xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

83f2f911f6d7ea736a4c990f84950822c72fd4c2

181

py

Python

func/python/bench_pidigits.py

J-Heinemann/faasm

6a7472d73ef7cc18e63617c72715c8775afd11a9

[ "Apache-2.0" ]

1

2020-04-21T07:33:42.000Z

func/python/bench_pidigits.py

J-Heinemann/faasm

6a7472d73ef7cc18e63617c72715c8775afd11a9

[ "Apache-2.0" ]

4

2020-02-03T18:54:32.000Z

2020-05-13T18:28:28.000Z

func/python/bench_pidigits.py

J-Heinemann/faasm

6a7472d73ef7cc18e63617c72715c8775afd11a9

[ "Apache-2.0" ]

null

from pyperformance.benchmarks.bm_pidigits import calc_ndigits, DEFAULT_DIGITS def faasm_main(): calc_ndigits(DEFAULT_DIGITS * 3) if __name__ == "__main__": faasm_main()

18.1

77

0.762431

23

181

5.347826

0.695652

0.178862

0.292683

0.390244

0

0.006494

0.149171

181

9

78

20.111111

0.792208

0

0.044199

0

1

0.2

true

0

0.2

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

5

83f926e7897725029d5f5be26e904638d2aed142

184

py

Python

HackerRank/GradingStudents.py

kokuraxc/play-ground

48b5291f3cca117e0cd0a17bf9255ec4dc1a5cdd

[ "MIT" ]

null

HackerRank/GradingStudents.py

kokuraxc/play-ground

48b5291f3cca117e0cd0a17bf9255ec4dc1a5cdd

[ "MIT" ]

null

HackerRank/GradingStudents.py

kokuraxc/play-ground

48b5291f3cca117e0cd0a17bf9255ec4dc1a5cdd

[ "MIT" ]

null

# https://www.hackerrank.com/challenges/grading/problem def gradingStudents(grades): # Write your code here return [(g+2)//5*5 if (g >= 38) and (g%5>2) else g for g in grades]

36.8

71

0.673913

32

184

3.875

0.75

0

0.045752

0.168478

184

4

72

46

0.764706

0.402174

0

0.25

0

1

0.5

false

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

f7bfde39fde1e97851f152092a45c7e8444e5603

43

py

Python

dataloaders/__init__.py

atch841/CCT

3a0b05d63fde9118ea369f2c2d512ae4c814c248

[ "MIT" ]

null

dataloaders/__init__.py

atch841/CCT

3a0b05d63fde9118ea369f2c2d512ae4c814c248

[ "MIT" ]

null

dataloaders/__init__.py

atch841/CCT

3a0b05d63fde9118ea369f2c2d512ae4c814c248

[ "MIT" ]

null

from .voc import VOC from .lits import LiTS

21.5

22

0.790698

8

43

4.25

0.5

0

0.162791

43

2

22

21.5

0.944444

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

f7dad31d36143600c87b9f030c56e5d55d765965

54

py

Python

some_module/__init__.py

nalbarr/hello-luke-python

cdd96789073395f7119d489b0854ffa3fb839ea4

[ "MIT" ]

null

some_module/__init__.py

nalbarr/hello-luke-python

cdd96789073395f7119d489b0854ffa3fb839ea4

[ "MIT" ]

null

some_module/__init__.py

nalbarr/hello-luke-python

cdd96789073395f7119d489b0854ffa3fb839ea4

[ "MIT" ]

null

# module some_module from .item import Item, BaseItem

27

32

0.796296

8

54

5.25

0.75

0

0.148148

54

2

32

27

0.913043

0.333333

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

f7f139df7ad99c12dc2fc523e50bb2e44ec93923

103

py

Python

loginlimiter/admin.py

bsarsgard/django-loginlimiter

58fcd69be58d92b3a1eefb7065bd3d924598f51d

[ "Apache-2.0" ]

1

2016-08-09T22:13:07.000Z

loginlimiter/admin.py

bsarsgard/django-loginlimiter

58fcd69be58d92b3a1eefb7065bd3d924598f51d

[ "Apache-2.0" ]

null

loginlimiter/admin.py

bsarsgard/django-loginlimiter

58fcd69be58d92b3a1eefb7065bd3d924598f51d

[ "Apache-2.0" ]

null

from django.contrib import admin from .models import LoginAttempt admin.site.register(LoginAttempt)

14.714286

33

0.825243

13

103

6.538462

0.692308

0

0.116505

103

6

34

17.166667

0.934066

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7915d66060d1986a6d67af03f4b1ab325d9509f5

317

py

Python

db_upgrage2.py

djgidwani/remotetest

a8629fdaf4b66a40b25c2004915fde7d562d0245

[ "BSD-3-Clause" ]

null

db_upgrage2.py

djgidwani/remotetest

a8629fdaf4b66a40b25c2004915fde7d562d0245

[ "BSD-3-Clause" ]

null

db_upgrage2.py

djgidwani/remotetest

a8629fdaf4b66a40b25c2004915fde7d562d0245

[ "BSD-3-Clause" ]

null

#!flask/bin/python from migrate.versioning import api from config2 import SQLALCHEMY_DATABASE_URI from config2 import SQLALCHEMY_MIGRATE_REPO api.upgrade(SQLALCHEMY_DATABASE_URI, SQLALCHEMY_MIGRATE_REPO) v = api.db_version(SQLALCHEMY_DATABASE_URI, SQLALCHEMY_MIGRATE_REPO) print('Current database version: ' + str(v))

45.285714

68

0.85489

44

317

5.863636

0.454545

0.209302

0.244186

0.209302

0.325581

0

0.006826

0.07571

317

7

69

45.285714

0.87372

0.053628

0

0.086667

0

1

0

false

0

0.5

0

0.5

0.166667

0

null

1

0

1

0

null

0

1

0

5

793698eca227db779aeaa0ee85854679d578ff35

320

py

Python

lokalise/endpoints/languages_endpoint.py

carlmanaster/python-lokalise-api

ce4a43c5a7bf14f45a2432e096b1880ff28d6770

[ "BSD-3-Clause" ]

5

2020-09-09T15:22:34.000Z

2021-12-07T12:24:26.000Z

lokalise/endpoints/languages_endpoint.py

carlmanaster/python-lokalise-api

ce4a43c5a7bf14f45a2432e096b1880ff28d6770

[ "BSD-3-Clause" ]

39

2020-12-08T16:56:06.000Z

2022-03-28T15:18:52.000Z

lokalise/endpoints/languages_endpoint.py

carlmanaster/python-lokalise-api

ce4a43c5a7bf14f45a2432e096b1880ff28d6770

[ "BSD-3-Clause" ]

1

2021-03-25T02:55:49.000Z

""" lokalise.endpoints.languages_endpoint ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Module containing project languages endpoint. """ from .base_endpoint import BaseEndpoint class LanguagesEndpoint(BaseEndpoint): """Describes project languages endpoint. """ PATH = "projects/$parent_id/languages/$resource_id"

24.615385

55

0.68125

28

320

7.642857

0.678571

0.238318

0.224299

0

0.115625

320

12

56

26.666667

0.756184

0.5125

0

0.293706

0

1

0

false

0

0.333333

0

1

0

1

0

null

1

0

null

0

1

0

1

0

5

f730ae92f94c6a1c98bcbfd1b9c656dbf9f0d677

576

py

Python

emr_mine_python_scipts/pq_tree/Queue.py

debprakash/emr-view

6b5690c2335482e97b8dabbdec616c8a1d7df898

[ "MIT" ]

null

emr_mine_python_scipts/pq_tree/Queue.py

debprakash/emr-view

6b5690c2335482e97b8dabbdec616c8a1d7df898

[ "MIT" ]

null

emr_mine_python_scipts/pq_tree/Queue.py

debprakash/emr-view

6b5690c2335482e97b8dabbdec616c8a1d7df898

[ "MIT" ]

1

2018-10-24T02:54:40.000Z

''' Created on Dec 30, 2010 @author: patnaik ''' from collections import deque class Queue(object): def __init__(self, data = None): if data: self.internal_queue = deque(data) else: self.internal_queue = deque() def enqueue(self, value): self.internal_queue.append(value) def dequeue(self): return self.internal_queue.popleft() def __len__(self): return len(self.internal_queue) def __str__(self): return "%s" % (list(self.internal_queue))

20.571429

49

0.578125

65

576

4.846154

0.492308

0.228571

0.32381

0.139683

0

0.015267

0.317708

576

28

49

20.571429

0.78626

0.071181

0

0.003788

0

1

0.333333

false

0

0.066667

0.2

0.666667

0

null

1

0

null

0

1

0

1

0

5

f7418f0b52075a49fb21243f3295f02f023d4821

65

py

Python

faqt/__init__.py

kapoorlab/FAQT

2f3bc0574a350341988987ca3beb7bcf68203b6c

[ "MIT" ]

null

faqt/__init__.py

kapoorlab/FAQT

2f3bc0574a350341988987ca3beb7bcf68203b6c

[ "MIT" ]

null

faqt/__init__.py

kapoorlab/FAQT

2f3bc0574a350341988987ca3beb7bcf68203b6c

[ "MIT" ]

null

from .helpers import * from .Augmentation2D import Augmentation2D

32.5

42

0.846154

7

65

7.857143

0.571429

0

0.034483

0.107692

65

2

42

32.5

0.913793

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

f76b0a6f7ca8c5d5a8a4f7b599e04604a3892608

38

py

Python

tests/test_instrumentum.py

FedericoMontana/instrumentum

0d07f6503c3c0fc980d349aeb6f47c960a4afe9c

[ "MIT" ]

1

2022-02-22T17:27:39.000Z

tests/test_instrumentum.py

FedericoMontana/instrumentum

0d07f6503c3c0fc980d349aeb6f47c960a4afe9c

[ "MIT" ]

1

2021-12-03T21:43:42.000Z

tests/test_instrumentum.py

FedericoMontana/instrumentum

0d07f6503c3c0fc980d349aeb6f47c960a4afe9c

[ "MIT" ]

null

from instrumentum import instrumentum

19

37

0.894737

4

38

8.5

0.75

0

0.105263

38

1

38

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

e39d3bb8197f7bcfee43fcf98c2586a565fdea16

209

py

Python

d107/moeda.py

renankalfa/Curso_em_Video

d9012e7f8c87fcc0ea27082279da234364f7e9a8

[ "MIT" ]

3

2022-01-08T23:16:07.000Z

2022-01-17T14:11:25.000Z

d107/moeda.py

renankalfa/Curso_em_Video

d9012e7f8c87fcc0ea27082279da234364f7e9a8

[ "MIT" ]

null

d107/moeda.py

renankalfa/Curso_em_Video

d9012e7f8c87fcc0ea27082279da234364f7e9a8

[ "MIT" ]

null

def aumentar(n=0): return n * 1.5 def diminuir(n=0): return n * 0.5 def dobro(n=0): return n * 2 def metade(n=0): return n / 2 def moeda(n=0): return f'R${n:.2f}'.replace('.', ',')

11

41

0.521531

40

209

2.725

0.4

0.110092

0.366972

0.330275

0.238532

0

0.078947

0.272727

209

18

42

11.611111

0.638158

0

0.052632

0

1

0.5

false

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

5

e3d018f1e45c789930923f62c22e6abd08829e71

19

py

Python

detect_secrets/__init__.py

gazali-alfatih/detect-secrets

cb632c7b7f7611823939a237726b056df232d85b

[ "Apache-2.0" ]

766

2015-11-14T07:30:39.000Z

2022-03-05T11:45:28.000Z

detect_secrets/__init__.py

gazali-alfatih/detect-secrets

cb632c7b7f7611823939a237726b056df232d85b

[ "Apache-2.0" ]

81

2016-06-02T22:32:50.000Z

2021-05-17T00:52:06.000Z

detect_secrets/__init__.py

gazali-alfatih/detect-secrets

cb632c7b7f7611823939a237726b056df232d85b

[ "Apache-2.0" ]

122

2015-11-02T02:38:24.000Z

2020-06-03T08:22:15.000Z

VERSION = '0.13.0'

9.5

18

0.578947

4

19

2.75

0.75

0

0.25

0.157895

19

1

19

0.4375

0

0.315789

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

e3ef2d27d9beffa064ffe2cbd358aec4714da2cb

132

py

Python

atcoder/abc/a024.py

tomato-300yen/coding

db6f440a96d8c83f486005c650461a69f27e3926

[ "MIT" ]

null

atcoder/abc/a024.py

tomato-300yen/coding

db6f440a96d8c83f486005c650461a69f27e3926

[ "MIT" ]

null

atcoder/abc/a024.py

tomato-300yen/coding

db6f440a96d8c83f486005c650461a69f27e3926

[ "MIT" ]

null

A, B, C, K = map(int, input().split()) S, T = map(int, input().split()) print(A * S + B * T - ((S + T) * C if (S + T) >= K else 0))

33

59

0.454545

28

132

2.142857

0.5

0.1

0.366667

0.533333

0

0.010101

0.25

132

3

60

44

0.59596

0

1

0

true

0

0.333333

1

0

null

0

1

0

1

0

null

0

1

0

5

54029d2a342394dc4d0c71066b665c9d9e4ca2d7

165

py

Python

CH_09_documentation/apidoc_example/b.py

mastering-python/code_2

441af8b67402c8216c482cca7c002e1d7f0f1baa

[ "MIT" ]

null

CH_09_documentation/apidoc_example/b.py

mastering-python/code_2

441af8b67402c8216c482cca7c002e1d7f0f1baa

[ "MIT" ]

null

CH_09_documentation/apidoc_example/b.py

mastering-python/code_2

441af8b67402c8216c482cca7c002e1d7f0f1baa

[ "MIT" ]

null

from . import a class B(a.A): def regular_method(self): '''This regular method overrides :meth:`a.A.regular_method` ''' pass

13.75

40

0.545455

21

165

4.190476

0.619048

0.443182

0

0.333333

165

11

41

15

0.8

0.339394

0

1

0.25

false

0.25

0

0.75

0

1

0

null

1

0

null

0

1

0

1

0

1

0

5

540509880de1e75e3474b62ae5a47202bdea82c3

71

py

Python

disnakeSuperUtils/music/lavalink/__init__.py

Delta-Discord-Bot/disnakeSuperUtils

8a021d3a47ff56f22e0687d92827faa0b652b14c

[ "MIT" ]

91

2021-07-14T13:01:31.000Z

2022-03-25T10:28:49.000Z

discordSuperUtils/music/lavalink/__init__.py

KortaPo/discord-super-utils

b8c1cd1a986bc5c78eaf472bb5caf44dd7b605e4

[ "MIT" ]

14

2021-08-13T14:23:54.000Z

2022-03-25T09:57:12.000Z

discordSuperUtils/music/lavalink/__init__.py

KortaPo/discord-super-utils

b8c1cd1a986bc5c78eaf472bb5caf44dd7b605e4

[ "MIT" ]

42

2021-08-02T00:27:24.000Z

2022-03-31T15:47:37.000Z

from .lavalink import * from .equalizer import * from .player import *

17.75

24

0.746479

9

71

5.888889

0.555556

0.377358

0

0.169014

71

3

25

23.666667

0.898305

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

58175bfaa318aee8516cf66ec2a5f0ca868c1274

46

py

Python

btest1/ex2.py

originlab/Noho-Training

8823adc2d5a1c05ccbdb2104e0eff943f596dd93

[ "MIT" ]

null

btest1/ex2.py

originlab/Noho-Training

8823adc2d5a1c05ccbdb2104e0eff943f596dd93

[ "MIT" ]

null

btest1/ex2.py

originlab/Noho-Training

8823adc2d5a1c05ccbdb2104e0eff943f596dd93

[ "MIT" ]

null

print('hello') print('hello2') print('hello3')

15.333333

15

0.695652

6

46

5.333333

0.666667

0

0.045455

0.043478

46

3

16

15.333333

0.681818

0

0.361702

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

5824df28e11dec336994b7bae048057ef2875bf6

304

py

Python

src/debugpy/_vendored/pydevd/tests_python/resources/_debugger_case_linecache_existing_file.py

r3m0t/debugpy

090e3c3ef5758e5b316514c9d6f44f9b9b488cf1

[ "MIT" ]

695

2020-01-30T14:34:51.000Z

2022-03-31T09:31:57.000Z

src/debugpy/_vendored/pydevd/tests_python/resources/_debugger_case_linecache_existing_file.py

r3m0t/debugpy

090e3c3ef5758e5b316514c9d6f44f9b9b488cf1

[ "MIT" ]

845

2020-01-29T23:53:36.000Z

2022-03-31T19:45:04.000Z

src/debugpy/_vendored/pydevd/tests_python/resources/_debugger_case_linecache_existing_file.py

r3m0t/debugpy

090e3c3ef5758e5b316514c9d6f44f9b9b488cf1

[ "MIT" ]

66

2020-01-30T13:10:38.000Z

2022-03-29T07:11:17.000Z

import linecache import sys import os sys.path.append(os.path.dirname(os.path.abspath(__file__))) import _debugger_case_stepping linecache.updatecache(_debugger_case_stepping.__file__) assert linecache.getline(_debugger_case_stepping.__file__, 1) _debugger_case_stepping.Call() print('TEST SUCEEDED')

23.384615

61

0.845395

41

304

5.682927

0.487805

0.206009

0.343348

0.206009

0

0.003509

0.0625

304

12

62

25.333333

0.814035

0

0.042763

0

0.111111

1

0

true

0

0.444444

0

0.444444

0.111111

0

null

1

0

null

0

1

0

1

0

5

582b7b89c3f82cffae7935deb30b16a40a2a8fde

110

py

Python

semantic-python/test/fixtures/2-07-closure-over-scope.py

Temurson/semantic

2e9cd2c006cec9a0328791e47d8c6d60af6d5a1b

[ "MIT" ]

8,844

2019-05-31T15:47:12.000Z

2022-03-31T18:33:51.000Z

semantic-python/test/fixtures/2-07-closure-over-scope.py

Qanora/semantic

b0eda9a61bbc690a342fb177cfc12eec8c1c001c

[ "MIT" ]

401

2019-05-31T18:30:26.000Z

2022-03-31T16:32:29.000Z

semantic-python/test/fixtures/2-07-closure-over-scope.py

Qanora/semantic

b0eda9a61bbc690a342fb177cfc12eec8c1c001c

[ "MIT" ]

504

2019-05-31T17:55:03.000Z

2022-03-30T04:15:04.000Z

def const(a, b): def result(): return a def zilch(b): return b return result()

11

19

0.490909

15

110

3.6

0.466667

0.259259

0

0.4

110

9

20

12.222222

0.818182

0

1

0.5

false

0

0.333333

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

5835fdad99965193032439ac562a60c09baec642

135

py

Python

nmtpytorch/layers/__init__.py

awesome-archive/nmtpytorch

7c0ea21b29fc85a1f30ef4400d62b9d8e3d88be4

[ "MIT" ]

1

2021-03-30T02:05:46.000Z

nmtpytorch/layers/__init__.py

adakum/nmtpytorch

db4beb75146097a35babc90788d6ac26cc3186f7

[ "MIT" ]

null

nmtpytorch/layers/__init__.py

adakum/nmtpytorch

db4beb75146097a35babc90788d6ac26cc3186f7

[ "MIT" ]

null

from .attention import Attention from .ff import FF from .text_encoder import TextEncoder from .cond_decoder import ConditionalDecoder

27

44

0.851852

18

135

6.277778

0.555556

0

0.118519

135

4

45

33.75

0.94958

0

1

0

true

0

1

0

1

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1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

583fe1dce2c84329b98a22f43df49d3e557eecfd

192

py

Python

contrib/frontends/py/nntpchan/db.py

majestrate/nntpchan

f92f68c3cdce4b7ce6d4121ca4356b36ebcd933f

[ "MIT" ]

233

2015-08-06T02:51:52.000Z

2022-02-14T11:29:13.000Z

contrib/frontends/py/nntpchan/db.py

Revivify/nntpchan

0d555bb88a2298dae9aacf11348e34c52befa3d8

[ "MIT" ]

98

2015-09-19T22:29:00.000Z

2021-06-12T09:43:13.000Z

contrib/frontends/py/nntpchan/db.py

Revivify/nntpchan

0d555bb88a2298dae9aacf11348e34c52befa3d8

[ "MIT" ]

49

2015-08-06T02:51:55.000Z

2020-03-11T04:23:56.000Z

from nntpchan import config import sqlalchemy def allowsMessage(msgid): return True def allowsNewsgroup(group): return True def init(): """ initialize db backend """

11.294118

27

0.677083

21

192

6.190476

0.761905

0.153846

0.2

0

0.244792

192

16

28

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0.896552

0.109375

0

0.285714

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0.428571

false

0

0.285714

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0

1

0

null

0

1

0

null

0

1

0

1

0

5

585f012b7437b69ccfc8751784cdf554cd0f899b

232

py

Python

BusinessLogic/BLDayView.py

willemserruys/HourRegistration

ed64762f36adf57d12b9ecef0f6679d7a0150168

[ "MIT" ]

null

BusinessLogic/BLDayView.py

willemserruys/HourRegistration

ed64762f36adf57d12b9ecef0f6679d7a0150168

[ "MIT" ]

null

BusinessLogic/BLDayView.py

willemserruys/HourRegistration

ed64762f36adf57d12b9ecef0f6679d7a0150168

[ "MIT" ]

null

from DataAccess import DADayView from BusinessEntities import DayView import sqlite3 class BLDayView: def __init__(self,conn): self.DAL = DADayView.DADayView(conn) def GetAll(self): return self.DAL.GetAll()

23.2

44

0.728448

28

232

5.892857

0.571429

0.084848

0

0.005376

0.198276

232

10

45

23.2

0.88172

0

1

0.25

false

0

0.375

0.125

0.875

0

1

0

null

0

null

0

1

0

1

0

5

587eb825778953bebc917cfdb2bbb1314610cc6a

169

py

Python

desafio15.py

DantonMatheus/desafios-python

709a3f1774596fc536dd4b882c78a6b951c92a9c

[ "MIT" ]

null

desafio15.py

DantonMatheus/desafios-python

709a3f1774596fc536dd4b882c78a6b951c92a9c

[ "MIT" ]

null

desafio15.py

DantonMatheus/desafios-python

709a3f1774596fc536dd4b882c78a6b951c92a9c

[ "MIT" ]

null

print('===== DESAFIO 15 =====') d = int(input('Quantos dias alugados? ')) km = float(input('Quantos Km rodados? ')) print(f'O total a pagar é R${(d*60)+(km*0.15):.2f}')

33.8

52

0.591716

29

169

3.448276

0.758621

0.24

0

0.054422

0.130178

169

4

53

42.25

0.62585

0

0.633136

0.142012

0

1

0

false

0

0.5

1

0

null

1

0

1

0

1

0

null

0

1

0

5

546fb4b62a2408ca2f09a370f4218e0fd6967bde

81

py

Python

serverless/libwrapper.py

ChuckBowers/phish_viz

0849ab9a53b6d5e18f127e6e4ab5d8b8cc3144da

[ "MIT" ]

null

serverless/libwrapper.py

ChuckBowers/phish_viz

0849ab9a53b6d5e18f127e6e4ab5d8b8cc3144da

[ "MIT" ]

null

serverless/libwrapper.py

ChuckBowers/phish_viz

0849ab9a53b6d5e18f127e6e4ab5d8b8cc3144da

[ "MIT" ]

null

from phishvizlib.test import test def test_wrapper(event, context): test()

13.5

33

0.740741

11

81

5.363636

0.727273

0

0.17284

81

5

34

16.2

0.880597

0

1

0.333333

false

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

547b2c7c378a02b831f2bf2b90797ecb47a448c7

26,083

py

Python

lnn/symbolic/_gm.py

namin/LNN

4a033546ec544b3c00bba27f6f8a8b17ee5fac49

[ "Apache-2.0" ]

null

lnn/symbolic/_gm.py

namin/LNN

4a033546ec544b3c00bba27f6f8a8b17ee5fac49

[ "Apache-2.0" ]

null

lnn/symbolic/_gm.py

namin/LNN

4a033546ec544b3c00bba27f6f8a8b17ee5fac49

[ "Apache-2.0" ]

null

## # Copyright 2021 IBM Corp. All Rights Reserved. # # SPDX-License-Identifier: Apache-2.0 ## from ..constants import Direction, Join from .._utils import negate_bounds import copy import torch from itertools import chain from typing import Tuple, Union, List, TypeVar, Set """ Grounding management module All functions in this module assume a _Formula level scope """ _Grounding = TypeVar('_Grounding') _Formula = TypeVar('_Formula') def upward_bounds(self: _Formula, operands: Tuple[_Formula, ...], groundings: Set[Union[str, Tuple[str, ...]]] = None ) -> Union[None, Tuple[torch.Tensor, None], Tuple[torch.Tensor, Set[_Grounding]]]: """returns (input_bounds, groundings)""" result = _operational_bounds(self, Direction.UPWARD, operands, groundings) return result def downward_bounds(self: _Formula, operands: Tuple[_Formula, ...], groundings: Set[Union[str, Tuple[str, ...]]] = None ) -> Union[None, Tuple[torch.Tensor, torch.Tensor, None], Tuple[torch.Tensor, torch.Tensor, Set[_Grounding]]]: """returns (output_bounds, input_bounds, groundings)""" result = _operational_bounds(self, Direction.DOWNWARD, operands, groundings) return result def disjoint(pred_vars): return not any( [all([v in _vars for _vars in pred_vars]) for v in pred_vars[0]]) _Variable = TypeVar('_Variable') def unique_variables(*variables: Tuple[_Variable, ...]) -> Tuple: """combines all predicate variables into a unique tuple the tuple is sorted by the order of appearance of variables in the operands """ result = list() for op_vars in variables: for v in op_vars: if v not in result: result.append(v) return tuple(result) def _operational_bounds(self: _Formula, direction: Direction, operands: Tuple[_Formula, ...], groundings: Set[Union[str, Tuple[str, ...]]] = None, ) -> Union[None, Tuple[torch.Tensor, None], Tuple[torch.Tensor, torch.Tensor, None], Tuple[torch.Tensor, Set[_Grounding]], Tuple[torch.Tensor, torch.Tensor, Set[_Grounding]]]: # propositional / hash join for homogeneous operand variables if (self.propositional # propositional or (all([v == self.var_remap[0] for v in self.var_remap]) # homogenous variables and not self._has_bindings())): # bindings if self.propositional: # propositional bounds if True in ([op.is_contradiction() for op in operands] + [self.is_contradiction()]): return input_bounds = _masked_negate( self, torch.stack([op.get_facts() for op in operands], dim=-1)) if direction is Direction.UPWARD: return input_bounds, None return self.get_facts(), input_bounds, None else: # FOL bounds if groundings is None: groundings = set(chain.from_iterable( [op.grounding_table for op in operands])) if direction is Direction.DOWNWARD: groundings.update(self.grounding_table.keys()) else: groundings = set(map(self._ground, groundings)) for g in groundings: for op in operands: op._add_groundings(g) groundings = _hash_join(operands, groundings) input_bounds = _masked_negate(self, torch.stack( [op.get_facts(*groundings) for op in operands], dim=-1)) self._add_groundings(*groundings) if direction is Direction.UPWARD: return input_bounds, groundings output_bounds = self.get_facts(*groundings) if len(output_bounds) == 0: return return output_bounds, input_bounds, groundings # nested loop join for bindings / heterogenous operand variables else: if self.propositional: raise TypeError('proposition should not reach here') grounding_tables = [] for op in operands: g_t = dict() for g in op.grounding_table: if g.name[0] != '(': g_t[eval("('" + g.name + "',)")] = g else: g_t[eval(g.name)] = g # op.grounding_table[g] grounding_tables.append(g_t) tmp_bindings = [tuple([str(b) if b is not None else b for b in g] if isinstance(g, List) else str(g) if g is not None else g for g in op) for op in self.bindings] tmp_binding_str = [', '.join([f'{v}' for v in op]) for op in self.var_remap] if self.join_method is Join.INNER: ground_tuples, ground_objects = _nested_loop_join_inner( grounding_tables, tmp_binding_str, tmp_bindings, operands) elif self.join_method is Join.OUTER: ground_tuples, ground_objects = _nested_loop_join_outer( grounding_tables, tmp_binding_str, tmp_bindings, operands) elif self.join_method is Join.OUTER_PRUNED: ground_tuples, ground_objects = _nested_loop_join_outer_pruned( grounding_tables, tmp_binding_str, tmp_bindings, operands) if ground_objects is None or \ all([len(o) == 0 for o in ground_objects]): return tmp_ground_tuples = [g[0] for g in ground_tuples] if ( len(self.unique_vars) == 1) else ground_tuples groundings = tuple() for t in tmp_ground_tuples: groundings += (self._ground(t),) input_bounds = _masked_negate(self, torch.stack( [op.get_facts(*ground_objects[i]) for i, op in enumerate(operands)], dim=-1)) self._add_groundings(*groundings) if direction is Direction.UPWARD: return input_bounds, groundings output_bounds = self.get_facts(*groundings) if len(output_bounds) == 0: return return output_bounds, input_bounds, groundings @torch.no_grad() def _nested_loop_join_outer(g_list, arg_str, bindings, operands): """ E.g Join two Predicates P1(x,y) and P2(x,z,y) with groundings (x1,y1) : g11 (ground object) and (x1,z1,y1) : g12 (x2,y2) : g21 (ground object) and (x2,z2,y2) : g22 (x1,y3) : g31 (ground object) and (x2,z3,y2) : g32 Inputs arg_str : is the list of strings : ['x,y','x,z,y'] bindings : list of bindings for each variable g_list : is the list [ g_list[0], g_list[1]] where g_list[0] is the dictionary g_list[0] [(x1,y1)] = g11 ; [(x2,y2)] = g21 ; [(x1,y3)] = g31 and g_list[1] is the dictionary g_list[1] [(x1,z1,y1)] = g12;[(x2,z2,y2)] = g2;[(x2,z3,y3)] = g32 **Returns** list_tuples: List of joined ground tuples: [(x1,y1,z1), (x2,y2,z2), ...] object: List of list of ground objects for each operand [[g11,g21], [g12,g22], ...] """ n_ops = len(g_list) var_list = [g.split(', ') for g in arg_str] _vars = set() var_map = {} var_count = 0 var_remap = [] for v in var_list: var_remap_t = [] for v2 in v: if v2 not in _vars: var_map[v2] = var_count var_remap_t.append(var_count) var_count = var_count + 1 _vars.add(v2) else: var_remap_t.append(var_map[v2]) var_remap.append(var_remap_t) def find_rev_joined_pos(full_map, op_map): rev_index = [] rev_pos = [] for i_, o_ in enumerate(full_map): if o_ in op_map: rev_index.append(i_) rev_pos.append(op_map.index(o_)) return rev_index, rev_pos def find_joined_vars(var_map1, var_map2): match_pos1 = [] match_pos2 = [] for v in var_map1: if v in var_map2: match_pos1.append(var_map1.index(v)) match_pos2.append(var_map2.index(v)) umatch_pos2 = [var_map2.index(v) for v in var_map2 if v not in var_map1] joined_vars = [v for v in var_map1] for v in var_map2: if v not in joined_vars: joined_vars.append(v) scatter_pos2 = [] for v in var_map2: scatter_pos2.append(joined_vars.index(v)) return match_pos1, match_pos2, umatch_pos2, joined_vars, scatter_pos2 curr_merged = g_list[0] curr_map = var_remap[0] all_vars = [] n_z_index = [] for i, a_ in enumerate(var_remap): for aa_ in a_: if aa_ not in all_vars: all_vars.append(aa_) if len(g_list[i]) != 0: n_z_index.append(i) n_z_vars = [] for i in n_z_index: for a_ in var_remap[i]: if a_ not in n_z_vars: n_z_vars.append(a_) if (set(all_vars) != set(n_z_vars)): return None, None reorder_pos = [None]*len(all_vars) for i in range(len(n_z_vars)): reorder_pos[i] = all_vars.index(n_z_vars[i]) curr_merged = g_list[n_z_index[0]] curr_map = var_remap[n_z_index[0]] for i in n_z_index[1:]: colllected_g_list_full = set() curr_to_merge = g_list[i] match_pos1, match_pos2, umatch_pos2, joined_vars, scatter_pos2 = \ find_joined_vars(curr_map, var_remap[i]) for a1 in curr_merged: for a2 in curr_to_merge: m1 = [a1[i] for i in match_pos1] m2 = [a2[i] for i in match_pos2] if m1 == m2: j1 = tuple(list(a1) + [a2[k] for k in umatch_pos2]) colllected_g_list_full.add(j1) else: j1 = tuple(list(a1) + [a2[k] for k in umatch_pos2]) j2 = [None]*len(joined_vars) j2[0:len(a1)] = a1 for i, j in enumerate(scatter_pos2): j2[j] = a2[i] j2 = tuple(j2) colllected_g_list_full.add(j1) colllected_g_list_full.add(j2) curr_map = joined_vars curr_merged = list(colllected_g_list_full) ground_objects = [[] for i in range(len(operands))] for i in range(n_ops): rev_index, rev_pos = find_rev_joined_pos(curr_map, var_remap[i]) curr_op = copy.copy(g_list[i]) for curr_tup in curr_merged: found = False m1 = [None]*len(var_remap[i]) for i_, r_ in enumerate(rev_index): m1[rev_pos[i_]] = curr_tup[r_] m1 = tuple(m1) for op_tup in curr_op: if m1 == op_tup: if operands[i].arity == 1: g_obj = operands[i]._ground(op_tup[0]) else: g_obj = operands[i]._ground(op_tup) ground_objects[i].append(g_obj) found = True if not found: if operands[i].arity == 1: g_obj = operands[i]._ground(m1[0]) operands[i]._add_groundings(g_obj) else: g_obj = operands[i]._ground(m1) operands[i]._add_groundings(g_obj) ground_objects[i].append(g_obj) curr_op[m1] = g_obj return curr_merged, ground_objects @torch.no_grad() def _nested_loop_join_outer_pruned(g_list, arg_str, bindings, operands): """ E.g Join two Predicates P1(x,y) and P2(x,z,y) with groundings (x1,y1) : g11 (ground object) and (x1,z1,y1) : g12 (x2,y2) : g21 (ground object) and (x2,z2,y2) : g22 (x1,y3) : g31 (ground object) and (x2,z3,y2) : g32 Inputs arg_str : is the list of strings : ['x,y','x,z,y'] bindings : list of bindings for each variable g_list : is the list [ g_list[0], g_list[1]] where g_list[0] is the dictionary g_list[0] [(x1,y1)] = g11 ; [(x2,y2)] = g21 ; [(x1,y3)] = g31 and g_list[1] is the dictionary g_list[1] [(x1,z1,y1)] = g12;[(x2,z2,y2)] = g2;[(x2,z3,y3)] = g32 **Returns** list_tuples: List of joined ground tuples: [(x1,y1,z1), (x2,y2,z2), ...] object: List of list of ground objects for each operand [[g11,g21], [g12,g22], ...] """ n_ops = len(g_list) var_list = [g.split(', ') for g in arg_str] _vars = set() var_map = {} var_count = 0 var_remap = [] for v in var_list: var_remap_t = [] for v2 in v: if v2 not in _vars: var_map[v2] = var_count var_remap_t.append(var_count) var_count = var_count + 1 _vars.add(v2) else: var_remap_t.append(var_map[v2]) var_remap.append(var_remap_t) def find_rev_joined_pos(full_map, op_map): rev_index = [] rev_pos = [] for i_, o_ in enumerate(full_map): if o_ in op_map: rev_index.append(i_) rev_pos.append(op_map.index(o_)) return rev_index, rev_pos def find_joined_vars(var_map1, var_map2): match_pos1 = [] match_pos2 = [] for v in var_map1: if v in var_map2: match_pos1.append(var_map1.index(v)) match_pos2.append(var_map2.index(v)) umatch_pos2 = [var_map2.index(v) for v in var_map2 if v not in var_map1] joined_vars = [v for v in var_map1] for v in var_map2: if v not in joined_vars: joined_vars.append(v) scatter_pos2 = [] for v in var_map2: scatter_pos2.append(joined_vars.index(v)) return match_pos1, match_pos2, umatch_pos2, joined_vars, scatter_pos2 curr_merged = g_list[0] curr_map = var_remap[0] all_vars = [] n_z_index = [] n_z_groundings = False for i, a_ in enumerate(var_remap): for aa_ in a_: if aa_ not in all_vars: all_vars.append(aa_) if len(g_list[i]) != 0: n_z_index.append(i) else: n_z_groundings = True n_z_vars = [] for i in n_z_index: for a_ in var_remap[i]: if a_ not in n_z_vars: n_z_vars.append(a_) if (set(all_vars) != set(n_z_vars)): return None, None reorder_pos = [None]*len(all_vars) for i in range(len(n_z_vars)): reorder_pos[i] = all_vars.index(n_z_vars[i]) curr_merged = g_list[n_z_index[0]] curr_map = var_remap[n_z_index[0]] first_op = True for i in n_z_index[1:]: colllected_g_list_obj = {} curr_to_merge = g_list[i] match_pos1, match_pos2, umatch_pos2, joined_vars, scatter_pos2 = \ find_joined_vars(curr_map, var_remap[i]) for a1 in curr_merged: for a2 in curr_to_merge: m1 = [a1[i_] for i_ in match_pos1] m2 = [a2[i_] for i_ in match_pos2] if m1 == m2: j1 = tuple(list(a1) + [a2[k] for k in umatch_pos2]) if first_op: colllected_g_list_obj[j1] = \ [curr_merged[a1]]+[curr_to_merge[a2]] else: colllected_g_list_obj[j1] = \ curr_merged[a1]+[curr_to_merge[a2]] else: j1 = tuple(list(a1) + [a2[k] for k in umatch_pos2]) j2 = [None]*len(joined_vars) j2[0:len(a1)] = a1 for i_, j_ in enumerate(scatter_pos2): j2[j_] = a2[i_] j2 = tuple(j2) colllected_g_list_obj[j1] = \ [curr_merged[a1]]+[curr_to_merge[a2]] colllected_g_list_obj[j2] = \ [curr_merged[a1]]+[curr_to_merge[a2]] if first_op: colllected_g_list_obj[j1] = \ [curr_merged[a1]]+[curr_to_merge[a2]] colllected_g_list_obj[j2] = \ [curr_merged[a1]]+[curr_to_merge[a2]] else: colllected_g_list_obj[j1] = \ curr_merged[a1]+[curr_to_merge[a2]] colllected_g_list_obj[j2] = \ curr_merged[a1]+[curr_to_merge[a2]] curr_map = joined_vars curr_merged = colllected_g_list_obj first_op = False if n_z_groundings: g_obj2 = {} for g in curr_merged: g_ = [None]*len(g) for i, a_ in enumerate(g): g_[reorder_pos[i]] = a_ g_ = tuple(g_) g_obj = [curr_merged[g]] g_new = [] g_obj_indx = 0 for i in range(n_ops): if i not in n_z_index: rev_index, rev_pos = \ find_rev_joined_pos(all_vars, var_remap[i]) m1 = [None]*len(var_remap[i]) for i_, r_ in enumerate(rev_index): m1[rev_pos[i_]] = g_[r_] m1 = tuple(m1) if operands[i].arity == 1: g_obj_n = operands[i]._ground(m1[0]) operands[i]._add_groundings(g_obj_n) else: g_obj_n = operands[i]._ground(m1) operands[i]._add_groundings(g_obj_n) g_new.append(g_obj_n) else: g_new.append(g_obj[g_obj_indx]) g_obj_indx = g_obj_indx + 1 g_obj2[g_] = g_new curr_merged = g_obj2 g_obj = [None] * n_ops for i in range(n_ops): g_obj[i] = [] for gg in curr_merged.values(): for i in range(n_ops): g_obj[i].append(gg[i]) return list(curr_merged.keys()), g_obj @torch.no_grad() def _nested_loop_join_inner(g_list, arg_str, bindings, operands): """ E.g Join two Predicates P1(x,y) and P2(x,z,y) with groundings (x1,y1) : g11 (ground object) and (x1,z1,y1) : g12 (x2,y2) : g21 (ground object) and (x2,z2,y2) : g22 (x1,y3) : g31 (ground object) and (x2,z3,y2) : g32 Inputs arg_str : is the list of strings : ['x,y','x,z,y'] bindings : list of bindings for each variable g_list : is the list [ g_list[0], g_list[1]] where g_list[0] is the dictionary g_list[0] [(x1,y1)] = g11 ; [(x2,y2)] = g21 ; [(x1,y3)] = g31 and g_list[1] is the dictionary g_list[1] [(x1,z1,y1)] = g12;[(x2,z2,y2)] = g2;[(x2,z3,y3)] = g32 **Returns** list_tuples: List of joined ground tuples: [(x1,y1,z1), (x2,y2,z2), ...] object: List of list of ground objects for each operand [[g11,g21], [g12,g22], ...] """ n_ops = len(g_list) var_list = [g.split(', ') for g in arg_str] _vars = set() var_map = {} var_count = 0 var_remap = [] for v in var_list: var_remap_t = [] for v2 in v: if v2 not in _vars: var_map[v2] = var_count var_remap_t.append(var_count) var_count = var_count + 1 _vars.add(v2) else: var_remap_t.append(var_map[v2]) var_remap.append(var_remap_t) def find_rev_joined_pos(full_map, op_map): rev_index = [] rev_pos = [] for i_, o_ in enumerate(full_map): if o_ in op_map: rev_index.append(i_) rev_pos.append(op_map.index(o_)) return rev_index, rev_pos def find_joined_vars(var_map1, var_map2): match_pos1 = [] match_pos2 = [] for v in var_map1: if v in var_map2: match_pos1.append(var_map1.index(v)) match_pos2.append(var_map2.index(v)) umatch_pos2 = [var_map2.index(v) for v in var_map2 if v not in var_map1] joined_vars = [v for v in var_map1] for v in var_map2: if v not in joined_vars: joined_vars.append(v) scatter_pos2 = [] for v in var_map2: scatter_pos2.append(joined_vars.index(v)) return match_pos1, match_pos2, umatch_pos2, joined_vars, scatter_pos2 all_vars = [] n_z_index = [] n_z_groundings = False for i, a_ in enumerate(var_remap): for aa_ in a_: if aa_ not in all_vars: all_vars.append(aa_) if len(g_list[i]) != 0: n_z_index.append(i) else: n_z_groundings = True n_z_vars = [] for i in n_z_index: for a_ in var_remap[i]: if a_ not in n_z_vars: n_z_vars.append(a_) if (set(all_vars) != set(n_z_vars)): curr_merged = g_list[0] g_obj = [None] * n_ops for i in range(n_ops): g_obj[i] = [] return list(curr_merged.keys()), g_obj reorder_pos = [None]*len(all_vars) for i in range(len(n_z_vars)): reorder_pos[i] = all_vars.index(n_z_vars[i]) curr_merged = g_list[n_z_index[0]] curr_map = var_remap[n_z_index[0]] first_op = True for i in n_z_index[1:]: colllected_g_list_obj = {} curr_to_merge = g_list[i] match_pos1, match_pos2, umatch_pos2, joined_vars, _ = \ find_joined_vars(curr_map, var_remap[i]) for a1 in curr_merged: for a2 in curr_to_merge: m1 = [a1[i_] for i_ in match_pos1] m2 = [a2[i_] for i_ in match_pos2] if m1 == m2: j1 = tuple(list(a1) + [a2[k] for k in umatch_pos2]) if first_op: colllected_g_list_obj[j1] = \ [curr_merged[a1]]+[curr_to_merge[a2]] else: colllected_g_list_obj[j1] = \ curr_merged[a1]+[curr_to_merge[a2]] curr_map = joined_vars curr_merged = colllected_g_list_obj first_op = False if n_z_groundings: g_obj2 = {} for g in curr_merged: g_ = [None]*len(g) for i, a_ in enumerate(g): g_[reorder_pos[i]] = a_ g_ = tuple(g_) g_obj = [curr_merged[g]] g_new = [] g_obj_indx = 0 for i in range(n_ops): if i not in n_z_index: rev_index, rev_pos =\ find_rev_joined_pos(all_vars, var_remap[i]) m1 = [None]*len(var_remap[i]) for i_, r_ in enumerate(rev_index): m1[rev_pos[i_]] = g_[r_] m1 = tuple(m1) if operands[i].arity == 1: g_obj_n = operands[i]._ground(m1[0]) operands[i]._add_groundings(g_obj_n) else: g_obj_n = operands[i]._ground(m1) operands[i]._add_groundings(g_obj_n) g_new.append(g_obj_n) else: g_new.append(g_obj[g_obj_indx]) g_obj_indx = g_obj_indx + 1 g_obj2[g_] = g_new curr_merged = g_obj2 g_obj = [None] * n_ops for i in range(n_ops): g_obj[i] = [] for gg in curr_merged.values(): for i in range(n_ops): g_obj[i].append(gg[i]) return list(curr_merged.keys()), g_obj def is_grounding_in_bindings(self: _Formula, operand_idx: int, operand_grounding: _Grounding, ) -> bool: return all(True if self.bindings[operand_idx][slot] == [None] else ( operand_grounding.partial_grounding[slot] in self.bindings[operand_idx][slot]) for slot in range(len(self.bindings[operand_idx]))) @torch.no_grad() def _hash_join(operands: _Formula, groundings: Set) -> Set: """get groundings that appear in all children""" # limit grounding_table join to given groundings grounding_tables = list({g: op.grounding_table[g] for g in groundings if g in op.grounding_table} for op in operands) result = list() for g in groundings: if all(g in grounding_tables[slot] for slot in range(len(operands))): result.append(g) return set(result) def _masked_negate(self: _Formula, bounds: torch.Tensor, dim: int = -2): """negate bounds where weights are negative""" if hasattr(self.neuron, 'weights'): result = bounds.where( self.neuron.weights.data >= 0, negate_bounds(bounds, dim)) return result return bounds

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Python

utils/gym/spaces/__init__.py

stefanbschneider/keras-rl

216c3145f3dc4d17877be26ca2185ce7db462bad

[ "MIT" ]

3,350

2018-03-07T09:46:43.000Z

2022-03-31T11:25:35.000Z

utils/gym/spaces/__init__.py

stefanbschneider/keras-rl

216c3145f3dc4d17877be26ca2185ce7db462bad

[ "MIT" ]

223

2018-03-11T00:07:46.000Z

2022-03-09T13:26:01.000Z

utils/gym/spaces/__init__.py

stefanbschneider/keras-rl

216c3145f3dc4d17877be26ca2185ce7db462bad

[ "MIT" ]

1,007

2018-03-08T11:26:49.000Z

2022-03-14T05:19:34.000Z

from .discrete import Discrete

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plugins/phabricator/komand_phabricator/util/editor/__init__.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

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2019-06-05T20:47:58.000Z

2022-03-29T10:18:01.000Z

plugins/phabricator/komand_phabricator/util/editor/__init__.py

lukaszlaszuk/insightconnect-plugins

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[ "MIT" ]

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2022-03-30T17:35:01.000Z

plugins/phabricator/komand_phabricator/util/editor/__init__.py

lukaszlaszuk/insightconnect-plugins

8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892

[ "MIT" ]

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2019-07-09T14:13:58.000Z

2022-03-28T12:04:46.000Z

from .maniphestedit import * from .testaction import *

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Python

sindy_bvp/library_builders/__init__.py

sheadan/SINDy-BVP

ac5b2bb4854bb311e4f6f26b180dde87cc10c13d

[ "MIT" ]

8

2020-05-19T23:56:39.000Z

2022-03-04T19:22:56.000Z

sindy_bvp/library_builders/__init__.py

sheadan/SINDy-BVP

ac5b2bb4854bb311e4f6f26b180dde87cc10c13d

[ "MIT" ]

null

sindy_bvp/library_builders/__init__.py

sheadan/SINDy-BVP

ac5b2bb4854bb311e4f6f26b180dde87cc10c13d

[ "MIT" ]

3

2020-08-07T17:57:02.000Z

2021-03-19T23:44:44.000Z

from .noise_maker import NoiseMaker from .term_builder import TermBuilder __all__ = ["noise_maker", "term_builder"]

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Python

tests/graph/test_subgraph_isomorphic.py

enavarro51/retworkx

71e34d111623d1de2e4870a8227eddacfb3ade4c

[ "Apache-2.0" ]

null

tests/graph/test_subgraph_isomorphic.py

enavarro51/retworkx

71e34d111623d1de2e4870a8227eddacfb3ade4c

[ "Apache-2.0" ]

null

tests/graph/test_subgraph_isomorphic.py

enavarro51/retworkx

71e34d111623d1de2e4870a8227eddacfb3ade4c

[ "Apache-2.0" ]

1

2022-03-24T05:00:30.000Z

# Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import unittest import retworkx class TestSubgraphIsomorphic(unittest.TestCase): def test_empty_subgraph_isomorphic_identical(self): g_a = retworkx.PyGraph() for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertTrue(retworkx.is_subgraph_isomorphic(g_a, g_a, id_order=id_order)) def test_empty_subgraph_isomorphic(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertTrue(retworkx.is_subgraph_isomorphic(g_a, g_b, id_order=id_order)) def test_empty_subgraph_isomorphic_compare_nodes(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertTrue( retworkx.is_subgraph_isomorphic( g_a, g_b, lambda x, y: x == y, id_order=id_order ) ) def test_subgraph_isomorphic_identical(self): g_a = retworkx.PyGraph() nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3"]) g_a.add_edges_from([(nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2")]) for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertTrue(retworkx.is_subgraph_isomorphic(g_a, g_a, id_order=id_order)) def test_subgraph_isomorphic_mismatch_node_data(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3", "a_4"]) g_a.add_edges_from( [ (nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2"), (nodes[0], nodes[3], "a_3"), ] ) nodes = g_b.add_nodes_from(["b_1", "b_2", "b_3"]) g_b.add_edges_from([(nodes[0], nodes[1], "b_1"), (nodes[1], nodes[2], "b_2")]) for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertTrue(retworkx.is_subgraph_isomorphic(g_a, g_b, id_order=id_order)) def test_subgraph_isomorphic_compare_nodes_mismatch_node_data(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3", "a_4"]) g_a.add_edges_from( [ (nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2"), (nodes[0], nodes[3], "a_3"), ] ) nodes = g_b.add_nodes_from(["b_1", "b_2", "b_3"]) g_b.add_edges_from([(nodes[0], nodes[1], "b_1"), (nodes[1], nodes[2], "b_2")]) for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertFalse( retworkx.is_subgraph_isomorphic( g_a, g_b, lambda x, y: x == y, id_order=id_order ) ) def test_subgraph_isomorphic_compare_nodes_identical(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3", "a_4"]) g_a.add_edges_from( [ (nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2"), (nodes[0], nodes[3], "a_3"), ] ) nodes = g_b.add_nodes_from(["a_1", "a_2", "a_3"]) g_b.add_edges_from([(nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2")]) for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertTrue( retworkx.is_subgraph_isomorphic( g_a, g_b, lambda x, y: x == y, id_order=id_order ) ) def test_is_subgraph_isomorphic_nodes_compare_raises(self): g_a = retworkx.PyGraph() nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3"]) g_a.add_edges_from([(nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2")]) def compare_nodes(a, b): raise TypeError("Failure") self.assertRaises( TypeError, retworkx.is_subgraph_isomorphic, (g_a, g_a, compare_nodes), ) def test_subgraph_isomorphic_compare_edges_identical(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3", "a_4"]) g_a.add_edges_from( [ (nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2"), (nodes[0], nodes[3], "a_3"), ] ) nodes = g_b.add_nodes_from(["a_1", "a_2", "a_3"]) g_b.add_edges_from([(nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2")]) for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertTrue( retworkx.is_subgraph_isomorphic( g_a, g_b, edge_matcher=lambda x, y: x == y, id_order=id_order, ) ) def test_subgraph_isomorphic_node_count_not_ge(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() nodes = g_a.add_nodes_from(["a_1", "a_2"]) g_a.add_edges_from([(nodes[0], nodes[1], "a_1")]) nodes = g_b.add_nodes_from(["a_0", "a_1", "a_3"]) g_b.add_edges_from([(nodes[0], nodes[1], "a_1")]) for id_order in [False, True]: with self.subTest(id_order=id_order): self.assertFalse(retworkx.is_subgraph_isomorphic(g_a, g_b, id_order=id_order)) def test_non_induced_subgraph_isomorphic(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() nodes = g_a.add_nodes_from(["a_1", "a_2", "a_3"]) g_a.add_edges_from( [ (nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2"), (nodes[2], nodes[0], "a_3"), ] ) nodes = g_b.add_nodes_from(["a_1", "a_2", "a_3"]) g_b.add_edges_from([(nodes[0], nodes[1], "a_1"), (nodes[1], nodes[2], "a_2")]) for id_order in [False, True]: with self.subTest(id_order=id_order, induced=True): self.assertFalse( retworkx.is_subgraph_isomorphic(g_a, g_b, id_order=id_order, induced=True) ) with self.subTest(id_order=id_order, induced=False): self.assertTrue( retworkx.is_subgraph_isomorphic(g_a, g_b, id_order=id_order, induced=False) ) def test_subgraph_isomorphic_edge_matcher(self): first = retworkx.PyGraph() first.extend_from_weighted_edge_list([(0, 1, "a"), (1, 2, "b"), (2, 0, "c")]) second = retworkx.PyGraph() second.extend_from_weighted_edge_list([(0, 1, "a"), (1, 2, "b")]) self.assertTrue( retworkx.is_subgraph_isomorphic( first, second, induced=False, edge_matcher=lambda x, y: x == y ) ) def test_subgraph_isomorphic_mismatch_edge_data_parallel_edges(self): first = retworkx.PyGraph() first.extend_from_weighted_edge_list([(0, 1, "a"), (0, 1, "f"), (1, 2, "b"), (2, 0, "c")]) second = retworkx.PyGraph() second.extend_from_weighted_edge_list([(0, 1, "a"), (0, 1, "a"), (1, 2, "b")]) self.assertFalse( retworkx.is_subgraph_isomorphic( first, second, id_order=True, edge_matcher=lambda x, y: x == y ) ) def test_subgraph_isomorphic_parallel_edges(self): first = retworkx.PyGraph() first.extend_from_edge_list([(0, 1), (1, 2), (2, 3)]) second = retworkx.PyGraph() second.extend_from_edge_list([(0, 1), (0, 1)]) self.assertFalse(retworkx.is_subgraph_isomorphic(first, second, induced=True)) self.assertFalse(retworkx.is_subgraph_isomorphic(first, second, induced=False)) def test_non_induced_grid_subgraph_isomorphic(self): g_a = retworkx.generators.grid_graph(2, 2) g_b = retworkx.PyGraph() g_b.add_nodes_from([0, 1, 2, 3]) g_b.add_edges_from_no_data([(0, 1), (2, 3)]) self.assertFalse(retworkx.is_subgraph_isomorphic(g_a, g_b, induced=True)) self.assertTrue(retworkx.is_subgraph_isomorphic(g_a, g_b, induced=False)) def test_non_induced_subgraph_isomorphic_parallel_edges(self): first = retworkx.PyGraph() first.extend_from_edge_list([(0, 1), (0, 1), (1, 2), (1, 2)]) second = retworkx.PyGraph() second.extend_from_edge_list([(0, 1), (1, 2), (1, 2)]) self.assertFalse(retworkx.is_subgraph_isomorphic(first, second, induced=True)) self.assertTrue(retworkx.is_subgraph_isomorphic(first, second, induced=False)) def test_subgraph_vf2_mapping(self): graph = retworkx.generators.grid_graph(10, 10) second_graph = retworkx.generators.grid_graph(2, 2) mapping = retworkx.graph_vf2_mapping(graph, second_graph, subgraph=True) self.assertEqual(next(mapping), {0: 0, 1: 1, 10: 2, 11: 3}) def test_subgraph_vf2_all_mappings(self): graph = retworkx.generators.path_graph(3) second_graph = retworkx.generators.path_graph(2) mapping = retworkx.graph_vf2_mapping(graph, second_graph, subgraph=True, id_order=True) self.assertEqual(next(mapping), {0: 0, 1: 1}) self.assertEqual(next(mapping), {0: 1, 1: 0}) self.assertEqual(next(mapping), {2: 1, 1: 0}) self.assertEqual(next(mapping), {1: 1, 2: 0}) def test_subgraph_vf2_mapping_vf2pp(self): graph = retworkx.generators.grid_graph(3, 3) second_graph = retworkx.generators.grid_graph(2, 2) mapping = retworkx.graph_vf2_mapping(graph, second_graph, subgraph=True, id_order=False) self.assertEqual(next(mapping), {4: 0, 3: 2, 0: 3, 1: 1}) def test_vf2pp_remapping(self): temp = retworkx.generators.grid_graph(3, 3) graph = retworkx.PyGraph() dummy = graph.add_node(0) graph.compose(temp, dict()) graph.remove_node(dummy) second_graph = retworkx.generators.grid_graph(2, 2) mapping = retworkx.graph_vf2_mapping(graph, second_graph, subgraph=True, id_order=False) self.assertEqual(next(mapping), {5: 0, 4: 2, 1: 3, 2: 1}) def test_empty_subgraph_vf2_mapping(self): g_a = retworkx.PyGraph() g_b = retworkx.PyGraph() for id_order in [False, True]: with self.subTest(id_order=id_order): mapping = retworkx.graph_vf2_mapping(g_a, g_b, id_order=id_order, subgraph=True) self.assertEqual({}, next(mapping)) def test_subgraph_vf2_mapping_out_size(self): first = retworkx.PyGraph() first.add_nodes_from([0, 1, 2, 3]) first.add_edges_from_no_data([(0, 1), (0, 2), (1, 2), (2, 3)]) second = retworkx.PyGraph() second.add_nodes_from([0, 1, 2, 3]) second.add_edges_from_no_data([(0, 1), (0, 2), (1, 3)]) mapping = retworkx.graph_vf2_mapping( first, second, subgraph=True, id_order=True, induced=False ) self.assertEqual(next(mapping), {0: 0, 1: 2, 2: 1, 3: 3})

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null

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1

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null

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5

3fb657b7dcbf6e746b8b0e491f149af0c7b4df2d

125

py

Python

pyshex/__init__.py

vemonet/PyShEx

0004641fbfefc069be615067dd7e78b19e0d7967

[ "Apache-2.0" ]

null

pyshex/__init__.py

vemonet/PyShEx

0004641fbfefc069be615067dd7e78b19e0d7967

[ "Apache-2.0" ]

null

pyshex/__init__.py

vemonet/PyShEx

0004641fbfefc069be615067dd7e78b19e0d7967

[ "Apache-2.0" ]

1

2019-03-08T15:38:22.000Z

from pyshex.prefixlib import PrefixLibrary, standard_prefixes, known_prefixes from pyshex.shex_evaluator import ShExEvaluator

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3fba71e81298f542468f6ac9ce4ce3a640b4d7ff

37

py

Python

medimodule/Lung/__init__.py

daeun02/MI2RLNet

55f32e3908dc1d5fa6100f9d9fccd23a2636adbb

[ "Apache-2.0" ]

null

medimodule/Lung/__init__.py

daeun02/MI2RLNet

55f32e3908dc1d5fa6100f9d9fccd23a2636adbb

[ "Apache-2.0" ]

null

medimodule/Lung/__init__.py

daeun02/MI2RLNet

55f32e3908dc1d5fa6100f9d9fccd23a2636adbb

[ "Apache-2.0" ]

null

from .module import LungSegmentation

18.5

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null

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null

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5

b78e20bf9b58829d78aff51211a39331a19b298e

332

py

Python

talks-articles/languages-n-runtimes/python/learnpythonthehardway/ex08.py

abhishekkr/tutorials_as_code

f355dc62a5025b710ac6d4a6ac2f9610265fad54

[ "MIT" ]

37

2015-02-01T23:16:39.000Z

2021-12-22T16:50:48.000Z

talks-articles/languages-n-runtimes/python/learnpythonthehardway/ex08.py

abhishekkr/tutorials_as_code

f355dc62a5025b710ac6d4a6ac2f9610265fad54

[ "MIT" ]

1

2017-03-02T04:55:48.000Z

2018-01-14T10:51:11.000Z

talks-articles/languages-n-runtimes/python/learnpythonthehardway/ex08.py

abhishekkr/tutorials_as_code

f355dc62a5025b710ac6d4a6ac2f9610265fad54

[ "MIT" ]

15

2015-03-02T08:09:01.000Z

2021-06-10T03:25:41.000Z

# -*- coding: utf-8 -*- # printing, printing..... formatter = "%r %r %r %r" print formatter % (1, 2, 3, 4) print formatter % ("one", "two", "three", "four") print formatter % (True, True, False, False) print formatter % (formatter, formatter, formatter, formatter) print formatter % ( '123', 'abc', 456, __name__)

22.133333

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1

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1

0

5

b7bd6f331eaa47fb18f9626ea1a44c055f3b5114

2,857

py

Python

setup.py

bhill-slac/cameralink-gateway

61e85fddee91b3f2cd1f4c89cd822e29ae8e6a34

[ "BSD-3-Clause-LBNL" ]

3

2019-03-28T04:33:30.000Z

2021-07-21T08:32:45.000Z

setup.py

bhill-slac/cameralink-gateway

61e85fddee91b3f2cd1f4c89cd822e29ae8e6a34

[ "BSD-3-Clause-LBNL" ]

7

2020-01-28T10:10:58.000Z

2021-10-19T23:40:09.000Z

setup.py

bhill-slac/cameralink-gateway

61e85fddee91b3f2cd1f4c89cd822e29ae8e6a34

[ "BSD-3-Clause-LBNL" ]

5

2019-07-12T09:29:37.000Z

2021-04-29T23:16:46.000Z

from setuptools import setup # use softlinks to make the various "board-support-package" submodules # look like subpackages. Then __init__.py will modify # sys.path so that the correct "local" versions of surf etc. are # picked up. A better approach would be using relative imports # in the submodules, but that's more work. -cpo setup( name = 'cameralink_gateway', description = 'LCLS II cameralink package', packages = [ 'cameralink_gateway', 'cameralink_gateway.surf', 'cameralink_gateway.surf.misc', 'cameralink_gateway.surf.ethernet.mac', 'cameralink_gateway.surf.ethernet.xaui', 'cameralink_gateway.surf.ethernet.gige', 'cameralink_gateway.surf.ethernet.ten_gig', 'cameralink_gateway.surf.ethernet', 'cameralink_gateway.surf.ethernet.udp', 'cameralink_gateway.surf.protocols', 'cameralink_gateway.surf.protocols.pgp', 'cameralink_gateway.surf.protocols.ssp', 'cameralink_gateway.surf.protocols.rssi', 'cameralink_gateway.surf.protocols.jesd204b', 'cameralink_gateway.surf.protocols.ssi', 'cameralink_gateway.surf.protocols.i2c', 'cameralink_gateway.surf.protocols.batcher', 'cameralink_gateway.surf.protocols.clink', 'cameralink_gateway.surf.xilinx', 'cameralink_gateway.surf.devices.microchip', 'cameralink_gateway.surf.devices.ti', 'cameralink_gateway.surf.devices', 'cameralink_gateway.surf.devices.transceivers', 'cameralink_gateway.surf.devices.analog_devices', 'cameralink_gateway.surf.devices.micron', 'cameralink_gateway.surf.devices.linear', 'cameralink_gateway.surf.devices.nxp', 'cameralink_gateway.surf.devices.cypress', 'cameralink_gateway.surf.devices.silabs', 'cameralink_gateway.surf.devices.intel', 'cameralink_gateway.surf.axi', 'cameralink_gateway.l2si_core', 'cameralink_gateway.LclsTimingCore', 'cameralink_gateway.axipcie', 'cameralink_gateway.lcls2_pgp_fw_lib', 'cameralink_gateway.lcls2_pgp_fw_lib.shared', 'cameralink_gateway.ClinkFeb', ], package_dir = { 'cameralink_gateway': 'firmware/python/cameralink_gateway', 'cameralink_gateway.surf': 'firmware/submodules/surf/python/surf', 'cameralink_gateway.axipcie': 'firmware/submodules/axi-pcie-core/python/axipcie', 'cameralink_gateway.LclsTimingCore': 'firmware/submodules/lcls-timing-core/python/LclsTimingCore', 'cameralink_gateway.lcls2_pgp_fw_lib': 'firmware/submodules/lcls2-pgp-fw-lib/python/lcls2_pgp_fw_lib', 'cameralink_gateway.ClinkFeb': 'firmware/submodules/clink-gateway-fw-lib/python/ClinkFeb', 'cameralink_gateway.l2si_core': 'firmware/submodules/l2si-core/python/l2si_core', } )

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null

1

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1

null

0

1

0

5

b7c61e5f4bd66f67283e5293b4139e161808fef1

26,457

py

Python

Thank you Obama!/convertCSV.py

rahulShrestha89/493_fall16_finalSet

719973dff1aafaeca108422e1697fd0a210b3ff7

[ "BSD-Source-Code" ]

null

Thank you Obama!/convertCSV.py

rahulShrestha89/493_fall16_finalSet

719973dff1aafaeca108422e1697fd0a210b3ff7

[ "BSD-Source-Code" ]

null

Thank you Obama!/convertCSV.py

rahulShrestha89/493_fall16_finalSet

719973dff1aafaeca108422e1697fd0a210b3ff7

[ "BSD-Source-Code" ]

null

import csv, pickle emoDict = pickle.load(open('monthMoodsDec.pkl', 'rb')) urlDict = pickle.load(open('faceUrls.pkl', 'rb')) #emoDict = { "01/2009" : [0.1, 0.2, 0.3, 0.01, 0.02, 0.03, 0.04, 0.08], # "02/2009" : [0.5, 0.6, 0.7, 0.8, 0.09, 0.01, 0.042, 0.085] # } #urlDict = { "01/2009" : 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", # "02/2009" : 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" # } with open('names.csv', 'w') as csvfile: fieldnames = ['Date', 'Anger', 'Contempt', 'Disgust', 'Fear', 'Happiness', 'Neutral', 'Sadness', 'Surprise'] writer = csv.DictWriter(csvfile, fieldnames=fieldnames) writer.writeheader() for key in emoDict: emoList = emoDict[key] if len(emoList) == 0: writer.writerow({'Date': key, 'Anger': 0.0, 'Contempt': 0.0, 'Disgust': 0.0, 'Fear': 0.0, 'Happiness': 0.0, 'Neutral': 0.0, 'Sadness': 0.0, 'Surprise': 0.0}) else: writer.writerow({'Date':key,'Anger':emoList[0],'Contempt':emoList[1],'Disgust':emoList[2],'Fear':emoList[3],'Happiness':emoList[4],'Neutral':emoList[5],'Sadness':emoList[6],'Surprise':emoList[7]})

979.888889

13,875

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824

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30.779126

0.865291

0.000631

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0.001341

0.005836

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0.006085

26,457

26

13,876

1,017.576923

0.815828

0.968326

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0.264423

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1

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1

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false

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0.076923

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5

b7c927782651dd3289e7cbfd1962353ac143ec7d

32,417

py

Python

thread_lab.py

Locottus/Python

8a6a864c54371fff2b9f34c3c2a69a387c6266f1

[ "MIT" ]

null

thread_lab.py

Locottus/Python

8a6a864c54371fff2b9f34c3c2a69a387c6266f1

[ "MIT" ]

null

thread_lab.py

Locottus/Python

8a6a864c54371fff2b9f34c3c2a69a387c6266f1

[ "MIT" ]

null

import arcpy,os,sys,thread,time def Carga_DGN(DGN,Gdbtmp,CurrDir): Gdbtmp = CurrDir + r'\' + Gdbtmp.rstrip('.RED') try: arcpy.QuickImport_interop("IGDS," + DGN + ","RUNTIME_MACROS,""METAFILE,designScanLevelNames,_XPNDCELL,YES,_PRESERVE_INSERTS,NO,EXPAND_UNNAMED_CELLS,NO,PRESERVE_UNNAMEDCELL_INSERTS,NO,SPLIT_MULTITEXT,YES,_TEXTTAGS,NO,EXPLODE_DIMENSION_ELEM,YES,_DROP_COMPLEX,NO,READ_XREF_FILES,NO,READ_XREF_UPTO_FIRST_LVL,NO,_IGDS_MSLINKS,YES,_IGDS_FRAMME,YES,_IN_UNITS,IGDS_MASTER_UNITS,OVERRIDE_GLOBAL_ORIGIN,NO,_UOR_GLOBAL_ORIGIN_X,,_UOR_GLOBAL_ORIGIN_Y,,APPLY_WORLD_FILE,YES,_USE_LEVEL_NAMES,yes,_MERGE_SCHEMAS,YES"",META_MACROS,""SourceMETAFILE,designScanLevelNames,Source_XPNDCELL,YES,Source_PRESERVE_INSERTS,NO,SourceEXPAND_UNNAMED_CELLS,NO,SourcePRESERVE_UNNAMEDCELL_INSERTS,NO,SourceSPLIT_MULTITEXT,YES,Source_TEXTTAGS,NO,SourceEXPLODE_DIMENSION_ELEM,YES,Source_DROP_COMPLEX,NO,SourceREAD_XREF_FILES,NO,SourceREAD_XREF_UPTO_FIRST_LVL,NO,Source_IGDS_MSLINKS,YES,Source_IGDS_FRAMME,YES,Source_IN_UNITS,IGDS_MASTER_UNITS,SourceOVERRIDE_GLOBAL_ORIGIN,NO,Source_UOR_GLOBAL_ORIGIN_X,,Source_UOR_GLOBAL_ORIGIN_Y,,SourceAPPLY_WORLD_FILE,YES,Source_USE_LEVEL_NAMES,yes"",METAFILE,designScanLevelNames,COORDSYS,""""""ESRIWKT|WGS_1984_UTM_Zone_15N|PROJCS[""""WGS_1984_UTM_Zone_15N"""",GEOGCS[""""GCS_WGS_1984"""",DATUM[""""D_WGS_1984"""",SPHEROID[""""WGS_1984"""",6378137.0,298.257223563]],PRIMEM[""""Greenwich"""",0.0],UNIT[""""Degree"""",0.0174532925199433]],PROJECTION[""""Transverse_Mercator""""],PARAMETER[""""False_Easting"""",500000.0],PARAMETER[""""False_Northing"""",0.0],PARAMETER[""""Central_Meridian"""",-93.0],PARAMETER[""""Scale_Factor"""",0.9996],PARAMETER[""""Latitude_Of_Origin"""",0.0],UNIT[""""Meter"""",1.0]]"""""",IDLIST,,__FME_DATASET_IS_SOURCE__,true"", Gdbtmp ) except Exception, e: print arcpy.GetMessages() thread.start_new_thread(Carga_DGN,(r'CTZ10.RED',r'CTZ10',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ100.RED',r'CTZ100',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ101.RED',r'CTZ101',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ102.RED',r'CTZ102',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ103.RED',r'CTZ103',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ104.RED',r'CTZ104',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ105.RED',r'CTZ105',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ106.RED',r'CTZ106',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ107.RED',r'CTZ107',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ108.RED',r'CTZ108',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ109.RED',r'CTZ109',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ11.RED',r'CTZ11',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ110.RED',r'CTZ110',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ111.RED',r'CTZ111',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ112.RED',r'CTZ112',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ113.RED',r'CTZ113',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ114.RED',r'CTZ114',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ115.RED',r'CTZ115',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ116.RED',r'CTZ116',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ117.RED',r'CTZ117',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ118.RED',r'CTZ118',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ119.RED',r'CTZ119',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ12.RED',r'CTZ12',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ120.RED',r'CTZ120',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ121.RED',r'CTZ121',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ122.RED',r'CTZ122',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ123.RED',r'CTZ123',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ124.RED',r'CTZ124',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ125.RED',r'CTZ125',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ126.RED',r'CTZ126',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ127.RED',r'CTZ127',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ128.RED',r'CTZ128',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ129.RED',r'CTZ129',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ13.RED',r'CTZ13',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ130.RED',r'CTZ130',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ131.RED',r'CTZ131',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ132.RED',r'CTZ132',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ133.RED',r'CTZ133',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ134.RED',r'CTZ134',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ135.RED',r'CTZ135',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ136.RED',r'CTZ136',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ137.RED',r'CTZ137',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ138.RED',r'CTZ138',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ139.RED',r'CTZ139',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ14.RED',r'CTZ14',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ140.RED',r'CTZ140',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ141.RED',r'CTZ141',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ142.RED',r'CTZ142',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ143.RED',r'CTZ143',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ144.RED',r'CTZ144',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ145.RED',r'CTZ145',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ146.RED',r'CTZ146',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ147.RED',r'CTZ147',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ148.RED',r'CTZ148',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ149.RED',r'CTZ149',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ15.RED',r'CTZ15',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ150.RED',r'CTZ150',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ151.RED',r'CTZ151',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ152.RED',r'CTZ152',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ153.RED',r'CTZ153',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ154.RED',r'CTZ154',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ155.RED',r'CTZ155',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ156.RED',r'CTZ156',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ157.RED',r'CTZ157',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ158.RED',r'CTZ158',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ159.RED',r'CTZ159',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ16.RED',r'CTZ16',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ160.RED',r'CTZ160',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ161.RED',r'CTZ161',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ162.RED',r'CTZ162',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ163.RED',r'CTZ163',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ164.RED',r'CTZ164',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ165.RED',r'CTZ165',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ166.RED',r'CTZ166',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ167.RED',r'CTZ167',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ168.RED',r'CTZ168',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ169.RED',r'CTZ169',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ17.RED',r'CTZ17',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ170.RED',r'CTZ170',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ171.RED',r'CTZ171',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ172.RED',r'CTZ172',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ173.RED',r'CTZ173',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ174.RED',r'CTZ174',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ175.RED',r'CTZ175',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ176.RED',r'CTZ176',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ177.RED',r'CTZ177',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ178.RED',r'CTZ178',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ179.RED',r'CTZ179',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ18.RED',r'CTZ18',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ180.RED',r'CTZ180',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ181.RED',r'CTZ181',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ182.RED',r'CTZ182',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ183.RED',r'CTZ183',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ184.RED',r'CTZ184',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ185.RED',r'CTZ185',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ186.RED',r'CTZ186',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ187.RED',r'CTZ187',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ188.RED',r'CTZ188',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ189.RED',r'CTZ189',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ19.RED',r'CTZ19',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ190.RED',r'CTZ190',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ191.RED',r'CTZ191',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ192.RED',r'CTZ192',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ193.RED',r'CTZ193',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ194.RED',r'CTZ194',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ195.RED',r'CTZ195',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ196.RED',r'CTZ196',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ197.RED',r'CTZ197',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ198.RED',r'CTZ198',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ199.RED',r'CTZ199',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ20.RED',r'CTZ20',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ200.RED',r'CTZ200',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ201.RED',r'CTZ201',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ202.RED',r'CTZ202',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ203.RED',r'CTZ203',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ204.RED',r'CTZ204',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ205.RED',r'CTZ205',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ206.RED',r'CTZ206',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ207.RED',r'CTZ207',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ208.RED',r'CTZ208',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ209.RED',r'CTZ209',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ21.RED',r'CTZ21',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ210.RED',r'CTZ210',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ211.RED',r'CTZ211',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ212.RED',r'CTZ212',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ213.RED',r'CTZ213',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ214.RED',r'CTZ214',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ215.RED',r'CTZ215',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ216.RED',r'CTZ216',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ217.RED',r'CTZ217',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ218.RED',r'CTZ218',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ219.RED',r'CTZ219',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ22.RED',r'CTZ22',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ220.RED',r'CTZ220',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ221.RED',r'CTZ221',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ222.RED',r'CTZ222',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ223.RED',r'CTZ223',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ224.RED',r'CTZ224',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ225.RED',r'CTZ225',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ226.RED',r'CTZ226',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ227.RED',r'CTZ227',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ228.RED',r'CTZ228',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ229.RED',r'CTZ229',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ23.RED',r'CTZ23',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ230.RED',r'CTZ230',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ231.RED',r'CTZ231',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ232.RED',r'CTZ232',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ233.RED',r'CTZ233',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ234.RED',r'CTZ234',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ235.RED',r'CTZ235',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ236.RED',r'CTZ236',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ237.RED',r'CTZ237',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ238.RED',r'CTZ238',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ239.RED',r'CTZ239',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ24.RED',r'CTZ24',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ240.RED',r'CTZ240',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ241.RED',r'CTZ241',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ242.RED',r'CTZ242',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ243.RED',r'CTZ243',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ244.RED',r'CTZ244',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ245.RED',r'CTZ245',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ246.RED',r'CTZ246',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ247.RED',r'CTZ247',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ248.RED',r'CTZ248',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ249.RED',r'CTZ249',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ25.RED',r'CTZ25',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ250.RED',r'CTZ250',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ251.RED',r'CTZ251',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ252.RED',r'CTZ252',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ253.RED',r'CTZ253',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ254.RED',r'CTZ254',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ255.RED',r'CTZ255',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ256.RED',r'CTZ256',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ257.RED',r'CTZ257',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ258.RED',r'CTZ258',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ259.RED',r'CTZ259',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ26.RED',r'CTZ26',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ260.RED',r'CTZ260',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ261.RED',r'CTZ261',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ262.RED',r'CTZ262',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ263.RED',r'CTZ263',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ264.RED',r'CTZ264',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ265.RED',r'CTZ265',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ266.RED',r'CTZ266',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ267.RED',r'CTZ267',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ268.RED',r'CTZ268',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ269.RED',r'CTZ269',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ27.RED',r'CTZ27',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ270.RED',r'CTZ270',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ271.RED',r'CTZ271',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ272.RED',r'CTZ272',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ273.RED',r'CTZ273',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ274.RED',r'CTZ274',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ275.RED',r'CTZ275',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ276.RED',r'CTZ276',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ277.RED',r'CTZ277',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ278.RED',r'CTZ278',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ279.RED',r'CTZ279',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ28.RED',r'CTZ28',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ280.RED',r'CTZ280',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ281.RED',r'CTZ281',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ282.RED',r'CTZ282',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ283.RED',r'CTZ283',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ284.RED',r'CTZ284',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ285.RED',r'CTZ285',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ286.RED',r'CTZ286',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ287.RED',r'CTZ287',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ288.RED',r'CTZ288',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ289.RED',r'CTZ289',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ29.RED',r'CTZ29',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ290.RED',r'CTZ290',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ291.RED',r'CTZ291',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ292.RED',r'CTZ292',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ293.RED',r'CTZ293',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ294.RED',r'CTZ294',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ295.RED',r'CTZ295',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ296.RED',r'CTZ296',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ297.RED',r'CTZ297',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ298.RED',r'CTZ298',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ299.RED',r'CTZ299',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ30.RED',r'CTZ30',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ300.RED',r'CTZ300',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ301.RED',r'CTZ301',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ302.RED',r'CTZ302',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ303.RED',r'CTZ303',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ304.RED',r'CTZ304',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ305.RED',r'CTZ305',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ306.RED',r'CTZ306',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ307.RED',r'CTZ307',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ308.RED',r'CTZ308',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ309.RED',r'CTZ309',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ31.RED',r'CTZ31',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ310.RED',r'CTZ310',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ311.RED',r'CTZ311',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ312.RED',r'CTZ312',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ313.RED',r'CTZ313',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ314.RED',r'CTZ314',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ315.RED',r'CTZ315',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ316.RED',r'CTZ316',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ317.RED',r'CTZ317',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ318.RED',r'CTZ318',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ319.RED',r'CTZ319',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ32.RED',r'CTZ32',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ320.RED',r'CTZ320',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ321.RED',r'CTZ321',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ322.RED',r'CTZ322',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ323.RED',r'CTZ323',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ324.RED',r'CTZ324',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ325.RED',r'CTZ325',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ326.RED',r'CTZ326',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ327.RED',r'CTZ327',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ328.RED',r'CTZ328',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ329.RED',r'CTZ329',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ33.RED',r'CTZ33',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ330.RED',r'CTZ330',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ331.RED',r'CTZ331',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ332.RED',r'CTZ332',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ333.RED',r'CTZ333',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ334.RED',r'CTZ334',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ335.RED',r'CTZ335',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ336.RED',r'CTZ336',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ337.RED',r'CTZ337',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ338.RED',r'CTZ338',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ339.RED',r'CTZ339',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ34.RED',r'CTZ34',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ340.RED',r'CTZ340',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ341.RED',r'CTZ341',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ342.RED',r'CTZ342',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ343.RED',r'CTZ343',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ344.RED',r'CTZ344',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ345.RED',r'CTZ345',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ346.RED',r'CTZ346',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ347.RED',r'CTZ347',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ348.RED',r'CTZ348',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ349.RED',r'CTZ349',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ35.RED',r'CTZ35',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ350.RED',r'CTZ350',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ351.RED',r'CTZ351',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ352.RED',r'CTZ352',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ353.RED',r'CTZ353',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ354.RED',r'CTZ354',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ355.RED',r'CTZ355',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ356.RED',r'CTZ356',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ357.RED',r'CTZ357',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ358.RED',r'CTZ358',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ359.RED',r'CTZ359',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ36.RED',r'CTZ36',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ360.RED',r'CTZ360',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ361.RED',r'CTZ361',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ362.RED',r'CTZ362',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ363.RED',r'CTZ363',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ364.RED',r'CTZ364',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ365.RED',r'CTZ365',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ366.RED',r'CTZ366',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ367.RED',r'CTZ367',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ368.RED',r'CTZ368',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ369.RED',r'CTZ369',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ37.RED',r'CTZ37',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ370.RED',r'CTZ370',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ371.RED',r'CTZ371',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ372.RED',r'CTZ372',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ373.RED',r'CTZ373',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ374.RED',r'CTZ374',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ375.RED',r'CTZ375',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ376.RED',r'CTZ376',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ377.RED',r'CTZ377',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ378.RED',r'CTZ378',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ379.RED',r'CTZ379',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ38.RED',r'CTZ38',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ380.RED',r'CTZ380',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ381.RED',r'CTZ381',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ382.RED',r'CTZ382',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ383.RED',r'CTZ383',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ384.RED',r'CTZ384',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ385.RED',r'CTZ385',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ386.RED',r'CTZ386',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ387.RED',r'CTZ387',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ388.RED',r'CTZ388',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ389.RED',r'CTZ389',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ39.RED',r'CTZ39',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ390.RED',r'CTZ390',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ391.RED',r'CTZ391',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ392.RED',r'CTZ392',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ393.RED',r'CTZ393',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ394.RED',r'CTZ394',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ395.RED',r'CTZ395',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ396.RED',r'CTZ396',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ397.RED',r'CTZ397',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ398.RED',r'CTZ398',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ399.RED',r'CTZ399',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ4.RED',r'CTZ4',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ40.RED',r'CTZ40',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ400.RED',r'CTZ400',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ401.RED',r'CTZ401',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ402.RED',r'CTZ402',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ403.RED',r'CTZ403',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ404.RED',r'CTZ404',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ405.RED',r'CTZ405',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ406.RED',r'CTZ406',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ407.RED',r'CTZ407',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ408.RED',r'CTZ408',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ409.RED',r'CTZ409',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ41.RED',r'CTZ41',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ410.RED',r'CTZ410',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ411.RED',r'CTZ411',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ412.RED',r'CTZ412',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ413.RED',r'CTZ413',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ414.RED',r'CTZ414',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ415.RED',r'CTZ415',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ416.RED',r'CTZ416',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ417.RED',r'CTZ417',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ418.RED',r'CTZ418',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ419.RED',r'CTZ419',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ42.RED',r'CTZ42',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ420.RED',r'CTZ420',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ421.RED',r'CTZ421',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ422.RED',r'CTZ422',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ423.RED',r'CTZ423',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ424.RED',r'CTZ424',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ425.RED',r'CTZ425',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ426.RED',r'CTZ426',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ427.RED',r'CTZ427',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ428.RED',r'CTZ428',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ429.RED',r'CTZ429',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ43.RED',r'CTZ43',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ430.RED',r'CTZ430',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ431.RED',r'CTZ431',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ44.RED',r'CTZ44',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ45.RED',r'CTZ45',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ46.RED',r'CTZ46',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ47.RED',r'CTZ47',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ48.RED',r'CTZ48',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ49.RED',r'CTZ49',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ5.RED',r'CTZ5',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ50.RED',r'CTZ50',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ51.RED',r'CTZ51',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ52.RED',r'CTZ52',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ53.RED',r'CTZ53',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ54.RED',r'CTZ54',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ55.RED',r'CTZ55',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ56.RED',r'CTZ56',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ57.RED',r'CTZ57',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ58.RED',r'CTZ58',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ59.RED',r'CTZ59',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ60.RED',r'CTZ60',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ61.RED',r'CTZ61',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ62.RED',r'CTZ62',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ63.RED',r'CTZ63',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ64.RED',r'CTZ64',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ65.RED',r'CTZ65',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ66.RED',r'CTZ66',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ67.RED',r'CTZ67',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ68.RED',r'CTZ68',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ69.RED',r'CTZ69',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ7.RED',r'CTZ7',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ70.RED',r'CTZ70',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ71.RED',r'CTZ71',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ72.RED',r'CTZ72',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ73.RED',r'CTZ73',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ74.RED',r'CTZ74',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ75.RED',r'CTZ75',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ76.RED',r'CTZ76',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ77.RED',r'CTZ77',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ78.RED',r'CTZ78',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ79.RED',r'CTZ79',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ8.RED',r'CTZ8',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ80.RED',r'CTZ80',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ81.RED',r'CTZ81',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ82.RED',r'CTZ82',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ83.RED',r'CTZ83',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ84.RED',r'CTZ84',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ85.RED',r'CTZ85',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ86.RED',r'CTZ86',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ87.RED',r'CTZ87',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ88.RED',r'CTZ88',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ89.RED',r'CTZ89',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ9.RED',r'CTZ9',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ90.RED',r'CTZ90',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ91.RED',r'CTZ91',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ92.RED',r'CTZ92',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ93.RED',r'CTZ93',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ94.RED',r'CTZ94',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ95.RED',r'CTZ95',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ96.RED',r'CTZ96',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ97.RED',r'CTZ97',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ98.RED',r'CTZ98',r'C:\DGN')) thread.start_new_thread(Carga_DGN,(r'CTZ99.RED',r'CTZ99',r'C:\DGN'))

74.693548

1,674

0.7381

6,239

32,417

3.610995

0.088796

0.151982

0.265347

0.379067

0.649252

0.644192

0.642905

0

0.077653

0.028318

32,417

434

1,675

74.693548

0.637576

0

0.300578

0.004658

0

null

0

0.004608

null

0.002304

0

null

0

1

0

1

0

1

0

null

0

1

0

5

4d6780740354f89eb0777e653ebc76687fe1a1de

177

py

Python

src/products/models/__init__.py

tlgtaa/education-backend

86f8af315f9cff2c1fd19406899d593fc0852124

[ "MIT" ]

1

2021-03-03T19:51:24.000Z

src/products/models/__init__.py

tlgtaa/education-backend

86f8af315f9cff2c1fd19406899d593fc0852124

[ "MIT" ]

null

src/products/models/__init__.py

tlgtaa/education-backend

86f8af315f9cff2c1fd19406899d593fc0852124

[ "MIT" ]

null

from products.models.bundle import Bundle from products.models.course import Course from products.models.record import Record __all__ = [ Bundle, Course, Record, ]

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177

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1

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0

null

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1

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5

4d84a444f2a53283c6de1b3e601f11d5f427c1d0

54

py

Python

cwltool/__main__.py

wtsi-hgi/cwltool

6d3e9f0b0f2c4fb78b76eb4270451f29515322f3

[ "Apache-2.0" ]

2

2017-07-06T13:25:23.000Z

2017-07-06T13:26:15.000Z

cwltool/__main__.py

igormusinov/cwl_parser_python3

5b2cd24496c424fbe0923d6b1f715076fab1ca4c

[ "Apache-2.0" ]

1

2018-05-10T06:45:21.000Z

cwltool/__main__.py

wtsi-hgi/cwltool

6d3e9f0b0f2c4fb78b76eb4270451f29515322f3

[ "Apache-2.0" ]

null

import sys from . import main sys.exit(main.main())

9

21

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9

54

4.222222

0.555556

0

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54

5

22

10.8

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true

0

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1

0

null

0

1

0

1

0

1

0

5

4dba9ccea667444659f3e91b54e09326de06427b

211

py

Python

bitmovin/resources/models/encodings/pertitle/__init__.py

koraygulcu/bitmovin-python

e8b896e2cb44142c91828533b8fb02f20eb0fbe5

[ "Unlicense" ]

null

bitmovin/resources/models/encodings/pertitle/__init__.py

koraygulcu/bitmovin-python

e8b896e2cb44142c91828533b8fb02f20eb0fbe5

[ "Unlicense" ]

null

bitmovin/resources/models/encodings/pertitle/__init__.py

koraygulcu/bitmovin-python

e8b896e2cb44142c91828533b8fb02f20eb0fbe5

[ "Unlicense" ]

null

from .auto_representation import AutoRepresentation from .per_title import PerTitle from .h264_per_title_configuration import H264PerTitleConfiguration from .per_title_configuration import PerTitleConfiguration

42.2

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211

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211

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null

0

1

0

1

0

5

4dd37f4b86bc0f15bd5ee2c15c35b793b1cfd681

67

py

Python

src/experiment/experiment3.py

RiemanBall/hello-world

03d7705eb258e43928b365bfa3a3947c97ac20ce

[ "MIT" ]

null

src/experiment/experiment3.py

RiemanBall/hello-world

03d7705eb258e43928b365bfa3a3947c97ac20ce

[ "MIT" ]

null

src/experiment/experiment3.py

RiemanBall/hello-world

03d7705eb258e43928b365bfa3a3947c97ac20ce

[ "MIT" ]

null

import numpy as np class Experiement3: def __init__(self): pass

13.4

20

0.761194

10

67

4.7

1

0

0.018182

0.179104

67

5

21

13.4

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0

1

0.25

false

0.25

0

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1

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null

0

1

0

1

0

1

0

5

15024239aff3ee3a58f9078fc02f364dbb174723

70

py

Python

src/processing/__init__.py

mafshar/xray-ensemble

ad3edaad1dab192b29ab0a0174914b014eef5e0d

[ "Apache-2.0" ]

4

2018-05-20T05:04:20.000Z

2021-03-12T02:42:18.000Z

src/processing/__init__.py

mafshar/xray-ensemble

ad3edaad1dab192b29ab0a0174914b014eef5e0d

[ "Apache-2.0" ]

1

2018-03-29T04:32:23.000Z

src/processing/__init__.py

mafshar/xray-ensemble

ad3edaad1dab192b29ab0a0174914b014eef5e0d

[ "Apache-2.0" ]

1

2019-01-28T10:12:53.000Z

# import classes import datasets import utils import transformations

11.666667

22

0.842857

8

70

7.375

0.625

0

0.142857

70

5

23

14

0.983333

0.2

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1

0

true

0

1

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1

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null

0

1

0

null

0

1

0

1

0

1

0

5

15097820bf46c79f1872f2df781eeb89d355ff74

127

py

Python

python/ql/test/3/query-tests/Classes/equals-ne/test.py

vadi2/codeql

a806a4f08696d241ab295a286999251b56a6860c

[ "MIT" ]

4,036

2020-04-29T00:09:57.000Z

2022-03-31T14:16:38.000Z

python/ql/test/3/query-tests/Classes/equals-ne/test.py

vadi2/codeql

a806a4f08696d241ab295a286999251b56a6860c

[ "MIT" ]

2,970

2020-04-28T17:24:18.000Z

2022-03-31T22:40:46.000Z

python/ql/test/3/query-tests/Classes/equals-ne/test.py

ScriptBox99/github-codeql

2ecf0d3264db8fb4904b2056964da469372a235c

[ "MIT" ]

794

2020-04-29T00:28:25.000Z

2022-03-30T08:21:46.000Z

class OK: def __eq__(self, other): return False class NotOK2: def __ne__(self, other): return True

11.545455

28

0.590551

16

127

4.1875

0.6875

0.268657

0.447761

0

0.011765

0.330709

127

10

29

12.7

0.776471

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false

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0

null

1

0

null

0

1

0

1

0

5

12b5ba070771b364a307852a815dc7d8912f7bd7

463

py

Python

Scripts/bitflag.py

rockbyo5/Skyrim-NX-Toolkit

0097c1da6f2b76751884355ee688d11dffd1172c

[ "MIT" ]

84

2018-08-07T12:37:35.000Z

2022-01-07T09:16:49.000Z

Scripts/bitflag.py

Lord-Akkrand/SkyrimNX

22d5054af694337e9e7665dde86cb5af5bb78192

[ "MIT" ]

32

2018-08-07T00:25:02.000Z

2021-10-06T03:25:56.000Z

Scripts/bitflag.py

Lord-Akkrand/SkyrimNX

22d5054af694337e9e7665dde86cb5af5bb78192

[ "MIT" ]

11

2018-09-12T00:05:08.000Z

2021-01-28T18:51:40.000Z

#! /usr/bin/env python # -*- coding: utf-8 -*- class BitFlag(object): def __init__(self, *args): if len(args)==0: self.value = 0 else: self.value = 0 for val in args: SetFlag(self, val) def IsSet(self, flag): return (self.value & flag) != 0 def SetFlag(self, flag): self.value = self.value | flag return self.value def UnsetFlag(self, flag): self.value = flags & ~flag return self.value def GetValue(self): return self.value

21.045455

33

0.639309

70

463

4.171429

0.414286

0.277397

0.205479

0.195205

0.150685

0

0.013736

0.213823

463

22

34

21.045455

0.788462

0.092873

0

0.277778

0

1

0.277778

false

0

0.111111

0.555556

0

null

1

0

null

0

1

0

1

0

5

12d0e6089ccd6084389fc57286d38ae89dfc6cb2

166

py

Python

queries.py

dev-easyshares/company

61842839121f308619c59a8f52ab76c8b9dcdd30

[ "MIT" ]

null

queries.py

dev-easyshares/company

61842839121f308619c59a8f52ab76c8b9dcdd30

[ "MIT" ]

null

queries.py

dev-easyshares/company

61842839121f308619c59a8f52ab76c8b9dcdd30

[ "MIT" ]

null

from django.db import models from django.db.models.functions import Cast, Coalesce from datetime import datetime date_real = Coalesce('date_report', 'date_assembly')

33.2

53

0.819277

24

166

5.541667

0.541667

0.150376

0.180451

0

0.10241

166

5

54

33.2

0.892617

0

0.143713

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false

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0.75

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null

0

1

0

1

0

null

0

1

0

1

0

5

42207e130486e77d17faaa52d371317291facdad

19,854

py

Python

pyzoo/test/zoo/orca/learn/spark/test_estimator_for_spark.py

thalvari/analytics-zoo

4f4c5095c3db9363f5a23ca312a95bbdc6a3db91

[ "Apache-2.0" ]

1

2021-06-06T02:26:15.000Z

pyzoo/test/zoo/orca/learn/spark/test_estimator_for_spark.py

thalvari/analytics-zoo

4f4c5095c3db9363f5a23ca312a95bbdc6a3db91

[ "Apache-2.0" ]

null

pyzoo/test/zoo/orca/learn/spark/test_estimator_for_spark.py

thalvari/analytics-zoo

4f4c5095c3db9363f5a23ca312a95bbdc6a3db91

[ "Apache-2.0" ]

2

2020-09-10T04:24:37.000Z

2021-06-06T02:26:47.000Z

# # Copyright 2018 Analytics Zoo Authors. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # import os import shutil import tempfile from unittest import TestCase import numpy as np import tensorflow as tf from bigdl.optim.optimizer import SeveralIteration from pyspark.sql.context import SQLContext import zoo.orca.data.pandas from zoo import init_nncontext from zoo.orca.data.tf.data import Dataset from zoo.orca.learn.tf.estimator import Estimator from zoo.orca.learn.tf.utils import save_tf_checkpoint, load_tf_checkpoint, get_checkpoint_state resource_path = os.path.join(os.path.split(__file__)[0], "../../../resources") class SimpleModel(object): def __init__(self): self.user = tf.placeholder(dtype=tf.int32, shape=(None,)) self.item = tf.placeholder(dtype=tf.int32, shape=(None,)) self.label = tf.placeholder(dtype=tf.int32, shape=(None,)) feat = tf.stack([self.user, self.item], axis=1) self.logits = tf.layers.dense(tf.to_float(feat), 2) self.loss = tf.reduce_mean(tf.losses.sparse_softmax_cross_entropy(logits=self.logits, labels=self.label)) class TestEstimatorForGraph(TestCase): def test_estimator_graph(self): import zoo.orca.data.pandas tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), "y": df['label'].to_numpy() } return result data_shard = data_shard.transform_shard(transform) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], outputs=[model.logits], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}) est.fit(data=data_shard, batch_size=8, epochs=10, validation_data=data_shard) data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), } return result data_shard = data_shard.transform_shard(transform) predictions = est.predict(data_shard).collect() assert 'prediction' in predictions[0] print(predictions) def test_estimator_graph_fit(self): import zoo.orca.data.pandas tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), "y": df['label'].to_numpy() } return result data_shard = data_shard.transform_shard(transform) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}) est.fit(data=data_shard, batch_size=8, epochs=10, validation_data=data_shard) def test_estimator_graph_evaluate(self): import zoo.orca.data.pandas tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), "y": df['label'].to_numpy() } return result data_shard = data_shard.transform_shard(transform) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}) result = est.evaluate(data_shard) assert "loss" in result print(result) def test_estimator_graph_predict(self): import zoo.orca.data.pandas tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) est = Estimator.from_graph( inputs=[model.user, model.item], outputs=[model.logits]) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), } return result data_shard = data_shard.transform_shard(transform) predictions = est.predict(data_shard).collect() print(predictions) def test_estimator_graph_fit_clip(self): import zoo.orca.data.pandas tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), "y": df['label'].to_numpy() } return result data_shard = data_shard.transform_shard(transform) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), clip_norm=1.2, metrics={"loss": model.loss}) est.fit(data=data_shard, batch_size=8, epochs=10, validation_data=data_shard) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), clip_value=0.2, metrics={"loss": model.loss}) est.fit(data=data_shard, batch_size=8, epochs=10, validation_data=data_shard) def test_estimator_graph_checkpoint(self): import zoo.orca.data.pandas tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), "y": df['label'].to_numpy() } return result data_shard = data_shard.transform_shard(transform) temp = tempfile.mkdtemp() model_dir = os.path.join(temp, "test_model") est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}, model_dir=model_dir ) est.fit(data=data_shard, batch_size=8, epochs=6, validation_data=data_shard, checkpoint_trigger=SeveralIteration(4)) est.sess.close() tf.reset_default_graph() model = SimpleModel() est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}, model_dir=model_dir ) est.load_latest_orca_checkpoint(model_dir) est.fit(data=data_shard, batch_size=8, epochs=10, validation_data=data_shard) result = est.evaluate(data_shard) assert "loss" in result print(result) shutil.rmtree(temp) def test_estimator_graph_fit_dataset(self): import zoo.orca.data.pandas tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), "y": df['label'].to_numpy() } return result data_shard = data_shard.transform_shard(transform) dataset = Dataset.from_tensor_slices(data_shard) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}) est.fit(data=dataset, batch_size=8, epochs=10, validation_data=dataset) result = est.evaluate(dataset, batch_size=4) assert 'loss' in result def test_estimator_graph_predict_dataset(self): tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) est = Estimator.from_graph( inputs=[model.user, model.item], outputs=[model.logits]) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), } return result data_shard = data_shard.transform_shard(transform) dataset = Dataset.from_tensor_slices(data_shard) predictions = est.predict(dataset).collect() assert len(predictions) == 10 def test_estimator_graph_dataframe(self): tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") sc = init_nncontext() sqlcontext = SQLContext(sc) df = sqlcontext.read.csv(file_path, header=True, inferSchema=True) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], outputs=[model.logits], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}) est.fit(data=df, batch_size=8, epochs=10, feature_cols=['user', 'item'], labels_cols=['label'], validation_data=df) result = est.evaluate(df, batch_size=4, feature_cols=['user', 'item'], labels_cols=['label']) print(result) prediction_df = est.predict(df, batch_size=4, feature_cols=['user', 'item']) assert 'prediction' in prediction_df.columns predictions = prediction_df.collect() assert len(predictions) == 10 def test_estimator_graph_dataframe_exception(self): tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") sc = init_nncontext() sqlcontext = SQLContext(sc) df = sqlcontext.read.csv(file_path, header=True, inferSchema=True) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], outputs=[model.logits], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}) with self.assertRaises(Exception) as context: est.fit(data=df, batch_size=8, epochs=10, feature_cols=['user', 'item'], validation_data=df) self.assertTrue('label columns is None; it should not be None in training' in str(context.exception)) est.fit(data=df, batch_size=8, epochs=10, feature_cols=['user', 'item'], labels_cols=['label'] ) with self.assertRaises(Exception) as context: predictions = est.predict(df, batch_size=4).collect() self.assertTrue('feature columns is None; it should not be None in prediction' in str(context.exception)) with self.assertRaises(Exception) as context: est.fit(data=df, batch_size=8, epochs=10, feature_cols=['user', 'item'], labels_cols=['label'], validation_data=[1, 2, 3]) self.assertTrue('train data and validation data should be both Spark DataFrame' in str(context.exception)) def test_checkpoint_remote(self): tf.reset_default_graph() model = SimpleModel() sess = tf.Session() sess.run(tf.global_variables_initializer()) saver = tf.train.Saver(tf.global_variables()) temp = tempfile.mkdtemp() save_tf_checkpoint(sess, os.path.join(temp, "simple.ckpt"), saver) ckpt = get_checkpoint_state(temp) assert ckpt.model_checkpoint_path == os.path.join(temp, "simple.ckpt") assert ckpt.all_model_checkpoint_paths[0] == os.path.join(temp, "simple.ckpt") load_tf_checkpoint(sess, os.path.join(temp, "simple.ckpt"), saver) shutil.rmtree(temp) def test_estimator_graph_tf_dataset(self): tf.reset_default_graph() model = SimpleModel() dataset = tf.data.Dataset.from_tensor_slices((np.random.randint(0, 200, size=(100,)), np.random.randint(0, 50, size=(100,)), np.ones(shape=(100,), dtype=np.int32))) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], outputs=[model.logits], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}) est.fit(data=dataset, batch_size=8, epochs=10, validation_data=dataset) result = est.evaluate(dataset, batch_size=4) assert 'loss' in result predict_dataset = tf.data.Dataset.from_tensor_slices(( np.random.randint(0, 200, size=(20,)), np.random.randint(0, 50, size=(20,)))) predictions = est.predict(predict_dataset).collect() assert predictions[0]['prediction'].shape[1] == 2 def test_estimator_graph_tensorboard(self): tf.reset_default_graph() model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), "y": df['label'].to_numpy() } return result data_shard = data_shard.transform_shard(transform) temp = tempfile.mkdtemp() # only set model dir, summary generated under model dir model_dir = os.path.join(temp, "test_model") est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}, model_dir=model_dir ) est.fit(data=data_shard, batch_size=8, epochs=5, validation_data=data_shard) train_tp = est.get_train_summary("Throughput") val_scores = est.get_validation_summary("loss") assert len(train_tp) > 0 assert len(val_scores) > 0 # set tensorboard dir to different directory est.set_tensorboard("model", "test") est.fit(data=data_shard, batch_size=8, epochs=5, validation_data=data_shard) train_tp = est.get_train_summary("Throughput") val_scores = est.get_validation_summary("loss") assert len(train_tp) > 0 assert len(val_scores) > 0 # no model dir, no tensorboard dir, no summary saved est2 = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss} ) est2.fit(data=data_shard, batch_size=8, epochs=5, validation_data=data_shard) train_tp = est2.get_train_summary("Throughput") val_scores = est2.get_validation_summary("loss") assert train_tp is None assert val_scores is None shutil.rmtree(temp) def test_estimator_graph_save_load(self): import zoo.orca.data.pandas tf.reset_default_graph() # save model = SimpleModel() file_path = os.path.join(resource_path, "orca/learn/ncf.csv") data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), "y": df['label'].to_numpy() } return result data_shard = data_shard.transform_shard(transform) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], outputs=[model.logits], loss=model.loss, optimizer=tf.train.AdamOptimizer(), metrics={"loss": model.loss}, sess=None ) est.fit(data=data_shard, batch_size=8, epochs=10, validation_data=data_shard) temp = tempfile.mkdtemp() model_checkpoint = os.path.join(temp, 'test.ckpt') est.save_tf_checkpoint(model_checkpoint) est.sess.close() tf.reset_default_graph() # load with tf.Session() as sess: model = SimpleModel() saver = tf.train.Saver(tf.global_variables()) saver.restore(sess, model_checkpoint) est = Estimator.from_graph( inputs=[model.user, model.item], labels=[model.label], outputs=[model.logits], loss=model.loss, metrics={"loss": model.loss}, sess=sess ) data_shard = zoo.orca.data.pandas.read_csv(file_path) def transform(df): result = { "x": (df['user'].to_numpy(), df['item'].to_numpy()), } return result data_shard = data_shard.transform_shard(transform) predictions = est.predict(data_shard).collect() assert 'prediction' in predictions[0] print(predictions) shutil.rmtree(temp) if __name__ == "__main__": import pytest pytest.main([__file__])

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19,854

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1

0

1

0

null

0

5

4229f2cfbb8f76a3c582122a7bd64f2a2d13a8e8

121

py

Python

restApi/product/admin.py

rtx-abir/ecom

87a7ae00ca06934151155ae0dca4230397386cd7

[ "MIT" ]

null

restApi/product/admin.py

rtx-abir/ecom

87a7ae00ca06934151155ae0dca4230397386cd7

[ "MIT" ]

null

restApi/product/admin.py

rtx-abir/ecom

87a7ae00ca06934151155ae0dca4230397386cd7

[ "MIT" ]

null

from django.contrib import admin from .models import product # Register your models here. admin.site.register(product)

17.285714

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121

5.705882

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null

0

1

0

1

0

1

0

5

424a6da9ee02379f7a2b9bca0385d298a3ba95e1

40

py

Python

server/util.py

rrjha/dosp

21f3624abfec815434007f76504488896a091f6d

[ "BSD-3-Clause" ]

null

server/util.py

rrjha/dosp

21f3624abfec815434007f76504488896a091f6d

[ "BSD-3-Clause" ]

1

2017-06-14T23:36:20.000Z

2017-06-14T23:36:29.000Z

server/util.py

rrjha/dosp

21f3624abfec815434007f76504488896a091f6d

[ "BSD-3-Clause" ]

null

def dp(s): print("DEBUG: " + str(s))

10

27

0.5

7

40

2.857143

0.857143

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0.225

40

3

28

13.333333

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0

null

0

1

0

null

0

1

0

1

0

5

426e7bc053651182c5fa80f9368b6063cb300d19

727

py

Python

tools/bin/pythonSrc/pychecker-0.8.18/test_input/test15.py

YangHao666666/hawq

10cff8350f1ba806c6fec64eb67e0e6f6f24786c

[ "Artistic-1.0-Perl", "ISC", "bzip2-1.0.5", "TCL", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "PostgreSQL", "BSD-3-Clause" ]

450

2015-09-05T09:12:51.000Z

2018-08-30T01:45:36.000Z

tools/bin/pythonSrc/pychecker-0.8.18/test_input/test15.py

YangHao666666/hawq

10cff8350f1ba806c6fec64eb67e0e6f6f24786c

[ "Artistic-1.0-Perl", "ISC", "bzip2-1.0.5", "TCL", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "PostgreSQL", "BSD-3-Clause" ]

1,274

2015-09-22T20:06:16.000Z

2018-08-31T22:14:00.000Z

tools/bin/pythonSrc/pychecker-0.8.18/test_input/test15.py

YangHao666666/hawq

10cff8350f1ba806c6fec64eb67e0e6f6f24786c

[ "Artistic-1.0-Perl", "ISC", "bzip2-1.0.5", "TCL", "Apache-2.0", "BSD-3-Clause-No-Nuclear-License-2014", "MIT", "PostgreSQL", "BSD-3-Clause" ]

278

2015-09-21T19:15:06.000Z

2018-08-31T00:36:51.000Z

"doc" def xx(**kw): return None def yy(): c = yy g, h = 1, 2 xx(a='', b=c.a.d.f, e=5, jj=xx(j=5), f=(g+h), k=("%s" % "df")) def zz(): b = zz xx(b=(1, 2, 3), c={ 'a': b}, d=[1, 2, 3], k=(1 < 2)) def aa(obj): print obj.x.y print obj.x.y.z print obj.x.y.z.a print obj.x.y.z.a.b print obj.x.y.z.a.b.c class Obj: 'd' def __init__(self, xx): self.xx = xx self.xx.y = 0 self.xx.y.z = 0 self.xx.y.z.a = 0 self.xx.y.z.a.b = 0 self.xx.y.z.a.b.c = 0 def prn(self): print self.xx print self.xx.y print self.xx.y.z print self.xx.y.z.a print self.xx.y.z.a.b print self.xx.y.z.a.b.c

18.175

66

0.442916

161

727

1.975155

0.223602

0.245283

0.220126

0.201258

0.471698

0.36478

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0

0.035565

0.342503

727

39

67

18.641026

0.629707

0

0.012397

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null

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null

0.34375

0

1

null

1

0

null

0

1

0

5

c4262d247d97535d6791947178c44072c5390207

126

py

Python

tests/client/test_func.py

koskotG/ebonite

9f9ae016b70fb24865d5edc99142afb8ab4ddc59

[ "Apache-2.0" ]

270

2019-11-14T15:46:08.000Z

2021-09-17T16:43:03.000Z

tests/client/test_func.py

leepand/ebonite

b01b662c43709d152940f488574d78ff25f89ecf

[ "Apache-2.0" ]

14

2019-11-29T11:49:39.000Z

2022-02-10T00:23:59.000Z

tests/client/test_func.py

leepand/ebonite

b01b662c43709d152940f488574d78ff25f89ecf

[ "Apache-2.0" ]

18

2019-11-22T13:15:14.000Z

2021-09-01T13:36:12.000Z

def func(kek: str): return "kek" # FIXME otherwise ebonite collects all the dependencies in file with `func` declaration

25.2

87

0.746032

18

126

5.222222

0.888889

0

0.18254

126

4

88

31.5

0.912621

0.674603

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0.076923

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0.25

0

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false

0

0.5

1

0

1

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null

0

1

0

null

0

1

0

1

0

1

0

5

c443d0e3a46eadf1e9561541e4bb06047a2c76ab

96

py

Python

training_codes/bio2lif_model_intFire4_rl/run_rl2_g8_8_test500ms_inh_lif_syn_z110.py

zqwei/LIF_Vis_model

16f651ac827ba5f0feb40a0e619e600f1251d009

[ "MIT" ]

null

training_codes/bio2lif_model_intFire4_rl/run_rl2_g8_8_test500ms_inh_lif_syn_z110.py

zqwei/LIF_Vis_model

16f651ac827ba5f0feb40a0e619e600f1251d009

[ "MIT" ]

null

training_codes/bio2lif_model_intFire4_rl/run_rl2_g8_8_test500ms_inh_lif_syn_z110.py

zqwei/LIF_Vis_model

16f651ac827ba5f0feb40a0e619e600f1251d009

[ "MIT" ]

null

import start as start start.run_simulation('config_rl2_g8_8_test500ms_inh_lif_syn_z110.json')

19.2

71

0.864583

17

96

4.352941

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null

0

1

0

1

0

5

c465fa4c2dcb6e388489585d29731fb1a8db467b

231

py

Python

tests/test_predictor.py

TheHonestGene/risk-predicator

7b45a1e7d21af89efbd15d7d8035b8e97748f638

[ "MIT" ]

null

tests/test_predictor.py

TheHonestGene/risk-predicator

7b45a1e7d21af89efbd15d7d8035b8e97748f638

[ "MIT" ]

null

tests/test_predictor.py

TheHonestGene/risk-predicator

7b45a1e7d21af89efbd15d7d8035b8e97748f638

[ "MIT" ]

null

import pytest from riskpredictor.core import predictor class TestPredictor: def test_predict(self): raise Exception('Test not implemented') def test_validate(self): raise Exception('Test not implemented')

23.1

47

0.731602

27

231

6.185185

0.62963

0.083832

0.215569

0.263473

0.431138

0

0.199134

231

10

48

23.1

0.902703

0

0.285714

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false

0

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null

0

1

0

null

0

1

0

1

0

5

c472cec4822f9a785354cff6119f64b3d4cb1291

857

py

Python

excel_2021-01-21_21-41-12.py

ClointFusion-Community/CFC-Projects

c6381738ade07e6e8979bbae37400ec2b4e626c5

[ "MIT" ]

null

excel_2021-01-21_21-41-12.py

ClointFusion-Community/CFC-Projects

c6381738ade07e6e8979bbae37400ec2b4e626c5

[ "MIT" ]

null

excel_2021-01-21_21-41-12.py

ClointFusion-Community/CFC-Projects

c6381738ade07e6e8979bbae37400ec2b4e626c5

[ "MIT" ]

null

# This code is generated automatically by ClointFusion BOT Builder Tool. import ClointFusion as cf import time cf.window_show_desktop() cf.mouse_click(int(cf.pg.size()[0]/2),int(cf.pg.size()[1]/2)) cf.key_write_enter('ote',key='') time.sleep(0) cf.key_press('enter') time.sleep(1) cf.key_write_enter('hi',key='') time.sleep(1) cf.key_press('space') time.sleep(0) cf.key_write_enter('sushil',key='') time.sleep(0) cf.key_press('space') time.sleep(0) cf.key_write_enter('how',key='') time.sleep(0) cf.key_press(ctrl+X) time.sleep(0) cf.key_press('space') time.sleep(0) cf.key_write_enter('ru',key='') time.sleep(1) cf.key_press('space') time.sleep(1) cf.key_press(ctrl+C) time.sleep(0) cf.key_press(ctrl+Z) time.sleep(2) time.sleep(0) time.sleep(1) cf.key_press('alt+f4') time.sleep(0) time.sleep(1) cf.key_write_enter('n',key='') time.sleep(0)

17.14

72

0.715286

165

857

3.569697

0.260606

0.275042

0.186757

0.162988

0.624788

0.597623

0.40747

0.322581

0

0.029077

0.077013

857

49

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17.489796

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0

null

1

0

1

0

null

0

1

0

5

670577573aa85431d39f345ad67c4276a9c34ca2

186

py

Python

DeepAlignmentNetwork/menpofit/atm/__init__.py

chiawei-liu/DeepAlignmentNetwork

52621cd2f697abe372b88c9ea0ee08f0d93b43d8

[ "MIT" ]

220

2019-09-01T01:52:04.000Z

2022-03-28T12:52:07.000Z

DeepAlignmentNetwork/menpofit/atm/__init__.py

chiawei-liu/DeepAlignmentNetwork

52621cd2f697abe372b88c9ea0ee08f0d93b43d8

[ "MIT" ]

80

2015-01-05T16:17:39.000Z

2020-11-22T13:42:00.000Z

DeepAlignmentNetwork/menpofit/atm/__init__.py

chiawei-liu/DeepAlignmentNetwork

52621cd2f697abe372b88c9ea0ee08f0d93b43d8

[ "MIT" ]

64

2015-02-02T15:11:38.000Z

2022-02-28T06:19:31.000Z

from .base import HolisticATM, PatchATM, MaskedATM, LinearATM, LinearMaskedATM from .fitter import LucasKanadeATMFitter from .algorithm import ForwardCompositional, InverseCompositional

46.5

78

0.865591

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186

9.470588

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1

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1

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5

670595479e1f7f938eec262dec5df1f6574a4f1b

351

py

Python

src/status.py

JeyDi/GameOfLife

963d2d084e82321eb814e07d146af9af4e6106ff

[ "MIT" ]

null

src/status.py

JeyDi/GameOfLife

963d2d084e82321eb814e07d146af9af4e6106ff

[ "MIT" ]

null

src/status.py

JeyDi/GameOfLife

963d2d084e82321eb814e07d146af9af4e6106ff

[ "MIT" ]

null

class Cell: def __init__(self): self._status = False def set_alive(self): self._status = True def set_dead(self): self._status = False def check_status(self): return self._status def print_status(self): if self.check_status(): return "*" else: return "0"

18.473684

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0.547009

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4.365854

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0.212291

0.24581

0

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18

32

19.5

0.791111

0

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0.357143

false

0

0.071429

0.642857

0.071429

0

null

1

0

null

0

1

0

1

0

5

670e484778f3159aeb3d13f8103eef133d8c0bdd

1,340

py

Python

pnk_server/users/permissions.py

RomzaLabs/pnk_server

543d966b2f713794f0b6bdc90a535a2ee3cd0bb4

[ "MIT" ]

null

pnk_server/users/permissions.py

RomzaLabs/pnk_server

543d966b2f713794f0b6bdc90a535a2ee3cd0bb4

[ "MIT" ]

18

2019-06-05T14:24:32.000Z

2021-03-09T04:48:25.000Z

pnk_server/users/permissions.py

RomzaLabs/pnk_server

543d966b2f713794f0b6bdc90a535a2ee3cd0bb4

[ "MIT" ]

null

from rest_framework.permissions import BasePermission, SAFE_METHODS class IsSuperuserOrReadOnly(BasePermission): """ Object-level permission to only allow admin members to edit it. """ def has_permission(self, request, view): return bool( request.method in SAFE_METHODS or request.user.is_authenticated and request.user.is_superuser ) class IsUserOrReadOnly(BasePermission): """ Object-level permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): if request.method in SAFE_METHODS: return True return obj == request.user class IsCommanderOrReadOnly(BasePermission): """ Object-level permission to only allow owners of an object to edit it. """ def has_object_permission(self, request, view, obj): if request.method in SAFE_METHODS: return True return obj.commander == request.user class IsMemberOrReadOnly(BasePermission): """ Object-level permission to only allow member to edit it. """ def has_permission(self, request, view): return bool( request.method in SAFE_METHODS or request.user.is_authenticated and request.user.user_type == "MEM" )

26.27451

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0.658209

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5.587097

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1,340

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1

0

1

0

1

0

null

0

1

0

5

67460178cb214b564b489c4e4f018cdfe8369651

828

py

Python

test/test_imports.py

IamMarcIvanov/haystack

4f30f038226886114087fa1369d7b86bafe63bc6

[ "Apache-2.0" ]

null

test/test_imports.py

IamMarcIvanov/haystack

4f30f038226886114087fa1369d7b86bafe63bc6

[ "Apache-2.0" ]

null

test/test_imports.py

IamMarcIvanov/haystack

4f30f038226886114087fa1369d7b86bafe63bc6

[ "Apache-2.0" ]

null

def test_module_imports(): from haystack import Finder from haystack.database.sql import SQLDocumentStore from haystack.indexing.cleaning import clean_wiki_text from haystack.indexing.utils import convert_files_to_dicts, fetch_archive_from_http from haystack.reader.farm import FARMReader from haystack.reader.transformers import TransformersReader from haystack.retriever.tfidf import TfidfRetriever from haystack.utils import print_answers assert Finder is not None assert SQLDocumentStore is not None assert clean_wiki_text is not None assert convert_files_to_dicts is not None assert fetch_archive_from_http is not None assert FARMReader is not None assert TransformersReader is not None assert TfidfRetriever is not None assert print_answers is not None

41.4

87

0.799517

113

828

5.681416

0.336283

0.070093

0.126168

0.186916

0

0.179952

828

19

88

43.578947

0.945508

0

0.5

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true

0

0.5

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0.555556

0.111111

0

null

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0

null

0

1

0

1

0

1

0

1

0

5

67863f6005574aa6401e365dcb609b9b0abda349

246

py

Python

examples/docs_snippets/docs_snippets/intro_tutorial/advanced/repositories/repos.py

rpatil524/dagster

6f918d94cbd543ab752ab484a65e3a40fd441716

[ "Apache-2.0" ]

1

2021-01-31T19:16:29.000Z

examples/docs_snippets/docs_snippets/intro_tutorial/advanced/repositories/repos.py

rpatil524/dagster

6f918d94cbd543ab752ab484a65e3a40fd441716

[ "Apache-2.0" ]

null

examples/docs_snippets/docs_snippets/intro_tutorial/advanced/repositories/repos.py

rpatil524/dagster

6f918d94cbd543ab752ab484a65e3a40fd441716

[ "Apache-2.0" ]

1

2019-09-11T03:02:27.000Z

from dagster import repository from .complex_job import complex_job from .hello_cereal import hello_cereal_job # start_repos_marker_0 @repository def hello_cereal_repository(): return [hello_cereal_job, complex_job] # end_repos_marker_0

17.571429

42

0.829268

36

246

5.222222

0.416667

0.234043

0.148936

0

0.009302

0.126016

246

13

43

18.923077

0.865116

0.158537

0

1

0.166667

true

0

0.5

0.166667

0.833333

0

null

1

0

null

0

1

0

1

0

5

67aa1555cd981f8d816f8e837b9818d909c38241

135

py

Python

harnessed_jobs/cti_BOT/v0/validator_cti_BOT.py

duncanwood/EO-analysis-jobs

26d22e49c0d2e32fbf2759f504048754f66ecc45

[ "BSD-3-Clause-LBNL" ]

2

2018-07-26T09:32:46.000Z

2019-05-28T20:57:43.000Z

harnessed_jobs/cti_BOT/v0/validator_cti_BOT.py

duncanwood/EO-analysis-jobs

26d22e49c0d2e32fbf2759f504048754f66ecc45

[ "BSD-3-Clause-LBNL" ]

3

2018-03-18T21:55:07.000Z

2019-04-18T18:26:06.000Z

harnessed_jobs/cti_BOT/v0/validator_cti_BOT.py

duncanwood/EO-analysis-jobs

26d22e49c0d2e32fbf2759f504048754f66ecc45

[ "BSD-3-Clause-LBNL" ]

2

2020-11-12T19:47:42.000Z

2022-02-25T21:43:03.000Z

#!/usr/bin/env ipython """ Validator script for BOT PTC analysis. """ from bot_eo_validators import run_validator run_validator('cte')

19.285714

43

0.77037

20

135

5

0.8

0.24

0

0.111111

135

6

44

22.5

0.833333

0.444444

0

0.044776

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

67e3ee76e6b1e6fb10521ad1d99478856d0d5039

333

py

Python

multispinsys/__init__.py

Marcupio/SpinProgram

4d47e5e5048423ae69869a0300558e1fee809bf0

[ "Apache-2.0" ]

null

multispinsys/__init__.py

Marcupio/SpinProgram

4d47e5e5048423ae69869a0300558e1fee809bf0

[ "Apache-2.0" ]

null

multispinsys/__init__.py

Marcupio/SpinProgram

4d47e5e5048423ae69869a0300558e1fee809bf0

[ "Apache-2.0" ]

null

from multispinsys import Hamiltonians from multispinsys import FilteredStates from multispinsys import tools from multispinsys import DisorderVEntropy from multispinsys import processmod from multispinsys import AdjacentGapRatio __all__=["Hamiltonians", "FilteredStates", "tools", "processmod" ]

25.615385

41

0.75976

29

333

8.586207

0.344828

0.385542

0.53012

0

0.198198

333

12

42

27.75

0.932584

0

0.123123

0

1

0

false

0

0.545455

0

0.545455

0

1

0

null

1

0

null

0

1

0

1

0

5

db12ee655f526db8be7b3dbca218609a89828e29

62

py

Python

src/olympus/surfaces/surface_zakharov/__init__.py

priyansh-1902/olympus

f57ad769918c0d5d805c439ab5ffbd180af698fa

[ "MIT" ]

36

2020-10-10T14:05:40.000Z

2022-02-12T07:21:47.000Z

src/olympus/surfaces/surface_zakharov/__init__.py

kiminh/olympus

054f7b4012faf6e516b5e4c895093c9fea0c793f

[ "MIT" ]

12

2020-10-14T09:04:06.000Z

2021-10-01T19:25:34.000Z

src/olympus/surfaces/surface_zakharov/__init__.py

kiminh/olympus

054f7b4012faf6e516b5e4c895093c9fea0c793f

[ "MIT" ]

8

2020-10-24T12:43:45.000Z

2022-02-12T07:21:50.000Z

#!/usr/bin/env python from .wrapper_zakharov import Zakharov

15.5

38

0.790323

9

62

5.333333

0.888889

0

0.112903

62

3

39

20.666667

0.872727

0.322581

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

e1d181f9d52cd37ef041c82dac0f162c0602fdd3

62

py

Python

marshmallow_polyfield/__init__.py

authentik8/marshmallow-polyfield

22215159cc073ff6a4783516042865b972503132

[ "Apache-2.0" ]

1

2018-10-05T15:07:47.000Z

marshmallow_polyfield/__init__.py

authentik8/marshmallow-polyfield

22215159cc073ff6a4783516042865b972503132

[ "Apache-2.0" ]

2

2018-10-05T14:54:57.000Z

2018-12-14T09:43:33.000Z

marshmallow_polyfield/__init__.py

macbeth322/marshmallow-polyfield

36270d28b0ce73ff8b6ec1dbc5f114ac5db9cada

[ "Apache-2.0" ]

null

from marshmallow_polyfield.polyfield import PolyField # noqa

31

61

0.854839

7

62

7.428571

0.714286

0

0.112903

62

1

62

0.945455

0.064516

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

c01dfb3715085a7d86b2854343f158bdd3213c26

163

py

Python

examples/sp2bench/catalog.py

uwescience/raco

1f2bedbef71bacf715340289f4973d85a3c1dc97

[ "BSD-3-Clause" ]

61

2015-02-09T17:27:40.000Z

2022-03-28T14:37:53.000Z

examples/sp2bench/catalog.py

uwescience/raco

1f2bedbef71bacf715340289f4973d85a3c1dc97

[ "BSD-3-Clause" ]

201

2015-01-03T02:46:19.000Z

2017-09-19T02:16:36.000Z

examples/sp2bench/catalog.py

uwescience/raco

1f2bedbef71bacf715340289f4973d85a3c1dc97

[ "BSD-3-Clause" ]

17

2015-06-03T12:01:30.000Z

2021-11-27T15:49:21.000Z

# Schemas corresponding to Myrial examples { 'public:adhoc:sp2bench' : [('subject', 'STRING_TYPE'), ('predicate','STRING_TYPE'), ('object','STRING_TYPE')], }

27.166667

114

0.674847

17

163

6.294118

0.764706

0.280374

0

0.006944

0.116564

163

5

115

32.6

0.736111

0.245399

0

0.628099

0.173554

0

1

0

true

0

1

0

null

1

0

1

0

1

0

null

0

1

0

5

c0298e274d4001fc699b19d10028fa2af634febb

112

py

Python

finetune/model/__init__.py

sackoh/KoBigBird

3e51a9004c032291bbd99a9d77a72cd95eb8ffca

[ "Apache-2.0" ]

154

2021-11-08T06:46:59.000Z

2022-03-22T04:04:42.000Z

finetune/model/__init__.py

sackoh/KoBigBird

3e51a9004c032291bbd99a9d77a72cd95eb8ffca

[ "Apache-2.0" ]

2

2021-12-27T03:14:16.000Z

2021-12-28T11:33:27.000Z

finetune/model/__init__.py

sackoh/KoBigBird

3e51a9004c032291bbd99a9d77a72cd95eb8ffca

[ "Apache-2.0" ]

14

2021-11-08T08:13:27.000Z

2021-12-27T06:46:06.000Z

from model.cls import ClsModel from model.qa import QAModel MODEL_CLASS_MAP = {"cls": ClsModel, "qa": QAModel}

22.4

50

0.758929

17

112

4.882353

0.529412

0.216867

0

0.133929

112

4

51

28

0.85567

0

0.044643

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

c0459da474045b3877cc69231738c485bb676406

27

py

Python

core/__init__.py

EdwardjkFeng/RAFT

756902fa429283218969a8285324a7dfbe81020e

[ "BSD-3-Clause" ]

null

core/__init__.py

EdwardjkFeng/RAFT

756902fa429283218969a8285324a7dfbe81020e

[ "BSD-3-Clause" ]

null

core/__init__.py

EdwardjkFeng/RAFT

756902fa429283218969a8285324a7dfbe81020e

[ "BSD-3-Clause" ]

null

import core.utils as utils

13.5

26

0.814815

5

27

4.4

0.8

0

0.148148

27

1

27

0.956522

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

fbffeb8546945ba296991bcef65ceff78f07409e

53

py

Python

scripts/__init__.py

IntelEuclid/euclid_configuration_node

e46af8d31512805bd22136ab12460334cc3189bd

[ "BSD-3-Clause" ]

1

2019-04-18T06:03:19.000Z

scripts/__init__.py

IntelEuclid/euclid_configuration_node

e46af8d31512805bd22136ab12460334cc3189bd

[ "BSD-3-Clause" ]

null

scripts/__init__.py

IntelEuclid/euclid_configuration_node

e46af8d31512805bd22136ab12460334cc3189bd

[ "BSD-3-Clause" ]

2

2018-01-31T10:03:08.000Z

2020-04-22T05:12:30.000Z

# from CsNetworkController import CsNetworkController

53

0.90566

4

53

12

0.75

0

0.075472

53

1

53

0.979592

0.962264

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

1

null

0

1

0

1

0

null

0

1

0

5

2220ff318303ad7b577a830354d85b5c0948dfc5

40

py

Python

mpf/modes/attract/code/__init__.py

Scottacus64/mpf

fcfb6c5698b9c7d8bf0eb64b021aaa389ea6478a

[ "MIT" ]

163

2015-01-25T02:19:50.000Z

2022-03-26T12:00:28.000Z

mpf/modes/attract/code/__init__.py

Scottacus64/mpf

fcfb6c5698b9c7d8bf0eb64b021aaa389ea6478a

[ "MIT" ]

1,086

2015-03-23T19:53:17.000Z

2022-03-24T20:46:11.000Z

mpf/modes/attract/code/__init__.py

Scottacus64/mpf

fcfb6c5698b9c7d8bf0eb64b021aaa389ea6478a

[ "MIT" ]

148

2015-01-28T02:31:39.000Z

2022-03-22T13:54:01.000Z

"""Code of the default attract mode."""

20

39

0.675

6

40

4.5

1

0

0.15

40

1

40

0.794118

0.825

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

2246700534f099dc4af36477c59a4046d5b0193e

384

py

Python

tests/__init__.py

hostcc/pyg90alarm

8af1373b87ff27978573fd83238bd6ee3dd57bad

[ "MIT" ]

null

tests/__init__.py

hostcc/pyg90alarm

8af1373b87ff27978573fd83238bd6ee3dd57bad

[ "MIT" ]

10

2022-01-19T10:30:46.000Z

2022-03-16T16:48:23.000Z

tests/__init__.py

hostcc/pyg90alarm

8af1373b87ff27978573fd83238bd6ee3dd57bad

[ "MIT" ]

null

import unittest from .test_base_commands import * # noqa: F401,F403 from .test_paginated_commands import * # noqa: F401,F403 from .test_discovery import * # noqa: F401,F403 from .test_notifications import * # noqa: F401,F403 from .test_alarm import * # noqa: F401, F403 from .test_callback import * # noqa: F401, F403 if __name__ == '__main__': unittest.main(verbosity=3)

32

57

0.734375

53

384

5.018868

0.358491

0.180451

0.315789

0.406015

0.548872

0.255639

0

0.115265

0.164063

384

11

58

34.909091

0.713396

0.252604

0

0.028571

0

1

0

true

0

0.777778

0

0.777778

0

null

0

1

0

null

0

1

0

1

0

1

0

5

22744e19985140a6b04c7a9195b59b9a2485d5b2

197

py

Python

oembed/admin.py

ccnmtl/django-oembed

55066c2062034c09419ab941c5ac771d00086162

[ "BSD-3-Clause" ]

null

oembed/admin.py

ccnmtl/django-oembed

55066c2062034c09419ab941c5ac771d00086162

[ "BSD-3-Clause" ]

null

oembed/admin.py

ccnmtl/django-oembed

55066c2062034c09419ab941c5ac771d00086162

[ "BSD-3-Clause" ]

null

from __future__ import unicode_literals from django.contrib import admin from oembed.models import ProviderRule, StoredOEmbed admin.site.register(ProviderRule) admin.site.register(StoredOEmbed)

21.888889

52

0.852792

24

197

6.791667

0.583333

0.110429

0.208589

0

0.091371

197

8

53

24.625

0.910615

0

1

0

true

0

0.6

0

0.6

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

227832b7dda58549c89f31324df3332cadd59ceb

90

py

Python

django_shares/forms/__init__.py

InfoAgeTech/django-shares

1b301852fa261a7eb6c872dc912517368da6cb33

[ "MIT" ]

null

django_shares/forms/__init__.py

InfoAgeTech/django-shares

1b301852fa261a7eb6c872dc912517368da6cb33

[ "MIT" ]

null

django_shares/forms/__init__.py

InfoAgeTech/django-shares

1b301852fa261a7eb6c872dc912517368da6cb33

[ "MIT" ]

null

from .delete import SharedObjectRemoveShareForm from .mixins import SharedObjectFormMixin

30

47

0.888889

8

90

10

0.75

0

0.088889

90

2

48

45

0.97561

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

97ece26425f80fe12ee5d6f7375bca296eba2742

175

py

Python

genlist.py

RiseofRice/password-Creator

0013ebc4b8ce18ef78e4686b97c1723525e57275

[ "MIT" ]

null

genlist.py

RiseofRice/password-Creator

0013ebc4b8ce18ef78e4686b97c1723525e57275

[ "MIT" ]

null

genlist.py

RiseofRice/password-Creator

0013ebc4b8ce18ef78e4686b97c1723525e57275

[ "MIT" ]

null

from genpasswds import generate_passwords def gen_list(q, length): pwlist = [] for i in range(q): pwlist.append(generate_passwords(length)) return pwlist

21.875

49

0.697143

23

175

5.173913

0.73913

0.285714

0

0.217143

175

8

50

21.875

0.868613

0

1

0

1

0.166667

false

0.333333

0.166667

0

0.5

0

1

0

null

1

0

1

0

1

0

null

0

1

0

5

3f377a1d6b5a6ca2b61cbef43cf33166de7c72d4

166

py

Python

MLMCPy/model/__init__.py

Rustinante/MLMCPy

fbdf9c116bfa35b76305e9f934e1ffe342f10266

[ "NASA-1.3" ]

47

2018-11-07T21:47:15.000Z

2022-03-30T12:20:39.000Z

MLMCPy/model/__init__.py

Rustinante/MLMCPy

fbdf9c116bfa35b76305e9f934e1ffe342f10266

[ "NASA-1.3" ]

16

2018-11-16T20:00:45.000Z

2019-08-21T20:50:37.000Z

MLMCPy/model/__init__.py

Rustinante/MLMCPy

fbdf9c116bfa35b76305e9f934e1ffe342f10266

[ "NASA-1.3" ]

17

2018-11-01T20:03:58.000Z

2022-03-20T11:15:02.000Z

from CovarianceWrapperModel import CovarianceWrapperModel from Model import Model from ModelFromData import ModelFromData from CDFWrapperModel import CDFWrapperModel

33.2

57

0.903614

16

166

9.375

0.375

0

0.096386

166

4

58

41.5

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

3f3a7f94d97fce65c4c1e00973be33383669c798

54

py

Python

src/__init__.py

saattrupdan/scandi-models

49635e3743e11aae7298245c5f1c5df4cd822be1

[ "MIT" ]

null

src/__init__.py

saattrupdan/scandi-models

49635e3743e11aae7298245c5f1c5df4cd822be1

[ "MIT" ]

null

src/__init__.py

saattrupdan/scandi-models

49635e3743e11aae7298245c5f1c5df4cd822be1

[ "MIT" ]

null

from .trainer import get_ner_trainer, get_bin_trainer

27

53

0.87037

9

54

4.777778

0.666667

0

0.092593

54

1

54

0.877551

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

3f3ace027b5a3d5f2118697127b5cce7b035fe7f

55

py

Python

ANN_Python/Async_ANN.py

KTMonadjem/Masters

54fbcfde8fb9fb3e061315c84e475bc3e0e9c550

[ "Unlicense" ]

null

ANN_Python/Async_ANN.py

KTMonadjem/Masters

54fbcfde8fb9fb3e061315c84e475bc3e0e9c550

[ "Unlicense" ]

null

ANN_Python/Async_ANN.py

KTMonadjem/Masters

54fbcfde8fb9fb3e061315c84e475bc3e0e9c550

[ "Unlicense" ]

null

import numpy as np import thread import threading

11

19

0.763636

8

55

5.25

0.75

0

0.236364

55

4

20

13.75

1

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

3f5207284564cfa94ddcd58f9e840bfac83253e4

29

py

Python

wave/noise/__init__.py

jedhsu/wave

a05d8f4b0a96722bdc2f5a514646c7a44681982b

[ "Apache-2.0" ]

null

wave/noise/__init__.py

jedhsu/wave

a05d8f4b0a96722bdc2f5a514646c7a44681982b

[ "Apache-2.0" ]

null

wave/noise/__init__.py

jedhsu/wave

a05d8f4b0a96722bdc2f5a514646c7a44681982b

[ "Apache-2.0" ]

null

# exacty how does this pair?

14.5

28

0.724138

5

29

4.2

1

0

0.206897

29

1

29

0.913043

0.896552

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

58b67aeceb9e6f91337f519de8acd4e2694304d1

45

py

Python

bob/db/swan/config_protocol_grandtest1_voice_licit.py

bioidiap/bob.db.swan

676510d47cb08b65be04f51d45746127c36bf2ce

[ "BSD-3-Clause" ]

null

bob/db/swan/config_protocol_grandtest1_voice_licit.py

bioidiap/bob.db.swan

676510d47cb08b65be04f51d45746127c36bf2ce

[ "BSD-3-Clause" ]

null

bob/db/swan/config_protocol_grandtest1_voice_licit.py

bioidiap/bob.db.swan

676510d47cb08b65be04f51d45746127c36bf2ce

[ "BSD-3-Clause" ]

null

database.protocol = 'grandtest1-voice-licit'

22.5

44

0.8

5

45

7.2

1

0

0.02381

0.066667

45

1

45

0.833333

0

0.488889

0

1

0

true

0

1

0

null

0

1

0

1

null

0

1

0

5

45071e3903b396722efedfd0b014011a626c73a0

116

py

Python

Uche Clare/Phase 1/Python Basic 1/Day 15/task 2.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

6

2020-05-23T19:53:25.000Z

2021-05-08T20:21:30.000Z

Uche Clare/Phase 1/Python Basic 1/Day 15/task 2.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

8

2020-05-14T18:53:12.000Z

2020-07-03T00:06:20.000Z

Uche Clare/Phase 1/Python Basic 1/Day 15/task 2.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

39

2020-05-10T20:55:02.000Z

2020-09-12T17:40:59.000Z

#Write a Python program to list home directory without absolute path. import os.path print(os.path.expanduser('~'))

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0

0.12069

116

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29

0.882353

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null

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1

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1

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5

4537bec7cccecc7f8006ffbaca03e5cc82fa5d2c

107

py

Python

tests/examples-bad/7.py

JohannesBuchner/pystrict3

f442a89ac6a23f4323daed8ef829d8e9e1197f90

[ "BSD-2-Clause" ]

1

2020-06-05T08:53:26.000Z

tests/examples-bad/7.py

JohannesBuchner/pystrict3

f442a89ac6a23f4323daed8ef829d8e9e1197f90

[ "BSD-2-Clause" ]

1

2020-06-04T13:47:19.000Z

2020-06-04T13:47:57.000Z

tests/examples-bad/7.py

JohannesBuchner/pystrict3

f442a89ac6a23f4323daed8ef829d8e9e1197f90

[ "BSD-2-Clause" ]

1

2020-11-07T17:02:46.000Z

import itertools print([itertools.fancycount(s) for s in 'a, b and C'.split()]) ## error, does not exist

26.75

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0.691589

18

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5

18b07c47972234d9d53f964015f1f650e0a7395b

26,196

py

Python

tests/test_resource.py

Informasjonsforvaltning/datacatalogtordf

7e21186e9bd03e434a0319b2f36aecf78d7c16ee

[ "Apache-2.0" ]

2

2020-05-18T06:57:12.000Z

2020-06-25T12:46:42.000Z

tests/test_resource.py

Informasjonsforvaltning/datacatalogtordf

7e21186e9bd03e434a0319b2f36aecf78d7c16ee

[ "Apache-2.0" ]

42

2020-03-17T16:09:56.000Z

2022-03-28T06:12:01.000Z

tests/test_resource.py

Informasjonsforvaltning/datacatalogtordf

7e21186e9bd03e434a0319b2f36aecf78d7c16ee

[ "Apache-2.0" ]

null

"""Test cases for the resource module.""" from concepttordf import Contact import pytest from rdflib import Graph from rdflib.compare import graph_diff, isomorphic from datacatalogtordf import Agent, Dataset, Relationship, Resource """ A test class for testing the _abstract_ class Resource. Using Dataset class in order to instantiate Resource. """ def test_instantiate_resource_should_fail_with_TypeError() -> None: """It returns a TypeErro exception.""" with pytest.raises(TypeError): _ = Resource() # type: ignore def test_to_graph_should_return_identifier() -> None: """It returns an identifier graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_publisher() -> None: """It returns a publisher graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.publisher = "http://example.com/publisher/1" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:publisher <http://example.com/publisher/1> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_publisher_agent() -> None: """It returns a publisher graph isomorphic to spec.""" publisher = Agent() publisher.identifier = "http://example.com/agents/1" publisher.name = {"en": "James Bond", "nb": "Djeims Bånd"} resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.publisher = publisher src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . <http://example.com/datasets/1> a dcat:Dataset ; dct:publisher <http://example.com/agents/1> ; . <http://example.com/agents/1> a foaf:Agent ; foaf:name "James Bond"@en, "Djeims Bånd"@nb ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_publisher_agent_bnode() -> None: """It returns a publisher graph isomorphic to spec.""" publisher = Agent() publisher.name = {"en": "James Bond", "nb": "Djeims Bånd"} resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.publisher = publisher src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix foaf: <http://xmlns.com/foaf/0.1/> . <http://example.com/datasets/1> a dcat:Dataset ; dct:publisher [ a foaf:Agent ; foaf:name "James Bond"@en, "Djeims Bånd"@nb ; ] ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_title() -> None: """It returns a title graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.title = {"nb": "Tittel 1", "en": "Title 1"} src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:title "Title 1"@en, "Tittel 1"@nb ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_access_rights() -> None: """It returns a access_rights graph isomorphic to spec.""" access_rights = ["PUBLIC", "RESTRICTED", "NON-PUBLIC"] for _r in access_rights: resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.access_rights = ( f"http://publications.europa.eu/resource/authority/access-right/{_r}" ) src = ( "@prefix dct: <http://purl.org/dc/terms/> ." "@prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> ." "@prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> ." "@prefix dcat: <http://www.w3.org/ns/dcat#> .\n" "<http://example.com/datasets/1> a dcat:Dataset ;" "\tdct:accessRights\t" "<http://publications.europa.eu/resource/authority/access-right/" f"{_r}> ." ) g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_conformsTo() -> None: """It returns a conformsTo graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.conformsTo.append("http://example.com/standards/1") resource.conformsTo.append("http://example.com/standards/2") src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:conformsTo <http://example.com/standards/1> , <http://example.com/standards/2> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_contactpoint() -> None: """It returns a contactpoint graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" # Create contact: contact = Contact() contact.name = { "en": "Norwegian Digitalisation Agency", "nb": "Digitaliseringsdirektoratet", } contact.email = "sbd@example.com" contact.url = "https://digdir.no" contact.telephone = "12345678" # Set the contactpoint to new contact: resource.contactpoint = contact src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix vcard: <http://www.w3.org/2006/vcard/ns#> . <http://example.com/datasets/1> a dcat:Dataset ; dcat:contactPoint [ a vcard:Organization ; vcard:hasEmail <mailto:sbd@example.com> ; vcard:hasOrganizationName "Norwegian Digitalisation Agency"@en, "Digitaliseringsdirektoratet"@nb ; vcard:hasURL <https://digdir.no> ; vcard:hasTelephone <tel:12345678> ; ] ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_creator() -> None: """It returns a creator graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.creator = "http://example.com/creator/1" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:creator <http://example.com/creator/1> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_description() -> None: """It returns a description graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.description = {"nb": "Beskrivelse", "en": "Description"} src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:description "Description"@en, "Beskrivelse"@nb ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_hasPolicy() -> None: """It returns a hasPolicy graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.has_policy = "http://example.com/policies/1" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix odrl: <http://www.w3.org/ns/odrl/2/> . <http://example.com/datasets/1> a dcat:Dataset ; odrl:hasPolicy <http://example.com/policies/1> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_is_Referenced_By() -> None: """It returns an isReferencedBy isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" other = Dataset() other.identifier = "http://example.com/datasets/1" resource.is_referenced_by.append(other) another = Dataset() another.identifier = "http://example.com/datasets/2" resource.is_referenced_by.append(another) src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:isReferencedBy <http://example.com/datasets/1> , <http://example.com/datasets/2> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_keyword() -> None: """It returns a keyword graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" _keyword = {} _keyword["nb"] = "Etnøkkelord" _keyword["nn"] = "Eitnøkkelord" _keyword["en"] = "Akeyword" resource.keyword = _keyword src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dcat:keyword "Akeyword"@en, "Etnøkkelord"@nb, "Eitnøkkelord"@nn ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_landingPage() -> None: """It returns a landingPage graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.landing_page.append("http://example.com/landingpages/1") resource.landing_page.append("http://example.com/landingpages/2") src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dcat:landingPage <http://example.com/landingpages/1> , <http://example.com/landingpages/2> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_license() -> None: """It returns a license graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.license = "http://example.com/licenses/1" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:license <http://example.com/licenses/1> . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_language() -> None: """It returns a language graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.language.append("http://id.loc.gov/vocabulary/iso639-1/en") resource.language.append("http://id.loc.gov/vocabulary/iso639-1/nb") src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:language <http://id.loc.gov/vocabulary/iso639-1/en> , <http://id.loc.gov/vocabulary/iso639-1/nb> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_relation() -> None: """It returns a relation graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.resource_relation.append("http://example/resources/1") resource.resource_relation.append("http://example/resources/2") src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:relation <http://example/resources/1> , <http://example/resources/2> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_rights() -> None: """It returns a rights graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.rights = "http://example.com/rights/1" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:rights <http://example.com/rights/1> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_qualifiedRelation() -> None: """It returns a qualifiedRelation graph isomorphic to spec.""" # Create the dataset to be related to: _dataset = Dataset() _dataset.identifier = "http://example.org/Original987" # Create the relationship: _relationship = Relationship() # _relationship.identifier = "http://example.com/relationships/1" _relationship.relation = _dataset _relationship.had_role = "http://www.iana.org/assignments/relation/original" # Add relationship to resource (dataset): resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.qualified_relation.append(_relationship) src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dcat:qualifiedRelation [ a dcat:Relationship ; dct:relation <http://example.org/Original987> ; dcat:hadRole <http://www.iana.org/assignments/relation/original> ] ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_release_date() -> None: """It returns a issued graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.release_date = "2020-03-24" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:issued "2020-03-24"^^xsd:date ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_theme() -> None: """It returns a theme graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.theme.append("http://example.com/themes/1") resource.theme.append("http://example.com/themes/2") src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dcat:theme <http://example.com/themes/1> , <http://example.com/themes/2> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_type() -> None: """It returns a type graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.type_genre = "http://example.com/concepts/1" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:type <http://example.com/concepts/1> ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_modification_date() -> None: """It returns a modified graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" resource.modification_date = "2020-03-24" src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix xsd: <http://www.w3.org/2001/XMLSchema#> . <http://example.com/datasets/1> a dcat:Dataset ; dct:modified "2020-03-24"^^xsd:date ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_to_graph_should_return_qualified_attributions() -> None: """It returns a qualified_attributions graph isomorphic to spec.""" resource = Dataset() resource.identifier = "http://example.com/datasets/1" qualified_attribution = {} qualified_attribution["agent"] = "http://example.com/agents/1" qualified_attribution[ "hadrole" ] = "http://registry.it.csiro.au/def/isotc211/CI_RoleCode/distributor" resource.qualified_attributions.append(qualified_attribution) src = """ @prefix dct: <http://purl.org/dc/terms/> . @prefix rdf: <http://www.w3.org/1999/02/22-rdf-syntax-ns#> . @prefix rdfs: <http://www.w3.org/2000/01/rdf-schema#> . @prefix dcat: <http://www.w3.org/ns/dcat#> . @prefix prov: <http://www.w3.org/ns/prov#> . <http://example.com/datasets/1> a dcat:Dataset ; prov:qualifiedAttribution [ a prov:Attribution ; prov:agent <http://example.com/agents/1> ; dcat:hadRole <http://registry.it.csiro.au/def/isotc211/CI_RoleCode/distributor> ] ; . """ g1 = Graph().parse(data=resource.to_rdf(), format="turtle") g2 = Graph().parse(data=src, format="turtle") _isomorphic = isomorphic(g1, g2) if not _isomorphic: _dump_diff(g1, g2) pass assert _isomorphic def test_serialization_formats_that_should_work() -> None: """It returns no exception.""" dataset = Dataset() dataset.identifier = "http://example.com/datasets/1" TURTLE = "text/turtle" XML = "application/rdf+xml" # TODO: this is to avoid a bug in rdflib, # ref https://github.com/RDFLib/rdflib/issues/1387 # JSONLD = "application/ld+json" JSONLD = "json-ld" NT = "application/n-triples" N3 = "text/n3" _g = Graph() _g.parse(data=dataset.to_rdf(format=TURTLE), format=TURTLE) _g.parse(data=dataset.to_rdf(format=XML), format=XML) _g.parse(data=dataset.to_rdf(format=JSONLD), format=JSONLD) _g.parse(data=dataset.to_rdf(format=NT, encoding=None), format=NT) _g.parse(data=dataset.to_rdf(format=N3), format=N3) # ---------------------------------------------------------------------- # # Utils for displaying debug information def _dump_diff(g1: Graph, g2: Graph) -> None: in_both, in_first, in_second = graph_diff(g1, g2) print("\nin both:") _dump_turtle(in_both) print("\nin first:") _dump_turtle(in_first) print("\nin second:") _dump_turtle(in_second) def _dump_turtle(g: Graph) -> None: for _l in g.serialize(format="turtle").splitlines(): if _l: print(_l)

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5

18bb4c10d244f0040b9e2b7f5f5814a004bf6ca3

169

py

Python

cmdb/hosts/handler.py

fox0014/cmdb

ef14411b6d637bb73a532f48409eb0f853367c34

[ "Apache-2.0" ]

null

cmdb/hosts/handler.py

fox0014/cmdb

ef14411b6d637bb73a532f48409eb0f853367c34

[ "Apache-2.0" ]

null

cmdb/hosts/handler.py

fox0014/cmdb

ef14411b6d637bb73a532f48409eb0f853367c34

[ "Apache-2.0" ]

null

from . models import Asset class Host(object): def __init__(self): self.name = '' def get_name(self): return Asset.objects.get(id='100').dc_id

18.777778

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5

18c9476e936a9107f80e09945f2cfaf29eef626d

6,895

py

Python

svae/dataset_utils/datasets.py

APodolskiy/SentenceVAE

afe82504922de700810b24638f7df0dbf1d8fa11

[ "MIT" ]

null

svae/dataset_utils/datasets.py

APodolskiy/SentenceVAE

afe82504922de700810b24638f7df0dbf1d8fa11

[ "MIT" ]

null

svae/dataset_utils/datasets.py

APodolskiy/SentenceVAE

afe82504922de700810b24638f7df0dbf1d8fa11

[ "MIT" ]

null

import os import random import re from typing import Optional, Sequence, Tuple, Union, List from tqdm import tqdm from torchtext.utils import unicode_csv_reader from torchtext.data import Dataset, Field, Example class PTB(Dataset): urls = ['https://raw.githubusercontent.com/wojzaremba/lstm/master/data/ptb.train.txt', 'https://raw.githubusercontent.com/wojzaremba/lstm/master/data/ptb.valid.txt', 'https://raw.githubusercontent.com/wojzaremba/lstm/master/data/ptb.test.txt'] name = 'ptb' dirname = '' def __init__(self, path: str, fields: Sequence[Tuple[str, Field]], max_len: Optional[int] = None, **kwargs): examples = [] with open(path, 'r') as fp: for line in tqdm(fp): if max_len is not None: line_parts = line.split() truncated_line_parts = line_parts[:max_len] line = ' '.join(truncated_line_parts) if line != '': examples.append(Example.fromlist(data=(line, line), fields=fields)) super().__init__(examples=examples, fields=fields, **kwargs) @classmethod def splits(cls, fields, max_len=None, root='data', train='ptb.train.txt', validation='ptb.valid.txt', test='ptb.test.txt', **kwargs): return super(PTB, cls).splits( root=root, train=train, validation=validation, test=test, fields=fields, max_len=max_len, **kwargs ) class YelpReview(Dataset): urls = ['https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9QhbZlU4dXhHTFhZQU0'] name = 'yelp_review' dirname = '' def __init__(self, path: str, fields: Sequence[Tuple[str, Field]], num_samples: Optional[int] = None, add_cls: bool = False, random_state: int = 162, max_len: Optional[int] = None, verbose: bool = True, **kwargs): duplicate_spaces_re = re.compile(r' +') with open(path, 'r', encoding='utf-8') as fp: all_data = [] reader = unicode_csv_reader(fp) for row in reader: cls, text = row[0], row[1] if max_len is not None and len(text.split()) > max_len: continue text = text.replace('\\n\\n', '\\n ') text = duplicate_spaces_re.sub(' ', text) data = (text, text, cls) if add_cls else (text, text) all_data.append(data) if num_samples is not None and num_samples < len(all_data): random.seed(random_state) all_data = random.sample(all_data, num_samples) examples = [] for data in tqdm(all_data, desc='Converting data into examples', disable=not verbose): examples.append(Example.fromlist(data=data, fields=fields)) super().__init__(examples=examples, fields=fields, **kwargs) @classmethod def splits(cls, fields: Sequence[Tuple[str, Field]], root: str = 'data', split_ratio: Union[float, List[float]] = 0.7, stratified: bool = False, strata_field: str = 'label', num_samples: Optional[int] = None, add_cls: bool = False, random_state: int = 162, max_len: Optional[int] = None, verbose: bool = True, **kwargs): path = os.path.join(root, cls.name, 'train.csv') full_dataset = YelpReview(path=path, fields=fields, num_samples=num_samples, verbose=verbose, add_cls=add_cls, random_state=random_state, max_len=max_len, **kwargs) splitted_data = full_dataset.split(split_ratio=split_ratio, stratified=stratified, strata_field=strata_field) return splitted_data class YahooAnswers(Dataset): urls = ['https://drive.google.com/uc?export=download&id=0Bz8a_Dbh9Qhbd2JNdDBsQUdocVU'] name = 'yahoo_answers' dir_name = '' def __init__(self, path: str, fields: Sequence[Tuple[str, Field]], num_samples: Optional[int] = None, add_cls: bool = False, random_state: int = 162, max_len: Optional[int] = None, verbose: bool = True, **kwargs): duplicate_spaces_re = re.compile(r' +') with open(path, 'r', encoding='utf-8') as fp: all_data = [] reader = unicode_csv_reader(fp) for row in reader: cls, question_title, question_content, answer = row text = question_content + answer if max_len is not None and len(text.split()) > max_len: continue text = text.replace('\\n\\n', '\\n ') text = duplicate_spaces_re.sub(' ', text) data = (text, text, cls) if add_cls else (text, text) all_data.append(data) if num_samples is not None and num_samples < len(all_data): random.seed(random_state) all_data = random.sample(all_data, num_samples) examples = [] for data in tqdm(all_data, desc='Converting data into examples', disable=not verbose): examples.append(Example.fromlist(data=data, fields=fields)) super().__init__(examples=examples, fields=fields, **kwargs) @classmethod def splits(cls, fields: Sequence[Tuple[str, Field]], root: str = 'data', split_ratio: Union[float, List[float]] = 0.7, stratified: bool = False, strata_field: str = 'label', num_samples: Optional[int] = None, add_cls: bool = False, random_state: int = 162, max_len: Optional[int] = None, verbose: bool = True, **kwargs): path = os.path.join(root, cls.name, 'train.csv') full_dataset = YahooAnswers(path=path, fields=fields, num_samples=num_samples, verbose=verbose, add_cls=add_cls, random_state=random_state, max_len=max_len, **kwargs) splitted_data = full_dataset.split(split_ratio=split_ratio, stratified=stratified, strata_field=strata_field) return splitted_data if __name__ == '__main__': tokenize = lambda x: x.strip().split() text_field = Field(sequential=True, use_vocab=True, init_token='<s>', eos_token='</s>', tokenize=tokenize, include_lengths=True) print(PTB.splits(fields=(('inp', text_field), ('trg', text_field))))

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null

0

1

0

null

0

5

18ea552e07ec066510829144e8bd7362e763ceda

703

py

Python

webelementspy/__version__.py

0xYasser/webelementspy

5780426f9a371763afcac2b2b782be9ef1c890b7

[ "MIT" ]

1

2021-12-10T00:05:29.000Z

webelementspy/__version__.py

0xYasser/webelementspy

5780426f9a371763afcac2b2b782be9ef1c890b7

[ "MIT" ]

null

webelementspy/__version__.py

0xYasser/webelementspy

5780426f9a371763afcac2b2b782be9ef1c890b7

[ "MIT" ]

null

# _ _ _ # | | | | | | # __ _____| |__ ___| | ___ _ __ ___ ___ _ __ | |_ ___ _ __ _ _ # \ \ /\ / / _ \ '_ \ / _ \ |/ _ \ '_ ` _ \ / _ \ '_ \| __/ __| '_ \| | | | # \ V V / __/ |_) | __/ | __/ | | | | | __/ | | | |_\__ \ |_) | |_| | # \_/\_/ \___|_.__/ \___|_|\___|_| |_| |_|\___|_| |_|\__|___/ .__/ \__, | # | | __/ | # |_| |___/ __version__ = '0.0.5'

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1

0

null

0

5

e14ed9ea079c35f0c1fe99727d05c5a0f4b7fd00

137

py

Python

test/test_uom.py

Nukleon84/openikcape

7612a7c68237920373c11f137130d74f7ad134eb

[ "MIT" ]

19

2020-09-08T07:23:10.000Z

2022-01-10T19:12:51.000Z

test/test_uom.py

Nukleon84/openikcape

7612a7c68237920373c11f137130d74f7ad134eb

[ "MIT" ]

null

test/test_uom.py

Nukleon84/openikcape

7612a7c68237920373c11f137130d74f7ad134eb

[ "MIT" ]

2

2020-09-09T15:10:39.000Z

2021-08-05T00:53:28.000Z

import sys sys.path.append('bin') import openikcape as ikc def test_add(): assert ikc.add(2,3) == 5 assert ikc.add(5,-2) == 3

13.7

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0.635036

25

137

3.44

0.6

0.209302

0.27907

0

0.055046

0.20438

137

10

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null

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1

0

1

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5

e16bdd8f380df743a2913b3198951a172de688ae

58

py

Python

src/labster/domain2/__init__.py

jean3108/labandco

4317e7d3875f10d76076ad5fc68c1ba3c12badba

[ "Apache-2.0" ]

2

2019-11-11T22:09:58.000Z

2020-01-20T19:44:30.000Z

src/labster/domain2/__init__.py

jean3108/labandco

4317e7d3875f10d76076ad5fc68c1ba3c12badba

[ "Apache-2.0" ]

15

2020-03-31T10:58:37.000Z

2022-01-22T09:14:49.000Z

src/labster/domain2/__init__.py

jean3108/labandco

4317e7d3875f10d76076ad5fc68c1ba3c12badba

[ "Apache-2.0" ]

2

2021-05-28T12:20:24.000Z

2021-09-08T11:27:57.000Z

"""Nouveau domaine.""" from __future__ import annotations

19.333333

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null

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1

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1

0

1

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5

e16fb93807cc2a860fe040bb0335f2512eff814e

50

py

Python

visdialch/utils/__init__.py

shubhamagarwal92/visdial-challenge-starter-pytorch

556def30bbce2fadb6a818637b21d29a89ec1a9f

[ "BSD-3-Clause" ]

187

2018-07-09T00:41:08.000Z

2022-03-20T01:39:18.000Z

visdialch/utils/__init__.py

shubhamagarwal92/visdial-challenge-starter-pytorch

556def30bbce2fadb6a818637b21d29a89ec1a9f

[ "BSD-3-Clause" ]

39

2018-07-12T13:29:38.000Z

2022-03-11T23:36:51.000Z

visdialch/utils/__init__.py

qmdnls/efficient-attention-visdial

474ceb338b5f5dbed8236fc59212a4debcb40576

[ "BSD-3-Clause" ]

56

2018-07-13T14:12:22.000Z

2022-02-06T16:51:58.000Z

from .dynamic_rnn import DynamicRNN # noqa: F401

25

49

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5.428571

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1

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0.833333

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true

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null

0

1

0

1

0

1

0

5

e17b590fa5c94f2de56d4338cb3cb1220107bb48

185

py

Python

Django/Django Ecomerce/sales/admin.py

Akhadafi/WEB-Framework

4547a682ac1f007aa6f97512baf76b92ef1c9b9a

[ "MIT" ]

null

Django/Django Ecomerce/sales/admin.py

Akhadafi/WEB-Framework

4547a682ac1f007aa6f97512baf76b92ef1c9b9a

[ "MIT" ]

null

Django/Django Ecomerce/sales/admin.py

Akhadafi/WEB-Framework

4547a682ac1f007aa6f97512baf76b92ef1c9b9a

[ "MIT" ]

null

from django.contrib import admin from .models import CSV, Position, Sale # Register your models here. admin.site.register(Position) admin.site.register(Sale) admin.site.register(CSV)

20.555556

39

0.794595

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185

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true

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null

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1

0

5

e1bccbba17084326e5a73d49d9e45a469cf8be9a

172

py

Python

0x02project_candy_name_generator/main.py

walleieve/Reverse-Engineering

c1d018c623e4ed71ea17583c296a1342376172a7

[ "Apache-2.0" ]

3,418

2020-02-21T11:21:35.000Z

2021-03-24T19:23:12.000Z

0x02project_candy_name_generator/main.py

momed081/Reverse-Engineering

dc08977f55ea21d482963e9b1e2fb21454ed0c0d

[ "Apache-2.0" ]

6

2020-09-30T05:51:52.000Z

2020-10-01T15:52:45.000Z

0x02project_candy_name_generator/main.py

momed081/Reverse-Engineering

dc08977f55ea21d482963e9b1e2fb21454ed0c0d

[ "Apache-2.0" ]

317

2021-03-25T01:29:35.000Z

2022-03-29T07:08:44.000Z

candy_title = input('What is the candy title? ') candy_flavor = input('What is the candy flavor? ') print('It shall be called {0} {1}!'.format(candy_title, candy_flavor))

34.4

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0.184874

0.235294

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5

bed6ee2c5c0270c9330264ae9bf48e09e8ff3b8f

10,951

py

Python

tests/test_orm.py

Alphasite/python-sqlalchemy

cba658a6876f219fc817591d1f0abd0c344bbfd4

[ "Apache-2.0" ]

16

2017-09-03T17:33:58.000Z

2021-08-05T15:43:51.000Z

tests/test_orm.py

Alphasite/python-sqlalchemy

cba658a6876f219fc817591d1f0abd0c344bbfd4

[ "Apache-2.0" ]

9

2017-09-01T15:26:28.000Z

2020-12-04T08:28:30.000Z

tests/test_orm.py

Alphasite/python-sqlalchemy

cba658a6876f219fc817591d1f0abd0c344bbfd4

[ "Apache-2.0" ]

14

2017-10-16T05:26:22.000Z

2021-04-05T10:12:24.000Z

import unittest from sqlalchemy import create_engine, MetaData, Table, Column, Integer, String from sqlalchemy.ext.declarative import declarative_base from sqlalchemy.exc import IntegrityError, OperationalError from sqlalchemy.orm import sessionmaker import sqlalchemy_opentracing from .dummies import * Base = declarative_base() class User(Base): __tablename__ = 'users' id = Column(Integer, primary_key=True) name = Column(String) class TestSQLAlchemyORM(unittest.TestCase): def setUp(self): self.engine = create_engine('sqlite:///:memory:') self.session = sessionmaker(bind=self.engine)() User.metadata.create_all(self.engine) def tearDown(self): sqlalchemy_opentracing._clear_tracer() def test_traced_simple(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session sqlalchemy_opentracing.set_traced(session) session.add(User(name='John Doe')) session.commit() self.assertEqual(1, len(tracer.spans)) self.assertEqual('insert', tracer.spans[0].operation_name) self.assertEqual(True, tracer.spans[0].is_finished) self.assertEqual(tracer.spans[0].tags, { 'component': 'sqlalchemy', 'db.statement': 'INSERT INTO users (name) VALUES (?)', 'db.type': 'sql', 'sqlalchemy.dialect': 'sqlite', }) def test_traced_none(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session session.add(User(name='John Doe')) session.commit() self.assertEqual(0, len(tracer.spans)) # test that when trace all is not True, we get nothing. # test mixing insert with select and insert def test_traced_all(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, trace_all_queries=True) sqlalchemy_opentracing.register_engine(self.engine) session = self.session session.add(User(name='John Doe')) session.add(User(name='Jason Bourne')) session.add(User(name='Foo Bar')) session.commit() self.assertEqual(3, len(tracer.spans)) self.assertEqual(True, all(map(lambda x: x.operation_name == 'insert', tracer.spans))) self.assertEqual(True, all(map(lambda x: x.is_finished, tracer.spans))) def test_traced_error(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) # Don't trace this one. session = self.session session.add(User(name='John Doe', id=1)) session.commit() # Trace this one. sqlalchemy_opentracing.set_traced(session) session.add(User(name='John Doe', id=1)) try: session.commit() except IntegrityError: pass self.assertEqual(1, len(tracer.spans)) self.assertEqual('insert', tracer.spans[0].operation_name) self.assertEqual(True, tracer.spans[0].is_finished) self.assertEqual(tracer.spans[0].tags, { 'component': 'sqlalchemy', 'db.statement': 'INSERT INTO users (id, name) VALUES (?, ?)', 'db.type': 'sql', 'sqlalchemy.dialect': 'sqlite', 'sqlalchemy.exception': 'UNIQUE constraint failed: users.id', 'error': 'true', }) def test_traced_parent(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session parent_span = DummySpan('parent') sqlalchemy_opentracing.set_parent_span(session, parent_span) session.query(User).all() session.query(User).all() session.commit() self.assertEqual(2, len(tracer.spans)) self.assertEqual(True, all(map(lambda x: x.operation_name == 'select', tracer.spans))) self.assertEqual(True, all(map(lambda x: x.is_finished, tracer.spans))) self.assertEqual(True, all(map(lambda x: x.child_of == parent_span, tracer.spans))) def test_traced_text(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session span = DummySpan('parent span') sqlalchemy_opentracing.set_parent_span(session, span) session.execute('SELECT name FROM users') self.assertEqual(1, len(tracer.spans)) self.assertEqual(tracer.spans[0].operation_name, 'textclause') self.assertEqual(tracer.spans[0].is_finished, True) self.assertEqual(tracer.spans[0].child_of, span) self.assertEqual(tracer.spans[0].tags, { 'component': 'sqlalchemy', 'db.statement': 'SELECT name FROM users', 'db.type': 'sql', 'sqlalchemy.dialect': 'sqlite', }) def test_traced_text_error(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session span = DummySpan('parent span') sqlalchemy_opentracing.set_parent_span(session, span) try: session.execute('SELECT zipcode FROM addresses') except OperationalError: pass self.assertEqual(1, len(tracer.spans)) self.assertEqual(tracer.spans[0].operation_name, 'textclause') self.assertEqual(tracer.spans[0].is_finished, True) self.assertEqual(tracer.spans[0].child_of, span) self.assertEqual(tracer.spans[0].tags, { 'component': 'sqlalchemy', 'db.statement': 'SELECT zipcode FROM addresses', 'db.type': 'sql', 'sqlalchemy.dialect': 'sqlite', 'sqlalchemy.exception': 'no such table: addresses', 'error': 'true', }) def test_traced_after_commit(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session sqlalchemy_opentracing.set_traced(session) session.add(User(name='John Doe')) session.commit() self.assertEqual(1, len(tracer.spans)) tracer.clear() # Issue a pair of statements, # making sure we are not tracing # the session's transaction anymore. session.add(User(name='Jason Bourne')) session.query(User).all() session.commit() self.assertEqual(0, len(tracer.spans)) def test_traced_after_rollback(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session sqlalchemy_opentracing.set_traced(session) session.query(User).all() # will be evaluated RIGHT AWAY session.add(User(name='John Doe')) # delayed (not committed) session.rollback() self.assertEqual(1, len(tracer.spans)) self.assertEqual(True, tracer.spans[0].is_finished) self.assertEqual('select', tracer.spans[0].operation_name) tracer.clear() # Rollback should have stopped # the tracing for this session session.query(User).all() session.add(User(name='Jason Bourne')) session.commit() self.assertEqual(0, len(tracer.spans)) def test_traced_commit_repeat(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) parent_span1 = DummySpan('parent1') session = self.session sqlalchemy_opentracing.set_parent_span(session, parent_span1) session.add(User(name='John Doe')) session.commit() self.assertEqual(1, len(tracer.spans)) self.assertEqual(True, tracer.spans[0].is_finished) self.assertEqual(parent_span1, tracer.spans[0].child_of) # Register the session again for tracing, # now with a different parent span parent_span2 = DummySpan('parent2') sqlalchemy_opentracing.set_parent_span(session, parent_span2) session.add(User(name='Jason Bourne')) session.commit() self.assertEqual(2, len(tracer.spans)) self.assertEqual(True, tracer.spans[1].is_finished) self.assertEqual(parent_span2, tracer.spans[1].child_of) @unittest.skip('SQLite doesnt properly handle savepoints') def test_traced_savepoint(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session sqlalchemy_opentracing.set_traced(session) session.add(User(name='John Doe')) session.begin_nested() session.add(User(name='Jason Bourne')) session.commit() session.add(User(name='Paris Texas')) session.commit() self.assertEqual(3, len(tracer.spans)) self.assertEqual(True, all(map(lambda x: x.is_finished, tracer.spans))) def test_traced_bulk_insert(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) parent_span = DummySpan('parent') session = self.session sqlalchemy_opentracing.set_parent_span(session, parent_span) users = [User(name = 'User-%s' % i) for i in xrange(10)] session.bulk_save_objects(users) self.assertEqual(1, len(tracer.spans)) self.assertEqual(True, tracer.spans[0].is_finished) self.assertEqual(parent_span, tracer.spans[0].child_of) self.assertEqual(tracer.spans[0].tags, { 'component': 'sqlalchemy', 'db.statement': 'INSERT INTO users (name) VALUES (?)', 'db.type': 'sql', 'sqlalchemy.dialect': 'sqlite', }) def test_traced_clear_session(self): tracer = DummyTracer() sqlalchemy_opentracing.init_tracing(tracer, False, False) sqlalchemy_opentracing.register_engine(self.engine) session = self.session sqlalchemy_opentracing.set_traced(session) session.add(User(name='John Doe')) session.add(User(name='Jason Bourne')) # Clear the tracing info right before committing. sqlalchemy_opentracing.clear_traced(session) session.commit() self.assertEqual(0, len(tracer.spans))

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94

0.652908

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0.756699

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0.664565

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10,951

293

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1

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null

0

5

bed917d8b1eea14ad171fca3d22623d2582538b9

295

py

Python

tests/test_actions.py

Speccy-Rom/BigFile

ad0911776613d8735be167a68727f3c4e51a797c

[ "MIT" ]

null

tests/test_actions.py

Speccy-Rom/BigFile

ad0911776613d8735be167a68727f3c4e51a797c

[ "MIT" ]

null

tests/test_actions.py

Speccy-Rom/BigFile

ad0911776613d8735be167a68727f3c4e51a797c

[ "MIT" ]

null

# Relative Import import sys sys.path.append("..") # END Relative Import from app.actions import get_file_size def test_get_file_size(): # assert isinstance(get_file_size('test.txt', '../uploaded_files/'), int) == True assert isinstance(get_file_size('test.txt', './'), int) == True

22.692308

85

0.701695

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null

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0

1

0

1

0

5

bed965ba9ad484d0177265b36fd60cc7f1c89480

9,056

py

Python

plugins/hsqc/fonc_util.py

bsavelev/medipy

f0da3750a6979750d5f4c96aedc89ad5ae74545f

[ "CECILL-B" ]

null

plugins/hsqc/fonc_util.py

bsavelev/medipy

f0da3750a6979750d5f4c96aedc89ad5ae74545f

[ "CECILL-B" ]

null

plugins/hsqc/fonc_util.py

bsavelev/medipy

f0da3750a6979750d5f4c96aedc89ad5ae74545f

[ "CECILL-B" ]

1

2022-03-04T05:47:08.000Z

""" Functions used in Metabolite annotation """ import numpy as np from scipy.interpolate import interpolate from scipy.optimize import leastsq def find(a,cond): b=np.nonzero(cond) return b def cauchy(p2,p3): siz=(p2-1)/2*(np.ones(2)) xxrange = np.arange(-siz[1],siz[1]+1) yyrange = np.arange(-siz[1],siz[1]+1) X,Y = np.meshgrid(xxrange,yyrange) arg=((1/(p3[0]*3.14159))/((1/p3[0])**2+(X*X)))*((1/(p3[1]*3.14159))/((1/p3[1])**2+(Y*Y))) eps=2.2204*10**(-16) h=arg h[h<(eps*np.amax(h))]=0 sumh=np.sum(h) if sumh!=0: h=h/sumh h=h/np.amax(h) return h def expon(p2,p3): siz=(p2-1)/2*(np.ones(2)) xxrange = np.arange(-siz[1],siz[1]+1) yyrange = np.arange(-siz[1],siz[1]+1) X,Y = np.meshgrid(xxrange,yyrange) #arg=((1/p3[0])/((1/p3[0])**2+(X*X)))*((1/p3[1])/((1/p3[1])**2+(Y*Y))) arg=(1/6.28)*(1/p3[0])*np.exp(-X*X/(2*p3[0]**2))*(1/p3[1])*np.exp(-X*X/(2*p3[1]**2)) eps=2.2204*10**(-16) h=arg h[h<(eps*np.amax(h))]=0 sumh=np.sum(h) if sumh!=0: h=h/sumh h=h/np.amax(h) return h def exponcauchy(p2,p3): siz=(p2-1)/2*(np.ones(2)) xxrange = np.arange(-siz[1],siz[1]+1) yyrange = np.arange(-siz[1],siz[1]+1) X,Y = np.meshgrid(xxrange,yyrange) #arg=((1/p3[0])/((1/p3[0])**2+(X*X)))*((1/p3[1])/((1/p3[1])**2+(Y*Y))) arg=(1/3.14159)*(1/p3[0])*np.exp(-X*X/(2*p3[0]**2))*((1/(p3[1]*3.14159))/((1/p3[1])**2+(Y*Y))) eps=2.2204*10**(-16) h=arg h[h<(eps*np.amax(h))]=0 sumh=np.sum(h) if sumh!=0: h=h/sumh h=h/np.amax(h) return h def cauchyexpon(p2,p3): siz=(p2-1)/2*(np.ones(2)) xxrange = np.arange(-siz[1],siz[1]+1) yyrange = np.arange(-siz[1],siz[1]+1) X,Y = np.meshgrid(xxrange,yyrange) #arg=((1/p3[0])/((1/p3[0])**2+(X*X)))*((1/p3[1])/((1/p3[1])**2+(Y*Y))) arg=((1/(p3[0]*3.14159))/((1/p3[0])**2+(X*X)))*(1/3.14159)*(1/p3[1])*np.exp(-Y*Y/(2*p3[0]**2)) eps=2.2204*10**(-16) h=arg h[h<(eps*np.amax(h))]=0 sumh=np.sum(h) if sumh!=0: h=h/sumh h=h/np.amax(h) return h def subpix2(z,ii,jj): trange = np.arange(7) ttrange = np.arange(7) X,Y = np.meshgrid(trange,ttrange) outgrid = interpolate.interp2d(X,Y,z,kind='quintic') xx=yy=np.arange(61)/10. l=outgrid(xx,yy) l=l[30-9:30+10,30-9:30+10] ind=find(l,l==np.amax(l)) #print l #print ind[0][0],ind[1][0] ni=ii+(ind[0][0]-9.)/10 nj=jj+(ind[1][0]-9.)/10 #print ii,jj #print ni,nj return[ni,nj] def dephcl(z): e = lambda v,z,: np.sum(np.abs(z-z[9,9]*cauchy(19,v)),1) vi=[0.3,0.3] v, success = leastsq(e, vi, args=(z), maxfev=1000) if v[0]<0.001 or v[0]>2 or v[1]<0.001 or v[1]>2 : v[0]=v[1]=0.3+np.random.normal(0, 0.05, 1) return v def dephcg(z): e = lambda v,z,: np.sum(np.abs(z-z[9,9]*expon(19,v)),1) vi=[1,1] #z[z<0]=0 v, success = leastsq(e, vi, args=(z), maxfev=1000) if v[0]<0.1 or v[0]>4 or v[1]<0.1 or v[1]>4 : v[0]=v[1]=2+np.random.normal(0, 0.05, 1) return v def dephcaprio(z,a,b,c): if c[0]=='g' and c[1]=='g': e = lambda v,z,: np.sum(np.abs(z-z[9,9]*expon(19,v)),1) vi=[a,b] #z[z<0]=0 v, success = leastsq(e, vi, args=(z), maxfev=1000) if np.abs(float(v[0]-a))>1 or v[0]<0.5 or v[0]>6: v[0]=a+np.random.normal(0, 0.05, 1) if np.abs(float(v[1]-b))>1 or v[0]<0.5 or v[0]>6: v[1]=b+np.random.normal(0, 0.05, 1) if c[0]=='l' and c[1]=='l': e = lambda v,z,: np.sum(np.abs(z-z[9,9]*cauchy(19,v)),1) a=float(1/float(a)) b=float(1/float(b)) vi=[a,b] v, success = leastsq(e, vi, args=(z), maxfev=1000) #print vi if np.abs(float(v[0]-float(1/float(a))))>0.5 or v[0]<0.08 or v[0]>4: v[0]=a+np.random.normal(0, 0.05, 1) #print float(1/float(a)) v[0]=1/v[0] if np.abs(float(v[1]-float(1/float(b))))>0.5 or v[1]<0.08 or v[1]>4: v[1]=b+np.random.normal(0, 0.05, 1) v[1]=1/v[1] if c[0]=='g' and c[1]=='l': e = lambda v,z,: np.sum(np.abs(z-z[9,9]*exponcauchy(19,v)),1) b=float(1/float(b)) vi=[a,b] v, success = leastsq(e, vi, args=(z), maxfev=1000) #print 'ham',v #print vi if np.abs(float(v[0]-a))>1 or v[0]<0.5 or v[0]>6: v[0]=a+np.random.normal(0, 0.05, 1) #print float(1/float(a)) if np.abs(float(v[1]-float(b)))>0.5 or v[1]<0.08 or v[1]>4: v[1]=b+np.random.normal(0, 0.05, 1) v[1]=1/v[1] if c[0]=='l' and c[1]=='g': e = lambda v,z,: np.sum(np.abs(z-z[9,9]*cauchyexpon(19,v)),1) a=float(1/float(a)) vi=[a,b] v, success = leastsq(e, vi, args=(z), maxfev=1000) #print vi if np.abs(float(v[1]-b))>1 or v[0]<0.5 or v[0]>6: v[1]=b+np.random.normal(0, 0.05, 1) #print float(1/float(a)) if np.abs(float(v[0]-float(1/float(a))))>0.5 or v[1]<0.08 or v[1]>4: v[0]=a+np.random.normal(0, 0.05, 1) v[0]=1/v[0] #print c #print vi #print v return v,c def exp_hand(z,newn): c=0 for i in range(len(z)): if z[i]==newn: c=1 break return c def exp_yn(amp,ampref,test): artest=np.array(test) ol=np.nonzero(artest==1) #print np.size(ol) #print len(amp)/2 #print amp if np.size(ol)>len(amp)/2: ver=0 else: o=np.nonzero(artest==0) vamp=np.array(amp) vampref=np.array(ampref) ivamref=vampref[o] ivam=vamp[o] ii=ivamref[ivamref==np.amax(ivamref)] jj=ivam[ivamref==np.amax(ivamref)] ver=1 if np.size(ol)>1: ol=ol[0] #print np.size(ol) #print vampref #print vamp #print ol if np.size(ol)>1: for kkk in range(np.size(ol)): #print float(((vampref[ol[kkk]]/ii)/(vamp[ol[kkk]]/jj))) if (((vampref[ol[kkk]]/ii)/(vamp[ol[kkk]]/jj)))>50 or (((vampref[ol[kkk]]/ii)/(vamp[ol[kkk]]/jj)))<0.0200: #print 'lela' ver=0 else: for kkk in range(np.size(ol)): #print float(((vampref[ol[kkk]][0]/ii)/(vamp[ol[kkk]][0]/jj))[0]) <0.001 if (((vampref[ol[kkk]][0]/ii)/(vamp[ol[kkk]][0]/jj))[0])>50 or (((vampref[ol[kkk]][0]/ii)/(vamp[ol[kkk]][0]/jj))[0])<0.0200: #print 'lela' ver=0 return ver def exp_ync(amp,ampref,test): artest=np.array(test) ol=np.nonzero(artest==1) #print np.size(ol) #print len(amp)/2 if np.size(ol)>len(amp)/2: ver=0 else: o=np.nonzero(artest==0) vamp=np.array(amp) vampref=np.array(ampref) ivamref=vampref[o] ivam=vamp[o] ii=ivamref[ivamref==np.amax(ivamref)] jj=ivam[ivamref==np.amax(ivamref)] ver=1 if np.size(ol)>1: ol=ol[0] #print np.size(ol) #print vampref #print vamp #print ol if np.size(ol)>1: for kkk in range(np.size(ol)): #print float(((vampref[ol[kkk]]/ii)/(vamp[ol[kkk]]/jj))) if (((vampref[ol[kkk]]/ii)/(vamp[ol[kkk]]/jj)))>10 or (((vampref[ol[kkk]]/ii)/(vamp[ol[kkk]]/jj)))<0.065: #print 'lela' ver=0 else: for kkk in range(np.size(ol)): #print float(((vampref[ol[kkk]][0]/ii)/(vamp[ol[kkk]][0]/jj))[0]) if (((vampref[ol[kkk]][0]/ii)/(vamp[ol[kkk]][0]/jj))[0])>10 or (((vampref[ol[kkk]][0]/ii)/(vamp[ol[kkk]][0]/jj))[0])<0.065: #print 'lela' ver=0 return ver def ser_mat(tabp): boc=-1 inp=[] inm=[] while boc<len(tabp)-1: boc+=1 a=str(tabp[boc][2]) newn='' for j in range(len(a)): if (a[j]=='_')==1: break newn+=a[j] r1=[] r1.append((boc)) for jj in range(boc+1,len(tabp)): nomn=str(tabp[jj][2]) #print nomn[0:j] try: if nomn[0:j+1]==newn+'_': r1.append((jj)) #print 'ok' else: break except: break boc=boc+len(r1)-1 inm.append(newn) inp.append(r1) return inm,inp def tab2tab(X): Z=[] for i in range(len(X)): Z.append([X[i]]) Z=np.array(Z) return Z def norm(a,b,c): A=(float(a)/float(a+b))*float(c) B=(float(b)/float(a+b))*float(c) return A,B

31.227586

140

0.461241

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0.088146

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0.026852

0.031647

0.768401

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0.738672

0.72069

0.710141

0

0.096255

0.307089

9,056

289

141

31.33564

0.568446

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false

0

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0

0.142857

0

null

0

1

0

null

0

5

bee34e1830547095a2405bf09511a1314eff0191

55

py

Python

IDRSolutions/__init__.py

idrsolutions/idrsolutions-python-client

f92869333ed41ca80ed068a5d7be96bd1e7b8984

[ "Apache-2.0" ]

2

2020-08-27T06:46:58.000Z

2020-12-01T14:48:41.000Z

IDRSolutions/__init__.py

idrsolutions/idrsolutions-python-client

f92869333ed41ca80ed068a5d7be96bd1e7b8984

[ "Apache-2.0" ]

null

IDRSolutions/__init__.py

idrsolutions/idrsolutions-python-client

f92869333ed41ca80ed068a5d7be96bd1e7b8984

[ "Apache-2.0" ]

null

from IDRSolutions.IDRCloudClient import IDRCloudClient

27.5

54

0.909091

5

55

10

0.8

0

0.072727

55

1

55

0.980392

0

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true

0

1

0

1

0

1

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null

0

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0

null

0

1

0

1

0

1

0

5

834b3df19e9e823fcd60b3991391837a47e5bca4

57

py

Python

string/12string_count.py

senthilraja112/Learn_python

0135544c5d6febdc70f4c7d1dbeee5326bfb534e

[ "MIT" ]

4

2017-08-22T19:14:09.000Z

2017-09-08T12:02:41.000Z

string/12string_count.py

senthilraja112/Learn_python

0135544c5d6febdc70f4c7d1dbeee5326bfb534e

[ "MIT" ]

1

2017-09-04T07:47:10.000Z

2021-02-23T14:50:54.000Z

string/12string_count.py

senthilraja112/Learn_python

0135544c5d6febdc70f4c7d1dbeee5326bfb534e

[ "MIT" ]

2

2018-10-20T16:56:30.000Z

2019-02-01T06:46:24.000Z

s = "abcsssaa" print(s.count('a')) print(s.count('s'))

9.5

19

0.578947

10

57

3.3

0.5

0.363636

0.666667

0

0.122807

57

5

20

11.4

0.66

0

0.175439

0

1

0

false

0

0.666667

1

0

null

1

0

1

0

null

0

1

0

5

8367743bb662fcabca5355deea2a552e23981457

117

py

Python

application/database/redis_client.py

alirzaev/fastapi-auth-service

c843874d117282385b064ff6bd875e1b0f12d9d5

[ "MIT" ]

null

application/database/redis_client.py

alirzaev/fastapi-auth-service

c843874d117282385b064ff6bd875e1b0f12d9d5

[ "MIT" ]

null

application/database/redis_client.py

alirzaev/fastapi-auth-service

c843874d117282385b064ff6bd875e1b0f12d9d5

[ "MIT" ]

null

import aioredis from application.core.config import config redis_client = aioredis.from_url(config.REDIS_URL)

19.5

51

0.803419

16

117

5.6875

0.5625

0.263736

0

0.136752

117

5

52

23.4

0.90099

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

55d090c603c6b7e29be4c8c7bb76d2dc974f39b3

116

py

Python

test.py

abhinavrawat882/FpsShooter

9c9dac7fa4995326c6c0334bbd6bb0d94326edf9

[ "MIT" ]

null

test.py

abhinavrawat882/FpsShooter

9c9dac7fa4995326c6c0334bbd6bb0d94326edf9

[ "MIT" ]

null

test.py

abhinavrawat882/FpsShooter

9c9dac7fa4995326c6c0334bbd6bb0d94326edf9

[ "MIT" ]

null

a=[[1,2,3],[4,5,6]] b=[[0,0],[0,0],[0,0]] for i in range(3): for y in range(2): b[i][y]=a[y][i] print(b)

19.333333

23

0.431034

32

116

1.5625

0.46875

0.2

0.24

0.12

0

0.150538

0.198276

116

6

24

19.333333

0.387097

0

1

0

false

0

0.166667

0

1

null

0

1

0

1

0

1

0

null

0

5

55dab8795620cc1f2b1179710deecca5c3b27021

104

py

Python

telegraph/__init__.py

ds19991999/ONote

29f9fed5625e83aec0521cde0d4ede788484e2db

[ "MIT" ]

2

2019-12-05T12:54:15.000Z

2020-02-01T17:27:36.000Z

telegraph/__init__.py

ds19991999/ONote

29f9fed5625e83aec0521cde0d4ede788484e2db

[ "MIT" ]

1

2019-12-05T12:45:32.000Z

telegraph/__init__.py

ds19991999/ONote

29f9fed5625e83aec0521cde0d4ede788484e2db

[ "MIT" ]

1

2021-08-25T03:34:31.000Z

#!/usr/bin/env python # -*- coding:utf-8 -*- from .api import Telegraph from .telenote import TeleNote

17.333333

30

0.701923

15

104

4.866667

0.8

0

0.011236

0.144231

104

6

30

17.333333

0.808989

0.394231

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

3606720052bd3df90c2aadb6f25ca784ec9e42d6

48

py

Python

servo/__main__.py

johnnewman/PiServoServer

410675570a196d7ce48dce5d0010d785e50f1587

[ "MIT" ]

1

2018-11-19T20:47:06.000Z

servo/__main__.py

johnnewman/PiServoServer

410675570a196d7ce48dce5d0010d785e50f1587

[ "MIT" ]

null

servo/__main__.py

johnnewman/PiServoServer

410675570a196d7ce48dce5d0010d785e50f1587

[ "MIT" ]

null

import server server.ServoServer(9338).start()

12

32

0.791667

6

48

6.333333

0.833333

0

0.090909

0.083333

48

3

33

16

0.772727

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

3611d03412ee85f9b490d2a96c1780e8016fdae1

26

py

Python

zbarcam/version.py

evilboss/qrReader

794fbb2338808b0edde172f82fc43d6349ff6779

[ "MIT" ]

null

zbarcam/version.py

evilboss/qrReader

794fbb2338808b0edde172f82fc43d6349ff6779

[ "MIT" ]

null

zbarcam/version.py

evilboss/qrReader

794fbb2338808b0edde172f82fc43d6349ff6779

[ "MIT" ]

null

__version__ = '2017.1220'

13

25

0.730769

3

26

5

1

0

0.347826

0.115385

26

1

26

0.304348

0

0.346154

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

5

3612907dc83cbe64e756042cc96aaf8383998f1a

243

py

Python

website/models.py

Vorsku/certiphy

613610236e50e2d1ea362efe0550dae7d75e95ef

[ "MIT" ]

null

website/models.py

Vorsku/certiphy

613610236e50e2d1ea362efe0550dae7d75e95ef

[ "MIT" ]

1

2022-03-15T06:21:34.000Z

website/models.py

Vorsku/certiphy

613610236e50e2d1ea362efe0550dae7d75e95ef

[ "MIT" ]

null

from . import db class Monitors(db.Model): id = db.Column(db.Integer, primary_key=True) domain = db.Column(db.String(100)) port = db.Column(db.Integer) status = db.Column(db.String(150)) expires = db.Column(db.String(100))

30.375

48

0.670782

38

243

4.263158

0.5

0.246914

0.308642

0.296296

0.234568

0

0.044776

0.17284

243

8

49

30.375

0.761194

0

1

0

false

0

0.142857

0

1

0

null

1

0

1

0

null

0

1

0

5

362c6f77e6c4454beee85205a1b55726488f2d47

86

py

Python

8KYU/pipe_fix.py

yaznasivasai/python_codewars

25493591dde4649dc9c1ec3bece8191a3bed6818

[ "MIT" ]

4

2021-07-17T22:48:03.000Z

2022-03-25T14:10:58.000Z

8KYU/pipe_fix.py

yaznasivasai/python_codewars

25493591dde4649dc9c1ec3bece8191a3bed6818

[ "MIT" ]

null

8KYU/pipe_fix.py

yaznasivasai/python_codewars

25493591dde4649dc9c1ec3bece8191a3bed6818

[ "MIT" ]

3

2021-06-14T14:18:16.000Z

2022-03-16T06:02:02.000Z

def pipe_fix(nums: list) -> list: return [n for n in range(nums[0], nums[-1] + 1)]

43

52

0.604651

17

86

3

0.705882

0

0.043478

0.197674

86

2

52

43

0.695652

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

364fbca1e02c0127edaa2676d13f42a919ae138a

4,420

py

Python

scripts/config/user_input/console.py

bosepchuk/Ada_Drivers_Library

f123af4fb8bb411021a19e8d366549e4d8c04e29

[ "BSD-3-Clause" ]

6

2017-05-28T04:37:11.000Z

2020-11-22T11:26:19.000Z

scripts/config/user_input/console.py

bosepchuk/Ada_Drivers_Library

f123af4fb8bb411021a19e8d366549e4d8c04e29

[ "BSD-3-Clause" ]

2

2019-08-30T10:57:40.000Z

2020-02-11T21:34:14.000Z

scripts/config/user_input/console.py

bosepchuk/Ada_Drivers_Library

f123af4fb8bb411021a19e8d366549e4d8c04e29

[ "BSD-3-Clause" ]

2

2017-02-07T19:42:02.000Z

2020-11-22T11:26:20.000Z

#! python import sys def valid_int(str): try: int(str) return True except ValueError: return False def valid_float(str): try: float(str) return True except ValueError: return False def query_bool(question, default="yes"): valid = {"yes": 'True', "y": 'True', "ye": 'True', "True": 'True', "no": 'False', "n": 'False', "False": 'False'} if default is None and default not in valid: prompt = " [y/n]\n" elif default == "yes" or default == 'y' or default == "True": prompt = " [Y/n]\n" elif default == "no" or default == 'n' or default == "False": prompt = " [y/N]\n" else: raise ValueError("invalid default answer: '%s'" % default) while True: sys.stdout.write(question + prompt) choice = raw_input().lower() if choice == '?': continue elif default is not None and choice == '': return valid[default] elif choice in valid: return valid[choice] else: sys.stdout.write("Please respond with 'yes' or 'no' " "(or 'y' or 'n').\n") def query_string(question, default): prompt = " [default: '%s']\n? " % (default) while True: sys.stdout.write(question + prompt) choice = raw_input() if choice == '?': continue elif default is not None and choice == '': return default else: return choice def query_choice(question, choices, default): while True: print question cnt = 0 for item in choices: print " - (%d) %s" % (cnt, item) cnt += 1 sys.stdout.write("? ") choice = raw_input() if choice == '?': continue elif default is not None and choice == '': return default elif choice in choices: return choice elif valid_int(choice) and 0 <= int(choice) <= len(choices) - 1: return choices[int(choice)] else: sys.stdout.write("Please respond with an item of the list.\n") def query_int(question, range_from, range_to, default): has_range = range_from is not None and range_to is not None if has_range and range_from > range_to: raise ValueError("invalid range : %d .. %d" % (range_from, range_to)) if has_range and default is not None and \ not range_from <= default <= range_to: raise ValueError("invalid default answer: %d" % default) if has_range: prompt = " [%d .. %d] default:%s\n" % (range_from, range_to, default) else: prompt = " [default: %s]\n" % (default) while True: sys.stdout.write(question + prompt) choice = raw_input().lower() if choice == '?': continue elif default is not None and choice == '': return default elif not valid_int(choice): sys.stdout.write("'%s' is not a valid int value\n" % choice) elif not has_range or range_from <= int(choice) <= range_to: return int(choice) else: sys.stdout.write("'%s' is not in the range of valid values\n" % choice) def query_float(question, range_from, range_to, default): has_range = range_from is not None and range_to is not None if has_range and range_from > range_to: raise ValueError("invalid range : %d .. %d" % (range_from, range_to)) if has_range and default is not None and \ not range_from <= default <= range_to: raise ValueError("invalid default answer: %d" % default) if has_range: prompt = " [%d .. %d] default:%s\n" % (range_from, range_to, default) else: prompt = " [default: %s]\n" % (default) while True: sys.stdout.write(question + prompt) choice = raw_input().lower() if choice == '?': continue elif default is not None and choice == '': return default elif not valid_int(choice): sys.stdout.write("'%s' is not a valid float value\n" % choice) elif not has_range or range_from <= float(choice) <= range_to: return int(choice) else: sys.stdout.write("'%s' is not in the range of valid values\n" % choice)

30.273973

77

0.547738

555

4,420

4.266667

0.124324

0.031672

0.065034

0.045608

0.752956

0.738176

0.720017

0.649071

0

0.001357

0.333032

4,420

145

78

30.482759

0.8019

0.00181

0

0.663793

0

0.131263

0

null

0

0.008621

null

0.017241

0

null

0

1

0

1

0

null

0

1

0

5

3668793ee978687a80a8c1cf1397f96c14ff28cc

185

py

Python

CircuitPython_Templates/cpu_temperature_f/code.py

caternuson/Adafruit_Learning_System_Guides

eb6403abe4d0ad094a7efe369ef261460d78561b

[ "MIT" ]

1

2021-01-05T02:08:27.000Z

CircuitPython_Templates/cpu_temperature_f/code.py

caternuson/Adafruit_Learning_System_Guides

eb6403abe4d0ad094a7efe369ef261460d78561b

[ "MIT" ]

1

2020-10-16T15:30:22.000Z

CircuitPython_Templates/cpu_temperature_f/code.py

caternuson/Adafruit_Learning_System_Guides

eb6403abe4d0ad094a7efe369ef261460d78561b

[ "MIT" ]

1

2020-10-16T15:23:04.000Z

"""CircuitPython CPU temperature example in Fahrenheit""" import time import microcontroller while True: print(microcontroller.cpu.temperature * (9 / 5) + 32) time.sleep(0.15)

23.125

57

0.735135

23

185

5.913043

0.782609

0.205882

0

0.044872

0.156757

185

7

58

26.428571

0.826923

0.275676

0

1

0

true

0

0.4

0

0.4

0.2

1

0

null

1

0

1

0

null

0

1

0

1

0

5

3684109284b5f07cf8c7fd2dbcdd3c62c284430c

191

py

Python

Factory/RectanglePen.py

aurora314156/Design-Pattern_python

f00982dd32b2b7ac3698b8a673c23d2f534aeefb

[ "MIT" ]

null

Factory/RectanglePen.py

aurora314156/Design-Pattern_python

f00982dd32b2b7ac3698b8a673c23d2f534aeefb

[ "MIT" ]

null

Factory/RectanglePen.py

aurora314156/Design-Pattern_python

f00982dd32b2b7ac3698b8a673c23d2f534aeefb

[ "MIT" ]

null

from Pen import Pen from PenType import PenType class RectanglePen(Pen): def __init__(self, name): self.name = name def getType(self): return PenType.PenTypeRect

21.222222

34

0.675393

24

191

5.208333

0.541667

0.128

0

0.256545

191

9

34

21.222222

0.880282

0

1

0.285714

false

0

0.285714

0.142857

0.857143

0

1

0

null

0

1

0

null

0

1

0

1

0

5

36fb48d446974eb80f8fe2b9d6961d1482ad273d

54

py

Python

eca_catalogue/material/tests/models.py

byteweaver/django-eca-catalogue

a2d2eb4e03785c53f03fcf6afe0c4285e329472f

[ "BSD-3-Clause" ]

3

2015-03-26T04:04:56.000Z

2018-08-12T10:34:44.000Z

eca_catalogue/material/tests/models.py

byteweaver/django-eca-catalogue

a2d2eb4e03785c53f03fcf6afe0c4285e329472f

[ "BSD-3-Clause" ]

3

2020-02-11T21:18:46.000Z

2021-06-10T17:23:28.000Z

eca_catalogue/material/tests/models.py

byteweaver/django-eca-catalogue

a2d2eb4e03785c53f03fcf6afe0c4285e329472f

[ "BSD-3-Clause" ]

2

2017-03-02T03:28:12.000Z

2017-05-14T20:41:54.000Z

from eca_catalogue.material.abstract_models import *

18

52

0.851852

7

54

6.285714

1

0

0.092593

54

2

53

27

0.897959

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5