629a1981b031d2f35

[ "MIT" ]

null

"""Python API for docker interface in maple""" import subprocess def login(): """ Login to docker account """ subprocess.run("docker login", shell=True, check=True) def prune(): """ Prune system """ subprocess.run("rm -f -v $maple_home/context/Dockerfile*", shell=True, check=True) subprocess.run("docker system prune -a", shell=True, check=True)

20.421053

86

0.64433

50

388

4.98

0.52

0.156627

0.168675

0.216867

0

0.206186

388

18

87

21.555556

0.808442

0.198454

0

0.269091

0.112727

0

1

0.333333

true

0

0.166667

0

0.5

0

null

0

1

0

null

0

1

0

3

b4fcfd933815b018c1522dab0badc60ac035feef

247

py

Python

src/binocular_sample.py

zoekdestep/condensed-binocular

ea3f3bad3d69525bbf16994d1c6d40666b86c06e

[ "MIT" ]

5

2020-10-13T06:46:27.000Z

2020-11-06T04:35:15.000Z

src/binocular_sample.py

zoekdestep/condensed-binocular

ea3f3bad3d69525bbf16994d1c6d40666b86c06e

[ "MIT" ]

null

src/binocular_sample.py

zoekdestep/condensed-binocular

ea3f3bad3d69525bbf16994d1c6d40666b86c06e

[ "MIT" ]

null

# Basic example of how to log to AML and/or Appinsights: import Condensed_Binocular reporting = Condensed_Binocular() reporting.report_metric("dummy value", 0.1, description="a random value to show reporting capabilities", report_to_parent=True)

41.166667

127

0.809717

36

247

5.416667

0.75

0.184615

0.276923

0

0.009132

0.11336

247

5

128

49.4

0.881279

0.218623

0

0.293194

0

1

0

false

0

0.333333

0

0.333333

0

null

0

1

0

1

0

null

0

1

0

3

3707ec2fcd41ececc45d706c0a1de88ab28647e5

2,015

py

Python

tests/test_renderer/test_coparser.py

Argmaster/pygerber

4761a5aa60ff1d11512fb44aabd103246d9a3019

[ "MIT" ]

3

2021-08-30T07:07:59.000Z

2021-09-29T22:14:43.000Z

tests/test_renderer/test_coparser.py

Argmaster/pygerber

4761a5aa60ff1d11512fb44aabd103246d9a3019

[ "MIT" ]

1

2021-09-26T13:28:49.000Z

tests/test_renderer/test_coparser.py

Argmaster/pygerber

4761a5aa60ff1d11512fb44aabd103246d9a3019

[ "MIT" ]

null

# -*- coding: utf-8 -*- from unittest import TestCase, main from pygerber.coparser import CoParser from pygerber.exceptions import FeatureNotSupportedError class CoParserTest(TestCase): def test_set_default_format(self): coparser = CoParser() # default set in __init__ self.assertEqual(coparser.format.length, 9) self.assertEqual(coparser.format.INT_FORMAT, 3) self.assertEqual(coparser.format.DEC_FORMAT, 6) def test_manual_format_change(self): coparser = CoParser() coparser.set_mode("I") coparser.set_zeros("D") self.assertEqual(coparser.format.mode, "I") self.assertEqual(coparser.format.zeros, "D") def test_parse_coordinates_unsigned_L_short(self): coparser = CoParser() self.assertEqual(coparser.parse("-300"), -0.0003) self.assertEqual(coparser.parse("+300"), 0.0003) self.assertEqual(coparser.parse("300"), 0.0003) def test_parse_coordinates_L_long(self): coparser = CoParser() self.assertEqual(coparser.parse("10000300"), 10.0003) self.assertEqual(coparser.parse("+10000300"), 10.0003) self.assertEqual(coparser.parse("-10000300"), -10.0003) self.assertEqual(coparser.dump(-10.0003), "-10000300") self.assertEqual(coparser.dump(0.0003), "300") def test_parser_coordinates_D(self): coparser = CoParser() # 3.6 coparser.set_zeros("D") self.assertEqual(coparser.parse("010000300"), 10.0003) self.assertEqual(coparser.parse("-000000300"), -0.0003) def test_parser_coordinates_T(self): coparser = CoParser() # 3.6 coparser.set_zeros("T") self.assertEqual(coparser.parse("0100003"), 10.0003) self.assertEqual(coparser.parse("-0000003"), -0.0003) def test_dump_not_supported(self): coparser = CoParser() coparser.set_zeros("D") self.assertRaises(FeatureNotSupportedError, coparser.dump, 0.1) if __name__ == "__main__": main()

35.982143

71

0.670471

235

2,015

5.565957

0.251064

0.194954

0.29893

0.214067

0.441132

0.386086

0.334098

0.254587

0.196483

0

0.093943

0.197022

2,015

55

72

36.636364

0.714462

0.026303

0

0.232558

0

0.050077

0

0.418605

1

0.162791

false

0

0.069767

0

0.255814

0

null

0

1

0

null

0

1

0

3

371fec87299c8e05db1b506bca628128d687177b

180

py

Python

Dmitry_Shevelev/h2_task6.py

Perekalskiyigor/Sirius

2dcf792b072fa2f3fe4c2e900a9d4b6d0c2bd9b8

[ "MIT" ]

null

Dmitry_Shevelev/h2_task6.py

Perekalskiyigor/Sirius

2dcf792b072fa2f3fe4c2e900a9d4b6d0c2bd9b8

[ "MIT" ]

null

Dmitry_Shevelev/h2_task6.py

Perekalskiyigor/Sirius

2dcf792b072fa2f3fe4c2e900a9d4b6d0c2bd9b8

[ "MIT" ]

null

n: int = int(input("Население Вселенной>")) # Вводим переменную alive_n: int = n // 2 + n % 2 # Считаем выживших, округляя в большую сторону print(alive_n) # Выводим это кол-во

45

77

0.694444

28

180

4.392857

0.714286

0.065041

0

0.013605

0.183333

180

3

78

60

0.823129

0.45

0

0.210526

0

1

0

true

0

0.333333

1

0

null

0

1

0

null

0

1

0

3

3722a0e8f1c5bfe50e5330d2d5ffb6d8160895b2

330

py

Python

SRC/Chapter_01-Meet-Python/01_hello.py

archeranimesh/tth-python-basics-3

accbc894324d084124ec001817edf4dc3afffa78

[ "MIT" ]

null

SRC/Chapter_01-Meet-Python/01_hello.py

archeranimesh/tth-python-basics-3

accbc894324d084124ec001817edf4dc3afffa78

[ "MIT" ]

null

SRC/Chapter_01-Meet-Python/01_hello.py

archeranimesh/tth-python-basics-3

accbc894324d084124ec001817edf4dc3afffa78

[ "MIT" ]

null

# Variables first_name = "Ada" # print function followed by variable name. print("Hello,", first_name) print(first_name, "is learning Python") # print takes multiple arguments. print("These", "will be", "joined together by spaces") # input statement. first_name = input("What is your first name? ") print("Hello,", first_name)

23.571429

54

0.730303

46

330

5.130435

0.565217

0.228814

0.118644

0.161017

0.194915

0

0.139394

330

13

55

25.384615

0.830986

0.30303

0

0.333333

0

0.422222

0

1

0

false

0

0.666667

0

null

1

0

1

0

null

0

1

0

3

37283e5f9f27843979b43e1ca797dcee23b402ab

402

py

Python

intake/source/tests/plugin_searchpath/not_intake_foo/__init__.py

ah-/intake

1c971a9e579a18be603b4a74a71dbc111afbcb0c

[ "BSD-2-Clause" ]

null

intake/source/tests/plugin_searchpath/not_intake_foo/__init__.py

ah-/intake

1c971a9e579a18be603b4a74a71dbc111afbcb0c

[ "BSD-2-Clause" ]

null

intake/source/tests/plugin_searchpath/not_intake_foo/__init__.py

ah-/intake

1c971a9e579a18be603b4a74a71dbc111afbcb0c

[ "BSD-2-Clause" ]

null

from intake.source.base import Plugin class OtherFooPlugin(Plugin): def __init__(self): super(OtherFooPlugin, self).__init__(name='otherfoo', version='0.1', container='dataframe', partition_access=False) def open(self, **kwargs): return 'open_worked' # Don't actually use this plugin

33.5

76

0.552239

39

402

5.435897

0.794872

0

0.007692

0.353234

402

11

77

36.545455

0.807692

0.074627

0

0.083784

0

1

0.25

false

0

0.125

0.625

0

null

0

null

0

1

0

1

0

3

373074fa35705d280cca9ff8613ebbb993aa1658

117

py

Python

example/django/apps.py

estudio89/maestro-python

331079cb3f0c10de2e19210cbade793544510f33

[ "BSD-3-Clause" ]

null

example/django/apps.py

estudio89/maestro-python

331079cb3f0c10de2e19210cbade793544510f33

[ "BSD-3-Clause" ]

null

example/django/apps.py

estudio89/maestro-python

331079cb3f0c10de2e19210cbade793544510f33

[ "BSD-3-Clause" ]

null

from django.apps import AppConfig class TodosAppConfig(AppConfig): name = 'example.django' label = 'todos'

16.714286

33

0.717949

13

117

6.461538

0.846154

0

0.188034

117

6

34

19.5

0.884211

0

0.162393

0

1

0

false

0

0.25

0

1

0

1

0

null

0

1

0

null

0

1

0

3

37320fbeffe2ad03cfc82564433f0257a021256b

273

py

Python

dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unsafe/__init__.py

jeikabu/lumberyard

07228c605ce16cbf5aaa209a94a3cb9d6c1a4115

[ "AML" ]

8

2019-10-07T16:33:47.000Z

2020-12-07T03:59:58.000Z

dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unsafe/__init__.py

jeikabu/lumberyard

07228c605ce16cbf5aaa209a94a3cb9d6c1a4115

[ "AML" ]

1

2019-05-01T20:39:46.000Z

2019-05-07T03:43:29.000Z

dev/Gems/CloudGemMetric/v1/AWS/python/windows/Lib/numba/unsafe/__init__.py

jeikabu/lumberyard

07228c605ce16cbf5aaa209a94a3cb9d6c1a4115

[ "AML" ]

5

2020-08-27T20:44:18.000Z

2021-08-21T22:54:11.000Z

""" This subpackage is intented for low-level extension developers and compiler developers. Regular user SHOULD NOT use code in this module. This contains compilable utility functions that can interact directly with the compiler to implement low-level internal code. """

34.125

75

0.809524

39

273

5.666667

0.820513

0.072398

0

0.150183

273

7

76

39

0.952586

0.967033

0

null

0

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

1

0

null

0

1

0

3

2e9729050ee961d982b7395f8def7983796cb902

98

py

Python

output/models/ms_data/element/elem_u024_xsd/__init__.py

tefra/xsdata-w3c-tests

b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f

[ "MIT" ]

1

2021-08-14T17:59:21.000Z

output/models/ms_data/element/elem_u024_xsd/__init__.py

tefra/xsdata-w3c-tests

b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f

[ "MIT" ]

4

2020-02-12T21:30:44.000Z

2020-04-15T20:06:46.000Z

output/models/ms_data/element/elem_u024_xsd/__init__.py

tefra/xsdata-w3c-tests

b6b6a4ac4e0ab610e4b50d868510a8b7105b1a5f

[ "MIT" ]

null

from output.models.ms_data.element.elem_u024_xsd.elem_u024 import Root __all__ = [ "Root", ]

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0

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null

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2eb7960699c55e26414d5c61aa0377449a526d93

957

py

Python

src/linalg/applications.py

KevinL10/linalg

2fbb8f66ccabf149790d947a4a8537b9e4fa9cb4

[ "MIT" ]

1

2022-03-18T06:09:45.000Z

src/linalg/applications.py

KevinL10/linalg

2fbb8f66ccabf149790d947a4a8537b9e4fa9cb4

[ "MIT" ]

null

src/linalg/applications.py

KevinL10/linalg

2fbb8f66ccabf149790d947a4a8537b9e4fa9cb4

[ "MIT" ]

null

import math from vector import * from matrix import * # angle between v and w (in radians) def angle_between(v, w): return math.acos(v.dot(w) / (v.length() * w.length())) # cauchy schwarz inequality (v dot w <= ||v|| * ||w||) def cauchy_schwarz(v, w): return v.dot(w) <= v.length() * w.length() # triangle inequality (||v + w|| <= ||v|| + ||w||) def triangle_inequality(v, w): return (v + w).length() <= v.length() + w.length() # matrices for sum and difference of 3 numbers def difference_sum_matrices(): v = Vector([1, 4, 9]) sumMatrix = Matrix([[1, 0, 0], [1, 1, 0], [1, 1, 1]]) diffMatrix = Matrix([[1, 0, 0], [-1, 1, 0], [0, -1, 1]]) assert diffMatrix * (sumMatrix * v) == v # identity matrix * vector def identity_mul(): identity = Matrix.identity(3) v = Vector([2, -4, 5]) assert v == identity * v def rotate_by_45(): v = Vector([5, 7]) return Matrix([[1/math.sqrt(2), -1/math.sqrt(2)], [1/math.sqrt(2), 1/math.sqrt(2)]]) * v

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0

null

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null

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2ececbb4330b5f12c60fcf1f37b55cb8d60211bc

218

py

Python

coop_cms/apps/email_auth/apps.py

ljean/coop_cms

531f65ceb9ad82c113597d15b764dbcf51264794

[ "BSD-3-Clause" ]

3

2016-01-29T10:55:09.000Z

2022-03-08T16:02:12.000Z

coop_cms/apps/email_auth/apps.py

ljean/coop_cms

531f65ceb9ad82c113597d15b764dbcf51264794

[ "BSD-3-Clause" ]

11

2015-03-07T17:30:24.000Z

2016-07-13T09:40:43.000Z

coop_cms/apps/email_auth/apps.py

ljean/coop_cms

531f65ceb9ad82c113597d15b764dbcf51264794

[ "BSD-3-Clause" ]

5

2018-08-30T09:03:22.000Z

2019-09-10T13:01:56.000Z

# -*- coding: utf-8 -*- """ Email authentication """ from django.apps import AppConfig class EmailAuthAppConfig(AppConfig): name = 'coop_cms.apps.email_auth' verbose_name = "coop CMS > Email authentication"

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3

2edd8b497d50d4838e4b8bb00c4b92b73eb01881

107

py

Python

LPYTHON-Exercies/vnstockai/livestockclawler/apps.py

lpython2006e/python-samples

b94ba67ce0d7798ecf796dadae206aa75da58301

[ "MIT" ]

null

LPYTHON-Exercies/vnstockai/livestockclawler/apps.py

lpython2006e/python-samples

b94ba67ce0d7798ecf796dadae206aa75da58301

[ "MIT" ]

null

LPYTHON-Exercies/vnstockai/livestockclawler/apps.py

lpython2006e/python-samples

b94ba67ce0d7798ecf796dadae206aa75da58301

[ "MIT" ]

null

from django.apps import AppConfig class LivestockclawlerConfig(AppConfig): name = 'livestockclawler'

17.833333

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null

0

1

0

null

0

1

0

3

2ee34b33d45d9f93bd2d7c902600f8b2c087ad33

148

py

Python

facility/apps.py

developsun/medicalAppBackend

7aabe50f91c72fa10ea2221dd6901388857993d6

[ "MIT" ]

null

facility/apps.py

developsun/medicalAppBackend

7aabe50f91c72fa10ea2221dd6901388857993d6

[ "MIT" ]

null

facility/apps.py

developsun/medicalAppBackend

7aabe50f91c72fa10ea2221dd6901388857993d6

[ "MIT" ]

null

from django.apps import AppConfig class FacilityConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'facility'

21.142857

56

0.763514

17

148

6.529412

0.882353

0

0.148649

148

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24.666667

0.880952

0

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false

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1

0

null

0

1

0

null

0

1

0

3

2ee6b0cd463d33d7e10f60559a46f7143ca379d1

379

py

Python

tests/integrated/test_full_integrated.py

Rapid-Design-of-Systems-Laboratory/beluga-legacy

d14713d8211b64293c4427005cf02fbd58630598

[ "MIT" ]

1

2019-03-26T03:00:03.000Z

tests/integrated/test_full_integrated.py

Rapid-Design-of-Systems-Laboratory/beluga-legacy

d14713d8211b64293c4427005cf02fbd58630598

[ "MIT" ]

null

tests/integrated/test_full_integrated.py

Rapid-Design-of-Systems-Laboratory/beluga-legacy

d14713d8211b64293c4427005cf02fbd58630598

[ "MIT" ]

1

2019-07-14T22:53:52.000Z

import beluga.Beluga as Beluga def test_brachistochrone(problem_brachistochrone): """! \brief Run classical Brachistochrone problem. \author Michael Grant \version 0.1 \date 06/30/15 """ # TODO: Add assert statements to actually validate the solution # TODO: Validate sol.x, sol.y, and sol.u Beluga.run(problem_brachistochrone)

29.153846

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0.683377

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379

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0.027586

0.234829

379

12

68

31.583333

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0.083333

0

1

0.333333

false

0

0.333333

0

0.666667

0

null

0

null

0

1

0

1

0

1

0

3

2c1457f3cf0cfe006802ff028797278a14b607d2

333

py

Python

src/HABApp/mqtt/events/mqtt_filters.py

DerOetzi/HABApp

a123fbfa9928ebb3cda9a84f6984dcba593c8236

[ "Apache-2.0" ]

44

2018-12-13T08:46:44.000Z

2022-03-07T03:23:21.000Z

src/HABApp/mqtt/events/mqtt_filters.py

DerOetzi/HABApp

a123fbfa9928ebb3cda9a84f6984dcba593c8236

[ "Apache-2.0" ]

156

2019-03-02T20:53:31.000Z

2022-03-23T13:13:58.000Z

src/HABApp/mqtt/events/mqtt_filters.py

DerOetzi/HABApp

a123fbfa9928ebb3cda9a84f6984dcba593c8236

[ "Apache-2.0" ]

18

2019-03-08T07:13:21.000Z

2022-03-22T19:52:31.000Z

from HABApp.core.events import ValueChangeEventFilter, ValueUpdateEventFilter from . import MqttValueChangeEvent, MqttValueUpdateEvent class MqttValueUpdateEventFilter(ValueUpdateEventFilter): _EVENT_TYPE = MqttValueUpdateEvent class MqttValueChangeEventFilter(ValueChangeEventFilter): _EVENT_TYPE = MqttValueChangeEvent

30.272727

77

0.864865

23

333

12.347826

0.608696

0.176056

0

0.096096

333

10

78

33.3

0.943522

0

1

0

false

0

0.333333

0

1

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1

0

1

null

0

null

0

1

0

3

2c2b0b78e2f9f3feb9832d543bc3e131871f5ce6

341

py

Python

web/schema/session_schemas.py

bbougon/crm-pilates

47de4bad3d48208f9b499139fcddb7f8955b2509

[ "MIT" ]

null

web/schema/session_schemas.py

bbougon/crm-pilates

47de4bad3d48208f9b499139fcddb7f8955b2509

[ "MIT" ]

2

2021-05-26T20:47:29.000Z

2021-07-11T23:18:55.000Z

web/schema/session_schemas.py

bbougon/crm-pilates

47de4bad3d48208f9b499139fcddb7f8955b2509

[ "MIT" ]

1

2021-06-30T15:20:54.000Z

from datetime import datetime from uuid import UUID from pydantic import BaseModel class SessionCheckin(BaseModel): classroom_id: UUID session_date: datetime attendee: UUID class SessionCheckout(BaseModel): attendee: UUID class AttendeeSessionCancellation(BaseModel): classroom_id: UUID session_date: datetime

17.05

45

0.777126

37

341

7.054054

0.405405

0.137931

0.153257

0.183908

0.329502

0

0.178886

341

19

46

17.947368

0.932143

0

0.5

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true

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null

0

1

0

null

0

1

0

1

0

3

25896efe3a299c9d7020c4092fcd87f29eace4ca

2,205

py

Python

restAPI/serializers.py

GarlandQ/project-2-photoshare-api

76430894bb83b0d9e786c0d4bf2b9ac2b3cc87dd

[ "Apache-2.0" ]

null

restAPI/serializers.py

GarlandQ/project-2-photoshare-api

76430894bb83b0d9e786c0d4bf2b9ac2b3cc87dd

[ "Apache-2.0" ]

null

restAPI/serializers.py

GarlandQ/project-2-photoshare-api

76430894bb83b0d9e786c0d4bf2b9ac2b3cc87dd

[ "Apache-2.0" ]

null

from rest_framework import serializers from users.models import Profile from feed.models import Post, Comment from django.shortcuts import get_object_or_404 class ProfileSerializer(serializers.HyperlinkedModelSerializer): url = serializers.HyperlinkedIdentityField( view_name="profile-detail", read_only=True ) user = serializers.CharField(source="user.username", read_only=True) class Meta: model = Profile fields = ["id", "user", "image", "bio", "url"] class CommentSerializer(serializers.HyperlinkedModelSerializer): user = serializers.CharField(source="user.username", read_only=True) class Meta: model = Comment fields = ["user", "comment", "comment_date"] read_only_fields = ["comment_date"] class PostUserSerializer(serializers.HyperlinkedModelSerializer): url = serializers.HyperlinkedIdentityField( view_name="profile-detail", read_only=True ) user = serializers.CharField(source="user.username") class Meta: model = Profile fields = ["id", "user", "url"] class PostSerializer(serializers.HyperlinkedModelSerializer): user = PostUserSerializer(source="user.profile", read_only=True) comments = CommentSerializer(many=True, read_only=True) url = serializers.HyperlinkedIdentityField(view_name="post-detail", read_only=True) class Meta: model = Post fields = [ "id", "user", "picture", "date_posted", "comments", "description", "url", ] read_only_fields = ["date_posted"] class PostDetailSerializer(serializers.HyperlinkedModelSerializer): user = PostUserSerializer(source="user.profile", read_only=True) comments = CommentSerializer(many=True, read_only=True) url = serializers.HyperlinkedIdentityField(view_name="post-detail", read_only=True) class Meta: model = Post fields = [ "id", "user", "picture", "date_posted", "comments", "description", "url", ] read_only_fields = ["picture", "date_posted"]

28.269231

87

0.646259

207

2,205

6.73913

0.231884

0.074552

0.086022

0.12043

0.726882

0.689606

0

0.001805

0.246259

2,205

77

88

28.636364

0.837545

0

0.637931

0

0.133787

0

1

0

false

0

0.068966

0

0.431034

0

null

0

1

0

1

0

null

0

3

258fddd6d67b959467d399de816ca3fcb091983f

4,060

py

Python

exercises/en/test_06_08b.py

UBC-MDS/exploratory-data-viz

83b704ce10d1ff5e10bfd4cdfa872ac52993fd54

[ "CC-BY-4.0" ]

null

exercises/en/test_06_08b.py

UBC-MDS/exploratory-data-viz

83b704ce10d1ff5e10bfd4cdfa872ac52993fd54

[ "CC-BY-4.0" ]

88

2020-12-04T06:56:51.000Z

2021-05-10T22:02:45.000Z

exercises/en/test_06_08b.py

UBC-MDS/exploratory-data-viz

83b704ce10d1ff5e10bfd4cdfa872ac52993fd54

[ "CC-BY-4.0" ]

4

2021-01-13T09:30:57.000Z

2021-08-03T20:49:31.000Z

def test(): # Here we can either check objects created in the solution code, or the # string value of the solution, available as __solution__. A helper for # printing formatted messages is available as __msg__. See the testTemplate # in the meta.json for details. # If an assertion fails, the message will be displayed assert not world_df is None, "Your answer for world_df does not exist. Have you loaded the TopoJSON data to the correct variable name?" assert "topo_feature" in __solution__, "The loaded data should be in TopoJSON format. In order to read TopoJSON file correctly, you need to use the alt.topo_feature() function." assert ( "quantitative" in __solution__ or "pop_density:Q" in __solution__ ), "Make sure you use pop_density column from gapminder_df for the color encoding. Hint: since pop_density column does not exist in world_df, Altair can't infer its data type and you need to specify that it is quantitative data." assert type(world_df) == alt.UrlData, "world_df does not appear to be an Altair UrlData object. Have you assigned the Altair UrlData object for the TopoJSON data to the correct variable?" assert world_df.url == data.world_110m.url, "Make sure you are loading the data from correct url." assert (world_df.format != alt.utils.schemapi.Undefined and world_df.format.type == 'topojson' ), "The loaded data should be in TopoJSON format. In order to read TopoJSON file correctly, you need to use the alt.topo_feature() function." assert world_df.format.feature == "countries", "Make sure to specify 'countries' feature when loading the TopoJSON file using alt.topo_feature()." assert not pop_dense_plot is None, "Your answer for pop_dense_plot does not exist. Have you assigned the plot to the correct variable name?" assert type(pop_dense_plot) == alt.Chart, "pop_dense_plot does not appear to be an Altair Chart object. Have you assigned the Altair Chart object for the plot to the correct variable?" assert pop_dense_plot.mark == 'geoshape', "Make sure you are using mark_geoshape for pop_dense_plot." assert pop_dense_plot.encoding.color != alt.utils.schemapi.Undefined and ( pop_dense_plot.encoding.color.shorthand in {'pop_density:quantitative', 'pop_density:Q'} or (pop_dense_plot.encoding.color.shorthand == 'pop_density' and pop_dense_plot.encoding.color.type == 'quantitative') or pop_dense_plot.encoding.color.field in {'pop_density:quantitative', 'pop_density:Q'} or (pop_dense_plot.encoding.color.field == 'pop_density' and pop_dense_plot.encoding.color.type == 'quantitative') ), "Make sure you use pop_density column from gapminder_df for the color encoding. Hint: since pop_density column does not exist in world_df, Altair can't infer its data type and you need to specify that it is quantitative data." assert pop_dense_plot.encoding.color.scale != alt.utils.schemapi.Undefined and ( pop_dense_plot.encoding.color.scale.scheme != alt.utils.schemapi.Undefined ), "Make sure to specify a colour scheme." assert pop_dense_plot.encoding.color.scale.domainMid == 81, "Make sure you set the domainMid of the color scale as the global median (81)." assert type(pop_dense_plot.transform) == list and ( len(pop_dense_plot.transform) == 1 and pop_dense_plot.transform[0]['from'] != alt.utils.schemapi.Undefined and pop_dense_plot.transform[0]['from'].fields == ['pop_density'] and pop_dense_plot.transform[0]['from'].key ), "Make sure you use .transform_lookup() to lookup the column 'pop_density' from the gapminder_df data using 'id' as the connecting column. Hint: 'pop_density' should be inside a list." assert pop_dense_plot.projection != alt.utils.schemapi.Undefined and ( pop_dense_plot.projection.scale == 80 ), "Make sure you use 'equalEarth' projection. Hint: you can use .project() method with type argument to specify projection type." __msg__.good("You're correct, well done!")

82.857143

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4.65016

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0.068705

0.579526

0.518379

0.450361

0.349021

0.321539

0

0.00389

0.176847

4,060

48

234

84.583333

0.867145

0.072906

0

0.055556

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0.222222

0.551091

0.012773

0

0.416667

1

0.027778

true

0

0.027778

0

null

0

1

0

null

0

1

0

1

0

3

2590d3bc780b4146ff7f23d380a633901e96a1ff

142

py

Python

MiniProjects/Python-Challenges/Password_Gen.py

GitInitDev/ZohoUniv

966704837e65f58b52492b56d08e7958df3d220a

[ "Unlicense" ]

null

MiniProjects/Python-Challenges/Password_Gen.py

GitInitDev/ZohoUniv

966704837e65f58b52492b56d08e7958df3d220a

[ "Unlicense" ]

null

MiniProjects/Python-Challenges/Password_Gen.py

GitInitDev/ZohoUniv

966704837e65f58b52492b56d08e7958df3d220a

[ "Unlicense" ]

null

import random char = 'qwertyuiopasdfghjklzxcvbnm!@#$%^&*(()' stren = 10 password = "".join(random.sample(char , stren)) print (password)

23.666667

48

0.669014

14

142

6.785714

0.714286

0

0.016393

0.140845

142

5

49

28.4

0.762295

0

0.270073

0

1

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false

0.4

0.2

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0.2

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0

null

0

1

0

null

0

1

0

3

2596a121f75c0a84a57c9d2da30a7e882330ffb8

551

py

Python

lamp/utils.py

Den4200/lamp

85219d207863032b64e30d07c7ea05c4a5251ad9

[ "MIT" ]

null

lamp/utils.py

Den4200/lamp

85219d207863032b64e30d07c7ea05c4a5251ad9

[ "MIT" ]

3

2021-06-08T21:21:16.000Z

2022-01-13T02:33:12.000Z

lamp/utils.py

Den4200/lamp

85219d207863032b64e30d07c7ea05c4a5251ad9

[ "MIT" ]

null

class SimpleSpriteList: def __init__(self) -> None: self.sprites = list() def draw(self) -> None: for sprite in self.sprites: sprite.draw() def update(self) -> None: for sprite in self.sprites: sprite.update() def append(self, sprite) -> None: self.sprites.append(sprite) def remove(self, sprite) -> None: self.sprites.remove(sprite) def pop(self, index: int = -1): self.sprites.pop(index) def clear(self) -> None: self.sprites.clear()

22.04

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66

551

4.712121

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0.192926

0.122187

0.392283

0.231511

0

0.002597

0.30127

551

24

38

22.958333

0.805195

0

0.117647

0

1

0.411765

false

0

0.470588

0

null

1

0

null

0

1

0

3

d31dae9adebf377650654bacbc575ce6a85d5f52

989

py

Python

spconv/pytorch/__init__.py

xiaobaishu0097/spconv

4ef83629ea763477217a405f274fc870037eb93a

[ "Apache-2.0" ]

909

2019-01-19T03:46:36.000Z

2022-03-31T11:43:30.000Z

spconv/pytorch/__init__.py

xiaobaishu0097/spconv

4ef83629ea763477217a405f274fc870037eb93a

[ "Apache-2.0" ]

437

2019-01-21T04:58:21.000Z

2022-03-31T02:02:04.000Z

spconv/pytorch/__init__.py

xiaobaishu0097/spconv

4ef83629ea763477217a405f274fc870037eb93a

[ "Apache-2.0" ]

277

2019-01-23T15:40:00.000Z

2022-03-31T21:52:07.000Z

import platform from pathlib import Path import numpy as np import torch from spconv.pytorch import ops from spconv.pytorch.conv import (SparseConv2d, SparseConv3d, SparseConvTranspose2d, SparseConvTranspose3d, SparseInverseConv2d, SparseInverseConv3d, SubMConv2d, SubMConv3d) from spconv.pytorch.core import SparseConvTensor from spconv.pytorch.identity import Identity from spconv.pytorch.modules import SparseModule, SparseSequential from spconv.pytorch.ops import ConvAlgo from spconv.pytorch.pool import SparseMaxPool2d, SparseMaxPool3d from spconv.pytorch.tables import AddTable, ConcatTable, JoinTable class ToDense(SparseModule): """convert SparseConvTensor to NCHW dense tensor. """ def forward(self, x: SparseConvTensor): return x.dense() class RemoveGrid(SparseModule): """remove pre-allocated grid buffer. """ def forward(self, x: SparseConvTensor): x.grid = None return x

30.90625

83

0.743175

105

989

7

0.514286

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0.185034

0.040816

0.084354

0

0.012516

0.192113

989

31

84

31.903226

0.907384

0.085945

0

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1

0.095238

false

0

0.571429

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0.857143

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null

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null

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Python

udacity/cs101-intro-cs/code/lesson2/problem-set/find_last.py

mi1980/projecthadoop3

32c83ceb14aef04c22ab9e428104f651ea8962e7

[ "MIT" ]

null

udacity/cs101-intro-cs/code/lesson2/problem-set/find_last.py

mi1980/projecthadoop3

32c83ceb14aef04c22ab9e428104f651ea8962e7

[ "MIT" ]

null

udacity/cs101-intro-cs/code/lesson2/problem-set/find_last.py

mi1980/projecthadoop3

32c83ceb14aef04c22ab9e428104f651ea8962e7

[ "MIT" ]

2

2018-02-25T03:35:30.000Z

2018-08-18T12:14:05.000Z

# Define a procedure, find_last, that takes as input # two strings, a search string and a target string, # and returns the last position in the search string # where the target string appears, or -1 if there # are no occurrences. # # Example: find_last('aaaa', 'a') returns 3 # Make sure your procedure has a return statement. def find_last(a,b): if (a.find(b) == -1): return -1 location = a.find(b) while (a.find(b, location) != -1): location = a.find(b, location) + 1 return location - 1 print find_last('aaaa', 'a') #>>> 3 print find_last('aaaaa', 'aa') #>>> 3 print find_last('aaaa', 'b') #>>> -1 print find_last("111111111", "1") #>>> 8 print find_last("222222222", "") #>>> 9 print find_last("", "3") #>>> -1 print find_last("", "") #>>> 0

19.15

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0.182768

766

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19.15

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